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29,922 Article Results

The role of social support and self-regulation on work readiness among students in vocational high school

10.11591/ijere.v9i4.20578
Fatwa Tentama , Eva Riyansha Riskiyana
Work readiness is an important factor that can determine the quality of prospective graduates and vocational high schools as one of the educational institutions that prepare human resources to need to pay attention to factors that can improve work readiness. This study aimed to empirically examine how social support and self-regulation influence the work readiness of vocational High School students. The population in this study was all students of grade XII in Vocational High School Muhammadiyah 1 Yogyakarta (a vocational high school), totaling 170 students, and the sample of this study was 111 students. The sampling technique used was randomized sampling using cluster random sampling technique. The data were collected with the work readiness scale, social support scale, and self-regulation scale. The data were then analyzed with multiple linear regression techniques. There was a very significant correlation between social support and selfregulation and they simultaneously influence work readiness (r = 0.490, p = 0.000). There was a very significant correlation between social support and work readiness (r = 0.344, p = 0.000). There is a very significant correlation between self-regulation and work readiness (r = 0.490, p = 0.000). Selfregulation plays dominant role in shaping work readiness.
Volume: 9
Issue: 4
Page: 826-832
Publish at: 2020-12-01

The LSTM technique for demand forecasting of e-procurement in the hospitality industry in the UAE

10.11591/ijai.v9.i4.pp757-765
Elezabeth Mathew , Sherief Abdulla
The hospitality industry is growing at a faster pace across the world which has resulted in the accumulation of a huge amount of data in terms of employee details, property details, purchase details, vendor details, and so on. The industry is yet to fully benefit from these big data by applying ML and AI. The data has not been fully investigated for decision-making or revenue/budget forecasting. In this research data is collected from a chain hotel for advanced predictive analytics. Descriptive and diagnostic analytics is done to an extent across the hotel industry, whereas predictive and prescriptive analysis is done rarely. Demand forecasting for spend and quantity is done using the LSTM technique in e-procurement within the hospitality industry in the UAE. Five years of historical data from a chain hotel in the UAE is used for deep learning in this study. The results confirm the ability of LSTM model to predict e-procurement spend and order forecast for six months. LSTM time series analysis is considered the most suitable technique for demand forecasting to optimize e-procurement.
Volume: 9
Issue: 4
Page: 757-765
Publish at: 2020-12-01

Design of a conductive material detection system

10.11591/ijra.v9i4.pp292-299
Freddy Artadima Silaban , Setiyo Budiyanto , Lukman Medriavin Silalahi
The development of technology and industry development in the 4.0 era is very fast along with these developments in the control of production results such as medicine, food, and safety must be faster and more accurate. To face free trade and global economic competition, every company is required to produce products that have good quality by the standards. By using an experimental method which is the development of this study aims to make a conductive material detector (metal detector) for the pharmaceutical industry, the food industry, and security as compared to using conductive material sensors that are integrated with the Arduino microcontroller. Application testing is carried out to find out whether the Blynk application on an android smartphone with Blynk on a Debian server that has been made previously runs well or not and the alarm system testing uses a buzzer and LED to detect conductive material passing through. Conductive sensor test results showed that the instrument can detect 6 conductivity materials such as stainless steel, aluminum, steel, zinc, copper, and tin. The average response time to detect conductive material is 3 seconds, the average ADC value of the conductive material is 0.55. The test results also successfully send information and data to the Blynk application so that it can be monitored online.
Volume: 9
Issue: 4
Page: 292-299
Publish at: 2020-12-01

Enhance the accuracy of control algorithm for multilevel inverter based on artificial neural network

