Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

29,939 Article Results

Mitigation of packet loss with end-to-end delay in wireless body area network applications

10.11591/ijece.v12i1.pp460-470
Suha Sahib Oleiwi , Ghassan N. Mohammed , Israa Al_Barazanchi
The wireless body area network (WBAN) has been proposed to offer a solution to the problem of population ageing, shortage in medical facilities and different chronic diseases. The development of this technology has been further fueled by the demand for real-time application for monitoring these cases in networks. The integrity of communication is constrained by the loss of packets during communication affecting the reliability of WBAN. Mitigating the loss of packets and ensuring the performance of the network is a challenging task that has sparked numerous studies over the years. The WBAN technology as a problem of reducing network lifetime; thus, in this paper, we utilize cooperative routing protocol (CRP) to improve package delivery via end-to-end latency and increase the length of the network lifetime. The end-to-end latency was used as a metric to determine the significance of CRP in WBAN routing protocols. The CRP increased the rate of transmission of packets to the sink and mitigate packet loss. The proposed solution has shown that the end-to-end delay in the WBAN is considerably reduced by applying the cooperative routing protocol. The CRP technique attained a delivery ratio of 0.8176 compared to 0.8118 when transmitting packets in WBAN.
Volume: 12
Issue: 1
Page: 460-470
Publish at: 2022-02-01

Design of multiple-input and multiple-output antenna for modern wireless applications

10.12928/telkomnika.v20i1.19355
Karrar Shakir; Department of Computer Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq Muttair , Oras Ahmed; Department of Computer Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq Shareef , Ahmed Mohammed Ahmed; Department of Electronics Engineering, College of Electronics Engineering, Ninevah University, Mosul, Iraq Sabaawi , Mahmood Farhan; Department of Computer Engineering Techniques, Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq Mosleh
In this paper, multiple-input and multiple-output (MIMO) antennas are designed and simulated. The designed antennas are compact double-sided printed microstrip patch antennas and fed by a microstrip line. These antennas are designed for 3.5 to 10 GHz frequencies used for medical, industrial, sciences, and various fields of 5G communications and networking applications. Furthermore, a MIMO system is designed using the polarization variability of the individual antennas, which yields better results in terms of mutual coupling (S12 and S21), reflection coefficient (S11 and S22), and voltage standing wave ratio (VSWR), which is less than 2 indicate improved matching conditions. The designed antennas showed an acceptable gain (around 2 dB) and an envelope correlation coefficient (ECC) is <0.002. In addition, the proposed MIMO antennas exhibited isolation is -25 dB at 6 GHz, which is preferable in 5G mobile antennas.
Volume: 20
Issue: 1
Page: 34-42
Publish at: 2022-02-01

An optimum location of on-grid bifacial based photovoltaic system in Iraq

10.11591/ijece.v12i1.pp250-261
Amina Mahmoud Shakir , Siba Monther Yousif , Anas Lateef Mahmood
Bifacial photovoltaic (PV) module can gain 30% more energy compared to monofacial if a suitable location were chosen. Iraq (a Middle East country) has a variable irradiation level according to its geographic coordinates, thus, the performance of PV systems differs. This paper an array (17 series, 13 parallel) was chosen to produce 100 kWp for an on-grid PV system. It investigates the PV system in three cities in Iraq (Mosul, Baghdad, and Basrah). Effect of albedo factor, high and pitch of the bifacial module on energy yield have been studied using PVsyst (software). It has been found that the effect is less for a pitch greater than 6 m. The energy gained from bifacial and monofacial PV system module in these cities shows that Mosul is the most suitable for installing both PV systems followed by Baghdad and lastly Basrah. However, in Basrah, the bifacial gain is 12% higher in the energy than monofacial as irradiation there is higher than the other locations, especially for elevation above 1.5 m. Moreover, the cost of bifacial array is 7.23% higher than monofacial, but this additional cost is acceptable since the bifacial gain is about 11.3% higher energy compared to the monofacial.
Volume: 12
Issue: 1
Page: 250-261
Publish at: 2022-02-01

Solution for intra/inter-cluster event-reporting problem in cluster-based protocols for wireless sensor networks

10.11591/ijece.v12i1.pp868-879
Raed Taleb Al-Zubi , Abdulraheem Ahmed Kreishan , Mohammad Qasem Alawad , Khalid Ahmad Darabkh
In recent years, wireless sensor networks (WSNs) have been considered one of the important topics for researchers due to their wide applications in our life. Several researches have been conducted to improve WSNs performance and solve their issues. One of these issues is the energy limitation in WSNs since the source of energy in most WSNs is the battery. Accordingly, various protocols and techniques have been proposed with the intention of reducing power consumption of WSNs and lengthen their lifetime. Cluster-oriented routing protocols are one of the most effective categories of these protocols. In this article, we consider a major issue affecting the performance of this category of protocols, which we call the intra/inter-cluster event-reporting problem (IICERP). We demonstrate that IICERP severely reduces the performance of a cluster-oriented routing protocol, so we suggest an effective Solution for IICERP (SIICERP). To assess SIICERP’s performance, comprehensive simulations were performed to demonstrate the performance of several cluster-oriented protocols without and with SIICERP. Simulation results revealed that SIICERP substantially increases the performance of cluster-oriented routing protocols.
Volume: 12
Issue: 1
Page: 868-879
Publish at: 2022-02-01

Hybrid scheduling algorithms in cloud computing: a review

10.11591/ijece.v12i1.pp880-895
Neeraj Arora , Rohitash Kumar Banyal
Cloud computing is one of the emerging fields in computer science due to its several advancements like on-demand processing, resource sharing, and pay per use. There are several cloud computing issues like security, quality of service (QoS) management, data center energy consumption, and scaling. Scheduling is one of the several challenging problems in cloud computing, where several tasks need to be assigned to resources to optimize the quality of service parameters. Scheduling is a well-known NP-hard problem in cloud computing. This will require a suitable scheduling algorithm. Several heuristics and meta-heuristics algorithms were proposed for scheduling the user's task to the resources available in cloud computing in an optimal way. Hybrid scheduling algorithms have become popular in cloud computing. In this paper, we reviewed the hybrid algorithms, which are the combinations of two or more algorithms, used for scheduling in cloud computing. The basic idea behind the hybridization of the algorithm is to take useful features of the used algorithms. This article also classifies the hybrid algorithms and analyzes their objectives, quality of service (QoS) parameters, and future directions for hybrid scheduling algorithms.
Volume: 12
Issue: 1
Page: 880-895
Publish at: 2022-02-01

Design and simulation of a software defined networking-enabled smart switch for internet of things-based smart grid

10.11591/ijeecs.v25.i2.pp780-787
Mustafa Abdulkadhim , Noor Qusay Abdulmuhsen , Aymen M. Al-Kadhimi
Using sustainable energy is the future of our planet earth, this became not only economically efficient but also a necessity for the preservation of life on earth. Because of such necessity, smart grids became a very important issue to be researched. Many literatures discussed this topic and with the development of internet of things (IoT) and smart sensors, smart grids are developed even further. On the other hand, software defined networking is a technology that separates the cntrol plane from the data plan of the network. It centralizes the management and the orchestration of the network tasks by using a network controller. The network controller is the heart of the SDN-enabled network, and it can control other networking devices using software defined networking (SDN) protocols such as OpenFlow. A smart switching mechanism called (SDN-smgrid-sw) for the smart grid will be modeled and controlled using SDN. We modeled the environment that interact with the sensors, for the sun and the wind elements. The Algorithm is modeled and programmed for smart efficient power sharing that is managed centrally and monitored using SDN controller. Also, all if the smart grid elements (power sources) are connected to the IP network using IoT protocols.
Volume: 25
Issue: 2
Page: 780-787
Publish at: 2022-02-01

Determination of optimum load resistances of MQ-series gas sensor circuit for specific gas concentrations

