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Why some religious individuals are not emotionally smart? The explanatory role of spirituality

10.11591/ijere.v9i1.20455
Hui Wen Ng , Kususanto Ditto Prihadi
In two studies, we intend to investigate whether spirituality can explain the relationship between intrinsic religious orientation (IRO) and emotional intelligence (EI). Seventy-three worshipping houses-going adults, aged 18-56, had participated in the study. Data was collected by employing Intrinsic Scale of Religious Orientation Scale, Spirituality Assessment Scale, and the Schutte Self-Report Emotional Intelligence Test. Our first study discovered that IRO is not a significant predictor of EI. Nevertheless, Bootstrap analysis with 5000 samples and 95% interval confidence indicated that spirituality fully mediated the link between intrinsic religious orientation and emotional intelligence in our second study. In other words, without high level of spirituality one’s religious orientation does not significantly predict their emotional intelligence. Limitation and suggestion are discussed at the end of the paper. 
Volume: 9
Issue: 1
Page: 83-92
Publish at: 2020-03-01

Online geocode in postal address using GPS with synchronous database accessing

10.11591/ijeecs.v17.i3.pp1487-1492
Mohammad Riyadh R. Sharba , Hakim Adil Kadhim , Salam A. W. Al-Abassi , Nabeel Salih Ali
Postal addressing information is a crucial issue in any organization for business targets, especially in developed countries. Thus, required to convert postal address data to an absolute value like latitude and longitude coordinates by a procedure called geocoding. In this paper, discuss how to make long coordinates into simple geocode via maps services. Besides, conduct a smartphone application to save the geocode with details information to be a GIS for the future used by end-users. The information includes address name, type, and phone number as well as a small note. The app can search for a particular location like hospitals, schools, restaurants, etc.
Volume: 17
Issue: 3
Page: 1487-1492
Publish at: 2020-03-01

Dual axis solar tracker with IoT monitoring system using arduino

10.11591/ijpeds.v11.i1.pp451-458
Siti Amely Jumaat , Mohamad Nur Aiman Mohd Said , Clarence Rimong Anak Jawa
This project aims to develop dual axis solar tracker with IOT monitoring system using Arduino. Generally, solar energy is the technology to get useful energy from sunlight. Solar energy has been used in many traditional technologies over the centuries and has been widely used in the absence of other energy supplies. Its usefulness is widespread when awareness of the cost of the environment and the supply is limited by other energy sources such as fuel. The solar tracking system is the most effective technology to improve the efficiency of solar panels by tracking and following the sun's movement. With the help of this system, solar panels can improve the way of sunlight detection so that more electricity can be collected as solar panels can maintain a sunny position. Thus the project discusses the development of two-axis solar-tracking developers using Arduino Uno as main controller the system. For develops this project, four light-dependent resistors (LDRs) have been used for sunlight detection and a maximum light intensity. Two servo motors have been used to rotate the solar panel according to the sun's light source detected by the LDR. Next a WIFI ESP8266 device is used as an intermediary between device and IOT monitoring system. The IOT monitoring system is a website that functions to store data. The efficiency of this system has been tested and compared with a single axial solar tracker. As a result, the two-axis solar tracking system generates more power, voltage and current.
Volume: 11
Issue: 1
Page: 451-458
Publish at: 2020-03-01

Symmetrical high voltage gain half-bridge inverter based double-Y-source networks with reduced voltage stress

10.11591/ijpeds.v11.i1.pp515-522
Hussain Sayed , Oday A Ahmed , Dhari Y Mahmood , Kanaan A. Jalal , Waleed H. Habeeb
A single-stage symmetrical high voltage gain half-bridge (HB) DC-AC converter is proposed in this paper. Using two Y-source impedance networks, the following key features are utilized from the proposed topology: single stage inverter with very high voltage gain compared to conventional HB inverter, symmetrical output voltage waveform, low voltage stress across the passive components because it is distributed across two impedance networks, and only two switching devices are needed for the converter. Furthermore, important merit of the proposed topology is that the current drawn by the Y-coupled inductors is symmetrical around the X-axis which helps to prevent the Y-network cores from reaching the saturation state. And the last compelling feature is a virtual neutral point for the load connection is inherited in the proposed double Y-source impedance networks converter with no need for DC-Link capacitors. For low voltage sources such as photovoltaic (PV) and fuel cell, the converter is designed to achieve continuous input current operation. The operation modes and principles of the inverter are analyzed and discussed deeply in this paper. A detailed mathematical equations system is derived and verified for the presented converter. Finally, PSpice simulation tools are used to simulate the converter and verify the derived mathematical formulas.
Volume: 11
Issue: 1
Page: 515-522
Publish at: 2020-03-01

Wireless power transfer framework for minirobot based on resonant inductive coupling and impedance matching

10.11591/ijpeds.v11.i1.pp317-325
Kin Yun Lum , Jyi-Shyan Chow , Kah Haur Yiauw
Minirobots which are under the field of miniature robotics, have a dimension of a few centimetres to even a few millimetres. Conventionally, these small sized robots are usually powered up by batteries. The batteries can take up a lot of space and result in a bulky system. Isolating the energy storage components from the robot itself can provide a good alternative to further down sized the robot. This can be done with the incorporation of wireless power transfer (WPT) technology. However, studies of small-size WPT are usually reported with poor efficiency. The objective of this paper is to present an efficient wireless power transfer framework for the minirobot by employing the resonant inductive coupling together with impedance matching technique. The theory and design process will be discussed. Then, a simple prototyping experiment was conducted to verify the proposed framework. Result showed 35% transfer efficiency had been achieved on a transmission distance of 0.5 cm. The proposed framework had also successfully powered a 4 watts minirobot prototype at about 16% transfer efficiency where its receiver coil was located 3.5 cm above the transmitter coil.
Volume: 11
Issue: 1
Page: 317-325
Publish at: 2020-03-01

Design and implementation of high frequency induction heating with LLC resonant load matching using ELTA

10.11591/ijpeds.v11.i1.pp178-188
Suganthi Karuppusamy , Sunandhitha V , Suraj R , Roja T S , Sundararaman K
Induction heating is a non-contact method of producing heat which can be used to perform various processes like hardening, annealing, tempering, welding, brazing, melting, forging, etc. This paper discusses the design and implementation of induction heating on a given work-piece, using an LLC resonant circuit and a transformer for impedance matching, so as to transfer a maximum power of 5KW to the load. The load parameters are found out using ELTA software which calculates the values based on the dimensions of the work piece, operating frequency and temperature. The inverter used is based on SiC MOSFETs which minimizes the losses at high frequencies and high temperatures. The theoretical and simulated results from MATLAB are analysed and verified.  The hardware is implemented for the LLC circuit with transformer and the results are presented.
Volume: 11
Issue: 1
Page: 178-188
Publish at: 2020-03-01

Estimation of water quality index using artificial intelligence approaches and multi-linear regression

10.11591/ijai.v9.i1.pp126-134
Muhammad Sani Gaya , Sani Isah Abba , Aliyu Muhammad Abdu , Abubakar Ibrahim Tukur , Mubarak Auwal Saleh , Parvaneh Esmaili , Norhaliza Abdul Wahab
Water quality index is a measure of water quality at a certain location and over a period of time. High value indicates that the water is unsafe for drinking and inadequate in quality to meet the designated uses. Most of the classical models are unreliable producing unpromising forecasting results. This study presents Artificial Intelligence (AI) techniques and a Multi Linear Regression (MLR) as the classical linear model for estimating the Water Quality Index (WQI) of Palla station of Yamuna river, India. Full-scale data of the river were used in validating the models. Performance measures such as Mean Square Error (MSE), Root Mean Squared Error (RMSE) and Determination Coefficient (DC) were utilized in evaluating the accuracy and performance of the models. The obtained result depicted the superiority of AI models over the MLR model. The results also indicated that, the best model of both ANN and ANFIS proved high improvement in performance accuracy over MLR up to 10% in the verification phase. The difference between ANN and ANFIS accuracy is negligible due to a slight increment in performance accuracy indicating that both ANN and ANFIS could serve as reliable models for the estimation of WQI.
Volume: 9
Issue: 1
Page: 126-134
Publish at: 2020-03-01

PI controller for DC motor speed realized with simulink and practical measurements

10.11591/ijpeds.v11.i1.pp119-126
Mohammed A. Ibrahim , Ali N. Hamoodi , Bashar M. Salih
This article describes the methodology of speed control by understanding control method of DC motor, definitely, armature and field resistances with additional to armature voltage control methods. The speed of DC motor is controlled PI controller as donor in this work. Using Matlab simulation and practical measurements, Terco DC motor speed control is achieved in this work. The results that obtained from Matlab simulation circuit is appeared approximately similar that obtained by practical connection. 
Volume: 11
Issue: 1
Page: 119-126
Publish at: 2020-03-01

Differential game theory with FPA optimization in multi-area power system

10.11591/ijpeds.v11.i1.pp302-308
S. Khadarvali , V. Madhusudhan , R. Kiranmayi
The distribution generation penetration increases due to the increased need of power. These penetration causes problem of frequency deviations. In this paper the in multi-area power system the combination of renewable energy resources is proposed. Here the area 1 & area 2 are thermal power plant. Hydro power generation plant is taken in area-3 & area-4. Renewable energy system is considered in area-5. Here the cyber security attack is taken as change in power in the entire area. This can make the power block out or wrong data entry. Here differential game theory-based problem formulation is done. The PI controller and differential game theory with flower pollination are compared for performance of fast response. The MATLAB 2017b is used for building the areas and algorithm
Volume: 11
Issue: 1
Page: 302-308
Publish at: 2020-03-01

Large-scale image-to-video face retrieval with convolutional neural network features

