Computer Reviews Journal <p><em>Computer Reviews</em> is scientific, international peer-reviewed/Referred online journal that is devoted to fields of&nbsp;computing to provide rapid publication of articles frequently in its issues.</p> PURKH en-US Computer Reviews Journal 2581-6640 <p>Authors retain the copyright of their manuscripts, and all Open Access articles are distributed under the terms of the&nbsp;<a href="">Creative Commons Attribution License</a>, which permits unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.</p> <p><a href="" rel="bookmark">Computer Reviews Journal</a>&nbsp;allow the author(s) to retain publishing rights without restrictions.</p> ARMED for the Mobile Processing War <p>This article offers an explanation for why the ARM computer architecture won the hearts and minds of the mobile device manufacturers when incumbents like Intel and AMD had such a huge head start and such a large economic barrier to entry. Our conclusion is that ARM had a better business model, and not a better architecture. To make up for the perception of speed issues, ARM is joining the multi-core arms race. This may soon lead to desktop domination leaving only a legacy code base and sequential programming to enable incumbents to hold on.</p> Douglas Lyon Copyright (c) 2019 Douglas Lyon 2019-04-17 2019-04-17 3 1 3 Experimental Evaluation Platform for Voice Transmission Over Internet of Things (VoIoTs) <p class="Abstract">Internet of Things (IoTs) is an example of the last advances in Information and Communication Technologies. In particular, with the revolutionary development of Wireless Sensor Network (WSN) technologies, researchers largely focused on take benefits of integration embedded low-cost, low-power WSN technology in a various IoTs applications. Real-time voice transmission over IoTs is one interesting application that began to be explored by many researchers. Thus, this paper presents a performance study for transmission of voice over WSN (VoWSN) with and without presence of Internet. A framework using a Raspberry Pi3 (RPi3) and open source FFmpeg technology for processing, compressing and streaming voice to a remote computer is proposed, implemented and evaluated. The performance of the proposed framework is evaluated by studying its behavior utilizing three audio encoding algorithms: AC3, MP3 and OPUS with different sampling rates and a set of evaluation metrics such as :One-way delay, jitter, Bandwidth (B.W), CPU usage and packet losses.</p> Qutaiba Ibrahim Ina'am Fathi Jassim M. Abdul-Jabbar Copyright (c) 2019 Qutaiba Ibrahim, Ina'am Fathi, Jassim M. Abdul-Jabbar 2019-04-30 2019-04-30 3 4 17 An Optimized Robust and Secure Digital Image Watermarking Technique Based on Modified Periodic Plus Smooth Decomposition <p>An optimized Robust and Secure Digital Image Watermarking technique based on modified Periodic Plus Smooth Decomposition (PPSD) is proposed. This proposed technique based on Periodic Plus Smooth Decomposition (PPSD), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The host and watermark image is decomposed into a smooth and periodic component. The smooth component decomposed into its frequency sub-bands through 2nd level DWT. Later by SVD, the watermark singular matrix is combined with the singular matrix of the transformed image. The watermarked image is obtained by using the inverse of DWT. Through the proposed technique we improved the different parameters like PSNR is 92.9075, SSIM watermarked 0.8039, SSIM extracted 0.9924, NCC 0.9929. The experimental result displays that the proposed technique is imperceptible and robust to different attacks. This technique combines the advantages like a false positive problem that is solved by the digital signature. Digital signature gives authentication before extracting watermarks.</p> khushi yadav Sunil Joshi Navneet Agrawal Copyright (c) 2019 khushi yadav, Sunil Joshi, Navneet Agrawal 2019-04-17 2019-04-17 3 18 30 Enhanced AODV Protocol for Hybrid Wireless Network <p>Performance of algorithms in hybrid wireless network routing environments depends on end to end communication delay. Due to the fact that the end to end communication delay includes delay needed for finding the routing path &amp; delay needed for actual routing. This delay increases exponentially as number of nodes increases, and can only be controlled till a certain network size, after which it is not optimum to use the underlying routing protocol, and change it in order to reduce the route computational delay. Thus, in order to provide improvement in Quality of Service (QoS) of hybrid wireless networks we need to off load this complex computational task to a high power and dedicated entity, which will be solely responsible for high speed route calculations. In this paper, we propose a cloud based routing algorithm, which utilizes the compute layer of the cloud in order to optimize the end to end communication delay, reduce the energy consumption, improve the network throughput and reduce the end to end communication delay jitter of the wireless networks.