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arXiv 2021年

作者： Irrgang, Christopher Boers, Niklas Sonnewald, Maike Barnes, Elizabeth A. Kadow, Christopher Staneva, Joanna Saynisch-Wagner, Jan Helmholtz Centre Potsdam German Research Centre for Geosciences GFZ Potsdam Germany Department of Mathematics and Computer Science Free University of Berlin Germany Potsdam Institute for Climate Impact Research Potsdam Germany Department of Mathematics and Global Systems Institute University of Exeter United Kingdom Program in Atmospheric and Oceanic Sciences Princeton University PrincetonNJ08540 United States NOAA OAR Geophysical Fluid Dynamics Laboratory Ocean and Cryosphere Division PrincetonNJ08540 United States University of Washington School of Oceanography SeattleWA United States Colorado State University Fort Collins United States German Climate Computing Center DKRZ Hamburg Germany Helmholtz-Zentrum Geesthacht Center for Material and Coastal Research HZG Geesthacht Germany

We outline a perspective of an entirely new research branch in Earth and climate sciences, where deep neural networks and Earth system models are dismantled as individual methodological approaches and reassembled as learning, self-validating, and interpretable Earth system model-network hybrids. Following this path, we coin the term"Neural Earth System Modelling" (NESYM) and highlight the necessity of a transdisciplinary discussion platform, bringing together Earth and climate scientists, big data analysts, and AI experts. We examine the concurrent potential and pitfalls of Neural Earth System Modelling and discuss the open question whether artificial intelligence will not only infuse Earth system modelling, but ultimately render them obsolete. © 2021, CC BY.

关键词： Climate models

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Adaptive Coordination Offsets for Signalized Arterial Intersections using Deep Reinforcement Learning

arXiv

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arXiv 2020年

作者： Diaz, Keith Anshilo Dailisan, Damian Sharaf, Umang Santos, Carissa Gan, Qijian Uy, Francis Aldrine Lim, May T. Bayen, Alexandre M. The School of Civil Environmental and Geological Engineering Mapua University Manila Philippines The National Institute of Physics University of the Philippines Diliman Philippines The Analytics Computing and Complex Systems Laboratory Asian Institute of Management Philippines The Electrical Engineering and Computer Sciences department at University of California Berkeley United States The PATH program in the Institute of Transportation Studies University of California Berkeley United States The Electrical Engineering and Computer Sciences Department The Department of Civil and Environmental Engineering The Institute of Transportation Studies University of California Berkeley United States

Coordinating intersections in arterial networks is critical to the performance of urban transportation systems. Deep reinforcement learning (RL) has gained traction in traffic control research along with data-driven approaches for traffic control systems. To date, proposed deep RL-based traffic schemes control phase activation or duration. Yet, such approaches may bypass low-volume links for several cycles to optimize the network-level traffic flow. Here we propose a deep RL framework that dynamically adjusts offsets based on traffic states and preserves the planned phase timings and order derived from model-based methods. This framework improves arterial coordination while maintaining phase order and timing predictability. Using a validated and calibrated traffic model, we trained the policy of a deep RL agent that aims to reduce travel delays in the network. To evaluate the resulting policy, we compared its performance against the phase offsets deployed along a segment of Huntington Drive in the city of Arcadia. The resulting policy dynamically readjusts phase offsets in response to changes in traffic demand. Simulation results show that the proposed deep RL agent outperformed the baseline on average, effectively reducing delay time by 13.21% in the AM Scenario, 2.42% in the Noon scenario, and 6.2% in the PM scenario when offsets are adjusted in 15-minute intervals. Finally, we also show the robustness of our agent to extreme traffic conditions, such as demand surges in off-peak hours and localized traffic incidents. Copyright © 2020, The Authors. All rights reserved.