10.12928/telkomnika.v20i1.21091
Ajiboye Aye; Department of Computer Engineering, University of Ilorin, Ilorin, Nigeria. Taiwo , Opadiji Jayeola Femi Jayeola; Department of Computer Engineering, University of Ilorin, Ilorin, Nigeria. Femi , Ajayi Adebimpe; Department of Computer Engineering, University of Ilorin, Ilorin, Nigeria. Ruth , Popoola Joshua; Department of Computer Engineering, University of Ilorin, Ilorin, Nigeria. Olusogo
MQ-series gas sensors are frequently used in gas concentration sensing owing to their high sensitivity and relatively cheap cost. Reportedly, both the sensor’s circuit sensitivity (𝑆) and power dissipation (𝑃𝑆 ) are functions of sensor circuit load resistance (𝑅𝐿 ). However, there is no well-established standard method for determining 𝑅𝐿 value that can simultaneously yield maximum sensor circuit sensitivity (𝑆𝑀) and acceptable 𝑃𝑆 for a given value of gas concentration. To obtain optimum 𝑅𝐿 , the dependence of 𝑆 and 𝑃𝑆 on 𝑅𝐿 for a given gas concentration was thoroughly investigated. The model equations for determining 𝑆, 𝑃𝑆 and 𝑅𝐿 at 𝑆𝑀 (𝑅𝐿,𝑀𝐴𝑋) were derived and MQ-6 gas sensor’s response to its associated gases was used for demonstrating the proposed method. Variations of both 𝑆 and 𝑃𝑆 with respect to 𝑅𝐿 were investigated when each of the associated gases has concentration of 1000 ppm. The sensor circuit optimal 𝑅𝐿 must satisfy the dual conditions of (i) S=𝑆𝑀 and (ii) 𝑃𝑆 < set threshold. Results obtained from the analysis revealed that the values of 𝑅𝐿,𝑀𝐴𝑋 were 20, 24, 64, 120, and 152 kΩ for liquefied petroleum gas (LPG), CH4, H2, alcohol and CO respectively, corresponding to sensor powers of 0.3125, 0.2589, 0.0977, 0.0521, and 0.0411 mW.
Volume: 20
Issue: 1
Page: 158-165
Publish at: 2022-02-01

Classification of three pathological voices based on specific features groups using support vector machine

10.11591/ijece.v12i1.pp946-956
Muneera Altayeb , Amani Al-Ghraibah
Determining and classifying pathological human sounds are still an interesting area of research in the field of speech processing. This paper explores different methods of voice features extraction, namely: Mel frequency cepstral coefficients (MFCCs), zero-crossing rate (ZCR) and discrete wavelet transform (DWT). A comparison is made between these methods in order to identify their ability in classifying any input sound as a normal or pathological voices using support vector machine (SVM). Firstly, the voice signal is processed and filtered, then vocal features are extracted using the proposed methods and finally six groups of features are used to classify the voice data as healthy, hyperkinetic dysphonia, hypokinetic dysphonia, or reflux laryngitis using separate classification processes. The classification results reach 100% accuracy using the MFCC and kurtosis feature group. While the other classification accuracies range between~60% to~97%. The Wavelet features provide very good classification results in comparison with other common voice features like MFCC and ZCR features. This paper aims to improve the diagnosis of voice disorders without the need for surgical interventions and endoscopic procedures which consumes time and burden the patients. Also, the comparison between the proposed feature extraction methods offers a good reference for further researches in the voice classification area.
Volume: 12
Issue: 1
Page: 946-956
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

Optical fiber sensors: review of technology and applications

10.11591/ijeecs.v25.i2.pp1038-1046
Mahmoud M. A. Eid
There is a huge increase in the usage of optical fiber sensors in various fields, especially the field of communications, as these sensors have been employed in a promising industry, namely, the internet of things. This industry is witnessing a growing demand for more sensors as well as employing them in new applications, and there is an urgent need to invent new sensors to meet our requirements in providing more time, luxury, and effort with the highest quality and the best possible performance. But there is now a lot of information about optical sensors as well as many classifications and applications. There are also some developments in a scientific research yard. The main objective of this paper is to introduce short, effective, and concentrated points in optical fiber sensors such as a brief historical background, their structure, and their different operation principles, different classifications for these sensors according to different categories, and finally advantages of fiber optical sensors compared to traditional electronic sensors. I hope this content will be very useful to anyone interested in these types of sensors. This review is done with particular assurance on the recently published information.
Volume: 25
Issue: 2
Page: 1038-1046
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

Day-ahead solar irradiance forecast using sequence-to-sequence model with attention mechanism

10.11591/ijeecs.v25.i2.pp900-909
Sowkarthika Subramanian , Yasoda Kailasa Gounder , Sumathi Lingana
The increasing integration of distributed energy resources (DERs) into power grid makes it significant to forecast solar irradiance for power system planning. With the advent of deep learning techniques, it is possible to forecast solar irradiance accurately for a longer time. In this paper, day-ahead solar irradiance is forecasted using encoder-decoder sequence-to-sequence models with attention mechanism. This study formulates the problem as structured multivariate forecasting and comprehensive experiments are made with the data collected from National Solar Radiation Database (NSRDB). Two error metrics are adopted to measure the errors of encoder-decoder sequence-to-sequence model and compared with smart persistence (SP), back propagation neural network (BPNN), recurrent neural network (RNN), long short term memory (LSTM) and encoder-decoder sequence-to-sequence LSTM with attention mechanism (Enc-Dec-LSTM). Compared with SP, BPNN and RNN, Enc-Dec-LSTM is more accurate and has reduced forecast error of 31.1%, 19.3% and 8.5% respectively for day-ahead solar irradiance forecast with 31.07% as forecast skill.
Volume: 25
Issue: 2
Page: 900-909
Publish at: 2022-02-01

Development smart eyeglasses for visually impaired people based on you only look once

10.12928/telkomnika.v20i1.22457
Hassan Salam; University of Technology, Iraq Abdul-Ameer , Hassan Jaleel; University of Technology, Iraq Hassan , Salma Hameedi; University of Technology, Iraq Abdullah
Visually impaired people are facing many problems in their life. One of these problems is how they can find the objects in their indoor environment. This research was presented to assists visually impaired people in finding the objects in office. Object detection is a method used to detect the objects in images and videos. Many algorithms used for object detection such as convolutional neural network (CNN) and you only look once (YOLO). The proposed method was YOLO which outperforms the other algorithms such as CNN. In CNN the algorithm splits the image into regions. These regions sequentially enters the neural network for object detection and recognition so CNN does not deal with all the regions at the same time but YOLO looks the entire image then it produces the bounding boxes with convolutional network and the probabilities of these boxes, this makes YOLO faster than other algorithms. Open source computer vision (OpenCV) used to capture frames by using camera. Then YOLO used to detect and recognize the objects in each frame. Finally, the sound in Arabic language was generated to tell the visually impaired people about the objects. The proposed system can detect 6 objects and achieve an accuracy of 99%.
Volume: 20
Issue: 1
Page: 109-117
Publish at: 2022-02-01

Robust least square approach for optimal development of quadratic fuel quantity function for steam power stations

10.11591/ijeecs.v25.i2.pp732-740
Ikenna Onyegbadue , Cosmas Ogbuka , Theophilus Madueme
Ordinary Least Square (OLS) and Robust Least Square (RLS) consisting of Least Absolute Residual and Bi-square approaches were deployed to obtain the fuel consumption characteristic curve and the coefficients of the quadratic fuel consumption function for thermal stations in Nigeria. Results were compared based on convergence property, Root Mean Square Error, R-Square value, Adjusted R-Square value, and Width Interval of coefficients. Valve Point loading effects of Egbin and Sapele power stations were used to develop the quadratic fuel consumption characteristic curve and function. The average difference in width interval for the coefficients a, b, c, d, and e of the two stations, after comparing Bi-square and OLS technique, were 0.02084, 8.5055, 1856.565, 520.8855, and 0.0082, respectively. The R-square values obtained from the Bi-Square technique were superior to the OLS technique with arithmetic differences of 0.6196 and 0.5254 for Egbin and Sapele generating stations, respectively. Bi-Square technique also offered better adjusted R-Square value for Egbin and Sapele stations with arithmetic differences of 0.622 and 0.5287, respectively. Bi-Square technique offered smaller Root Mean Square Error than the Ordinary Least Square technique for both stations. The coefficients obtained from Bi-Square technique were used to develop the fuel quantity function for the studied stations.
Volume: 25
Issue: 2
Page: 732-740
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
1 2 3
...
1995 1996
Show 860 of 1996

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration