Digital Commons Network^™

Leveraging Large Language Models For Career Mobility Analysis: A Study Of Gender, Race, And Job Change Using Us Online Resume Profiles, Palakorn Achananuparp, Ye Xu, Yao Lu, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

We present a large-scale analysis of career mobility of college-educated U.S. workers using online resume profiles to investigate how gender, race, and job change options are associated with upward mobility. This study addresses key research questions of how the job changes affect their upward career mobility, and how the outcomes of upward career mobility differ by gender and race. We address data challenges – such as missing demographic attributes, missing wage data, and noisy occupation labels – through various data processing and Artificial Intelligence (AI) methods. In particular, we develop a large language models (LLMs) based occupation classification method known …

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 …

Generalized Visual Relation Detection With Diffusion Models, Kaifeng Gao, Siqi Chen, Hanwang Zhang, Jun Xiao, Yueting Zhuang, Qianru Sun

Research Collection School Of Computing and Information Systems

Visual relation detection (VRD) aims to identify relationships (or interactions) between object pairs in an image. Although recent VRD models have achieved impressive performance, they are all restricted to pre-defined relation categories, while failing to consider the semantic ambiguity characteristic of visual relations. Unlike objects, the appearance of visual relations is always subtle and can be described by multiple predicate words from different perspectives, e.g., “ride” can be depicted as “race” and “sit on”, from the sports and spatial position views, respectively. To this end, we propose to model visual relations as continuous embeddings, and design diffusion models to achieve …

Memoryart: Enhancing Llms Via Multi-Memory Models With Adaptive Resonance Theory For Healthcare Agents, Renke Dai, Hebin Hu, Jiahui Zhang, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Though promising in healthcare consultation applications, large language models (LLMs) face critical limitations in retaining and utilizing long-term memory across multiturn interactions. In particular, existing memory enhancing paradigms are constrained by limited context windows and embedding-based retrieval, often failing to maintain task relevance and still suffering from memory prototype collapse in multi-turn healthcare consultation. To address these challenges, we propose a cognitively-inspired memory framework named MemoryART, which is grounded in Adaptive Resonance Theory (ART)—a cognitive and learning theory of how humans and animals adapt to dynamic environments. MemoryART employs three memory modules—working memory, episodic memory, and semantic memory to support …

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 …

Paid Search Marketing Vs. Search Engine Optimization: Analytical Models Of Search Marketing Based On Search Engine Quality, Kai Li, Chunyang Shen, Mei Lin, Zhangxi Lin

Research Collection School Of Computing and Information Systems

As search engines are leading revenue growth in online marketing, search marketing has become a popular area of academic research. Although search engine advertising has interested researchers for decades and much has been learned, one thing that puzzles scholars is why search engine optimization companies are tolerated rather than excluded from the market, even though they capture a significant share of the advertising market. In this paper, we shed light on this phenomenon and establish an analytical model based on organic search quality. Through analysis of the model, we were able to draw several intriguing conclusions. First, there is no …

Security-Enhanced Decentralized Conditional Privacy-Preserving Authentication In Vanets, Suqin Luo, Xinghua Li, Yinbin Miao, Xuelin Cao, Zhan Zhang, Yunwei Wang, Deng R.H.

Research Collection School Of Computing and Information Systems

To ensure the legitimacy of communicators while ad dressing the privacy concerns of vehicles in vehicular ad-hoc networks (VANETs), conditional privacy-preserving authentication (CPPA) schemes have been proposed. Given that existing schemes suffer from single point of failure due to centralized authorities, several distributed CPPA schemes have been proposed. However, these schemes all ignore the tight cementation between system secret keys and the authority, which could be a serious threat to system security, that the compromised authority may leak the system secret key. To address these issues, we propose a security enhanced decentralized conditional privacy-preserving authentication (DCPPA) scheme. DCPPA first introduces …

Tempo: Training-Time Equilibration Of Modalities For Per-Sample Optimization In Multimodal Sentiment, Yi Zhao, Erik Cambria, Xiaosong E, Xianxun Zhu

Research Collection School Of Computing and Information Systems

Multimodal sentiment models often become over-reliant on the “easiest” modality (typically text), leading to three coupled sub-problems: (i) representation-level dominance, where weaker modalities contribute little to the fused representation; (ii) optimization-level dominance, where the strongest modality drives most gradient updates and suppresses learning in others; and (iii) robustness degradation, where audio or vision fail under noise or missing inputs at test time. We present TEMPO, a plug-and-play training framework that mitigates these issues by rebalancing learning pressure across modalities while leaving inference unchanged. For each mini-batch, TEMPO estimates relative modality strength and applies two synchronized, training-only controls: selective forward attenuation …

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 …

Look, Compare And Draw: Differential Query Transformer For Automatic Oil Painting, Lingyu Liu, Yaxiong Wang, Li Zhu, Lizi Liao, Zhedong Zheng

Research Collection School Of Computing and Information Systems

This work introduces a new approach to automatic oil painting that emphasizes the creation of dynamic and expressive brushstrokes. A pivotal challenge lies in mitigating the duplicate and common-place strokes, which often lead to less aesthetic outcomes. Inspired by the human painting process, i.e., observing, comparing, and drawing, we incorporate differential image analysis into a neural oil painting model, allowing the model to effectively concentrate on the incremental impact of successive brushstrokes. To operationalize this concept, we propose the Differential Query Transformer (DQ-Transformer), a new architecture that leverages differentially derived image representations enriched with positional encoding to guide the stroke …

Portfoliopilot: An Agentic Platform For Financial Portfolio Management Algorithm Development And Evaluation, Jared Chan Xu Yang, Haokai Ma, Yunshan Ma

Research Collection School Of Computing and Information Systems

Developing new portfolio-management algorithms typically demands substantial programming effort, limiting rapid experimentation and excluding finance professionals without coding skills. Current robo-advisory tools offer pre-built but rigid strategies, restricting customization and experimentation. We introduce PortfolioPilot, an open-source, agentic platform that enables users to generate bespoke portfolio through natural-language descriptions. Leveraging the Anthropic Claude API, PortfolioPilot dynamically synthesizes executable TypeScript algorithms that run in the frontend with security validation. The system integrates real-time backtesting with historical market data, classical optimization algorithms (Markowitz, LSTM, ARIMA), and interactive performance visualizations.

Potent But Stealthy: Rethink Profile Pollution Against Sequential Recommendation Via Bi-Level Constrained Reinforcement Paradigm, Jiajie Su, Zihan Nan, Yunshan Ma, Xiaobo Xia, Xiaohua Feng, Weiming Liu, Xiang Chen, Xiaolin Zheng, Chaochao Chen

Research Collection School Of Computing and Information Systems

Sequential Recommenders, which exploit dynamic user intents through interaction sequences, are vulnerable to adversarial attacks. While existing attacks primarily rely on data poisoning, they require large-scale user access or fake profiles, thus lacking practicality. In this paper, we focus on the Profile Pollution Attack that subtly contaminates partial user interactions to induce targeted mispredictions. Previous PPA methods suffer from two limitations, i.e., i) overreliance on sequence horizon impact restricts fine-grained perturbations on item transitions, and ii) holistic modifications cause detectable distribution shifts. To address these challenges, we propose a constrained reinforcement driven attack CREAT that synergizes a bi-level optimization framework …

Nondeterministic Polynomial-Time Problem Challenge: An Ever-Scaling Reasoning Benchmark For Llms, Chang Yang, Ruiyu Wang, Junzhe Jiang, Qi Jiang, Qinggang Zhang, Yanchen Deng, Shuxin Li, Shuyue Hu, Bo Li, Florian T. Pokorny, Xiao Huang, Xinrun Wang

Research Collection School Of Computing and Information Systems

Reasoning is the fundamental capability of large language models (LLMs). Due to the rapid progress of LLMs, there are two main issues of current benchmarks: i) these benchmarks can be crushed in a short time (less than 1 year), and ii) these benchmarks may be easily hacked. To handle these issues, we propose the ever-scalingness for building the benchmarks which are scaling over complexity against crushing, instance against hacking and exploitation, oversight for easy verification, and coverage for real-world relevance. This paper presents Nondeterministic Polynomial-time Problem Challenge (NPPC), an ever-scaling reasoning benchmark for LLMs. Specifically, the NPPC has three main …

Evaluating Large Language Models For Line-Level Vulnerability Localization, Jian Zhang, Chong Wang, Anran Li, Weisong Sun, Cen Zhang, Wei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

Recently, Automated Vulnerability Localization (AVL) has attracted growing attention, aiming to facilitate diagnosis by pinpointing the specific lines of code responsible for vulnerabilities. Large Language Models (LLMs) have shown potential in various domains, yet their effectiveness in line-level vulnerability localization remains underexplored. In this work, we present the first comprehensive empirical evaluation of LLMs for AVL. Our study examines 19 leading LLMs suitable for code analysis, including ChatGPT and multiple open-source models, spanning encoder-only, encoder-decoder, and decoder-only architectures, with model sizes from 60M to 70B parameters. We evaluate three paradigms including few-shot prompting, discriminative fine-tuning, and generative fine-tuning with and …

