Showing papers in "Cybernetics and Information Technologies in 2014"

An optimized scheduling algorithm on a cloud workflow using a discrete particle swarm

Abstract: In order to solve the problems of security threats on workflow scheduling in cloud computing environments, the security of tasks and virtual machine resources are quantified using a cloud model, and the users' satisfaction degree with the security of tasks assigned to the virtual resources is measured through the similarity of the security cloud. On this basis, combined with security, completion time and cost constraints, an optimized cloud workflow scheduling algorithm is proposed using a discrete particle swarm. The particle in the particle swarm indicates a different cloud workflow scheduling scheme. The particle changes its velocity and position using the evolution equation of the standard particle swarm algorithm, which ensures that it is a feasible solution through the feasible solution adjustment strategies. The simulation experiment results show that the algorithm has better comprehensive performance with respect to the security utility, completion time, cost and load balance compared to other similar algorithms.

Analysis Of Hotspots In The Field Of Domestic Knowledge Discovery Based On Co-Word Analysis Method

Abstract: In this paper, choosing highly frequent keywords from core journals in the field of 1992-2013 national knowledge discovery in CNKI database, counting the number of two frequent keywords co-occurrences in the same journal, then constructing the highly frequent keywords matrix, and transforming the highly frequent keywords matrix into a correlation matrix and a dissimilarity matrix, we analyze the dissimilarity matrix based on the use of factor analysis, cluster analysis. After discussing the results of the analysis, we found that the current hotspots in the field of domestic knowledge discovery have focused on the following six aspects, knowledge discovery based on data research, knowledge discovery algorithm optimization research, the model of knowledge discovery and references research, knowledge management based on domain ontology, expert system construction research, and applied research of the knowledge discovery. Finally, we summarized the research hotspots in the field of international knowledge discovery in the same way and suggested the domestic scholars to extend some directions of the research in the field of knowledge discovery.

Secret Image Sharing Scheme Based on a Boolean Operation

Abstract: Traditionally extensive researches have been done on secret image sharing which support the fault tolerance property. But their reconstruction complexity is high. Some research papers on secret image sharing are also available with smaller reconstruction complexity, due to the use of a Boolean operation. But these research works lack the fault tolerance property which is the heart of secret sharing. This paper deals with a general k, n secret image sharing scheme for gray scale images with both low reconstruction complexity and preservation of the fault tolerance property. Moreover, the proposed sharing generation technique can also be applied on colour images.

A Teaching Quality Evaluation Model Based on a Wavelet Neural Network Improved by Particle Swarm Optimization

Abstract: In order to improve the teaching quality of higher education, the paper constructed a teaching quality evaluation index system with five first level indicators and twenty two second level indicators according to the teaching level evaluation index system of ordinary higher education. For the complex nonlinear relationships between the evaluation indices, a mathematical model for evaluating the teaching quality based on WNN, whose parameters were optimized by PSO, was presented in the paper. The experimental results showed that the method proposed could better improve the accuracy of the teaching quality evaluation target by making the mean square error of the actual output value and the desired output value smaller. Simultaneously, the method has been widely used in teaching quality evaluation of our college.

Natural Language Generation and Semantic Technologies

Abstract: The paper presents a survey of the domain of Natural Language Generation NLG with its models, techniques, applications, and investigates how the semantic technologies are drawn into text generation. The idea and facilities of Semantic Web initiative are discussed in connection with the new opportunities offered to the Natural Language Generation.

Improved structure-adaptive anisotropic filter based on a nonlinear structure tensor

Abstract: A variety of structure-adaptive filters are proposed to overcome the blurred effects of image structures caused by the classical Gaussian weighted mean filter. However, two major issues are needed to be dealt with carefully for structure-adaptive anisotropic filters. One is to properly construct the filter kernel and the other is to accurately estimate the orientation of the image structures. In this paper we propose to improve the structure-adaptive anisotropic filtering approach based on the nonlinear structure tensor NLST analysis technique. According to the anisotropism measurements of image structures, a new kernel construction method is designed to make the filter shape fine adapted to image features. Through the accurately estimated orientation of the image structures, the filter kernels are then properly aligned to perform the filtering process. Experimental results show that the proposed filter denoises the noisy images carefully and image features, such as corners and junctions are well preserved. Compared with some other known filters, the proposed filter obtains great improvements both in Mean Square Error MSE and visual quality.

