Open AccessArticle
An N100-P300 Spelling Brain-Computer Interface with Detection of Intentional Control
Computers 2016, 5(4), 31; doi:10.3390/computers5040031 -
Abstract
A brain-computer interface (BCI) is a tool to communicate with a computer via brain signals without the user making any physical movements, thus enabling disabled people to communicate with their environment and with others. P300-based ERP spellers are a widely used spelling visual
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A brain-computer interface (BCI) is a tool to communicate with a computer via brain signals without the user making any physical movements, thus enabling disabled people to communicate with their environment and with others. P300-based ERP spellers are a widely used spelling visual BCI using the P300 component of event-related potential (ERP). However, they have a technical problem in that at least 2N flashes are required to present N characters. This prevents the improvement of accuracy and restricts the typing speed. To address this issue, we propose a method that uses N100 in addition to P300. We utilize novel stimulus images to detect the user’s gazing position by using N100. By using both P300 and N100, the proposed visual BCI reduces the number of flashes and improves the accuracy of the P300 speller. We also propose using N100 to classify non-control (NC) and intentional control (IC) states. In our experiments, the detection accuracy of N100 was significantly higher than that of P300 and the proposed method exhibited a higher information transfer rate (ITR) than the P300 speller. Full article
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Open AccessArticle
Store-Carry and Forward-Type M2M Communication Protocol Enabling Guide Robots to Work together and the Method of Identifying Malfunctioning Robots Using the Byzantine Algorithm
Computers 2016, 5(4), 30; doi:10.3390/computers5040030 -
Abstract
This paper concerns a service in which multiple guide robots in an area display arrows to guide individual users to their destinations. It proposes a method of identifying malfunctioning robots and robots that give wrong directions to users. In this method, users’ mobile
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This paper concerns a service in which multiple guide robots in an area display arrows to guide individual users to their destinations. It proposes a method of identifying malfunctioning robots and robots that give wrong directions to users. In this method, users’ mobile terminals and robots form a store-carry and forward-type M2M communication network, and a distributed cooperative protocol is used to enable robots to share information and identify malfunctioning robots using the Byzantine algorithm. The robots do not directly communicate with each other, but through users’ mobile terminals. We have introduced the concept of the quasi-synchronous number, so whether a certain robot is malfunctioning can be determined even when items of information held by all of the robots are not synchronized. Using simulation, we have evaluated the proposed method in terms of the rate of identifying malfunctioning robots, the rate of reaching the destination and the average length of time to reach the destination. Full article
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Open AccessArticle
An Improved Retrievability-Based Cluster-Resampling Approach for Pseudo Relevance Feedback
Computers 2016, 5(4), 29; doi:10.3390/computers5040029 -
Abstract
Cluster-based pseudo-relevance feedback (PRF) is an effective approach for searching relevant documents for relevance feedback. Standard approach constructs clusters for PRF only on the basis of high similarity between retrieved documents. The standard approach works quite well if the retrieval bias of the
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Cluster-based pseudo-relevance feedback (PRF) is an effective approach for searching relevant documents for relevance feedback. Standard approach constructs clusters for PRF only on the basis of high similarity between retrieved documents. The standard approach works quite well if the retrieval bias of the retrieval model does not create any effect on the retrievability of documents. In our experiments we observed when a collection contains retrieval bias, then high retrievable documents of clusters are frequently retrieved at top positions for most of the queries, and these drift the relevance feedback away from relevant documents. For reducing (retrieval bias) noise, we enhance the standard cluster construction approach by constructing clusters on the basis of high similarity and retrievability. We call this retrievability and cluster-based PRF. This enhanced approach keeps only those documents in the clusters that are not frequently retrieve due to retrieval bias. Although this approach improves the effectiveness, however, it penalizes high retrievable documents even if these documents are most relevant to the clusters. To handle this problem, in a second approach, we extend the basic retrievability concept by mining frequent neighbors of the clusters. The frequent neighbors approach keeps only those documents in the clusters that are frequently retrieved with other neighbors of clusters and infrequently retrieved with those documents that are not part of the clusters. Experimental results show that two proposed extensions are helpful for identifying relevant documents for relevance feedback and increasing the effectiveness of queries. Full article
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Open AccessArticle
DeepCAD: A Computer-Aided Diagnosis System for Mammographic Masses Using Deep Invariant Features
Computers 2016, 5(4), 28; doi:10.3390/computers5040028 -
Abstract
The development of a computer-aided diagnosis (CAD) system for differentiation between benign and malignant mammographic masses is a challenging task due to the use of extensive pre- and post-processing steps and ineffective features set. In this paper, a novel CAD system is proposed
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The development of a computer-aided diagnosis (CAD) system for differentiation between benign and malignant mammographic masses is a challenging task due to the use of extensive pre- and post-processing steps and ineffective features set. In this paper, a novel CAD system is proposed called DeepCAD, which uses four phases to overcome these problems. The speed-up robust features (SURF) and local binary pattern variance (LBPV) descriptors are extracted from each mass. These descriptors are then transformed into invariant features. Afterwards, the deep invariant features (DIFs) are constructed in supervised and unsupervised fashion through multilayer deep-learning architecture. A fine-tuning step is integrated to determine the features, and the final decision is performed via softmax linear classifier. To evaluate this DeepCAD system, a dataset of 600 region-of-interest (ROI) masses including 300 benign and 300 malignant masses was obtained from two publicly available data sources. The performance of DeepCAD system is compared with the state-of-the-art methods in terms of area under the receiver operating characteristics (AUC) curve. The difference between AUC of DeepCAD and other methods is statistically significant, as it demonstrates a sensitivity (SN) of 92%, specificity (SP) of 84.2%, accuracy (ACC) of 91.5% and AUC of 0.91. The experimental results indicate that the proposed DeepCAD system is reliable for providing aid to radiologists without the need for explicit design. Full article
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Open AccessArticle
A Security Analysis of Cyber-Physical Systems Architecture for Healthcare
Computers 2016, 5(4), 27; doi:10.3390/computers5040027 -
Abstract
This paper surveys the available system architectures for cyber-physical systems. Several candidate architectures are examined using a series of essential qualities for cyber-physical systems for healthcare. Next, diagrams detailing the expected functionality of infusion pumps in two of the architectures are analyzed. The
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This paper surveys the available system architectures for cyber-physical systems. Several candidate architectures are examined using a series of essential qualities for cyber-physical systems for healthcare. Next, diagrams detailing the expected functionality of infusion pumps in two of the architectures are analyzed. The STRIDE Threat Model is then used to decompose each to determine possible security issues and how they can be addressed. Finally, a comparison of the major security issues in each architecture is presented to help determine which is most adaptable to meet the security needs of cyber-physical systems in healthcare. Full article
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Open AccessArticle
Development and Evaluation of the Virtual Prototype of the First Saudi Arabian-Designed Car
Computers 2016, 5(4), 26; doi:10.3390/computers5040026 -
Abstract
Prototyping and evaluation are imperative phases of the present product design and development process. Although digital modeling and analysis methods are widely employed at various product development stages, still, building a physical prototype makes the present typical process expensive and time consuming. Therefore,
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Prototyping and evaluation are imperative phases of the present product design and development process. Although digital modeling and analysis methods are widely employed at various product development stages, still, building a physical prototype makes the present typical process expensive and time consuming. Therefore, it is necessary to implement new technologies, such as virtual prototyping, which can enable industry to have a rapid and more controlled decision making process. Virtual prototyping has come a long way in recent years, where current environments enable stereoscopic visuals, surround sound and ample interaction with the generated models. It is also important to evaluate how representative the developed virtual prototype is when compared to the real-world counterpart and the sense of presence reported by users of the virtual prototype. This paper describes the systematic procedure to develop a virtual prototype of Gazal-1 (i.e., the first car prototype designed by Saudi engineers) in a semi-immersive virtual environment. The steps to develop a virtual prototype from CAD (computer-aided design) models are explained in detail. Various issues involved in the different phases for the development of the virtual prototype are also discussed comprehensively. The paper further describes the results of the subjective assessment of a developed virtual prototype of a Saudi Arabian-designed automobile. User’s feedback is recorded using a presence questionnaire. Based on the user-based study, it is revealed that the virtual prototype is representative of the real Saudi Arabian car and offers a flexible environment to analyze design features when compared against its physical prototype. The capabilities of the virtual environment are validated with the application of the car prototype. Finally, vital requirements and directions for future research are also presented. Full article
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Open AccessArticle
Low Noise Low Power CMOS Telescopic-OTA for Bio-Medical Applications
Computers 2016, 5(4), 25; doi:10.3390/computers5040025 -
Abstract
The preamplifier block is crucial in bio-medical signal processing. The power intensive Operational Transconductance Amplifier (OTA) is considered, and the performance of preamplifier is studied. A low noise and low power telescopic OTA is proposed in this work. To reduce the noise contribution
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The preamplifier block is crucial in bio-medical signal processing. The power intensive Operational Transconductance Amplifier (OTA) is considered, and the performance of preamplifier is studied. A low noise and low power telescopic OTA is proposed in this work. To reduce the noise contribution in the active load transistors, source degeneration technique is incorporated in the current stealing branch of the OTA. The OTA design optimization is achieved by gm/Id methodology, which helps to determine the device geometrical parameters (W/L ratio). The proposed design was implemented in CMOS 90 nm with bias current and supply voltage of 1.6 µA and 1.2 V, respectively. The post layout simulation results of the proposed amplifier gave a gain of 62 dB with phase margin 57°, CMRR 78 dB, input referred noise 3.2 µVrms, Noise Efficiency Factor (NEF) 1.86 and power consumption of 1.92 µW. Full article
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Open AccessReview
Quantum Genetic Algorithms for Computer Scientists
Computers 2016, 5(4), 24; doi:10.3390/computers5040024 -
Abstract
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the
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Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum-mechanical phenomena to perform operations on data) has led to a new class of GAs known as “Quantum Genetic Algorithms” (QGAs). In this review, we present a discussion, future potential, pros and cons of this new class of GAs. The review will be oriented towards computer scientists interested in QGAs “avoiding” the possible difficulties of quantum-mechanical phenomena. Full article
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Open AccessArticle
Non-Invasive Sensor Technology for the Development of a Dairy Cattle Health Monitoring System
Computers 2016, 5(4), 23; doi:10.3390/computers5040023 -
Abstract
The intention of this research is to establish a relationship between dairy cattle diseases with various non-invasive sensors for the development of a health monitoring system. This paper expands on the conference paper titled “Sensor technology for animal health monitoring” published in the
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The intention of this research is to establish a relationship between dairy cattle diseases with various non-invasive sensors for the development of a health monitoring system. This paper expands on the conference paper titled “Sensor technology for animal health monitoring” published in the International Journal on Smart Sensing and Intelligent Systems (s2is) for the proceedings of International Conference on Sensing Technology (ICST) 2014. This paper studies and explores particular characteristics of dairy cattle’s health and behavioural symptoms. The aim is to consider the nature of the diseases a cow may have and relate it with one or many sensors that are suitable for accurate measurement of the behavioural changes. The research uses ontological relationship mapping or ontology matching to integrate heterogeneous databases of diseases and sensors and explains it in detail. This study identifies the sensors needed to determine illnesses in a dairy cow and how they would be beneficial for the development of non-invasive, wearable, smart, dairy cattle health monitoring system to be placed on the cows’ neck. It also explains how the primary sensors identified by this research can be used to forecast cattle health in a simple, basic manner. The scope of this paper is limited to the discussion about the non-invasive, wearable sensors that are needed to determine the cattle diseases. We focused only on non-invasive sensors because they are easy to install on cows and no training is required for them to be installed as compared to invasive sensors. Development of such a system and its evaluation is not in the scope of this paper and is left for our next paper. Full article
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Open AccessReview
Ambient Technology to Assist Elderly People in Indoor Risks
Computers 2016, 5(4), 22; doi:10.3390/computers5040022 -
Abstract
While elderly people perform their daily indoor activities, they are subjected to several risks. To improve the quality of life of elderly people and promote healthy aging and independent living, elderly people need to be provided with an assistive technology platform to rely
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While elderly people perform their daily indoor activities, they are subjected to several risks. To improve the quality of life of elderly people and promote healthy aging and independent living, elderly people need to be provided with an assistive technology platform to rely on during their activities. We reviewed the literature and identified the major indoor risks addressed by assistive technology that elderly people face during their indoor activities. In this paper, we identify these risks as: fall, wrong self-medication management, fire, burns, intoxication by gas/smoke, and the risk of inactivity. In addition, we discuss the existing assistive technology systems and classify the risk detection algorithms, techniques and the basic system principles and interventions to enhance safety of elderly people. Full article
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Open AccessReview
A Survey of 2D Face Recognition Techniques
Computers 2016, 5(4), 21; doi:10.3390/computers5040021 -
Abstract
Despite the existence of various biometric techniques, like fingerprints, iris scan, as well as hand geometry, the most efficient and more widely-used one is face recognition. This is because it is inexpensive, non-intrusive and natural. Therefore, researchers have developed dozens of face recognition
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Despite the existence of various biometric techniques, like fingerprints, iris scan, as well as hand geometry, the most efficient and more widely-used one is face recognition. This is because it is inexpensive, non-intrusive and natural. Therefore, researchers have developed dozens of face recognition techniques over the last few years. These techniques can generally be divided into three categories, based on the face data processing methodology. There are methods that use the entire face as input data for the proposed recognition system, methods that do not consider the whole face, but only some features or areas of the face and methods that use global and local face characteristics simultaneously. In this paper, we present an overview of some well-known methods in each of these categories. First, we expose the benefits of, as well as the challenges to the use of face recognition as a biometric tool. Then, we present a detailed survey of the well-known methods by expressing each method’s principle. After that, a comparison between the three categories of face recognition techniques is provided. Furthermore, the databases used in face recognition are mentioned, and some results of the applications of these methods on face recognition databases are presented. Finally, we highlight some new promising research directions that have recently appeared. Full article
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Open AccessArticle
Array Multipliers for High Throughput in Xilinx FPGAs with 6-Input LUTs
Computers 2016, 5(4), 20; doi:10.3390/computers5040020 -
Abstract
Multiplication is the dominant operation for many applications implemented on field-programmable gate arrays (FPGAs). Although most current FPGA families have embedded hard multipliers, soft multipliers using lookup tables (LUTs) in the logic fabric remain important. This paper presents a novel two-operand addition circuit
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Multiplication is the dominant operation for many applications implemented on field-programmable gate arrays (FPGAs). Although most current FPGA families have embedded hard multipliers, soft multipliers using lookup tables (LUTs) in the logic fabric remain important. This paper presents a novel two-operand addition circuit (patent pending) that combines radix-4 partial-product generation with addition and shows how it can be used to implement two’s-complement array multipliers. The circuit is specific to modern Xilinx FPGAs that are based on a 6-input LUT architecture. Proposed pipelined multipliers use 42%–52% fewer LUTs, and some versions can be clocked up to 23% faster than delay-optimized LogiCORE IP multipliers. This allows 1.72–2.10-times as many multipliers to be implemented in the same logic fabric and potentially offers 1.86–2.58-times the throughput by increasing the clock frequency. Full article
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Open AccessArticle
Fractal Aspects in Classical Parallel Computing
Computers 2016, 5(3), 19; doi:10.3390/computers5030019 -
Abstract
In this paper, we prove that many parallel communication topologies and several parallel algorithms have fractal properties, which leads to the idea that there is a strong connection between the classical parallel computing and a plausible computing on a fractal medium. Furthermore, we
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In this paper, we prove that many parallel communication topologies and several parallel algorithms have fractal properties, which leads to the idea that there is a strong connection between the classical parallel computing and a plausible computing on a fractal medium. Furthermore, we show that some parallel algorithms are suitable for incursive and hyperincursive computation, which links parallel computing to quantum computing and a possible fractal computing. Full article
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Open AccessArticle
A University-Based Smart and Context Aware Solution for People with Disabilities (USCAS-PWD)
Computers 2016, 5(3), 18; doi:10.3390/computers5030018 -
Abstract
(1) Background: A disabled student or employee in a certain university faces a large number of obstacles in achieving his/her ordinary duties. An interactive smart search and communication application can support the people at the university campus and Science Park in a number
