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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 33 Documents
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Search results for , issue "Vol 7, No 3: September 2017" : 33 Documents clear
Secure Cloud based Privacy Preserving DataMinning Platform S Kumaraswamy; Manjula S H; K R Venugopal
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp830-838

Abstract

The adoption of cloud environment for various application uses has led to security and privacy concern of user’s data. To protect user data and privacy on such platform is an area of concern. Many cryptography strategy has been presented to provide secure sharing of resource on cloud platform.  These methods tries to achieve a secure authentication strategy to realize feature such as self-blindable access tickets, group signatures, anonymous access tickets, minimal disclosure of tickets and revocation but each one varies in realization of these features. Each feature requires different cryptography mechanism for realization. Due to this it induces computation complexity which affects the deployment of these models in practical application. Most of these techniques are designed for a particular application environment and adopt public key cryptography which incurs high cost due to computation complexity. To address these issues this work present an secure and efficient privacy preserving of mining data on public cloud platform by adopting party and key based authentication strategy. The proposed SCPPDM (Secure Cloud Privacy Preserving Data Mining) is deployed on Microsoft azure cloud platform. Experiment is conducted to evaluate computation complexity. The outcome shows the proposed model achieves significant performance interm of computation overhead and cost.
Classification Of Category Selection Title Undergraduate Thesis Using K-Nearest Neighbor Method Ratih Kumalasari Niswatin; Ardi Sanjaya
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp846-854

Abstract

This research makes the classification system of  category selection title undergraduate thesis titleuse k-nearest neighbor method. This research will be conducted on the students of Informatics Engineering Department Faculty of Engineering, Universitas Nusantara PGRI Kediri. The purpose of making this system is to employee department and students to more easily make a classification of category selection undergraduate thesis title based on the field of interest and field of expertise of each student. The method used to classify the selection of undergaduate thesis title categories is k-nearest neighbormethod using several criteria based on students' interests and expertise in a particular field or course. The result of this sitem is an information category of undergraduate thesis title of students who have been processed based on the field of interest and field of expertise of each student.
An Efficient Patient Inflow Prediction Model For hospital Resource Management Kottalanka Srikanth; D. Arivazhagan
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp809-817

Abstract

There has been increasing demand in improving service provisioning in hospital resources management. Hospital industries work with strict budget constraint at the same time assures quality care. To achieve quality care with budget constraint an efficient prediction model is required. Recently there has been various time series based prediction model has been proposed to manage hospital resources such ambulance monitoring, emergency care and so on.  These models are not efficient as they do not consider the nature of scenario such climate condition etc. To address this artificial intelligence is adopted. The issues with existing prediction are that the training suffers from local optima error.  This induces overhead and affects the accuracy in prediction. To overcome the local minima error, this work presents a patient inflow prediction model by adopting resilient backpropagation neural network. Experiment are conducted to evaluate the performance of proposed model inter of RMSE and MAPE. The outcome shows the proposed model reduces RMSE and MAPE over existing back propagation based artificial neural network. The overall outcomes show the proposed prediction model improves the accuracy of prediction which aid in improving the quality of health care management.
Developing a Modified HMAX Model Based on Combined with the Visual Featured Model Yaghoub Pourasad
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp773-785

Abstract

Identify objects based on modeling the human visual system, as an effective method in intelligent identification, has attracted the attention of many researchers. Although the machines have high computational speed but are very weak as compared to humans in terms of diagnosis. Experience has shown that in many areas of image processing, algorithms that have biological backing had more simplicity and better performance. The human visual system, first select the main parts of the image which is provided by the visual featured model, then pays to object recognition which is a hierarchical operations according to this, HMAX model is also provided. HMAX object recognition model from the group of hierarchical models without feedback that its structure and parameters selected based on biological characteristics of the visual cortex. This model is a hierarchical model neural network with four layers, is composed of alternating layers that are simple and complex. Due to the high complexity of the human visual system is virtually impossible to replicate it. For each of the above, separate models have been proposed but in the human visual system, this operation is performed seamlessly, thus, by combining the principles of these models is expected to be closer to the human visual system and obtain a higher recognition rate. In this paper, we introduce an architecture to classify images based on a combination of previous work is based on the basic operation of the visual cortex. According to the results presented, the proposed model compared with the main HMAX model has a much higher recognition rate. Simulations was performed on the database of Caltech101.
Artificial Neural Network Application for Thermal Image Based Condition Monitoring of Zinc Oxide Surge Arresters Novizon Novizon; Zulkurnain Abdul-Malek; Aulia Aulia
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp593-605

Abstract

Manual analysis of thermal image for detecting defects and classifying of condition of surge arrester take a long time. Artificial neural network is good tool for predict and classify data. This study applied neural network for classify the degree of degradation of surge arrester. Thermal image as input of neural network was segmented using Otsu’s segmentation and histogram method to get features of thermal image. Leakage current as a target of supervise neural network was extracted and applied Fast Fourier Transform to get third harmonic of resistive leakage current. The classification results meet satisfaction with error about 3%.
Selective MAC for Obstacle Aware CEV Environmental Model for V2V Usha Rani B; Suraiya Tarannum
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp724-736

