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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 64 Documents
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Search results for , issue "Vol 28, No 1: October 2022" : 64 Documents clear
Fully automated model on breast cancer classification using deep learning classifiers Mudhafar Jalil Jassim Ghrabat; Zaid Alaa Hussien; Mustafa S. Khalefa; Zaid Ameen Abduljabbar; Vincent Omollo Nyangaresi; Mustafa A. Al Sibahee; Enas Wahab Abood
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp183-191

Abstract

Deep learning models on the same database have varied accuracy ratings; as such, additional parameters, such as pre-processing, data augmentation and transfer learning, can influence the models’ capacity to obtain higher accuracy. In this paper, a fully automated model is designed using deep learning algorithm to capture images from patients and pre-process, segment and classify the intensity of cancer spread. In the first pre-processing step, pectoral muscles are removed from the input images, which are then downsized. The removal of pectoral muscles after identification may become crucial in classification systems. Finally, the pectoral musclesaredeleted from the picture by using an area expanding segmentation. All mammograms are downsized to reduce processing time. Each stage of the fully automated model uses an optimisation approach to obtain highaccuracy results at respective stages. Simulation is conducted to test the efficacy of the model against state-of-art models, and the proposed fully automated model is thoroughly investigated. For a more accurate comparison, we include the model in our analysis. In a nutshell, this work offers a wealth of information as well as review and discussion of the experimental conditions used by studies on classifying breast cancer images.
Major depressive disorder diagnosis based on PSD imaging of electroencephalogram EEG and AI Ammar Falih Mahdi; Aseel Khalid Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp535-544

Abstract

One of the most common causes of functional frailty is major depressive disorder (MDD). MDD is a chronic condition that requires long-term therapy and professional assistance. Additionally, MDD effective treatment requires early detection. Unfortunately, it has intricated clinical characteristics that make early diagnosis and treatment difficult for clinicians. Furthermore, there are currently no clinically effective diagnostic biomarkers that can confirm an MDD diagnosis. However, electroencephalogram (EEG) data from the brain have recently been used to make a quantitative diagnosis of MDD. In addition, As being among the most cutting-edge artificial intelligence (AI) technologies, deep learning (DL) has exhibited superior performance in a wide range of real-world applications, from computer vision to healthcare. However, an additional challenge could be the extraction of information from the ECG raw data. This paper presents a method for converting EEG data to power spectral density (PSD) images, and then they were classified as healthy or MDD using a deep neural network for feature extraction and a machine learning (ML) classifier. When employing the proposed approach, the images formed from the PSD show a considerably improved performance in classification results.
IoT-based drinking water quality measurement: systematic literature review Yulieth Carriazo-Regino; Rubén Baena-Navarro; Francisco Torres-Hoyos; Juan Vergara-Villadiego; Sebastián Roa-Prada
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp405-418

Abstract

Sustainable development throughout the world depends on several factors such as the economy, quality education, agriculture, industry, among others, but the environment is one of the most important. Industrialization and new land use plans have caused the proliferation of pollutants in water resources, which poses a serious public challenge. As outlined in the sustainable development goals (SDGs), innovative water quality monitoring methods are needed to ensure access to water, sustainable management and sanitation. In this sense, technologies are sought that contribute to the development and implementation of groundwater and surface water quality monitoring systems in real time, so that their parameters can be evaluated through descriptive analysis, in rural populations and areas of difficult access. Nowadays, the internet of things (IoT) and the development of modern sensors are more used, so this research reviews the latest technologies to monitor and evaluate water quality using the potential and possibilities of the IoT. The main contribution of this article is to present an overview of the state of the art of IoT applications and instrumentation for water quality monitoring, focusing on the latest innovations, in order to identify interesting and challenging areas that can be explored in future research.
Development of data encryption standard algorithm based on magic square Suhad Muhajer Kareem; Abdul Monem S. Rahma
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp297-305

Abstract

Data encryption standard is one of the famous algorithms that used in many fields for security purpose but it s susceptible for many attacks. This paper+ proposes a new modification of data encryption standard (DES) algorithm called magic square data encryption standard (MSDES) algorithm in order to include a high-level security by increase the mixing between the plaintext (96 bit) and the key (48 bit). This modification is done by using magic square 3×3 and an additional key is created using linear first shift register (LFSR) in each round of the Feistel of DES. A colour image encryption is simulated and presented as the comparison between the original DES and MSDES algorithm. The proposed algorithm gets the best results in complexity, histogram, entropy, peak-signal-to-noise ratio-(PSNR) and coefficient-correlation.
Estimation of channel distortion in orthogonal frequency division multiplexing system using pilot technique Nisha Mary Joseph; C. Puttamadappa
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp106-114

Abstract

Orthogonal frequency-division multiplexing (OFDM) is resistant to frequency selective fading due to the longer symbol duration. However, mobile applications channel timing fluctuations in one OFDM signal cause intercarrier-interference (ICI), which reduces performance. This research presented the support vector regression (SVR) model-based channel estimation technique for coherent optical communication systems. Due to the coherent optical orthogonal frequency-division-multiplexed (COOFDM) system, a channel model is developed that includes linear fibre dispersion effects, noise from optical amplifiers, and inter-carrier interference generated by laser phase noise. As a result, for such a system, an accurate channel estimate is essential. Based on this concept, derivation of channel estimation and phase estimation for the system of CO-OFDM. The proposed method is tested and evaluated using MATLAB software. Computer simulation results for several standard methods such as extreme learning machines (ELM) and artificial neural networks (ANN) validate the feasibility of the suggested methodology. The CO-OFDM system’s transmission experiments and computer simulations prove that the support vector machine-based model following pilot-assisted phase estimation gives the optimal performance. Therefore, results depicted that the channel estimation utilizing the SVR model gives good performance than the other methods, thus the proposed model gives an accurate CE process, respectively.
Reliable efficient cluster routing protocol based HTDE scheme for UWSN Vignesh Prasanna Natarajan; Kavitha Thandapani
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp498-507