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(1) Background: A disabled student or employee in a certain university faces a large number of obstacles in achieving his/her ordinary duties. An interactive smart search and communication application can support the people at the university campus and Science Park in a number of ways. Primarily, it can strengthen their professional network and establish a responsive eco-system. Therefore, the objective of this research work is to design and implement a unified flexible and adaptable interface. This interface supports an intensive search and communication tool across the university. It would benefit everybody on campus, especially the People with Disabilities (PWDs). (2) Methods: In this project, three main contributions are presented: (A) Assistive Technology (AT) software design and implementation (based on user- and technology-centered design); (B) A wireless sensor network employed to track and determine user’s location; and (C) A novel event behavior algorithm and movement direction algorithm used to monitor and predict users’ behavior and intervene with them and their caregivers when required. (3) Results: This work has developed a comprehensive and universal application with a unified, flexible, and adaptable interface to support the different conditions of PWDs. It has employed an interactive smart based-location service for establishing a smart university Geographic Information System (GIS) solution. This GIS solution has been based on tracking location service, mobility, and wireless sensor network technologies. (4) Conclusion: The proposed system empowered inter-disciplinary interaction between management, staff, researchers, and students, including the PWDs. Identifying the needs of the PWDs has led to the determination of the relevant requirements for designing and implementing a unified flexible and adaptable interface suitable for PWDs on the university campus. Full article
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Open AccessArticle
Color Reduction in an Authenticate Live 3D Point Cloud Video Streaming System
Computers 2016, 5(3), 17; doi:10.3390/computers5030017 -
Abstract
In this paper, an authenticate live 3D point cloud video streaming system is presented, using a low cost 3D sensor camera, the Microsoft Kinect. The proposed system is implemented on a client-server network infrastructure. The live 3D video is captured from the Kinect
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In this paper, an authenticate live 3D point cloud video streaming system is presented, using a low cost 3D sensor camera, the Microsoft Kinect. The proposed system is implemented on a client-server network infrastructure. The live 3D video is captured from the Kinect RGB-D sensor, then a 3D point cloud is generated and processed. Filtering and compression are used to handle the spatial and temporal redundancies. A color histogram based conditional filter is designed to reduce the color information for each frame based on the mean and standard deviation. In addition to the designed filter, a statistical outlier removal filter is used. A certificate-based authentication is used where the client will verify the identity of the server during the handshake process. The processed 3D point cloud video is live streamed over a TCP/IP protocol to the client. The system is evaluated in terms of: compression ratio, total bytes per points, peak signal to noise ratio (PSNR), and Structural Similarity (SSIM) index. The experimental results demonstrate that the proposed video streaming system have a best case with SSIM 0.859, PSNR of 26.6 dB and with average compression ratio of 8.42 while the best average compression ratio case is about 15.43 with PSNR 18.5128 dB of and SSIM 0.7936. Full article
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Open AccessArticle
Intelligent Intrusion Detection of Grey Hole and Rushing Attacks in Self-Driving Vehicular Networks
Computers 2016, 5(3), 16; doi:10.3390/computers5030016 -
Abstract
Vehicular ad hoc networks (VANETs) play a vital role in the success of self-driving and semi self-driving vehicles, where they improve safety and comfort. Such vehicles depend heavily on external communication with the surrounding environment via data control and Cooperative Awareness Messages (CAMs)
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Vehicular ad hoc networks (VANETs) play a vital role in the success of self-driving and semi self-driving vehicles, where they improve safety and comfort. Such vehicles depend heavily on external communication with the surrounding environment via data control and Cooperative Awareness Messages (CAMs) exchanges. VANETs are potentially exposed to a number of attacks, such as grey hole, black hole, wormhole and rushing attacks. This work presents an intelligent Intrusion Detection System (IDS) that relies on anomaly detection to protect the external communication system from grey hole and rushing attacks. These attacks aim to disrupt the transmission between vehicles and roadside units. The IDS uses features obtained from a trace file generated in a network simulator and consists of a feed-forward neural network and a support vector machine. Additionally, the paper studies the use of a novel systematic response, employed to protect the vehicle when it encounters malicious behaviour. Our simulations of the proposed detection system show that the proposed schemes possess outstanding detection rates with a reduction in false alarms. This safe mode response system has been evaluated using four performance metrics, namely, received packets, packet delivery ratio, dropped packets and the average end to end delay, under both normal and abnormal conditions. Full article
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Open AccessArticle
A New Scalable, Distributed, Fuzzy C-Means Algorithm-Based Mobile Agents Scheme for HPC: SPMD Application
Computers 2016, 5(3), 14; doi:10.3390/computers5030014 -
Abstract
The aim of this paper is to present a mobile agents model for distributed classification of Big Data. The great challenge is to optimize the communication costs between the processing elements (PEs) in the parallel and distributed computational models by the way to
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The aim of this paper is to present a mobile agents model for distributed classification of Big Data. The great challenge is to optimize the communication costs between the processing elements (PEs) in the parallel and distributed computational models by the way to ensure the scalability and the efficiency of this method. Additionally, the proposed distributed method integrates a new communication mechanism to ensure HPC (High Performance Computing) of parallel programs as distributed one, by means of cooperative mobile agents team that uses its asynchronous communication ability to achieve that. This mobile agents team implements the distributed method of the Fuzzy C-Means Algorithm (DFCM) and performs the Big Data classification in the distributed system. The paper shows the proposed scheme and its assigned DFCM algorithm and presents some experimental results that illustrate the scalability and the efficiency of this distributed method. Full article
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Open AccessArticle
Strong Authentication Scheme Based on Hand Geometry and Smart Card Factors
Computers 2016, 5(3), 15; doi:10.3390/computers5030015 -
Abstract
In 2009, Xu et al. presented a safe, dynamic, id-based on remote user authentication method that has several advantages such as freely chosen passwords and mutual authentication. In this paper, we review the Xu–Zhu–Feng scheme and indicate many shortcomings in their scheme. Impersonation
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In 2009, Xu et al. presented a safe, dynamic, id-based on remote user authentication method that has several advantages such as freely chosen passwords and mutual authentication. In this paper, we review the Xu–Zhu–Feng scheme and indicate many shortcomings in their scheme. Impersonation attacks and insider attacks could be effective. To overcome these drawbacks, we propose a secure biometric-based remote authentication scheme using biometric characteristics of hand-geometry, which is aimed at withstanding well-known attacks and achieving good performance. Furthermore, our work contains many crucial merits such as mutual authentication, user anonymity, freely chosen passwords, secure password changes, session key agreements, revocation by using personal biometrics, and does not need extra device or software for hand geometry in the login phase. Additionally, our scheme is highly efficient and withstands existing known attacks like password guessing, server impersonation, insider attacks, denial of service (DOS) attacks, replay attacks, and parallel-session attacks. Compared with the other related schemes, our work is powerful both in communications and computation costs. Full article
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Open AccessArticle
Prediction of Dermoscopy Patterns for Recognition of both Melanocytic and Non-Melanocytic Skin Lesions
Computers 2016, 5(3), 13; doi:10.3390/computers5030013 -
Abstract
A differentiation between all types of melanocytic and non-melanocytic skin lesions (MnM–SK) is a challenging task for both computer-aided diagnosis (CAD) and dermatologists due to the complex structure of patterns. The dermatologists are widely using pattern analysis as a first step with clinical
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A differentiation between all types of melanocytic and non-melanocytic skin lesions (MnM–SK) is a challenging task for both computer-aided diagnosis (CAD) and dermatologists due to the complex structure of patterns. The dermatologists are widely using pattern analysis as a first step with clinical attributes to recognize all categories of pigmented skin lesions (PSLs). To increase the diagnostic accuracy of CAD systems, a new pattern classification algorithm is proposed to predict skin lesions patterns by integrating the majority voting (MV–SVM) scheme with multi-class support vector machine (SVM). The optimal color and texture features are also extracted from each region-of-interest (ROI) dermoscopy image and then these normalized features are fed into an MV–SVM classifier to recognize seven classes. The overall system is evaluated using a dataset of 350 dermoscopy images (50 ROIs per class). On average, the sensitivity of 94%, specificity of 84%, 93% of accuracy and area under the receiver operating curve (AUC) of 0.94 are achieved by the proposed MnM–SK system compared to state-of-the-art methods. The obtained result indicates that the MnM–SK system is successful for obtaining the high level of diagnostic accuracy. Thus, it can be used as an alternative pattern classification system to differentiate among all types of pigmented skin lesions (PSLs). Full article
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Open AccessArticle
Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
Computers 2016, 5(2), 12; doi:10.3390/computers5020012 -
Abstract
This research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The
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This research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA) technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was expected to produce the desirable electrical and optical properties of the thin film. The performance of GSA in this research was compared with that of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Artificial Immune System (AIS) and Ant Colony Optimization (ACO). Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process. Full article
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