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29,939 Article Results

An investigation study for risk calculation of security vulnerabilities on android applications

10.11591/ijeecs.v25.i3.pp1736-1748
Radhwan M. Abdullah , Abedallah Zaid Abualkishik , Najla Matti Isaacc , Ali A. Alwan , Yonis Gulzar
Applications within mobile devices, although useful and entertaining, come with security risks to private information stored within the device such as name, address, and date of birth. Standards, frameworks, models, and metrics have been proposed and implemented to combat these security vulnerabilities, but they remain to persist today. In this review, we discuss the risk calculation of android applications which is used to determine the overall security of an application. Besides, we also present and discuss the permission-based access control models that can be used to evaluate application access to user data. The study also focuses on examining the predictive analysis of security risks using machine learning. We conduct a comprehensive review of the leading studies accomplished on investigating the vulnerabilities of the applications for the Android mobile platform. The review examines various well-known vulnerabilities prediction models and highlights the sources of the vulnerabilities, prediction technique, applications and the performance of these models. Some models and frameworks prove to be promising but there is still much more research needed to be done regarding security for Android applications.
Volume: 25
Issue: 3
Page: 1736-1748
Publish at: 2022-03-01

A review on efficiency improvement methods in organic Rankine cycle system: an exergy approach

10.11591/ijaas.v11.i1.pp1-10
Gollangi Raju , Nagamalleswara Rao Kanidarapu
Exergy, one of the handed-down energy conservation techniques, which can obtain from thermodynamic laws (first and second), will disclose the work presented within the system, the amount of irreversibility as well as what are the possible ways to reduce inefficiencies in the system. This discourse mainly highlighted various techniques and possible methods for efficiency improvement in the organic Rankine cycle (ORC). That means mainly concentrated on following key parameters like the selection of working fluid, suitable expander, the different heat sources of an evaporator, and modifications in heat exchanger based on the application of ORC system through an exergy approach for better performance, decrease energy losses, and destruction rate. This review can help to pontificate for better-summarized results that were done before and suggest some ideas for how to select an optimized parameter for better efficiency and to decrease the destruction rate in the ORC system. 
Volume: 11
Issue: 1
Page: 1-10
Publish at: 2022-03-01

The correlation of the understanding of Indonesian history, multiculturalism, and historical awareness to students’ nationalistic attitudes

10.11591/ijere.v11i1.22075
Muhammad Basri , Johan Setiawan , Marzius Insani , Muhammad Rijal Fadli , Kian Amboro , Kuswono Kuswono
This study aimed to analyze the relationship between understanding Indonesian history, multiculturalism, and historical awareness with the nationalist attitudes of state high school students in Yogyakarta. This type of research was correlational research with a quantitative approach. The sample consisted of 126 students. Data collection used tests and questionnaires. The test was used to reveal data about understanding of Indonesian history and multiculturalism, while the questionnaire was used for revealing students’ historical awareness and nationalistic attitudes. The validity of the instrument used a biserial point correlation test and a reliability test with the KR-20 formula. The data then were analyzed by using quantitative descriptive analysis technique. The pre-requisite analysis consisted of the normality test, linearity test and multicollinearity test. The hypothesis testing used Product Moment Correlation, multiple correlation, relative contribution, and effective contribution. The results showed that there is a positive and significant relationship between understanding of Indonesian history, multiculturalism, and historical awareness with students' nationalism. History learning will be much more meaningful if these four concepts are used as the objectives of history learning.
Volume: 11
Issue: 1
Page: 369-376
Publish at: 2022-03-01

Expressive writing during the COVID-19 pandemic: themes of mixed expressive writing

10.11591/ijphs.v11i1.21101
Hao Yue Tay , Chengen Yu , Chen Sung Wong , Kususanto Ditto Prihadi
In order to curb the depression levels among youth during the coronavirus disease 2019 (COVID-19) outbreak, we examined the recurrent themes of mixed expressive writing among undergraduates during the pandemic. Previous quantitative studies had emphasized on the effectiveness of expressive writing in reducing depressive symptoms, however, less qualitative studies were conducted in evaluating the content within people’s writings. As the pandemic had caused major disruptions among people, we implemented mixed expressive writing in capturing both positive and negative experiences during the pandemic. Ten participants were recruited to perform mixed expressive writing twice per week, for four consecutive weeks. Thematic analysis was used in analyzing their writings and forming the emerged themes. Five themes were formed, which included ‘school’, ‘relationships’, ‘reflection’, ‘work’, and “random incidents’. Future research should examine the effectiveness of expressive writing in writing specific themes on improving its respective psychological constructs.
Volume: 11
Issue: 1
Page: 195-203
Publish at: 2022-03-01

Frequency recommendation for long term evolution network implementation using simple multi attribute rating technique

10.11591/ijeecs.v25.i3.pp1563-1570
Putri Angelia , Rendy Munadi , Nachwan Mufti Adriansyah
The increasing demand for telecommunication services causes data traffic density. Therefore, in this research, the long-term evolution (LTE) network expansion was carried out using a choice of frequency bands of 700 MHz, 2100 MHz, and 2300 MHz. The analysis was carried out from the technical and economic aspects. Frequency band recommendations were obtained using the simple multi-attribute rating technique (SMART) method. This research was conducted using a case study of Semarang City. Based on the simulation results, the average of reference signal receive power (RSRP) values for frequency 700 MHz and 2300 MHz is in the very good range, while the frequency of 2100 MHz is in the good range. The signal to interference noise ratio (SINR) values for the three frequencies are in the normal category and the throughput values are in the very good category. The techno-economic calculations of the three frequencies, namely the value of internal rate of return (IRR), net present value (NPV), and payback period are included in the business category that is feasible to do. Based on the ranking results, the 700 MHz frequency is the most superior, both in terms of technical and economic aspects.
Volume: 25
Issue: 3
Page: 1563-1570
Publish at: 2022-03-01

Analyzing semantic similarity amongst textual documents to suggest near duplicates

10.11591/ijeecs.v25.i3.pp1703-1711
Viji Devarajan , Revathy Subramanian
Data deduplication techniques removing repeated or redundant data from the storage. In recent days, more data has been generated and stored in the storage environment. More redundant and semantically similar content of the data occupied in the storage environment due to this storage efficiency will be reduced and cost of the storage will be high. To overcome this problem, we proposed a method hybrid bidirectional encoder representation from transformers for text semantics using graph convolutional network hybrid bidirectional encoder representation from transformers (BERT) model for text semantics (HBTSG) word embedding-based deep learning model to identify near duplicates based on the semantic relationship between text documents. In this paper we hybridize the concepts of chunking and semantic analysis. The chunking process is carried out to split the documents into blocks. Next stage we identify the semantic relationship between documents using word embedding techniques. It combines the advantages of the chunking, feature extraction, and semantic relations to provide better results.
Volume: 25
Issue: 3
Page: 1703-1711
Publish at: 2022-03-01

An optimal proportional integral derivative tuning for a magnetic levitation system using metamodeling approach

10.11591/ijeecs.v25.i3.pp1356-1366
Abdualrhman Abdalhadi , Herman Wahid , Dirman Hanafi Burhanuddin
A magnetic levitation system (MLS) is a complex nonlinear system that requires an electromagnetic force to levitate an object in the air. The electromagnetic field is extremely sensitive to noise which can cause the acceleration on the spherical object, leading it to move into the unbalanced region. This paper presents a comparative assessment of controllers for the magnetic levitation system using proportional integral derivative (PID) controller based optimal tuning. The analysis was started by deriving the mathematical model followed by the implementation of radial basis function neural network (RBFNN) based metamodel. The optimal tuning of the PID controller has offered better transient responses with the improvement of overshoot and the rise time as compared to the standard optimization methods. It is more robust and tolerant as compared to gradient descent method. The simulation output using the radial basis based metamodel approach showed an overshoot of 9.34% and rise time of 9.84 ms, which are better than the gradient descent (GD) and conventional PID methods. For the verification purpose, a Simscape model has been developed which mimic the real model. It was found that the model has produced about similar performance as what has been obtained from the MATLAB simulation.
Volume: 25
Issue: 3
Page: 1356-1366
Publish at: 2022-03-01

Machine learning algorithms for electrical appliances monitoring system using open-source systems

10.11591/ijai.v11.i1.pp300-309
Viet Hoang Duong , Nam Hoang Nguyen
Two main methods to minimize the impact of electricity generation on the environment are to exploit clean fuel resources and use electricity more effectively. In this paper, we aim to change the user's electricity usage by providing feedback about the electrical energy consumed by each device. The authors introduced two devices, load monitoring device (LMD) and activity monitoring device (AMD). The function of the LMD is to provide feedback on the operating status and energy consumption of electrical appliances in a home, which will help people consume electrical energy more efficiently. The parameters of LMD are used to predict the on/off state of each electrical appliance thanks to machine learning algorithms. AMD with audio sensors can assist LMD to distinguish electrical devices with the same or varying power over time. The system was tested for three weeks and achieved a state prediction accuracy of 93.60%.
Volume: 11
Issue: 1
Page: 300-309
Publish at: 2022-03-01

Modelling minicab drivers' disordered behaviour for choosing passenger and destination in Akure, Nigeria

10.11591/ijaas.v11.i1.pp19-28
Adetayo Olaniyi Adeniran , Olorunfemi Samuel , Njoku Ikpechukwu
This study investigated the disordered behaviour of minicab drivers for choosing passenger and destination in Akure using the multinomial model and nested logit model respectively. Information was gathered by the distribution of questionnaires to minicab drivers plying the Federal University of Technology Akure (FUTA) North gate to the Oja-Oba axis in Akure, Nigeria. The objectives were to validate the performance of logit models; to identify the major parameters for selecting passenger and destination by disordered minicab drivers, and to examine the interrelationships of variables employed. Primary data was obtained from 314 respondents. The study found that the nested logit model gives a better utility value than the multinomial logit model with ρ02 = 0.48 more than ρc2 = 0.46 which justifies the assertion. Also, the major parameters for selecting passengers and destination by disordered minicab drivers in Akure are transport rates variable, distance variable, and travel time variable. The study recommends that an accurate pricing policy of minicab operation should be efficiently formulated, implemented, and enacted to prevent overcharging and undercharging.
Volume: 11
Issue: 1
Page: 19-28
Publish at: 2022-03-01

Multi-feature based automatic facial expression recognition using deep convolutional neural network

10.11591/ijeecs.v25.i3.pp1406-1419
Anjali Dixit , Tanmay Kasbe
Deep multi-task learning is one of the most challenging research topics widely explored in the field of recognition of facial expression. Most deep learning models rely on the class labels details by eliminating the local information of the sample data which deteriorates the performance of the recognition system. This paper proposes multi-feature-based deep convolutional neural networks (D-CNN) that identify the facial expression of the human face. To enhance the accuracy of recognition systems, the multi-feature learning model is employed in this study. The input images are preprocessed and enhanced via three filtering methods i.e., Gaussian, Wiener, and adaptive mean filtering. The preprocessed image is then segmented using a face detection algorithm. The detected face is further applied with local binary pattern (LBP) that extracts the facial points of each facial expression. These are then fed into the D-CNN that effectively recognizes the facial expression using the features of facial points. The proposed D-CNN is implemented, and the results are compared to the existing support vector machine (SVM). The analysis of deep features helps to extract the local information from the data without incurring a higher computational effort.
Volume: 25
Issue: 3
Page: 1406-1419
Publish at: 2022-03-01

Quality of life and its demographic predictors among workers at a plastic factory in Malaysia: a cross-sectional study

10.11591/ijphs.v11i1.21275
Asem Iyad Ahmed Alnabih , Belal Aldabbour , Mohd Faizal Mat Tahir , Nor Kamaliana Khamis
Quality of life (QOL) is an individualized measure that reflects a person’s subjective feelings towards the different aspects of his or her life and incorporates them into his overall health evaluation. The WHOQOL-BREF is a QOL measurement tool that has been validated in worldwide and local studies, with good reliability and sensitivity. WHOQOL-BREF questionnaire was used to evaluate the QOL of 89 workers at a plastic factory in Selangor, Malaysia. These were compared using t-test and Spearman’s bivariate correlation test to assess for significant correlations and predictors of performance in the different domains. The performance of the sample, both overall and for individual domains, was significantly lower than reported in previous studies. Local workers, highly educated workers, workers with shorter employment, and workers who did not take overtime performed significantly better than their respective counterparts. Also, lower education, foreign nationality, longer employment at the factory, overtime, and crushing jobs were associated with lower QOL scores. Studies evaluating QOL in industrial workers in Malaysia are scarce. Our sample is more diverse than the previous similar studies from Malaysia, and hence it offers new insights into the QOL of plastic industrial workers in the country.
Volume: 11
Issue: 1
Page: 106-112
Publish at: 2022-03-01

Investing in Malaysian healthcare using technique for order preference by similarity to ideal solution

