• Electronics and Telecommunications Trends
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• v.37 no.6
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• pp.32-42
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• 2022

Recently, decentralized approaches to artificial intelligence (AI) development, such as federated learning are drawing attention as AI development's cost and time inefficiency increase due to explosive data growth and rapid environmental changes. Collaborative AI technology that dynamically organizes collaborative groups between different agents to share data, knowledge, and experience and uses distributed resources to derive enhanced knowledge and analysis models through collaborative learning to solve given problems is an alternative to centralized AI. This article investigates and analyzes recent technologies and applications applicable to the research of multi-agent collaboration of AI bots, which can provide collaborative AI functionality autonomously.

• Asia Pacific Journal of Corpus Research
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• v.1 no.1
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• pp.95-125
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• 2020

This paper aims to inform people how to support each other on social media. It alludes to an architecture for social media discourse and proposes a novel theory of support in social media discourse. It makes a methodological contribution. It combines predominately artificial intelligence with corpus linguistics analysis. It is on a large-scale dataset of anonymised diabetes-related user's posts from the Facebook platform. Log-likelihood and precision measures help with validation. A multi-method approach with Discourse Analysis helps in understanding any potential patterns. People living with Diabetes are found to employ sophisticated high-frequency patterns of device-enabled categories of purpose and content. It is with, for example, linguistic forms of Advice with stance-taking and targets such as Diabetes amongst other interactional ways. There can be uncertainty and variation of effect displayed when sharing information for support. The implications of the new theory aim at healthcare communicators, corpus linguists and with preliminary work for AI support-bots. These bots may be programmed to utilise the language patterns to support people who need them automatically.

• Smart Media Journal
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• v.11 no.6
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• pp.51-63
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• 2022

Metaverse provides a simulated environment where a large number of users can participate in various activities. In order for Metaverse to be sustainable, it is necessary to study ethics that can be applied to a Metaverse service platform. In this paper, Metaverse ethics and the rules for applying to the platform are explored. And, in order to judge the ethicality of avatar actions in social Metaverse, the identity, interaction, and relationship of an avatar are investigated. Then, an action-based audit approach to avatar interactions (e.g., dialogues, gestures, facial expressions) is introduced in two cases that an avatar enters a digital world and that an avatar requests the auditing to subjects, e.g., avatars controlled by human users, artificial intelligence (AI) avatars (e.g., as conversational bots), and virtual objects. Pseudocodes for performing the two cases in a system are presented and they are examined based on the description of the avatars' actions.

• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.761-770
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• 2012

CAPTCHAs(Completely Automated Public Turing tests to tell Computer and Human Apart) have been widely used for preventing the automated attacks such as spam mails, DDoS attacks, etc.. In the early stages, the text-based CAPTCHAs that were made by distorting random characters were mainly used for frustrating automated-bots. Many researches, however, showed that the text-based CAPTCHAs were breakable via AI or image processing techniques. Due to the reason, the image-based CAPTCHAs, which employ images instead of texts, have been considered and suggested. In many image-based CAPTCHAs, however, the huge number of source images are required to guarantee a fair level of security. In 2008, Kang et al. suggested a new image-based CAPTCHA that uses test images made by composing multiple source images, to reduce the number of source images while it guarantees the security level. In their paper, the authors showed the convenience of their CAPTCHA in use through the use study, but they did not verify its security level. In this paper, we verify the security of the image-based CAPTCHA suggested by Kang et al. by performing several attacks in various scenarios and consider other possible attacks that can happen in the real world.