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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 :
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Articles 64 Documents
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Search results for , issue "Vol 31, No 1: July 2023" : 64 Documents clear
Nested approach for X-ray image enhancement based on contrast adaptive using histogram equalization Mostafa Satea
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp417-422

Abstract

Medical image enhancement is a topic of great interest to researchers due to the rapid evolution of technology and advancements in communication. There are many types of medical images such as X-ray images, computed tomography (CT) scans, magnetic resonance imaging (MRI) scans, ultrasound images, positron emission tomography (PET) scans, single photon emission computed tomography (SPECT) scans, digital radiography images, mammography images and Fluoroscopy images. X-ray imaging is a valuable tool for diagnosis, monitoring, and treatment of many medical conditions, and its non-invasive, widely available, low cost and fast nature makes it a popular choice for many medical professionals. The proposed approach presents an algorithm for enhancing X-ray images, improving their visual appearance and making their content more useful and meaningful. The results of the algorithm show that enhanced images have a more natural look and provide accurate details of the objects in the X-ray images. Overall, this algorithm can aid in the diagnostic process by providing clearer and more detailed images for medical professionals to interpret.
Review: machine and deep learning methods in Malaysia for COVID-19 Mohammed Adam Kunna Azrag; Jasni Mohamad Zain; Tuty Asmawaty Abdul Kadir; Marina Yusoff; Tao Hai
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp514-520

Abstract

The global pandemic of the coronavirus disease COVID-19 has impacted a variety of operations. This dilemma is also attributable to the lockdown measures taken by the afflicted nations. The entire or partial shutdown enacted by nations across the globe affected the majority of hospitals and clinics until the pandemic was contained. The judgements made by the authorities of each impacted nation vary based on a number of variables, including the nation's severity of reported cases, the availability of vaccines, beds in intensive care unit (ICU), staff number, patient number, and medicines. Consequently, this work offers a thorough analysis of the most recent machine learning (ML) and deep learning (DL) approaches for COVID-19 that can assist the medical field in offering quick and exact COVID-19 diagnosis in Malaysia. This research aims to review the machine learning and deep learning methods that were used to help diagnose COVID-19 in Malaysia.
A low-power high speed full adder cell using carbon nanotube field effect transistors Ramakrishna Reddy Eamani; Vinodhkumar Nallathambi; Sasikumar Asaithambi
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp134-142

Abstract

The adder circuit is basic component of arithmetic logic design and that is the most important block of processor architecture. Moreover, power consumption is the main concern for real-time digital systems. In recent times, carbon nanotube field effect transistors (CNTFET) used for arithmetic circuit designs with high performance. A creative substitute for highspeed, less power, and small size in area designs is the CNTFET. This paper presents 1- bit full adder with CNTFETs for low power and high performance. Using the computer aided design (CAD) tool the proposed 1-bit full adder design model is simulated using 32 nm with CNTFET technology, a voltage supply of +0.9V. Performance comparisons between various proposed designs and existing 1-bit full adder design have been made in terms of the delay, power, and power delay product (PDP). The proposed CNFET logic also design for n-bit carry look adder (CLA) and compare it to other CLAs to evaluate performance and reliability. The simulation results shows that the proposed adder consume less power than existing adders.
Optimization and control algorithm for calculating separating membranes pore shapes Zhanat Umarova; Sevara D. Kurakbayeva; Aizhan T. Kalbayeva; Pernekul A. Kozhabekova; Zhalgasbek D. Iztayev; Nabat Suieuova
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp143-150

Abstract

This work was aimed at researching and developing a computer model, as well as an optimization and control algorithm for calculating pore shapes for separating membranes in separation processes. Two types of flow fluid rates through separation membranes with various pores configurations were considered. Here, the first type of pores had the form of a tortuous channel with sharp narrowing endings, which, in turn, could be assumed as “zero” wall thickness holes. The second type of pores had conical narrowing at the ends, which is closer to the real shape of the pores. As a result of the analysis of the performed calculations and models, data were obtained on the effect of the thickness of the selective layer on the performance of the membrane. In computer calculations, it was determined that the optimal volumetric porosity should be limited to 0.15, which affects the mechanical strength of the membrane. Calculations were also carried out on the Chemcad software product, which resulted in graphs of the optimal permeability of various liquids, depending on the differ curvature and pore volume of the separation membranes.
Positioning an electric wheelchair in 2D grid map based on natural landmarks for navigation using Q-learning Ba-Viet Ngo; Thanh-Hai Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp115-125

Abstract

Self-mobility electric wheelchairs are very useful for people with disabilities, so they can move without help in indoor environments. To create one selfmobility electric wheelchair, modern methods for control such as computer vision and machine learning can be applied. In particular, this electric wheelchair can move from any position in the indoor environment to the desired destination. For accuracy, natural landmarks are used and the navigation of the wheelchair is determined using a Q-learning reinforcement learning algorithm. In particular, this algorithm is applied to find the best path for the wheelchair to reach the destination. The article proposes a method to build one 2D grid map for wheelchair movement based on natural landmarks in the indoor environment. The new point of this method is that the position of the wheelchair can be accurately determined from a certain landmark instead of many landmarks applied in traditional methods. Some practical experiments were performed to illustrate the effectiveness of the proposed method in the indoor environment. This proposed method can be developed in more complex environments with natural landmarks.
Precipitation forecasting using machine learning in the region of Beni Mellal-Khenifra Hamza Jdi; Noureddine Falih
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp451-458

Abstract

Agriculture in the region of Beni Mellal-Khenifra, Morocco relies on irrigation from rain and dams, but recently there has been a lack of precipitation which may negatively affect crop growth. This has made accurate precipitation forecasts even more important for farmers, as they need this information to make informed decisions about their crops. However, a lack of data-driven research utilizing past data presents a challenge for the development of such research and leaves farmers relying solely on weather forecasts from TV, which cannot relied upon in systems such as irrigation. The objective of this paper is to propose various approaches for forecasting precipitation in the region of Beni Mellal-Khenifra using big data analytics and machine learning techniques. The study made use of Apache Spark, a big data analytics tool, and five machine-learning algorithms: Lasso regression, ridge regression, elastic net, auto regressive integrated moving average, and random forest. These algorithms were applied on dataset of daily rainfall from 2000 to 2015 to forecast the amount of precipitation in the region. The results of the study showed that the random forest algorithm had the lowest mean absolute error, making it the most effective at forecasting precipitation in the region.
Fragmentation aware heuristic algorithm for routing and wavelength assignment in optical networks Hamsaveni Mogannaiah; Savita Choudhary; Paramesha Kenchappa
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp305-312

Abstract

Wavelength division multiplexing (WDM) is one of the dominating technologies with high-capacity back bone networks. The cost associated with the high-capacity networks given more importance. The major issue is allocating and managing the available resources. To achieve this most efficient algorithms has to be used. We are considering the routing of lightpath and wavelength assignment problem, called as the routing and wavelength assignment (RWA) problem. The optimization of wavelength fragmentation in the WDM network is very much important in resource utilization. Wavelength fragmentation is one of the most important challenges in the area of the WDM network. Where it leads to some serious issues for the operators, such as the rejection of new requests. We are using integer linear program (ILP), here the problem is based on the node link formation. It is based on the multilayer concept and the original WDM network consists of several layers. We propose an efficient heuristic approach to solve this problem of finding the shortest path and assigning a wavelength without wavelength conversion. The model achieves better performance with fragmentation aware wavelength allocation strategy that minimizes fragmentation.
Efficient matrix key homomorphic encryption of medical images Prabhavathi Krishnegowda; Anandaraju M. Boregowda
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp406-416

Abstract

A sure way of providing privacy to sensitive images is to encrypt them, especially when they are stored in a public cloud server. Homomorphic encryption enables arithmetic operations over encrypted data without access to the secret key. This facility can be well harnessed for secure outsourced image processing by exploiting the available computational capabilities of modern cloud servers. This paper presents a new homomorphic image encryption scheme that uses integer matrix keys. The homomorphic operations are carried out in the finite field Zp to avail the advantages of integer arithmetic and to limit the cipher text sizes to reasonable levels. Our method does not use any error vector as in learning with errors (LWE) to improve the security.
Swarm energy efficient power efficient gathering in sensor information systems protocol in wireless sensor networks Kandrakunta Chinnaiah; Kunjam Nageswara Rao
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp459-469

Abstract

Wireless sensor network (WSN) is a network, which has more numbers of sensors that are small in nature and are self organised. The inbuilt battery system is provided in the sensor nodes through which the nodes can communicate and do good operations among the other nodes available in the network. Lifetime is the most essential parameter which needs to be maximised for the WSN. This measure is more important for conservation of energy, for adequate and efficient performance of sensor networks. This paper proposes a swarm energy efficient power efficient gathering in sensor information systems (PEGASIS) (SEE-PEG) based energy optimization algorithm for WSN in which clustering and clustering head selection are done by using modified particle swarm optimization (MPSO) algorithm with respect to minimizing the consumption of power in WSN. The parameters evaluated for the proposed method is compared with existing technique like energy efficient PEGASIS without optimization. The simulation results are obtained using matlab tool.
Automated model for identification on mastoid of temporal bone image Syafri Arlis; Sarjon Defit; Sumijan Sumijan
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp570-581

Abstract

Mastoiditis occurs due to inflammation that can affect the structure of the mastoid bone. The mastoid bone consists of the mastoid air cell system (MACS) which protects the ear structures and regulates air pressure in the ear and has different sizes and characteristics, making it very difficult to identify precisely. This study aims to identify and find the right MACS size by developing an automatic identification model and obtaining the optimal threshold value in the segmentation process using the extended adaptive threshold (eAT) method. The research dataset uses computed tomography (CT)-scan images of 308 slices of 12 patients indicated for mastoiditis. The results of this study provide identification that has the right MACS accuracy and size. Overall, the optimal segmentation process obtained the smallest threshold value of 57 and the largest threshold value of 63, the smallest MACS size is 4.025 cm2 and the largest is 8.816 cm2 with an accuracy rate of 93.4%. The smaller MACS size indicates inflammation in the mastoid area and these patients require more intensive treatment.

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