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31,456 Article Results

DC and RF characteristics of 20 nm gate length InAlAs/InGaAs/InP HEMTs for high frequency application

10.11591/ijece.v10i2.pp1248-1254
Amin Boursali , Ahlam Guen-Bouazza , Choukria Sayah
lnAlAs/lnGaAs/InP high electron mobility transistor (HEMT) offers excellent high frequency operation.In this work,the DC and RF performance of a 20 nm gate length enhancement mode InAlAs/InGaAs/InP high electron mobility transistor (HEMT) on InP substrate are presented.The SILVACO-TCAD simulations performed at room temperature using the appropriate model sshowed that the studied device exhibit excellent pinch-off characteristics, with a maximum transconductance of 1100ms/mm, a threshold voltage of 0,62V, and an Ion/Ioff ratio of 2.106. The cut-off frequency and maximum frequency of oscillation are 980 GHz and 1.3THz respectively. These promising results allow us to affirm that this device is intended to be used in high frequency applications.
Volume: 10
Issue: 2
Page: 1248-1254
Publish at: 2020-04-01

Grey wolf optimizer based fuzzy-PI active queue management design for network congestion avoidance

10.11591/ijeecs.v18.i1.pp199-208
Sana Sabah Sabry , Nada Mahdi Kaittan
Congestion is one of the most important issues in communication networks which has attracted much research attention. To ensure a stable TCP network, we can use active queue management (AQM for early congestion detection and router queue length regulation. In this study, it was proposed to use the Grey Wolf Optimizer (GWO) algorithm in designing a fuzzy proportional integral (fuzzy-PI) controller as a novel AQM for internet routers congestion control and for achieving a low steady-state error and fast response. The suggested Fuzzy logic-based network traffic control strategy permit us to deploy linguistic knowledge for depicting the dynamics of probability marking functions and ensures a more accurate use of multiple inputs to depict the   the network’s state. The possibility of incorporating human knowledge into such a control strategy using Fuzzy logic control methodology was demonstrated. The postulated controller was compared to proportion integral (PI) through several MATLAB simulation scenarios. The results indicated the stability of the postulated controller and its ability to attain a faster response in a dynamic network with varying network load and target queue length.
Volume: 18
Issue: 1
Page: 199-208
Publish at: 2020-04-01

Developing barcode scan system of a small-scaled reverse vending machine to sorting waste of beverage containers

10.12928/telkomnika.v18i4.14776
Erikson Ferry; Swiss German University Sinaga , Richard; Swiss German University Irawan
Reduce, Reuse, and Recycle is a campaign which aims to reduce the production of waste. Industry used plastic bottle and cans to store the beverage. A research was done by University of Georgia, United States and was published by Wall Street Journal stated that Indonesia is the second predicate country which produced and mismanaged plastic waste in the world. This condition shoud be overcome and this research project was intended to develop reverse vending machine (RVM) to sorting waste of beverage containers either plastic bottles or cans as a campaign to reduce the production of waste. This RVM machine uses barcode scanning as the sorting system to determine whether the plastic bottle or can could be recycled or not. In order to check the weight of the beverage container, a load cell sensor is used to check whether the beverage container is empty or not. The machine will receive the container from the conveyor station, check the weight, and finally transfer it to the sorting station. The container will be sorted as cans or plastic bottle by the aid of barcode scanning and compare it to database. Furthermore, the plastic bottle will be sorted as clear or colored plastic bottle. Unrecyclable plastic or can container or any unemptied container will be classified as rejected container and be returned to the user through the outlet passage. The performance testing was done with 12 different types of plastic bottle and can and 10 samples for each type, so there were total 120 items tested and the result showed that the success rate was 94% while the processing time was varying in between 8 to 13 seconds.
Volume: 18
Issue: 4
Page: 2087-2094
Publish at: 2020-03-18

Efficiency comparison of capacitive wireless power transfer for different materials

10.11591/ijpeds.v11.i1.pp200-212
F. K. A. Rahman , Shakir Saat , Y. Yusop , S. H. Husin , M. H. Jamaluddin
This paper describes the application of several types of materials to act as capacitive plates in a Capacitive Power Transfer (CPT) system. In general, the efficiency of CPT system is greatly influenced by the coupling capacitance which is varied by distances and permittivity values. Thus this paper intended to compare the performance of CPT system in terms of the output efficiency for several types of capacitive plates. To be specific, copper plate, zinc, and aluminium are used in this work to act as coupling plates to the CPT system. The CPT system in this work applied class E inverter as it has lowest switching losses among its competitors, i.e. class D and class F. The work is validated through experimental setup of CPT system in which copper material provides the best efficiency of the system.
Volume: 11
Issue: 1
Page: 200-212
Publish at: 2020-03-01

