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Showing papers in "International Journal of Advancements in Computing Technology in 2012"


Journal ArticleDOI
TL;DR: The present study proposes a new method for solving threat risk analysis problem by means of modified Attack-Defense Trees (ADT) considering the effect of both the attack cost and defense cost and provides an effective means of reconstructing the attack profiles and evaluating the countermeasures in the evolutional process of security management for cloud security.
Abstract: The existing attack trees and attack graphs schemes focused on depicting the possible intrusions by presenting the suspected attack profiles, not for interactions between threats and defenses. Consequently, it limits the adoption of the safeguards with which to select the effective defensive strategies. Accordingly, the present study proposes a new method for solving threat risk analysis problem by means of modified Attack-Defense Trees (ADT) considering the effect of both the attack cost and defense cost. The effectiveness of the proposed approach was evaluated by a set of metrics for mitigating new network threats, like APT attacks. In addition, an illustration case of threat risk analysis of cloud security is given to demonstrate our approach. Finally, the adaptability of the proposed scheme is investigated by the attributes comparison with that of the scheme presented by Edge et al. (2007). Overall, our approach provides an effective means of reconstructing the attack profiles and evaluating the countermeasures in the evolutional process of security management for cloud security.

37 citations


Journal ArticleDOI
TL;DR: 3D skeleton tracking technique using a depth camera known as a Kinect sensor with the ability to approximate human poses to be captured, reconstructed and displayed 3D skeleton in the virtual scene using OPENNI, NITE Primesense and CHAI3D open source libraries is proposed.
Abstract: Current research on skeleton tracking techniques focus on image processing in conjunction with a video camera constrained by bones and joint movement detection limits. The paper proposed 3D skeleton tracking technique using a depth camera known as a Kinect sensor with the ability to approximate human poses to be captured, reconstructed and displayed 3D skeleton in the virtual scene using OPENNI, NITE Primesense and CHAI3D open source libraries. The technique could perform the bone joint movement detections in real time with correct position tracking and display a 3D skeleton in a virtual environment with abilities to control 3D character movements for the future research.

35 citations


Journal ArticleDOI
TL;DR: Simulation results show that the mobile robot achieves both overall and local obstacle-avoidance during motion, in association with an optimum path, which verifies the feasibility and effectiveness of the path-planning method.
Abstract: A path-planning method based on a combination of the static global and the dynamic local pathplanning methods is proposed for robot path planning under a complex environment. There are known static obstacles and unknown dynamic obstacles in any complex environment. The local-path planner dynamically generates a local path using obstacle-motion prediction and a rolling window for dynamic path planning to partially adjust the global path. Simulation results show that the mobile robot achieves both overall and local obstacle-avoidance during motion, in association with an optimum path, which verifies the feasibility and effectiveness of the method.

30 citations



Journal ArticleDOI
TL;DR: This paper discusses the teaching design and multimedia teaching resources development using information processing theory that promotes the reform of higher education teaching methods.
Abstract: The teaching design and multimedia teaching resources development with information processing theory are at the initial stage at home and abroad. There is not yet successful experiences and standardize the design for our use in teaching. This paper discusses the teaching design and multimedia teaching resources development using information processing theory that promotes the reform of higher education teaching methods.

24 citations


Journal ArticleDOI
TL;DR: A cardinality constrained mean-variance model is introduced for the portfolio optimization problems, a mixed quadratic and integer programming problem for which efficient algorithms do not exist and artificial bee colony algorithm is used to solve this model.
Abstract: In this paper, a cardinality constrained mean-variance model is introduced for the portfolio optimization problems. This model is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. The use of heuristic algorithms in this case is necessary. Some studies have investigated the cardinality constrained mean-variance model using heuristic algorithm. But almost none of these studies deal with artificial bee colony algorithm. The purpose of this paper is to use artificial bee colony algorithm to solve this model. The experimental results show that the proposed algorithm performs well for the portfolio optimization problem.

24 citations


Journal ArticleDOI
TL;DR: A SURF-based method to tackle the problem of detecting image forgery in both flat region and non-flat region by using matching algorithms of similar blocked images, which results in the completing of the entire image tamper detection.
Abstract: Techniques for digital image tampering are becoming widespread for the availability of low cost technology in which the image could be easily manipulated. Copy-move forgery is one of the tampering techniques that are frequently used and has recently received significant attention. But the existing methods, including block-matching and key point matching based methods, are not able to be used to solve the problem of detecting image forgery in both flat region and non-flat region. In this paper, combining the thinking of these two types of methods, we develop a SURF-based method to tackle this problem. In addition to the determination of forgeries in non-flat region through key point features, our method can be used to detect flat region in images in an effective way, and extract FMT features after blocking the region. By using matching algorithms of similar blocked images, image forgeries in flat region can be determined, which results in the completing of the entire image tamper detection. Experimental results are presented to demonstrate the effectiveness of the proposed method.

24 citations



Journal ArticleDOI
TL;DR: By recognizing the differences of CSFs for large organization with SMEs, stakeholders can better develop and use suitable and useful implementation models / frameworks to improve the successful of ERP implementations in enterprises with any sizes.
Abstract: The main goal of this research is to explore the difference between the critical success factors (CSFs) of enterprise resource planning (ERP) system implementation in large firms with small and medium-sized enterprises (SMEs) in developing countries. Understanding this subject can help the implementers and users of ERP systems to notice the CSFs of their particular enterprises and to improve the success rate of these systems. The number of seventeen resources of studies evaluating the CSFs of ERP in SMEs and equal numbers of resources were used for the large enterprises. Following an evaluation of each category was conducted to elicit similarities and diversities in CSFs of these two groups. This research shows that there are some significant differences among the CSFs of ERP implementation in SMEs and large firm of developing countries. There was lacking of studies that have been focused on large firm and SMEs separately. The study explored the need for more research that is focused on CSFs studies with regard of distinct separated size of enterprises. By recognizing the differences of CSFs for large organization with SMEs, stakeholders can better develop and use suitable and useful implementation models / frameworks to improve the successful of ERP implementations in enterprises with any sizes. This paper appears to be one of the first studies to focus on comparing of CSFs in implementation of ERP in SMEs with large enterprise in developing countries.

23 citations


Journal ArticleDOI
TL;DR: This paper proposes a scheme of internet of things running in a distributed intelligent detector network that can act according to the command coming from the system, since it is not self-possessed and self-aware.
Abstract: The internet of things demand adequate sensing element so as to get enough information to control its internal objects. In this paper, we propose a scheme of internet of things running in a distributed intelligent detector network. The surroundings is parted by distributed detectors, each partition is supervised by corresponding detectors. In such a distributed system, the moving object can act according to the command coming from the system, since it is not self-possessed and self-aware. We conduct some experiments to exam the performance of the system and the experiments obtain acceptable results.

20 citations


Journal ArticleDOI
TL;DR: Experiments on source-end defense against SYN flooding attacks show the efficacy of the nonparametric adaptive CUSUM (Cumulative Sum) method in detecting low intensity anomalies.
Abstract: Detecting anomalies that disrupt the symmetry in two-way communications is an important task for network defense systems. The subtlety and complexity of anomalous traffic challenge the existing detection methods, and the bottleneck is how to set thresholds to adapt to the variability in network traffic. In this paper, a nonparametric adaptive CUSUM (Cumulative Sum) method is presented to meet this challenge. It has three distinct features. (i) No assumption is made on the distribution of the observations. (ii) Its detection threshold is self-adjusted so that it can adapt itself to various traffic conditions. (iii) It can react to the end of an anomaly within a required delay time. Several practical expressions for evaluating this method on its probability of false alarms and detection delays are deduced. Experiments on source-end defense against SYN flooding attacks show the efficacy of this method in detecting low intensity anomalies.

