This PDF file contains the front matter associated with SPIE Proceedings Volume 8349, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

In this paper, ISOMAP algorithm is applied into anomaly detection on the basis of feature analysis in hyperspectral images. Then an improved ISOMAP algorithm is developed against the limitation existed in ISOMAP algorithm. The improved ISOMAP algorithm selects neighborhood according to spectral angel, thus avoiding the instability of the neighborhood in the high-dimension spectral space. Experimental results show the effectiveness of the algorithm in improving the detection performance.

Domain ontology is a descriptive representation of any particular domain which in detail describes the concepts in a domain, the relationships among those concepts and organizes them in a hierarchal manner. It is also defined as a structure of knowledge, used as a means of knowledge sharing to the community. An Important aspect of using ontologies is to make information retrieval more accurate and efficient. Thousands of domain ontologies from all around the world are available online on ontology repositories. Ontology repositories like SWOOGLE currently have over 1000 ontologies covering a wide range of domains. It was found that up to date there was no ontology available covering the domain of "Sufism". This unavailability of "Sufism" domain ontology became a motivation factor for this research. This research came up with a working "Sufism" domain ontology as well a framework, design of the proposed framework focuses on the resolution to problems which were experienced while creating the "Sufism" ontology. The development and working of the "Sufism" domain ontology are covered in detail in this research. The word "Sufism" is a term which refers to Islamic mysticism. One of the reasons to choose "Sufism" for ontology creation is its global curiosity. This research has also managed to create some individuals which inherit the concepts from the "Sufism" ontology. The creation of individuals helps to demonstrate the efficient and precise retrieval of data from the "Sufism" domain ontology. The experiment of creating the "Sufism" domain ontology was carried out on a tool called Protégé. Protégé is a tool which is used for ontology creation, editing and it is open source.

There are some advantages to describe knowledge with discernibility matrix ,As for the discernibility matrix of decision tables, this paper finds that there exist that some redundant information of discernibility matrix. so this paper defines a new discernibility matrix ,which is named Simple Discernibility matrix .it has no redundant information and could reduce the number of comparisons of individuals ,and improve the efficiency.

Inter-class testing is the testing of classes for composing an object-oriented system or subsystem during integration. MM Path is defined as an interleaved sequence of method executions linked by messages. It represents the interactions between methods in object-oriented software well, hence fits for object-oriented integration testing. However, the current MM Path generation methods only support intra-class testing. In this paper, a call-graph-based approach is proposed to promote MM Path automatic generation from intra-class to inter-class level. The approach is evaluated by controlled experiments on 12 Java benchmark programs with two typical call graph construction algorithms, Class Hierarchy Analysis and Anderson's Points-to Analysis. Then, the impact of the two algorithms on inter-class MM path generation efficiency is studied. The result shows that our approach is practicable and Anderson's Points-to Analysis outperforms Class Hierarchy Analysis for inter-class MM Path generation.

Moral education website offers an available solution to low transmission speed and small influence areas of traditional moral education. The aim of this paper is to illustrate the design of one moral education website and the advantages of using it to help moral teaching. The reason for moral education website was discussed at the beginning of this paper. Development tools were introduced. The system design was illustrated with module design and database design. How to access data in SQL Server database are discussed in details. Finally a conclusion was made based on the discussions in this paper.

Web services have gained an increasing popularity, however, also shown challenge in appropriate web service selection. Because of the wide variety of web services might be offered to perform one specific task, it is essential that users are supported in the selection of appropriate web services. Keyword based web service discovery, one of the most practical approaches, ignores the reaction of user context which is considered to be valuable. In this paper, we propose a user context model which enables user context to participate in the process of web service discovery. Our main contribution is a user context utilization method which improves the accuracy of keyword based approaches. Experiments and results are provided to evaluate the proposed method.

The article put forward a method which had been used for video image acquisition and processing, and a system based on Java media framework (JMF) had been implemented by it. The method could be achieved not only by B/S mode but also by C/S mode taking advantage of the predominance of the Java language. Some key issues such as locating video data source, playing video, video image acquisition and processing and so on had been expatiated in detail. The operation results of the system show that this method is fully compatible with common video capture device. At the same time the system possesses many excellences as lower cost, more powerful, easier to develop and cross-platform etc. Finally the application prospect of the method which is based on java and JMF is pointed out.

Web image search results usually contain duplicate copies. This paper considers the problem of detecting and clustering duplicate images contained in web image search results. Detecting and clustering the duplicate images together facilitates users' viewing. A novel method is presented in this paper to detect and cluster duplicate images by measuring similarity between their topics. More specifically, images are viewed as documents consisting of visual words formed by vector quantizing the affine invariant visual features. Then a statistical model widely used in text domain, the PLSA(Probabilistic Latent Semantic Analysis) model, is utilized to map images into a probabilistic latent semantic space. Because the main content remains unchanged despite small digital alteration, duplicate images will be close to each other in the derived semantic space. Based on this, a simple clustering process can successfully detect duplicate images and cluster them together. Comparing to those methods based on comparison between hash value of visual words, this method is more robust to the visual feature level alteration posed on the images. Experiments demonstrates the effectiveness of this method.

In this paper, we develop a new image denoising method based on block-matching and transform-domain filtering. The developed method is derived from the current state-of-the-art denoising method (BM3D). We separate the 3D transform in the original method to two steps 1D transform, to further enhance the sparsity for signals whose elements are highly similar and to weaken the sparsity for those signals whose elements are dissimilar. Because the 1D filtering is on highly similar elements and the 2D filtering on image blocks are all removed, the image details can be better reserved and fewer artifacts are introduced than original method. Experimental results demonstrate that the developed method is competitive and better than some of the current state-of-the-art denoising methods in terms of peak signal-to-noise ratio, structural similarity, and subjective visual quality.

Using SAR to monitor oil spill is a useful method. As the performance of oil spill on SAR images is similar with other oceanic phenomenon, it is difficult to distinguish between oil spill and "look-alikes". This paper presents a novel multi- level method to extract the oil film from original SAR image. The method can retain original edge information of oil film while separated it from the background. This paper applied lee filter, fuzzy c means, coherence filter and morphological operations to de-noise and segment SAR image. Experimental results show that the method can not only distinguish oil film and the sea, but revert part of edge information lost in the process of de-noising and the segmentation.

Aimed projective distortion caused by tilted camera in traditional photogrammetry, a projective distortion self-corrected photogrammetry is proposed used to measure the projectile coordinates. The causes of projective distortion and the impact on the measurement accuracy are analyzed. Through the analysis of the imaging model of random points on the target, The formula to solve the object distance is deduced. The correspondence between the coordinates on the image and the coordinate on the target of the projectiles is established. According to Extraction and calculation of 4 markers sited on the target, the constant in the correspondence is solved. The measurement error caused by projective distortion is overcome. The absolute measurement of projectile coordinate on the target is realized. The test result shows that the projectile coordinate on the target can be accurately measured using the method designed in this paper. The accuracy and consistency of fire intensity measuring is increased. It also can be used to check the other related automatic measuring equipments.

This paper presents an algorithm to detect the eyes and mouth of the faces under various imaging conditions such as with different poses, dimensions, illuminations, resolutions, wearing glasses or not and having different expressions is proposed. Initially, the algorithm converted the face region detected by the Viola-Jones algorithm into gray-scale and reduced the resolution by decimation to achieve low resolution region. The pixels that are darker than their surroundings are later located by 8 individual filters. Finally, the center of eyes and mouth are searched using a triangle model. Experiment show that, the algorithm produced 98.7% accuracy in detecting the eyes and mouth.

An image registration method is proposed in this paper for accurately aligning two images of the same scene captured simultaneously by visible CCD and IR (infrared) cameras. In image fusion systems, CCD and IR sensors are physically aligned as closely as possible and yet significant image mis-alignment remains due to differences in field of view, lens distortion and other camera characteristics. So, affine transformation is considered for aligning two images. At first, the corresponding feature point pairs are selected manually and that are used to calculate transform coefficients. Then, the value of the transform coefficients are optimized further by MI (mutual information) in global image. After the unregistered image is transformed by optimal transform coefficients, the accurately registered image can be obtained. The experimental results demonstrate that this method can provide highly accurate registered images for image fusion.

Super-resolution image reconstruction aims to obtain a high-resolution image from multiple low-resolution images to get a better visual effect. It is widely used in many applications such as video surveillance, image recognition. This paper proposes a POCS super-resolution image reconstruction algorithm based on the projection residue to improve the visual effect of reconstructed HR image. The characteristic of this method is that it takes full advantage of the statistical property of projection residue included in the constraints and changes the modified threshold adaptively. The cause of the projection residue is analyzed and its characteristic parameter is calculated to restrain the solution. Experimental results show that our algorithm is effective in visual evaluation, and the PSNR is improved.

Using optical sensor array, a precision motion control system in a conveyer follows the irregular shaped leather sheet to measure its surface area. In operation, irregular shaped leather sheet passes on conveyer belt and optical sensor array detects the leather sheet edge. In this way outside curvature of the leather sheet is detected and is then feed to the controller to measure its approximate area. Such system can measure irregular shapes, by neglecting rounded corners, ellipses etc. To minimize the error in calculating surface area of irregular curve to the above mentioned system, the motion control system only requires the footprint of the optical sensor to be small and the distance between the sensors is to be minimized. In the proposed technique surface area measurement of irregular shaped leather sheet is done by defining velocity and detecting position of the move. The motion controller takes the information and creates the necessary edge profile on point-to-point bases. As a result irregular shape of leather sheet is mapped and is then feed to the controller to calculate surface area.

A novel and efficient method called marked bounding box method based on marching cubes is presented for the point cloud data reduction of sole patterns. This method is characterized in that each bounding box is marked with an index during the process of data reduction and later for use of data reconstruction. The data reconstruction is implemented from the simplified data set by using triangular meshes, the indices being used to search the nearest points from adjacent bounding boxes. Afterwards, the normal vectors are estimated to determine the strength and direction of the surface reflected light. The proposed method is used in a sole pattern classification and query system which uses OpenGL under Visual C++ to render the image of sole patterns. Digital results are given to demonstrate the efficiency and novelty of our method. Finally, conclusion and discussions are made.

Multiple-exposure-based methods have been an effective means for high dynamic range (HDR) imaging technology. The current methods are greatly dependent on tone mapping, and most of them are unable to accurately recover the local details and colors of the scene. In this work, we present a novel HDR method by using multiple image cues for the image merging process. Firstly, all the images with various exposure times are divided into some uniform sub-regions and an exposure estimation technique is implemented to judge the well exposed one. With all the image blocks have best exposing quality are selected, a blending function is proposed to remove the transition boundaries between these blocks. A fidelity metric index is introduced to assess the final fusion image, and experimental results on public image libraries are given to demonstrate its high performance.

A new method of image denoising was presented via combining contourlet transform and the stationary wavelet transform which has an iterative filer bank with stationary wavelet transform and the directional filter banks (DFB). The experimental results show that in terms of image denoising, the proposed method can suppress speckle in SAR images effectively while preserving the edge features and textural information of the scene.

It's reviewed that the measurement system of road surface profile and the calculation method of segment road test data have been introduced. Because of there are sudden vertical steps at the connection points of segment data which will influence the application of road surface data in automotive engineering. So a new smooth connection method of segment test data is proposed which revised the sudden vertical steps connection by the Signal Local Baseline Adjustment (SLBA) method. Besides, there is an actual example which mentioned the detailed process of the smooth connection of segment test data by the SLBA method and the adjusting results at these connection points. The application and calculation results show that the SLBA method is simple and has achieved obvious effect in smooth connection of the segment road test data. The method of SLBA can be widely applied to segment road surface data processing or the long period vibration signal processing.

The aim of this paper is to provide the line drawing algorithm which is accurate and effective in dissimilar hardware platforms and different application requirements. The most famous algorithm to draw a straightness line in a smooth fashion is Bresenham algorithm. It is advantageous that the classic Bresenham algorithm processes are all integer numeric without division and decimal fraction. Meanwhile, it is imperfect that the algorithm generates only one pixel at a computation time. So a common inevitable phenomenon of the algorithm is its slow efficiency to some extend. Firstly, this paper fully analyzes recent researches of the Bresenham Line Drawing algorithm. Secondly, in this paper we give full attention to the initiative relation between line generation model and its linear slope, and then we present an improved algorithm which can generate pixels of a line row-major by raster graphics display device. What needs to stress, the core principle of the improved algorithm is utilizing the counterpart of both ends of line and the symmetry for segments. Thirdly, after discussing theory and structure, the improved algorithm implementation and simulation are given. The corresponding project, it means that the hardware acceleration in the use of circular subtraction technology based on shift register was briefly described. Finally, results were presented to demonstrate that the new algorithm inherits the advantage of classic Bresenham algorithm without division and decimal fraction, the speed has been increased greatly, and it is easy to implement by hardware.

The current most desirable image retrieval feature is retrieving images based on their semantic content. In order to improve the retrieval accuracy of content-based image retrieval systems, research focus has been shifted from designing sophisticated low-level feature extraction algorithms to reducing the 'semantic gap' between the visual features and the richness of human semantics. In this paper, we put forward a system framework of image retrieval based on content and ontology, which has the potential to fully describe the semantic content of an image, allowing the similarity between images and retrieval query to be computed accurately. In the system, we identify third major categories of techniques in narrowing down the "semantic gap": (1) using object ontology to define high-level concepts; (2) using machine learning methods to associate low-level features with query concepts; (3) using ontology reasoning to extend image retrieval. Finally, the paper does some testing experiment, whose result shows the feasibility of the system framework.

Combined with the newest Machine Vision technology, various characteristic algorithms for border detection are introduced. The norm for the quality of border detection algorithms and the direction of the new algorithms are proposed in the end.

A new fuzzy based thresholding method for medical images especially cervical cytology images having blob and mosaic structures is proposed in this paper. Many existing thresholding algorithms may segment either blob or mosaic images but there aren't any single algorithm that can do both. In this paper, an input cervical cytology image is binarized, preprocessed and the pixel value with minimum Fuzzy Gaussian Index is identified as an optimal threshold value and used for segmentation. The proposed technique is tested on various cervical cytology images having blob or mosaic structures, compared with various existing algorithms and proved better than the existing algorithms.

This paper aims to solve the problem of detecting ghost object; which is a common problem in background subtraction algorithm. Ghost object is the false object detected which is not corresponding to any actual object in current image. In this work, we proposed ghost detection and removal method using color similarity comparison. Proposed solution is designed based on the assumption that ghost problem occurs due to the existence of the object in background image instead of in the current image. We are using color similarity between detected foreground area and its surrounding area to first determine whether the object appear in background or current image, consequently identify whether the detected object is a ghost or an actual object. Proposed solution has been tested using various datasets including PETS2001 and own datasets and it is proved that the proposed method is able to solve ghost problem.

In this paper, a variational method for motion segmentation has been proposed, which is realized by first estimate discontinuity-preserving optical flow field and then segmenting. Specifically, the complementarity between estimation and segmentation was emphasized, so two main improvements were presented: firstly, a segmentation-oriented diffusion tensor has been suggested in the optical flow model, which combines the image and flow information and determine the boundaries more effectively; Secondly, according to the characteristic of vector field, a motion segmentation model with considerations of both motion boundaries and region information were established. The results were illustrated with examples of sequence images which show the usefulness of the proposed approach for various problems.

Robust image partitioning technique with limited space-time requirement is crucial for real-time high-resolution mobile imaging applications. Simultaneous handling of color components is a stumbling block in segmentation of color image. This paper presents a strategy for segregating multi-dimensional complexity that resembles human visual perception. First-order regions are developed employing the distribution of base color (hue) creating meaningful partitions of the image. Each region being self-contained can be transmitted independently. Further segmentations on each hue region can be done concurrently with respective local distributions of saturation (S). Finally, each of the subregions can undergo a third-order segmentation based on intensity (I) distribution at local level. Experiments indicate that the segregation process improves throughput and quality of segmentation. Self-contained partitions are convenient for multi-host image sharing as well as progressive reconstruction of images in the receiver.

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Basic aim of our study is to analyze the medical image. In computer vision, segmentationRefers to the process of partitioning a digital image into multiple regions. The goal ofSegmentation is to simplify and/or change the representation of an image into something thatIs more meaningful and easier to analyze. Image segmentation is typically used to locateObjects and boundaries (lines, curves, etc.) in images.There is a lot of scope of the analysis that we have done in our project; our analysis couldBe used for the purpose of monitoring the medical image. Medical imaging refers to theTechniques and processes used to create images of the human body (or parts thereof) forClinical purposes (medical procedures seeking to reveal, diagnose or examine disease) orMedical science (including the study of normal anatomy and function).As a discipline and in its widest sense, it is part of biological imaging and incorporatesRadiology (in the wider sense), radiological sciences, endoscopy, (medical) thermography, Medical photography and microscopy (e.g. for human pathological investigations).Measurement and recording techniques which are not primarily designed to produce images.

Birefringence of asymmetric photonic crystal fiber is investigated using the finite element method, under the circumstance of perturbation. By comparing the value of birefringence on the different value of large air-hole, the results indicate that when the intrinsic-birefringence is smaller, the random offset of hole-position has large influence on the birefringence. With the intrinsic-birefringence increasing, the little effect on birefringence regardless of the offset of hole-position or the variation of hole-diameter.

Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.

The illumination variation problem is one of the well-known problems in face recognition in uncontrolled environment. Due to that both Gabor feature and LTP(local ternary pattern) are testified to be robust to illumination variations, we proposed a new approach which achieved illumination variable face recognition by combining Gabor filters with LTP operator. The experimental results compared with the published results on Yale-B and CMU PIE face database of changing illumination verify the validity of the proposed method.

This paper proposes a Swarm Intelligence based Memetic algorithm for Task Allocation and scheduling in distributed systems. The tasks scheduling in distributed systems is known as an NP-complete problem. Hence, many genetic algorithms have been proposed for searching optimal solutions from entire solution space. However, these existing approaches are going to scan the entire solution space without considering the techniques that can reduce the complexity of the optimization. Spending too much time for doing scheduling is considered the main shortcoming of these approaches. Therefore, in this paper memetic algorithm has been used to cope with this shortcoming. With regard to load balancing efficiently, Bee Colony Optimization (BCO) has been applied as local search in the proposed memetic algorithm. Extended experimental results demonstrated that the proposed method outperformed the existing GA-based method in terms of CPU utilization.

