Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

29,922 Article Results

An application of machine learning on corporate tax avoidance detection model

10.11591/ijai.v9.i4.pp721-725
Rahayu Abdul Rahman , Suraya Masrom , Normah Omar , Maheran Zakaria
Corporate tax avoidance reduces government revenues which could limit country development plans. Thus, the main objectives of this study is to establish a rigorous and effective model to detect corporate tax avoidance to assist government to prevent such practice. This paper presents the fundamental knowledge on the design and implementation of machine learning model based on five selected algorithms tested on the real dataset of 3,365 Malaysian companies listed on bursa Malaysia from 2005 to 2015. The performance of each machine learning algorithms on the tested dataset has been observed based on two approaches of training. The accuracy score for each algorithm is better with the cross-validation training approach. Additionationally, with the cross-validation training approach, the performances of each machine learning algorithm were tested on different group of features selection namely industry, governance, year and firm characteristics. The findings indicated that the machine learning models present better reliability with industry, governance and firm characteristics features rather than single year determinant mainly with the Random Forest and Logistic Regression algorithms.
Volume: 9
Issue: 4
Page: 721-725
Publish at: 2020-12-01

Aging study of a lead-acid storage bank in a multi-source hybrid system

10.11591/ijeecs.v20.i3.pp1109-1117
El Mehdi Laadissi , Jaouad Khalfi , Fouad Belhora , Chouaib Ennawaoui , Abdessamad El Ballouti
Autonomous and grid-connected systems play an important role in the massive integration of renewable energy sources necessary for the global development of a sustainable society. In this regard, the analysis of the behavior of electrochemical storage devices such as lead-acid batteries installed on hybrid energy systems and microgrids in terms of lifespan and economic profitability is an important research subject. The purpose of this article is to present a methodology for calculating the aging rate of a storage battery inserted in a hybrid multisource system. The approach consists in first knowing the solicitations of the battery during a year knowing at every moment its state of charge. This curve is obtained from a dynamic simulator taking into account the intermittences of the sources and the load. The second step is to determine the number of cycles and the depth of discharge of each from the stat of charge. Finally, based on the battery life characteristic given by the manufacturer (cycle number vs. discharge depth), the aging rate of the battery for one year of operation is determined.
Volume: 20
Issue: 3
Page: 1109-1117
Publish at: 2020-12-01

Classification and evaluation of digital forensic tools

10.12928/telkomnika.v18i6.15295
Azra; Jamia Millia Islamia (A Central University) Parveen , Zishan Husain; Jamia Millia Islamia (A Central University) Khan , Syed Naseem; Jamia Millia Islamia (A Central University) Ahmad
Digital forensic tools (DFTs) are used to detect the authenticity of digital images. Different DFTs have been developed to detect the forgery like (i) forensic focused operating system, (ii) computer forensics, (iii) memory forensics, (iv) mobile device forensics, and (v) software forensics tools (SFTs). These tools are dedicated to detect the forged images depending on the type of the applications. Based on our review, we found that in literature of the DFTs less attention is given to the evaluation and analysis of the forensic tools. Among various DFTs, we choose SFTs because it is concerned with the detection of the forged digital images. Therefore,the purpose of this study is to classify the different DFTs and evaluate the software forensic tools (SFTs) based on the different features which are present in the SFTs. In our work, we evaluate the following five SFTs, i.e.,“FotoForensics”, “JPEGsnoop”, “Ghiro”, “Forensically”, and “Izitru”, based on different features so that new research directions can be identified for the development of the SFTs.
Volume: 18
Issue: 6
Page: 3096-3106
Publish at: 2020-12-01

Perceptions and experiences of students on the use of interactive online learning technologies in Mauritius

10.11591/ijere.v9i4.20692
Parmeswar Ramkissoon , Louis Jinot Belle , Trishnee Bhurosy
With the advent of e-learning, advocates use the term interactivity instead of interaction among students, and between the teacher and the students. Many universities use Moodle for online teaching and learning. This paper explores the perceptions and experiences of students in three Higher Education Institutions (HEIs) in Mauritius. A mixed-methods approach was used, with an online survey questionnaire administered to 600 students and focus group discussions were conducted with 15 students from these institutions. It was found that 68.4% of respondents used WhatsApp compared to only 23.6% of them who used the e-learning platform, Moodle. There were no associations between the use or frequency of using WhatsApp or Facebook and the types of HEI to which the students belonged. Students preferred WhatsApp due to its facility for knowledge sharing and construction, its interactivity, its usability, respect for privacy and instant communication. From the findings, it is recommended that HEIs bring a shift in their approaches to teaching and learning from cognitivism to socio-constructivism, connectivism and heutagogy.
Volume: 9
Issue: 4
Page: 833-839
Publish at: 2020-12-01

Average dynamical frequency behaviour for multi-area islanded micro-grid networks

10.12928/telkomnika.v18i6.16805
M. Saifuzam; Universiti Teknikal Malaysia Melaka Jamri , Muhammad Nizam; Universiti Teknikal Malaysia Melaka Kamarudin , Mohd Luqman; Universiti Teknikal Malaysia Melaka Mohd Jamil
A micro-grid is a part of power system which able to operates in grid or islanding mode. The most important variable that able to give us information about the stability in islanded micro-grid network is the frequency dynamical responses. The frequency analysis for multi-area micro-grid network model may involve a complicated of mathematical equations. This makes the researcher intending to omit several unnecessary parameters in order to simplify the equations. The purpose of this paper is to show an approach to derive the mathematical equations to represent the average behavior of frequency dynamical responses for two different micro-grid areas. Both of networks are assumed to have non-identical distributed generator behavior with different parameters. The prime mover and speed governor systems are augmented with the general swing equation. The tie line model and the information of rotor angle was considered. Then, in the last section, the comparison between this technique with the conventional approach using centre of inertia (COI) technique was defined.
Volume: 18
Issue: 6
Page: 3324-3330
Publish at: 2020-12-01

Web application authentication using ZKP and novel 6D chaotic system

10.11591/ijeecs.v20.i3.pp1522-1529
Shatha J. Mohammed , Sadiq A. Mehdi
Text password has long been a dominant approach to user authentication used by a huge quantity of Internet services. Web applications are now widely used for the implementation of a range of significant services. The securing of such applications has thus become a significant process. Currently the frequent use of passwords and the need for them make them more vulnerable to theft or guesswork. In the proposed research, the researcher designed an algorithm that has the ability to perform registration or to access web applications safely. The researcher designed an algorithm in the proposed research, which has the ability to securely perform registration or access web applications. The proposed idea based on the notion of Zero-knowledge proof. A complex generation of random number initiated by proposed novel 6D-Hyper chaotic system. The bottom line is that both parties (web application, user), have a secret number. These two numbers used to do the process of registration without requiring a password. Results from the research showed the importance of the proposed method by which the keys were managed and distributed in a safe and effective way.
Volume: 20
Issue: 3
Page: 1522-1529
Publish at: 2020-12-01

Visual control system for grip of glasses oriented to assistance robotics

10.11591/ijece.v10i6.pp6330-6339
Robinson Jimenez-Moreno , Astrid Rubiano , Jose L. Ramirez
Assistance robotics is presented as a means of improving the quality of life of people with disabilities, an application case is presented in assisted feeding. This paper presents the development of a system based on artificial intelligence techniques, for the grip of a glass, so that it does not slip during its manipulation by means of a robotic arm, as the liquid level varies. A faster R-CNN is used for the detection of the glass and the arm's gripper, and from the data obtained by the network, the mass of the beverage is estimated, and a delta of distance between the gripper and the liquid. These estimated values are used as inputs for a fuzzy system which has as output the torque that the motor that drives the gripper must exert. It was possible to obtain a 97.3% accuracy in the detection of the elements of interest in the environment with the faster R-CNN, and a 76% performance in the grips of the glass through the fuzzy algorithm.
Volume: 10
Issue: 6
Page: 6330-6339
Publish at: 2020-12-01

Reliable and efficient data dissemination schemein VANET: a review

10.11591/ijece.v10i6.pp6423-6434
Sami Abduljabbar Rashid , Lukman Audah , Mustafa Maad Hamdi , Mohammed Salah Abood , Sameer Alani
Vehicular ad-hoc network (VANET), identified as a mobile ad hoc network MANETs with several added constraints. Basically, in VANETs, the network is established on the fly based on the availability of vehicles on roads and supporting infrastructures along the roads, such as base stations. Vehicles and road-side infrastructures are required to provide communication facilities, particularly when enough vehicles are not available on the roads for effective communication. VANETs are crucial for providing a wide range of safety and non-safety applications to road users. However, the specific fundamental problem in VANET is the challenge of creating effective communication between two fast-moving vehicles. Therefore, message routing is an issue for many safety and non-safety of VANETs applications. The challenge in designing a robust but reliable message dissemination technique is primarily due to the stringent QoS requirements of the VANETs safety applications. This paper investigated various methods and conducted literature on an idea to develop a model for efficient and reliable message dissemination routing techniques in VANET.
Volume: 10
Issue: 6
Page: 6423-6434
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

Fall risk in the aging population: fall prevention using smartphones technology and multiscale sample entropy

10.12928/telkomnika.v18i6.15980
Yeison Alberto; Universidad Católica de Manizales Garcés-Gómez , Paula Andrea; Universidad Católica de Manizales Duque , Angela Viviana; Universidad de Caldas Alzate-García , Nicolás; Universidad Nacional de Colombia-Sede Manizales Tóro-García
Falls are an important aspect of older people's health because they trigger major injuries and even death in one-third of fallen patients, making them  a major public health problem. Given the risk of physical and psychological injury, if serious injuries occur as a result of a fall, prevention is an important consideration in today's health care landscape, where the population is predominantly adult world wide. This paper presents the applicability ofa simple technique of analysis of gait signals capturedby mobile devices with the objective to the generation of early warnings on the risk of falls in older adults, which correlates with subjective scales. The technique is tested in a population of patients showing results of the significant risk of falls inpatients that the subjective scales could not detect, demonstrating that mobile devices and signal processing can become important tools in the service of elderly care in fall risk prevention.
Volume: 18
Issue: 6
Page: 3058-3066
Publish at: 2020-12-01

Design of frequency selective surface comprising of dipoles using artificial neural network

10.11591/ijaas.v9.i4.pp276-283
Monojit Rudra , P Soni Reddy , Rajatsubhra Chakraborty , Partha Pratim Sarkar
This paper depicts the design of Frequency Selective Surface (FSS) comprising of dipoles using Artificial Neural Network (ANN). It has been observed that with the change of the dimensions and periodicity of FSS, the resonating frequency of the FSS changes. This change in resonating frequency has been studied and investigated using simulation software. The simulated data were used to train the proposed ANN models. The trained ANN models are found to predict the FSS characteristics precisely with negligible error. Compared to traditional EM simulation softwares (like ANSOFT Designer), the proposed technique using ANN models is found to significantly reduce the FSS design complexity and computational time. The FSS simulations were made using ANSOFT Designer v2 software and the neural network was designed using MATLAB software.
Volume: 9
Issue: 4
Page: 276-283
Publish at: 2020-12-01

