-------- Forwarded Message --------
Subject: [AISWorld] Call for papers: International Journal of Art,
Culture and Design Technologies
Date: Wed, 30 Jun 2021 14:00:34 -0500
From: Jeff Morris <morris(a)tamu.edu>
To: aisworld(a)lists.aisnet.org
Hello all,
I hope you will keep our journal in mind for any relevant work you are
doing. The following is our current call for papers. Apologies for
cross-posting.
Best,
JM
—————————————————————————
Call for papers: International Journal of Art, Culture and Design
Technologies
Deadline for next issue: September 1, 2021.
The mission of the International Journal of Art, Culture and Design
Technologies is to promote interdisciplinary research concerning the
influence of technological innovation on creativity and other human issues.
Our journal bridges the humanities, artistic, scientific, and technical
disciplines. It is a nexus for information exchange among academia and
industry addressing theory, criticism, and practice.
Topics to be discussed in this journal include (but are not limited to) the
following:
- Aesthetics of technology
- Artificial intelligence
- Computational creativity
- Cybernetics
- Design and professional applications
- Digital humanities, identity, and heritage
- Human issues and cultural impacts of technology
- Human-computer interaction
- Information visualization and sonification
- Internet culture
- Music and sound art, new media art, net art, performance art, and visual
arts
- Psychology and cognition
- Social and ethical issues
- Technology in arts and humanities education
- Video games
- Virtual, augmented, and mixed realities
- Visual, aural, and other modes of communication or expression
SUBMIT ONLINE AT
https://www.igi-global.com/calls-for-papers/international-journal-art-cultu…
Only original, previously unpublished articles will be considered.
Interested authors must consult the journal’s guidelines for manuscript
submissions at
http://www.igi-global.com/publish/contributor-resources/before-you-write/
prior to submission. All submissions will be subjected to double-blind peer
review by at least three members of the IJACDT Editorial Review Board.
Final decision regarding acceptance, revision, or rejection will be based
on these reviews. Only electronic submissions will be accepted.
All inquiries should be directed to the attention of:
Editor-in-Chief Jeffrey M. Morris at morris(a)tamu.edu
Jeff Morris, D. Mus. Arts in Composition | Assoc. Prof.
Department of Performance Studies
morris(a)tamu.edu
4240 TAMU | College Station, TX 77843-4240
Tel. 979.845.6751 | Fax 979.862.2666 | perf.tamu.edu
Liberal Arts—Arts & Humanities Building | Room 229
Texas A&M University
_______________________________________________
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-------- Forwarded Message --------
Subject: [AISWorld] CFP: Blockchain Technology and Applications @ EMCIS
2021
Date: Wed, 30 Jun 2021 08:46:39 +0100
From: Paulo Rupino Cunha <rupino(a)dei.uc.pt>
To: ISWorld list <aisworld(a)lists.aisnet.org>
Dear colleagues,
Please consider submitting to the EMCIS 2021 track on Blockchain
Technology and Applications.
Submission Deadline: 31 Jul, 2021
Conference proceedings will be published in a Springer Lecture Notes in
Business Information Processing volume. Indexed by ISI Proceedings,
DBLP, EI and Scopus.
Substantially extended versions of some EMCIS papers may be selected for
publication in academic journals.
** Call for Papers **
Blockchain Technology and Applications
A Blockchain is a decentralized digital ledger that saves transactions
on thousands of computers around the globe. Blockchain, the technology
underlying the infamous Bitcoin cryptocurrency, has been receiving
considerable attention in recent years, as new use cases in the public
and private sector are identified. What started as a mechanism to avoid
the double spending problem with digital money is being experimented in
scenarios where a trusted third party (e.g. a notary or a bank) was
normally required. Using this technology, transactions are securely
registered in a ledger distributed across a network of peers that
validate the entries using a consensus mechanism. The high importance of
blockchain has attracted the attention of organizations in different
sectors and has resulted in the development of innovative organizations
and new job positions. Currently, few if any could predict the full
extent of the disruptive innovations that would emerge fostered by
Blockchain technology. This track seeks to serve as an annual venue that
will enable the discussion on the trends, challenges and developments of
Blockchain technology. In doing so, it aims to speed up the study and
accelerate the adoption of this technology. Topics of interest include
the following but are not limited to:
• Blockchain case studies
• Blockchain infrastructure
• Blockchain and banking
• Blockchain and peer-to-peer transfers
• Blockchain and digital currencies
• Blockchain and Internet of Things
• Blockchain and markets
• Blockchain and marketplaces
• Blockchain and healthcare
• Blockchain applications
• Blockchain and e-government
• Blockchain and Banking sector
• Blockchain interoperability and scalability
• Blockchain and regulatory frameworks
• Barriers to blockchain adoption
• Decentralized Finance
• Non-Fungible Tokens (NFTs)
• Central Bank Digital Currency (CBDC)
• Fintech applications