关键词： Reinforcement learning

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"So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

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International Journal of Information Management 2023年 71卷

作者： Dwivedi, Yogesh K. Kshetri, Nir Hughes, Laurie Slade, Emma Louise Jeyaraj, Anand Kar, Arpan Kumar Baabdullah, Abdullah M. Koohang, Alex Raghavan, Vishnupriya Ahuja, Manju Albanna, Hanaa Albashrawi, Mousa Ahmad Al-Busaidi, Adil S. Balakrishnan, Janarthanan Barlette, Yves Basu, Sriparna Bose, Indranil Brooks, Laurence Buhalis, Dimitrios Carter, Lemuria Chowdhury, Soumyadeb Crick, Tom Cunningham, Scott W. Davies, Gareth H. Davison, Robert M. Dé, Rahul Dennehy, Denis Duan, Yanqing Dubey, Rameshwar Dwivedi, Rohita Edwards, John S. Flavián, Carlos Gauld, Robin Grover, Varun Hu, Mei-Chih Janssen, Marijn Jones, Paul Junglas, Iris Khorana, Sangeeta Kraus, Sascha Larsen, Kai R. Latreille, Paul Laumer, Sven Malik, F. Tegwen Mardani, Abbas Mariani, Marcello Mithas, Sunil Mogaji, Emmanuel Nord, Jeretta Horn O'Connor, Siobhan Okumus, Fevzi Pagani, Margherita Pandey, Neeraj Papagiannidis, Savvas Pappas, Ilias O. Pathak, Nishith Pries-Heje, Jan Raman, Ramakrishnan Rana, Nripendra P. Rehm, Sven-Volker Ribeiro-Navarrete, Samuel Richter, Alexander Rowe, Frantz Sarker, Suprateek Stahl, Bernd Carsten Tiwari, Manoj Kumar van der Aalst, Wil Venkatesh, Viswanath Viglia, Giampaolo Wade, Michael Walton, Paul Wirtz, Jochen Wright, Ryan Digital Futures for Sustainable Business & Society Research Group School of Management Swansea University Bay Campus Fabian Bay Wales Swansea United Kingdom Maharashtra Pune India Bryan School of Business and Economics University of North Carolina at Greensboro United States University of Bristol Business School University of Bristol BS8 1SD United Kingdom Professor of Information Systems Raj Soin College of Business Wright State University 3640 Colonel Glenn Highway DaytonOH45435 United States School of Artificial Intelligence Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Studies Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Information Systems Faculty of Economics and Administration King Abdulaziz University Jeddah Saudi Arabia School of Computing Middle Georgia State University MaconGA United States Client Advisory and Transformation Stackroute NIIT Limited India Department of Information Systems Analytics and Operations College of Business University of Louisville United States Northumbria University London United Kingdom IRC-FDE KFUPM Saudi Arabia ISOM KFUPM Business School KFUPM Saudi Arabia Innovation and Technology Transfer Center Sultan Qaboos University Oman Department of Business Communication Sultan Qaboos University Oman Department of Management Studies National Institute of Technology Tiruchirappalli India Montpellier France FORE School of Management New Delhi India Indian Institute of Management Ahmedabad Vastrapur Ahmedabad380015 India Information School University of Sheffield United Kingdom Bournemouth University Business School Poole United Kingdom School of Information Systems and Technology Management University of New South Wales Sydney Australia Information Operations and Management Sciences Department TBS Business School 1 Place Alphonse Jourdain Toulouse31068 France Department of Education & Childhood Studies Swansea Univers

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics;digital transformation of organisations and societies;and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI;examining biases of generative AI attributable to training datasets and processes;exploring business and societal contexts best suited for generative AI implementation;determining optimal combinations of human and generative AI for various tasks;identifying ways to assess accuracy of text produced by generative AI;and uncovering the ethical and legal issues in using generative AI across different contexts. © 2023 The Authors

关键词： Marketing

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Content-Based Echo Chamber Detection on Social Media Platforms

Content-Based Echo Chamber Detection on Social Media Platfor...

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Fernando H. Calderón Li-Kai Cheng Ming-Jen Lin Yen-Hao Huang Yi-Shin Chen Social Networks and Human Centered Computing Taiwan International Graduate Program Institute of Information Science Academia Sinica Hsinchu City Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu City Taiwan National Taiwan University Taipei City Taiwan

ISBN: (数字)9781450368681

ISBN: (纸本)9781450368681

“Echo chamber” is a metaphorical description of a situation in which beliefs are amplified inside a closed network, and social media platforms provide an environment that is well-suited to this phenomenon. Depending on the scale of the echo chamber, a user's judgment of different opinions may be restricted. The current study focuses on detecting echoing interaction between a post and its related comments to then quantify the predominating degree of echo chamber behavior on Facebook pages. To enable such detection, two content-based features are designed; the first aids stance representation of comments on a particular discussion topic, and the second focuses on the type and intensity of emotion elicited by a subject. This work also introduces data-driven semi-supervised approaches to extract such features from social media data.

关键词： Feature extraction Social network services Fans Urban areas Connectors Linguistics Computational modeling

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The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia

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The Lancet Psychiatry 2022年第6期9卷 477-486页

作者： Gumley, Andrew I Bradstreet, Simon Ainsworth, John Allan, Stephanie Alvarez-Jimenez, Mario Aucott, Lorna Birchwood, Maximillian Briggs, Andrew Bucci, Sandra Cotton, Sue M Engel, Lidia French, Paul Lederman, Reeva Lewis, Shôn Machin, Matthew MacLennan, Graeme McLeod, Hamish McMeekin, Nicola Mihalopoulos, Cathy Morton, Emma Norrie, John Schwannauer, Matthias Singh, Swaran P Sundram, Suresh Thompson, Andrew Williams, Chris Yung, Alison R Farhall, John Gleeson, John Glasgow Institute of Health and Wellbeing University of Glasgow Glasgow United Kingdom Division of Psychology and Mental Health School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Division of Informatics Imaging and Data Sciences School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Orygen Melbourne Melbourne VIC Australia Centre for Youth Mental Health University of Melbourne Melbourne VIC Australia School of Computing and Information Systems Faculty of Engineering and Information Technology University of Melbourne Melbourne VIC Australia Centre for Healthcare Randomised Trials (CHaRT) University of Aberdeen Aberdeen United Kingdom Centre for Mental Health and Wellbeing Research Warwick Medical School University of Warwick Warwick United Kingdom Department of Health Services Research and Policy London School of Hygiene & Tropical Medicine London United Kingdom Greater Manchester Mental Health NHS Foundation Trust Manchester United Kingdom School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia Department of Psychiatry School of Clinical Sciences Monash University Melbourne VIC Australia School of Medicine Deakin University Melbourne VIC Australia Department of Psychiatry Manchester Metropolitan University Manchester United Kingdom Department of Psychiatry University of British Columbia Vancouver BC Canada The Usher Institute University of Edinburgh Edinburgh United Kingdom School for Health in Social Sciences University of Edinburgh Edinburgh United Kingdom Mental Health Program Monash Health Melbourne VIC Australia Department of Psychology and Counselling La Trobe University Melbourne VIC Australia NorthWestern Mental Health The Royal Melbourne Hospital Epping VIC Australia Healthy Brain and Mi

Background: Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia. Methods: This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262). Findings: We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Au

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Implementation on Indonesian property real estate industry based on service oriented architecture

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IOP Conference Series: Materials Science and Engineering 2020年第1期725卷

作者： Ahmad Nurul Fajar Nunung Nurul Qomariyah Albert Baihaqi Siregar Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia 11480 Department of Information Technology Universitas Sumatera Utara Medan Indonesia

This study focuses on the implementation of business property in real estate market. This is due to inability of the current technology to support the property products. Some people feel uncomfortable to buy houses from the online market. Buyers need to be very careful to deal with the sellers as the houses price is considered quite expensive. On the other hand, improving real estate market is still a challenge. This business still needs a physical representation, although it can be sold from the online market. In this paper, we propose the Service Oriented Architecture (SOA) system of virtual reality and drone. We use drone to help scanning the property units and then make 3D models with visual mapping so it can be run in a virtual reality environment, video 360. In real estate, business process can be developed in various ways. Our proposed SOA in this study can be used to integrate all of them.

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Conventional and adaptive strategies applied to DC motor control using microcontroller PIC18F4520 7

Conventional and adaptive strategies applied to DC motor con...

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7th Brazilian Electrical systems Symposium, SBSE 2018

作者： Taveiros, Filipe Emanuel Vieira Barros, Luciano Sales Barros, Camila Mara Vital Electrical Engineering and Computing Graduate Program of Federal University of Rio Grande Do Norte Natal Brazil Electrical Engineering Department of Federal University of Rio Grande Do Norte Natal Brazil Computer Systems Department of Federal University of Paraíba João Pessoa Brazil

ISBN: (纸本)9781538633632

In this paper strategies to control the speed of a generic DC motor system are discussed. They range from the conventional, like PID and state-feedback, to reference model adaptive algorithms such as MRAC, VS-MRAC and DMARC. The goal of this study is to determine the best control strategy for high-performance applications regarding to stability, robustness and optimal controller effort. In theory and sometimes in practice, all these control strategies proof themselves reliable, however, in heavy-duty set-point references the application requires high performance of the controller under disturbances, unmodeled dynamics and variable speed reference conditions. The use of appropriate control strategies can highly contribute to this purpose. To support the conclusions, the control strategies have been embedded in a microcontroller PIC18F4520 and applied to a test motor in order to obtain experimental results. © 2018 IEEE.

关键词： Three term control systems

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Using causal loop diagrams to explore the maternal and child health system response to payment for performance in Zambia, and it’s generalisability across settings

SSM - Health Systems

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SSM - Health systems 2025年 5卷

作者： Chitalu Miriam Chama-Chiliba Nkenda Sachingongu Rachel Cassidy Peter Binyaruka Collins Chansa Agnes Rwashana Semwanga Josephine Borghi Institute of Economic and Social Research University of Zambia P O Box 32379 Plot 2631 Munali Road Chudleigh Lusaka 10101 Zambia Department of Gender Studies University of Zambia P O Box 32379 Great East Road Campus Lusaka 10101 Zambia KPM Center for Public Management University of Bern Bern 3012 Switzerland Swiss Institute for Translational and Entrepreneurial Medicine Bern 3010 Switzerland Department of Global Health and Development London School of Hygiene and Tropical Medicine 15-17 Tavistock Place London WC1H 9SH UK Ifakara Health Institute P O Box 78373 Dar es Salaam Tanzania Health Nutrition and Population Global Practice World Bank Group Monrovia Liberia Heidelberg Institute of Global Health Heidelberg University Hospital and Medical Faculty Heidelberg Germany Information Systems Department College of Computing and Information Sciences Makerere University P O Box 7062 Kampala Uganda Social Cohesion Health and Wellbeing Research Group Population and Just Societies Program International Institute for Applied Systems Analysis Austria

This study investigates the generalisability of pathways depicted by causal loop diagrams (CLDs) in payment for performance (P4P) schemes by adapting and validating the Tanzanian CLDs to the Zambian context. Specifically, it explores whether the health system pathways represented by CLDs, are consistent across different settings and how variations in programme design and local context influence these pathways. Using a five-stage approach, the study adapted the Tanzanian CLDs to reflect the Zambian P4P programme context, validating them through stakeholder interviews, workshops, and secondary qualitative data. The findings show that while the overarching pathways influencing P4P outcomes are similar, differences in programme design and contextual factors shape their intensity and impact. Notably, Zambia’s higher facility autonomy and stronger trust in the health system contributed to greater health worker motivation and service delivery compared to Tanzania. programme design features such as safeguards for non-incentivised services and adequate funding for facility investment with provider autonomy influenced performance outcomes. Additionally, contextual factors such as trust in the system mitigated programme delays, while decentralised procurement systems enhanced P4P effectiveness. These findings highlight the need for context-specific adaptation when implementing P4P programmes. The study advances the application of CLDs for cross-country health system analysis, highlighting both their potential and limitations in comparing health interventions across diverse settings.

