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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
 628   629   630   631   632 
Performance analysis of patch antenna for underwater wireless communication in seawater Siti Harliza Mohd Razali; Razali Ngah; Yoshihide Yamada; Kamilia Kamardin
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.pp857-865

Abstract

Underwater wireless communication in seawater is becoming more interesting and challenging in recent years. The development of antenna for underwater wireless communication in seawater at 900 MHz UHF range frequency is implemented by using patch antenna. In this paper, the antennas were designed using FEKO, an electromagnetic simulation software, and a suitable size for rectangular patch antenna for seawater application was developed to study the relevance between λ0 with W and L in seawater. The difference between the patches in free space and seawater was the L size, which was slightly bigger, about 0.9 mm, than free space size. But the gain for patch antenna in seawater was found at -2.51 dBi, lower than patch antenna in free space, which was 5.76 dBi due to the path loss in seawater. This shows that attenuation happened, and a better antenna will be design. The one that has better gain, which is around above 2 dBi in seawater, in order to get better performance antenna in seawater environment.
Remote sensing data driven bathing water quality assessment using sentinel-3 Antonia Senta; Ljiljana Šerić
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1634-1647

Abstract

In this paper we are investigating the possibility of usage of remote sensing satellite data, more precisely sentinel-3 OLCI and SLSTR data, for assessment of bathing water quality. In this research we used data driven approach and analysis of data in order to pinpoint aspects of remote sensing data that can be useful for bathing water quality assessment. For this purpose we collected satellite images for period from start of June till end of September of 2019 and results of in-situ measurement for the same period. Results of in-situ measurement were correlated with satellite images bands and analyzed. We propose a simple method for rapid assessment of possible deterioration of bathing water quality to be used by public health authorities for better planning of in situ measurements. Results of implementation of predictive models based on k-nearest neighbour (KNN) and decision tree (DT) are described.
Aligned vertical growth of zinc oxide nanorods on glass substrates using optimum hydrothermal synthesis technique Mohd Hafiz Jali; Md Ashadi Md Johari; Hazli Rafis Abdul Rahim; Haziezol Helmi Mohd Yusof; Aminah Ahmad; Mohamad Faizal Baharom; Sulaiman Wadi Harun
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp694-700

Abstract

This paper reported an optimized hydrothermal synthesis technique to grow zinc oxide (ZnO) nanorods vertically on the normal microscope glass. ZnO nanorods exhibited various advantages such as strong binding energy, non toxicity, large surface to volume ratio and versatility for optical detections. However, the growth of nanorods which aligned vertically on the glass substrates is rather complicated. It required a thorough process based on optimized concentration, growth duration, growth temperature and solvent variations. The morphological structure result has shown an exceptional vertical growth of the nanorods on the glass surfaces which increase the nanorods density. The optimized synthesis technique produced high density ZnO nanorods up to 3 ???? 1013 nanorods/m2 which is double as compared to conventional synthesis technique.
Network intrusion detection system: machine learning approach Ameera S. Jaradat; Malek M. Barhoush; Rawan S. Bani Easa
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 2: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i2.pp1151-1158

Abstract

The main goal of intrusion detection system (IDS) is to monitor the network performance and to investigate any signs of any abnormalities over the network. Recently, intrusion detection systems employ machine learning techniques, due to the fact that machine learning techniques proved to have the ability of learning and adapting in addition to allowing a prompt response. This work proposes a model for intrusion detection and classification using machine learning techniques. The model first acquires the data set and transforms it in the proper format, then performs feature selection to pick out a subset of attributes that worth being considered. After that, the refined data set was processed by the Konstanz information miner (KNIME). To gain better performance and a decent comparative analysis, three different classifiers were applied. The anticipated classifiers have been executed and assessed utilizing the KNIME analytics platform using (CICIDS2017) datasets. The experimental results showed an accuracy rate ranging between (98.6) as the highest obtained while the average was (90.59%), which was satisfying compared to other approaches. The gained statistics of this research inspires the researchers of this field to use machine learning in cyber security and data analysis and build intrusion detection systems with higher accuracy.
A YOLO and convolutional neural network for the detection and classification of leukocytes in leukemia Shakir Mahmood Abas; Adnan Mohsin Abdulazeez; Diyar Qader Zeebaree
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.pp200-213

Abstract

The developing of deep learning systems that used for chronic diseases diagnosing is challenge. Furthermore, the localization and identification of objects like white blood cells (WBCs) in leukemia without preprocessing or traditional hand segmentation of cells is a challenging matter due to irregular and distorted of nucleus. This paper proposed a system for computer-aided detection depend completely on deep learning with three models computer-aided detection (CAD3) to detect and classify three types of WBC which is fundamentals of leukemia diagnosing. The system used modified you only look once (YOLO v2) algorithm and convolutional neural network (CNN). The proposed system trained and evaluated on dataset created and prepared specially for the addressed problem without any traditional segmentation or preprocessing on microscopic images. The study proved that dividing of addressed problem into sub-problems will achieve better performance and accuracy. Furthermore, the results show that the CAD3 achieved an average precision (AP) up to 96% in the detection of leukocytes and accuracy 94.3% in leukocytes classification. Moreover, the CAD3 gives report contain a complete information of WBC. Finally, the CAD3 proved its efficiency on the other dataset such as acute lymphoblastic leukemia image database (ALL-IBD1) and blood cell count dataset (BCCD).
Artificial intelligence based handover decision and network selection in heterogeneous internet of vehicles Shaik Mazhar Hussain; Kamaludin Mohamad Yusof; Rolito Asuncion; Shaik Ashfaq Hussain
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.pp1124-1134

