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30,185 Article Results

Design and testing of systolic array multiplier using fault injecting schemes

10.11591/csit.v3i1.p1-9
Kurada Verra Bhoga Vasantha Rayudu , Dhananjay Ramachandra Jahagirdar , Patri Srihari Rao
Nowadays low power design circuits are major important for data transmission and processing the information among various system designs. One of the major multipliers used for synchronizing the data transmission is the systolic array multiplier, low power designs are mostly used for increasing the performance and reducing the hardware complexity. Among all the mathematical operations, multiplier plays a major role where it processes more information and with the high complexity of circuit in the existing irreversible design. We develop a systolic array multiplier using reversible gates for low power appliances, faults and coverage of the reversible logic are calculated in this paper. To improvise more, we introduced a reversible logic gate and tested the reversible systolic array multiplier using the fault injection method of built-in self-test block observer (BILBO) in which all corner cases are covered which shows 97% coverage compared with existing designs. Finally, Xilinx ISE 14.7 was used for synthesis and simulation results and compared parameters with existing designs which prove more efficiency.
Volume: 3
Issue: 1
Page: 1-9
Publish at: 2022-04-21

A hybrid of the selected mapping and partial transmit sequence approaches for reducing the high peak average to power ratio based on multi-carrier systems – review

10.11591/csit.v3i1.p10-21
Ali Nahar , Mohammed A. Hussein
The orthogonal frequency division multiplexing (OFDM)-4G and 5G filter technology suffer a drawback that represents the direction of the peak average to power ratio (PAPR) in orthogonal frequency division multiplexing due to the nonlinear nature of the transmitter. There are a lot of traditional and hybrid methods of these traditional methods to reduce the harmful high PAPR value. Newly, several new hybrid methods have been adopted to reduce PAPR but it faces an increasing level of computational complexity in the system. In this paper, two important and effective conventional methods for reducing PAPR are studied, analyzed, and investigated for the hybrid pathway which is the incorporation of selective mapping (SLM) method and partial transport sequencing (PTS) method, which achieve increased efficiency of PAPR reduction while computing the computational complexity of each method. The method depends and balances with computational complexity. The search is based on multi-carrier connections such as multi carrier-code division multiple access (MC-CDMA) and OFDM.
Volume: 3
Issue: 1
Page: 10-21
Publish at: 2022-04-21

Quality of experience aware network selection model for service provisioning in heterogeneous network

10.11591/ijece.v12i2.pp1839-1848
Nagaraja Gadde , Basavaraj Jakkali , Ramesh Babu Halasinanagenahalli Siddamallaih , Gowrishankar Gowrishankar
Heterogeneous wireless networks (HWNs) are capable of integrating the different radio access technologies that make it possible to connect mobile users based on the performance parameters. Further quality of service (QoS) is one of the major topics for HWNs, moreover existing radio access technology (RAT) methodology are designed to provide network QoS criteria. However, limited work has been carried out for the RAT selection mechanism considering user QoS preference and existing models are developed based on the multi-mode terminal under a given minimal density network. For overcoming research issues this paper present quality of experience (QoE) RAT (QOE-RAT) selection methodology, incorporating both network performance criteria and user preference considering multiple call and multi-mode HWNs environment. First, this paper presents fuzzy preference aware weight (FPAW) and multi-mode terminal preference aware TOPSIS (MMTPA-TOPSIS) for choosing the best RAT for gaining multi-services. Experiment outcomes show the QOE-RAT selection method achieves much superior packet transmission outcomes when compared with state-of-art Rat selection methodologies.
Volume: 12
Issue: 2
Page: 1839-1848
Publish at: 2022-04-01

Method of optimization of the fundamental matrix by technique speeded up robust features application of different stress images

10.11591/ijece.v12i2.pp1429-1436
Ahmed Chater , Hicham Benradi , Abdelali Lasfar
The purpose of determining the fundamental matrix (F) is to define the epipolar geometry and to relate two 2D images of the same scene or video series to find the 3D scenes. The problem we address in this work is the estimation of the localization error and the processing time. We start by comparing the following feature extraction techniques: Harris, features from accelerated segment test (FAST), scale invariant feature transform (SIFT) and speed-up robust features (SURF) with respect to the number of detected points and correct matches by different changes in images. Then, we merged the best chosen by the objective function, which groups the descriptors by different regions in order to calculate ‘F’. Then, we applied the standardized eight-point algorithm which also automatically eliminates the outliers to find the optimal solution ‘F’. The test of our optimization approach is applied on the real images with different scene variations. Our simulation results provided good results in terms of accuracy and the computation time of ‘F’ does not exceed 900 ms, as well as the projection error of maximum 1 pixel, regardless of the modification.
Volume: 12
Issue: 2
Page: 1429-1436
Publish at: 2022-04-01

A heuristic approach to minimize three criteria using efficient solutions

10.11591/ijeecs.v26.i1.pp334-341
Dara Ali Hassan , Nezam Mehdavi Amiri , Ayad Mohammed Ramadan
In optimization, scheduling problems is concerning allocations of some resources which are usually limited. These allocations are done in order to fulfil some criterion by performing some tasks or jobs to optimize one or more objective functions. Simultaneous multi-criteria scheduling problem is known as np-hard optimization problem. Here, we consider three criteria for scheduling a number of jobs on a single machine. The problem is to minimize the sum of total completion time, maximum earliness and maximum tardiness. Every job is to be processed without interruption and becomes available for processing at time zero. The aim is to find a processing order of the jobs to minimize three-objective functions simultaneously. We present a new heuristic approach to find a best overall solution (accepted) of the problem using efficient solutions of one of the other related criteria. We establish a result to restrict the range of the optimal solution, and the lower bound depends on the decomposition of the problem into three subproblems. The approach is tested on a set of problems of different number of jobs. Computational results demonstrate the efficiency of the proposed approach.
Volume: 26
Issue: 1
Page: 334-341
Publish at: 2022-04-01

Crop leaf disease detection and classification using machine learning and deep learning algorithms by visual symptoms: a review

10.11591/ijece.v12i2.pp2079-2086
Pallepati Vasavi , Arumugam Punitha , T. Venkat Narayana Rao
A Quick and precise crop leaf disease detection is important to increasing agricultural yield in a sustainable manner. We present a comprehensive overview of recent research in the field of crop leaf disease prediction using image processing (IP), machine learning (ML) and deep learning (DL) techniques in this paper. Using these techniques, crop leaf disease prediction made it possible to get notable accuracies. This article presents a survey of research papers that presented the various methodologies, analyzes them in terms of the dataset, number of images, number of classes, algorithms used, convolutional neural networks (CNN) models employed, and overall performance achieved. Then, suggestions are prepared on the most appropriate algorithms to deploy in standard, mobile/embedded systems, Drones, Robots and unmanned aerial vehicles (UAV). We discussed the performance measures used and listed some of the limitations and future works that requires to be focus on, to extend real time automated crop leaf disease detection system.
Volume: 12
Issue: 2
Page: 2079-2086
Publish at: 2022-04-01

Measurement of information technology governance capability level: a case study of PT Bank BBS

10.12928/telkomnika.v20i2.21668
Punto; Universitas Indonesia Widharto , Zaldy; Universitas Pamulang Suhatman , Rizal Fathoni; Universitas Indonesia Aji
The very close involvement of technology in the banking industry makes almost all banking activities and products currently dependent on information technology (IT). PT BPRS Bhakti Sumekar (PT BBS Bank) is one of the banks that realizes the importance of IT in the digital era and has included IT as part of the company's strategic plan. The company states that compliance with regulations, best practices, and standards is key to a successful IT implementation. In this study, the measurement of the capability level of corporate IT governance was conducted to determine what IT priorities were based on the company's strategic objectives and what recommendations could be given based on best practices to improve IT services in support of the company's strategic goals. The framework to be used is control objective for information and related technology (COBIT); the most widely used framework suitable for service-oriented organizations. The results of research using COBIT 2019 show how IT governance is needed by the company and what should be prioritized. The measurement results found that there is still a gap between management's expectations and the current level of capability and provide recommendations on what companies need to improve performance in order to meet expectations.
Volume: 20
Issue: 2
Page: 296-306
Publish at: 2022-04-01

Simulating the Covid-19 epidemic event and its prevention measures using python programming

10.11591/ijeecs.v26.i1.pp278-288
Mustofa Abi Hamid , Dimas Aditama , Endi Permata , Nur Kholifah , Muhammad Nurtanto , Nuur Wachid Abdul Majid
A simulation is needed to observe and indicate how much preventive measures influence the pandemic flow, controlling and stopping it. This study succeeded in making a stochastic susceptible infected recovered deceased (SIRD) simulation using Python programming language to determine the effectiveness of prevention methods such as masks policy, social distancing, vaccination, quarantine, and lockdown. Every preventive measure is modeled based on an equivalent actual event and every essential aspect that affects the course of the pandemic. A person is represented as a circle moving freely in two-dimensional space, and disease spreads through person-to-person contact. This simulator then tested using parameters to simulate COVID-19 and found significant results between communities that implement preventive measures and those that do not. We found that within 106 days, 284 people were infected, but when five preventive methods are applied for a total of 33 days, only 31 people were infected. Adequate to simulate epidemic events and their prevention measures, this simulator can also be used as a learning tool with factors in epidemic events such as population density, mobility, infection rate, disease mortality, and every effect of each preventive measure. Users can change and influence the simulation course using interactive and straightforward software tools.
Volume: 26
Issue: 1
Page: 278-288
Publish at: 2022-04-01

