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29,939 Article Results

The optimal solution for unit commitment problem using binary hybrid grey wolf optimizer

10.11591/ijece.v12i1.pp122-130
Ali Iqbal Abbas , Afaneen Anwer
The aim of this work is to solve the unit commitment (UC) problem in power systems by calculating minimum production cost for the power generation and finding the best distribution of the generation among the units (units scheduling) using binary grey wolf optimizer based on particle swarm optimization (BGWOPSO) algorithm. The minimum production cost calculating is based on using the quadratic programming method and represents the global solution that must be arriving by the BGWOPSO algorithm then appearing units status (on or off). The suggested method was applied on “39 bus IEEE test systems”, the simulation results show the effectiveness of the suggested method over other algorithms in terms of minimizing of production cost and suggesting excellent scheduling of units.
Volume: 12
Issue: 1
Page: 122-130
Publish at: 2022-02-01

Performance evaluation of ad-hoc on-demand distance vector protocol in highway environment in VANET with MATLAB

10.12928/telkomnika.v20i1.20876
Osama A.; Northern Technical University Qasim , Mohammed Sami; Northern Technical University Noori , Mohand Lokman; Northern Technical University Ahmad Al Dabag
Vehicular ad-hoc network (VANET), the development of this network in recent years has become one of the most important areas of research. The primary goal of using the VANET network is to reduce the number of deaths and enhance road safety. VANET network faces some problems when routing packets between vehicles, due to the high-speed movement of vehicles. Therefore, researchers have begun to develop routing protocols in the VANET network to overcome these problems when routing packets between vehicles. In this study, the effect of changing the number of vehicles on the performance of ad-hoc on-demand distance vector (AODV) protocol will be studied in the highway environment and in the case of vehicle movement at variable speeds between (40-120 km/h) and the simulation time is 200 sec. The ad-hoc ondemand distance vector protocol performance was evaluated by three performance measures (end-to-end delay, dropped packets, overhead and packet delivery ratio).
Volume: 20
Issue: 1
Page: 194-200
Publish at: 2022-02-01

Sierpinski carpet fractal monopole antenna for ultra-wideband applications

10.11591/ijece.v12i1.pp983-996
Medhal Bharathraj Kumar , Praveen Jayappa
Microstrip antenna is broadly used in the modern communication system due to its significant features such as light weight, inexpensive, low profile, and ease of integration with radio frequency devices. The fractal shape is applied in antenna geometry to obtain the ultra-wideband antennas. In this paper, the sierpinski carpet fractal monopole antenna (SCFMA) is developed for base case, first iteration and second iteration to obtain the wideband based on its space filling and self-similar characteristics. The dimension of the monopole patch size is optimized to minimize the overall dimension of the fractal antenna. Moreover, the optimized planar structure is proposed using the microstrip line feed. The monopole antenna is mounted on the FR4 substrate with the thickness of 1.6 mm with loss tangent of 0.02 and relative permittivity of 4.4. The performance of this SCFMA is analyzed in terms of area, bandwidth, return loss, voltage standing wave ratio, radiation pattern and gain. The proposed fractal antenna achieves three different bandwidth ranges such as 2.6-4.0 GHz, 2.5-4.3 GHz and 2.4-4.4 GHz for base case, first and second iteration respectively. The proposed SCFMA is compared with existing fractal antennas to prove the efficiency of the SCFMA design. The area of the SCFMA is 25×20 mm2, which is less when compared to the existing fractal antennas.
Volume: 12
Issue: 1
Page: 983-996
Publish at: 2022-02-01

Thriving information system through business intelligence knowledge management excellence framework

10.11591/ijece.v12i1.pp506-514
Abdul Karim Mohamad , Mailasan Jayakrishnan , Mokhtar Mohd Yusof
In the current digitalization dilemma of an organization, there is a need for the business intelligence and knowledge management element for enhancing a perspective of learning and strategic management. These elements will comprise a significant evolution of learning, insight gained, experiences and knowledge through compelling theoretical impact for practitioners, academicians, and scholars in the pertinent field of interest. This phenomenon occurs due to digitalization transformation towards industry revolution 5.0 and organizational excellence in the information system area. This research focuses on the characteristic of a comprehensive performance measure perspective in an organization that conceives information assessment and key challenges of Business Intelligence and Knowledge Management in perceiving a relevant organizational excellence framework. The dynamic research focusing on the decision-making process and leveraging better knowledge creation. The future of organization excellence seemed to be convergent in determining the holistic performance measure perspective and its factors towards industry revolution 5.0. The research ends up with a typical basic excellence framework that will mash up some characteristics in designing an organizational strategic performance framework. The output is a conceptual performance measure framework for a typical decision-making application for organizational strategic performance management dashboarding.
Volume: 12
Issue: 1
Page: 506-514
Publish at: 2022-02-01

Amateur radio sensing technique using a combination of energy detection and waveform classification

10.11591/ijece.v12i1.pp399-410
Narathep Phruksahiran
A critical problem in spectrum sensing is to create a detection algorithm and test statistics. The existing approaches employ the energy level of each channel of interest. However, this feature cannot accurately characterize the actual application of public amateur radio. The transmitted signal is not continuous and may consist only of a carrier frequency without information. This paper proposes a novel energy detection and waveform feature classification (EDWC) algorithm to detect speech signals in public frequency bands based on energy detection and supervised machine learning. The energy level, descriptive statistics, and spectral measurements of radio channels are treated as feature vectors and classifiers to determine whether the signal is speech or noise. The algorithm is validated using actual frequency modulation (FM) broadcasting and public amateur signals. The proposed EDWC algorithm's performance is evaluated in terms of training duration, classification time, and receiver operating characteristic. The simulation and experimental outcomes show that the EDWC can distinguish and classify waveform characteristics for spectrum sensing purposes, particularly for the public amateur use case. The novel technical results can detect and classify public radio frequency signals as voice signals for speech communication or just noise, which is essential and can be applied in security aspects.
Volume: 12
Issue: 1
Page: 399-410
Publish at: 2022-02-01

Misalignment fading effects on the ACC performance of relay-assisted MIMO/FSO systems over atmospheric turbulence channels

10.11591/ijece.v12i1.pp966-973
Huu Ai Duong , Van Loi Nguyen , Khanh Ty Luong
The continuous development of internet of things (IoT) technology enables many devices to be interconnected through the external environment. Meanwhile, 5G technology provides an enhanced quality of services with high data transmission rates, requiring IoT implementation in the 5G architecture. Free-space optical communication (FSO) is considered a promising technique that can provide high-speed communication links, so FSO is an optimal choice for wireless networks to fulfill the full potential of 5G technology, providing speeds of 100 Gb/s or more. By implementing 5G features in IoT, IoT coverage and performance will be enhanced by using FSO models. Therefore, the paper proposed and investigated the multiple-input and multiple-output/free-space optical communication (MIMO/FSO) model using subcarrier quadrature amplitude modulation (SC-QAM) and relay stations over atmospheric turbulence channels by log-normal and gamma-gamma distribution under different turbulence conditions. The performance is examined based on the average channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE) parameters while changing the different parameters of the model. The mathematical formulas of ACC for atmospheric turbulence cases are calculated and discussed the influence of turbulence strength, the different number of relay stations, misalignment effects, and different MIMO configurations.
Volume: 12
Issue: 1
Page: 966-973
Publish at: 2022-02-01

Characteristic's analysis of associative switching system

10.12928/telkomnika.v20i1.17640
Svetlana A; Tashkent University of Information Technologies, Republic of Uzbekistan Sadchikova , Mubarak; Tashkent University of Information Technologies, Republic of Uzbekistan Abdujapparova
This paper introduced new method and model of telecommunication switching system design which can be applied to wavelength-division multiplexing (WDM) optical networks, circuit-switching networks or virtual channel/path connections in an asynchronous transfer mode (ATM) networks. Modern data switching systems such as electronic private branch exchange (PBX), routers and switches include switching matrix which are constructed in the form of bipartite graphs. In such systems, the issues of requests’ processing are considered from the queuing theory point of view. Associative switching systems are fundamentally new structures, therefore it is necessary to develop adequate methods for their throughput determination. Article covered matters of throughput determination basics of an associative switching system and the obtained formulas used for state probability calculation of switching modules and system throughput.
Volume: 20
Issue: 1
Page: 27-33
Publish at: 2022-02-01

Exploiting performance gap among two users in reconfigurable intelligent surfaces-aided wireless systems

10.12928/telkomnika.v20i1.19001
Dinh-Thuan; Industrial University of Ho Chi Minh City Do , Chi-Bao; Industrial University of Ho Chi Minh City Le
In this work, we study the outage performance of a reconfigurable intelligent surfaces (RIS)-aided wireless systems in the presence of non-orthogonal multiple access (NOMA). In particular, different power factors are allocated to users which belong a dedicated group. We derive exact outage probability of two users in a group. Specifically, it is assumed that the RIS is placed between the source and the users and far user has better performance under assistance of RIS. We also provide comparison analysis to investigate the effect of the main parameters on the outage performance of our proposed system, such as the number of tunable elements of the RIS, power allocation factors, target rates and the average signal-to-noise ratio at the base station. If we set small tunable elements for RIS, we can obtain the best performance. By using MonteCarlo simulation, we verify our analytical results via simulations. Our main results reported in this paper show the positive effect once we deploy RISs for guaranteeing fairness among NOMA users in wireless systems.
Volume: 20
Issue: 1
Page: 1-8
Publish at: 2022-02-01

Radial radio number of chess board graph and king’s graph

10.12928/telkomnika.v20i1.19493
Kulandaivel Maruthamuthu; Mathematics Section, Department of Information Technology, University of Technology and Applied Sciences-Al Mussanah, Sultanate of Oman. Paramasivam , Kins; Assistant Professor, PG and Research Department of Mathematics, Loyola College (Autonomous), Chennai, Tamilnadu, India. Yenoke , Baby Smitha Kanaka; Assistant Professor, Department of Mathematics, Devas-wom Board College, Thalayolaparambu, Kottayam, Kerala, India. Muralidharan
A radial radio labeling ℸ of a connected graph G = (V, E) with radius rad(G) is a mapping from V (G) to N ∪ {0} satisfying |ℸ(u) − ℸ(w)|+ d(u, w) ≥ 1 + rad(G), ∀ u, v ∈ V (G). The span of a radial radio labeling ℸ, denoted by rr(ℸ) is the greatest number in the range of ℸ. The minimum span taken over all radial radio labelings ℸ of G is called the radial radio nmber of G and it is denoted by rr(G). In this article, we have investigated the upper bounds for rr(G) of chess board graphs and king’s graph.
Volume: 20
Issue: 1
Page: 9-18
Publish at: 2022-02-01

Hybrid bypass technique to mitigate leakage current in the grid-tied inverter

10.11591/ijece.v12i1.pp131-140
Geetha Kamurthy , Sreenivasappa Bhupasandra Veeranna
The extensive use of fossil fuel is destroying the balance of nature that could lead to many problems in the forthcoming era. Renewable energy resources are a ray of hope to avoid possible destruction. Smart grid and distributed power generation systems are now mainly built with the help of renewable energy resources. The integration of renewable energy production system with the smart grid and distributed power generation is facing many challenges that include addressing the issue of isolation and power quality. This paper presents a new approach to address the aforementioned issues by proposing a hybrid bypass technique concept to improve the overall performance of the grid-tied inverter in solar power generation. The topology with the proposed technique is presented using traditional H5, oH5 and H6 inverter. Comparison of topologies with literature is carried out to check the feasibility of the method proposed. It is found that the leakage current of all the proposed inverters is 9 mA and total harmonic distortion is almost about 2%. The proposed topology has good efficiency, common mode and differential mode characteristics.
Volume: 12
Issue: 1
Page: 131-140
Publish at: 2022-02-01

Deep segmentation of the liver and the hepatic tumors from abdomen tomography images

10.11591/ijece.v12i1.pp303-310
Nermeen Elmenabawy , Mervat El-Seddek , Hossam El-Din Moustafa , Ahmed Elnakib
A pipelined framework is proposed for accurate, automated, simultaneous segmentation of the liver as well as the hepatic tumors from computed tomography (CT) images. The introduced framework composed of three pipelined levels. First, two different transfers deep convolutional neural networks (CNN) are applied to get high-level compact features of CT images. Second, a pixel-wise classifier is used to obtain two output-classified maps for each CNN model. Finally, a fusion neural network (FNN) is used to integrate the two maps. Experimentations performed on the MICCAI’2017 database of the liver tumor segmentation (LITS) challenge, result in a dice similarity coefficient (DSC) of 93.5% for the segmentation of the liver and of 74.40% for the segmentation of the lesion, using a 5-fold cross-validation scheme. Comparative results with the state-of-the-art techniques on the same data show the competing performance of the proposed framework for simultaneous liver and tumor segmentation.
Volume: 12
Issue: 1
Page: 303-310
Publish at: 2022-02-01

Determinants of e-learning adoption in higher education in Iraq an academics and students’ perspective

10.12928/telkomnika.v20i1.21550
Soreen Ameen; University of Babylon Fattah , Ayad Hameed; University of Kerbala Mousa , Mowafak; University of Kerbala K. Mohsen , Shahad Dakhil; University of Kerbala Khalaf , Seham Hameed; University of Kerbala Mousa
E-learning allows the students to access, repeat and use the scientific materials wherever and whenever the users want. Both academics and learners are the leading and essential actors in the process of the learning process. Moreover, the acceptance of a technology is the positive react for users by using such technology. Due to the COVID-19 pandemic, e-learning has become mandatory over the world, thus, there is a necessity to investigate the determinants of e-learning adoption in higher education institutions (HEIs) in Iraq. Consequently, this paper aims to investigate elearning adoption and identify the determinants of e-learning in HEIs. An instrument was developed with eight dimensions based on technology organization and environmental (TOE) elements. The sample selection was of 580 students and 130 university lecturers who spread over several colleges. A clustering sampling method was used in the sampling selection process. Some hypotheses were proposed and tested via the paired T-test tool. To evaluate the relationship between the TOE variables and e-learning adoption, a regression analysis was carried out. The study findings classified into two categories, first, it helps to determine to what extent e-learning be adopted. Second, it provides meaningful guidance for higher education institutions that should follow as a pre-requested before adopting e-learning
Volume: 20
Issue: 1
Page: 201-211
Publish at: 2022-02-01

Decentralised optimal deployment of mobile underwater sensors for covering layers of the ocean

10.11591/ijeecs.v25.i2.pp840-846
Valimohammad Nazarzehi , Rasoul Damani
This paper presents the problem of sensing coverage of layers of the ocean in three dimensional underwater environments. We propose distributed control laws to drive mobile underwater sensors to optimally cover a given confined layer of the ocean. By applying this algorithm at first the mobile underwater sensors adjust their depth to the specified depth. Then, they make a triangular grid across a given area. Afterwards, they randomly move to spread across the given grid. These control laws only rely on local information also they are easily implemented and computationally effective as they use some easy consensus rules. The feature of exchanging information just among neighbouring mobile sensors keeps the information exchange minimum in the whole networks and makes this algorithm practicable option for undersea. The efficiency of the presented control laws is confirmed via mathematical proof and numerical simulations.
Volume: 25
Issue: 2
Page: 840-846
Publish at: 2022-02-01

Classification of chest X-ray images using a hybrid deep learning method

10.11591/ijeecs.v25.i2.pp867-874
Panida Songram , Chatklaw Jareanpon , Phatthanaphong Chomphuwiset , Khanabhorn Kawattikul , Chatklaw Jareanpon
This work presents a technique for classifying X-ray images of the chest (CXR) by applying deep learning-based techniques. The CXR will be classified into three different types, i.e. (i) normal, (ii) COVID-19, and (iii) pneumonia. The classification challenge is raised when the X-ray images of COVID-19 and pneumonia are subtle. The CXR images of the chest are first proceeded to be standardized and to improve the visual contrast of the images. Then, the classification is performed by applying a deep learningbased technique that binds two deep learning network architectures, i.e., convolution neural network (CNN) and long short-term memory (LSTM), to generate a hybrid model for the classification problem. The deep features of the images are extracted by CNN before the final classification is performed using LSTM. In addition to the hybrid models, this work explores the validity of image pre-processing methods that improve the quality of the images before the classification is performed. The experiments were conducted on a public image dataset. The experimental results demonstrate that the proposed technique provides promising results and is superior to the baseline techniques.
Volume: 25
Issue: 2
Page: 867-874
Publish at: 2022-02-01

Control of a servo-hydraulic system utilizing an extended wavelet functional link neural network based on sine cosine algorithms

10.11591/ijeecs.v25.i2.pp847-856
Shaymaa Mahmood Mahdi , Omar Farouq Lutfy
Servo-hydraulic systems have been extensively employed in various industrial applications. However, these systems are characterized by their highly complex and nonlinear dynamics, which complicates the control design stage of such systems. In this paper, an extended wavelet functional link neural network (EWFLNN) is proposed to control the displacement response of the servo-hydraulic system. To optimize the controller's parameters, a recently developed optimization technique, which is called the modified sine cosine algorithm (M-SCA), is exploited as the training method. The proposed controller has achieved remarkable results in terms of tracking two different displacement signals and handling external disturbances. From a comparative study, the proposed EWFLNN controller has attained the best control precision compared with those of other controllers, namely, a proportional-integralderivative (PID) controller, an artificial neural network (ANN) controller, a wavelet neural network (WNN) controller, and the original wavelet functional link neural network (WFLNN) controller. Moreover, compared to the genetic algorithm (GA) and the original sine cosine algorithm (SCA), the M-SCA has shown better optimization results in finding the optimal values of the controller's parameters.
Volume: 25
Issue: 2
Page: 847-856
Publish at: 2022-02-01
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