A5050964166- E-Government and Public Services
- Social Media and Politics
- Reinforcement Learning in Robotics
- Robot Manipulation and Learning
- Internet Traffic Analysis and Secure E-voting
- Technology Adoption and User Behaviour
- ICT Impact and Policies
- Smart Cities and Technologies
- International Business and FDI
- Public Policy and Administration Research
- Multimodal Machine Learning Applications
- Robotic Locomotion and Control
- Privacy, Security, and Data Protection
- Diverse Aspects of Tourism Research
- Digital Marketing and Social Media
- Ethics and Social Impacts of AI
- Human Mobility and Location-Based Analysis
- Information and Cyber Security
- Economic Growth and Development
- Cultural Industries and Urban Development
- Consumer Behavior in Brand Consumption and Identification
- Topic Modeling
- Corruption and Economic Development
- Evolutionary Algorithms and Applications
- Natural Language Processing Techniques
Google (United States)
2019-2024
DeepMind (United Kingdom)
2024
Institute of Electrical and Electronics Engineers
2024
University of Memphis
2024
Engineering Systems (United States)
2024
University of Massachusetts Boston
2012-2023
Hong Kong Polytechnic University
2013-2021
Corvallis Environmental Center
2020
Southampton General Hospital
2018
Federal Reserve Board of Governors
2018
Large language models can encode a wealth of semantic knowledge about the world. Such could be extremely useful to robots aiming act upon high-level, temporally extended instructions expressed in natural language. However, significant weakness is that they lack real-world experience, which makes it difficult leverage them for decision making within given embodiment. For example, asking model describe how clean spill might result reasonable narrative, but may not applicable particular agent,...
This case study reports an innovative e‐government experiment by a local government in Seoul, South Korea—Gangnam‐gu. A new political leadership Gangnam made strategic use of applications to exert greater control over the civil service bureaucracy. The authors find that possess properties can be applied effectively as instruments improve bureaucracy well enhance essential accountability and transparency. circumstances underlying development its impact on are reported, along with key...
This study focuses on the impact of cultural distance behavior international pleasure tourists who visited Hong Kong. It analyzes data drawn from Kong Tourism Board's Visitor Profile Report, and tests whether has a similar as noted in previous studies examining physical distance. The concludes that exerts modest such attributes demand, travel party composition, trip profile, behaviors, expenditure satisfaction.
Large, high-capacity models trained on diverse datasets have shown remarkable successes efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led a consolidation of pretrained models, with general backbones serving as starting point for many Can such happen in robotics? Conventionally, robotic learning methods train separate model every application, robot, and even environment. we instead generalist X-robot policy that can be adapted new robots,...
E-government has been touted by many as a technological answer to improve citizen participation, government accountability, and transparency facilitating greater level of communication flow public information between citizens the government. This article examines how political environment, structure, nature individual e-government applications influence likelihood adoption. Using data obtained from multiple sources, logistic regressions are conducted on sample six that possess varying...
Background Near-peer teaching is used in anatomy education because of its benefits to the learner, teacher and faculty members. Despite range reports focusing on advantages for teacher, which are thought include communication skills, subject knowledge employability, only beginning be explored. Method A questionnaire was distributed teachers involved near-peer at University Southampton Brighton Sussex Medical School (BSMS). This designed using a rating scale 0–10 assess perspectives their...
This study aims to address strategies, models, and the motivation behind smart cities by analyzing two city project cases in medium-sized cities, i.e., Gimpo Namyangju South Korea. The case of Smartopia represents a top-down, infrastructure-focused innovation that invested building state-of-the-art big data infrastructure for crime prevention, traffic alleviation, environmental preservation, disaster management. On other hand, 4.0 strategy focused on internal process through extensive...
While there has been growth in the literature exploring governance of artificial intelligence (AI) and recognition critical importance guiding public values, lacks a systematic study focusing on values as well challenges solutions to advance these values. This article conducts review relationships between sector AI identify impacts solutions. It further explores perspectives U.S. government employees via national survey. The results suggest need for broad inclusion diverse salience...
