Probabilistic Causal Modeling of Barriers to Accessibility for Persons with Disabilities in Canada DOI Creative Commons
Mouri Zakir, Gregor Wolbring, Svetlana Yanushkevich

и другие.

Smart Cities, Год журнала: 2024, Номер 8(1), С. 4 - 4

Опубликована: Дек. 24, 2024

This paper utilizes a methodological two-step process incorporating statistical and causal probabilistic modeling techniques to investigate factors affecting the accessibility experiences of persons with disabilities in Canada. We deploy network-based approach using empirical data perform holistic assessment relations between various demographic features (e.g., age, gender type disability) barriers. A measurement method is applied that structural equation supported by exploratory factor analysis. For modeling, Bayesian networks are employed as straightforward compact way interpret knowledge representation. reasoning analyzes nature frequency encountering barriers based on understand risk contributing pressing issues. Furthermore, evaluate network performance overcome any limitations, synthetic generation create validate artificial built real-world knowledge. The proposed framework strives provide prevalence physical, social, communication or technological encountered their daily lives. study contributes identification areas for prioritization facilitating regulation practices realize an inclusive society.

Язык: Английский

Generative AI in AI-Based Digital Twins for Fault Diagnosis for Predictive Maintenance in Industry 4.0/5.0 DOI Creative Commons
Emilia Mikołajewska, Dariusz Mikołajewski, Tadeusz Mikołajczyk

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(6), С. 3166 - 3166

Опубликована: Март 14, 2025

Generative AI (GenAI) is revolutionizing digital twins (DTs) for fault diagnosis and predictive maintenance in Industry 4.0 5.0 by enabling real-time simulation, data augmentation, improved anomaly detection. DTs, virtual replicas of physical systems, already use generative models to simulate various failure scenarios rare events, improving system resilience prediction accuracy. They create synthetic datasets that improve training quality while addressing scarcity imbalance. The aim this paper was present the current state art perspectives using AI-based DTs 4.0/5.0. With GenAI, enable proactive minimize downtime, their latest implementations combine multimodal sensor generate more realistic actionable insights into performance. This provides operational profiles, identifying potential traditional methods may miss. New area include incorporation Explainable (XAI) increase transparency decision-making reliability key industries such as manufacturing, energy, healthcare. As emphasizes a human-centric approach, DT can seamlessly integrate with human operators support collaboration decision-making. implementation edge computing increases scalability capabilities smart factories industrial Internet Things (IoT) systems. Future advances federated learning ensure privacy exchange between enterprises diagnostics, evolution GenAI alongside ensuring long-term validity. However, challenges remain managing computational complexity, security, ethical issues during implementation.

Язык: Английский

Процитировано

0
A Systematic Review of the Digital Twin Technology in Buildings, Landscape and Urban Environment from 2018 to 2024 DOI Creative Commons
Wenhui Liu,

Yihan Lv,

Qian Wang

и другие.

Buildings, Год журнала: 2024, Номер 14(11), С. 3475 - 3475

Опубликована: Окт. 31, 2024

Digital Twin (DT) technologies have demonstrated a positive impact across various stages of the Architecture, Engineering, and Construction (AEC) industry. Nevertheless, industry has been slow to undergo digital transformation. The paper utilizes Systematic Literature Review (SLR) approach study total 842 papers on application DT in buildings, landscapes, urban environments (BLU) from 2018 2024. Based research results, suggestions made for future practical directions. Meanwhile, it provides assistance BLU’s designers, constructors, managers, policymakers establishing their understanding transformation AEC existing relevant can be mainly divided into three categories: case study, framework technology study. Compared with buildings environment industries, number depth landscape are relatively low. Through in-depth analysis BLU projects, trends determined: (1) design planning stage; (2) development tools basic theory based model; (3) exploration

Язык: Английский

Процитировано

1
Probabilistic Causal Modeling of Barriers to Accessibility for Persons with Disabilities in Canada DOI Creative Commons
Mouri Zakir, Gregor Wolbring, Svetlana Yanushkevich

и другие.

Smart Cities, Год журнала: 2024, Номер 8(1), С. 4 - 4

Опубликована: Дек. 24, 2024

This paper utilizes a methodological two-step process incorporating statistical and causal probabilistic modeling techniques to investigate factors affecting the accessibility experiences of persons with disabilities in Canada. We deploy network-based approach using empirical data perform holistic assessment relations between various demographic features (e.g., age, gender type disability) barriers. A measurement method is applied that structural equation supported by exploratory factor analysis. For modeling, Bayesian networks are employed as straightforward compact way interpret knowledge representation. reasoning analyzes nature frequency encountering barriers based on understand risk contributing pressing issues. Furthermore, evaluate network performance overcome any limitations, synthetic generation create validate artificial built real-world knowledge. The proposed framework strives provide prevalence physical, social, communication or technological encountered their daily lives. study contributes identification areas for prioritization facilitating regulation practices realize an inclusive society.

Язык: Английский

Процитировано

0