At present many blind assistive systems have been implemented but there is no such kind of good system to navigate a blind person and also to track the movement of a blind person and rescue him/her if he/she is lost. In this paper, we have presented a blind assistive and tracking embedded system. In this system the blind person is navigated through a spectacle interfaced with an android application. The blind person is guided through Bengali/English voice commands generated by the application according to the obstacle position. Using voice command a blind person can establish voice call to a predefined number without touching the phone just by pressing the headset button. The blind assistive application gets the latitude and longitude using GPS and then sends them to a server. The movement of the blind person is tracked through another android application that points out the current position in Google map. We took distances from several surfaces like concrete and tiles floor in our experiment where the error rate is 5%.
Cloud computing enables clients with limited computational power to economically outsource their large scale computations to a public cloud with huge computational power. Cloud has the massive storage, computational power and software which can be used by clients for reducing their computational overhead and storage limitation. But in case of outsourcing, privacy of client's confidential data must be maintained. We have designed a protocol for outsourcing large scale Eigen value problem to a malicious cloud which provides input/output data security, result verifiability and client's efficiency. As the direct computation method to find all eigenvectors is computationally expensive for large dimensionality, we have used power iterative method for finding the largest Eigen value and the corresponding Eigen vector of a matrix. For protecting the privacy, some transformations are applied to the input matrix to get encrypted matrix which is sent to the cloud and then decrypting the result that is returned from the cloud for getting the correct solution of Eigen value problem. We have also proposed result verification mechanism for detecting robust cheating and provided theoretical analysis and experimental result that describes high-efficiency, correctness, security and robust cheating resistance of the proposed protocol.
Mar 26 2014 cs.CV
This paper presents a method of capturing objects appearances from its environment and it also describes how to recognize unknown appearances creating an eigenspace. This representation and recognition can be done automatically taking objects various appearances by using robotic vision from a defined environment. This technique also allows extracting objects from some sort of complicated scenes. In this case, some of object appearances are taken with defined occlusions and eigenspaces are created by accepting both of non-occluded and occluded appearances together. Eigenspace is constructed successfully every times when a new object appears, and various appearances accumulated gradually. A sequence of appearances is generated from its accumulated shapes, which is used for recognition of the unknown objects appearances. Various objects environments are shown in the experiment to capture objects appearances and experimental results show effectiveness of the proposed approach.
This paper presents two different evolutionary systems - Evolutionary Programming Network (EPNet) and Novel Evolutions Strategy (NES) Algorithm. EPNet does both training and architecture evolution simultaneously, whereas NES does a fixed network and only trains the network. Five mutation operators proposed in EPNet to reflect the emphasis on evolving ANNs behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. On the other hand, NES uses two new genetic operators - subpopulation-based max-mean arithmetical crossover and time-variant mutation. The above-mentioned two algorithms have been tested on a number of benchmark problems, such as the medical diagnosis problems (breast cancer, diabetes, and heart disease). The results and the comparison between them are also presented in this paper.
Fuzzy systems may be considered as knowledge-based systems that incorporates human knowledge into their knowledge base through fuzzy rules and fuzzy membership functions. The intent of this study is to present a fuzzy knowledge integration framework using a Novel Evolutionary Strategy (NES), which can simultaneously integrate multiple fuzzy rule sets and their membership function sets. The proposed approach consists of two phases: fuzzy knowledge encoding and fuzzy knowledge integration. Four application domains, the hepatitis diagnosis, the sugarcane breeding prediction, Iris plants classification, and Tic-tac-toe endgame were used to show the performance ofthe proposed knowledge approach. Results show that the fuzzy knowledge base derived using our approach performs better than Genetic Algorithm based approach.
Cloud computing platform gives people the opportunity for sharing resources, services and information among the people of the whole world. In private cloud system, information is shared among the persons who are in that cloud. Presently, different types of internet based systems are running in Cloud Computing environment. E-commerce is one of them. Present models are not secured enough for executing e-transactions easily, especially in cloud platform. Again, most of the time, clients fail to distinguish between the good online business companies and the bad one, which discourages clients and companies to migrate in cloud. In this paper, we have proposed a newer e-commerce architecture depends on encryption based secured and fuzzy logic based certain trust model which will be helpful to solve present e-commerce problems. We had discussed about the whole working procedure of the model in this paper. Finally, at the end of this paper, we have discussed some experimental results about our proposed model which will help to show the validity of our model.