A Virtual Firewall Mechanism Using Army Nodes to Protect Cloud Infrastructure from DDoS Attacks

Abstract: Cloud is not exempted from the vulnerability of Distributed Denial of Service (DDoS) attack, a serious threat to any distributed network and has considerably less effective solutions to deploy in the network. This paper introduces a novel mechanism to protect and prevent the cloud from the spurious packets targeting the depletion of server resources. The army nodes called "Cloud DDoS Attack Protection" (CDAP) nodes are installed at the cloud server farm/ Datacenter (DC). These army nodes act as virtual firewall without destroying the Cloud Infrastructure and improve the availability of DC, even at the time of DDoS attack. By continuously monitoring the incoming packets, CDAP filters the attack packets intruding the Cloud DC. Availability is further improved by handing over the threat detection and attack mitigation to CDAP nodes and by redirecting the malicious user requests to the dump network. The simulation results prove that the introduction of CDAP nodes improve the availability and reduce the response time and the cost incurred.

Codes on Key Errors

Abstract: Coding theory has started with the intention of detection and correction of errors which have occurred during communication. Different types of errors are produced by different types of communication channels and accordingly codes are developed to deal with them. In 2013 Sharma and Gaur introduced a new kind of an error which will be termed "key error". This paper obtains the lower and upper bounds on the number of parity-check digits required for linear codes capable for detecting such errors. Illustration of such a code is provided. Codes capable of simultaneous detection and correction of such errors have also been considered.

Feedback Linearization Control of the Inertia Wheel Pendulum

Abstract: Abstract In this paper, two feedback linearizing control laws for the stabilization of the Inertia Wheel Pendulum are derived: a full-state linearizing controller, generalizing the existing results in literature, with friction ignored in the description and an inputoutput linearizing control law, based on a physically motivated definition of the system output. Experiments are carried out on a laboratory test bed with significant friction in order to test and verify the suggested performance and the results are presented and discussed. The main point to be made as a consequence of the experimental evaluation is the fact that actually the asymptotic stabilization was not achieved, but rather a limit cycling behavior was observed for the full-state linearizing controller. The input-output linearizing controller was able to drive the pendulum to the origin, with the wheel speed settling at a finite value

Iot Forest Environmental Factors Collection Platform Based On Zigbee

Abstract: Nowadays the development of Internet of Things IoT technology has witnessed great changes in the world. As it has often been mentioned, IoT Environment Monitoring Technologies and IOT Smart Home Technologies have been gradually accepted by people and have good prospects for development. Now we can research a networking based intelligent platform to monitor our forest environmental factors in time with the new IoT technology based on ZIGBEE protocol. ZIGBEE based networking technologies has the advantages of low power dissipation, low data rate and high-capacity transportation, which makes it more suitable for the design of the node of forest environmental factors collection platform. So, we are going to discuss a kind of IoT forest environment factors collection platform based on ZIGBEE protocol.

Rqa based approach to detect and prevent ddos attacks in voip networks

Abstract: Voice over Internet Protocol VoIP is a family of technologies for the transmission of voice over Internet. Voice is converted into digital signals and transmitted as data packets. The Session Initiation Protocol SIP is an IETF protocol for VoIP and other multimedia. SIP is an application layer protocol for creating, modifying and terminating sessions in VoIP communications. Since SIP is a more flexible and simple protocol, it is quite easy to add features to it. Distributed Denial of Service Attack DDoS floods the server with numerous requests from various hosts. Hence, the legitimate clients will not be able to get their intended services. A major concern in VoIP and almost in all network domains is availability rather than data consistency. Most of the surviving techniques could prevent VoIP network only after collision. This paper proposes a Recurrence Quantification based approach to detect and prevent VoIP from a DDoS attack. This model detects the attack at an earlier stage and also helps to prevent from further attacks. In addition, this techniques enables the efficient utilization of resources. QUALNET has been used to simulate the operation of the proposed technology.

A Prevention Model for Session Hijack Attacks in Wireless Networks Using Strong and Encrypted Session ID

Abstract: Most of the web applications are establishing the web session with the client. It is very important to protect the wireless networks against session hijacking attack. Session Hijack attack is easy to execute and difficult to detect. Wireless networks do not have specific boundary regions for the packets to be transferred. As the data packets are transferred in air, the chances of sniffing the network packets by the hackers or attackers are high by using the network sniffing tools. In this paper, we have proposed the Strong and Encrypted Session ID to prevent the session hijack attacks in web applications. Session ID is generated and the generated Session ID is encrypted, using a Secret Key Sharing algorithm and decrypted at the client side. We have tested the integrity of the session ID of length 32, 92 and 212 characters in a web application. Attacks are executed to capture the session ID of a web application. Our experimental results proved that 212 characters encrypted session ID completely prevents the session hijack attacks in web applications of wireless networks.

A Unified Modeling Language-Based Design And Application For A Library Management Information System

Abstract: This paper firstly introduces the main content of the Unified Modeling Language (UML) and proves that it can transmit information among the users, the developers, the designers and the managers efficiently, which improves their collaboration capabilities and greatly increases the degree of industrialization in software development projects Secondly, a library management system development and design is carried out, based on UML modeling mechanism to analyze a simple library management system Thirdly, a demand analysis mode of the management system is built with the help of a case diagram and an analysis diagram after analysis of a simple library management system, using UML modeling mechanism Then a book lending management subsystem has been designed in the library management system by a design class diagram and a sequence diagram The design process indicates that as a modeling language of software engineering, UML has a very good application prospect

Underwater Acoustic Sensor Networks Deployment Using Improved Self-Organize Map Algorithm

Abstract: The traditional Self-Organize Map SOM method is used for the arrangement of seabed nodes in this paper. If the distance between the nodes and the events is long, these nodes cannot be victory nodes and they will be abandoned, because they cannot move to the direction of events, and as a result they are not being fully utilized and are destroying the balance of energy consumption in the network. Aiming at this problem, this paper proposes an improved self-organize map algorithm with the introduction of the probability-selection mechanism in Gibbs sampling to select victory nodes, thus optimizing the selection strategy for victory nodes. The simulation results show that the Improved Self-Organize Map ISOM algorithm can balance the energy consumption in the network and prolong the network lifetime. Compared with the traditional self-organize map algorithm, the adopting of the improved self-organize map algorithm can make the event driven coverage rate increase about 3%.

Dynamical Topology Analysis Of Vanet Based On Complex Networks Theory

Abstract: A Vehicular Ad hoc NETwork VANET is a special subset of multi-hop Mobile Ad hoc Networks, in which the vehicles wireless interfaces can communicate with each other, as well as with fixed equipments alongside city roads or highways. Vehicular mobility dynamic characteristics, including high speed, predictable, restricted mobility pattern significantly affect the performance of routing protocols in a real VANET. Based on the existing studies, here we propose a testing network according to the preferential attachment on the degree of nodes and analyze VANET model characteristics for finding out the dynamic topology from the instantaneous degree distribution, instantaneous clustering coefficient and average path length. Analysis and simulation results demonstrate that VANET has a small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The dynamic topology analysis indicates a possible mechanism of VANET, which might be helpful in the traffic congestion, safety and management.

Nonlinear pd controllers with gravity compensation for robot manipulators

Abstract: A Nonlinear Proportional-Derivative NPD controller with gravity compensation is proposed and applied to robot manipulators in this paper. The proportional and derivative gains are changed by the nonlinear function of errors in the NPD controller. The closed-loop system, composed of nonlinear robot dynamics and NPD controllers, is globally asymptotically stable in position control of robot manipulators. The comparison of the simulation experiments in the position control the step response of a robot manipulator with two degrees of freedom is also presented to illustrate that the NPD controller is superior to the conventional PD controller in a position control system. The experimental results show that the NPD controller can obtain a faster response velocity and higher position accuracy than the conventional PD controller in the position control of robot manipulators because the proportional and derivative gains of the NPD controller can be changed by the nonlinear function of errors. The NPD controller provides a novel approach for robot control systems.

Telephone Speech Endpoint Detection using Mean-Delta Feature

Abstract: In the study the efficiency of three features for trajectory-based endpoint detection is experimentally evaluated in the fixed-text Dynamic Time Warping DTW - a based speaker verification task with short phrases of telephone speech. The employed features are Modified Teager Energy MTE, Energy-Entropy EE feature and Mean-Delta MD feature. The utterance boundaries in the endpoint detector are provided by means of state automaton and a set of thresholds based only on trajectory characteristics. The training and testing have been done with noisy telephone speech short phrases in Bulgarian language with length of about 2 s selected from BG-SRDat corpus. The results of the experiments have shown that the MD feature demonstrates the best performance in the endpoint detection tests in terms of the verification rate.

Solution Bounds for Algebraic Equations in Control Theory

Abstract: A book “Solution Bounds for Algebraic Equations in Control Theory” by Svetoslav Savov, has been recently published by “Prof. Marin Drinov” Academic Publishing House (ISBN 978-954-322-750-1). The research work is supported by FP7 Grant AComIn No 316087, funded by the European Commission for Capacity Programmes in 2012-2016. The book is intended for a wide circle of readers, including engineers, applied mathematicians, graduate students, etc., seeking a comprehensive view of the main results on the estimation of solutions of four algebraic equations, namely, the continuous-time and the discrete-time Lyapunov and Riccati equations. The book is organized as follows. A detailed summary of the proposed various solution bounds for the considered algebraic equations since 1970-ies, is presented in Chapter I. Different approaches are discussed in order to demonstrate the efficiency and the shortcomings of a particular method. As a consequence of this analysis and motivated by the conservatism in solution estimation, the author suggests a new approach to extend the sets of coefficient matrices, for which various bounds are valid under less restrictive conditions. The main contributions can be briefly formulated as follows. 1. It has been proved that extensions can be achieved by taking into account the singular value decomposition of the coefficient matrix for both continuous-time (Chapter 2) and discrete-time (Chapter 3) equations. 2. Much attention is paid to the improvement of the solution bounds. It is shown how the available bounds can be used to derive new tighter estimates. The bounds proposed in the book are illustrated by eleven numerical examples, including four real data cases in Chapter 4. The results are analyzed with respect to the tightness and validity measured by several error indicators. The book provides quick and easy references for the solution of different engineering and mathematical problems. Since both the mathematical development and the applications are considered, it can be useful for solving problems and for research purposes as well.

Adaptive Sliding Mode Control Based on a Filter for Four-Wheel Omni-Directional Mobile Robots

Abstract: Since there are usually parameter uncertainties and influence of the exogenous disturbances on the dynamic model of a four-wheel omni-directional mobile robot FOMR, the traditional strategy for motion control has not good performance. A sliding mode control based on an adaptive approach and a filter AFSMC is presented in this paper. First, according to identifying the reaching gain by a Radial Basis Function based neural network, and combining a filter, AFSMC can reduce the inherent impact that is produced by the normal sliding mode control. Second, the adaptive approach is applied to deal with the uncertainties and the influence of exogenous disturbances. Numerical simulations are carried out to assess the performance of the controller. All the simulation results indicate that the proposed control strategy is efficient to solve the problem.

A Framework for Visual Dynamic Analysis of Ray Tracing Algorithms

Abstract: A novel approach is presented for recording high volume data about ray tracing rendering systems' runtime state and its subsequent dynamic analysis and interactive visualization in the algorithm computational domain. Our framework extracts light paths traced by the system and leverages on a powerful filtering subsystem, helping interactive visualization and exploration of the desired subset of recorded data. We introduce a versatile data logging format and acceleration structures for easy access and filtering. We have implemented a plugin based framework and a tool set that realize all ideas presented in this paper. The framework provides data logging API for instrumenting production-ready, multithreaded, distributed renderers. The framework visualization tool enables deeper understanding of the ray tracing algorithms for novices, as well as for experts.

Privacy preservation in fuzzy association rules using rough computing and DSR

Abstract: In the present age of Internet, data is accumulated at a dramatic pace. The accumulated huge data has no relevance, unless it provides certain useful information pertaining to the interest of the organization. But the real challenge lies in hiding sensitive information in order to provide privacy. Therefore, attribute reduction becomes an important aspect for handling such huge database by eliminating superfluous or redundant data to enable a sensitive rule hiding in an efficient manner before it is disclosed to the public. In this paper we propose a privacy preserving model to hide sensitive fuzzy association rules. In our model we use two processes, named a pre-process and post-process to mine fuzzified association rules and to hide sensitive rules. Experimental results demonstrate the viability of the proposed research.

Secure Routing in Manet Using Synchronization and Data Authencity

Abstract: In recent years synchronization plays a major issue for secure transmission in mobile adhoc networks. When an attacker modifies the time synchronization algorithm, the nodes will have faulty estimates of other nodes location, leading to chaos. While transmitting under these adverse conditions, packets might be lost or might be sent to wrong locations. Data replication and data diffusion are two methods which are used to solve the problem of data availability. In this paper we propose an algorithm for secure multi hop transmission used for external attacks.

Error reduction in promoted confidence factor of a rule using improved fuzzy rule promotion technique

Abstract: A dynamic fuzzy rule promotion approach for the promotion of a confidence factor of a rule for every successful session in diagnosis of a disease in crops by using the specific rules, has already been proposed in literature This technique has the limitation that an error in the initial estimation of weights reduces linearly after every session the rule is being used In this paper an improved approach has been proposed using the square root of sum of squares of frequencies, which are spread around the mean true value to reduce the error around a mean value A rule set for the diseases and their symptoms for the paddy plant has been provided to make comparison between the previous and the improved approach It has been shown that the improved approach decreases the error in uncertainty of estimation of weight for rules after every successful session It has also been proposed that the improved approach must be applied in agricultural information dissemination system

Benchmark of Different Gradient Descents in OCR

Abstract: In this paper we implement six different learning algorithms in Optical Character Recognition OCR problem and achieve the criteria of end-time, number of iterations, train-set performance, test-set performance, validate-set performance and overall performance of these methods and compare them. Finally, we show the advantages and disadvantages of each method.

Stability and Fractal Patterns of Complex Logistic Map

Abstract: The intent of this paper is to study the fractal patterns of one dimensional complex logistic map by finding the optimum values of the control parameter using Ishikawa iterative scheme. The logistic map is shown to have bounded and stable behaviour for larger values of the control parameter. This is well depicted via time series analysis and interesting fractal patterns as well are presented

A Novel Fuzzy Clustering Recommendation Algorithm Based On Pso

Abstract: Aiming at the problem of recommendation systems, this paper proposes a fuzzy clustering algorithm based on particle swarm optimization. This algorithm can find the best solution, using the capacity of global search in PSO algorithm with a powerful global and defining a proportion factor, which can adjust the position and reduce the search space automatically. Then using mutation particles it replaces the particles flying out the solution space by new particles during the searching process. In order to check the performance of the proposed algorithm, by testing with typical ZDT1, ZDT2, ZDT3 functions, the experimental results show that the improved method not only has a better ability to converge to the global point, but can also efficiently avoid premature convergence.

Clustering of Authors’ Texts of English Fiction in the Vector Space of Semantic Fields

Abstract: This paper describes the analysis of possible differentiation of the author's idiolect in the space of semantic fields; it also analyzes the clustering of text documents in the vector space of semantic fields and in the semantic space with orthogonal basis. The analysis showed that using the vector space model on the basis of semantic fields is efficient in cluster analysis algorithms of author's texts in English fiction. The study of the distribution of authors' texts in the cluster structure showed the presence of the areas of semantic space that represent the idiolects of individual authors. Such areas are described by the clusters where only one author dominates. The clusters, where the texts of several authors dominate, can be considered as areas of semantic similarity of author's styles. SVD factorization of the semantic fields matrix makes it possible to reduce significantly the dimension of the semantic space in the cluster analysis of author's texts. Using the clustering of the semantic field vector space can be efficient in a comparative analysis of author's styles and idiolects. The clusters of some authors' idiolects are semantically invariant and do not depend on any changes in the basis of the semantic space and clustering method.

Multi-Targets Tracking Based On Bipartite Graph Matching

Abstract: Multi-target tracking is a challenge due to the variable number of targets and the frequent interaction between targets in complex dynamic environments. This paper presents a multi-target tracking algorithm based on bipartite graph matching. Unlike previous approaches, the method proposed considers the target tracking as a bipartite graph matching problem where the nodes of the bipartite graph correspond to the targets in two neighboring frames, and the edges correspond to the degree of the similarity measure between the targets in different frames. Finding correspondence between the targets is formulated as a maximal matching problem which can be solved by the dynamic Hungarian algorithm. Then, merging and splitting of the targets detection is proposed, the candidate occlusion region is predicted according to the overlapping between the bounding boxes of the interacting targets to handle the mutual occlusion problem. The extensive experimental results show that the algorithm proposed can achieve good performance on dynamic target interactions compared to state-of-the-art methods.

Face Recognition Based on Wavelet Kernel Non-Negative Matrix Factorization

Abstract: Abstract In this paper a novel face recognition algorithm, based on wavelet kernel non-negative matrix factorization (WKNMF), is proposed. By utilizing features from multi-resolution analysis, the nonlinear mapping capability of kernel nonnegative matrix factorization could be improved by the method proposed. The proposed face recognition method combines wavelet kernel non-negative matrix factorization and RBF network. Extensive experimental results on ORL and YALE face database show that the suggested method possesses much stronger analysis capability than the comparative methods. Compared with PCA, non-negative matrix factorization, kernel PCA and independent component analysis, the proposed face recognition method with WKNMF and RBF achieves over 10 % improvement in recognition accuracy.

Wireless Sensor Network Localization Based On A Mobile Beacon And Tsvm

Abstract: In this paper a new wireless sensor network localization algorithm, based on a mobile beacon and TSVM Transductive Support Vector Machines is proposed, which is referred to as MTSVM. The new algorithm takes advantage of a mobile beacon to generate virtual beacon nodes and then utilizes the beacon vector produced by the communication between the nodes to transform the problem of localization into one of classification. TSVM helps to minimize the error of classification of unknown fixed nodes unlabeled samples. An auxiliary mobile beacon is designed to save the large volumes of expensive sensor nodes with GPS devices. As shown by the simulation test, the algorithm achieves good localization performance.