Abstract

Internet of vehicles (IoV) is an emerging area that gives support for vehicles via internet assisted communication. IoV with 5G provides ubiquitous connectivity due to the participation of more than one radio access network. The mobility of vehicles demands to make handover in such heterogeneous network. The vehicles at short range uses dedicated short range communication (DSRC), while it has to use better technology for long range and any type of traffic. Usually, the previous work will directly select the network for handover or it connects with available radio access. Due to this, the occurrence of handover takes place frequently.  In this paper, the integration of DSRC, LTE and mmWave 5G on IoV is incorporated with novel handover decision making, network selection and routing. The handover decision is to ensure whether there is a need for vertical handover by using Dynamic Q-learning algorithm that uses entropy function for threshold prediction as per the current characteristics of the environment. Then the network selection is based on fuzzy-convolution neural network (F-CNN) that creates fuzzy rules from signal strength, distance, vehicle density, data type and line of sight. V2V chain routing is proposed to select V2V pairs using jellyfish optimization algorithm (JOA) that takes in account of channel, vehicle and transmission metrics. This system is developed in OMNeT++ simulator and the performances are evaluated in terms of success probability, handover failure, unnecessary handover, mean throughput, delay and packet loss.
Miniaturised tri-band microstrip patch antenna design for radio and millimetre waves of 5G devices Dhurgham Abdulridha Jawad Al-Khaffaf; Ihsan A. Alshimaysawe
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1594-1601

Abstract

This research presents an extremely small, cheap and simple structure of multiple bands antenna, where is the proposed design comprise square-slotted a microstrip patch antenna with triple bands of RF and mm-wave for 5G. The conducting material is a perfect electrical conductor on both sides. The antenna is printed on FR-4 lossy with a 3.9 of epsilon. Our tiny antenna has a size of 1.5357 x 1.5357 mm2. First, the design parameters were calculated using formulas and then these were simulated by the CST MWS. The simulation results show the antenna performance at the RF band from 0 to 3.4096 GHz with 3.29 gain, a value of return loss S11 and bandwidth of -13.229644 and 3.4096 GHz. The designed antenna works at the mm-wave band ranges 43.5-64 GHz with 3.49 gain, -42.419084 S11 and 20.252 GHz BW. Our antenna can also operate at the mm-wave from 81-95 GHz with -22.269547 S11, 4.52 gain, and 14.085 GHz BW. The small size and supported bandwidth of the designed antenna is suitable for thin and fast transmission devices.
Automated data monitoring of MEMS cleanroom parametric requirements Jean M. Capanang; Jobelle P. Panganiban; Glenn N. Ortiz; Mark Joseph B. Enojas
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp701-708

Abstract

Cleanroom parameters such as temperature, relative humidity and particle count are vital in maintaining cleanliness. People and machines working inside the cleanroom are main contributors for the sudden changes of the separameters. Measurements and monitoring of these parameters are therefore necessary to reduce rejects and downtime in the production of micro-electro-mechanical systems (MEMS). This paper presents a method of developmentof an automated data monitoring of MEMS cleanroom parametric requirements. The prototype developed uses DHT11 sensor and Sharp dust sensor for measuring the temperature, humidity and particle count respectively which are displayed in an LCD display. These parameters are recorded through a data logger for analysis and control. Additionally, agraphical user interface was also developed using visual studio for the working personnel and for supervisory monitoring and control. As a result, the possible quality compromise in the production of MEMS is detected when the monitored parameters are beyond the range.
Physical layer security in DF full-duplex relaying network: performance analysis Phu Tran Tin; Tan N. Nguyen; Van-Duc Phan; Minh Tran
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.pp865-873

Abstract

In this letter, the system performance of the DF full-duplex (FD) Relaying communication network is investigated with Physical Layer Security (PLS). In this system model, the source (S) and the destination (D) communicate via a helping relay (R) in the presence of the Eavesdropper (E). From the system model, we derive the closed-form expressions for Intercept Probability (IP) and secrecy outage probability (SOP). For verifying the correctness of the analytical analysis, the Monte Carlo simulation is conducted. In addition, the influence of the main system parameter on the system performance is investigated. Finally, the results show that the analytical and the simulation values agree well with each other.
Fog attenuation penalty analysis in terrestrial optical wireless communication-modified duo-binary return-to-zero system with various receiver pointing errors Mustafa H. Ali; Tariq A. Hassan; Hiba A. Abu-Alsaad
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.pp414-424

Abstract

In metropolitan communication infrastructures a revolutionary technique is emerge known as terrestrial optical wireless communication (OWC), which makes a high-rise building connection is possible. Even with this solution, there are many other problems like the influence of haze and fog in the propagation channel which obstruct and scatter OWC propagation light and consequently led to a big attenuation, due to propagate in temporal, angular and spatial of the light signal. Not to mention the minimum visibility that discourages the implementation of the pointing errors (PE) and tracking system. This present work aims to analyze the interrelation between multiple scattering (dense fog, heavy fog, light fog, heavy haze and light haze) and receiver PE under modified duo-binary return-to-zero (MDRZ) system. We found that PE caused by beam swag is the main controlling factor and industriously minimize the link margin, signal-to-noise ratio (SNR), and raise the bit error rate (BER) when there is an increasing the turbulence strength and the track length. We recommended to guarantee transmitter– receiver alignment by installing a variable field of view (FOV) receiver (a tracking system) to overcome the scattering impact of the fog that make render urban laser communication effective in the presence of PE.

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