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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 116 Documents

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Search results for , issue "Vol 10, No 5: October 2020" : 116 Documents clear

Optimal scheduling of smart microgrids considering electric vehicle battery swapping stations J. Garcia -Guarin; W. Infante; J. Ma; D. Alvarez; S. Rivera
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Smart microgrids belong to a set of networks that operate independently. These networks have technologies such as electric vehicle battery swapping stations that aim to economic welfare with own resources of smart microgrids. These resources should support other services, for example, the supply of energy at peak hours. This study addresses the formulation of a decision matrix based on operating conditions of electric vehicles and examines economically viable alternatives for a battery swapping station. The decision matrix is implemented to manage the swapping, charging, and discharging of electric vehicles. Furthermore, this study integrates a smart microgrid model to assess the operational strategies of the aggregator, which can act like a prosumer by managing both electric vehicle battery swapping stations and energy storage systems. The smart microgrid model proposed includes elements used for demand response and generators with renewable energies. This model investigates the effect of the wholesale, local and electric-vehicle markets. Additionally, the model includes uncertainty issues related to the planning for the infrastructure of the electric vehicle battery swapping station, variability of electricity prices, weather conditions, and load forecasting. This article also analyzes how both the user and the providers maximize their economic benefits with the hybrid optimization algorithm called variable neighborhood search - differential evolutionary particle swarm optimization. The strategy to organize the infrastructure of these charging stations reaches a reduction of 72% in the overall cost. This reduction percentage is obtained calculating the random solution with respect to the suboptimal solution.

An energy optimization with improved QOS approach for adaptive cloud resources Danthuluri Sudha; Sanjay Chitnis
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (ACRR) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model ACRR in terms of average run time, power consumption and average power required than any other state-of-art techniques.

Low-cost and portable automatic sheet cutter Mohd Syafiq Mispan; Ahmad Haﬁzzudin Mustafa; Hafez Sarkawi; Aiman Zakwan Jidin
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Process automation is crucial to increase productivity, more efficient use of materials, better product quality, improved safety, etc. In small-medium enterprise (SME) businesses related to household retailing, one of the process automation needed is the measurement and cutting of the mat or sheet, made of rubber or polyvinyl chloride (PVC) materials. Most of the household retailers that selling the sheet, the process of measuring and cutting according to the customer’s requirements are manually performed using a measuring tape and scissors. These manual processes can cause inaccuracy in length, inefficient use of material, low productivity and reduce product quality. This paper presents a low cost and portable automatic sheet cutter using the Arduino development board, which is used to control the process of measuring and cutting the materials. The system uses a push-button where the user can set the required length and quantity of the sheet. Once the required information is set, the stepper motor rolls the sheet until the required length is satisfied. Subsequently, another stepper motor moves the cutter horizontally and cut the sheet. With the automatic sheet cutter, the material is cut with acceptable precision. The design of the automatic sheet cutter is low cost and portable which significantly suitable to be used by SME household retailers.

A dynamic cruise control system (DCCS) for effective navigation system T. Someswari; Anil Kumar Tiwari; Nagraj R
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

With the fast development of artificial intelligence, robotics, and embedded system along with sensor technologies, the speed control mechanism is required in various other applications such as automatic or self-piloting aircraft, auto-driven vehicles, auto driven lifts and much other robotics based automation plants, etc. For each unpredictable and progressed vehicular framework accompanies a better route that is fit for utilizing the two GPS and INS related sign. There have been a noteworthy number of research works being completed towards creating sliding mode control framework. In case of inaccurate navigational data or no availability of navigational service, the cruise control could also stop working. Hence, there is a need to evolve up with a novel system offering reliable and fault tolerant navigation system in order to minimize the dependencies on GPS-based information and maximize the utilization of INS based information. This manuscript presents a dynamic cruise control system to achieve better navigation under uncertainties. The performance of the system is analyzed by incorporating sliding mode and fuzzy logic and achieves better accuracy in tracking error, computational complexity (28 sec of simulation time) under chattering and switching action operation.

Sentimental classification analysis of polarity multi-view textual data using data mining techniques Ali Hameed Yassir; Ali A. Mohammed; Adel Abdul-Jabbar Alkhazraji; Mustafa Emad Hameed; Mohammed Saad Talib; Mohanad Faeq Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics.

Islanded microgrid congestion control by load prioritization and shedding using ABC algorithm L. O. Mogaka; G. N. Nyakoe; Michael J. Saulo
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

The continued growth in load demand and the gradual change of generation sources to smaller distributed plants utilizing renewable energy sources (RESs), which supply power intermittently, is likely to strain existing power systems and cause congestion. Congestion management still remains a challenging issue in open access transmission and distribution systems. Conventionally, this is achieved by load shedding and generator rescheduling. In this study, the control of the system congestion on an islanded micro grid (MG) supplied by RESs is analyzed using artificial bee colony (ABC) algorithm. Different buses are assigned priority indices which forms the basis of the determination of which loads and what amount of load to shed at any particular time during islanding mode operation. This is to ensure as minimal load as possible is shed during a contingency that leads to loss of mains and ensure a congestion free microgrid operation. This is tested and verified on a modified IEEE 30-bus distribution systems on MATLAB platform. The results are compared with other algorithms to prove the applicability of this approach.

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Tole Sutikno

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Home Page

OAI Link

Editorial Team

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Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

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