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Fwd: [WI] BigDat 2020 Autumn: early registration June 26
by Gustaf Neumann 09 Jun '20

09 Jun '20

-------- Forwarded Message -------- Subject: [WI] BigDat 2020 Autumn: early registration June 26 Date: Tue, 09 Jun 2020 03:33:38 +0200 From: IRDTA <irdta(a)irdta.eu> Reply-To: IRDTA <irdta(a)irdta.eu> To: wi(a)lists.kit.edu BigDat 2020 Autumn: early registration June 26 *To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line* ********************************************** *7th INTERNATIONAL SCHOOL ON BIG DATA* *BigDat 2020 Autumn* *Beersheba, Israel* *October 25-29, 2020* Co-organized by: Ben-Gurion University of the Negev Department of Software and Information Systems Engineering Data Science Research Center Institute for Research Development, Training and Advice (IRDTA) Brussels/London https://irdta.eu/bigdat2020a/ ********************************************** --- Early registration deadline: June 26, 2020 --- ********************************************** *SCOPE:* BigDat 2020 Autumn will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of big data. Previous events were held in Tarragona, Bilbao, Bari, Timisoara, Cambridge and Ancona. Big data is a broad field covering a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, medicine, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience. Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, security and privacy, and applications (to biological and health sciences, to business, finance and transportation, to online social networks, etc.). Major challenges of analytics, management and storage of big data will be identified through 24 four-hour and a half courses, 2 keynote lectures and 1 round table, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. *ADDRESSED TO:* Master's students, PhD students, postdocs, and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2020 Autumn is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators. *VENUE:* BigDat 2020 Autumn will take place in Beersheba, the largest city in the Negev desert of southern Israel and an important technology center. The venue will be: Ben-Gurion University of the Negev Marcus Family Campus https://in.bgu.ac.il/en/Pages/interactive.aspx *STRUCTURE:* 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. *KEYNOTE SPEAKERS:* tba *PROFESSORS AND COURSES:* (to be completed) Paolo Addesso (University of Salerno), [introductory/intermediate] Data Fusion for Remotely Sensed Data Thomas Bäck & Hao Wang (Leiden University), [introductory/intermediate] Data Driven Modeling and Optimization for Industrial Applications Paul Bliese (University of South Carolina), [introductory/intermediate] Using R for Mixed-effects (Multilevel) Models Altan Cakir (Istanbul Technical University), [intermediate] Big Data Analytics with Apache Spark Edward Chang (Stanford University), [intermediate] Artificial Intelligence for Disease Diagnosis and Precision Surgery Michael X. Cohen (Radboud University Nijmegen), [introductory] Dimension Explosion and Dimension Reduction in Brain Electrical Activity Ian Fisk (Flatiron Institute), [introductory] The Infrastructure to Support Data Science Michael Freeman (University of Washington), [intermediate] Interactive Data Visualization Using D3 + Observable David Gerbing (Portland State University), [introductory] Derive Meaning from Data with R Visualizations Yifan Hu (Yahoo Research), [introductory/advanced] Data Visualization and Machine Learning Wagner A. Kamakura (Rice University), [intermediate] Advanced Business Analytics using Excel Addins Ravi Kumar (Google), [intermediate/advanced] Clustering for Big Data Victor O.K. Li (University of Hong Kong), [intermediate] Deep Learning and Applications Panos Pardalos (University of Florida), [intermediate/advanced] Optimization and Data Sciences Techniques for Large Networks Valeriu Predoi (University of Reading), [introductory] A Beginner's Guide to Big Data Analysis: How to Connect Scientific Software Development with Real World Problems Alexandre Vaniachine (VirtualHealth), [intermediate] Open-source Columnar Databases Sebastián Ventura (University of Córdoba), [intermediate/advanced] Supervised Descriptive Pattern Mining Xiaowei Xu (University of Arkansas, Little Rock), [introductory/advanced] Deep Learning for Text Mining *OPEN SESSION:* An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david(a)irdta.eu by October 17, 2020. *INDUSTRIAL SESSION:* A session will be devoted to 10-minute demonstrations of practical applications of big data in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People participating in the demonstration must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by October 17, 2020. *EMPLOYER SESSION:* Firms searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by October 17, 2020. *ORGANIZING COMMITTEE:* Stavi Baram (Beersheba) Mark Last (Beersheba) Carlos Martín-Vide (Tarragona, program chair) Sara Morales (Brussels) Manuel J. Parra-Royón (Granada) Lior Rokach (Beersheba, co-chair) Bracha Shapira (Beersheba, co-chair) David Silva (London, co-chair) *REGISTRATION:* It has to be done at https://irdta.eu/bigdat2020a/registration/ The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue is exhausted. It is highly recommended to register prior to the event. *FEES:* Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. Refunding of registration fees will not be possible. However, an exception will be made in case the event must be postponed due to the continuation of the coronavirus crisis in Autumn (which is a scenario the organizers do not expect). *ACCOMMODATION:* Suggestions for accommodation will be available in due time. *CERTIFICATE:* A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. *QUESTIONS AND FURTHER INFORMATION:* david(a)irdta.eu *ACKNOWLEDGMENTS:* Ben-Gurion University of the Negev Institute for Research Development, Training and Advice (IRDTA) – Brussels/London -- Mailing-Liste: wi(a)lists.kit.edu Administrator: wi-request(a)lists.kit.edu Konfiguration: https://www.lists.kit.edu/wws/info/wi

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Fwd: [AISWorld] Last call for registering at dg.o 2020
by Gustaf Neumann 09 Jun '20

09 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] Last call for registering at dg.o 2020 Date: Tue, 9 Jun 2020 02:11:58 +0000 From: Luis Felipe Luna Reyes <luisf.luna(a)udlap.mx> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> ========================================================== The 21st International Digital Government Research Conference dg.o 2020 Intelligent Government in the Intelligent Information Society June 15-19, 2020 ========================================================== This is one last reminder about registering for dg.o 2020, which will be a virtual conference from June 15 to 19. We are featuring more than 60 presentations including posters, parallel presentations and several plenary addresses See full program at http://dgsociety.org/wp-content/uploads/2017/04/2020-dg.o-conference-progra…. Already confirmed are presentations by Prof. Jane Fountain, Prof Yelena Yesha, Prof. Marijn Janssen and Prof. Ramon Gil-Garcia. We also have a guest plenary presentation by Dr. Kate Hohman and Dr. Robert Domansky from New York City, who will share their first-hand experience responding to the pandemic and digital government in The City. Overall, we are looking for a great conference!!! Registration is still open at http://dgsociety.org/dgo-2020/registration/. Best Regards, Luis Luna-Reyes President of the Digital Government Society _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] 3rd Call For Book Chapters: Handbook of Research on Intelligent Analytics with Multi-Industry Applications
by Gustaf Neumann 09 Jun '20

