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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6,301 Documents
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Implementation of SHE-PWM technique for single-phase inverter based on Arduino Laith A. Mohammed; Taha A. Husain; Ahmed M. T. Ibraheem
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp2907-2915

Abstract

This paper presents design and practical implementation of single-phase inverter based on selective harmonic elimination-pulse width modulation (SHE-PWM) technique. Microcontroller mega type Arduino used as a controller for producing the gate pulses. The optimized switching angles determination results in wide range of output voltage. Depending on number of switching angles, the lower order harmonics (LOHs) can be eliminated to improve the output voltage waveform. A comparison study using MATLAB/Simulink for sinusoidal-PWM and SHE-PWM techniques, which shows for the same LOH in the output voltage waveform, the SHE-PWM has less number of pulses per half cycle than sinusoidal-PWM strategy. The reduction in number of pulses results less switching losses. The simulation done using ten switching angles to drive R-L load. A prototype of SHE-PWM inverter with R-L load is used to validate the simulation results.
Solving the order batching and sequencing problem with multiple pickers: A grouped genetic algorithm Jose Alejandro Cano; Pablo Cortés; Emiro Antonio Campo; Alexander Alberto Correa-Espinal
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2516-2524

Abstract

This paper introduces a grouped genetic algorithm (GGA) to solve the order batching and sequencing problem with multiple pickers (OBSPMP) with the objective of minimizing total completion time. To the best of our knowledge, for the first time, an OBSPMP is solved by means of GGA considering picking devices with heterogeneous load capacity. For this, an encoding scheme is proposed to represent in a chromosome the orders assigned to batches, and batches assigned to picking devices. Likewise, the operators of the proposed algorithm are adapted to the specific requirements of the OBSPMP. Computational experiments show that the GGA performs much better than six order batching and sequencing heuristics, leading to function objective savings of 18.3% on average. As a conclusion, the proposed algorithm provides feasible solutions for the operations planning in warehouses and distribution centers, improving margins by reducing operating time for order pickers, and improving customer service by reducing picking service times.
A novel weather parameters prediction scheme and their effects on crops Naveen Lingaraju; Hosaagrahara Savalegowda Mohan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp639-648

Abstract

Weather forecast is significantly imperative in today’s smart technological world. A precise forecast model entails a plentiful data in order to attain the most accurate predictions. However, a forecast of future rainfall from historical data samples has always been challenging and key area of research. Hence, in modern weather forecasting a combo of computer models, observation, and knowledge of trends and patterns are introduced. This research work has presented a fitness function based adaptive artificial neural network scheme in order to forecast rainfall and temperature for upcoming decade (2021-2030) using historical weather data of 20 different districts of Karnataka state. Furthermore, effects of these forecasted weather parameters are realized over five major crops of Karnataka namely rice, wheat, jowar, maize, and ragi with the intention of evaluation for efficient crop management in terms of the passing relevant messages to the farmers and alternate measures such as suggesting other geographical locations to grow the same crop or growing other suitable crops at same geographical location. A graphical user interface (GUI) application has been developed for the proposed work in order to ease out the flow of work.
Design and implementation of speech recognition system integrated with internet of things Ademola Abdulkareem; Tobiloba E. Somefun; Oji K. Chinedum; Felix Agbetuyi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1796-1803

Abstract

The process of speech recognition is such that a speech signal from a client or user is received by the system through a microphone, then the system analyses this signal and extracts useful information from the signal which is converted to text. This study focuses on the design and implementation of a speech recognition system integrated with internet of thing (IoT) to control electrical appliances and door with raspberry pi as a core element. To design the speech recognition system, digital signal processing (DSP) technique and hidden Markov model were fully considered for processing, extraction and high predictive accuracy of the system. The Google application programming interface (API) was used as a cloud server to store command and give the system to assess to the internet. With 150 speech samples on the system, a high level of accuracy of over 80% was obtained.
An adaptive multi-hop routing with IoT abstraction for minimizing delay-node capacity trade-offs in mobile ad-hoc network Haitham Shiaibth Chasib; Saddam Raheem Salih; Israa Jaber Khalaf Al-Ogaili
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5315-5326

Abstract

Delay and node capacity are incompatible mobile ad hoc constraints because of the network's versatility and self-disciplined design. It is a challenging problem to maximize the trade-off between the above mobility correlation factors. This manuscript proposes an adaptive multi-hop routing (A.M.R.) for mobile ad-hoc network (MANET) to minimize the trade-off by integrating the internet of things (IoT). IoT nodes' smart computing and offloading abilities are extended to ad-hoc nodes to improve routing and transmission. Dor MANET nodes in route exploration, neighbor selection, and data transmission, the beneficial features of IoT include enhanced decision making. The traditional routing protocols use IoT at the time of the neighbor discovery process in updating the routing table and localization. The harmonizing technologies with their extended support improve the performance of MANETs has been estimated. The proposed method achieves better throughput (14.16 Mbps), delay (0.118), packet drop (126), and overhead (36 packets) when compared to existing methods.
Selecting the best stochastic systems for large scale engineering problems Mahmoud H. Alrefaei; Mohammad H. Almomani; Sarah N. Alabed Alhadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4289-4299

Abstract

Selecting a subset of the best solutions among large-scale problems is an important area of research. When the alternative solutions are stochastic in nature, then it puts more burden on the problem. The objective of this paper is to select a set that is likely to contain the actual best solutions with high probability. If the selected set contains all the best solutions, then the selection is denoted as correct selection. We are interested in maximizing the probability of this selection; P(CS). In many cases, the available computation budget for simulating the solution set in order to maximize P(CS) is limited. Therefore, instead of distributing these computational efforts equally likely among the alternatives, the optimal computing budget allocation (OCBA) procedure came to put more effort on the solutions that have more impact on the selected set. In this paper, we derive formulas of how to distribute the available budget asymptotically to find the approximation of P(CS). We then present a procedure that uses OCBA with the ordinal optimization (OO) in order to select the set of best solutions. The properties and performance of the proposed procedure are illustrated through a numerical example. Overall results indicate that the procedure is able to select a subset of the best systems with high probability of correct selection using small number of simulation samples under different parameter settings.
A review of intelligent methods for condition monitoring and fault diagnosis of stator and rotor faults of induction machines Omar Alshorman; Ahmad Alshorman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp2820-2829

Abstract

Nowadays, induction motor (IM) is extensively used in industry, including mechanical and electrical applications. However, three main types of IM faults have been discussed in the literature, bearing, stator, and rotor. Importantly, stator and rotor faults represent approximately 50%. Traditional condition monitoring (CM) and fault diagnosis (FD) methods require a high processing cost and much experience knowledge. To tackle this challenge, artificial intelligent (AI) based CM and FD techniques are extensively developed. However, there have been many review research papers for intelligent CM and FD machine learning methods of rolling elements bearings of IM in the literature. Whereas there is a lack in the literature, and there are not many review papers for both stator and rotor intelligent CM and FD. Thus, the proposed study's main contribution is in reviewing the CM and FD of IM, especially for the stator and the rotor, based on AI methods. The paper also provides discussions on the main challenges and possible future works.
Smart system for maintaining aquascape environment using internet of things based light and temperature controller Daniel Patricko Hutabarat; Rudy Susanto; Bryan Prasetya; Barry Linando; Senanayake Mudiyanselage Namal Senanayake
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp896-902

Abstract

The purpose of this research is to create a smart system based on internet of things (IoT) application for a plant aquarium. This smart system helps users to maintain the environment's parameters of the plant aquarium. In this study, the parameters to be controlled by the system are light intensity and temperature. The hardware used to develop this system is the ESP32 as the microcontroller, BH1750FVI as the light sensor, high power led (HPL) light-emitting diodes (LED) lamp as the light source, DS18B20 as temperature sensor, the heater, and the 220 VAC fan that is used to raise and lower the temperature. In this study also developed an application that is used by the user to provide input to the system. The developed application is then installed on the user's smartphone and used to connect the user to the system via the internet. The ease of adding and removing devices used on the system is a capability that is also being developed in this smart system. The developed system can produce light intensity with accuracy rate of 96% and always manage to keep the temperature within the predetermined range.
High speed modified carry save adder using a structure of multiplexers Ahmed Salah Hameed; Marwa Jawad Kathem
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1591-1598

Abstract

Adders are the heart of data path circuits for any processor in digital computer and signal processing systems. Growth in technology keeps supporting efficient design of binary adders for high speed applications. In this paper, a fast and area-efficient modified carry save adder (CSA) is presented. A multiplexer based design of full adder is proposed to implement the structure of the CSA. The proposed design of full adder is employed in designing all stages of traditional CSA. By modifying the design of full adder in CSA, the complexity and area of the design can be reduced, resulting in reduced delay time. The VHDL implementations of CSA adders including (the proposed version, traditional CSA, and modified CSAs presented in literature) are simulated using Quartus II synthesis software tool with the altera FPGA EP2C5T144C6 device (Cyclone II). Simulation results of 64-bit adder designs demonstrate the average improvement of 17.75%, 1.60%, and 8.81% respectively for the worst case time, thermal power dissipation and number of FPGA logic elements.
An improvement and a fast DSP implementation of the bit flipping algorithms for low density parity check decoder Mouhcine Razi; Mhammed Benhayoun; Anass Mansouri; Ali Ahaitouf
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4774-4784

Abstract

For low density parity check (LDPC) decoding, hard-decision algorithms are sometimes more suitable than the soft-decision ones. Particularly in the high throughput and high speed applications. However, there exists a considerable gap in performances between these two classes of algorithms in favor of soft-decision algorithms.  In order to reduce this gap, in this work we introduce two new improved versions of the hard-decision algorithms, the adaptative gradient descent bit-flipping (AGDBF) and adaptative reliability ratio weighted GDBF (ARRWGDBF).  An adaptative weighting and correction factor is introduced in each case to improve the performances of the two algorithms allowing an important gain of bit error rate. As a second contribution of this work a real time implementation of the proposed solutions on a digital signal processors (DSP) is performed in order to optimize and improve the performance of these new approchs. The results of numerical simulations and DSP implementation reveal a faster convergence with a low processing time and a reduction in consumed memory resources when compared to soft-decision algorithms. For the irregular LDPC code, our approachs achieves gains of 0.25 and 0.15 dB respectively for the AGDBF and ARRWGDBF algorithms.

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