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The paper based public transport ticketing system, prevailing in the megacity Dhaka (Bangladesh), introduces severe malfunction in the system, malicious argument among public, corruption and most of all traffic jam. This paper actually suggests a much more public friendly, automated system of ticketing as well as the credit transaction with the use of RFID based tickets. The total system mainly acts to bring out the consistency among various bus agencies that will conclude in uniform access of passengers in daily rides through an automated server being updated every single time the passengers travel by carrying the RFID based tickets.

An online energy analysis system for paper machine dryer section is developed. The data and information share is realized in different types of database. Supervisory and analysis software plays an important role in the system, such as iFIX of GE and eTMS. the techniques of gathering and analyzing the real time data from the paper machine dryer section and communication between different software are also introduced. The running result of the test shows that the system has a good effect for the paper machine optimizing operation, energy-saving, and consumption-reducing.

With the rapid development of virtualization technology, virtual machine (VM) is widely used by cloud computing - the more and more popular computing paradigm. Thus, in order to guarantee the security of cloud computing, it is necessary to securely identify the kernel of VM, the software stack running on VM and the hardware platform which VM relies on. This paper designs a system of trusted connection based on virtual machine architecture and implements a system prototype. Our system not only can securely measure and identify the kernel of VM, the software stack running on VM and the hardware platform which VM relies on, but also can realize isolations to untrusted VMs. There are three main parts in our system: trusted chain, attestation and isolation. The experiments described in this paper prove that our system ensures trusted connection of VMs and achieves isolations to untrusted VMs. The performance of our system is also analyzed and evaluated. According to the analysis results, our system is practical in terms of performance.

Spatial Data Warehouses (SDWs) combine spatial databases (SDBs) and data warehouses (DWs) allowing analysis of historical data. This data can be queried using Spatial On-Line Analytical Processing (SOLAP). SDW and SOLAP systems are emerging areas that raise several research issues. In this paper, we refer to a different problem existing in SDWs that motivated us to propose a framework - a conceptual multidimensional model able to express users' requirements for SDW and SOLAP applications. We present a different research direction that is important to consider providing satisfactory solutions for SDW and for SOLAP systems. That important area is spatial query optimization. For the past several years, the research on spatial database systems has actively progressed because the applications using the spatial information such as geographic information systems (GIS), computer aided design (CAD) and multimedia systems have increased. However, most of the research has dealt with only a part of spatial database systems such as data models, spatial indexes, spatial join algorithms, or cost models. There has been a little research on the spatial query optimization which can integrate them. Most of the spatial query optimization techniques published until now has not properly reflected the characteristics of the SDBs. This paper presents query optimization strategies which take the characteristics of SDBs into account. The application of standard query processing and optimization techniques in the context of an integrated SDB environment is discussed.

This paper presents a method to improve the performance of Information Retrieval System (IRS) by increasing the no of relevant documents retrieved. There are several types of uncertainty and fuzziness associated with IRS like search term uncertainty, relevance uncertainty involved in retrieving of irrelevant documents. The aim of this paper is to eliminate different types of uncertainty and increase the chance of retrieving relevant documents. In the framework a method is proposed which first calculate query and document cluster similarity which not only retrieve the documents matching query terms as well as similar to retrieved documents by calculating the query and cluster similarity. This helps to reduce search term uncertainty and tries to reduce the fuzziness associated with document relevance in two steps. First modification is made in general term frequency-inverse document frequency (tf-idf) scoring mechanism to give importance of informativeness of a document contents and secondly calculating query and document summary overlap. All the above information is used to measure the document relevant score. Finally retrieved documents are filtered by Pearson correlation coefficient between query vector and document vector to find out only those documents correlated with query. In experiment standard NPL test collection prepared by Vaswani and Cameron at the National Physical Laboratory in England was used. After full implementation of above methodology it was found that proposed work is better in comparison with existing methods.

In this paper with studying of all parameters in grid environment a new scheduling algorithm for independent task is introduced according to Genetic Algorithm. This algorithm can be more efficient and more dependable than similar previous algorithms. The simulated results and reasons for reaching to better makespan and more efficiency in the grid environment. In the grids with high fault with high fault rate for fault tolerant is used from check point method that has more efficiency that other methods such as retry, migration and replication. This method maintains effective efficiency in these situations. So the servicing quality increases in various grid environments and also the average time of task recoveries decreases considerably The main purpose of this paper is reducing the repeating of the generations in Genetic Algorithm for reaching higher speed and also considering the communications costs (available in fitness function) with maintaining the fitness efficiency. The simulations are done with Gridsim for showing the created improvement at proposed algorithm rather than previous algorithms.

The paper deals with the text classification problem where labeled training samples are very limited while unlabeled data are readily available in large quantities. The paper proposes an efficient classification algorithm that incorporates a weighted k-means clustering scheme into an Expectation Maximization (EM) process. It aims to balance predictive values between labeled and unlabeled training data and improve classification accuracy. Since the algorithm is based on a fast clustering method, it can be applied to classify documents in large datasets. Preliminary experiments with several text classification collections show that the proper use of unlabeled data built in this proposed text classification algorithm could significantly improve classification accuracy.

Data mining has attracted a great deal of attention in higher education in recent years, not only in student's management, but also teacher's management, such as individualized personnel training, prediction and comparison on students' achievement, online teaching, teaching effectiveness evaluation, and so on. However, the research and application of data mining technology to teachers' position settlement have not yet carried out. This paper utilizes the famous data mining software SPSS Clementine to two-step cluster analyze teachers' position settlement, and shows through an example. This paper can provide strong information support for administrators to set positions, thus deepen reformation.

Security is to grant access to a legal user, and to prevent the system from illegal or non authorized person. The so called process of Authentication has five factors in modern era. Something You have (e.g., a hardware token/credit card), Something You are (e.g., a fingerprint, eye print), Something You know (e.g., a password/PIN code), Somebody You know and Something You Process. In this paper, we have developed such a technique which provides more security to a user in typing his password, in a public place, and in case that user is in critical position, of accessing his computer system. In this paper we have developed a technique of Authentication by the factor “Something You Process”. SHOULDER ATTACKS is one of the latest weapons used by hackers or adversaries in an organization to hack an account or to authenticate in a secure zone. In a shoulder attack a person is watching the user while he is typing the password and reads his fingers that what he has typed or makes a video of him typing the password and so comes to know that what the password is.

Trust and reputation systems are widely used in electronic commerce, social network, search engine, and so on. They have become a very important element in cyberspace. However the theoretical research actualities of this field are lagging behind applications. Various existing works are rarely relevant and without consensus. Aiming at the above problems, this paper proposes a general model for trust and reputation systems. The model mainly solves the following basic problems in this field: i) redefine the concepts of trust and reputation and discuss the relationship between them; ii) design and construction of the general model, especially the basic element of trust and reputation systems, and iii) the applications of the general model for trust and reputation systems. According to this work, this paper gets some key results of this field. These results will provide research foundations and framework for the future work.

In order to solve the problem of face recognition in natural illumination, a new face recognition algorithm using Eigenface-Fisher Linear Discriminant (EFLD) and Dynamic Fuzzy Neural Network (DFNN) is proposed in this paper, which can solve the dimension of feature, and deal with the problem of classification easily. In this paper, we use EFLD model to extract the face feature, which will be considered as the input of the DFNN. And the DFNN is implemented as a classifier to solve the problem of classification. The proposed algorithm has been tested on ORL face database. The experiment results show that the algorithm reduces the dimension of face feature and finds a best subspace for the classification of human face. And by optimizing the architecture of dynamic fuzzy neural network reduces the classification error and raises the correct recognition rate. So the algorithm works well on face database with different expression, pose and illumination.

This paper focus on the methods of the build process of Real-Time Workshop (RTW), the influencing factors on code efficiency and development of a custom embedded target. In order to generate embedded C code and download it to a user-specified micro-controller (Freescale™ MC9S08DZ60 for example in this paper) conveniently, an embedded target is developed. The embedded target developing consists of the target device drivers and the interface to CodeWarrior IDE. The user can develop custom device drivers by following the steps of creating a C MEX S-function, masking the blocks and writing TLC files. In particular, this paper provides the ways of designing two special blocks for interrupt service routine (ISR) and target resource configuration. Through the comparison between automatic generation codes and codes written by bands in PC environment and embedded system, it is concluded that automatic generation codes is accurate and efficient, but the execution time is slower than the code written by hand in micro-controller.

AdaBoost is known as an effective method for improving the performance of base classifiers both theoretically and empirically. However, previous studies have shown that AdaBoost is prone to overfitting, especially in noisy domains. On the other hand, the k-nearest neighbors (kNN) rule is one of the oldest and simplest methods for pattern classification, when cleverly combined with prior knowledge, it often yields competitive results. In this paper, an improved boosting algorithm is proposed where AdaBoost and kNN naturally complement each other. First, AdaBoost is run on the training data to capitalize on some statistical regularity in the data. Then, a weighted kNN algorithm designed in this paper is run on the feature space composed of classifiers produced by AdaBoost to achieve competitive results. AdaBoost is then used to enhance the classification accuracy and avoid overfitting by editing the data sets using the weighted kNN algorithm for improving the quality of training data. Experiments performed on ten different UCI data sets show that the new Boosting algorithm almost always achieves considerably better classification accuracy than AdaBoost.

To the limitation of the application of professional GIS tools in the development of landslide stability evaluation system, the method to develop landslide stability evaluation software based on the underlying GIS platform is discussed in the paper. Firstly, a vector graphics system which can handle points, lines, polylines, circles, arcs, polygons and text annotations is constructed. And then a database system which can save and query the geometries and the attributive information is developed. Then the underlying GIS platform, which can manage the spatial data, execute the spatial relationship operation and realize the visualization of spatial data, is formed after integrating the vector graphic system and database system. Based on this underlying GIS platform, a landslide stability evaluation system is developed at last. With the help of this GIS platform, the identification of the slip surface, the slice division and the calculation and extraction of parameters of the slices can be done easily. And the safe coefficient of the landslide which is waiting for evaluating can be worked out and stability level of the landslide can be determined successfully by the system. The stability evaluation software developed in the paper also consider the affection of surface load and reinforced to the stability of the landslide and the most dangerous slip surface can be searched according to the envelop region given by the users. The examples given by Australian Computer Application Society are used in the experimental calculation to verify the accuracy of the system. And the calculation results show that the software developed in the paper is accurate, reliable and of high practical value.

In the implementation of Observer pattern by OOP, the subject objects and the observer objects must implement an interface or extend an abstract class to indicate their roles. When the pattern is implemented by AOP, there is not such a requirement. The participants and their relations are defined in an aspect, it isn't necessary for these participants to implement an interface or extending an abstract class. But users are required to know an aspect language to use this method. This paper provides a novel method to implement this pattern; participant objects and their relations are defined by Java annotations. On the basis of analyzing Observer pattern implemented by AOP, the paper discusses how to define annotations to annotate participant classes and define their relations, how to establish the association between the subject and the observer is discussed in details. After analyzing classes annotated, the aspect is generated, then compiling and weaving this aspect with the target classes is done. So users may use Aspect implementation by Java annotation.

Aiming to overcome the shortcomings of Grid resource discovery, this paper presents a Grid resource discovery model with different layers, which adopts P2P (Peer-to-Peer) technology in Grid resource discovery mechanism. The model includes three layers based on three different peers: the Super peer_Agent, Super Peer and Ordinary peer. According to the model, this paper produces a novel Grid resource discovery algorithm, which adopts Keywords Mach algorithm based on Hash Table, employees TF_IDF to product resource keywords, locates and search s resource based on Consistent Hashing Chord, access lower latency and higher credibility peer by ant colony algorithm based on adaptively adjusting pheromone. It is testified by simulation implement that the algorithm can find the most suitable resources and improve resource discovery efficiency.

Spatial data compression is particularly important for the development of Mobile GIS. This paper gives a review on vector data compression of Mobile GIS. Firstly, the definition and classification of vector data compression algorithms are introduced. Secondly, the traditional, new and optimal algorithms are analyzed separately, and their principles, research status, strengths and weaknesses are further discussed in detail. In the end, this paper makes an important comparison among Douglas-Peucker algorithm, wavelet-based algorithm and dynamic programming-based algorithm.

Assessment for computer network attack is a technology for assessing hostile attacks against computer network system. In the paper, relevance vector machine is applied to assessment for computer network attack. Compared with support vector machine assessment method, the RVM method can provide better classification accuracy. The experimental data collected in the paper include U2R attack, R2L attack, Probe attack and DoS attack. It can be seen from the experimental results that it is an effective model for assessment of network attack.

