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arXiv 2021年

作者： Suzuki, Atsushi Nitanda, Atsushi Wang, Jing Xu, Linchuan Cavazza, Marc Yamanishi, Kenji School of Computing and Mathematical Sciences Faculty of Liberal Arts and Sciences University of Greenwich United Kingdom Department of Artificial Intelligence Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Japan Department of Computing Hong Kong Polytechnic University Hong Kong Department of Mathematical Informatics Graduate School of Information Science and Technology University of Tokyo Japan

Hyperbolic ordinal embedding (HOE) represents entities as points in hyperbolic space so that they agree as well as possible with given constraints in the formof entity i ismore similar to entity j than to entity k. It has been experimentally shown that HOE can obtain representations of hierarchical data such as a knowledge base and a citation network effectively, owing to hyperbolic space's exponential growth property. However, its theoretical analysis has been limited to ideal noiseless settings, and its generalization error in compensation for hyperbolic space's exponential representation ability has not been guaranteed. The difficulty is that existing generalization error bound derivations for ordinal embedding based on the Gramian matrix do not work in HOE, since hyperbolic space is not inner-product space. In this paper, through our novel characterization of HOE with decomposed Lorentz Gramian matrices, we provide a generalization error bound of HOE for the first time, which is at most exponential with respect to the embedding space's radius. Our comparison between the bounds of HOE and Euclidean ordinal embedding shows that HOE's generalization error is reasonable as a cost for its exponential representation ability. Copyright © 2021, The Authors. All rights reserved.

关键词： Knowledge based systems

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Location embedding based pairwise distance learning for fine-grained diagnosis of urinary stones

arXiv

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arXiv 2024年

作者： Jin, Qiangguo Huang, Jiapeng Sun, Changming Cui, Hui Xuan, Ping Su, Ran Wei, Leyi Wu, Yu-Jie Wu, Chia-An Duh, Henry B.L. Lu, Yueh-Hsun School of Software Northwestern Polytechnical University Shaanxi China Yangtze River Delta Research Institute of NPU Suzhou China CSIRO Data61 Sydney Australia Department of Computer Science and Information Technology La Trobe University Melbourne Australia School of Engineering Shantou University Guangdong China College of Intelligence and Computing Tianjin University Tianjin China School of Information Xiamen University Xiamen China AIDD Faculty of Applied Science Macao Polytechnic University China Department of Radiology Shuang-Ho Hospital Taipei Medical University Taipei Taiwan Master of Public Health Program National Yang Ming Chiao Tung University Taipei Taiwan School of Design The Hong Kong Polytechnic University Hong Kong Department of Radiology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan

The precise diagnosis of urinary stones is crucial for devising effective treatment strategies. The diagnostic process, however, is often complicated by the low contrast between stones and surrounding tissues, as well as the variability in stone locations across different patients. To address this issue, we propose a novel location embedding based pairwise distance learning network (LEPD-Net) that leverages low-dose abdominal X-ray imaging combined with location information for the fine-grained diagnosis of urinary stones. LEPD-Net enhances the representation of stone-related features through context-aware region enhancement, incorporates critical location knowledge via stone location embedding, and achieves recognition of fine-grained objects with our innovative fine-grained pairwise distance learning. Additionally, we have established an in-house dataset on urinary tract stones to demonstrate the effectiveness of our proposed approach. Comprehensive experiments conducted on this dataset reveal that our framework significantly surpasses existing state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Embeddings

