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31,456 Article Results

Series active power filter supplied by fuel cell for mitigating power quality issues

10.11591/ijape.v9.i2.pp173-192
Abdallah Ben Abdelkader , Othmane Abdelkhalek , Youssef Mouloudi , Mohamed Amine Hartani , Benabid Slimane
In this paper, the combination of the series active power filter (SAPF) with a fuel cell (FC) source is deliberated. The FC based on the SAPF aims to compensate voltage deviations or disturbances that occur in the system caused by power quality issues. The proposed system consists of a fuel cell source connected to the DC l ink through two DC-DC converters, the first extracts the maximum power of the FC source through pulse width modulation (PWM) signals generated from the maximum power point tracker (MPPT) controller. Thus, the second converter is used to regulate the high voltage side of the converter through closed control loops, in addition to a voltage source inverter (VSI) and a series injection transformer. Despite of fluctuations of the DC link during the compensation of the needed energy, MPPT and closed control loops generate PWM signals to the switching devices of DC-DC boost converters in order to extract maximum fuel cell power and to maintain the bus voltage within its limits and around its reference values respectively. The proposed topology is simulated in MATLAB/Simulink software, where simulation results show that the proposed FC based SAPF can efficiently reduce problems of voltage sags-wells and harmonics.
Volume: 9
Issue: 2
Page: 173-192
Publish at: 2020-08-01

Polar wolf optimization algorithm for solving optimal reactive power problem

10.11591/ijape.v9.i2.pp107-112
Kanagasabai Lenin
This paper proposes polar wolf optimization (PWO) algorithm to solve the optimal reactive power problem. Proposed algorithm enthused from actions of polar wolves. Leader’s wolves which denoted as xα are accountable for taking judgment on hunting, resting place, time to awaken etc. second level is xβ those acts when there is need of substitute in first case. Then xγ be as final level of the wolves. In the modeling social hierarchy is developed to discover the most excellent solutions acquired so far. Then the encircling method is used to describe circle-shaped vicinity around every candidate solutions. In order to agents work in a binary space, the position modernized accordingly. Proposed PWO algorithm has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show the projected algorithms reduced the real power loss considerably.
Volume: 9
Issue: 2
Page: 107-112
Publish at: 2020-08-01

Real power loss diminution by predestination of particles wavering search algorithm

10.11591/ijict.v9i2.pp92-99
Kanagasabai Lenin
In this work Predestination of Particles Wavering Search (PPS) algorithm has been applied to solve optimal reactive power problem. PPS algorithm has been modeled based on the motion of the particles in the exploration space. Normally the movement of the particle is based on gradient and swarming motion.  Particles are permitted to progress in steady velocity in gradient-based progress, but when the outcome is poor when compared to previous upshot, immediately particle rapidity will be upturned with semi of the magnitude and it will help to reach local optimal solution and it is expressed as wavering movement. In standard IEEE 14, 30, 57,118,300 bus systems Proposed Predestination of Particles Wavering Search (PPS) algorithm is evaluated and simulation results show the PPS reduced the power loss efficiently.
Volume: 9
Issue: 2
Page: 92-99
Publish at: 2020-08-01

Modeling and control of 41-level inverter using best switching angles calculation method

10.11591/ijape.v9.i2.pp153-158
Alla Eddine Toubal Maamar , M'hamed Helaimi , Rachid Taleb , Abdelatif Gadoum
In this paper, analysis and modeling of a single-phase H-bridge forty-one level inverter are con sidered. The control of proposed inverter by equal-phase and half-height methods is implemented. MATLAB/Simulink environments are used to simulate the model an d show obtained results of waveforms with FFT analysis. Eventually, the total harmonic distortion obtained for each level with the two methods is presented, comparatively, for a comparison.
Volume: 9
Issue: 2
Page: 153-158
Publish at: 2020-08-01

Performance evaluation of MANET routing protocols based on QoS and energy parameters

