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31,456 Article Results

Medical remotely caring with COVID-19 virus infected people using optimized wireless arm tracing system

10.12928/telkomnika.v18i6.16331
Mohammed Azher; Al-Furat Al-Awsat Technical University Therib , Ahmed Fahem; Al-Furat Al-Awsat Technical University Al-Baghdadi , Heyam; Al-Furat Al-Awsat Technical University Marzog
A human arm makes many functions that a robotic arm always programmed to make same functions. The human limbs motion can be captured using sensors that they will always copy hand movement. The rapid spread of the Coronavirus (COVID-19) virus and contacting the infections make the number of patients doubled in short time. The system proposed in this research can protect clinicians against infection with virus by reducing the contact with the infected and treat them remotely. This system type can be useful in different other fields of industrial works and defense where dangerous and delicate task can be done remotely without actual touch. Xbee shield is used to allow a hand glove flex sensor to communicate with the robotic arm using Zigbee wirelessly. Zigbee here is based on Xbee module from Max stream that can be communicate outdoor for 300 feet with the line of sight and indoor for 100 feet. Proportional, integral and derivative (PID) controller used in the proposed system to achieve smooth movement of limbs. The desired signal comes from flex sensor that connected to each limb. Kalman estimator proposed to find current state of each limb. In order to get better performance, particle swarm optimization (PSO) is used.
Volume: 18
Issue: 6
Page: 2886-2893
Publish at: 2020-12-01

Best neural simultaneous approximation

10.11591/ijeecs.v20.i3.pp1584-1590
Hawraa Abbas Almurieb , Eman S. Bhaya
For many years, approximation concepts has been investigated in view of neural networks for the several applications of the two topics. Researchers studied simultaneous approximation in the 2-normed space and proved essential theorems concern with existence, uniqueness and degree of best approximation. Here, we define a new 2-norm in Lp-space, with p<1, so we call it Lp quasi 2- normed space (Lp,2). The set of approximations is a space of feedforward neural networks that is constructed in this paper. Existence and uniqueness of best neural approximation for a function from  is proved, describing the rate of best approximation in terms of modulus of smoothness.
Volume: 20
Issue: 3
Page: 1584-1590
Publish at: 2020-12-01

Biometric authenticator algorithm based on multiresolution analysis

10.11591/ijeecs.v20.i3.pp1332-1341
Kerrache Soumia , Beladgham Mohammed , Hamza Aymen , Kadri Ibrahim
In this paper, we propose a feature extraction method for two-dimensional imageauthentication algorithm using curvelet transform and principal component analysis(PCA). Since wavelet transform can not adequately describe facial curves features,Theproposed approach involves image denoising applying a 2D-Curvelet transform toachieve compact representations of curves singularities. To assess the performanceof the presented method, we have employed three classifification techniques: Neuralnetworks (NN), K-Nearest Neighbor (KNN) and Support Vector machines (SVM).Extensive experimental results and comparison with the existing methods show the effectiveness of the proposed recognition method in the ORL face database and CASIAiris database.
Volume: 20
Issue: 3
Page: 1332-1341
Publish at: 2020-12-01

Temperature characteristics of FinFET based on channel fin width and working voltage

10.11591/ijece.v10i6.pp5650-5657
Yousif Atalla , Yasir Hashim , Abdul Nasir Abd. Ghafar , Waheb A. Jabbar
This paper shows the temperature sensitivity of FinFET and the possibility of using FinFET as a temperature Nano sensor based on Fin width of transistor. The multi-gate field effect transistor (MuGFET) simulation tool is used to examine the temperature effect on FinFET characteristics. Current-voltage characteristics with various temperatures and channel Fin width (WF= 5,10,20,40 and 80 nm) are at first simulated, the diode mode connection has been used in this study. The best temperature sensitivity of the FinFET is has been considered under the biggest ∆I at the working voltage VDD with range of 0–5 V. According to the results, the temperature sensitivity increased linearly with all the range of channel Fin width (5-80 nm), also, the lower gate Fin width (WF=5nm) with higher sensitivity can achieved with lower working voltage (VDD=1.25 V).
Volume: 10
Issue: 6
Page: 5650-5657
Publish at: 2020-12-01

Machine learning for plant disease detection: an investigative comparison between support vector machine and deep learning

10.11591/ijai.v9.i4.pp670-683
Aliyu Muhammad Abdu , Musa Mohd Muhammad Mokji , Usman Ullah Ullah Sheikh
Image-based plant disease detection is among the essential activities in precision agriculture for observing incidence and measuring the severity of variability in crops. 70% to 80% of the variabilities are attributed to diseases caused by pathogens, and 60% to 70% appear on the leaves in comparison to the stem and fruits. This work provides a comparative analysis through the model implementation of the two renowned machine learning models, the support vector machine (SVM) and deep learning (DL), for plant disease detection using leaf image data. Until recently, most of these image processing techniques had been, and some still are, exploiting what some considered as "shallow" machine learning architectures. The DL network is fast becoming the benchmark for research in the field of image recognition and pattern analysis. Regardless, there is a lack of studies concerning its application in plant leaves disease detection. Thus, both models have been implemented in this research on a large plant leaf disease image dataset using standard settings and in consideration of the three crucial factors of architecture, computational power, and amount of training data to compare the duos. Results obtained indicated scenarios by which each model best performs in this context, and within a particular domain of factors suggests improvements and which model would be more preferred. It is also envisaged that this research would provide meaningful insight into the critical current and future role of machine learning in food security
Volume: 9
Issue: 4
Page: 670-683
Publish at: 2020-12-01

Dual method cryptography image by two force secure and steganography secret message in IoT

10.12928/telkomnika.v18i6.15847
Maisa'a Abid Ali K.; University of Technology Al-Dabbas , Ashwak; University of Kerbala Alabaichi , Ahmed Saleem; University of Babylon Abbas
With the go on the evolution of both computer and internet technology, videos, sounds, and scripts are used more and more often. It can be used in sundry techniques in ciphering and data concealing. The objective of this paper is leading to the suggestion of a new method of the combination between encryption and concealment of information so as to make it difficult to identify the transmitted datavia networks. This study has used two force secure (2FS) to encrypt the images, in other words, the SF is frequent twice on the image, to obtain powerful encryption then the concealing of the secret message is done inside the cryptography of the image has been performed using a secret key (cosine curve), and this stego-encryption image has been transformed forthe Internet of things storage in the database in IoT (data flow), when the user needs any information can be access inviaof internet of things (IoTs). The outcome of the proposed system is obtained tobe evaluated through different measures, such aspeak signal noise ratio (PSNR), mean square error (MSE), entropy,correlation coefficient, and histogram. The proposed system is good, efficient, fast, has high security, robustness, and transparency.
Volume: 18
Issue: 6
Page: 2928-2938
Publish at: 2020-12-01

The role of social support and self-regulation on work readiness among students in vocational high school

10.11591/ijere.v9i4.20578
Fatwa Tentama , Eva Riyansha Riskiyana
Work readiness is an important factor that can determine the quality of prospective graduates and vocational high schools as one of the educational institutions that prepare human resources to need to pay attention to factors that can improve work readiness. This study aimed to empirically examine how social support and self-regulation influence the work readiness of vocational High School students. The population in this study was all students of grade XII in Vocational High School Muhammadiyah 1 Yogyakarta (a vocational high school), totaling 170 students, and the sample of this study was 111 students. The sampling technique used was randomized sampling using cluster random sampling technique. The data were collected with the work readiness scale, social support scale, and self-regulation scale. The data were then analyzed with multiple linear regression techniques. There was a very significant correlation between social support and selfregulation and they simultaneously influence work readiness (r = 0.490, p = 0.000). There was a very significant correlation between social support and work readiness (r = 0.344, p = 0.000). There is a very significant correlation between self-regulation and work readiness (r = 0.490, p = 0.000). Selfregulation plays dominant role in shaping work readiness.
Volume: 9
Issue: 4
Page: 826-832
Publish at: 2020-12-01

Cyber DoS attack based security simulator for VANET

10.11591/ijece.v10i6.pp5832-5843
Muntadher Naeem Yasir , Muayad Sadik Croock
At the late years, researches focused on the cyber Denial of Service (DoS) attacks in the Vehicle Ad hoc Networks (VANETS). This is due to high importance of ensuring the save receiving of information in terms of Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I) and Vehicle to Road Side Unit (V2R). In this paper, a cyber-security system is proposed to detect and block the DoS attacks in VANET. In addition, a simulator for VENAT based on lightweight authentication and key exchange is presented to simulate the network performance and attacks. The proposed system consists of three phases: registration, authentication as well as communications and DoS attack detection. These phases improve the system ability to detect the attacks in efficient way. Each phase working is based in a proposed related algorithm under the guidance of lightweight protocol. In order to test the proposed system, a prototype is considered includes six cars and we adopt police cars due to high importance of exchanged information. Different case studies have been considered to evaluate the proposed system and the obtained results show a high efficiency of performance in terms of information exchange and attack detection.
Volume: 10
Issue: 6
Page: 5832-5843
Publish at: 2020-12-01

Development modeling methods of analysis and synthesis of fingerprint deformations images

10.11591/ijece.v10i6.pp6053-6060
Haider Hassan Majeed AlKaraawi , Mohammed Qasim Dhahir , Ibrahim Ahmed Alameri , Mowafak K. Mohsen
The current study is to develop modeling methods, Analysis and synthesis of fingerprints deformations images and their application in problems of automatic fingerprint identification. In the introduction justified urgency of the problem, is given a brief description of thematic publications. In this study will review of modern technologies of biometric technologies and methods of biometric identification, the review of fingerprint identification systems, investigate for distorting factors. The influence of deformations is singled out, the causes of deformation of fingerprints are analyzed. The review of modern ways of the account and modeling of deformations in problems of automatic fingerprint identification is given. The scientific novelty of the work is the development of information technologies for the analysis and synthesis of deformations of fingerprint images. The practical value of the work in the application of the developed methods, algorithms and information technologies in fingerprints identification systems. In addition, it has been found that our paper "devoted to research methods and synthesis of the fingerprint deformations" is a more appropriate choice than other papers.
Volume: 10
Issue: 6
Page: 6053-6060
Publish at: 2020-12-01

Experimental results of vector control for an asynchronous machine

10.12928/telkomnika.v18i6.12707
Zineb; University of Abdelmalek Essaadi Mekrini , Seddik; Moulay Ismail University Bri , Jamal; Superior School of Technology Bouchnaif , Badre; Superior School of Technology Bossoufi
The aim of this article is contributeto the advanced vector control strategy of asynchronous machines. Analyzes of experimental of indirect field-oriented control are presented. In this context, we propose vector control algorithms to provide solutions to the disadvantages of field-oriented control FOC.The results obtained from various methods of determining the parameters for asynchronous machine are compared. We calculate the various parameters and then we present the technical characteristics of each element of the asynchronous machine; finally, we implement the vector control used asbasis of comparison between the simulation under Matlab/Simulink software and experiments. The simulation and experimental tests show that the proposed controller is suitable for medium and high-performance applications.
Volume: 18
Issue: 6
Page: 3285-3292
Publish at: 2020-12-01

Design and implementation of 4 bit binary weighted current steering DAC

10.11591/ijece.v10i6.pp5642-5649
Jayeshkumar J. Patel , Amisha P. Naik
A compact current-mode Digital-to-Analog converter (DAC) suitable for biomedical application is repesented in this paper .The designed DAC is binary weighted in 180nm CMOS technology with 1.8V supply voltage. In this implementation, authors have focused on calculaton of Non linearity error say INL and DNL for 4 bit DAC having various type of switches: NMOS, PMOS and Transmission Gate. The implemented DAC uses lower area and power compared to unary architecture due to absence of digital decoders. The desired value of Integrated non linearity (INL) and Differential non linearity (DNL) for DAC for are within a range of +0.5LSB. Result obtained in this works for INL and DNL for the case DAC using Transmission Gate is +0.34LSB and +0.38 LSB respectively with 22mW power dissipation.
Volume: 10
Issue: 6
Page: 5642-5649
Publish at: 2020-12-01

Vehicle logo recognition using histograms of oriented gradient descriptor and sparsity score

