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 Arabian Journal for Science and Engineering   [SJR: 0.345]   [H-I: 20]   [5 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1319-8025    Published by Springer-Verlag  [2353 journals]
• DCCD: Distributed N -Body Rigid Continuous Collision Detection for
Large-Scale Virtual Environments
• Authors: Peng Du; Jieyi Zhao; Weijuan Cao; Yigang Wang
Pages: 3141 - 3147
Abstract: Abstract Continuous collision detection (CCD) is a process to interpolate the trajectory of polygons and detect collisions between successive time steps. However, this process is time-consuming, especially for a large number of moving polygons. In this paper, we present a parallel CCD algorithm, which aims to accelerate N-body rigid CCD culling by distributing the load across a distributed-memory system. This algorithm is particularly suitable for large-scale distributed simulations. Experimental results, based on a message passing interface implementation, demonstrate that our approach is more computationally efficient than existing sequential CCD approaches.
PubDate: 2017-08-01
DOI: 10.1007/s13369-016-2411-0
Issue No: Vol. 42, No. 8 (2017)

• An Efficient Distributed Algorithm for Big Data Processing
• Authors: Mohammed S. Al-kahtani; Lutful Karim
Pages: 3149 - 3157
Abstract: Abstract This paper introduces an efficient distributed data analysis framework for big data which comprises data processing at the data collecting nodes and the central server end as opposed to the existing framework that only comprises data processing at the central server end. As data are being processed at the data collecting end in the proposed framework, the amount of data is reduced to be processed at the server side by the commodity computers. The proposed distributed algorithm works both in low-powered nodes such as sensors and high-speed commodity computers and also performs sequential and parallel processing based on the amount of data received at the central server. Simulation results demonstrate that the proposed distributed algorithm outperforms traditional distributed algorithms in terms of the size of data to be processed at the central server and data processing time.
PubDate: 2017-08-01
DOI: 10.1007/s13369-016-2405-y
Issue No: Vol. 42, No. 8 (2017)

• Pedestrian Detection with Minimal False Positives per Color-Thermal Image
• Authors: Masoud Afrakhteh; Park Miryong
Pages: 3207 - 3219
Abstract: Abstract This research is based on aggregate channel features utilized for pedestrian detection, and the main focus is to investigate a simple way to reduce the number of false positives per image. The importance of this will be to increase the accuracy of the detector by removing the excessive number of false positives while maintaining the missing rate as low as possible. To omit such unwanted false positives, we utilized an image categorization method for day and night images in order to minimize the misclassification rate. Furthermore, the best extension of the aggregate channel features method was analyzed and is recommended as a base detector. As a result, a night-time pre-trained pedestrian detector is only applied to night images, and a daytime detector is applied to daytime images. Thus, a large number of false positives are avoided while the missing rate is greatly reduced.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2424-3
Issue No: Vol. 42, No. 8 (2017)

• A Novel Shape-Based Character Segmentation Method for Devanagari Script
• Authors: Khushneet Jindal; Rajiv Kumar
Pages: 3221 - 3228
Abstract: Abstract This paper presents a new algorithm to extract shape-oriented feature vectors using pixel intensities from offline printed Devanagari script documents. Almost, all the characters of the script contain Shirorekha (header line) on the upper portion, which makes segmentation a difficult and complex problem. The problem gets more challenging when images are in multiple gray levels, skewed and noisy. A new fast and effective algorithm is designed using gradient structural information, and its performance is evaluated on a challenging dataset containing 80 printed documents consisting of around 87,000 characters. Experimental results show that the proposed algorithm has 98.56% accuracy, which is 02.66% higher than that reported in literature. Also, the proposed algorithm is time efficient and less complex in comparison with the existing methods.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2420-7
Issue No: Vol. 42, No. 8 (2017)

• An Enhanced Vertical Handover Based on Fuzzy Inference MADM Approach for
Heterogeneous Networks
• Authors: Aymen Ben Zineb; Mohamed Ayadi; Sami Tabbane
Pages: 3263 - 3274
Abstract: Abstract Seamless handover between different radio access technologies is a great challenge since it needs to guarantee the link continuity and satisfy the subscriber’s quality-of-services (QoS) requirements. The performances of roaming across different technologies depend on the number of implemented handover criteria, which can be large. In this case, multiple attribute decision making (MADM) methods such as simple additive weighting, technique for order preference by similarity to ideal solution and the compromise ranking method called (VIKOR: VlseKriterijumska Optimizacija I Kompromisno Resenje) have been proposed to solve this kind of multi-criteria problems. However, the major shortcomings of these techniques are the high decision delay and the complexity. In this paper, we propose a novel handover (HO) scheme called Fuzzy-MADM. It is based on the combination of one classical MADM method with a fuzzy logic inference system in order to reduce decisional time. The optimal network is selected, based on multiple criteria such as network QoS indicators, speed of mobile station, battery level and signal strength. The efficiency of our approach is evaluated through appropriate simulations. The results related to HO delays, throughput, complexity and number of executed handovers show the performances of our proposal when compared to classical MADM and load balancing methods.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2418-1
Issue No: Vol. 42, No. 8 (2017)

