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2023 International Conference on Electrical engineering and informatics, ICEEI 2023

作者： Jeremy, Jason Hidayat, Egi Muhammad Idris Siregar, Simon Trilaksono, Bambang Riyanto Habibullah, Natsir School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Telkom University Faculty of Applied Science Department Computer Engineering Bandung Indonesia

ISBN: (纸本)9798350381290

Autonomous Underwater Gliders (AUGs) are extensively developed vehicles capable of prolonged exploration and observation in complex marine environments. Control of the AUG is challenging due to its slow response system and its constraints. In this research, a linear model representation of AutoRegressive eXogenous input (ARX) will be constructed using input and output data from the AUG system, built Model Predictive Control (MPC), analyzed the performance, comparing with traditional Proportional-Integral-Derivative (PID). The objective is to enhance setpoint tracking accuracy and minimize energy to extend exploration time while faced with constraints. Simulation results reveal MPC exhibits potential setpoint tracking, low overshoot as low as 0.6% up to 0.3m/s maximum depth rate, has relatively low input changes indicating good efficiency compared to PID. MPC approach effectively addresses slow response systems, managing momentum, and handling actuator constraints commonly encountered in AUG. © 2023 IEEE.

关键词： Model predictive control

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Classification of Alzheimer’s Disease Using the Convolutional Neural Network (CNN) with Transfer Learning and Weighted Loss

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2023年第3期50卷

作者： Oktavian, Muhammad Wildan Yudistira, Novanto Ridok, Achmad Informatics Engineering Faculty of Computer Science Brawijaya University 65145 Indonesia Informatics Engineering Faculty of Computer Science Brawijaya University 65145 Indonesia

Alzheimer’s disease is a progressive neurodegenerative disorder that gradually deprives the patient of cognitive function and can end in death. With the advancement of technology today, it is possible to detect Alzheimer’s disease through Magnetic Resonance Imaging (MRI) scans. With MRI technology and image recognition, early diagnosis of Alzheimer’s disease can be performed automatically using machine learning. Although machine learning has many advantages, currently, deep learning is more widely applied because it has more robust learning capabilities and is suitable for solving image recognition problems. However, several challenges must be faced to implement deep learning, such as the need for large datasets, computing resources, and careful parameter setting to prevent overfitting or underfitting. In responding to the challenge of classifying Alzheimer’s disease using deep learning, this study proposes the Convolutional Neural Network (CNN) with the Residual Layer (ResNet-18) architecture. Transfer learning from ImageNet and weighting the loss function are then applied so that each class has a weight depending on its size. It is proposed to overcome the need for a large and balanced dataset. Furthermore, this study experimented with changing the network activation function to a Mish activation function. From the results of the tests, the model’s accuracy of 88.30% is produced using transfer learning, weighted loss, and the Mish activation function. This accuracy is better than the baseline model, which only gets an accuracy of 69.10%. © (2023), (International Association of Engineers). All Rights Reserved.

关键词： Chemical activation

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Implementation of Convolutional Neural Network for COVID19 Screening using X-Rays Images

Implementation of Convolutional Neural Network for COVID19 S...

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2023 International Conference on computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Delimayanti, Mera Kartika Mardiyono, Anggi Warsuta, Bambang Puspitaningrum, Eka Suci Naryanto, Rizqi Fitri Naryaningsih, Agustien Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Indonesia Universitas Negeri Semarang Faculty of Engineering Department of Mechanical Engineering Indonesia Fisheries Research Center Indonesia

ISBN: (纸本)9798350320954

Various unwelcome conditions have existed since the introduction of the novel coronavirus illness (COVID-19). COVID-19 can cause fever, muscle soreness, shortness of breath, cough, headache, and other symptoms. Diagnosis at an early stage is a crucial aspect of successful treatment. Therefore, it is necessary to seek out alternate methods for COVID-19 detection. Among the existing imaging resources, X-ray images are generally accessible and inexpensive. Consequently, an alternate diagnostic tool for detecting COVID-19 instances is provided using available resources. In the first stages of COVID-19, X-rays detected the disease before it spread to the lungs and caused more damage. Machine learning models can help clinicians accomplish jobs more quickly and accurately. In addition to chest X-ray pictures and fundus images, deep learning algorithms have been used to diagnose illnesses. This research was conducted to classify the X-ray chest images in COVID-19 and normal cases based on the public datasets which were used. This analysis uses 5600 images from the accessible resources, and a Convolutional Neural Network (CNN) architecture with the VGG16 algorithm was employed to diagnose COVID19. VGG16 is object identification and classification method that can classify with greater precision than most other deep learning algorithms. Transfer learning and fine-tuning were employed to help for improving the performance. The results showed that the VGG16 network had an accuracy of 98.13%. This research has implications for the early detection of COVID-19 by using X-ray images. The experiment and analysis reveal our suggested method's promising and stable performance compared to the current standard. © 2023 IEEE.

关键词： COVID-19

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Implementation of the SMART Method and Location Based Service Technology in a Sewing Service Search Application 9

Implementation of the SMART Method and Location Based Servic...

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9th IEEE Information Technology International Seminar, ITIS 2023

作者： Mumpuni, Retno Santoso, Bagus Jati Wahanani, Henni Endah Rahajoe, Ani Dijah Maulana, Hendra Maghfiro, Feronika Nur Universitas Pembangunan Nasional 'Veteran' Jawa Timur Faculty of Computer Science Department of Informatics Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia

ISBN: (纸本)9798350306835

The tailoring business involves services where tailors create or repair clothing. Currently, the number of tailors with various skill sets is on the rise. However, customers often struggle to find tailors who meet their specific needs. They have to spend time visiting tailor shops, just to assess whether a tailor is a suitable match or to place an order, even when the distance and location are uncertain. This inefficiency hampers the process. In this rapidly advancing technological era, many businesses leverage technology to promote their services, including the tailoring industry. To address this issue, the author aims to develop an Android-based Tailor Locator Application that utilizes Location Based Services (LBS) and the SMART Method. This application will utilize LBS technology to display the distance and location between customers and tailors, while continuously updating the location information of both customers and tailors. The application will also implement the SMART method to rank tailors based on ratings and provide tailor recommendations. © 2023 IEEE.

关键词： Location based services

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A Neutrosophic based C-Means Approach for Improving Breast Cancer Clustering Performance

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Neutrosophic Sets and Systems 2023年 53卷 317-330页

作者： Abdelhafeez, Ahmed Mohamed, Hoda K Maher, Ali Abdelmonem, Ahmed Faculty of Information Systems and Computer Science October 6th University Cairo12585 Egypt Faculty of Engineering Ain shams University Cairo11566 Egypt Military Technical College Cairo18711 Egypt Faculty of computers and informatics Zagazig University Zagazig11544 Egypt

Breast cancer is among the most prevalent cancers, and early detection is crucial to successful treatment. One of the most crucial phases of breast cancer treatment is a correct diagnosis. Numerous studies exist about breast cancer classification in the literature. However, analyzing the cancer dataset in the context of clusterability for unsupervised modeling is rare. This work analyzes pointedly the breast cancer dataset clusterability via applying the widely used c-means clustering algorithm and its evolved versions fuzzy and neutrosophic ones. An in-depth comparative study is conducted utilizing a set of quantitative and qualitative clustering efficiency metrics. The study's outcomes divulge the presented neutrosophic c-means clustering superiority in segregating similar breast cancer instances into clusters © 2023, Neutrosophic Sets and *** Rights Reserved.

关键词： Diseases

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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore Software Maintenance

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computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the Internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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AVIG: A Real-Time Visual Inspection for Guava Grading System Using computer Vision and XGBoost 23

AVIG: A Real-Time Visual Inspection for Guava Grading System...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Setyawan, Raden Arief Perdana, Rizal Setya Harilegawa, Made Wena Balantimuhe, Alan Stevrie Basuki, Achmad Department of Electrical Engineering Faculty of Engineering Brawijaya University Malang Indonesia Department of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia Directorate of Information Technology Brawijaya University Malang Indonesia

ISBN: (纸本)9798400708503

The conventional approach to manual inspection can be described by its considerable time and labor demands and the unavoidable occurrence of human error when faced with the inspection of a large number of products. Therefore, the application of an automated visual inspection system is frequently employed. The camera(s) can easily capture visual features for automatic visual inspection. However, it is essential to note that there are limitations when using this method to estimate the size-based grading system. The volume measurement is an essential feature in the field of automatic image analysis for fruit and vegetable grading, specifically guava. In this study, we propose a novel image analysis approach that utilizes a dual-view camera system to enhance the accuracy of volume approximation, particularly in scenarios involving non-perfect spherical objects. Hence, this research presents the training process of a comprehensive model for estimating the volume of objects with irregular shapes, named AVIG (Automatic Visual Inspection for Grading). The model utilizes the ellipsoid approximation technique, a dual-view camera, and XGBoost algorithm. The results from the accuracy comparison demonstrate that XGBoost shows the highest degree of accuracy, specifically 86%, thereby outperforming the performance of other algorithms. The comprehensive experiment conducted in this study has shown that the proposed architecture, AVIG, exhibits superior performance compared to previous research in terms of automatic evaluation of moving objects. © 2023 ACM.

关键词： computer vision

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Numerical P Systems: Variants and Applications 24

Numerical P Systems: Variants and Applications

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24th Conference Information Technologies - Applications and Theory, ITAT 2024

作者： Bobe, Radu Traian Gheorghe, Marian Ipate, Florentin Niculescu, Ionuţ Mihai Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Str Academiei 14 Bucharest010014 Romania Faculty of Engineering and Informatics University of Bradford Bradford West YorkshireBD7 1DP United Kingdom

Numerical P systems are compuational models which are inspired by cellular processes and use numerical values inside the membrane structure. In this paper we will present the variants of numerical P systems that have been proposed in the literature. In particular, we will discuss the advantages introduced by these extensions in terms of Turing completeness and potential applications. Moreover, using a reference example, we will experiment a mapping between some important numerical P systems variants. © 2024 CEUR-WS. All rights reserved.

关键词： Membrane structures

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Test-Driven Simulation of Robots Controlled by Enzymatic Numerical P Systems Models 15th

Test-Driven Simulation of Robots Controlled by Enzymatic N...

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15th EAI International Conference on Simulation Tools and Techniques, SIMUTools 2023

ISBN: (纸本)9783031575228

The simulation of robots behavior and the use of robust models are very important for building controllers. Testing is an important aspect in this process. In this paper, a test-driven approach for designing robot controllers based on enzymatic numerical P systems models is introduced. Four such models are defined and tested using three distinct scenarios. The paper reveals an effective way of using modelling, simulation and testing in a coherent way. © ICST Institute for computer Sciences, Social informatics and Telecommunications engineering 2024.

关键词： Controllers

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Overview of Load Disaggregation Models, Methods and Hardware 59

Overview of Load Disaggregation Models, Methods and Hardware

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59th International Universities Power engineering Conference, UPEC 2024

作者： Lancranjan, Mircea N. Muresan, Alexandru Jurj, Dacian I. Berciu, Alexandru Polycarpou, Alexis Czumbil, Levente Micu, Dan D. Technical University of Cluj-Napoca Department Electrical Engineering Cluj-Napoca Romania Technical University of Cluj-Napoca Faculty of Automation and Computer Science Cluj-Napoca Romania Department of Electrical and Computer Engineering and Informatics Frederick University Nicosia Cyprus

ISBN: (纸本)9798350379730

In the dynamic landscape of energy efficiency, a domain garnering ever increasing attention and urgency, the cornerstone of informed decision-making resides in the acquisition of reliable data. This paper summarizes the main approaches, methods and hardware used to gather, process and disaggregate such data on an appliance-by-appliance basis. The paper explores a critical analysis of the various models and techniques that support the gathering of energy data at the appliance level. A range of approaches, including hardware-based solutions such as smart meters, submeters, and sensor arrays, placing a special focus on intrusive load monitoring (ILM) and non-intrusive load monitoring (NILM) algorithms that employ advanced signal processing and machine learning techniques, are examined for their effectiveness, scalability, and suitability for both industrial and commercial contexts. Furthermore, the challenges of data acquisition capabilities, reconciling scalability, cost-effectiveness, and user-friendliness - prerequisites for widespread acceptance and uptake are also investigated. © 2024 IEEE.

关键词： AI Data Cleaning Energy Efficiency Energy Signature Load Disaggregation Load Monitoring NILM

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