• Smart contracts
• Innovation in blockchain
• Privacy, Security and Identity in blockchain
For more information, please visit: http://emcis.eu
Track co-Chairs:
Paulo Rupino da Cunha, Coimbra University, Portugal
Email: rupino(a)dei.uc.pt <mailto:rupino@dei.uc.pt>
Klitos Christodoulou, University of Nicosia, Cyprus
Email: Christodoulou.kl(a)unic.ac.cy <mailto:Christodoulou.kl@unic.ac.cy>
Elias Iosif, University of Nicosia, Cyprus
Email: Iosif.e(a)unic.ac.cy <mailto:Iosif.e@unic.ac.cy>
Paulo Rupino da Cunha
Professor Associado com Agregação
Associate Professor w/ Habilitation
Universidade de Coimbra • Departamento de Engenharia Informática
Pólo II | 3030-290 COIMBRA • PORTUGAL Tel.: Phone +351 239 790 050
E-mail: rupino(a)dei.uc.pt <mailto:rupino@dei.uc.pt>
eden.dei.uc.pt/~rupino <http://eden.dei.uc.pt/~rupino>
_______________________________________________
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-------- Forwarded Message --------
Subject: [AISWorld] ISeB JCR journal - CFP: SI on Agile, Lightweight
and Lean IT Service Management Approaches for Business Agility
Date: Tue, 29 Jun 2021 16:48:24 +0000
From: Jose Manuel Mora Tavarez <jose.mora(a)edu.uaa.mx>
To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org>
Information Systems and e-Business Management (JCR indexed journal)
Call for Papers: Special Issue on Agile, Lightweight and Lean IT Service
Management Approaches for Business Agility
Deadline for submissions: 30 September 2021
Special Issue Guest Editors:
• Prof. Manuel Mora, Autonomous University of Aguascalientes, Mexico
• Prof. Jorge Marx Gómez, University of Oldenburg, Germany
• Assoc. Prof. Olayele Adelakun, DePaul University, USA
• Prof. Fen Wang, Central Washington University, USA
Full information about this CFP at:
https://www.springer.com/journal/10257/updates/19311184
------------------------------------------------------------
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>
------------------------------------------------------------
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-------- Forwarded Message --------
Subject: [AISWorld] [IEEE ICHMS 2021] CfP: Intl. Summer School on
Situation Awareness <> CfP: Late Braking Papers, PhD & Demo Track - July
19th
Date: Tue, 29 Jun 2021 21:47:25 +0200
From: Andreas Nuernberger <andreas.nuernberger(a)ovgu.de>
To: aisworld(a)lists.aisnet.org
* Call for Participation *
**** Please forward this e-mail to potentially interested
students/researchers ****
International Summer School on Situation Awareness in Cognitive
Technologies 2021
Theory and Application
September 6-11th, 2021 at Magdeburg, Germany: http://isact.cogsy.de/
In conjunction with ICHMS 2021:
2nd IEEE International Conference on Human-Machine Systems (ICHMS 2021)
Magdeburg, Germany, 8-10 September 2021 (Hybrid Event)
Late Braking Papers, PhD & Demo Track open until July 19th:
https://www.ichms2021.de
*** Scope of the Summer School: ***
We are pleased to announce that the International Summer School on
Situation Awareness in Cognitive Technologies (ISACT 2021) will be held
from September 6 to 11, 2021 in Magdeburg, Germany, in conjunction with
the IEEE International Conference on Human-Machine Systems (ICHMS 2021).
Situation Awareness in Cognitive Technologies is a trending research
direction that gained a lot of interest from the industry in recent
years. Therefore, the summer school aims to present the fundamental
aspects of situation awareness in cognitive technologies which can be
discussed in an interdisciplinary context. There are a couple of aspects
to consider: Situation Awareness, Cognitive Technologies, Human-Computer
Interaction (HCI) and Explainable AI (XAI). Especially the HCI context
provides a link between theory and application which receives special
attention in this summer school along with the recent trends in
Explainable AI. To make this school an interactive learning experience,
we would encourage the participants to share their research
presentations (posters) related to the above-mentioned topics.
This year’s edition intends to bring together academia and industry to
provide a large practical perspective to undergraduate and graduate
(including early-stage PhD) students, as well as to young industry
personnel. Attendees will be able to extend their knowledge in both
theoretical and practical aspects of:
- Situation Awareness
- Cognitive Technologies
- Brain-Computer Interaction
- Human-Computer Interaction
- Explainable AI
The International Summer School on Situation Awareness in Cognitive
Technologies is a great opportunity to learn about new technologies,
meet fellow students/employees, discuss ideas with experts, participate
in an international conference and simply have a splendid time in the
city of Otto von Guericke!
*** Important Dates: ***
Application Deadline: July 19th, 2021
Notification of Acceptance: July 28th, 2021
Summer School Date: September 6-11th, 2021
*** Submissions: ***
The application deadline is July 19th, 2021. Please fill out the
application form at isact.cogsy.de/apply and upload your CV to
isact.cogsy.de/cv. Moreover, we also accept applications for travel
grants. The travel grant intends to cover the travelling costs to the
summer school's venue. Therefore, the application must provide an
additional list of estimated travel costs to Magdeburg. For further
information please refer to isact.cogsy.de.
