International Journal of Electrical and Computer 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.
Articles
6,393 Documents
The students’ acceptance of learning management systems in Saudi Arabian Universities
Mutasem K. Alsmadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i4.pp4155-4161
For distance learners, continuous official education is very important for improving knowledge and learning experience in order to meet the career challenges in the modern world. This work studies the success factors which affect the use of LMS and evaluates the ability to apply the proposed model in the field of distance learning (DL) particularly in higher education. The survey was carried out on higher education learners who were included in the DL instructions. This work has utilized a questionnaire that was modified from literature to inspect three measurements, system design, system usage, and system outcome. Utilizing the obtained survey data for students of DL (N=149), the path analysis discovered that the design of the system has a significant effect on the satisfaction of users and intention for using LMS which affects the use of the system. Consequently, the satisfaction of users and the system used has a great impact on the net benefit.
Comparison study of machine learning classifiers to detect anomalies
Nisha P Shetty;
Jayashree Shetty;
Rohil Narula;
Kushagra Tandona
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp5445-5452
In this era of Internet ensuring the confidentiality, authentication and integrity of any resource exchanged over the net is the imperative. Presence of intrusion prevention techniques like strong password, firewalls etc. are not sufficient to monitor such voluminous network traffic as they can be breached easily. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database.Thus, the need for real-time detection of aberrations is observed. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database. Machine learning classifiers are implemented here to learn how the values of various fields like source bytes, destination bytes etc. in a network packet decides if the packet is compromised or not . Finally the accuracy of their detection is compared to choose the best suited classifier for this purpose. The outcome thus produced may be useful to offer real time detection while exchanging sensitive information such as credit card details.
Multicast routing strategy for SDN-cluster based MANET
Jaber Ibrahim Naser;
Ahmed Jawad Kadhim
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp4447-4457
The energy limitation and frequent movement of the mobile Ad hoc network (MANET) nodes (i.e., devices) make the routing process very difficult. The multicast routing problem is one of the NP-complete problems. Therefore, the need for a new power-aware approach to select an optimum multicast path with minimum power consumption that can enhance the performance and increase the lifetime of MANET has become urgent. Software defined network (SDN) is a new technique that can solve many problems of the traditional networks by dividing the architecture into data part and control part. This paper presents three power-aware multicast routing strategies for MANET. First one called a Reactive Multicast routing strategy for cluster based MANET by using SDN (RMCMS), second one called proactive multicast routing strategy for cluster based MANET by using SDN (PMCMS) and third one represents modification of PMCMS called M-PMCMS. Moreover, it produces a new mathematical model to build a multicast tree with minimum power consumption and takes into account the remaining power in each node. All proposed multicast strategies operate based on this mathematical model and aim to maximize the MANET lifetime by exploiting the advantages of SDN and clustering concepts. They consider the multicast tree with minimum power consumption as an optimal one. The simulation results illustrated that RMCMS is better than PMCMS, M-PMCMS, and MAODV in terms of power consumption and network overhead while M-PMCMS is the best one in terms of dropped packets ratio (DPR) and average end to end (E2E) delay.
An adaptive anomaly request detection framework based on dynamic web application profiles
Cho Do Xuan;
Nam Nguyen;
Hoa Nguyen Dinh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp5335-5346
Web application firewall is a highly effective application in protecting the application layer and database layer of websites from attack access. This paper proposes a new web application firewall deploying method based on Dynamic Web application profiling (DWAP) analysis technique. This is a method to deploy a firewall based on analyzing website access data. DWAP is improved to integrate deeply into the structure of the website to increase the compatibility of the anomaly detection system into each website, thereby improving the ability to detect abnormal requests. To improve the compatibility of the web application firewall with protected objects, the proposed system consists of two parts with the main tasks are: i) Detect abnormal access in web application (WA) access; ii) Semi-automatic update the attack data to the abnormal access detection system during WA access. This new method is applicable in real-time detection systems where updating of new attack data is essential since web attacks are increasingly complex and sophisticated.
Analysis of back propagation and radial basis function neural networks for handover decisions in wireless communication
Payal Mahajan;
Zaheeruddin Zaheeruddin
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp4835-4843
In mobile systems, handoff is a vital process, referring to a process of allocating an ongoing call from one BS to another BS. The handover technique is very important to maintain the Quality of service. Handover algorithms, based on neural networks, fuzzy logic etc. can be used for the same purpose to keep Quality of service as high as possible. In this paper, it is proposed that back propagation networks and radial basis functions may be used for taking handover decision in wireless communication networks. The performance of these classifiers is evaluated on the basis of neurons in hidden layer, training time and classification accuracy. The proposed approach shows that radial basis function neural network give better results for making handover decisions in wireless heterogeneous networks with classification accuracy of 90%.
Comparative study on machine learning algorithms for early fire forest detection system using geodata
Zouiten Mohammed;
Chaaouan Hanae;
Setti Larbi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp5507-5513
Forest fires have caused considerable losses to ecologies, societies and economies worldwide. To minimize these losses and reduce forest fires, modeling and predicting the occurrence of forest fires are meaningful because they can support forest fire prevention and management. In recent years, the convolutional neural network (CNN) has become an important state-of-the-art deep learning algorithm, and its implementation has enriched many fields. Therefore, a competitive spatial prediction model for automatic early detection of wild forest fire using machine learning algorithms can be proposed. This model can help researchers to predict forest fires and identify risk zonas. System using machine learning algorithm on geodata will be able to notify in real time the interested parts and authorities by providing alerts and presenting on maps based on geographical treatments for more efficacity and analyzing of the situation. This research extends the application of machine learning algorithms for early fire forest prediction to detection and representation in geographical information system (GIS) maps.
CL-SA-OFDM: Cross-layer and smart antenna based OFDM system performance enhancement
Shivapanchakshari T. G.;
H. S. Aravinda
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp4663-4670
The growing usage of wireless services is lacking in providing high-speed data communication in recent times. Hence, many of the modulation techniques are evolved to attain these communication needs. The recent researches have widely considered OFDM technology as the prominent modulation mechanism to fulfill the futuristic needs of wireless communication. The OFDM can bring effective usage of resources, bandwidth, and system performance enhancement in collaboration with the smart antenna and resource allocation mechanism (adaptive). However, the usage of adaptive beamforming with the OFDM leads to complication in the design of medium access layer and which causes a problem in adaptive resource allocation mechanism (ARAM). Hence, the proposed manuscript intends to design an OFDM system by considering different switched beam smart antenna (SBSA) along with the cross-layer adaptive resource allocation (CLARA) and hybrid adaptive array (HAA). In this, various smart antenna mechanism are considered to analyze the quality of service (QoS) and complexity reduction in the OFDM system. In this paper, various SA schemes are used as per the quality of service (QoS) requirement of the different users. The performance analysis is conducted by considering data traffic reduction, bit-rate reduction, and average delay.
Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms
Thuan Thanh Nguyen;
Van-Duc Phan;
Bach Hoang Dinh;
Tan Minh Phan;
Thang Trung Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp5123-5130
In this paper, Cuckoo search algorithm (CSA) is suggested for determining optimal operation parameters of the combined wind turbine and hydrothermal system (CWHTS) in order to minimize total fuel cost of all operating thermal power plants while all constraints of plants and system are exactly satisfied. In addition to CSA, Particle swarm optimization (PSO), PSO with constriction factor and inertia weight factor (FCIWPSO) and Social Ski-Driver (SSD) are also implemented for comparisons. The CWHTS is optimally scheduled over twenty-four one-hour interval and total cost of producing power energy is employed for comparison. Via numerical results and graphical results, it indicates CSA can reach much better results than other ones in terms of lower total cost, higher success rate and faster search process. Consequently, the conclusion is confirmed that CSA is a very efficient method for the problem of determining optimal operation parameters of CWHTS.
An efficient hardware logarithm generator with modified quasi-symmetrical approach for digital signal processing
Minh-Hong Nguyen
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i5.pp4671-4678
This paper presents a low-error, low-area FPGA-based hardware logarithm generator for digital signal processing systems which require high-speed, real time logarithm operations. The proposed logarithm generator employs the modified quasi-symmetrical approach for an efficient hardware implementation. The error analysis and implementation results are also presented and discussed. The achieved results show that the proposed approach can reduce the approximation error and hardware area compared with traditional methods.
An analysis of software aging in cloud environment
Shruthi P.;
Nagaraj G. Cholli
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i6.pp5985-5991
Cloud Computing is the environment in which several virtual machines (VM) run concurrently on physical machines. The cloud computing infrastructure hosts multiple cloud service segments that communicate with each other using the interfaces. This creates distributed computing environment. During operation, the software systems accumulate errors or garbage that leads to system failure and other hazardous consequences. This status is called software aging. Software aging happens because of memory fragmentation, resource consumption in large scale and accumulation of numerical error. Software aging degrads the performance that may result in system failure. This happens because of premature resource exhaustion. This issue cannot be determined during software testing phase because of the dynamic nature of operation. The errors that cause software aging are of special types. These errors do not disturb the software functionality but target the response time and its environment. This issue is to be resolved only during run time as it occurs because of the dynamic nature of the problem. To alleviate the impact of software aging, software rejuvenation technique is being used. Rejuvenation process reboots the system or re-initiates the softwares. This avoids faults or failure. Software rejuvenation removes accumulated error conditions, frees up deadlocks and defragments operating system resources like memory. Hence, it avoids future failures of system that may happen due to software aging. As service availability is crucial, software rejuvenation is to be carried out at defined schedules without disrupting the service. The presence of Software rejuvenation techniques can make software systems more trustworthy. Software designers are using this concept to improve the quality and reliability of the software. Software aging and rejuvenation has generated a lot of research interest in recent years. This work reviews some of the research works related to detection of software aging and identifies research gaps.