KES2025 invited session on
Design of Nigiwai: Places Embracing Values
10, 11, & 12 Sept, 2025
Ritsumeikan University Osaka Ibaraki Campus (OIC)
Ritsumeikan University
2-150 Iwakura-cho, Ibaraki
Osaka 567-8570 JAPAN
Session Themes: [Design of Nigiwai: Places Embracing Values]
So far, we have been organizing sessions on Chance Discovery, that is research
to study how to discover rare or novel events which may potentially cause
significant situation but may also cause fatal accidents.
We have discussed limitations of conventional methods for machine learning
and data mining, and introduced concepts and methods for human-based
discovery.
In order to deal with events in the real world, we integrated artificial,
natural, and social intelligence. In addition, we learned it is important
to discuss effective the evaluation, selection, and creation of such events.
Furthermore, we discussed the ``curation'' of chance events, which implies
to actively present hints of chance to users.
All in all, we acquired the research direction toward sensing, presenting,
using, and creating values - both positive and negative - in the real world.
This session will discuss problems relevant to how to design Nigiwai,
which means the state of a place that accepts diverse people sustainably.
This does not mean a sheer ``bustling'' or ``lively'' place where many people
or a lot of money gather, but a place where opportunities and risks coexist;
that is, an environment where the discovery and creation of values can be
expected through the crossover of ideas and mutual stimulation, but if not
observed and managed well, individuals may suffer from infectious diseases,
crime, and anxiety (this balance between expectations and fears may be a
design factor). Thus, we deal with Nigiwai as an environment for the discovery and management of chances.
In this session, we aim to exchange participants' studies, wisdoms, and
opinions relevant to this topic and discussing issues and methods for
designing, managing, and optimizing Nigiwai places.
Topics to be discussed (will not be restricted to):
- Place-Making Strategies with Big data: Methods and approaches to create meaningful and engaging environments that foster social interaction, community cohesion, and a sense of belonging.
- Participatory Design: Approaches to involve stakeholders, including residents, businesses, and community groups, in the design process.
- Environmental Psychology: Relationship between the built environment and human behavior, emotions, and well-being, and explore design interventions.
- Smart Cities and Technologies: Integration of digital technologies, data analytics, and Internet of Things (IoT) solutions to enhance the functionality, efficiency, and sustainability of urban spaces and infrastructure.
Continuing from the previous invited session;
- Analysis of human behaviour.
- Analysis of complex systems (society, community etc.).
- Applications of Chance Discovery.
- Innovations as Chance Discovery.
- Value sensing in Chance Discovery.
- Chance synthesis
- Characterization of ``Chance.''
- Logical foundations for Chance Discovery.
- Theories and methodologies to discover rare or novel events.
- Theories and methodologies to foretell next trends.
- Theories and methodologies to make aware of significant events.
- Theories and methodologies for an evaluation and selection of chance.
- Models and methodologies for effective suggestion of chance.
- Relationship between computational and manual methods.
- Integration of computational and manual methods.
- Curation of chance
- Data market, data jacket
- Data Exchange and Collaboration etc.
Reference:
Yukio Ohsawa, Sae Kondo, Yi Sun, and Kaira Sekiguchi:
Generating a Map of Well-being Regions Using
Multiscale Moving Direction Entropy on Mobile Sensors,
AAAI Spring Symposium. pp. 389--390 (2024)
Submission:
Page formatting:
The guide length for full papers is 8 to 10 pages (maximum).
The paper format as a PDF document is available here.
Please consult important FAQs about document preparation to be found here.
An MS Word template
is available here.
For the LaTex users, this package
can be used.
For a paper to be published in the Procedia proceedings
- no changes may be made to the Procedia template and the instructions must be followed exactly
- the maximum length of 10 pages must not be exceeded
- the paper must be presented at the conference
It is the author's responsibility to ensure that their paper does not contain any errors. Also, kindly note that Elsevier will publish what they receive so it is important that the authors submit the final version of their papers.
Proofs will not be sent to authors at any time during production.
Submissions are invited on previously unpublished research.
Your papers can be submitted to:
Important Dates:
[tentative]
- 20 May, 2025: Submission deadline of papers
(all extended!!)
- 25 May, 2025: Notification of acceptance of papers.
- 2 June, 2025: Deadline for camera-ready papers (via Easy Chair)
- 2 June, 2025: Early Registratoin Deadline
attention!! Hard deadline - will not be extended more
Every paper must have at least one author who has registered for the
conference with payment by the Early Registration Deadline for the paper
to appear in the proceedings.
- 10, 11, or 13 Sept, 2025: Session
Review:
All submissions will be reviewed on the basis of relevance, originality,
significance, soundness and clarity. At least two referees will review
each submission independently.
Publication:
All accepted papers will be published in the KES2024 Proceedings (Procedia Computer Science).
Extended versions of selected papers will be considered for
publication in the KES Journal (International Journal of
Knowledge-Based and Intelligent Engineering Systems) published by IOS
Press, and other journals.
Chairs:
- Akinori Abe
Faculty of Letters, Chiba University
1-33 Yayoicho, Inageku, Chiba 263-8522, JAPAN
E-mail: ave@chiba-u.jp
- Yukio Ohsawa
The Univeristy of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 JAPAN
E-mail: ohsawa@sys.t.u-tokyo.ac.jp
- Sae Kondo
Mie University, and The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 JAPAN