We invite applicants to submit an accompanying paper in the PhD Track of
ICHMS 2021 (https://www.ichms2021.de). Activities of both events will be
synchronized so that participation at selected sessions is possible.
_______________________________________________
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-------- Forwarded Message --------
Subject: [wkwi] CfP Special Issue "Trust in AI for electronic markets"
Date: Tue, 29 Jun 2021 10:48:18 +0200
From: editors(a)electronicmarkets.org
Reply-To: editors(a)electronicmarkets.org
To: wkwi(a)listserv.dfn.de
.
CfP Special Issue "Trust in AI for electronic markets"
<https://ocis.aom.org/ocis/communities/community-home/digestviewer/viewthrea…>
--- Apologies for cross-postings---
Call for Papers: "*Trust in AI for electronic markets*" in "Electronic
Markets - The International Journal on Networked Business"
Submission deadline: December, 15, 2021
*Guest Editors*
Wolfgang Maass, Saarland University and German Research Center for
Artificial Intelligence (DFKI), Germany, wolfgang.maass(at)dfki.de
Roman Lukyanenko, HEC Montréal, Canada, roman.lukyanenko(at)hec.ca
Veda C. Storey, Georgia State University, USA, vstorey(at)gsu.edu
*Theme*
Electronic markets for trading physical, as well as digital, goods offer
a wide variety of services based on Artificial Intelligence
technologies, as smart market services. Smart market services generate
recommendations and predictions using Artificial Intelligence (AI)
technologies on data available and accessible in electronic markets. For
instance, financial high-speed trading is only feasible by smart market
services that autonomously execute transactions according to market
signals based on AI models trained with big data. Electronic
marketplaces, including Amazon and Alibaba, are using AI technologies to
provide smart services to consumers, optimize logistics, analyze
consumer behavior, and derive innovative product and service designs.
Some business leaders even consider there to be major threats to society
from sophisticated AI solutions, while using AI extensively for their
own business. Because AI systems elude human understanding and
scrutinization, trust in AI is crucial for the success of smart market
services, as well as other AI or machine learning-based systems .
Gaining trust in AI begins with transparency in the reviews of (a) data
so that biases and gaps in knowledge of a domain are controlled, (b) AI
models and objective functions, (c) model performance and (d) results
generated by AI models for decision making. Trust becomes an important
factor for overcoming uncertainty on AI-based recommendations in general
and in electronic markets in particular.
The quality of smart market services depends on shared understanding and
conceptual models of data used for training AI models; data quality; the
selection and training of appropriate models; and the embedding of
models into smart market services. Providers of smart market services
are required to build trust relationships with business and end
customers based on limited possibilities for opening the "black boxes"
of Artificial Intelligence systems due to increased complexity of
machine learning models. Empirical studies on trust in AI indicate
heterogenous results.
Companies and end-users appreciate benefits and opportunities provided
by smart market services. At the same time, concerns are raised with
respect to privacy issues and biases of data, models and algorithms.
Overly optimistic customers might become disappointed if smart market
services do not deliver as expected. Proof of privacy leaks and biases
might reinforce prejudices. Both may lead to decrease of trust in AI.
Challenging research questions are to identify which methods, indicators
and experiences have increasing effects on trust in AI. For instance,
explainable AI is a technical means for opening "black boxes" of AI
systems, generally, and smart market services, specifically.
This special issue seeks contributions on trust in Artificial
Intelligence in the context of electronic markets. Contributions that
help to understand challenges from an economic, legal or technical
perspective are invited.
*Central issues and topics*
Possible topics of submissions include, but are not limited to:
* Trust behavior and AI
* Mental models, conceptual models and AI models
* Psychological and sociological factors for trust in AI
* Human-centric design of smart market services
* Explainable AI for smart market services
* Threats for trust in AI
* Frameworks for smart markets
* Business and legal aspects influencing trust in AI
* Relationships between trust and Business models with smart market
services
* Transparency of data, AI models and recommendations
* Case studies on building trust in AI
*Submission*:
Electronic Markets is a Social Science Citation Index (SSCI)-listed
journal (IF 2.981 in 2019) in the area of information systems. We
encourage original contributions with a broad range of methodological
approaches, including conceptual, qualitative and quantitative research.
Please also consider position papers and case studies for this special
issue. All papers should fit the journal scope (for more information,
see www.electronicmarkets.org/about-em/scope/
<http://www.electronicmarkets.org/about-em/scope/>) and will undergo a
double-blind peer-review process. Submissions must be made via the
journal's submission system and comply with the journal's formatting
standards. The preferred average article length is approximately 8,000
words, excluding references. If you would like to discuss any aspect of
this special issue, you may either contact the guest editors or the
Editorial Office.
*Keywords*: Trust, Interpretability, Mental Models, Conceptual Models,
Explainable AI, Smart Market Services, Privacy, Fairness of Artificial
Intelligence, Biases, Transparency
*Important deadline: ** Submission Deadline: December, 15, 2021
*References*
Domingos, P. (2012). A few useful things to know about machine learning.
Communications of the ACM, 55(10), 78-87.
doi.org/10.1145/2347736.2347755 <https://doi.org/10.1145/2347736.2347755>.
