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Comments on a Key Agreement Scheme for the V2G System 14th

Comments on a Key Agreement Scheme for the V2G System

引用

14th International Conference on Frontier Computing, FC 2024

作者： Chang, Ya-Fen Chang, Wen-Ting Tai, Wei-Liang Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung Taiwan

ISBN: (纸本)9789819623945

Vehicle-to-grid (V2G) technology supporting bidirectional power transfer allows electric vehicles (EVs) to contribute and consume energy bidirectionally. Because the specific properties and requirements of V2G, Khan et al. proposed a key agreement scheme for the V2G system to ensure the security of communication between a vehicle user and the grid server. However, after analyzing Khan et al.’s scheme, we find that it suffers from some flaws such that it cannot ensure anonymity, resist impersonation attack, man-in-the-middle attack and denial-of-service attack, and work as expected. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Anonymity

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A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

引用

2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

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DigiEMine: Towards Leveraging Decision Mining and Context Data for Quality Control 28th

DigiEMine: Towards Leveraging Decision Mining and Context D...

引用

28th International Conference on Enterprise Design, Operations, and Computing, EDOC 2024

作者： Wais, Beate Rinderle-Ma, Stefanie Faculty of Computer Science Research Group Workflow Systems and Technology University of Vienna Vienna Austria UniVie Doctoral School Computer Science DoCS University of Vienna Vienna Austria TUM School of Computation Information and Technology Technical University of Munich Garching Germany

ISBN: (纸本)9783031783371

Quality control processes in manufacturing often still rely on manual tasks. Applying decision mining can support users by providing valuable insight into the process. This paper discusses the potential of integrating contextual information into decision mining to achieve accurate and meaningful decision rules in the context of a case study stemming from the manufacturing domain. To explore this, a new approach, DigiEMine, is presented, which addresses the gap between information extraction and practical decision mining applications by integrating information extracted from engineering drawings with time sequence data in the form of diameter measurements of workpieces. The discovery of relational decision rules is enabled, allowing for contextualization of the decision rules. The output of this approach is presented in both textual decision rules and visually on engineering drawings, empowering users to make informed quality control decisions. The case study includes three datasets originating from cylindrical workpiece production. Results demonstrate the feasibility of the approach and the ability to generate meaningful decision rules across the tested datasets. Its potential applicability extends beyond the presented case study, with conceivable scenarios in multiple domains, such as healthcare or logistics, where integrating context information, such as regulatory data, with time sequence data is required to provide additional context for decisions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Data quality

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7th International Conference of computer and Informatics Engineering, IC2IE 2024

作者： Wandy, Wandy Adi, Kusworo Ayu, Media Anugerah Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science South Jakarta Indonesia

ISBN: (纸本)9798331505530

Full-marathon and Half-marathon distances are categorized as road running. Full-marathon running is becoming increasingly popular, and Half-marathon is increasing worldwide in both sexes and all age groups. Some aspects might relate to Full-marathon and Half-marathon running performance during training and races. technology also plays an essential role in supporting runners and running races. technology like artificial intelligence (AI) now supports the running athlete, not only predicting performance and results. It can also be used later to help the coach generate training programs for the athlete. This research aimed to find many aspects of marathons and performance and analyze them to see if artificial intelligence could later support them. It used secondary data and a systematic literature review proposed by Kitchenham. Out of the 58 articles, 21 of them (36.21%) received a score of 1 from Q1. Additionally, 19 articles (32.76%) received a score of 1 from both Q2 and Q3. Among the 58 articles, 9 (15.52%) received a total score of 3, with all three Q1, Q2, and Q3 scores being 1. This indicates that artificial intelligence will likely support the content of these nine articles. Several factors were also discovered to be connected to marathons and athletic performance. These findings suggested that additional investigation into marathons and performance, later backed by artificial intelligence, remained pertinent and essential. © 2024 IEEE.

关键词： artificial intelligence aspects marathon performance

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Analyzing User Comments on Fintech E-wallet Applications in Indonesia Using the LDA Algorithm 7

Analyzing User Comments on Fintech E-wallet Applications in ...

引用

7th International Conference on information technology, InCIT 2023

作者： Widiantoro, Albertus Dwiyoga Mustafid, Mustafid Sanjaya, Ridwan Diponegoro University Doctoral Program of Information System School of Postgraduate Studies Semarang Indonesia Soegijapranata Catholic University Information System Computer Science Fakulcty Semarang Indonesia

ISBN: (纸本)9798350358698

The main objective of this article is to compare user comments from 4 Fintech applications in Indonesia using the Latent Dirichlet Allocation (LDA) algorithm. This research is word processing research carried out using text mining. The statistical population is comments from Fintech users Ovo, Dana, LinkAja, and Doku, with data taken from May 2022-May 2023. LDA and the Python programming language are applied to analyze the data and implement text mining algorithms from topic modeling. Each application group has different topic coherence, each application group is analyzed and 4 large categories are found, namely system convenience, system problems, customer service (CS) problems, and service ease. The results of text mining and processing using Coherence and Latent Dirichlet allocation can be used to identify hidden topics and be used as input for system improvements © 2023 IEEE.

关键词： Population statistics

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Clustering Satellite Images of Forest Area Change in Nabire Regency with NDVI, SAVI, MSAVI, VCI, TCI, dan VHI Method 6

Clustering Satellite Images of Forest Area Change in Nabire ...

引用

6th International Seminar on Research of information technology and Intelligent Systems, ISRITI 2023

作者： Prayitno, Gunawan Sediyono, Eko Sembiring, Irwan Prasetyo, Sri Yulianto Adi, Puput Dani Prasetyo Satya Wacana Christian University Indonesia Doctoral Program of Computer Science Faculty of Information Technology Salatiga Indonesia Satya Wacana Christian University Indonesia Salatiga Indonesia Bandung Indonesia

ISBN: (纸本)9798350358346

Based on data from the Forestry and Plantation Service of Nabire Regency, the forest area in Nabire Regency is 3.26% of the total forest area in Papua, which is 42,224,840 Ha. The existence of forests in Nabire Regency greatly supports the survival of unique animals such as cuscus, birds of paradise, cassowary, peacocks, and parrots, and there are also various types of reptiles, mammals, and insects. By looking at the diversity of animals and ornamental plants in the forests of Nabire Regency, further research is needed to see the development and change of forests as an effort to estimate forest destruction. This research focuses on developing a research model to classify forest areas as vulnerable to collapse. The methods used in this study used OLI Landsat 8 satellite imagery and advanced analysis methods to assess and predict potential forest destruction in Nabire District, Indonesia;using OLI Landsat 8 satellite imagery and multi-band sensors, the developed research model can present a systematic approach that understands forest dynamics. Research has several stages, such as data preparation, data classification, vegetation index analysis, interpolation, and grouping of vegetation index data. Applying vegetation indices such as NDVI, SAVI, MSAVI, VCI, TCI, and VHI yields insights into vegetation health and distribution, enabling comprehensive monitoring of ecosystem change. © 2023 IEEE.

关键词： Landsat

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Leveraging Attention to Achieve Generalization for Image Forgery Detection 1

Leveraging Attention to Achieve Generalization for Image For...

引用

1st International Conference of Intelligent Methods, Systems and Applications, IMSA 2023

作者： Atta, Mohamed Nile University Artificial Intelligence Program School of Information Technology and Computer Science Giza Egypt

ISBN: (纸本)9798350335569

Recently, image forgery has become an alarming trend with the growth of available easy-to-use editing and generation tools. Modern DeepFake methods have achieved extraordinary progress in realistic face manipulation, thus raising concerns among the public about the misuse of such technologies. Unfortunately, with the obnoxiously wide range of possible manipulation and artifact-covering methods, most existing state-of-the-art detection methods lack the generalization capability to handle the output variations. To address this issue, a noticeable shift towards using attention mechanisms has emerged using balanced portions of the latest challenging datasets to detect intra-and inter-spatial relations. Our paper provides a comprehensive analysis of modern deep learning-based methods, showing the benefits of the shift. In addition, we make propositions for future research directions and dataset-building methodology. © 2023 IEEE.

关键词： Generative adversarial networks

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Enabling Smart Home Energy Management through Gesture-Based Control and IoT technology

Enabling Smart Home Energy Management through Gesture-Based ...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Rambe, Khairul Hawani Ou, Chia-Ho International Master Program in Information Technology and Applications Sweden National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

The Internet of Things (IoTs) have become ubiquitous in all aspects of public needs today. The application of IoT technology is crucial for promoting energy-saving behavior. This paper presents a control system used for smart home devices based on hand gesture control and Android applications. The hardware design uses the ESP32 microcontroller, which has an in-chip Wi-Fi module, making it very suitable for creating IoT application systems. The software was designed using the Arduino IDE, and the application display design was developed using Kodular Creator, which is used to control the lamps and switches. The experiment results show that the electrical equipment can be activated using the Android application with gesture sensors by waving down, up, left, and right. © 2023 IEEE.

关键词： Internet of things

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Advancements in Deep Learning Optimization for Post-Earthquake Building Damage Detection A Systematic Review

Advancements in Deep Learning Optimization for Post-Earthqua...

引用

2024 International Conference on Advanced information Scientific Development, ICAISD 2024

作者： Sonang, Sahat Yuhandri, Y. Tajuddin, Muhammad Universitas Putra Indonesia Yptk Information Technology Study Program Padang Indonesia Universitas Bumigora Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350392036

This study conducts a systematic literature review (SLR) that focuses on optimizing deep-learning techniques for post-earthquake building damage detection. By employing the PRISMA protocol, this review aimed to collect, analyze, and summarize the findings of various studies published between 2014 and 2024. This research identifies and evaluates optimization methods such as hyperparameter tuning, transfer learning, and data augmentation, highlighting their effectiveness and implementation. Challenges such as data quality, computational costs, and model interpretability were also discussed. The findings indicate that while deep learning techniques significantly enhance the accuracy and efficiency of damage detection, further research is required to address existing challenges and improve model robustness in diverse earthquake scenarios. © 2024 IEEE.

关键词： Contrastive Learning

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Feature Learning using Deep Variational Autoencoder for Prediction of Defects in Car Engine

Feature Learning using Deep Variational Autoencoder for Pred...

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2024 International Conference on information technology Research and Innovation, ICITRI 2024

作者： Susanto, Nanang Pardede, Hilman Ferdinandus Universitas Nusa Mandiri Computer Science Study Program Jakarta Indonesia National Research and Innovation Agency Indonesia Universitas Nusa Mandiri Computer Science Faculty of Information Technology Jakarta Indonesia

ISBN: (纸本)9798350376210

Machine learning has been employed to automatically detect the defects on car engines in several studies. One of crucial challenges on applying machine learning is on the amount of defect data collected is often large with high dimensional data, making manual detection inefficient and inaccurate. The other problem is on the missing data as oftentimes the collected data are incomplete. In this paper, we employ machine learning frameworks for engine defect detection. It comprises the data pre-processing stage which includes imputing missing value data, then performing feature correlation using the Pearson method, and selecting the features to use. After that, the label encoder and standard scaler are carried out. The experimental process begins with creating a baseline, then continues with improving imbalance data using SMOTE, and feature reconstruction using variational autoencoder (VAE). Afterwards, for classification, we employ convolutional neural networks (CNN). The proposed method achieved precision 99.63%. We collect engine quality dataset of 224,239 data with 90 features from major automobile manufacturing in Indonesia. This showed that SMOTE and Variational Autoencoder dimensional reconstruction method can overcome defect predictions in car engine defect data with data imbalance conditions. This novel methodology distinguished our study from prior methods and shows considerable increases in precision and recall matrix. © 2024 IEEE.

关键词： Convolutional neural networks

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