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Performance evaluation of new blind OFDM signal recognition based on properties of the second-order statistics using universal software radio peripheral platform

10.11591/ijeecs.v23.i2.pp1227-1236
Mohamed Firdaoussi , Hicham Ghennioui , Mohamed El Kamili , Mohamed Lamrini
In the context of cognitive radio (CR) or various military and civilian applications, modulation recognition (MR) is one of the most popular technical processes in the field of communication system recognition, by which the modulation type of the unknown received signal can be identified automatically by estimating one or more parameters of the modulated signal. This paper presents the performance evaluation of the new proposed blind system recognition method using only a particular property of the second-order statistics of the orthogonal frequency division multiplexing (OFDM) modulated signal. The effectiveness of the proposed method is illustrated using the implementation on universal software radio peripheral (USRP) platform. A comparison with computer simulations using MATLAB software is also performed, emphasizing the good performances of the method while the results obtained are close. We show the efficiency and behavior of the proposed method in the context of wireless communication systems based on OFDM modulation (3GPP/LTE, WiMAX, DVBT-2K, IEEE 802.22-1K,IEEE 802.22-2K, IEEE 802.22-4K). The proposed method can detect OF DM signals among other digital signals in a systematic and intelligent way even with low SNR values (when approaching to SNR=-2dB, the decision criteria tends towards 0).
Volume: 23
Issue: 2
Page: 1227-1236
Publish at: 2021-08-01

Analysis of inventory management of slow-moving spare parts by using ABC techniques and EOQ model-a case study

10.11591/ijeecs.v23.i2.pp1159-1169
Walid Emar , Zakaria Anas Al-Omari , Sami Alharbi
Computer spare parts (CSPs) inventory management (IM) is very important for many companies. Excess inventory leads to high storage costs. On the other hand, the lack of CSP has a strong impact on the quality of service. This study was conducted by Power-One Jordan Computer Hardware-Software company (POJCHSC), Amman, Jordan. The focus area was the IM department and the target sample was employees working in the management department. The results showed that factors influencing the management of slow moving CSPs include production costs, obsolescence and CSPs dependence availability and transportation costs. By forecasting during the study, the results showed that the demand for adapters and chargers would increase by 20%. This demand forecast was performed using the economical order quantity (EOQ) model. The percentage of profits made by this company is 48%, and this requires some intervention to prevent losses. The results of this study are useful to the company, as well as to other similar industries that deal with slow-moving items. These results will help to simplify IM of slow-moving items. When we focused on POJCHSC manufacturers, the disadvantages of using the traditional ABC classification model were identified. Therefore, there is a need to have an ABC classification that is improved and which takes into consideration the criticality of the slow-moving CSP.
Volume: 23
Issue: 2
Page: 1159-1169
Publish at: 2021-08-01

A fully integrated violence detection system using CNN and LSTM

10.11591/ijece.v11i4.pp3374-3380
Sarthak Sharma , B. Sudharsan , Saamaja Naraharisetti , Vimarsh Trehan , Kayalvizhi Jayavel
Recently, the number of violence-related cases in places such as remote roads, pathways, shopping malls, elevators, sports stadiums, and liquor shops, has increased drastically which are unfortunately discovered only after it’s too late. The aim is to create a complete system that can perform real-time video analysis which will help recognize the presence of any violent activities and notify the same to the concerned authority, such as the police department of the corresponding area. Using the deep learning networks CNN and LSTM along with a well-defined system architecture, we have achieved an efficient solution that can be used for real-time analysis of video footage so that the concerned authority can monitor the situation through a mobile application that can notify about an occurrence of a violent event immediately.
Volume: 11
Issue: 4
Page: 3374-3380
Publish at: 2021-08-01

Breast cancer diagnosis system using hybrid support vector machine-artificial neural network

