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BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2023年第9期104卷 S146-S206页

作者： Johnson, G. C. Lumpkin, R. Met Office Hadley Center Exeter United Kingdom NOAA/OAR Atlantic Oceanographic and Meteorological Laboratory Miami Florida Cooperative Institute for Marine and Atmospheric Studies University of Miami Miami Florida NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland Cooperative Institute for Climate Ocean and Ecosystem Studies University of Washington Seattle Washington NOAA/OAR Pacific Marine Environmental Laboratory Seattle Washington NASA Goddard Space Flight Center Greenbelt Maryland Morgan State University Baltimore Maryland College of Marine Science University of South Florida St. Petersburg Florida Woods Hole Oceanographic Institution Woods Hole Massachusetts International Center for Climate and Environment Sciences Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China Cooperative Institute for Marine and Atmospheric Studies University of Miami Rosenstiel School of Marine Atmospheric and Earth Science University of Miami Miami Florida Science Systems and Applications Inc. Lanham Maryland Science Systems and Applications Inc. Hampton Virginia Scripps Institution of Oceanography University of California San Diego La Jolla California Center for Coastal Physical Oceanography Old Dominion University Norfolk Virginia Australian Antarctic Program Partnership Institute for Marine and Antarctic Studies Australian Research Council Centre of Excellence for Climate Extremes University of Tasmania Hobart Tasmania NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Department of Atmosphere Ocean and Earth System Modeling Research Meteorological Research Institute Japan Meteorological Agency Tsukuba Japan National Oceanography Centre Liverpool United Kingdom Flanders Marine Institute InnovOcean Campus Ostend Belgium NOAA/NWS NCWCP Laboratory for Satellite Altimetry College Par

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Application of Message Security Application Using Vigenere Cipher Algorithm Utilizing One Time Pad (OTP) Algorithm as a Key Generator 1

Application of Message Security Application Using Vigenere C...

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1st Workshop on Environmental science, Society, and technology, WESTECH 2018

作者： Pardede, A.M.H. Br Sitepu, Lorena Perbina Zarlis, Muhammad Tulus Iskandar, Akbar Sriadhi, S. Manurung, Rosida Tiurma Siregar, Nurintan Asyiah Sari, Ayu Esteka Yunawati, Sri Mursyidah, M. Mursalin, M. Kurniasih, Nuning Kurniawan, Citra Winarno, Edy STMIK Kaputama Sumatera Utara Binjai Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Program Study of Accounting Pasir Pengaraian University Riau Indonesia Departement of Information Technology and Computer Politeknik Negeri Lhokseumawe Aceh Indonesia Department of Mathematics Education Universitas Malikussaleh Aceh Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Cryptography is the science and art of maintaining the security of messages when messages are sent from one place to another. One of the ways securing the form of text message information is by the encryption process using the Vigenere Cipher algorithm and utilizing the One Time Pad (OTP) algorithm as a key generator, where the message will be random when it is opened. The message encryption process used the vigenere cipher algorithm while OTP is used to secure the key with the same formula. After this research has been done, an application was designed to secure text messages by converting the text message into a random message so that the message was unreadable due to a secret message that could not be known by others. The results achieved can secure an encrypted message that cannot be reopened and if those messages were reopened, they must be decrypted. © Published under licence by IOP Publishing Ltd.

关键词： Cryptography

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Exploring students’ learning outcome and gender differences in a digital video clip course 26

Exploring students’ learning outcome and gender differences...

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26th International Conference on Computers in Education, ICCE 2018

作者： Liao, Yi-Wen Zhen, Xu-Jia Hwang, Gwo-Haur Department of Information Management Cheng Shiu University Taiwan Bachelor Program in Interdisciplinary Studies National Yunlin University of Science and Technology Taiwan

ISBN: (纸本)9789869721424

This study explores whether gender differences have significant impact on learning outcomes in the course of digital video clips. The subjects of the experiment were third-year students of the University of science and technology of Southern Taiwan. The learning goal of the course is to complete the 18-week course with all function operations and the project of digital video clips. The course adopts Project-Based Learning (PBL) teaching method. The midterm test includes several digital video clip discipline concepts and practical implementation. The final exam consists of several digital video clip works and project production. The project scoring method is peer-to-peer evaluation. There are 50 valid samples, including 25 boys and 25 girls. The experimental results show that girls' learning performance are higher than those of boys are. Therefore, in the digital video clip course, how to design suitable teaching strategies for different gender students' needs and improve the learning performance of students of different genders is a research topic worth exploring in the future. © 2018 Asia-Pacific Society for Computers in Education..All Rights Reserved.

