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31,456 Article Results

Miniaturized UWB elliptical patch antenna for skin cancer diagnosis imaging

10.11591/ijece.v10i2.pp1422-1429
Sameer Alani , Zahriladha Zakaria , A. Ahmad
The biomedical imaging shows promising results in many applications such as protein characterization and cancer detection using non-ionizing radiation. Skin cancer is one of the most common types of cancer because it is exposed by sun rays during the day. Many techniques have been offered to detect the tumor in the early stage such as ultrasonic and MW imaging. However, most of these studies showed a large printing area with lower BW so as the low resolution. To overcome these drawbacks, a new low profile UWB elliptical patch antenna with high performance is designed on PTFE as a substrate. Then a layer of Indium Tin Oxide (ITO) applies to improve the antenna radiation characteristics. The proposed antenna has a broad BW from 3.9 GHz to 30 GHz along with a resonance at 2.4 GHz. Furthermore, the antenna presents a maximum gain of 7.3 dB, maximum directivity of 7.78 dBi, the maximum radiation efficiency of 92 %, and consistent, stable radiation pattern throughout the frequency band. Besides, the time-domain characteristics show that the antenna can be a suitable candidate for microwave imaging of skin cancer.
Volume: 10
Issue: 2
Page: 1422-1429
Publish at: 2020-04-01

Myanmar named entity corpus and its use in syllable-based neural named entity recognition

10.11591/ijece.v10i2.pp1544-1551
Hsu Myat Mo , Khin Mar Soe
Myanmar language is a low-resource language and this is one of the main reasons why Myanmar Natural Language Processing lagged behind compared to other languages. Currently, there is no publicly available named entity corpus for Myanmar language. As part of this work, a very first manually annotated Named Entity tagged corpus for Myanmar language was developed and proposed to support the evaluation of named entity extraction. At present, our named entity corpus contains approximately 170,000 name entities and 60,000 sentences. This work also contributes the first evaluation of various deep neural network architectures on Myanmar Named Entity Recognition. Experimental results of the 10-fold cross validation revealed that syllable-based neural sequence models without additional feature engineering can give better results compared to baseline CRF model. This work also aims to discover the effectiveness of neural network approaches to textual processing for Myanmar language as well as to promote future research works on this understudied language.
Volume: 10
Issue: 2
Page: 1544-1551
Publish at: 2020-04-01

Interference aware resource allocation model for D2D under cellular network

10.11591/ijece.v10i2.pp1612-1621
Ruksar Fatima , Rohina Khanam , Shaik Humera Tauseef
Device-to-Device communication (D2D) has emerged as an efficient communication model in future generation cellular network for offloading cellular traffic and enhance overall network performance. D2D communication aid in attaining better spectrum utilization, lower delay, and less energy consumption, which can well adapt to meet demand of higher transmission rate, larger network capacity. Further, enhances spectral efficiency by reutilizing resource. However, it may result in severe cross-tier interference and co-tier interference. Therefore, efficient interference modelling design are required to address performance degradation caused by the interferences. The existing model has focused on addressing interference considering D2D association operating on same cell with the cellular association. As a result, it incurs interference to the cellular user located in the same cell. However, practically D2D association in overlapping area will reutilize spectrum of multiple neighboring cells. As a result, it incurs interference in multiple cells. For overcoming research challenges, this work presented Interference Aware Resource Allocation (IARA) model for D2D under cellular network as a game theory model. This work consider a resource allocation game where base station as a contender for catering D2D resource needs under different assumptions. Experiment are conducted to evaluate performance of IARA. The outcome shows IARA attained significant performance improvement over state-of-art models in terms of sum rate (utility), successful packet transmission, revenue, and delay.
Volume: 10
Issue: 2
Page: 1612-1621
Publish at: 2020-04-01

Switching pulse generation for DC-DC boost converter using Xilinx-ISE with FPGA processor

10.11591/ijece.v10i2.pp1722-1727
R. Palanisamy , C. S. Boopathi , K. Selvakumar , K. Vijayakumar
This paper explains steps to generate switching pulse using Xilinx-ISE with FPGA processor for DC-DC boost converter. The switching pulse generated using Very high speed integrated circuit Hardware Description Language (VHDL) with Xilinx-ISE. VHDL is a programming language, which is used to model and design any complex circuits in a dynamic environment. This paper gives the course of action for generation of switching pulses for dc-dc boost converter using Xilinx-ISE and matlab simulink. The switching pulse generated using Xilinx-ISE with FPGA-Spartan 6 processor compared with switching pulse generated using matlab.
Volume: 10
Issue: 2
Page: 1722-1727
Publish at: 2020-04-01