The degree to which a cryptographic protocol is susceptible to successful attacks or penetrations cannot be accurately calculated because of the more fine and fast algorithms to break ciphers, being introduced. To deal with the issue, analysis of a cryptographic protocol becomes more vital; and more exhaustive search for vulnerabilities is required. Kerberos is a widely used security protocol for authentication of the communicating parties. It is usually thought to be the most secure protocol. In this paper, it is shown that a man in the middle attack is possible against Kerberos protocol. This is done using the Strand Spaces, where a series of attacks are carried to verify the authenticity of participants in the Kerberos protocol using formal methods. To make the paper self-contained we also provide a solution on how to solve the problem.

The Apriori algorithm is a most influential one to excavate association rules. The basic idea of the algorithm is: identify all the frequent itemsets to get association rule. This paper presents the improved Apriori algorithm based on interested items, which mainly construct an ordered interested table and traverse it to excavate frequent itemsets quickly. The paper also by writing c# code achieves the improved algorithm. Confirmed by many experiments, this algorithm is better than traditional algorithms in time consuming.

Methods for the identification of temperature in intelligent building and building equipments is one of hot topics focused by lots of researchers in that research area. To implement the process of inspecting and forecasting of energy efficiency in building and its accessory, a feed forward neural network is used as the identification structure for temperature identification of internal space in building in this paper and Identification parameters of the identification structure optimized with genetic algorithm is given in this paper too. The number of neurons in input layer of desired network is optimized with RBF neural network and the number of neurons in hidden of the desired network is optimized with BP neural network in our experiment. Experimental results show that the precision and stability of our proposed method are good enough with time requirement satisfied.

Logs are important sources of the security audit systems, this paper analyzes the defects of traditional security audit systems, and proposes the forward-secure digital signature scheme as the tamper resistance protection of the server logs. Even if the signer's private key is divulged, the attacker can still not recover the plain message of the signcryption of this and past time, so he can not tamper the logs which are encrypted before key exposed. In this paper, we describes the scheme's theory and implementation. And we make simulation test and security analysis in detail. Finally, We come to the conclusion, the scheme can effectively resist any illegal tamper on historical logs.

Studied the basic framework of the knowledge collaborative supply chain management system based on SOA under the SaaS model, this paper proposes the knowledge collaborative supply chain management system architecture based on SOA under the SaaS model. Futherrnore, after the in-depth research on the key technical knowledge coordination, knowledge-based web service request and response dispatching of the architecture, the paper builds a knowledge collaborative supply chain management prototype system based on SOA under the SaaS model.

This paper presents a new type of a more complete system verification method, which combines a high-level verification methodology based on verification methodology manual (VMM) techniques for functional simulation and system-on-a-programmable-chip (SOPC) techniques for board-level verification, effectively improve the adequacy and reliability of verification and validation efficiency. This paper gives a scalable hierarchical verification platform used systemverilog, which achieved the constraint-random stimulus generation, assertion monitoring, automatic real-time comparison for outputs and coverage statistics. Additionally, this paper describes the development of the test environment and the entire physical verification platform.

Today information systems have become the key factor of current computer based engineering applications. So database are designed to support data storage, processing, and retrieval activities related to data management, and they are the key to implementing engineering information models. However, the current mainstream databases are mainly used for business applications, some new engineering requirements challenge today's database technologies and promote their evolvement. The main focus of this paper is to determining the requirements of a database for STEP-Geometry entities that supports integrity validation of versioned design artifacts through effective management of evolving constraints. In this paper develop a tool for separate and store the geometric data from STEP file using EXPRESS entities. Finally this tool operates around a version model that uses a well-defined configuration management strategy to manage and storage of geometric data.

the paper suggests a meta-ontology for C4ISR capability conceptualization. Under which, by taking advantage of the UML profile mechanism, the paper defines a domain-specific modeling language for C4ISR capability requirement. The abstract syntax, concrete syntax and formal semantic of the modeling language have been discussed in the paper. A case study of C4ISR architectural simulation modeling is provided to demonstrate the availability and applicability of the language.

Since e-commerce always suffers from the uncertainty, cheats and attacks, concepts of trust and risk are introduced into e-business. Several models or frameworks to deal with uncertainty and threats have been proposed, but the system cannot adjust policies appropriately to the changing strategies by malicious attackers in time. Existing frameworks that contain game theory are not very applicable to the ecommerce. This paper presents a novel framework which considers trust and risk as two key dimensions and utilizes static game model with incomplete to obtain optimal solutions in e-commerce. The combination of game model, trust and risk can strengthen interactions in e-commerce. In addition, a new model of trust evaluation is proposed to represent the confidence in the peer. To appease people's anxiety about loss, a model of risk assessment is also presented to indicate impacts on resources. At the end of this paper, simulation results also indicate that our framework is able to enhance interactions in e-commerce more powerfully, efficiently and rationally.

The paper is about the identification method of event descriptive unit based on the rules of predicate identification and consolidation, in order to divide the whole sentence into event descriptive unit. The training set and testing set involved in the experiment are from TCT Corpus of news academic. Through the rules summarized from the event descriptive unit in 14248 sentences, 3751 sentences have been identified into event descriptive unit automatically. The experiment shows that by the method of rules handling, event descriptive unit can be identified effectively. The paper is supported by Science and Technology Department of Shanxi Province international cooperation and exchange project “China-Japan Cooperation Research on Chinese Intelligent Interactive Question and Answer System Based on Web” (Grant No.2009g18).

The 3D terrain visualization of coastal zone is based on the seamless integration of geospatial data from water to land. Because of the differences in surveying methods and application areas, the land elevation data and the water-depth data are different in spatial reference, data accuracy and data type. This paper presents a methodology to integrate multisource terrain data of coastal zone and build an integrated DEM from water to land. Based on the C++ and OpenGL, this paper offers a 3D visualization system which realizes the realistic 3D terrain visualization of coastal zone with the instantaneous shorelines generation.

Even as the rate of IPv6 deployment increases, there continues to be a number of key technical, operational and political challenges that have limited the overall adoption rate of IPv6. This paper is intended to explore the IPv6 technical features, advantages, research improvements, potential business benefits. This paper also investigates how some of the challenges have slowed the transition process to date and will also address some of the common myths about IPv6 adoption. A special attention is paid on this paper to highlight the key issues behind the IPv6 co-existence with IPv4 and to accelerate and promote the research directions. The paper will help the companies and enterprises to realize the benefits and move to the immediate deployment of IPv6 enterprise environments globally.

In this paper we present a new algorithm that extends Seitz and Dyer's voxel coloring algorithm [1]. This paper explores a method of voxel coloring which scans only the voxels on the surface of 3d reconstructed scene and the voxels of the nearest neighbors of the 3d reconstructed scene. This method reduces significantly the number of voxels to be processed and retaining the accuracy of actual voxel coloring method. With our algorithm, the time complexity rather than being O(n3), reduces to O(number of voxels on the surface of reconstructed scene). The significant advantage of our algorithm can be seen while increasing the number of voxels (or reducing the size of voxels), for greater accuracy of reconstructed results. We present efficiency measurements for comparisons. Our algorithm can also be used with the Voxel coloring method reported in [2], increasing significantly the speed of the scan.

this paper analyzes and contrasts the development of modern general examination systems first. We make a summary of existing Examination Evaluation Systems and indicate the shortage that exists in them. Design and Implementation an Examination Evaluation System which is base on a certain type of equipment's Multimedia Emulation Repair Training System. Use Visual Studio 2003 as a platform to develop the Examination Evaluation System. This paper focuses on the characteristics and methods of one kind of Examination Evaluation System which for the purpose of simulation training.

In this paper, we introduce an effective method of ontology data management on flash memory based SSD. Ontology is the concept to manage semantic web data. However, ontology is used not only in semantic web but also in life sciences, intelligence and CRM/ERP nowadays. Adapting ontology concept on these field, ontology have been managing large amount of data. Therefore, we suggest the effective method to enhance random reading of large ontology data by using SSDs in this paper.

This paper studies how computer games can be used to popularize the forestry science knowledge and proposes a method of 3D game development based on Virtools platform, which creates 3D models in 3ds max and Maya, then realizes the game functions in Virtools. This paper designs and develops a game based on 3D forest scenes which gets a better balance between knowledge and gameplay. The game enhances the users' interaction experience by adding the gamepad, and has high referential and practical value. Computer games will play an increasingly important role in the popularization of forestry science.

Nowadays, it is certain that we have to deal with massive data and abstract implicit regularity from massive data. In this paper, the reduction algorithm based on Rough Sets is proposed as a practical data mining technology and the procedure of telecommunication decision is analyzed. In the paper, the procedure of telecommunication based on data mining of Rough Sets is discussed. The factor set is established including condition attribute and decision attribute. The attribute reduction algorithm based on Rough Sets is used to eliminate the redundant risk factor and its value of decision table. It can be generalized to some useful rules and we can make proper decision from the rules to improve precision and explanatory ability in practice.

This paper proposes a framework for consolidating laboratory data by adopting an Enterprise Service Bus as a backbone for interchanging laboratory data between: medical instruments, the Laboratory Information Management System and the Hospital Information System. A laboratory test result is one of the major components in medical diagnosis and procedures. It can be used to plan a patient's treatment and monitor the disease over time. The existing architecture has two disadvantages, the security and maintenance issues. The proposed framework can tackle these limitations and reduce the time interval for polling the test requests and results. The Enterprise Service Bus is used for the connectivity layer in the proposed framework and it provides many advantages. The paper also shows the implementation of the proposed framework.

In this paper, the authors discussed in detail about the framework of integrating Radio Frequency Identification (RFID) with Building Information Modeling (BIM) technologies. The proposed framework can be used in the computer-aided design, manufacturing, engineering, and installation processes. In specific, this paper explained how to use RFID technology for structural steel components, such as a steel beam or column. The paper discussed the framework of the decision support system to transmit data read from RFID, retrieve the requested information, integrate the information in analysis process, and update the BIM project model when a decision is reached. The suggested result would have great potential of saving installation time, decrease cost, improve safety record, or achieve better quality in the end of the construction process.

This paper introduces a approach of TD-HSUPA modeling for system level simulation and then proposes the framework of TD-HSUPA system level platform. The focus in this paper is on the introduction of core models of this platform. This approach is based on discrete event and time-driven mechanism. The simulation framework, which is programmed by Matlab software, is aim to analyze the significant performance for TD-HSUPA system and provide reliable parameters in network planning and dimensioning. Consequently, the cost of network construction is reduced, and the construction period is also shorten.

Anonymous authentication is an important feature for trusted computing. Firstly, this paper describes two kinds of authentication model Trusted Computing Group (TCG) proposed -TTP model and DAA model, and then analyses their advantages and disadvantages. Secondly, the paper proposes an improved solution based on the elliptic curve algorithm (ECC) in the base of the original DAA model. Finally, the paper detailed analysis the performance of the improved solution.

A method of the remote upgrade proposed in this paper because of the problem of software upgrades and maintenance difficulty in wireless network optimization monitoring system base on the Flash memory of LPC2138. And details of hardware and software realization are proposed in this paper. It not only supports the function of software upgrades and resuming broken downloads, but also supports the function of switching software versions in old and new. Experiments show the validity of this method and the applicability for practical projects.

Image segmentation is a relevant research area in Computer Vision, and several methods of segmentation have been proposed in the last 40 years. This paper presents the implementation using the GUI feature of the MATLAB and one best result can be selected for any algorithm using the subjective evaluation. This process can help to find out the best suitable value of parameters for the segmentation of different types of imagery. In this paper, one best algorithm has considered for each method of image segmentation. The interactive based method provides the facility to select the desired area as an object and produces better result. The proposed process also displays the duration of segmentation of each algorithm.

Automated test case generation from use cases in early development phase is of great benefit to system testing. The paper proposes IFA (interaction finite automaton), a state based model concentrating on formulizing a system's behaviors specified in use cases without knowing its internal structures. The algorithms for transformation from use cases to IFA and generating test cases from IFA are represented in detail. Based on these algorithms, test cases could be generated from use cases automatically. The supporting tool is also presented in this paper.

In this paper, we present the theory and methods which implement the rapid web publication of spatial data based on WebGIS system using ArcGIS and other open-source software. The original spatial data is configured and landscaped by ArcMap or ArcIMS Author, to generate MXD or AXL files. Subsequently, corresponding map service could be easily created by ArcIMS Administrator. And then, some programming work is carried out to build hierarchical map tiles, and further to achieve the organization and management. The key technologies include coordinate conversion, map tiles generation based on Java program, storage strategy based on five-level directory, and management platform based on web application. Finally, the map tiles would be rapidly and seamlessly published in web pages. The method is successfully applied in our research projects, which are demonstrated in the last section of the paper.

