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29,734 Article Results

Comparing the linear and logarithm normalized extreme learning machine in flow curve modeling of magnetorheological fluid

10.11591/ijeecs.v13.i3.pp1065-1072
Irfan Bahiuddin , Abdul Y Abd Fatah , Saiful A Mazlan , Mohd I Shapiai , Fitrian Imaduddin , Ubaidillah Ubaidillah , Dewi Utami , Mohd N Muhtazaruddin
The extreme learning machine (ELM) plays an important role to predict magnetorheological (MR) fluid behavior and to reduce the computational fluid dynamics (CFD) calculation cost while simulating the MR fluid flow of an MR actuator. This paper presents a logarithm normalized method to enhance the prediction of ELM of the flow curve representing the MR fluid rheological properties. MRC C1L was used to test the performance of the proposed method, and different activation functions of ELMs were chosen to be the neural networks setting. The Normalized Root Mean Square Error (NRMSE) was selected as the indicator of the ELM prediction accuracy. NRMSE of the proposed method is found to improve the model accuracy up to 77.10 % for the prediction or testing case while comparing with the linear normalized ELM
Volume: 13
Issue: 3
Page: 1065-1072
Publish at: 2019-03-01

A categorical data analysis of impact of biogas on women of rural households – with examples from Nepal

10.11591/ijaas.v8.i1.pp34-43
Jyoti U. Devkota
This paper is based on primary data collected from 400 households of biogas consumers. A detailed structured questionnaire was developed and pretested. Here response to each question was given as a multiple choice option resulting in more than 450 categorical data. These variables studied various aspects of households using biogas. The results focused on women of these households. Interrelationships between several other variables including the role of a woman in various decisions related to the plant were analyzed. Logistic regression of decision making of woman on several variables including asset index of the family was done. This asset index was calculated from the principle component analysis of socio-economic variables. The family dynamics in the choice of biogas as renewable energy source was quantified using odds ratio and regression coefficients. The interdependence between variables was tested using Chi square test of Independence of Attributes. A novel data based approach of generation and analysis of categorical data is demonstrated here. The suitability of generation of categorical data in the absence of accurate measurement instruments is highlighted. This method is also suitable for countries without a strong backbone of good quality official records, and provides a good backup data for official statistics.
Volume: 8
Issue: 1
Page: 34-43
Publish at: 2019-03-01

A new formula for conjugate parameter computation based on the quadratic model

10.11591/ijeecs.v13.i3.pp954-961
Basim Abbas Hassan
The conjugancy coefficient is the very basis of a diversity of the conjugate gradient methods. In this research, we derivation a new formula of conjugate gradient methods based on the quadratic model. Our arithmetical findings have revealed that, our new method has the most excellent performance contrast to the other standard CG methods. Also give proof viewing that this method converges globally.
Volume: 13
Issue: 3
Page: 954-961
Publish at: 2019-03-01

Cyberbullying among secondary school teachers by parents

10.11591/ijere.v8i1.16549
Rüyam Küçüksüleymanoğlu
Cyberbullying which is known as violence on the Internet is a dimension of peer bullying takes places through electronic communication technologies. Cyberbullying which can occur in any environment regardless of the time and place is the way in which individuals with higher ability to use communication technologies to lead other individuals in a series of negative behaviors over time. With the rapid development of technology and the ease with which internet access becomes easier and cheaper, it becomes a problem that needs to be studied more and more importantly day by day. Facebook, twitter and whatss up, the most widely used social network today, has the potential to become the most commonplace for cyberbullying behaviors. The purpose of this study was to determine cyberbullying towards teachers by parents in secondary schools based on teachers views according to sex, tenure and school size. The sample of the study was 181 teachers from 14 secondary schools. The experiences and perspectives of 181 teachers were assessed regarding the incidence and perceptions of the likelihood of cyber harassment by parents. The results presented here indicate that nearly3/4 of teachers in the sample had received harassing or threatening messages from parents.
Volume: 8
Issue: 1
Page: 151-157
Publish at: 2019-03-01

Autonomous coop cooling system using renewable energy and water recycling

10.11591/ijeecs.v13.i3.pp1303-1310
Shamsul Kamal Ahmad Khalid , Nurul Shafiqah Che Dan , Noor Azah Samsudin , Muhammad Syariff Aripin , Nor Amirul Amri Nordin
Extreme temperature in a chicken coop can significantly affect the growth and productivity of poultry. Therefore, the temperature inside the chicken coop need to be controlled to protect it from extreme temperatures. Most of the technology use electrical energy supplied to an evaporative cooling system to control the temperature of a coop. This paper presents an autonomous chicken coop cooling system using renewable energy and water recycling (REMACT). In this study, a monitoring system with necessary hardware, control application, powered with solar power source and water recycling, has been developed. The proposed cooling system consists of hardware part such as an Internet of Things (IOT) controller platform, temperature sensor, solar panel, water pump, water storage, water drain and pipe. When the temperature sensor detects extreme temperature more than 28℃ in a chicken coop, the water in storage tank will flow throughout the pipe and pass into water pump before it irrigates the chicken coop roof. When the temperature is below 22℃, the bulb will light up to transfer heat to the chicken coop and cause the temperature drop back to a healthy range. The water drain that is attached to the roof will collect the water and return the water back to the water storage again. The software components required by the project are Arduino IDE, Thinger.io, and Android Studio Framework. Several experiments have been conducted with hot and cold scenarios. The system was able to stabilise the temperature back to a healthy range. A usability testing result demonstrates 80% satisfactory rate. The findings from the experiments show that IoT, renewable energy and water recycling have the potential for temperature control of a chicken coop.
Volume: 13
Issue: 3
Page: 1303-1310
Publish at: 2019-03-01

Investigation of the static current gain for InP/InGaAs single heterojunction bipolar transistor

10.11591/ijeecs.v13.i3.pp1345-1354
Jihane Ouchrif , Abdennaceur Baghdad , Aicha Sshel , Abdelmajid Badri , Abdelhakim Ballouk
Heterojunction Bipolar Transistors are being used increasingly in communication systems due to their electrical performances. They are considered as excellent electronic devices. This paper presents an investigation of the static current gain β based on two technological parameters related to the device geometry for InP/InGaAs Single Heterojunction Bipolar Transistor (SHBT). These parameters are the base width  and the emitter length . We used Silvaco’s TCAD tools to design the device structure, and to extract the static current gain β from I-V output characteristics figures. According to this investigation, we determined the optimal values of the examined parameters which allow obtaining the highest static current gain β.
Volume: 13
Issue: 3
Page: 1345-1354
Publish at: 2019-03-01

The effect of psychological factors on Syrian refugees’ participation in lifelong education

10.11591/ijere.v8i1.16557
Mehmet Fatih Karacabey , Kivanc Bozkus
The purpose of this research was to determine the effect of psychological factors on Syrian refugees’ participation in lifelong education. The ex post facto co-relational causal design was employed in this research. A questionnaire form consisted of four scales was used to collect data from 297 refugees participated in lifelong education. The structural equation modeling analysis revealed that psychological factors affect participation in lifelong education and learning approaches played the biggest role in this effect. It was claimed that learning approach is a strong predictor of participation in lifelong education. The effect of locus of control on participation in lifelong education was medium while the effects of self-efficacy and self-worth were weak. Recommendations to education providers, decision-makers and researchers to align both formal and lifelong education curricula with the results were given.
Volume: 8
Issue: 1
Page: 138-144
Publish at: 2019-03-01

An improved radial basis function networks in networks weights adjustment for training real-world nonlinear datasets

10.11591/ijai.v8.i1.pp63-76
Lim Eng Aik , Tan Wei Hong , Ahmad Kadri Junoh
In neural networks, the accuracies of its networks are mainly relying on two important factors which are the centers and the networks weight. The gradient descent algorithm is a widely used weight adjustment algorithm in most of neural networks training algorithm. However, the method is known for its weakness for easily trap in local minima. It suffers from a random weight generated for the networks during initial stage of training at input layer to hidden layer networks. The performance of radial basis function networks (RBFN) has been improved from different perspectives, including centroid initialization problem to weight correction stage over the years. Unfortunately, the solution does not provide a good trade-off between quality and efficiency of the weight produces by the algorithm. To solve this problem, an improved gradient descent algorithm for finding initial weight and improve the overall networks weight is proposed. This improved version algorithm is incorporated into RBFN training algorithm for updating weight. Hence, this paper presented an improved RBFN in term of algorithm for improving the weight adjustment in RBFN during training process. The proposed training algorithm, which uses improved gradient descent algorithm for weight adjustment for training RBFN, obtained significant improvement in predictions compared to the standard RBFN. The proposed training algorithm was implemented in MATLAB environment. The proposed improved network called IRBFN was tested against the standard RBFN in predictions. The experimental models were tested on four literatures nonlinear function and four real-world application problems, particularly in Air pollutant problem, Biochemical Oxygen Demand (BOD) problem, Phytoplankton problem, and forex pair EURUSD. The results are compared to IRBFN for root mean square error (RMSE) values with standard RBFN. The IRBFN yielded a promising result with an average improvement percentage more than 40 percent in RMSE.
Volume: 8
Issue: 1
Page: 63-76
Publish at: 2019-03-01

