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Journal receives papers in continuous flow and we will consider articles from a wide range of Information Technology disciplines encompassing the most basic research to the most innovative technologies. Please submit your papers electronically to our submission system at http://jatit.org/submit_paper.php in an MSWord, Pdf or compatible format so that they may be evaluated for publication in the upcoming issue. This journal uses a blinded review process; please remember to include all your personal identifiable information in the manuscript before submitting it for review, we will edit the necessary information at our side. Submissions to JATIT should be full research / review papers (properly indicated below main title).

Journal of Theoretical and Applied Information Technology
October 2019 | Vol. 97 No.19

Title:	EFFICIENT REQUIREMENT PRIORITIZATION BASED ON ENHANCED MULTI-VERSE OPTIMIZER
Author:	KHALID K. ADHIM , AMJAD HUDAIB , BASHAR AL-SHBOUL
Abstract:	Nowadays software development has more popular, and there are several methods have been introduced for achieving the software faster to meets the customer requirements. At the same time, the engineering requirements are one of the historic software engineering processes for identifying, analyzing, and validating requirements. The prioritization is most essential step for decision making and software product planning. Requirement prioritization is used for determining the requirements of a software product which should be included in the certain release and it is used in improving software product management. To achieve this Enhanced Multi-Verse Optimizer (EMVO) method is proposed. To achieve this more efficiently, MVO (Multi-Verse Optimizer) algorithm is utilized; it contains cosmology of three concepts such as the White hole, Blackhole, and Wormhole. The aim of this paper is to achieve the requirements prioritization in software with high efficient and high accuracy. The evaluation results proved the accuracy of the proposed method and are compared with various existing techniques.
Keywords:	Enhanced Multi Verse Optimizer, Engineering Process, Requirement Prioritization, Optimization, Metaheuristic Algorithms.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	MODULAR REPRESENTATIONS OF THE FpWn-SPECHT MODULES SK(,) AS LINEAR CODES
Author:	JINAN F. N. AL-JOBORY, EMAD B. AL-ZANGANA, FAEZ HASSAN ALI
Abstract:	We will find in this paper a generating matrix of the subspace representing the Specht module for each field K of characteristic 0, and for each field K  Fp  GF(p), where p  3, 5. We will also find the representation matrices of two kinds of transpositions and give the way to find the representation of any permutation w belongs to the Weyl group Wn of type Bn. The main aim of this paper is finding the linear codes of the subspaces which represent the Specht modules. We mention that some of the ideas of this work in this paper has been influenced by that of Adalbert Kerber and Axel Kohnert [11], even though that their paper is about the symmetric group and this paper is about the Weyl groups of type Bn.
Keywords:	Field of characteristic 0 (infinite field), Finite field Fp  GF(p), Weyl group Wn of type Bn, group ring FpWn, FpWn-module, FpWn-submodule, pair of partitions of a positive integer n, Specht polynomial, Specht module, -tableau, row standard -tableau, standard -tableau, vector space , subspace, generating matrix, linear code.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	A REVIEW OF CACHING STRATEGIES AND ITS CATEGORIZATIONS IN INFORMATION CENTRIC NETWORK
Author:	MOHAMMAD ALKHAZALEH , S. A. ALJUNID , NASEER SABRI
Abstract:	Information-centric networking (ICN) is one of the rising Internet paradigms proposed to beat the defect of the current host-centric Internet. ICN relies on the name to access contents rather than its original location, which provides substantial flexibility for users to obtain the contents. In-network caching is one of the most important features of the ICN because it has a significant role in improving network performance such as reducing server load, congestion, and delay caused by users. In-network caching is managed by a caching strategy that determines what, where and when to cache the content, to make content is available for requesters without going to servers. In recent years, caching strategies have attracted considerable interest from researchers, and they have proposed many caching strategies to manage the contents to enhance the performance of ICN. In this paper, the caching strategies and its characteristics are clearly described and discussed; furthermore, the caching strategies are categorized based on a set of common characteristics to be easy to understand.