10.11591/ijece.v11i4.pp3059-3069
Tze Sheng Lim , Kim Gaik Tay , Audrey Huong , Xiang Yang Lim
Breast cancer is the second most common cancer occurring in women. Early detection through mammogram screening can save more women’s lives. However, even senior radiologists may over-diagnose the clinical condition. Machine learning (ML) is the most used technique in the diagnosis of cancer to help reduce human errors. This study is aimed to develop a computer-aided detection (CAD) system using ML for classification purposes. In this work, 80 digital mammograms of normal breasts, 40 of benign and 40 of malignant cases were chosen from the mini MIAS dataset. These images were denoised using median filter after they were segmented to obtain a region of interest (ROI) and enhanced using histogram equalization. This work compared the performance of artificial neural network (ANN), support vector machine (SVM), reduced features of SVM and the hybrid SVM-ANN for classification process using the statistical and gray level co-occurrence matrix (GLCM) features extracted from the enhanced images. It is found that the hybrid SVM-ANN gives the best accuracy of 99.4% and 100% in differentiating normal from abnormal, and benign from malignant cases, respectively. This hybrid SVM-ANN model was deployed in developing the CAD system which showed relatively good accuracy of 98%.
Volume: 11
Issue: 4
Page: 3059-3069
Publish at: 2021-08-01

Mining the crime data using naïve Bayes model

10.11591/ijeecs.v23.i2.pp1084-1092
Lourdes M. Padirayon , Melvin S. Atayan , Jose Sherief Panelo , Jr, Carlito R. Fagela
A massive number of documents on crime has been handled by police departments worldwide and today's criminals are becoming technologically elegant. One obstacle faced by law enforcement is the complexity of processing voluminous crime data. Approximately 439 crimes have been registered in sanchez mira municipality in the past seven years. Police officers have no clear view as to the pattern crimes in the municipality, peak hours, months of the commission and the location where the crimes are concentrated. The naïve Bayes modelis a classification algorithm using the Rapid miner auto model which is used and analyze the crime data set. This approach helps to recognize crime trends and of which, most of the crimes committed were a violation of special penal laws. The month of May has the highest for index and non-index crimes and Tuesday as for the day of crimes. Hotspots were barangay centro 1 for non-index crimes and barangay centro 2 for index crimes. Most non-index crimes committed were violations of special law and for index crime rape recorded the highest crime and usually occurs at 2 o’clock in the afternoon. The crime outcome takes various decisions to maximize the efficacy of crime solutions.
Volume: 23
Issue: 2
Page: 1084-1092
Publish at: 2021-08-01

Single line to ground fault detection and location in medium voltage distribution system network based on neural network

10.11591/ijeecs.v23.i2.pp621-632
Ahmed K. Abbas , Sumaya Hamad , Nuha A. Hamad
The aim of this project was to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL). Compared with anther faults, single line-to-ground (SLG) is the most frequent. The neural network (NN) algorithm was advanced in order to discover and locate SLG faults. The network is simulated through simulated numerous defects at various locations, as well as changing earth resistance from (or 100 Ω) to TL to gather all of the data. In the electromagnetic transients’ program (EMTP) program software, the existing fault have been measured. In addition, the waves were evaluated by utilize MATLAP's fastfourier-transform to calculate the waves of top three of them, On the MV network are fifty hundred faults are simulated all data in the neural network at MATLAB were trained and examined to improve the NN algorithm according to this data. Comparing all the simulated location faults that have been applied with those all locations detected in the NN algorithm, the overall error between them has been found to be very low and not to exceed 0.7. The Simulink circuit was created from this algorithm and checked in order to predict each failure could occur in the future in the MV network.
Volume: 23
Issue: 2
Page: 621-632
Publish at: 2021-08-01

Implementation of SHE-PWM technique for single-phase inverter based on Arduino

10.11591/ijece.v11i4.pp2907-2915
Laith A. Mohammed , Taha A. Husain , Ahmed M. T. Ibraheem
This paper presents design and practical implementation of single-phase inverter based on selective harmonic elimination-pulse width modulation (SHE-PWM) technique. Microcontroller mega type Arduino used as a controller for producing the gate pulses. The optimized switching angles determination results in wide range of output voltage. Depending on number of switching angles, the lower order harmonics (LOHs) can be eliminated to improve the output voltage waveform. A comparison study using MATLAB/Simulink for sinusoidal-PWM and SHE-PWM techniques, which shows for the same LOH in the output voltage waveform, the SHE-PWM has less number of pulses per half cycle than sinusoidal-PWM strategy. The reduction in number of pulses results less switching losses. The simulation done using ten switching angles to drive R-L load. A prototype of SHE-PWM inverter with R-L load is used to validate the simulation results.
Volume: 11
Issue: 4
Page: 2907-2915
Publish at: 2021-08-01

Optimal path discovery for two moving sinks with a common junction in a wireless sensor network

10.11591/ijeecs.v23.i2.pp879-889
Satish Tunga , Sadashiva V. Chakrasali , N. Shylashree , Latha B. N. , Mamatha A. S.
A new algorithm is described for determining the optimal round-trip paths for two moving sinks in a wireless sensor network. The algorithm uses binary integer programming to select two non-overlapping shortest paths except having a common junction node to cover all the sensor nodes. The two paths are balanced as nearly equal as possible. That is the sensor nodes along each path are equal or differ by just one depending on whether the total number of sensor nodes excluding the junction node is even or odd. In this method, both the path lengths are made equal or very nearly equal while the total length is minimized. This integrated approach is a novel and unique solution to solve the dual moving sink path problem in a wireless sensor network.
Volume: 23
Issue: 2
Page: 879-889
Publish at: 2021-08-01

Assessment of voltage stability based on power transfer stability index using computational intelligence models

10.11591/ijece.v11i4.pp2790-2797
Ahmed Majeed Ghadban , Ghassan Abdullah Salman , Husham Idan Hussein
In this paper, the importance of voltage stability is explained, which is a great problem in the EPS. The estimation of VS is made a priority so as to make the power system stable and prevent it from reaching voltage collapse. The power transfer stability index (PTSI) is used as a predictor utilized in a PSN to detect the instability of voltages on weakened buses. A PSI is used to obtain a voltage assessment of the PSNs. Two hybrid algorithms are developed. The (CA-NN) and the (PSO-NN). After developing algorithms, they are compared with the actual values of PTSI NR method. The algorithms installed on the 24 bus Iraqi PS. The actual values of PTSI are the targets needed. They are obtained from the NR algorithm when the input data is Vi, δi, Pd, Qd for the algorithm. The results indicate that a weak bus that approaches voltage collapse and all results were approximately the same. There is a slight difference with the actual results and demonstrated classical methods are slower and less accurate than the hybrid algorithms. It also demonstrates the validation and effectiveness of algorithms (CA-NN, and PSO-NN) for assessing voltage-prioritizing algorithms (CA-NN). The MATLAB utilized to obtain most of the results.
Volume: 11
Issue: 4
Page: 2790-2797
Publish at: 2021-08-01

One input voltage and three output voltage universal biquad filters with orthogonal tune of frequency and bandwidth

10.11591/ijece.v11i4.pp2962-2973
May Phu Pwint Wai , Amornchai Chaichana , Winai Jaikla , Surapong Siripongdee , Peerawut Suwanjan
This research paper contributes the one input three output voltage mode universal biquad filters with linear and electronic control of the natural frequency (w0), using two commercially available ICs, LT1228s as active device with two grounded capacitors, five resistors. The presented universal biquad filters can simultaneously provide three voltage-mode filtering functions, low-pass (LP), high-pass (HP) and band-pass (BP) without changing the circuit architecture. Furthermore, the first presented biquad filter provides low impedance at HP, BP voltage output nodes and LP, BP output voltage nodes are low impedance for the second proposed filter which is easy cascade ability with other voltage mode circuits without the employment of buffer circuits. The quality factor (Q) of both proposed filters is orthogonally adjusted from the passband voltage gain and w0. The proposed filters are simulated and experimented with commercially accessible ICs, LT1228. The simulated and experimental results demonstrate the filtering performances.
Volume: 11
Issue: 4
Page: 2962-2973
Publish at: 2021-08-01

A smart management system of electric vehicles charging plans on the highway charging stations

10.11591/ijeecs.v23.i2.pp752-759
Ibrahim El-Fedany , Driss Kiouach , Rachid Alaoui
Electric vehicles (EVs) are seen as one of the principal pillars of smart transportation to relieve the airborne pollution induced by fossil CO2 emissions. However, the battery limit, especially where the journey is with a long-distance road remains the most formidable obstacle to the large-scale use of EVs. To overcome the issue of prolonged waiting charging time due to the large number of EVs may have a charging plan at the same charging station (CS) along the highway, we propose a communication system to manage the EVs charging demands. The architecture system contains a smart scheduling algorithm to minimize trip time including waiting time, previous reservations and energyare needed to reach the destination. Moreover, an automatic mechanism for updating reservation is integrated to adjust the EVs charging plans. The results of the evaluation under the Moroccan highway scenario connecting Rabat and Agadir show the effectiveness of our proposal system. 
Volume: 23
Issue: 2
Page: 752-759
Publish at: 2021-08-01

An electric circuit model for a lithium-ion battery cell based on automotive drive cycles measurements

10.11591/ijece.v11i4.pp2798-2810
Jaouad Khalfi , Najib Boumaaz , Abdallah Soulmani , El Mehdi Laadissi
The on-board energy storage system plays a key role in electric vehicles since it directly affects their performance and autonomy. The lithium-ion battery offers satisfactory characteristics that make electric vehicles competitive with conventional ones. This article focuses on modeling and estimating the parameters of the lithium-ion battery cell when used in different electric vehicle drive cycles and styles. The model consists of an equivalent electrical circuit based on a second-order Thevenin model. To identify the parameters of the model, two algorithms were tested: Trust-Region-Reflective and Levenberg-Marquardt. To account for the dynamic behavior of the battery cell in an electric vehicle, this identification is based on measurement data that represents the actual use of the battery in different conditions and driving styles. Finally, the model is validated by comparing simulation results to measurements using the mean square error (MSE) as model performance criteria for the driving cycles (UDDS, LA-92, US06, neural network (NN), and HWFET). The results demonstrate interesting performance mostly for the driving cycles (UDDS and LA-92). This confirms that the model developed is the best solution to be integrated in a battery management system of an electric vehicle.
Volume: 11
Issue: 4
Page: 2798-2810
Publish at: 2021-08-01

Determination of the price for a hydro resource with consideration of operating conditions of hydropower plants using complex criteria of profit maxmization

10.11591/ijece.v11i4.pp2733-2742
T. V. Myatezh , Y. A. Sekretarev
In this paper, a universal method has been developed to determine the price of a hydro resource (one cubic meter) for the operational regulation of a hydropower plant (HPP), which is a combination of an optimization method and a method for assessing the marginal utility. The proposed approach is based on the correct representation of differential incremental rate characteristics of water at an HPP and fuel at a thermal power plant (TPP). To know the price of a hydro resource used for electricity generation at a hydropower plant. This gives the possibility to increase the efficiency of management both at a hydropower plant, and in a water utilization system as a whole. Using the examples of Novosibirsk HPP, it is expected to develop an estimation of economic effect from the implementation of the developed criteria, the proposed method of the calculation of a hydro resource price at HPP, and the method of separating fuel costs at CHPP. As a result of the implementation the developed method for the HPP, a price of electricity sold in the flexible energy market will be compared to the price of the electricity produced and sold at CHPP, being equal to approximately 330 rubles/MW h.
Volume: 11
Issue: 4
Page: 2733-2742
Publish at: 2021-08-01

Text classification model for methamphetamine-related tweets in Southeast Asia using dual data preprocessing techniques

10.11591/ijece.v11i4.pp3617-3628
Narongsak Chayangkoon , Anongnart Srivihok
Methamphetamine addiction is a prominent problem in Southeast Asia. Drug addicts often discuss illegal activities on popular social networking services. These individuals spread messages on social media as a means of both buying and selling drugs online. This paper proposes a model, the “text classification model of methamphetamine tweets in Southeast Asia” (TMTA), to identify whether a tweet from Southeast Asia is related to methamphetamine abuse. The research addresses the weakness of bag of words (BoW) by introducing BoW and Word2Vec feature selection (BWF) techniques. A domain-based feature selection method was performed using the BoW dataset and Word2Vec. The BWF dataset provided a smaller number of features than the BoW and TF–IDF dataset. We experimented with three candidate classifiers: Support vector machine (SVM), decision tree (J48) and naive bayes (NB). We found that the J48 classifier with the BWF dataset provided the best performance for the TMTA in terms of accuracy (0.815), F-measure (0.818), Kappa (0.528), Matthews correlation coefficient (0.529) and high area under the ROC Curve (0.763). Moreover, TMTA provided the lowest runtime (3.480 seconds) using the J48 with the BWF dataset.
Volume: 11
Issue: 4
Page: 3617-3628
Publish at: 2021-08-01

Performance evaluation of hierarchical clustering protocols with fuzzy C-means

10.11591/ijece.v11i4.pp3212-3221
Hamid Barkouk , El Mokhtar En-Naimi , Aziz Mahboub
The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.
Volume: 11
Issue: 4
Page: 3212-3221
Publish at: 2021-08-01
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