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The rank of contextuality

arXiv

引用

arXiv 2022年

作者： Horodecki, Karol Zhou, Jingfang Stankiewicz, Maciej Salazar, Roberto Horodecki, Pawel Raussendorf, Robert Horodecki, Ryszard Ramanathan, Ravishankar Tyhurst, Emily Institute of Informatics National Quantum Information Centre Faculty of Mathematics Physics and Informatics University of Gdańsk Wita Stwosza 57 Gdańsk80-308 Poland International Centre for Theory of Quantum Technologies University of Gdańsk Wita Stwosza 63 Gdańsk80-308 Poland Department of Applied Physics Graduate School of Engineering University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków30-348 Poland Faculty of Applied Physics and Mathematics National Quantum Information Centre Gdańsk University of Technology Gabriela Narutowicza 11/12 Gdańsk80-233 Poland Department of Physics and Astronomy University of British Columbia VancouverBCV6T 1Z1 Canada Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong Department of Physics University of Toronto TorontoON Canada

Quantum contextuality is one of the most recognized resources in quantum communication and computing scenarios. We provide a new quantifier of this resource, the rank of contextuality (RC). We define RC as the minimum number of non-contextual behaviors that are needed to simulate a contextual behavior. We show that the logarithm of RC is a natural contextuality measure satisfying several properties considered in the spirit of the resource-theoretic approach. The properties include faithfulness, monotonicity, and additivity under tensor product. We also give examples of how to construct contextual behaviors with an arbitrary value of RC exhibiting a natural connection between this quantifier and the arboricity of an underlying hypergraph. We also discuss exemplary areas of research in which the new measure appears as a natural quantifier. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum communication

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SYNAPSE: An international roadmap to large brain imaging

引用

Physics Reports 2023年 999卷 1-60页

作者： Stampfl, Anton P.J. Liu, Zhongdong Hu, Jun Sawada, Kei Takano, H. Kohmura, Yoshiki Ishikawa, Tetsuya Lim, Jae-Hong Je, Jung-Ho Low, Chian-Ming Teo, Alvin Tok, Eng Soon Tan, Tin Wee Ban, Kenneth Libedinsky, Camilo Tan, Francis Chee Kuan Chen, Kuan-Peng Yang, An-Cheng Chuang, Chao-Chun Chen, Nan-Yow Shih, Chi-Tin Lee, Ting-Kuo Yang, De-Nian Lai, Hsu-Chao Shuai, Hong-Han Cheng, Chang-Chieh Ching, Yu-Tai Li, Chia-Wei Charng, Ching-Che Lo, Chung-Chuan Chiang, Ann-Shyn Recur, Benoit Petibois, Cyril Cheng, Chia-Liang Chen, Hsiang-Hsin Yang, Shun-Min Hwu, Yeukuang Rojviriya, Catleya Rugmai, Supagorn Rujirawat, Saroj Margaritondo, Giorgio Australian Nuclear Science and Technology Organization Lucas Heights 2234 NSW Australia Henan university of Technology Zhengzhou China Shanghai Institute of Applied Physics Chinese Academy of Science Shanghai China RIKEN SPring-8 Center Hyogo 679-5148 Japan Pohang Accelerator Laboratory Pohang University of Science and Technology Pohang Gyeongbuk 37673 South Korea Department of Materials Science and Engineering Pohang University of Science and Technology Gyeongbuk Pohang 37673 South Korea Department of Pharmacology Department of Anaesthesia and Healthy Longevity Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore School of Chemical and Life Sciences Nanyang Polytechnic Singapore eMaGIC-Lab Department of Physics National University of Singapore Singapore National Supercomputing Center Singapore Department of Psychology The N1 Institute for Health National University of Singapore Singapore Institute of Molecular and Cell Biology A*STAR Singapore Department of Anaesthesia National University Hospital National University Health System Singapore National Center for High-Performance Computing Hsinchu Taiwan Department of Physics Tunghai University Taichung Taiwan Department of Physics National Tsing Hua University Hsinchu Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Information Technology Service Center National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Life Science National Tsing Hua University Hsinchu Taiwan Institute of Systems Neuroscience and Brain Research Center National Tsing Hua University Hsinchu Taiwan Institute of Physics Academia Sinica Taipei Taiwan Department of Physics National Dong Hwa University

Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been collaborating in a major project called “SYNAPSE” (Synchrotrons for Neuroscience: an Asia-Pacific Scientific Enterprise). They use x-ray imaging to attack in a coordinated fashion one of the major issues in modern science: the structure of animal and human brains, including neurons and connections. The objective is to develop Google-like maps also including detailed structural and functional information for selected regions of interest. The sheer mass of data needed for the objective poses huge problems for the acquisition, processing, storage and use of images. In order to complete the task within a reasonable time, the key element of the SYNAPSE strategy is the parallel and coordinated work of several facilities on the same specimens. This article reviews different aspects of the enterprise, including the foundations of synchrotron radiation, coherence and of its role in advanced imaging, electron accelerators, x-ray optics and detectors. This will provide the foundation for an extensive presentation of the different components of SYNAPSE, with an overview of results already obtained within the consortium. © 2022

关键词： Brain mapping Phase contrast Radiology Supercomputing Synchrotron X-rays

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Optimize Performance Load Balancing Techniques Using Binary Vote Assignment Grid Quorum (BVAGQ): A Systematic Review 1

引用

2nd International Conference on Advanced Data and information Engineering, DaEng 2015

作者： Fairuzullah, A. Noraziah, Ahmad Arshah, Ruzaini Abdullah Herawan, Tutut Faculty of Computer Systems & Software Engineering University Malaysia Pahang Gambang KuantanPahang26300 Malaysia Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

ISBN: (数字)9789811317996

ISBN: (纸本)9789811317972

This paper present load balancing technique in a heterogeneous environment allows the usage for geographically widely distributed and multi-owner resources to solve large-level application, usage of load balancing algorithms was important to keep maintaining the balance of workload between emerged infrastructures like grid. This replication generally referred as mechanism to improve availability and performance in distributed databases especially handling fragmented database replication becomes demanding issue. Intended in this paper we address various kinds of load balancing algorithms for the heterogeneous network like grid, especially Binary Vote Assignment Grid Quorum (BVAGQ) and to identify various metric and gaps between them. Many load balancing algorithms are already implemented which work against various issues like heterogeneity, scalability, etc. Different load balancing algorithms for the grid environment work on various metrics such as make span, time, average resource utilization rate, communication overhead, reliability, stability, and fault tolerance. However the aim is to find improved query response time and overall throughput as compared to other scheme. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Fault tolerance

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BENHA@IDAT: Improving irony detection in Arabic tweets using ensemble approach 11

BENHA@IDAT: Improving irony detection in Arabic tweets using...

引用

11th Forum for information Retrieval Evaluation, FIRE 2019

作者： Nayel, Hamada A. Medhat, Walaa Rashad, Metwally Department of Computer Science Faculty of Computers and Artificial Intelligence Benha University Egypt Department of Information Systems Faculty of Computers and Artificial Intelligence Benha University Egypt

This paper describes the methods and experiments that have been used in the development of our model submitted to Irony Detec- tion for Arabic Tweets shared task. We submitted three runs based on our model using Support Vector Machines (SVM), Linear and Ensemble classifiers. Bag-of-Words with range of n-grams model have been used for feature extraction. Our submissions achieved accuracies of 82.1%, 81.6% and 81.1% for ensemble based, SVM and linear classifiers respectively. © Copyright 2019 for this paper by its authors.

关键词： Support vector machines

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Enhanced Heat Recovery in a Biogas Power Plant through a Multi-Stage Approach Utilizing Brayton, Organic Flash, and SCO 2 Cycles;Thermal-Economic Optimization Utilizing ANNs, NSGA-II, and LINMAP

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International Journal of Refrigeration 2025年

作者： Tianwen Yin Ali Basem LeI Chang Mohamed Shaban Fahad M. Alhomayani Ashit Kumar Dutta H. Elhosiny Ali Salah Knani SCHOOL OF ECONOMICS AND MANAGEMENT SHIHEZI UNIVERSITY 832000 ShiheziChina Faculty of Engineering Warith Al-Anbiyaa University Karbala 56001 Iraq School of Economics and Management Anhui University of Science and Technology Taifeng Road 168 Huainan 232001 Anhui Province PR China Department of Physics Faculty of Science Islamic University of Madinah Madinah 42351 Saudi Arabia College of Computers and Information Technology Taif University Saudi Arabia Applied College Taif University Saudi Arabia Department of Computer Science and Information Systems College of Applied Sciences AlMaarefa University Ad Diriyah Riyadh 13713 Kingdom of Saudi Arabia Physics Department Faculty of Science King Khalid University P.O. Box 9004 Abha Saudi Arabia Department of Physics College of Science Northern Border University Arar Saudi Arabia

This study presents a novel multi-heat recovery design integrated with a modified gas turbine power plant featuring a biogas-fueled oxyfuel combustion process and a CO 2 capture unit. The proposed method utilizes a multi-stage parallel-series heat recovery approach, integrating a closed Brayton cycle with a modified organic flash cycle alongside a supercritical CO 2 plant paired with a heating provider and an organic flash cycle. Engineering equation solver software is employed to model the suggested configuration, allowing for analyzing its thermodynamic, sustainability, and financial performance metrics. Additionally, an artificial intelligence-aided optimization process is implemented, utilizing artificial neural networks, NSGA-II methodology, and LINMAP decision-making techniques. The optimization focuses on exergy efficiency and payback period as the objective functions. Results indicate an improvement in exergy efficiency by 5.22 percentage points over the baseline model, achieving a value of 42.15%. The payback period has also been reduced by 9.31%, demonstrating a value of 2.63 years. Under optimal conditions, the system can produce an electrical output of 1402 kW and a heating load of 206.7 kW. Furthermore, calculations demonstrate a CO 2 capture potential of 0.278 kg/s, a sustainability index of 1.73, a total net present value of 18.48 M$, and a total unit production cost of 34.83 $/GJ.

关键词：

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Advancing Chinese biomedical text mining with community challenges

arXiv

引用

arXiv 2024年

作者： Zong, Hui Wu, Rongrong Cha, Jiaxue Feng, Weizhe Wu, Erman Li, Jiakun Shao, Aibin Tao, Liang Li, Zuofeng Tang, Buzhou Shen, Bairong Joint Laboratory of Artificial Intelligence for Critical Care Medicine Department of Critical Care Medicine Institutes for Systems Genetics Frontiers Science Center for Disease-related Molecular Network West China Hospital Sichuan University Chengdu610041 China Shanghai Key Laboratory of Signaling and Disease Research Laboratory of Receptor-Based Bio-Medicine Collaborative Innovation Center for Brain Science School of Life Sciences and Technology Tongji University Shanghai200092 China Department of Urology West China Hospital Sichuan University Chengdu610041 China Faculty of Business Information Shanghai Business School Shanghai201400 China Takeda Co. Ltd. Shanghai200040 China Department of Computer Science Harbin Institute of Technology Shenzhen518055 China

Objective: This study aims to review the recent advances in community challenges for biomedical text mining in China. Methods: We collected information of evaluation tasks released in community challenges of biomedical text mining, including task description, dataset description, data source, task type and related links. A systematic summary and comparative analysis were conducted on various biomedical natural language processing tasks, such as named entity recognition, entity normalization, attribute extraction, relation extraction, event extraction, text classification, text similarity, knowledge graph construction, question answering, text generation, and large language model evaluation. Results: We identified 39 evaluation tasks from 6 community challenges that spanned from 2017 to 2023. Our analysis revealed the diverse range of evaluation task types and data sources in biomedical text mining. We explored the potential clinical applications of these community challenge tasks from a translational biomedical informatics perspective. We compared with their English counterparts, and discussed the contributions, limitations, lessons and guidelines of these community challenges, while highlighting future directions in the era of large language models. Conclusion: Community challenge evaluation competitions have played a crucial role in promoting technology innovation and fostering interdisciplinary collaboration in the field of biomedical text mining. These challenges provide valuable platforms for researchers to develop state-of-the-art solutions. © 2024, CC BY-SA.

关键词： Data description

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A New Approach to Secure and Manage Load Balancing of the Distributed Database Using SQL Firewall 1

引用

2nd International Conference on Advanced Data and information Engineering, DaEng 2015

作者： Fairuzullah, A. Noraziah, Ahmad Mohd, Wan Maseri Wan Herawan, Tutut Faculty of Computer Systems & Software Engineering University Malaysia Pahang Gambang KuantanPahang26300 Malaysia Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

ISBN: (数字)9789811317996

ISBN: (纸本)9789811317972

This paper is the current approach database security of organization need layers of security around their data, with each layer protecting a specific area. The current trend of security attack is targeting any valuable data stored in a database such as financial data and student mark, including data theft, data modification or replay and data disruption. To understand how the system works, the system setting and the weaknesses of Enterprise Distributed Database. This paper is about the design and development to secure database access, a framework based on packet and content filtering on IP address, port and SQL statement. And simulate the framework and design database security framework. We address how to build the outcome of this is to reduce the risk of data manipulation and reduce the impact of internal threat and malicious insiders. The result shows that the proposed method succeeded in meeting those aspects of information security. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Security of data

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Using Susceptible-Exposed-Infectious-Recovered Model to Forecast Coronavirus Outbreak

引用

computers, Materials & Continua 2021年第5期67卷 1595-1612页

作者： Debabrata Dansana Raghvendra Kumar Arupa Parida Rohit Sharma Janmejoy Das Adhikari Hiep Van Le Binh Thai Pham Krishna Kant Singh Biswajeet Pradhan Department of Computer Science and Engineering GIET UniversityGunupurOdishaIndia Department of Electronics&Communication Engineering Faculty of Engineering and TechnologySRM Institute of Science and TechnologyNCR CampusDelhi-NCR CampusModinagarGhaziabadIndia Institute of Research and Development Duy Tan UniversityDa Nang550000Viet Nam University of Transport Technology Hanoi100000Viet Nam Department of ECE KIET Group of InstitutionsGhaziabadIndia Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) University of Technology SydneySydneyNSW2007Australia Department of Energy and Mineral Resources Engineering Sejong UniversitySeoul05006Korea Center of Excellence for Climate Change Research King Abdulaziz UniversityJeddah21589Saudi Arabia Earth Observation Center Institute of Climate ChangeUniversiti Kebangsaan Malaysia43600SelangorMalaysia

The Coronavirus disease 2019(COVID-19)outbreak was rst discovered in Wuhan,China,and it has since spread to more than 200 *** World Health Organization proclaimed COVID-19 a public health emergency of international concern on January 30,***,a quickly spreading infection that could jeopardize the well-being of countless individuals requires prompt action to forestall the malady in a timely ***19 is a major threat worldwide due to its ability to rapidly *** vaccines are yet available for *** objective of this paper is to examine the worldwide COVID-19 pandemic,specically studying Hubei Province,China;Taiwan;South Korea;Japan;and Italy,in terms of exposed,infected,recovered/deceased,original conrmed cases,and predict conrmed cases in specic countries by using the susceptible-exposed-infectious-recovered model to predict the future outbreak of *** applied four differential equations to calculate the number of conrmed cases in each country,plotted them on a graph,and then applied polynomial regression with the logic of multiple linear regression to predict the further spread of the *** also compared the calculated and predicted cases of conrmed population and plotted them in the graph,where we could see that the lines of calculated and predicted cases do intersect with each other to give the perfect true results for the future spread of the *** study considered the cases from 22 January 2020 to 25 April 2020.

关键词： COVID-19 SEIR forecasting global pandemic predict conrmed case

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