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arXiv 2021年

作者： Bueckle, Andreas Buehling, Kilian Shih, Patrick C. Börner, Katy Department of Intelligent Systems Engineering Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Research Group Knowledge and Technology Transfer Fakultät Wirtschaftswissenschaften Technische Universität Dresden Germany Department of Informatics Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Department of Information and Library Science Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States

Working with organs and extracted tissue blocks is an essential task in many medical surgery and anatomy environments. In order to prepare specimens from human donors for further analysis, wet-bench workers must properly dissect human tissue and collect metadata for downstream analysis, including information about the spatial origin of tissue. The Registration User Interface (RUI) was developed to allow stakeholders in the Human Biomolecular Atlas Program (HuBMAP) to register tissue blocks-i.e., to record the size, position, and orientation of human tissue data with regard to reference organs. The RUI has been used by tissue mapping centers across the HuBMAP consortium to register a total of 45 kidney, spleen, and colon tissue blocks, with planned support for 17 organs in the near future. In this paper, we compare three setups for registering one 3D tissue block object to another 3D reference organ (target) object. The first setup is a 2D Desktop implementation featuring a traditional screen, mouse, and keyboard interface. The remaining setups are both virtual reality (VR) versions of the RUI: VR Tabletop, where users sit at a physical desk which is replicated in virtual space;VR Standup, where users stand upright while performing their tasks. All three setups were implemented using the Unity game engine. We then ran a user study for these three setups involving 42 human subjects completing 14 increasingly difficult and then 30 identical tasks in sequence and reporting position accuracy, rotation accuracy, completion time, and satisfaction. All study materials were made available in support of future study replication, alongside videos documenting our setups. We found that while VR Tabletop and VR Standup users are about three times as fast and about a third more accurate in terms of rotation than 2D Desktop users (for the sequence of 30 identical tasks), there are no significant differences between the three setups for position accuracy when normalized by the heigh

关键词： Virtual reality

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Unveiling the Inventive Process from Patents by Extracting Problems, Solutions and Advantages with Natural Language Processing

SSRN

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SSRN 2022年

作者： Giordano, Vito Puccetti, Giovanni Chiarello, Fllippo Pavanello, Tommaso Fantoni, Gualtiero Department of Information Engineering Via Girolamo Caruso 16 Pisa56122 Italy Scuola Normale Superiore Piazza dei Cavalieri 7 Pisa56126 Italy Department of Energy Systems Territory and Construction Engineering Largo Lucio Lazzarino 2 Pisa56122 Italy Erre Quadro S.R.L Largo Padre Renzo Spadoni c/o Cittadella Galileiana Pisa56126 Italy Department of civil and industrial engineering Largo Lucio Lazzarino 2 Pisa56122 Italy Business Engineering for Data Science B4DS Research Laboratory Italy

Patents are the main means for disclosing an invention. These documents encompass many steps of the inventive process starting with the definition of the problem to be solved and ending with the identification of a solution. In this study we focus on three fundamental concepts of the inventive process: (A) technical problems;(B) solutions;and (C) advantageous effects of the invention, which, based on the WIPO guidelines, any patent should *** propose a system based on Natural Language Processing (NLP) pipeline that uses transformer language models to identify technical problems, solutions and advantageous effects from patents. We use a training dataset composed of 480,000 patents sentences contained in sections manually labeled by inventors or *** model reaches a F1 score of 90%. The model is evaluated on a random set of patents to assess its deployability in a real world *** proposed model can be used as a novel tool for prior art mapping, novel ideas generation and technological evolution identification and can help to disclose valuable information hidden in patent documents. © 2022, The Authors. All rights reserved.

关键词： Patents and inventions

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Feature Extraction and Classification from Planetary Science datasets enabled by Machine Learning

Feature Extraction and Classification from Planetary Science...

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IEEE Conference on Aerospace

作者： Conor A. Nixon Zachary Yahn Ethan Duncan Ian Neidel Alyssa C. Mills Benoît Seignovert Andrew Larsen Kathryn Gansler Charles Liles Catherine C. Walker Douglas M. Trent John Santerre Planetary Systems Laboratory NASA Goddard Space Flight Center Greenbelt MD Computer Science Department University of Virginia Charlottesville VA School of Information University of California Berkeley Berkeley CA Yale University Timothy Dwight College New Haven CT Geosciences Department Baylor University Waco TX Nantes Université Laboratoire De Planétologie Et Géosciences Nantes France Business Intelligence Division Inntopia Stowe VT Department of Geology University of Maryland College Park MD NASA Langley Research Center Center Operations Directorate Virginia Department of Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Massachusetts OCIO Information Data & Analytics Services SAIC | East-2 NASA Langley Research Center Virginia

In this paper we present two examples of recent investigations that we have undertaken, applying Machine Learning (ML) neural networks (NN) to image datasets from outer planet missions to achieve feature recognition. Our first investigation was to recognize ice blocks (also known as rafts, plates, polygons) in the chaos regions of fractured ice on Europa. We used a transfer learning approach, adding and training new layers to an industry-standard Mask R-CNN (Region-based Convolutional Neural Network) to recognize labeled blocks in a training dataset. Subsequently, the updated model was tested against a new dataset, achieving 68% precision. In a different application, we applied the Mask R-CNN to recognize clouds on Titan, again through updated training followed by testing against new data, with a precision of 95% over 369 images. We evaluate the relative successes of our techniques and suggest how training and recognition could be further improved. The new approaches we have used for planetary datasets can further be applied to similar recognition tasks on other planets, including Earth. For imagery of outer planets in particular, the technique holds the possibility of greatly reducing the volume of returned data, via onboard identification of the most interesting image subsets, or by returning only differential data (images where changes have occurred) greatly enhancing the information content of the final data stream.

关键词： Training Earth Image recognition Transfer learning Streaming media Feature extraction Ice

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A Brief Review of Explainable Artificial Intelligence in Healthcare

SSRN

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SSRN 2023年

作者： Sadeghi, Zahra Alizadehsani, Roohallah Cifci, Mehmet Akif Kausar, Samina Rehman, Rizwan Mahanta, Priyakshi Bora, Pranjal Kumar Almasri, Ammar Alkhawaldeh, Rami S. Hussain, Sadiq Alatas, Bilal Shoeibi, Afshin Moosaei, Hossein Hladík, Milan Nahavandi, Saeid Pardalo, Panos M. Institute for Big Data Analytics Faculty of Computer Science Dalhousie University Canada Deakin University Geelong Australia The Institute of Computer Technology Tu Wien University Vienna1040 Austria University of Kotli Azad Jammu and Kashmir Azad Kashmir Kotli Pakistan Centre for Computer Science and Applications Dibrugarh University Assam India Department of Management Information Sys Al-Balqa Applied University Salt19117 Jordan Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Examination Branch Dibrugarh University Assam Dibrugarh India Department of Software Eng. Firat University Elazig23100 Turkey Data Science and Computational Intelligence Institute University of Granada Spain Department of Informatics Faculty of Science Jan Evangelista Purkyně University in Ústí nad Labem Czech Republic Department of Applied Mathematics School of Computer Science Faculty of Mathematics and Physics Charles University Prague Czech Republic Harvard Paulson School of Engineering and Applied Sciences Harvard University AllstonMA02134 United States Swinburne University of Technology HawthornVIC3122 Australia Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville32611 United States

XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-stakes decision-making situations, such as medical domain have increased the demand for transparency and explainability since wrong predictions may have severe consequences. Model explainability and interpretability are vital successful deployment of AI models in healthcare practices. AI applications' underlying reasoning needs to be transparent to clinicians in order to gain their trust. This paper presents a systematic review of XAI aspects and challenges in the healthcare domain. The primary goals of this study are to review various XAI methods, their challenges, and related machine learning models in healthcare. The methods are discussed under six categories: Features-oriented methods, global methods, concept models, surrogate models, local pixel-based methods, and human-centric methods. Most importantly, the paper explores XAI role in healthcare problems to clarify its necessity in safety-critical applications. The paper intends to establish a comprehensive understanding of XAI-related applications in the healthcare field by reviewing the related experimental results. To facilitate future research for filling research gaps, the importance of XAI models from different viewpoints and their limitations are investigated. © 2023, The Authors. All rights reserved.

关键词： Decision making

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-Neural network-based optimization of hydrogen fuel production energy system with proton exchange electrolyzer supported nanomaterial

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Fuel 2023年第Part1期332卷

作者： Hai, Tao Hikmat Hama Aziz, Kosar Zhou, Jincheng Dhahad, Hayder A. Sharma, Kamal Fahad Almojil, Sattam Ibrahim Almohana, Abdulaziz Fahmi Alali, Abdulrhman Ismail Kh, Teeba Mehrez, Sadok Abdelrahman, Anas School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun 558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Guizhou Duyun 558000 China nstitute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Selangor Shah Alam 40450 Malaysia Department of Chemistry College of Science University of Sulaimani Qlyasan Street Kurdistan Region 46001 Iraq Department of Medical Laboratory of Science College of Health Sciences University of Human Development Sulaimaniyah Iraq Mechanical Engineering Department University of Technology Baghdad Iraq Institute of Engineering and Technology GLA University Uttar Pradesh Mathura 281406 India Department of Civil Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Computer Engineering College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq Department of Mechanical Engineering College of Engineering at Al Kharj Prince Sattam bin Abdulaziz University 16273 Saudi Arabia Department of Mechanical Engineering University of Tunis El Manar ENIT BP 37 Le Belvédère Tunis 1002 Tunisia Department of Chemical Engineering Faculty of Engineering & Technology Future University in Egypt New Cairo 11500 Tunisia Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan Duyun 558000 China

In this research, we try to investigate a solar-geothermal energy system. This system includes three turbines for power production, a PEM electrolyzer for hydrogen production, and a thermoelectric for generating electricity from excess heat. In addition, the seawater will be passed through the osmotic cycle to gain fresh water. The required power for this osmotic cycle will be obtained through the energy produced by the main turbines. The generated load, hydrogen production flow rate, purified water flow rate, and heating consumption are assessed in this study. The results showed that this system can produce 3.8 megawatts of electricity as well as 8 g per second of hydrogen fuel at the operating point. Also, the energy efficiency of this system is estimated to be 19%. Afterward, machine learning methods are used to optimize designing parameters, and the optimum operating point in terms of useful power and stored fuel flow rate is obtained by a genetic algorithm. The optimum operating point of this energy system has a useful power output of 4.099 megawatts and a hydrogen flow rate of 29 g per second. In the end, the distribution of the design parameters is displayed for points of the beam curve. © 2022

关键词： Biofuel Electrolyzer Fuel production Hydrogen fuel Optimization Solar energy

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Ultra-compact beam steering nanolasers

arXiv

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arXiv 2024年

作者： Chen, Xinghong Gu, Mingxuan Tang, Jiankai Sang, Yungang Xiang, Bingrui Zhang, Kong Zhang, Guanjie Wang, Xingyuan Guo, Xuhan Zhou, Linjie Wu, Wengang Mao, Yifei School of Sensing Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China College of Mathematics and Physics Beijing University of Chemical Technology Beijing100029 China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China National Key Laboratory of Science and Technology on Micro/Nano Fabrication School of Integrated Circuits Peking University Beijing100871 China Beijing Advanced Innovation Center for Integrated Circuits Beijing100871 China Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China

The miniaturization and integration of beam steering devices have consistently been the focus of the field. Conventional methods alter the eigenmode of the optical cavity by regulating the refractive index. Due to the weak nonlinear effect of the optical system, the device must be sufficiently large to achieve sufficient light modulation. The effective method for miniaturizing beam steering devices currently in use is based on metasurfaces. However, this type of device necessitates the input of a laser source, which precludes the simultaneous generation and control of light in a single device. Here we propose a miniaturized beam steering device that employs mode selection between different bound states in the continuum (BIC) states through phase change material. The device is capable of simultaneously achieving both light generation and beam steering (33°) in a single device with a size of only 25 μm and with a low threshold of 8.9 kW cm-2. Furthermore, it is possible to achieve a significant degree of dynamic wavelength tunability, with a range extending up to 296 nm. This method achieves high-efficient regulation of light properties by dynamically controlling the system’s topological charge, circumventing the problem of weak nonlinearity in traditional methods. Furthermore, the integration of phase change materials with nanolasers enables the direct alteration of lasing properties, which provides a novel idea for dynamic light control. The device process scheme based on phase change materials is straightforward, direct, and highly compatible, which will be advantageous for its intended application. Copyright © 2024, The Authors. All rights reserved.

关键词： Phase change materials

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Robust personalized pricing under uncertainty of purchase probabilities

arXiv

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arXiv 2024年

作者： Ikeda, Shunnosuke Nishimura, Naoki Sukegawa, Noriyoshi Takano, Yuichi Product Development Management Office Data Management & Planning Office Recruit Co. Ltd. 1–9–2 Chiyoda–ku Tokyo100–6640 Japan Department of Advanced Sciences Hosei University 3–7–2 Kajinocho Koganei–shi Tokyo184–8584 Japan Graduate School of Science and Technology University of Tsukuba 1–1–1 Tennodai Tsukuba–shi Ibaraki305–8573 Japan Institute of Systems and Information Engineering University of Tsukuba 1–1–1 Tennodai Tsukuba–shi Ibaraki305–8573 Japan

This paper is concerned with personalized pricing models aimed at maximizing the expected revenues or profits for a single item. While it is essential for personalized pricing to predict the purchase probabilities for each consumer, these predicted values are inherently subject to unavoidable errors that can negatively impact the realized revenues and profits. To address this issue, we focus on robust optimization techniques that yield reliable solutions to optimization problems under uncertainty. Specifically, we propose a robust optimization model for personalized pricing that accounts for the uncertainty of predicted purchase probabilities. This model can be formulated as a mixed-integer linear optimization problem, which can be solved exactly using mathematical optimization solvers. We also develop a Lagrangian decomposition algorithm combined with line search to efficiently find high-quality solutions for large-scale optimization problems. Experimental results demonstrate the effectiveness of our robust optimization model and highlight the utility of our Lagrangian decomposition algorithm in terms of both computational efficiency and solution quality. Copyright © 2024, The Authors. All rights reserved.

关键词： Profitability

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Communication Experiment of Iridium Satellite and Super Pressure Balloon over Antarctica

Communication Experiment of Iridium Satellite and Super Pres...

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Asia-Pacific Conference on Microwave

作者： Takana Kaho Yoshitaka Saito Yoshihiro Tomikawa Faculty of Engineering Shonan Institute of Technology Fujisawa Kanagawa Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Sagamihara City Kanagawa Japan National Institute of Polar Research Tokyo Japan Department of Polar Science The Graduate University for Advanced Studies SOKENDAI Tokyo Japan Polar Environment Data Science Center Research Organization of Information and Systems Tokyo Japan

ISBN: (数字)9784902339567

ISBN: (纸本)9781665451086

An experiment (LODEWAVE) was conducted from January to February 2022 to measure the atmospheric gravity wave over the Antarctica using a super pressure balloon and the PANSY radar located at Syowa Station in the Antarctica. The short burst communication of the Iridium satellite was used for communication with the balloon. In this paper, we report the experimental results on the error of the position information of the balloon and the communication quality due to the use of Iridium over Antarctica.

关键词： Satellites Thermometers Atmospheric measurements Spaceborne radar Redundancy Extraterrestrial measurements Antarctica

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An improved entropy function for the intuitionistic fuzzy sets with application to cloud vendor selection

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Decision Analytics Journal 2023年 7卷

作者： Krishankumar, Raghunathan Ravichandran, K.S. Aggarwal, Manish Pamucar, Dragan Information Technology Systems and Analytics Area Indian Institute of Management Bodh Gaya Bihar Bodh Gaya 824234 India Department of Mathematics Amrita School of Physical Sciences Coimbatore Amrita Vishwa Vidyapeetham India School of Artificial Intelligence and Data Science IIT Jodhpur Jodhpur India Digital Humanties IIT Jodhpur Jodhpur India Faculty of Organizational Sciences University of Belgrade Serbia College of Engineering Yuan Ze University Taiwan

This study proposes a novel entropy function for the intuitionistic fuzzy sets to improve the existing fuzzy entropy measure. We introduce an attitude-based entropy measure by methodically calculating the experts’ attitude values through variance approach. We discuss several important properties and present an example to demonstrate the applicability and efficacy of the proposed method. An illustrative example exhibits the effectiveness of the proposed intuitionistic fuzzy entropy functions and measures. We further show the superiority of the proposed intuitionistic fuzzy entropy measures over the existing measures. © 2023 The Author(s)

关键词： Aggarwal entropy Cloud vendor selection Decision-making Intuitionistic fuzzy sets Uncertainty

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A Comparative Study of Job-Related Stress in Long-Term Care Workers in Japan and China 9

A Comparative Study of Job-Related Stress in Long-Term Care ...

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9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020

作者： Yu, Yating Taki, Seiko Takanokura, Masato Kawakami, Masaru Yamada, Tetsuo Liang, Shuyu Kitami Institute of Technology Regional Management Engineering Course Kitami Japan Chiba Institute of Technology Faculty of Social Systems Science Department of Management Information Science Chiba Japan Kanagawa University Faculty of Engineering Department of Industrial Engineering and Management Yokohama Japan Jichi Medical University Faculty of Nursing Tochigi Japan The University of Electro-Communications Department of Informatics Tokyo Japan Shandong University Data Science Institute Jian China

ISBN: (纸本)9781728173979

Japan revised and implemented the Occupational Safety and Health Act in December 2015 to mandate that businesses with 50 or more workers have all of their workers tested for stress annually. In China, one effect of the 'one child policy' and the nuclearization of the family has been that the number of children has decreased, while the number of elderly people living alone continues to grow. This growth is increasing the demand for long-term care workers. However, because the aging of the Chinese population has been more rapid than in Japan, and China has yet to develop a long-term care system to cope with the aging of its population, the burden on long-term care staff appears to be increasing. Although the resulting need for more support for long-term care staff has become an issue, China has yet to develop a mental health policy like that of Japan that mandates the monitoring of mental health, for example, through annual testing of workers for stress. As a result, the factors underlying long-term care worker stress have yet to be *** study attempted to discover, through a comparison of long-term care worker stress in Japan and China, the kinds of job-related stress care workers tended to have and what the principal underlying factors resulting in high levels of stress may be in each country. To that end, data were collected on workers' psychological and physical stress using the Brief Job Stress Questionnaire (BJSQ) and analyzed to find out how stress may differ by country, gender, job responsibilities, having to work night shifts, or having certain qualifications. © 2020 IEEE.

关键词： Health

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