In this paper, an extended projection temporal logic(EPTL), based on a primitive operator prj , is formalized. Further, as an executable subset of EPTL, an object-oriented MSVL is presented, which extends the temporal logic programming language MSVL to support object, class, aliasing, inheritance and overloading features. An example of modeling and simulating digital signal processing is given to illustrate how to use and execute the language.

A new hybrid genetic algorithm is generated in this paper, which is based on the simple genetic algorithm. In this algorithm, some genetic operators such as crossover operator are improved. In the crossover operator, the crossover method based on threshold and the two-points-crossover method are combined into a new hybrid crossover method. An example which is Resource-Constrained Project Scheduling Problem (RCPSP) is given, whose activity network, the execution time and the number of resource required for each activity, selection and crossover operator are also referred. In addition, there are examples to prove the superior of the new algorithm, which is benefit to speed up the evolution and get the optimal solution.

By analyzing the dynamic scheduling needs of its inherent nature, made wearable computing based on human-computer natural interaction forms the basis of EOTAS dynamic scheduling methods, and the targeted building, a new concept of wearable man-machine cooperative forms, turn around its concrete implementation and application, a color based on extended fuzzy Petri net EOTAS dynamic scheduling method for the preliminary settlement of the business operating environment EOTAS field applications of the fast scheduling problem.

With the rapid development of information technology and extensive requirement of network resource sharing, plenty of resource hotlinking phenomenons appear on the internet. The hotlinking problem not only harms the interests of legal websites but also leads to a great affection to fair internet environment. The anti-leech technique based on session identifier is highly secure, but the transmission of session identifier in plaintext form causes some security flaws. In this paper, a proxy hotlinking technique based on session identifier is introduced firstly to illustrate these security flaws; next, this paper proposes an improved anti-leech mechanism based on session identifier, the mechanism takes the random factor as the core and detects hotlinking request using a map table that contains random factor, user's information and time stamp; at last the paper analyzes the security of mechanism in theory. The result reveals that the improved mechanism has the merits of simple realization, high security and great flexibility.

A remote video monitoring system based on Java Media Framework (JMF) is put forward in this paper. It is of cross-platform, lower time-delay and lower bandwidth. The system is consisted of three layers that are data acquisition layer, service layer and client layer. The hardware of system is connected with local area network and various video devices can be identified in the system. The software based on Java and JMF is programmed to capture, compress, send, receive and play video data and can be run on different operating system without modification. H.263 compression algorithm is adopted and RTP protocol is used to transport video data with RTCP protocol in the system. The client layer can access to the system by Internet or 3G and has convenient and flexible features. Maintenance personnel can easily supervise the device status at any time so that the equipments are always in good condition. It is helpful to enhance the competitive power of power plants.

This paper concerns the problem of video stitching automatically in a multi-camera surveillance system. Previous approaches have used multiple calibrated cameras for video mosaic in large scale monitoring application. In this work, we formulate video stitching as a multi-image registration and blending problem, and not all cameras are needed to be calibrated except a few selected master cameras. SURF is used to find matched pairs of image key points from different cameras, and then camera pose is estimated and refined. Homography matrix is employed to calculate overlapping pixels and finally implement boundary resample algorithm to blend images. The result of simulation demonstrates the efficiency of our method.

On the asis of User Datagram Protocol (UserDatagram Protocol, UDP), to do some improvement and design a welding robot network communication protocol (welding robot network communicate protocol: WRNCP), working on the fields of the transport layer and application layer of TCP / IP protocol. According to the characteristics of video data, to design the radio push-type (Broadcast Push Model, BPM) transmission method, improving the efficiency and stability of video transmission.and to designed the network information transmission system, used for real-time control of welding robot network.

Multi-cue-based Camshift algorithm is presented for object tracking in complex scenes. Because color-based Camshift algorithm suffers from objects with color clutter in backgrounds, this paper integrates motion cue with color cue to extend its application areas. Moreover, the robust real-time multiresolution algorithm is used to obtain motion information in dynamic background. Experimental work verifies that the proposed multiple cues strategy really improves the tracking performance of the classical Camshift using a single cue.

License plate recognition (LPR) system play an important role in intelligent transportation systems (ITSs). It is difficult to locate a license plate in complex scene. Our location strategy integrates blue region, vertical texture and contrast features of LP in the framework of improved visual attention model. We improve visual attention model by changing normalization and linear combination into feature image binarization and logical operation. Multi-scale center-surround differences mechanism in visual attention model make the feature extraction robust. Tests on pictures captured by different equipments under different environments give delightful result, the success rate for location is as high as 95.28%.

This paper introduces a face verification system implementation. In feature extraction, the algorithm is based on a classical texture descriptor, Local Binary Patterns (LBP). In decision making, a new method is proposed to determine the Client Dependent threshold (CD-th). Compared with the traditional fixed threshold, it significantly reduces error rate. Moreover, a symmetry factor is defined to increase frontal face detection rate. And a storage mode is designed to reduce time consumption in feature extraction. The implemented face verification system requires only one sample per person, and overcomes the difficulties appearing in multi-sample face verification system, including image capture problem, storage limitation and time-consumption. The experiments demonstrate the effectiveness of our proposed system.

Subscriber radio location techniques for code division multiple access (CDMA) cellular networks has been studied extensively in recent years. The network-based angle of arrival (AOA), time difference of arrival (TDOA), and time of arrival (TOA) techniques offer solutions to the position estimation problem. In this paper, The signal processing scheme of wireless location system based IS-95 is presented, in which TOA of reverse access channel transmissions is measured using sub-correlation detection algorithms and TOA estimation accuracy is improved using second search. Furthermore, reverse access channel decoding is implemented used to identify access channel message type, mobile identification, and dialed number.

With the rapidly increasing of biomedical literature, the deluge of new articles is leading to information overload. Extracting the available knowledge from the huge amount of biomedical literature has become a major challenge. GDRMS is developed as a tool that extracts the relationship between disease and gene, gene and gene from biomedical literatures using text mining technology. It is a ruled-based system which also provides disease-centre network visualization, constructs the disease-gene database, and represents a gene engine for understanding the function of the gene. The main focus of GDRMS is to provide a valuable opportunity to explore the relationship between disease and gene for the research community about etiology of disease.

Large-scale and high-quality Video-On-Demand technology has been a hot topic to researchers. In recent years, the development of cloud computing theory and virtualization cluster technology also provides a new solution of thoughts to the construction of large-scale Video-On-Demand system. This paper presents a design of Distributed Video-On- Demand System Based on Cloud Computing (DCC-VOD System), which can be widely applied to various large and medium network environment. It also introduces the components of the core technology, focusing on the implementation of the load balancing server studies for distributed system. Finally, results of comparison tests in the simulated environment show that this system not only can enhance the server performance and resource utilization, but also increase the number of accessed users as much as possible. It greatly improves the reliability and stability of the system, and achieves high cost-effective to meet the current needs of the variety of medium-sized and even the large-scale-sized network environment of video-on-demand.

Fingerprint identification is one of the most important biometric technologies. The performance of the minutiae extraction and the speed of the fingerprint verification system rely heavily on the quality of the input fingerprint images, so the enhancement of the low fingerprint is a critical and difficult step in a fingerprint verification system. In this paper we proposed an effective algorithm for fingerprint enhancement. Firstly we use normalization algorithm to reduce the variations in gray level values along ridges and valleys. Then we utilize the structure tensor approach to estimate each pixel of the fingerprint orientations. At last we propose a novel algorithm which combines the advantages of onedimensional Gabor filtering method and anisotropic method to enhance the fingerprint in recoverable region. The proposed algorithm has been evaluated on the database of Fingerprint Verification Competition 2004, and the results show that our algorithm performs within less time.

The system uses machine vision technology to inspect logarithmic spiral bevel gears. This is a new non-contact measurement technique with high precision and efficiency. Use two cameras in a different location to shoot two images of gear, and collect gear images into the computer. Use correspondence between feature points of two images and optical imaging geometric model to solve three-dimensional coordinates of the tooth surface points. Then, discriminate the tooth shape by comparing to ideal surface point parameters. This kind of inspection method flexibility and provides technical support for processing, detection and correction of logarithmic spiral bevel gears.

We present a sensor fusion framework for real-time tracking applications combining inertial sensors with a camera. In order to make clear how to exploit the information in the inertial sensor, two different fusion models gyroscopes only model and accelerometers model are presented under extended Kalman filter framework. Gyroscopes only model uses gyroscopes to support the vision-based tracking without considering acceleration measurements. Accelerometers model utilizes both measurements from the gyroscopes, accelerometers and vision data to estimate the camera pose, velocity, acceleration and sensor biases. Synthetic data and real image experimental sequences show dramatic improvements in tracking stability and robustness of estimated motion parameters for gyroscope model, when the accelerometer measurements exist drift.

Recognition of handwritten Uighur word is important for Uighur information automation and new generation handwritten input system development on mobile platform. Robust and accurate handwritten character segmentation algorithm provides an important prerequisite for Uighur recognition. Based on the comprehensive consideration of computation, robustness and the characteristics of the text itself, a simple but effective handwritten Uighur character segmentation algorithm is proposed. Furthermore, we develop an Uighur input system on the intelligent mobile platform, and construct a medium scale Uighur handwritten word database simultaneously. The segmentation algorithm is detailed evaluated on the database and the extensive experiments demonstrate the robustness and efficiency of the proposed algorithm.

An ID-based authenticated group key agreement (AGKA) protocol allows a group of members to share a key and provide an assurance of key sharing with an intended group with the user's identity, which is used for conferencing environments. In 2004, Choi et al proposed an ID-based authenticated group key agreement with bilinear maps (also called CHL protocols), which was extended from Burmester and Desmedt conference key agreement protocols. Unfortunately, their protocols were found to be vulnerable to the insider attacks in which cases that the two malicious users have the previous authentication transcripts of the party by Zhang, Chen and Shim. In this paper, we proposed an improved ID-based AGKA. In our scheme, each session has a unique session identity which is published by Key Generation Center. With such unique session identity binding to each session, our protocols can prevent the insider attack. Especially, our protocols can not enhance the computationally cost and it is still efficient.

This paper proposes a new paradigm for the design of cryptographic filesystems. Traditionally, cryptographic file systems have mainly focused on encrypting entire files or directories. In this paper, we envisage encryption at a finer granularity, i.e. encrypting parts of files. Such an approach is useful for protecting parts of large files that typically feature in novel applications focused on handling a large amount of scientific data, GIS, and XML data. We extend prior work by implementing a user level file system on Linux, UsiFe, which supports fine grained encryption by extending the popular ext2 file system. We further explore two paradigms in which the user is agnostic to encryption in the underlying filesystem, and the user is aware that a file contains encrypted content. Popular file formats like XML, PDF, and PostScript can leverage both of these models to form the basis of interactive applications that use fine grained access control to selectively hide data. Lastly, we measure the performance of UsiFe, and observe that we can support file access for partially encrypted files with less than 15% overhead.

Support Vector Machine (SVM) based on Structural Risk Minimization (SRM) of Statistical Learning Theory has excellent performance in fault diagnosis. However, its training speed and diagnosis speed are relatively slow. Signed Directed Graph (SDG) based on deep knowledge model has better completeness that is knowledge representation ability. However, much quantitative information is not utilized in qualitative SDG model which often produces a false solution. In order to speed up the training and diagnosis of SVM and improve the diagnostic resolution of SDG, SDG and SVM are combined in this paper. Training samples' dimension of SVM is reduced to improve training speed and diagnosis speed by the consistent path of SDG; the resolution of SDG is improved by good classification performance of SVM. The Matlab simulation by Tennessee-Eastman Process (TEP) simulation system demonstrates the feasibility of the fault diagnosis algorithm proposed in this paper.

Ever since the concept of analog network coding(ANC) was put forward by S.Katti, much attention has been focused on how to utilize analog network coding to take advantage of wireless interference, which used to be considered generally harmful, to improve throughput performance. Previously, only the case of two nodes that need to exchange information has been fully discussed while the issue of extending analog network coding to more than three nodes remains undeveloped. In this paper, we propose a practical transmission scheme to extend analog network coding to more than two nodes that need to exchange information among themselves. We start with the case of three nodes that need to exchange information and demonstrate that through utilizing our algorithm, the throughput can achieve 33% and 20% increase compared with that of traditional transmission scheduling and digital network coding, respectively. Then, we generalize the algorithm so that it can fit for occasions with any number of nodes. We also discuss some technical issues and throughput analysis as well as the bit error rate.

There are usual complex causal relationships among faults to constitute complex system. Based on the introduction of Cellular Automata (CA) and its evolution theory, fault-relating pattern analysis method based on CA was studied. Application of CA for fault-relating pattern was proposed. Extended CA (ECA) and its algorithm were also proposed. Simulation and analysis for evolvement of complex process of multi-fault relating chain were realized. The example analysis of mechanical system fault-relating based on CA shows that the proposed ECA method breaks through limit of spatial rules and homogeneity homogeneous of CA and provides a suitable analytical tool for researches on fault-relating pattern. The preliminary study and explore results show that the method can effectively reveal the association patterns among many fault in the system.

The article focus on an application of chemical engineering. A fuzzy modeling methodology designed to determinate two relevant characteristics of a chemical compound (ferrocenylsiloxane polyamide) for self-assembling - surface tension and maximum UV absorbance measured as temperature and concentration functions. One of the most important parts of a fuzzy rule-based inference system for the polyamide solution characteristics determinations is that it allows to interpret the knowledge contained in the model and also to improve it with a-priori knowledge. The results obtained through proposed method are highly accurate and its can be optimized by utilizing the available information during the modeling process. The results showed that it is feasible in theory and reliable on calculation applying Mamdani fuzzy inference system to the estimation of optical and surface properties of a polyamide solution.

The OWL (Web Ontology Language) is the de facto standard ontology description language used by the Semantic Web. Because OWL is mainly designed for use by applications that need to process the content of information, it is difficult to read and understand by domain experts to build or verify domain ontologies expressed by OWL. ORM (Object Role Modeling) is a conceptual modeling language with graphical notations, its models/schemas can be translated into pseudo natural language that make it easier, also for domain experts who is a non-IT specialist, to create, check and adapt the knowledge about the UoD (Universe of Domain). Based on formal logic analysis of OWL DL and ORM and extending ORM notations, mapping rules has been presented to visualize OWL DL ontologies with ORM.

Virtualization is one of the hottest research topics nowadays. Several academic researchers and developers from IT industry are designing approaches for solving security and manageability issues of Virtual Machines (VMs) residing on virtualized cloud infrastructures. Moving the application from a physical to a virtual platform increases the efficiency, flexibility and reduces management cost as well as effort. Cloud computing is adopting the paradigm of virtualization, using this technique, memory, CPU and computational power is provided to clients' VMs by utilizing the underlying physical hardware. Beside these advantages there are few challenges faced by adopting virtualization such as management of VMs and network traffic, unexpected additional cost and resource allocation. Virtual Machine Monitor (VMM) or hypervisor is the tool used by cloud providers to manage the VMs on cloud. There are several heterogeneous hypervisors provided by various vendors that include VMware, Hyper-V, Xen and Kernel Virtual Machine (KVM). Considering the challenge of VM management, this paper describes several techniques to monitor and manage virtualized cloud infrastructures.

A new face recognition method is proposed in this paper. The proposed method is based on fuzzy regularized linear discriminant analysis (FR-LDA) and combines the regularized linear discriminant analysis (R-LDA) and the fuzzy set theory. R-LDA is based on a new regularized Fisher's discriminant criterion, which is particularly robust against the small sample size problem compared to the traditional one used in LDA. In the proposed method, we calculate the membership degree matrix by Fuzzy K-nearest neighbor (FKNN) and then incorporate the membership degree into the definition of the between-class and within-class scatter matrices and get the fuzzy between-class and within-class scatter matrices. Experimental results obtained on the FERET database demonstrate that the proposed method improves the classification rate performance.

In this paper, a high precision and convenient extension simulation platform for satellite attitude and orbit system is developed, to demonstrate the satellite attitude and orbit system for given space mission, and test the new underdeveloped algorithms for attitude/orbit dynamics, attitude determination, orbit navigation, and attitude/orbit control. The simulation platform is based on Matlab/Simulink software, using the technique of Simulink modeling, importing C/Fortran code in Matlab/Simulink, and embedded Matlab function, with beautiful reusability, inheritability and expansibility. The paper orderly presents the background behind the development of the platform, the platform design architecture and capability, the validity of the platform, the inheritability and expansibility of the platform, the platform implementation example for Chinese weather satellite (FY-3), and the future development for the platform.

A route detecting algorithm was proposed for the cucumber picking robot navigation in greenhouse environment. Possible navigation route was determined from the additive value of the column scanning results. Color difference between cucumber plants and the mid row soil was analyzed through combining the RGB elements segregations with extra-green (ExG) value and extra-red (ExR) value. The obtained gray image was segmented with OTSU threshold method, which made the gray-color abruptly changed pixels along the two sides of the central line identified. Mean value of these selected pixels in each line was calculated to provide the discrete points along the navigation route. Finally least square method was used to fit these discrete points to provide the navigation lines, from which, the route for current navigation scheme can be determined. The proposed algorithm was applied to multiple images for its high speed and anti-noise verification.

Nowadays, photocopiers are commonly available as part of the reprinting or duplication of documents particularly reference books. Therefore, it could be a major setback for the publishers and the authors to retail the books to the readers. Since the field of photometry and colorimetry are advancing in terms of research, it is discovered that the colours comprise of luminance values that are analogous to grayscale intensities ranging from white to black. By exploiting the luminance from the colour properties, grayscale photocopying is greatly discouraged when the grayscale printed copies or grayscale photocopies are scarcely visible of the contents.