Exploration on digital marketing as business strategy model among Malaysian entrepreneurs via neurocomputing

10.11591/ijai.v9.i1.pp18-24
Hazrita Ab Rahim , Shafaf Ibrahim , Saadi Bin Ahmad Kamaruddin , Nor Azura Md. Ghani , Ismail Musirin
Artificial Intelligence is great when it comes to routine activities and vast amounts of data are analyzed. This can be done more quickly and efficiently than men. In the world of digital marketing, Artificial Intelligence is quickly coming into play. With Artificial Intelligence joining the digital marketing environment, predicting user behavior, search cycles, and much more will be easier. This can support websites that are highly user-friendly for organizations. Moreover, with the aid of Artificial Intelligence, content creation has become a faster and easier task for brands. Practically, a company's degree of enterprise marketing can have an effect on its overall business efficiency. Entrepreneurial marketing is driven by entrepreneurial opportunities which involves the proactive identification and exploitation of opportunities for acquiring and retaining profitable customers through Digital approaches to risk management, resource leveraging and value creation. This research was done by collecting data using semi structure questionnaire distributed to 169 start up owners in Klang Valley area. Using two-layer 6-3-1 with hyperbolic tangent-purelin configurations neural network model, it was found that proactiveness, risk taking, resource leveraging, opportunity focus, intensity and value add are the significant factors towards digital marketing respectively. It is expected that the findings would give some inputs to the Malaysian entrepreneurs on innovative digital marketing in their businesses, regardless the sizes.
Volume: 9
Issue: 1
Page: 18-24
Publish at: 2020-03-01

Artificial neural network model and fuzzy logic control of dissolved oxygen in a bioreactor

10.11591/ijeecs.v17.i3.pp1289-1297
Nor Hana Mamat , Samsul Bahari Mohd Noor , Laxshan A/L Ramar , Azura Che Soh , Farah Saleena Taip , Ahmad Hazri Ab. Rashid
In a fermentation process, dissolved oxygen is the one of the key process variables that needs to be controlled because of the effect they have on the product quality. In a penicillin production, dissolved oxygen concentration influenced biomass concentration. In this paper, multilayer perceptron neural network (MLP) and Radial Basis Function (RBF) neural network is used in modeling penicillin fermentation process. Process data from an industrial scale fed-batch bioreactor is used in developing the models with dissolved oxygen and penicillin concentration as the outputs. RBF neural network model gives better accuracy than MLP neural network. The model is further used in fuzzy logic controller design to simulate control of dissolved oxygen by manipulation of aeration rate.  Simulation result shows that the fuzzy logic controller can control the dissolved oxygen based on the given profile.
Volume: 17
Issue: 3
Page: 1289-1297
Publish at: 2020-03-01

Voltage tracking of bridgeless PFC cuk converter using PI controller

10.11591/ijpeds.v11.i1.pp367-373
W. M. Utomo , N. A. A. Isa , A. A. Bakar , A. F. H. A. Gani , B. E. Prasetyo , H. Elmunsyah , Y.M.Y Buswig
This paper proposes a Proportional-Integral (PI) control voltage tracking of Bridgeless Power Factor Correction (BPFC) Cuk converter.  In order to investigate the behaviour of different output voltages during overshoot, steady state and step response, P.I controller is designed to set the -42 V, -48 V, -54 V output voltages. The simulation results show that the proposed PI controller able to control the output voltage and achieve fast steady state and step response of BPFC Cuk converter.  When the value of output voltage increase, the overshoot voltage will become higher but the steady state respond will be faster. Furthermore, BPFC Cuk converter with P.I controller have low output voltage ripples.
Volume: 11
Issue: 1
Page: 367-373
Publish at: 2020-03-01

Homestay save rent method through consumer self-management of electricity power consumption

10.11591/ijpeds.v11.i1.pp425-432
Dirman Hanafi , Kamal Khairi Kamaruddin , Hisyam Abdul Rahman , Yudhi Gunardi
The rapid growth in the number of homestays and hotels, competition has increased among them. Homestay that is a relatively newcomer in this business should find the way to become competitive. One way is to make rental fees more affordable. In this paper a method to reduce the homestay rental fees are proposed. This is done by separating the component of the electricity cost from the whole rental fees. Then it requires the consumer to pay their own electricity used and also gives opportunity to them to manage their own electricity used how much they need. This mechanism is implemented by equipping the homestay with the coin kilowatt hour (ckWh) meter. The consumer can plan how much they will use the power since they stay by inserting the certain amount of coin into the ckWh meter. After insert the coin the electricity sources will on and ready to use. The main components of this ckWh meter consist of the Arduino Uno microcontroller as a brain of the device, the coin acceptor where the coin will insert, and kilowatt hour meter. Besides that, it also equipped with liquid-crystal display (LCD) to show the amount of money currently available. The experimental test shows that the device develop work well and can control the used of the electricity related to the amount money that has been inserted.
Volume: 11
Issue: 1
Page: 425-432
Publish at: 2020-03-01

Development of option c measurement and verification model using hybrid artificial neural network-cross validation technique to quantify saving

10.11591/ijai.v9.i1.pp25-32
Wan Nazirah Wan Md Adnan , Nofri Yenita Dahlan , Ismail Musirin
This paper aims to develop a hybrid artificial neural network for Option C Measurement and Verification model to predict monthly building energy consumption. In this work, baseline energy model development using artificial neural networks embedded with artificial bee colony optimization and cross validation technique for a small dataset were considered. Artificial bee colony optimization with coefficient of correlation fitness function was used in optimizing the neural network training process and selecting the optimal values of initial weights and biases. Working days, class days and cooling degree days were used as input meanwhile monthly electricity consumption as an output of artificial neural network. The results indicated that this hybrid artificial neural network model provided better prediction results compared to the other model. The best model with the highest value of coefficient of correlation was selected as the baseline model hence is used to determine the saving. 
Volume: 9
Issue: 1
Page: 25-32
Publish at: 2020-03-01

Improvement of protection relay with a single phase autoreclosing mechanism based on artificial neural network

10.11591/ijpeds.v11.i1.pp505-514
Zozan Saadallah Hussain , Ahmed J. Ali , Ahmed A. Allu , Rakan Khalil Antar
This paper presents a developed logical tripping scheme to improve conventional protection performance. Adaptive single pole auto reclosure (ASPAR) system is proposed that considers, automatically tripping and reclosing of a multi-shot independent pole technique of a circuit breaker at a predetermined sequence, which can be used to boost the synchronization of the power grid under the transient fault conditions. Moreover, the ASPAR can be utilized to enhance the electrical system stability and reliability at the same operating conditions. Based on the three-phase system, the Artificial neural network (ANN) in this work has been done in order to diagnose and detect healthy and faulted phases. The proposed ANN fault classifier method consists of the logic gates, router circuits, timers, and positive and negative sequence analyses circuit. In addition, it is used to give the ability to recognize a fault type, which by training on the sequence angle values and coordination of the transmission line. Three-phase overhead transmission line including the proposed ASPAR is built in MATLA \SIMULINK environment. Thus the performance ANN-fault classified is tested under different fault conditions. Simulation results show that the proposed ASPAR based on ANN is accurate and well performance. Whereas resultant tripping and reclosing signals of ASPAR are successfully provided that enhances the circuit breaker mechanism under these operating condition.
Volume: 11
Issue: 1
Page: 505-514
Publish at: 2020-03-01

New insider threat detection method based on recurrent neural networks

10.11591/ijeecs.v17.i3.pp1474-1479
Mohammed Nasser Al-mhiqani , Rabiah Ahmad , Zaheera Zainal Abidin , Warusia Yassin , Aslinda Hassan , Ameera Natasha Mohammad
Insider threat is a significant challenge in cybersecurity. In comparison with outside attackers, inside attackers have more privileges and legitimate access to information and facilities that can cause considerable damage to an organization. Most organizations that implement traditional cybersecurity techniques, such as intrusion detection systems, fail to detect insider threats given the lack of extensive knowledge on insider behavior patterns. However, a sophisticated method is necessary for an in-depth understanding of insider activities that the insider performs in the organization. In this study, we propose a new conceptual method for insider threat detection on the basis of the behaviors of an insider. In addition, gated recurrent unit neural network will be explored further to enhance the insider threat detector. This method will identify the optimal behavioral pattern of insider actions.
Volume: 17
Issue: 3
Page: 1474-1479
Publish at: 2020-03-01

Solar fed BLDC motor drive for mixer grinder using a boost converter

10.11591/ijpeds.v11.i1.pp56-63
Deekshitha S Nayak , R Shivarudraswamy
The existing mixer grinder comprises of the universal motor operating in alternating current supply due to high starting torque characteristics and simple controlling of the speed. The absence of brushes and the reduction of noise in the Brushless DC (BLDC) extends its lifetime and makes it ideal in a mixer grinder. A novel solar-powered BLDC motor drive for mixer grinder is presented in this paper. A DC-DC boost converter has been utilised to operate a PV (photovoltaic) array at its highest power. The proposed hysteresis current control BLDC system has been developed in the MATLAB. A performance comparison is made using the commercially available mixer grinder along with the simulated proposed system.
Volume: 11
Issue: 1
Page: 56-63
Publish at: 2020-03-01

Feature selection for DDoS detection using classification machine learning techniques

10.11591/ijai.v9.i1.pp137-145
Andi Maslan , Kamaruddin Malik Bin Mohamad , Feresa Binti Mohd Foozy
Computer system security is a factor that needs to be considered in the era of industrial revolution 4.0, namely by preventing various threats to the system, as well as being able to detect and repair any damage that occurs to the computer system. DDoS attacks are a threat to the company at this time because this attack is carried out by making very large requests for a site or website server so that the system becomes stuck and cannot function at all. DDoS attacks in Indonesia and developed countries always increase every year to 6% from only 3%. To minimize the attack, we conducted a study using Machine Learning techniques. The dataset is obtained from the results of DDoS attacks that have been collected by the researchers. From the datasets there is a training and testing of data using five techniques classification: Neural Network, Naïve Bayes and Random Forest, KNN, and Support Vector Machine (SVM), datasets processed have different percentages, with the aim of facilitating in classifying. From this study it can be concluded that from the five classification techniques used, the Forest random classification technique achieved the highest level of accuracy (98.70%) with a Weighted Avg 98.4%. This means that the technique can detect DDoS attacks accurately on the application that will be developed.
Volume: 9
Issue: 1
Page: 137-145
Publish at: 2020-03-01

Comparative study of two control strategies proportional integral and fuzzy logic for the control of a doubly fed induction generator dedicated to a wind application

10.11591/ijpeds.v11.i1.pp263-274
Chebel Ahlem , Benretem A , Dobrev I , Barkati Barkati
This paper presents a study analysis of a complete wind energy conversion system, the system based on a doubly fed induction generator (DFIG); a vector control with stator flux orientation of the DFIG is also used to control independently the active and reactive powers. A comparative study have been performed between the conventional PI controller and fuzzy logic control to investigate its dynamic and static performances. This research work involves the study of a phase in advance, to provide effective assistance, to all those who have to make decisions regarding the planning and implementation of wind energy projects. The main objective is to model the wind chain and the use of two types of strategies for the control of this generator to ensure a good regulation we started with the modeling of the wind chain then the modeling of the DFIG and then the use of the two strategies for the regulation of the latter .The complete system is modeled and simulated in the MATLAB/ Simulink. The performance and robustness are analyzed and compared by Matlab / Simulink .Simulation results prove the excellent performance of fuzzy control unit as improving power quality and stability of wind turbine.
Volume: 11
Issue: 1
Page: 263-274
Publish at: 2020-03-01

Modelling and control of fouling in submerged membrane bioreactor using neural network internal model control

10.11591/ijai.v9.i1.pp100-108
Nurazizah Mahmod , Norhaliza Abdul Wahab , Muhammad Sani Gaya
Membrane bioreactor (MBR) is one of the best solutions for water and wastewater treatment systems in producing high quality effluent that meets its standard regulations. However, fouling is one of the main issues in membrane filtration for membrane bioreactor system. The prediction of fouling is crucial in the membrane bioreactor control system design. This paper presents an intelligence modeling system so called artificial neural network (ANN). The feedforward neural network (FFNN), radial basis function neural network (RBFNN) and nonlinear autoregressive exogenous neural network (NARXNN) are applied to model the submerged MBR filtration system. The simulation results show good predictions for all methods which the highest performance of the model given by RBFNN. Based on the developed models, the neural network internal model control (NNIMC) is implemented to control fouling development in membrane filtration process. Three different control structures of the NNIMC are proposed. The FFNN IMC, RBFNN IMC and NARXNN IMC controllers are compared to the conventional IMC. The RBFNN IMC has a superior performance both in tracking and disturbance rejections.
Volume: 9
Issue: 1
Page: 100-108
Publish at: 2020-03-01
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