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Articles 601 - 630 of 23190
Full-Text Articles in Entire DC Network
Hybrid Learning And Optimization Methods For Solving Capacitated Vehicle Routing Problem, Monit Sharma, Hoong Chuin Lau
Hybrid Learning And Optimization Methods For Solving Capacitated Vehicle Routing Problem, Monit Sharma, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We propose a hybrid quantum–classical framework for the Capacitated Vehicle Routing Problem (CVRP) that integrates the Augmented Lagrangian Method (ALM) with deep reinforcement learning (RL). Directly solving CVRP via Variational Quantum Eigensolver (VQE) requires a slack-based QUBO formulation, where converting inequalities to equalities greatly increases the qubit count. To circumvent this, we employ an ALM-based reformulation that enforces constraints through Lagrange terms instead of slack variables, drastically reducing quantum resource demands. An RL agent, trained with Soft Actor–Critic, adaptively tunes the Lagrange penalties to improve convergence and feasibility. Experiments show that RL-Q-ALM outperforms static-penalty and plain VQE baselines in both …
Realign: Text-To-Motion Generation Via Step-Aware Reward-Guided Alignment, Wanjiang Weng, Xiaofeng Tan, Junbo Wang, Guo-Sen Xie, Pan Zhou, Hongsong Wang
Realign: Text-To-Motion Generation Via Step-Aware Reward-Guided Alignment, Wanjiang Weng, Xiaofeng Tan, Junbo Wang, Guo-Sen Xie, Pan Zhou, Hongsong Wang
Research Collection School Of Computing and Information Systems
Text-to-motion generation, which synthesizes 3D human motions from text inputs, holds immense potential for applications in gaming, film, and robotics. Recently, diffusion-based methods have been shown to generate more diversity and realistic motion. However, there exists a misalignment between text and motion distributions in diffusion models, which leads to semantically inconsistent or low-quality motions. To address this limitation, we propose Reward-guided sampling Alignment (ReAlign), comprising a step-aware reward model to assess alignment quality during the denoising sampling and a reward-guided strategy that directs the diffusion process toward an optimally aligned distribution. This reward model integrates step-aware tokens and combines a …
Airaclex: Automated Detection Of Price Oracle Manipulations Via Llm-Driven Knowledge Mining And Prompt Generation, Bo Gao, Yuan Wang, Qingsong Wei, Yong Liu, Rick Siow Mong Goh, David Lo
Airaclex: Automated Detection Of Price Oracle Manipulations Via Llm-Driven Knowledge Mining And Prompt Generation, Bo Gao, Yuan Wang, Qingsong Wei, Yong Liu, Rick Siow Mong Goh, David Lo
Research Collection School Of Computing and Information Systems
Decentralized finance (DeFi) applications depend on accurate price oracles to ensure secure and fair transactions. However, poorly integrated oracles remain susceptible to manipulation, enabling attackers to exploit smart contract logic for unfair asset valuation and financial gain. While many such vulnerabilities are only detected after deployment, smart contracts are typically immutable once deployed, making post-hoc fixes costly or infeasible. This highlights the critical need for detecting oracle manipulation risks before deployment. In this paper, we propose AiRacleX, a novel LLM-driven framework that enables pre-deployment detection of price oracle manipulation vulnerabilities by leveraging the complementary strengths of multiple large language models …
Freedom Of Expression Protection And Corporate Concealment Of Bad News: Evidence From State Anti-Slapp Laws, Jimmy Lee, Shaphan Ng, Il Sun Yoo, Liandong Zhang
Freedom Of Expression Protection And Corporate Concealment Of Bad News: Evidence From State Anti-Slapp Laws, Jimmy Lee, Shaphan Ng, Il Sun Yoo, Liandong Zhang
Research Collection School Of Accountancy
The protection of free speech enhances the ability of various public stakeholders to disseminate privately observed adverse information about public firms, making it difficult for corporate managers to conceal negative information about their companies. Using the staggered enactment of anti strategic lawsuit against public participation (anti-SLAPP) laws across U.S. states as a shock that strengthens free speech protection, we show that stronger protection is associated with less concealment of bad news. This is evidenced by a lower likelihood of stock price crashes, a decreased probability of accounting fraud, and an increased frequency of firm-initiated negative press releases. These results are …