Abstract

Vehicular adhoc network (VANET) adopts or resembles a similar structure of Mobile adhoc network (MANET).  The communication in VANET are generally classified into following three categories such as Vehicle to Infrastructure (V2I), Vehicle to Vehicle (V2V) and Hybrid network which is a combination of V2V and V2I network. VANET using the IEEE 802.11p standard has great potential of achieving objectives of Smart intelligent transport system (SITS) for improving transport and road safety efficiency. As more and more services is been provided for V2V based VANET network. It is a challenging task to provide QoS to end user, due to wireless medium that has limited channel availability for transmission. To guarantee QoS and provide efficient network performance, a prioritized MAC need to be designed. Many priority based MAC has been designed in recent times to improve the quality of data delivery to end user. However these do not consider the impact of environment and presence of obstacle which affects the signal attenuation at the receiver end and affecting the QoS of channel availability. To address, this work present an obstacle based radio propagation model, obstacle based CEV (City, Expressway and Village) environmental model and a selective MAC to provide QoS for different services. The proposed model efficiency is evaluated in term of throughput achieved per channel, Collison and success packet transmission. To evaluate the adaptive performance of proposed AMACexperiment are conducted under CEV environment and are compared with existing MAC NCCMA. The outcome achieved shows that the proposed model is efficient in term of reducing Collison, improving packet transmission and throughput performance considering two types of services.
Software Aging Forecasting Using Time Series Model I M Umesh; G N Srinivasan; Matheus Torquato
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp839-845

Abstract

With the emergence of virtualization and cloud computing technologies, several services are housed on virtualization platform. Virtualization is the technology that many cloud service providers rely on for efficient management and coordination of the resource pool. As essential services are also housed on cloud platform, it is necessary to ensure continuous availability by implementing all necessary measures.  Windows Active Directory is one such service that Microsoft developed for Windows domain networks. It is included in Windows Server  operating systems as a set of processes and services for authentication and authorization of users and computers in a Windows domain type network. The service is required to run continuously without downtime. As a result, there are chances of accumulation of errors or garbage leading to software aging which in turn may lead to system failure and associated consequences. This results in software aging. In this work, software aging patterns of Windows active directory service is studied. Software aging of active directory needs to be predicted properly so that rejuvenation can be triggered to ensure continuous service delivery. In order to predict the accurate time, a model that uses time series forecasting technique is built.
Evaluation of Various Maintenance Strategies for Reliability Assessment of Thermal Power Plants Sima Zarei; Peiman Ghaedi-Kajuei
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp617-624

Abstract

In recent years, the world has had a phenomenal economic growth due to the acquisition of innovative technologies and globalization. In the meantime, electrical power plants are regarded as a fundamental element in industrial and production, and any deficiency in supplying may lead to significant financial detriment. Regard to the deep dependency of modern lifestyle to electricity, providing a high-quality and reliable electricity for consumers has taken on paramount importance. The reliability of a power plant depends on the configuration of elements and the reliability of each utility. The reliability, continuous service, flexibility in operation, simplicity, maintenance, development availability, meeting required standards etc. constitute the decisive factors for selection of a utility. Hence, each component of a power system must maintain the adequate level of reliability. In general, the maintenance approaches are classified into two parts: 1- The maintenance which must be carried out within determined and specified time intervals; 2- The maintenance which must be performed when required or in emergencies. To evaluate the maintenance and its effect on reliability, two types of deterministic and probabilistic approaches are presented. In this paper, a comprehensive description of both models is issued, and a detailed comparison is drawn. The results obviously show that the probabilistic models have considerable priority to deterministic models regard to their abilities for maximization of reliability or minimization of costs.
A Survey on Software Estimation Techniques in Traditional and Agile Development Models B. Prakash; V. Viswanathan
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp867-876

Abstract

Software projects mostly exceeds budget, delivered late and does not meet with the customer’s satisfaction for years. In the past, many traditional development models like waterfall, spiral, iterative, and prototyping methods are used to build the software systems. In recent years, agile models are widely used in developing the software products. The major reasons are – simplicity, incorporating the requirement changes at any time, light-weight approach and delivering the working product early and in short duration. Whatever the development model used, it still remains a challenge for software engineer’s to accurately estimate the size, effort and the time required for developing the software system. This survey focuses on the existing estimation models used in traditional as well in agile software development.
Comparative Analysis of Carrier based techniques for Single phase Diode Clamped MLI and Hybrid inverter with reduced components Nunsavath Susheela
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp687-697

Abstract

The multilevel inverters have highly desirable characteristics in high power high voltage applications. The multilevel inverter was started first with diode clamped multilevel inverter. Later, various configurations have been came into existence for many applications. However the multilevel inverters have some demerits such as requiring higher number of components, PWM control method is complex and capacitor voltage balancing problem. The hybrid multilevel inverter presented in this paper has superior characteristics over conventional multilevel inverters. The hybrid multilevel inverter employs fewer components and less carrier signals when compared to conventional multilevel inverters. It consists of level generation and polarity generation stages which involves high frequency and low frequency switches. The complexity and overall cost for higher output voltage levels are greatly reduced. Implementation of single phase 7-level, 9-level and 11-level diode clamped multilevel inverter and hybrid multilevel inverter has been performed using sinusoidal pulse width modulation (SPWM) strategies i.e., phase disposition (PD), alternate phase opposition disposition (APOD). Also these techniques are compared in terms of total harmonic distortion (THD) for various modulation indices and observed to be greatly improved in case of hybrid inverter when compared to diode clamped inverter. The comparative study of performance for single phase diode clamped multilevel inverter and hybrid inverter is analyzed with different loads.  Simulation is performed using MATLAB/ SIMULINK. 

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