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31,456 Article Results

Development of a real-time framework for farm monitoring using drone technology

10.11591/ijra.v9i4.pp244-250
Adekunle T. Oyelami , Adedayo S. Akinade , Kingsley C. Obianefo
This work developed a cost-effective framework for agriculturists to regularly monitor their crops against intruding rodents and other security concerns using modern drone technology through configuration and deployment of an autonomous UAV which also functions as a remotely piloted vehicle. This was done by configuring a quadcopter capable of causing a disturbance when a rodent is observed through an inbuilt alarm system whose sound is amplified to be loud enough to cause the animals to leave the farm area. A framework for real-time image and live video transmission from the farm to a designated remote base station was developed. This was achieved through programming codes that configured the drone to operate an intelligent alarm and object tracking systems which enables a live feed from the UAV using Arduino IDE and Mission Planner for autonomous flight control. The requisite algorithms were developed using the framework of tracking, learning and detection (TLD) in the OpenCV software. The drone movement is equally controlled remotely over a Wi-Fi network using an ESP8266 Wi-Fi module for redirection and controlling of the drone movement to monitor specific locations.
Volume: 9
Issue: 4
Page: 244-250
Publish at: 2020-12-01

A new exact equivalent circuit of the medium voltage three-phase induction motor

10.11591/ijece.v10i6.pp6164-6171
Laura Collazo Solar , Angel A. Costa Montiel , Miriam Vilaragut Llanes , Vladimir Sousa Santos , Abel Curbelo Colina
This paper proposes a new equivalent circuit for medium voltage and great power induction motors considering the more complete information given by the manufacturer. A methodology for obtaining the parameters of the equivalent circuit is presented, having this circuit the advantage of allowing the electrical calculation of all the power losses and the realization of the power balance. It is an achievement of this work a new way of calculating and representing the additional losses using a resistance located in the rotor circuit. Then, three types of losses are considered as a part of a power balance: the conventional or joule effect variable losses, the constant losses, and the additional losses. The proposed method is straight and non-iterative. It was applied to a case study motor of 6000 V and 2500 kW located at the Maximo Gomez Power Plant in Cuba.
Volume: 10
Issue: 6
Page: 6164-6171
Publish at: 2020-12-01

An efficient method to classify GI tract images from WCE using visual words

10.11591/ijece.v10i6.pp5678-5686
R. Ponnusamy , S. Sathiamoorthy , R. Visalakshi
The digital images made with the Wireless Capsule Endoscopy (WCE) from the patient's gastrointestinal tract are used to forecast abnormalities. The big amount of information from WCE pictures could take 2 hours to review GI tract illnesses per patient to research the digestive system and evaluate them. It is highly time consuming and increases healthcare costs considerably. In order to overcome this problem, the CS-LBP (Center Symmetric Local Binary Pattern) and the ACC (Auto Color Correlogram) were proposed to use a novel method based on a visual bag of features (VBOF). In order to solve this issue, we suggested a Visual Bag of Features(VBOF) method by incorporating Scale Invariant Feature Transform (SIFT), Center-Symmetric Local Binary Pattern (CS-LBP) and Auto Color Correlogram (ACC). This combination of features is able to detect the interest point, texture and color information in an image. Features for each image are calculated to create a descriptor with a large dimension. The proposed feature descriptors are clustered by K- means referred to as visual words, and the Support Vector Machine (SVM) method is used to automatically classify multiple disease abnormalities from the GI tract. Finally, post-processing scheme is applied to deal with final classification results i.e. validated the performance of multi-abnormal disease frame detection.
Volume: 10
Issue: 6
Page: 5678-5686
Publish at: 2020-12-01

A multi-objective optimization based model for the deployment of reclosers and remote-controlled switches using NSGA2 and entropy weighted TOPSIS method

10.11591/ijeecs.v20.i3.pp1128-1139
Anass Lekbich , Abdelaziz Belfqih , Tayeb Ouaderhman , Chaimae Zedak , Jamal Boukherouaa , Faissal El Mariami
Since they are fast, remote controlled, automated and intelligent, reclosers and switches are an inevitable solution for improving the reliability of intelligent electrical distribution networks at optimal cost. However, their location and coordination have great effects on the protection and automation strategies of complex electrical distribution networks against multiple unpredictable faults. Which requires a flexible and multi-criteria optimization method. In this article, we propose a multi-objective method based on an analytical model by considering the fault rate, restoration times, outage cost and coordination between devices. The non-dominated genetic sorting algorithm II was proposed to obtain the optimal Pareto solutions, and a technique of performance control by similarity with the ideal solution was used to classify them. The objective criteria weights are based on the entropy method which allows solutions to be obtained and better classified with the minimum of subjectivity. The IEEE33 and IEEE13 bus test networks were used to verify the method. The results obtained are compared to a binary multi-objective particle swarm optimization method and the results show that the proposed method reduces the overall costs, reduces the undelivered energy of the system and improves the reliability of the service.
Volume: 20
Issue: 3
Page: 1128-1139
Publish at: 2020-12-01

Developing the scale on discipline expectations of students: A validity and reliability study

10.11591/ijere.v9i4.20585
Gülsen Özcan , Işıl Aktağ , Kaine Gülözer
The study aimed to develop a valid and reliable scale to measure the expectations of students from the discipline program implemented in their schools. The study was conducted with students studying in seven different high schools in fall semester of 2019-2020 school year. As a result of the Confirmatory Factor Analysis (CFA), a 5-point Likert scale with 3 dimensions and 22 items was established. It was revealed that the fit index values for the final form of the scale are χ2 = 360.92, df = 206, P = 0.00, RMSEA = 0.062, GFI = 0.86, AGFI = 0.82, CFI = 0.93, RMR = 0.063; NNFI = 0.92. Cronbach Alpha reliability test was used to test the reliability of the ultimate scale and test retest reliability value was used to measure the stability of the test. Reliability value for the whole test was determined as .823, for the factor of Effective Teaching Discipline Expectation as 717, for the factor of Behavioral Discipline Expectation as 596, and for the factor of Social Discipline Expectation as .636. Test retest reliability of the test was determined as .763. Upon the evaluation of the analyses made, it was concluded that scale on discipline expectations of students is a valid and reliable scale to measure the discipline expectations of the students studying in secondary education institutions in Turkey.
Volume: 9
Issue: 4
Page: 840-846
Publish at: 2020-12-01

Offline drone instrumentalized ambulance for emergency situations

10.11591/ijra.v9i4.pp251-255
Hitesh Mohapatra
In this paper, an offline drone instrumentalized ambulance (ODIA) mechanism has been discussed. The rapid increase in the urban population directly influences every sector of society. The sectors are maybe food, health care, education, transportation, etc. Normally, it has been observed that when any accidents happen on the urban road or any remote places then, the availability of immediate medical help is very rare. It is not because of the unaware or unavailability of medical facilities rather it happens because of overcrowding on the urban road and geographical odd-isolation of places. Hence, here an ODIA concept has been discussed which uses offline maps and offline first-aid medical videos through which immediate medical help can be made available at the patient end. This model helps to save the life of an accident victim by providing immediate medical attention. The key strength of ODIA is, it is independent of internet service that is why it is more suitable for harsh and hostile environments.
Volume: 9
Issue: 4
Page: 251-255
Publish at: 2020-12-01

A simulated risk assessment of human-robot interaction in the domestic environment

10.11591/ijra.v9i4.pp300-310
Tamanna E Kaonain , Mohd Azizi Abdul Rahman , Mohd Hatta Mohammed Ariff , Kuheli Mondal
In human-robot interaction, the use of collaborative robots or cobots in many industries is of major importance to researchers in human-robot interaction (HRI). The interaction between human robot carries several challenges, the greatest being the risk of human injury. In addition to reducing the proximity between robots and humans, increased difficulty of human-robot encounters raises the likelihood of accidents only. This paper proposes a virtual collaborative robot in the simulated non-industrial workspace. The safety during human-robot interaction using simulation software was investigated by measuring the risks for planning and control. A reactive robot controller was formulated to minimize the risk during human-robot interaction. A Gazebo software is used in this article, written in Python language, to replicate complex environments that a robot can face. This paper also investigated the robot’s speed. It can be reduced before a collision with a human about to happen, and it minimized the risk of the collision or reduced the damage of the risk. After the successful simulation, this can be applied to the real robot in a practical domestic environment.
Volume: 9
Issue: 4
Page: 300-310
Publish at: 2020-12-01

An analysis of software aging in cloud environment

10.11591/ijece.v10i6.pp5985-5991
Shruthi P. , Nagaraj G. Cholli
Cloud Computing is the environment in which several virtual machines (VM) run concurrently on physical machines. The cloud computing infrastructure hosts multiple cloud service segments that communicate with each other using the interfaces. This creates distributed computing environment. During operation, the software systems accumulate errors or garbage that leads to system failure and other hazardous consequences. This status is called software aging. Software aging happens because of memory fragmentation, resource consumption in large scale and accumulation of numerical error. Software aging degrads the performance that may result in system failure. This happens because of premature resource exhaustion. This issue cannot be determined during software testing phase because of the dynamic nature of operation. The errors that cause software aging are of special types. These errors do not disturb the software functionality but target the response time and its environment. This issue is to be resolved only during run time as it occurs because of the dynamic nature of the problem. To alleviate the impact of software aging, software rejuvenation technique is being used. Rejuvenation process reboots the system or re-initiates the softwares. This avoids faults or failure. Software rejuvenation removes accumulated error conditions, frees up deadlocks and defragments operating system resources like memory. Hence, it avoids future failures of system that may happen due to software aging. As service availability is crucial, software rejuvenation is to be carried out at defined schedules without disrupting the service. The presence of Software rejuvenation techniques can make software systems more trustworthy. Software designers are using this concept to improve the quality and reliability of the software. Software aging and rejuvenation has generated a lot of research interest in recent years. This work reviews some of the research works related to detection of software aging and identifies research gaps.
Volume: 10
Issue: 6
Page: 5985-5991
Publish at: 2020-12-01

The quadrotor dynamic modeling and study of meta-heuristic algorithms performance on optimization of PID controller index to control angles and tracking the route

10.11591/ijra.v9i4.pp256-270
Ata Jahangir Moshayedi , Mahyar Gheibollahi , Liefa Liao
In the last decade, because of the unique specification of vertical fliers, scientists and researchers had a special focus on them. The particular abilities of these fliers can be mentioned such as: high maneuver ability, low expenses, decrease in radar identifier and low threat for the human life. They also have no limitation in dimension. Moreover, because of some applications like photography, topography, news coverage, study of power lines and aerology analysis, they can be notable for using. These fliers also are significantly important because of monitoring in urban regions, agricultural harvest and spray poison, illegal imports, exports administration and fire distinction in order to control the fire. Besides, seek and rescue missing people and also natural disasters can be pre-determined which causes stimulus investigators to act and put different topics in front of them. One of these fields is using meta-heuristic algorithms with the capability of using in control systems. The PID controller as a classic model has some limitations, but by optimization of special index through meta-heuristic algorithms, it has shown acceptable results. In this study, first, the history of vertical fliers and quadrotor are investigated. Then, after a review of overused methods, the quadrotor control has been done. Afterward, the cinematic and dynamic of quadrotor is presented. Next by designing of PID controller, PID index optimization by nature inspired algorithm, particle swarm optimization (PSO), genetic algorithms (GA), and firefly algorithms (FA) have been studied. Dynamic system, controller and mentioned optimization methods of PID controller index have also been implemented in MATLAB software. Also, with due attention to the comparison criteria the PID-PSO controller has shown the best performance. Next, by applying challenging routes, the stability of controller in the simulation is evaluated. Then, making quadrotor is done in practice along with introducing the used implementation of PID-PSO controller results on the real robot, and its stability is evaluated practically.
Volume: 9
Issue: 4
Page: 256-270
Publish at: 2020-12-01

Do the school adaptation levels of preschoolers vary according to their relationship with their teachers?

10.11591/ijere.v9i4.20540
Filiz Erbay , Neslihan Durmuşoğlu Saltalı
In this study, the differentiation status of preschool children's adaptation to school according to their relationship with teachers was examined. The study participants consisted of 326 children aged 60-72 months and 21 preschool teachers in different preschool educational institutions affiliated to the Provincial Directorate of National Education in Konya, Turkey. The School Adaptation Teacher Assessment Scale and Teacher-Student Relationship Scale were utilized to collect the research data. In the evaluation of the research data, firstly, teacher-child relationship scores were divided into groups for cluster analysis: conflictual/non-conflictual, dependent/ independent, and close/distant teacher-child relationship. The data gathered were analyzed using the independent-samples t-test. The results of the study revealed that the level of school adaptation of the children who had close, non-conflictual, and independent relationships with their teachers differed significantly from that of children who had distant, conflictual, and dependent relationships with their teachers. Positive teacher-child relationships reflected positively on the level of the child's school adaptation level. Teachers should establish close relationships with children in order to facilitate their adaptation to the school in the preschool period.
Volume: 9
Issue: 4
Page: 857-864
Publish at: 2020-12-01

Steam turbine controllers design based on soft-computing techniques

10.11591/ijra.v9i4.pp281-291
Nasir Ahmed Alawaad
Steam turbine is viewed as a standout among hotspots for control age in the most recent decades, its elements examination end up being dynamically more basic. For this investigation, the model chose is of turbine speed control framework. The purpose behind this is that model is regularly experienced in refineries in a type of steam turbine that utilization hydraulic governor to control the speed of the turbine. To suit plan prerequisites, a mathematical model for the turbine was determined in light of transfer function and state space definition. There are two sorts of controllers for steam turbines which are traditional and modern controllers. Internal mode control with proportional integral derivative (IMC-PID) and linear quadratic controller (LQR) are classical type. Fuzzy logic controller (FLC) and intelligent optimization techniques like, ant colony algorithm (ACOA) and genetic algorithm (GA) are modern type. The proposed work centers on classical verses modern controllers. Results got demonstrate that embracing such a controller (GA) improves the design requirements and transient stability. The system control was actualized in simulation utilizing MATLAB/Simulink.
Volume: 9
Issue: 4
Page: 281-291
Publish at: 2020-12-01

A multilayer perceptron artificial neural network approach for improving the accuracy of intrusion detection systems

10.11591/ijai.v9.i4.pp609-615
Abdulrahman Jassam Mohammed , Muhanad Hameed Arif , Ali Adil Ali
Massive information has been transmitted through complicated network connections around the world. Thus, providing a protected information system has fully consideration of many private and governmental institutes to prevent the attackers. The attackers block the users to access a particular network service by sending a large amount of fake traffics. Therefore, this article demonstrates two-classification models for accurate intrusion detection system (IDS). The first model develops the artificial neural network (ANN) of multilayer perceptron (MLP) with one hidden layer (MLP1) based on distributed denial of service (DDoS). The MLP1 has 38 input nodes, 11 hidden nodes, and 5 output nodes. The training of the MLP1 model is implemented with NSL-KDD dataset that has 38 features and five types of requests. The MLP1 achieves detection accuracy of 95.6%. The second model MLP2 has two hidden layers. The improved MLP2 model with the same setup achieves an accuracy of 2.2% higher than the MLP1 model. The study shows that the MLP2 model provides high classification accuracy of different request types.
Volume: 9
Issue: 4
Page: 609-615
Publish at: 2020-12-01

Automatic amyotrophic lateral sclerosis detection using tunable Q-factor wavelet transform

10.11591/ijai.v9.i4.pp744-756
Abdelouahad Achmamad , Abdelali Belkhou , Atman Jbari
Early diagnosis of amyotrophic lateral sclerosis (ALS) based on electromyography (EMG) is crucial. The processing of a non-stationary EMG signal requires powerful multi-resolution methods. Our study analyzes and classifies the EMG signals. In the present work, we introduce a novel flexible method for classification of EMG signals using tunable Q-factor wavelet transform (TQWT). Different sub-bands generated by the TQWT technique were served to extract useful information related to energy and then the calculated features were selected using a filter selection (FS) method. The effectiveness of the feature selection step resulted not only in the improvement of classification performance but also in reducing the computation time of the classification algorithm. The selected feature subsets were used as inputs to multiple classifier algorithms, namely, k-nearest neighbor (k-NN), least squares support vector machine (LS-SVM) and random forest (RF) for automated diagnosis. The experimental results show better classification measures with k-NN classifier compared with LS-SVM and RF. The robustness of the classification task was tested using a ten-fold cross-validation method. The outcomes of our proposed approach can be exploited to aid clinicians in neuromuscular disorders detection.
Volume: 9
Issue: 4
Page: 744-756
Publish at: 2020-12-01

Arduino based gas leakage and temperature monitoring and control system

10.11591/ijict.v9i3.pp171-178
Adoyi Boniface , A.Y. Nasir , A. M. Hassan
Gas leakage is a major problem with industrial sectors, residential premises and gas powered vehicles like CNG (Compressed Natural Gas) buses etc. One of the preventive methods to stop accidents associated with the gas leakage is to install a gas leakage detection device at vulnerable places. The aim of this project is to develop such a device that can automatically detect and control gas leakages and also monitor temperature in vulnerable areas. The system detects the leakage of the LPG (Liquefied Petroleum Gas) using a gas sensor and then also monitors the temperature using a temperature sensor. When the LPG concentration in the air exceeds a certain level, the gas sensor senses the gas leakage and the output of the sensor goes LOW, the system then opens the exit windows, and then uses the GSM to alert the person about the gas leakage via SMS. Also, when the temperature of the environment exceeds a certain limit, it then turns ON the LED (indicator) and make an alarm through the buzzer. An LCD (16x2) displays the current temperature and gas leakage status in degree Celsius and PPM respectively.
Volume: 9
Issue: 3
Page: 171-178
Publish at: 2020-12-01

Tuberculosis detection using deep learning and contrastenhanced canny edge detected X-Ray images

10.11591/ijai.v9.i4.pp713-720
Stefanus Kieu Tao Hwa , Abdullah Bade , Mohd Hanafi Ahmad Hijazi , Mohammad Saffree Jeffree
Tuberculosis (TB) is a disease that causes death if not treated early. Ensemble deep learning can aid early TB detection. Previous work trained the ensemble classifiers on images with similar features only. An ensemble requires a diversity of errors to perform well, which is achieved using either different classification techniques or feature sets. This paper focuses on the latter, where TB detection using deep learning and contrast-enhanced canny edge detected (CEED-Canny) x-ray images is presented. The CEED-Canny was utilized to produce edge detected images of the lung x-ray. Two types of features were generated; the first was extracted from the Enhanced x-ray images, while the second from the Edge detected images. The proposed variation of features increased the diversity of errors of the base classifiers and improved the TB detection. The proposed ensemble method produced a comparable accuracy of 93.59%, sensitivity of 92.31% and specificity of 94.87% with previous work.
Volume: 9
Issue: 4
Page: 713-720
Publish at: 2020-12-01
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