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Simple solution for low cost bandwidth management

10.12928/telkomnika.v19i4.17109
I Made; Udayana University Sukarsa , I Nyoman; Udayana University Piarsa , I Gede Bagus; Udayana University Premana Putra
Organizations in this era can't be separated from information technology, especially in communication and information sharing. The existence of information technology, especially computer networks, greatly facilitates agencies in terms of communication. Organizations that have used computer networks generally don’t have tools to handle security and bandwidth management issues in large numbers, resulting in wasteful use of bandwidth for unproductive purposes, such as accessing video streaming. The fact is professional tools to overcome the problem of security and bandwidth management issues are already in the market, but have hundreds of millions of priced. The high price of professional devices gave an opportunity to develop a bandwidth management system based on the integration of the remote authentication dial in user service (RADIUS) server and Mikrotik RouterBoard, at a lower cost. RADIUS server was chosen as a service for network security, because it supports the legal authentication for users via AAA protocol. The RADIUS server can be integrated with MySQL database, it can be developed SSO systems. Bandwidth management can be done with Mikrotik feature, but has the disadvantages of scalable storage, that problem can overcome by integrating Mikrotik and RADIUS server, then defining time doing data packet quota for the client and its implementation can help with hypertext preprocessor (PHP) scripts.
Volume: 19
Issue: 4
Page: 1419-1427
Publish at: 2021-08-01

Sensitivity of shortest distance search in the ant colony algorithm with varying normalized distance formulas

10.12928/telkomnika.v19i4.18872
Rahmad; Universitas Sumatera Utara Syah , Mahyuddin KM; Universitas Sumatera Utara Nasution , Erna Budhiarti; Universitas Sumatera Utara Nababan , Syahril; Universitas Sumatera Utara Efendi
The ant colony algorithm is an algorithm adopted from the behavior of ants which naturally ants are able to find the shortest route on the way from the nest to places of food sources based on footprints on the track that has been passed. The ant colony algorithm helps a lot in solving several problems such as scheduling, traveling salesman problems (TSP) and vehicle routing problems (VRP). In addition, ant colony has been developed and has several variants. However, in its function to find the shortest distance is optimized by utilizing several normalized distance formulas with the data used in finding distances between merchants in the mercant ecosystem. Where in the test normalized distance is superior Hamming distance in finding the shortest distance of 0.2875, then followed by the same value, namely the normalized formula Manhattan distance and normalized Euclidean distance with a value of 0.4675 and without using the normalized distance formula or the original ant colony algorithm gets a value 0.6635. Given the sensitivity in distance search using merchant ecosystem data, the method works well on the ant colony Algorithm using normalized Hamming distance.
Volume: 19
Issue: 4
Page: 1251-1259
Publish at: 2021-08-01

Text classification model for methamphetamine-related tweets in Southeast Asia using dual data preprocessing techniques

10.11591/ijece.v11i4.pp3617-3628
Narongsak Chayangkoon , Anongnart Srivihok
Methamphetamine addiction is a prominent problem in Southeast Asia. Drug addicts often discuss illegal activities on popular social networking services. These individuals spread messages on social media as a means of both buying and selling drugs online. This paper proposes a model, the “text classification model of methamphetamine tweets in Southeast Asia” (TMTA), to identify whether a tweet from Southeast Asia is related to methamphetamine abuse. The research addresses the weakness of bag of words (BoW) by introducing BoW and Word2Vec feature selection (BWF) techniques. A domain-based feature selection method was performed using the BoW dataset and Word2Vec. The BWF dataset provided a smaller number of features than the BoW and TF–IDF dataset. We experimented with three candidate classifiers: Support vector machine (SVM), decision tree (J48) and naive bayes (NB). We found that the J48 classifier with the BWF dataset provided the best performance for the TMTA in terms of accuracy (0.815), F-measure (0.818), Kappa (0.528), Matthews correlation coefficient (0.529) and high area under the ROC Curve (0.763). Moreover, TMTA provided the lowest runtime (3.480 seconds) using the J48 with the BWF dataset.
Volume: 11
Issue: 4
Page: 3617-3628
Publish at: 2021-08-01

Smartphone’s off grid communication network by using Arduino microcontroller and microstrip antenna

10.12928/telkomnika.v19i4.15949
Yaqdhan Mahmood; Universiti Teknologi Malaysia Hussain , H. O.; Universiti Teknologi Malaysia Hanoosh , Z.; Universiti Teknikal Malaysia Melaka Zakaria , Fahad Taha; Universiti Teknologi Malaysia Al-Dhief , Murtaja Ali; Universiti Teknologi Malaysia Saare , Mustafa Muhammad; Universiti Teknologi Malaysia Jawad , Alaa Hamza; Universiti Teknologi Malaysia Omran , Ali Abdulateef; Universiti Teknologi Malaysia Abdulbari
After a major disaster, the present communication system fails in providing the services in the affected area. No means of communication proves to be more dangerous as the rescue and relief operations become more difficult. Our current research is about establishing a network in such a disaster-prone area, which would facilitate to communicate and carry out the rescue missions. This research project used Java to create a fire-chat application and used it with the smartphone android system. It used Bluetooth model HC-05 linked with Arduino UNO by the SPI interface to connect Arduino with the smartphone. The FR-model HCW69 connected with Arduino by using UART to transceiver the message. The microstrip antenna 915 MHz connected with the FR-model HCW69 to give us more distance. The maximum effective range of the transceiver was 1 kilometer, to communicate by forming a mesh network. This application is helpful in the case when the smartphone is out of service; it (smartphone) can be communicated connected to the other nearby users with a message.
Volume: 19
Issue: 4
Page: 1100-1106
Publish at: 2021-08-01

Impact of pointing error on SISO/MISO drones swarm-based free space optical system in weak turbulence regime

10.11591/ijeecs.v23.i2.pp918-926
Abdullah Jameel Mahdi , Wamidh Jalil Mazher , Osman Nuri Ucan
Applying the drone-based free space optical (FSO) technology is recent in communication systems. The FSO technology hashigh-security features dueto narrow beamwidth, insusceptible to interferences, free license and landline connection is not appropriate. However, these advantages face many obstacles that affect the system's performance, such as random weather conditions and misalignment. The pointing error Hpis one of the critical factors of the channel gain H. The related parameters of the Hp factor: the pointing error angles θr and the path length Z, were manipulated to extract the applicable values at various receiver diameter values. The proposed system has two topologies: single input single output (SISO) and multiple input single output (MISO), flying in weak atmospheric turbulence. The simulation was done using MATLAB software 2020. The average bit error rate (ABER) for the system versus signal-to-noise ratio (SNR) were verified and analyzed. The results showed that at θr=10−3rad, Z increased in the range 10~100m for each one-centimeter increase of DR. At θr=10−2rad, the applicable Z was nearly 10% of the link distance Z when θr=10−3rad was applied. Consequently, an increase in θr must correspond decrease in Z and vice versa to maintain the system at high performance.
Volume: 23
Issue: 2
Page: 918-926
Publish at: 2021-08-01

A machine learning approach for the recognition of melanoma skin cancer on macroscopic images

10.12928/telkomnika.v19i4.20292
Jairo; Pontifícia Universidad Javeriana Hurtado , Francisco; Pontificia Universidad Javeriana Reales
In the last years, computer vision systems for the detection of skin cancer have being proposed, specially using machine learning techniques for the classification of the disease and features based on the ABCD dermatology criterion, which gives information on the status of the skin lesion based on static properties such as geometry, color and texture, making it an appropriate criterion for medical diagnosis systems that work through images. This paper proposes a novel skin cancer classification system that works on images taken from a standard camera and studies the impact on the results of the smoothed bootstrapping, which was used to augment the original dataset. Eight classifiers with different topologies (KNN, ANN and SVM) were compared, with and without data augmentation, showing that the classifier with the highest performance as well as the must balanced one was the ANN with data augmentation, achieving an AUC of 87.1%, which saw an improvement from an AUC of 84.3% of the ANN trained with the original dataset.
Volume: 19
Issue: 4
Page: 1357-1368
Publish at: 2021-08-01

Investigation of energy efficiency of two-way relay-assisted multi-band machine-to-machine communications

10.11591/ijeecs.v23.i2.pp863-870
Hoang Thien Van , Vo Tien Anh , Danh Hong L. , Chi Duong Thi Kim , Hoang-Sy Nguyen
In this paper, we improve the uplink energy efficiency (EE) of the multi-band machine-to-machine (M2M) communications underlaying cellular networks. In particular, based on the theory of stochastic geometry, we derive the closed-form expressions of the outage probability (OP), and the average energy efficiency of cellular and Machine-to-Machine users in two-way cooperative relaying networks with three-time-slot setting. We ensure the quality of service (QoS) by considering the OP and the average energy efficiency of all links. It is concluded that the three-time-slot relay-aided Machine-to-Machine communication can offer considerably high QoS and low transmission power for fairly distant machine-to-machine networks.
Volume: 23
Issue: 2
Page: 863-870
Publish at: 2021-08-01

Characterizing user behavior in online social networks: Analysis of the regular use of Facebook