Foreground algorithms for detection and extraction of an object in multimedia

10.11591/ijece.v10i2.pp1849-1858
Rekha V. , Natarajan K. , Innila Rose J.
Background Subtraction of a foreground object in multimedia is one of the major preprocessing steps involved in many vision-based applications. The main logic for detecting moving objects from the video is difference of the current frame and a reference frame which is called “background image” and this method is known as frame differencing method. Background Subtraction is widely used for real-time motion gesture recognition to be used in gesture enabled items like vehicles or automated gadgets. It is also used in content-based video coding, traffic monitoring, object tracking, digital forensics and human-computer interaction. Now-a-days due to advent in technology it is noticed that most of the conferences, meetings and interviews are done on video calls. It’s quite obvious that a conference room like atmosphere is not always readily available at any point of time. To eradicate this issue, an efficient algorithm for foreground extraction in a multimedia on video calls is very much needed. This paper is not to just build Background Subtraction application for Mobile Platform but to optimize the existing OpenCV algorithm to work on limited resources on mobile platform without reducing the performance. In this paper, comparison of various foreground detection, extraction and feature detection algorithms are done on mobile platform using OpenCV. The set of experiments were conducted to appraise the efficiency of each algorithm over the other. The overall performances of these algorithms were compared on the basis of execution time, resolution and resources required.
Volume: 10
Issue: 2
Page: 1849-1858
Publish at: 2020-04-01

The best sextic approximation of hyperbola with order twelve

10.11591/ijece.v10i2.pp2192-2199
Abedallah Rababah , Esra’a Rababah
In this article, the best uniform approximation for the hyperbola of degree 6 that has approximation order 12 is found. The associated error function vanishes 12 times and equioscillates 13 times. For an arc of the hyperbola, the error is bounded by 2:4 x 10-4. We explain the details of the derivation and show how to apply the method. The method is simple and this encourages and motivates people working in CG and CAD to apply it in their works.
Volume: 10
Issue: 2
Page: 2192-2199
Publish at: 2020-04-01

Noncontact monitoring of heart rate responses to taste stimuli using a video camera

10.11591/ijeecs.v18.i1.pp293-300
Masnani Bt Mohamed , Makoto Yoshizawa , Norihiro Sugita , Shunsuke Yamaki , Kei Ichiji
Pleasant or unpleasant feeling stimulated by taste usually expressed to describe the acceptance or rejection of food and beverages intake by a human. Since it stimulates the emotional reactions, therefore it also induces other response such as heart rate variations. Traditional sensory tools used only subjective measurement such as self-report, to estimate the feeling of tasting. This method sometimes failed to show some differences between the pleasant and unpleasant type of feelings unconsciously. Previous unconscious measurement methods used the intrusive technique by placing some sensors in contact with the body, which may affect the results of sensory analysis. This study was conducted to avoid the effects of using contact sensors and validate the contact-less method of monitoring heart rate due to emotional changes by extracting plethysmographic signal from the green component of the video images. The videos were recorded while the subject responded to pleasant, unpleasant and neutral stimuli. The findings indicated that the heart rate was significantly related to taste stimuli that also reflected the subjective feelings. The unpleasant-taste influenced heart rate to increase more compared to pleasant-taste and neutral-taste. This proposed approach can be used to remotely detect the feeling/emotion that not overtly express through facial expression, speech or gestures.
Volume: 18
Issue: 1
Page: 293-300
Publish at: 2020-04-01

Development of DC voltage control from wind turbines using proportions and integrals for three-phase grid-connected inverters

10.11591/ijece.v10i2.pp1701-1711
Arckarakit Chaithanakulwat
This research article presents the method to control the DC voltage of the boost converter by using a proportional-integral (PI) controller. With AC voltage from a wind turbine generator, converting to DC voltage level by rectifier, this DC voltage controlled by PI controller is to control boost converter that sends DC links to the inverter which converting alternating current voltage to direct current voltage through three-phase load and to the grid-connected system. For switching the IGBTs in the inverter, the PWM signal, on the hysteresis current control, is controlled by the signal from the detected reference voltage based on the grid-connected system and the voltage from a wind turbine generator. The tests made the comparison of results from the simulation with the MATLAB/Simulink program and result from the hardware on the prototype. The power quality results, such as harmonic, power factor, are in acceptable ranges.
Volume: 10
Issue: 2
Page: 1701-1711
Publish at: 2020-04-01

Data mining, fuzzy AHP and TOPSIS for optimizing taxpayer supervision

10.11591/ijeecs.v18.i1.pp75-87
M. Jupri , Riyanarto Sarno
The achievement of accepting optimal tax need effective and efficient tax supervision can be achieved by classifying taxpayer compliance to tax regulations. Considering this issue, this paper proposes the classification of taxpayer compliance using data mining algorithms; i.e. C4.5, Support Vector Machine, K-Nearest Neighbor, Naive Bayes, and Multilayer Perceptron based on the compliance of taxpayer data. The taxpayer compliance can be classified into four classes, which are (1) formal and material compliant taxpayers, (2) formal compliant taxpayers, (3) material compliant taxpayers, and (4) formal and material non-compliant taxpayers. Furthermore, the results of data mining algorithms are compared by using Fuzzy AHP and TOPSIS to determine the best performance classification based on the criteria of Accuracy, F-Score, and Time required. Selection of the taxpayer's priority for more detailed supervision at each level of taxpayer compliance is ranked using Fuzzy AHP and TOPSIS based on criteria of dataset variables. The results show that C4.5 is the best performance classification and achieves preference value of 0.998; whereas the MLP algorithm results from the lowest preference value of 0.131. Alternative taxpayer A233 is the top priority taxpayer with a preference value of 0.433; whereas alternative taxpayer A051 is the lowest priority taxpayer with a preference value of 0.036.
Volume: 18
Issue: 1
Page: 75-87
Publish at: 2020-04-01

Dynamics performance of the wind-power supply chain with transmission capacity constraints

10.11591/ijece.v10i2.pp1142-1148
Milton M. Herrera , Mauricio Uriona , Isaac Dyner
Previous studies have shown that poor performance of energy supply chains arises from incorrectly interpret feedback information and time delays between decisions and actions in energy policy. This paper assesses alternatives to improve performance of wind-power supply chain with transmission constraints that contribute to enhance response capacity of the wind industry to changes of energy policy. In order to test these alternatives, this paper used a simulation model with system dynamics (SD), taking as case study Brazil. The simulation model represents the main time lags and fluctuations that exist in the wind-power supply chain. Four simulation scenarios were proposed to evaluate changes in auction-based policy in wind industry of Brazil. The results are related to operational capacity, inventory levels and response capacity. This paper provides an analysis of different scenarios that contribute with synchronization of auctions policy, including transmission capacity constraints.
Volume: 10
Issue: 2
Page: 1142-1148
Publish at: 2020-04-01

Inverse kinematic analysis of 4 DOF pick and place arm robot manipulator using fuzzy logic controller

10.11591/ijece.v10i2.pp1376-1386
Tresna Dewi , Siti Nurmaini , Pola Risma , Yurni Oktarina , Muhammad Roriz
The arm robot manipulator is suitable for substituting humans working in tomato plantation to ensure tomatoes are handled efficiently. The best design for this robot is four links with robust flexibility in x, y, and z-coordinates axis. Inverse kinematics and fuzzy logic controller (FLC) application are for precise and smooth motion. Inverse kinematics designs the most efficient position and motion of the arm robot by adjusting mechanical parameters. The FLC utilizes data input from the sensors to set the right position and motion of the end-effector. The predicted parameters are compared with experimental results to show the effectiveness of the proposed design and method. The position errors (in x, y, and z-axis) are 0.1%, 0.1%, and 0.04%. The rotation errors of each robot links (θ1, θ2, and θ3) are 0%, 0.7% and 0.3%. The FLC provides the suitable angle of the servo motor (θ4) responsible in gripper motion, and the experimental results correspond to FLC’s rules-based as the input to the gripper motion system. This setup is essential to avoid excessive force or miss-placed position that can damage tomatoes. The arm robot manipulator discussed in this study is a pick and place robot to move the harvested tomatoes to a packing system.
Volume: 10
Issue: 2
Page: 1376-1386
Publish at: 2020-04-01