Solving large traveling salesman problem (TSP) in an efficient way is a challenging area for the researchers of computer science. This paper presents a modified version of the ant colony system (ACS) algorithm called Red-Black Ant Colony System (RB-ACS) for the solutions of TSP which is the most prominent member of the combinatorial optimization problem. RB-ACS uses the concept of ant colony system together with the parallel search of genetic algorithm for obtaining the optimal solutions quickly. In this paper, it is shown that the proposed RB-ACS algorithm yields significantly better performance than the existing best-known algorithms.
Trustworthiness especially for service oriented system is very important topic now a day in IT field of the whole world. There are many successful E-commerce organizations presently run in the whole world, but E-commerce has not reached its full potential. The main reason behind this is lack of Trust of people in e-commerce. Again, proper models are still absent for calculating trust of different e-commerce organizations. Most of the present trust models are subjective and have failed to account vagueness and ambiguity of different domain. In this paper we have proposed a new fuzzy logic based Certain Trust model which considers these ambiguity and vagueness of different domain. Fuzzy Based Certain Trust Model depends on some certain values given by experts and developers. can be applied in a system like cloud computing, internet, website, e-commerce, etc. to ensure trustworthiness of these platforms. In this paper we show, although fuzzy works with uncertainties, proposed model works with some certain values. Some experimental results and validation of the model with linguistics terms are shown at the last part of the paper.
Apr 16 2013 cs.NE
Large set of linear equations, especially for sparse and structured coefficient (matrix) equations, solutions using classical methods become arduous. And evolutionary algorithms have mostly been used to solve various optimization and learning problems. Recently, hybridization of classical methods (Jacobi method and Gauss-Seidel method) with evolutionary computation techniques have successfully been applied in linear equation solving. In the both above hybrid evolutionary methods, uniform adaptation (UA) techniques are used to adapt relaxation factor. In this paper, a new Jacobi Based Time-Variant Adaptive (JBTVA) hybrid evolutionary algorithm is proposed. In this algorithm, a Time-Variant Adaptive (TVA) technique of relaxation factor is introduced aiming at both improving the fine local tuning and reducing the disadvantage of uniform adaptation of relaxation factors. This algorithm integrates the Jacobi based SR method with time variant adaptive evolutionary algorithm. The convergence theorems of the proposed algorithm are proved theoretically. And the performance of the proposed algorithm is compared with JBUA hybrid evolutionary algorithm and classical methods in the experimental domain. The proposed algorithm outperforms both the JBUA hybrid algorithm and classical methods in terms of convergence speed and effectiveness.
For small number of equations, systems of linear (and sometimes nonlinear) equations can be solved by simple classical techniques. However, for large number of systems of linear (or nonlinear) equations, solutions using classical method become arduous. On the other hand evolutionary algorithms have mostly been used to solve various optimization and learning problems. Recently, hybridization of evolutionary algorithm with classical Gauss-Seidel based Successive Over Relaxation (SOR) method has successfully been used to solve large number of linear equations; where a uniform adaptation (UA) technique of relaxation factor is used. In this paper, a new hybrid algorithm is proposed in which a time-variant adaptation (TVA) technique of relaxation factor is used instead of uniform adaptation technique to solve large number of linear equations. The convergence theorems of the proposed algorithms are proved theoretically. And the performance of the proposed TVA-based algorithm is compared with the UA-based hybrid algorithm in the experimental domain. The proposed algorithm outperforms the hybrid one in terms of efficiency.
Apr 12 2013 cs.NI
This paper presents the characterization of power control in WCDMA systems. We know that CDMA is an interference limited system. It is shown that the unbalance scheme is reliable and successful for both 2-way and 3-way soft handover. Unbalance scheme minimizes interference and speed up the soft handover algorithm to support more users quickly. Furthermore it requires minimum time to make decision for proper power control in soft handover status.