Molecular techniques applied to investigations of abundance of the ammonia oxidizing bacteria and ammonia oxidizing archaea microorganisms in the environment

10.11591/ijaas.v8.i1.pp1-7
Amjed Ginawi , Yan Yunjun
This review shows regards of the recently experienced concerning the environments of ammonia oxidizing bacteria (AOB), ammonia oxidizing archaea (AOA) microorganisms, and denitrifying microbes. The advancements of molecular biology techniques have encouraged staggeringly to the fast recent developments in the sector. Various methods for implementing so are discussed. The function of AOB, AOA, and denitrifying microorganism composition was investigated through a high throughput of the 16S rRNA amplicon sequencing protocol. There is potential to observe the specific species appearance of these microorganisms in each environment and get to the evaluated relative abundance of several kinds. There is information indicated which the structure of denitrifying and nitrifying group was monitored field to significant fluctuations and the complexes, together in space and in time. More effort is required to enhance and isolate those microorganisms that common of the progressions and to function them through the compound of molecular techniques, biochemical and physiological. However, the investigation with deoxyribonucleic acid (DNA), antibodies, and the polymerase chain reaction (PCR) was preferred mainly to report the composition of chemolithoautotrophic bacteria, surveys of their characteristics in environmental that needed quantification at the transcriptional level is presently not available.
Volume: 8
Issue: 1
Page: 1-7
Publish at: 2019-03-01

Jobseeker-industry matching system using automated keyword selection and visualization approach

10.11591/ijeecs.v13.i3.pp1124-1129
Norhaslinda Kamaruddin , Abdul Wahab Abdul Rahman , Ramizah Amirah Mohd Lawi
Learning opportunities are available with the accessibility of new learning technologies, discovery of untraditional learning pathways and awareness of the importance of connecting current knowledge with new learning. Such situation allows the expansion in the number of courses, programs and professional certifications offered to the students resulting to the increment of the number of graduates annually. The graduates then employed by the industry for executing the job. However, there is a growing concern about the increment of unemployed graduates in the job market. One of the reasons of the mismatch between graduates’ skills and employers’ needs is that the jobseekers tend to choose wrong job because they are overwhelmed by the choices and typically they just randomly send the application because it is time consuming to filter relevant advert. Such action may have repercussion to the industry because the employers need to select relevant candidates to fill up the post from the unfiltered pile of applications making the selection process lengthy and time consuming. In this paper we proposed an automated approach to match the graduates’ and employers’ needs using a hybrid of text mining and visualization approach to facilitate jobseekers’ task of relevant job application. The important keywords are automatically extracted based on the frequency of the word used in the adverts. Then, the graduates’ skills are matched from their personalized profile. Relevant visualization approaches are incorporated to facilitate the selection. It is practical and feasible for the proposed approach to be incorporated in job searching websites that can optimize jobseekers and employers time and effort for a suitable match.
Volume: 13
Issue: 3
Page: 1124-1129
Publish at: 2019-03-01

An enhanced hybridized artificial bee colony algorithm for optimization problems

10.11591/ijai.v8.i1.pp87-94
Xingwang Huang , Xuewen Zeng , Rui Han , Xu Wang
Artificial bee colony (ABC) algorithm is a popular swarm intelligence based algorithm. Although it has been proven to be competitive to other population-based algorithms, there still exist some problems it cannot solve very well. This paper presents an Enhanced Hybridized Artificial Bee Colony (EHABC) algorithm for optimization problems. The incentive mechanism of EHABC includes enhancing the convergence speed with the information of the global best solution in the onlooker bee phase and enhancing the information exchange between bees by introducing the mutation operator of Genetic Algorithm to ABC in the mutation bee phase. In addition, to enhance the accuracy performance of ABC, the opposition-based learning method is employed to produce the initial population. Experiments are conducted on six standard benchmark functions. The results demonstrate good performance of the enhanced hybridized ABC in solving continuous numerical optimization problems over ABC GABC, HABC and EABC.
Volume: 8
Issue: 1
Page: 87-94
Publish at: 2019-03-01

Identification of plasmodium falciparum and plasmodium vivax on digital image of thin blood films gf

10.11591/ijeecs.v13.i3.pp933-944
Hanung Adi Nugroho , Made Satria Wibawa , Noor Akhmad Setiawan , E. Elsa Herdiana Murhandarwati , Ratna Lestari Budiani Buana
Observing presence of Plasmodium parasite of stained thick or thin blood films through microscopic examination is a gold standard for malaria diagnosis.  Although the microscopic examination has been extensively used, misidentification might occur caused by human factors.  In order to overcome misidentification problem, several studies have been conducted to develop a computer-aided malaria diagnosis (CADx) to assist paramedics in decision-making.  This study proposes an approach to identify species and stage of Plasmodium falciparum and Plasmodium vivax on thin blood films collected from the Laboratory of Parasitology, Faculty of Medicine, Universitas Gadjah Mada.  Adaptive k-means clustering is applied to segment Plasmodium parasites.  A total of 39 features consisting of shape and texture features are extracted and then selected by using wrapper-based forward and backward directions.  Classification is evaluated in two schemes.  The first scheme is to classify the species of parasite into two classes. The second scheme is to classify the species and stage of parasite into six classes.  Three classifiers applied are k-nearest neighbour (KNN), support vector machine (SVM) and multi-layer perceptron (MLP).  Furthermore, to facilitate the multiclass classification, one-versus-one (OVO) and one-versus-all (OVA) methods are implemented.  The first scheme achieves the accuracy of 88.70% based on MLP classifier using three selected features.  While the accuracy gained by the second scheme is 95.16% based on OVO and MLP classifier using 29 selected features.  These results indicate that the proposed approach successfully identifies the species and stage of parasite on thin blood films and has potential to be implemented in the CADx system for assisting paramedics in diagnosing malaria.
Volume: 13
Issue: 3
Page: 933-944
Publish at: 2019-03-01

What are the dimensions of thinking skills in Turkish literature: a content analysis study?

10.11591/ijere.v8i1.17215
Yalçın Dilekli
New world needs thinking generation. However, growing thinking generation is very difficult because there are many discrepancies in defining of thinking and thinking skills. Without defining thinking and its dimensions, it is nearly impossible to grow such generation. For having thinking generation, thinking and its dimensions should be described. In the past 20 years, there have been many different definitions with regard to thinking and thinking skills. But, three different approaches for defining thinking skills and needed basic cognitive operations were commonly accepted. Aim of this study whether these three approaches for defining thinking skills were accepted in Turkish literature or not. For this aim, 14 studies, selected from Turkish database, related to thinking skills were analyzed. According the content analysis results, Turkish literature follows these three movements for defining thinking skills except for belonging to specific areas. 
Volume: 8
Issue: 1
Page: 110-118
Publish at: 2019-03-01

Comparative between (LiNbO3) and (LiTaO3) in detecting acoustics microwaves using classification

10.11591/ijai.v8.i1.pp33-43
Hafdaoui Hichem , Benatia Djamel
Our work is mainly about detecting acoustics microwaves in the type of BAW (Bulk acoustic waves), where we compared between Lithium Niobate (LiNbO3) and Lithium Tantalate (LiTaO3), during the propagation of acoustic microwaves in a piezoelectric substrate. In this paper, We have used the classification by Probabilistic Neural Network (PNN) as a means of numerical analysis in which we classify all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity for conclude whichever is the best in utilization for generating bulk acoustic waves.This study will be very interesting in modeling and realization of acoustic microwaves devices (ultrasound) based on the propagation of acoustic microwaves.
Volume: 8
Issue: 1
Page: 33-43
Publish at: 2019-03-01

Statistical analysis of night radiance RH using VIIRS day/night band satellite time series data

10.11591/ijaas.v8.i1.pp26-33
Jyoti U. Devkota
Amount of night lights in an area is a proxy indicator of electricity consumption. This is interlinked to indicators of economic growth such as socio-economic activities, urban population size, physical capital, incidence of poverty. These night lights are generated by renewable and non renewable energy source. In this paper the behavior of night radiance RH data was minutely analyzed over a period of 28 hour; Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) satellite earth observation data were used. These 28 hours and 8936 observations time series data is from 2 September 2018 to 4 September 2018. The behavior of night radiance RH data over 122 time intervals was analyzed using box plots. It was seen that the arithmetic mean of RH data is more sensitive than the arithmetic mean of first order difference of RH data. The first order difference of night radiance RH was regressed on night radiance over 110 intervals of time. The box plot of slope and intercept of this linear regression showed the behavior of these regression parameters over 110 intervals of time. It is seen that the data are more scattered with respect to slope than with respect to intercept. 
Volume: 8
Issue: 1
Page: 26-33
Publish at: 2019-03-01
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