Keywords:	Information-Centric Networking, Content Caching Strategies, In-network Caching, Caching Mechanisms.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	IMPROVEMENT OF DETECTING SMALL-SIZED TRAFFIC SIGNS BASED ON DEEP LEARNING
Author:	HOANH NGUYEN
Abstract:	Traffic sign detection plays an important role in intelligent transportation systems. This paper proposes a new method for detecting small-sized traffic signs based on deep learning. MobileNets architecture is adopted as the base network to provide a rich and discriminative hierarchy of feature representations. A deconvolutional module is then integrated into Faster R-CNN framework to bring additional context information which is helpful to improve the detection accuracy for small-sized traffic signs. Additionally, atrous convolution is used in the region proposal network to enlarge the receptive field of the synthetic feature map. The proposed framework is trained and evaluated on German traffic sign detection benchmark. The results show that the proposed approach obtained an accuracy comparable to other the state-of-the-art approaches in traffic sign detection.
Keywords:	Traffic Sign Detection, Convolutional Neural Network, Intelligent Transportation Systems, Object Detection, Deep Learning
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	GLOBAL DOMINAT SIFT FOR VIDEO INDEXING AND RETRIEVAL
Author:	KAMAL ELDAHSHAN , HESHAM FAROUK , AMR ABOZEID , M. HAMZA. EISSA
Abstract:	e massive volume of videos is highly demanding for produce an efficient and effective video indexing and retrieving frameworks. Extracting and representation of visual features plays a significant role in the video/image retrieval and computer vision. This paper proposes a new compact descriptor named Global Dominant Scale Invariant Feature Transform (GD-SIFT). The GD-SIFT requires fewer bits (16 bits) to represent each visual feature. Importantly, the proposed descriptor is vocabulary-free, training-free and suitable for online and real-time applications. Also, this paper proposes a new video indexing and retrieving framework based on the proposed GD-SIFT descriptor. The proposed framework is a content-based video indexing and retrieving, which helps to retrieve videos by text (e.g. Video name or metadata), image (video frame) or video clip. The experiments carried out on the standard Stanford I2V dataset. Our experiments demonstrated that, the GD-SIFT descriptor is more efficient (in terms of speed and storage) and achieved high accuracy (about 78%) with respect to the related works. Moreover, the results indicated that, the proposed descriptor is more robust to variations (e.g. Scale, rotation, etc.).
Keywords:	Video Indexing, Video Search, SIFT, Descriptor, Query-By-Image
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	BIO-INSPIRED A NOVEL CONTINUUM ROBOT ARM WITH VARIABLE BACKBONE DESIGN: MODELLING AND VALIDATION
Author:	AZAMAT YESHMUKHAMETOV, ZHOLDAS BURIBAYEV, YEDILKHAN AMIRGALIYEV, BEIBUT AMIRGALIYEV, KONSTANTIN LATUTA
Abstract:	Dramatic growth in the robotics industry demands robots with exceptional working capabilities such as working in a confined environment and with safety features. Likewise, high requirement needs to meet robots of the new generation. In such a case, bio-inspired continuum robots could be a good alternative solution for such needs. This research paper proposes a continuum robot arm inspired by an elephant trunk. The novelty of this research is proposed variable backbone hardness provided by coil compression springs, such as elephant trunk muscles. Thus, the proposed robot design allows working in a highly constrained environment, such as the agriculture sector or in the rescue operations, where the working environment is unstructured and severe which requires exceptional features from the robot. This research paper will cover the following topics; backbone design concept, geometry modelling, forward kinematic solution and the robot application as well.