In near future, anticipated large number of mobile users may introduce very large centralized databases and increase end-to-end delays in location registration and call delivery on HLR-VLR database and will become infeasible. After observing several problems we propose some guidelines. Multitree distributed database, high throughput index structure, memory oriented database organization are used. Location management guidelines for moving user in overlapping network, neighbor discovery protocol (NDP), and global roaming rule are adopted. Analytic model and examples are presented to evaluate the efficiency of proposed guidelines.
Apr 10 2013 cs.NE
Now-a-days, it is important to find out solutions of Multi-Objective Optimization Problems (MOPs). Evolutionary Strategy helps to solve such real world problems efficiently and quickly. But sequential Evolutionary Algorithms (EAs) require an enormous computation power to solve such problems and it takes much time to solve large problems. To enhance the performance for solving this type of problems, this paper presents a new Distributed Novel Evolutionary Strategy Algorithm (DNESA) for Multi-Objective Optimization. The proposed DNESA applies the divide-and-conquer approach to decompose population into smaller sub-population and involves multiple solutions in the form of cooperative sub-populations. In DNESA, the server distributes the total computation load to all associate clients and simulation results show that the time for solving large problems is much less than sequential EAs. Also DNESA shows better performance in convergence test when compared with other three well-known EAs.
Apr 10 2013 cs.NE
For simple digital circuits, conventional method of designing circuits can easily be applied. But for complex digital circuits, the conventional method of designing circuits is not fruitfully applicable because it is time-consuming. On the contrary, Genetic Programming is used mostly for automatic program generation. The modern approach for designing Arithmetic circuits, commonly digital circuits, is based on Graphs. This graph-based evolutionary design of arithmetic circuits is a method of optimized designing of arithmetic circuits. In this paper, a new technique for evolutionary design of digital circuits is proposed using Genetic Programming (GP) with Subtree Mutation in place of Graph-based design. The results obtained using this technique demonstrates the potential capability of genetic programming in digital circuit design with limited computer algorithms. The proposed technique, helps to simplify and speed up the process of designing digital circuits, discovers a variation in the field of digital circuit design where optimized digital circuits can be successfully and effectively designed.
Apr 10 2013 cs.OH
In this paper, we presented the design and development of a new integrated device for measuring heart rate using fingertip to improve estimating the heart rate. As heart related diseases are increasing day by day, the need for an accurate and affordable heart rate measuring device or heart monitor is essential to ensure quality of health. However, most heart rate measuring tools and environments are expensive and do not follow ergonomics. Our proposed Heart Rate Measuring (HRM) device is economical and user friendly and uses optical technology to detect the flow of blood through index finger. Three phases are used to detect pulses on the fingertip that include pulse detection, signal extraction, and pulse amplification. Qualitative and quantitative performance evaluation of the device on real signals shows accuracy in heart rate estimation, even under intense of physical activity. We compared the performance of HRM device with Electrocardiogram reports and manual pulse measurement of heartbeat of 90 human subjects of different ages. The results showed that the error rate of the device is negligible.
The Decision Support System (DSS) contains more than one antecedent and the degrees of strength of the antecedents need to be combined to determine the overall strength of the rule consequent. The membership values of the linguistic variables in Fuzzy have to be combined using an aggregation operator. But it is not feasible to predefine the form of aggregation operators in decision making. Instead, each rule should be found based on the feeling of the experts and on their actual decision pattern over the set of typical examples. Thus this work illustrates how the choice of aggregation operators is intended to mimic human decision making and can be selected and adjusted to fit empirical data, a series of test cases. Both parametrized and nonparametrized aggregation operators are adapted to fit empirical data. Moreover, they provided compensatory properties and, therefore, seemed to produce a better decision support system. To solve the problem, a threshold point from the output of the aggregation operators is chosen as the separation point between two classes. The best achieved accuracy is chosen as the appropriate aggregation operator. Thus a medical decision can be generated which is very close to a practitioner's guideline.
