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31,456 Article Results

On the performance of energy harvesting AF partial relay selection with TAS and outdated channel state information over identical channels

10.11591/ijece.v10i5.pp5296-5305
Kehinde O. Odeyemi , Pius A. Owolawi
Energy scarcity has been known to be one of the most noticeable challenges in wireless communication system. In this paper, the performance of an energy harvesting based partial relay selection (PRS) cooperative system with transmit antenna selection (TAS) and outdated channel state information (CSI) is investigated. The system dual-hops links are assumed to follow Rayleigh distribution and the relay selection is based on outdated CSI of the first link. To realize the benefit of multiple antenna, the amplified-and-forward (AF) relay nodes then employs the TAS technique for signal transmission and signal reception is achieved at the destination through maximum ratio combining (MRC) scheme. Thus, the closed-form expression for the system equivalent end-to-end cumulative distribution function (CDF) is derived. Based on this, the analytical closed-form expressions for the outage probability, average bit error rate, and throughput for the delay-limited transmission mode are then obtained. The results illustrated that the energy harvesting time, relay distance, channel correlation coefficient, the number of relay transmit antennas and destination received antenna have significant effect on the system performance. Monte-carol simulation is employed to validate the accuracy of the derived expressions.
Volume: 10
Issue: 5
Page: 5296-5305
Publish at: 2020-10-01

Harvesting in electric vehicles: combining multiple power tracking and fuel-cells

10.11591/ijece.v10i5.pp5058-5073
Juan-Gerardo Parada-Salado , Luis-Fernando Gaona-Cárdenas , Martín-Antonio Rodríguez-Licea , Francisco-Javier Pérez-Pinal
Exploitation of green energy sources is essential to diminish the deterioration of our environment. The energy harvesting, represents an alternative to achieve greater range in electric and hybrid vehicles. An energy management strategy (EMS) must be optimized to obtain the best benefits in such vehicles, which is not a trivial task. If harvesting or energy recovery devices are added, the EMS becomes a dual-purpose algorithm: minimizing fuel consumption and maximizing energy harvest through maximum power point tracking (MPPT) controllers. Known studies consider separate EMS, one for traction and another for regenerative braking, without considering harvest devices such as solar panels, regenerative suspension, thermal generators, among others. Furthermore, the electronic power converters used, are not designed to handle such unequal power levels. In this article, an electronic platform to include multiple energy harvesting devices in a fuel-cell hybrid electric vehicle, was presented together with a multiple MPPT-EMS. The EMS is easily implementable, and considers quasiconstant cell energy extraction and filtering of current transients to the battery bank ensuring the longevity of the devices. A new mathematical model of the platform, a closed loop stability analysis, and numerical and Hardware-in-the-Loop (HIL) validations were presented. Some experimental validation results were also provided.
Volume: 10
Issue: 5
Page: 5058-5073
Publish at: 2020-10-01

The effect of gamma value on support vector machine performance with different kernels

10.11591/ijece.v10i5.pp5497-5506
Intisar Shadeed Al-Mejibli , Jwan K. Alwan , Dhafar Hamed Abd
Currently, the support vector machine (SVM) regarded as one of supervised machine learning algorithm that provides analysis of data for classification and regression. This technique is implemented in many fields such as bioinformatics, face recognition, text and hypertext categorization, generalized predictive control and many other different areas. The performance of SVM is affected by some parameters, which are used in the training phase, and the settings of parameters can have a profound impact on the resulting engine’s implementation. This paper investigated the SVM performance based on value of gamma parameter with used kernels. It studied the impact of gamma value on (SVM) efficiency classifier using different kernels on various datasets descriptions. SVM classifier has been implemented by using Python. The kernel functions that have been investigated are polynomials, radial based function (RBF) and sigmoid. UC irvine machine learning repository is the source of all the used datasets. Generally, the results show uneven effect on the classification accuracy of three kernels on used datasets. The changing of the gamma value taking on consideration the used dataset influences polynomial and sigmoid kernels. While the performance of RBF kernel function is more stable with different values of gamma as its accuracy is slightly changed.
Volume: 10
Issue: 5
Page: 5497-5506
Publish at: 2020-10-01