Journal ArticleDOI
TL;DR: The critical issues are explored, including challenges, repurposing processes, cost analyses, and optimal business models for transforming a used Li-ion battery pack retired from EV into ESS for its second-use application.
Abstract: The lithium-ion (Li-ion) battery of high power density and large electricity capacity is pioneering both uncultivated lands, the electric vehicle (EV) for driving longer distances, and the electricity storage system (ESS) for storing huger amount of electricity. Still, the high capital cost of Li-ion battery, around 50% of an EV, currently impede the universal market adoptions of EV and ESS industries. Through a sophisticated repurposing process and a clever business operation, the used Liion batteries retired from EV usually holding residual 70 ~ 80% electricity-storage capacities can create long-term and stable profits from proper second-use or repurposing applications, such as the electricity-storage batteries of an ESS for storing the electricity from renewable energy systems. From the viewpoint of environment protection, this transforming movement firmly meets with the “eco-3R” principles of recycle, reuse and reduce. During the “pre-recycling” period of second-use application, more creative technologies to dispose of the large-sized and unable-to-reuse Li-ion batteries can be developed. A complete eco-life of an EV Li-ion battery can be achieved. In this research, the critical issues are explored, including challenges, repurposing processes, cost analyses, and optimal business models for transforming a used Li-ion battery pack retired from EV into ESS for its second-use application. The estimated profit rate of a case study can reach around 39%; namely, a 10kWh Li-ion battery pack of 20-year calendar life primarily works in EV for 5 years, and then runs in ESS for following residual 15 years.




Journal ArticleDOI
TL;DR: Protection motivation theory (PMT) is used to explain the mobile health services acceptance of difference age groups and revealed that response efficacy and self efficacy had a significant impact on adoption intention for the group of young adults and middle age people, while for the groups of the elderly, only self efficacy determined the intention to use mobile health service.
Abstract: With the rapid development of the mobile devices, there arouses great interest in mobile health service. As a new phenomenon, previous studies tend to investigate the adoption behavior in terms of the general population or one special population. In order to target more populations as potential customers, our study will use protection motivation theory (PMT) to explain the mobile health services acceptance of difference age groups. During the research, the hypothesized model is tested using data collected from a field survey of 492 potential customers of three difference age groups. The results revealed that response efficacy and self efficacy had a significant impact on adoption intention for the group of young adults and middle age people, while for the group of the elderly, only self efficacy determined the intention to use mobile health service. Theoretical and practical implications are discussed.

Journal ArticleDOI
TL;DR: Experimental results show that the proposed approach, called OCABC, outperforms the original ABC, Particle Swarm Optimization (PSO) and opposition-based PSO for the majority of test functions.
Abstract: This paper presents a new Artificial Bee Colony (ABC) optimization algorithm to solve function optimization problems. The proposed approach is called OCABC, which introduces opposition-based learning concept and dynamic Cauchy mutation into the standard ABC algorithm. To verify the performance of OCABC, eight well-known benchmark function optimization problems are used in the experiments. Experimental results show that our approach outperforms the original ABC, Particle Swarm Optimization (PSO) and opposition-based PSO for the majority of test functions.

Journal ArticleDOI
TL;DR: This paper presents a pedestrian detection method based on the combination of Histograms of Oriented Gradient (HOG) feature and uniform local binary pattern (LBP) feature, which can detect pedestrian accurately.
Abstract: In this paper, we present a pedestrian detection method based on the combination of Histograms of Oriented Gradient (HOG) feature and uniform local binary pattern (LBP) feature, which can detect pedestrian accurately. To the problem of low recognition rate for a single feature, we combine contour information and texture information, and propose the cascade of the two types of features, HOG features and LBP features as the feature set. In order to compare the experimental results, Gentle AdaBoost is used to train the pedestrian classifier on the INRIA dataset. The experimental results show that these two features of pedestrian detection algorithm improve the accuracy and reduce the error rate. Our method achieve a detection rate of 94.05% at FPPW = 10 -4 , which is better than Dalal’s (detection rate of 84% to 89% at 10 -4 FPPW).

Journal ArticleDOI
TL;DR: A new hybrid algorithm, ant system-assisted genetic algorithm (ASaGA) to handle the travelling salesman problem (TSP) by using the results of ACO to replace that of GA after every certain number of runs during the process.
Abstract: The travelling salesman problem (TSP) is a classic problem of combinatorial optimization and has applications in planning, scheduling, and searching in many scientific and engineering fields. Genetic algorithms (GA) and ant colony optimization (ACO) have been successfully used in solving TSPs and many associated applications in the last two decades. However, both GA and ACO have difficulty in regularly reaching the global optimal solutions for TSPs. In this paper, we propose a new hybrid algorithm, ant system-assisted genetic algorithm (ASaGA) to handle this problem. The main change in ASaGA is to use the results of ACO to replace that of GA after every certain number of runs during the process. This provides a new mechanism to steer GA out of potential stagnation at local optima and thus enhances the chance in reaching the global optimal solution. Our simulation on three benchmark TSPs shows that this AS-assisted GA (ASaGA) algorithm can significantly improve quality of optimal solutions with a small increase in computing cost.


Journal ArticleDOI
TL;DR: The result shows that identifying debt-prone bugs can assist in monitoring and improving software quality, and build prediction models based on historical products to predict the time cost of fixing bugs.
Abstract: Fixing bugs is an important phase in software development and maintenance. In practice, the process of bug fixing may conflict with the release schedule. Such confliction leads to a trade-off between software quality and release schedule, which is known as the technical debt metaphor. In this article, we propose the concept of debt-prone bugs to model the technical debt in software maintenance. We identify three types of debt-prone bugs, namely tag bugs, reopened bugs, and duplicate bugs. A case study on Mozilla is conducted to examine the impact of debt-prone bugs in software products. We investigate the correlation between debt-prone bugs and the product quality. For a product under development, we build prediction models based on historical products to predict the time cost of fixing bugs. The result shows that identifying debt-prone bugs can assist in monitoring and improving software quality.


Journal ArticleDOI
TL;DR: The contribution of this paper is to identify the selection criteria of OSS adoption based on four dimensions: system quality, information quality, service quality, and other dimension which includes the potential internal constraints such as internal technical competencies and knowledge.
Abstract: The adoptions of open source software (OSS) are still continuously growing all over the world including at businesses, non-profits and public sector agencies because of the financial benefits. The OSS potential users may have their own selection criteria on adopting any product which may comply with the requirements specified. The criteria of selection may differ between the stakeholders within the organizations. Yet, the adoption rate is still low among OSS potential users because there is not an agreed acceptable set of criteria to evaluate and decide varieties of OSS projects, little documentation and user manuals, and immature products. Therefore, there is a tendency that the user’s biased perception on OSS characteristic or capability on solving problems. The contribution of this paper is to identify the selection criteria of OSS adoption based on four dimensions: system quality, information quality, service quality, and other dimension which includes the potential internal constraints such as internal technical competencies and knowledge. In this paper, the background research in OSS adoption and criteria of selection are discussed and explored which then moves to the selection issues and identified selection criteria of OSS adoption. Identifying the selection criteria will help to build confidence among users and better understanding of their perception of OSS.

Journal ArticleDOI
TL;DR: A binary version of artificial bee colony (BABC) algorithm is proposed, which represents a food source as a discrete binary variable and applies discrete operators to change the foraging trajectories of the employed bees, onlookers and scouts in the probability that a coordinate will take on a zero or one value.
Abstract: The Artificial Bee Colony (ABC) algorithm recently gained high popularity by providing a robust and efficient approach for solving continuous optimization problems. In order to apply ABC in discrete landscape, a binary version of artificial bee colony (BABC) algorithm is proposed in this manuscript. Unlike the original ABC algorithm, the proposed BABC represents a food source as a discrete binary variable and applies discrete operators to change the foraging trajectories of the employed bees, onlookers and scouts in the probability that a coordinate will take on a zero or one value. With four mathematical benchmark functions, BABC is proved to have significantly better performance than the other two successful discrete optimizer, namely the genetic algorithm (GA) and particle swarm optimization (PSO).

Journal ArticleDOI
TL;DR: The color constancy investigation in the hybridization of Wireless LAN and Camera positioning in the mobile phone is presented and there is no conventional searching algorithm required, thus it is expected to reduce the complexity of computation.
Abstract: This paper present our color constancy investigation in the hybridization of Wireless LAN and Camera positioning in the mobile phone. Five typical color constancy schemes are analyzed in different location environment. The results can be used to combine with RF signals from Wireless LAN positioning by using model fitting approach in order to establish absolute positioning output. There is no conventional searching algorithm required, thus it is expected to reduce the complexity of computation. Finally we present our preliminary results to illustrate the indoor positioning algorithm performance evaluation for an indoor environment set-up.


Journal ArticleDOI
TL;DR: This paper explores and presents implementation techniques for energy-efficient hardware acceleration of RSA cryptography and Blowfish cryptography and carefully implements the critical path as a customized coprocessor to improve the overall system throughput on Virtex-5 FieldProgrammable Gate Array (FGPA) platform.
Abstract: Data security, energy consumption, and computation speed have all become crucial criteria in the new era of computing and communication technology. Cryptography plays an important role for data security and integrity and is widely adopted. On one hand, we want to reduce the computation overhead of cryptography algorithms; on the other hand, we also want to reduce the energy consumption associated with this computation overhead. In this paper we explore and present implementation techniques for energy-efficient hardware acceleration of RSA cryptography and Blowfish cryptography. Instead of implementing the entire algorithm into hardware format, we provide a system design that focus on accelerating the execution of the critical path of each of the cryptography algorithm, which is the most computation-intensive component. We carefully implement the critical path as a customized coprocessor to improve the overall system throughput on Virtex-5 FieldProgrammable Gate Array (FGPA) platform. Subsequently, we make a comparison of the effectiveness and energy consumption between the pure software implementation of the cryptography algorithms and our proposed approach. The results show that our critical path enhancement design speeds up the execution of RSA by 11% and Blowfish by 58.8%; in the meantime, we are able to reduce the energy consumption by 9.6% for RSA and 36.0% for Blowfish, thus achieving our objective.

Journal ArticleDOI
TL;DR: The improvement of algorithm combined by soft-thresholding wavelet de-noise and the conventional prewitt operator is a much better method than the conventional edge detection operator when it detects the edge of the image with White Gauss Noise.
Abstract: In this paper, the improved version of Prewitt operator edge detection algorithm proposed which is based on the soft-threshold wavelet de-noising is aimed at processing the image with Gaussian white noise. A number of experiments show that this algorithm adds some advantages of wavelet de-noising, such as that the differential nature of the wavelet function can highlight the discontinuous edge of the image, The multi-resolution of wavelet transform overcome the contradiction between reduction of noise and the precision of edge positioning in the field of neighborhood selection. At the same time the wavelet transformation has the function of band-pass filter, and it can extraction the different levels of information. The improvement of algorithm combined by soft-thresholding wavelet de-noise and the conventional prewitt operator is a much better method than the conventional edge detection operator when it detects the edge of the image with White Gauss Noise.

Journal ArticleDOI
TL;DR: A solution of the existing method for selecting requiremnets engineering techniques based on the given project attributes is proposed by adding deliverable parameter to the project attribute and implement single solution, that reduce the task of selecting the proper set of requirements engineering techniques.
Abstract: One of the big issues of software development project is overspent and delays. Thus added to the equation is unsuficient quality of expected deliverables due to bad selection of requirements engineering techniques. There has been a method introduced for selecting requiremnets engineering techniques based on the given project attributes. But it produced a list of techniques, which left the engineers to figure out which set of techniques that should be selected to ensure that the proper deliverables can be produced. This paper proposed a solution of the existing method by adding deliverable parameter to the project attribute and implement single solution, that reduce the task of selecting the proper set of requirements engineering techniques. The new method, Advance MRETS (AMRETS) shows a promising results. It reduces the number of recommended techniques list from the previous method into a single alternative set of techniques. It ensures that the single alternative produces all required deliverables and minimizes the number of unnecessary deliverables. This method helps the project manager to do a better planning, especially for the requirements phase.