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29,922 Article Results

Cost implications analysis of grid supplied electricity and solar source of electricity in Nigeria

10.12928/telkomnika.v18i6.13558
Tobiloba; Covenant University Somefun , Claudius; Covenant University Awosope , Ademola; Covenant University Abdulkareem , Joseph; Covenant University Ojo , Elizabeth; Covenant University Amuta , Timilehin; Covenant University Sanni
Energy is a key component in the overall growth of every nation. Insufficient energy delivery hinders political growth, restricts social growth, limits economic growth, and negatively affects the standard of living of citizens, bothin urban and rural areas. Sufficient energy delivery increases food production, improves the standards of living of citizens, improves healthcare and enhancements in other human services, enhances industrial output, provides effective and efficient transportation not forgetting adequate shelter to the citizens of the nation. Currently, there is a significant level of deficiency in Nigeria’s energy sector. This study seeks to address this issue by analysing cost implications of conventional energy source and solar energy source. This study brings to focus the payback period of a solar powered home and the return on investment that might accrue during this time to the residential home owners. Furthermore, the best cost-effective load sharing option for residential owners considering two energy sources is also obtained.
Volume: 18
Issue: 6
Page: 3258-3265
Publish at: 2020-12-01

Data mining in web personalization using the blended deep learning model

10.11591/ijeecs.v20.i3.pp1507-1512
Qusay Abdullah Abed , Osamah Mohammed Fadhil , Wathiq Laftah Al-Yaseen
In general, multidimensional data (mobile application for example) contain a large number of unnecessary information. Web app users find it difficult to get the information needed quickly and effectively due to the sheer volume of data (big data produced per second). In this paper, we tend to study the data mining in web personalization using blended deep learning model. So, one of the effective solutions to this problem is web personalization. As well as, explore how this model helps to analyze and estimate the huge amounts of operations. Providing personalized recommendations to improve reliability depends on the web application using useful information in the web application. The results of this research are important for the training and testing of large data sets for a map of deep mixed learning based on the model of back-spread neural network. The HADOOP framework is using to perform a number of experiments in a different environment with a learning rate between -1 and +1. Also, using the number of techniques to evaluate the number of parameters, true positive cases are represent and fall into positive cases in this example to evaluate the proposed model
Volume: 20
Issue: 3
Page: 1507-1512
Publish at: 2020-12-01

Evaluation of leachate turbidity reduction in sanitary landfills following a coagulation/flocculation process enhanced by vegetable starch and thermal water

10.12928/telkomnika.v18i6.16150
César; Universidad Católica de Manizales Benavides , Sebastian; Universidad Católica de Manizales Pacheco , Yeison Alberto Garcés; Universidad Católica de Manizales Gómez , Fredy Edimer; Universidad Nacional de Colombia Hoyos
This study evaluates the reduction of leachate turbidity in landfills after applying a mixture of banana starch and thermal water. Principal component analysis was applied to study the combined effect with four variables: pH, concentration of starch and thermal water mixture, rapid mixing speed and slow mixing speed. The experimental design involved 16 experiments with repetition in the jar test to obtain the optimum dose while measuring turbidity as a response variable. The results showed that after the oxidation process of organic matter, under optimal conditions determined in the experiment, the mixture of starch and thermal water contributed to the reduction of leachate turbidity by 29.1%.
Volume: 18
Issue: 6
Page: 2962-2969
Publish at: 2020-12-01

The simulation analysis of torque ripple reduction by using optimal voltage vector in DTC fed by five-level CHB inverter

10.11591/ijeecs.v20.i3.pp1665-1676
Siti Azura Binti Ahmad Tarusan , Auzani Jidin , Mohd Luqman M. Jamil
In this paper, the improvement of torque ripple reduction will be focused based on the optimal voltage vector. This is attained by using five-level CHB inverter that applies in DTC drive control as a proposed method. The analysis is performed and simulated by using MATLAB/Simulink. In order to support the analysis, the comparison is realized between proposed method and conventional method which it applies two-level inverter. It will be analysed at constant torque region or steady-state operation on different range of operating speed which the speed is controlled by adjusting the motor load. Meaning that, the speed controller is neglected during analysis. Nevertheless, the adjustment of motor load must be applicable to the optimal voltage vector. The look-up table of five-level CHB inverter will become a guideline to select the optimal voltage vector. Therefore, it can maintain the simple structure of DTC hysteresis-based that fed by using five-level CHB inverter. As a result, the torque ripple can be minimized and torque capability can be retained even at low operating speed compared to the conventional DTC.
Volume: 20
Issue: 3
Page: 1665-1676
Publish at: 2020-12-01

Recognizing emotional state of user based on learning method and conceptual memories

10.12928/telkomnika.v18i6.16756
Maytham N.; Razi University Meqdad , Fardin; Razi University Abdali-Mohammadi , Seifedine; Beirut Arab University Kadry
With the increased use of computers, electronic devices and human interaction with computer in the broad spectrum of human life, the role of controlling emotions and increasing positive emotional states becomes more prominent. If a user's negative emotions increase, his/her efficiency will decrease greatly as well. Research has shown that colors are to be considered as one of the most influential basic functions in sight, identification, interpretation, perception and senses. It can be said that colors have impact on individuals' emotional states and can change them. In this paper, by learning the reactions of users with different personality types against each color, communication between the user's emotional states and personality and colors were modeled for the variable "emotional control". For the sake of learning, we used a memory-based system with the user’s interface color changing in accordance with the positive and negative experiences of users with different personalities. The end result of comparison of the testing methods demonstrated the superiority of memory-based learning in all three parameters of emotional control, enhancement of positive emotional states and reduction of negative emotional states. Moreover, the accuracy of memory- based learning method was almost 70 percent.
Volume: 18
Issue: 6
Page: 3033-3040
Publish at: 2020-12-01

An effective identification of crop diseases using faster region based convolutional neural network and expert systems

10.11591/ijece.v10i6.pp6531-6540
P. Chandana , G. S. Pradeep Ghantasala , J. Rethna Virgil Jeny , Kaushik Sekaran , Deepika N. , Yunyoung Nam , Seifedine Kadry
The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop.
Volume: 10
Issue: 6
Page: 6531-6540
Publish at: 2020-12-01

Strategies for use, treatment, management and final disposition of wastes in academic laboratories

10.12928/telkomnika.v18i6.14506
Vladimir Gaviria; Institución Universitaria Colegio Mayor de Antioquia González , Fredy Edimer Hoyos; Universidad Nacional de Colombia Velasco , John E.; Universidad Nacional de Colombia Candelo-Becerra
Laboratory higher education institutions can generate a wide range of wastes,many of which have hazardous characteristics. The uncontrolled accumulation of such wastes also has a significant impact on the environment, safety and health of the academic community. This work formulates strategies that allow the development of integrated solutions to mitigate the latent risk for the community at Institución Universitaria Colegio Mayor de Antioquia,Colombia, and its surroundings. Therefore, it is considered to quantify the generation of waste in the units of analysis of different experimental spacesand evaluate the factors involved in the implementation of strategies for diagnosis, waste recovery, treatment, and final disposition. Based on the diagnosis and characterization of wastes, alternatives are evaluated that help to prevent and, in other cases, mitigate the impacts that they can cause, in order to consolidate a protocol for waste management. Hazardous waste disposition strategies, treatment mechanisms and minimization strategies, such as microchemistry, precipitation recycling, encapsulation and immobilization methods, evaporation as well as solvent recovery, have been implemented.
Volume: 18
Issue: 6
Page: 3130-3141
Publish at: 2020-12-01

A novel pooling layer based on gaussian function with wavelet transform

10.11591/ijeecs.v20.i3.pp1289-1298
Aqeel M. Hamad alhussainy , Ammar D. Jasim
Convolution represent basic layer in the convolutional neural network, but it can result in big size of the data, which may increase the complexity of the network. Different pooling methods are used to perform down sample these data. In this paper, we have proposed a novel pooling method by using Gaussian function to determine the wavelet filter coefficients. At first, the basic statistics are determined for each pool size of the signal, then Gaussian probability distribution function is determined. According to the procedure of extracting the features, three methods are proposed, the first method is used the normalized values of basic statistics as wavelet filter to be multiplied by original signal, the second method used the determined statistics as features of the original signal, then multiplied it with constant wavelet filter based on Gaussian, while the third method is similar to first method, except it depend on entire signal instead of each pool size. The proposed methods are combined with other standard methods such as max and pooling. The experiments are performed on different datasets and the results show that the proposed methods perform or outperform other methods and can increase performance of the (CNN).
Volume: 20
Issue: 3
Page: 1289-1298
Publish at: 2020-12-01