Algorithm of detection, classification and gripping of occluded objects by CNN techniques and Haar classifiers

10.11591/ijece.v10i5.pp4712-4720
Paula Useche , Robinson Jimenez-Moreno , Javier Martinez Baquero
The following paper presents the development of an algorithm, in charge of detecting, classifying and grabbing occluded objects, using artificial intelligence techniques, machine vision for the recognition of the environment, an anthropomorphic manipulator for the manipulation of the elements. 5 types of tools were used for their detection and classification, where the user selects one of them, so that the program searches for it in the work environment and delivers it in a specific area, overcoming difficulties such as occlusions of up to 70%. These tools were classified using two CNN (convolutional neural network) type networks, a fast R-CNN (fast region-based CNN) for the detection and classification of occlusions, and a DAG-CNN (directed acyclic graph-CNN) for the classification tools. Furthermore, a Haar classifier was trained in order to compare its ability to recognize occlusions with respect to the fast R-CNN. Fast R-CNN and DAG-CNN achieved 70.9% and 96.2% accuracy, respectively, Haar classifiers with about 50% accuracy, and an accuracy of grip and delivery of occluded objects of 90% in the application, was achieved.
Volume: 10
Issue: 5
Page: 4712-4720
Publish at: 2020-10-01

A novel CAD system to automatically detect cancerous lung nodules using wavelet transform and SVM

10.11591/ijece.v10i5.pp4745-4751
Ayman A. Abu Baker , Yazeed Ghadi
A novel cancerous nodules detection algorithm for computed tomography images (CT-images) is presented in this paper. CT-images are large size images with high resolution. In some cases, number of cancerous lung nodule lesions may missed by the radiologist due to fatigue. A CAD system that is proposed in this paper can help the radiologist in detecting cancerous nodules in CT- images. The proposed algorithm is divided to four stages. In the first stage, an enhancement algorithm is implement to highlight the suspicious regions. Then in the second stage, the region of interest will be detected. The adaptive SVM and wavelet transform techniques are used to reduce the detected false positive regions. This algorithm is evaluated using 60 cases (normal and cancerous cases), and it shows a high sensitivity in detecting the cancerous lung nodules with TP ration 94.5% and with FP ratio 7 cluster/image.
Volume: 10
Issue: 5
Page: 4745-4751
Publish at: 2020-10-01

Modified sub-gradient based combined objective technique and evolutionary programming approach for economic dispatch involving valve-point loading, enhanced prohibited zones and ramp rate constraints

10.11591/ijece.v10i5.pp5048-5057
Susanta Kumar Gachhayat , Saroja Kumar Dash
A security constrained non-convex power dispatch problem with prohibited operation zones and ramp rates is formulated and solved using an iterative solution method based on the feasible modified sub-gradient algorithm (FMSG). Since the cost function, all equality and inequality constraints in the nonlinear optimization model are written in terms of the bus voltage magnitudes, phase angles, off-nominal tap settings, and the Susceptance values of static VAR (SVAR) systems, they can be taken as independent variables. The actual power system loss is included in the current approach and the load flow equations are inserted into the model as the equality constraints. The proposed modified sub gradient based combined objective technique and evolutionary programming approach (MSGBCAEP) with as decision variable and cost function as fitness function is tested on the IEEE 30-bus 6 generator test case system. The absence of crossover operation and adoption of fast judicious modifications in initialization of parent population, offspring generation and normal distribution curve selection in EP enables the proposed MSGBCAEP approach to ascertain global optimal solution for cost of generation and emission level shown in Table 6 and displayed in Figure 2 and Figure 3 respectively.
Volume: 10
Issue: 5
Page: 5048-5057
Publish at: 2020-10-01