10.11591/ijece.v10i4.pp3635-3642
Salma S. Mohamed , Abdel-Fatah I. Abdel-Fatah , Mohamed A. Mohamed
Routing selection and supporting Quality of Service (QoS) are fundamental problems in Mobile Ad Hoc Network (MANET). Many different protocols have been proposed in the literature and some performance simulations are made to address this challenging task. This paper discusses the performance evaluation and comparison of two typical routing protocols; Ad Hoc On-Demand Distance Vector (AODV) and Destination-Sequenced Distance-Vector (DSDV) based on measuring the power consumption in network with varing of the QoS parameters. In this paper, we have studied and analyzed the impact of variations in QoS parameter combined with the choice of routing protocol, on network performance. The network performance is measured in terms of average throughput, packet delivery ratio (PDR), average jitter and energy consumption. The simulations are carried out in NS-3. The simulation results show that DSDV and AODV routing protocols are less energy efficient. The main aim of this paper is to highlight the directions for the future design of routing protocol which would be better than the existing ones in terms of energy utilization and delivery ratio.
Volume: 10
Issue: 4
Page: 3635-3642
Publish at: 2020-08-01

Power system state estimation using teaching learning-based optimization algorithm

10.12928/telkomnika.v18i4.14159
Surender Reddy; Woosong University Salkuti
The main goal of this paper is to formulate power system state estimation (SE) problem as a constrained nonlinear programming problem with various constraints and boundary limits on the state variables. SE forms the heart of entire real time control of any power system. In real time environment, the state estimator consists of various modules like observability analysis, network topology processing, SE and bad data processing. The SE problem formulated in this work is solved using teaching leaning-based optimization (TLBO) technique. Difference between the proposed TLBO and the conventional optimization algorithms is that TLBO gives global optimum solution for the present problem. To show the suitability of TLBO for solving SE problem, IEEE 14 bus test system has been selected in this work. The results obtained with TLBO are also compared with conventional weighted least square (WLS) technique and evolutionary based particle swarm optimization (PSO) technique.
Volume: 18
Issue: 4
Page: 2125-2131
Publish at: 2020-08-01

Survey on wireless sensor networks: energy efficient optimization routing algorithms

10.11591/ijeecs.v19.i2.pp756-765
V. Sivasankarareddy , G. Sundari
Wireless Sensor Network is extensively utilized in numerous places, such as protection surveillance. In Wireless Sensor Network, sensing unit networks are particular arbitrarily in addition to likewise in-network relying upon the technique is used to extend the network. As sensing unit nodes make use of strength from batteries for noticing the facts in addition to forwarding data, it uses the capability for those answers. The sizable troubles in cordless networks include power optimization, protection, directing, and project type. In this paper, current procedures in escaping power utilization of Wireless Sensor Network in addition to distinctive protocols and also Methods are researched. Additionally, destiny research have a look at on strength efficiency in Wireless Sensor Network putting forward new terms as well as targets for in addition examination is mentioned. Depiction of optimizing strategies like particle swarm optimization set of rules as well as ant swarm optimization Formula is already possible for lowering the electricity loss and complements the life of sensor community but those strategies take in greater time. This paper gives surveying extraordinary different optimization techniques below the multi-objective facet that takes region in tradeoffs. Information extracting in sensing unit networks is the technique of obtaining software-enabled plans in addition to patterns with gratifying accuracy from a constant, speedy, in addition to probable non-ended flow of facts streams from sensor networks. Various boundaries in preceding optimization Algorithms and suggesting a great deal better treatment through applying Data extracting Strategies for Wireless Sensing unit Networks is carried out.
Volume: 19
Issue: 2
Page: 756-765
Publish at: 2020-08-01

Predicting depression using deep learning and ensemble algorithms on raw twitter data

10.11591/ijece.v10i4.pp3751-3756
Nisha P. Shetty , Balachandra Muniyal , Arshia Anand , Sushant Kumar , Sushant Prabhu
Social network and microblogging sites such as Twitter are widespread amongst all generations nowadays where people connect and share their feelings, emotions, pursuits etc. Depression, one of the most common mental disorder, is an acute state of sadness where person loses interest in all activities. If not treated immediately this can result in dire consequences such as death. In this era of virtual world, people are more comfortable in expressing their emotions in such sites as they have become a part and parcel of everyday lives. The research put forth thus, employs machine learning classifiers on the twitter data set to detect if a person’s tweet indicates any sign of depression or not.
Volume: 10
Issue: 4
Page: 3751-3756
Publish at: 2020-08-01

QR code based two-factor authentication to verify paper-based documents

10.12928/telkomnika.v18i4.14339
Maysaa Abd Ulkareem; Technology University of Basrah Naser , Eman Talib; Technology University of Basrah Jasim , Haider M.; Technology University of Basrah Al-Mashhadi
Important paper-based documents Exposed to forgery such as: official certificates, birth, marriage, death certificates, selling and buying documents and other legal documents is more and more serious and sophisticated. With the purposes of fraud, appropriation of property, job application and assignment in order to swindle public authorities, this forgery has led to material loss, belief deterioration as well as social instability. There are many techniques has been proposed to overcome this issues such as: ink stamps, live signatures, documented the transaction in third party like the court or notary. In this paper, it’s proposed a feasible solution for forgery prevention for paper-based documents using cloud computing application. With the application of Quick Response bidirectional barcode and the usage of hash algorithm. The study aims at developing an electronic verification system for official and issued books (documents, endorsements, and other official books) to/from different sections of the Institute using QR technology.
Volume: 18
Issue: 4
Page: 1834-1842
Publish at: 2020-08-01

Ant-colony and nature-inspired heuristic models for NOMA systems: a review

10.12928/telkomnika.v18i4.14995
Law Poh; Multimedia University Liyn , Hadhrami; Multimedia University Ab. Ghani , Farah Najwa; Multimedia University Roslim , Nur Asyiqin; Multimedia University Amir Hamzah , Saeed Mohammed; Multimedia University Abdulghani Mohammed , Nor Hidayati; Multimedia University Abdul Aziz , Azlan Abd.; Multimedia University Aziz , Tan Kim; Multimedia University Geok , Azizul; Universiti Teknologi Malaysia Azizan
The increasing computational complexity in scheduling the large number of users for non-orthogonal multiple access (NOMA) system and future cellular networks lead to the need for scheduling models with relatively lower computational complexity such as heuristic models. The main objective of this paper is to conduct a concise study on ant-colony optimization (ACO) methods and potential nature-inspired heuristic models for NOMA implementation in future high-speed networks. The issues, challenges and future work of ACO and other related heuristic models in NOMA are concisely reviewed. The throughput result of the proposed ACO method is observed to be close to the maximum theoretical value and stands 44% higher than that of the existing method. This result demonstrates the effectiveness of ACO implementation for NOMA user scheduling and grouping.
Volume: 18
Issue: 4
Page: 1754-1761
Publish at: 2020-08-01

Designing and verifying a tool for diagnosing scientific misconceptions in genetics topic

10.11591/ijere.v9i3.20544
Sasithorn Kantahan , Putcharee Junpeng , Sompong Punturat , Keow Ngang Tang , Perman Gochyyev , Mark Wilson
The main purpose of this study was to design and verify the quality of an assessment aimed at diagnosing scientific misconceptions among students enrolled in 10th-grade biology subjects. A sample consisted of N=200 students from schools under the administration of the Office of Secondary Educational Service 31, Nakhon Ratchasima province. We employed the design-based approach, which consists of four phases, namely, construct map, item design, outcome space, and Wright map. Multidimensional Random Coefficient Multinomial Logit Model (MRCMLM) was used to evaluate the quality of the assessment tool. The assessment tool consists of two dimensions, namely, knowledge and reasoning. The assessment tool is comprised of 40 items, with 20 items tapping each of the dimensions. Findings form item analysis and modeling revealed sufficient evidence on the internal structure and validity of the instrument. It can be concluded that the unidimensional model is more appropriate than the multidimensional model for diagnosing scientific misconceptions in the genetics topic for dichotomously scored with four options in each item. The polytomous scored type should be further investigated to determine the best fit model in the items relating to evidence-based reasoning for supporting students’ answers.
Volume: 9
Issue: 3
Page: 564-571
Publish at: 2020-08-01

Evaluation of load balancing approaches for Erlang concurrent application in cloud systems