Keywords:	Bio-Inspired Manipulator, Continuum Robot, Elephant Trunk, Kinematics, Design.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	CLASSIFICATION AT INCOMPLETE TRAINING INFORMATION: USAGE OF GROUP CLUSTERING TO IMPROVE PERFORMANCE
Author:	VLADIMIR BERIKOV, YEDILKHAN AMIRGALIYEV , LYAILYA CHERIKBAYEVA, DIDAR YEDILKHAN, BAKYT TULEGENOVA
Abstract:	In this paper, we propose a method for semi-supervised classification based on a group solution to cluster analysis in combination with Laplacian regularization of similarity graph. The averaged co-association matrix obtained with the cluster ensemble is considered as a similarity matrix in the regularization context. We use a low-rank representation of the matrix that allows us to speed-up computations and save memory in the solution of the derived system of linear equations. Both theoretical studies and numerical experiments on artificial data and hyperspectral imagery confirm the efficiency of the method.
Keywords:	Co-Association Matrix, Cluster Ensemble, Low-Rank Representation, Semi-Supervised Learning.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	AN OPTIMIZATION OF PERTURB AND OBSERVE MPPT ALGORITHM BASED ON FUZZY LOGIC FOR PV SYSTEM
Author:	O. LAGDANI, 1M. TRIHI, B. BOSSOUFI
Abstract:	Several approaches of the MPPT techniques have been used in distinct ways. In this work, a new adaptive P&O algorithm with variable step size has been studied and implemented using fuzzy logic controller. The proposed method is evaluated to optimize maximum power point tracking (MPPT) performance of photovoltaic (PV) systems and it has been simulated using MATLAB/Simulink environment and compared to the conventional P&O algorithm under different insolation.
Keywords:	Photovoltaic (PV), Maximum Power Point Tracking (MPPT), Perturb and Observe (P&O), Variable step-size, Modified Perturb and Observe (MP&O).
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	IMAGE SEGMENTATION BASED ON LOCAL SIMILARITY FACTOR FOR UNEVEN ILLUMINATED IMAGES
Author:	R.PRADEEP KUMAR REDDY , DR. C. NAGARAJU
Abstract:	In many of the applications the content of an uneven illuminated images needs to be improved or recognized. For the degraded source images the global thresholding algorithm fails to produce adequate results. Due to this reason many applications used local thresholding techniques to binarize each pixel based on gray scale information of its neighborhood pixels. This paper discusses about the design and development of local thresholding techniques using specific fuzzy inclusion and entropy measures with fixed ‘r’ and variable ‘r’. The noise influence on thresholding also tested using different noises like salt & pepper, Gaussian and speckle noises at different proportions. Different statistical parameters are evaluated to test the performance of the local thresholding algorithm with fixed ‘r’ and variable ‘r’. It is evidenced from the results that the local thresholding method with variable ‘r’ produced better results than compared to other methods.
Keywords:	Non-uniform Illumination, Global Thresholding, Local Thresholding, Fuzzy Inclusion, Entropy Measures.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	DIGITAL IMAGE STEGANOGRAPHY IN SPATIAL DOMAIN A COMPREHENSIVE REVIEW
Author:	MOHAMMED SABRI ABUALI, C.B.M. RASHIDI, MUATAZ H. SALIH, R. A. A. RAOF, SAFA SAAD HUSSEIN
Abstract:	Prevalent current day scenario with the predominant accelerated utilisation of the internet, is witnessing the increased interest in the method of transmitting concealed secret information (information hiding) via several variant techniques. One of the eminent and significant form of information hiding is Steganography. Hence, Steganography involves scientific techniques in concealing information inside the host object, which serves as the transporter of the hidden information, to be communicated in a secured undetected and safe form to another party. It engages multitudinous forms of host carriers that could be utilised in the form of texts, audio, visual images, protocols and DNA. Due to its frequent use on the internet, digital images are the favoured form of carrier host documents.. This study reviews the various latest related publications pertaining to image Steganography within the spatial domain, by assessing, accumulating, synthesising and analysing the difficulties, problems and issues faced in these different studies.. The objectives of this study is to execute a review as to render a summary of image Steganography, and to compare certain elements between the selected studies. Discussions will be made in accordance to the selection of pixel for the images, the capacity of the payload and the embedding algorithm, which will enable significant research issues for future researches. It is also aimed in the furtherance of securing a more robust Steganography technique.
Keywords:	Information Hiding , Image Steganography , Spatial Domain , Stego-Image , Different Types Of Steganography.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	MULTI-OBJECTIVE OPTIMAL REACTIVE POWER DISPATCH USING HYBRID TIME VARYING PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
Author:	SABHAN KANATA, SUWARNO, GIBSON HILMAN SIANIPAR, NUR ULFA MAULIDEVI
Abstract:	The hybrid time varying particle swarm optimization and genetic algorithm method (TVPSOGA) was introduced to solve multi-objective reactive power dispatch (MORPD) problems. MORPD as a non-linear multi-objective optimization problem that has the characteristics of non-convex, multi-constraint, and multi-variable which consists of a mixture of solutions that have discrete and continuous variables. The feasibility of the proposed method was tested on the IEEE 57-bus and IEEE 118-bus power systems. Comparison of simulation results shows the efficacy of the proposed optimization method compared to methods such as multi-objective enhanced particle swarm optimization (MOEPSO), multi-objective particle swarm optimization (MOPSO) and multi-objective ant lion optimization (MOALO) for the case of IEEE 57-bus power system. As for the case of the IEEE 118-bus power system, this method shows better efficacy compared to biogeography based optimization (BBO), the particle swarm optimization method with an aging leader and challengers (ALC-PSO), the enhanced gaussian bare-bones water cycle algorithm (NGBWCA) and PSO with a gravitational search algorithm (PSOGSA).
Keywords:	Time Varying Particle Swarm Optimization, Genetic Algorithm, Multi-Objective Reactive Power Dispatch, The Real Power Losses, The Total Voltage Deviation
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	STUDYING SYSTEMS OF OPEN SOURCE MESSAGING
Author:	ALEKSANDER BONDARENKO, KONSTANTIN ZAYTSEV
Abstract:	Modern large industrial and financial structures apply numerous various information systems (IS) which exchange data while communicating with each other. In order to implement such communication nowadays, specialized messaging systems are used or transport components comprised of one or several software products. This article compares four open source software products used in messaging systems: Apache Kafka, gRPC, ZeroMQ, and RabbitMQ, which satisfy criteria of Secure Sockets Layer/Transport Layer Security (SSL/TLS) encryption and possibility to operate directly with Java platform applications, that is, to provide Java API. In order to perform these studies, comparison environment was generated with four coordinates: supported communication type, productivity, reliability, and community support.
Keywords:	Open Source Systems, Apache Kafka, Grpc, Zeromq, Rabbitmq, Messaging, Publish&Subscribe, RPC, Streaming.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	IDENTIFICATION OF GUAVA FRUIT MATURITY USING DEEP LEARNING WITH CONVOLUTIONAL NEURAL NETWORK METHOD
Author:	P.A. SUNARYA, A.B. MUTIARA, R. REFIANTI, M. HUDA
Abstract:	Guava is one of the most popular agricultural commodities. Guava is not only rich in vitamin C but also contains several types of minerals that can counteract various types of degenerative diseases, and maintain body fitness. One type of guava is Red Guava Getas. Identifying the maturity of guava fruit by farmers is still done manually by doing direct visual observations on the fruit to be classified. Weaknesses in performing visual observations are directly influenced by human consistency in the identification process, so that in certain conditions will occur inaccurately. Therefore, a technology is needed to use computer assistance to help identify the results of the examination and conclude the identification results more accurately. This application uses deep learning with the Convolutional Neural Network (CNN) method with LeNet architecture. Making this application uses the Python programming language and Keras as a back-end Tensorflow. From the tests carried out, it is obtained a percentage of 50% for 100 training data and 10 epochs, a percentage of 85% for 100 training data and 20 epochs, a percentage of 92% for 140 training data and 10 epochs, and the last percentage of 100% for 140 training data and 20 epochs.
Keywords:	Convolutional Neural Network, Deep Learning, Image Classification, LeNet, Guava Fruit, Python
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	DIAGNOSIS OF ESCHERICHIA COLI BACTERIA PATIENT BY DATA MINING
Author:	AMIR RAJAEI , VAHID HEYDARI
Abstract:	The number and size of medical databases are rapidly growing and thus, developed models of data mining technique can help physicians to make effective decisions. The present paper is aimed at reporting a research project to compare data mining algorithms according to their precision, characteristics and speed in order to select the most accurate model in diagnosis of E.coli activities in urine specimens. In this paper, the practical application of data mining in diagnosing the activities of bacteria using the recorded data in the database which helps physicians to provide necessary information and knowledge for a better decision-making. Providing intelligent diagnosis system for the patient identification , in addition improving the rate and accuracy of detection are the subsequent paper aims. Activities of the bacteria in patients are divided into three groups: normal, active and semi-active. We have applied Fuzzy C Mean clustering and Differential Evolution on the collected database. The obtained results indicated that FCM algorithm was the same as DE algorithm in terms of precision, but it had better function than DE algorithm in terms of speed.
Keywords:	Escherichia Coli (E.coli), Data Mining, Differential Evolution Algorithm (DE), Fuzzy C-Means Algorithm, Healthcare, Diagnosis.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	AN EVALUATION OF THE USAGE OF ASPECT ORIENTATION AND THE GAP BETWEEN ACADEMIC RESEARCH AND INDUSTRY NEEDS
Author:	AWS A. MAGABLEH, ANAS M. R. ALSOBEH AND AHMAD F. KLAIB
Abstract:	In industrialized nations there is a very strong relationship between university research centers and industry players, which supports the exchange of knowledge and the development of new technologies, particularly in the software engineering domain. This paper analyzes the extent of cooperation between university and industry specifically in relation to research and utilization of aspect orientation (AO). It also assesses whether AO is still an area of interest for software engineering researchers and ICT industry professionals. The study achieves these aims by gathering and analyzing the opinions of 52 researchers and 66industry professionals by means of domain-specific questionnaire surveys. Out of an original sample size of 196, 118 participated in this study, representing a 60.2% response rate. The originality and value of this study lies in the fact that it is the first to examine AO from two different perspectives (research and industry).The findings reveal the level of correlation between the behaviors of researchers and industry professionals toward AO. The research outcomes indicate that while there is an acceptable level of cooperation and synchronization between research institutes and ICT firms, it is less than ideal. The results also show that there are significant differences between the respondents’ points of view by experience, gender and/or job role/research interest. In light of these findings, some suggestions are made to improve the synergy between research and industry. Generally, both parties need to have more trust in AO in order to employ it in all stages of the software development life cycle. Thus, more workshops, seminars and training sessions need to be conducted to increase awareness of the capabilities of AO to encourage is utilization in both research and industry.
Keywords:	Aspect Orientation, AO, Software Engineering, ICT Industry, Empirical Study, University Research Center
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	THE IMPACT OF CHARACTERISTICS OF ONLINE FAN COMMUNITY AND FANS ON LOYALTY TO STARS AND THE COMMUNITIES
Author:	JONGHUN KIM, MINCHEOL KANG, KIMIN KIM
Abstract:	This study seeks to enhance understanding of online fan communities. We examined how online fan communities and their members affect loyalty to stars and the communities. We also examined how social and psychological factors such as social presence and identification mediate those impacts. By surveying online fans of Korean Wave Stars, we found that, among the online fan community characteristics, social connectedness, self-disclosure and deep profiling affect social presence, and, among the fan characteristics, self-focused attention and empathy affect social presence. We also found that social presence affects online fan community identification and star identification, which in turn affect online fan community loyalty and star loyalty. Moreover, star identification is found to transit to online fan community identification while star loyalty transited to online fan community loyalty. These findings provide significant theoretical and practical implications for the entertainment and media industries by adding to scant research on online fan communities.
