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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Pryandi, Pinnus Dewantara, Muhammad Bayu Warnars, Harco Leslie Hendric Spits Arief, Ramadhan Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Telkom University Bandung11480 Indonesia

ISBN: (纸本)9798350398496

In life, various challenges and problems faced by deaf people such as communication skills and other problems, including emotional, mental, and societal development. However, technology is needed that can help the process. This Smart Application try to build communication between the deaf to share thoughts in group chats, including getting information about the deaf, so that the communication learning process for the deaf becomes easier. The proposed model is using Unified Modeling Languages (UML) diagrams, such as case diagrams for the current proposed idea process and class diagrams for relational tables or database stores. In addition, the User interface (UI) is implemented in this research work, Personal Home Pages (PHP) as a web server programming and MySQL database as an open-source database. © 2023 IEEE.

关键词： User interfaces

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Formal Security Verification for Searchable Symmetric Encryption Using ProVerif

Formal Security Verification for Searchable Symmetric Encryp...

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International Symposium on Information Theory and Its Applications, ISITA

作者： Takehiko Mieno Hiroyuki Okazaki Kenichi Arai Yuichi Futa Hiroaki Yamamoto Graduate School of Medicine Science and Technology Shinshu University EPSON AVASYS CORPORATION Graduate School of Science and Technology Shinshu University Graduate School of Engineering Nagasaki University School of Computer Science Tokyo University of Technology Faculty of Engineering Shinshu University

ISBN: (数字)9784885523519

ISBN: (纸本)9798331533335

With the rapid proliferation of various cloud storage services in recent years, the development of technology to efficiently search data while ensuring its confidentiality during cloud usage is an important issue. The technology that enables keyword searches on encrypted files using previously set keywords is called searchable symmetric encryption (SSE). In this paper, we propose a method formally representing encrypted document, and verify the security of SSE using the formal verification tool ProVerif. Our proposed method considers the channel-type terms of ProVerif as a Document that includes different keywords to verify the indistinguishability of encrypted documents.

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Annotator Subjectivity in the MusicCaps Dataset 2

Annotator Subjectivity in the MusicCaps Dataset

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2nd Workshop on Human-Centric Music Information Retrieval, HCMIR 2023

作者： Lee, Minhee Doh, Seungheon Jeong, Dasaem Department of Computer Science and Engineering Sogang University Korea Republic of Graduate School of Culture Technology KAIST Korea Republic of Department of Art & Technology Sogang University Korea Republic of

Musical caption, when expressed in free-form text as opposed to more structured and limited musical tags, often encompasses the individual characteristics of the annotator, thereby injecting a degree of subjectivity into the resultant dataset. This study explores the impact of such annotator subjectivity within the MusicCaps dataset, a pioneering collection of human-annotated captions explaining 10-second music audio clips. We conducted three distinct analyzes to investigate the presence of this subjectivity. This includes examining the frequency distribution of tag categories (i.e., genre, mood, or instruments) among different annotators, a qualitative assessment of caption embeddings through UMAP visualizations, and a quantitative analysis where we train and compare cross-modal retrieval models using an annotator-specified training split. Our findings underscore the significant annotator subjectivity inherent in the MusicCaps dataset, emphasizing the need for its consideration when collecting free-form text annotations on music or developing machine-learning models using this type of dataset. © 2023 CEUR-WS. All rights reserved.

关键词： Music

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Unifying Emotion-Oriented and Cause-Oriented Predictions for Emotion-Cause Pair Extraction

SSRN

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SSRN 2024年

作者： Hu, Guimin Zhao, Yi Lu, Guangming School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School Shenzhen518000 China School of Science Harbin Institute of Technology Shenzhen Graduate School Shenzhen518000 China

Emotion-cause pair extraction (ECPE) is an extraction task aiming to simultaneously identify the emotions and causes from the text without emotion annotations. Let $c_{i}$ and $c_{j}$ be the emotion clause and the cause clause of a document, respectively, and set we can predict one from the other and vice versa. Previous works fail to take advantage of this bidirectional opportunity. We refer to the prediction from $c_{i}$ to $c_{j}$, i.e., $c_{i}\rightarrow c_{j}$, as an emotion-oriented cause prediction (EoCP) task and the prediction from $c_{j}$ to $c_{i}$, i.e., $c_{j}\rightarrow c_{i}$, as a cause-oriented emotion prediction (CoEP) task. After the new decomposition of the ECPE task, we propose a novel unified architecture for ECPE, which takes EoCP and CoEP as cells and unifies them into a single-chain architecture. Meanwhile, we redefine emotion-cause pair extraction as a closed-loop structure detection problem to alleviate the mismatch between emotion and cause clauses. To better train the architecture, we define a new loss and provide a procedure for estimating the confidence the extraction system has for its emotion-cause pairs. We demonstrate the superiority of our proposed model through extensive experiments on two public datasets and reap a new state-of-the-art performance. Our method especially obtains significant improvement in multiple emotion-cause pair extraction. © 2024, The Authors. All rights reserved.