关键词： Health system Causal loop diagram Payment for performance Maternal and child health Zambia Tanzania

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Regularization of Extreme Learning Machines with information of spatial relations of the projected data

Regularization of Extreme Learning Machines with information...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Lourenço R. G. Araújo Luiz C. B. Torres Leonardo J. Silvestre Carla Takahashi Antônio P. Braga Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Computing and Systems Federal University of Ouro Preto Jo??o Monlevade Brazil Department of Computing and Electronics Federal University of Esp??rito Santo S??o Mateus ES Brazil Loggi Tecnologia Alameda Santos S??o Paulo SP Brazil Department of Electronics Engineering Federal University of Minas Gerais Belo Horizonte MG Brazil

The following work presents a new approach to automatic selection of Tikhonov's regularization parameter, responsible for controlling the weight value of an ELM neural network. A strategy based on measurements obtained from data projection (Fisher-Score) is introduced. Seven datasets are tested and results are compared to those obtained when the regularization parameter is selected through cross-validation. The strategy shows satisfactory classification performance (in terms of p-value), while presenting significant training time reduction.

关键词： Neurons Training Cybernetics Minimization Testing Biological neural networks Aerospace electronics

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Bipolar Early Intervention Using New Digital Technologies (BLEND): A Pilot Randomised Controlled Trial of a Novel Blended-Digital Early Intervention Model of Care for Youth With Bipolar Disorder I or II

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Early Intervention in Psychiatry 2025年第6期19卷

作者： Aswin Ratheesh Jesse Gates Dylan Hammond Clare Shelton Craig Macneil Melissa Hasty M Arup Dhar Simon D'Alfonso Lianne Schmaal Lars V. Kessing John F. Gleeson Chris Davey Andrew Chanen Greg Murray Sue M. Cotton Patrick D. McGorry Michael Berk Mario Alvarez-Jimenez Orygen Parkville Australia Centre for Youth Mental Health The University of Melbourne Parkville Australia Discipline of Psychiatry and Mental Health The University of New South Sydney Australia School of Health and Biomedical Sciences RMIT University Melbourne Australia Orygen Specialist Program The Royal Melbourne Hospital Parkville Australia School of Computing and Information Systems The University of Melbourne Parkville Australia Copenhagen Affective Disorders Research Center (CADIC) Psychiatric Center Copenhagen Mental Health Services Capital Region of Denmark Copenhagen Denmark Department of Clinical Medicine University of Copenhagen Copenhagen Denmark Healthy Brain and Mind Research Centre Australian Catholic University Fitzroy Australia Department of Psychiatry The University of Melbourne Parkville Australia Centre for Mental Health and Brain Sciences Swinburne University of Technology Hawthorn Australia School of Psychological Sciences Monash University Clayton Australia Institute for Mental and Physical Health and Clinical Translation (IMPACT) Deakin University Geelong Australia

Background Despite evidence for early interventions for bipolar disorder (BD), there are relatively few accessible treatment models. We developed a digitally augmented model of care termed BLEND (BipoLar early interventions using New Digital technologies) which aims to improve mood symptoms in BD. BLEND includes: (a) guideline-concordant pharmacotherapy; (b) in-person psychological therapies blended with digital therapeutic content and (c) digital relapse monitoring. The aim of this study was twofold: (i) describe the acceptability, safety and feasibility of delivering BLEND and (ii) examine the feasibility of an efficacy trial of BLEND compared with enhanced standard care (ESC). Method We conducted a parallel-group, open-label, 2:1 randomised pilot trial within a youth mental-health outpatient service in Melbourne, Australia. We included youth aged 15–25 years with BD I or II, who had not previously accessed multidisciplinary care. All participants received similar background care. BLEND differed from ESC in having manualised blended digital and in-person psychological therapies and digital relapse monitoring. Results We randomised 21 young people over a 12-month recruitment period, predominantly female participants (71.4%) with BD Type II (85.7%). Both treatment models were acceptable and safe, but the BLEND group had greater reductions in suicidal ideation. Among components of BLEND, in-person psychological therapy and psychopharmacological interventions could be delivered with fidelity. Digital therapy engagement was high, but participants used digital relapse monitoring variably. Conclusions The BLEND model was safe and acceptable and may lead to improvements in suicidality compared with ESC. Concordant with the aims of a pilot study, there is scope for the content to be rationalised based on feedback to improve feasibility of the digital therapy. Relapse monitoring may usefully be extended to depressive symptoms. The next step is to confirm the efficacy of BLE

关键词： bipolar disorder depression early medical intervention mania mental health pilot projects psychiatry

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