Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Filter Icon

Filters article

Years

FAQ Arrow
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

31,456 Article Results

Target-based test path prioritization for UML activity diagram using weight assignment methods

10.11591/ijece.v11i1.pp575-588
Walaiporn Sornkliang , Thimaporn Phetkaew
The benefit of exploratory testing and ad hoc testing by tester’s experience is that crucial bugs are found quickly. Regression testing and test case prioritization are important processes of software testing when software functions have been changed. We propose a test path prioritization method to generate a sequence of test paths that would match the testers’ interests and focuses on the target area of interest or on the changed area. We generate test paths form the activity diagrams and survey the test path prioritization from testers. We define node and edge weight to the symbols of activity diagrams by applying Time management, Pareto, Buffett, Binary, and Bipolar method. Then we propose a test path score equation to prioritize test paths. We also propose evaluation methods i.e., the difference and the similarity of test path prioritization to testers’ interests. Our proposed method had the least average of the difference and the most average of the similarity compare with the tester’s prioritization of test paths. The Bipolar method was the most suitable for assigning weights to match test path rank by the tester. Our proposed method also has given the affected path by changing area higher priority than the other test path.
Volume: 11
Issue: 1
Page: 575-588
Publish at: 2021-02-01

A hybrid feature selection on AIRS method for identifying breast cancer diseases

10.11591/ijece.v11i1.pp728-735
Achmad Ridok , Nashi Widodo , Wayan Firdaus Mahmudy , Muhaimin Rifa’i
Breast cancer may cause a death due to the late diagnosis. A cheap and accurate tool for early detection of this disease is essential to prevent fatal incidence. In general, the cheap and less invasive method to diagnose the disease could be done by biopsy using fine needle aspirates from breast tissue. However, rapid and accurate identification of the cancer cell pattern from the cell biopsy is still challenging task. This diagnostic tool can be developed using machine learning as a classification problem. The performance of the classifier depends on the interrelationship between sample sizes, some features, and classifier complexity. Thus, the removal of some irrelevant features may increase classification accuracy. In this study, a new hybrid feature selection fast correlation based feature (FCBF) and information gain (IG) was used to select features on identifying breast cancer using AIRS algorithm. The results of 10 times the crossing (CF) of our validation on various AIRS seeds indicate that the proposed method can achieve the best performance with accuracy =0.9797 and AUC=0.9777 at k=6 and seed=50.
Volume: 11
Issue: 1
Page: 728-735
Publish at: 2021-02-01

Investigation on the PAPR performance of odd-bit QAM constellations for DFT spread OFDM systems

10.11591/ijeecs.v21.i2.pp1005-1013
Ahmed M. Sana , Amer T. Saeed , Yaseen Kh. Yaseen
Adaptive quadrature amplitude modulation (QAM) is a crucial scheme that enables the modern communication systems to overcome the adverse effects of channel fluctuations and maintain an acceptable spectral efficiency. In order to enhance adaptive modulation even further, adoption of odd-bit QAM constellations alongside even constellations had been suggested to improve the transmission efficiency of adaptive QAM modulation. Hence, odd-bit QAM had been extensively studied, analyzed, and tested by many researchers for various patterns, sizes, and communication systems in terms of bit error rate (BER) and peak to average power ratio (PAPR). However, the PAPR performance of odd-bit QAM constellation with single carrier transmission systems adopted in the uplink of the 4G long term evolution (LTE) standards caught almost no research interest. In this paper, the PAPR performance of both cross and rectangular odd-bit QAM constellations are investigated for DFT-S-OFDM systems. Complementary cumulative distribution functions (CCDFs) and probability density functions (PDFs) curves for PAPR are also obtained. Finally, an equation for PAPR PDF is empirically derived for odd-bit cross QAM based DFT-S-OFDM. The results show that cross odd-bit QAM outperforms the rectangular odd-bit QAM in terms of PAPR by 1.02 dB for 8-QAM and 1.3 dB for 32-QAM. This proves that cross odd-bit QAM is a better choice in terms of PAPR for DFT-S-OFDM systems. 
Volume: 21
Issue: 2
Page: 1005-1013
Publish at: 2021-02-01

