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Journal of Energy Systems 2023年第1期7卷 57-66页

作者： Tanrıverdi, Harun Karakuş, Güzide Ulukan, Ahmet Abdullah Gul University Graduate School of Engineering and Science Electrical and Computer Engineering Kayseri Turkey Necmettin Erbakan University Faculty of Aeronautics and Astronautics Department of Aviation Management Konya Turkey

The facilities on wind energy generation are increasingly finding usage areas in line with the ecologically friendly energy generation approach. One of the important activities of wind power generation facilities, which have high investment cost, low operating cost and low environmental impact is the maintenance and repair of wind turbines. A preventive maintenance approach is dominant to reduce maintenance times and eliminate lost time in wind turbines. Damage inspection of turbines has been evolved from tower crane access, rope access, camera viewing, and other applications to image with manual drones over the years. However, when these methods are evaluated within the framework of criteria such as cost, performance, occupational safety and data reliability, they are still insufficient and the need for inspection with autonomous drones arises. The advantages and disadvantages of autonomous drones used in the determination of damage in wind turbines are analyzed and the results are considered to contribute to the practitioners operating in the sector and academicians working in the field. © 2023 Published by peer-reviewed open access scientific journal.

关键词： Wind power

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An Event-Trigger-Based Variable Gain Robust Formation Control for Multi-Agent Systems with Mismatched Uncertainties 3

An Event-Trigger-Based Variable Gain Robust Formation Contro...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Asada, Daiki Sawato, Hayate Takahashi, Haruto Shibuya, Kouki Oya, Hidetoshi Hoshi, Yoshikatsu Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University Department of Computer Science Tokyo Japan

ISBN: (纸本)9798331540319

This paper proposes a design method for an event-trigger-based robust formation controller for multi-agent systems (MASs) with mismatched uncertainties. The multi-agent system under consideration has a leader-follower structure. The pro-posed control law consists of stabilizing state feedback inputs, state feedback inputs for consensus, and compensation inputs with adjustable parameters, and is designed by explicitly taking relative positions into account. In this paper, we show that sufficient conditions for the existence of the proposed robust formation control system are provided in terms of Linear Matrix Inequalities (LMIs). © 2024 IEEE.

关键词： State feedback

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Adaptive Gain Robust Preview Controllers for Uncertain Linear Discrete-Time Systems 3

Adaptive Gain Robust Preview Controllers for Uncertain Linea...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Shibuya, Kouki Asada, Daiki Sawato, Hayate Takahashi, Haruto Hoshi, Yoshikatsu Oya, Hidetoshi Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University The Department of Computer Science Tokyo Japan

ISBN: (纸本)9798331540319

This paper deals with a design method of adaptive robust preview controllers for uncertain linear discrete-time systems. The proposed control law consists of a state feedback term, an integral one, a preview input and a compensation input with adjustable parameters. In this paper, we show that sufficient conditions for the existence of the proposed adaptive robust preview controllers are given in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to demonstrate the effective of the proposed approach. © 2024 IEEE.

关键词： Discrete time control systems

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Smart Services Implementation in Smart Cities: A Comprehensive Review of State-of-the-art Technologies 23

Smart Services Implementation in Smart Cities: A Comprehensi...

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5th International Conference on Management science and Industrial engineering, MSIE 2023

作者： Arin, Ikrar Adinata Supangkat, Suhono Harso Gaol, Ford Lumban Ranti, Benny Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Indonesia Smart City and Community Innovation Center Institut Teknologi Bandung Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Indonesia

ISBN: (纸本)9798400708381

This paper discusses comprehensively the advanced technologies used in the implementation of smart services, which are key elements of a smart city. Smart cities are becoming eco-friendly, livable, and sustainable to deliver essential services to their citizens by leveraging internet and communication technology advancements. Starting from a short literature review about smart cities and smart services, a recent trend in the technology used to implement smart services is collected. Smart service can be defined as a service conveyed using intelligent products that possess awareness and connectivity. All kinds of smart services can be connected in smart cities to offer citizens comprehensive solutions. Pre-emptive services, self-services, or highly interactive services, for example, have the potential to be implemented using current technology such as the internet of things, artificial intelligence, cloud computing, big data, machine learning, machine-to-machine communications, and the digital twin. Therefore, there is scope for research and implementation of other technology for smart services in the future. © 2023 ACM.

