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31,456 Article Results

Multi-level cyber security system for VANET

10.11591/ijeecs.v19.i2.pp940-948
Muntadher Naeem Yasir , Muayad Sadik Croock
Recently, the cyber security of vehicular ad-hoc network (VANET) including two practicable: car-to-car and car-to-infrastructure has been considered due to importance. It has become possible to keep pace with the development in the world, where the safety of people is a priority in the development of technology in general and in particular in the field of VANET. In this paper, a cyber security system for VANET has been proposed to tackle the DOS attacks. The proposed system includes three security levels. Firstly, the registeration level that ask vehicles to be registered in the system, in which the network exclude the unrigestered ones. Secondly, the authentication level that checks the vehicles before joining the network. This is done by applying a proposed algorithm that considers the hash function and factory number. Thirdly, the proposed system ables to detect the DOS attack by any involved vehicle using the monitoring algorithm that allocate such vehicle to be excluded from the network. The obtained results show the efficient performance of the proposed system in managing the security of the VANET network. The multi-level system increases the security of the network, in which the attacks can be eliminated.
Volume: 19
Issue: 2
Page: 940-948
Publish at: 2020-08-01

Text classification based on gated recurrent unit combines with support vector machine

10.11591/ijece.v10i4.pp3734-3742
Muhammad Zulqarnain , Rozaida Ghazali , Yana Mazwin Mohmad Hassim , Muhammad Rehan
As the amount of unstructured text data that humanity produce largely and a lot of texts are grows on the Internet, so the one of the intelligent technique is require processing it and extracting different types of knowledge from it. Gated recurrent unit (GRU) and support vector machine (SVM) have been successfully used to Natural Language Processing (NLP) systems with comparative, remarkable results. GRU networks perform well in sequential learning tasks and overcome the issues of “vanishing and explosion of gradients in standard recurrent neural networks (RNNs) when captureing long-term dependencies. In this paper, we proposed a text classification model based on improved approaches to this norm by presenting a linear support vector machine (SVM) as the replacement of Softmax in the final output layer of a GRU model. Furthermore, the cross-entropy function shall be replaced with a margin-based function. Empirical results present that the proposed GRU-SVM model achieved comparatively better results than the baseline approaches BLSTM-C, DABN.
Volume: 10
Issue: 4
Page: 3734-3742
Publish at: 2020-08-01

Exploration of the best performance method of emotions classification for arabic tweets

10.11591/ijeecs.v19.i2.pp1010-1020
Mohammed Abdullah Al-Hagery , Manar Abdullah Al-assaf , Faiza Mohammad Al-kharboush
Arab users of social media have significantly increased, thus increasing the opportunities for extracting knowledge from various areas of life such as trade, education, psychological health services, etc. The active Arab presence on Twitter motivates many researchers to classify and analysis Arabic tweets from numerous aspects. This study aimed to explore the best performance scenarios in the classification of emotions conveyed through Arabic tweets. Hence, various experiments were conducted to investigate the effects of feature extraction techniques and the N-gram model on the performance of three supervised machine learning algorithms, which are support vector machine (SVM), naïve bayes (NB), and logistic regression (LR). The general method of the experiments was based on five steps; data collection, preprocessing, feature extraction, emotion classification, and evaluation of results. To implement these experiments, a real-world Twitter dataset was gathered. The best result achieved by the SVM classifier when using a bag of words (BoW) weighting schema (with unigrams and bigrams or with unigrams, bigrams, and trigrams) exceeded the best performance results of other algorithms.
Volume: 19
Issue: 2
Page: 1010-1020
Publish at: 2020-08-01

A new quasi-newton equation on the gradient methods for optimization minimization problem

10.11591/ijeecs.v19.i2.pp737-744
Basim Abbas Hassan , Ghada M. Al-Naemi
The quasi-Newton equation is the very foundation of an assortment of the quasi-Newton methods for optimization minimization problem. In this paper, we deriving a new quasi-Newton equation based on the second-order Taylor’s series expansion. The global convergence is established underneath suitable conditions and numerical results are reported to show that the given algorithm is more effective than those of the normal BFGS method.
Volume: 19
Issue: 2
Page: 737-744
Publish at: 2020-08-01

Value preferences and requirements of the students attending the regional boarding secondary schools

10.11591/ijere.v9i3.20539
Sibel Yazıcı , Nuray Kurtdede Fidan
The aim of the study was to reveal the preferences and requirements of the students attending the Regional Boarding Secondary Schools (YBO) concerning the values contain in the educational program of the social studies course. The study was designed within the framework of phenomenology which is among the qualitative research methods. The participants of the study are 79 eight grade students attending a regional boarding secondary school in the Turkey. The data of the study are collected through a survey questionnaire with two parts which contains open-ended items. The data were analysed using the descriptive and content analyses. The findings of the study show that the participants do not differ based on gender and the socio-economic background of their families. The frequently preferred values by the participants are found to be attaching importance to the family unity, honesty, sympathy and patriotism. Another finding is that the participants do not provide a clear justification for each of the values they preferred. This suggests that it is difficult to establish a justification for the value. However, requirements value justifications are analyzed, it is seen that students they express the definition of value, its importance and the expectations of having this specific value.
Volume: 9
Issue: 3
Page: 635-643
Publish at: 2020-08-01

Deep-learning based single object tracker for night surveillance

10.11591/ijece.v10i4.pp3576-3587
Zulaikha Kadim , Mohd Asyraf Zulkifley , Nabilah Hamzah
Tracking an object in night surveillance video is a challenging task as the quality of the captured image is normally poor with low brightness and contrast. The task becomes harder for a small object as fewer features are apparent. Traditional approach is based on improving the image quality before tracking is performed. In this paper, a single object tracking algorithm based on deep-learning approach is proposed to exploit its outstanding capability of modelling object’s appearance even during night. The algorithm uses pre-trained convolutional neural networks coupled with fully connected layers, which are trained online during the tracking so that it is able to cater for appearance changes as the object moves around. Various learning hyperparameters for the optimization function, learning rate and ratio of training samples are tested to find optimal setup for tracking in night scenarios. Fourteen night surveillance videos are collected for validation purpose, which are captured from three viewing angles. The results show that the best accuracy is obtained by using Adam optimizer with learning rate of 0.00075 and sampling ratio of 2:1 for positive and negative training data. This algorithm is suitable to be implemented in higher level surveillance applications such as abnormal behavioral recognition.
Volume: 10
Issue: 4
Page: 3576-3587
Publish at: 2020-08-01

Enhancenig OLSR routing protocol using K-means clustering in MANETs

10.11591/ijece.v10i4.pp3715-3724
Y. Hamzaoui , M. Amnai , A. Choukri , Y. Fakhri
The design of robust routing protocol schemes for MANETs is quite complex, due to the characteristics and structural constraints of this network. A numerous variety of protocol schemes have been proposed in literature. Most of them are based on traditional method of routing, which doesn’t guarantee basic levels of Qos, when the network becomes larger, denser and dynamic. To solve this problem we use one of the most popular methods named clustering. In this work we try to improve the Qos in MANETs. We propose an algorithm of clustering based in the new mobility metric and K-Means method to distribute the nodes into several clusters; it is implemented to standard OLSR protocol giving birth a new protocol named OLSR Kmeans-SDE. The simulations showed that the results obtained by OLSR Kmeans-SDE exceed those obtained by standard OLSR Kmeans and OLSR Kmed+ in terms of, traffic Control, delay and packet delivery ratio.
Volume: 10
Issue: 4
Page: 3715-3724
Publish at: 2020-08-01

Phenomenological model of information operation in social networking services

10.11591/ijeecs.v19.i2.pp1078-1087
Kateryna Molodetska , Yuriy Tymonin , Oleksandr Markovets , Andrii Melnychyn
In modern conditions, social networking services have become the users’ leading channel of communication, which are called actors. Therefore, social networking services are used by intruders to gain benefits in the information space of virtual communities for further influence on political and social processes in the state. In the article the phenomenological model of information operation in social networking services is developed. The model allows to take into account the processes of development of social networking services through the formation of new relationships between actors and the formation of virtual communities. At the same time, behind the model are the processes of degradation of social networking services that are associated with the dissipation of content. The developed model is used for experimental research of real information operation in social networking services. The obtained results will increase the efficiency and effectiveness of counteracting the threats to information security of the state in social networking services by the relevant departments.
Volume: 19
Issue: 2
Page: 1078-1087
Publish at: 2020-08-01

Performance enhancement of DC/DC converters for solar powered EV

10.11591/ijece.v10i4.pp3423-3430
Nagaraj S. , Ranihemamalini R. , Rajaji L.
The paper initially presents the essential drive arrangement required for electric vehicle. It requests high power bidirectional stream ability, with wide info voltage range, and yield voltage of vitality stockpiling gadgets, for example, super capacitors or batteries shift with the adjustment in stack. At that point the tenacity and outline of previously mentioned converter is proposed in this paper. The converter which relates a half extension topology, has high power stream ability and least gadget focuses on that can appropriately interface a super capacitor with the drive prepare of a crossover electric vehicle. Besides, by contrasting the fundamental qualities and applications with some ordinary bidirectional DC/DC converter, the proposed converter has low gadget rating and can be controlled by obligation cycle and stage move. Finally, the most essential attributes of this converter is that it utilizes the transformer spillage inductance as the essential vitality exchange component and control parameters, Simulation waveforms in light of MATLAB recreation are given to exhibit the integrity of this novel topology, and this converter is additionally reasonable for high power application, specifically to control the charge-release of super capacitors or batteries that can be utilized as a part of cross breed solar based electric vehicle.
Volume: 10
Issue: 4
Page: 3423-3430
Publish at: 2020-08-01

Real power loss reduction by tundra wolf algorithm

10.11591/ijict.v9i2.pp100-104
Kanagasabai Lenin
In this work Tundra wolf algorithm (TWA) is proposed to solve the optimal reactive power problem. In the projected Tundra wolf algorithm (TWA) in order to avoid the searching agents from trapping into the local optimal the converging towards global optimal is divided based on two different conditions. In the proposed Tundra wolf algorithm (TWA) omega tundra wolf has been taken as searching agent as an alternative of indebted to pursue the first three most excellent candidates. Escalating the searching agents numbers will perk up the exploration capability of the Tundra wolf wolves in an extensive range.  Proposed Tundra wolf algorithm (TWA) has been tested in standard IEEE 14, 30 bus test systems and simulation results show the proposed algorithm reduced the real power loss effectively.
Volume: 9
Issue: 2
Page: 100-104
Publish at: 2020-08-01

Social and emotional learning in education and care policy in Croatia

10.11591/ijere.v9i3.20495
Maja Ljubetic , Toni Maglica
Worldwide practises and then scientific research is showing that social-emotional learning represents a highly promising approach for positive development and adjustment, improvement of academic success in children and even prevention of behavioural problems. But despite these findings, there is no systematic approach in the implementation of the social-emotional learning in Croatia, and the practice of it is not yet structured and comprehensive and occurs rather occasionally and spontaneously. This paper is trying to ascertain is there a formal and legal platform for implementing social-emotional learning in the crucial documents that regulate educational and care practises in Croatia. The analysis of the documents was conducted according to the criterium of key social-emotional competencies and the associated social-emotional skills.
Volume: 9
Issue: 3
Page: 650-659
Publish at: 2020-08-01

Enhanced routing for secured ad-hoc network

10.11591/ijeecs.v19.i2.pp949-956
U Kumaran , A Ramachandran , J Jegan , E.K. Subramanian
A self-configured network forming an arbitrary topology of mobile routers through wireless connection is commonly referred as MANET (mobile ad-hoc network).  Random movement of routers allows the network to organize arbitrarily hence rapid unpredictable changes may occur in the topology of the wireless network. When there is no possibility of setting up permanent networks, MANETs are set up for carrying out the operations temporarily. As there is no fixed frame for this system, usage of available resources for reliable communication is a great challenge for MANETs. The nodes participating in packet routing in ad-hoc networks faces security issues such as maintaining the confidentiality of the packets, integration, availability of the network to meet the traffic, requirement of authentication for reliable data communication etc. Dropping of packets maliciously in an attack is known as black hole attack.An attempt is made in this paper to detect dynamically using the security of cross layer called as honeypot and classify the mechanisms to understand the strengths & threats of the protocols used for routing to suggest a concrete solution for the problems related to the mobile ad-hoc networks. The methodology of honeypot detects and isolates the attacks of the black hole. The results prove better delivery of packets with decreased load of the network.
Volume: 19
Issue: 2
Page: 949-956
Publish at: 2020-08-01

A quick study on SRL profiles of online learning participants during the anticipation of the spread of COVID-19

10.11591/ijere.v9i3.20642
Dwi Sulisworo , Nur Fatimah , Septi Shinta Sunaryati , Sanidi Sanidi
The spread of the COVID-19 coronavirus occurs in all countries. This pandemic incident has been taken seriously by various sectors including in the world of education. This research is a quantitative descriptive study to explain the Self-Regulated Learning (SRL) profile of Indonesian students in online learning which is carried out in COVID-19 emergencies. The research commenced three days after the establishment of the WHO COVID-19 pandemic. The respondents were taken by accident sampling at several schools implementing online learning after the designation of this mode by the Indonesian Ministry of Education and Culture on March 15, 2020. The schools comprised general high schools and vocational schools. The data were collected via Google Form filled out by 10th to 12th-grade students. The instrument used was a questionnaire with a scale of 1 to 5 (from absolutely disagree to absolutely agree) consisting of planning, monitoring, controlling, and reflecting aspects. There were two analytical techniques used i.e., descriptive statistics and ANOVA. The results of this study indicate that students in Indonesia still need assistance and mentoring from teachers to improve SRL. Several mentoring strategies can be applied to manage active learning. The teachers should explicitly include the process of mentoring, strengthening the students’ SRL. Teachers need to be aware that online learning is not only to master certain subject matters but also to strengthen SRL.
Volume: 9
Issue: 3
Page: 723-730
Publish at: 2020-08-01

Power system fault identification and localization using multiple linear regression of principal component distance indices

10.11591/ijape.v9.i2.pp113-126
Alok Mukherjee , Palash Kr. Kundu , Arabinda Das
This paper is focused on the application of principal component analysis (PCA) to classify and localize power system faults in a three phase, radial, long transmission line using receiving end line currents taken almost at the midpoint of the line length. The PCA scores are analyzed to compute principal component distance index (PCDI) which is further analyzed using a ratio based analysis to develop ratio index matrix (R) and ratio error matrix (RE) and ratio error index (REI) which are used to develop a fault classifier, which produces a 100% correct prediction. The later part of the paper deals with the development of a fault localizer using the same PCDI corresponding to six intermediate training locations, which are analyzed with tool like Multiple Linear Regression (MLR) in order to predict the fault location with significantly high accuracy of only 87 m for a 150 km long radial transmission line.
Volume: 9
Issue: 2
Page: 113-126
Publish at: 2020-08-01

Electrochemical properties of kenaf-derived activated carbon electrodes under different activation time durations for supercapacitor application

10.11591/ijeecs.v19.i2.pp1105-1112
Muhammad Nizam Abdul Razak , Zulkarnain Ahmad Noorden , Farid Nasir Ani , Zulkurnain Abdul Malek , Jasrul Jamani Jamian , Nouruddeen Bashir
The electrochemical properties of supercapacitors with kenaf-derived activated carbon electrodes under different activation time durations were evaluated. The study aims to determine the optimum activation time required that contributes to highest supercapacitor’s perfomance. Kenaf fibre was firstly carbonized at 400 °C to remove its water content and any volatile substances. The resulted kenaf-derived carbon was then impregnated in potassium hydroxide (KOH) with 4:1 impregnation ratio and left overnight. After the impregnation process, the carbon sample was activated at 600 °C with different heating time durations of 1, 2, 3 and 4 hours and named as A600-1, A600-2, A600-3 and A600-4, repectively. Four supercapacitors with the kenaf-derived activated carbon samples as the electrodes were fabricated based on two-electrode symmetrical test cell system. Specific capacitances of 108, 189, 242, and 126 F/g for supercapacitors with activated carbon A600-1, A600-2, A600-3 and A600-4 electrodes, respectively were achieved. These were much higher than previously reported values of only up to 37 F/g. The finding suggests that an inexpensive fibrous carbon material derived from kenaf by a facile pyrolysis process may be a remarkable choice to construct high performance supercapacitor.
Volume: 19
Issue: 2
Page: 1105-1112
Publish at: 2020-08-01
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