关键词： Extraction

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Remote Inter-beat Interval Estimation: A Signal Reconstruction Approach with Multi-channel Input and Channel-Wise Attention Mechanism

Remote Inter-beat Interval Estimation: A Signal Reconstructi...

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International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Shengze Wang Mondher Bouaziz Tomoaki Ohtsuki Graduate School of Science and Technology Keio University Department of Information and Computer Science Faculty of Science and Technology Keio University Yokohama Japan

ISBN: (数字)9798350350548

ISBN: (纸本)9798350350555

This paper presents a radar-based heart rate monitoring and Inter-beat interval (IBI) estimation. Traditional IBI estimation relies on peak detection combined with signal processing techniques. Our approach uses signal reconstruction with a neural network, which significantly improves the accuracy and robustness of IBI estimation compared to conventional methods. By utilizing multi-channel input data, our approach effectively mitigates various sources of noise and interference, resulting in highly accurate and reliable IBI predictions. Instead of relying solely on peak detection, we use the U-net architecture and cross-channel attention mechanism to reconstruct the triangular waveform generated from the ground truth ECG signals. The incorporation of multi-channel input and channel-wise attention mechanism improves our model's ability to discriminate and em-phasize critical features from different input channels, further improving IBI estimation accuracy. To evaluate the accuracy and robustness of our proposed method, we trained our model on the open-source dataset [1], and then performed leave-one-subject-out validation, which ensures our approach to be evaluated only on unseen independent subjects. We have achieved a Root Mean Square Error (RMSE) of 26.7 ms for the IBI of each heart-beat. Our results demonstrate the transformative potential of adopting signal reconstruction methods supported by state-of-the-art deep learning techniques. This shift in perspective promises more accurate and robust heart rate and IBI estimation, opening new avenues for improving the accuracy and reliability of cardiac monitoring systems. 1 1 This work was supported by JST ASPIRE Grant Number JPMJAP2326, Japan.

关键词： Heart rate Accuracy Attention mechanisms Noise Neural networks Estimation Signal reconstruction Robustness Root mean square Monitoring

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High-Resolution Hydrogen Molecule Detection Utilizing a Nanocandle-Based Optical Sensor 16

High-Resolution Hydrogen Molecule Detection Utilizing a Nano...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Park, Nu-Ri Kim, Min-Joong Lee, Jongsu Seo, Minah Ryu, Yong-Sang Kim, Myung-Ki KU-KIST Graduate School of Converging Science and Technology Korea University Seoul02841 Korea Republic of Korea Institute of Science and Technology Sensor System Research Center Seoul02792 Korea Republic of Northwestern University Department of Electrical Engineering and Computer Science EvanstonIL60208 United States School of Biomedical Engineering Korea University Seoul02481 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02481 Korea Republic of

Our research introduces a novel method for safe hydrogen detection. We've developed an advanced nano-candle sensor, combining Pd with nano-candles, enabling accurate detection of low-concentration hydrogen ( ©... 详细信息

ISBN: (纸本)9798350372076

关键词： Nanoclay

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Model of Text-to-Text Transfer Transformer for Hadith Question Answering System

Model of Text-to-Text Transfer Transformer for Hadith Questi...

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International Conference on Information technology, computer and Electrical Engineering (ICITACEE)

作者： Bambang Sulistio Derwin Suhartono Haryono Soeparno Widodo Budiharto Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Doctor of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389302

ISBN: (纸本)9798350389319

The advancement of Artificial Intelligence (AI), notably in Natural Language Processing (NLP), has been remarkable. Among its applications, Question-Answering (QA) systems stand out, assisting users in accessing pertinent information across various topics, including religious contexts. Religion plays a significant role in providing guidance on moral values to modern society, such as tolerance, compassion and social norms. Religious practices taught by religion serve as significant foundations for addressing the increasingly advancing influence of technology. The primary goal of this paper is to create a question-answering system proficient in analyzing user inquiries and precisely extracting data from translated Indonesian Hadith datasets. This research endeavors to enhance question-answering accuracy through Deep Learning techniques. Employing pre-processing methods, the system interprets user query intents. Furthermore, the Text-to-Text Transfer Transformer (T5), a text-based language Transformer model, is utilized to streamline the retrieval process for Hadith-related queries based on relevant subjects. The research findings demonstrate the precision of answers through BLEU and ROUGE scores. The novelty of this study lies in the creation of a dataset of hadith translations in Indonesian and the fine-tuning of the T5 model that has been trained using a dataset of questions and answers based on these translations. This research demonstrates the following evaluation scores: BLEU: 0.606, ROUGE-1: 0.702, ROUGE-2: 0.548, and ROUGE-L: 0.701, indicating that the answers generated by this particular research model are better compared to those produced using the standard mT5 model.

关键词： Electrical engineering Deep learning Ethics Large language models Transformers Question answering (information retrieval) Data mining Information technology Standards Testing

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Deep Learning Based Jujube Quality Assessment: An Automated Surface Defect Detection Approach 24

Deep Learning Based Jujube Quality Assessment: An Automated ...

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7th International Conference on Signal Processing and Machine Learning, SPML 2024

作者： Gao, Yujie Yuan, Baoxi Zhu, Qing Zhao, Jiyuan Ma, Xiangyang Chen, Jialu Wang, Feng Chu, Peng Wang, Chunlan School of Electronic Information Xijing University China Beijing Hengyue Intelligent Information Technology Co. Ltd. China School of Computer Science Xijing University China Graduate Office Xijing University China

ISBN: (纸本)9798400717192

Defects such as bird pecking, splitting, and mildew can affect the quality of red jujubes during their growth, transportation, and processing. To ensure the quality of red jujube products, grading the appearance of the jujubes is particularly important. Utilizing computer vision technology for classifying the appearance of red jujubes is a more cost-effective, faster, and more accurate alternative to manual screening. This paper introduces a method for grading the appearance of red jujubes based on YOLOv8. The results include a detection model with an mAP50 of 0.987 and a segmentation model with an mAP50 of 0.986, both based on the YOLOv8s model and a segmentation model with an mAP50 of 0.985 based on the YOLOv8n model. By employing the advanced YOLOv8 algorithm for jujube Surface Defect Detection, this study holds significant implications for improving quality control in the jujube industry. This technology not only enhances detection efficiency but also reduces labor costs, aligning with the trend toward industrial automation and intelligence. It offers scientific support to jujube enterprises, boosts their competitiveness, and contributes to elevating the development of agriculture to a higher standard. © 2024 ACM.

关键词： Wages

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Formulate Full View Camera Sensor Coverage by Using Group Set Coverage 15th

Formulate Full View Camera Sensor Coverage by Using Group S...

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15th EAI International Conference on Wireless Internet, WiCON 2022

作者： Du, Hongwei Zhang, Zhao Duan, Zhenhua Tian, Cong Du, Ding-Zhu Department of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School Shenzhen China College of Mathematics and Computer Science Zhejiang Normal University Zhejiang Jinhua321004 China ICTT and ISN Laboratory Xidian University Xian710071 China Department of Computer Science University of Texas at Dallas RichardsonTX75080 United States

ISBN: (纸本)9783031270406

Full view is an important subject in the study of wireless camera sensor coverage. It involves three issues, camera direction selection, camera location selection, and moving-directional target coverage. In this paper, we study them step by step, from one issue, two issue, to three issues. In each step, we formulate a group set cover- age problem, and study its computational complexity and approximation solutions. Especially, we employ a new type of approximations, the global approximation of local optimality for nonsubmodular optimization. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Cameras

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Leveraging Advanced computer Vision for Hazardous Behavior Monitoring on Campus Safety Maintenance 4

Leveraging Advanced Computer Vision for Hazardous Behavior M...

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Tsai, Shang-Te Wu, Zong-Rong Chang, Yu-Cheng Lin, Wei-Hsin Lee, Jia-Yi Chien, Wei Business School Yulin Normal University Yulin China National Yunlin University of Science and Technology Department of Technical and Vocational Program in Artificial Intelligence Yunlin Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan Taiwan National Pingtung University Department of International Business Pintung Taiwan

ISBN: (纸本)9798350360721

There was an incident on a campus involving the casualty of students. It created social unrest and heightened concerns over campus security. Consequently, it becomes important to prevent such incidents. Thus, we developed a solution for enhancing campus security and creating a safer school environment using deep learning. © 2024 IEEE.

关键词： computer vision

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