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International Journal of Electrical and Computer Engineering

IJECE
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Published by Institute of Advanced Engineering and Science

ISSN : 20888708 EISSN : 27222578 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 151 Documents

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Search results for , issue "Vol 8, No 6: December 2018" : 151 Documents clear

Cerebellar Model Controller with new Model of Granule Cell-golgi Cell Building Blocks and Two-phase Learning Acquires Multitude of Generalization Capabilities in Controlling Robot Joint without Exponential Growth in Complexity Lavdim Kurtaj; Vjosa Shatri; Ilir Limani
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Processing in the cerebellum is roughly described as feed forward processing of incoming information over three layers of the cerebellar cortex that send intermediate output to deep cerebellar nuclei, the only output from the cerebellum. Beside this main picture there are several feedback routes, mainly not included in models. In this paper we use new model for neuronal circuit of the cerebellar granule cell layer, as collection of idealized granule cell–golgi cell building blocks with capability of generating multi-dimensional receptive fields modulated by separate input coming to lower dendrite tree of Golgi cell. Resulting cerebellar model controller with two-phase learning will acquire multitude of generalization capabilities when used as robot joint controller. This will usually require more than one Purkinje cell per output. Functionality of granule cell-Golgi cell building block was evaluated with simulations using Simulink single compartment spiking neuronal model. Trained averaging cerebellar model controller attains very good tracking results for wide range of unlearned slower and faster trajectories, with additional improvements by relearning at faster trajectories. Inclusion of new dynamical effects to the controller results with linear growth in complexity for inputs targeting lower dendrite tree of Golgi cell, important for control applications in robotics, but not only.

A Novel Design of Voltage Controlled Oscillator By using the Method of Negative Resistance Ayoub Malki; Larbi El Abdellaoui; Jamal Zbitou; A. Errkik; A. Tajmouati; Mohamed Latrach
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

The objective of this paper is to develop a new design of a voltage controlled microwave oscillator by using the method of negative resistance in order to fabricate VCO with very good performance in terms of tuning rang, phase noise, output power and stability. The use of hybrid microwave integrated circuit technology’s (HMIC) offers a lot of advantage for our structure concerning size, cost, productivity, and Q factor. This VCO is designed at [480MHz; 1.4GHz] frequency for applications in the phase locked loop (PLL) for signal tracking, FM demodulation, frequency modulation, mobile communication, etc. The different steps of studied voltage controlled oscillator’s design are thoroughly described. Initially designed at a fixed frequency meanwhile the use of a varactor allow us to tune the frequency of the second design. It has been optimized especially regarding tuning bandwidth, power, phase noise, consumption and size of the whole circuit. The achieved results and proposed amendment are the product of theoretical study and predictive simulations with advanced design system microwave design software. A micro-strip VCO with low phase noise based on high gain ultra low noise RF transistor BFP 740 has been designed, fabricated, and characterized. The VCO delivers a sinusoidal signal at the frequency 480 MHz with tuning bandwidth 920 MHz, spectrum power of 12.62 dBm into 50 Ω load and phase noise of -108 dBc/Hz at 100 Hz offset. Measurement results and simulation are in good agreement. Circuit is designed on FR4 substrate which includes integrated resonators and passive components.

Pattern Approximation Based Generalized Image Noise Reduction Using Adaptive Feedforward Neural Network Nagaraj Bhat; U. Eranna; Manoj Kumar Singh
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

The problem of noise interference with the image always occurs irrespective of whatever precaution is taken. Challenging issues with noise reduction are diversity of characteristics involved with source of noise and in result; it is difficult to develop a universal solution. This paper has proposed neural network based generalize solution of noise reduction by mapping the problem as pattern approximation. Considering the statistical relationship among local region pixels in the noise free image as normal patterns, feedforward neural network is applied to acquire the knowledge available within such patterns. Adaptiveness is applied in the slope of transfer function to improve the learning process. Acquired normal patterns knowledge is utilized to reduce the level of different type of noise available within an image by recorrection of noisy patterns through pattern approximation. The proposed restoration method does not need any estimation of noise model characteristics available in the image not only that it can reduce the mixer of different types of noise efficiently. The proposed method has high processing speed along with simplicity in design. Restoration of gray scale image as well as color image has done, which has suffered from different types of noise like, Gaussian noise, salt &peper, speckle noise and mixer of it.

UDP Pervasive Protocol Integration with IoT for Smart Home Environment using LabVIEW Mochammad Hannats Hanafi Ichsan; Wijaya Kurniawan; Sabriansyah Rizqika Akbar
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Pervasive computing is an environment which is used and integrated into every object and activities to meet human needs and its existence isn’t perceived as something specific. The concept of Smart Home is to assist human needs in an everyday object that performs controls or being controlled. Based on previous research the used communication protocol is UDP (User Datagram Protocol) and the programming language is LabVIEW. UDP is used because it does not require handshaking in the broadcast process, as well as on the use of memory more efficient than other protocols. Devices which perform controls called Host and which is controlled called Client. Both of them (Things) have an ability to send data to the Internet without any human interaction. So this research wants to conduct pervasive protocol between Host and Client which each device is integrated with the Internet of Things (IoT). Data are posted at dweet.io that is a cloud server website that contains a simple online data submission which has free services. This research is conducted to measure the communication performance between host to client, host to cloud server and client to cloud server that represents household equipment.

Automation of DMPS Manufacturing by using LabView & PLC Fareeza F; Chunchu Rambabu; S. Krishnaveni; Abel Chernet Kabiso
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

This Paper is to enable the Siemens (Programmable Logic Control) CPU 313-5A to communicate with the Lab VIEW and to control the process accuracy by image processing. The communication between CPU 313-5A and Lab VIEW is via OPC (OLE for Process Control).Process Accuracy is achieved with the use of Labview Image Processing and Gray Scale matching Pattern. Accuracy in the gray scale matching will purely depend on the calibration of the camera with respect to the corresponding image. The digital output from the labview is communicated to PLC via Ethernet Protocol for the industrial process control. With the use of Labview the dead time while using the normal image vision module in PLC can be minimized. Labview uses the gray scale matching technique which is more accurate than the normal image vision module used in PLC.

Average Channel Capacity of Amplify-and-forward MIMO/FSO Systems Over Atmospheric Turbulence Channels Duong Huu Ai
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

In amplify-and-forward (AF) relay channel, when the direct link between source and destination terminals is deeply faded, the signal from the source terminal to the destination terminal propagates through the relay terminals, each of which relays a signal received from the previous terminal to the next terminal in series. This paper, we theoretically analyze the performance of multiple-input multiple-output (MIMO) AF free-space optical (FSO) systems. The AF-MIMO/FSO average channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE) is derived taking into account the atmospheric turbulence effects on the MIMO/FSO channel. They are modeled by log-normal and the gamma-gamma distributions for the cases of weak-to-strong turbulence conditions. We extract closed form mathematical expression for the evaluation of the ACC and we quantitatively discuss the influence of turbulence strength, link distance, different number of relay stations and different MIMO configurations on it.

Secure Privacy Implications for Clients and End-users through Key Assortment Crypto Techniques Implicated Algorithm Ramesh D; Rama B
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

The main role of key assortment crypto techniques will helpful to provide the security to the sensitive data and play the key role for business developments. Some of the problems are rising when the scheme will sustain the possession control to present the latest set of technical and business concerns. Some of the complex challenges are waiting for the optimistic solutions. The challenges are: In the planned storage confidentiality implicated outline, the stipulation of encryption framework for the data which is conserve the self tunning to execute major key constratints by concerining their files which is imposed plaintext belonging, the owners of the privacy-data preserve the seclusion power over their own information to formulate assured wide-ranging service operations and the owners of data are facing the complexity to organize their possess data which is accessible-mode in cloud servers, concerned inner services: topology architecture type of implicated data with their operations, associated secrecy-privacy-secrecy dynamic replicas for make use of the databased security within their range of format and secretarial services with their encrypted data execution control. To overcome theses in convinces this paper is proposing the technical ideals through the algorithmic methodology along the graphical flow based architecture. This paper is proposing the key assortment crypto techniques implicated algorithm for clients and end-users to reduce the above mention complex difficulties; it describes the primary encryption implicated techniques and various levels of cryptographic algorithms with their implications along with extensions of cloud implicated data security and digital forensics implicated appliances which is implicated with enhanced various hash functions.

Domain Examination of Chaos Logistics Function As A Key Generator in Cryptography Alz Danny Wowor; Vania Beatrice Liwandouw
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

The use of logistics functions as a random number generator in a cryptography algorithm is capable of accommodating the diffusion properties of the Shannon principle. The problem that occurs is initialization x was static and was not affected by changes in the key, so that the algorithm will generate a random number that is always the same. This study design three schemes that can providing the ﬂexibility of the input keys in conducting the examination of the value of the domain logistics function. The results of each schemes do not show a pattern that is directly proportional or inverse with the value of x0 and relative error x and successfully fulﬁll the properties of the butterﬂy effect. Thus, the existence of logistics functions in generating chaos numbers can be accommodated based on key inputs. In addition, the resulting random numbers are distributed evenly over the chaos range, thus reinforcing the algorithm when used as a key in cryptography.

Using Data Mining to Identify COSMIC Function Point Measurement Competence Selami Bagriyanik; Adem Karahoca
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Cosmic Function Point (CFP) measurement errors leads budget, schedule and quality problems in software projects. Therefore, it’s important to identify and plan requirements engineers’ CFP training need quickly and correctly. The purpose of this paper is to identify software requirements engineers’ COSMIC Function Point measurement competence development need by using machine learning algorithms and requirements artifacts created by engineers. Used artifacts have been provided by a large service and technology company ecosystem in Telco. First, feature set has been extracted from the requirements model at hand. To do the data preparation for educational data mining, requirements and COSMIC Function Point (CFP) audit documents have been converted into CFP data set based on the designed feature set. This data set has been used to train and test the machine learning models by designing two different experiment settings to reach statistically significant results. Ten different machine learning algorithms have been used. Finally, algorithm performances have been compared with a baseline and each other to find the best performing models on this data set. In conclusion, REPTree, OneR, and Support Vector Machines (SVM) with Sequential Minimal Optimization (SMO) algorithms achieved top performance in forecasting requirements engineers’ CFP training need.

Intelligent Sensing Using Metal Oxide Semiconductor Based-on Support Vector Machine for Odor Classification Nyayu Latifah Husni; Siti Nurmaini; Irsyadi Yani; Ade Silvia
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Classifying odor in real experiment presents some challenges, especially the uncertainty of the odor concentration and dispersion that can lead to a difficulty in obtaining an accurate datasets. In this study, to enhance the accuracy, datasets arrangement based on MOS sensors parameters using SVM approach for odor classification is proposed. The sensors are tested to determine the sensors' time response, sensors' peak duration, sensors' sensitivity, and sensors' stability when applied to the various sources at different range. Three sources were used in experimental test, namely: ethanol, methanol, and acetone. The gas sensors characteristics are analyzed in open sampling method to see the sensors' performance in real situation. These performances are considered as the base of choosing the position in collecting the datasets. The sensors in dynamic experiment have average of precision of 93.8-97.0%, the accuracy 93.3-96.7%, and the recall 93.3-96.7%. This values indicates that the collected datasets can support the SVM in improving the intelligent sensing when conducting odor classification work.

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Home Page

OAI Link

Editorial Team

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Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

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Abstract

Abstract

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Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA