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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,174 Documents
 617   618   619   620   621 
Design of high power amplifier based on wilkinson power combiner for wireless communications Tran Van Hoi; Ngo Thi Lanh
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp330-337

Abstract

Thisarticlepresentsthedesign and fabrication ofa high power amplifierbased onwilkinson power combiner. A 45W basic amplifier module isdesigned usinglaterally-diffused metal-oxide semiconductor (LDMOS) fieldeffect transistor (FET) PTFA260451E transistor. Wilkinson power combineris used to combine two input powers toproduce 90W of power. Theproposed power amplifier is researched, designed and optimized usingadvanced design system(ADS) software.Experimental results show that thegain is 11.5 dB greater than at 2.45-3.0GHz frequency band and achieving maximum power gain of 13.5dB at 2.65GHz centre frequency; output power increased to 49.3dBm; Power added efficiency of 62.1% and good impedances matching: input reflection coefficient (S11)<-10dB, output reflection coefficient (S22)<-15dB. The designed amplifier can be used for4G, 5G mobile communications andS-band satellite communication.
Effective task scheduling algorithm in cloud computing with quality of service alert bees and grey wolf optimization Nidhi Bansal; Ajay Kumar Singh
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp550-560

Abstract

Quality-based services are an indicative factor in providing a meaningful measure. These measures allow labeling for upcoming targets with a numerical comparison with a valid mathematical proof of reading and publications. By obtaining valid designs, organizations put this measure into the flow of technology development operations to generate higher profits. Since the conditions were met from the inception of cloud computing technology, the market was captured heavily by providing support through cloud computing. With the increase in the use of cloud computing, the complexity of data has also increased greatly. Applying natural theory to cloud technology makes it a fruit cream. Natural methods often come true, because survival depends on the live events and happenings, so using it in real life as well as any communication within technology will always be reliable. The numerical results are also showing a better value by comparing the optimization method. Finally, the paper introduces an adaptation theory with effective cloudsim coding of honey bees and grey wolf in conjunction with their natural life cycle for solving task scheduling problems. Using adapted bees improved the results by 50% compared with the original bees and secondly by honeybees and grey wolf improved 60%.
Energy consumption study of channel access modes and modulation schemes of the 2.4 GHz narrowband IEEE 802.15.6 Marwa Boumaiz; Mohammed El Ghazi; Mohammed Fattah; Anas Bouayad; Moulhime El Bekkali
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1505-1512

Abstract

Energy efficiency is an important challenge for wireless body area networks. Therefore, choosing the channel access modes and modulation schemes that guarantee lower energy consumption is necessary to increase the network lifetime, especially in wireless body area network (WBAN) medical applications. The purpose of this paper is to analyze the network energy consumption in on-body medical applications (which are classified as low data rate, medium data rate, and high data rate applications) for two channel access mechanisms: random and scheduled access modes, and two modulation schemes: differential quadrature phase shift keying (DQPSK) and differential binary phase shift keying (DBPSK), which are supported by the 2.4 GHz band of the Institute of Electrical and Electronics Engineers (IEEE) 802.15.6 standard. The considered on-body area network (BAN) of the study supports two communication scenarios: the line-of-sight transmission and the non-line-of-sight communications, referenced as CM3A and CM3B path loss models respectively. Simulation results have demonstrated that the scheduled access mode based on time-division multiple access (TDMA), and DQPSK are the optimal choices to be made at the media access control (MAC) and physical layer levels respectively, in terms of energy efficiency, in low, medium, and high data rate on-body WBAN applications.
Design and implementation of a stability control system for TCP/AQM network Salam Waley Shneen; Mohammed Qasim Sulttan; Manal Kadhim Oudah
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp129-136

Abstract

In this work, we used a new approach as active queue management (AQM) to avoid data congestion in TCP/IP networks. The new approach is PSO-PI controller which use the proportional-integral controller as a control unit and particle swarm optimization (PSO) algorithm as an optimization technique to improve the performance of the PI controller and therefore improving the performance of TCP/IP networks as a required goal. The optimization control (PSO-PI) is characterized by access to design and choosing the optimal parameters of (K_1 and K_p) to reach optimal solutions in a short way (fewer iterations). The implementation of the PSO algorithm is achieving by using the mathematical system model and M-file and SIMULINK in Mathlab program. Simulation results show good congestion management performance with PSO-PI controller better than the PI controller as AQM in TCP networks, and the proposed method was very fast and required few iterations.
Investigation on the PAPR performance of odd-bit QAM constellations for DFT spread OFDM systems Ahmed M. Sana; Amer T. Saeed; Yaseen Kh. Yaseen
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1005-1013

Abstract

Adaptive quadrature amplitude modulation (QAM) is a crucial scheme that enables the modern communication systems to overcome the adverse effects of channel fluctuations and maintain an acceptable spectral efficiency. In order to enhance adaptive modulation even further, adoption of odd-bit QAM constellations alongside even constellations had been suggested to improve the transmission efficiency of adaptive QAM modulation. Hence, odd-bit QAM had been extensively studied, analyzed, and tested by many researchers for various patterns, sizes, and communication systems in terms of bit error rate (BER) and peak to average power ratio (PAPR). However, the PAPR performance of odd-bit QAM constellation with single carrier transmission systems adopted in the uplink of the 4G long term evolution (LTE) standards caught almost no research interest. In this paper, the PAPR performance of both cross and rectangular odd-bit QAM constellations are investigated for DFT-S-OFDM systems. Complementary cumulative distribution functions (CCDFs) and probability density functions (PDFs) curves for PAPR are also obtained. Finally, an equation for PAPR PDF is empirically derived for odd-bit cross QAM based DFT-S-OFDM. The results show that cross odd-bit QAM outperforms the rectangular odd-bit QAM in terms of PAPR by 1.02 dB for 8-QAM and 1.3 dB for 32-QAM. This proves that cross odd-bit QAM is a better choice in terms of PAPR for DFT-S-OFDM systems. 
Joint inter-intra representation learning for pornographic video classification Phan, Dinh-Duy; Nguyen, Quang-Huy; Nguyen, Thanh-Thien; Tran, Hoang-Loc; Vu, Duc-Lung
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1481-1488

Abstract

This paper addresses video inter-intra similarity retrieval for pornographic classification. The main approaching method is obtaining the internal representation and external similarity between a single unlabeled video and batches of labeled videos, then combining together to determine its label. For the internal representation, we extracted inner features within frames and clustered them to find the representative centroid as the intra-feature. For the external similarity, we utilized a similarity video learning named ViSiL to calculate distance score between two videos using chamfer similarity. With distance scores between input video and batches of pornographic/nonpornographic videos, the inter feature of the input video is obtained. Finally, the inter similarity vector and the intra representation are then concatenated together and fed to a final classifier to identify whether the video is for adults or not. In experiment, our method performs 96.88% accuracy on NPDI-2k, achieved a comparative result comparing to other state-of-the-art methods on the pornographic classification problem.
Vibration harvesting integrated into vehicle suspension and bodywork Souad Touairi; Mustapha Mabrouki
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp188-196

Abstract

This work proposes a new piezoelectric transducer system with four freedoms of movement modelled and evaluated by mechatronic techniques. The proposed modelling techniques (finite element and bond graph) were performed in a 20-Sim framework attached to the ANSYS software. The established harvester system has the ability to increase the driver's comfort when travelling on several types of road surfaces. The piezoelectric harvester is designed to investigate and provide the health requirement and ride comfort of the vehicle's drives on random road surfaces. The simulation results affirm that the improved piezoelectric transducer arrangement is more productive for various aspects. The power recovery is significantly enhanced as well as the driving comfort on the three road categories. Finally, the harvestable power amount is highlighted and is graphically discussed for several specific applications.
An experimental evaluation of localization methods used in wireless sensor networks Laaouafy, Mostapha; Lakrami, Fatima; Labouidya, Ouidad; Elkamoun, Najib
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1518-1528

Abstract

The problem of localization in wireless sensor networks has received considerable attention from researchers over the past decades. Several methods and algorithms have been proposed to solve this problem. The effectiveness of these algorithms depends on the accuracy of the estimated positions and the information required to calculate the coordinates. In this paper, we propose to evaluate four of the most commonly used localization methods in sensor networks. Our study considers a mathematical description of the studied methods in order to evaluate their complexity, and then a practical implementation on the simulation tool Cooja. We evaluate the performance of the studied methods as a function of the number of deployed sensor nodes and their degree of mobility in terms of several performance metrics. The objective is to reveal the most suitable localization method for a particular case of deployment. Improvement proposals are also provided to improve the most relevant localization method for the investigated study.
ROI-based features for classification of skin diseases using a multi-layer neural network Thanh-Hai Nguyen; Ba-Viet Ngo
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp216-228

Abstract

Skin diseases have a serious impact on human life and health. This article aims to represent the classification accuracy of skin diseases for supporting the physicians’ correct decision on patients for early treatment. In particular, 100 images in each type of five skin diseases from ISIC database are used for balanced datasets related to the classification accuracy. In addition, this paper focuses on processing images for extracting six optimal types of eleven features of skin disease image for higher classification performance and also this takes less time for training. Therefore, skin disease images are filtered and segmented for separating region of interests (ROIs) before extracting optimal features. First, the skin disease images are processed by normalizing sizes, removing noises, segmenting to separate region of interests (ROIs) showing skin disease signs. Next, a gray-level co-occurrence matrix (GLCM) method is applied for texture analysis to extract eleven features. With the optimal six features chosen, the high classification accuracy of skin diseases is about 92% evaluated using a matrix confusion. The result showed to illustrate the effectiveness of the proposed method. Furthermore, this method can be developed for other medical datasets for supporting in disease diagnosis.
A comparative analysis on traditional wired datasets and the need for wireless datasets for IoT wireless intrusion detection Teh Boon Seong; Vasaki Ponnusamy; Noor Zaman Jhanjhi; Robithoh Annur; M N Talib
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp1165-1176

Abstract

IoT networks mostly rely on wireless mediums for communication, and due to that, they are very susceptible to intrusions. And due to the tiny nature, processing complexity, and limited storage capacities, IoT networks require very reliable intrusion detection systems (IDS). Although there are many IDS types of research available in the literature, most of these systems are suitable for wired network environments, and the benchmark datasets used for these research works are mostly relying on wired datasets such as KDD Cup’99 and NSL-KDD. IoT and wireless networks are distinct in nature as wireless networks give more emphasis on the data link layer and physical layer. These concerns are not given much attention in traditional wired datasets in the body of knowledge. Therefore, in this research, an IDS system is developed using a newly available IoT wireless dataset (NaBIoT) in the literature with the datasets focusing much on the common IoT related attacks, and related layers are taken into consideration. The IDS system developed is evaluated by comparing with various machine learning algorithms in terms of evaluation metrics such as accuracy, F1 score, false positive, and false negative. Moreover, the IoT wireless dataset is compared against the traditional NSL-KDD datasets to evaluate the need for IoT wireless datasets. The NaBIoT datasets show its effectiveness in detecting wireless intrusions. Besides that, the simulation is performed with different combinations of features to conclude that certain features are primary in detecting attacks, and IDS does not require all the features to perform detection. This can reduce the detection time mainly for machine learning and creating the models. This research results have proposed some of the critically important features to be used and eliminating not such important features.   

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