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International Journal of Electrical and Computer Engineering

IJECE
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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 115 Documents

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Search results for , issue "Vol 10, No 4: August 2020" : 115 Documents clear

Electromagnetic pollution maps as a resource for assessing the risk of emissions from mobile communications antennas Yeison Alberto Garces-Gomez; Vladimir Henao-Cespedes; Luis Fernando Diaz-Cadavid
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Electromagnetic pollution has taken on importance in recent decades, as interest is growing in knowing how the proliferation of mobile communication devices can affect the environment and generate health problems in the population. In this document, a systematic review of the methodologies for measuring electromagnetic radiation is carried out with a view to generating pollution profiles. It also develops a novel methodology for measuring electromagnetic pollution (EMP) in urban areas, and is validated with a case study using a map of EMP in the city of Manizales (Colombia), determining the spatial distribution of radiation levels. In order to generate the map, EMP measurements were carried out in the bands of local mobile telephone operators, in addition to the LPWAN (low power wide area network) LoRaWAN and Sigfox networks, Wi-Fi, and those related to IoT technologies.

Vertical intent prediction approach based on Doc2vec and convolutional neural networks for improving vertical selection in aggregated search Sanae Achsas; El Habib Nfaoui
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Vertical selection is the task of selecting the most relevant verticals to a given query in order to improve the diversity and quality of web search results. This task requires not only predicting relevant verticals but also these verticals must be those the user expects to be relevant for his particular information need. Most existing works focused on using traditional machine learning techniques to combine multiple types of features for selecting several relevant verticals. Although these techniques are very efficient, handling vertical selection with high accuracy is still a challenging research task. In this paper, we propose an approach for improving vertical selection in order to satisfy the user vertical intent and reduce user’s browsing time and efforts. First, it generates query embeddings vectors using the doc2vec algorithm that preserves syntactic and semantic information within each query. Secondly, this vector will be used as input to a convolutional neural network model for increasing the representation of the query with multiple levels of abstraction including rich semantic information and then creating a global summarization of the query features. We demonstrate the effectiveness of our approach through comprehensive experimentation using various datasets. Our experimental findings show that our system achieves significant accuracy. Further, it realizes accurate predictions on new unseen data.

Discrete penguins search optimization algorithm to solve flow shop scheduling problem Ilyass Mzili; Mohammed Essaid Riffi; Fatiha Benzakri
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (558.535 KB)

Flow shop scheduling problem is one of the most classical NP-hard optimization problem. Which aims to find the best planning that minimizes the makespan (total completion time) of a set of tasks in a set of machines with certain constraints. In this paper, we propose a new nature inspired metaheuristic to solve the flow shop scheduling problem (FSSP), called penguins search optimization algorithm (PeSOA) based on collaborative hunting strategy of penguins.The operators and parameter values of PeSOA redefined to solve this problem. The performance of the penguins search optimization algorithm is tested on a set of benchmarks instances of FSSP from OR-Library, The results of the tests show that PeSOA is superior to some other metaheuristics algorithms, in terms of the quality of the solutions found and the execution time.

Local feature extraction based facial emotion recognition: a survey Khadija Slimani; Mohamed Kas; Youssef El Merabet; Yassine Ruichek; Rochdi Messoussi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Notwithstanding the recent technological advancement, the identification of facial and emotional expressions is still one of the greatest challenges scientists have ever faced. Generally, the human face is identified as a composition made up of textures arranged in micro-patterns. Currently, there has been a tremendous increase in the use of local binary pattern based texture algorithms which have invariably been identified to being essential in the completion of a variety of tasks and in the extraction of essential attributes from an image. Over the years, lots of LBP variants have been literally reviewed. However, what is left is a thorough and comprehensive analysis of their independent performance. This research work aims at filling this gap by performing a large-scale performance evaluation of 46 recent state-of-the-art LBP variants for facial expression recognition. Extensive experimental results on the well-known challenging and benchmark KDEF, JAFFE, CK and MUG databases taken under different facial expression conditions, indicate that a number of evaluated state-of-the-art LBP-like methods achieve promising results, which are better or competitive than several recent state-of-the-art facial recognition systems. Recognition rates of 100%, 98.57%, 95.92% and 100% have been reached for CK, JAFFE, KDEF and MUG databases, respectively.

Advanced energy management system with the incorporation of novel security features Raheel Muzzammel; Rabia Arshad; Saba Mehmood; Danista Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Nowadays, energy management is a subject of great importance and complexity. Pakistan, being in a state of developing country, generates electrical power mainly by using non-renewable sources of energy. Non-renewable entities are fossil fuels such as furnace oil, natural gas, coal, and nuclear power. Pakistan has been facing a severe shortage of production in energy sector for last two decades. This shortfall is affecting the industrial development as well as economic growth. With the growing population, the load demand is rapidly increasing and there must be a need to expand the existing ones or to build new power systems. In this paper, an autonomous management system has been proposed to enhance quality, reliability and confidence of utilization of energy between end consumers and suppliers. Such objectives can only be fulfilled by making the power supply secure for end consumers. Distributed and centralized control systems are involved for maintaining a balance between renewable energy resources and base power, so that end consumers demand can be fulfilled when required. A reliable Two-way communication system between suppliers and end consumers has been proposed by using Message Digest algorithm which ensures that there would be no energy theft. Simulations have been done in MATLAB/ Simulink environment and results have been presented to show the effectiveness of the proposed model.

Self-checking method for fault tolerance solution in wireless sensor network Muayad Sadik Croock; Saja Dhyaa Khuder; Zahraa Abbas Hassan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

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.

Internet service providers responsibilities in botnet mitigation: a Nigerian perspective Julius Olatunji Okesola; Marion Adebiyi; Tochukwu Osi-Okeke; Adeyinka Adewale; Ayodele Adebiyi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Botnet-based attack is dangerous and extremely difficult to overcome as all the primary mitigation methods are passive and limited in focus. A combine efforts of Internet Service Providers (ISPs) are better guides since they can monitor the traffic that traverse through their networks. However, ISPs are not legally banded to this role and may not view security as a primary concern. Towards understudying the involvement of ISPs in Botnet mitigation in Nigeria, this study elicited and summarized mitigation measures from scientific literatures to create a reference model which was validated by structured interview. Although, ISPs role is seen to be voluntary and poorly incentivized, the providers still take customers security very serious but concentrate more on preventive and notification measures.

Design an active verification mechanism for certificates revocation in OCSP for internet authentication Khalid Fazaa Mahmmod; Mohammed Muzahem Azeez; Zeyad Hashem Ismael
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

No doubt that data security online is crucial. Therefore, great attention has been paid to that aspect by companies and organizations given its economic and social implications. Thus, online certificate status protocol (OCSP) is considered one of the most prominent protocol functioning in this field, which offers a prompt support for certificates online. In this research, a model designed based on field programable gate array (FPGA) using Merkel’s tree has been proposed to overcome the delay that might have occurred in sorting and authentication of certificates. Having adopted this model and with the assistance of Hash function algorithm, more than 50% of certificates have been processed in comparison with standard protocol. Moreover, certificates have been provided with substantial storage space with high throughput. Basically, Hash function algorithm has been designed to arrange and specify a site of verified or denied certificates within time of validity to protect servers from intrusion and clients from using applications with harmful contents.

Dynamic resource allocation for opportunistic software-defined IoT networks: stochastic optimization framework Sharhabeel H. Alnabelsi; Haythem A. Bany Salameh; Zaid M. Albataineh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Several wireless technologies have recently emerged to enable efficient and scalable internet-of-things (IoT) networking. Cognitive radio (CR) technology, enabled by software-defined radios, is considered one of the main IoT-enabling technologies that can provide opportunistic wireless access to a large number of connected IoT devices. An important challenge in this domain is how to dynamically enable IoT transmissions while achieving efficient spectrum usage with a minimum total power consumption under interference and traffic demand uncertainty. Toward this end, we propose a dynamic bandwidth/channel/power allocation algorithm that aims at maximizing the overall network’s throughput while selecting the set of power resulting in the minimum total transmission power. This problem can be formulated as a two-stage binary linear stochastic programming. Because the interference over different channels is a continuous random variable and noting that the interference statistics are highly correlated, a suboptimal sampling solution is proposed. Our proposed algorithm is an adaptive algorithm that is to be periodically conducted over time to consider the changes of the channel and interference conditions. Numerical results indicate that our proposed algorithm significantly increases the number of simultaneous IoT transmissions compared to a typical algorithm, and hence, the achieved throughput is improved.

Comparison between handwritten word and speech record in real-time using CNN architectures Javier Orlando Pinzón-Arenas; Robinson Jiménez-Moreno
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents the development of a system of comparison between words spoken and written by means of deep learning techniques. There are used 10 words acquired by means of an audio function and, these same words, are written by hand and acquired by a webcam, in such a way as to verify if the two data match and show whether or not it is the required word. For this, 2 different CNN architectures were used for each function, where for voice recognition, a suitable CNN was used to identify complete words by means of their features obtained with mel frequency cepstral coefficients, while for handwriting, a faster R-CNN was used, so that it both locates and identifies the captured word. To implement the system, an easy-to-use graphical interface was developed, which unites the two neural networks for its operation. With this, tests were performed in real-time, obtaining a general accuracy of 95.24%, allowing showing the good performance of the implemented system, adding the response speed factor, being less than 200 ms in making the comparison.

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Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

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Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA

Abstract

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

Phone -

Journal Mail Official ijece@iaesjournal.com

Editorial Address -

Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA