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31,377 Article Results

Optimal power flow based congestion management using enhanced genetic algorithms

10.11591/ijece.v9i2.pp875-883
Seong-Cheol Kim , Surender Reddy Salkuti
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Volume: 9
Issue: 2
Page: 875-883
Publish at: 2019-04-01

Bandwidth enhancement and miniaturization of circular-shaped microstrip antenna based on beleved half-cut structure for MIMO 2x2 application

10.11591/ijece.v9i2.pp1110-1121
Teguh Firmansyah , Supriyanto Praptodiyono , Herudin Herudin , Didik Aribowo , Syah Alam , Dian Widi Astuti , Muchamad Yunus
In this paper, circular-shaped microstrip antenna was simulated, fabricated, and measured accordingly. As the novelty, to enhance bandwidth and reduce antenna size, beleved half-cut microstrip structure is proposed. Further, this proposed antenna structure will be applied to multiple input multiple output (MIMO) antenna 2´2. Therefore, this research was investigated conventional circular shape antenna (CCSA), circular shaped beleved antenna (CSBA), and MIMO circular shaped beleved antenna (MIMO-CBSA) as Model 1, Model 2, and Model 3, respectively. An FR4 substrate with er= 4.4, thickness h=1.6 mm, and tan d=0.0265 was used. The simulation has been conducted using Advanced Design System (ADS). The antenna CCSA/CSBA/ MIMO-CBSA achieve 1.831GHz/2.265 GHz/2.256 GHz, -15.13dB/-17.37dB/-17.25 dB, 1.42/1.31/1.33, and 1.474/2.332/2.322 for center frequency, reflection coefficient, VSWR, and bandwidth, respectively. This antenna has a size 63x90 mm and 51.5x90 mm for CCSA (Model 1) and CSBA (Model 2), respectively. After the structure of MIMO 2´2 was applied, the size of antenna MIMO-CBSA (Model 3) became 180 mm x 180 mm with a mutual coupling (S21)=-26.18 dB and mutual coupling (S31)=-26.41 dB. The result showed that proposed antenna CSBA (Model 2) has wider-bandwidth of 58,2% and smaller-size of 18.2%. Furthermore, after CSBA (Model 2) structure was applied to MIMO 2´2 (Model 3) and the MIMO antenna obtain good mutual coupling (<-15dB). Moreover, the measured results are good agreement with the simulated results. In conclusion, all of these advantages make it particularly valuable in multistandard antenna applications design such as GSM950, WCDMA1800, LTE2300, and WLAN2400.
Volume: 9
Issue: 2
Page: 1110-1121
Publish at: 2019-04-01

Framework for progressive segmentation of chest radiograph for efficient diagnosis of inert regions

10.11591/ijece.v9i2.pp982-991
Savitha S. K. , N. C. Naveen
Segmentation is one of the most essential steps required to identify the inert object in the chest x-ray. A review with the existing segmentation techniques towards chest x-ray as well as other vital organs was performed. The main objective was to find whether existing system offers accuracy at the cost of recursive and complex operations. The proposed system contributes to introduce a framework that can offer a good balance between computational performance and segmentation performance. Given an input of chest x-ray, the system offers progressive search for similar image on the basis of similarity score with queried image. Region-based shape descriptor is applied for extracting the feature exclusively for identifying the lung region from the thoracic region followed by contour adjustment. The final segmentation outcome shows accurate identification followed by segmentation of apical and costophrenic region of lung. Comparative analysis proved that proposed system offers better segmentation performance in contrast to existing system.
Volume: 9
Issue: 2
Page: 982-991
Publish at: 2019-04-01

Influence of optimization of control factors on threshold voltage of 18 nm HfO2/TiSi2 NMOS

10.11591/ijeecs.v14.i1.pp295-302
Norani Atan , Burhanuddin Bin Yeop Majlis , Ibrahim Bin Ahmad , K. H. Chong
This paper presents the influence of control factors as the process in development of 18 nm gate length NMOS transistor. The threshold voltage (VTH) can be minimized by optimal the control factors. Five control factors were selected through experiments. They are Adjustment VTH Implantation, Compensation Implantation, Compensation Energy Implantation, Source/Drain Implantation and Halo Implantation.  While the two noise factors were introduced which are Phosphor Silicate Glass (PSG) temperature and Boron Phosphor Silicate Glass (BPSG) temperature to complete the combination with five control factors in process of Taguchi method L27 orthogonal array. The purpose of this research is to find the best value of interaction between combination controls factors and noise factors to achieve the best point of threshold voltage.  In CMOS design, the threshold voltage is the benchmarking of physical parameter for determining the functional of transistor. The Virtual Wafer Fabrication SILVACO software was used to fabricate the 18 nm NMOS device. Hafnium Oxide (HfO2) and Titanium dioxide (TiO2) were utilized as the high-K materials and the Titanium Silicide (TiSi2) was utilized as metal gate. The statistics data are from the signal noise ratio (SNR) with nominal-the best (NTB) and the analysis of variance (ANOVA) of L27 orthogonal array are executed to minimize the variance of threshold voltage. The results show that the optimization and interaction method is achieved to perform the threshold voltage value with least variance  is 0.3055 volts while the target value that is 0.302 ± 12.7% volts from value recommendation by the International Roadmap for Semiconductor prediction 2012.
Volume: 14
Issue: 1
Page: 295-302
Publish at: 2019-04-01

Energy distribution in formant bands for arabic vowels

10.11591/ijece.v9i2.pp1163-1167
Mohamed Farchi , Karim Tahiry , Soufyane Mounir , Badia Mounir , Ahmed Mouhsen
The acoustic cues play a major role in speech segmentation phase; the extraction of these indexes facilitates the characterization of the speech signal. In this work, we aim to study Arabic vowels (/a/, /a:/, /i/, /i:/, /u/ and /u:/), especially the long ones. We are interested in characterizing this type of vowels in terms of time, frequency and energy. The cues extracted and analyzed in this work are: segment length, voicing degree and formants values.
Volume: 9
Issue: 2
Page: 1163-1167
Publish at: 2019-04-01

Noise reduction in ECG signals for bio-telemetry

10.11591/ijece.v9i2.pp1028-1035
V. Jagannaveen , K. Murali Krishna , K. Raja Rajeswari
In Biotelemetry, Biomedical signal such as ECG is extremely important in the diagnosis of patients in remote location and is recorded commonly with noise. Considered attention is required for analysis of ECG signal to find the patho-physiology and status of patient. In this paper, LMS and RLS algorithm are implemented on adaptive FIR filter for reducing power line interference (50Hz) and (AWGN) noise on ECG signals .The ECG signals are randomly chosen from MIT_BIH data base and de-noising using algorithms. The peaks and heart rate of the ECG signal are estimated. The measurements are taken in terms of Signal Power, Noise Power and   Mean Square Error.
Volume: 9
Issue: 2
Page: 1028-1035
Publish at: 2019-04-01

Comparing bags of features, conventional convolutional neural network and AlexNet for fruit recognition

10.11591/ijeecs.v14.i1.pp333-339
Nik Noor Akmal Abdul Hamid , Rabiatul Adawiya Razali , Zaidah Ibrahim
This paper presents a comparative study between Bag of Features (BoF), Conventional Convolutional Neural Network (CNN) and Alexnet for fruit recognition.  Automatic fruit recognition can minimize human intervention in their fruit harvesting operations, operation time and harvesting cost.  On the other hand, this task is very challenging because of the similarities in shapes, colours and textures among various types of fruits. Thus, a robust technique that can produce good result is necessary. Due to the outstanding performance of deep learning like CNN and its pre-trained models like AlexNet in image recognition, this paper investigates the accuracy of conventional CNN, and Alexnet in recognizing thirty different types of fruits from a publicly available dataset.  Besides that, the recognition performance of BoF is also examined since it is one of the machine learning techniques that achieves good result in object recognition.   The experimental results indicate that all of these three techniques produce excellent recognition accuracy. Furthermore, conventional CNN achieves the fastest recognition result compared to BoF, and Alexnet.
Volume: 14
Issue: 1
Page: 333-339
Publish at: 2019-04-01

Spatial domain image enhancement techniques for acute myeloid leukemia (M1,M4,M5,M7)

10.11591/ijeecs.v14.i1.pp250-257
A.S. A.Salam , M.N. M.Isa , M. I. Ahmad
In this paper, several techniques of image enhancement spatial domain is elucidated and analyzed for the purpose of enhancing Acute Myeloid Leukemia (AML) subtype of M1, M4, M5 and M7. The techniques involved contrast stretching of greyscale images, image subtraction and image sharpening. The three methods compared with one another to achieve the highest PSNR value for the suitability technique of AML subtypes (M1, M4, M5 and M7). Firstly, subtypes images converted into grayscale. Then, each four images tested with contrast stretching techniques followed by image subtraction and image sharpening. The performances were evaluated based on Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). Due to its higher value obtained, image sharpening is a good enhancement techniques for Acute Myeloid Leukemia with 68.2083 dB and the lowest MSE achieved of 0.0103.
Volume: 14
Issue: 1
Page: 250-257
Publish at: 2019-04-01

Travel route scheduling based on user’s preferences using simulated annealing

10.11591/ijece.v9i2.pp1275-1287
Z. K. A. Baizal , Kemas M. Lhaksmana , Aniq A. Rahmawati , Mizanul Kirom , Zidni Mubarok
Nowadays, traveling has become a routine activity for many people, so that many researchers have developed studies in the tourism domain, especially for the determination of tourist routes. Based on prior work, the problem of determining travel route is analogous to finding the solution for travelling salesman problem (TSP). However, the majority of works only dealt with generating the travel route within one day and also did not take into account several user’s preference criteria. This paper proposes a model for generating a travel route schedule within a few days, and considers some user needs criteria, so that the determination of a travel route can be considered as a multi-criteria issue. The travel route is generated based on several constraints, such as travel time limits per day, opening/closing hours and the average length of visit for each tourist destination. We use simulated annealing method to generate the optimum travel route. Based on evaluation result, the optimality of the travel route generated by the system is not significantly different with ant colony result. However, our model is far more superior in running time compared to Ant Colony method.
Volume: 9
Issue: 2
Page: 1275-1287
Publish at: 2019-04-01

Real time control and monitoring of grid power systems using cloud computing

10.11591/ijece.v9i2.pp941-949
Nachiket Kulkarni , S. V. N. L. Lalitha , Sanjay A. Deokar
The use of grid power systems based on the combinations of various electrical networks, information technology, and communication layers called as Smart Grid systems. The technique of smart grid suppressed the problems faced by conventional grid systems such as inefficient energy management, improper control actions, grid faults, human errors, etc. The recent research on smart grid provides the approach for the real-time control and monitoring of grid power systems based on bidirectional communications. However, the smart grid is yet to improve regarding efficiency, energy management, reliability, and cost-effectiveness by considering its real-time implementation. In this paper, we present the real-time design of efficient monitoring and control of grid power system using the remote cloud server. We utilized the remote cloud server to fetch, monitor and control the real-time power system data to improve the universal control and response time. The proper hardware panel designed and fabricated to establish the connection with the grid as well as remote cloud users. The authenticated cloud users are provisioned to access and control the grid power system from anywhere securely. For the user authentication, we proposed the novel approach to secure the complete smart grid system. Finally, we demonstrated the effectiveness of real-time monitoring and control of the grid power method with the use of structure of practical framework.
Volume: 9
Issue: 2
Page: 941-949
Publish at: 2019-04-01

Enabling social WEB for IoT inducing ontologies from social tagging

10.11591/ijict.v8i1.pp19-24
Mohammed Alruqimi , Noura Aknin
Semantic domain ontologies are increasingly seen as the key for enabling interoperability across heterogeneous systems and sensor-based applications. The ontologies deployed in these systems and applications are developed by restricted groups of domain experts and not by semantic web experts. Lately, folksonomies are increasingly exploited in developing ontologies. The “collective intelligence”, which emerge from collaborative tagging can be seen as an alternative for the current effort at semantic web ontologies. However, the uncontrolled nature of social tagging systems leads to many kinds of noisy annotations, such as misspellings, imprecision and ambiguity. Thus, the construction of formal ontologies from social tagging data remains a real challenge. Most of researches have focused on how to discover relatedness between tags rather than producing ontologies, much less domain ontologies. This paper proposed an algorithm that utilises tags in social tagging systems to automatically generate up-to-date specific-domain ontologies. The evaluation of the algorithm, using a dataset extracted from BibSonomy, demonstrated that the algorithm could effectively learn a domain terminology, and identify more meaningful semantic information for the domain terminology. Furthermore, the proposed algorithm introduced a simple and effective method for disambiguating tags.Semantic domain ontologies are increasingly seen as the key for enabling interoperability across heterogeneous systems and sensor-based applications. The ontologies deployed in these systems and applications are developed by restricted groups of domain experts and not by semantic web experts. Lately, folksonomies are increasingly exploited in developing ontologies. The “collective intelligence”, which emerge from collaborative tagging can be seen as an alternative for the current effort at semantic web ontologies. However, the uncontrolled nature of social tagging systems leads to many kinds of noisy annotations, such as misspellings, imprecision and ambiguity. Thus, the construction of formal ontologies from social tagging data remains a real challenge. Most of researches have focused on how to discover relatedness between tags rather than producing ontologies, much less domain ontologies. This paper proposed an algorithm that utilises tags in social tagging systems to automatically generate up-to-date specific-domain ontologies. The evaluation of the algorithm, using a dataset extracted from BibSonomy, demonstrated that the algorithm could effectively learn a domain terminology, and identify more meaningful semantic information for the domain terminology. Furthermore, the proposed algorithm introduced a simple and effective method for disambiguating tags.
Volume: 8
Issue: 1
Page: 19-24
Publish at: 2019-04-01

Neural soft computing based secured transmission of intraoral gingivitis image in e-health care

10.11591/ijeecs.v14.i1.pp178-184
Arindam Sarkar , Joydeep Dey , Minakshi Chatterjee , Anirban Bhowmik , Sunil Karforma
 In this paper, a key based soft computing transmission of intraoral gingivitis image has been proposed without the exchange of common key in between the nodes. Gingivitis has been a type of periodontal disease caused due to bacterial colonization inside the mouth, having the early signs of gum bleeding and inflammations in human beings. In E-health care strata, online transmission of such intraoral images with secured encryption technique is needed. Session key based neural soft computing transmission by the dentists has been proposed in this paper with an eye to preserve patients’ confidentiality factor. To resist the data distortion by the eavesdroppers while on the transmission path, secured transmission in a group of tree parity machines was carried out. Topologically same tree parity machines with equal seed values were used by all users of that specified group. A common session key synchronization method was applied in that group. Intraoral image has been encrypted to generate multiple secret shares. Multiple secrets were transmitted to individual nodes in that group. The original gingivitis image can only be reconstructed upon the merging of threshold number of shares. Regression statistics along with ANOVA analysis were carried out on the result set obtained from the proposed technique. The outcomes of such tests were satisfactory for acceptance.
Volume: 14
Issue: 1
Page: 178-184
Publish at: 2019-04-01

Implementation of sequential design based water level monitoring and controlling system

10.11591/ijece.v9i2.pp967-972
Hussain Attia , Beza Getu , Abdullah Asaad , Ahmed Abbas , Mahmoud Al Nuaimi , Abdulhadi Brazi
In currently decades, water usage either for domestic or commercial purposes is facing critical conditions which negatively affects the sustainability of our environment. From this point of view, reducing water consumptions will participate in the solution of water saving. Monitoring and controlling the tank water level are important functions which effect and work on reduction of water consumption.  Many studies in literature focus on proposing a high performance water level monitoring and controlling systems based on either computerized units or microcontroller units. However these systems are characterized by complexity and high cost. In this paper, a highly flexible implemented electronic system is introduced based on sequential design by using general purpose discrete components. The proposed system present simple design of water level sensing stage, in addition, this paper showing full design, simulation, and implementation steps of an automation system which is able to control switching the state of the water pump in accordance to the current level of water in the tank.
Volume: 9
Issue: 2
Page: 967-972
Publish at: 2019-04-01

Improved optimization of numerical association rule mining using hybrid particle swarm optimization and cauchy distribution

10.11591/ijece.v9i2.pp1359-1373
Imam Tahyudin , Hidetaka Nambo
Particle Swarm Optimization (PSO) has been applied to solve optimization problems in various fields, such as Association Rule Mining (ARM) of numerical problems. However, PSO often becomes trapped in local optima. Consequently, the results do not represent the overall optimum solutions. To address this limitation, this study aims to combine PSO with the Cauchy distribution (PARCD), which is expected to increase the global optimal value of the expanded search space. Furthermore, this study uses multiple objective functions, i.e., support, confidence, comprehensibility, interestingness and amplitude. In addition, the proposed method was evaluated using benchmark datasets, such as the Quake, Basket ball, Body fat, Pollution, and Bolt datasets. Evaluation results were compared to the results obtained by previous studies. The results indicate that the overall values of the objective functions obtained using the proposed PARCD approach are satisfactory.
Volume: 9
Issue: 2
Page: 1359-1373
Publish at: 2019-04-01

Operational performance of a PV generator feeding DC shunt and induction motors with MPPT

10.11591/ijece.v9i2.pp771-782
Mohammed I. Abuashour , Tha'er O. Sweidan , Mohammad S. Widyan , Mohammed M. Hattab , Mohammed A. Ma'itah
This paper presented the transient and operational behavior of a parallel Combination of DC Shunt Motor and IM fed by a photovoltaic generator at different solar irradiance levels. The maximum power point of current/voltage (I/V) characteristic of the PV generator was achieved for different solar intensities, by utilizing an open circuit voltage method. The nonlinear operational behavior of (I/V) characteristics of the PV generator at various solar intensities and the magnetization curve of the ferromagnetic material of the DC shunt motor were both modeled by high order polynomial mathematical expressions. The study investigated the response of the system at different solar irradiance levels and changing the torque loads for both motors and then following step change in solar intensity levels with fixed loading torques for both motors. All numerical simulations were executed using MATLAB software.
Volume: 9
Issue: 2
Page: 771-782
Publish at: 2019-04-01
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