Low-cost and portable automatic sheet cutter

10.11591/ijece.v10i5.pp5139-5146
Mohd Syafiq Mispan , Ahmad Hafizzudin Mustafa , Hafez Sarkawi , Aiman Zakwan Jidin
Process automation is crucial to increase productivity, more efficient use of materials, better product quality, improved safety, etc. In small-medium enterprise (SME) businesses related to household retailing, one of the process automation needed is the measurement and cutting of the mat or sheet, made of rubber or polyvinyl chloride (PVC) materials. Most of the household retailers that selling the sheet, the process of measuring and cutting according to the customer’s requirements are manually performed using a measuring tape and scissors. These manual processes can cause inaccuracy in length, inefficient use of material, low productivity and reduce product quality. This paper presents a low cost and portable automatic sheet cutter using the Arduino development board, which is used to control the process of measuring and cutting the materials. The system uses a push-button where the user can set the required length and quantity of the sheet. Once the required information is set, the stepper motor rolls the sheet until the required length is satisfied. Subsequently, another stepper motor moves the cutter horizontally and cut the sheet. With the automatic sheet cutter, the material is cut with acceptable precision. The design of the automatic sheet cutter is low cost and portable which significantly suitable to be used by SME household retailers.
Volume: 10
Issue: 5
Page: 5139-5146
Publish at: 2020-10-01

Sentimental classification analysis of polarity multi-view textual data using data mining techniques

10.11591/ijece.v10i5.pp5526-5534
Ali Hameed Yassir , Ali A. Mohammed , Adel Abdul-Jabbar Alkhazraji , Mustafa Emad Hameed , Mohammed Saad Talib , Mohanad Faeq Ali
The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics.
Volume: 10
Issue: 5
Page: 5526-5534
Publish at: 2020-10-01

Energy-aware strategy for data forwarding in IoT ecosystem

10.11591/ijece.v10i5.pp4863-4871
K. Nagarathna
The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay.
Volume: 10
Issue: 5
Page: 4863-4871
Publish at: 2020-10-01

Face recognition using selected topographical features

10.11591/ijece.v10i5.pp4695-4700
Maitham Ali Naji , Ghalib Ahmed Salman , Muthna Jasim Fadhil
This paper represents a new features selection method to improve an existed feature type. Topographical (TGH) features provide large set of features by assigning each image pixel to the related feature depending on image gradient and Hessian matrix. Such type of features was handled by a proposed features selection method. A face recognition feature selector (FRFS) method is presented to inspect TGH features. FRFS depends in its main concept on linear discriminant analysis (LDA) technique, which is used in evaluating features efficiency. FRFS studies feature behavior over a dataset of images to determine the level of its performance. At the end, each feature is assigned to its related level of performance with different levels of performance over the whole image. Depending on a chosen threshold, the highest set of features is selected to be classified by SVM classifier
Volume: 10
Issue: 5
Page: 4695-4700
Publish at: 2020-10-01

Design and analysis of optimized CORDIC based GMSK system on FPGA platform

10.11591/ijece.v10i5.pp4679-4686
Renuka Kajur , K. V. Prasad
The Gaussian minimum shift keying (GMSK) is one of the best suited digital modulation schemes in the global system for mobile communication (GSM) because of its constant envelop and spectral efficiency characteristics. Most of the conventional GMSK approaches failed to balance the digital modulation with efficient usage of spectrum. In this article, the hardware architecture of the optimized CORDIC-based GMSK system is designed, which includes GMSK Modulation with the channel and GMSK Demodulation. The modulation consists of non-return zero (NRZ) encoder, an integrator followed by Gaussian filtering and frequency modulation (FM). The GMSK demodulation consists of FM demodulator, followed by differentiation and NRZ decoder. The FM Modulation and demodulation use the optimized CORDIC model for an In-phase (I) and quadrature (Q) phase generation. The optimized CORDIC is designed by using quadrant mapping and pipelined structure to improve the hardware and computational complexity in GMSK systems. The GMSK system is designed on the Xilinx platform and implemented on Artix-7 and Spartan-3EFPGA. The hardware constraints like area, power, and timing utilization are summarized. The comparison of the optimized CORDIC model with similar CORDIC approaches is tabulated with improvements.
Volume: 10
Issue: 5
Page: 4679-4686
Publish at: 2020-10-01

The electromagnetic interference caused by high voltage power lines along the electrical railway equipment