10.11591/ijeecs.v25.i3.pp1723-1730
Farah Waheeda Azhar , Zati Halwani Abd Rahim , Norasyikin Abdullah Fahami , Siti Khatijah Nor Abdul Rahim , Hilwana Abd Karim
The purpose of this research is to assess the financial performance of Malaysian Healthcare companies using the multi-criteria and decision-making method, namely technique for order preference by similarity to ideal solution (TOPSIS). The financial data of 20 companies in 2019 are retrieved from Datastream. For many years, ratios of financial aspects have been employed to analyse the companies’ financial performance. However, some studies indicate that the traditional ratio analysis is insufficient to measure a firm's financial performance. Thus, this paper employs the technique for order preference by similarity to ideal solution, or simply TOPSIS, to gain a more comprehensive result. The TOPSIS approach involves seven steps, utilizing significant ratios in financial aspect such as debt ratio, debt to equity ratio, current ratio, return on equity (ROE), acid-test ratio, earnings per share (EPS), and return on asset (ROA), as the criteria to evaluate the companies' financial performances. The result of this study ranks 20 healthcare companies in Malaysia and makes recommendations for investment-worthy companies to the investors, allowing the maximization of investment benefits. The results from this research are crucial for investors, companies, market participants, public and private policymakers to enhance their investment decision-making.
Volume: 25
Issue: 3
Page: 1723-1730
Publish at: 2022-03-01

Joint inter-intra representation learning for pornographic video classification

10.11591/ijeecs.v25.i3.pp1481-1488
Dinh-Duy Phan , Quang-Huy Nguyen , Thanh-Thien Nguyen , Hoang-Loc Tran , Duc-Lung Vu
This paper addresses video inter-intra similarity retrieval for pornographic classification. The main approaching method is obtaining the internal representation and external similarity between a single unlabeled video and batches of labeled videos, then combining together to determine its label. For the internal representation, we extracted inner features within frames and clustered them to find the representative centroid as the intra-feature. For the external similarity, we utilized a similarity video learning named ViSiL to calculate distance score between two videos using chamfer similarity. With distance scores between input video and batches of pornographic/nonpornographic videos, the inter feature of the input video is obtained. Finally, the inter similarity vector and the intra representation are then concatenated together and fed to a final classifier to identify whether the video is for adults or not. In experiment, our method performs 96.88% accuracy on NPDI-2k, achieved a comparative result comparing to other state-of-the-art methods on the pornographic classification problem.
Volume: 25
Issue: 3
Page: 1481-1488
Publish at: 2022-03-01

Learning achievement of extroverted students in algebraic operations by tutorial learning: A single subject research

10.11591/ijere.v11i1.21747
Sri Adi Widodo , Desi D. Sari , Samsul Maarif , Dafid S. Setiana , Krisna S. Perbowo
The purpose of this study was to improve the learning achievement of extroverted students on algebraic operations using the tutorial method. This type of research was a single subject with AB design, where A is the baseline condition, and B is an intervention condition. The research subjects were selected based on a purposive sampling technique with the help of the Keirsey Temperament Sorter (KTS) test in selecting extrovert subjects. Data collection techniques were using observation and test methods. Observation was used to collect data and record all behavior of extrovert subjects during the study. The tests in this study were the KTS and learning achievement tests. The KTS was used to determine subjects with an extroverted temperament while learning achievement tests are used to determine the ability of extrovert students to solve algebraic operation questions at the junior high school level. The results showed that the tutorial method had a positive effect on extrovert student learning achievement in algebraic operation material. This can be seen from the results of the analysis in conditions and between conditions which show that the intervention condition has a better tendency when compared to the baseline condition to the intervention. Besides that, the mean level obtained at the baseline is 50 and increases in the intervention condition with a mean level of 88.5.
Volume: 11
Issue: 1
Page: 99-107
Publish at: 2022-03-01

AraBERT transformer model for Arabic comments and reviews analysis

10.11591/ijai.v11.i1.pp379-387
Hicham EL Moubtahij , Hajar Abdelali , El Bachir Tazi
Arabic language is rich and complex in terms of word morphology compared to other Latin languages. Recently, natural language processing (NLP) field emerges with many researches targeting Arabic language understanding (ALU). In this context, this work presents our developed approach based on the Arabic bidirectional encoder representations from transformers (AraBERT) model where the main required steps are presented in detail. We started by the input text pre-processing, which is, then, segmented using the Farasa segmentation technique. In the next step, the AraBERT model is implemented with the pertinent parameters. The performance of our approach has been evaluated using the ARev dataset which contains more than 40,000 comments-remarks records relate to the tourism sector such as hotel reviews, restaurant reviews and others. Moreover, the obtained results are deeply compared with other relevant states of the art methods, and it shows the competitiveness of our approach that gives important results that can serve as a guide for further improvements in this field.
Volume: 11
Issue: 1
Page: 379-387
Publish at: 2022-03-01
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