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29,922 Article Results

Energy cost savings based on the UPS

10.11591/ijece.v10i4.pp4237-4243
Phu Tran Tin , Duy Hung Ha , Minh Tran , Quang Sy Vu
Energy-saving, improving energy efficiency, and finding a new efficient way to use energy are considered as an urgent problem in over the world. In this paper, we consider the economics of energy use in combination with energy storage units where two forms of electricity exist in the power system. Then the problem of optimizing the installation capacity (to optimize the investment costs for energy storage) is presented and investigated in connection with the conversion systems. The topic opens a very significant result, including the introduction of a mathematical model to calculate the simulation in optimizing the installation capacity of the equipment in the system, multi-source power, as well as voltage and power stability benefits.
Volume: 10
Issue: 4
Page: 4237-4243
Publish at: 2020-08-01

Optimized placement of multiple FACTS devices using PSO and CSA algorithms

10.11591/ijece.v10i4.pp3350-3357
Basanagouda Patil , S. B. Karajgi
This paper is an attempt to develop a multi-facts device placementin deregulated power system using optimization algorithms. The deregulated power system is the recent need in the power distribution as it has many independent sellers and buyers of electricity. The problem of deregulation is the quality of the power distribution as many sellers are involved. The placement of FACTS devices provides the solution for the above problem. There are researches available for multiple FACTS devices. The optimization algorithms like Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are implemented to place the multiple FACTS devices in a power system. MATLAB based implementation is carried out for applying Optimal Power Flow (OPF) with variation in the bus power and the line reactance parameters. The cost function is used as the objective function. The cost reduction of FACTS as well as generation by placement of different compensators like, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC). The cost calculation is done on the 3-seller scenario. The IEEE 14 bus is taken here as 3-seller system.
Volume: 10
Issue: 4
Page: 3350-3357
Publish at: 2020-08-01

Smart monitoring system of Najran dam

10.11591/ijece.v10i4.pp3999-4007
A. H. M. Almawgani , M. A. Alshorman , M. A. Alyami , H. M. Alhmammi , D. S. Almahri , M. A. Alkhuraym , A. H. Alwasel
Najran city faces the flood situation every year due to intensive rain and climatic disturbances. Flooding also causes loss of money, along with loss of life and property and the destruction of agriculture and livestock. Thus, this project proposes a conceptual framework with three main phases: monitoring the water level inside the dam and level in water stream before and after the dam, controlling the opening and closing of the dam gate and measuring the water pressure at the dam barrier. In the case of high water level dam is monitored through water sensors placed at the top of the dam and then these sensors give a reference to the stepper motor and the flow of the stepper motor is controlled by the dam gate. The experimental results shows that the proposed system has the capability to reliably tackle the flood water. It can accurately measure the water level and control the gate of dam as soon as the level of the water reaches to danger level and water pressure at the barrier is measured by the sensor. The developed real-time monitoring system in Najran dam will help authorities to take preventive actions to deal with flood disaster.
Volume: 10
Issue: 4
Page: 3999-4007
Publish at: 2020-08-01

Design of probe for NQR/NMR detection

10.11591/ijece.v10i4.pp3468-3475
Preeti Hemnani , A. K. Rajarajan , Gopal Joshi , S. V. G. Ravindranath
Nuclear Magnetic Resonance (NMR) is a RF technique that is able to detect any compound by sensing the excited resonance signals from atomic nuclei having non-zero spin. NQR is similar to NMR but the only difference is NMR needs a DC magnetic field and due to this its application in the field is limited. A FPGA based NQR spectrometer is designed using a single FPGA chip to perform the digital tasks required for NQR spectrometer. Design of Probe for NMR/NQR spectrometer is researched. Parallel tuned and series tuned Probes are discussed and simulated.14N NQR from NaNO2 is observed from spectrometer designed with parallel tuned probe.
Volume: 10
Issue: 4
Page: 3468-3475
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

Novel holistic architecture for analytical operation on sensory data relayed as cloud services

10.11591/ijece.v10i4.pp4322-4330
Manujakshi B. C , K. B. Ramesh
With increasing adoption of the sensor-based application, there is an exponential rise of the sensory data that eventually take the shape of the big data. However, the practicality of executing high end analytical operation over the resource-constrained big data has never being studied closely. After reviewing existing approaches, it is explored that there is no cost effective schemes of big data analytics over large scale sensory data processiing that can be directly used as a service. Therefore, the propsoed system introduces a holistic architecture where streamed data after performing extraction of knowedge can be offered in the form of services. Implemented in MATLAB, the proposed study uses a very simplistic approach considering energy constrained of the sensor nodes to find that proposed system offers better accuracy, reduced mining duration (i.e. faster response time), and reduced memory dependencies to prove that it offers cost effective analytical solution in contrast to existing system.
Volume: 10
Issue: 4
Page: 4322-4330
Publish at: 2020-08-01

Conflict-free dynamic route multi-AGV using dijkstra floyd-warshall hybrid algorithm with time windows

10.11591/ijece.v10i4.pp3596-3604
Solichudin Solichudin , Aris Triwiyatno , Munawar A. Riyadi
Autonomous Guided Vehicle is a mobile robot that can move autonomously on a route or lane in an indoor or outdoor environment while performing a series of tasks. Determination of the shortest route on an autonomous guided vehicle is one of the optimization problems in handling conflict-free routes that have an influence on the distribution of goods in the manufacturing industry's warehouse. Pickup and delivery processes in the distribution on AGV goods such as scheduling, shipping, and determining the route of vehicle with short mileage characteristics, is very possible to do simulations with three AGV units. There is a windows time limit on workstations that limits shipping. The problem of determining the route in this study is considered necessary as a multi-vehicle route problem with a time window. This study aims to describe the combination of algorithms written based on dynamic programming to overcome the problem of conflict-free AGV routes using time windows. The combined approach of the Dijkstra and Floyd-Warshall algorithm results in the optimization of the closest distance in overcoming conflict-free routes.
Volume: 10
Issue: 4
Page: 3596-3604
Publish at: 2020-08-01

An adaptation of Text2Onto for supporting the French language

10.11591/ijece.v10i4.pp3743-3750
Morad Hajji , Mohammed Qbadou , Khalifa Mansouri
The ontologies are progressively imposing themselves in the field of knowledge management. While the manual construction of an ontology is by far the most reliable, this task has proved to be too tedious and expensive. To assist humans in the process of building an ontology, several tools have emerged proposing the automatic or semi-automatic construction of ontologies. In this context, Text2Onto has become one of the most recognized ontology learning tools. The performance of this tool is confirmed by several research works. However, the development of this tool is based on Princeton WordNet (PWN) for English. As a result, it is limited to the processing of textual resources written in English. In this paper, we present our approach based on JWOLF, a Java API to access the free WordNet for French that we have developed to adapt this tool for the construction of ontologies from corpus in French. To evaluate the usefulness of our approach, we assessed the performance of the improved version of Text2Onto on a simplistic corpus of French language documents. The results of this experiment have shown that the improved version of Text2Onto according to our approach is effective for the construction of an ontology from textual documents in the French language.
Volume: 10
Issue: 4
Page: 3743-3750
Publish at: 2020-08-01

Texture classification of fabric defects using machine learning

10.11591/ijece.v10i4.pp4390-4399
Yassine Ben Salem , Mohamed Naceur Abdelkrim
In this paper, a novel algorithm for automatic fabric defect classification was proposed, based on the combination of a texture analysis method and a support vector machine SVM. Three texture methods were used and compared, GLCM, LBP, and LPQ. They were combined with SVM’s classifier. The system has been tested using TILDA database. A comparative study of the performance and the running time of the three methods was carried out. The obtained results are interesting and show that LBP is the best method for recognition and classification and it proves that the SVM is a suitable classifier for such problems. We demonstrate that some defects are easier to classify than others.
Volume: 10
Issue: 4
Page: 4390-4399
Publish at: 2020-08-01

Measuring information credibility in social media using combination of user profile and message content dimensions

10.11591/ijece.v10i4.pp3537-3549
Erwin B. Setiawan , Dwi H. Widyantoro , Kridanto Surendro
Information credibility in social media is becoming the most important part of information sharing in the society. The literatures have shown that there is no labeling information credibility based on user competencies and their posted topics. This study increases the information credibility by adding new 17 features for Twitter and 49 features for Facebook. In the first step, we perform a labeling process based on user competencies and their posted topic to classify the users into two groups, credible and not credible users, regarding their posted topics. These approaches are evaluated over ten thousand samples of real-field data obtained from Twitter and Facebook networks using classification of Naive Bayes (NB), Support Vector Machine (SVM), Logistic Regression (Logit) and J48 algorithm (J48). With the proposed new features, the credibility of information provided in social media is increasing significantly indicated by better accuracy compared to the existing technique for all classifiers.
Volume: 10
Issue: 4
Page: 3537-3549
Publish at: 2020-08-01

Comparative method of moora, copras and topsis based on weighting of best worst method in supplier selection at ABC mining companies in Indonesia

10.11591/ijeecs.v19.i2.pp890-899
Ryco Puji Setyono , Riyanarto Sarno
Supplier selection is essential to the business. The risks posed by suppliers will have a significant impact on the company's performance. Each business has distinct supplier features to mitigate this.These characteristics are divided into criteria in supplier selection. In this study, the criteria in supplier selection will be weighted by best worst method (BWM) and comparing the three ranking methods, complex proportional assessment (COPRAS), multi-objective optimization berdasarkan analisis rasio (MOORA) and technique for order preference by similarity to ideal solution (TOPSIS). The sample in this study is an ABC manufacturing company engaged in mining from Indonesia. From the results of the study, there were 16 criteria using the Delphi Method. These criteria are divided into four main criteria, namely service, quality, cost and time. From the results of weighting BWM, the price sub criteria on cost criteria have the greatest weight for ABC companies. The results of the weighting are then carried out by supplier ranking by comparing the COPRAS, MOORA and TOPSIS approaches. In comparing these three methods, approaches are used based on accuracy and complexity. The COPRAS method has the highest accuracy and lowest complexity according to the ABC company.
Volume: 19
Issue: 2
Page: 890-899
Publish at: 2020-08-01

A NURBS-optimized dRRM solution in a mono-channel condition for IEEE 802.11 entreprise Wlan networks

10.11591/ijece.v10i4.pp4189-4207
Mehdi Guessous , Lahbib Zenkouar
Dynamic radio resource management, RRM, is an essential design block in the functional architecture of any Wifi controller in IEEE 802.11 indoor dense enterprise Wlans. In a mono-channel condition, it helps tackle co-channel interference problem and enrich end-to-end Wifi clients experience. In this work, we present our dRRM solution: WLCx, and demonstrate its performance over related-work and vendor approaches. Our solution is built on a novel and realistic per-Beam coverage representation approach. Unlike the other RRM solutions, WLCx is dynamic: even the calculation system parameters are processed. This processing comes at price in terms of processing time. To overcome this limitation, we constructed and implemented a NURBS surface-based optimization to our RRM solution. Our NURBS optimized WLCx, N-WLCx, solution achieves almost 92.58% time reduction in comparison with basic WLCx. Furthermore, our optimization could easily be extended to enhance others, vendors and research, RRM solutions.
Volume: 10
Issue: 4
Page: 4189-4207
Publish at: 2020-08-01

Self-checking method for fault tolerance solution in wireless sensor network

10.11591/ijece.v10i4.pp4416-4425
Muayad Sadik Croock , Saja Dhyaa Khuder , Zahraa Abbas Hassan
Recently, the wireless sensor network (WSN) has been considered in different application, particularly in emergency systems. Therefore, it is important to keep these networks in high reliability using software engineering techniques in the field of fault tolerance. This paper proposed a fault node detection method in WSN using the self-checking technique according to the rules of software engineering. Then, the detected faulted node is covered employing the reading of nearest neighbor nodes (sensors). In addition, the proposed method sends a message for maintenance to solve the fault. The proposed method can reduce the time between the detection and recovery of a fault to prevent the confusion of adopting wrong readings, in which the detection is making with mistake. Moreover, it guarantees the reliability of the WSN, in terms of operation and data transmission. The proposed method has been tested over different scenarios and the obtained results show the superior efficiency in terms of recovery, reliability, and continuous data transmission.
Volume: 10
Issue: 4
Page: 4416-4425
Publish at: 2020-08-01

Power minimization of WBSN using adaptive routing protocoL

10.11591/ijeecs.v19.i2.pp837-846
Ammar Sabeeh Hmoud Altamimi , Omar Raad K. Al-Dulaimi , Amar A. Mahawish , M. M. Hashim , Mustafa S. T.
The present work was an attempt to address a challenge of energy utilization or consumption in WBSN, it used a proposed routing algorithm based on ant optimization technique to distribute energy utilization efficiently on nodes. Thus reducing consumed energy and extending the life cycle of nodes, as well as avoiding damages might be occurred in tissues of patient`s body. At the beginning the proposed protocol was compared with conventional routing protocol LEACH to prove it`s efficiency in the extending of the life cycle of node, then it was used with experimental network was employed to examine energy utilizations. The obtained results were compared with others attained by conventional and developed routing protocols, there was considerable minimizing in the energy consumption that proved efficiency of proposed algorithm.
Volume: 19
Issue: 2
Page: 837-846
Publish at: 2020-08-01

Feature selection for multiple water quality status: Integrated bootstrapping and SMOTE approach in imbalance classes

10.11591/ijece.v10i4.pp4331-4339
Shofwatul Uyun , Eka Sulistyowati
STORET is one method to determine the river water quality into four classes (very good , good, medium and bad) based on the data of water for each attribute or feature. The success of the formation of pattern recognition model much depends on the quality of data. There are two issues as the concern of this research as follows: the data having disproportionate amount among the classes (imbalance class) and the finding of noise on its attribute. Therefore, this research integrates the SMOTE Technique and bootstrapping to handle the problem of imbalance class. While an experiment is conducted to eliminate the noise on the attribute by using some feature selection algorithms with filter approach (information gain, rule, derivation, correlation and chi square). This research has some stages as follows: data understanding, pre-processing, imbalance class, feature selection, classification and performance evaluation. Based on the result of testing using 10-fold cross validation, it shows that the use of the SMOTE-bootstrapping technique is able to increase the accurate value from 83.3% to be 98.8%. While the process of noise elimination on the data attribute is also able to increase the accuracy to be 99.5% (the use of feature subset produced by the information gain algorithm and the decision tree classification algorithm).
Volume: 10
Issue: 4
Page: 4331-4339
Publish at: 2020-08-01
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