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29,939 Article Results

Postgraduate students’ perspective on supporting “learning from home” to solve the COVID-19 pandemic

10.11591/ijere.v10i2.21240
Ihsana El Khuluqo , Abdul Rahman A. Ghani , Arum Fatayan
The objective of this present research was to reveal how the postgraduate student perceive of or respond to the online learning process. Quantitative method was adopted in this present research. The results showed that most students who had experienced of the online learning activities encountered some obstacles because they had never conducted Learning From Home (LFH) activities before. The respondents were 428 postgraduate students who actively joined in the LFH activities. There were 316 students used the platform Zoom as the supporting application in the LFH activities. Respondents filled in Google Form, then the collected data could be quickly and accurately processed. Other respondents preferred Google Classroom, WhatsApp and other applications in following the learning activities according to the agreement and features provided in each platform. There were 408 respondents experienced Two-ways communication between the lecturers and the students during the LFH activities. They stated that the limited internet network hindered the online lecturing. There were 31 respondents declared that technology limitations hampered the online lecturing and 105 students revealed that it is the limitations in using the application that caused the online lecturing to become obstacles. 
Volume: 10
Issue: 2
Page: 615-623
Publish at: 2021-06-01

A smart method for spark using neural network for big data

10.11591/ijece.v11i3.pp2525-2534
Md. Armanur Rahman , J. Hossen , Aziza Sultana , Abdullah Al Mamun , Nor Azlina Ab. Aziz
Apache spark, famously known for big data handling ability, is a distributed open-source framework that utilizes the idea of distributed memory to process big data. As the performance of the spark is mostly being affected by the spark predominant configuration parameters, it is challenging to achieve the optimal result from spark. The current practice of tuning the parameters is ineffective, as it is performed manually. Manual tuning is challenging for large space of parameters and complex interactions with and among the parameters. This paper proposes a more effective, self-tuning approach subject to a neural network called Smart method for spark using neural network for big data (SSNNB) to avoid the disadvantages of manual tuning of the parameters. The paper has selected five predominant parameters with five different sizes of data to test the approach. The proposed approach has increased the speed of around 30% compared with the default parameter configuration.
Volume: 11
Issue: 3
Page: 2525-2534
Publish at: 2021-06-01

Using online multiple choice questions with multiple attempts: A case for self-directed learning among tertiary students

10.11591/ijere.v10i2.21008
Ng Wen Lee , Wan Noor Farah Wan Shamsuddin , Lim Chia Wei , Muhammad Nur Adilin Mohd Anuardi , Chan Swee Heng , Ain Nadzimah Abdullah
Criticisms on multiple choice questions (MCQs) include the possibility of students answering MCQs correctly by guessing, and MCQs generally are said to fall short in cultivating independent learning skills, such as taking charge of their learning goals. Countering these common concerns, this research used online MCQ exercises with multiple attempts to investigate the experiences that drove students to become self-directed learners. In this research, 60 students completed two sets of online MCQ exercises with multiple attempts outside of classroom time for six weeks consecutively. Both focus group interviews and an online survey were conducted to investigate the experiences of using online MCQ exercise with multiple attempts in relation to the development of self-directed learning (SDL). The findings of the study showed that the criticisms may be unfounded. Data leads to the conclusion that the majority of the students do not just try to guess at the correct answers. Rather, many of them attempted the online MCQ exercises more than once to improve themselves indicating that they were interested in self-learning. Students also reported that they utilised search and inquiry skills that clearly showed motivated initiatives to plan how to overcome their weaknesses by independently looking for relevant resources, determine their own learning goals, and evaluate their own learning performance as a firm indicator of SDL development. Based on the findings, this study is able to refute the claim that MCQs are unable to cultivate independent learning skills.
Volume: 10
Issue: 2
Page: 553-568
Publish at: 2021-06-01

Impact on teaching in times of COVID-19 pandemic: A qualitative study

10.11591/ijere.v10i2.21129
Alejandro Almonacid-Fierro , Rodrigo Vargas-Vitoria , Ricardo Souza De Carvalho , Manuel Almonacid Fierro
This article makes an analysis of the pedagogical teaching practices used and developed by Chilean physical education teachers during the coronavirus disease 19 (COVID-19) pandemic periods. The virus from China spread around the world, changed our daily lives and as such, at the same time impacted the educational system in a matter of weeks. Confinement led educational systems to eliminate face-to-face and use virtual teaching in order to continue with the teaching-learning processes, including the physical education discipline. From the methodological point of view, the study is installed in the interpretive-qualitative perspective, in such a way that 14 semi-structured interviews were carried by physical education teachers from the Maule-Chile region, via team, Zoom, Skype, because of the pandemic, face-to-face contact was impossible. The result of the study shows the impact on the quality of life of teachers and students because of the confinement. The pedagogical reconfiguration that teachers experienced in a matter of days, led them to use different virtual platforms to continue connected with their students, in order to deploy the learning objectives defined by the Chilean Ministry of Education. However, the foregoing shows the scarce possibility of verifying student learning, due to the difficulties of monitoring and feedback.
Volume: 10
Issue: 2
Page: 432-440
Publish at: 2021-06-01

Intelligent read-out circuit for space radiation detection

10.11591/ijeecs.v22.i3.pp1411-1418
'Umar Abdul Aziz , Siti Fauziah Toha , Rabiatuladawiah Abu Hanifah , Nurul Fadzlin Hasbullah
In the design of the satellite system, space radiation is among the important factors that need to be taken care of as it may contribute to system failure. This research aims to design and implement an intelligent read-out circuit to detect the level of radiation. It has the capability to measure the level of radiation. The capability of the designed device to measure the level of radiation and also the type of radiation exposure are the key components to be considered in the design of the system.  In this research, the intelligent read-out circuit has been successfully designed and tested to detect the level of radiation. The results show the capability of the system to measure the level of radiation and determine the status of radiation level using both visual and sound indicators. The designed system is able to determine the level of radiation in a short time and strengthen by the danger-alert mechanism present in the system.
Volume: 22
Issue: 3
Page: 1411-1418
Publish at: 2021-06-01

Pre-trained deep learning models in automatic COVID-19 diagnosis

10.11591/ijeecs.v22.i3.pp1540-1547
Ahmed Wasif Reza , Md Mahamudul Hasan , Nazla Nowrin , Mir Moynuddin Ahmed Shibly
Coronavirus Disease (COVID-19) is a devastating pandemic in the history of mankind. It is a highly contagious flu that can spread from human to human without revealing any symptoms. For being so contagious, detecting patients with it and isolating them has become the primary concern for healthcare professionals. This study presented an alternative way to identify COVID-19 patients by doing an automatic examination of chest X-rays of the patients. To develop such an efficient system, six pre-trained deep learning models were used. Those models were: VGG16, InceptionV3, Xception, DenseNet201, InceptionResNetV2, and EfficientNetB4. Those models were developed on two open-source datasets that have chest X-rays of patients diagnosed with COVID-19. Among the models, EfficientNetB4 achieved better performances on both datasets with 96% and 97% of accuracies. The empirical results were also exemplary. This type of automated system can help us fight this dangerous virus outbreak.
Volume: 22
Issue: 3
Page: 1540-1547
Publish at: 2021-06-01

Amazigh-Sys: Intelligent system for recognition of amazigh words

10.11591/ijai.v10.i2.pp482-489
Rachid Ammari , Lahbib Zenkouar
Amazigh-sys is an intelligent morphological analysis system for Amazigh language based on xerox’s finite-state transducer (XFST). Our system can process simultaneously five lexical units. This paper begins with the development of Amazigh lexicon (AMAlex) for attested nouns, verbs, pronouns, prepositions, and adverbs and the characteristics relating to each lemma. A set of rules are added to define the inflectional behavior and morphosyntactic links of each entry as well as the relationship between the different lexical units. The use of finite-state technology ensures the bidirectionality of our system (analysis and generation). Amazigh-sys is the first general morphological analysis system for Amazigh based on xerox finite state able to process and recognize all lexical units and ensures a high recognition rate of input words. This contribution facilitates the implementation of other applications related to the automatic processing of the Amazigh language.
Volume: 10
Issue: 2
Page: 482-489
Publish at: 2021-06-01

Design and implementation of remotely monitoring system for pH level in Baghdad drinking water networks

10.12928/telkomnika.v19i3.12921
Hussein A.; University of Information Technology and communications Mohammed , Sura F.; University of Information Technology and communications ismail
Many people in the recent days have suffering from number of diseases due to unsafe and impure drinking water, especially in rural areas. As typical laboratory experiments and official water quality tests take considerable amount of time to obtain results and due to non availability of a simple device that can measure such water quality parameters in real time, therefore in this paper a remote pH level monitoring system for Baghdad drinking water system is proposed. A PH level sensing and monitoring nodes are distributed at different location. These nodes are proactively measured pH level of water and send data to the maintenance center to give them overall picture about pH level via global position system (GSM). This proposed system gives a robust, low-cost and effective method for the drinking water maintenance center to measure and monitoring the water quality in real time environment.
Volume: 19
Issue: 3
Page: 1030-1038
Publish at: 2021-06-01

Studying faculty members’ readiness to use Shaqra University e-learning platform

10.11591/ijeecs.v22.i3.pp1556-1564
Raed Alotaibi , Abdulrahman Alghamdi
In Saudi Arabia, most universities are seeking to implement e-learning to improve education access and processes. Although some universities have already implemented e-learning, most have not. Shaqra University is aiming to implement an e-learning system. Therefore, through the use of a questionnaire, this study examines faculty members’ readiness to use the e-learning platform and assesses their readiness based on gender differences and user experience. Factors considered were usage self-efficacy, self-confidence in dealing with e-learning, Attitude towards e-learning and educational needs towards e-learning. The results revealed that, based on all these factors, faculty members were ready to use the platform of e-learning. There were no differences between male and female participants in self-efficacy in using information and communications technology, self-confidence in e-learning and educational needs towards e-learning. The females’ mean score was significantly higher than the males’ mean score. Between faculty members with no experience and faculty members’ who were experienced in e-learning, user experience was significantly different for self-efficacy of using information and communications technology, self-confidence in e-learning and attitude towards e-learning. These results revealed that faculty members are ready to use a platform of e-learning and these results may help decision makers in Shaqra University to successfuly adopt an e-learning platform.
Volume: 22
Issue: 3
Page: 1556-1564
Publish at: 2021-06-01

Automated tumor segmentation in MR brain image using fuzzy c-means clustering and seeded region methodology

10.11591/ijai.v10.i2.pp284-290
Mustafa Zuhaer Nayef AL-Dabagh
Automated segmentation of a tumor is still a considerably exciting research topic in the medical imaging processing field, and it plays a considerable role in forming a right diagnosis, to aid effective medical treatment. In this work, a fully automated system for segmentation of the brain tumor in MRI images is introduced. The suggested system consists of three parts: Initially, the image is pre-processed to enhance contrast, eliminate noise, and strip the skull from the image using filtering and morphological operations. Secondly, segmentation of the image happens using two techniques, fuzzy c-means clustering (FCM) and with the application of a seeded region growing algorithm (SGR). Thirdly, this method proposes a post-processing step to smooth segmentation region edges using morphological operations. The testing of the proposed system involved 233 patients, which included 287 MRI images. A comparison of the results ensued, with the manual verification of the traces performed by doctors, which ultimately proved an average Dice Coefficient of 90.13% and an average Jaccard Coefficient of 82.60% also, by comparison with traditional segmentation techniques such as FCM method. The segmentation results and quantitative data analysis demonstrates the effectiveness of the suggested system.
Volume: 10
Issue: 2
Page: 284-290
Publish at: 2021-06-01

Overlapped hierarchical clusters routing protocol for improving quality of service

10.12928/telkomnika.v19i3.18354
Hayder Fakher; Mustansiriyah University Jassim , Mohammed A.; Mustansiriyah University Tawfeeq , Sawsan M.; Mustansiriyah University Mahmoud
The rapid development in communications and sensors technologies make wireless sensor networks (WSNs) as essential key in several advanced applications such as internet of things (IoT). The increasing demands on using WSNs required high quality of services (QoS) because most WSNs applications have critical requirements. This work aims to offer a routing protocol to improve the QoS in WSNs, taking in consideration its ability to prolong the lifetime of the network, optimize the utilization of the limited bandwidth available, and decrease the latency that accompanies the packets transmitted to the gateway. The proposed protocol is called overlapped hierarchical cluster routing protocol (OHCRP). OHCRP is compared with the traditional routing protocols such as SPEED, and THVR. The results show that OHCRP reduces latency effectively and achieve high energy conservation, which lead to increase the network lifetime and insure network availability.
Volume: 19
Issue: 3
Page: 705-715
Publish at: 2021-06-01

School space selection preferences: Architectural perspective toward formal school