In order to improve the safety and reliability of capacitive equipment developed online monitoring system of capacitive equipment dielectric loss. Introduce the structure and function of the software, based on the B/S skeleton, uses the modular design, improve the readability and scalability. Detail the design of communication module, parameter setting module, data acquisition and processing module, the user management module, database systems, etc. The entire process is given. By testing the monitoring software work is stable, reliable, long-term continuous and effective monitoring capacitive equipment various insulation data, can satisfy the requirements on site application.

We use an onboard computer and a smart webcam built a practical real-time detection visual system. Installed in a driving cabin in a specific way, it is able to determine the degree of closure of the driver's eyelids for further study of detecting and mitigating driver drowsiness and fatigue. For a practical real-time application, both the temporal resolution and the image resolution of video processing are key performances. Instead of the traditional video processing strategy which detects face in the first frame and keep tracking in the following, a frame-by-frame detecting and locating strategy is adopted, which firstly locates face region in a size-reduced image, secondly face region in original image is located by linear mapping calculation, thirdly eye region is located in face region according to the characteristics of a facial geometric model, this model allows personal calibration intuitively in run-time according to different individuals. A novel combination of several practical methods proved effective in computer vision is proposed, including capturing and resizing frames, face and eye localization, adaptive-threshold segmentation, mathematical morphology etc. Experiments show that the proposed system achieves a performance of image resolution of 640×480 pixels, temporal resolution of 53 frames / second, average eye-blink detection accuracy of 96% under various illumination conditions.

Music notations can be considered as very important information for musicians as well as for music fans. To recreate music which was heard before one has to know the musical notes which were included in that music piece. From many years computer scientists and engineers have tried to come up with various techniques to automate the task of finding out musical notes from a music piece. With the advent of computer science many digital format arrived which facilitated storing and encoding music information. But with the dynamic nature of any sound information still the problem of analyzing those stays. Many statistical methods have been proposed in literature. But implementation specific detail is very hard to find. With this paper we try to address that issue. At research lab, University of Moratuwa, we came up with a system implemented in Java programming language which performs automatic music transcription on monophonic music with a good accuracy level called Miyaesi.

Restoration techniques are applied to degraded face samples. The techniques considered are those of Wiener Filtering, Lucy Richardson deconvolution, Blind deconvolution and Constrained least squares filtering (CLSF). Images degraded by low blur, high blur and low blur with noise are experimented with and the results are expounded.

A flexible grinding technology based on the electric current control is presented to resolve the problem of low rigidity of PCB during grinding, the thickness of which varies from 0.1mm up to 3.5 mm. The comparative results between the real-time current and the setting current in the process of grinding control the frequency and the number of servo pulse, and then the servo motor adjusts the grinding depth of brushing roller at several different rotational speeds, namely, realizing the constant grinding force during grinding. The results show that the PCB can be grinded efficiently and accurately by means of the flexible grinding technology based on the electric current control.

In order to improve the accuracy and precision of license plate location in license plate recognition system.The text introduces a license plate location algorithm with an adaptive threshold, which can achieve the exact location of the license plate based on an improved texture characteristic. The features of character segmentation are in the projection threshold which is able to change according to different images. Finally BP neural network is used to identify each character. Experimental results show that the method can achieve accurate license plate recognition and it has the following advantages such as accurate positioning, robustness and so on.

In mechanical process, such as milling parts, cutting parts and coiling sheets, line and arc is two kinds of the most common and most simple machining track. So the extraction of line and arc is of important significance in the practical application. Therefore, in this paper, the research object is a continuous, uninterrupted and uncrossed curve. This paper presents a method for identifying lines and arc based on line recognition algorithm of Freeman chain code, finally the basic geometric feature of round and rectangle is extracted. Experimental results prove that this method is feasible.

Text mining and ontology learning can be effectively employed to acquire the Chinese semantic information. This paper explores a framework of semantic text mining based on ontology learning to find the potential semantic knowledge from the immensity text information on the Internet. This framework consists of four parts: Data Acquisition, Feature Extraction, Ontology Construction, and Text Knowledge Pattern Discovery. Then the framework is applied into an actual case to try to find out the valuable information, and even to assist the consumers with selecting proper products. The results show that this framework is reasonable and effective.

The Supercritical Main Steam has a large inertia, delay and nonlinear and dynamic characteristics change with the operating conditions, it is difficult to establish the precise mathematical model, this algorithm based on RBF neural network GGAP posed a direct neural network predictive controller, the combination of online learning and control to a supercritical power plant main stream temperature as the research object, MATLAB simulation results show that the superheated steam temperature system can achieve effective control, performance than the conventional PID control has greatly improved.

The traditional PID control with RBF function the nerve network integration and made based on RBF the nerve network the PID controller. the controller for the supercritical main system, the network for temperature control system RBF an on-line to identify and build up the reference in the line and PID controller model for providing information and controllers of the online study to their control, adjust the parameter from online, the performance indicators. MATLAB simulation results show that the controller for temperature system has good control, not only keep track of good performance and robustness better.

In this regard, this research deals with a method for hybrid fuzzy least-squares regression. The extension of symmetric triangular fuzzy coefficients to asymmetric trapezoidal fuzzy coefficients is considered as an effective measure for removing unnecessary fuzziness of the linear fuzzy model. First, trapezoidal fuzzy variable is applied to derive a bivariate regression model. In the following, normal equations are formulated to solve the four parts of hybrid regression coefficients. Also the model is extended to multiple regression analysis. Eventually, method is compared with Y-H.O. chang's model.

The existence of outliers in a set of experimental data can cause incorrect interpretation of the fuzzy linear regression results. This paper is to introduce some limitation on constraints of fuzzy linear regression models for determining fuzzy parameters with outliers by value trapezoidal fuzzy data.

Intelligent video surveillance has found a wide range of applications in public security. This paper describes the state-of- the-art techniques in video surveillance system with single camera. This can serve as a starting point for building practical video surveillance systems in developing regions, leveraging existing ubiquitous infrastructure. In addition, this paper discusses the gap between existing technologies and the requirements in real-world scenario, and proposes potential solutions to reduce this gap.

Marine engine simulator is broadly used in maritime education and training. Maritime education and training institutions usually use this facility to cultivate the hands-on ability and fault-treat ability of marine engineers and students. In this study, the structure and main function of DMS-2005 marine engine simulator is briefly introduced, several teaching methods are discussed. By using Delphi method and AHP method, a comprehensive evaluation system is built and the competence of marine engineers is assessed. After analyzing the calculating data, some conclusions can be drawn: comprehensive evaluation system could be used to assess marine engineer's competence; the training of marine engine simulator is propitious to enhance marine engineers' integrated ability, especially on the aspect of judgment of abnormal situation capacity, emergency treatment ability and safe operation ability.

RFID middleware is regarded as the nerve of RFID systems. Firstly this paper analysis and discuss relatively mature RFID middleware, and propose a RFID middleware which based on service-oriented architecture. Then in this paper we introduce the CEP (complex event processing), and it is a new technology for event and data processing. With the widespread usage of RFID technology, complex event processing becomes a very important part in RFID application. Through introducing its work, we indicate the basis of introducing CEP to RFID middleware. We focus on the complex event processing technology in RFID data processing, and present a based on CEP data processing model, and study cache, Event Filter and Complex Event Builder key technologies. Moreover, a query language for detecting RFID complex events is also introduced.

In order to embody the reuse significance of software reuse framework fully, this paper will analyze in detail about the single object model mentioned in the article "The overall design of software reuse framework" and induce them as add and delete and modify mode, check mode, and search and scroll and display integrated mode. Three modes correspond to their own interface design template, class and database design concept. The modelling idea helps developers clear their minds and speed up. Even laymen can complete the development task easily.

The paper mainly expands the definition of Granular Sets which was proposed by predecessors. We know that we often discuss and give some general topics that g is the subset of X( g is a granule and X is a given set).Conversely, this paper would discuss the case that X is the subset of g. and define some concepts of lower and upper approximation of X, and discuss some properties.

With the rapid development of computer networks, especially with the introduction of the Semantic Web perspective, the problem of trust computation in the network has become an important research part of current computer system theoretical. In this paper, according the information properties of the Semantic Web and interact between nodes, the definition semantic trust as content trust of information and the node trust between the nodes of two parts. By Calculate the content of the trust of information and the trust between nodes, then get the final credibility num of information in semantic web. In this paper , we are improve the computation algorithm of the node trust .Finally, stimulations and analyses show that the improved algorithm can effectively improve the trust of information more accurately.

ORM (Object Role Modeling), current version is 2.0, is a fully communication oriented information modeling method. Currently, ORM has been used in ontology engineering to model domain ontologies. To ensure the semantics of ORM model is consistent, it needs using reasoning engines to check semantic conflicts and redundancy. Furthermore, only publish ORM domain ontologies on the Semantic Web described by OWL can it is shared by different applications. Therefore, it needs to map ORM models into OWL DL. Several methods to transform ORM models have been considered and a series of general OWL DL formalization rules have been proposed.

According to the characteristics and construction goals of distribution sales enterprises, the intelligent sale management system design and development methods based on caller ID display which take full advantage of the advanced telephone and network technologies. Based on the above methods and technologies, the intelligent sale management system had been developed. Moreover, in practical applications, it has achieved good results, and is a good complement for CTI and CRM systems.

Survivable network refers to the system that can continue to fulfill the basic services set in advance when the system faces some threats, such as external attacks and intrusions, interior errors and confusions and so on, until the system backs to normal. The most significant feature of survivable network lies in that the key services of the system can keep on running when the system is in a desperate environment. Therefore, in a survivable network, how to ensure the nonstop running of the key services becomes very important. As a technology, apart from the basic features of Agent, such as response, autonomy and target-oriented, Mobile Agent also has its own unique feature--mobility. Based on the analysis of the survivability theory and the features of Mobile Agent, this paper proposes MESMMA (A Model for Essential Services Mobility Based on Mobile Agent), a Mobile Agent mobility-based model used to ensure the nonstop running of key services of survivable networks. Besides, this paper deeply discusses the structure design, running process and various Mobile Agent functions of the MESMMA system.

The high pressure air blowing ballast tanks are the most effective means of emergency to restore under flooded submarine. As the process of blowing, the ballast compartment complexity of the flow of gas-liquid mixture, led to the theoretical models have certain limitations.The paper simulates the dynamic process of high-pressure air blowing ballast tanks by VOF two-phase flow model to analyze gas-liquid mixture phenomena,pressure changes, the ballast tank drainage rate during the process of blowing ballast tank, which provides the basis to theoretical models for the establishment of the high pressure air blowing ballast tanks.

The double-stage Involute Cylindrical Gear assistant design transmission system was developed according to Programmed Design process, uder the software environment of VB6.0. All the users need to do is to enter the relevant parameters, then the system could judge whether the Cylindrical Gear transmission system is satisfactory in Fatigue Strength and Bending Strength, thus the time of checking by handwork calculation can be saved.

Based on the push - pull theory, this article show the empirical studies of tourists' travel motivation to Guangzhou Ecological Park. We identified four push factors and three pull factors which are of the potential features of travel motivation, and on this basis, using analysis of variance to further test the significant differences of push and pull factors in the demographic characteristics of different groups. The conclusion has a certain reference value to the Ecological Park in Guangzhou to attract tourists.

This paper proposes a method for the design of governor foot mechanism on high-speed printing press. According to the technological conditions, an optimal design model is presented to achieve the minimum deviation between the desired and actual track points. The physical dimensions of the linkages and the angular stroke of the driven cam can be gained by solving the presented optimum model.Then the driven cam's profile is calculated. The effectiveness of the proposed method is proved through an illustrative design example of a governor foot mechanism for high-speed operation.

This paper analyzes the respective characteristics of VS2005 and MATLAB and their performances and introduces several methods of mixed programming. Then, the paper discusses the advantages and great applications of texture synthesis from sample (TSFS) and Image Quilting algorithm which is a typical algorithm of TSFS. Further, the paper realizes the Image Quilting algorithm by using mixed programming between VS2005 and MATLAB2007a via COM. We can perceive that mixed programming via COM that is used in developing texture synthesis program can not only speeds up its efficiency and reliability, but also strengthen the convenience of operation and visualization. Finally, the paper summarizes the relationship between texture synthesis parameters and synthesis effects from the experiment.

This paper deals with three-point boundary value problem for singular integro-differential equations at resonance in Banach spaces. Using a specially constructed cone and fixed point theory of strict-set-contraction operators, we obtain some new sufficient conditions of the existence and multiplicity of positive solution.

The Access Grid (AG) targets an advanced collaboration environment, with which multi-party group of people from remote sites can collaborate over high-performance networks. However, current AG still employs VIC (Video Conferencing Tool) to offer only pure video for remote communication, while most AG users expect to collaboratively refer and manipulate the 3D geometric models of grid services' results in live videos of AG session. Augmented Reality (AR) technique can overcome the deficiencies with its characteristics of combining virtual and real, real-time interaction and 3D registration, so it is necessary for AG to utilize AR to better assist the advanced collaboration environment. This paper introduces an effort to augment the AG by adding support for AR capability, which is encapsulated in the node service infrastructure, named as Augmented Reality Service (ARS). The ARS can merge the 3D geometric models of grid services' results and real video scene of AG into one AR environment, and provide the opportunity for distributed AG users to interactively and collaboratively participate in the AR environment with better experience.

With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.

The unweighted networks only reflect the connection type between nodes and the network topology characteristics, by contrast, the weighted networks could describe the strength of interaction between nodes. For this reason, the weighted networks will give a better understanding of the characteristics of real-world networks and the complicated features of complex systems. The evaluation of node importance is a very meaningful research in weighted complex networks. This paper analyze the characteristics of weighted complex network and consider the effects of edge weights for the evaluation of node importance, introduces the idea of data field in theoretical physics and establishes the evaluation model of node importance in weighted complex network. Through the theoretical and experimental analysis, it is proved that this method can evaluate the importance of node in weighted complex network in a fast and accurate way, which is significant both to theory and practice.

The current selected features and profiles in a mobile device is usually set manually and do not use the external environment automatically to change it. The features and profile can be switching to silent mode in office, selecting a formal ringtone in office, describing the mood in the social network sites and a whole lot of similar things. These features and profiles of the mobile is usually related to facial expression of the person (happiness, sadness, disgust, anger, fear, and surprise), external appearance (different clothes in office and home) and surroundings of the person (office, home, park etc). The idea of the paper is to the use the above mentioned external events and changes the theme of the mobile phone. The change may be changing the color of mobile screen, select particular category of word suggestion during writing SMS, notes or document, select music playlist, call buddy with whom user would like to share stuff. Basically user will have a mobile that can understand user's emotion and do accordingly. The paper presents details about emotion reading and implementation using patter recognition technique to capture.

In this paper, study optimization performance of damping semi-active viscose MR in order to reduce the seismic vibrations of a building with 12 floors. For this purpose, we used genetic algorithms to obtain optimal number and optimal situation in 15 major earthquakes with different frequency content through which final status damping are determined. Investigating the influence of this type of damper on the construct dynamic response, the construct equation has been written regarding dampers .Then, the aforesaid equation has been transmitted to the situational setting ,the optimum quantity of each damper in the form of time function has been computed using optimization algorithm genetic and, the construct response has been determined. The results show that different positions of optimal in the structure height can have different effects on different responses. In a way that aligned damping in the upper parts of structures although much reduced Roof floor shift but are less than the rate of decline in shear force base. It also aligned damping in the bottom parts of structures are less than the rate of decline in base shear force roof and floor shift. Therefore, by determining optimized position of optimal by genetic algorithms that can simultaneously optimize the rate of reduction in the structure response.

TC center location is important for weather forecast and TC analysis. However the appearance of TC centers has different shapes and sizes at different time. At different stages of TC lifetime, the difficulty of locating TC center is different. In order to improve the automatism and precision, we present a TC center location scheme for eye TCs and non-eye TCs. Fisher discriminant is used to segment TC so that we can get the binary image automatically and effectively. Since the cloud wall near the non-eye TC center is homocentric circle, Chan-Vese model is used to get TC contour. Experimental results on TCs show that our scheme can achieve an average error within 0.3 degrees in longitude/latitude in comparison with the best tracks by CMA and RSMC.

In the industrial wireless network, determinacy, reliability and real-time applications have been bottleneck of the network. The existed routing protocols of the wireless sensor network cannot be fully corresponded with the industrial applications. In this paper, a routing algorithm based LQI (link quality indicator) and deterministic scheduling is proposed, which is focus to solve the issue of high reliability. The test results in ISA100.11a DL subnet show the superiority of the proposed algorithm, which has much more superiority to reduce the network overhead and save the network resources.

Energy demand forecasting is a key issue for consumers and generators in all energy markets in the world. This paper presents a new forecasting algorithm for daily gas demand prediction. This algorithm combines a wavelet transform and forecasting models such as multi-layer perceptron (MLP), linear regression or GARCH. The proposed method is applied to real data from the UK gas markets to evaluate their performance. The results show that the forecasting accuracy is improved significantly by using the proposed method.

The active and reactive power decoupling control for the double-fed induction generator wind turbines(DFIG) does not play a positive role to the frequency response ability of power grid because it performs as the hidden inertia for the power grid. If we want to improve the transient frequency stability of the wind turbine when it is integrated with the system, we must ameliorate its frequency response characteristics. The inability of frequency control due to DFIG decoupling control could be overcome through releasing (or absorbing) a part of the kinetic energy stored in the rotor, so as to increase (or decrease) active power injected to the power system when the deviation of power system frequency appears. This paper discusses the mathematical model of the variable speed DFIG, including the aerodynamic model, pitch control system model, shaft model, generator model and inverter control model, and other key components, focusing on the mathematical model of the converters in rotor side and grid side. Based on the existing model of wind generator, the paper attaches the frequency control model on the platform of the simulation software DIgSILENT/PowerFactory. The simulation results show that the proposed control strategy can response quickly to transient frequency deviation and prove that wind farms can participate in the system frequency regulation to a certain extent. Finally, the result verifies the accuracy and plausibility of the inverter control model which attaches the frequency control module.

In order to prevent accidents and improve the safety level of the railway operations, based on the statistical analysis of railway operation accidents at home and abroad over the years, the safety factors set of railway operation was built in the paper by researching the evolution laws of human, equipment, environment and management in railway transport system. And then, through analyzing the interaction relationships of safety factors from the systematic view, a network which reflected the complex interaction relationships between the safety factors was established, and based on ISM (Interpretative Structural Modeling) method, a hierarchical structure model of safety factors of railway operation in which the complex interaction relationships were divided hierarchically as to explain the deep causes of the railway accidents, then a comprehensive safety factors system of railway operations was established, in order to control and prevent the railway operation accident, to lay the foundation for quantitative analysis and prediction of railway operation accident, and to guide the scientific safety management of railway operation.

Group Technology is a method of increasing the productivity for manufacturing high quality products and improving the flexibility of manufacturing systems in the many variety and small batch production. The parts with the same or similar process route are gathered into a group through production flow analysis. Each part processing route was analyzed. The production flow analysis figure of the parts was drawn. The fuzzy clustering algorithm was used to classify the machine tools and the parts. The fuzzy similar matrices and the relay closure matrices were obtained based on MATLAB. Then the corresponding relations between each group of the parts and each group of the machine tools were found. The similar parts were gathered and the workshop machine layout was reconstructed. The steps of production flow analysis and the fuzzy clustering analysis were introduced. The effectiveness of the method was proved by an example.

The objective of the paper is to propose a safety enhancement model for application software in accelerating the respective self checking strategies similar to bio enzymatic actions. The application software components which are safety critical may have to be assessed periodically or on demand to achieve not only the functional correctness but also the safety specifications or features while getting executed. The design and deployment of such software modules can be formally verified for possible safety flaws using self checking capabilities and software enzymatic actions. The self checks must sense the safety holes in the software and decide to activate the built-in software components called enzymes to do the safe guard operations in a timely manner to mitigate the safety faults using the proposed enzyme calculus. The various application hazards due to the boolean faults in the functional and behavioral model that lead to software safety issues are considered in this approach.

Curve fitting is an important preliminary work for data compression and path interpolator in numerical control (NC). The paper gives a simple conic spline approximation algorithm for G01 code. The algorithm is mainly formed by three steps: divide the G01 code to subsets by discrete curvature detection, find the polygon line segment approximation for each subset within a given error and finally, fit each polygon line segment approximation with a conic Bezier spline. Naturally, B-spline curve can be obtained by proper knots selection. The algorithm is designed straightforward and efficient without solving any global equation system or optimal problem. It is complete with the selection of curve's weight. To design the curve more suitable for NC, we present an interval for the weight selection and the error is then computed.

According to tradition empirical formula form, the cutting force regression model for turning Hastelloy X alloy is assigned for the exponential form. Turning experiments were carried out based on the experimental plan designed on the principle of the quadratic rotary combination design technique. By identifying regression coefficient using genetic algorithm toolbox in MALAB7.1, cutting force regression models were established. The rule that the prediction models reveal is identical with both visual analyses result of experiment data and tradition basic cutting theory, in addition the residual error is smaller, so the regression models are fitted very well.

Recommendation system is considered a tool that can be used to recommend researchers about resources that are suitable for their research of interest by using content-based filtering. In this paper, clustering algorithm as an unsupervised learning is introduced for grouping objects based on their feature selection and similarities. The information of publication in Science Cited Index is used to be dataset for clustering as a feature extraction in terms of dimensionality reduction of these articles by comparing Latent Dirichlet Allocation (LDA), Principal Component Analysis (PCA), and K-Mean to determine the best algorithm. In my experiment, the selected database consists of 2625 documents extraction extracted from SCI corpus from 2001 to 2009. Clustering into ranks as 50,100,200,250 is used to consider and using F-Measure evaluate among them in three algorithms. The result of this paper showed that LDA technique given the accuracy up to 95.5% which is the highest effective than any other clustering technique.

A new method of infrared image generation for typical aircraft that based on GPU is proposed. Complete procedure of infrared simulation including temperature model, radiation model, atmosphere model and image-forming system model is built in this paper. All of these models are solved and rendered with GPU which has powerful calculating ability. The result shows that dynamic infrared image of aircraft which varies with the status of aircraft could be generated efficiently with this method. Considering that temperature field could not be calculated real-timely and the unsatisfied simulation details in former infrared simulation methods, a new implementation method of calculating the temperature field with vertex texture of GPU is proposed.

Design knowledge of modern mechatronics product is based on information processing as the center of the knowledge-intensive engineering, thus product design innovation is essentially the knowledge and information processing innovation. Analysis of the role of mechatronics product design knowledge and information management features, a unified model of XML-based product information processing method is proposed. Information processing model of product design includes functional knowledge, structural knowledge and their relationships. For the expression of product function element, product structure element, product mapping relationship between function and structure based on the XML model are proposed. The information processing of a parallel friction roller is given as an example, which demonstrates that this method is obviously helpful for knowledge-based design system and product innovation.

This paper deals with the design of fuzzy tool for creating conceptual model under uncertainty. The paper identifies a problem in current approach of creating conceptual model of information system and suggests new methodics and tool for creating conceptual model, which can processes uncertain user requirements. The proposed tool uses a general model of the decision support system, that works with the vague input values and IF-THEN fuzzy rules, and creates a list of appropriate and acceptable solutions, and then allows to choose the best solution. In the proposed tool entities, attributes and relations between entitites in the resulting conceptual model are selected via a decision support system. In the paper we present six main parts of proposed tool, that generates suitable entities, attributes and relations between entities, then generates them to XML format and finally visualizes the resulting conceptual model. The created conceptual model illustrates the analysis of information system requirements. The proposed tool is shown on creating conceptual model of the hotel information system.

Port industries are the basic industries in the national economy. The industries have become the most modernized departments in every country. The development of the port industry is not only advantageous to promote the optimizing arrangement of social resources, but also to promote the growth of foreign trade volume through enhancing the transportation functions. Return on equity (ROE) is a direct indicator related to the maximization of company's wealth. It makes up the shortcomings of earnings per share (EPS). The aim of this paper is to prove the correlation between ROE and other financial indicators by choosing the listed port companies as the research objectives and selecting the data of these companies from 2000 to 2008 as empirical sample data with statistical analysis of the chartered figure and coefficient. The detailed analysis method used in the paper is the combination of trend analysis, comparative analysis and the ratio of the factor analysis method. This paper analyzes and compares all these factors and draws the conclusions as follows: Firstly, ROE has a positive correlation with total assets turnover, main profit margin and fixed asset ratio, while has a negative correlation with assets liabilities ratio, total assets growth rate and DOL. Secondly, main profit margin has the greatest positive effect on ROE among all these factors. The second greatest factor is total assets turnover, which shows the operation capacity is also an important indicator after the profitability. Thirdly, assets liabilities ratio has the greatest negative effect on ROE among all these factors.

Service-oriented software system is facing a challenge to regulate itself promptly because of the evolving Internet environment and user requirements In this paper, a new way that describe the dynamic evolution of services according to 3C mode(Will 1990) is proposed, and Extended workflow net is utilized to describe the abstract model of dynamic evolution of services from specific-functional-domain which is defined in this paper to the whole system.

To solve the problem of data quality in data warehouse, the process of data stream in data warehouse and the factors influencing data quality were analyzed; a method for controlling data quality based on quality grading was proposed and the frame of data quality grading system was established. In each process of ETL, the data quality grading system would execute script to calculate values, such as total, component and standard measures in accordance with the definition of Unit Measure, so as to get representation indexes; and then the quality report would be generated according to the indexes and the quality would be graded. The method is applicable to various data warehouse systems.

It is a new access control problem that how to protect individual privacy included by electronic records and ensure individual could control his privacy. Based on the Role Based Access Control (RBAC) model, the concept of electronic badge (E-badge) is introduced and E-Badge-Based Access Control (EB-RBAC) Model is proposed then a formal definition is defined. In the EB-RBAC model, person can set access policy of the privacy information. Users or roles obtain authority to operate the objects, only when access to an object is granted by the policies defined in its attached ebadges. These satisfy the design demands of the access control by this person can protect individual privacy.

This paper presents a design procedure for a Robust and Adaptive Fuzzy Logic based Power System Stabilizer (RAFLPSS) to improve the small signal stability of Power System. The parameters of RAFLPSS are tuned by adaptive neural network. This RAFLPSS uses ANFIS network (Adaptive Network based Fuzzy Inference System) which provides a natural framework of multi-layered feed forward adaptive network using fuzzy logic inference system. In this approach, the hybrid-learning algorithm tunes the fuzzy rules and the membership functions of the RAFLPSS. The dynamic performance of SMIB system with the proposed RAFLPSS under different operating conditions and change in system parameters has been investigated. The simulation results obtained from the conventional PSS (CPSS) and Fuzzy logic based PSS (FPSS) are compared with the proposed RAFLPSS. The simulation results demonstrate that the proposed RAFLPSS performs well in damping and quicker response when compared with the other two PSSs.