关键词： Students

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Effect Implementation of information technology Software On Improving Performance Capacity Academic and Non Academic Service Sunan Ampel Islamic University of Surabaya

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Journal of Physics: Conference Series 2021年第1期1779卷

作者： Ilham Anis Eliyana Ahmad Rizki Sridadi Indrianawati Usman Agung Purnomo Information Systems Study Program Department of Technology Faculty of Science and Technology Sunan Ampel Islamic University Of Surabaya Department of Management Faculty of Economics and Business Airlangga University Bina Nusantara Institute of Creative Technology Malang Ahmad Yani 117 Street Surabaya East Java

This research was conducted to examine the effect of applying information technology software to increase the capacity of academic and non-academic performance at the Sunan Ampel State Islamic University in Surabaya as a work support tool. The aim is to apply a software that is able to identify the needs of increasing performance capacity at Sunan Ampel State Islamic University in Surabaya, both academic and non-academic, so that systematic control and evaluation of all academic and non-academic operations can be carried out. The research respondents were 60 students and employees from the Faculty of science and technology of the Sunan Ampel State Islamic University in Surabaya. This research uses a quantitative approach with the analysis technique used is path analysis with SmartPLS software-based data processing and the overall results support the hypothesis. Based on the results of the study stated that information technology has a positive and significant effect on performance, information technology has a positive and significant effect on academic services, information technology has a positive and significant effect on non-academic services, but performance has no effect on academic and non-academic services. The conclusion of the research is the influence of the application of information technology software can improve academic and non-academic performance and services at the Sunan Ampel State Islamic University of Surabaya

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Classification of the Structural Integrity by the General Vibration Method

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Procedia Computer science 2019年 157卷 382-387页

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information Systems Information Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Traditionally, for the purpose of classifying the integrity of an engineering structure, one may use the information of the natural frequencies or mode shapes or some other measures derived from the two. In this research, we propose a classification method on the basis of the general vibration model. The general vibration model is essentially a set of differential equations describing the dynamics of the structure under consideration. For the purpose of damage detection, a deviation of the general vibration model from the dynamic equilibrium point marks the occurrence of the damage. To demonstrate the effectiveness of the method, we study two simplest dynamical systems consisting of one- and two-concentrated masses subjected to a prescribed dynamic load. The structural damages are introduced artificially by reducing the stiffness of spring in the structures. We find that the general vibration model is more sensitive to damages than the traditional methods.

关键词： General Vibration Model Structural Integrity Structural Health Monitoring Power Spectral Density Damage Index

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A Study of the Sensitivity of the Fuel Consumption to Driving Strategy by Micro Simulation

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Procedia Computer science 2019年 157卷 375-381页

Global warming due to excessive emission greenhouse gases is a significant issue faced by humanity, and collectively, cars and trucks contribute about 20% to the entire global-warming gases. For a reason, recently, many attempts have been endured to reduce the emission and to increase fuel efficiency, including vehicle platooning, better driving strategy, and increasing engine efficiency. This study intends to provide a more detail assessment regarding the effects of the driving strategy to fuel consumption. For the purpose, the vehicle dynamics are quantified by employing the car-following model based on the optimal velocity model. The fuel consumption is estimated from the regression model of Ahn 18 . The result suggests that the braking distance strongly affects fuel consumption.

关键词： Optimal Velocity Model Micro Simulation Car-Following Model Fuel Efficiency

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From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence

arXiv

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arXiv 2023年

作者： Oniani, David Hilsman, Jordan Peng, Yifan Poropatich, Ronald K. Pamplin, Jeremy C. Legault, Gary L. Wang, Yanshan Department of Health Information Management University of Pittsburgh PittsburghPA United States Department of Population Health Sciences Weill Cornell Medicine New YorkNY United States Division of Pulmonary Allergy & Critical Care Medicine University of Pittsburgh PittsburghPA United States Center for Military Medicine Research University of Pittsburgh PittsburghPA United States Telemedicine & Advanced Technology Research Center US Army Fort DetrickMD United States Department of Surgery Uniformed Services University BethesdaMD United States Virtual Medical Center Brooke Army Medical Center San AntonioTX United States Intelligent Systems Program University of Pittsburgh PittsburghPA United States Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Clinical and Translational Science Institute University of Pittsburgh PittsburghPA United States University of Pittsburgh Medical Center Hillman Cancer Center PittsburghPA United States

In 2020, the U.S. Department of Defense officially disclosed a set of ethical principles to guide the use of Artificial Intelligence (AI) technologies on future battlefields. Despite stark differences, there are core similarities between the military and medical service. Warriors on battlefields often face life-altering circumstances that require quick decision-making. Medical providers experience similar challenges in a rapidly changing healthcare environment, such as in the emergency department or during surgery treating a life-threatening condition. Generative AI, an emerging technology designed to efficiently generate valuable information, holds great promise. As computing power becomes more accessible and the abundance of health data, such as electronic health records, electrocardiograms, and medical images, increases, it is inevitable that healthcare will be revolutionized by this technology. Recently, generative AI has captivated the research community, leading to debates about its application in healthcare, mainly due to concerns about transparency and related issues. Meanwhile, concerns about the potential exacerbation of health disparities due to modeling biases have raised notable ethical concerns regarding the use of this technology in healthcare. However, the ethical principles for generative AI in healthcare have been understudied, and decision-makers often fail to consider the significance of generative AI. In this paper, we propose GREAT PLEA ethical principles, encompassing governance, reliability, equity, accountability, traceability, privacy, lawfulness, empathy, and autonomy, for generative AI in healthcare. Furthermore, we introduce a framework for adopting and expanding practical ethical principles that have been useful in the military to healthcare for generative AI, based on contrasting their ethical concerns and risks. We aim to proactively address the ethical dilemmas and challenges posed by the integration of generative AI in healthcare. C