A proxy signature scheme is an important extension of the digital signature scheme, nowadays, is an active research topic, which attracts more researchers' attentions. As an ordinary digital signature scheme, a proxy signature is a vulnerable to the key exposure problem. In case, the secret signing key of the authorized user is be revealed or stolen. The aim of this paper is to put forth a proxy signature scheme, which has forward secrecy technique to mitigate the damage caused by the key exposure problem, which is proved secure. In this paper, the definition and security model of a forward-secure proxy signature scheme is formalized. Then, a generic forward-secure proxy-protected signature scheme is proposed based on the strong RSA assumption. By the reduction proof technique, the proposed scheme is proved secure against existential forgery adaptive chosen message attacks.

Internet evolution, along with the advancement of digital multimedia tools have create a major impact in making the storage and distribution of multimedia content a straightforward tasks. Thus security of multimedia contents becomes a vital issue and there is a need in protecting the digital content against counterfeiting, piracy and malicious manipulations. Digital watermarking is an evolving field that requires continuous effort to find for the best possible method in protecting multimedia content. In this paper, we describe overview of digital image watermarking technique and proposed an algorithm for copy write protection of digital images in DCT domain. Digital watermarking can be defined as the process of embedding a certain piece of information, technically known as watermark into multimedia content including text documents, images, audio or video streams, such that the watermark can detected or extracted later to make an assertion about the data. We have also implemented this algorithm using MATLAB 7.x and code is also given in this paper.

Cloud computing, as an emerging computing model, is drawing much attention from academia and industry. Storage resource, computing resource and network resource are three basic resources in a cloud computing infrastructure. How to utilize these resources efficiently and conveniently is a big challenge for building a good cloud computing infrastructure. This paper presents a service-oriented storage resource architecture intended to enable efficient storage resource utilization and management in a cloud computing infrastructure. A Web Service-based hierarchical Storage Resource Management approach is introduced into the design and implementation of such a system, and a concept-proofing system built on LAN and Linux has been developed. A WAN-based prototyping system is under development. Another idea of this paper is that it hopes to bring in a new prospective for the research of cloud computing infrastructure.

The problem of memory leakage in Java applications is researched in this paper. Our purpose is to find out the instances where the memory leak appears and to put forward the solutions to avoid it. Although the Garbage Collection (GC) mechanism can be regarded as the special Java function to release objects automatically by the garbage collector, the problem of memory leakage still exists in Java applications frequently. In this paper, the leakage problem is researched from memory mechanism of JVM, and some experiments are done in accordance with the way of memory access in Java. At last, the causes of memory leakage are classified and analyzed, and then the solutions to avoid this problem are proposed.

In the mobile agent system, the authentication and identity delegation of mobile agents are the important security problem. This paper focuses on the issues faced by a relying party when deciding to trust a CA and the certificates that it issues. The scope of this paper is limited to examining the basis for trusting a relying party places in an identity certificate signed by a CA. Some of the working group's discussion of the authentication and delegation of identity of mobile agent are also presented. This paper also gives a way to protect private keys and identity certificates in the mobile agent environment. The mobile agent and agent platform can use these certificates to build trust relationships between the CA and its registration authorities, or trust relationships between the end entities and the service providers.

Due to technological advances of handheld computing and communication devices, Mobile commerce (M-commerce) has emerged and attracted a growing number of research efforts. M-commerce not only extends Internet-based Electronic commerce (E-commerce), but also offers a unique business opportunity with its own features, such as ubiquity, accessibility, portability, etc. In this paper, we discuss some important issues in the design of an M-commerce platform based on agent technology and context-aware workflow analysis. Deploying mobile agents and context-awareness in M-commerce can reduce unnecessary network traffic, tolerate poor network connectivity, provide more advanced services, support automation of decision-making, reduce participation costs and improve trading efficiencies.

Network is more and more popular in the present society. Least squares support vector machine is a kind modified support vector machine for classification, which can solve a convex quadratic programming problem. Least squares support vector machine is presented to network intrusion detection. We apply KDDCUP99 experimental data of MIT Lincoln Laboratory to research the classification performance of LS-SVM classifier. Support vector machine, BP neural network are used to compare with the proposed method in the paper. The experimental indicates that LS-SVM detection method has higher detection accuracy than support vector machine, BP neural network.