Dwivedi, Y. K. et al. (2019). Artificial intelligence (AI):
Multidisciplinary perspectives on emerging challenges, opportunities,
and agenda for research, practice and policy. International Journal of
Information Management, 57, 101994,
doi.org/10.1016/j.ijinfomgt.2019.08.002.https://...
<https://doi.org/10.1016/j.ijinfomgt.2019.08.002.https:/www.sciencedirect.co…>
Jacovi, A., Marasovi, A., Miller, T., & Goldberg, Y. (2021). Formalizing
trust in artificial intelligence: Prerequisites, causes and goals of
human trust in ai. In Proceedings of the 2021 ACM Conference on
Fairness, Accountability, and Transparency, pp. 624-635.
doi.org/10.1145/3442188.3445923 <https://doi.org/10.1145/3442188.3445923>.
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs.
humans: The impact of artificial intelligence chatbot disclosure on
customer purchases. Marketing Science, 38(6), 937-947.
doi.org/10.1287/mksc.2019.1192 <https://doi.org/10.1287/mksc.2019.1192>.
Maass, W., Parsons, J., Purao, S., Storey, V. C., & Woo, C. (2018).
Data-driven meets theory-driven research in the era of big data:
opportunities and challenges for information systems research. Journal
of the Association for Information Systems, 19(12), 1.
doi.org/10.17705/1jais.00526 <https://doi.org/10.17705/1jais.00526>.
Maass, W., Parsons, J., Purao, S., & Storey, V. C. (2021). Pairing
conceptual modeling with machine learning. Data & Knowledge Engineering,
forthcoming.
Maass, W., Storey, V. C., & Lukyanenko, R. (2021). From mental models to
machine learning models via conceptual models. In Exploring Modeling
Methods for Systems Analysis and Development (EMMSAD 2021), Melbourne,
Australia, pp. 1–8. doi.org/10.1007/978-3-030-79186-5_19
<https://doi.org/10.1007/978-3-030-79186-5_19>.
Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). "Why should I trust
you?" Explaining the predictions of any classifier. In Proceedings of
the 22nd ACM SIGKDD international conference on knowledge discovery and
data mining, pp. 1135-1144. dx.doi.org/10.1145/2939672.2939778.
Siau, K., & Wang, W. (2018). Building trust in artificial intelligence,
machine learning, and robotics. Cutter Business Technology Journal,
31(2), 47-53.
Thiebes, S., Lins, S., & Sunyaev, A. Trustworthy artificial
intelligence. Electronic Markets, 31(2021)2.
doi.org/10.1007/s12525-020-00441-4
<https://doi.org/10.1007/s12525-020-00441-4>.
====================================================================
*Electronic Markets - The International Journal on Networked Business*
Editors-in-Chief: Rainer Alt, Leipzig University and Hans-Dieter
Zimmermann, FHS St.Gallen, University of Applied Sciences, Executive
Editor: Ramona Coia, Leipzig University
*Editorial Office*
c/o Information Systems Institute
Leipzig University
04109 Leipzig, Germany
Mail: editors(a)electronicmarkets.org <mailto:editors@electronicmarkets.org>
Phone: +49-341-9733600
http://www.electronicmarkets.org <http://www.electronicmarkets.org>
www.facebook.com/ElectronicMarkets
<https://www.facebook.com/ElectronicMarkets>
twitter.com/journal_EM <https://twitter.com/journal_EM>
www.springer.com/journal/12525 <https://www.springer.com/journal/12525>
Journal Impact Factor 2019: 2.981
-------- Forwarded Message --------
Subject: [AISWorld] Call for papers AIOPS 2021
Date: Tue, 29 Jun 2021 07:59:39 +0000
From: Bogatinovski, Jasmin <jasmin.bogatinovski(a)tu-berlin.de>
To: aisworld(a)lists.aisnet.org <aisworld(a)lists.aisnet.org>
CALL FOR SUBMISSIONS
Second International Workshop on Artificial Intelligence for IT Operations
collocated with
The 19-th International Conference on Service Oriented Computing (ICSOC
2021)
Dubai, UAE, November 22, 2021
>>> https://aiops2021.github.io/ <<<
SUBMISSIONS ARE NOW OPEN at:
https://easychair.org/conferences/?conf=aiops2021
The official Call for Papers can be found at:
https://easychair.org/cfp/AIOPS2021
Submission deadline: September 30, 2021
Scope
Large-scale IT systems, such as data centres, cloud computing
environments, edge clouds, IoT and embedded environments, are the key
enablers of digital transformation. Managing such systems puts an
enormous burden on the operators in dealing with the abundance of data,
oftentimes leading to severe economic implications. To mitigate this
issue IT operators increasingly rely on tools from artificial
intelligence for assistance in the operation of IT systems.
Artificial Intelligence for IT Operations (AIOps) is an emerging field
arising in the intersection between the research areas of machine
learning, big data, streaming analytics, and the management of IT
operations. The main goal is the analysis of system information of
heterogeneous type (metrics, logs, customer input, etc) to support
administrators by optimizing various objectives like prevention of SLA
violation, early anomaly detection and auto-remediation,
energy-efficient system operation, providing optimal QoE for customers,
predictive maintenance and many more. In this field, a constantly
growing interest can be observed, and thus, practical tools are
developed from both the academy and industry sector. We envision that,
with the advance of AIOps technologies, the IT industry will achieve
significant progress and sustained and exponential growth.
The main focus of this workshop is to bring together researchers from
both academia and industry to present their experiences, results, and
work in progress in this field. A major part of the workshop is to
strengthen the community and unite it towards the efforts for solving
the main challenges.
Topics of interest are the following:
*
Early anomaly, fault and failure (AFF) detection and analysis
*
Software dependability
*
Self-healing, self-correction and auto-remediation
*
Self-adaptive time-series based models for prognostics and forecasting
*
AFF identification, localization, and isolation
*
Root cause analysis
*
Adaptive fault tolerance policies
*
Forecasting of hardware and process quality
*
Performance management
*
Planning under uncertainty
*
Predictive and prescriptive maintenance
*
Maintenance scheduling and on-demand maintenance planning
*
Alarm correlation
*
Log analysis
*
Fault-tolerant system control
*
Resiliency, reliability, and quality assurance
*
Autonomic process optimization
*
Energy-efficient cloud operation
*
Distributed resource management
*
Autonomous service provisioning
*
Visual analytics and interactive machine learning
*
Active and life-long learning
*
Design of experiment (DoE) and benchmarking
*
Fault injection and chaos engineering
*
Use-cases, testbeds, evaluation scenarios
Publication: Post-workshop proceedings in Springer’s LNCS series.
Venue: collocated with ICSOC 2021 conference in Dubai 22 November 2021.
More information: http://www.icsoc.org/ <http://www.icsoc.org/> ,
AIOPS2021 (aiops2021.github.io/)
Important Dates:
Paper submission deadline: September 30, 2021
Acceptance notification: October 30, 2021
All deadlines are in Samoa Standard Time (SST = GMT – 11). Check the
time in the SST Zone here: https://time.is/SST.
Contact
Questions about submissions: aiops2021(a)googlegroups.com
<mailto:aiops2021@googlegroups.com>
Organizers
Roberto Natella, University of Naples Federico II, Italy
Jasmin Bogatinovski, Technical University Berlin, Germany
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-------- Forwarded Message --------
Subject: [AISWorld] IEEE BCCA 2021: The 3rd IEEE Conference on
Blockchain Computing and Applications
Date: Mon, 28 Jun 2021 20:49:56 +0300
From: Müge Erel-Özçevik <mugeerelozcevik(a)gmail.com>
To: aisworld(a)lists.aisnet.org
*The Third IEEE Conference on Blockchain Computing and Applications
(BCCA 2021)*
*NOV. 15 – 17, 2021 – TARTU, ESTONIA*
http://intelligenttech.org/BCCA2021/index.php
Blockchain is a revolutionary technology in decentralized systems that
enables secure decentralized transaction processing while ensuring data
privacy and authenticity. It is now playing a significant role in several
areas such the Internet of Things, supply-chain management, manufacturing,
cyber-physical systems, healthcare systems, and much more. Unlike
centralized transaction processing solutions, blockchain uses a distributed
ledger mechanism to record data transactions on multiple devices, this will
prevent data breach, identity theft, and a plethora of cyber-related
attacks, in essence, leading to a sustainability in data privacy and
security. This conference aims at to attract work of both researchers and
practitioners in the area of cyber-security to share and exchange their
experiences and research studies in both academia and industry in the field
of blockchain.