10.11591/ijece.v10i5.pp4581-4591
Moine El Hajji , Hassane Mahmoudi , Moussa Labbadi
The identification of risks linked to electromagnetic compatibility (EMC) in the electric railway is a major concern in identifying EMC problems and analyzing the unintentional various external disturbing sources as well as the probability of occurrence of interference, the level of interference along the railway system. The purpose of this analysis is to determine the electromagnetic interaction coupling generated by the high voltage (HV) lines located along the railway line by analyzing the voltage induced in the signaling transmission cables such as the European rail traffic management system/European train control system (ERTMS/ETCS) through the multi-conductor transmission line (MTL) theory which may have an impact on the transmitting information. Dubanton method and approximate calculation will be applied and simulated through COMSOL Multiphysics tool in order to analyze if the protection distance and coupling conditions are respected by the railway standards.
Volume: 10
Issue: 5
Page: 4581-4591
Publish at: 2020-10-01

Performance evaluation of decode and forward cooperative diversity systems over nakagami-m fading channels with non-identical interferers

10.11591/ijece.v10i5.pp5316-5328
Mamoun F. Al-Mistarihi , Rami Mohaisen , Khalid A. Darabkh
The deficiencies of regular cooperative relaying schemes were the main reason behind the development of Incremental Relaying (IR). Fixed relaying is one of the regular cooperative relaying schemes and it relies on using the relay node to help in transmitting the signal of the source towards the destination despite the channel’s condition. However, adaptive relaying methods allocate the channel resources efficiently; thus, such methods have drawn the attention of researchers in recent years. In this study, we analyze a two-hop Decode-and-Forward (DF) IR system’s performance via Nakagami-m fading channels with the existence of the several L distinguishable interferers placed close to the destination which diminishes the overall performance of the system due to the co-channel interference. Tight formulas for the Bit Error Rate (BER) and the Outage Probability (OP) are drawn. The assumptions are consolidated by numerical calculations.
Volume: 10
Issue: 5
Page: 5316-5328
Publish at: 2020-10-01

Real-time object control system using open source platform

10.11591/ijeecs.v20.i1.pp313-319
Chang-Gyu Cgseong , Jung-Yee Kim , Doo-Jin Park
Recently, the internet of things (IoT) has received great attention, and the demand for IOT applications in various fields is increasing. But drawbacks of IoT, such as having to use dedicated equipment and having to pay for a flat fee monthly, do not satisfy the consumers’ demands. These shortcomings of IoT is causing the appearance of users who try to design the environment of IoT that responds their demands and naturally, attempts to have monitoring system through open-source hardware like Arduino. Open source hardware has attracted a great deal of attention for the diffusion of the Internet of things as a key element of the Internet construction. The emergence of open source hardware, which has the advantage of low cost and easy and fast development, has made it possible to embody the idea of object Internet application services. In this paper, we design and implement a system that controls the objects in real time using open source hardware and MQTT protocol.
Volume: 20
Issue: 1
Page: 313-319
Publish at: 2020-10-01

Comparison between neural network and P&O method in optimizing MPPT control for photovoltaic cell

10.11591/ijece.v10i5.pp5083-5092
ِِِAhmed G. Abdullah , Mothanna Sh. Aziz , Bashar Abdullah Hamad
The demand for renewable energy has increased because it is considered a clean energy and does not result in any pollution or emission of toxic gases that negatively affect the environment and human health also requiring little maintenance, and emitting no noise, so it is necessary to develop this type of energy and increase its production capacity. In this research a design of maximum power point tracking (MPPT) control method using Neural Network (NN) for photovoltaic system is presented. First we design a standalone PV system linked to dc boost chopper with MPPT by perturbation and observation P&O technique, and then a design of MPPT by using ANN for the same system is presented. Comparative between two control methods are studied. The results explained in constant and adjustable weather settings such as irradiation and temperature. The results exposed that the proposed MPPT by ANN control can improve the PV array efficiency by reduce the oscillation around the MPP that accure in P&O method and so decreases the power losses. As well as decrease the the overshot that accure in transient response, and hence improving the performance of the solar cell.
Volume: 10
Issue: 5
Page: 5083-5092
Publish at: 2020-10-01
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