Recently hybrid evolutionary computation (EC) techniques are successfully implemented for solving large sets of linear equations. All the recently developed hybrid evolutionary algorithms, for solving linear equations, contain both the recombination and the mutation operations. In this paper, two modified hybrid evolutionary algorithms contained time-variant adaptive evolutionary technique are proposed for solving linear equations in which recombination operation is absent. The effectiveness of the recombination operator has been studied for the time-variant adaptive hybrid algorithms for solving large set of linear equations. Several experiments have been carried out using both the proposed modified hybrid evolutionary algorithms (in which the recombination operation is absent) and corresponding existing hybrid algorithms (in which the recombination operation is present) to solve large set of linear equations. It is found that the number of generations required by the existing hybrid algorithms (i.e. the Gauss-Seidel-SR based time variant adaptive (GSBTVA) hybrid algorithm and the Jacobi-SR based time variant adaptive (JBTVA) hybrid algorithm) and modified hybrid algorithms (i.e. the modified Gauss-Seidel-SR based time variant adaptive (MGSBTVA) hybrid algorithm and the modified Jacobi-SR based time variant adaptive (MJBTVA) hybrid algorithm) are comparable. Also the proposed modified algorithms require less amount of computational time in comparison to the corresponding existing hybrid algorithms. As the proposed modified hybrid algorithms do not contain recombination operation, so they require less computational effort, and also they are more efficient, effective and easy to implement.
Single document summarization generates summary by extracting the representative sentences from the document. In this paper, we presented a novel technique for summarization of domain-specific text from a single web document that uses statistical and linguistic analysis on the text in a reference corpus and the web document. The proposed summarizer uses the combinational function of Sentence Weight (SW) and Subject Weight (SuW) to determine the rank of a sentence, where SW is the function of number of terms (t_n) and number of words (w_n) in a sentence, and term frequency (t_f) in the corpus and SuW is the function of t_n and w_n in a subject, and t_f in the corpus. 30 percent of the ranked sentences are considered to be the summary of the web document. We generated three web document summaries using our technique and compared each of them with the summaries developed manually from 16 different human subjects. Results showed that 68 percent of the summaries produced by our approach satisfy the manual summaries.
In this paper, an improved GEF fast addition algorithm is proposed. The proposed algorithm reduces time and memory space. In this algorithm, carry is calculated on the basis of arrival timing of the operand's bits without overhead of sorting. Intermediate terms are generated from the most significant bit and the carry is generated from the least significant bit using the functions of efficient operators. This algorithm shows better performance for use in the fastest computational devices of the near future.
Apr 09 2013 cs.CV
Extracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification system. Because minutiae matching are certainly the most well-known and widely used method for fingerprint matching, minutiae are local discontinuities in the fingerprint pattern. In this paper a fingerprint matching algorithm is proposed using some specific feature of the minutiae points, also the acquired fingerprint image is considered by minimizing its size by generating a corresponding fingerprint template for a large fingerprint database. The results achieved are compared with those obtained through some other methods also shows some improvement in the minutiae detection process in terms of memory and time required.
Solving a set of simultaneous linear equations is probably the most important topic in numerical methods. For solving linear equations, iterative methods are preferred over the direct methods especially when the coefficient matrix is sparse. The rate of convergence of iteration method is increased by using Successive Relaxation (SR) technique. But SR technique is very much sensitive to relaxation factor, \omega. Recently, hybridization of classical Gauss-Seidel based successive relaxation technique with evolutionary computation techniques have successfully been used to solve large set of linear equations in which relaxation factors are self-adapted. In this paper, a new hybrid algorithm is proposed in which uniform adaptive evolutionary computation techniques and classical Jacobi based SR technique are used instead of classical Gauss-Seidel based SR technique. The proposed Jacobi-SR based uniform adaptive hybrid algorithm, inherently, can be implemented in parallel processing environment efficiently. Whereas Gauss-Seidel-SR based hybrid algorithms cannot be implemented in parallel computing environment efficiently. The convergence theorem and adaptation theorem of the proposed algorithm are proved theoretically. And the performance of the proposed Jacobi-SR based uniform adaptive hybrid evolutionary algorithm is compared with Gauss-Seidel-SR based uniform adaptive hybrid evolutionary algorithm as well as with both classical Jacobi-SR method and Gauss-Seidel-SR method in the experimental domain. The proposed Jacobi-SR based hybrid algorithm outperforms the Gauss-Seidel-SR based hybrid algorithm as well as both classical Jacobi-SR method and Gauss-Seidel-SR method in terms of convergence speed and effectiveness.
