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29,939 Article Results

Voltage stability enhancement for large scale squirrel cage induction generator based wind turbine using STATCOM

10.11591/ijpeds.v12.i3.pp1784-1794
Abedalgany Athamneh , Bilal Al Majali
A stable operation of wind turbines connected to the grid is an essential requirement to ensure the reliability and stability of the power system. To achieve such operational objective, installing static synchronous compensator static synchronous compensator (STATCOM) as a main compensation device guarantees the voltage stability enhancement of the wind farm connected to distribution network at different operating scenarios. STATCOM either supplies or absorbs reactive power in order to ensure the voltage profile within the standard-margins and to avoid turbine tripping, accordingly. This paper present new study that investigates the most suitable-location to install STATCOM in a distribution system connected wind farm to maintain the voltage-levels within the stability margins. For a large-scale squirrel cage induction generator squirrel-cage induction generator (SCIG-based) wind turbine system, the impact of STATCOM installation was tested in different places and voltage-levels in the distribution system. The proposed method effectiveness in enhancing the voltage profile and balancing the reactive power is validated, the results were repeated for different scenarios of expected contingencies. The voltage profile, power flow, and reactive power balance of the distribution system are observed using MATLAB/Simulink software. 
Volume: 12
Issue: 3
Page: 1784-1794
Publish at: 2021-09-01

Fraudulent credit card transaction detection using soft computing techniques

10.11591/ijeecs.v23.i3.pp1634-1642
Aishwarya Priyadarshini , Sanhita Mishra , Debani Prasad Mishra , Surender Reddy Salkuti , Ramakanta Mohanty
Nowadays, fraudulent or deceitful activities associated with financial transactions, predominantly using credit cards have been increasing at an alarming rate and are one of the most prevalent activities in finance industries, corporate companies, and other government organizations. It is therefore essential to incorporate a fraud detection system that mainly consists of intelligent fraud detection techniques to keep in view the consumer and clients’ welfare alike. Numerous fraud detection procedures, techniques, and systems in literature have been implemented by employing a myriad of intelligent techniques including algorithms and frameworks to detect fraudulent and deceitful transactions. This paper initially analyses the data through exploratory data analysis and then proposes various classification models that are implemented using intelligent soft computing techniques to predictively classify fraudulent credit card transactions. Classification algorithms such as K-Nearest neighbor (K-NN), decision tree, random forest (RF), and logistic regression (LR) have been implemented to critically evaluate their performances. The proposed model is computationally efficient, light-weight and can be used for credit card fraudulent transaction detection with better accuracy.
Volume: 23
Issue: 3
Page: 1634-1642
Publish at: 2021-09-01

Gait cycle prediction model based on gait kinematic using machine learning technique for assistive rehabilitation device

10.11591/ijai.v10.i3.pp752-763
Che Ani Adi Izhar , Z. Hussain , M. I. F. Maruzuki , Mohd Suhaimi Sulaiman , A. A. Abd. Rahim
The gait cycle prediction model is critical for controlling assistive rehabilitation equipment like orthosis. The human gait model has recently used statistical models, but the dynamic properties of human physiology limit the current approach. Current human gait cycle prediction models need detailed kinematic and kinetic data of the human body as input parameters, and measuring them requires special instruments, making them difficult to use in real-world applications. In our study, three separate machine learning algorithms were used to create a human gait model: Gaussian process regression, support vector machine, and decision tree. The algorithm used to create the model's input parameters are height, weight, hip and knee angle, and ground reaction force (GRF). For better gait cycle model prediction, the models produced were enhanced by incorporating different sliding window data. The best gait period prediction model was DT with sliding window data (t−3), which had a root mean square error of 3.3018 and the R-squared (R-Value) of 0.97. The projection model focused on hip and knee angle and GRF was a feasible solution to controlling assistive rehabilitation devices during the gait cycle.
Volume: 10
Issue: 3
Page: 752-763
Publish at: 2021-09-01

Integration of artificial neural networks for multi-source energy management in a smart grid

10.11591/ijpeds.v12.i3.pp1919-1927
Eziitouni Jarmouni , Ahmed Mouhsen , Mohammed Lamhammedi , Hicham Ouldzira
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
Volume: 12
Issue: 3
Page: 1919-1927
Publish at: 2021-09-01

Development of site-specific non-intrusive load monitoring for maximum demand control

10.11591/ijeecs.v23.i3.pp1814-1824
Azharudin Mukhtaruddin , Fakroul Ridzuan Hashim , Mat Kamil Awang , Husin Mamat , Hafizi Zakaria
Demand-side load management (DSM) requires greater role-play by end-users. To lower the investment for this load management concept, non-intrusive load management (NILM) was introduced as the solution. However, most of the mathematical techniques used in NILM are complex. This may hinder users from actively take part in the energy management effort. This paper explores the possibilities of applying change point detection techniques with help of differentiation and application of filters. These filters were selected strictly based on site-specific conditions. As part of the NILM implementation, a new and practical technique was developed for this paper. It was found that the developed technique, despite its simplicity it can identify the electrical equipment which added the significant load demand. The performance of the technique was found to be satisfactory as compared to results reported by other researchers.
Volume: 23
Issue: 3
Page: 1814-1824
Publish at: 2021-09-01

Effect of electrical discharge on the properties of natural esters insulating fluids

10.11591/ijeecs.v23.i3.pp1281-1288
Imran Sutan Chairul , Sharin Ab Ghani , Nur Hakimah Ab Aziz , Mohd Shahril Ahmad Khiar , Muhammad Syahrani Johal , Mohd Aizzat Azmi
Vegetable oils have been an alternative to mineral oil for oil-immersed transformers due to concern on less flammable, environmental-friendly, biodegradable, and sustainable resources of petroleum-based insulating oil. This paper presents the effect of electrical discharges (200 up to 1000 discharges) under 50 Hz inhomogeneous electric field on the properties (acidity, water content, and breakdown voltage) of two varieties of vegetable based insulating oils; i) natural ester (NE) and ii) low viscosity insulating fluids derived from a natural ester (NELV). Results show the water content, acidity and breakdown voltage of NE fluctuate due to applied discharges, while NELV display insignificant changes. Hence, results indicate that the low viscosity insulating fluids derived from natural ester tend to maintain their properties compared to natural ester.
Volume: 23
Issue: 3
Page: 1281-1288
Publish at: 2021-09-01

Boyer Moore string-match framework for a hybrid short message service spam filtering technique

10.11591/ijai.v10.i3.pp519-527
Arnold Adimabua Ojugo , David Ademola Oyemade
Advances in technology and the proliferation of mobile device have continued to advance the ubiquitous nature of computing alongside their many prowess and improved features it brings as a disruptive technology to aid information sharing amongst many online users. This popularity, usage and adoption ease, mobility, and portability of the mobile smartphone devices have allowed for its acceptability and popularity. Mobile smartphones continue to adopt the use of short messages services accompanied with a scenario for spamming to thrive. Spams are unsolicited message or inappropriate contents. An effective spam filter studies are limited as short-text message service (SMS) are 140bytes, 160-characters, and rippled with abbreviation and slangs that further inhibits the effective training of models. The study proposes a string match algorithm used as deep learning ensemble on a hybrid spam filtering technique to normalize noisy features, expand text and use semantic dictionaries of disambiguation to train underlying learning heuristics and effectively classify SMS into legitimate and spam classes. Study uses a profile hidden Markov network to select and train the network structure and employs the deep neural network as a classifier network structure. Model achieves an accuracy of 97% with an error rate of 1.2%.
Volume: 10
Issue: 3
Page: 519-527
Publish at: 2021-09-01

Control of teleoperation systems in the presence of cyber attacks: A survey

10.11591/ijra.v10i3.pp235-260
Mutaz M. Hamdan , Magdi S. Mahmoud
The teleoperation system is often composed of a human operator, a local master manipulator, and a remote slave manipulator that are connected by a communication network. This paper proposes a survey on feedback control design for the bilateral teleoperation systems (BTSs) in nominal situations and in the presence of cyber-attacks. The main idea of the presented methods is to achieve the stability of a delayed bilateral teleoperation system in the presence of several kinds of cyber attacks. In this paper, a comprehensive survey on control systems for BTSs under cyber-attacks is discussed. Finally, we discuss the current and future problems in this field.
Volume: 10
Issue: 3
Page: 235-260
Publish at: 2021-09-01

Relationship between sources and manifestations of stress among faculty members in Isabela State University

10.11591/ijphs.v10i3.20832
Helena B. Florendo , Annaliza R. Hernando
Stress is inevitable in any workplace. Stressed teachers in every school are prone to exhaustion and commit errors. In the Philippines, few studies have been discussed due to stress among faculty members, especially in tertiary education. In this study, the researchers shed light on sources, manifestations, and levels of stress, and discovered the relationship between sources and their manifestations among faculty members of the eight colleges of the Isabela State University-Main Campus. Data were randomly collected from 165 respondents, through the Teacher Stress Inventory developed by Fimian. Data revealed that the main sources and manifestations of stress by the respondents were Work-related and Professional Investment, and Fatigue Manifestations. The level of stress among the respondents was moderate. Likewise, the sources and manifestations of stress were found significantly correlated to each other. Results of the study press on the development of a proposed Stress Management Program supportive and essential in managing and coping stress of the faculty member
Volume: 10
Issue: 3
Page: 465-471
Publish at: 2021-09-01

Application of DPC and DPC-GA to the dual-rotor wind turbine system with DFIG

10.11591/ijra.v10i3.pp224-234
Habib Benbouhenni
The work presents the dual-rotor wind energy conversion system (DRWECS) with a direct driven doubly-fed induction generator (DFIG). The system consists of a dual-rotor wind turbine (DRWT) with a DFIG, the grid side converter (GSC), and the machine side converter (MSC). To command the MSC, the direct power command (DPC) based on genetic algorithm (GA) and classical pulse width modulation (PWM) has been applied. To achieve the maximum power from the DRWT, the maximum powe point tracking (MPPT) technique has been used. The performed simulation studies confirmed the high performances of the DPC-GA contro method.
Volume: 10
Issue: 3
Page: 224-234
Publish at: 2021-09-01

The development of homogeneity psycho cognition learning strategy in physical education learning

10.11591/ijere.v10i3.21713
Albertus Fenanlampir , Marleny Leasa , John Rafafy Batlolona
Many future studies have been developed by scientists today in the form of methods, models, strategies, and techniques in improving student learning outcomes that are oriented to psychology and the development of students' intelligence. One of the latest innovations in learning offered in this study is the homogeneity psycho cognition (HPC) strategy. The research objective was to develop the latest learning strategies in physical education, sports, and health learning. This development research uses a 4D model consisting of four stages: define, design, develop, and disseminate to produce products in the form of an HPC learning strategy. This study involved 115 elementary school students in several sample schools in Ambon City as participants. This study found that the HPC learning strategy had been developed following the relevant development directions and procedures. The validation of the HPC strategy by experts indicates that the HPC strategy is feasible to implement with due regard to minor revisions. The results of small and medium-scale trials show that the HPC strategy can improve student learning outcomes.
Volume: 10
Issue: 3
Page: 1047-1059
Publish at: 2021-09-01

Internet of things based attendance system design and development in a smart classroom

10.11591/ijeecs.v23.i3.pp1432-1439
Dania Eridani , Eko Didik Widianto , Ike Pertiwi Windasari , Wildan Budi Bawono , Nadia Febrianita Gunarto
Attendance records are one of the main administrative roles on campuses. Therefore, several technologies can be used on an attendance system, including barcode, radio frequency identification (RFID), fingerprint, and faceprint. The main functions of attendance systems on campuses are mainly focused on how to obtain the attendee data list, store on the database, and display the list on the information system. This research proposes an attendance system in the smart classroom which supports the system’s previous activities as well as its integration with security and classroom management. In this system, the NodeMCU which was connected to the Wi-Fi router served as the controller, while the fingerspot revo FF-153BNC functioned as the system input. In addition, the database server was used to allocate attendee and classroom management data. This system is connected with the information system and classroom display unit, and component and system testing were applied in this research. The results showed that each system unit successfully integrated and managed the attendance, security, and classroom schedule.
Volume: 23
Issue: 3
Page: 1432-1439
Publish at: 2021-09-01

Increasing the operating depth of an autonomous underwater vehicle using an intelligent magnetic field

10.11591/ijra.v10i3.pp207-223
Ali Jebelli , Arezoo Mahabadi , Hicham Chaoui , Mustapha C. E. Yagoub
Designing and manufacturing a suitable body is one of the most effective factors in increasing the efficiency of autonomous underwater vehicles (AUVs). In fact, increasing the propulsive power of an AUV by reducing the frictional drag on its body and increasing its maneuverability will positively affect key parts of the AUV’s hardware and software such as control system, sensors, AUV vision, batteries and thrusters. On the other hand, a suitable body should have features such as lightness, underwater vehicle’s balance, high mechanical strength, and enough space for equipment. Therefore, the design and manufacture of the body requires a lot of analysis in terms of body material, aerodynamic calculations, etc., increases the overall cost. This paper aims to reduce the stress in the body of a Polytetrafluoroethylene (PTFE) underwater robot and to increase its operating depth without changing the body’s structure by using fuzzy logic to intelligently controlling the magnetic force generated by the repulsion between the coil and the cylindrical magnet, which saves energy, reduces battery consumption, and increases system performance. The results show that the robot performance depth increases by more than 50% without changing the robot body structure.
Volume: 10
Issue: 3
Page: 207-223
Publish at: 2021-09-01

Technical study of the effect of laser engraving using uArm swift pro robot

10.11591/ijra.v10i3.pp182-191
Soumen Mondal , Ajoy Kumar Dutta
Laser engraving is the most non - traditional and efficient working method in the machining of materials of different geometry as compared to conventional methods. The main objective of this study is to determine the impact of uArm swift pro robot operated laser engraving process on a wooden pitch board piece. However, the robot was connected with uArm Studio 1.1.22 software to perform laser engraving operation. For this purpose the effect of process parameters like spot diameter and depth of penetration were investigated with different working length of the robot end effector, measured from wooden pitch board base. Experimental observation method was used to investigate the formation of deep and light engraving pattern on the pitch board surface by measuring penetration depth and spot diameter in suitable condition. The result obtained from the experiment and statistical parameters showed a new dimension to find a suitable working length of the robot assisted laser nozzle where the laser penetration effect was clearly perceptible for the wooden material.
Volume: 10
Issue: 3
Page: 182-191
Publish at: 2021-09-01

Development of a dynamic intelligent recognition system for a real-time tracking robot

10.11591/ijra.v10i3.pp161-169
Thair Ali Salih , Mohammed Talal Ghazal , Zaid Ghanim Mohammed
Nowadays, the development of computer vision technology help to overcome track and identify humans within a location in the complex environment through mobile robots, which gives the motivation to presents a vision-based approach to a mobile security robot. The proposed system utilizes a wireless camera to detect the objects in the field of robot view. Principle component analysis (PCA) algorithm and filters are used to implement and demonstrate the process of the images. This gives the designed system the ability to recognize objects independently from current light conditions. Frame tracking in the images uses an attention system to get an estimate of the position of a person. This estimate helps the applied camera to identify objects with changing background lighting conditions such as a fire inside a building. By using this estimate, the applied camera could identify objects with changing background lighting conditions such as a fire inside premises. The system has been tested using the MATLAB environment, and the empirical performance explains the efficiency and strongness of the suggested device.
Volume: 10
Issue: 3
Page: 161-169
Publish at: 2021-09-01
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