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31,456 Article Results

GIS based probabilistic method in sinkhole susceptibility hazard zones

10.11591/ijeecs.v16.i3.pp1539-1546
Mohd Asri Hakim Mohd Rosdi , Ainon Nisa Othman , Zulkiflee Abd Latif , Zaharah Mohd Yusoff
In this era of globalization, natural phenomena often invade the human population. Natural phenomena such as sinkholes often occur in countries whose topology lies in active limestone areas. Malaysia is one of the countries with active limestone areas, especially in the Klang Valley and its surrounding areas. Since 1968, the increase in sinkhole cases in Malaysia has been reported frequently. This has caused many building infrastructures to be destroyed, loss of life and destruction of property. So, one of the steps to overcome this problem is to do an in-depth study of the sinkhole. Therefore, Sinkhole Hazard Model (SHM) has been created with a combination of GIS integration by using probability techniques. There are five criteria suitable for Malaysian topography namely Lithology (LT), Soil Types (ST), Landuse (LU), Groundwater Level Decline (GLD) and Proximity to Groundwater Wells (PGW). Based on probability calculations, GLD and LU have shown a high impact on sinkhole formation. A hazard zonation map has been produced where it has been classified into five parts namely none, low, medium, high and very high. The results were validated with previous inventory data comprising 33 data. Based on the results obtained, 36.37% and 39.39% of the sinkhole formation has fallen into high and very high areas respectively. Based on these final results, the integration between GIS and probability techniques is useful in natural phenomena such as sinkhole formation.
Volume: 16
Issue: 3
Page: 1539-1546
Publish at: 2019-12-01

An energy-aware system-on-chip architecture for intra prediction in HEVC standard

10.11591/ijece.v9i6.pp5084-5094
Abdessamad El Ansari , Anas Mansouri , Ali Ahaitouf
High resolution 4K and 8K are becoming the more used in video applications. Those resolutions are well supported in the new HEVC standard. Thus, embedded solutions such as development of dedicated ystems-On-Chips (SOC) to accelerate video processing on one chip instead of only software solutions are commendable. This paper proposes a novel parallel and high efficient hardware accelerator for the intra prediction block. This accelerator achieves a high-speed treatment due to pipelined processing units and parallel shaped architecture. The complexity of memory access is also reduced thanks to the proposed design with less increased power consumption. The implementation was performed on the 7 Series FPGA 28 nm technology resources on Zynq-7000 and results show, that the proposed architecture takes 16520 LUTs and can reach 143.65 MHz as a maximum frequency and it is able to support the throughput of 3840×2160 sequence at 90 frames per second.
Volume: 9
Issue: 6
Page: 5084-5094
Publish at: 2019-12-01

A data modeling conceptual framework for ubiquitous computing based on context awareness

10.11591/ijece.v9i6.pp5495-5501
Stenly Richard Pungus , Jamaiah Haji Yahaya , Aziz Deraman , Noor Hasrina Binti Bakar
This paper introduces a framework for data modeling to support ubiquitous computing based on context-awareness.  Data always grow in term of volume, variety, velocity, and value. The problem arises when it grows exponentially. Consequently, data is anywhere and requirements change in early data definitions then data design become not as the plan.  Therefore, suitable approach with new paradigm and methods of data modeling needs to be enhanced to solve the problems in the real world. Data model must consider the active object that related to each other. Any objects may interact with each other in a ubiquitous way and recorded in digital technology. Sensors, actuator devices, and radio frequency identification technology may support communication between objects through ubiquitous computing. The data model in Ubiquitous Computing needs to restructure to become active and dynamic.  Ubiquitous computing is a model that enable all objects around the people to communicate and invisible. In order to support this paradigm, a new perspective of how data are designed and stored on each object is needed. Furthermore, using ubiquitous computing, the pervasive network can request and response information, which means the devices may communicate and has the initiative to solve a problem without human intervention.  Human wants more intelligence objects. Therefore, more sensors and memory are required. Data structures need to enhance or embedded into any devices that interact with the human.
Volume: 9
Issue: 6
Page: 5495-5501
Publish at: 2019-12-01

Energy performance of 5G backhaul wireless network utilizing hybrid centric-distributed architecture