An accurate inter-turn short circuit faults model dedicated to induction motors

10.11591/ijece.v11i1.pp9-16
Fatima Babaa , Ouafae Bennis
Safety, disponibility and continuity of industrial systems are major issue in maintenance. In the last decades, these points are the important axes in the field of research. In fact, in many industrial processes research has picked up a fervent place and a particular importance in the area of fault diagnosis of electrical machines, in fact, a fault prognosis has become almost indispensable. The need of a mathematical model of three-phase induction machine, suitable for the simulation of machines behaviour under fault conditions, has received considerable attention. The paper presents a new practical and more precise model for induction motors after introducing inter turn short circuits faults. The proposed model is based on coupled magnetic circuit theory, capable to take into account any electrical asymmetry conditions. To verify the exactitude and the effectiveness of the model, simulation results for induction machine under interturn short circuit fault are presented. In spite of its simplicity, the proposed model is able to provide useful indications for diagnostic purposes. Experimental study is presented at the end of the paper to show that the proposed model predicts the induction machine behavior with a good accuracy.
Volume: 11
Issue: 1
Page: 9-16
Publish at: 2021-02-01

Detection and tracking of moving object using modified background subtraction and Kalman filter

10.11591/ijece.v11i1.pp217-223
Jeevith S. H. , Lakshmikanth S.
Moving object detection and tracking (MODT) is the major challenging issue in computer vision, which plays a vital role in many applications like robotics, surveillance, navigation systems, militaries, environmental monitoring etc. There are several existing techniques, which has been used to detect and track the moving object in Surveillance system. Therefore it is necessary to develop new algorithm or modified algorithm which is robust to work in both day and night time. In this paper, modified BGS technique is proposed. The video is first converted to number of frames, then these frame are applied to modified background subtraction technique with adaptive threshold which gives detected object. Kalman filter technique is used for tracking the detected object. The experimental results shows this proposed method can efficiently and correctly detect and track the moving objects with less processing time which is compared with existing techniques.
Volume: 11
Issue: 1
Page: 217-223
Publish at: 2021-02-01

A comparison of activation functions in multilayer neural network for predicting the production and consumption of electricity power

10.11591/ijece.v11i1.pp163-170
Abdulwahed Salam , Abdelaaziz El Hibaoui , Abdulgabbar Saif
Predicting electricity power is an important task, which helps power utilities in improving their systems’ performance in terms of effectiveness, productivity, management and control. Several researches had introduced this task using three main models: engineering, statistical and artificial intelligence. Based on the experiments, which used artificial intelligence models, multilayer neural networks model has proven its success in predicting many evaluation datasets. However, the performance of this model depends mainly on the type of activation function. Therefore, this paper introduces an experimental study for investigating the performance of the multilayer neural networks model with respect to different activation functions and different depths of hidden layers. The experiments in this paper cover the comparison among eleven activation functions using four benchmark electricity datasets. The activation functions under examination are sigmoid, hyperbolic tangent, SoftSign, SoftPlus, ReLU, Leak ReLU, Gaussian, ELU, SELU, Swish and Adjust-Swish. Experimental results show that ReLU and Leak ReLU activation functions outperform their counterparts in all datasets.
Volume: 11
Issue: 1
Page: 163-170
Publish at: 2021-02-01

Design an expert system for students graduation projects in Iraq universities: Basrah University

10.11591/ijece.v11i1.pp602-610
Maysaa Abd Ulkareem Naser , Sajad Mohammed Hasen
A graduation project is a form or work that the study authority requests from the student to measure what he made during the study. Designed an expert system for students’ graduation projects at the University of Basrah for students who are obligated to submit a project that qualifies them to graduate from the university. The system works according to a set of requirements, the most important is first: The student's possession of a high rate that qualifies him for the project. Second: he must possess half of the skills required for the project provided that it includes at least one programming language example (c ++, java, PHP, c #, etc ...). The system has many features that help the Supervisors and Students Committee to manage students' projects efficiently. System is built as a web-based system, with access limited only to the university's local network.
Volume: 11
Issue: 1
Page: 602-610
Publish at: 2021-02-01

Relationship of drain induced barrier lowering and top/bottom gate oxide thickness in asymmetric junctionless double gate MOSFET

10.11591/ijece.v11i1.pp232-239
Hakkee Jung
The relationship of drain induced barrier lowering (DIBL) phenomenon and channel length, silicon thickness, and thicknesses of top and bottom gate oxide films is derived for asymmetric junctionless double gate (JLDG) MOSFETs. The characteristics between the drain current and the gate voltage is derived by using the potential distribution model to propose in this paper. In this case, the threshold voltage is defined as the corresponding gate voltage when the drain current is (W/L) × 10-7 A, and the DIBL representing the change in the threshold voltage with respect to the drain voltage is obtained. As a result, we observe the DIBL is proportional to the negative third power of the channel length and the second power of the silicon thickness and linearly proportional to the geometric mean of the top and bottom gate oxide thicknesses, and derive a relation such as DIBL =25.15ηL_g^(-3) t_si^2 √(t_ox1∙t_ox2 ), where η is a static feedback coefficients between 0 and 1. The η is found to be between 0.5 and 1.0 in this model. The DIBL model of this paper has been observed to be in good agreement with the result of other paper, so it can be used in circuit simulation such as SPICE.
Volume: 11
Issue: 1
Page: 232-239
Publish at: 2021-02-01

Design of a model reference adaptive PID control algorithm for a tank system

10.11591/ijece.v11i1.pp300-318
Yohan Darcy Mfoumboulou
This paper describes the design of an adaptive controller based on model reference adaptive PID control (MRAPIDC) to stabilize a two-tank process when large variations of parameters and external disturbances affect the closed-loop system. To achieve that, an innovative structure of the adaptive PID controller is defined, an additional PI is designed to make sure that the reference model produces stable output signals and three adaptive gains are included to guarantee stability and robustness of the closed-loop system. Then, the performance of the model reference adaptive PID controller on the behaviour of the closed-loop system is compared to a PI controller designed on MATLAB when both closed-loop systems are under various conditions. The results demonstrate that the MRAPIDC performs significantly better than the conventional PI controller.
Volume: 11
Issue: 1
Page: 300-318
Publish at: 2021-02-01

Social-sine cosine algorithm-based cross layer resource allocation in wireless network

10.11591/ijece.v11i1.pp458-470
Praveena T. , Nagaraja G. S.
Cross layer resource allocation in the wireless networks is approached traditionally either by communications networks or information theory. The major issue in networking is the allocation of limited resources from the users of network. In traditional layered network, the resource are allocated at medium access control (MAC) and the network layers uses the communication links in bit pipes for delivering the data at fixed rate with the occasional random errors. Hence, this paper presents the cross-layer resource allocation in wireless network based on the proposed social-sine cosine algorithm (SSCA). The proposed SSCA is designed by integrating social ski driver (SSD) and sine cosine algorithm (SCA). Also, for further refining the resource allocation scheme, the proposed SSCA uses the fitness based on energy and fairness in which max-min, hard-fairness, proportional fairness, mixed-bias and the maximum throughput is considered. Based on energy and fairness, the cross-layer optimization entity makes the decision on resource allocation to mitigate the sum rate of network. The performance of resource allocation based on proposed model is evaluated based on energy, throughput, and the fairness. The developed model achieves the maximal energy of 258213, maximal throughput of 3.703, and the maximal fairness of 0.868, respectively.
Volume: 11
Issue: 1
Page: 458-470
Publish at: 2021-02-01

System uncertainties estimation based adaptive robust backstepping control for DC DC buck converter

10.11591/ijece.v11i1.pp347-355
Ali Hussien Mary , Abbas Hussien Miry , Mohammed Hussein Miry
This paper proposed a novel adaptive robust backstepping control scheme for DC-DC buck converter subjected to external disturbance and system uncertainty. Uncertainty in the load resistance and the input voltage represent the big challenge in buck converter control. In this work, an adaptive estimator for matched and mismatched uncertainties based backstepping control is applied for DC-DC buck converter. The updating laws are determined based on the lyapunov theorem. Thus, the difference between the estimated parameters and actual parameters converges to zero. The proposed control method is compared with the conventional sliding mode control and integral sliding mode control. Simulation results demonstrate the effectiveness and robustness of the proposed controller.
Volume: 11
Issue: 1
Page: 347-355
Publish at: 2021-02-01

Bulk power system availability assessment with multiple wind power plants

10.11591/ijece.v11i1.pp27-36
Angie C. Cepeda , Mario A. Rios
The use of renewable non-conventional energy sources, as wind electric power energy and photovoltaic solar energy, has introduced uncertainties in the performance of bulk power systems. The power system availability has been employed as a useful tool for planning power systems; however, traditional methodologies model generation units as a component with two states: in service or out of service. Nevertheless, this model is not useful to model wind power plants for availability assessment of the power system. This paper used a statistical representation to model the uncertainty of power injection of wind power plants based on the central moments: mean value, variance, skewness and kurtosis. In addition, this paper proposed an availability assessment methodology based on application of this statistical model, and based on the 2m+1 point estimate method the availability assessment is performed. The methodology was tested on the IEEE-RTS assuming the connection of two wind power plants and different correlation among the behavior of these plants.
Volume: 11
Issue: 1
Page: 27-36
Publish at: 2021-02-01

GPON and V-band mmWave in green backhaul solution for 5G ultra-dense network

10.11591/ijece.v11i1.pp390-401
Ayodeji Akeem Ajani , Vitalice Kalecha Oduol , Zachaeus Kayode Adeyemo
Ultra-dense network (UDN) is characterized by massive deployment of small cells which resulted into complex backhauling of the cells. This implies that for 5G UDN to be energy efficient, appropriate backhauling solutions must be provided. In this paper, we have evaluated the performance of giga passive optical network (GPON) and V-band millimetre wave (mmWave) in serving as green backhaul solution for 5G UDN. The approach was to first reproduce existing backhaul solutions in Very Dense Network (VDN) scenario which served as benchmark for the performance evaluation for the UDN scenario. The best two solutions, GPON and V-band solutions from the VDN were then deployed in 5G UDN scenario. The research was done by simulation in MATLAB. The performance metrics used were power consumption and energy efficiency against the normalized hourly traffic profile. The result revealed that GPON and V-band mmWave outperformed other solutions in VDN scenario. However, this performance significantly dropped in the UDN scenariodue to higher data traffic requirement of UDN compared to VDN. Thus, it can be concluded that GPON and V-band mmWave are not best suited to serve as green backhaul solution for 5G UDN necessitating further investigation of other available backhaul technologies.
Volume: 11
Issue: 1
Page: 390-401
Publish at: 2021-02-01

Fully symbolic-based technique for solving complex state-space control systems

10.11591/ijece.v11i1.pp272-283
Amera M. Abd-Alrahem , Hala M. Elhadidy , Kamel A. Elserafi , Hassen T. Dorrah
Despite the superiority of symbolic approaches over the purely numerical approaches in many aspects, it does not receive the proper attention due to its significant complexity, high resources requirement and long drawn time which even grows significantly with the increase of model dimensions. However, its merits deserve every attempt to overcome the difficulties being faced. In this paper, a fully generic symbolic-based technique is proposed to deal with complex state space control problems. In this technique, depending on the model dimension if exceeds a predefined limit, the state space is solved using the partitioned matrices theory and block wise inversion formula. Experimental results demonstrate that the proposed technique overcomes all the previously mentioned barriers and gives the same results when compared to numerical methods (Simulink). Moreover, it can be used to gain useful information about the system itself, provides an indication of which parameters are more important and reveals the sensitivity of system model to single parameter variations.
Volume: 11
Issue: 1
Page: 272-283
Publish at: 2021-02-01

Design of spark ignition engine speed control using bat algorithm

10.11591/ijece.v11i1.pp794-801
Herlambang Setiadi , Karl O. Jones , Teguh Aryo Nugroho , Muhammad Abdillah , Herri Trilaksana , Tahta Amrillah
The most common problem in spark ignition engine is how to increase the speed performance. Commonly researchers used traditional mathematical approaches for designing speed controller of spark ignition engine. However, this solution may not be sufficient. Hence, it is important to design the speed controller using smart methods. This paper proposes a method for designing speed controller of a spark ignition engine using the bat algorithm (BA). The simulation is carried out using the MATLAB/SIMULINK environment. Time domain simulation is carried out to investigate the efficacy of the proposed method. From the simulation results, it is found that by designing speed controller of spark ignition engine using PI based bat algorithm, the speed performance of spark ignition engine can be enhanced both in no load condition and load condition compared to conventional PI controler.
Volume: 11
Issue: 1
Page: 794-801
Publish at: 2021-02-01
Show 1125 of 2098

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration