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International Conference on Computational science and Computational Intelligence (CSCI)

作者： Kunyanuth Kularbphettong Rujijan Vichivanives Pannawat Kanjanaprakarn Jaruwan Chutrtong Nareenart Ruksuntorn Computer Science Program Suan Sunandha Rajabhat University Bangkok Thailand Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok Thailand Robotics Engineering program Faculty of Industrial Technology Suan Sunandha Rajabhat University Bangkok Thailand

This paper presents the use of natural language processing for the problem of information extraction and sentiment analysis. The dataset is from Twitter that has the information of people mentioning about COVID-19, this study has two tasks: (i) classification approach for information extraction task and (ii) deep learning approach for sentiment analysis task. In information extraction task, the data was gathered from twitter that related to COVID-19 information, and the sequence labelling method applied to classify text before giving it to classification algorithms (K-NN, Naïve Bayes, Decision Tree, Random Forest, and SVM). In sentiment analysis task, data was classified by convert the word into index and using word embedding, then to process deep learning algorithm (Bi-directional GRU). The accuracy of two tasks are 98% and 79% respectively.

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Child-Centred AI Design: Definition, Operation, and Considerations

Child-Centred AI Design: Definition, Operation, and Consider...

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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023

作者： Wang, Ge Sun, Kaiwen Atabey, Ayça Pothong, Kruakae Lin, Grace C. Zhao, Jun Yip, Jason Department of Computer Science University of Oxford United Kingdom School of Information University of Michigan United States School of Law Centre for Data Culture & Society University of Edinburgh United Kingdom Department of Media and Communications The London School of Economics and Political Science 5Rights Foundation United Kingdom Scheller Teacher Education Program The Education Arcade The Massachusetts Institute of Technology United States Information School University of Washington United States

ISBN: (纸本)9781450394222

AI systems and related algorithms are starting to play a variety of roles in the digital ecosystems of children - being embedded in the connected toys, smart home IoT technologies, apps, and services they interact with on a daily basis. Going forward, AI systems will, in all likelihood, become even more pervasive in children's applications simply due to their sheer usefulness in creating compelling, adaptive, and personal user experiences. Yet, understanding the ways that AI-driven systems used by children operate, and how AI could be designed to better anticipate and respond to children's diverse requirements is still a new and emerging area of investigation. Our goals of this workshop are to (1) extend the current critically constructive dialogue around the meaning of child-centred AI design and (2) explore ways to operationalise such child-centred AI design in practice, and finally (3) further expand and foster a community for those who are interested in designing and developing child-centred AI systems. © 2023 Owner/Author.

关键词： Automation

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Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

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Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

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Unbiased Approximations for Stationary Distributions of McKean-Vlasov SDEs

arXiv

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arXiv 2024年

作者： Awadelkarim, Elsiddig Chada, Neil K. Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematics City University of Hong Kong Hong Kong School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China

We consider the development of unbiased estimators, to approximate the stationary distribution of Mckean-Vlasov stochastic differential equations (MVSDEs). These are an important class of processes, which frequently appear in applications such as mathematical finance, biology and opinion dynamics. Typically the stationary distribution is unknown and indeed one cannot simulate such processes exactly. As a result one commonly requires a time-discretization scheme which results in a discretization bias and a bias from not being able to simulate the associated stationary distribution. To overcome this bias, we present a new unbiased estimator taking motivation from the literature on unbiased Monte Carlo. We prove the unbiasedness of our estimator, under assumptions. In order to prove this we require developing ergodicity results of various discrete time processes, through an appropriate discretization scheme, towards the invariant measure. Numerous numerical experiments are provided, on a range of MVSDEs, to demonstrate the effectiveness of our unbiased estimator. Such examples include the Currie-Weiss model, a 3D neuroscience model and a parameter estimation problem. © 2024, CC BY-NC-SA.

关键词： Stochastic systems

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Integration of the Use of Conventional technology Towards Smart Home technology for People in the City of Jakarta

Integration of the Use of Conventional Technology Towards Sm...

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International Conference on ICT For Smart Society (ICISS)

作者： Tanty Oktavia Febian Wijaya Lintang Gerald Christian Ongko Griselda Valerie Michelle Benedicta Vieri Aska Juneio Sembiring Zaldy Raditya Ananta Takaaki Hosoda Ford Lumban Gaol Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Decision Science Department Advanced Institute of Industrial Technology Tokyo Japan Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

Smart Home technology offers technological concepts that can be controlled through smart devices to make it easier for the community. Therefore, smart home technology is starting to seize the home electronics market in Indonesia, especially in the city of Jakarta. This study aims to determine the integration of conventional technology into smart home technology for people in Jakarta. The research model in this study uses UTAUT2 which analyzes nine variables, namely Perceived Usefulness, Perceived Cost, Perceived Ease of Use, Social Influence, Perceived Compatibility, Trust, Perceived Pleasure, and Effort Expectations, Intention to Use Smart Home technology. After the responses were received, data analysis was carried out using the PLS-SEM approach with the SmartPLS application. The results of this study show that there are many people who live in Jakarta who are helped by the presence of smart home technology. However, there are some people who don't really know how to use a smart home because of a lack of knowledge about this technology.

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Economics of Semantic Communication in Metaverse: An Auction Approach

Economics of Semantic Communication in Metaverse: An Auction...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Zi Qin Liew Hongyang Du Wei Yang Bryan Lim Zehui Xiong Dusit Niyato Han Yu Alibaba-NTU Singapore Joint Research Institute Nanyang Technological Univerity Singapore School of Computer Science and Engineering Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Computer Science and Engineering Nanyang Technological University Singapore

Metaverse provides embodied artificial-reality experience to the users in the virtual spaces. Many innovative and creative services such as virtual conference and tourism have been realized in the digital twins maintained by the virtual service providers (VSP) in Metaverse. Digital twins are digital copies of the physical world constructed virtually by the VSPs using real-world data. For a realistic experience, VSPs need to collect data that is up-to-date and relevant to their services. In this paper, we propose an incentive design framework to support the data trading between VSPs and edge devices. In the auction model, we model the valuation of data by considering data relatedness and data freshness. In our model, the semantic communication model is used to filter the relevant data, and the age of information (AoI) metric is used to assess the data freshness. Results show that by considering the data freshness, our mechanism helps to increase the average update frequency so that the VSPs obtain fresh data for construction of digital twins. Our model ensures the desired properties of individual rationality, incentive compatibility, and budget balance.

关键词： Measurement Metaverse Data integrity Semantics Streaming media Information filters Data models

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‘Do I Belong Here, There, or Elsewhere?’: The Materiality and Intangible Benefits of technology in Digital Nomads' Place-Belongingness

‘Do I Belong Here, There, or Elsewhere?’: The Materiality ...

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International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Hesam Mohseni Marcos Antonio de Almeida Daniel Schneider António Correia Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Systems Engineering and Computer Science Program (PESC) Federal University of Rio de Janeiro Rio de Janeiro Brazil Postgraduate Program in Informatics (PPGI) Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (数字)9798350354423

ISBN: (纸本)9798350354430

The advent of digital technology has contributed to experiencing liquid lifestyles and flexible work arrangements with different mobility routes and targets. Escaping the exhausting routine of commuting to and from work has been a key driver of digital nomadism, a phenomenon that has become increasingly widespread across the globe and is often centered around cross-border travel and expatriate settlement. Due to their frequent mobility, digital nomads face unique challenges in fostering a sense of place-belongingness compared to most other types of workers. Despite the popularity of digital nomadic work/life in the current public discourse, there is no standardized guidebook for understanding how digital technology already supports or could potentially support the sense of place-belongingness among these voluntary migrants. Motivated by this line of research, in our paper, we propose an initial guide with practical methodological considerations on how to investigate this phenomenon using qualitative and quantitative materials. Such studies can assist strategists and organizations in attracting new talent and fostering more inclusive environments.

关键词： Liquids Standards organizations Organizations Mediation Faces

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Semi-Automated Classification of Arabic User Requirements into Functional and Non-Functional Requirements using NLP Tools

Semi-Automated Classification of Arabic User Requirements in...

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2021 International Conference on Information technology, ICIT 2021

作者： Shehadeh, Karmel Arman, Nabil Khamayseh, Faisal Palestine Polytechnic University Deanship of Graduate Studies/Master's of Informatics Program Hebron Palestine Palestine Polytechnic University Department of Computer Science and Information Technology Hebron Palestine

ISBN: (纸本)9781665428705

Functional and non-functional requirements are equally important in software engineering. Both of them are mixed together within the same software requirement document. Usually, they are expressed in natural languages. So, a lot of human effort is required to classify them. Software requirements classification is a challenging task. Requirements classification can help developers to deliver quality software that meets users' expectations completely. In this paper, we present a Semi-Automated classification approach of Arabic functional and non-functional requirements using a natural language processing (NLP) tool. We propose a set of heuristics based on basic constructs of Arabic sentences in order to extract information from Arabic software requirements to classify the requirements into functional and non-functional requirements. This research aims to help software engineers by reducing the cost and time required in performing manual classification of software requirements. © 2021 IEEE.

关键词： Requirements engineering

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A Finite Difference Method for a Normalized Time-Fractional Black–Scholes Equation

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International Journal of Applied and Computational Mathematics 2025年第3期11卷 1-17页

作者： Nam, Yunjae Wang, Jian Lee, Chaeyoung Choi, Yongho Bang, Minjoon Li, Zhengang Kim, Junseok Program in Actuarial Science and Financial Engineering Korea University Seoul 02841 South Korea School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 China Department of Mathematics Kyonggi University Suwon 16227 South Korea Computer and Information Engineering Daegu University Gyeongsan 38453 South Korea Department of Mathematics Korea University Seoul 02841 South Korea

In this article, we propose a normalized time-fractional Black–Scholes (TFBS) equation. The proposed model uses a normalized time-fractional derivative which has a distinctive feature wherein a weight function possesses the property that its integral with respect to time is always equal to one. This feature ensures a well-balanced integration over time and provides a fair comparison between different fractional orders. An implicit finite difference method is used for the numerical solution of the TFBS equation. We perform several standard numerical tests to examine the effect of the fractional parameter on the option pricing. These experiments are designed to investigate how variations in the fractional parameter influence pricing outcomes and provide valuable insights into the model’s behavior under different conditions. The computational results demonstrate the model’s potential for capturing more intricate market dynamics, which makes the proposed model a promising tool for financial analysis. In the appendix, we provide a computer program that implements the numerical methods discussed in the paper for interested readers. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2025.

关键词： Implicit finite difference method Memory effect Normalized time-fractional Black–Scholes equation

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Unbiased Estimation of the Vanilla and Deterministic Ensemble Kalman–Bucy Filters

arXiv

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arXiv 2022年

作者： Álvarez Ballesteros, Miguel Ángel Chada, Neil K. Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

In this article we consider the development of an unbiased estimator for the ensemble Kalman–Bucy filter (EnKBF). The EnKBF is a continuous-time filtering methodology which can be viewed as a continuous-time analogue of the famous discrete-time ensemble Kalman filter. Our unbiased estimators will be motivated from recent work [Rhee & Glynn 2010, [31]] which introduces randomization as a means to produce unbiased and finite variance estimators. The randomization enters through both the level of discretization, and through the number of samples at each level. Our estimator will be specific to linear and Gaussian settings, where we know that the EnKBF is consistent, in the particle limit N → ∞, with the KBF. We highlight this for two particular variants of the EnKBF, i.e. the deterministic and vanilla variants, and demonstrate this on a linear Ornstein–Uhlenbeck process. We compare this with the EnKBF and the multilevel (MLEnKBF), for experiments with varying dimension size. We also provide a proof of the multilevel deterministic EnKBF, which provides a guideline for some of the unbiased methods. © 2022, CC BY-NC-SA.

关键词： Continuous time systems

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