Systematic review on evaluating planning process in agile development methods

10.12928/telkomnika.v18i6.16425
Iqbal; University of Chittagong Ahmed
Agile development methods have been catering the need of faster delivery of theever-demanding domain of software engineering. These methods are able to deliver value to users and businesses via fast, reliable, and repeatable process.  Planning requirements and processes takes the driving seat in a dynamic environment because the value proposition rapidly changes. This paper exhibits asystematic literature review of planning processes implementedby various agile methods in order to find the best suited agile method in terms of robust planning. Keywords: It was found that Scrum is the best suited agile method for planning processes.
Volume: 18
Issue: 6
Page: 2970-2976
Publish at: 2020-12-01

New prediction method for data spreading in social networks based on machine learning algorithm

10.12928/telkomnika.v18i6.16300
Maytham N.; Al-Mustaqbal University College Meqdad , Rawya; Koblenz-Landau University Al-Akam , Seifedine; Beirut Arab University Kadry
Information diffusion prediction is the study of the path of dissemination of news, information, or topics in a structured data such as a graph. Research in this area is focused on two goals, tracing the information diffusion path and finding the members that determine future the next path. The major problem of traditional approaches in this area is the use of simple probabilistic methods rather than intelligent methods. Recent years have seen growing interest in the use of machine learning algorithms in this field. Recently, deep learning, which is a branch of machine learning, has been increasingly used in the field of information diffusion prediction. This paper presents a machine learning method based on the graph neural network algorithm, which involves the selection of inactive vertices for activation based on the neighboring vertices that are active in a given scientific topic. Basically, in this method, information diffusion paths are predicted through the activation of inactive vertices byactive vertices. The method is tested on three scientific bibliography datasets: The Digital Bibliography and Library Project (DBLP), Pubmed, and Cora. The method attempts to answer the question that who will be the publisher of thenext article in a specific field of science. The comparison of the proposed method with other methods shows 10% and 5% improved precision in DBL Pand Pubmed datasets, respectively.
Volume: 18
Issue: 6
Page: 3331-3338
Publish at: 2020-12-01

Reframing the effectiveness of feedback in improving teaching and learning achievement

10.11591/ijere.v9i4.20654
Anne Malar Selvaraj , Hazita Azman
Student feedback is established as an imperative learning and teaching technique, but feedback from students is less likely. The potential of feedback to boost learning outcomes refers to scholarly writing and is considered together as one of the most impressive methods for enhancing the success of students. In education, there is, nevertheless a lack of clarification about what feedback means and far less clarification on how one should interpret it. Feedback guides students to learn and supports them in order to achieve the aim of the lesson. The goal of this paper is to discuss teacherwritten reviews and obstacles to student feedback in order to recognise the usefulness of feedback in the education domain. Feedback from students illustrates the comprehensions, boundaries and features that knowledge should be compiled and employed to establish work or learning approach. The assessment study renders the appropriate feedback, and, in this manner, the students learn how to accomplish their learning goals. While feedback is not exclusively evaluated, these are the essential ingredients of making evaluation a mechanism for teachers’ and students’ future learning.
Volume: 9
Issue: 4
Page: 1055-1062
Publish at: 2020-12-01

A new modification of LEACH for efficient energy in WSN

10.11591/ijeecs.v20.i3.pp1495-1506
Taous Lechani , Victor Tourtchine , Said Amari
The limited energy of nodes in wireless sensor networks and the impossibility of replacing their batteries, have lead to protocols development which optimize and balance the energy consumption over the network. LEACH is the most used hierarchical protocol. However, one major weakness of the LEACH protocol lies in both of its random cluster formation and cluster head election. In this paper, we present two new protocols based virtual grid clustering on coverage area. In the first one, sensing area is devided into grids as squares named as VSG-LEACH and in the second one into grids as hexagons named as VHG-LEACH. In each zone, one cluster head is elected according to its residual energy and its distance from the cell center. The simulation results show that the network lifetime is prolonged by 169.67% and the energy consumption is improved by 80.97% compared to LEACH protocol.
Volume: 20
Issue: 3
Page: 1495-1506
Publish at: 2020-12-01
1 2 3
...
1994 1995
Show 1047 of 1995

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration