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Computer Science and Information Technologies (CSIT)
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csit@aptikom-journal.id
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APTIKOM Journal on Computer Science and Information Technologies (CSIT)
ISSN : 25282417     EISSN : 25282425     DOI : 10.34306
APTIKOM Journal on Computer Science and Information Technologies is a peer-reviewed international journal that publish original research article, review papers, short communications that will have an immediate impact on the ongoing research in all areas of Computer Science, Informatics, Electronics Engineering, Communication Network and Information Technologies. The journal is published four-monthly (March, July and November) by the Indonesian Association of Higher Education Institutions in Computer Science and Information Technology (APTIKOM).
Articles 50 Documents
SURVEY BASED CLASSIFICATION OF BUG TRIAGE APPROACHES Yadav, Asmita; Singh, Sandeep Kumar
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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Abstract

This paper presents a comprehensive survey of bug triaging approaches in three classes namely machine learning based, meta-data based and profile based. All approaches under three categories are critically compared and some potential future directions and challenges are reported. Findings from the survey show that there is a lot of scope to work in cold-start problem, developer- profiling, load balancing, and reopened bug analysis.
WIRELESS SENSOR NETWORK FOR REAL-TIME FLOOD MONITORING BASED ON 6LOWPAN COMMUNICATION STANDARD Nuhu, B Kontagora; Arulogun, O. T.; Adeyanju, Ibrahim Adepoju; M., Abdullahi I.
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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Riverine flood is a major disaster faced by most countries and has significant adverse effect on long term economic growth of affected regions and their environments. Several systems have previously employed different technologies to monitor riverine flood but are expensive with low accuracy and consumes high amount of energy. In this paper, we proposed an energy efficient and accurate flood monitoring system. The system leverages on Internet Protocol Version 6 over Low Power Wireless Personal Area Network (6loWPAN) technology to construct a Wireless Sensor Network (WSN) comprising of two XM1000 motes and a rule-base water level monitoring application. The motes were configured using NesC programming for flood monitoring with Basestation and water level sensing applications. The water level sensing mote samples and transmits real-time water level information to the Basestation mote which interfaces with a rule-based water level monitoring application. The application compares current water level with a predetermined threat level and alerts relevant agencies when flood is imminent via an email. The results obtained from the emulation of the developed system showed that, it achieved an accuracy of 95.3% in water level monitoring with a Mean Squared Error of 5.1. The power consumed in transmitting a packet of 2 bytes payload plus other overhead was 0.4?J and 0.0396mJ with and without 6loWPAN configuration respectively.
EVALUATING BLIND IMAGE QUALITY USING RBF NEURAL NETWORK Soliga, Abi; Jasil, Godlin
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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Blind Image Quality Assessment (BIQA) methods are the most part feeling mindful. The BIQA method learns regression models from preparing images with human subjective scores to predict the perceptual nature of test images. The general quality of image and the nature of every image patches are measured by normal pooling. By coordinating the components of normal picture measurements got from different signs, we take a multivariate Gaussian model of picture patches from an accumulation of unblemished regular pictures. The proposed radial bias function neural network method is used to evaluate the quality of images and this method represents the structure of picture distortions with flexibility.
PERFORMANCE ANALYSIS OF REED-SOLOMON CODES CONCATENATED WITH CONVOLUTIONAL CODES OVER AWGN CHANNEL Mergu, Kattaswamy
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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With rapid growth in today?s technology, digital communication is playing a major role to provide hostile environment to meet various applications. In this communication, Coding plays a prominent role to contribute error free transmission through channel coding which improves capacity of a channel by adding some redundant bit to the original information. One way to provide a better performance of the communication system is by concatenating different types of channel coding techniques. The concatenation can be done either in parallel or serial. The primary aim of this paper is to concatenate the Reed-Solomon codes with Convolutional codes in series, which provides better results comparing with single coding techniques. The performance of the concatenation of Reed-Solomon codes with Convolutional codes can be evaluated by finding bit error rate with various values of signal-to-noise ratio over AWGN channel. The analytical result has been obtained by using MATLAB/OCTAVE.
FUZZY-ANT COLONY BASED ROUTING ON ROAD NETWORKS Saravanan, S.; Jayanthiladevi, A.; Geetha, M.
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 1 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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Route selection is essential in everyday life. We have several algorithms for detecting efficient route on Large Road Networks. This paper introduces the hierarchical community, is presented. It splits large road networks into hierarchical structure. It introduces a multi parameter route selection system which employs Fuzzy Logic (FL) and ant?s behavior in nature is applied to the dynamic routing. The important rates of parameters such as path length and traffic are adjustable by the user. The purposes of the new hierarchical routing algorithm significantly reduce the search space. We develop a community-based hierarchical graph model that supports Dynamic, efficient route computation on large road networks.
HOLE DETECTION AND HEALING IN HYBRID WIRELESS SENSOR NETWORK Kalwaghe, Samidha N; Dusane, Atul Vasudev
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 2 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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The emerging technology of wireless sensor network (WSN) is expected to provide a broad range of applications, such as battlefield surveillance, environmental monitoring, smart spaces and so on. The coverage problem is a fundamental issue in WSN, which may cause due to low residual energy of nodes or poor installment. But in order to get full coverage of sensing area Coverage problem must be avoided. If the problem is unavoidable the coverage hole must be healed. Current hole healing algorithms uses complicated hole detection strategies like TENT rule. This project seeks to address the problem of hole detection and healing in mobile WSNs by deploying mobile sensors in the network, which is called hybrid sensor network. An enhanced hole detection and healing method (MHEAL) is proposed. MHEAL is a distributed and localized algorithm that operates in two distinct phases. First, is Distributed Hole Detection (DHD) proposed to identify the boundary nodes and discover holes. Second, is hole healing which uses a virtual forces based hole healing approach where only the nodes located at an appropriate distance from the hole and the nodes having maximum energy will be involved in the healing process. Unlike existing algorithms, proposed algorithm uses QURD based node detection and energy efficient Hole healing and thus solves the problem of hole with 100% coverage, minimum node movements and minimum node distance travelled thus giving a cost efficient solution.
BNIMS: BLOCK-BASED NON-ITERATIVE MEAN-SHIFT SEGMENTATION ALGORITHM FOR MEDICAL IMAGES Naik, P. Pedda Sadhu; Gopal, T. Venu
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 2 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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This paper proposed a novel Block based Mean Shift Image Segmentation Algorithm to significantly reduce the computation and improve the segmentation accuracy for high resolution Medical Image. One of the challenging tasks in the image analysis and computer vision area is to correctly classify the pixels as there are no crisp borders among entities in an image. In this proposed methodology, it is observed that the computational complexity of the procedure is diminished by combining the pixels of an image of size MXN into non overlapping image blocks of size 3x3 by eliminating the iterative way of the mean shift procedure. This proposed algorithm shrinks the size of the image by one third of its original image for the computational purpose and then equalizes the number of computations for each new image pixel by constructing links between pixels using their first mean-shift vectors without any iteration process. The accurateness and effectiveness of the proposed methodology is matched with the existing Iterative Mean Shift Algorithm by accomplishing the empherical experiments on the Medical Images (Pathologies Buccales and Eye Retina) composed along with the similarity measures.
ACOUSTIC ECHO CANCELLATION USING COMPUTATIONALLY EFFICIENT ADAPTIVE ALGORITHM TECHNIQUES Shaik, Mastan Sharif; Prasad, K. Satya; Shaik, Rafi Ahamed; Rao, D. Venkata
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 2 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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Several sign based LMS adaptive filters, which are computationally free having multiplier free weight update loops, are proposed for acoustic echo cancellation. The adaptive filters essentially minimizes the mean- squared error between a primary input, which is the echo, and a reference input, which is either echo that is correlated in some way with the echo in the primary input. The results show that the performance of the signed regressor. LMS algorithm is superior than conventional LMS algorithm, the performance of signed LMS and sign- sign LMS based realizations are comparable to that of the LMS based filtering techniques in terms of Average Attenuation and computational complexity.
CONSTRUCTING RELATIONSHIP BETWEEN SOFTWARE METRICS AND CODE REUSABILITY IN OBJECT ORIENTED DESIGN M., Manoj H.; N., Nandakumar A.
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 2 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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The role of design pattern in the form of software metric and internal code architecture for object-oriented design plays a critical role in software en-gineering in terms of production cost efficiency. This paper discusses about code reusability that is a frequently exercised cost saving methodology in IT produc-tion. After reviewing existing literatures towards study on software metrics, we found that very few studies are witnessed to incline towards code reusability. Hence, we developed a simple analytical model that establishes relationship between the design components of standard software metric and code reusability using case studies of three software projects (Customer Relationship Management project, Supply Chain Management project, and Enterprise Relationship Management project). We also testify our proposal using stochastic based Markov model to find that proposed system can extract significant information of maximized values of code reusability with increasing level of uncertainties of software project methodologies.
PATH-LOSS PREDICTION FOR UHF/VHF SIGNAL PROPAGATION IN EDO STATE: NEURAL NETWORK APPROACH O., Ogbeide K.; E. J, Eko Mwenrenren
APTIKOM Journal on Computer Science and Information Technologies Vol 1 No 2 (2016): APTIKOM Journal on Computer Science and Information Technologies (CSIT)
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The aim of this paper is to present and evaluate artificial neural network model used for path loss prediction of signal propagation in the VHF/UHF spectrum in Edo state.Measurement data obtained from three television broadcasting stations in Edo state, operating at 189.25MHz, 479.25MHz, and 743.25MHz, is used to train and evaluate the artificial neural network. A two layer neural network with one hidden and one output layer is evaluated regarding prediction accuracy and generalization properties. The path loss prediction results obtained by using the artificial neural network model are evaluated against the Hata and Walfisch-Ikegami empirical path loss models .Result analysis shows that the artificial neural network performs well as regards to prediction accuracy and generalization ability. The ANN performed better across all performance measures in comparison to the Hata and Walfisch-Ikegami and Line of Sight models in estimating path loss in vhf/uhf spectrum in Edo state.