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29,905 Article Results

A significant energy management control strategy for a hybrid source EV

10.11591/ijece.v9i6.pp4580-4585
A Geetha , C Subramani
The conceptualization of Electric vehicles has been significant in solving the pollution due to the transportation problem. However, its design and working has not yet been perfected and can be optimized. An effective model of the electric vehicle is the integration of batteries and supercapacitors. In this paper, the optimal sharing of energy between the battery and the supercapacitor is provided by the Particle Swarm Optimization (PSO). The results reveal that the proposed algorithm can better share the energy between the hybrid sources. The simulations are carried out in MATLAB Simulink platform and the results obtained for ECE-15 driving cycle is presented.
Volume: 9
Issue: 6
Page: 4580-4585
Publish at: 2019-12-01

Robust controller for an open irrigation canal prototype

10.11591/ijeecs.v17.i1.pp237-247
Nardjes Merabti , Arbaoui Faycel , Saidi Mohamed Larbi , Said Yahmedi
A Management and control of irrigation canals is a very important task whether for irrigation of agricultural land, to provide clean water, or to avoid floods. Irrigation canals are sometimes subject to intense variations due to climate change and inclement weather. For this reasons, a robust controller that allows dealing with large variation in operating conditions is proposed to control the water level of a multi-pool open irrigation canal prototype. The main objective of this study is to regulate the downstream level of each canal's pool at a constant value even with inflow disturbances.  The robust controller is designed and tested in simulation for different operating conditions. The results obtained show the good behavior and the effectiveness of the designed controller.
Volume: 17
Issue: 1
Page: 237-247
Publish at: 2019-11-14

A descent extension of the Dai - Yuan conjugate gradient technique

10.11591/ijeecs.v16.i2.pp661-668
Basim Abbas Hassan , Zeyad M. Abdullah , Hawraz N. Jabbar
Based on Dai - Yuan technique, a new extension method was proposed. In contrary to the CG classical method, this proposed method employs a coefficient that has an important role in constructing the new formula with less computational efforts. This proposed method was found to be efficient on the basis of theory analysis and numerical results.
Volume: 16
Issue: 2
Page: 661-668
Publish at: 2019-11-01

Time performance analysis of advanced encryption standard and data encryption standard in data security transaction

10.11591/ijeecs.v16.i2.pp988-994
Zolidah Kasiran , Hikma Farah Ali , Noorhayati Mohamed Noor
The advancement of the data communication technologies has increased the traffic of data exchange over the internet and at the same time created the opportunity of data attack by various party.  This paper present  Time Performance Analysis Of Advanced Encryption Standard And Data Encryption Standard  in Data Security Transaction. In this study we proposed an AES algorithm with  different key size, and different file format. Our aim is to safely to transfer the file for using the AES algorithm. Proposed algorithm has done by analyzing the different time taken for both AES and DES, experiments were done by three different file  format which were text, image, and voice. Each file format type was tested with five different file sizes. The result of each experiments were analysed and it was confirmed that  the AES algorithm have better performance in term of time taken as compared to DES.
Volume: 16
Issue: 2
Page: 988-994
Publish at: 2019-11-01

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

Automating quranic verses labeling using machine learning approach

10.11591/ijeecs.v16.i2.pp925-931
A. Adeleke , N. Samsudin , A. Mustapha , S. Ahmad Khalid
Classification of Quranic verses into predefined categories is an essential task in Quranic studies. However, in recent times, with the advancement in information technology and machine learning, several classification algorithms have been developed for the purpose of text classification tasks. Automated text classification (ATC) is a well-known technique in machine learning. It is the task of developing models that could be trained to automatically assign to each text instances a known label from a predefined state. In this paper, four conventional ML classifiers: support vector machine (SVM), naïve bayes (NB), decision trees (J48), nearest neighbor (k-NN), are used in classifying selected Quranic verses into three predefined class labels: faith (iman), worship (ibadah), etiquettes (akhlak). The Quranic data comprises of verses in chapter two (al-Baqara) of the holy scripture. In the results, the classifiers achieved above 80% accuracy score with naïve bayes (NB) algorithm recording the overall highest scores of 93.9% accuracy and 0.964 AUC.
Volume: 16
Issue: 2
Page: 925-931
Publish at: 2019-11-01

Automatic classification of paddy leaf disease

10.11591/ijeecs.v16.i2.pp767-774
Shafaf Ibrahim , Nurnazihah Wahab , Ahmad Firdaus Ahmad Fadzil , Nur Nabilah Abu Mangshor , Zaaba Ahmad
RiceisastaplefoodinmostoftheAsiancountries.Itisanimportantcrop, andoverhalfoftheworldpopulationreliesonitforfood.However,paddy leafdiseasecanaffectboththequalityandquantityofpaddyinagriculture production.Theclassificationofpaddyleafdiseaseisanimportantand urgenttaskasitdestroysabout10%to15%ofproductioninAsia.Thus,a studyonautomaticclassificationofpaddyleafdiseaseusingimage processingispresented.Featureextractiontechniquesofcolor,texture,and shapewereimplementedtoanalyzethecharacteristicsofthepaddyleaf disease.Inanother note,aSupportVector Machine(SVM)isused toclassify thefourtypesofpaddyleafdiseasewhicharethebrownspot,bacterialleaf blight,tungrovirus,andleaf scald.Theperformanceofthe proposedstudyis evaluatedto160testingimageswhichreturned86.25%ofclassification accuracy.Theoutcomeofthisstudyisexpectedtoassisttheagrotechnology industryinearlydetectionofpaddyleafdiseaseinwhichanappropriate actioncould be taken accordingly.
Volume: 16
Issue: 2
Page: 767-774
Publish at: 2019-11-01

Detecting candidates of depression, anxiety and stress through malay-written tweets: a preliminary study

10.11591/ijeecs.v16.i2.pp787-793
Muhammad Zahier Nasrudin , Ruhaila Maskat , Ramli Musa
Depression, anxiety and stress are not trivial conditions applicable for only the weak-hearted. They can be inflicted by anyone of all age groups, gender, race and social status. While some are courageous to acknowledge their condition, others shy away in shame or denial. In this paper, we proposed a “proactive” approach to detecting candidates of depression, anxiety and stress in an unobtrusive manner by tapping into what Malaysians tweet in Malay language. From this preliminary study, we constructed 165 Malay layman terms which describe depression, anxiety or stress as identified in M-DASS-42 scale. Since Twitter is an informal platform, construction of Malay layman terms is an essential step to the detection of candidates. Our study on 1,789 Malay tweets discovered 6 Twitter users as potential candidates, having high frequency of tweets with any of the layman terms. We can conclude that using tweets can be useful in unobtrusively detecting candidates of depression, anxiety or stress. This paper also identifies open research areas.
Volume: 16
Issue: 2
Page: 787-793
Publish at: 2019-11-01

Privacy preserving outsourcing algorithm for two-point linear boundary value problems

10.11591/ijeecs.v16.i2.pp1065-1069
Nedal Mohammed , Laman R. Sultan , Santosh Lomte
One of a powerful application in the age of cloud computing is the outsourcing of scientific computations to cloud computing which makes cloud computing a very powerful computing paradigm, where the customers with limited computing resource and storage devices can outsource the sophisticated computation workloads into powerful service providers. One of scientific computations problem is Two-Point Boundary Value Problems(BVP) is a basic engineering and scientific problem, which has application in various domains. In this paper, we propose a privacy-preserving, verifiable and efficient algorithm for Two-Point Boundary Value Problems in outsourcing paradigm. We implement the proposed schema on the customer side laptop and using AWS compute domain elastic compute cloud (EC2) for the cloud side.
Volume: 16
Issue: 2
Page: 1065-1069
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
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