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Metal-embedded SU-8 Slab Techniques for Low-resistance Micromachined Inductors

10.11591/ijece.v8i6.pp4772-4780
Manot Mapato , Prapong Klysuban , Thanatchai Kulworawanichpong , Nimit Chomnawang
This work presents a new fabrication technique for micro power inductors by using metal-embedded SU-8 slab molding techniques. The proposed technique uses X-ray lithography to fabricate high-aspect-ratio LIGA-like microstructures in form of embedded structures in the SU-8 slab. This process was applied to fabricate an inductor’s windings with an aspect ratio of 10, which can provide very low resistance but still preserve a small form factor and low profile. Inductors were designed as pot-core structures with overall heights of 370 μm and embedded with 250-μm-thick windings. From the advantage of metal embedded SU-8 slab techniques, 8 μm-thick permalloy core could be fabricated by electroplating around the winding in a single step that could help simplify the process. Four types of inductors were fabricated with 3, 5, 10, and 16 turns in the area of 1.8 to 9.5 mm2. The measured inductance was in the range of 70 nH to 1.3 μH at 1 MHz and DC resistance of 30–336 mΩ for 3–16 turns, respectively. The DC resistance of fabricated inductor was low, as expected, and showed good result compared with the results in literature.
Volume: 8
Issue: 6
Page: 4772-4780
Publish at: 2018-12-01

Applying of Double Seasonal ARIMA Model for Electrical Power Demand Forecasting at PT. PLN Gresik Indonesia

10.11591/ijece.v8i6.pp4892-4901
Ismit Mado , Adi Soeprijanto , Suhartono Suhartono
The prediction of the use of electric power is very important to maintain a balance between the supply and demand of electric power in the power generation system. Due to a fluctuating of electrical power demand in the electricity load center, an accurate forecasting method is required to maintain the efficiency and reliability of power generation system continuously. Such conditions greatly affect the dynamic stability of power generation systems. The objective of this research is to propose Double Seasonal Autoregressive Integrated Moving Average (DSARIMA) to predict electricity load. Half hourly load data for of three years period at PT. PLN Gresik Indonesia power plant unit are used as case study. The parameters of DSARIMA model are estimated by using least squares method. The result shows that the best model to predict these data is subset DSARIMA with order ([1,2,7,16,18,35,46],1,[1,3,13,21,27,46])(1,1,1)48(0,0,1)336 with MAPE about 2.06%. Thus, future research could be done by using these predictive results as models of optimal control parameters on the power system side.
Volume: 8
Issue: 6
Page: 4892-4901
Publish at: 2018-12-01

A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing

10.11591/ijece.v8i6.pp4646-4653
T. Francis
Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing has also become an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies resulted in a new area of computing called mobile cloud computing. This combined technology is used to augment the resources existing in Smart devices. In recent times, Fog computing, Edge computing, and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail and provides a comparative study of them. It also addresses the differences in these technologies and how each of them is effective for organizations and developers.
Volume: 8
Issue: 6
Page: 4646-4653
Publish at: 2018-12-01

Harmonic Mitigation in Traction Supply Substation Using Cascaded H-Bridge Converter

10.11591/ijpeds.v9.i4.pp1745-1754
A. Awalludin , C. L. Toh
The conventional three-level inverter has been proposed to act as a recuperating converter in Traction Supply Substation. This converter is mainly used to feed back the regenerative braking energy to the grid. However, passive filter is desired to mitigate the current and voltage harmonics. Therefore, this paper investigates the possibility to use a seven-level Cascaded H-Bridge (CHB) converter as the recuperating converter without additional filtering. The proposed converter is modeled with MATLAB/Simulink simulation software. It is then simulated with two potential modulation schemes, namely Phase-Shifted PWM (PS-PWM) and Phase-Disposition PWM (PD-PWM). The quality of AC waveforms produced by these two modulation methods is compared and studied. The results show that PS-PWM technique is preferable for this application as it offered a clean AC current waveform with less than 5% harmonic distortion. However, a twenty-one-level CHB was predicted to comply with the 8% voltage harmonic requirement.
Volume: 9
Issue: 4
Page: 1745-1754
Publish at: 2018-12-01

Low Complexity Fluctuation Measurement in Image Processing Considering Order

10.11591/ijece.v8i6.pp4253-4257
Tareq Khan
The standard deviation can measure the spread out of a set of numbers and entropy can measure the randomness. However, they do not consider the order of the numbers. This can lead to misleading results where the order of the numbers is vital. An image is a set of numbers (i.e. pixel values) that is sensitive to order. In this paper, a low complexity and efficient method for measuring the fluctuation is proposed considering the order of the numbers. The proposed method sums up the changes of consecutive numbers and can be used in image processing applications. Simulation shows that the proposed method is 8 to 33 times faster than other related works.
Volume: 8
Issue: 6
Page: 4253-4257
Publish at: 2018-12-01

Developing an Userfriendly Online Shopping Web-Site

10.11591/ijeecs.v12.i3.pp1126-1131
G saibaba , prasanth vaidya
In this era of internet, e-commerce is growing by leaps and bounds keeping the growth of brick-and-mortar businesses in the dust. In many cases, brick-and-mortar businesses are resorting to having a counterpart which is internet or e-commerce driven. People in the developed world and a growing number of people in the developing world now use ecommerce websites on a daily basis to make their everyday purchases. Still the proliferation of e-commerce in the underdeveloped world is not that great and there is a lot to desire for It consists of the planning process, which starts with determining the use case, domain modeling and architectural pattern of the web application. The entire development process is primarily divided into two parts: the front-end development and the back end development. The database design is also discussed with an emphasis on its relational connectivity.
Volume: 12
Issue: 3
Page: 1126-1131
Publish at: 2018-12-01

Brushless DC Motor Speed Control Using Single Input Fuzzy PI Controller

10.11591/ijpeds.v9.i4.pp1952-1966
N. N. Baharudin , S. M. Ayob
Brushless DC (BLDC) motor is more reliable than classic DC motor with higher efficiency. Commonly used conventional linear controller such as PI, PID and PD controller. FLC is considered a replacement to conventional controller due to advantages on non-linear system. Hybrid controller e.g Fuzzy PI controller is developed to cope with drawback of both controller. Simplification of FLC in previous study is the pioneer of the idea of proposed method. Single-Input Fuzzy PI Controller (SIFPIC) is a hybrid controller that combines advantages of linear PI controller and fuzzy controller in one control structure. Since it is a single input based fuzzy controller, it yields simpler design and tuning process.  Simulation is done using MATLAB/Simulink and the performance is observed through speed response under several conditions namely constant speed, changing seed and changing load torque. The performance of SIFPIC is compared with conventional PI and fuzzy PI controller. SIFPIC is as expected produced a response similar with the conventional fuzzy PI controller with both fuzzy based controller produce response with better dynamic.
Volume: 9
Issue: 4
Page: 1952-1966
Publish at: 2018-12-01

Comparative Study of Classification Method on Customer Candidate Data to Predict its Potential Risk

10.11591/ijece.v8i6.pp4763-4771
Mujiono Sadikin , Fahri Alfiandi
Leasing vehicles are a company engaged in the field of vehicle loans. Purchase by way of credit becomes a mainstay because it can attract potential customers to generate more profit. But if there is a mistake in approving a customer candidate, the risk of stalled credit payments can happen. To minimize the risk, it can be applied the certain data mining technique to predict the future behavior of the customers. In this study, it is explored in some data mining techniques such as C4.5 and Naive Bayes for this purpose. The customer attributes used in this study are: salary, age, marital status, other installments and worthiness. The experiments are performed by using the Weka software. Based on evaluation criteria, i.e. accuracy, C4.5 algorithm outperforms compared to Naive Bayes. The percentage split experiment scenarios provide the precision value of 89.16% and the accuracy value of 83.33% wheres the cross validation experiment scenarios give the higher accuracy values of all used k-fold. The C4.5 experiment results also confirm that the most influential instant data attribute in this research is the salary.
Volume: 8
Issue: 6
Page: 4763-4771
Publish at: 2018-12-01

Robust Multi-Objective Control of Power System Stabilizer Using Mixed H2/H∞ and µ Analysis

10.11591/ijece.v8i6.pp4800-4809
Javad Mashayekhi Fard
In order to study the dynamic stability of the system, having a precise dynamic model including the energy generation units such as generators, excitation system and turbine is necessary. The aim of this paper is to design a power stabilizer for Mashhad power plant and assess its effects on the electromechanical fluctuations. Due to lack of certainty in the system, designing an optimized robust controller is crucial. In this paper, the establishment of balance between the nominal and robust performance is done by the weight functions. In the frequencies where the uncertainty is high, in order to achieve to the robust performance of the controller, μ analysis is more profound, otherwise, in order to achieve to nominal performance, robust stability, noise reduction and decrease of controlling signal, the impact of the controller H2/H∞ is more profound. The results of the simulation studies represent the advantages and effectiveness of the suggested method.
Volume: 8
Issue: 6
Page: 4800-4809
Publish at: 2018-12-01

Voltage Tracking Control of DC- DC Boost Converter Using Fuzzy Neural Network

10.11591/ijpeds.v9.i4.pp1657-1665
Waleed Ishaq Hameed , Baha Aldeen Sawadi , Ali Muayed
This paper deals with voltage tracking control of DC- DC boost converter based on Fuzzy neural network. Maintaining the output voltage of the boost converter in some applications are very important, especially for sudden change in the load or disturbance in the input voltage. Traditional control methods usually have some disadvantages in eliminating these disturbances, as the speed of response to these changes is slow and thus affect the regularity of the output voltage of the converter. The strategy is to sense the output voltage across the load and compare it with the reference voltage to ensure that it follows the required reference voltages. In this research, fuzzy neural was introduced to achieve the purpose of voltage tracking by training the parameter of controller based on previous data. These data sets are the sensing input voltage of the converter and the value of the output load changes. To establish the performance of proposed method, MATLAB/SIMULINK environments are presented, simulation results shows that proposed method works more precisely, faster in response and elimination the disturbances
Volume: 9
Issue: 4
Page: 1657-1665
Publish at: 2018-12-01

Wireless Mesh Networks Based on MBPSO Algorithm to Improvement Throughput

10.11591/ijece.v8i6.pp4374-4381
Shivan Qasim Ameen , Firas Layth Khaleel
Wireless Mesh Networks can be regarded as a type of communication technology in mesh topology in which wireless nodes interconnect with one another. Wireless Mesh Networks depending on the semi-static configuration in different paths among nodes such as PDR, E2E delay and throughput. This study summarized different types of previous heuristic algorithms in order to adapt with proper algorithm that could solve the issue. Therefore, the main objective of this study is to determine the proper methods, approaches or algorithms that should be adapted to improve the throughput. A Modified Binary Particle Swarm Optimization (MBPSO) approach was adapted to improvements the throughput. Finally, the finding shows that throughput increased by 5.79% from the previous study.
Volume: 8
Issue: 6
Page: 4374-4381
Publish at: 2018-12-01

Detection and Separation of Eeg Artifacts Using Wavelet Transform

10.11591/ijict.v7i3.pp149-156
R. Suresh Kumar , P. Manimegalai
Bio-medical signal processing is one of the most important techniques of multichannel sensor network and it has a substantial concentration in medical application. However, the real-time and recorded signals in multisensory instruments contains different and huge amount of noise, and great work has been completed in developing most favorable structures for estimating the signal source from the noisy signal in multichannel observations. Methods have been developed to obtain the optimal linear estimation of the output signal through the Wide-Sense-Stationary (WSS) process with the help of time-invariant filters. In this process, the input signal and the noise signal are assumed to achieve the linear output signal. During the process, the non-stationary signals arise in the bio-medical signal processing in addition to it there is no effective structure to deal with them. Wavelets transform has been proved to be the efficient tool for handling the non-stationary signals, but wavelet provide any possible way to approach multichannel signal processing. Based on the basic structure of linear estimation of non-stationary multichannel data and statistical models of spatial signal coherence acquire through the wavelet transform in multichannel estimation. The above methods can be used for Electroencephalography (EEG) signal denoising through the original signal and then implement the noise reduction technique to evaluate their performance such as SNR, MSE and computation time.
Volume: 7
Issue: 3
Page: 149-156
Publish at: 2018-12-01

Real-Time Implementation and Performance Optimization of Local Derivative Pattern Algorithm on GPUs

10.11591/ijece.v8i6.pp5457-5471
Nisha Chandran , Durgaprasad Gangodkar , Ankush Mittal
Pattern based texture descriptors are widely used in Content Based Image Retrieval (CBIR) for efficient retrieval of matching images. Local Derivative Pattern (LDP), a higher order local pattern operator, originally proposed for face recognition, encodes the distinctive spatial relationships contained in a local region of an image as the feature vector. LDP efficiently extracts finer details and provides efficient retrieval however, it was proposed for images of limited resolution. Over the period of time the development in the digital image sensors had paid way for capturing images at a very high resolution. LDP algorithm though very efficient in content-based image retrieval did not scale well when capturing features from such high-resolution images as it becomes computationally very expensive. This paper proposes how to efficiently extract parallelism from the LDP algorithm and strategies for optimally implementing it by exploiting some inherent General-Purpose Graphics Processing Unit (GPGPU) characteristics. By optimally configuring the GPGPU kernels, image retrieval was performed at a much faster rate. The LDP algorithm was ported on to Compute Unified Device Architecture (CUDA) supported GPGPU and a maximum speed up of around 240x was achieved as compared to its sequential counterpart.
Volume: 8
Issue: 6
Page: 5457-5471
Publish at: 2018-12-01

Overview of Bifluid-based Photovoltaic Thermal (PVT) Systems

10.11591/ijpeds.v9.i4.pp1912-1917
Nurul Shahirah Binti Rukman , Ahmad Fudholi , Saleem H. Zaidi , Kamaruzzaman Sopian
This review presents various research and development, as well as design and performances of bifluid-based PVT systems. Moreover, the development of PVT system is a very promising area of research. PVT systems using in various applications, such as solar drying, solar cooling, water heating, desalination, and pool heating. With the recognition of the potentials and contributions of PV system, considerable research has been conducted to attain the most advancement which may produce reliable and sustainable PVT system. The cooling system’s design refers to the absorber design which mostly focuses on water and air-based PVT systems. An air-based system has been developed through different absorber configurations, air flow modes and single- or double-pass design. Bifluid-based PVT system is used to remove heat accumulated in a PV panel and reuses the waste heat (hot air and water) in an appropriate way. PV, thermal and PVT efficiencies of bifluid PVT systems were 6.6%-18.6%, 31%–90% and 60%-83%, respectively. 
Volume: 9
Issue: 4
Page: 1912-1917
Publish at: 2018-12-01

A Novel Hybrid Classification Approach for Sentiment Analysis of Text Document

10.11591/ijece.v8i6.pp4554-4567
Yassine Al Amrani , Mohamed Lazaar , Kamal Eddine El Kadiri
Sentiment analysis is a more popular area of highly active research in Automatic Language Processing. She assigns a negative or positive polarity to one or more entities using different natural language processing tools and also predicted high and low performance of various sentiment classifiers. Our approach focuses on the analysis of feelings resulting from reviews of products using original text search techniques. These reviews can be classified as having a positive or negative feeling based on certain aspects in relation to a query based on terms. In this paper, we chose to use two automatic learning methods for classification: Support Vector Machines (SVM) and Random Forest, and we introduce a novel hybrid approach to identify product reviews offered by Amazon. This is useful for consumers who want to research the sentiment of products before purchase, or companies that want to monitor the public sentiment of their brands. The results summarize that the proposed method outperforms these individual classifiers in this amazon dataset.
Volume: 8
Issue: 6
Page: 4554-4567
Publish at: 2018-12-01
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