Interpretable Multimodal Zero Shot Ecg Diagnosis Via Structured Clinical Knowledge Alignment, Jialu Tang, Hung Manh Pham, Ignace De Lathauwer, Henk S. Schipper, Yuan Lu, Dong Ma, Aaqib Saeed

Research Collection School Of Computing and Information Systems

Electrocardiogram (ECG) interpretation is essential for cardiovascular disease diagnosis, but current automated systems often struggle with transparency and generalization to unseen conditions. To address this, we introduce ZETA, a zero-shot multimodal framework designed for interpretable ECG diagnosis aligned with clinical workflows. ZETA uniquely compares ECG signals against structured positive and negative clinical observations, which are curated through an LLM-assisted, expertvalidated process, thereby mimicking differential diagnosis. Our approach leverages a pre-trained multimodal model to align ECG and text embeddings without disease-specific fine-tuning. Empirical evaluations demonstrate ZETA’s competitive zero-shot classification performance and, importantly, provide qualitative and quantitative evidence of enhanced interpretability, grounding …

Stock Market Reactions To Interest Rate Changes: Evidence From Emerging Markets, Binali Selman Eren

The Indonesian Capital Market Review

This study investigates the impact of interest rate decisions made by national central banks, including the Federal Reserve (Fed), and the European Central Bank (ECB), on the stock markets of emerging economies. It analyzed stock market reactions to interest rate hikes and cuts through the use of an event study approach. The findings provided evidence of heterogeneous effects of interest rate decisions by national central banks, the Fed, and the ECB on stock markets in emerging economies. Specifically, the results indicated that, in most emerging economies, stock markets reacted negatively to interest rate hikes and positively to cuts by national …

The Impact Of Shariah Law, Liquidity And Interest Rate On Sukuk Growth In Malaysia In Short And Long Run: The Ardl Estimation, Dheya Hamood Saif Al-Fakih, Shahsuzan Zakaria, Md Khairu Amin Ismail

The Indonesian Capital Market Review

The issuance of sukuk has been steadily increasing over time, underscoring its growing significance and the need for further scholarly examination. As a global leader in the Islamic finance industry and a prominent issuer of sukuk, Malaysia serves as a critical case study for understanding this phenomenon. It is essential to investigate various factors and their impact on the growth of sukuk. The study analyzes the relationship between sukuk growth and factors such as interest rate, liquidity (M1), and Shariah law using monthly data from April 2011 to December 2020 obtained from Thomson Reuters Eikon. The study employs the ARDL …

Awareness And Decision-Making In Cryptocurrency Investment Among Students In Guwahati: A Comprehensive Study, Rituparna Roy Dr, Anupam Chanda Dr, Bidangsha Basumatary

The Indonesian Capital Market Review

This study investigates the awareness and decision-making processes related to cryptocurrency investment among students in Guwahati, Assam. Cryptocurrency, a form of digital money designed for online transactions without government or bank oversight, has initiated significant shifts in the global financial sector. The decentralization of cryptocurrencies offers transparency, security, and efficiency, challenging traditional financial systems. Despite the growing global interest in cryptocurrencies, their adoption faces barriers such as limited technological expertise, regulatory uncertainty, and security concerns. These issues are particularly pronounced among students, a demographic increasingly interested in digital currencies but often lacking foundational financial knowledge. The research aims to fill …

Identifying Risk-Free Asset Proxies In Companies Listed On The Indonesia Stock Exchange From 2017 To 2023 Using The Zero-Beta Capital Asset Pricing Model, Fajri Alan Ghazali Mr., Lenny Suardi Mrs.

The Indonesian Capital Market Review

This study evaluates Bank Indonesia Certificates (SBI), IndONIA, and gold as zero-beta proxies for Indonesian equities. Using daily returns for 213 firms listed on the Indonesia Stock Exchange (2017–2023) and the Jakarta Composite Index as the market return, we estimate firm-level zero-beta CAPMs and compute Wald statistics test to identify the appropriate risk- free asset proxy for each individual company; and firm-level outcomes are then aggregated under a Bernoulli/Binomial criterion with a 95% threshold. Empirical results show that gold satisfies the zero-beta condition for 207 of 213 firms (97.18%), whereas SBI and IndONIA satisfy it for five (2.35%) and six …

Escaping The Crash? The Protective Power Of Liquidity In The Pakistan Stock Market, Sana Saleem, Muhammad Usman, Amna Rafique

The Indonesian Capital Market Review

This study investigates the effect of stock liquidity on the risk of stock price crashes, taking sample of non-financial firms listed on the Pakistan Stock Exchange, from 2009 to 2024. A two-step system GMM estimation is applied to test the hypotheses. The results reveal that greater stock liquidity significantly reduces crash risk, whereas illiquidity amplifies it. Two underlying channels explain this relationship; first, liquidity strengthens block holders’ capacity to intervene, discouraging managerial tendencies to withhold adverse information, second, liquidity enhances price informativeness, limiting managerial discretion to manipulate prices through delayed disclosure of bad news. The findings imply that liquid stocks …

Green Credit, Climate Risk, And Credit Risk In The Indonesian Banking Industry, Titi Dewi Warninda, Shelby Devianty Widodo

The Indonesian Capital Market Review

As the largest archipelagic country, Indonesia's industries and regions are particularly vulnerable to the impacts of climate change. This research examines the effects of green credit policy and climate risk, specifically sea level rise and precipitation, on bank credit risk. Using data from 2019 to 2023 and system GMM, the research results show that the higher the sea level rise and precipitation, the higher the credit risk. The findings of this research also indicate that a higher proportion of green credit lowers bank credit risk, and bank inefficiency strengthens the impact of green credit on credit risk. The results of …

Pedagogical Readiness And Adaptability In Higher Education In Egypt: An Exploration Of Generational Disparities In Ai Adoption., Maha Ahmed Zaki Dajani, Israa Lewaa, Hadia Fakhreldin

Business Administration

ABSTRACT

Dajani, M., LewaaElhamd, I., & FakhrEldin, H. (2025). Pedagogical readiness and adaptability in higher education in Egypt: An exploration of generational disparities in AI adoption. In Conference proceedings for the Annual Conference of Business, Economics and Politics in the Middle East (BEP-ME) 2025 (pp. 96,116). The British University in Egypt.

This study investigates generational differences in the adoption of AI tools in Egyptian higher education, examining how pedagogical readiness and adaptability influence engagement among students and educators. It addresses a key gap in the literature—the lack of an integrated pedagogical framework combining Kolb’s Experiential Learning Theory and Constructivist …

Potential Fiscal Stability Effects Of The African Continental Free Trade Area: An Empirical Analysis, Simon Abendin, Duan Pingfang, Umer Shahzad

Journal of African Trade

This study analyzes the potential effects of the African Continental Free Trade Area (AfCFTA) on fiscal stability, using panel data from 54 African economies that have ratified the AfCFTA from 2010 to 2021. The study uses a dynamic system GMM model to address endogeneity, simultaneity, measurement bias, and reverse causality issues. The findings indicate that the AfCFTA agreement may reduce government revenue and spending. Furthermore, the study found that the AfCFTA could lead to an increase in government debt

The Price Of Precision: Financial Insights From A Robotic Nephrectomy Transition, Jill M. Knolle Msw, Mph, Aiden Tobin, George Rofaiel Md

Department of Surgery

No abstract provided.

Designing For Trust, Transparency, And Public Understanding: Insights From Paul (The Polling Monitor), Stacia Tipton

Theses and Dissertations

Americans are curious about each other, despite the shouting matches, polarizing news and political ads made to outrage. When given the chance to find out what their fellow citizens think, most people take it. Traditional polling formats, including the industry's routine charts, percentages, findings and crosstabs, report what the public thinks, but they rarely facilitate a conversation or the understanding that might follow. This thesis asks whether better design can change that: can public opinion polling be more than descriptive statistics…. can it facilitate understanding across lines of difference?

Specifically, this project asks whether a better-designed presentation of polling data …

Angle-Based Formation Stabilization And Maneuvers In Port-Hamiltonian Form With Bearing And Velocity Measurements, Ningbo Li, Pablo Borja, Arjan Van Der Schaft, Jacquelien M.A. Scherpen

School of Engineering, Computing and Mathematics

This paper proposes a port-Hamiltonian approach for angle-based formation stabilization and maneuvers using bearing and velocity measurements with an underlying triangulated Laman graph. The corresponding port-Hamiltonian controller is designed using virtual couplings on the errors of angle constraints in angle space. Then, the angle constraints and agent actuators are mapped by the constraint Jacobian, which can be applied to other formation constraints. In addition, to avoid unavailable distance terms in the control law, an estimator is designed based on port-Hamiltonian theory and the property that energy is coordinate-free for different sensor modalities using bearing and velocity measurements, which permits our …

Children And Adults Across 15 Countries Believe In Human Uniqueness Of Mind: A Cross-Cultural Investigation Of Cross-Species Mind Perception, Karri Neldner, Luke Maurits, Magie Junker, Lara Abbas, Nayrouz Abbas, Arianna Abis, Federica Amici, Bernardo Arroyo-Garcia, Negar Asghari, Giovanna Barragán Pardo, Zhen Zhang, Junior Peña Chumacero, Ardain Dzabatou, Dustin Eirdosh, Susan Hanisch, Tom Herrnsdorf, Tom Hovehne, Alicia Junker, Patricia Kanngiesser, Felipe Villa Larens, Safaa Mahmoud, Sandra Masaquiza, Iino Masato, Risma Illa Maulany, Tongtong Meng, Kardelen Mutlu, Putu Oka Ngakan, Ebru Peközer, Ljubica Petrović, Mirella Christy Rehatalanit

School of Psychology

The way humans relate to other animals is fundamentally shaped by whether we perceive ourselves as unique, with feelings and thoughts not shared by other animals. How beliefs about animals’ ability to feel and think develop across cultures remains largely unexplored. We asked children and adolescents (4–17 years, N = 1025) and adults (N = 190) from 33 urban and rural communities across 15 countries whether animals have thoughts or feelings (judgments of presence), and whether those thoughts or feelings are human-like (judgments of similarity). Bayesian analyses revealed that participants generally ascribed non-human animals the ability for thoughts and feelings. …

A Randomized Controlled Trial In A Teaching Hospital Comparing The Outcomes Of ‎Single-Layer Versus Double-Layer Uterine Suturing With Polyglactin In The Development ‎Of Uterine Niche Following Caesarean Section, Ahmed A. Kassab, Ali E. Khayal

Journal of Medicine in Scientific Research

Background Caesarean section (CS) rates are rising globally, with Egypt reporting one of the highest rates. A potential complication of CS is the development of a uterine scar defect, or niche, which may be associated with abnormal bleeding, dysmenorrhea, and infertility. The technique of uterine closure may play a significant role in the prevention of niche formation. Aim To evaluate the effectiveness of double-layer uterine closure versus single-layer closure in preventing niche formation after a first CS, as assessed by transvaginal ultrasound (TVUS) at six weeks postpartum. Methods This randomized controlled trial was conducted at Mataryia Teaching Hospital, Cairo, including …

Prevalence Of Diabetic-Nephropathy In Children And Adolescents With Type-One- Diabetes Mellitus: A Recent Perspective, Randa Mohamed Darwish, Ayat Ibrahim Ghanem, Jehan Ibrahim Altohamy, Dina Mahmoud Khalifa

Journal of Medicine in Scientific Research

Background Among the most important microvascular complications in Type-one-Diabetes Mellitus (T-1-DM) in adolescents and children, Diabetic-nephropathy (DN) stands high. Early detection is crucial to prevent its progress to chronic kidney disease. Objective This study was designed aiming at the elaboration of an updated prevalence for Diabetic-nephropathy and to identify the risk factors among pediatric patients age group with T-1-DM . Methods The present cross-sectional-study was conducted starting from September 2023 to September 2025 including a group of 100 cases of adolescents and children with T-1- DM (aged 5–16 years) and 100-matched age and sex healthy control group. Clinical evaluation included …

Effectiveness Of Interferential Stimulation And Anorectal Neuromuscular Electrical Stimulation On Secondary Encopresis In Children: A Comparative Randomized Controlled Clinical Trial, Seham M. Abd El-Moghny, Mohamed I. Elsepaee, Abdelaty Alghonimy, Rabab S. Mohamed

Journal of Medicine in Scientific Research

Background Encopresis, fecal soiling is often secondary to functional constipation and retention. It is significantly impact a child's psychological health as it can result in feelings of shame, social isolation, and low self-esteem and negatively affect their quality of life and their families. Objective To evaluate and compare the efficacy and safety of interferential stimulation (IF) applied on sigmoid colon and anorectal neuromuscular electrical stimulation (NMES), in combination with behavioral therapy and pelvic floor muscle training (PFMT), in improving continence outcomes in children with secondary encopresis refractory to laxatives. Methods In this comparative randomized controlled clinical trial, 30 children (5–10 …