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29,922 Article Results

Development and validation of early childhood care and education pre-service lecturer instrument

10.11591/ijere.v9i1.20415
Shazlyn Milleana Shaharudin , Noorazrin Abd Rajak , Noor Wahida Md. Junus , Nor Azah Samat
This paper presents to develop and validate the Early Childhood Care and Pre-Service Lecturer Instrument constructed to determine their level of competencies toward the quality of early childhood carers-educators’ professionalism in Malaysia. Components which affect the early childhood quality were characterized through inclusive literature reviews alongside interviews conducted with experts and experienced lecturers. In this study, two experts were elected to review this instrument so as to enhance its validity while 70 more lecturers in Malaysia were involved. There are four scales in principal component analysis pertaining the quality of early childhood professionalism, namely: (1) disposition, (2) knowledge, (3) skills, and (4) practices. The component loading range or respective instrument item were between 0.56 and 0.79, while the range for respective scales the alpha reliability coefficient were between 0.90 and 0.94. Concisely, the findings from this study corroborated the weight and consistency of the ECCE Pre-Service Lecturer Instrument.
Volume: 9
Issue: 1
Page: 188-194
Publish at: 2020-03-01

Artificial neural network model and fuzzy logic control of dissolved oxygen in a bioreactor

10.11591/ijeecs.v17.i3.pp1289-1297
Nor Hana Mamat , Samsul Bahari Mohd Noor , Laxshan A/L Ramar , Azura Che Soh , Farah Saleena Taip , Ahmad Hazri Ab. Rashid
In a fermentation process, dissolved oxygen is the one of the key process variables that needs to be controlled because of the effect they have on the product quality. In a penicillin production, dissolved oxygen concentration influenced biomass concentration. In this paper, multilayer perceptron neural network (MLP) and Radial Basis Function (RBF) neural network is used in modeling penicillin fermentation process. Process data from an industrial scale fed-batch bioreactor is used in developing the models with dissolved oxygen and penicillin concentration as the outputs. RBF neural network model gives better accuracy than MLP neural network. The model is further used in fuzzy logic controller design to simulate control of dissolved oxygen by manipulation of aeration rate.  Simulation result shows that the fuzzy logic controller can control the dissolved oxygen based on the given profile.
Volume: 17
Issue: 3
Page: 1289-1297
Publish at: 2020-03-01

Islanding detection of integrated distributed generation with advanced controller

10.11591/ijeecs.v17.i3.pp1626-1631
J Rajesh Reddy , A Pandian , R Dhanasekaran , Rami Reddy Ch , B Prasanna Lakshmi , B Neelima Devi
Grid integration of non conventional energy resources is increasing in day to day life to supply the global energy utilization requirement. The major problem with such integrated Distributed Generation (DG) is islanding. The islanding is originated in the integrated system when a part of the power system is disconnected from the grid and continue to feed the local load. The islanding is not safe to field persons and equipment. As per IEEE 1547 standards, the islanding should be detected within 2 seconds with the equipments associated with it. In this paper, a new islanding detection method is proposed with fuzzy rule based approach with inputs as the change in frequency and power. This method classifies the islanding and non islanding events efficiently compared to other passive methods. The simulations are carried on Matlab/ Simulink 2018b environment.
Volume: 17
Issue: 3
Page: 1626-1631
Publish at: 2020-03-01

Voltage tracking of bridgeless PFC cuk converter using PI controller

10.11591/ijpeds.v11.i1.pp367-373
W. M. Utomo , N. A. A. Isa , A. A. Bakar , A. F. H. A. Gani , B. E. Prasetyo , H. Elmunsyah , Y.M.Y Buswig
This paper proposes a Proportional-Integral (PI) control voltage tracking of Bridgeless Power Factor Correction (BPFC) Cuk converter.  In order to investigate the behaviour of different output voltages during overshoot, steady state and step response, P.I controller is designed to set the -42 V, -48 V, -54 V output voltages. The simulation results show that the proposed PI controller able to control the output voltage and achieve fast steady state and step response of BPFC Cuk converter.  When the value of output voltage increase, the overshoot voltage will become higher but the steady state respond will be faster. Furthermore, BPFC Cuk converter with P.I controller have low output voltage ripples.
Volume: 11
Issue: 1
Page: 367-373
Publish at: 2020-03-01

Homestay save rent method through consumer self-management of electricity power consumption

10.11591/ijpeds.v11.i1.pp425-432
Dirman Hanafi , Kamal Khairi Kamaruddin , Hisyam Abdul Rahman , Yudhi Gunardi
The rapid growth in the number of homestays and hotels, competition has increased among them. Homestay that is a relatively newcomer in this business should find the way to become competitive. One way is to make rental fees more affordable. In this paper a method to reduce the homestay rental fees are proposed. This is done by separating the component of the electricity cost from the whole rental fees. Then it requires the consumer to pay their own electricity used and also gives opportunity to them to manage their own electricity used how much they need. This mechanism is implemented by equipping the homestay with the coin kilowatt hour (ckWh) meter. The consumer can plan how much they will use the power since they stay by inserting the certain amount of coin into the ckWh meter. After insert the coin the electricity sources will on and ready to use. The main components of this ckWh meter consist of the Arduino Uno microcontroller as a brain of the device, the coin acceptor where the coin will insert, and kilowatt hour meter. Besides that, it also equipped with liquid-crystal display (LCD) to show the amount of money currently available. The experimental test shows that the device develop work well and can control the used of the electricity related to the amount money that has been inserted.
Volume: 11
Issue: 1
Page: 425-432
Publish at: 2020-03-01

Artificial neural network forecasting performance with missing value imputations

10.11591/ijai.v9.i1.pp33-39
Nur Haizum Abd Rahman , Muhammad Hisyam Lee
This paper presents time series forecasting method in order to achieve high accuracy performance. In this study, the modern time series approach with the presence of missing values problem is developed. The artificial neural networks (ANNs) is used to forecast the future values with the missing value imputations methods used known as average, normal ratio and also the modified method. The results are validated by using mean absolute error (MAE) and root mean square error (RMSE). The result shown that by considering the right method in missing values problems can improved artificial neural network forecast accuracy. It is proven in both MAE and RMSE measurements as forecast improved from 8.75 to 4.56 and from 10.57 to 5.85 respectively. Thus, this study suggests by understanding the problem in time series data can produce accurate forecast and the correct decision making can be produced.
Volume: 9
Issue: 1
Page: 33-39
Publish at: 2020-03-01

Improvement of protection relay with a single phase autoreclosing mechanism based on artificial neural network

10.11591/ijpeds.v11.i1.pp505-514
Zozan Saadallah Hussain , Ahmed J. Ali , Ahmed A. Allu , Rakan Khalil Antar
This paper presents a developed logical tripping scheme to improve conventional protection performance. Adaptive single pole auto reclosure (ASPAR) system is proposed that considers, automatically tripping and reclosing of a multi-shot independent pole technique of a circuit breaker at a predetermined sequence, which can be used to boost the synchronization of the power grid under the transient fault conditions. Moreover, the ASPAR can be utilized to enhance the electrical system stability and reliability at the same operating conditions. Based on the three-phase system, the Artificial neural network (ANN) in this work has been done in order to diagnose and detect healthy and faulted phases. The proposed ANN fault classifier method consists of the logic gates, router circuits, timers, and positive and negative sequence analyses circuit. In addition, it is used to give the ability to recognize a fault type, which by training on the sequence angle values and coordination of the transmission line. Three-phase overhead transmission line including the proposed ASPAR is built in MATLA \SIMULINK environment. Thus the performance ANN-fault classified is tested under different fault conditions. Simulation results show that the proposed ASPAR based on ANN is accurate and well performance. Whereas resultant tripping and reclosing signals of ASPAR are successfully provided that enhances the circuit breaker mechanism under these operating condition.
Volume: 11
Issue: 1
Page: 505-514
Publish at: 2020-03-01

Autism spectrum disorder classification on electroencephalogram signal using deep learning algorithm

