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29,905 Article Results

Fuzzy n-s-homogeneity and fuzzy weak n-s-homogeneity

10.11591/ijece.v9i6.pp5395-5399
Samer Al Ghour , Almothana Azaizeh
Fuzzy n-s-homogeneity and fuzzy weak n-s-homogeneity are introduced in fuzzy bitopological spaces. Several relationships, characterizations and examples related to them are given.
Volume: 9
Issue: 6
Page: 5395-5399
Publish at: 2019-12-01

Estimation of object location probability for object detection using brightness feature only

10.11591/ijece.v9i6.pp5227-5234
Hyun Jun Park , Kwang Baek Kim
Most existing object detection methods use features such as color, shape, and contour. If there are no consistent features can be used, we need a new object detection method. Therefore, in this paper, we propose a new method for estimating the probability that an object can be located for object detection and generating an object location probability map using only brightness in a gray image. To evaluate the performance of the proposed method, we applied it to gallbladder detection. Experimental results showed 98.02% success rate for gallbladder detection in ultrasonogram. Therefore, the proposed method accurately estimates the object location probability and effectively detected gallbladder.
Volume: 9
Issue: 6
Page: 5227-5234
Publish at: 2019-12-01

Comparison by simulation of PEGASIS and IEEPB routing protocols

10.11591/ijeecs.v16.i3.pp1569-1576
Samah Alnajdi , Fuad Bajaber
As the applications of wireless sensor networks (WSNs) became widely used throughout the years the importance of advanced sensor networks techniques increased as well. One of the main techniques used in WSNs is hierarchical routing which mainly aims to reduce the consumption of sensor nodes energy by assigning different roles to the sensor nodes to create multi-layer scheme for data transmission. This paper embraces a simulation for two known hierarchical routing protocols: Power-Efficient Gathering in Sensor Information Systems (PEGASIS) protocol and an Improved Energy-Efficient PEGASIS-Based (IEEPB) protocol. Both protocols aim to reduce the transmission distance in order to save the nodes energy by performing chain-based clustering. For evaluation, we measured the residual energy and control overhead throughout the network operation time and the results showed major flaws in both protocols such as long link problem and poor leader selection method in PEGASIS. Moreover, high nodes density problem in IEEPB.
Volume: 16
Issue: 3
Page: 1569-1576
Publish at: 2019-12-01

Improve of contrast-distorted image quality assessment based on convolutional neural networks

10.11591/ijece.v9i6.pp5604-5614
Ismail Taha Ahmed , Chen Soong Der , Norziana Jamil , Mohamad Afendee Mohamed
Many image quality assessment algorithms (IQAs) have been developed during the past decade. However, most of them are designed for images distorted by compression, noise and blurring. There are very few IQAs designed specifically for Contrast Distorted Images (CDI), e.g. Reduced-reference Image Quality Metric for Contrast-changed images (RIQMC) and NR-IQA for Contrast-Distorted Images (NR-IQA-CDI). The existing NR-IQA-CDI relies on features designed by human or handcrafted features because considerable level of skill, domain expertise and efforts are required to design good handcrafted features. Recently, there is great advancement in machine learning with the introduction of deep learning through Convolutional Neural Networks (CNN) which enable machine to learn good features from raw image automatically without any human intervention. Therefore, it is tempting to explore the ways to transform the existing NR-IQA-CDI from using handcrafted features to machine-crafted features using deep learning, specifically Convolutional Neural Networks (CNN).The results show that NR-IQA-CDI based on non-pre-trained CNN (NR-IQA-CDI-NonPreCNN) significantly outperforms those which are based on handcrafted features. In addition to showing best performance, NR-IQA-CDI-NonPreCNN also enjoys the advantage of zero human intervention in designing feature, making it the most attractive solution for NR-IQA-CDI.
Volume: 9
Issue: 6
Page: 5604-5614
Publish at: 2019-12-01

An enhanced particle swarm optimization algorithm

10.11591/ijece.v9i6.pp4904-4907
Wameedh Riyadh Abdul-Adheem
In this paper, an enhanced stochastic optimization algorithm based on the basic Particle Swarm Optimization (PSO) algorithm is proposed. The basic PSO algorithm is built on the activities of the social feeding of some animals. Its parameters may influence the solution considerably. Moreover, it has a couple of weaknesses, for example, convergence speed and premature convergence. As a way out of the shortcomings of the basic PSO, several enhanced methods for updating the velocity such as Exponential Decay Inertia Weight (EDIW) are proposed in this work to construct an Enhanced PSO (EPSO) algorithm. The suggested algorithm is numerically simulated established on five benchmark functions with regards to the basic PSO approaches. The performance of the EPSO algorithm is analyzed and discussed based on the test results.
Volume: 9
Issue: 6
Page: 4904-4907
Publish at: 2019-12-01