Abstract

Underwater sensor networks (UWSNs) are recently recognized as a promising method for monitoring and exploring the underwater environment. Due to real-time remote data monitoring requirements, UWSN has become a preferred network to a large extent. But reliable and efficient secure data transmission to the receiver is one of the most important challenges for UWSNs, often suffer from irreplaceable batteries and high latency for long-distance communications. The most challenging task is extending network life, shortening transmission distances for each node. Thus, this paper presents the reliable efficient cluster routing (RECR) protocol, optimal shortest path finding (OSPF) algorithm and hill transformation data encryption (HTDE) algorithm for UWSNs. The proposed encryption algorithm encrypts the data from the source node, and the RECR protocol is used for reliable data delivery from source to destination. To extend the network's life, RECR employs autonomous underwater vehicle (AUV) from the sink node (SN) for data collection. The OSPF algorithm is used to find the shortest path for data transmission to avoid latency. The proposed RECR protocol, HTDE and OSPF algorithm enhance the secure data transmission efficiency, minimizing the energy consumption and improves the network life time. The proposed protocol decreases end-to-end latency, packet loss.
Sentiment analysis through twitter as a mechanism for assessing university satisfaction Omar Chamorro-Atalaya; Dora Arce-Santillan; Guillermo Morales-Romero; César León-Velarde; Primitiva Ramos-Salaza; Elizabeth Auqui-Ramos; Miguel Levano-Stella
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp430-440

Abstract

Currently, the data generated in the university environment related to the perception of satisfaction is generated through surveys with categorical response questions defined on a Likert scale, with factors already defined to be evaluated, applied once per academic semester, which generates very biased information. This leads us to wonder why this survey is applied only once and why it only asks about some factors. The objective of the article is to demonstrate the feasibility of a proposal to determine the degree of perception of student satisfaction through the use of data science and natural language processing (NLP), supported by the social network twitter, as an element of data collection. As a result of the application of this proposal based on data science, it was possible to determine the level of student satisfaction, being 57.27%, through sentiment analysis using the Python library "NLTK"; Thus, it was also possible to extract texts linked to the relevant factors of teaching performance to achieve student satisfaction, through the term frequency and inverse document frequency (TF-IDF) approach, these being those linked to the use of tools of simulation in the virtual learning process.
Secure authentication and privacy-preserving to improve video streaming vehicle ad-hoc network Akeel Kassim Leaby; Mustafa Khalefa; Mushtaq A. Hasson; Ali A. Yassin
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp480-487

Abstract

In vehicular ad hoc networks (VANET), the privacy of vehicle data symbolizes a big challenge towards malicious attacks. On the other side, vehicles in VANET can play a staple role in monitoring the environment by sensing the surrounding environment, compute the sensing information, and transfer the results if needed to the authorized party. Most of the modern VANETs systems encrypt the information to prevent hacking it but mostly neglect the decryption that occurred when data need to re-processed. In this paper, we try to cover this weak point by using fully homomorphic encryption (FHE) because of its specifications. The proposed work focus on twofold: first, create secure authentication and permission management system. While the second is to preserve the privacy of vehicle data that transferred among VANET infrastructure. This scheme also deals with metric security features, such as data privacy, data integrity, and key management. In the experimental results, there is good advance in the fields of interest comparing with the related works.
Binary decomposition-based image cipher algorithm with flexible method for key construction Salim Muhsin Wadi; Huda Hussein Abed; Nada Taher Malik; Ahmed Taha Abdullsadah
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp201-208

Abstract

Image security is still one of the important fields in multimedia processing because it’s used in our daily lives. Watermarking, steganography, and ciphering are three directions to keep an image secret. Encryption defined as the process of changing information (which called plaintext) into an unreadable secret format (which called cipher-text). A new ciphering algorithm based on binary decomposition and binary codes conversion is proposed in this paper. The key is constructed in a flexible way based on the size of a secret image using some logical operations to increase the security levels. Three test images in different sizes were used to evaluate the performance of the proposed algorithm. The results of the visual scene and statistical factors proved that the suggested method was ciphering the image with high security. The proposed work was validated to confirm its effectiveness. As conclusions, the uses of decomposition and simple binary operations have given high-level image security. Also, key construction is an important step to face several types of attackers.
Adaptive Wi-Fi offloading schemes in heterogeneous networks, the survey Ruliyanta Ruliyanta; Mohd Riduan Ahmad; Azmi Awang Md Isa
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp254-268

Abstract

At present, the need for data traffic is experiencing tremendous growth. The growth of smartphones technology offers new applications. On the other hand, the growth in cellular network access infrastructure has not been able to keep up with the increasing demand for data package services. For this reason, Wi-Fi offloading is needed, namely cellular users, using Wi-Fi access for their data needs. In 2016, global data communication traffic growth reached 63%. Many researchers have proposed the adaptive wireless fidelity (Wi-Fi) offloading (AAWO) algorithm to transfer data on heterogeneous networks. In this study, the proposed adaptive incentive scheme is classified, to obtain an adaptive scheme based on cost, energy, service quality, and others. From the survey results shown, there is no proposed adaptive algorithm based on the quality of experience (QoE). This provides an opportunity for further research where the Wi-Fi offloading scheme uses the perspective user or user experient options. In addition, open research uses artificial intelligence and machine learning methods as adaptive methods.

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