10.11591/ijece.v11i4.pp3329-3337
Jaafar Idrais , Yassine El Moudene , Abderrahim Sabour
The analysis of user behaviour in online social networks (OSNs) is one of the important research interests related to human-computer interactions. OSNs gives a large space to share news with no limits around the world and allows user to benefit from properties of this interactive and dynamic system. The study of user behaviour on a social and popular platform characterized by the use of new technologies requires to understand and the analysis of collective behaviour on Facebook. This paper aims to analyse the usage patterns in OSNs using the visible interactions of Facebook, by studying the time of activity and the evolution of human behaviour through a process of detection of visible and non-volatile interactions. In the first step, we perform a data collection process based on breadth first search algorithm (BFS) and semi-supervised crawler agent. In the second step, we build an interaction quantification process to measure users’ activities and analysis related time series. The study of the frequency of periodic use has shown that the communities monitored follow a weekly rhythm that decreases over time to reach a frequency of daily use, which reflects a stability of activities and a case of dependency of use.
Volume: 11
Issue: 4
Page: 3329-3337
Publish at: 2021-08-01

Experimental study of capacity and electrode structure of six cell dynamic lead acid battery

10.12928/telkomnika.v19i4.17845
Kurriawan Budi; Universitas PGRI Kanjuruhan Malang Pranata , Yuni; University of Brawijaya Triasari , Nur; University of Brawijaya Khairati , Istiroyah; University of Brawijaya Istiroyah , Mauludi Ariesto; University of Brawijaya Pamungkas , Muhammad; University of Brawijaya Ghufron
The six cells of the dynamic lead acid battery (DLAB) series have been made to resemble the accumulator with sulfuric acid single electrolyte. The tank was filled with 1200 mL of 30% sulfuric acid and circulated through each unit cell by a minipump during charge-discharge process. Experiments were carried out by providing a charging current of 2A, while the discharge current was varied at 0.5 A, 0.6 A, 0.7 A, 0.8 A for 10 continuous cycle to obtain the battery with the best characteristics. The experimental results show that all batteries have a working voltage of 10.8-14.4 volt. The discharging current is inversely proportional to the discharging duration. The resulting capacity has an efficiency ranging from 80.1-81.1%. DLAB with 0.5 A discharging current shows the best performance based on the length of duration and the average capacity with value of 109.61 h and 6168 mAh while for the ideal performance stability is obtained by DLAB with 0.7 A discharging current. The electrochemical reaction produces angelsite and plattnerite phases on the positive electrode. Meanwhile, angelsite and lead phases are formed on the negative electrode.
Volume: 19
Issue: 4
Page: 1369-1378
Publish at: 2021-08-01

Optimization of learning algorithms in multilayer perceptron for sheet resistance of reduced graphene oxide thin-film

10.11591/ijeecs.v23.i2.pp686-693
Noor Aiman bin Aminuddin , Nurlaila Ismail , Marianah Masrie , Siti Aishah Mohamad Badaruddin
Multilayer perceptron (MLP) optimization is carried out to investigate the classifier's performance in discriminating the uniformity of reduced Graphene Oxide(rGO) thin-film sheet resistance. This study used three learning algorithms: resilient back propagation (RP), scaled conjugate gradient (SCG) and levenberg-marquardt (LM). The dataset used in this study is the sheet resistance of rGO thin films obtained from MIMOS Bhd. This work involved samples selection from a uniform and non-uniform rGO thin-film sheet resistance. The input and output data were under going data pre-processing: data normalization, data randomization and data splitting. The data were dividedin to three groups; training,  validation and testing with a ratio of 70%: 15%: 15%, respectively. A varying number of hidden neurons optimized the learning algorithms in MLP from 1 to 10. Their behavior helped establish the best learning algorithms in discriminating MLP for rGO sheet resistance uniformity. The performances measured were the accuracy of training, validation and testing dataset, mean squared errors (MSE) andepochs. All the analytical work in this study was achieved automatically via MATLAB software version R2018a. It was found that the LM is dominant inthe optimization of a learning algorithm in MLP forrGO sheet resistance.The MSE for LM is the most reduced amid SCG and RP. 
Volume: 23
Issue: 2
Page: 686-693
Publish at: 2021-08-01

An electric circuit model for a lithium-ion battery cell based on automotive drive cycles measurements

10.11591/ijece.v11i4.pp2798-2810
Jaouad Khalfi , Najib Boumaaz , Abdallah Soulmani , El Mehdi Laadissi
The on-board energy storage system plays a key role in electric vehicles since it directly affects their performance and autonomy. The lithium-ion battery offers satisfactory characteristics that make electric vehicles competitive with conventional ones. This article focuses on modeling and estimating the parameters of the lithium-ion battery cell when used in different electric vehicle drive cycles and styles. The model consists of an equivalent electrical circuit based on a second-order Thevenin model. To identify the parameters of the model, two algorithms were tested: Trust-Region-Reflective and Levenberg-Marquardt. To account for the dynamic behavior of the battery cell in an electric vehicle, this identification is based on measurement data that represents the actual use of the battery in different conditions and driving styles. Finally, the model is validated by comparing simulation results to measurements using the mean square error (MSE) as model performance criteria for the driving cycles (UDDS, LA-92, US06, neural network (NN), and HWFET). The results demonstrate interesting performance mostly for the driving cycles (UDDS and LA-92). This confirms that the model developed is the best solution to be integrated in a battery management system of an electric vehicle.
Volume: 11
Issue: 4
Page: 2798-2810
Publish at: 2021-08-01

Robotic hex-nut sorting system with deep learning

10.11591/ijece.v11i4.pp3575-3583
Cristian Almanza , Javier Martínez Baquero , Robinson Jiménez-Moreno
This article exposes the design and implementation of an automation system based on a robotic arm for hex-nut classification, using pattern recognition and image processing.  The robotic arm work based on three servo motors and an electromagnetic end effector. The pattern recognition implemented allows classifying three different types of hex-nut through deep learning algorithms based on convolutional neural network architectures. The proposed methodology exposes four phases: the first is the design, implementation, and control of a robotic arm. The second is the capture, classification, and image treatment; the third allows gripping the nut through the robot’s inverse kinematic. The final phase is the re-localization of the hex-nut in the respective container. The automation system successfully classifies all the types of hex-nuts, where the convolutional network used is an efficient and recent pattern recognition method, with an accuracy of 100% in 150 iterations. This development allows for obtaining a novel algorithm for robotic applications in hex-nut sorting.
Volume: 11
Issue: 4
Page: 3575-3583
Publish at: 2021-08-01

Online 3D path planning for Tri-copter drone using GWO-IBA algorithm

10.12928/telkomnika.v19i4.18697
Sadiq Jawad; University of Baghdad R. , Muna H.; University of Baghdad Saleh
Robots at present are involved in many parts of life, especially mobile robots, which are two parts, ground robots and flying robots, and the best example of a flying robot is the drone. Path planning is a fundamental part of UAVs because the drone follows the path that leads it to goal with obstacle avoidance. Therefore, this paper proposes a hybrid algorithm (grey wolf optimization - intelligent bug algorithm GWO-IBA) to determine the best, shortest and without obstacles path. The hybrid algorithm was implemented and tested in the MATLAB program on the Tri-copter model, and it gave different paths in different environments. The paths obtained were characterized by being free of obstacles and the shortest paths available to reach the target.
Volume: 19
Issue: 4
Page: 1334-1341
Publish at: 2021-08-01

Audio compression using transforms and high order entropy encoding

10.11591/ijece.v11i4.pp3459-3469
Zainab J. Ahmed , Loay E. George , Raad Ahmed Hadi
Digital audio is required to transmit large sizes of audio information through the most common communication systems; in turn this leads to more challenges in both storage and archieving. In this paper, an efficient audio compressive scheme is proposed, it depends on combined transform coding scheme; it is consist of i) bi-orthogonal (tab 9/7) wavelet transform to decompose the audio signal into low & multi high sub-bands, ii) then the produced sub-bands passed through DCT to de-correlate the signal, iii) the product of the combined transform stage is passed through progressive hierarchical quantization, then traditional run-length encoding (RLE), iv) and finally LZW coding to generate the output mate bitstream. The measures Peak signal-to-noise ratio (PSNR) and compression ratio (CR) were used to conduct a comparative analysis for the performance of the whole system. Many audio test samples were utilized to test the performance behavior; the used samples have various sizes and vary in features. The simulation results appear the efficiency of these combined transforms when using LZW within the domain of data compression. The compression results are encouraging and show a remarkable reduction in audio file size with good fidelity.
Volume: 11
Issue: 4
Page: 3459-3469
Publish at: 2021-08-01

A new hybrid conjugate gradient algorithm for optimization models and its application to regression analysis

10.11591/ijeecs.v23.i2.pp1100-1109
Ibrahim Mohammed Sulaiman , Norsuhaily Abu Bakar , Mustafa Mamat , Basim A. Hassan , Maulana Malik , Alomari Mohammad Ahmed
The hybrid conjugate gradient (CG) method is among the efficient variants of CG method for solving optimization problems. This is due to their low memory requirements and nice convergence properties. In this paper, we present an efficient hybrid CG method for solving unconstrained optimization models and show that the method satisfies the sufficient descent condition. The global convergence prove of the proposed method would be established under inexact line search. Application of the proposed method to the famous statistical regression model describing the global outbreak of the novel COVID-19 is presented. The study parameterized the model using the weekly increase/decrease of recorded cases from December 30, 2019 to March 30, 2020. Preliminary numerical results on some unconstrained optimization problems show that the proposed method is efficient and promising. Furthermore, the proposed method produced a good regression equation for COVID-19 confirmed cases globally.
Volume: 23
Issue: 2
Page: 1100-1109
Publish at: 2021-08-01
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