关键词： Smart city

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Investigating the Impact of Data Augmentation for Fine-Grained Grocery Product Classification Based on Vision Transformer

Investigating the Impact of Data Augmentation for Fine-Grain...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Rahmania, Rissa Heryadi, Yaya Lukas, Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

The existence of fine-grained image classification supporting smart retail provides effectiveness in recognizing products with high similarity. However, the generic classification method performs poorly in identifying products from a subordinate category. This paper aims to identify augmentation techniques to leverage the Vision Transformer (ViT) model to classify the fine-grained grocery product, which involves embedding patches and transformer encoders to extract the main features. First, we develop a fine-grained image dataset with ColorJitter, CutOut, and combining both augmentations. Secondly, we perform experiments and analysis of ViT size, embedded patch size and image size in the patch embedding process. Lastly, the ViT model are evaluated according to the image sizes 224, 384, and 512 in accuracy, loss, and confusion matrix. The highest accuracy was obtained at 0.9922. The ColorJitter and CutOut improved the confusion matrix in ViT-B/16 and ViT-L/16 with an image size of 384 and 512. The results show that both augmentations in the ViT model are able to distinguish fine-grained grocery products. © 2023 IEEE.

关键词： Embeddings

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Machine Learning Approaches in Detecting Autism Spectrum Disorder 8

Machine Learning Approaches in Detecting Autism Spectrum Dis...

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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Daniel Dominic, Nicholas Cenggoro, Tjeng Wawan Pardamean, Bens Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Early detection of Autism Spectrum Disorder (ASD) needs to be increased to prevent further adverse impacts. Thus, the classification between ASD and Typically Development (TD) individuals is an intriguing task. This review study has collected 26 related papers to answer four research questions, i.e., what are the most used data inputs, brain atlases, and machine learning models for ASD classification, as also to discover the significant parts of the brain correlated with the ASD. It was eventually found that functional connectivity matrix, Support Vector Machine, and CC200 are the most frequently used data input, model, and brain atlas, respectively. Researchers also concluded that the posterior temporal fusiform cortex, intracalcarine cortex, cuneal cortex, subcallosal cortex, occipital pole, and lateral occipital cortex are the brain regions highly correlated with ASD. © 2023 The Authors. Published by Elsevier B.V.

关键词： autism spectrum disorder brain atlas brain region machine learning

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Sentiment Analysis for TikTok Review Using VADER Sentiment and SVM Model 8

Sentiment Analysis for TikTok Review Using VADER Sentiment a...

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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Isnan, Mahmud Elwirehardja, Gregorius Natanael Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

TikTok, a social networking site for uploading short videos, has become one of the most popular. Despite this, not all users are happy with the app;there are criticisms and suggestions, one of which is reviewed via the TikTok app on the Google Play Store. The reviews were extracted and then used for training a sentiment analysis model. The VADER sentiment method was utilized to offer the review's initial labeling (positive, neutral, and negative). The result revealed that most reviews were classified as positive, meaning that the data were imbalanced and challenging to handle in further analysis. Therefore, Random Under-sampling (RUS) and Random Over-sampling (ROS) methods were deployed to deal with that condition. The labeled reviews were subsequently pre-processed using tools such as case folding, noise removal, normalization, and stopwords before being used for training a Support Vector Machine (SVM) model for sentiment classification. The SVM trained without resampling produced the most favorable results, with an F1-score of 0.80. © 2023 The Authors. Published by Elsevier B.V.