Fuzzy logic control of hybrid systems including renewable energy in microgrids

10.11591/ijece.v10i6.pp5559-5569
Omar Feddaoui , Riad Toufouti , Labed Jamel , Salima Meziane
With a growing demand for more energy from subscribers, a traditional electric grid is unable to meet new challenges, in the remote areas remains the extension of the conventional electric network very hard to do make prohibitively expensive. Therefore, a new advanced generation of traditional electrical is inevitable and indispensable to move toward an efficient, economical, green, clean and self-correcting power system. The most well-known term used to define this next generation power system is Micro Grid (MG) based on renewable energy sources (RES). Since, the energy produced by RES are not constant at all times, a wide range of energy control techniques must be involved to provide a reliable power to consumers. To solve this problem in this paper we present a Fuzzy Logic Control of isolated Hybrid Systems (HRES) Including Renewable Energy in Micro-Grids to maintain a stability in voltage and frequency output especially in the standalone application. The considered HRES combine a wind turbine (WT) and photovoltaic (PV) panels as primary energy sources and an energy storage system (ESS) based on battery as a backup solution. Simulation results obtained from MATLAB/Simulink environment demonstrate the effectiveness of the proposed algorithm in decreasing the electricity bill of customer.
Volume: 10
Issue: 6
Page: 5559-5569
Publish at: 2020-12-01

Business students’ perspectives: What makes successful group performance?

10.11591/ijere.v9i4.20534
Rinny Cherill Rantung , Reggy Nelson Sarmita
Purpose of this study was to identify factors contributing to the successful group performance from the perspective of business students. The in-depth interview was done followed by a survey derived forty-five items variables, after some tests 21 items variables removed due to low item remainder coefficient resulted in 24 items questionnaires. A total of 355 respondents participated during the survey. Exploratory factor analysis with principal factor extraction was performed and five contributing factors were extracted. Those factors are cohesiveness, inter-relationship, norms, diversity and appointed of team leader.
Volume: 9
Issue: 4
Page: 896-902
Publish at: 2020-12-01

An improved swarm intelligence algorithms-based nonlinear fractional order-PID controller for a trajectory tracking of underwater vehicles

10.12928/telkomnika.v18i6.16282
Mustafa Wassef; university of Baghdad Hasan , Nizar Hadi; university of Baghdad Abbas
This paper presents a nonlinear fractional order proportional integral derivative (NL-FOPID) for autonomous underwater vehicle (AUV) to solve the path tracking problem under the unknown disturbances (model uncertainty or external disturbances). The considered controller schemes are tuned by two improved swarm intelligence optimization algorithms, the first on is the hybrid grey wolf optimization with simulated annealing (HGWO-SA) algorithm and an improved whale optimization algorithm (IWOA). The developed algorithms are assessed using a set of benchmark function (unimodal, multimodal, and fixed dimension multimodal functions) to guarantee the effectiveness of both proposed swarm algorithms. The HGWO-SA algorithm is used as a tuning method for the AUV system controlled by NL-FOPID scheme, and the IWOA is used as a tuning algorithm to obtain the PID controller’s parameters. The evaluation results show that the HGWO-SA algorithm improved the minimal point of the tested benchmark functions by 1-200 order, while the IWOA improved the minimum point by (1-50) order. Finally, the obtained simulation results from the system operated with NL-FOPID shows the competence in terms of the path tracking by 1-15% as compared to the PID method.
Volume: 18
Issue: 6
Page: 3173-3183
Publish at: 2020-12-01

Prediction of atmospheric pollution using neural networks model of fine particles in the town of Kennedy in Bogota

10.11591/ijece.v10i6.pp6574-6581
Juan Camilo Pedraza , Oswaldo Alberto Romero , Helbert Eduardo Espitia
This work shows an application based on neural networks to determine the prediction of air pollution, especially particulate material of 2.5 micrometers length. This application is considered of great importance due to the impact on human health and high impact due to the agglomeration of people in cities. The implementation is performed using data captured from several devices that can be installed in specific locations for a particular geographical environment, especially in the locality of Kennedy in Bogotá. The model obtained can be used for the design of public policies that control air quality.
Volume: 10
Issue: 6
Page: 6574-6581
Publish at: 2020-12-01

Stability and chaos with mathematical control of 4-D dynamical system

10.11591/ijeecs.v20.i3.pp1242-1251
Maysoon Mal-Allah Aziz , Dalya M. Merie
A new four-dimensional continuous-time system is dealt in this paper. The system employs eight simple terms involving two quadratic cross-product nonlinear terms. The fundamental characteristics of the system are analyzed by means of equilibrium points, stability analysis, dissipativity, wave form analysis, Lapiynuov Exponents and Kaplan-Yorke dimension. The maximum value of Lapiynuov exponent is obtain as (1.660748) andKaplan Yorke dimension obtain as (), that show the system is unstable and highly chaotic. As well, an optimal controller by adaptive control strategy is established to be system trajectories are stable. Finally, Adaptive synchronization of system (1) is clarified. Tables are made to compare the theoretical and graphical results of the system before and after control.
Volume: 20
Issue: 3
Page: 1242-1251
Publish at: 2020-12-01

Potentials of solar power plant in Waru Tua

10.12928/telkomnika.v18i6.15763
Ain; Sekolah Tinggi Teknologi Minyak dan Gas Bumi Balikpapan Sahara , Riza Hadi; Sekolah Tinggi Teknologi Minyak dan Gas Bumi Balikpapan Saputra , A. M. Miftahul; Sekolah Tinggi Teknologi Minyak dan Gas Bumi Balikpapan Huda
Penajam Paser Utara Regency is located on the coast of East Kalimantan Province. This regency has a huge solar resource potential, but the agreement in this regency still lacks electricity networks and can be resolved by the people in this regency still in dire need of electricity for street lighting, and daily electricity needs. One of them is in the village of Waru Tua, where this area is in great need of lighting in the dock area because it requires residents to make Aliving as a fisherman. Waru Tua really needs electricity for lighting at night Waru Tua Pier because it has to be a gathering place for residents before going to sea to prepare everything that must be prepared before going to sea. Discussing the research carried out examining the potential of solar power in Waru Tua. Based on existing considerations, and the potential proposed by the area, the method used is to measure the sunlight at Waru Tua Pier using Luxmeter, then the data is processed using the Simulink applicationin MATLAB to obtain the value of the amount of sunlight in the area, which is 16 KW with a total solar cell of 250 Wp.
Volume: 18
Issue: 6
Page: 3266-3275
Publish at: 2020-12-01

Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic hill climbing

10.11591/ijece.v10i6.pp5965-5973
Mr. Raghavendra Y. M. , Dr. U. B. Mahadevaswamy
In Wireless Sensor Networks (WSNs), the reduction of energy consumption in the batteries of a sensor node is an important task. Sensor nodes of WSNs perform three significant functions such as data sensing, data transmitting and data relaying. Routing technique is one of the methods to enhance the sensor nodes battery lifetime. Energy optimization is done by using one of the heuristic routing methods for sensing and transmitting the data. To enhance the energy optimization mainly concentrated on data relaying. In this work stochastic hill climbing is adapted. The proposed solution for data relaying utilizes geographical routing and mobile sink technique. The sink collects the data from cluster heads and movement of the sink is routed by stochastic hill climbing. Network simulator 2 is used for experimentation purpose. This work also compares with the existing routing protocols like Energy-efficient Low Duty Cycle (ELDC), Threshold sensitive Energy Efficient sensor Network (TEEN) and Adaptive clustering protocol. The proposed work shows promising results with respect to lifetime, average energy of nodes and packet delivery ratio.
Volume: 10
Issue: 6
Page: 5965-5973
Publish at: 2020-12-01
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