3D modeling of multimode and single mode fiber

10.11591/ijeecs.v16.i3.pp1398-1406
Murizah Kassim , Ahmad Syahir Arif Mohd Zaid , Azlina Idris , Shahrani Shahbudin , Roslina Mohamad , Cik Ku Haroswati Che Ku Yahaya
This paper presents a design of 3D modeling of Multimode and Single Mode Fiber using SolidWorks. Fiber technology is essential that presents optical fiber is the fastest optical cable laid by Internet Service Providers in network communication. The current design of both fibers has less detail animation on technical specifications of light propagations and cladding. Thus, characterization difficulties occur between this two fiber optics cables. It also has less promotion in media publications such as 3D model design as guidance to users. This paper presents details on 3D modeling of multimode mode and single mode fiber specifications held in the industry market.  A 3D design with SolidWorks and comparison of both fiber characteristics are presented. Based on the 3D designed model, users are analyzed on their perspective and searching information which benefits telecommunication’s company. Technical calculations like core-cladding diameter ratio in microns are animated. The propagation of light in 3D single mode and multimode fiber is simulated using SolidWorks animator that presents it real fiber conditions. Result presents 10 most country searching used of both fiber cables and the difference in users search for both cables. A number of user’s search presents 3% more of multimode than single mode fiber search cases. This research is significant in presenting an animator of single and multimode fiber to users of network infrastructure development especially network developers and Telecommunications Company which can present it lively with animator transitions.
Volume: 16
Issue: 3
Page: 1398-1406
Publish at: 2019-12-01

Design and implementation of a Context-Aware Health Service Platform (CAHS)

10.11591/ijece.v9i6.pp4993-5005
Siham Belhadi , Rachid Merzougui
Computers are no match to humans in deducing situational information from their environment and in using it in their interactions. The advent of the context-aware applications seems to offer a way out to the computer that is not context-sensitive. The context aware applications can adapt their behaviors according to the perceived context or situation, without explicit user intervention, thereby providing human-centric services. To simplify the complexity of developing applications, context aware framework, which introduces context awareness into the environment where the applications are executed, is highlighted to provide a homogeneous interface involving generic context management and adaptation solutions. This papier has focused on the design of Context-Aware Health Services (CAHS) platform, which provide a health applications framework embedded on mobile devices. Our proposed platform is capabilities for context manager and adaptations according to context changes. It is designed to base on the SOA principles for achieving a flexible and dynamic architecture.
Volume: 9
Issue: 6
Page: 4993-5005
Publish at: 2019-12-01

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

Job Satisfaction and performance of elementary school teachers

10.11591/ijere.v8i4.20264
Agustinus Kia Wolomasi , Sandra Ingried Asaloei , Basilius Redan Werang
Given the high demands of contemporary community on the development of the youth, teachers’ job performance both inside and outside the classroom is of crucial for all partake parties, including school leaders, parents, education policymakers, and community at large. This study was meant to describe job satisfaction of elementary school teachers of Boven Digoel district, Papua, and how it predicts their job performance. To do so, we applied a survey research. Two survey questionnaire were self-administered to 352 teacher-respondent which were incidentally drawn from amongst 412 elementary school teachers of Boven Digoel district, Papua. Derived data were examined statistically using simple linear regression analysis method by utilizing Statistical Package for the Social Sciences (SPSS) version 21. Result of data analysis showed that job performance of elementary school teachers of Boben Digoel district is significant positively predicted by their job satisfaction. Finding of this study may be imperative for the school management and education administrator at the regional authority to make paramount efforts of creating valuable plans for enhancing teacher’s satisfaction in order to promote a better job performance of elementary school teachers of Boven Digoel district, Papua.
Volume: 8
Issue: 4
Page: 575-580
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

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

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

Learning face similarities for face verification using hybrid convolutional neural networks

10.11591/ijeecs.v16.i3.pp1333-1342
Fadhlan Hafizhelmi Kamaru Zaman , Juliana Johari , Ahmad Ihsan Mohd Yassin
Face verification focuses on the task of determining whether two face images belong to the same identity or not. For unrestricted faces in the wild, this is a very challenging task. Besides significant degradation due to images that have large variations in pose, illumination, expression, aging, and occlusions, it also suffers from large-scale ever-expanding data needed to perform one-to-many recognition task. In this paper, we propose a face verification method by learning face similarities using a Convolutional Neural Networks (ConvNet). Instead of extracting features from each face image separately, our ConvNet model jointly extracts relational visual features from two face images in comparison. We train four hybrid ConvNet models to learn how to distinguish similarities between the face pair of four different face portions and join them at top-layer classifier level. We use binary-class classifier at top-layer level to identify the similarity of face pairs which includes a conventional Multi-Layer Perceptron (MLP), Support Vector Machines (SVM), Native Bayes, and another ConvNet. There are 3 face pairing configurations discussed in this paper. Results from experiments using Labeled face in the Wild (LFW) and CelebA datasets indicate that our hybrid ConvNet increases the face verification accuracy by as much as 27% when compared to individual ConvNet approach. We also found that Lateral face pair configuration yields the best LFW test accuracy on a very strict test protocol without any face alignment using MLP as top-layer classifier at 87.89%, which on-par with the state-of-the-arts. We showed that our approach is more flexible in terms of inferencing the learned models on out-of-sample data by testing LFW and CelebA on either model.
Volume: 16
Issue: 3
Page: 1333-1342
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
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