关键词： Artificial intelligence

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Deep learning-based air pollution analysis on carbon monoxide in Taiwan

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Ecological Informatics 2024年 80卷

作者： Cheng-Hong Yang Po-Hung Chen Chih-Hsien Wu Cheng-San Yang Li-Yeh Chuang Department of Information Management Tainan University of Technology Tainan Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan Division of Plastic and Reconstruction Surgery Department of Surgery Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering I-Shou University Kaohsiung Taiwan

Global air pollution poses a threat to humanity. Specifically, CO directly affects cardiovascular and other organ tissues and leads to numerous chronic diseases and major public health problems. The effective implementation of a deep learning model for predicting variations in CO levels would enable the early formulation of policies for controlling air pollution. In this study, a seasonal gated recurrent unit (SGRU) model, which is a deep learning time-series prediction model, was developed to predict the levels of CO in Taiwan. Atmospheric CO measurements from 2005 to 2021 were collected from the Environmental Protection Administration of Taiwan and preprocessed using the Kalman filter to achieve accurate forecasting. The performance of the proposed SGRU model was compared with that of the autoregressive integrated moving average (ARIMA), seasonal ARIMA, exponential smoothing (ETS), Holt–Winters ETS, support vector regression, and seasonal long short-term memory models in terms of mean absolute percentage error (MAPE) and root mean square error. The SGRU model achieved the lowest MAPE value of 0.94, which demonstrated its superior performance. The construction of an accurate air pollution prediction model can assist government entities in formulating health and social care strategies and in planning future air pollution control measures.

关键词： Air pollution Carbon Monoxide (CO) Deep learning Seasonal gated recurrent unit (SGRU)

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The Matter of Deep Reinforcement Learning Towards Practical AI Applications

The Matter of Deep Reinforcement Learning Towards Practical ...

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IEEE International Conference on Ubi-Media Computing

作者： Tipajin Thaipisutikul Yi-Cheng Chen Lin Hui Sheng-Chih Chen Pattanasak Mongkolwat Timothy K. Shih Department of Computer Science and Information Engineering National Central University Taiwan Department of Information Management National Central University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Faculty of Information and Communication Technology Mahidol University Thailand

ISBN: (数字)9781728128207

ISBN: (纸本)9781728128214

Reinforcement Learning (RL) is an extraordinarily paradigm that aims to solve a complex problem. This technique leverages the traditional feedforward networks with temporal-difference learning to overcome supervised and unsupervised real-world problems. However, RL is one of state-of-the-art topic due to the opaque aspects in design and implementation. Also, in which situation we will get performance gain from RL is still unclear. Therefore, This study firstly examines the impact of Experience Replay in Deep Q-Learning agent with Self-Driving Car application. Secondly, The impact of Eligibility Trace in RNN A3C agents with Breakout AI game application is studied. Our results indicated that these two techniques enhance RL performance by more than 20 percent as compared with traditional RL methods.

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Usability evaluation of exercise games for medical interactive rehabilitation assistance (MIRA) system for tele-rehabilitation

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AIP Conference Proceedings 2022年第1期2644卷

作者： Norasikin Fabil Waidah Ismail Evi Indriasari Mansor Kavintheran A/L Thambiratnam Rimuljo Hendradi 1Faculty Science and Technology Universiti Sains Islam Malaysia Bandar Baru Nilai 71800 Nilai Negeri Sembilan Malaysia 2Business Analytics Master Program Abu Dhabi School of Management Abu Dhabi United Arab Emirates 3Photonics Research Centre Deputy Vice Chancellor (Research & Innovation) Office University of Malaya 50603 Kuala Lumpur Malaysia 4Information System Study Program Universitas Airlangga Indonesia Kampus C Surabaya Indonesia

Rehabilitation therapy is a fundamental need for patients that suffer from illness, effects after accident or surgery. The patients need to perform traditional rehabilitation for undergo clinical therapy sessions handled by a therapist in monitoring the patient's improvement. Once the patients discharge, they need to perform consistently exercise remotely at home or outside from rehabilitation centre, Telerehabilitation was introduced. One of the exercises to encourage patients is using exercise games (exergames). In this paper, we are concentrating on usability evaluation of exergames named Medical Interactive Rehabilitation Assistance (MIRA) System with Twenty-eight exercises performed by patients. We performed data collection using qualitative and quantitative for 45 patients from SOSCO Rehabilitation Centre in Malacca. The questionnaire consists of three sections - demographic, usage of the MIRA system and lastly participant's opinion. In conclusion, the findings showed positive feedback in using exergames as part of their rehab exercise that can lead into implementation of Telerehabilitation.

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