Objects detection and tracking using fast principle component purist and kalman filter

10.11591/ijece.v10i2.pp1317-1326
Hadeel N. Abdullah , Nuha H. Abdulghafoor
The detection and tracking of moving objects attracted a lot of concern because of the vast computer vision applications. This paper proposes a new algorithm based on several methods for identifying, detecting, and tracking an object in order to develop an effective and efficient system in several applications. This algorithm has three main parts: the first part for background modeling and foreground extraction, the second part for smoothing, filtering and detecting moving objects within the video frame and the last part includes tracking and prediction of detected objects. In this proposed work, a new algorithm to detect moving objects from video data is designed by the Fast Principle Component Purist (FPCP). Then we used an optimal filter that performs well to reduce noise through the median filter. The Fast Region-convolution neural networks (Fast-RCNN) is used to add smoothness to the spatial identification of objects and their areas. Then the detected object is tracked by Kalman Filter. Experimental results show that our algorithm adapts to different situations and outperforms many existing algorithms.
Volume: 10
Issue: 2
Page: 1317-1326
Publish at: 2020-04-01

Online signature verification using hybrid wavelet transform

10.11591/ijece.v10i2.pp1823-1832
Manoj Chavan , Ravish R. Singh , Vinayak Bharadi
Online signature verification is a prominent behavioral biometric trait. It offers many dynamic features along with static two dimensional signature image. In this paper, the Hybrid Wavelet Transform (HWT) was generated using Kronecker product of two orthogonal transform such as DCT, DHT, Haar, Hadamard and Kekre. HWT has the ability to analyze the signal at global as well as local level like wavelet transform. HWT-1 and -2 was applied on the first 128 samples of the pressure parameter and first 16 samples of the output were used as feature vector for signature verification. This feature vector is given to Left to Right HMM classifier to identify the genuine and forged signature. For HWT-1, DCT HAAR offers best FAR and FRR. . For HWT-2, KEKRE 128 offers best FAR and FRR. HWT-1 offers better performance than HWT- 2 in terms of FAR and FRR. As the number of states increase, the performance of the system improves. For HWT - 1, KEKRE 128 offers best performance at 275 symbols whereas for HWT - 2, best performance is at 475 symbols by KEKRE 128.
Volume: 10
Issue: 2
Page: 1823-1832
Publish at: 2020-04-01

Novel modelling of clustering for enhanced classification performance on gene expression data

10.11591/ijece.v10i2.pp2060-2068
Sudha V. , Girijamma H. A.
Gene expression data is popularized for its capability to disclose various disease conditions. However, the conventional procedure to extract gene expression data itself incorporates various artifacts that offer challenges in diagnosis a complex disease indication and classification like cancer. Review of existing research approaches indicates that classification approaches are few to proven to be standard with respect to higher accuracy and applicable to gene expression data apart from unaddresed problems of computational complexity. Therefore, the proposed manuscript introduces a novel and simplified model capable using Graph Fourier Transform, Eigen Value and vector for offering better classification performance considering case study of microarray database, which is one typical example of gene expression data. The study outcome shows that proposed system offers comparatively better accuracy and reduced computational complexity with the existing clustering approaches.
Volume: 10
Issue: 2
Page: 2060-2068
Publish at: 2020-04-01

Short-term wind speed prediction based on MLP and NARX network models

10.11591/ijeecs.v18.i1.pp150-157
Yousra Amellas , Outman El bakkali , Abdelouahed Djebli , Adil Echchelh
The article aims to predict the wind speed by two artificial neural network’s models. The first model is a multilayer perceptron (MLP) treated by back-propagation algorithm and the second one is a recurrent neuron network type, processed by the NARX model. The two models having the same Network’s structure, which they are composed by 4 Inputs layers (Wind Speed, Pressure Temperature and Humidity), an intermediate layer defined by 20 neurons and an activation function, as well as a single output layer characterized by wind speed and a linear function. NARX shows the best results with a regression coefficient R = 0.984 et RMSE = 0.314.
Volume: 18
Issue: 1
Page: 150-157
Publish at: 2020-04-01
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