Foundation models that incorporate language, vision, and more recently actions have revolutionized the ability to harness internet scale data reason about useful tasks. However, one of key challenges training embodied foundation is lack grounded in physical world. In this paper, we propose AutoRT, a system leverages existing up deployment operational robots completely unseen scenarios with minimal human supervision. AutoRT vision-language (VLMs) for scene understanding grounding, further...
Civic technology is a nascent force in the relationship between governments and communities. Elements of civic ecosystem include open data, related information communications (ICT) innovations organizational boundary-spanning practices technology. This paper reports results an exploratory study adoption by local United States. The research compares 113 U.S. city recognized for their exemplary fiscal year 2012 popular annual financial (PAFRs) with 49 municipalities state Delaware that operate...
Manipulation and locomotion are closely related problems that often studied in isolation. In this work, we study the problem of coordinating multiple mobile agents to exhibit manipulation behaviors using a reinforcement learning (RL) approach. Our method hinges on use hierarchical sim2real -- simulated environment is used learn low-level goal-reaching skills, which then as action space for high-level RL controller, also trained simulation. The full policy transferred real world zero-shot...
The rapid advancement of AI technologies – machine learning, Big Data, Cloud Computing and Internet Things (IoT) other related has dramatically expanded the technological capacities government application in been accelerating into more substantial areas functions. Often compared to Fourth Industrial Revolution, are expected change our society a fundamental way this will create need for public sector adapt coordinate broader social transformation around new technology. At important juncture,...
Artificial Intelligence has emerged as a transformative force in public service delivery, promising improved efficiency and responsiveness to citizens’ needs, so it is essential understand the functional factors that influence adoption intention continue using such services. Drawing on technology acceptance model, this study investigates of six factors, namely, usefulness, ease use, reliability, quality, responsiveness, security, continued use AI-enabled services through mediating effect...
ROBEL is an open-source platform of cost-effective robots designed for reinforcement learning in the real world. introduces two robots, each aimed to accelerate research different task domains: D'Claw a three-fingered hand robot that facilitates dexterous manipulation tasks, and D'Kitty four-legged agile legged locomotion tasks. These low-cost, modular are easy maintain robust enough sustain on-hardware from scratch with over 14000 training hours registered on them date. To leverage this...
Reinforcement learning provides a general framework for robotic skills while minimizing engineering effort.However, most reinforcement algorithms assume that well-designed reward function is provided, and learn single behavior function.Such functions can be difficult to design in practice.Can we instead develop efficient methods acquire diverse without any function, then re-purpose these downstream tasks?In this paper, demonstrate recently proposed unsupervised skill discovery algorithm...
This paper provides a systematic literature review of cybersecurity concerns in public administration scholarship. The main intent is to outline the major shifts issues faced by and nonprofit sectors. We undertake this exercise also identify future research agenda emerging gaps. Our principal finding from that scholars practitioners have not given attention cyber-security until recently. Cyber-security did emerge as significant theme mid-2000s. There dichotomy treating technical problem or...
This note describes new data on household debt-to-income ratios (DTI) that is being provided in interactive maps as part of the Enhanced Financial Accounts (EFA).
Using a panel dataset gathered from 57 countries over the period 2003 to 2014, this paper examines impact of cultural factors on relationship between e-government development and corruption. The analysis reveals that have weak positive corruption levels across all but varied according different factors. Based typology GLOBE project, authors found was more effective in reducing with certain characteristics. Cultures put less emphasis controlling uncertainty shared power equally among members,...
This article explores the previously unexamined assumption that cultural profile of international tourists traveling to different destinations mirrors overall population a nation. Most studies adopt cross-sectional destination approach, comparing and contrasting visitors from source markets visit single destination. study adopts market approach by examining cohort socially demographically homogenous Koreans who have varying travel experiences. The results demonstrated no significant...
We present a deep-dive into real-world robotic learning system that, in previous work, was shown to be capable of hundreds table tennis rallies with human and has the ability precisely return ball desired targets.This puts together highly optimized perception subsystem, highspeed low-latency robot controller, simulation paradigm that can prevent damage real world also train policies for zero-shot transfer, automated environment resets enable autonomous training evaluation on physical...