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31,456 Article Results

Analysis of attribute domain for geometrical gesture performed by arm movements

10.11591/ijeecs.v16.i2.pp759-766
Wan Khairunizam , Khairul Ikram , Hafiz Halim , Azri Aziz , I. Zunaidi , S.A Bakar , W. Azani W. Mustafa
Hand gesture recognition commonly uses a camera to track hand movements and transformed into gesture database by using various computational approaches. Motion tracking utilized to map coordinate point of the subject movement, either in skeletal model or marker tracing. Data from motion trackers usually contains massive coordinate sequences of marker movement. A reliable method is required to select best features and analyze these data. However, the current issue whether the selected features and data presentation are significant for the research or not. This research brings the concept of ontology design for arm gesture recognition systems by utilizing the motion capture system. Ontology is the conceptual structure mainly used to retrieve information by establishing relation in complex data model. The proposed ontology framework is divided into three domains which are knowledge domain, attribute domain and process domain. Knowledge domain holds pre-processed gestural data from motion capture. The attribute domain is that the level where all the attribute elements were presented. This paper shows the analysis of the datasets in attribute domain. The analysis is divided into two parts which is precision measure and ANOVA test. Both analyses are to prove the reliability of datasets in attribute domain. The precision measure is used to remove all the common data for all gesture. A statistical analysis of p-value is lower than 0.01 which means the gestural data are statistically significant to be used for the similarity measure.
Volume: 16
Issue: 2
Page: 759-766
Publish at: 2019-11-01

Human face detection and recognition using contour generation and matching algorithm

10.11591/ijeecs.v16.i2.pp709-714
Arulananth T.S , Baskar M. , Sateesh R.
Face detection, monitoring of human face and recognition is a high-quality venture in safety, surveillance and regulation enforcement systems with greater accuracy. There are many motives at the back of in this trouble. Which include function of the human face; pose version, negative environmental conditions, terrible lightning and picture tilt etc,. So we must locate a few feasible solutions to clear up those issues by means of imposing a brand new system. Our proposed venture might be improving the issues on Face detection, monitoring of human face and recognition issues.
Volume: 16
Issue: 2
Page: 709-714
Publish at: 2019-11-01

Oscillation stability enhancement using multi-objective swarm based technique for smib system

10.11591/ijeecs.v16.i2.pp631-639
N. A. M. Kamari , I. Musirin , M. K. M. Zamani , S. A. Halim
This paper discussed the impact of multi-objective function in a swarm-based optimization approach for modulate proportional-integral-derivative (PID) controller parameters of a static var compensator (SVC) in a single machine infinite bus (SMIB) system. SVC is a Flexible Alternating Current Transmission Systems (FACTS) devices which often used to increase the damping of the synchronous generator. In this paper, three parameters of PID controller: proportional gain, KP, interval gain, KI and derivative gain, KD are tuned with particle swarm optimization (PSO) approach. One multi-objective function (MO) that derived from the consolidation of maximum damping factor, σmax and minimum damping ratio, ξmin is proposed to elevate the damping capability of the systems. Validation with respect to speed response and eigenvalues verification proved that the proposed MO is more competent than single objective function.
Volume: 16
Issue: 2
Page: 631-639
Publish at: 2019-11-01

Determination of news biasedness using content sentiment analysis algorithm

10.11591/ijeecs.v16.i2.pp882-889
Shri Bharathi SV , Angelina Geetha
Nowadays, identifying news biases in the social media is one of the most fundamental problems. News bias is a complex process that comprises several dimensions to be taken into account and it is interlinked with social, political and economic problems.  In general, news bias has the ability to reflect opinion of people about a topic or government policies and actions.  The proposed algorithm develops a system which can detect the biasedness of news topics from different news Websites.This approach automatically collects the news contents from various online news media portals and then consolidates them for the determination of news biasedness. In the experimental study, the news topics are gathered from various Websites of U.S., U.K., and India. For training dataset 3265 news sentences were collected under various news topics from 20 different news Websites. The effectiveness of classification of algorithm is proved by the extensive experimental study. The proposed algorithm provides a method improves the determination of news biasedness, which in turn may help in providing impartial, unbiased and reliable information.
Volume: 16
Issue: 2
Page: 882-889
Publish at: 2019-11-01