10.11591/ijai.v9.i1.pp91-99
Nur Alisa Ali
Autism Spectrum Disorder (ASD) is a neurodevelopmental that impact the social interaction and communication skills. Diagnosis of ASD is one of the difficult problems facing researchers. This research work aimed to reveal the different pattern between autistic and normal children via electroencephalogram (EEG) by using the deep learning algorithm. The brain signal database used pattern recognition where the extracted features will undergo the multilayer perceptron network for the classification process. The promising method to perform the classification is through a deep learning algorithm, which is currently a well-known and superior method in the pattern recognition field. The performance measure for the classification would be the accuracy. The higher percentage means the more effectiveness for the ASD diagnosis. This can be seen as the ground work for applying a new algorithm for further development diagnosis of autism to see how the treatment is working as well in future.
Volume: 9
Issue: 1
Page: 91-99
Publish at: 2020-03-01

New insider threat detection method based on recurrent neural networks

10.11591/ijeecs.v17.i3.pp1474-1479
Mohammed Nasser Al-mhiqani , Rabiah Ahmad , Zaheera Zainal Abidin , Warusia Yassin , Aslinda Hassan , Ameera Natasha Mohammad
Insider threat is a significant challenge in cybersecurity. In comparison with outside attackers, inside attackers have more privileges and legitimate access to information and facilities that can cause considerable damage to an organization. Most organizations that implement traditional cybersecurity techniques, such as intrusion detection systems, fail to detect insider threats given the lack of extensive knowledge on insider behavior patterns. However, a sophisticated method is necessary for an in-depth understanding of insider activities that the insider performs in the organization. In this study, we propose a new conceptual method for insider threat detection on the basis of the behaviors of an insider. In addition, gated recurrent unit neural network will be explored further to enhance the insider threat detector. This method will identify the optimal behavioral pattern of insider actions.
Volume: 17
Issue: 3
Page: 1474-1479
Publish at: 2020-03-01

Competence-driven engineering education: A case for T-shaped engineers and teachers

10.11591/ijere.v9i1.20274
Alabadan Babatope A , Taiwo M. Samuel , Philip I. Ajewole , Oluwakemi M. Anyanwu
The demand for engineering education and graduates is increasing daily because the current service and technological designs are unable to meet the needs of the society and the expected dramatic increase in the future. The emerging skill gap requires a shift in the type of expertise required of young professionals that will be needed to successfully lead organizations in the new economy. Researchers have identified various ‘shapes’ for the engineering professionals to make them relevant to the 21st century challenge, especially in the industry where their expertise is much needed. T-shaped professionals have skills that make them to be more preferred among others. The purpose of this paper is to present the need to upgrade engineering education curriculum to produce more T-shaped graduate engineers required in the changing industrial world. The potential benefits of T-shaped professionals to organizational performance are quite significant; hence, the demand for T-shaped professionals in knowledge-intensive, service-oriented economies is increasing. Unfortunately, the challenges associated with creating more T-shaped professionals are also significant. National regulatory bodies for engineering education in Nigeria are beginning to move towards integrated curriculum to break down discipline silos and produce T-shaped graduate engineers for the fast-changing industrial world. Service Science Management and Engineering (SSME) is an emerging discipline with over 250 programmes in 50 nations seeking to create more T-shaped professionals.
Volume: 9
Issue: 1
Page: 32-38
Publish at: 2020-03-01

Solar fed BLDC motor drive for mixer grinder using a boost converter

10.11591/ijpeds.v11.i1.pp56-63
Deekshitha S Nayak , R Shivarudraswamy
The existing mixer grinder comprises of the universal motor operating in alternating current supply due to high starting torque characteristics and simple controlling of the speed. The absence of brushes and the reduction of noise in the Brushless DC (BLDC) extends its lifetime and makes it ideal in a mixer grinder. A novel solar-powered BLDC motor drive for mixer grinder is presented in this paper. A DC-DC boost converter has been utilised to operate a PV (photovoltaic) array at its highest power. The proposed hysteresis current control BLDC system has been developed in the MATLAB. A performance comparison is made using the commercially available mixer grinder along with the simulated proposed system.
Volume: 11
Issue: 1
Page: 56-63
Publish at: 2020-03-01

The effect of coupled inquiry-5E in enhancing the understanding of Meiosis concept

10.11591/ijere.v9i1.20393
Nooraida Yakob , Kelvineh Kaliun , Ahmad Muslihin Ahmad , Rabiatul-Adawiah Ahmad Rashid , Amelia Abdullah
The purpose of this study is to investigate the effectiveness of coupled inquiry-5E approach on the understanding of meiosis concept among pre-service teachers. The research design of this study is one-group design with a pre-test -post-test-delayed post-test. A total of 31 pre-service teachers from one public university involved in this study. An instrument, Meoisis Conceptual Test with 19 items was used. Data was analysed using One Way Repeated Measure ANOVA. The result showed that there is a statistically significant effect for time, Wilks’ Lambda =.80, F (2,29) = 3.65, p<.05, multivariate eta squared = .20. From the analysis, it can be concluded that there is a statistically significant effect for time. Thus, this finding showed that couple inquiry learning approach has an effect on enhancing meiosis understanding among pre-service teachers. From this study, it is suggested that couple inquiry learning approach is a good method to be used in learning abstract concept such as meiosis.
Volume: 9
Issue: 1
Page: 129-137
Publish at: 2020-03-01

Comparison of student attitudes towards natural sciences

10.11591/ijere.v9i1.20394
Maison Maison , Haryanto Haryanto , Margaret Dwi Wiwik Ernawati , Yulia Ningsih , Nurdatul Jannah , Tari Okta Puspitasari , Dodi Setiawan Putra
The attitude of students during the learning process is essential to be known by an educator to understand how to deal with students in the class. This study aims to determine how students 'attitudes towards science subjects and this study also aim to determine whether there is a comparison of students' attitudes towards natural science subjects in junior high schools in Indonesia. This research was conducted at some state junior high schools in Jambi. Specifically, the research sites were Junior High School 5, Junior High School 6, and Junior High School 26 in Jambi. The research design used in this study was a quantitative approach with survey methods. The research instrument was a science attitude questionnaire. Data were analyzed using descriptive statistics and inferential statistics. The results showed that students' attitudes toward science subjects based on indicators of adoption of scientific attitudes, fun in learning science, and interest in increasing the time to study science were in good categories and also there are significant differences of students’ attitude towards science subjects in the three schools with a comparison value of 0.042 < 0.05.
Volume: 9
Issue: 1
Page: 54-61
Publish at: 2020-03-01

The opinions of students, professors and practice teachers on the teaching practice course

10.11591/ijere.v9i1.20363
Esra Töre
The goal of this study was the evaluation of the teaching practice course in the Psychological Counseling and Guidance (PCG) department by students, professors and practice teachers. It was a pneumology study designed with qualitative research method. The study group consists of seven students, five professors and five practice teachers from 3 different schools and 3 different universities in İstanbul. Study data were analyzed with content analysis. It was found that the communication and collaboration between the professors and practice teachers of the teaching practice course were low, and the applications within the scope of the course were inadequate. Additionally, the study has revealed that it is necessary to inform the practice teachers about the previous courses and internships the students have taken, to ensure the attendance of students to full-day practice courses on different days and that a detailed teaching practice course guide is prepared. This study is thought to benefit the literature in the sense that it shows how PCG teaching practice course differs from other teaching practice courses, in addition to suggestions to the decision makers and practitioners for improving the course.
Volume: 9
Issue: 1
Page: 10-20
Publish at: 2020-03-01

Comparative study of two control strategies proportional integral and fuzzy logic for the control of a doubly fed induction generator dedicated to a wind application

10.11591/ijpeds.v11.i1.pp263-274
Chebel Ahlem , Benretem A , Dobrev I , Barkati Barkati
This paper presents a study analysis of a complete wind energy conversion system, the system based on a doubly fed induction generator (DFIG); a vector control with stator flux orientation of the DFIG is also used to control independently the active and reactive powers. A comparative study have been performed between the conventional PI controller and fuzzy logic control to investigate its dynamic and static performances. This research work involves the study of a phase in advance, to provide effective assistance, to all those who have to make decisions regarding the planning and implementation of wind energy projects. The main objective is to model the wind chain and the use of two types of strategies for the control of this generator to ensure a good regulation we started with the modeling of the wind chain then the modeling of the DFIG and then the use of the two strategies for the regulation of the latter .The complete system is modeled and simulated in the MATLAB/ Simulink. The performance and robustness are analyzed and compared by Matlab / Simulink .Simulation results prove the excellent performance of fuzzy control unit as improving power quality and stability of wind turbine.
Volume: 11
Issue: 1
Page: 263-274
Publish at: 2020-03-01
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