Peer Effects Of Corporate Disclosures: Evidence From The Registration-Based Ipo System In China, Ruilin Liu, Beng Wee Goh, Dan Li, Zheyuan Zhang
Peer Effects Of Corporate Disclosures: Evidence From The Registration-Based Ipo System In China, Ruilin Liu, Beng Wee Goh, Dan Li, Zheyuan Zhang
Research Collection School Of Accountancy
China launched the registration-based IPO system in 2019 whereby all firms listed on the newly established STAR board (“peer firms”) are required to disclose specific innovation and industry-related information in their prospectus. Using this event as a quasi-experiment, our study investigates the causal effects of peer firms’ disclosures on individual firms’ disclosure strategy. We find that individual firms’ management earnings forecast (MEF) precision, both its form and width, significantly decreases when peer firms disclose more information during the IPO period. In cross-sectional analyses, we find this effect to be more pronounced for individual firms that are likely to experience greater …
The Effect Of Cybersecurity Breaches On Analysts’ Earnings Forecasts, Chih-Ying Chen, Beng Wee Goh, Kiat Bee Jimmy Lee, Na Li
The Effect Of Cybersecurity Breaches On Analysts’ Earnings Forecasts, Chih-Ying Chen, Beng Wee Goh, Kiat Bee Jimmy Lee, Na Li
Research Collection School Of Accountancy
We investigate the implications of cybersecurity breaches for financial analysts because they play an important role as information intermediaries in capital markets, and it is unknown whether analysts’ earnings forecasts are affected by cybersecurity breaches. Based on a sample of cybersecurity breaches from 2005 to 2018, we find that analysts’ earnings forecasts for firms with cybersecurity breaches are less accurate and more dispersed after a breach than for firms without such breaches. In cross-sectional analyses, we find that the adverse effects of cybersecurity breaches on analysts’ earnings forecasts are more pronounced for firms operating in more volatile business environments, for …
Does Auditor Quality Enhance Csr Disclosure?, Jimmy Lee, Chee Yeow Lim, Gerald J. Lobo, Yanping Xu
Does Auditor Quality Enhance Csr Disclosure?, Jimmy Lee, Chee Yeow Lim, Gerald J. Lobo, Yanping Xu
Research Collection School Of Accountancy
We investigate the relation between auditor quality and client firms’ corporate social responsibility (CSR) disclosure. Using an international sample of firms from 36 countries over the period 2009–2018 and a measure of the extent of CSR disclosure from Bloomberg, we find strong evidence that client firms with higher quality auditors provide more CSR disclosure. In cross-sectional analyses, we show that the relation between auditor quality and CSR disclosure is accentuated when the information environment is poorer and when the financial reporting environment and the legal institutions are weaker. Lastly, we document that firms with higher quality auditors also exhibit better …
Epiphanic Empires: Commentary On Sophie Grace Chappell's Epiphanies, Brandon Yip
Epiphanic Empires: Commentary On Sophie Grace Chappell's Epiphanies, Brandon Yip
Research Collection School of Social Sciences
Chappell provides a comprehensive ethical vision by reflecting on the nature of epiphanies. I suggest that two aspects of that vision, (1) the anti-theoretic impulse and (2) the republic of conversation, are in tension with the fact that our epiphanies are often imperious: they purport to authoritatively dictate normative reality to us.
What Must Change? Towards Gender-Equitable And Inclusive Academic Communities, Lily Kong
What Must Change? Towards Gender-Equitable And Inclusive Academic Communities, Lily Kong
Research Collection School of Social Sciences
University leadership has a responsibility to support gender equity that goes beyond simply holding senior roles, writes Lily Kong. Here, she calls for changes in career pathways, workload allocation and service expectations to open space for more women.
Paradox Mindset In Working Parenthood: Linking Dual-Role Enrichment To Pursuit, Success, And Satisfaction, Tengjiao Huang, Xiaoyu Dai, Chi-Ying Cheng, Angela Leung
Paradox Mindset In Working Parenthood: Linking Dual-Role Enrichment To Pursuit, Success, And Satisfaction, Tengjiao Huang, Xiaoyu Dai, Chi-Ying Cheng, Angela Leung
Research Collection School of Social Sciences
Managing the simultaneous demands of career and parenthood often generates tensions—particularly for women, who have historically been expected to take primary responsibility for caregiving. These gendered expectations persist, even as men increasingly express a desire to engage more actively in caregiving while maintaining their professional roles. Drawing on paradox mindset theory and work-family enrichment literature, this research investigated whether a paradox mindset—a cognitive tendency to embrace and value tensions—is positively associated with an aspiration for enrichment between work and parenting roles. In turn, this aspiration is hypothesized to predict intentions and outcomes related to dual-role pursuit. Three cross-sectional survey studies …
Walking Through Green And Grey: Exploring Sequential Exposure And Multisensory Environmental Effects On Psychological Restoration, Sifan Cheng, Binyu Lei, Kunihiko Fujiwara, Clayton Miller, Filip Biljecki, Jeroen Van Ameijde
Walking Through Green And Grey: Exploring Sequential Exposure And Multisensory Environmental Effects On Psychological Restoration, Sifan Cheng, Binyu Lei, Kunihiko Fujiwara, Clayton Miller, Filip Biljecki, Jeroen Van Ameijde
Research Collection College of Integrative Studies
Urban environments are increasingly recognised for their potential to support psychological restoration, yet most studies assess green and grey spaces in isolation and rely on static, lab-based measures. This study introduces a multi-layered analytical framework that integrates experimental walking, momentary perception tracking, and machine learning to investigate how multisensory urban features shape restoration. Conducted on a university campus, the experiment exposed 20 participants to sequential grey–green–grey walking routes. Restoration was measured through pre/post psychometric surveys, heart rate variability (HRV), and minute-level micro-surveys during walking. Results reveal three key insights: (1) green exposure induces a short-term “inoculation effect”, with restorative benefits …
An Ex-Post Analysis Framework For Assessing The Effectiveness And Driving Factors Of Green Building Certification Adoption: A Case Study Of Singapore, Hao Gu, Xiaoyu Jin, Fu Xiao, Maomao Hu, Clayton Miller
An Ex-Post Analysis Framework For Assessing The Effectiveness And Driving Factors Of Green Building Certification Adoption: A Case Study Of Singapore, Hao Gu, Xiaoyu Jin, Fu Xiao, Maomao Hu, Clayton Miller
Research Collection College of Integrative Studies
Cities worldwide are adopting green building certification policies to meet sustainability and decarbonization targets in the building sector. However, the effectiveness of green certifications remains contested due to the difficulty of decomposing multiple influencing factors on building energy consumption. This study proposes an econometrics-based ex-post analysis framework to assess the effectiveness of green building certification policies in energy savings and identify driving factors by decomposing multiple influential factors. The proposed framework incorporates time-fixed effect models to examine factors driving the adoption of green building certifications, and causality analysis to quantify the effectiveness. Applying the framework to analyze a panel dataset …
A General Algorithm For Assortment Optimization Under Random Utility Choice Models, Tien Mai, Andrea Lodi
A General Algorithm For Assortment Optimization Under Random Utility Choice Models, Tien Mai, Andrea Lodi
Research Collection School Of Computing and Information Systems
This work concerns the assortment optimization problem that refers to selecting a subset of items that maximizes the expected revenue in the presence of the substitution behavior of consumers specified by a random utility choice model. The key challenge lies in the computational difficulty of finding the best subset solution, which often requires exhaustive search. The literature on constrained assortment optimization lacks a practically efficient method that is general to deal with different types of customer choice models (e.g., the multinomial logit, mixed logit or general multivariate extreme value models). In this work, we propose a new approach that allows …