• EIMAKP: Heterogeneous Cross-Domain Authenticated Key Agreement Protocols
in the EIM System
• Authors: Chao Yuan; Wenfang Zhang; Xiaomin Wang
Pages: 3275 - 3287
Abstract: Abstract In recent years, instant messaging (IM) has increasingly become a popular communication technology around the world, and the enterprise instant messaging (EIM) system is one of IM’s applications for enterprise use. The existing studies of EIM systems are directed at the design of functional components and the process of communication, which are usually based on XMPP protocol suite. However, in this paper, the security of EIM is more concerned from another perspective, which is the problem of identity authentication and key agreement between users and services. Several EIM systems are based on public key infrastructure (PKI) to achieve the high-security requirements of enterprises, while identity-based cryptography (IBC) brings new development direction for EIM systems. Although most of the EIM applications are applied independently in different enterprises, users’ heterogeneous cross-domain service access has become an inevitable trend. However, there is still no heterogeneous cross-domain authentication protocol between the PKI domain and the IBC domain having been proposed. Therefore, in order to address this problem, a novel and detailed heterogeneous cross-domain authenticated key agreement scheme is proposed in this paper. By utilizing the PKI-based distributed trust model and the access authorization tickets, this scheme can realize interconnection and seamless authentication between the PKI domain and the IBC domain. Analysis shows that the proposed scheme is theoretically correct, while guaranteeing high security and efficiency.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2447-9
Issue No: Vol. 42, No. 8 (2017)

• Accurate and Fast Computation of Exponent Fourier Moment
• Authors: Satya P Singh; Shabana Urooj
Pages: 3299 - 3306
Abstract: Abstract Exponent Fourier moments (EFMs) are suitable for image representation and invariant pattern recognition. EFMs posses more number of uniformly distributed zeros as compared to Zernike Moments. However, these moments tend to be unstable near the center of image and also show a rise in reconstruction error for higher order of moments. In this paper, we propose a new computational framework for calculating the traditional EFM by partitioning the radial and angular part into equally spaced sectors. The proposed approach is simple and results in better image representation capability, numerical stability, and computational speed. Moreover, the proposed approach is completely stable near the center of image.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2465-7
Issue No: Vol. 42, No. 8 (2017)

• Enhancing Efficiency of the Test Case Prioritization Technique by
Improving the Rate of Fault Detection
• Authors: Soumen Nayak; Chiranjeev Kumar; Sachin Tripathi
Pages: 3307 - 3323
Abstract: Abstract Test case prioritization techniques organize test cases for implementation in a manner that enhance their efficacy in accordance with some performance goal. The main aim of regression testing is to test the amended software to assure that the amendments performed in software are correct. It is not always feasible to retest entire test cases in a test suite due to limited resources. Therefore, it is necessary to develop some effective techniques that can enhance the regression testing effectiveness by organizing the test cases in an order following some testing criterion. One possible criterion of such prioritization is to enhance a test suite’s fault detection rate. It aspires to arrange test cases in an order that higher priority test cases run earlier than lower ones. This paper proposed a methodology for prioritizing regression test cases based on four factors namely the rate of fault detection, the number of faults detected, the test case ability of risk detection and the test case effectiveness. The proposed approach is implemented on two projects. The resultant test case order is analyzed with other prioritization techniques such as no prioritization, random prioritization, reverse prioritization, optimal prioritization and along with previous works for project 1. We have applied our proposed approach for prioritizing test cases in an order that maximize fault coverage with least test suite execution and compared its effectiveness with other orderings. The result of proposed approach shows higher average percentage of fault detected value and outperforms all other approaches.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2466-6
Issue No: Vol. 42, No. 8 (2017)