10.11591/ijeecs.v16.i3.pp1343-1348
Hamza Mohammed Ridha Al-Khafaji , Hasan Shakir Majdi
This paper scrutinizes the influence of deployment scenarios on the energy performance of fifth-generation (5G) network at various backhaul wireless frequency bands. An innovative network architecture, the hybrid centric-distributed, is employed and its energy efficiency (EE) model is analyzed. The obtained results confirm that the EE of the 5G network increases with an increasing number of small cells and degrades with an increasing frequency of wireless backhaul and radius of small cells regardless of the network architectures. Moreover, the hybrid centric-distributed architecture augments the EE when compared with the distributed architecture.
Volume: 16
Issue: 3
Page: 1343-1348
Publish at: 2019-12-01

Power system voltage collapse prediction using a new line stability index (NLSI-1): A case study of the 330-kV nigerian national grid

10.11591/ijece.v9i6.pp5125-5133
I. A. Samuel , J. Katende , C. O. A. Awosope , A. A. Awelewa , A. I. Adekitan , F. A. Agbetuyi
The cumulative number of historical and recent power system outages substantiates the fact that further studies are necessary for an improved solution to the issue of voltage instability on the grid and the subsequent system collapse. Voltage collapse is a serious reliability issue which inhibits the objective of running a reliable and secure power system network. In this study, a new line stability index (NLSI_1) for predicting voltage collapse is presented.  The new index considers a switching logic which is derived from the difference of voltage angle between the two load buses. The index is deployed for performance analysis using the 28-bus, 330-kV Nigeria National Grid (NNG).  The simulation implemented in MATLAB shows that the index gives the same results as Line stability index (Lmn) and Fast Voltage Stability Index (FVSI) indices. The base case and the contingency scenarios were considered during the simulation. The base case analysis using the NNG values of all the three indices FVSI, Lmn, and NLSI_1 for simulation generates a value less than one for the entire lines which implies that the NNG is stable in this mode. The values of the three indices are almost the same, which confirms the accuracy of the novel index developed. The analysis for the contingency case reveals that the load bus 16 (Gombe) which has the lowest, maximum permissible reactive load of 139.5MVAR is the weakest; also power line 16-19 is identified as the critical line. The result of the simulation confirms that the accuracy was improved by using NLSI_1.
Volume: 9
Issue: 6
Page: 5125-5133
Publish at: 2019-12-01

Human activity recognition by using convolutional neural network

10.11591/ijece.v9i6.pp5270-5276
Hankil Kim , Sungock Lee , Hoekyung Jung
In recent years, many researchers have studied the HAR (Human Activity Recognition) system. HAR using smart home sensor is based on computing in smart environment, and intelligent surveillance system conducts intensive research on peripheral support life. The previous system studied in some of the activities is a fixed motion and the methodology is less accurate. In this paper, vision-based studies using thermal imaging cameras improve the accuracy of motion recognition in intelligent surveillance systems. We use one of the deep learning architectures widely used in image recognition systems called Convolutional Neural Networks (CNN). Therefore, we use CNN and thermal cameras to provide accuracy and many features through the proposed method.
Volume: 9
Issue: 6
Page: 5270-5276
Publish at: 2019-12-01

Design and implementation of smart farming system for fig using connected-argonomics

10.11591/ijece.v9i6.pp5653-5662
N. Zainal , N. Mohamood , M. F. Norman , D. Sanmutham
This paper proposes a design and implementation approach of smart farming system using connected-agronomics technique for fig farm application. Nowadays, fig plants having a rapid growth in the current market demand due to its rich in natural health benefiting nutrients, antioxidants and vitamins where some farming systems have been used  in maintaining fig plant’s environmental resources to grow without fail. Smart farming is a system applied to provide user with real time information and plan for desired plant such as time intervals for watering systems. There are two major problems on maintaining the fig fruit quality; watering system fail during emergency blackout and a contagious disease known as leaf rust due to external environments. The system implements two microcontrollers, the Arduino Uno & Raspberry Pi along with smartphone Android application. The system performance is evaluated based on the requirement specification, irrigation soil, surrounding temperature and moisture. It is found that all data collected by the sensors are within the optimal range of values, which are 1500 µS/cm to 1599 µS/cm for the EC reading of the fertilizer while 6.0 to 6.5 for the pH value of the soil. This prototype of smart farming was well developed and can be applied to the fig plantation environment.
Volume: 9
Issue: 6
Page: 5653-5662
Publish at: 2019-12-01

Hybrid swarm and GA based approach for software test case selection

10.11591/ijece.v9i6.pp4898-4903
Palak Palak , Preeti Gulia
Being a crucial step and deciding factor for software reliability, software testing has evolved a long way and always attracted researchers due to various inherent challenges. The quality of a software application depends on the effectiveness of the testing carried out during development and maintenance phase. Testing is a crucial but time consuming activity that influences the overall cost of software development. Thus a minimal but efficient test suite selection is the need of the hour. This paper presents a hybrid technique based on swarm based search technique and GA (Genetic Algorithm) for selection of promising test cases to reduce the overall development cost and time of the application. We took component based software into consideration as they offer some inherent advantages over traditional software development paradigms.
Volume: 9
Issue: 6
Page: 4898-4903
Publish at: 2019-12-01

Dual iris authentication system using dezert smarandache theory

10.11591/ijece.v9i6.pp4703-4712
Kamel Ghanem Ghalem , Fatiha Hendel
In this paper, a dual iris authentication using Dezert Smarandache theory is presented. The proposed method consists of three main steps: In the first one, the iris images are segmented in order to extract only half iris disc that contains relevant information and is less affected by noise. For that, a Hough transform is used. The segmented images are normalized by Daugman rubber sheet model. In the second step, the normalized images are analyzed by a bench of two 1D Log-Gabor filters to extract the texture characteristics. The encoding is realized with a phase of quantization developed by J. Daugman to generate the binary iris template. For the authentication and the similarity measurement between both binary irises templates, the hamming distances are used with a previously calculated threshold. The score fusion is applied using DSmC combination rule. The proposed method has been tested on a subset of iris database CASIA-IrisV3-Interval. The obtained results give a satisfactory performance with accuracy of 99.96%, FAR of 0%, FRR of 3.89%, EER of 2% and processing time for one iris image of 12.36 s.
Volume: 9
Issue: 6
Page: 4703-4712
Publish at: 2019-12-01

Developing the indonesian government enterprise architecture framework appropriate for Indonesian government agencies

10.11591/ijict.v8i3.pp152-161
Asbartanov Lase , Benny Ranti
This research was conducted to develop the Indonesian Government Enterprise Architecture (IGEA) framework which is suitable for Indonesian government agencies. Due to their complexity and expensive implementation cost, existing EA frameworks such as TOGAF and Zachman have so far not been the choice for building GEA by some countries including Australia and New Zealand. Those countries have built their own GEA namely Australia’s AGA and New Zealand’s GEA-NZ, respectively. Learning from this experience, the authors did a research to build Indonesia’s GEA or IGEA. This paper explains the research process which starts from mapping or comparing TOGAF, AGA, and GEA-NZ frameworks to get the underlying foundation for building GEA, analyzing framework artifacts, to building IGEA by adding specific Indonesian regulations and policies such as RPJMN and Nawacita. This IGEA framework is expected to become a reference for developing EA not only at institutional level but also the most important thing at national or cross institutional level, in order to increase the effectiveness of government IT spending.
Volume: 8
Issue: 3
Page: 152-161
Publish at: 2019-12-01

Backstepping based power control of a three-phase Single-stage Grid-connected PV system

10.11591/ijece.v9i6.pp4738-4748
Mohammed El malah , Abdellfattah Ba-razzouk , M’hammed Guisser , Elhassane Abdelmounim , Mhamed Madark
In order to reduce costs while maintaining superior performance, this paper presents a new control methodology of a three-phase grid connected photovoltaic system without using the intermediary DC/DC converter. Based on the synchronized nonlinear model of the whole photovoltaic system, two controllers have been proposed for the three-phase inverter in order to ensure the operation of the PV system at the maximum power point with unity power factor and minimum grid disturbance. Grid synchronization has been ensured by a three-phase 2nd order PLL (Phase-Locked Loop). The stability of each controller is demonstrated by means of Lyapunov analysis and evaluated under changing atmospheric conditions using the Matlab/Simulink environment, the simulation results clearly demonstrate the performance provided by each controller.
Volume: 9
Issue: 6
Page: 4738-4748
Publish at: 2019-12-01

Classification neutral to ground (NG) voltage using levenberg-marquardt neural network (LMNN)

10.11591/ijeecs.v16.i3.pp1189-1195
Suzaryfazli Kamaruddin , Ahmad Farid Abidin , Mohd Abdul Talib Mat Yusoh
In electrical systems nowadays, power quality issues have become a major concern for customers and electrical utilities. The high Neutral to ground (NG) voltage are one of the power quality issues which could cause adverse effect such as malfunction the devices, neutral overheating and electricity shock. Thus, the high NG voltage should be classified in order to perform the mitigation work accurately. This paper presents the classification of neutral to ground voltage using Levenberg-Marquardt Neural Network (LMNN) technique. The Discrete Wavelet Transform (DWT) is applied in this method to extract the features of NG voltage which needed in classification process.  The result shows the LMNN perform accurately in classify the types of NG voltage, where its accuracy result is reach more than 90% accuracy.
Volume: 16
Issue: 3
Page: 1189-1195
Publish at: 2019-12-01

On the classification of arrhythmia using supplementary features from Tetrolet transforms

10.11591/ijece.v9i6.pp5006-5015
G. Jayagopi , S. Pushpa
Heart diseases had been molded as potential threats to human lives, especially to elderly people in recent days due to the dynamically varying food habits among the people. However, these diseases could be easily caught by proper analysis of Electrocardiogram (ECG) signals acquired from individuals. This paper proposes a better method to detect and classify the arrhythmia using 15 features which include 4 R-R interval features, 3 statistical and 6 chaotic features estimated from ECG signals. Additionally, Entropy and Energy features had been gained after converting one dimensional ECG signals to two dimensional data and applied Tetrolet transforms on that.  Total numbers of 15 features had been utilized to classify the heart beats from the benchmark MIT-Arrhythmia database using Support Vector Machines (SVM). The classification performance was analyzed under various kernel functions and different Tetrolet decomposition levels. It is found that Radial Basis Function (RBF) kernel could perform better than linear and polynomial kernels. This research attempt yielded an accuracy of 99.35 % against the existing works. Moreover, addition of two more features had introduced a negligible overhead of time. Hence, this method is better suitable to detect and classify the Arrhythmia in both online and offline.
Volume: 9
Issue: 6
Page: 5006-5015
Publish at: 2019-12-01

Improving software development effort estimation using support vector regression and feature selection

10.11591/ijai.v8.i4.pp399-410
Abdelali Zakrani , Mustapha Hain , Ali Idri
Accurate and reliable software development effort estimation (SDEE) is one of the main concerns for project managers. Planning and scheduling a software project using an inaccurate estimate may cause severe risks to the software project under development such as delayed delivery, poor quality software, missing features. Therefore, an accurate prediction of the software effort plays an important role in the minimization of these risks that can lead to the project failure. Nowadays, the application of artificial intelligence techniques has grown dramatically for predicting software effort. The researchers found that these techniques are suitable tools for accurate prediction. In this study, an improved model is designed for estimating software effort using support vector regression (SVR) and two feature selection (FS) methods. Prior to building model step, a preprocessing stage is performed by random forest or Boruta feature selection methods to remove unimportant features. Next, the SVR model is tuned by a grid search approach. The performance of the models is then evaluated over eight wellknown datasets through 30%holdout validation method. To show the impact of feature selection on the accuracy of SVR models, the proposed model was compared with SVR model without feature selection. The results indicated that SVR with feature selection outperforms SVR without FS in terms of the three accuracy measures used in this empirical study.
Volume: 8
Issue: 4
Page: 399-410
Publish at: 2019-12-01

Novelty circular neighboring technique using reactive fault tolerance method

10.11591/ijece.v9i6.pp5211-5217
Ahmad Shukri Mohd Noor , Nur Farhah Mat Zian , Noor Hafhizah Abd Rahim , Rabiei Mamat , Wan Nur Amira Wan Azman
The availability of the data in a distributed system can be increase by implementing fault tolerance mechanism in the system. Reactive method in fault tolerance mechanism deals with restarting the failed services, placing redundant copies of data in multiple nodes across network, in other words data replication and migrating the data for recovery. Even if the idea of data replication is solid, the challenge is to choose the right replication technique that able to provide better data availability as well as consistency that involves read and write operations on the redundant copies. Circular Neighboring Replication (CNR) technique exploits neighboring policy in replicating the data items in the system performs well with regards to lower copies needed to maintain the system availability at the highest. In a performance analysis with existing techniques, results show that CNR improves system availability by average 37% by offering only two replicas needed to maintain data availability and consistency. The study demonstrates the possibility of the proposed technique and the potential of deploying in larger and complex environment.
Volume: 9
Issue: 6
Page: 5211-5217
Publish at: 2019-12-01
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