关键词： Google Play Store Sentiment Analysis SVM TikTok VADER Sentiment

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Cancer Prediction using Clinical and Genomic Data Fusion: A Systematic Review 6

Cancer Prediction using Clinical and Genomic Data Fusion: A ...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Julian, Kelvin Nugroho, Kuncahyo Setyo Nirwantono, Rudi Pardamean, Bens Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

This systematic review provides a comprehensive overview of the methods used to integrate genomic and clinical data in cancer prediction. The review includes 19 studies across various cancers, including breast, colorectal, melanoma, lung, pancreatic, and thyroid. The studies employed different methods to combine genomic and clinical data, including weighted polygenic risk scores, genetic and non-genetic risk scores, and different machine learning algorithms. The results show significant improvements in model prediction performance accuracy across multiple studies. The review highlights the potential benefits of integrating genetic and phenotypic information to improve disease risk prediction models and inform personalized healthcare strategies. © 2024 IEEE.

关键词： Lung cancer

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Exploring Shifted Domain Problem within MNIST Dataset

Exploring Shifted Domain Problem within MNIST Dataset

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

作者： Hidayaturrahman Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusatara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Domain data can be shifted in any direction so it will be shared in different distributions to its original domain. This could be a problem since the model was trained with different distributions. It is found that adversarial domain adaptation using domain adversarial neural networks (DANN) can help to solve this problem on some scale. DANN can minimize the discrepancy between source and target data so the model can work well in both domains. The experiment is done by utilizing MNIST dataset that shifted into some conditions. In a condition when the shifting of distribution is too far, DANN is struggling to maintain the knowledge extracted from source data which leads to underperformance in the source and target domain. In contrast, when the shifting is closer, DANN can easily fit the model so it can perform well in both domains. It proves DANN is one of the good approaches to performing domain adaptation in small discrepancies. © 2023 IEEE.

关键词： Adversarial Domain Adaptation Domain Shifting Problem MNIST Transfer Learning

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Downsizing and soft X-ray tomography for cellular uptake of interpenetrated metal-organic frameworks

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Journal of Materials Chemistry B 2024年第25期12卷 6079-6090页

作者： Yu, Yu-Sheng Liang, Yung-Yi Hsieh, Chia-Chun Lin, Zi-Jing Cheng, Po-Hsiu Cheng, Chih-Chan Chen, Shu-Ping Lai, Lee-Jene Wu, Kevin C.-W. National Taiwan University Department of Chemical Engineering Taipei Taiwan National Health Research Institute Institute of Biomedical Engineering and Nanomedicine Miaoli Taiwan Hsinchu Taiwan International Graduate Program of Molecular Science and Technology Taiwan International Graduate Program Academia Sinica Taipei Taiwan National Taiwan University Taipei Taiwan

Metal-organic frameworks (MOFs) are porous materials with potential in biomedical applications such as sensing, drug delivery, and radiosensitization. However, how to tune the properties of the MOFs for such applications remains challenging. Herein, we synthesized two MOFs, Zr-PEB and Hf-PEB. Zr-PEB can be classified as porous interpenetrated zirconium frameworks (PIZOFs) and Hf-PEB is its analogue. We controlled their sizes while maintaining their crystal structure by employing a coordination modulation strategy. They were designed to serve as sensitizer for X-ray therapy and as potential drug carriers. Comprehensive characterizations of the MOFs' properties have been conducted, and the in vitro biological impacts have been studied. Since viability assay showed that Hf-PEB was more biocompatible compared to Zr-PEB, the cellular uptake of Hf-PEB by cells was evaluated using both fluorescence microscopy and soft X-ray tomography (SXT), and the three-dimensional structure of Hf-PEB in cells was observed. The results revealed the potential of Zr-PEB and Hf-PEB as nanomaterials for biomedical applications and demonstrated that SXT is an effective tool to assist the development of such materials. © 2024 The Royal Society of Chemistry.

关键词： Organometallics

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