In a wired network, a packet can be transmitted to a specified destination only, no broadcasting required. But in ad hoc wireless network a packet transmitted by a node can reach all neighbors due to broadcasting. This broadcasting introduces unnecessary retransmissions of same message. Therefore, the total number of transmissions (forward nodes) is generally used as the cost criterion for broadcasting. The problem of finding the minimum number of forward nodes is NP-complete. In this paper, the goal is to reduce the number of forward nodes which will reduce redundant transmission as a result. Thus some of approximation approaches are analyzed, especially dominant pruning and total dominant pruning which use 2-hop neighborhood information and a new approach: Probability based algorithm is proposed with a view to minimizing number of forward nodes. Simulation results of applying this algorithm shows performance improvements with compared to dominant pruning and total dominant pruning algorithms.
Apr 02 2013 cs.OH
We present a new integrated, portable device to provide a convenient solution for remote monitoring heart rate at the fingertip and body temperature using Ethernet technology and widely spreading internet. Now a days, heart related disease is rising. Most of the times in these cases, patients may not realize their actual conditions and even it is a common fact that there are no doctors by their side, especially in rural areas, but now a days most of the diseases are curable if detected in time. We have tried to make a system which may give information about one's physical condition and help him or her to detect these deadly but curable diseases. The system gives information of heart rate and body temperature simultaneously acquired on the portable side in real time and transmits results to web. In this system, the condition of heart and body temperature can be monitored from remote places. Eventually, this device provides a low cost, easily accessible human health monitor solution bridging the gaps between patients and doctors.
Mar 07 2013 cs.NE
This paper proposes a generalized Hybrid Real-coded Quantum Evolutionary Algorithm (HRCQEA) for optimizing complex functions as well as combinatorial optimization. The main idea of HRCQEA is to devise a new technique for mutation and crossover operators. Using the evolutionary equation of PSO a Single-Multiple gene Mutation (SMM) is designed and the concept of Arithmetic Crossover (AC) is used in the new Crossover operator. In HRCQEA, each triploid chromosome represents a particle and the position of the particle is updated using SMM and Quantum Rotation Gate (QRG), which can make the balance between exploration and exploitation. Crossover is employed to expand the search space, Hill Climbing Selection (HCS) and elitism help to accelerate the convergence speed. Simulation results on Knapsack Problem and five benchmark complex functions with high dimension show that HRCQEA performs better in terms of ability to discover the global optimum and convergence speed.
Mar 05 2013 cs.NI
Due to mobility of nodes in ad hoc networks, the most challenging issue is to design and to make sound analysis of a routing protocol that determines its robustness to deliver packets in low routing packet overhead. In this paper, we thoroughly analyzed the Adaptive Monitor Based Routing (AMBR) protocol by varying different parameters that affect a routing protocol to measure its performance. Analysis shows that it requires less routing control overhead comparing with other prevalent routing protocols. An improved analytical model is also presented in this paper. All these analyses firmly prove that AMBR is a sound and robust protocol in terms of flooding, routing overhead and hence, enhances reliability.
Mar 05 2013 cs.CR
Trustworthiness especially for service oriented system is very important topic now a day in IT field of the whole world. Certain Trust Model depends on some certain values given by experts and developers. Here, main parameters for calculating trust are certainty and average rating. In this paper we have proposed an Extension of Certain Trust Model, mainly the representation portion based on probabilistic logic and fuzzy logic. This extended model can be applied in a system like cloud computing, internet, website, e-commerce, etc. to ensure trustworthiness of these platforms. The model uses the concept of fuzzy logic to add fuzziness with certainty and average rating to calculate the trustworthiness of a system more accurately. We have proposed two new parameters - trust T and behavioral probability P, which will help both the users and the developers of the system to understand its present condition easily. The linguistic variables are defined for both T and P and then these variables are implemented in our laboratory to verify the proposed trust model. We represent the trustworthiness of test system for two cases of evidence value using Fuzzy Associative Memory (FAM). We use inference rules and defuzzification method for verifying the model.