10.11591/ijeecs.v20.i3.pp1148-1158
Mohammed Rasheed , Moataz M. A. Alakkad , Rosli Omar , Marizan Sulaiman , Wahidah Abd Halim
In converters or multilevel inverters it is very important to ensure that the output of the multilevel inverters waveforms in term of the voltage or current of the waveforms is smooth and without distortion. The artificial neural network (ANN) technique to obtaining proper switching angles sequences for a uniform step asymmetrical modified multilevel inverter by eliminating specified higher-order harmonics while maintaining the required fundamental voltage and current waveform. However, through this paper a modified CHB-MLI are proposed using artificial intelligence optimization technique based on modulation selective harmonic elimination (SHE-PWM). A most powerful modulation technique that used to minimize a harmonic contants during the outout waveform of multilevel inverter is a SHE-PWM method. The proposed a five-level modified cascaded H-bridge multilevel inverter (M-CHBMI) with ANN controller to improve the output voltage and current performance and achieve a lower total harmonic distortion (THD). The main aims of this paper cover design, modeling, prediction for real-time generation of optimal switching angles in a single-phase topology of modified five level CHB-MLI. due to the heavy cost of computation to solving transcendental nonlinear equations with specified number, a real-time application of selective harmonic elimination-pulse width modulation (SHE-PWM) technique is limited. SHE equations known as a transcendental nonlinear equation that contain trigonometric functions. The prototype of a 5-level inverter in digital signal processing (DSP) TMS320F2812 reveals that the proposed method is highly efficient for harmonic reduction in modified multilevel inverter.
Volume: 20
Issue: 3
Page: 1148-1158
Publish at: 2020-12-01

Arts-based assessment in educational settings

10.11591/ijere.v9i4.20346
Jiří Kantor , Xianmei Lei
Arts-based assessment is an objective measure that incorporates artistic experience or artistic materials into the assessment process and enables to get unique contributions about pupils. The current survey focused on arts-based assessment in the Czech Republic to explore the following issues: how did arts therapists assess suitability of therapy for pupils; which areas of therapeutic process were evaluated and what made the process of arts-based assessments specific in educational institutions. A mixed methods study used a statistical analysis of a survey with “The Practice in Arts Therapies questionnaire” (n = 142 arts therapists) and an inductive analysis of qualitative interviews (n = 10 arts therapists). Results revealed that arts-based assessments were more likely to be characterized by qualitative nonstandardized assessments based on observation, analysis of artistic products/artistic process and reflexive techniques and are related to prevalent humanistic orientation. Educational environment influenced the assessments mainly in the content and organization of the process. On this basis, there is a need to support the usage of standardized arts-based assessments and to develop standards for the implementation of arts-based assessment suitable for educational institutions. More advanced training in this area should be included into professional courses and further education of arts therapists.
Volume: 9
Issue: 4
Page: 947-954
Publish at: 2020-12-01

The effect of technology-organization-environment on adoption decision of big data technology in Thailand

10.11591/ijece.v10i6.pp6412-6422
Wanida Saetang , Sakchai Tangwannawit , Tanapon Jensuttiwetchakul
Big data technology (BDT) is being actively adopted by world-leading organizations due to its expected benefits. However, most of the organizations in Thailand are still in the decision or planning stage to adopt BDT. Many challenges exist in encouraging the BDT diffusion in businesses. Thus, this study develops a research model that investigates the determinants of BDT adoption in the Thai context based on the technology-organization-environment (TOE) framework and diffusion of innovation (DOI) theory. Data were collected through an online questionnaire. Three hundred IT employees in different organizations in Thailand were used as a sample group. Structural equation modeling (SEM) was conducted to test the hypotheses. The result indicated that the research model was fitted with the empirical data with the statistics: Normed Chi-Square=1.651, GFI=0.895, AFGI=0.863, NFI=0.930, TLI=0.964, CFI=0.971, SRMR=0.0392, and RMSEA=0.046. The research model could, at 52%, explain decision to adopt BDT. Relative advantage, top management support, competitive pressure, and trading partner pressure show significant positive relation with BDT adoption, while security negatively influences BDT adoption.
Volume: 10
Issue: 6
Page: 6412-6422
Publish at: 2020-12-01

Development of a real-time framework for farm monitoring using drone technology

10.11591/ijra.v9i4.pp244-250
Adekunle T. Oyelami , Adedayo S. Akinade , Kingsley C. Obianefo
This work developed a cost-effective framework for agriculturists to regularly monitor their crops against intruding rodents and other security concerns using modern drone technology through configuration and deployment of an autonomous UAV which also functions as a remotely piloted vehicle. This was done by configuring a quadcopter capable of causing a disturbance when a rodent is observed through an inbuilt alarm system whose sound is amplified to be loud enough to cause the animals to leave the farm area. A framework for real-time image and live video transmission from the farm to a designated remote base station was developed. This was achieved through programming codes that configured the drone to operate an intelligent alarm and object tracking systems which enables a live feed from the UAV using Arduino IDE and Mission Planner for autonomous flight control. The requisite algorithms were developed using the framework of tracking, learning and detection (TLD) in the OpenCV software. The drone movement is equally controlled remotely over a Wi-Fi network using an ESP8266 Wi-Fi module for redirection and controlling of the drone movement to monitor specific locations.
Volume: 9
Issue: 4
Page: 244-250
Publish at: 2020-12-01

A native enhanced elastic extension tables multi-tenant database

10.11591/ijece.v10i6.pp6618-6628
Magy El Banhawy , Walaa Saber , Fathy Amer
A fundamental factor of digital image compression is the conversion processes. The intention of this process is to understand the shape of an image and to modify the digital image to a grayscale configuration where the encoding of the compression technique is operational. This article focuses on an investigation of compression algorithms for images with artistic effects. A key component in image compression is how to effectively preserve the original quality of images. Image compression is to condense by lessening the redundant data of images in order that they are transformed cost-effectively. The common techniques include discrete cosine transform (DCT), fast Fourier transform (FFT), and shifted FFT (SFFT). Experimental results point out compression ratio between original RGB images and grayscale images, as well as comparison. The superior algorithm improving a shape comprehension for images with grahic effect is SFFT technique.
Volume: 10
Issue: 6
Page: 6618-6628
Publish at: 2020-12-01

Prediction of atmospheric pollution using neural networks model of fine particles in the town of Kennedy in Bogota

10.11591/ijece.v10i6.pp6574-6581
Juan Camilo Pedraza , Oswaldo Alberto Romero , Helbert Eduardo Espitia
This work shows an application based on neural networks to determine the prediction of air pollution, especially particulate material of 2.5 micrometers length. This application is considered of great importance due to the impact on human health and high impact due to the agglomeration of people in cities. The implementation is performed using data captured from several devices that can be installed in specific locations for a particular geographical environment, especially in the locality of Kennedy in Bogotá. The model obtained can be used for the design of public policies that control air quality.
Volume: 10
Issue: 6
Page: 6574-6581
Publish at: 2020-12-01

A multi-objective optimization based model for the deployment of reclosers and remote-controlled switches using NSGA2 and entropy weighted TOPSIS method

10.11591/ijeecs.v20.i3.pp1128-1139
Anass Lekbich , Abdelaziz Belfqih , Tayeb Ouaderhman , Chaimae Zedak , Jamal Boukherouaa , Faissal El Mariami
Since they are fast, remote controlled, automated and intelligent, reclosers and switches are an inevitable solution for improving the reliability of intelligent electrical distribution networks at optimal cost. However, their location and coordination have great effects on the protection and automation strategies of complex electrical distribution networks against multiple unpredictable faults. Which requires a flexible and multi-criteria optimization method. In this article, we propose a multi-objective method based on an analytical model by considering the fault rate, restoration times, outage cost and coordination between devices. The non-dominated genetic sorting algorithm II was proposed to obtain the optimal Pareto solutions, and a technique of performance control by similarity with the ideal solution was used to classify them. The objective criteria weights are based on the entropy method which allows solutions to be obtained and better classified with the minimum of subjectivity. The IEEE33 and IEEE13 bus test networks were used to verify the method. The results obtained are compared to a binary multi-objective particle swarm optimization method and the results show that the proposed method reduces the overall costs, reduces the undelivered energy of the system and improves the reliability of the service.
Volume: 20
Issue: 3
Page: 1128-1139
Publish at: 2020-12-01

Offline drone instrumentalized ambulance for emergency situations

10.11591/ijra.v9i4.pp251-255
Hitesh Mohapatra
In this paper, an offline drone instrumentalized ambulance (ODIA) mechanism has been discussed. The rapid increase in the urban population directly influences every sector of society. The sectors are maybe food, health care, education, transportation, etc. Normally, it has been observed that when any accidents happen on the urban road or any remote places then, the availability of immediate medical help is very rare. It is not because of the unaware or unavailability of medical facilities rather it happens because of overcrowding on the urban road and geographical odd-isolation of places. Hence, here an ODIA concept has been discussed which uses offline maps and offline first-aid medical videos through which immediate medical help can be made available at the patient end. This model helps to save the life of an accident victim by providing immediate medical attention. The key strength of ODIA is, it is independent of internet service that is why it is more suitable for harsh and hostile environments.
Volume: 9
Issue: 4
Page: 251-255
Publish at: 2020-12-01

Blogging in ESL class- gender-based attitude of the engineering students

10.11591/ijere.v9i4.20673
Sahib Khatoon , Muhammad Jafre Zainol Abidin , Quratulain Mirza , Ashfaq Hussain
Online learning has given a new context to the teaching and learning environment. This virtual environment changes the attitude of students in language learning. This study aimed to look into the difference among the engineering students' attitudes towards blogging in an ESL class in terms of gender and the effect of multimodal features on their reading attitude. The research method adopted in the present study relied on a qualitative approach. Engineering students from computer science engineering from local public engineering university Mehran University of Engineering and Technology Jamshoro (MUET) were taught English under blogging and were interviewed. Respondents’ attitude is mainly positive towards blogging. There were very few differences pointed out from their attitude towards blogging.
Volume: 9
Issue: 4
Page: 1128-1137
Publish at: 2020-12-01

Mathematical self-concept among prospective teachers

10.11591/ijere.v9i4.20464
Johannis Takaria , Anderson Leonardo Palinussa
Mathematical self-concept (MS-C) is an important construct that prospective mathematics teachers must have in mathematics learning. The aim of the research was to analyze the increase of MS-C of prospective mathematics teachers. The research was quasi-experimental with the design of one group pretest-posttest. The results showed that for prospective teachers, MS-C increased in the medium category while the MS-C indicators achieved in the medium and low categories. The increase of MS-C is due to the effectiveness of collaborative mind mapping (CMM) learning strategy and the process of strengthening MS-C capacity of prospective teachers. The CMM facilitates prospective teachers to construct creative ideas through structured collective ideas that support the increase of MS-C among prospective teacher.
Volume: 9
Issue: 4
Page: 799-806
Publish at: 2020-12-01

A simulated risk assessment of human-robot interaction in the domestic environment

10.11591/ijra.v9i4.pp300-310
Tamanna E Kaonain , Mohd Azizi Abdul Rahman , Mohd Hatta Mohammed Ariff , Kuheli Mondal
In human-robot interaction, the use of collaborative robots or cobots in many industries is of major importance to researchers in human-robot interaction (HRI). The interaction between human robot carries several challenges, the greatest being the risk of human injury. In addition to reducing the proximity between robots and humans, increased difficulty of human-robot encounters raises the likelihood of accidents only. This paper proposes a virtual collaborative robot in the simulated non-industrial workspace. The safety during human-robot interaction using simulation software was investigated by measuring the risks for planning and control. A reactive robot controller was formulated to minimize the risk during human-robot interaction. A Gazebo software is used in this article, written in Python language, to replicate complex environments that a robot can face. This paper also investigated the robot’s speed. It can be reduced before a collision with a human about to happen, and it minimized the risk of the collision or reduced the damage of the risk. After the successful simulation, this can be applied to the real robot in a practical domestic environment.
Volume: 9
Issue: 4
Page: 300-310
Publish at: 2020-12-01

Object gripping algorithm for robotic assistance by means of deep learning

10.11591/ijece.v10i6.pp6292-6299
Robinson Jimenez-Moreno , Astrid Rubiano Fonseca , Jose Luis Ramirez
This paper exposes the use of recent deep learning techniques in the state of the art, little addressed in robotic applications, where a new algorithm based on Faster R-CNN and CNN regression is exposed. The machine vision systems implemented, tend to require multiple stages to locate an object and allow a robot to take it, increasing the noise in the system and the processing times. The convolutional networks based on regions allow one to solve this problem, it is used for it two convolutional architectures, one for classification and location of three types of objects and one to determine the grip angle for a robotic gripper. Under the establish virtual environment, the grip algorithm works up to 5 frames per second with a 100% object classification, and with the implementation of the Faster R-CNN, it allows obtain 100% accuracy in the classifications of the test database, and over a 97% of average precision locating the generated boxes in each element, gripping successfully the objects.
Volume: 10
Issue: 6
Page: 6292-6299
Publish at: 2020-12-01
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