Integrating Symbolic And Waveform Music Into Large Language Models, Teng Tu, Xiaohao Liu, Yunshan Ma, Ji Qi, Tat-Seng Chua
Integrating Symbolic And Waveform Music Into Large Language Models, Teng Tu, Xiaohao Liu, Yunshan Ma, Ji Qi, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Music, as a unique and integral element of human life, is characterized by its complex structures, intricate details, and the fusion of multimodal information. Recent study advance music understanding by leveraging knowledge and reasoning capabilities derived from Large Language Models (LLMs). However, they often lack compatibility and fail to fully utilize the complementary strengths of diverse representations (e.g., ABC, MIDI, Waveform). To address these limitations, we propose a unified music-language model framework, named UniMuLM, transitioning from single-representation approaches to the integration of multiple music representations for LLM. Unifying different music representation formats poses challenges such as patch integrity and boundary …
Shrinkflation And Consumer Demand, Aljoscha Janssen, Johannes Kasinger
Shrinkflation And Consumer Demand, Aljoscha Janssen, Johannes Kasinger
Research Collection School Of Economics
This study investigates shrinkflation—the practice of reducing product size while maintaining or slightly changing prices—in the U.S. retail grocery market. We analyze a decade of retail scanner data to assess the prevalence and patterns of product size changes across various product categories. Our findings show that approximately 1.92% of products have been downsized. When comparing total sales, product downsizing is more than five times as prevalent as upsizing. Product downsizing typically occurs without a corresponding decrease in price and is widespread across product categories. Consequently, consumers end up paying more per unit volume. We further find that consumers are more …
Childlessness And Health In Middle Age And Older Adulthood: Evidence From Singapore, Christine Ho, Dahye Kim, Rohan Ray, Bussarawan Teerawichitchainan
Childlessness And Health In Middle Age And Older Adulthood: Evidence From Singapore, Christine Ho, Dahye Kim, Rohan Ray, Bussarawan Teerawichitchainan
Research Collection School Of Economics
Health and well-being in mature adulthood are important concerns given the prevalence of individuals aging without children. We exploit two new instruments for childlessness— infertility and the number of childless siblings—and condition our analyses on a rich set of covariates including childhood health and financial status, to investigate the causal relationship between childlessness and health in middle age and older adulthood. Using a nationwide dataset of 1,500 Singaporeans aged 50 and above, we show that OLS underestimates the negativeeffects of childlessness on health. We find that childlessness leads to higher likelihood of poorer self-reported health and mental distress. The results …
Relevance Between Strict Liability Theory And Banking Crimes In The Transfer Of Customer Funds: Negligence And Intent, Astrid Athina Indradewi, Evi Kongres, Ananda Chrisna D. Panjaitan, Evelyn Hutami Gunawarman
Relevance Between Strict Liability Theory And Banking Crimes In The Transfer Of Customer Funds: Negligence And Intent, Astrid Athina Indradewi, Evi Kongres, Ananda Chrisna D. Panjaitan, Evelyn Hutami Gunawarman
Research Collection Yong Pung How School Of Law
This article discusses the relevance of the Strict Liability theory to banking crimes in the transfer of customer funds involving elements of negligence as well as intent committed by bank managers. Strict liability places responsibility on the perpetrator without the need to prove fault, but rather by establishing a causal relationship between the act and the harm. In the context of civil law, Articles 1365 and 1367 of the Indonesian Civil Code recognize a form of liability resembling this concept through the mechanism of vicarious liability, whereby the bank as employer may be held liable for the unlawful acts of …
Gui Test Migration Via Abstraction And Concretization, Yakun Zhang, Chen Liu, Xiaofei Xie, Yun Lin, Jin Song Dong, Dan Hao, Lu Zhang
Gui Test Migration Via Abstraction And Concretization, Yakun Zhang, Chen Liu, Xiaofei Xie, Yun Lin, Jin Song Dong, Dan Hao, Lu Zhang