The cloud computing platform gives people the opportunity for sharing resources, services and information among the people of the whole world. In private cloud system, information is shared among the persons who are in that cloud. For this, security or personal information hiding process hampers. In this paper we have proposed new security architecture for cloud computing platform. This ensures secure communication system and hiding information from others. AES based file encryption system and asynchronous key system for exchanging information or data is included in this model. This structure can be easily applied with main cloud computing features, e.g. PaaS, SaaS and IaaS. This model also includes onetime password system for user authentication process. Our work mainly deals with the security system of the whole cloud computing platform.
Mar 05 2013 cs.NE
Evolutionary computation techniques have mostly been used to solve various optimization and learning problems successfully. Evolutionary algorithm is more effective to gain optimal solution(s) to solve complex problems than traditional methods. In case of problems with large set of parameters, evolutionary computation technique incurs a huge computational burden for a single processing unit. Taking this limitation into account, this paper presents a new distributed evolutionary computation technique, which decomposes decision vectors into smaller components and achieves optimal solution in a short time. In this technique, a Jacobi-based Time Variant Adaptive (JBTVA) Hybrid Evolutionary Algorithm is distributed incorporating cluster computation. Moreover, two new selection methods named Best All Selection (BAS) and Twin Selection (TS) are introduced for selecting best fit solution vector. Experimental results show that optimal solution is achieved for different kinds of problems having huge parameters and a considerable speedup is obtained in proposed distributed system.
Apr 11 2012 cs.NI
We propose and analyze a new on the fly strategy that discovers, repairs and maintains routes in hierarchical and distributed fashion called Janitor Based Routing (JBR). The main motivation behind our JBR protocol is to decrease flooding and routing overhead and increase efficiencies in packet movement. An analytical model for the proposed JBR is presented and detailed simulation is used to observe the performance of JBR. This route discovery and maintenance protocol clearly achieved improvement in terms of reduction of flooding, routing overhead, and, hence, provides enhanced reliability.
May 26 2010 cs.CR
Radio Frequency Identification (RFID) technology one of the most promising technologies in the field of ubiquitous computing. Indeed, RFID technology may well replace barcode technology. Although it offers many advantages over other identification systems, there are also associated security risks that are not easy to be addressed. When designing a real lightweight authentication protocol for low cost RFID tags, a number of challenges arise due to the extremely limited computational, storage and communication abilities of Low-cost RFID tags. This paper proposes a real mutual authentication protocol for low cost RFID tags. The proposed protocol prevents passive attacks as active attacks are discounted when designing a protocol to meet the requirements of low cost RFID tags. However the implementation of the protocol meets the limited abilities of low cost RFID tags.
Apr 09 2010 cs.CR
Almost all existing RFID authentication schemes (tag/reader) are vulnerable to relay attacks, because of their inability to estimate the distance to the tag. These attacks are very serious since it can be mounted without the notice of neither the reader nor the tag and cannot be prevented by cryptographic protocols that operate at the application layer. Distance bounding protocols represent a promising way to thwart relay attacks, by measuring the round trip time of short authenticated messages. All the existing distance bounding protocols use random number generator and hash functions at the tag side which make them inapplicable at low cost RFID tags. This paper proposes a lightweight distance bound protocol for low cost RFID tags. The proposed protocol based on modified version of Gossamer mutual authentication protocol. The implementation of the proposed protocol meets the limited abilities of low-cost RFID tags.
Exact String Matching is an essential issue in many computer science applications. Unfortunately, the performance of Exact String Matching algorithms, namely, executing time, does not address the needs of these applications. This paper proposes a general platform for improving the existing Exact String Matching algorithms executing time, called the PXSMAlg platform. The function of this platform is to parallelize the Exact String Matching algorithms using the MPI model over the Master or Slaves paradigms. The PXSMAlg platform parallelization process is done by dividing the Text into several parts and working on these parts simultaneously. This improves the executing time of the Exact String Matching algorithms. We have simulated the PXSMAlg platform in order to show its competence, through applying the Quick Search algorithm on the PXSMAlg platform. The simulation result showed significant improvement in the Quick Search executing time, and therefore extreme competence in the PXSMAlg platform.