10.11591/ijere.v10i2.20726
Kurnia Widiastuti , Mohamad Joko Susilo , Hanifah Sausan Nurfinaputri
School space plays an essential role in creating a pleasurable learning atmosphere. The tendency of everyone to choose a school space also varies. By knowing this trend pattern, schools can be designed to improve student learning effectiveness. The purpose of this study was to find out which school spaces students choose to study, what kind of room criteria are needed, and distribution patterns of students' preference choices. This research used both the qualitative exploratory and quantitative methods using an open-ended question questionnaire for data collection. Data analysis techniques used qualitative analysis methods consisting of open coding, axial coding, and selective coding. The results showed that the library, mosque, and multimedia laboratory were the most preferred space for students to study at school. Some factors that influence the selection include thermal comfort, completeness of supporting facilities, and acoustic comfort.
Volume: 10
Issue: 2
Page: 502-511
Publish at: 2021-06-01

A hybrid deep learning model for air quality time series prediction

10.11591/ijeecs.v22.i3.pp1611-1618
Samit Bhanja , Abhisek Das
Air quality (mainly PM2.5) forecasting plays an important role in the early detection and control of air pollution. In recent times, numerous deep learning-based models have been proposed to forecast air quality more accurately. The success of these deep learning models heavily depends on the two key factors viz. proper representation of the input data and preservation of temporal order of the input data during the feature’s extraction phase. Here we propose a hybrid deep neural network (HDNN) framework to forecast the PM2.5 by integrating two popular deep learning architectures, viz. Convolutional neural network (CNN) and bidirectional long short-term memory (BDLSTM) network. Here we build a 3D input tensor so that CNN can extract the trends and spatial features more accurately within the input window. Here we also introduce a linking layer between CNN and BDLSTM to maintain the temporal ordering of feature vectors. In the end, our proposed HDNN framework is compared with the state-of-the-art models, and we show that HDNN outruns other models in terms of prediction accuracy.
Volume: 22
Issue: 3
Page: 1611-1618
Publish at: 2021-06-01

Fire-fighting UAV with shooting mechanism of fire extinguishing ball for smart city

10.11591/ijeecs.v22.i3.pp1320-1326
Nastaran Reza Nazar Zadeh , Ameralden H. Abdulwakil , Mike Joshua R. Amar , Bernadette Durante , Christian Vincent Nico Reblando Santos
With the growth of technology and massive city development, firefighting services have become more challenging to cope with a smart-city concept. One of the challenges that firefighters are facing is reaching the top floors of high-raised buildings. Firefighters need heavy and oversized pieces of equipment to reach top floors, which they sometimes fail to deliver on time due to big cities' traffic. The proposed solution to this global problem is using firefighting unmanned aerial vehicle (UAV) to reach the top floors fast and efficiently; It can also provide a better vision for the firefighting team and slow down the spread of fire using fire extinguishing ball. In this paper, a noble design for a Firefighting UAV with shooting and dropping mechanism of fire extinguishing ball has been developed and successfully tested. A Camera with night vision has been integrated into the UAV to provide a helpful aid for firefighters. The UAV has a controller with a 2.4 GHz radio frequency (RF) signal and video surveillance to regulate the UAV's movement. The controller is also for activating the shooting and dropping mechanism. The researchers examined the behavior of the drone in terms of its stability and functionality.
Volume: 22
Issue: 3
Page: 1320-1326
Publish at: 2021-06-01

A new approach for extracting and scoring aspect using SentiWordNet

10.11591/ijeecs.v22.i3.pp1731-1738
Tuan Anh Tran , Jarunee Duangsuwan , Wiphada Wettayaprasit
Aspect-based online information on social media plays a vital role in influencing people’s opinions when consumers concern with their decisions to make a purchase, or companies intend to pursue opinions on their product or services. Determining aspect-based opinions from the online information is necessary for business intelligence to support users in reaching their objectives. In this study, we propose the new aspect extraction and scoring system which has three procedures. The first procedure is normalizing and tagging part-of-speech for sentences of datasets. The second procedure is extracting aspects with pattern rules. The third procedure is assigning scores for aspects with SentiWordNet. In the experiments, benchmark datasets of customer reviews are used for evaluation. The performance evaluation of our proposed system shows that our proposed system has high accuracy when compared to other systems.
Volume: 22
Issue: 3
Page: 1731-1738
Publish at: 2021-06-01
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