Junfeng Jiao
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View article: Towards a digital twin for smart resilient cities: real-time fire and smoke tracking and prediction platform for community awareness (FireCom)
Towards a digital twin for smart resilient cities: real-time fire and smoke tracking and prediction platform for community awareness (FireCom) Open
This paper discusses the development and application of a digital twin (DT) for urban resilience, focusing on an integrated platform for real-time fire and smoke. The proposed platform, FireCom, adapts DT concepts for the unique challenges…
View article: Evaluating LLM Safety Across Child Development Stages: A Simulated Agent Approach
Evaluating LLM Safety Across Child Development Stages: A Simulated Agent Approach Open
Large Language Models (LLMs) are rapidly becoming part of tools used by children; however, existing benchmarks fail to capture how these models manage language, reasoning, and safety needs that are specific to various ages. We present Chil…
View article: HCOMC: A Hierarchical Cooperative On-Ramp Merging Control Framework in Mixed Traffic Environment on Two-Lane Highways
HCOMC: A Hierarchical Cooperative On-Ramp Merging Control Framework in Mixed Traffic Environment on Two-Lane Highways Open
Highway on-ramp merging areas are common bottlenecks to traffic congestion and accidents. Currently, a cooperative control strategy based on connected and automated vehicles (CAVs) is a fundamental solution to this problem. While CAVs are …
View article: TGLD: A Trust-Aware Game-Theoretic Lane-Changing Decision Framework for Automated Vehicles in Heterogeneous Traffic
TGLD: A Trust-Aware Game-Theoretic Lane-Changing Decision Framework for Automated Vehicles in Heterogeneous Traffic Open
Automated vehicles (AVs) face a critical need to adopt socially compatible behaviors and cooperate effectively with human-driven vehicles (HVs) in heterogeneous traffic environment. However, most existing lane-changing frameworks overlook …
View article: HLCG: A Hierarchical Lane-Changing Gaming Decision Model for Heterogeneous Traffic Flow on Two-Lane Highways
HLCG: A Hierarchical Lane-Changing Gaming Decision Model for Heterogeneous Traffic Flow on Two-Lane Highways Open
Discretionary lane-changing behavior is one of the most common highway operations, which seriously affects traffic efficiency and safety. Nowadays, connected and automated vehicles (CAVs) are advancing rapidly, though not yet fully widespr…
View article: Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-LLM Interactions
Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-LLM Interactions Open
As Large Language Models (LLMs) increasingly power applications used by children and adolescents, ensuring safe and age-appropriate interactions has become an urgent ethical imperative. Despite progress in AI safety, current evaluations pr…
View article: City Climate Data Decision Calendar (C2D2): Framework and Initial Results for Austin, Texas
City Climate Data Decision Calendar (C2D2): Framework and Initial Results for Austin, Texas Open
Various operations and activities in the city municipal departments are weather and climate data sensitive. However, there is limited understanding and documentation of how and what datasets and products are required or will be useful for …
View article: SafeMate: A Modular RAG-Based Agent for Context-Aware Emergency Guidance
SafeMate: A Modular RAG-Based Agent for Context-Aware Emergency Guidance Open
Despite the abundance of public safety documents and emergency protocols, most individuals remain ill-equipped to interpret and act on such information during crises. Traditional emergency decision support systems (EDSS) are designed for p…
View article: LLM Ethics Benchmark: A Three-Dimensional Assessment System for Evaluating Moral Reasoning in Large Language Models
LLM Ethics Benchmark: A Three-Dimensional Assessment System for Evaluating Moral Reasoning in Large Language Models Open
This study establishes a novel framework for systematically evaluating the moral reasoning capabilities of large language models (LLMs) as they increasingly integrate into critical societal domains. Current assessment methodologies lack th…
View article: A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models
A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models Open
Traditional Reinforcement Learning (RL) suffers from replicating human-like behaviors, generalizing effectively in multi-agent scenarios, and overcoming inherent interpretability issues.These tasks are compounded when deep environment unde…
View article: Mapping out AI Functions in Intelligent Disaster (Mis)Management and AI-Caused Disasters
Mapping out AI Functions in Intelligent Disaster (Mis)Management and AI-Caused Disasters Open
This study maps the functions of artificial intelligence in disaster (mis)management. It begins with a classification of disasters in terms of their causal parameters, introducing hypothetical cases of independent or hybrid AI-caused disas…
View article: LLMs and Childhood Safety: Identifying Risks and Proposing a Protection Framework for Safe Child-LLM Interaction
LLMs and Childhood Safety: Identifying Risks and Proposing a Protection Framework for Safe Child-LLM Interaction Open
This study examines the growing use of Large Language Models (LLMs) in child-centered applications, highlighting safety and ethical concerns such as bias, harmful content, and cultural insensitivity. Despite their potential to enhance lear…
View article: AGGA: A Dataset of Academic Guidelines for Generative AI and Large Language Models
AGGA: A Dataset of Academic Guidelines for Generative AI and Large Language Models Open
This study introduces AGGA, a dataset comprising 80 academic guidelines for the use of Generative AIs (GAIs) and Large Language Models (LLMs) in academic settings, meticulously collected from official university websites. The dataset conta…
View article: IGGA: A Dataset of Industrial Guidelines and Policy Statements for Generative AIs
IGGA: A Dataset of Industrial Guidelines and Policy Statements for Generative AIs Open
This paper introduces IGGA, a dataset of 160 industry guidelines and policy statements for the use of Generative AIs (GAIs) and Large Language Models (LLMs) in industry and workplace settings, collected from official company websites, and …
View article: Generative AI and LLMs in Industry: A text-mining Analysis and Critical Evaluation of Guidelines and Policy Statements Across Fourteen Industrial Sectors
Generative AI and LLMs in Industry: A text-mining Analysis and Critical Evaluation of Guidelines and Policy Statements Across Fourteen Industrial Sectors Open
The rise of Generative AI (GAI) and Large Language Models (LLMs) has transformed industrial landscapes, offering unprecedented opportunities for efficiency and innovation while raising critical ethical, regulatory, and operational challeng…
View article: Reconstructing missing data of damaged buildings from post-hurricane reconnaissance data using XGBoost
Reconstructing missing data of damaged buildings from post-hurricane reconnaissance data using XGBoost Open
Assessing building damage in coastal communities after a hurricane event is crucial for reducing both immediate and long-term disaster impacts, as well as for enhancing resilience planning and disaster preparedness. Despite the extensive d…
View article: AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem
AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem Open
This paper presents the development and functionalities of the AI-FEED web-based platform (ai-feed.ai), designed to address food and nutrition insecurity challenges within the food charity ecosystem. AI-FEED leverages advancements in artif…
View article: Toward an equitable transportation electrification plan: Measuring public electric vehicle charging station access disparities in Austin, Texas
Toward an equitable transportation electrification plan: Measuring public electric vehicle charging station access disparities in Austin, Texas Open
The deployment of public electric vehicle charging stations (EVCS) is a critical component of transportation electrification. Recent studies have highlighted growing concerns about disparities in accessibility to public chargers between di…
View article: Developing a transit desert interactive dashboard: Supervised modeling for forecasting transit deserts
Developing a transit desert interactive dashboard: Supervised modeling for forecasting transit deserts Open
Transit deserts refer to regions with a gap in transit services, with the demand for transit exceeding the supply. This study goes beyond merely identifying transit deserts to suggest actionable solutions. Using a multi-class supervised ma…
View article: Evaluating urban fire vulnerability and accessibility to fire stations and hospitals in Austin, Texas
Evaluating urban fire vulnerability and accessibility to fire stations and hospitals in Austin, Texas Open
Anthropogenic climate change has increased the frequency and intensity of fires. Despite their widespread consequences, current research has largely overlooked urban fires and their associated vulnerability. This study seeks to identify pa…
View article: The global landscape of academic guidelines for generative AI and Large Language Models
The global landscape of academic guidelines for generative AI and Large Language Models Open
The integration of Generative Artificial Intelligence (GAI) and Large Language Models (LLMs) in academia has spurred a global discourse on their potential pedagogical benefits and ethical considerations. Positive reactions highlight some p…
View article: Navigating LLM Ethics: Advancements, Challenges, and Future Directions
Navigating LLM Ethics: Advancements, Challenges, and Future Directions Open
This study addresses ethical issues surrounding Large Language Models (LLMs) within the field of artificial intelligence. It explores the common ethical challenges posed by both LLMs and other AI systems, such as privacy and fairness, as w…