</p> Uma Khemchand Thakur Copyright (c) 2019 Uma Khemchand Thakur 2019-04-17 2019-04-17 3 31 38 Collaborative and Adaptive Framework for Telediagnosis and Prescriptions in Herbal Medicine <p>Herbal medicine has been an age long tradition for the treatment and cure of diseases globally. Previous researches on telediagnosis and prescriptions in orthodox medicine studied applications of modern technological devices which could improve health care services. However, there is yet to be an exhaustive study on the audio-visual technological framework for telediagnosis and prescription in herbal medicine.&nbsp; Hence, the research developed a collaborative and adaptive framework for telediagnosis and prescriptions in herbal medicine. The framework and its system were developed consisting of multimedia features for videoconferencing; ability to record, capture and replay consultations; and capacity for editing, data compression and short message service amongst herbal tele-consultants. The system was experimented on Ladoke Akintola University of Technology hotspot network for a period of twenty one days in order to determine the system’s average packet loss rate and packet transmitted with five herbal tele-consultant nodes (node-1, node2, node3, node4 and node5). All nodes were allotted Internet Protocol addresses through which the intending herbal tele-consultant(s) could be connected to the telediagnosis videoconference session. Three performance metrics, System Reliability Index (SRI), System Degree of Relevance (SDR), and System Ease of Usage (SEU) were used to carry out subject to the evaluation of the system by administering one hundred questionnaires herbal consultants to harvest users’ perception of the system based on a Likert rating scale. The results obtained from telediagnosis session showed that the system recorded packet loss rates of 3.46, 3.13, 3.42, 3.61 and 3.36% at node1, node2, node3, node4 and node5, respectively. Also, the average packets of 3123.2, 5017.6, 5683.2, 4454.4 and 4249.6 bits were obtained at node1, node2, node3, node4 and node5, respectively. The summary of the subjected evaluation of the system indicate that the respondent’s response means of 3.20, 2.88. and 3.42 were obtained for the SRI, SDR and SEU, respectively on a rating scale of 1 to 5.</p> Sanni Abubakar O Ogirima Copyright (c) 2019 Sanni Abubakar O Ogirima 2019-04-17 2019-04-17 3 39 53 Novel Use of an Artificial Neural Network to Computationally Model Cognitive Processes in Science Learning <p>The purpose of this paper is to outline the creation of a computational model making use of an underlying processing element in the form of an artificial neural network (ANN). Within the study, the ANN models multiple conservation tasks as inputs from video game play during a high school science content learning game. This model is based upon the identification of cognitive attributes and integration of two advanced psychological and educational measurement theories. Using the approached of cognitive diagnostics, and item response theory (IRT) data examined for computational suitability. Once initial task response patterns are identified via IRT; the patterns are parametrized and presented to an artificial neural network (ANN) as probabilities. Using the ANN derived Student Task and Cognition Model (STAC-M); the study authors simulated a cognitive training intervention using 100,000 students in science classrooms. Results of the simulation suggest that it is possible to increase levels of student success using a targeted cognitive attribute approach and that computational modeling provides a means to develop future science education research and is a means to test current educational theory.</p> Richard Richard Lamb Copyright (c) 2019 Richard Richard Lamb 2019-04-17 2019-04-17 3 54 64 Fuzzy System and Game Theory for Green Supply Chain <p>In this paper, an optimization model using fuzzy game theory for three players is developed, which is affected by customer demands in a green supply chain. The proposed model includes a practical solution to increase the confidence level of players to choose plausible green strategy. Initially, the strategies are formulated using the game theory as manufacturer, costumer and government, to be able to optimize the pay-off uncertainty conditions of demands, by combining computational fuzzy set with ability of sensitive analysis of related fuzzy parameters to enhance the calculations and problem solving, with presenting Nash equilibrium the problem solving part.</p> Marwan Alakhras Copyright (c) 2019 Marwan Alakhras 2019-04-30 2019-04-30 3 65 87 A Mean Reverting Stochastic Process (MRSP) using an AR(n) Model and a Kalman Filter for Generating Intravalues for the Daily DJIA Time Series <p>This paper presents a model for generating intravalues of time-series. The model uses a mean reverting stochastic process (MRSP). The deterministic or mean part of the process is forecasted by an autoregressive of order n, AR(n), model. The unobservable AR(n) coefficients are calculated by a Kalman Filter using n time series observations. The stochastic part of the process is a Brownian motion multiplied by a volatility term. Measures of the Kalman filter covariance matrix along with the process itself are used to capture the volatility dynamics for the intravalues of the time-series. The MRSP model also provides for the evolution of the intravalues of the time series. Experimental results are presented demonstrating the applicability of the model using daily data from the Dow Jones Industrial Average (DJIA) time series.</p> Athina Petrou Bougioukou Apostolos Leros Theodoros Maris Copyright (c) 2019 Athina Petrou Bougioukou, Apostolos Leros, Theodoros Maris 2019-04-30 2019-04-30 3 88 110 Evolution and Trends in the Educational Model of Distance Education in Mexico, Towards an Education 4.0 <p>Currently, the development of increasingly sophisticated platforms to carry out Distance Education (ED) at a higher level is underway. Through the implementation of different types of emerging technologies, and with this, there is a pressing need to standardise a frame of reference sufficiently effective and adaptable that allows the restructuring of the established educational model that covers the inherent needs of the new practices of the teaching-learning process. For this reason, in this document, a brief description and analysis of the traditional educational model are carried out in this learning mode, in order to identify the most critical factors and propose an extrapolation alternative to a model within the framework of Education 4.0.</p> Tania Jezabel Lopez-Garcia Jesus Antonio Alverez-Cedillo Teodoro Alvarez-Sanchez Claudia Marina Vicario-solorzano Copyright (c) 2019 Tania Jezabel Lopez-Garcia, JESUS ANTONIO ALVAREZ-CEDILLO, DR., TEODORO ALVAREZ-SANCHEZ, DR., Claudia Marina Vicario-solorzano, Dra. 2019-04-17 2019-04-17 3 111 121 Comparative Analysis of Prognostic Model for Risk Classification of Neonatal Jaundice using Machine Learning Algorithms <p>This study focused on the development of a prediction model using identified classification factors in order to classify the risk of jaundice in selected neonates. Historical dataset on the distribution of the classification of risk of jaundice among neonates was collected using questionnaires following the identification of associated classification factors of risk of jaundice from medical practitioners. The dataset containing information about the classification factors identified and collected from the neonates were used to formulate predictive model for the classification of risk of jaundice using 2 machine learning algorithm – Naïve Bayes’ classifier and the multi-layer perceptron.The predictive model development using the decision trees algorithm was formulated and simulated using the WEKA software.The predictive model developed using the multi-layer perceptron and Naïve Bayes’ classifier algorithms were compared in order to determine the algorithm with the best performance.The result shows that 10 variables were identified by the medical expert to be necessary in predicting jaundice in neonates for which a dataset containing information of 23 neonates alongside their respective jaundice diagnosis (Low, Moderate and High) was also provided with 22 attributes following the identification of the required variables.The 10-fold cross validation method was used to train the predictive model developed using the machine learning algorithms and the performance of the models evaluated The multi-layer perceptron algorithm proved to be an effective algorithm for predicting the diagnosis of jaundice in Nigerian neonates</p> Peter Adebayo Idowu Ngozi Chidozie Egejuru Jeremiah Ademola Balogun Olusegun Ajibola Sarumi Copyright (c) 2019 Peter Adebayo Idowu, Ngozi Chidozie Egejuru, Jeremiah Ademola Balogun, Olusegun Ajibola Sarumi 2019-04-17 2019-04-17 3 122 146 Framework to Evaluate Emerging Systems Designed to Health Field <p>In recent years, several information and communication technology systems have emerged as tools to improve sleep quality. Research reveals that poor sleep quality may produce irritability and deficits in performance, concentration, and learning ability in the short term, and is associated with chronic disease in the long term. ICT proposals range from the old Polysomnography (PSG) to innovative systems, such as wearable devices, smartphone applications, and suites of sensors embedded in the users’ environment. Since these technological developments concern a health issue, they have raised important questions regarding their reliability and the level of rigor of the evaluations to which they are submitted. We found that some of the emerging systems that we studied, do not meet the requirements that health science demands to be accepted as clinical tools. The rationale behind this apparent weakness is explained with arguments from the field of evaluations for health interventions and evaluation of technological developments. We propose a framework to evaluate this kind of systems through appropriate scientific methods that provide valuable information to the research. These methods must be performed while designs mature and the feasibility of rigorous evaluations became appropriate.</p> Mabel Vazquez-Briseno Arturo Laflor Hernandez Juan Ivan Nieto-Hipolito Roberto conte Armando Garcia Berumen Everardo Gutierrez Juan de Dios Sanchez Lopez Copyright (c) 2019 Mabel Vazquez-Briseno 2019-04-17 2019-04-17 3 147 155 Efficiency Analysis of Hybrid Fuzzy C-Means Clustering Algorithms and their Application to Compute the Severity of Disease in Plant Leaves <p>Data clustering has a wide range of application varying from medical image analysis, social network analysis, market segmentation, search engines, recommender systems and image processing. A clustering algorithm should be fast as well accurate. Some applications give priority to the speed of the clustering algorithms while some emphasize more on the accuracy rather than speed. A number of clustering algorithms have been proposed in the literature. Some of these include Fuzzy C-Means (FCM), Intuitionistic Fuzzy C-Means (IFCM), Rough Fuzzy C-Means (RFCM) and Rough Intuitionistic Fuzzy C-Means (RIFCM). In this paper, we compare the accuracy and execution time of the fuzzy based clustering algorithms. The clustering algorithms are applied on an image dataset and their running time as well as accuracy is compared by varying the number of clusters. Our results show that there is a clear trade-off between execution time and accuracy of these clustering algorithms. Also, we apply these algorithms on two different diseased leaf images and compute the severity of the disease of the leaves.</p> Anmol Agrawal B.K. Tripathy Copyright (c) 2019 Anmol Agrawal, B.K. Tripathy 2019-04-17 2019-04-17 3 156 169 Application of Multi Objective Genetic Algorithm for Optimization of Core Configuration Design of a Fast Breeder Reactor <p>The optimization problem of nuclear fuel management, reported in the present&nbsp; study aimed at arriving at the optimal number of subassemblies in the two fuel enrichment zones of the core of a 500 MWe Fast Breeder Reactor. The elitist multi-objective approach of Genetic Algorithm, namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II), was employed in the study. The five parameters considered for optimization are: core excess reactivity, liner heat ratings of inner and outer fuel enrichment zones of the core, fissile material inventory, and breeding ratio. The results obtained from the study indicate that the algorithm is able to produce feasible solutions in an efficient manner while preserving the diversity amongst them. The fast convergence and the diversity-preserving feature of the algorithm are described. The major objective of the work is to study the viability of applying the NSGA-II into the nuclear fuel management problems of fast breeder reactors.</p> Jayalal M L Riyas A Jehadeesan R Devan K Sai Baba M Copyright (c) 2019 Jayalal M L, Riyas A, Jehadeesan R, Devan K, Sai Baba M 2019-04-17 2019-04-17 3 170 187 Social Network Infusion Model in Nigerian Tertiary Institutions <p>This study identified the Social Media that were most commonly used by students of tertiary institutions across south-western Nigeria. Structured questionnaires were used to collect information about the Social Media that were adopted by students of tertiary institutions in Nigeria. The results of the study showed that social media adopted were: Facebook, Twitter, Instagram, SnapChat, WhatsApp, LinkedIn, WeChat, ResearchGate, Academia and Line; the most commonly used social media included: Facebook, SnapChat, Twitter and Instagram by at least 55% of the students while ResearchGate, Line, Academia, WeChat and LinkedIn accessed only when there were notifications. The results also showed that the earliest adopted social media included: Facebook in 2007 with 1 user, Twitter in 2009 with 3 users, Instagram and WhatsApp in 2010 with 1 and 8 users respectively. The impact of social media showed that at least 67% of the students suggested it had good impacts on their productivity and functionality as students. This study concluded that among the identified social media, about 55% of students agreed that Facebook, Twitter, Instagram, SnapChat, LinkedIn, Line and ResearchGate were more presently in use. This study showed that using a polynomial model of degree m, the total number of students of higher institutions adopting social media from the year of adoption can be estimated based on the value of the number of years after social media adoption, n (in years).</p> Peter Adebayo Idowu Racheal Adefunke Oladejo Jeremiah Ademola Balogun Olusegun ` Sarumi Copyright (c) 2019 Peter Adebayo Idowu, Racheal Adefunke Oladejo, Mrs, Jeremiah Ademola Balogun, Olusegun ` Sarumi 2019-04-17 2019-04-17 3 188 202 Possibility to Realize an Accelerated Turing Machine <p>On the basis of a theorem, in which an evanescent photon is a superluminal particle, the author considers the possibility of realizing a high performance computer system compared with conventional silicon processors. To realize such a quantum computer utilizing evanescent photons, we must replace electronic components with optical ones, and thus an equivalent optical transistor is required. This critical component for quantum computing can be created using meta-material circuits with a non-linear refractive index. Based on this optical computer system, utilizing meta-material technology, it can be shown that superluminal computation, which is a new concept for an accelerated Turing machine, can be realized in the physical world.</p> Takaaki Musha Copyright (c) 2019 Takaaki Musha 2019-04-30 2019-04-30 3 203 217 An Infusion Model for The Adoption of Social Media in Nigerian Tertiary Institution <p>This study aims to understand the trend of social media adoption among youths especially undergraduates of Nigerian tertiary institutions. This study used a questionnaire for identifying the various social media platforms. Also, the study formulated a polynomial function for estimating the number of students who will adopt the use of social media platforms based on the number of years after the year of social media adoption. The results of the study show that the social media platform adopted by Nigerian undergraduate students include: Facebook, Twitter, Instagram, SnapChat, WhatsApp, LinkedIn, WeChat, ResearchGate, Academia and Line. The results show that the most commonly used platforms are: Facebook, SnapChat, Twitter and Instagram while the earliest adopted platforms include: Facebook in 2007, Twitter in 2009 including Instagram and WhatsApp in 2010. The results showed that the infusion model for the adoption of social media was formulated, using a polynomial function with the best fit of the cumulative frequency distribution of the number of users each year. He studies concluded that using the polynomial function of social media infusion, the total number of future adopters of social media can be estimated from the number of years from the year of the adoption of the platform.</p> Peter Adebayo Idowu Jeremiah Ademola Balogun Olusegun Sarumi Ngozi C Egejuru Racheal Adefunke Oladejo Copyright (c) 2019 Peter Adebayo Idowu, Jeremiah Ademola Balogun, Olusegun Sarumi, Ngozi C Egejuru, Racheal Adefunke Oladejo 2019-04-17 2019-04-17 3 218 235 The Energy Efficient FIR Filter for Biomedical Application using FPGA <p>This research work proposes a low power Finite Impulse Response (FIR) digital filter system using Field Programmable Gate Array (FPGA) to filter biomedical signals. A major issue regarding such implementations is associated with computational complexity that may hinder its practical application. Several researches that aim to overcome this problem have been found by using various designs like booth multiplier, distributive arithmetic design, reduce adder graph (RAG), common sub-expression elimination method etc. This work has achieved the target of power line frequency of 50Hz noise cancellation. It is shown that the proposed design using RAG can give faster speed and require less hardware resources than that for the Direct Structure-I design. The performance of the proposed method is also compared with several existing research works to study its efficacy and it is shown that proposed design can achieve nearly 2% area delay product and 43% less power consumptions in implementation of an FIR low-pass filter. The designed filter is also tested on ECG waves as example of biomedical signal from samples of the MIT-BIH Arrhythmia database corrupted with power frequency noise. The entire system has been implemented on the ALTERA DE-II FPGA education board by synthesizing Verilog HDL using Quartus II tool.</p> Foisal Ahmed Copyright (c) 2019 foisal ahmed 2019-04-17 2019-04-17 3 236 244 Pointing Error Reduction Using Fiber Bundle-based Receiver Design for 200km Inter-Satellite Optical-Wireless Communication (IsOWC) Link <p>Free Space Optical links have gained significant importance in future generation space optical communication, particularly to establish a reliable optical inter-satellite optical wireless link between two satellite platforms. But the performance of Optical wireless link is degraded very much due to vibration imposed by various sources like; thermal storms, other heavy particles collisions. To address this problem a fiber bundle-based receiver approach other than conventional array of photodetector is required to mitigate the effects of pointing error. The result shows that the effect of pointing errors is reduced in the fiber bundle-based receiver system in compare to conventional receiver and this newly designed receiver system is able to cope up to 10 urad pointing error to achieve minimum Bit Error Rate (BER) and Q-factor for a data rate of 1 Gbps over a 200 km distance. It is practically implementable in Low Earth Orbit (LEO) satellite optical wireless communication link.</p> Prakash Chandra Jat Copyright (c) 2019 PRAKASH CHANDRA JAT 2019-04-17 2019-04-17 3 245 254 State of Internet of Things (IoT) Security Attacks, Vulnerabilities and Solutions <p>Internet of things (IoT) security is the technology area concerned with safeguarding networks and connected devices in the internet of things (IoT). IoT involves adding internet connectivity to a system of mechanical and digital machines, interrelated computing devices, animals, people and/or objects. Each "thing" is provided a unique identifier and the ability to automatically transfer data over a network. Allowing devices to connect to the internet opens them up to a number of serious vulnerabilities if they are not properly protected. In this paper, we discuss the different attacks and vulnerabilities which is classified by layer in the architechture. We also proposed solutions to mitigate and counter these attacks and vulnerabilities.</p> Rosslin John Robles Daisy Endencio-Robles Copyright (c) 2019 Rosslin John Robles, Daisy Endencio-Robles 2019-04-17 2019-04-17 3 255 263