Researchers are encouraged to submit original research contributions in all
major areas, which include, but not limited to:
· *Track 01: Artificial Intelligence and Machine Learning*
o Blockchain based artificial Intelligent Systems applications in
Computers and Communications
o Blockchain based AI and Robotics Technologies
o Blockchain based AI and cloud computing
o Blockchain based Economic paradigms and game theory
o Blockchain based Machine and Deep Learning of Knowledge
o Blockchain based Distributed Knowledge and Processing
o Blockchain based Humans-Agents Interactions / Human-Robot Interactions
· *Track 02: IoT and Cyber-Physical Systems*
o Blockchain-based IoT Applications and Services
o Blockchain-based security for the Internet of Things and cyber-physical
systems
o Blockchain-based Internet of Things architectures and protocols
o Blockchain in Cyber Physical Systems (CPS)
o Blockchain-based application in Intelligent Manufacturing: Industrial
Internet of Things,
o Blockchain and Secure Critical Infrastructure with Industry 4.0
o Intelligent manufacture and management
o Consensus and mining algorithms suited for resource-limited IoTs
o Blockchain-based Controlled mobility and QoS
o Blockchain-based energy optimization techniques in WSN
o Blockchain-based Software defined networks
· *Track 03: Big Data*
o Blockchain in Data Fusion
o Blockchain Analytics and Data mining
o Distributed data store for blockchain
o Distributed transaction for blockchain
o Blockchain based Data Science and Data Engineering
o Protocols for management and access using blockchains
o Blockchain architectures tailored for domain-specific applications
· *Track 04: Security and Privacy on the Blockchain*
o Authentication and authorization in Blockchain
o Applications of blockchain technologies in digital forensic
o Privacy aspects of blockchain technologies
o Blockchain-based threat intelligence and threat analytics techniques
o Blockchain-based open-source tools
o Forensics readiness of blockchain technologies
o Blockchain Attacks on Existing Systems
o Blockchain Consensus Algorithms
o Blockchain-based Intrusion Detection/Prevention
o Security and Privacy in Blockchain and Critical Infrastructure
o Attacks on Blockchain and Critical Infrastructure
o Blockchain and Secure Critical Infrastructure with Smart Grid
· *Track 05: Blockchain Research & Applications for Innovative Networks and
Services*
o State-of-the-art of the Blockchain technology and cybersecurity
o Blockchain-based security solutions of smart cities infrastructures
o Blockchain in connected and autonomous vehicles (CAV) and ITS)
o Blockchain Technologies and Methodologies
o Recent development and emerging trends Blockchain
o New models, practical solutions and technological advances related to
Blockchain
o Theory of Blockchain in Cybersecurity
o Applications of blockchain technologies in computer & hardware security
o Implementation challenges facing blockchain technologies
o Blockchain in social networking
o Performance metric design, modeling and evaluation of blockchain systems
o Network and computing optimization in blockchains
o Experimental prototyping and testbeds for blockchains
All accepted papers in BCCA 2021 will be submitted to IEEEXplore, dblp and
Scopus for inclusion.
*General Co-Chair*
· Salil Kanhere, UNSW Sydney, Australia
· Öznur Özkasap, Koç University, Turkey
*Program Co-Chairs*
· Moayad Aloqaily, xAnalytics Inc., Canada
· Önder Gürcan, CEA LIST, Paris-Saclay University, France
· Hong-Ning Dai, Macau University of Science and Technology, Macau
*Keynote speakers:*
· Giancarlo Fortino, Università della Calabria, Italy
* Submission Link: *https://easychair.org/conferences/?conf=bcca2021
*Full paper Important Dates:*
Submission deadline: *July 1st, 2021*
Notification of Acceptance: Sept 15th, 2021
Submission of camera-ready: Oct 8th, 2021
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-------- Forwarded Message --------
Subject: [AISWorld] Call for book chapters: Handbook of Teaching and
Learning in Information Systems
Date: Mon, 28 Jun 2021 14:14:48 -0400
From: Mark Hwang <mark.hwang(a)cmich.edu>
To: aisworld(a)lists.aisnet.org
Dear Colleagues,
The goal of this project is to provide a comprehensive, one-stop book for
researchers interested in advancing IS education and IS pedagogical
research. Chapters should be between 8,000 and 10,000 words (each figure
counts as 500 words and each table as 300 words) and contain new and
original research. Any research type is welcome: quantitative or
qualitative; primary or secondary. The tentative deadline is June 30, 2022,
with an expected publication date of June 30, 2023. The *Handbook* will be
included in the Book Citation Index (part of the Web of Science) and the
SCOPUS citation index. See this link
<https://www.e-elgar.com/author-hub/handbooks/> for seven more reasons to
contribute a chapter to an Elgar handbook.
Please follow this link
<https://1drv.ms/w/s!ApSj8gjXHwd4goYMA51M_I7WRNGfrg?e=q1PWV6> for an
overview of the book’s structure. Issues related to IS education will be
organized into seven themes or sections. Each section is further divided
into chapters that deal with different issues or topics. These are
suggested topics, and you are welcome to pick a related topic for your
chapter.
There are no submission or publication fees. Every chapter will be
peer-reviewed to ensure the quality of the volume. Each author shall review
no more than one chapter. If you are interested in participating, please
send me a short proposal in about 150 words.
Best,
Mark Hwang
Professor, Information Systems
Central Michigan University
mark.hwang(a)cmich.edu
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-------- Forwarded Message --------
Subject: [AISWorld] CfP "Trust in AI for Electronic Markets",
Electronic Markets Journal
Date: Mon, 28 Jun 2021 12:52:33 +0200
From: Wolfgang Maass <wolfgang.maass(a)dfki.de>
To: aisworld(a)lists.aisnet.org
--- Apologies for cross-postings---
Dear colleagues,
*Electronic Markets* is seeking submissions for a *Special Issue on "Trust
in AI for electronic markets"*. Please find further details below.
Call for Papers: “Trust in AI for electronic markets”
Submission deadline: *December, 15, 2021*
Guest Editors
o Wolfgang Maass, Saarland University and German Research Center for
Artificial Intelligence (DFKI), Germany, wolfgang.maass(at)dfki.de
o Roman Lukyanenko, HEC Montréal, Canada, roman.lukyanenko(at)hec.ca
o Veda C. Storey, Georgia State University, USA, vstorey(a)gsu.edu
Theme
Electronic markets for trading physical, as well as digital, goods offer a
wide variety of services based on Artificial Intelligence technologies, as
smart market services. Smart market services generate recommendations and
predictions using Artificial Intelligence (AI) technologies on data
available and accessible in electronic markets. For instance, financial
high-speed trading is only feasible by smart market services that
autonomously execute transactions according to market signals based on AI
models trained with big data. Electronic marketplaces, including Amazon and
Alibaba, are using AI technologies to provide smart services to consumers,
optimize logistics, analyze consumer behavior, and derive innovative
product and service designs. Some business leaders even consider there to
be major threats to society from sophisticated AI solutions, while using AI
extensively for their own business. Because AI systems elude human
understanding and scrutinization, trust in AI is crucial for the success of
smart market services, as well as other AI or machine learning-based
systems . Gaining trust in AI begins with transparency in the reviews of
(a) data so that biases and gaps in knowledge of a domain are controlled,
(b) AI models and objective functions, (c) model performance and (d)
results generated by AI models for decision making. Trust becomes an
important factor for overcoming uncertainty on AI-based recommendations in
general and in electronic markets in particular.
The quality of smart market services depends on shared understanding and
conceptual models of data used for training AI models; data quality; the
selection and training of appropriate models; and the embedding of models
into smart market services. Providers of smart market services are required
to build trust relationships with business and end customers based on
limited possibilities for opening the “black boxes” of Artificial
Intelligence systems due to increased complexity of machine learning
models. Empirical studies on trust in AI indicate heterogenous results.
Companies and end-users appreciate benefits and opportunities provided by
smart market services. At the same time, concerns are raised with respect
to privacy issues and biases of data, models and algorithms. Overly
optimistic customers might become disappointed if smart market services do
not deliver as expected. Proof of privacy leaks and biases might reinforce
prejudices. Both may lead to decrease of trust in AI. Challenging research
questions are to identify which methods, indicators and experiences have
increasing effects on trust in AI. For instance, explainable AI is a
technical means for opening “black boxes” of AI systems, generally, and
smart market services, specifically.
This special issue seeks contributions on trust in Artificial Intelligence
in the context of electronic markets. Contributions that help to understand
challenges from an economic, legal or technical perspective are invited.
Central issues and topics
Possible topics of submissions include, but are not limited to:
o Trust behavior and AI
o Mental models, conceptual models and AI models
o Psychological and sociological factors for trust in AI
o Human-centric design of smart market services
o Explainable AI for smart market services
o Threats for trust in AI
o Frameworks for smart markets
o Business and legal aspects influencing trust in AI
o Relationships between trust and Business models with smart market services
o Transparency of data, AI models and recommendations
o Case studies on building trust in AI
Submission:
Electronic Markets is a Social Science Citation Index (SSCI)-listed journal
(IF 2.981 in 2019) in the area of information systems. We encourage
original contributions with a broad range of methodological approaches,
including conceptual, qualitative and quantitative research. Please also
consider position papers and case studies for this special issue. All
papers should fit the journal scope (for more information, see
www.electronicmarkets.org/about-em/scope/) and will undergo a double-blind
peer-review process. Submissions must be made via the journal’s submission
system and comply with the journal's formatting standards. The preferred
average article length is approximately 8,000 words, excluding references.
If you would like to discuss any aspect of this special issue, you may
either contact the guest editors or the Editorial Office.
Keywords:
Trust, Interpretability, Mental Models, Conceptual Models, Explainable AI,
Smart Market Services, Privacy, Fairness of Artificial Intelligence,
Biases, Transparency
Important deadline
* Submission Deadline: December, 15, 2021
References
Domingos, P. (2012). A few useful things to know about machine learning.
Communications of the ACM, 55(10), 78-87.
https://doi.org/10.1145/2347736.2347755.
Dwivedi, Y. K. et al. (2019). Artificial intelligence (AI):
Multidisciplinary perspectives on emerging challenges, opportunities, and
agenda for research, practice and policy. International Journal of
Information Management, 57, 101994,
https://doi.org/10.1016/j.ijinfomgt.2019.08.002.https://www.sciencedirect.c…
Jacovi, A., Marasovi, A., Miller, T., & Goldberg, Y. (2021). Formalizing
trust in artificial intelligence: Prerequisites, causes and goals of human
trust in ai. In Proceedings of the 2021 ACM Conference on Fairness,
Accountability, and Transparency, pp. 624-635.
https://doi.org/10.1145/3442188.3445923.
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs.
humans: The impact of artificial intelligence chatbot disclosure on
customer purchases. Marketing Science, 38(6), 937-947.
https://doi.org/10.1287/mksc.2019.1192.
Maass, W., Parsons, J., Purao, S., Storey, V. C., & Woo, C. (2018).
Data-driven meets theory-driven research in the era of big data:
opportunities and challenges for information systems research. Journal of
the Association for Information Systems, 19(12), 1.
https://doi.org/10.17705/1jais.00526.
Maass, W., Parsons, J., Purao, S., & Storey, V. C. (2021). Pairing
conceptual modeling with machine learning. Data & Knowledge Engineering,
forthcoming.
Maass, W., Storey, V. C., & Lukyanenko, R. (2021). From mental models to
machine learning models via conceptual models. In Exploring Modeling
Methods for Systems Analysis and Development (EMMSAD 2021), Melbourne,
Australia, pp. 1–8. https://doi.org/10.1007/978-3-030-79186-5_19.
Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). "Why should I trust you?"
Explaining the predictions of any classifier. In Proceedings of the 22nd
ACM SIGKDD international conference on knowledge discovery and data mining,
pp. 1135-1144. dx.doi.org/10.1145/2939672.2939778.
Siau, K., & Wang, W. (2018). Building trust in artificial intelligence,
machine learning, and robotics. Cutter Business Technology Journal, 31(2),
47-53.
Thiebes, S., Lins, S., & Sunyaev, A. Trustworthy artificial intelligence.
Electronic Markets, 31(2021)2. https://doi.org/10.1007/s12525-020-00441-4.
Best regards,
Rainer Alt, Hans-Dieter Zimmermann, Ramona Coia
====================================================================
Electronic Markets - The International Journal on Networked Business
Editors-in-Chief: Rainer Alt, Leipzig University and Hans-Dieter
Zimmermann, FHS St.Gallen, University of Applied Sciences
Executive Editor: Ramona Coia, Leipzig University Editorial Office:
c/o Information Systems Institute
Leipzig University
04109 Leipzig, Germany
Mail: editors(a)electronicmarkets.org
Phone: +49-341-9733600
http://www.electronicmarkets.orghttps://www.facebook.com/ElectronicMarketshttps://twitter.com/journal_EMhttps://www.springer.com/journal/12525
Journal Impact Factor 2019: 2.981
———
Univ.-Prof. Dr.-Ing. Wolfgang Maaß
German Research Center for Artificial Intelligence (DFKI)
Saarland Informatics Campus A5 4
66123 Saarbrücken, Germany
Phone: +49(0)681 302 64736
e-mail: wolfgang.maass(a)dfki.de
http://www.dfki.de/web/research/ssehttp://maasslab.de
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-------- Forwarded Message --------
Subject: [AISWorld] Special issue On Data-driven Analytics in the
Developments of a Smart City
Date: Mon, 28 Jun 2021 19:40:22 +0800
From: Yue Guo <yueggcn(a)aliyun.com>
Reply-To: Yue Guo <yueggcn(a)aliyun.com>
To: aisworld <aisworld(a)lists.aisnet.org>
Special issue On Data-driven Analytics in the Developments of a Smart City
https://www.emeraldgrouppublishing.com/journal/imds/data-driven-analytics-d…
Please note: Submissions for this special issue will open on 21st
September 2021.
Smart cities define an emerging paradigm containing heterogeneous
network infrastructure, ubiquitous sensor devices, big data processing,
and intelligent control systems. Their primary purpose is to improve the
quality of life of the citizens by providing intelligent services in a
wide variety of aspects like transportation, environment, energy, etc.
Big data analytics and operations research play an important role in
enabling and delivering such intelligent services. Therefore,
understanding how to use big data analytics and optimization for the
operation and management of a smart city from different aspects, such as
the allocation of power stations for electric taxis, charging batteries
for car sharing, renewable power storage facilities for metros, and the
charge/discharge management for all power storage facilities has aroused
widespread concern in both academia and practice.
Solving smart city issues can be costly and complicated and requires us
to develop novel research approaches based on empirical data to provide
more appropriate solutions to build smart city plans. The purpose of
this special issue is to publish insights and viewpoints from scholars
regarding solutions to smart city issues and challenges from different
aspects, including the resource allocation and optimization of power
stations, the location and capacity for shared car parking space,
transportation strategy, and operation management of car sharing.
Some topics of interest may include but are not limited to:
Rigorous case studies on using data analytics for smart city development
issues Data analytics for improving smart city operations efficiency
Data analytics for car-sharing demand prediction
Data analytics for transportation security The impact of smart cities on
social welfare
The application of data analytics to predict traffic congestion
Using smart city visibility data for resource allocation Security-driven
supply chain innovation
The charge and discharge management of energy storage facilities such as
subway capacitors, shared car batteries, and electric taxi batteries
Submission and review process
Please prepare the manuscript according to the journal’s “Guide for
Authors and submission guidelines”. Please clearly state in the cover
letter that the submission is made for this special issue. The review
process will follow the journal’s double-blind practice. More
information on the author guidelines can be found here.
Prospective authors should submit an electronic copy of their complete
manuscript via ScholarOne by selecting the article type “Data-Driven
Analytics in the Development of a Smart City” in the online submission
system here.
Publication Schedule
Submissions Open: September 21, 2021 Manuscript Submission Deadline:
January 11, 2022
Final Decision Date: September 7, 2022
Expected Publication (Tentative): Autumn of 2022
Guest Editors
Prof. Yue Guo
Southern University of Science and Technology, China
guoy(a)sustech.edu.cn
Prof. Lean Yu
University of Chinese Academy of Sciences, China
yulean(a)amss.ac.cn
Prof. Leandro C. Coelho
Université Laval, Canada
leandro.coelho(a)fsa.ulaval.ca
Prof. Yichuan Ding
McGill University, Canada
daniel.ding(a)mcgill.ca
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