• Popularity-Aware Content Caching for Distributed Wireless Helper Nodes
• Authors: Furqan H. Khan; Zeashan Khan
Pages: 3375 - 3389
Abstract: Abstract Content caching enables end users to obtain contents in a short time. To further reduce the time to access a mobile wireless network, we consider a device-to-device communication scenario where contents are distributed and users may obtain contents directly from neighbors instead of accessing the base station. For maximizing the cache hit rate per unit of bandwidth consumed, we derive a theoretical model based on the probability distribution of content popularity. To make the problem tractable, we propose a popularity-aware content caching mechanism using the modified weighted Zipf distribution. Through our simulation with a real YouTube trace, the proposed algorithm is compared with the existing well-known least-recently-used algorithm in terms of the achieved hit rate, caching time, cache eviction rate, and consumed bandwidth. The results show that our approach is able to achieve near-optimal performances and at the same time approximate the optimal cache time a cached content resides at the device.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2505-3
Issue No: Vol. 42, No. 8 (2017)

• An Algorithmic Approach for Predicting Unknown Information in Incomplete
Fuzzy Soft Set
• Authors: Sujit Das; Sumonta Ghosh; Samarjit Kar; Tandra Pal
Pages: 3563 - 3571
Abstract: Abstract This paper proposes a novel approach to estimate the missing or unknown information in incomplete fuzzy soft sets (FSSs). Incomplete information in fuzzy soft sets leads to more uncertainty and ambiguity in decision making. The need to represent unknown or missing information using the available knowledge is becoming increasingly important. The proposed method initially finds the mean value of each parameter exploiting the existing information. Then average distance of each parameter from the mean is computed. A pair of useful distance information is derived using the average distance and mean. Next we determine the unknown information using the probabilistic weight and distance information. In order to generalize the concept, we also extend the proposed approach for finding the missing or unknown information in the context of interval-valued fuzzy soft sets. Two illustrative examples are provided to show the effectiveness of the developed approaches. The result of the proposed method for FSS has been compared with the existing method using two well-known entropy measures, Kosko’s (Inf Sci 40:165–174, 1986) entropy and De Luca and Termini’s (Inf Control 20:301–312, 1972) entropy. The comparative analysis has shown that the proposed approach is preferable as it has less entropy, i.e., less degree of fuzziness than that of the existing approach.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2591-2
Issue No: Vol. 42, No. 8 (2017)

• Extended Absolute Fuzzy Connectedness Segmentation Algorithm Utilizing
Region and Boundary-Based Information
• Authors: T. H. Farag; W. A. Hassan; H. A. Ayad; A. S. AlBahussain; U. A. Badawi; M. K. Alsmadi
Pages: 3573 - 3583
Abstract: Abstract Image segmentation is the process of dividing an image into meaningful objects to perform different analysis operations. Fuzzy connectedness (FC)-based segmentation methods usually give robust segmentation results; on the other hand, they suffer from some weaknesses. The generalized or absolute fuzzy connectivity (GFC) segmentation method is the foundation of most FC-based methods. This method has two apparent weaknesses: It combines different objects in the case of their boundaries are blurred, and it can not find the object of interest if the threshold value determined without interactive manner. In this manuscript, we introduce extensions to the GFC algorithm to tackle the mentioned weaknesses. The FC and affinity functions in the extended algorithm utilize region- and boundary-based information to overcome the first weakness. Moreover, this algorithm suggests a near optimal threshold generated automatically to eliminate the need for any interaction. Comparisons has been made to quantitatively evaluate the proposed algorithm over a three sorts of data set of scenes. Measures of relevance have been calculated for two data sets. Results indicate improved segmentation accuracy and also showed that the weaknesses of the traditional GFC algorithms have been eliminated to some extent.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2577-0
Issue No: Vol. 42, No. 8 (2017)

• Foreground Detection via Background Subtraction and Improved Three-Frame
Differencing
• Authors: Sandeep Singh Sengar; Susanta Mukhopadhyay
Pages: 3621 - 3633
Abstract: Abstract Moving object detection is a widely used and important research topic in computer vision and video processing. Foreground aperture, ghosting and sudden illumination changes are the main problems in moving object detection. To consider the above problems, this work proposes two approaches: (i) improved three-frame difference method and (ii) combining background subtraction and improved three-frame difference method for the detection of multiple moving objects from indoor and outdoor real video dataset. This work accurately detects the moving objects with varying object size and number in different complex environments. We compute the detection error and processing time of two proposed as well as previously existing approaches. Experimental results and error rate analysis show that our methods detect the moving targets efficiently and effectively as compared to the traditional approaches.
PubDate: 2017-08-01
DOI: 10.1007/s13369-017-2672-2
Issue No: Vol. 42, No. 8 (2017)

• Synthesis and Characterization of Zeolite HS Using Natural Pyrophyllite as
New Clay Source
• Authors: A. El Gaidoumi; A. Chaouni Benabdallah; B. El Bali; A. Kherbeche
Abstract: Abstract Zeolite synthesis has been achieved by alkaline treatment of a local clay, pyrophyllite. The chemical, textural and structural characteristics of the modified clay were evaluated and compared to those of the raw clay. The samples were characterized by X-ray fluorescence, nitrogen adsorption–desorption studies, X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy and thermoanalysis (TG–DSC). The pyrophyllite was converted to porous hydroxysodalite (HS), nearly pure, which has a surface area of 19.56  $$\hbox {m}^{2}\,\hbox {g}^{-1}$$ with a spherical structure and cubic system.
PubDate: 2017-08-07
DOI: 10.1007/s13369-017-2768-8

• Removal of Freshwater Microalgae by Flocculation-Enhanced
Electro-flotation Using Stainless Steel Mesh Electrode
• Authors: Arpon Lucero; Young-Seek Park; Dong-Seog Kim
Abstract: Abstract This study was conducted to explore the possibility of increasing the efficiency of electro-flotation in two ways: (1) by using an appropriate electrode capable of generating more microbubbles and (2) by introducing flocculation. The generation of more microbubbles was achieved by using an electrode with higher surface area. To further increase the removal efficiency, two inorganic $$[\hbox {Al}_{2}(\hbox {SO}_{4})_{3}$$ and $$\hbox {Fe}_{2}(\hbox {SO}_{4})_{3}]$$ and two polymer coagulants (PAC and polymer anion) were used as enhancements to electro-flotation. The results showed that 3 out of the 4 coagulants used have the capacity to remove 95% of microalgae in 1 L of suspension by using electro-flotation. By retrofitting flocculation into electro-flotation, the coagulant dose was significantly decreased in comparison with conventional flocculation process. Moreover, 95% removal of microalgae suspension from local eutrophic river (Nakdong river) was achieved also with PAC by enhanced electro-flotation. The results of this study also showed that the current method tremendously decreased the coagulant consumption as compared to other removal methods such as flocculation and flotation by DAF as mentioned in the later section of this study. Hence, it is an economical microalgae removal method and at the same time an efficient way to reduce water contamination due to excessive doses of coagulant.
PubDate: 2017-08-04
DOI: 10.1007/s13369-017-2712-y

• Dynamic Authentication of Smartphone Users Based on Touchscreen Gestures
• Authors: Shatha J. Alghamdi; Lamiaa A. Elrefaei
Abstract: Abstract This paper proposes a dynamic authentication of smartphone users based on their gestures on touchscreen. The user authentication consists of three stages: collecting touch gestures’ data, extracting features, and classification. Tapping, scrolling, dragging and zooming gestures’ data are acquired using a developed android application. Then, features from these gestures are extracted. Finally, three different classifiers, medians vector proximity (MVP), k-nearest neighbor (k-NN) and random forest (RF), are applied to the extracted features. The performance of these classifiers are investigated and compared considering a single-touch gesture and all possible combinations of the extracted touch gestures on smartphone. The experimental results show that the MVP classifier brings the best results when using single gestures. When two gestures are combined together, the k-NN gives the best results. The k-NN classifier reaches an equal error rate of 0% using only three gestures. The RF is not ideal to be used on smartphone users’ authentication as it gives the worst results.
PubDate: 2017-08-04
DOI: 10.1007/s13369-017-2758-x

• Thermo-Mechanical Nonlinear Bending Analysis of Functionally Graded Thick
Circular Plates Resting on Winkler Foundation Based on Sinusoidal Shear
Deformation Theory
• Authors: Fatemeh Farhatnia; Jafar Babaei; Raana Foroudastan
PubDate: 2017-08-03
DOI: 10.1007/s13369-017-2753-2

• Mixed Integer Programming Formulations for Two-Machine Flow Shop
Scheduling with an Availability Constraint
• Authors: Zhijun Xu; Dehua Xu; Jie He; Qi Wang; Aihua Liu; Junfang Xiao
Abstract: Abstract A two-machine flow shop scheduling scenario with an availability constraint on one of the two machines is considered. Seven mixed integer programming formulations (MIPFs) are proposed for the problem where the availability constraint is imposed on the first machine. Seven analogs are proposed for its counterpart. Size complexity analysis of these MIPFs is provided. Numerical results indicate that, for either one of the two problems, each of the corresponding first three MIPFs can solve instances of size up to 100 jobs in reasonable times.
PubDate: 2017-08-02
DOI: 10.1007/s13369-017-2763-0