Research Collection School Of Computing and Information Systems
GUI test migration aims to produce test cases with events and assertions to test specific functionalities of a target app. Existing migration approaches typically focus on the widget-mapping paradigm that maps widgets from source apps to target apps. However, since different apps may implement the same functionality in different ways, direct mapping may result in incomplete or buggy test cases, thus significantly impacting the effectiveness of testing the target functionality and the practical applicability of migration approaches.In this article, we propose a new migration paradigm (i.e., the abstraction-concretization paradigm) that first abstracts the test logic for the target functionality and …
Dollar Challenger? Cbdcs, Complexities, And Monetary Hegemony, Heng Wang
Dollar Challenger? Cbdcs, Complexities, And Monetary Hegemony, Heng Wang
Research Collection Yong Pung How School Of Law
Digitalization is transforming the architecture of the international monetary system, reshaping how currencies function and financial infrastructures evolve. Among the significant developments are central bank digital currencies (CBDCs)—new digital forms of national currencies. While CBDCs promise benefits such as efficiency, they also generate relational, technological, legal, and governance complexities that would profoundly affect the global financial landscape. Against this backdrop, a compelling question arises: will CBDCs, particularly cross-border CBDCs, challenge U.S. dollar dominance?
To address this, this Article adopts a forward-looking approach to examine three interrelated crucial questions: what makes CBDCs complex? What governance complexity is likely to arise? Will …
‘Salami Slicing’ And Issue Estoppel: Foreign Decisions On The Governing Law, Adeline Chong
‘Salami Slicing’ And Issue Estoppel: Foreign Decisions On The Governing Law, Adeline Chong
Research Collection Yong Pung How School Of Law
Whether an issue estoppel arises over foreign decisions on the governing law of the claim has not been directly considered by an English court, but decisions in other jurisdictions show that this question is increasingly being raised in litigation. Is there identity of issue if the two courts apply different choice of law rules? The answer turns on whether a broad or narrow framing of the issue is adopted. It is suggested that, absent an issue which is subject to forum international public policy, forum overriding mandatory rules or which is one that the forum court retains the prerogative to …
A Case Study Of Gender And Online Team Communication In Software Engineering Education, Rita Garcia, Christoph Treude
A Case Study Of Gender And Online Team Communication In Software Engineering Education, Rita Garcia, Christoph Treude
Research Collection School Of Computing and Information Systems
Collaboration is crucial in Software Engineering (SE), yet factors like gender bias can shape team dynamics and behaviours. This descriptive case study examines an eight-week project involving 39 SE students across eight teams contributing to GitHub projects. Focusing on gender, we used a mixed-methods approach to analyse Slack communications, identifying gender differences in how students respond to initiated communications and comparing how students’ communications influenced other aspects of students’ performance, including learning gains. We found higher help-seeking and leadership behaviours in the all-woman team involved in this case study, while men responded more slowly. Although communication did not directly affect …
Gig Worker Social Referrals On An On-Demand Food Delivery Platform, Hai Wang, Hao Sun, Peter Zhang
Gig Worker Social Referrals On An On-Demand Food Delivery Platform, Hai Wang, Hao Sun, Peter Zhang
Research Collection School Of Computing and Information Systems
Social referral programs are commonly used by online labor platforms to incentivize labor supply by rewarding existing workers for successful referrals. This study investigates the impact of such programs on gig workers' labor supply in online labor platforms using data from an on-demand food delivery platform in Singapore. In particular, we analyze how gig workers' past labor supply and referral behavior influence the generation and value of social referrals. This research offers insights into the mechanisms that drive labor supply dynamics in the gig economy and highlights the effectiveness of social referral programs for shaping worker behavior and enhancing platform …
Generalization Bounds For Semi‑Supervised Matrix Completion With Distributional Side Information, Antoine Ledent, Mun Chong Soo, Minh Hieu Nong
Generalization Bounds For Semi‑Supervised Matrix Completion With Distributional Side Information, Antoine Ledent, Mun Chong Soo, Minh Hieu Nong
Research Collection School Of Computing and Information Systems
We study a matrix completion problem where both the ground truth R matrix and the unknown sampling distribution P over observed entries are low-rank matrices, and share a common subspace. We assume that a large amount M of unlabeled data drawn from the sampling distribution P is available, together with a small amount N of labeled data drawn from the same distribution and noisy estimates of the corresponding ground truth entries. This setting is inspired by recommender systems scenarios where the unlabeled data corresponds to ‘implicit feedback’ (consisting in interactions such as purchase, click, etc. ) and the labeled data …
Interpretable Machine Learning For In-Home Mild Cognitive Impairment Detection, Budhitama Subagdja, Shanthoshigaa D, Ah-Hwee Tan, Iris Rawtaer
Interpretable Machine Learning For In-Home Mild Cognitive Impairment Detection, Budhitama Subagdja, Shanthoshigaa D, Ah-Hwee Tan, Iris Rawtaer
Research Collection School Of Computing and Information Systems
This paper introduces a novel system for in-home cognitive health assessment using ambient sensors and a machine learning technology that can robustly detect mild cognitive impairment (MCI) despite limited available data. The learned model can explain the aspects of individuals’ daily lives led to the prediction, while reliably predicting MCI, providing more insights to healthcare workers for further clinical interventions. We developed the robust transparent machine learning model, based on fusion adaptive resonance theory (Fusion ART) neural network to learn individuals’ daily patterns of activity from continuous sensor data in terms of a suite of digital biomarkers reflecting four key …
Ai Systems For Physicians: A Review From Socio-Technical And Human-Computer Interaction Perspectives, Wu Jiaqi Young, Fiona Fui-Hoon Nah
Ai Systems For Physicians: A Review From Socio-Technical And Human-Computer Interaction Perspectives, Wu Jiaqi Young, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
The adoption of artificial intelligence (AI) in healthcare is accelerating, yet successful implementations of physician-facing AI systems remain limited and uneven. This paper presents a literature review of 40 peer-reviewed studies published between November 2022 and November 2024, spanning clinical, technical, and human-computer interaction (HCI) domains. Anchored in a socio-technical perspective, the review examines our existing understanding of how technical design, user expertise, and organizational factors shape the effectiveness of AI systems in real-world clinical settings. Our analysis identifies two meta-themes: (1) context as a dynamic, multi-level influence that actively reshapes AI system behavior, and (2) trust as an emergent …
Thinkmatter: Panoramic-Aware Instructional Semantics For Monocular Vision-And-Language Navigation, Guangzhao Dai, Shuo Wang, Hao Zhao, Bin Zhu, Qianru Sun, Xiangbo Shu
Thinkmatter: Panoramic-Aware Instructional Semantics For Monocular Vision-And-Language Navigation, Guangzhao Dai, Shuo Wang, Hao Zhao, Bin Zhu, Qianru Sun, Xiangbo Shu
Research Collection School Of Computing and Information Systems
Vision-and-Language Navigation in continuous environments (VLN-CE) requires an embodied robot to navigate the target destination following the natural language instruction. Most existing methods use panoramic RGB-D cameras for 360° observation of environments. However, these methods struggle in real-world applications because of the higher cost of panoramic RGB-D cameras. This paper studies a low-cost and practical VLN-CE setting, e.g., using monocular cameras of limited field of view, which means “Look Less” for visual observations and environment semantics. In this paper, we propose a ThinkMatter framework for monocular VLN-CE, where we motivate monocular robots to “Think More” by 1) generating novel views …
Learning-Based Graph Shrinking For Quantum Optimization Of Constrained Combinatorial Problems, Monit Sharma, Hoong Chuin Lau