An approach for cross-modality guided quality enhancement of liver image

10.11591/ijece.v12i2.pp1449-1455
Ahmed Elaraby , Ayman Taha
A novel approach for multimodal liver image contrast enhancement is put forward in this paper. The proposed approach utilizes magnetic resonance imaging (MRI) scan of liver as a guide to enhance the structures of computed tomography (CT) liver. The enhancement process consists of two phases: The first phase is the transformation of MRI and CT modalities to be in the same range. Then the histogram of CT liver is adjusted to match the histogram of MRI. In the second phase, an adaptive histogram equalization technique is presented by splitting the CT histogram into two sub-histograms and replacing their cumulative distribution functions with two smooths sigmoid. The subjective and objective assessments of experimental results indicated that the proposed approach yields better results. In addition, the image contrast is effectively enhanced as well as the mean brightness and details are well preserved.
Volume: 12
Issue: 2
Page: 1449-1455
Publish at: 2022-04-01

Radio frequency receiver of long-term evolution system design by MATLAB Simulink

10.12928/telkomnika.v20i2.20936
Fatima Faydhe; Middle Technical University (MTU) Al-Azzawi , Faeza Abbas; Middle Technical University MTU Abid , Maham Kamil; Middle Technical University Naji
For wireless broadband communication long-term evolution (LTE) is a standard for also mobile devices and data terminals, by using different radio interface together with core network improvements LTE increases the capacity and speed of mobile network. In this paper radio frequency receiver of radio-frequency long-term evolution (RF-LTE) is design and simulated using MATLAB Simulink, where the design based on illustrating parameters of each stage in LTE RF receiver from generating LTE waveform to error vector magnitude (EVM) measurements, where simulation results with 8 MHz bandwidth the transmitted signal power -3200 dBm, the received signal power (-140 to -160) dBm, while the demodulated signal reaches to -60 dBm difference between main loop and side loop witch lead to high confident recovered signal, also complementary cumulative distribution function (CCDF) measurements applied on output signals so that computes the power of complementary for cumulative distribution CCDF function from signal in time domain. Where CCDF curve shows value of time that a signal stand still above the level of average power for the measured signal or the probability of signal power will be above the level of average power.
Volume: 20
Issue: 2
Page: 244-251
Publish at: 2022-04-01

Micropower system optimization for the telecommunication towers based on various renewable energy sources

10.11591/ijece.v12i2.pp1069-1076
Ahmed Abdulmula , Kamaruzzaman Sopian , Norasikin Ahmad Ludin , Lim Chin Haw , Abdelnaser Elbreki , Fayez Aldawi , Hazim Moria
This study investigates the technical and cost-effective performance of options renewable energy sources to develop a green off-grid telecommunication tower to replace diesel generators in Malaysia. For this purpose, the solar, wind, pico-hydro energy, along with diesel generators, were examined to compare. In addition, the modeling of hybrid powering systems was conducted using hybrid optimization model for energy (HOMER) simulation based on techno-economic analysis to determine the optimal economically feasible system. The optimization findings showed that the hybrid high-efficiency fixed photovoltaic (PV) system with battery followed by 2 kW pico-hydropower and battery are the optimal configurations for powering off-grid telecommunication towers in Malaysia with the lowest net present cost (NPC) and cost of energy (COE). These costs of NPC and COE are more down than diesel generator costs with battery by 17.45%, 16.45%, 15.9%, and 15.5%, respectively. Furthermore, the economic evaluation of the high-efficiency solar fixed PV panels system annual cash flow compared to the diesel generator with the battery system indicated a ten-year payback period.
Volume: 12
Issue: 2
Page: 1069-1076
Publish at: 2022-04-01

Real-time twitter data analytics of mental illness in COVID-19: sentiment analysis using deep neural network

10.11591/ijeecs.v26.i1.pp560-567
Poonkuzhali Sugumaran , Anu Barathi Bhagavathi Kannu Uma
The World Health Organization (WHO) states that the COVID-19 epidemic is being treated as a pandemic, with thousands of individuals infected and dead worldwide. School and college students are suffering from their online classes without any physical activities. Working men and women are also suffering from their working situations, as lots of people have lost their jobs and unemployment rates have become high due to the pandemic, and people are also losing physical contact with other family members, friends, and colleagues. The main objective of the proposed model is to monitor and analyse the real-time Twitter data-related tweets, such as coronavirus mental illness that are commonly used while referencing the pandemic. We have compared three deep learning approaches to sentiment analysis and found them to be useful. The first deep learning technique is to use a basic recurrent neural network (RNN), and the second is to use a deep learning RRN with long short-term memory (LSTM), followed by a gated recurrent unit (GRU). The experiment results indicate that the recurrent neural network built using GRU has the maximum accuracy of 99.47% for positive, negative, and neutral words and statements in Twitter data.
Volume: 26
Issue: 1
Page: 560-567
Publish at: 2022-04-01

A data mining analysis of COVID-19 cases in states of United States of America

10.11591/ijece.v12i2.pp1754-1758
Özerk Yavuz
Epidemic diseases can be extremely dangerous with its hazarding influences. They may have negative effects on economies, businesses, environment, humans, and workforce. In this paper, some of the factors that are interrelated with COVID-19 pandemic have been examined using data mining methodologies and approaches. As a result of the analysis some rules and insights have been discovered and performances of the data mining algorithms have been evaluated. According to the analysis results, JRip algorithmic technique had the most correct classification rate and the lowest root mean squared error (RMSE). Considering classification rate and RMSE measure, JRip can be considered as an effective method in understanding factors that are related with corona virus caused deaths.
Volume: 12
Issue: 2
Page: 1754-1758
Publish at: 2022-04-01

Improvised convolutional auto encoder for thyroid nodule image enhancement and segmentation

10.11591/ijeecs.v26.i1.pp342-351
Drakshaveni Gunjali , Prasad Naik Hansavath
Thyroid ultrasonography and thermography are a widely used clinical technique for nodule diagnosis in thyroid regions. However, it remains difficult to detect and recognize the nodules due to low contrast, high noise, and diverse appearance of nodules. To alleviate doctors’ tremendous labor in the diagnosis procedure, we advocate a machine learning approach to the detection and recognition tasks in this paper. Moreover, this research mainly focuses on segmenting the image and finding the probable region. In this research work an improvised convolutional auto encoder (ICAE) is introduced for segmenting the image and finding the probable region of thyroid gland and it enhances image. ICAE comprises various layer and mechanism, each having their own task. Apart from the traditional approach, skip connection is applied for the image enhancement and dual frame is introduced for better feature extraction. Further optimization technique is used for increasing the learning rate. ICAE is evaluated considering digital database thyroid image (DDTI) dataset with performance metrics like accuracy, true positive rate, false positive rate, dice coefficient and similarity index (SI); also, comparative analysis is carried out with various existing model and proposed model simply outperforms the existing model.
Volume: 26
Issue: 1
Page: 342-351
Publish at: 2022-04-01

Optimization of system’s parameters for wavelength conversion of E-band signals

10.11591/ijece.v12i2.pp1659-1666
Yazan Alkhlefat , Sevia Mahdaliza Idrus Sutan Nameh , Farabi M. Iqbal
Current and future wireless communication systems are designed to achieve the user’s demands such as high data rate and high speed with low latency and simultaneously to save bandwidth and spectrum. In 5G and 6G networks, a high speed of transmitting and switching is required for internet of things (IoT) applications with higher capacity. To achieve these requirements a semiconductor optical amplifier (SOA) is considered as a wavelength converter to transmit a signal with an orthogonal frequency division multiplexing with subcarrier power modulation (OFDM-SPM). It exploits the subcarrier’s power in conventional OFDM block in order to send additional bits beside the normally transmitted bits. In this paper, we optimized the SOA’s parameters to have efficient wavelength conversion process. These parameters are included the injection current (IC) of SOA, power of pump and probe signals. A 7 Gbps OFDM-SPM signal with a millimeter waves (MMW) carrier of 80 GHz is considered for signal switching. The simulation results investigated and analyzed the performance of the designed system in terms of error vector magnitude (EVM), bit error rate (BER) and optical signal-to-noise ratio (OSNR). The optimum value of IC is 0.6 A while probe power is 9.45 and 8.9 dBm for pump power. The simulation is executed by virtual photonic integrated (VPI) software.
Volume: 12
Issue: 2
Page: 1659-1666
Publish at: 2022-04-01
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