• On the Linear Antenna Array Synthesis Techniques for Sum and Difference
Patterns Using Flower Pollination Algorithm
• Authors: V. V. S. S. S. Chakravarthy; P. S. R. Chowdary; Ganapati Panda; Jaume Anguera; Aurora Andújar; Babita Majhi
Abstract: Abstract Enhancement of performance of antenna array in terms of directive characteristics requires simultaneous control of both side-lobe level (SLL) and beam width (BW). The population-based evolutionary computing techniques are best suited for such array synthesis problems. In this paper, a novel evolutionary computing tool known as flower pollination algorithm (FPA) is applied to linear array synthesis problem. In addition, the performance of both amplitude only and amplitude–spacing-based methods is assessed. The proposed method estimates the weights of each objective so that the generated radiation patterns with desired SLL and BW are produced. The performance and the efficiency of FPA-based method are evaluated and also compared with those obtained using genetic algorithm and particle swarm optimization. The problem of synthesizing patterns with narrow and wide nulls is also investigated. Multiple narrow band nulls as well wide nulls are produced using the FPA with amplitude only method. The investigation has been made for both sum and difference patterns.
PubDate: 2017-08-02
DOI: 10.1007/s13369-017-2750-5

• An Approach to Adaptive Pedestrian Detection and Classification in
Infrared Images Based on Human Visual Mechanism and Support Vector Machine

• Authors: Rajkumar Soundrapandiyan; P. V. S. S. R. Chandra Mouli
Abstract: Abstract Pedestrian detection is challenging in infrared images because of the low signal-to-noise ratio (SNR), low contrast, lack of shape, and complex background. In this paper, an adaptive pedestrian detection method based on human visual mechanism and support vector machine is proposed to overcome these difficulties. As per the human visual attention mechanism, firstly mean and Laplacian of Gaussian (LoG) filter is employed to suppress background noise and increases the SNR value, but it increases contrast relation between the foreground and background. In addition, to remove the remaining noise, the morphological process is applied on the filtered image. The pedestrians and non-pedestrians are obtained by applying local thresholding segmentation to the morphological processed image. Further, to recognize the true pedestrian and to reduce the false alarm rate, support vector machine classifier is used. Experiments are carried out on the standard OTCBVS-BENCH-thermal collection over the OSU thermal pedestrian database by comparing with other methods. The proposed method shows the efficacy by high pedestrian detection rate and low false alarm rate. The contributions of this research work are as follows: (1) The parameters required for the processing of proposed method is calculated adaptively, (2) Background suppression and enhancement of pedestrian is done using human visual system property contrast mechanism, i.e., LoG filter with kurtosis, (3) The pedestrians and non-pedestrians are detected using L-moment-based local thresholding, and (4) The proposed method can work for an input image of any size with similar time complexity.
PubDate: 2017-08-02
DOI: 10.1007/s13369-017-2642-8

• Dielectric Characterizations and Microwave Heating Behavior of Zinc
Compound in Microwave Field
• Authors: Guo Lin; Tu Hu; Chenhui Liu; Libo Zhang; Jinhui Peng; Li Yang
Abstract: Abstract The microwave absorption capabilities of zinc acetate dihydrate and ZnO are explored by measuring the dielectric characterizations (real part, imaginary part and loss tangent) from room temperature to $$900\, {^{\circ }}\hbox {C}$$ using the microwave cylindrical resonant cavity technique at 2450 MHz. The dielectric characterizations of zinc acetate dihydrate increase substantially below $$100\, {^{\circ }}\hbox {C}$$ and present a linearly with temperature due to the evaporation of crystal water. As the temperature continues to increase, the three parameters decrease dramatically. Additionally, variations of $$\varepsilon '$$ , $$\varepsilon ''$$ and tan $$\updelta$$ are presented narrowly at different temperatures for ZnO. The decreasing penetration depth within the room temperature to $$100\, {^{\circ }}\hbox {C}$$ indicates the microwave absorption capability of crystal water is realized much more positive than $$\hbox {Zn(OAc)}_{2}$$ and ZnO. And the results also show that the absorption capability of free water is much larger than crystal water. Heating curves of zinc acetate dihydrate and ZnO at different power levels (400, 600 and 800 W) further suggest that the absorption capability of ZnO is perceived most poor. A higher crystallinity and smaller particle size can be obtained by microwave heating compared with conventional heating.
PubDate: 2017-08-02
DOI: 10.1007/s13369-017-2760-3

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