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31,456 Article Results

New improved hybrid MPPT based on neural network-model predictive control-kalman filter for photovoltaic system

10.11591/ijeecs.v20.i3.pp1230-1241
Nora Kacimi , Said Grouni , Abdelhakim Idir , Mohamed Seghir Boucherit
In this paper, new hybrid maximum power point tracking (MPPT) strategy for Photovoltaic Systems has been proposed. The proposed technique for MPPT control based on a novel combination of an artificial neural network (ANN) with an improved model predictive control using kalman filter (NN-MPC-KF). In this paper the Kalman filter is used to estimate the converter state vector for minimized the cost function then predict the future value to track the maximum power point (MPP) with fast changing weather parameters. The proposed control technique can track the MPP in fast changing irradiance conditions and a small overshoot. Finally, the system is simulated in the MATLAB/Simulink environment. Several tests under stable and variable environmental conditions are made for the four algorithms, and results show a better performance of the proposed MPPT compared to conventional Perturb and Observation (P&O), neural network based proprtional integral control (NN-PI) and Neural Network based model predictive control (NN-MPC) in terms of response time, efficiency and steady-state oscillations.
Volume: 20
Issue: 3
Page: 1230-1241
Publish at: 2020-12-01

Preparedness of members of the Indonesian emergency and disaster nurses association

10.11591/ijphs.v9i4.20500
Guruh Suprayitno , Ahsan Ahsan , Karyono Mintaroem
Disaster is a global issue all around the world, and Indonesia has shifted its disaster mitigation strategies from emergency response to disaster management preparedness. This research analysed factors influencing the preparedness of members of the Indonesian emergency and disaster association (IEDNA) in the face of natural disasters in Indonesia. This research is analytical-observational with a cross-sectional approach. Sampling was performed on a population of 510 member nurses of the IEDNA by the probability sampling technique. Out of the 510 member nurses of the IEDNA, 107 were enrolled in this research. The Fisher’s exact test results show that knowledge had p= 0.001 (p< 0.05), while facilities and infrastructures availability p= 0.000 (p< 0.05), in their effects on nurse preparedness. The multivariate analysis yielded Exp(B) of 0.022 for knowledge and Exp(B) of 0.003 for facilities and infrastructures availability, while the Nagelkerke’s R-squared obtained was 66%. The variable preparedness was largely good, and there were significant relationships of knowledge and facilities and infrastructures availability to the preparedness of members of the IEDNA. The strongest factor was knowledge.
Volume: 9
Issue: 4
Page: 393-398
Publish at: 2020-12-01

Relationship between social media addiction, game addiction and family functions

10.11591/ijere.v9i4.20680
Ebru Yayman , Okan Bilgin
This study examined the relationship between social media addiction, game addiction and family functions in adolescents. Respondent of this study is 762 students studying at four different high schools of the province of İstanbul. In the study, Pearson Moment Correlation Coefficient was found to determine the level of relationships between social media addiction, game addiction and family functions in adolescents. The effects of social media addiction and game addiction in adolescents on family functions were examined with regression analysis technique. When the relationships between social media addiction, game addiction and family functions in adolescents were examined, a positive relationship was found between social media and game addiction, while a positive significant relationship was found between both social media and game addiction and unhealthy family functions. In addition, it was also concluded that social media addiction and game addiction in adolescents were significant predictors of all subdimensions of family functions.
Volume: 9
Issue: 4
Page: 979-986
Publish at: 2020-12-01

Calculating algorithm of service quality statistical parameters for asynchronous network subscribers

10.11591/ijeecs.v20.i3.pp1485-1494
Kemelbekova Zh. S. , Sembiyev O. Z. , Umarova Zh. R
It is often necessary to determine statistical parameters that characterize the quality of service on the network by managing when designing computer networks using the concept of virtual connections with bypass directions. In many ways, the attainable level of quality of the services provided is determined at the stage of network design, when decisions was made regarding the subscriber capacity of stations, the capacity of bundles of trunk lines, the composition and volume of telecommunication services provided. Despite constant progress in the field of network technologies, the problem of determining the necessary amount of network resources and ensuring the quality of user service remains relevant. In this regard, this article discusses a broadband digital network with service integration, based on an asynchronous network in which an iterative method implemented. Here the flow distribution is determined by the route matrix, and the load distribution between the nodes of each pair of nodes made through the path tree obtained on the matrix of routes when calculating this pair. At the same time, an algorithm has been built for allow optimal allocation of channel resources between circuit switching and packet switching subnets within an asynchronous network.
Volume: 20
Issue: 3
Page: 1485-1494
Publish at: 2020-12-01

Improving the initial values of VFactor suitable for balanced modulus

10.11591/ijece.v10i6.pp6446-6452
Kritsanapong Somsuk
The aim of this study is to estimate the new initial values of VFactor. In general, this algorithm is one of the members in a group of special proposed integer factorization algorithm. It has very high performance whenever the result of the difference between two prime factors of the modulus is a little, it is also called as balanced modulus. In fact, if this situation is occurred, RSA which is a type of public key cryptosystem will be broken easily. In addition, the main process of VFactor is to increase and decrease two odd integers in order to compute the multiplication until the targets are found. However, the initial values are far from the targets especially that the large value of the difference between two prime factors that is not suitable for VFactor. Therefore, the new initial values which are closer to the targets than the traditional values are proposed to decrease loops of the computation. In experimental results, it is shown that the loops can be decreased about 26% for the example of 256 bits-length of modulus that is from the small result of the difference between prime factors.
Volume: 10
Issue: 6
Page: 6446-6452
Publish at: 2020-12-01

New voltage and temperature scalable gate delay model applied to a 14nm technology

10.11591/ijeecs.v20.i3.pp1210-1220
Kenza Charafeddine , Faissal Ouardi
The following work shows an innovative approach to model the timing of standard cells. By using mathematical models instead of the classical SPICE-based characterization, a high amount of CPU (Central Processing Unit) cores is saved and less amount of data is stored. In the present work, characterization of cells of a standard cell library is done in an hour whereas it is done in 650 hours with the classical method. Also, a method for validating and verification of the precision of the modelled data is resented by comparing them on a implemented circuit. The output of implementations shows less than 3% of error between the two methods.
Volume: 20
Issue: 3
Page: 1210-1220
Publish at: 2020-12-01

Machine learning for plant disease detection: an investigative comparison between support vector machine and deep learning

10.11591/ijai.v9.i4.pp670-683
Aliyu Muhammad Abdu , Musa Mohd Muhammad Mokji , Usman Ullah Ullah Sheikh
Image-based plant disease detection is among the essential activities in precision agriculture for observing incidence and measuring the severity of variability in crops. 70% to 80% of the variabilities are attributed to diseases caused by pathogens, and 60% to 70% appear on the leaves in comparison to the stem and fruits. This work provides a comparative analysis through the model implementation of the two renowned machine learning models, the support vector machine (SVM) and deep learning (DL), for plant disease detection using leaf image data. Until recently, most of these image processing techniques had been, and some still are, exploiting what some considered as "shallow" machine learning architectures. The DL network is fast becoming the benchmark for research in the field of image recognition and pattern analysis. Regardless, there is a lack of studies concerning its application in plant leaves disease detection. Thus, both models have been implemented in this research on a large plant leaf disease image dataset using standard settings and in consideration of the three crucial factors of architecture, computational power, and amount of training data to compare the duos. Results obtained indicated scenarios by which each model best performs in this context, and within a particular domain of factors suggests improvements and which model would be more preferred. It is also envisaged that this research would provide meaningful insight into the critical current and future role of machine learning in food security
Volume: 9
Issue: 4
Page: 670-683
Publish at: 2020-12-01

Q-Learning vertical handover scheme in two-tier LTE-A networks

10.11591/ijece.v10i6.pp5824-5831
Ammar Bathich , Mohd Asri Mansor , Saiful Izwan Suliman , Sinan Ghassan Abid Ali
Global mobile communication necessitates improved capacity and proper quality assurance for services. To achieve these requirements, small cells have been deployed intensively by long term evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. Accomplishment of seamless handover between Macrocell layer (first tier) and Femtocell layer (second tier) is one of the key challenges to attain the QoS requirements. Handover related information gathering becomes very hard in high dense femtocell networks, effective handover decision techniques are important to minimize unnecessary handovers occurred and avoid Ping-Pong effect. In this work, we proposed and implemented an efficient handover decision procedure based on users’ profiles using Q-learning technique in an LTE-A macrocell-femtocell networks. New multi-criterion handover decision parameters are proposed in typical/dense femtocells in microcells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. The simulation results showed noteworthy reduction in the average number of handovers.
Volume: 10
Issue: 6
Page: 5824-5831
Publish at: 2020-12-01

A proposed system for opinion mining using machine learning, NLP and classifiers

10.11591/ijai.v9.i4.pp726-733
Poonam Tanwar , Priyanka rai
In today’s life consumer reviews are the part of everyday life. User read the reviews before purchase, or stores it for finding the best product through comparison of the product review. From customers view point the reviews play vital role to make a decision regarding an online purchase as well as spammers to write the fake reviews which can increase or defame the reputation of any product. Spammers are using these platforms illegally for financial benefits/incentives are involved in writing fake reviews and they are trying to achieve their motive in terms of financial or to defeat the competitor which causes an explosive growth of sentiment/opinion spamming of writing forged/fake reviews. The present studies and research are used to analyse and categorize the opinion spamming into three different detection targets opinion spam, spammers, and to find the collusive opinion spammer groups so that false opinions can be avoided. Opinion spamming further divided into three different types based on textual and linguistic, behavioral, and relational features. The motivation behind this work is to study the dynamics of spam diffusion and extract the latent features that fuel the diffusion process. The user-based features and content-based features have been used for the categorization of spam/non-spam content. The contributions of this work are building the datasetwhich assists as the ground-truth for classifying/analyzing the variation of fraud/genuine and non-spam/spam information diffusion and to analyze the effects of topics over the diffusibility of non-spam and spam evidences/information. The paper, carried out an in-depth analysis of Twitter Spam diffusion.
Volume: 9
Issue: 4
Page: 726-733
Publish at: 2020-12-01

Ear biometric verification approach based on morphological and geometric invariants

10.11591/ijeecs.v20.i3.pp1479-1484
Wurood A. Jbara
Biometric verification based on ear features is modern filed for scientific research. As known, there are many biometric identifiers that can identify people such as fingerprints, iris and speech. In this paper, the focus is placed on the ear biometric model in order to verifying the identity of persons. The main idea is based on used the moments as ear feature extractors. The proposed approach included some operations as follow: image capturing, edge detection, erosion, feature extraction, and matching. The proposed approach has been tested using many images of the ears with different states. Experimental results using several trails verified that the proposed approach is achieved high accuracy level over a wide variety of ear images. Also, the verification process will be completed by matching query ear image with ear images that kept in database during real time.
Volume: 20
Issue: 3
Page: 1479-1484
Publish at: 2020-12-01

A risk and security assessment of VANET availability using attack tree concept

10.11591/ijece.v10i6.pp6039-6044
Meriem Houmer , Moulay Lahcen Hasnaoui
The challenging nature of insecure wireless channels and the open-access environment make the protection of vehicular ad hoc network (VANET) a particularly critical issue. Researchers and interested authorities have therefore paid more attention to this issue. Therefore, robust approaches to protect this network's security and privacy against adversaries and attacks need to be improved, trying to achieve an adequate level, to secure the confidential information of drivers and passengers. Accordingly, to improve the security of VANET, it is necessary to carry out a risk assessment, in order to evaluate the risk that faces this network. This paper focuses on the security threats in vehicular network especially on the availability of this network. We propose a novel risk assessment approach to evaluate the risk of the attack that the attacker can lead against the availability of VANET. We adopt a tree structure called attack tree to model the attacker's potential attack strategies. Based on this attack tree model, we can estimate the degree that a certain threat can lead to the VANET and identify possible attack sequences that an attacker may launch against the availability of this network. Then we utilize the multi-attribute utility theory to calculate the system’s total risk value also the probabilities of each attack sequence. The analysis results can provide support for decision-makers to make corresponding protection measures against the attack on the availability of this network.
Volume: 10
Issue: 6
Page: 6039-6044
Publish at: 2020-12-01

Student performance prediction using simple additive weighting method

10.11591/ijai.v9.i4.pp630-637
Harco Leslie Hendric Spits Warnars , Arif Fahrudin , Wiranto Herry Utomo
In the world of student education is an important component where the role of students is as someone who is psychologically ready to receive lessons or other input from the school. However, each student has different performance and development, therefore it is important to do monitoring so that student performance will always be monitored by the school for improving student quality maintenance. Also, in the process of valuing education for students needs to be done by giving an appreciation in the form of giving gifts or just giving words and motivation so that students can perform better in learning and participating in other activities at school. In terms of selecting students with good performance or those who have a very declining development using the school method not only assess students by one criterion but with several criteria to produce a decision that can be accepted by many people. Performance Students must also be monitored by the school or the related rights. In this paper, the student performance prediction was assessed with 5 criteria components and the result shows there are 10 very satisfy students, 10 satisfying students, 10 well students, and 10 Enough students from sample 40 students.
Volume: 9
Issue: 4
Page: 630-637
Publish at: 2020-12-01

Development of a photovoltaic characteristics generator based on mathematical models for four PV panel technologies

10.11591/ijece.v10i6.pp6101-6110
Samia Jenkal , Mustapha Kourchi , Driss Yousfi , Ahmed Benlarabi , Mohamed Larbi Elhafyani , Mohamed Ajaamoum , Mhand Oubella
A good study of photovoltaic system requests to have very precise current-voltage characteristic curves of photovoltaic modules for different technologies. The photovoltaic emulator provides an efficient solution to maintain the same current-voltage output of photovoltaic module. It includes three parts: the PV model, the control strategy, and the power converter. This paper provides three classes of modeling and simulation of photovoltaic arrays and presents the synthesis results of the current-voltage characteristic performances obtained by the modeling approaches. The models of the first class are based on electrical circuit model, those of the second class are based on multiple straight lines model, and for the third class, it is based on the look up table. The mathematical model is built using MATLAB/ Simulink, and an experimental bench was carried out to acquire an up-to-date and representative experimental database of four PV panels. This database is used for the validation of these models for the different PV panel technologies under Moroccan meteorological conditions. Following this comparative study, we came to a high agreement between the experimental and simulated current-voltage characteristics for the emulator under study.
Volume: 10
Issue: 6
Page: 6101-6110
Publish at: 2020-12-01

Physical layer security and energy efficiency over different error correcting codes in wireless sensor networks

10.11591/ijece.v10i6.pp6673-6681
Mohammed Ahmed Magzoub , Azlan Abd Aziz , Mohammed Ahmed Salem , Hadhrami Ab Ghani , Azlina Abdul Aziz , Azwan Mahmud
Despite the rapid growth in the market demanding for wireless sensor networks (WSNs), they are far from being secured or efficient. WSNs are vulnerable to malicious attacks and utilize too much power. At the same time, there is a significant increment of the security threats due to the growth of the several applications that employ wireless sensor networks. Therefore, introducing physical layer security is considered to be a promising solution to mitigate the threats. This paper evaluates popular coding techniques like Reed solomon (RS) techniques and scrambled error correcting codes specifically in terms of security gap. The difference between the signal to nose ratio (SNR) of the eavesdropper and the legitimate receiver nodes is defined as the security gap. We investigate the security gap, energy efficiency, and bit error rate between RS and scrambled t-error correcting codes for wireless sensor networks. Lastly, energy efficiency in RS and Bose-Chaudhuri-Hocquenghem (BCH) is also studied. The results of the simulation emphasize that RS technique achieves similar security gap as scrambled error correcting codes. However, the analysis concludes that the computational complexities of the RS is less compared to the scrambled error correcting codes. We also found that BCH code is more energy-efficient than RS.
Volume: 10
Issue: 6
Page: 6673-6681
Publish at: 2020-12-01

Cuckoo search algorithm based for tunning both PI and FOPID controllers for the DFIG-Wind energy conversion system

10.11591/ijece.v10i6.pp6319-6329
Mostafa A. Al-Gabalawy , N. S. Hosny , Shimaa A. Hussien
Wind Energy has received great attention in this century. It influences the new power systems, adding new challenges to the power system expansion problem. Nowadays, double feed induction generator (DFIG) wind turbines are used majorly in wind farms, due to their advantages over other types. Therefore, the analysis of the system using this type has become very important. In this paper, a wind turbine modelling was introduced with suggested controllers, in order to enhance the system response, with respect to both pitch control and maximum output power. Cuckoo search algorithm (CSA), a meta-heuristic optimization technique, was implemented to determine the gains of a proportional-integral (PI) controller and fractional order proportional-integral-derivative (FOPID) controller to optimize the system, which considered three control loops: pitch, rotor-side converter, and grid-side converter control loop. Simulation results were determined using MATLAB/Simulink. The comparative analysis of the results showed that the PI Controller gave the simplest and the best response in case of the pitch and rotor-side control loops while the FOPID was the best when applied to the grid-side control loop. Based on the results and discussion, a suggestion of using a compination of each controller was introduced.
Volume: 10
Issue: 6
Page: 6319-6329
Publish at: 2020-12-01
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