10.11591/ijai.v9.i1.pp40-45
Imane Hachchane , Abdelmajid Badri , Aïcha Sahel , Yassine Ruichek
Convolutional neural network features are becoming the norm in instance retrieval. This work investigates the relevance of using an of the shelf object detection network, like Faster R-CNN, as a feature extractor for an image-to-video face retrieval pipeline instead of using hand-crafted features. We use the objects proposals learned by a Region Proposal Network (RPN) and their associated representations taken from a CNN for the filtering and the re-ranking steps. Moreover, we study the relevance of features from a finetuned network. In addition to that we explore the use of face detection, fisher vector and bag of visual words with those CNN features. We also test the impact of different similarity metrics. The results obtained are very promising.
Volume: 9
Issue: 1
Page: 40-45
Publish at: 2020-03-01

Development of option c measurement and verification model using hybrid artificial neural network-cross validation technique to quantify saving

10.11591/ijai.v9.i1.pp25-32
Wan Nazirah Wan Md Adnan , Nofri Yenita Dahlan , Ismail Musirin
This paper aims to develop a hybrid artificial neural network for Option C Measurement and Verification model to predict monthly building energy consumption. In this work, baseline energy model development using artificial neural networks embedded with artificial bee colony optimization and cross validation technique for a small dataset were considered. Artificial bee colony optimization with coefficient of correlation fitness function was used in optimizing the neural network training process and selecting the optimal values of initial weights and biases. Working days, class days and cooling degree days were used as input meanwhile monthly electricity consumption as an output of artificial neural network. The results indicated that this hybrid artificial neural network model provided better prediction results compared to the other model. The best model with the highest value of coefficient of correlation was selected as the baseline model hence is used to determine the saving. 
Volume: 9
Issue: 1
Page: 25-32
Publish at: 2020-03-01

Prediction of energy consumption using recurrent neural networks (RNN) and nonlinear autoregressive neural network with external input (NARX)

10.11591/ijeecs.v17.i3.pp1215-1223
Wan Muhammad Zafri Wan Yahaya , Fadhlan Hafizhelmi Kamaru Zaman , Mohd Fuad Abdul Latip
Recurrent Neural Networks (RNN) and Nonlinear Autoregressive Neural Network with External Input (NARX) are recently applied in predicting energy consumption. Energy consumption prediction for depth analysis of how electrical energy consumption is managed on Tower 2 Engineering Building is critical in order to reduce the energy usage and the operational cost. Prediction of energy consumption in this building will bring great benefits to the Faculty of Electrical Engineering UiTM Shah Alam. In this work, we present the comparative study on the performance of prediction of energy consumption in Tower 2 Engineering Building using RNN and NARX method. The model of RNN and NARX are trained using data collected using smart meters installed inside the building. The results after training and testing using RNN and NARX show that by using the recorded data we can accurately predict the energy consumption in the building. We also show that RNN model trained with normalized data performs better than NARX model.
Volume: 17
Issue: 3
Page: 1215-1223
Publish at: 2020-03-01

IoT based facial recognition door access control home security system using raspberry pi

10.11591/ijpeds.v11.i1.pp417-424
Syafeeza Ahmad Radzi , M.K. Mohd Fitri Alif , Y. Nursyifaa Athirah , A. S. Jaafar , A. H. Norihan , M. S. Saleha
The home security system has become vital for every house. Previously, most doors can be open by using traditional ways, such as keys, security cards, password or pattern. However, incidents such as a key loss has led to much worrying cases such as robbery and identity fraud. This has become a significant issue. To overcome this problem, face recognition using deep learning technique was introduced and Internet of Thing (IoT) also been used to perform efficient door access control system. Raspberry Pi is a programmable small computer board and used as the main controller for face recognition, youth system and locking system. The camera is used to capture images of the person in front of the door. IoT system enables the user to control the door access.
Volume: 11
Issue: 1
Page: 417-424
Publish at: 2020-03-01

Closed-loop speed control of switched reluctance motor drive fed from novel converter with reduced number of switches

10.11591/ijpeds.v11.i1.pp189-199
Ashok Kumar Kolluru , Malligunta Kiran Kumar
This paper presents a novel converter configuration with fewer for switched reluctance motor (SRM) drive. The proposed novel converter insists for less number of switches compared to conventional asymmetrical type of converter configuration for switched reluctance motor. Switch count reduction in converter reduces the losses, volume of heat sink, and number of gate drive circuits and thereby the performance of the system. Closed loop speed control of switched reluctance motor fed from proposed novel converter topology was presented in this paper. Performance of closed loop operation is compared to open loop system. Further the proposed converter for SRMT is evaluated with loaded condition and comparative analysis of no-load and loaded SRM is presented. The model presented is developed and the results are analyzed using MATLAB/SIMULINK software. Closed loop performance of proposed novel converter fed switched reluctance motor drive is verified at fixed speed and variable speed conditions.
Volume: 11
Issue: 1
Page: 189-199
Publish at: 2020-03-01

Application of artificial neural network in sizing a stand-alone photovoltaic system: a review

10.11591/ijpeds.v11.i1.pp342-349
Ahmad Fateh Mohamad Nor , Suriana Salimin , Mohd Noor Abdullah , Muhammad Nafis Ismail
Artificial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.
Volume: 11
Issue: 1
Page: 342-349
Publish at: 2020-03-01
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