Keywords:	Online Fan Community, Korean Wave Stars, Loyalty, Social Presence, Identification
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	CLOUD COMPUTING BASED ATTACKS AND COUNTERMEASURES: A SURVEY
Author:	LAMYAA S. ALSALEEM , SARAH A. ALQAHTANI , SARAH F. ALHARBI , RACHID AGROUBA
Abstract:	Nowadays, cloud computing and its related security issues are one of the most debated topics in today’s research field. Cloud computing raises the efficiency and proposes many advantages to users, but at the same time it is still a new technology that needs a lot of enhancement in term of security. This survey presents cloud service delivery models, deployments and characteristics. Furthermore, it gives a detailed explanation on known attacks that threaten the cloud core components and how it might occur in cloud systems and discusses possible solutions to mitigate these attacks. Lastly, it summarizes the attacks and compares between the discussed solutions.
Keywords:	Cloud Computing, Attacks, Security, Network, Virtualization, Storage, Countermeasure.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	AN ALGORITHM TO ESTIMATE OBSTACLE DISTANCE FOR ASSISTIVE SYSTEM OF VISUALLY IMPAIRED
Author:	POOJA GUNDEWAR, SANIKA PATANKAR, HEMANT ABHYANKAR, JAYANT KULKARNI
Abstract:	For safe navigation of visually impaired, an assistive system that can estimate the distance between visually impaired and obstacle and can intimate the user is needed. Estimation of the distance between an obstacle and visually impaired (user) is challenging due to artifacts in the real environment such as variation in speed of obstacle and non-uniform illumination conditions. This paper presents a novel algorithm to estimate the distance of an obstacle from the user using Speeded Up Robust Features (SURF). Instead of traditional distance measurement sensors, SURF features are used for distance measurement of an obstacle from visually impaired. The input video frames are preprocessed, and correction for non-uniform illumination is applied. The dominant points in each input video frame are located. The correspondence between the dominant points in successive frames is derived. For a typical camera, the average magnitude of SURF features is a linear function of a distance between the user and the obstacle. This function is used to estimate the distance between obstacle and user. The proposed algorithm is tested on videos recorded in a dynamic environment. For videos captured with Microsoft webcam, an average % error for distance estimation is 1.31%, and for speed, estimation is 4.18%. For videos captured with an Iball camera, the average % error for distance estimation is 2.134%, and for speed, estimation is 0.399%. The performance of the proposed algorithm is compared with existing techniques on the basis of an error in distance estimation, standard deviation, space complexity, and time complexity.
Keywords:	Visually Impaired, Assistive System, Distance Estimation, Speeded Up Robust Features, Feature Matching.
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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Title:	THE RELATIONSHIP BETWEEN SELF-CONCEPTS AND FLAMING BEHAVIOR: POLARITY OF THE ONLINE COMMENTS
Author:	JUNGYONG LEE, CHANGHYUN JIN
Abstract:	This study aims to explore how the sub-factors of self-concepts such as self-identity and self-monitoring are associated with flaming behavior, demonstrate whether polarity of online comments plays the moderating variable and show how flaming behavior affects corporate brands and product purchases. The study was conducted in groups of approximately 1060 subjects. Self-monitoring, self-identity and self-control had a strongly associated with flaming behavior. Therefore, when writing online comments on the internet, self-monitoring, self-identity and self-control seem to play an important role when explain internet users’ flaming behavior in cyberspace. Users with strong self-concepts tended to respond sensitively with comments when looking at online comments than did users with lower self-concepts. In spite of the fact that flaming behavior has been the chief obstacle to internet culture; however, it is true that there has still been a lack of academic interest in flaming. Therefore, this study is significant in arousing academic interest in flaming.
Keywords:	Flaming Behavior, Online Comments, Self-Concepts, Purchase Intention
Source:	Journal of Theoretical and Applied Information Technology 15^th October 2019 -- Vol. 97. No. 19 -- 2019
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