10.12928/telkomnika.v18i6.16133
Kittikhun; Suan Sunandha Rajabhat University Meethongjan , Thongchai; Suan Sunandha Rajabhat University Surinwarangkoon , Vinh Truong; Ho Chi Minh City Open University Hoang
Most of vehicle have the similar structures and designs. It is extremely complicated and difficult to identify and classify vehicle brands based on their structure and shape. As we requirea quick and reliable response, so vehicle logos are an alternative method of determining the type of a vehicle. In this paper, we propose a method for vehicle logo recognition based on feature  selection method in a hybrid way. Vehicle logo images are first characterized by histograms of oriented gradient descriptors and the final features vector are then applied feature selection method to reduce the irrelevant information. Moreover, we release a new benchmark dataset for vehicle logo recognition and retrieval task namely, VLR-40. The experimental results are evaluated on this database which show the efficiency of the proposed approach.
Volume: 18
Issue: 6
Page: 3019-3025
Publish at: 2020-12-01

Space charge phenomena on low-density poly ethylene film breakdown under heavy water absorption

10.12928/telkomnika.v18i6.16537
Eka Putra; Universitas Andalas Waldi , Rudy; Universitas Andalas Fernandez , Yoshinobu; Toyohashi University of Technology Murakami , Naohiro; Toyohashi University of Technology Hozumi , Masayuki; Toyohashi University of Technology Nagao
The effect of dry and heavy water absorption on the electrical breakdown of low-density poly ethylene film was investigated. The temperature rise of the sample was observed by thermograph until the electrical breakdown using    direct current ramp voltage. The conduction current of low-density poly ethylene film was also measured, and the result was then correlated with thermograph measurement. Meanwhile, the space charge distribution in asample was measured by the pulse electro-acoustic method. From the thermograph, the result can be seen that under the heavy water absorption, the sample was more dissipated than the dry condition. Then, the breakdown occurs at the lower value of the voltage application, but the higher conduction current. Furthermore, the pulse electric acoustic show that increases the charge injection to the sample in the heavy water absorption. Increased space charges associated with an increase in the current conduction and the formation of heating, which results in a thermal breakdown.
Volume: 18
Issue: 6
Page: 3276-3284
Publish at: 2020-12-01

Automatic amyotrophic lateral sclerosis detection using tunable Q-factor wavelet transform

10.11591/ijai.v9.i4.pp744-756
Abdelouahad Achmamad , Abdelali Belkhou , Atman Jbari
Early diagnosis of amyotrophic lateral sclerosis (ALS) based on electromyography (EMG) is crucial. The processing of a non-stationary EMG signal requires powerful multi-resolution methods. Our study analyzes and classifies the EMG signals. In the present work, we introduce a novel flexible method for classification of EMG signals using tunable Q-factor wavelet transform (TQWT). Different sub-bands generated by the TQWT technique were served to extract useful information related to energy and then the calculated features were selected using a filter selection (FS) method. The effectiveness of the feature selection step resulted not only in the improvement of classification performance but also in reducing the computation time of the classification algorithm. The selected feature subsets were used as inputs to multiple classifier algorithms, namely, k-nearest neighbor (k-NN), least squares support vector machine (LS-SVM) and random forest (RF) for automated diagnosis. The experimental results show better classification measures with k-NN classifier compared with LS-SVM and RF. The robustness of the classification task was tested using a ten-fold cross-validation method. The outcomes of our proposed approach can be exploited to aid clinicians in neuromuscular disorders detection.
Volume: 9
Issue: 4
Page: 744-756
Publish at: 2020-12-01

Business students’ perspectives: What makes successful group performance?

10.11591/ijere.v9i4.20534
Rinny Cherill Rantung , Reggy Nelson Sarmita
Purpose of this study was to identify factors contributing to the successful group performance from the perspective of business students. The in-depth interview was done followed by a survey derived forty-five items variables, after some tests 21 items variables removed due to low item remainder coefficient resulted in 24 items questionnaires. A total of 355 respondents participated during the survey. Exploratory factor analysis with principal factor extraction was performed and five contributing factors were extracted. Those factors are cohesiveness, inter-relationship, norms, diversity and appointed of team leader.
Volume: 9
Issue: 4
Page: 896-902
Publish at: 2020-12-01
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