10.12928/telkomnika.v18i4.13150
Chanintorn; Assumption University. Jittawiriyanukoon
Cloud system accommodates the computing environment including PaaS (platform as a service), SaaS (software as a service), and IaaS (infrastructure as service) that enables the services of cloud systems.  Cloud system allows multiple users to employ computing services through browsers, which reflects an alternative service model that alters the local computing workload to a distant site. Cloud virtualization is another characteristic of the clouds that deliver virtual computing services and imitate the functionality of physical computing resources. It refers to an elastic load balancing management that provides the flexible model of on-demand services. The virtualization allows organizations to improve high levels of reliability, accessibility, and scalability by having a capability to execute applications on multiple resources simultaneously. In this paper we use a queuing model to consider a flexible load balancing and evaluate performance metrics such as mean queue length, throughput, mean waiting time, utilization, and mean traversal time. The model is aware of the arrival of concurrent applications with an Erlang distribution. Simulation results regarding performance metrics are investigated. Results point out that in Cloud systems both the fairness and load balancing are to be significantly considered.
Volume: 18
Issue: 4
Page: 1795-1801
Publish at: 2020-08-01

Application of neural network method for road crack detection

10.12928/telkomnika.v18i4.14825
Yuslena; Universitas Lambung Mangkurat Sari , Puguh Budi; Universitas Lambung Mangkurat Prakoso , Andreyan Rizky; Universitas Lambung Mangkurat Baskara
The study presents a road pavement crack detection system by extracting picture features then classifying them based on image features. The applied feature extraction method is the gray level co-occurrence matrices (GLCM). This method employs two order measurements. The first order utilizes statistical calculations based on the pixel value of the original image alone, such as variance, and does not pay attention to the neighboring pixel relationship. In the second order, the relationship between the two pixel-pairs of the original image is taken into account. Inspired by the recent success in implementing Supervised Learning in computer vision, the applied method for classification is artificial neural network (ANN). Datasets, which are used for evaluation are collected from low-cost smart phones. The results show that feature extraction using GLCM can provide good accuracy that is equal to 90%.
Volume: 18
Issue: 4
Page: 1962-1967
Publish at: 2020-08-01

Ethnoconstructivism analysis: Study of pedagogic mathematics competence of primary school teachers

10.11591/ijere.v9i3.20256
Syahrial Syahrial , Asrial Asrial , Maison Maison , Amirul Mukminin , Dwi Agus Kurniawan
The teacher has an important role in realizing quality learning. Qualified teachers are shown with good competence. Teacher competency can be improved through teacher understanding of non-constructivism knowledge in mathematics learning. Teachers can integrate cultural values and local wisdom into mathematical concepts to shape student knowledge. Integrating cultural values and local wisdom into mathematics learning makes students learn through their cultural background experiences. This research wasa descriptive research employed 691 respondents. The instruments in this study were questionnaires, tests and interviews to reinforce quantitative results. The purpose of this study was to determine the level of teacher pedagogical knowledge, teacher ethnoconstructivism knowledge, the influence and impact of ethnoconstivism knowledge in mathematics learning. The results of this study indicate the competence of elementary school teachers in Batanghari, Muaro Jambi, and Jambi City tends to be generally not good, and teachers have applied ethno-constructivism in mathematics learning through the use of media, models, and learning strategy. Teachers still encounter many obstacles in the implementation process. And the age range of the teacher has an impact on the level of ethnoconstructivism knowledge in mathematics learning.
Volume: 9
Issue: 3
Page: 614-624
Publish at: 2020-08-01

A novel similarity measure for missing link prediction in social networks

10.11591/ijeecs.v19.i2.pp1071-1077
Gogulamudi Naga Chandrika , E. Srinivasa Reddy
Social Networks progress over time by the addition of new nodes and links, form associations with one community to the other community. Over a few decades, the fast expansion of Social Networks has attracted many researchers to pay more attention towards complex networks, the collection of social data, understand the social behaviors of complex networks and predict future conflicts. Thus, Link prediction is imperative to do research with social networks and network theory. The objective of this research is to find the hidden patterns and uncovered missing links over complex networks. Here, we developed a new similarity measure to predict missing links over social networks. The new method is computed on common neighbors with node-to-node distance to get better accuracy of missing link prediction. We tested the proposed measure on a variety of real-world linked datasets which are formed from various linked social networks. The proposed approach performance is compared with contemporary link prediction methods. Our measure makes very effective and intuitive in predicting disappeared links in linked social networks.
Volume: 19
Issue: 2
Page: 1071-1077
Publish at: 2020-08-01
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