Distributed Embedded Systems have significant applications in automobile industry as steer-by-wire, fly-by-wire and brake-by-wire systems. In this paper, we provide a general framework for fault detection in a distributed embedded real time system. We use heartbeat monitoring, check pointing and model based redundancy to design a scalable framework that takes care of task scheduling, temperature control and diagnosis of faulty nodes in a distributed embedded system. This helps in diagnosis and shutting down of faulty actuators before the system becomes unsafe. The framework is designed and tested using a new simulation model consisting of virtual nodes working on a message passing system.

The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

Micro-blog websites are increasingly attracting the attention of academic and industry researchers. Its market value has been widely concerned and the exploration of its monetization model has entered a substantial stage. In this paper, we describe the history of Micro-blog and propose a comprehensive classification. We then discuss key characteristics based on existing websites mainly in China. A monetization model is concluded according to different features of microblog and the Hype Cycle theory[1]. The paper can be used for future academic research or making strategies for Microblog website practitioners.

Fuzzy logic controller is a controller for designing the challenging nonlinear control systems by If-Then laws that is like human intelligence and it increase the accuracy of the control action .This paper present a success control function using a Fuzzy System approach which is to control the Ball-Beam balance system, throughout modeling, simulation, and implementation. First we applied fuzzy logic for system which means for the outer loop a fuzzy logic controller is designed and for the inner loop of a ball and beam system a PD controller is implemented. We design a traditional PID controller and pole placement controller for the beam position in order to compare the performance of these three types of controllers; thus FLC found to give better transient and steady state results and there is less overshoot in compare with classical PID and pole placement controller. Simulation results are presented to show the better performance of the ball and beam using these controllers.

In This paper the previous Li-Ion battery charger techniques are reviewed and compared and the new fuzzy logic battery charging method which is proposed to optimize and improve the battery charger efficiently. According to results of comparison, using the fuzzy control charging system can shorten the charging time with higher efficiency and lower temperature rise. Additionally, we have used optimal Li-ion battery charging frequency by using AC impedance technique which means if the battery is charged by the optimal charging frequency fZmin, that obtain from Bode Plot of the Li-ion battery, the charging time and charging efficiency will improve. Thus using the switching frequency (fZmin) of the battery charger and the fuzzy logic control on the same system can optimize the performance on the charging process. According to the experimental results, the proposed charger can charge the Li-ion batteries with higher efficiency 97.16%, lower temperature rise1.513degree celosias, fast charging period around 50.43 minute and long life cycle. The results in this paper are presented by using MATLAB and dsPIC30F2020 is used as controller applying designed fuzzy logic inside.

Short span notifications or acknowledgment of events plays a major criterion in our world. Henceforth this module can be rigged up with any system in order to control the activity and acknowledge the user at any preconfigured parameter. Approximated that toxic chemicals are mixed every 14.7 seconds Over 2 million Aquatic Creatures are affected every year. About 65% of reported water pollution resulted from Tanneries and Chemical factories. The pH-COP bestows the solution for these catastrophic events. This module being robust can be attached to any system viz. Voltage monitor, Security system, Fluid level/ pressure controller, pH sensor cum controller, etc. The pH-COP primarily comprises of a microcontroller and a DTMF transceiver. This control systems which is efficient enough to be interfaced with the TELE-ALERT MODULE or the pH-COP.

With the continuous improvement of mobile performance, mobile entertainment applications market trend has been increasingly clear, mobile entertainment applications will be after the PC entertainment applications is another important business growth. Through the full analysis of the current mobile entertainment applications market demand and trends, the author has accumulated a lot of theoretical knowledge and practical experience. Rational, using of some new technology for a mobile entertainment games design, and described the development of key technologies required for mobile game an analysis and design of the game, and to achieve a complete game development. Light of the specific mobile game project - "Battle City", detailed the development of a mobile game based on the J2ME platform, the basic steps and the various key elements, focusing on how to use object-oriented thinking on the role of mobile phones in the abstract and Game Animation package, the source code with specific instructions.

Electro Discharge Machine (EDM) is the commonest untraditional method of production for forming metals and the Non-Oxide ceramics. The increase of smoothness, the increase of the remove of filings, and also the decrease of proportional erosion tool has an important role in this machining. That is directly related to the choosing of input parameters.The complicated and non-linear nature of EDM has made the process impossible with usual and classic method. So far, some methods have been used based on intelligence to optimize this process. At the top of them we can mention artificial neural network that has modelled the process as a black box. The problem of this kind of machining is seen when a workpiece is composited of the collection of carbon-based materials such as silicon carbide. In this article, besides using the new method of mono-pulse technical of EDM, we design a fuzzy neural network and model it. Then the genetic algorithm is used to find the optimal inputs of machine. In our research, workpiece is a Non-Oxide metal called silicon carbide. That makes the control process more difficult. At last, the results are compared with the previous methods.

Modern distribution systems use replication to improve communication delay experienced by their clients. Some techniques have been developed for web server replica placement. One of the previous studies was Greedy algorithm proposed by Qiu et al, that needs knowledge about network topology. In This paper, first we introduce a genetic algorithm for web server replica placement. Second, we compare our algorithm with Greedy algorithm proposed by Qiu et al, and Optimum algorithm. We found that our approach can achieve better results than Greedy algorithm proposed by Qiu et al but it's computational time is more than Greedy algorithm.

The main focus of this paper is to design a Fuzzy based control algorithm to realize an improvement in the input power factor of a multiple connected AC-DC converter fed drive system. It incorporates the role of fuzzy inference principles to generate appropriate PWM pulses for the power switches at the second stage of the power module. The philosophy is developed, with a view to reshape the input current phasor and enables it to align with the supply voltage wave in the perspective of improving the input power factor. The closed loop scheme evaluated using MATLAB based simulation exhibits an enhancement in supply power factor over a range of operating loads in addition to illustrating the speed regulating capability of the drive.

The proliferation of unstructured data continues to grow within organizations of all types. This data growth has introduced the key question of how we effectively find and manage them in the growing sea of information. As a result, there has been an increasing demand for efficient search on them. Providing effective indexing and search on unstructured data is not a simple task. Unstructured data include documents, images, audio, video and so on. In this paper, we propose an efficient indexing and searching framework for unstructured data. In this framework, text-based and content-based approaches are incorporated for unstructured data retrieval. Our retrieval framework can support various types of queries and can accept multimedia examples and metadata-based documents. The aim of this paper is to use various features of multimedia data and to make content-based multimedia retrieval system more efficient.

The decomposition algorithm is the one of the method that have be applied for converting large scale problem into one or more smaller problem. In the condition of uncertainty, one way is using fuzzy linear programming(FLP) to solve this algorithm . For solving FLP problems we can use ranking functions of fuzzy numbers. in this paper, we use a new ranking function suggested by Hajarri[11], and propose a method for solving fuzzy revised simplex algorithm and then apply this algorithm to solve fuzzy decomposition algorithm, in the case of bounded space.

In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.

We describe the requirements and architecture for decision making in the context of a home safety system. The architecture is capable of local- and network supported decision making. To develop and test the architecture in practice we define a use case of an elderly man in his daily chores. We also discuss the ethical concerns posed by such a system.

Existing data storage format can not meet the needs of information analysis, data warehouse onto the historical stage, the data warehouse is to support business decision making and the creation of specially designed data collection. With the data warehouse, the companies will all collected information is stored in the data warehouse. The data warehouse is organized according to some, making information easy to access and has value. This paper focuses on the establishment of data warehouse and analysis, design, data warehouse, two barrier models, and compares them.

The design and implementation of Real-Time Database System is a very complicated issue, a simulator for real-time algorithm research and evaluation is helpful. In this paper, we propose a simulator named AgiSim for real-time transaction scheduling and concurrent control, through which researchers can test, simulate and evaluate many real-time transaction scheduling and concurrent control algorithms. AgiSim is composed of transaction generation component, transaction scheduling component and data management component. The simulator is designed with UML, a state diagram and a sequence diagram of real-time transaction scheduling are given. Two mixed transaction schedulers are designed and simulated in AgiSim.

Support vector machine (SVM) was initially used for binary classification. How to generalize the result of two-class classification to multi-class classification has been a problem which needs to be more investigated and studied. A general overview of existing representative methods for multi-category support vector machines was presented and their performances were compared in the paper. Then, the algorithms were applied in the Chinese question classification. Chinese question classification hierarchy and the feature selection of the question were also discussed in the paper. Then, The four algorithms of SVM multi-category classification were applied to Chinese question classification and some contrast experiments were done. The result of the experiments has shown that the binary-tree algorithm is more effective than the other algorithms in the Chinese question classification.

Time dependent performance degradation due to negative bias thermal instability (NBTI) is one of the most important reliability concerns for deep nano scale regime VLSI circuits. Under worst case NBTI can degrade circuit performance in terms of timing by more than 10% over a period of 3 years. Reliability decisions taken early in system design can bring significant benefits in terms of design quality. The proposed approach deals with use of latches and NBTI aware scheduling of DFG to overcome the timing violations caused by NBTI. The experimental results suggest that it incurs a very low area overhead and no performance penalty. We propose an algorithm to schedule the DFG and show results for some of the common filters like EW and AR.