Learning-Based Graph Shrinking For Quantum Optimization Of Constrained Combinatorial Problems, Monit Sharma, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Graph shrinking has recently emerged as a powerful preprocessing technique for hybrid classical–quantum optimization, enabling variable and constraint reduction before quantum solving. Conventional approaches rely on Semi-Definite Programming (SDP) relaxations to compute vertex correlations, but these methods suffer from high computational overhead, instance-specific tuning, and limited generalizability. In this work, we replace the handcrafted SDP correlation stage with a reinforcement learning (RL) based correlation estimator, trained to predict merge quality directly from graph structure. We reformulate the graph shrinking process as a Markov Decision Process (MDP), design a Graph Neural Network (GNN) policy to guide vertex merging, and integrate the …
Food Recognition With Visual Language Models: Search Re-Ranking Or Retrieval-Augmented Generation?, Kian Yu Gan, Phuong Anh Nguyen, Chong-Wah Ngo
Food Recognition With Visual Language Models: Search Re-Ranking Or Retrieval-Augmented Generation?, Kian Yu Gan, Phuong Anh Nguyen, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Despite the rapid advances in Visual Language Models (VLMs), these models struggle to recognize culture-specific food items. While VLMs are effective in recognizing popular cultural dishes, their performance is suboptimal for dishes that are unique but not widely known internationally. Specifically, VLMs often generate either generic labels or hallucinated names for dishes that are localized to a particular culture. As a result, retrieval-augmented generation (RAG), which retrieves relevant recipes as references for VLMs, emerges as a promising approach. Nevertheless, recipe retrieval, which is itself imperfect, could mislead VLMs into generating inaccurate or culturally inappropriate dish names. This paper presents a …
Analysis Theories On Artificial Intelligence, Chatgpt, Data Science, And Metaverse: The Case Of Digital Medicine, Yin Yang, Xingyun Liu, Jorge Luis Cuyubamba Dominguez, Yuan Fang, Wen Xie, Bairong Shen, Keng Siau
Analysis Theories On Artificial Intelligence, Chatgpt, Data Science, And Metaverse: The Case Of Digital Medicine, Yin Yang, Xingyun Liu, Jorge Luis Cuyubamba Dominguez, Yuan Fang, Wen Xie, Bairong Shen, Keng Siau
Research Collection School Of Computing and Information Systems
Healthcare organizations are increasingly adopting digital technologies, with Artificial Intelligence (AI), Data Science, and the metaverse driving significant advancements in smart healthcare. Al facilitates personalized medicine and efficient drug development, while Data Science enables predictive analytics and big data management, enhancing patient outcomes and healthcare quality. The metaverse introduces immersive training and telemedicine platforms, revolutionizing patient engagement and healthcare research. This study conducts' a scoping review of 6,171 articles, analyzing the transformational impact of AI, ChatGPT, Data Science, and the metaverse on healthcare. It highlights the benefits and risks of these technologies, identifies research gaps in their application within the …
Trajlens: Visual Analysis For Constructing Cell Developmental Trajectories In Cross-Sample Exploration, Qipeng Wang, Shaolun Ruan, Rui Sheng, Yong Wang, Min Zhu, Huamin Qu
Trajlens: Visual Analysis For Constructing Cell Developmental Trajectories In Cross-Sample Exploration, Qipeng Wang, Shaolun Ruan, Rui Sheng, Yong Wang, Min Zhu, Huamin Qu
Research Collection School Of Computing and Information Systems
Constructing cell developmental trajectories is a critical task in single-cell RNA sequencing (scRNA-seq) analysis, enabling the inference of potential cellular progression paths. However, current automated methods are limited to establishing cell developmental trajectories within individual samples, necessitating biologists to manually link cells across samples to construct complete cross-sample evolutionary trajectories that consider cellular spatial dynamics. This process demands substantial human effort due to the complex spatial correspondence between each pair of samples. To address this challenge, we first proposed a GNN-based model to predict cross-sample cell developmental trajectories. We then developed TrajLens, a visual analytics system that supports biologists in …