09 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] 3rd Call For Book Chapters: Handbook of Research on Intelligent Analytics with Multi-Industry Applications Date: Tue, 9 Jun 2020 13:10:57 +1000 From: Zhaohao Sun <zhaohao.sun(a)gmail.com> To: aisworld(a)lists.aisnet.org, cmoyer(a)igi-global.com, Jun Han <jun_han(a)buaa.edu.cn> BOOK: Handbook of Research on Intelligent Analytics with Multi-Industry Applications EDITED BY PROF. DR. ZHAOHAO SUN TO BE PUBLISHED BY IGI Global, USA https://www.igi-global.com/publish/call-for-papers/call-details/4539 or http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=96711 or https://www.researchgate.net/project/Intelligent-Analytics-with-Applications Introduction Intelligent analytics is an emerging scientific paradigm that integrates big data/information/knowledge/wisdom, analytics and artificial intelligence (AI) to provide smart services to our work, business, life, industry and society. From a fundamental perspective, intelligent analytics at least includes intelligent big data analytics, intelligent big information analytics, intelligent big knowledge analytics, intelligent big wisdom analytics. Intelligent analytics has been revolutionizing our work, life, business, management, organization and industry. It becomes disruptive technology for healthcare, web services, service computing, cloud computing, 5G development, blockchain and social networking computing. However, many fundamental, technological and managerial issues in developing and applying intelligent analytics with multi-industry applications remain open. For example, what is the foundation of intelligent analytics? what are the elements of intelligent analytics? What are the real big characteristics of intelligent analytics? How can apply intelligent analytics to improve healthcare, mobile commerce, web services, cloud services, blockchain, 5G development, digital transformation and industries? What is the effect of intelligent analytics on business, management, the Internet of things, cloud computing, blockchain, service and society? This book will address these issues by exploring the cutting-edge theory, technologies and methodologies of intelligent analytics with multi-industry applications and emphasize integration of AI, business intelligence, big data/information/knowledge/wisdom, and analytics from a perspective of computing, service and management. This book also provides applications of the proposed theory, technologies and methodologies of intelligent analytics to e-SMACS (electronic, social, mobile, analytics, cloud and service) commerce and services, healthcare, the Internet of things, sharing economy, cloud computing, blockchain, and Industry 4.0 in the real world. This book titled “Intelligent Analytics with Multi-industry Applications” is the first book to reveal the cutting-edge theory, technologies, methodologies of intelligent analytics with applications. This is also the first book demonstrating that intelligent analytics is an important enabler for developing cloud computing, 5G, blockchains, digital transformation, business, management, governance and services in multi-industry applications. The proposed approaches will facilitate research, development and applications of intelligent analytics, big data/information/knowledge/wisdom analytics, data science, digital transformation, e-business and web service, service computing, cloud computing and social computing. Aims, Scope and Target Audience This book’s primary aim is to convey the foundations, technologies, thoughts, and methods of intelligent analytics with multi-industry applications to scientists, engineers, educators and university students, business, service and management professionals, policy makers and decision makers and others who have interest in big data, big information, big knowledge and big intelligence and wisdom, intelligent analytics, AI, cloud computing, the Internet of things (IoT), digital transformation, SMACS intelligence and computing, commerce and service as well as data science, information science, and knowledge science. Primary audiences for this book are undergraduate, postgraduate students and variety of professionals in the fields of big data, data science, information science and technology, knowledge technology and engineering, intelligence science, analytics, AI, computing, commerce, business, services, management and government. The variety of readers in the fields of government, consulting, marketing, business and trade as well as the readers from all the social strata can also be benefited from this book to improve understanding of the cutting-edge theory, technologies, methodologies and applications of intelligent analytics with applications. Papers as book chapters of all theoretical and technological approaches, and applications of intelligent analytics are welcome. Submissions that cross multiple disciplines such as management, service, business, artificial intelligence, intelligent systems, data science, optimization, statistics, information systems, decision sciences, and industries to develop theory and provide technologies and applications that could move theory and practice forward in intelligent analytics, are especially encouraged. Topics Topics of contributions to this book include four parts: foundations, technologies, applications and emerging technologies and applications of intelligent analytics as follows. Part I. Foundations of intelligent analytics Topics: fundamental concepts, models/architectures, frameworks/schemes or foundations for developing, operating, evaluating, managing intelligent analytics. The following topics might also include, but not limited to. • Intelligent analytics as a Science and Technology (IAaaST) • Big Data science • Big Data intelligence • Intelligent Analytics for big data, information, knowledge, intelligence and wisdom • Intelligent analytics in business ecosystems • Decision science for intelligent analytics • Computing and foundations of intelligent analytics • New computational models for Big Data • Mathematical fundamentals of intelligent Big Data analytics • Fuzzy logic approach to intelligent analytics • Graph theory for intelligent analytics • ICT fundamentals for analytics • Intelligent visualization techniques for analytics • Statistical modelling for intelligent analytics • Machine learning for intelligent analytics • Optimization techniques for intelligent analytics • Data mining for intelligent analytics • Business models for intelligent analytics • Real-time algorithms for intelligent analytics • Computing thinking for intelligent analytics Part II. Technologies for intelligent analytics Topics: Technologies for developing intelligent analytics might also include the following topics, but not limited to. * Intelligent Analytics as a System (IAaaSy) * Intelligent Analytics as a Service (IAaaSe) * Intelligent Analytics as a Management (IAaaM) * Intelligent Analytics as a Business (IAaaB) * Rule-based systems, * Machine learning, * Multi-agent systems, * Neural networks systems, * Fuzzy logic, * Cased-based reasoning, * Genetic algorithms, * Data mining algorithms, * Intelligent agents, * Intelligent user interfaces * Web technologies, * Intelligent big data/information/knowledge technologies, * Intelligent service technologies, * Social networking technologies, * Intelligent decision technologies, * Intelligent management technologies and business technologies. * Machine-to-machine communication Part III. Multi-industry Applications of intelligent analytics Topics: cases for using foundations and technologies in Part I, II in multi-industry applications and various domains such as digital transformation, blockchain, 5G, SMACS computing, commerce and services, financial services, legal services, healthcare services, educational services, and military services taking into account intelligent diagnostic, descriptive, predictive and prescriptive analytics. The following topics might also include, but not limited to. * Intelligent Analytics as an application * Intelligent analytics with applications * Intelligent analytics-based innovation and entrepreneurship * Intelligent analytics in business ecosystems * Intelligent analytics with public and open data * Intelligent analytics and markets * Intelligent analytics for e-commerce * Intelligent analytics for cloud computing * Intelligent analytics for IoT * Intelligent analytics for blockchain * Intelligent analytics for 5G applications * Intelligent analytics in business decision making * Intelligent analytics in healthcare * Marketing Analytics * Intelligent analytics in banking industry * Intelligent analytics in social networking services * Intelligent analytics for Big Data, information, knowledge and intelligence * Cybersecurity and privacy issues in Intelligent analytics. * Intelligent analytics for management * Intelligent analytics for risk management * Organization analytics Part IV. Emerging technologies and applications for intelligent analytics Topics: Emerging technologies, methodologies, and applications for intelligent analytics. The following topics might also include, but not limited to * Emergent AI-based technologies * Emergent intelligent analytics technologies * Challenges for intelligent big data analytics * Challenges for intelligent big information analytics * Challenges for intelligent big knowledge analytics * Challenges for intelligent analytics research * Challenges for intelligent analytics applications * Challenges for intelligent analytics tools Submission Procedure Please submit a brief summary (abstract) consisting of title and round 150-200 words for the proposed chapter clearly identifying the main objectives of your contribution online by clicking “propose a chapter” at https://www.igi-global.com/publish/call-for-papers/call-details/4539 or to the editor at zhaohao.sun(a)gmail.com by May 30, 2020. Authors of the accepted proposals will be notified and provided with detailed guidelines. Full chapters are to be submitted by June 30, 2020. Submission Format and Evaluation This book will be developed using the eEditorial Discovery™ online submission manager. Therefore, all manuscripts of book chapter must be submitted online using https://www.igi-global.com/submission/submit-chapter/?projectid=8480e8ad-d6… Every book chapter submission should consist of 8,000-12,000 words, and be structured into sections including Abstract, Introduction, background (or related work), main sections, future research directions, conclusion, references. Every book chapter must be submitted in Microsoft® Word, and be typewritten in English in APA style based on “manage source” and “insert citation” function. Every book chapter submission is original. Only ORIGINAL articles will be accepted for publication by IGI-Global. Upon acceptance of your article, you will be required to sign a warranty that your article is original and has NOT been submitted for publication or published elsewhere. All chapter submissions undergo a double-blind peer-review using the eEditorial Discovery™ online submission manager. Conditioned chapters will have an additional opportunity for being improved and evaluated. In the second evaluation, a definitive editorial decision among: accepted or rejected will be reported. All of the accepted chapters must be submitted according to the Editorial publishing format rules timely. Instructions for authors can be downloaded at: http://www.igi-global.com/Files/AuthorEditor/guidelinessubmission.pdf. The final chapters are copy edited/proofed by the authors prior to submission, following the IGI Global chapter formatting and submission guidelines. Important Dates * June 30, 2020: Proposal Submission Deadline * July 05, 2020: Notification of Acceptance * July 30, 2020: Full Chapter Submission * August 25, 2020: Review Results Returned * August 26, 2020: Final Acceptance Notification * September 2, 2020: Final Chapter Submission. * September – November 2020: estimated publishing period. Editor Information Prof. Dr. Zhaohao Sun, Ph.D. Editor of Handbook of Research on Intelligent Analytics with Multi-Industry Applications Research Centre of Big Data Analytics and Intelligent Systems (BAIS) Department of Business Studies PNG University of Technology Morobe, PNG & Federation University Australia zhaohao.sun(a)gmail.com; z.sun(a)federation.edu.au _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] CFP: HICSS-54 Mini-track: Human-Robot Interactions
by Gustaf Neumann 09 Jun '20

09 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] CFP: HICSS-54 Mini-track: Human-Robot Interactions Date: Tue, 9 Jun 2020 12:28:02 +0900 From: Sangseok You <sangyou(a)umich.edu> To: This is the AISWorld List Server <aisworld(a)lists.aisnet.org> Mini-track Title: Human-Robot Interactions General Research Track: Collaboration Systems and Technologies HICSS-54, January 5-8, 2021 Kauai, Hawaii New Deadline: July 15, 2020, 11:59 p.m. HST Journal Fast-track Opportunity: Information Systems Frontiers, Special Issue on Social Robotics Business and Computing Robots are increasingly being adopted in private and public spaces, leading to a proliferation of human‒robot interactions in the home, workplace, and other public settings. Robots in the home are performing household chores and acting as home companions and home health care providers. Robots at work are fulfilling traditional human roles in logistics, transportation, and manufacturing, serving as both co-workers and supervisors. Robots are also being utilized as tour guides, janitors, and security officers in public spaces such as museums and airports. Although these interactions are often collaborative, they are by no means always cooperative. Robot interactions with humans across this array of roles and settings pose interesting questions to scholars in various fields such as information systems, robotics, psychology, and sociology. Interaction with robots is distinct from that with other artificial intelligence (AI)-enabled technologies in that robots have a physical body that allows them to manifest physical actions. People cannot only talk to robots but also touch and be touched by robots. This distinguishes interactions with robots from interactions with disembodied AI agents, such as voice agents like Siri by Apple and Alexa by Amazon. Thus, research on human‒robot interaction can differ significantly from that of human interaction with disembodied AI agents. The mini-track welcomes research papers that explore human‒robot interaction and robot design at any level (i.e. individual, team, organizational, and societal). This mini-track also covers human‒robot interaction as much as possible beyond the notion of "robots as teammates.” Thus, we encourage submissions that examine many facets of interactions in any context (e.g., homes, work, and public services) and role (e.g., companion, co-worker, boss, and adversary). Topics of interest include, but are not limited to, the following: • Promoting cooperative and collaborative interaction with robots • Examining uncooperative and adversarial human interactions with robots • The role of adoption and appropriation in human‒robot interactions • Empirical studies examining the cognitive, psychological, emotional, and social aspects of human‒robot interactions • The impact of haptic feedback and touch on human‒robot interaction • The role of robot attractiveness on human‒robot interaction • Ethics on human‒robot interactions • Social-emotional models of human‒robot interaction • Theoretical frameworks for human‒robot interaction • Case studies of human‒robot interaction • Design implications for robot interactions at home, work and public spaces • Human-oriented practices that promote human‒robot interactions • New methodological approaches to studying human‒robot interactions Important Dates: • Submission Opens: April 20, 2020 • Paper Submission Deadline: July 15, 2020, 11:59 p.m. HST • Notice of Acceptance: August 23, 2020 • Camera-ready Version Deadline: September 22, 2020 Mini-track Co-Chairs: • Sangseok You, HEC Paris, you(a)hec.fr • Lionel Robert, University of Michigan, lprobert(a)umich.edu _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] IEEE ICDM 2020: Call for Tutorials (due Jul 10)
by Gustaf Neumann 09 Jun '20

09 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] IEEE ICDM 2020: Call for Tutorials (due Jul 10) Date: Tue, 9 Jun 2020 01:03:43 -0500 From: Carson Leung (IEEE ICDM 2020) <icdm(a)cs.umanitoba.ca> To: aisworld(a)lists.aisnet.org CC: Ting Bai <baiting(a)bupt.edu.cn> IEEE ICDM 2020: Call for Tutorials (due Jul 10) 20th IEEE International Conference on Data Mining (IEEE ICDM 2020) Sorrento, Italy November 17-20, 2020 http://icdm2020.bigke.org/ The safety and well-being of all conference participants is our priority. We closely monitor the current COVID-19 situation. Depending on the situation, we will have the conference either as planned in Sorrento, Italy or as an online event. In any case, all deadlines and the conference dates remain the same. The Program Chairs and other organizers will post more information as soon as possible. The 20th IEEE International Conference on Data Mining (IEEE ICDM 2020) will host tutorials that focus on new research directions and initiatives. We invite proposals for tutorials from active researchers and experienced tutors. Ideally, a tutorial will cover the state-of-the-art research, development and applications in a specific data mining direction, and stimulate and facilitate future work. Tutorials on interdisciplinary directions, novel and fast growing directions, and significant applications are highly encouraged. We also encourage hands-on-tutorials that allow attendees to learn a particular suite of tools, software and applications that are relevant to the data mining community. Software and tools should preferably be open-sourced and readily available to all participants. We note that a tutorial should not only focus on the presenters' previous work. In principle, the tutorial authors' previous work should not occupy more than 50% of the tutorial coverage. The tutorials are part of the main conference technical program, and are free of charge to the registrants of the conference. The conference will provide the following support for each tutorial: * an honorarium of $500, and * a complimentary registration for one of the tutorial presenters who is not also a presenting author. Tutorial presenters will be responsible for covering all their other expenses. FORMAT OF THE SUBMISSION A tutorial proposal should be formatted into the following sections: * Title * Abstract (up to 150 words) * Rationale: Why do you believe this is an interesting and significant subject for the data mining and machine learning community at large? Is this tutorial or a similar one presented by the same or some authors in some other venues? * Content details: An outline of the tutorial in the form of a bulleted list with references and estimates for the time that will be devoted to each subject (up to 1 page). * Target audience and prerequisites (up to 100 words): From which areas do you expect potential participants to come? What prior knowledge, if any, do you expect from the audience? What will the participants learn? How many participants do you expect? * Relevance and rationale of presenting the tutorial at ICDM 2020 (up to 200 words). * A list of forums and their time, location, and the number of attendees (if available) if the tutorial or a similar/highly related tutorial has been presented by the same author(s) before, and a short description highlighting the similarity/difference between those and the one proposed for ICDM 2020 (up to 100 words for each entry). * A list of tutorials on the similar/highly related topics given by others, and a short description highlighting the differences between yours and theirs (up to 100 words for each entry). * Tutor's short bio and their expertise related to the tutorial (up to 100 words per tutor). * Proposed length of the tutorial: please choose from: 2.5 hours (half-day) and 5 hours (full day). If you are flexible, please indicate in the outline the content that will not be included if a short tutorial is given. * A list of up to 20 most important references that will be covered in the tutorial. * (Optional) URLs of the slides/notes/video of the previous tutorials given by the authors, and any specific audio/video/computer requirements for the tutorial. IMPORTANT DATES * Tutorial proposals due: July 10, 2020 * Notification: August 20, 2020 All deadlines are at 11:59PM Pacific Standard Time. PROPOSAL SUBMISSION Please email your proposals to icdm2020tutorials(a)gmail.com with subject line ICDM2020_<tutorial_name>. TUTORIAL CO-CHAIRS * Diane Cook, Washington State University, USA * Min-Ling Zhang, Southeast University, China PUBLICITY CO-CHAIRS * Ting Bai, Beijing University of Posts and Telecommunications, China * Carson K. Leung, University of Manitoba, Canada * Washio Takashi, Osaka University, Japan _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] 2nd CfP: ICMI 2020 (Virtual) Workshop on Modeling Socio-Emotional and Cognitive Processes from Multimodal Data in the Wild
by Gustaf Neumann 08 Jun '20

08 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] 2nd CfP: ICMI 2020 (Virtual) Workshop on Modeling Socio-Emotional and Cognitive Processes from Multimodal Data in the Wild Date: Mon, 8 Jun 2020 09:32:40 +0000 From: Maike Paetzel <maike.paetzel(a)it.uu.se> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> * 2nd Call for Papers * Workshop on Modeling Socio-Emotional and Cognitive Processes from Multimodal Data in the Wild https://sites.google.com/view/modeling-multimodal-data/home To be held remotely as part of the 22nd ACM International Conference on Multimodal Interaction (ICMI) https://icmi.acm.org/2020/ Submission deadline: 17 August 2020 =========================================================== This workshop is part of the 22nd ACM International Conference on Multimodal Interaction (ICMI) to be held remotely due to COVID-19. Machine Learning (ML) on sensor data of human users in the wild poses numerous technical, theoretical, and ethical challenges. Modeling of intelligent adaptive systems in human-computer or human-robot interaction (HCI, HRI) can be based on a broad spectrum of multimodal signals. For example, eye gaze or EEG may reveal cues about a person's focus of attention, and multimodal data from posture, voice, or facial expressions are frequently examined to predict user engagement, affective responses, or impending breakdown of the interaction. In short, multimodal signal processing is essential for the design of more intelligent, adaptive, or even empathic applications and systems in the wild. However, important issues remain largely unresolved: Starting from low-level processing and integration of noisy data streams, over theoretical pitfalls (e.g., concerning the role of context), up to increasingly pressing ethical questions about what artificial systems and ML can and should do. In this workshop, we will provide a forum for discussion of the state-of-the-art in modeling user states from multimodal signals in the wild. --------------------------------------------------------------------------------------------------------- Invited Speaker: Tony Belpaeme, Ghent University, Belgium --------------------------------------------------------------------------------------------------------- We welcome the presentation of evaluation studies, field research, theoretical and interdisciplinary contributions, novel modeling approaches, and insights on the ethical design of intelligent adaptive systems in the wild, including: * Multimodal modeling of emotions and social action tendencies * Multimodal engagement, attention, stress, memory, and workload estimation * Modeling and response estimation with biological signals (e.g., EEG, EDA, EMG, HR) * Eye tracking and shared attention * Studies bridging multimodal research between the laboratory and the wild * Case studies involving rich and dynamic signal modeling * Cognition-adaptive human-computer interfaces * Experiment design for cognitive processes * Ethical perspectives on current Human-Computer Interaction (HCI), Human-Robot Interaction (HRI) and applications of Artificial Intelligence (AI) * Interdisciplinary collaborations to understand the underpinnings of multimodal data --------------------------------------------------------------------------------------------------------- Submission instructions: Submissions of short (4 pages) and long (8 pages) should follow the ACM conference proceedings format. Links to the templates are available on the ACM website (https://www.acm.org/publications/proceedings-template). Each paper will be sent to at least two expert reviewers and will have one of the organizers assigned as editor. Review will be double-blind. Papers should be submitted via the Microsoft Conference Management Toolkit (CMT; https://cmt3.research.microsoft.com/MSECP2020). Workshop proceedings will be separate from the main conference proceedings. **Workshop papers will be indexed by ACM.** --------------------------------------------------------------------------------------------------------- Important dates: Submission deadline: *17 August 2020* Notifications of acceptance: 7 September 2020 Camera-ready versions 30 September 2020 Workshop date: TBD (either 25 or 29 October 2020) --------------------------------------------------------------------------------------------------------- Organizing Committee: Dennis Küster, University of Bremen, Germany Felix Putze, University of Bremen, Germany Patrícia Alves-Oliveira, University of Washington, USA Maike Paetzel, Uppsala University, Sweden Tanja Schultz, University of Bremen, Germany När du har kontakt med oss på Uppsala universitet med e-post så innebär det att vi behandlar dina personuppgifter. För att läsa mer om hur vi gör det kan du läsa här: http://www.uu.se/om-uu/dataskydd-personuppgifter/ E-mailing Uppsala University means that we will process your personal data. For more information on how this is performed, please read here: http://www.uu.se/en/about-uu/data-protection-policy _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] Special Issue on Blockchain Innovations: Business Opportunities and Management Challenges - Information and Management (I&M) ***Submission Deadline 20 July 2020***
by Gustaf Neumann 08 Jun '20

08 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] Special Issue on Blockchain Innovations: Business Opportunities and Management Challenges - Information and Management (I&M) ***Submission Deadline 20 July 2020*** Date: Mon, 8 Jun 2020 12:21:59 +0000 From: Eric Lim <e.t.lim(a)unsw.edu.au> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> CC: caishun(a)xmu.edu.cn <caishun(a)xmu.edu.cn>, virpi.tuunainen(a)aalto.fi <virpi.tuunainen(a)aalto.fi>, Jie YU (Joseph) <Jie.YU(a)nottingham.edu.cn> ==Special Issue Call for Papers (CFP): Information and Management (I&M)== Blockchain Innovations: Business Opportunities and Management Challenges Links: https://www.journals.elsevier.com/information-and-management/call-for-papers https://www.journals.elsevier.com/information-and-management/call-for-paper… ==Guest Editors== Prof. Shun Cai – Department of Management Science, Xiamen University, China– [caishun(a)xmu.edu.cn] Dr. Jie (Joseph) Yu – Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, China – [jie.yu(a)nottingham.edu.cn] Dr. Eric Lim – School of Information Systems and Technology Management, University of New South Wales, Sydney, Australia - [e.t.lim(a)unsw.edu.au] Prof. Virpi Kristiina Tuunainen – Department of Information and Service Management, Aalto University School of Business, Finland - [virpi.tuunainen(a)aalto.fi] ==Important Dates== - Submission opens: 20 May 2020 - Submission deadline: 20 July 2020 - First round review decision to authors: 20 October 2020 - Revised manuscript due: 20 Jan 2021 - Second round review decision to authors: 20 April 2021 - Final revised manuscript due: 20 May 2021 - Final author notification of acceptance: 20 June 2021 ==Introduction== Blockchain was originally conceptualized by Satoshi Nakamoto in 2008 as the core component to support transactions of cryptocurrencies, such as Bitcoin. Blockchain was meant to serve as an open ledger for all transactions within a network of users to resolve the double-spend problem by combining peer-to-peer technology with public-key cryptography [1-2]. Literally, a Blockchain, as the name suggests, consists of a chain of blocks of information related to e.g. Bitcoin transactions. How these blocks of information could be added to a Blockchain is governed by a stringent set of protocols that dictates how the validity of each block is verified and stored to ensure that the blocks of information cannot be altered or erased without raising any alarms within the network. The program algorithms and the computational infrastructure of creating, inserting, and using the blocks are considered as the Blockchain technology [2]. It has been widely postulated that Blockchain as a technology has the potential to change the way transactions are conducted in business and even in people’s everyday life and redefine how organizations and societies operate. The application of Blockchain technology is not limited to keeping transaction records of cryptocurrencies, but is increasingly being applied to various environments where protecting and managing digital assets and keeping records of them in immutable forms [2-3] is important. While the Blockchain technology has generated enormous impacts in many aspects of business and our lives, research on the Blockchain technology in the Information Systems discipline is still sparse. In particular, little is known about the technical and organizational factors influencing the technical applications and management decisions in adopting this technology and in how this technology could be utilized in addressing different current and emerging issues. Although we share the enthusiasm for its potential to impact how societies function, we are at the same time, wary of the hype that often comes with new technologies. A look back at earlier research on technological innovations indicates that if there were to be a “Blockchain revolution”, there is still a need to overcome many barriers that could be technological, governmental, organizational, and societal in nature. The goal of this special issue in Information and Management is to foster investigations in Blockchain innovations and to provide an opportunity to assess if and how our earlier knowledge on managing other types of information systems can provide the basis for understanding novel technological, organizational and societal settings involving Blockchain technology. This special issue is focused on contributions that draw upon and contribute to the stock of knowledge within the IS discipline, and incorporate management-oriented approaches into the Blockchain research. The special issue welcomes contributions in the following technological and management themes, but is not limited to them: • Changes to business systems, models, applications, and value creation processes enabled or induced by Blockchain. • Evaluation and governance of Blockchain for compliances. • Blockchain and its implications for managing policy, legislation, ethical, moral, and societal norms. • Transparency, anonymity, information and privacy control, and fairness in next-generation Blockchain • Societal issues related to the use of Blockchain • Financial systems and Blockchain • Supply chains and Blockchain • Blockchain based knowledge and innovation management References: [1] Swan M. Blockchain: Blueprint for a New Economy. O’Reilly Media, Inc., 2015. [2] Zhao, J. L., Fan, S. & Yan, J. Overview of business innovations and research opportunities in blockchain and introduction to the special issue, Financial Innovation, 2016, 2:28, 2-7. [3] Iansiti, M. & Lakhani, K. R. The Truth About Blockchain, Harvard Business Review, 2017 January-Febuary, 1-11 ====================================================== Dr. Eric T.K. Lim 林芷光 Senior Lecturer School of Information Systems and Technology Management Partner - Cyber Security Cooperative Research Centre (CRC) Honorary Associate Professor in Information Systems - The University of Nottingham Ningbo China (UNNC) E: e.t.lim(a)unsw.edu.au W: www.unsw.edu.au <http://www.unsw.edu.au/> Web UNSW: https://www.business.unsw.edu.au/our-people/eric-t-k-lim Web UNSW Research: https://research.unsw.edu.au/people/dr-eric-tze-kuan-lim Web UNNC: https://www.nottingham.edu.cn/en/business/people/academic/erictzekuanlim.as… Twitter: https://twitter.com/limerictk LinkedIn: https://au.linkedin.com/in/erictklim Research Interests: FinTech, Blockchain, Cryptocurrencies, Cashless Society, Digital Innovations, Sharing Economy, Big Data, Internet of Things _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] SPECIAL ISSUE ON Group Decision-Making Support Systems for Pandemic Crises - CFP IJDSST
by Gustaf Neumann 08 Jun '20

08 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] SPECIAL ISSUE ON Group Decision-Making Support Systems for Pandemic Crises - CFP IJDSST Date: Mon, 8 Jun 2020 15:46:43 +0000 From: Jose Manuel Mora Tavarez <jose.mora(a)edu.uaa.mx> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> CC: Fen Wang <Fen.Wang(a)cwu.edu>, jorge.marx.gomez(a)uni-oldenburg.de <jorge.marx.gomez(a)uni-oldenburg.de>, Gloria Wren <gwren(a)loyola.edu> SUBMISSION DUE DATE: December 15, 2020 SPECIAL ISSUE ON Group Decision-Making Support Systems for Pandemic Crises International Journal of Decision Support System Technology (IJDSST) https://www.igi-global.com/journal/international-journal-decision-support-s… INTRODUCTION: Group Decision-Making Support Systems (GDMSS) have been widely investigated and used from their origins in the '80s-'90s decades (Huber, 1984; DeSanctis and Gallupe, 1987; Nunamaker et al; 1987; Gray, 1987; Dickson et al., 1993; Fjermestad and Hiltz, 1998), and until nowadays (Gray et al., 2011; Zarate et al., 2013; Mora et al., 2014; Carneiro et al., 2019; Sakka et al., 2019; Ghavami et al., 2019; Aghazadeh and Padoano, 2020). GDMSS have been proposed for supporting critical group decisions demanded from high- social and economic impact events (Belardo and Harrald, 1992; Jefferson and Harrald, 2007; Levy and Taji, 2007; Xu et al., 2015). Furthermore, GDMSS have also supported the group decisions required in the healthcare sector in the last 30 years ago (Hatcher, 1990; Liu et al., 2018). Nowadays, the worldwide COVID-19 crisis with the highest impacts on public health, economic and social dimensions have challenged (Liu et al., 2020) the group decision-making process and GDMSS that can provide effective, efficient and systemic-view support including the impacted health, economic, and social dimensions among other relevant ones (Rehfuess et al., 2019; Portela et al., 2019). Furthermore, relevant studies have reported critical misconceptions on public governmental decisions that occurred due to the utilization of a single pandemic modeling perspective (Ionnadis, 2020), which calls for more systemically designed GDMSS (Luke and Stamatakis, 2012; Araz, 2013). Consequently, whereas there is a vast availability of GDMSS, the COVID-19 crisis has revealed that updated GDMSS concepts, frameworks, methods and technologies (Hevner et al., 2004; Arnott and Pervan, 2014), from a systemic perspective, are required to address effectively, efficiently, and ethically a group decision-making process conducted by policymakers in the context of a pandemic crisis (WHO, 2009; Moghadas et al., 2009; Moberg et al., 2018; Shearer et al., 2020; Squazzoni et al., 2020; Aghazadeh and Padoano, 2020). REFERENCES Aghazadeh, A., and Padoano, E. (2020). A Literature Review of the Concepts of Resilience and Sustainability in Group Decision-Making. Sustainability, 12(7), 2602. Araz, O. M. (2013). Integrating complex system dynamics of pandemic influenza with a multi-criteria decision making model for evaluating public health strategies. Journal of Systems Science and Systems Engineering, 22(3), 319-339. Arnott, D., and Pervan, G. (2014). A Critical Analysis of Decision Support Systems Research Revisited: The Rise of Design Science. Journal of Information Technology, 29(4), 269-293. Belardo, S., and Harrald, J. (1992). A framework for the application of group decision support systems to the problem of planning for catastrophic events. IEEE transactions on Engineering Management, 39(4), 400-411. Carneiro, J., Saraiva, P., Conceicao, L., Santos, R., Marreiros, G., and Novais, P. (2019). Predicting satisfaction: perceived decision quality by decision-makers in web-based group decision support systems. Neurocomputing, 338, 399-417. DeSanctis, G., and Gallupe, R. B. (1987). A foundation for the study of group decision support systems. Management Science, 33(5), 589-609. Dickson, G. W., Partridge, J. E. L., and Robinson, L. H. (1993). Exploring modes of facilitative support for GDSS technology. MIS Quarterly, 173-194. Fjermestad, J, and Hiltz, S. R. (1998). An assessment of group support systems experimental research: methodology and results. Journal of Management Information Systems, 15(3), 7-149. Ghavami, S. M., Maleki, J., and Arentze, T. (2019). A multi-agent assisted approach for spatial Group Decision Support Systems: A case study of disaster management practice. International Journal of Disaster Risk Reduction, 38, 101223. Gray, P. (1987). Group decision support systems. Decision support systems, 3(3), 233-242. Gray, P., Johansen, B., Nunamaker, J., Rodman, J., and Wagner, G. R. (2011). GDSS past, present, and future. In Decision support (pp. 1-24). Springer, New York, NY. Hatcher, M. (1990). Uniqueness of group decision support systems (GDSS) in medical and health applications. Journal of Medical Systems, 14(6), 351-364. Hevner, A. R., March, S. T., Park, J., and Ram, S. (2004). Design science in information systems research. MIS Quarterly, 75-105. Huber, G. P. (1984). Issues in the design of group decision support systems. MIS Quarterly, 8(3), 195-204. Ioannidis, J.P. (2020).Coronavirus disease 2019 - the harms of exaggerated information and non-evidence-based measures. European Journal of Clinical Investigation, 50(4), e13222. Jefferson, T. I., and Harrald, J. R. (2007). Collaborative technology: providing agility in response to extreme events. International Journal of Electronic Governance, 1(1), 79-93. Levy, J. K., and Taji, K. (2007). Group decision support for hazards planning and emergency management: A Group Analytic Network Process (GANP) approach. Mathematical and Computer Modelling, 46(7-8), 906-917. Liu, H. C., You, X. Y., Tsung, F., and Ji, P. (2018). An improved approach for failure mode and effect analysis involving large group of experts: an application to the healthcare field. Quality Engineering, 30(4), 762-775. Liu, P., Zhong, X., and Yu, S. (2020). Striking a balance between science and politics: understanding the risk-based policy-making process during the outbreak of COVID-19 epidemic in China. Journal of Chinese Governance, 1-15. Luke, D. A., and Stamatakis, K. A. (2012). Systems science methods in public health: dynamics, networks, and agents. Annual Review of Public Health, 33, 357-376. Moberg, J., Oxman, A. D., Rosenbaum, S., Schünemann, H. J., Guyatt, G., Flottorp, S., ... and Alonso-Coello, P. (2018). The GRADE Evidence to Decision (EtD) framework for health system and public health decisions. Health Research Policy and Systems, 16(1), 45. Moghadas, S. M., Pizzi, N. J., Wu, J., and Yan, P. (2009). Managing public health crises: the role of models in pandemic preparedness. Influenza and Other Respiratory Viruses, 3(2), 75-79. Mora, M., Phillips-Wren, G., and Wang, F. (2014). An integrative evaluation framework for determining the value of group decision support systems. Engineering Management Journal, 26(2), 24-38. Nunamaker Jr, J. F., Applegate, L. M., and Konsynski, B. R. (1987). Facilitating group creativity: Experience with a group decision support system. Journal of Management Information Systems, 3(4), 5-19. Portela, A., Tunçalp, Ö., and Norris, S. L. (2019). Taking a complexity perspective when developing public health guidelines. Bulletin of the World Health Organization, 97(4), 247. Rehfuess, E. A., Stratil, J. M., Scheel, I. B., Portela, A., Norris, S. L., and Baltussen, R. (2019). The WHO-INTEGRATE evidence to decision framework version 1.0: integrating WHO norms and values and a complexity perspective. BMJ Global Health, 4(Suppl 1), e000844. Sakka, A., Bosetti, G., Grigera, J., Camilleri, G., Fernández, A., Zaraté, P., ... and Sautot, L. (2019). UX Challenges in GDSS: An Experience Report. In International Conference on Group Decision and Negotiation (pp. 67-79). Springer, Cham. Shearer, F. M., Moss, R., McVernon, J., Ross, J. V., and McCaw, J. M. (2020). Infectious disease pandemic planning and response: Incorporating decision analysis. PLoS Medicine, 17(1). Squazzoni, F., Polhill, J. G., Edmonds, B., Ahrweiler, P., Antosz, P., Scholz, G., ... and Gilbert, N. (2020). Computational models that matter during a global pandemic outbreak: A call to action. Journal of Artificial Societies and Social Simulation, 23(2). WHO (2009). WHO Guide to identifying the Economic Consequences of Disease and Injury. Department of Health Systems Financing Health Systems and Services, World Health Organization, Geneva, Switzerland. Xu, X. H., Du, Z. J., and Chen, X. H. (2015). Consensus model for multi-criteria large-group emergency decision making considering non-cooperative behaviors and minority opinions. Decision Support Systems, 79, 150-160. Zaraté, P., Konate, J. and Camilleri, G. (2013) Collaborative Decision Making Tools: A Comparative Study Based on Functionalities. (2013) In: 13th International Conference Group Decision and Negotiation (GDN 2013), 17-21 June, Stockholm, Sweden. OBJECTIVE OF THE SPECIAL ISSUE: This special issue pursues to advance group decision-making methods and tools to meet severe health, economic, and social challenges that emerged from the Covid-19 pandemic crisis in this decade. High-quality conceptual and empirical research papers are invited from the international interdisciplinary scientific community interested in helping to provide better group decision-making support to policymakers in the context of a pandemic crisis. RECOMMENDED TOPICS: Topics to be addressed in this special issue include (but are not limited to) the following ones: • Conceptual analysis of the WHO-INTEGRATE Evidence to Decision Framework with a group decision-making perspective. • Conceptual group decision-making methods derived from the WHO-INTEGRATE Evidence to Decision Framework. • Empirical designs and evaluations of GDMSS tools derived from the WHO-INTEGRATE Evidence to Decision Framework. • Systems science methods applied in group decision-making methods and tools in the context of pandemic crisis. • Descriptive Analytics applied in group decision-making methods and tools in the context of a pandemic crisis. • Predictive Analytics applied in group decision-making methods and tools in the context of a pandemic crisis. • Prescriptive Analytics applied in group decision-making methods and tools in the context of a pandemic crisis. • Efficient, effective, and usable MADM methods for enhancing GDMSS. • System Science methods (System Dynamics, Agent-based Simulation, and Network Analysis) for enhancing GDMSS. SUBMISSION PROCEDURE: Researchers and practitioners are invited to submit papers for this special theme issue on Group Decision-Making Support Systems for Pandemic Crises on or before December 15, 2020. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL'S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations. PUBLICATION SCHEDULE: · first submission deadline - December 15, 2020 · first editorial decision deadline - February 15, 2021 · second version submission deadline (conditioned papers) - March 15, 2021 · definitive editorial decision deadline - April 15, 2021 · camera-ready paper submission deadline - May 15, 2021 All inquires and paper submission should be directed to the attention of: Prof. Manuel Mora – lead guest editor International Journal of Decision Support Technology (IJDSST) E-mail: jose.mora(a)edu.uaa.mx<mailto:jose.mora@edu.uaa.mx> Guest Editors: Prof. Manuel Mora, Autonomous University of Aguascalientes, Mexico Prof. Gloria Phillips-Wren, Loyola University Maryland, USA Prof. Jorge Marx Gomez, University of Oldenburg, Germany Prof. Fen Wang, Central Washington University, USA ------------------------------------------------------------ Prof. Dr. José Manuel Mora Tavarez Depto. de Sistemas de Información Centro de Ciencias Básicas Universidad Autónoma de Aguascalientes Ave. Universidad 940 Aguascalientes, AGS. México 20131 Email: jose.mora(a)edu.uaa.mx <https://www.researchgate.net/profile/Manuel_Mora> ResearchGate Weblink<https://www.researchgate.net/profile/Manuel_Mora> <https://scholar.google.com.mx/citations?user=97rTgbkAAAAJ&hl=en&oi=sra> Scholar Google Weblink<https://scholar.google.com.mx/citations?user=97rTgbkAAAAJ&hl=en&oi=sra> Linkedin Weblink<https://www.linkedin.com/in/manuel-mora-engd-37b03a1/> SCOPUS Weblink<https://www.scopus.com/authid/detail.uri?authorId=25823339800> ------------------------------------------------------------ _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [AISWorld] CFP (WiMob 2020), the 16th International Conference on Wireless and Mobile Computing, Networking and Communications.
by Gustaf Neumann 08 Jun '20

08 Jun '20

-------- Forwarded Message -------- Subject: [AISWorld] CFP (WiMob 2020), the 16th International Conference on Wireless and Mobile Computing, Networking and Communications. Date: Mon, 8 Jun 2020 18:02:46 +0000 From: Adel Sharar Aldalbahi <aaldalbahi(a)kfu.edu.sa> To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org> [Apologies if you receive multiple copies of this message] ========================================================== CALL FOR PAPERS Submissions Deadline: June 15, 2020 >> Extended versions of selected papers will be considered for publication in special issues of indexed journals. ****************************************************************** IEEE 16th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2020), October 12-14, 2020 in Thessaloniki, Greece. http://wimob.org/wimob2020/ ****************************************************************** ** IEEE Communication Society sponsorship ** ------------------------------------------------------------- Note: WiMob 2020 will be held physically in Thessaloniki as scheduled from 12 to 14, October 2020 with the guarantees of hygienic conditions. The organizing committee is closely monitoring the development of the COVID-19 situation. In case of travel restrictions that prohibit physical appearance, video presentation will be accepted as an alternative of presentation. For now, it is too early; but if the situation becomes worse, we can also decide to have a virtual conference (in such case, the registration fees will be very lower). The WiMob conference is an international forum for the exchange of experience and knowledge among researchers and developers concerned with wireless and mobile technology. For thirteen years, the International WiMob conference has provided unique opportunities for researchers to interact, share new results, show live demonstrations, and discuss emerging directions in - Wireless Communication, - Wireless Networking, Mobility and Nomadicity, - Ubiquitous Computing, Services and Applications, - Green and sustainable communications and network computing and - Security on Wireless and mobile Networks. WiMob 2020 is soliciting high quality technical papers addressing research challenges in the areas of wireless communications, wireless networking, mobility, nomadicity, ubiquitous computing, services and applications. Papers should present original work validated via analysis, simulation or experimentation. Practical experiences and Testbed trials also are welcome. WiMob 2020 will host FIVE parallel symposia: 1. Wireless Communications (WC) 2. Wireless Networking, Mobility and Nomadicity (WNMN) 3. Ubiquitous Computing, Services and Applications (UCSA) 4. Green and Sustainable Communications and Network computing (GSCN) 5. Security on Wireless and Mobile Networks (SWMN) For the detailed topics, you can refer to WiMob 2020 web site. Important Dates - Submissions Date: June 15, 2020 - Notifications Date: July 20, 2020 - Camera ready Date: September 10, 2020 - Registrations for authors: September 20, 2020 INSTRUCTIONS FOR PAPER SUBMISSION Authors are required to submit fully formatted, original papers (PDF), with graphs, images, and other special areas arranged as intended for the final publication. Papers should be written in English conforming to the IEEE standard conference format (two-column, 10 pt font, etc., including figures, tables, and references). The review submissions are limited to six pages, with two additional pages for final papers (additional charges may apply for additional pages). Conference content will be submitted for inclusion into IEEE Xplore as well as other Abstracting and Indexing (A&I) databases. Each accepted paper must be presented at the conference by one of the co-authors or a third party, otherwise it will not be indexed and archived through IEEE Xplore. Only timely submissions through EDAS will be accepted. For more details, please visit the WiMob'2020 official website (http://wimob.org/wimob2020/) and Facebook page for WiMob 2020: https://www.facebook.com/WiMob-342284676621021/ ACCEPTED PAPERS All accepted papers will be published in the conference proceedings and presented for inclusion in IEEE Xplore Digital Library. Assistant Professor Vice Dean for Academic affairs KFU College of Engineering Electrical Engineering Dept Hofuf Saudi Arabia Office +966135899<tel:+966135899589>363 Cell +9665<tel:+966553822022>43388552 _______________________________________________ AISWorld mailing list AISWorld(a)lists.aisnet.org

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Fwd: [computational.science] CFP: Resilience@Euro-Par 2020 - Papers due June 12 (REMINDER)
by Gustaf Neumann 08 Jun '20

08 Jun '20

-------- Forwarded Message -------- Subject: [computational.science] CFP: Resilience@Euro-Par 2020 - Papers due June 12 (REMINDER) Date: Mon, 8 Jun 2020 12:24:36 -0400 (EDT) From: Thomas Naughton via computational.science <computational.science(a)lists.iccsa.org> Reply-To: Thomas Naughton <naughtont(a)ornl.gov> To: computational.science(a)lists.iccsa.org We apologize if you receive multiple copies of this call for papers. -------------------------------------------------------------------------------- 13th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids <https://www.csm.ornl.gov/srt/conferences/Resilience/2020> in conjunction with the 26th International European Conference on Parallel and Distributed Computing (Euro-Par), Warsaw, Poland August 24 - 28, 2020 <http://2020.euro-par.org> 2020 Workshop Format: Due to the exceptional situation of COVID-19, this year Euro-Par and its workshops will be organized as an all-virtual event. This includes the main conference and workshops. The accepted workshop papers must be presented by one of the authors in order to be included in the proceedings. There will be a single minimal registration fee for each accepted paper in order to cover expenses associated with organization and proceedings publication. Only one author per paper needs to register (150 euros). Lastly, the preferred presentation format for the workshop will be via a streaming presentation, with slides and pre-recorded video presentations used in exceptional situations. Overview: Resilience is a critical challenge as high performance computing (HPC) systems continue to increase component counts, individual component reliability decreases (such as due to shrinking process technology and near-threshold voltage (NTV) operation), hardware complexity increases (such as due to heterogeneous computing) and software complexity increases (such as due to complex data- and workflows, real-time requirements and integration of artificial intelligence (AI) technologies with traditional applications). Correctness and execution efficiency, in spite of faults, errors, and failures, is essential to ensure the success of the HPC systems, cluster computing environments, Grid computing infrastructures, and Cloud computing services. The impact of faults, errors, and failures in such HPC systems can range from financial losses due to system downtime (sometimes several tens-of-thousands of Dollars per lost system-hour), to financial losses due to unnecessary overprovision (acquisition and operating costs), to financial losses and legal liabilities due to erroneous or delayed output. The emergence of AI technology opens up new possibilities, but also new problems. Using AI technology for operational intelligence that enables resilience in HPC systems and centers is a complex control problem, while designing resilient AI technology for HPC applications is a difficult algorithmic problem. Resilience for HPC systems encompasses a wide spectrum of fundamental and applied research and development, including theoretical foundations, error/failure and anomaly detection, monitoring and control, end-to-end data integrity, enabling infrastructure, and resilient algorithms. This workshop brings together experts in the community to further research and development in HPC resilience and to facilitate exchanges across the computational paradigms of extreme-scale HPC, cluster computing, Grid computing, and Cloud computing. Submission Guidelines: Authors are invited to submit papers electronically in English in PDF format. Submitted manuscripts should be structured as technical papers and BETWEEN 10 AND 12 PAGES, including figures, tables and references, using Springer's Lecture Notes in Computer Science (LNCS) format at <http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>. Papers with less than 10 or more than 12 pages will not be accepted due to publisher guidelines. Submissions should include abstract, key words and the e-mail address of the corresponding author. Papers not conforming to these guidelines may be returned without review. All manuscripts will be reviewed and will be judged on correctness, originality, technical strength, significance, quality of presentation, and interest and relevance to the conference attendees. Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date or not appropriately structured may also not be considered. The proceedings will be published in Springer's LNCS as post-conference proceedings. At least one author of an accepted paper must register for and attend the workshop for inclusion in the proceedings. Authors may contact the workshop program chairs for more information. Important websites: - Resilience 2020 Website: <https://www.csm.ornl.gov/srt/conferences/Resilience/2020> - Resilience 2020 Submissions: <https://easychair.org/conferences/?conf=europar2020workshop> - Euro-Par 2020 website: <http://2020.euro-par.org> Topics of interest include, but are not limited to: - Theoretical foundations for resilience: - Metrics and measurement - Statistics and optimization - Simulation and emulation - Formal methods - Efficiency modeling and uncertainty quantification - Experience reports - Error/failure/anomaly detection and reliability/dependability modeling: - Statistical analyses - Machine learning and artificial intelligence - Digital twins - Data collection and aggregation - Information visualization - Monitoring and control for resilience: - Center, system and application monitoring and control - Reliability, availability, serviceability and performability - Tunable fidelity and quality of service - Automated response and recovery - Operational intelligence to enable resilience - End-to-end integrity: - Fault tolerant design of centers, systems and applications - Forward migration and verification - Degraded operation - Error propagation, failure cascades, and error/failure containment - Testing and evaluation, including fault/error/failure injection - Enabling infrastructure for resilience: - Reliability, availability, serviceability systems - System software and middleware - Resilience extensions for programming models - Tools and frameworks - Support for resilience in heterogeneous architectures - Resilient algorithms: - Algorithmic detection and correction - Resilient solvers and algorithm-based fault tolerance - Fault tolerant numerical methods - Robust iterative algorithms - Resilient artificial intelligence Important Dates: - Workshop papers due: June 12, 2020 (extended) - Workshop author notification: July 21, 2020 - Workshop author registration: TBA - Workshop paper (for informal workshop proceedings): July 21, 2020 - Workshop date: August 24 or 25, 2020 - Workshop camera-ready papers: September 11, 2020 (after the conference) General Co-Chairs: - Stephen L. Scott Tennessee Tech University, USA scottsl(a)ornl.gov - Christian Engelmann Oak Ridge National Laboratory , USA engelmannc(a)ornl.gov Program Co-Chairs: - Ferrol Aderholdt Middle Tennessee State University, USA ferrol.aderholdt(a)mtsu.edu - Thomas Naughton Oak Ridge National Laboratory , USA naughtont(a)ornl.gov Workshop Chair Emeritus: - Chokchai (Box) Leangsuksun Louisiana Tech University, USA box(a)latech.edu Program Committee: - Wesley Bland, Intel Corporation, USA - Hans-Joachim Bungartz, Technical University of Munich, Germany - Marc Casas, Barcelona Supercomputer Center, Spain - Zizhong Chen, University of California at Riverside, USA - Robert Clay, Sandia National Laboratories, USA - Nathan DeBardeleben, Los Alamos National Laboratory, USA - James Elliott, Sandia National Laboratories, USA - Kurt Ferreira, Sandia National Laboratories, USA - Saurabh Hukerikar, NVIDIA, USA - Ignacio Laguna, Lawrence Livermore National Laboratory, USA - Scott Levy, Sandia National Laboratories, USA - Rolf Riesen, Intel Corporation, USA - Yves Robert, ENS Lyon, France - Thomas Ropars, Universite Grenoble Alpes, France - Martin Schulz, Technical University of Munich, Germany - Keita Teranishi, Sandia National Laboratories, USA _________________________________________________________________________ Thomas Naughton naughtont(a)ornl.gov Research Associate (865) 576-4184

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