Simulation of simultaneous localization and mapping using 3D point cloud data

10.11591/ijeecs.v16.i2.pp941-949
Shuzlina Abdul-Rahman , Mohamad Soffi Abd Razak , Aliya Hasanah Binti Mohd Mushin , Raseeda Hamzah , Nordin Abu Bakar , Zalilah Abd Aziz
Abstract—This paper presents a simulation study of Simultaneous Localization and Mapping (SLAM) using 3D point cloud data from Light Detection and Ranging (LiDAR) technology.  Methods like simulation is useful to simplify the process of learning algorithms particularly when collecting and annotating large volumes of real data is impractical and expensive. In this study, a map of a given environment was constructed in Robotic Operating System platform with Gazebo Simulator. The paper begins by presenting the most currently popular algorithm that are widely used in SLAM namely Extended Kalman Filter, Graph SLAM and Fast SLAM. The study performed the simulations by using standard SLAM with Turtlebot and Husky robots. Husky robot was further compared with ACML algorithm. The results showed that Hector SLAM could reach the goal faster than ACML algorithm in a pre-defined map. Further studies in this field with other SLAM algorithms would certainly beneficial to many parties due to the demands of robotic application.
Volume: 16
Issue: 2
Page: 941-949
Publish at: 2019-11-01

File encryption based on reduced-round AES with revised round keys and key schedule

10.11591/ijeecs.v16.i2.pp897-905
Edjie Malonzo De Los Reyes , Ariel M. Sison , Ruji P. Medina
The continuing advancement of technology had provided security issues in protecting the confidentiality of information. The need to protect unauthorized access of a third party is warranted.  In this paper, the reduced-round modified AES with revised round keys and key schedule is proposed to ensure file confidentiality.  The modifications to the AES cipher round was the reduction of the round iterations from 10 to 6, and additional key permutations were added in between states; while in the key schedule, additional byte substitution process was appended.  Time and throughput were utilized to measure the performance of the application's encryption/decryption process; while the avalanche effect and randomness tests were used to measure the security of the modified AES algorithm.  The results of evaluations have shown that the encryption and decryption time have improved by 1.27% and 1.21% respectively while the throughput has similarly improved by 1.29% and 3.19% for both encryption and decryption respectively.  Whereas the avalanche effect of the modified AES was 50.06% which was more than the ideal value of 50% and it was also better than the standard AES which was 49.94% using the sample dataset.  Finally, all the ciphertext outputs of the modified AES passed the randomness tests.
Volume: 16
Issue: 2
Page: 897-905
Publish at: 2019-11-01

A heat waste recovery system via thermoelectric generator

10.11591/ijeecs.v16.i2.pp586-590
Chai-Phing Chen , Siaw-Paw Koh , Sieh-Kiong Tiong , Jian-Ding Tan , Albert Yu-Chooi Fong
Be it in the power production or consumption end, improvement on the power efficiency has become one of the most pivoting research topics over the past few decades. In order to reduce the reliance on fossil fuels and negative impacts on the environment, many ways are found to show promising results to increase power efficiency. One of the most effective ways is to recover and reuse heat waste. In this research, a heat waste recovery system is proposed by using thermoelectric generators (TEGs). This proposed heat recovery system can be implemented at the exhaust or the chiller section of a power system to abstract the excessive and unwanted heat and reuse it before it dissipates into the environment or goes to waste. Experiments are setup and conducted with controlled heat levels to investigate the performance of the proposed system in converting heat waste into electricity under different temperatures. The results show that the generated power hikes as the heat set-points increase from 30°C to 240°C. The output power fluctuates and shows no significant increase as the temperature increases from 240°C onwards. The maximum power is generated at 290°C. It can thus be concluded that the proposed system successfully generates electricity under different level of heat waste temperature. In time to come, this research can further explore the possibility on the optimization of the generated power.
Volume: 16
Issue: 2
Page: 586-590
Publish at: 2019-11-01

An efficient two-stage user association scheme for green C-RAN systems

10.11591/ijeecs.v16.i2.pp794-802
Ismail Hburi , H. F. Khazaal
This paper addresses the energy efficiency (EE) based user-association problem in cloud radio-access network. In specific, a low-complexity 2-stage iterative algorithm is developed for this purpose by jointly employing the coordinated multi-point (CoMP) and user-clustering techniques. The first stage of the algorithm applies a greedy search to form user-cluster and activate corresponded remote radio heads (RRHs) for CoMP transmission, only an RRH j with good channel gain could be included in the serving cluster of user k. Next, in the second stage, a re-clustering procedure is utilized to mitigate inter-cluster interference (ICI) and assign optimal power for scheduled users. Our obtained findings confirm that the transmit power, RRH density, and the number of users served by these RRHs can significantly affect the EE. Also, the results show that under certain system settings the proposed scheme can enhance the EE by almost 39.6% compared to conventional CoMP without user clustering technique.
Volume: 16
Issue: 2
Page: 794-802
Publish at: 2019-11-01

Obstacle aware delay optimized rectilinear steiner minimum tree routing

10.11591/ijeecs.v16.i2.pp640-652
Shyamala G , G R Prasad
This work presents a method to solve the problem of constructing Rectilinear Steiner Minimum Tree (RSMT) for a group of pins in the presence of obstacles. In modern very large-scale integrated circuit (VLSI) designs, the obstacles, generally blocks the metal and the device layer. Therefore routing on top of blockage is a possible solution but buffers cannot be placed over the obstacle. Modern VLSI design OARSMT construction has long wire length, which results in signal violation. To address this issue a slew constraint interconnect need to be considered in routing over obstacle. This is called the Obstacle-Avoiding Rectilinear Steiner minimum trees (OARSMT) problem with slew constraints over obstacles. The drawback of traditional OARSMT is that they only consider slew constraint, and delay constraints are neglected. It induces high routing resources overhead due to buffer insertion and does not solve global routing solution. This work presents an Obstacle Aware Delay Optimized Rectilinear Steiner Minimum Tree (OADORSMT) Routing to address the delay, slew constraint and reduce the routing resources. Experiments are conduced to evaluate the performance of proposed approach over existing approach in term of wire length and worst negative slack. The experiments are conducted for small and large nets considering fixed and varied obstacles and outcome shows the proposed efficiency over existing approaches. The OADORSMT is designed in such a way where it can be parallelized to obtain better efficiency.
Volume: 16
Issue: 2
Page: 640-652
Publish at: 2019-11-01

Modelling emotion expression through agent oriented methodology

10.11591/ijeecs.v16.i2.pp972-977
S.Filzah Zulkifli , CW Shiang , N Jali , M.A. Khairuddin
This paper presents Modelling Emotion Expression through Agent Oriented Methodology. Considering emotions of the intended users in the software engineering can uncover new requirements to improve and more accepted the system. While emotion is paying much attention nowadays, there is lacking systematic way to model the emotion based system. Without the systematic approach, it is hard to debug, design and develop an emotion based system. Since the emotional requirement of people has not being fully investigated, the research outcome propose the emotion modelling as part of the complete set of agent-oriented modelling for virtual character in eLearning system, The contribution of this paper is to introduce agent oriented modelling to systematic model an emotion based solution for an eLearning system and instructional video design. With the emotion model, it can serve as a guide to design, redesign, and discuss the emotion elements among the software development team. This is important for better debugging and project management especially for emotion led system.
Volume: 16
Issue: 2
Page: 972-977
Publish at: 2019-11-01

Optimal sizing and location of multiple distributed generation for power loss minimization using genetic algorithm

10.11591/ijeecs.v16.i2.pp956-963
Abdulhamid Musa , Tengku Juhana Tengku Hashim
This paper presents a Genetic Algorithm (GA) for optimal location and sizing of multiple distributed generation (DG) for loss minimization. The study is implemented on a 33-bus radial distribution system to optimally allocate different numbers of DGs through the minimization of total active power losses and voltage deviation at power constraints of 0 – 2 MW and 0 – 3 MW respectively. The study proposed a PQ model of DG and Direct Load Flow (DLF) technique that uses Bus Incidence to Branch current (BIBC) and Branch Current to Bus Voltage (BCBV) matrices. The result obtained a minimum base case voltage level of 0.9898 p.u at bus 18 with variations of voltage improvements at other buses after single and multiple DG allocations in the system. Besides, the total power loss before DG allocation is observed as 0.2243 MW, and total power loss after DG allocation was determined based on the power constraints. Various optimal locations were seen depending on the power limits of different DG sizes. The results have shown that the impact of optimal allocation and sizing of three DG is more advantageous concerning voltage improvement, reduction of the voltage deviation and also total power loss in the distribution system. The results obtained in the 0 – 2 MW power limit is consistent to the 0 – 3 MW power limits regarding the influence of allocating DG to the network and minimization of total power losses.
Volume: 16
Issue: 2
Page: 956-963
Publish at: 2019-11-01

Neuro-physiological porn addiction detection using machine learning approach

10.11591/ijeecs.v16.i2.pp964-971
Norhaslinda Kamaruddin , Abdul Wahab , Yasmeen Rozaidi
Pornography is a portrayal of sexual subject contents for the exclusive purpose of sexual arousal that can lead to addiction. The availability and easy accessibility of the Internet connectivity have created unprecedented opportunities for sexual education, learning, and growth for adolescences to be in the rise. Hence, the risk of porn addiction developed by teenagers has also increased due to highly prevalent porn consumption. To date, the only available means of detecting porn addiction is through questionnaire. However, while answering the questions, participants may suppress or exaggerate their answers because porn addiction is considered taboo in the community. Hence, the purpose of this project is to develop an engine with multiple classifiers to recognize porn addiction using electroencephalography (EEG) signals and to compare classifiers performance. In the experimental study, the neuro-physiological signals of EEG data were collected previously in Indonesia among students age 9 to 13 years old by researchers from the International Islamic University Malaysia (IIUM). The EEG data were pre-processed, and relevant features are extracted using Mel-Frequency Cepstral Coefficients (MFCC). Then, the features are classified to produce the outputs of valance and arousal. Subsequently, three different classifiers of Multilayer Perceptron (MLP), Naive Bayesian (NB), and Random Forest (RF) are employed to determine whether the participant is a porn addict or otherwise. The experimental results show that the MLP classifier yields slightly better accuracy compared to Naïve Bayes and Random Forest classifiers making the MLP classifier preferable for porn addiction recognition. Although this work is still at infancy stage, it is envisaged for the work to be expanded for comprehensive porn addiction recognition system so that early intervention and appropriate support can be given for the teenagers with pornography addiction problem.
Volume: 16
Issue: 2
Page: 964-971
Publish at: 2019-11-01

Evaluation review of effectiveness and security metrics performance on information technology domain

10.11591/ijeecs.v16.i2.pp1059-1064
Roshidi Din , Rosmadi Bakar , Azizan Ismail , Aida Mustapha , Sunariya Utama
Information Technology (IT) development is the vital required for human life activities in this global era. This implementation of IT system has becomes competitive among developers to increase the quality of system performance. In order to discover the IT performance of system, it neccesary to evaluate the IT implementation performance. It determines the anticipated system output to prepare to enhance the application performance. In this paper the evaluation performance that is reviewd are effectiveness and security metrics because both of evaluations able to improve the development and protection of system. Therefore, this paper classifies some IT domain development that used in term of effectiveness and security metric approach from previous researchers’ effort. It is categorized the domain based on both evaluation term of effectiveness and security metrics from specific parameter their used. The concern of this paper is to discover the important effectiveness and security metrics in IT domain performance that is anticipated to achieve expected performance.
Volume: 16
Issue: 2
Page: 1059-1064
Publish at: 2019-11-01

Traffic-based floor preference for the scheduling of elevators in elevator group control system

10.11591/ijeecs.v16.i2.pp835-842
Malan Dipak Sale , V. Chandra Prakash
Modern high-rise buildings require complex yet efficient Elevator Group Control Systems (EGCSs). In vertical transportation through an elevator, a passenger must make a hall call by pressing a landing call button installed at each floor and located near the cars of the elevator group. Conventionally, the EGCS allocates one of the cars for each hall call. Waiting time for the arrival of car and journey time inside a car are two parameters, which provide a suitable measure for quality and efficiency of EGCSs. The proposed system deals with this car-call allocation problem. The proposed work analyzes the generated traffic patterns to dispatch a certain number of cars to certain floors in order to reduce overall wait time of passengers. The proposed algorithm is simulated for high-rise building with 20 floors and provides a better result with the reduced wait time for more number of passengers.
Volume: 16
Issue: 2
Page: 835-842
Publish at: 2019-11-01

A review on various methods of collaborative computing

10.11591/ijeecs.v16.i2.pp1002-1008
Mohd Afiq Bin Zamanhuri , Zalilah Abd Aziz , Rose Hafsah Abd Rauf , Elly Johana Johan , Noratikah Shamsudin
Currently, mosques in Malaysia distribute their lecture schedules either on paper-based form or by uploading the schedule on their social media platform. This has some disadvantages such as paper schedules are susceptible to damages and information on social media platform is often not updated to current changes. Collaborative Computing is a system that enable individuals to work together remotely by making use of the reach ability of the internet. In order to utilise the Internet’s obvious advantages over paper-based and rapid information distribution and asynchronous communication, a review is conducted to study the available methods of collaborative computing, further analyse current research papers. Result shows that Centralized Computing method is the most suitable method for developing collaborative mobile application for Islamic Lectures schedule.
Volume: 16
Issue: 2
Page: 1002-1008
Publish at: 2019-11-01
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