Digital Commons Network^™

Leakage-Resilient Easily Deployable And Efficiently Searchable Encryption (Edese), Jiaming Yuan, Yingjiu Li, Jun Li, Daoyuan Wu, Jianting Ning, Yangguang Tian, Robert H. Deng

Research Collection School Of Computing and Information Systems

Easily Deployable and Efficiently Searchable Encryption (EDESE) is a cryptographic primitive designed for practical searchable applications, offering efficient search and easy deployment. However, it remains vulnerable to Leakage-Abuse attacks, allowing adversaries to exploit keyword-matching processes to extract sensitive information. To address these vulnerabilities, we introduce Leakage-Resilient EDESE (LR-EDESE) with k-indistinguishability and controlled leakage functions. We then propose Volume Leakage-Resilient EDESE (VLR-EDESE), a new scheme to protect against both query and document volume leakage. Our experimental results demonstrate that at k = 5000 (maximum security setting), VLR-EDESE incurs an overhead of 63× compared to the baseline EDESE without leakage protection, outperforming …

Diversity Optimization For Travelling Salesman Problem Via Deep Reinforcement Learning, Qi Li, Zhiguang Cao, Yining Ma, Yaoxin Wu, Yue-Jiao Gong

Research Collection School Of Computing and Information Systems

Existing neural methods for the Travelling Salesman Problem (TSP) mostly aim at finding a single optimal solution. To discover diverse yet high-quality solutions for Multi-Solution TSP (MSTSP), we propose a novel deep reinforcement learning based neural solver, which is primarily featured by an encoder-decoder structured policy. Concretely, on the one hand, a Relativization Filter (RF) is designed to enhance the robustness of the encoder to affine transformations of the instances, so as to potentially improve the quality of the found solutions. On the other hand, a Multi-Attentive Adaptive Active Search (MA3S) is tailored to allow the decoders to strike a …

An Efficient Diffusion-Based Non-Autoregressive Solver For Traveling Salesman Problem, Mingzhao Wang, You Zhou, Zhiguang Cao, Yubin Xiao, Xuan Wu, Wei Pang, Yuan Jiang, Hui Yang, Peng Zhao, Yuanshu Li

Research Collection School Of Computing and Information Systems

Recent advances in neural models have shown considerable promise in solving Traveling Salesman Problems (TSPs) without relying on much hand-crafted engineering. However, while non-autoregressive (NAR) approaches benefit from faster inference through parallelism, they typically deliver solutions of inferior quality compared to autoregressive ones. To enhance the solution quality while maintaining fast inference, we propose DEITSP, a diffusion model with efficient iterations tailored for TSP that operates in a NAR manner. Firstly, we introduce a one-step diffusion model that integrates the controlled discrete noise addition process with self-consistency enhancement, enabling optimal solution prediction through simultaneous denoising of multiple solutions. Secondly, we …

Information Bottleneck‑Guided Mlps For Robust Spatial‑Temporal Forecasting, Min Chen, Guansong Pang, Wenjun Wang, Cheng Yan

Research Collection School Of Computing and Information Systems

Spatial-temporal forecasting (STF) plays a pivotal role in urban planning and computing. Spatial-Temporal Graph Neural Networks (STGNNs) excel at modeling spatial-temporal dynamics, thus being robust against noise perturbations. However, they often suffer from relatively poor computational efficiency. Simplifying the architectures can improve efficiency but also weakens robustness with respect to noise interference. In this study, we investigate the problem: can simple neural networks such as Multi-Layer Perceptrons (MLPs) achieve robust spatial-temporal forecasting while remaining efficient? To this end, we first reveal the dual noise effect in spatial-temporal data and propose a theoretically grounded principle termed Robust Spatial-Temporal Information Bottleneck (RSTIB), …

Quantum Technologies In Decentralisation, Paul Robert Griffin, Rudy Raymond, Tsuyoshi Idé

Research Collection School Of Computing and Information Systems

Quantum technologies, rooted in the manipulation of quantum information, are revolutionizing computing and networking domains. Their impact on blockchains and decentralized systems is twofold. While much attention has been given to the potential of quantum computing to attack blockchains, these advanced technologies also offer avenues for strengthening and optimizing them. This chapter delves into the intricacies of quantum technologies, from the foundational concepts of qubits, quantum gates, and quantum networks to their implications for blockchains. We explore both the vulnerabilities of blockchains in a quantum-dominant era and the promising solutions quantum technologies provide, culminating in a use case examining their …

Finir: The 2nd Workshop On Financial Information Retrieval In The Era Of Generative Ai, Fengbin Zhu, Yunshan Ma, Fuli Feng, Chao Wang, Huanbo Luan, Guangnan Ye, Shuo Zhang, Dhagash Mehta, Pingping Chen, Bing Xiang, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Recent advancements in Generative AI, such as Large Language Models (LLMs), have demonstrated remarkable success across various general tasks. Extensive studies have explored leveraging generative models in finance, but significant challenges persist. This half-day workshop explores potential approaches and research directions to address these challenges by equipping generative models with advanced Information Retrieval (IR) models. Specifically, this workshop seeks to provide a platform for discussing innovative ideas that facilitate the advancement of IR technology to enrich generative models in finance from four key perspectives: (i) financial IR techniques (ii) financial IR benchmarking and evaluation (iii) financial systems and agents/assistants (iv) …

Fashiondpo: Fine‑Tune Fashion Outfit Generation Model Using Direct Preference Optimization, Mingzhe Yu, Yunshan Ma, Lei Wu, Changshuo Wang, Xue Li, Lei Meng

Research Collection School Of Computing and Information Systems

Personalized outfit generation aims to construct a set of compatible and personalized fashion items as an outfit. Recently, generative AI models have received widespread attention, as they can generate fashion items for users to complete an incomplete outfit or create a complete outfit. However, they have limitations in terms of lacking diversity and relying on the supervised learning paradigm. Recognizing this gap, we propose a novel framework FashionDPO, which fine-tunes the fashion outfit generation model using direct preference optimization. This framework aims to provide a general fine-tuning approach to fashion generative models, refining a pre-trained fashion outfit generation model using …

What Are Anomalies In A Network?, Kai Ming Ting, Zhong Zhuang, Guansong Pang, Zongyou Liu, Tianrun Liang, Qiuran Zhao

Research Collection School Of Computing and Information Systems

This article examines a collection of assumptions used in the current literature on node anomaly detection in a network. The examination raises the question: What are anomalies in a network? Our attempt to answer this question has provided some interesting findings and led to some open questions. This is the first article which formally defines anomalies in a network and introduces the concept of self-verifiability of a detector without ground-truths in a network. They enable existing detectors to be categorized into two types along the line whether they are self-verifiable or not. We suggest a method to evaluate self-verifiable detectors …

Cracking Aegis: An Adversarial Llm-Based Game For Raising Awareness Of Vulnerabilities In Privacy Protection, Jiaying Fu, Yiyang Lu, Zehua Yang, Fiona Fui-Hoon Nah, Ray Lc

Research Collection School Of Computing and Information Systems

Traditional methods for raising awareness of privacy protection often fail to engage users or provide hands-on insights into how privacy vulnerabilities are exploited. To address this, we incorporate an adversarial mechanic in the design of the dialogue-based serious game Cracking Aegis. Leveraging LLMs to simulate natural interactions, the game challenges players to impersonate characters and extract sensitive information from an AI agent, Aegis. A user study (n=22) revealed that players employed diverse deceptive linguistic strategies, including storytelling and emotional rapport, to manipulate Aegis. After playing, players reported connecting in-game scenarios with real-world privacy vulnerabilities, such as phishing and impersonation, and …

Exploring The Capabilities Of Llms For Code-Change-Related Tasks, Lishui Fan, Jiakun Liu, Zhongxin Liu, David Lo, Xin Xia, Shanping Li

Research Collection School Of Computing and Information Systems

Developers deal with code-change-related tasks daily, e.g., reviewing code. Pre-trained code and code-change-oriented models have been adapted to help developers with such tasks. Recently, large language models (LLMs) have shown their effectiveness in code-related tasks. However, existing LLMs for code focus on general code syntax and semantics rather than the differences between two code versions. Thus, it is an open question how LLMs perform on code-change-related tasks.To answer this question, we conduct an empirical study using 1B parameters LLMs on three code-change-related tasks, i.e., code review generation, commit message generation, and just-in-time comment update, with in-context learning (ICL) and parameter-efficient …

Explaining Explanations: An Empirical Study Of Explanations In Code Reviews, Ratnadira Widyasari, Ting Zhang, Abir Bouraffa, Walid Maalej, David Lo

Research Collection School Of Computing and Information Systems

Code reviews are central for software quality assurance. Ideally, reviewers should explain their feedback to enable authors of code changes to understand the feedback and act accordingly. Different developers might need different explanations in different contexts. Therefore, assisting this process first requires understanding the types of explanations reviewers usually provide. The goal of this article is to study the types of explanations used in code reviews and explore the potential of Large Language Models (LLMs), specifically ChatGPT, in generating these specific types. We extracted 793 code review comments from Gerrit and manually labeled them based on whether they contained a …

How Are We Detecting Inconsistent Method Names? An Empirical Study From Code Review Perspective, Kisub Kim, Xin Zhou, Dongsun Kim, Julia Lawall, Kui Liu, Tegawendé F. Bissyandé, Jacques Klein, Jaekwon Lee, David Lo

Research Collection School Of Computing and Information Systems

Proper naming of methods can make program code easier to understand, and thus enhance software maintainability. Yet, developers may use inconsistent names due to poor communication or a lack of familiarity with conventions within the software development lifecycle. To address this issue, much research effort has been invested into building automatic tools that can check for method name inconsistency and recommend consistent names. However, existing datasets generally do not provide precise details about why a method name was deemed improper and required to be changed. Such information can give useful hints on how to improve the recommendation of adequate method …

Can Esg Reduce Credit Risk? An Empirical Investigation Across Asean-5 Markets, Arrafif Pratama Zaini, Maria Ulpah

The Indonesian Capital Market Review

Based on stakeholder theory and signaling theory, companies with strong ESG performance send signals to various stakeholders, thus building trust and influencing better credit risk evaluation. This study empirically examines the effect of Environmental, Social, and Governance (ESG) performance on the credit risk of non-financial public companies in ASEAN-5 countries (Indonesia, Malaysia, Philippines, Singapore, and Thailand) over the period 2019-2023. Corporate credit risk is measured using 2 main approaches: the accounting-based and market-based models. Merton's KMV model calculates the probability of default (PD) using a market-based approach. In contrast, the Altman Z-Score predicts bankruptcy risk based on financial ratios in …

Personal Bankruptcy: A Bibliometric Analysis And Future Research Directions, Aqilah Nadiah Md Sahiq, Saida Farhanah Sarkam, Putri Aliah Mohd Hidzir, Nurwahida Yaakub, Shafinar Ismail, Nurbaity Sabri, Hanifiyah Yuliatul Hijriah, Himmatul Kholidah

The Indonesian Capital Market Review

Personal bankruptcy is a pertinent topic to discuss due to the surge in personal bankruptcy cases around the world and it is an important indicator of household financial problems nationally. However, only few comprehensive reviews have been conducted to date. Hence, this study provides a bibliometric review of 210 studies on personal bankruptcy authored by 496 scholars. Bibliographical data were extracted from the Scopus database and analyzed it using the Bibliometrix-R software. Based on the citation analysis metrics, we revealed the most influential articles, journals, authors, and institutions. Using the network and conceptual structure analysis, we identified three underlying research …

The Impact Of Effective Tax Rate And Cash Effective Tax Rate On The Capital Structure, Nguyen Vinh Khuong Dr., Tran Thao Vy, Nguyen Phuong Anh, Pham Thi Anh Hong, Bui Thi Ngoc Trinh, Cao Phuong Uyen

The Indonesian Capital Market Review

The study examines the impact of tax avoidance on the capital structure of listed companies on the Vietnam’s stock market. Conducting GLS regression testing and analysis through data of 657 enterprises listed on the two stock exchanges of Hanoi and Ho Chi Minh City in the period from 2015 to 2022. Research results have shown that initially, when businesses carry out tax avoidance, it will reduce the capital structure of the business because the marginal benefits received from tax avoidance are lower than the marginal costs from tax avoidance. However, after businesses carry out tax avoidance and the benefits from …

Earnings Management In Borsa Istanbul During Seasoned Equity Offerings, Mahmoud Ashour, Asuman Atik

The Indonesian Capital Market Review

To increase share prices during the issuance of seasoned equity shares, firms may be motivated to boost earnings through earnings management, particularly just before the offering. This study examines the earnings management practices of non-financial firms listed in Borsa Istanbul and surrounding seasoned equity offerings. Using the cross-sectional Modified Jones and Roychowdhury (2006) models, both accrual-based and real earnings management practices were analyzed from 2005 to 2018. The sample consists of 120 rights offerings within the research period. The results indicate that firms listed on Borsa Istanbul did not engage in earnings management the year before the offering. Instead, earnings …

Underpricing Of The Malaysian Initial Public Offerings (Ipos), Wahidah Shari

The Indonesian Capital Market Review

This study evaluates the short-term performance of 469 Malaysian IPOs between 2002 and 2020. Previous studies have found that IPOs are underpriced in the short-term yet underperform in the long term. The short-term underpricing describes the phenomenon characterized by a significant increase from the offer price to the first day of closing price. The finding shows that Malaysian IPOs are significantly underpriced by 24.6% using offer-to-close return (OTC), which confirms the findings reported in previous literature. Separating OTC to offer-to-ask (OTA) and ask-to-close (ATC) indicates that a significant positive return is observed only in the OTA period but not in …

Duration Of Inter-Pregnancy Interval And Its Predictors Among A Sample Of Pregnant Women In Reproductive Age Attending Primary Health Care Centers In Al-Russafa /Al-Shaab Sector, Russul Mohammed, Huda Habib

Iraqi Postgraduate Medical Journal

Background: Inter-pregnancy interval is defined as the time in completed months from the reported date of live birth of the previous child to the self-reported last normal menstrual period.Study objectives: To assess the duration of inter-pregnancy interval, and to assess the possible predictors associated with the duration of inter-pregnancy interval.Participants & Methods: A cross-sectional study was carried out during the period from 1st March to 1st August 2023. A convenient sample of pregnant women in the reproductive age group (15-49 years) who attended PHCCS in Al-Shaab sector, Baghdad-Alrusafa Health Directorate. Data was collected by direct interviews with the target population, …

Level Of Awareness About Diabetic Retinopathy And Eye Checkup Practice Among Type 2 Diabetic Patients Attending Baghdad Teaching Hospital 2023., Ali Olaiwei, Mohammed Ibrahim

Iraqi Postgraduate Medical Journal

Background: Diabetic retinopathy is a common and serious complication of diabetes that can lead to vision loss or even blindness if not detected and treated early. However, some people may not have any symptoms until the condition is advanced. Therefore, regular eye exams with dilated pupils are recommended for people with diabetes to check for signs of diabetic retinopathy and other eye problems regardless of the symptoms.Objectives of the study: To measure patients’ awareness and practices regarding diabetic retinopathy, to detect the barriers for eye screening and receiving eye check-up, and to find if there is any association between level …

Intracerebral Hemorrhage In Covid-19: A Case Series Study, Naqa'a Al-Zubaidi, Hasan Al-Hamadani

Iraqi Postgraduate Medical Journal

Background:SARS-CoV can cause dysfunction of multiple organs and systems. Cardiovascular complications after COVID-19 have now been reported very often but the knowledge of neurovascular complications especially Intracerebral hemorrhage is undetermined. Aim of the study: To describe the natural history of acute Intracranial Hemorrhage (ICH) in COVID-19 patients.Patients and Methods:A case series study was performed at Al-Imamain Al-Kadhimain medical city and Saad Alwitry Hospital for Neuroscience in 2021.Result: Twenty patients with ICH were included in this study, 12 (60%) participants were males while females were 8 (40%) participants with mean age of 54.38±10.51 years; 10 (50%) patients had high systolic & …

Medico-Legal Study Of Sudden Death Among People Younger Than 40 Years In Baghdad, Kauthar Maree, Saad Kareem

Iraqi Postgraduate Medical Journal

Background: Sudden death is a significant global public health concern affecting individuals under 40. Understanding sudden death dynamics is crucial for addressing health and legal implications. Exploring epidemiology, causes, and risk factors is essential for implementing preventive measures, healthcare policies, and forensic practices.Objective: To identify the causes of sudden death among individuals under 40 in Baghdad. To assess the impact of lifestyle and family history contributions and examine the patterns of age, sex, and gender in sudden death cases within this particular demographic group.Methods: A cross-sectional study was conducted on 69 medico-legal cases involving individuals under the age of 40 …

Genu Valgum Relation With Sociodemographic Factors In A Sample Of Iraqi Children Attending Sadr Al Qanat Center For Prosthetics And Orthotics, Abdulnasser Mohammed, Faiq Gorial

Iraqi Postgraduate Medical Journal

Background: Genu valgum is a deformity resulting from the separation of ankles, when the medial faces of the knees are in contact while the person is in anatomical position, the patella and the hallux turning to the anterior direction.Aim: To evaluate the features of genu valgum and associated sociodemographic factors in children.Patients and methods: A cross-sectional study was conducted at Sader Al-Qanat Center for Prosthetics and Orthotics, a tertiary referral center in Baghdad/Iraq during the period from January to December 2022. A convenient sampling method was adopted to enrol 60 patients aged 2-14 years with genu valgum who attained the …

Detection Of Thyroid Antibodies In Non Segmental Vitiligo Patients And Using As Screening Test To Autoimmune Thyroid Disease, Mariam Abd-Al Hussein

Iraqi Postgraduate Medical Journal

Background:Vitiligo is chronic autoimmune disease characterized by pale white patches developing on the skin caused by lack of melanin pigment which produced by melanocytes. Most common autoimmune disease association with vitiligo is autoimmune thyroid disease that characterized by presence of autoantibody (anti-thyroperoxidase, anti-thyroglobulin) in serum of vitiligo patients. Aim of study:Detection of serum anti-thyroperoxidase and anti-thyroglobulin antibodies in patients with non-segmental vitiligo.Subject and Methods:Serum level of Anti-thyroperoxidase and anti-thyroglobulin antibodies were assessed in 50 non segmental vitiligo patients in the dermatology Consultation Clinic of IMAM ALSADIQ Teaching Hospital / Babil Health Directorate compare with 30 apparently healthy control, their age …

Examination Of An Experimental Paradigm Of Impaired Control Over Alcohol Use, Emily K. Junkin

Psychology Theses & Dissertations

Alcohol use disorders peak during young adulthood with nearly 27% of individuals aged 18 to 30 meeting diagnostic criteria. Impaired control, or difficulty limiting alcohol use, has been identified as one of the earliest symptoms of an alcohol use disorder and is predictive of alcohol use severity. Despite the relevance of impaired control for identifying and preventing hazardous drinking behaviors, there is a dearth of research that exists on this critical risk factor. The current study tested an experimental paradigm of impaired control whereby participants self-administered alcohol following guidelines to limit consumption to a low level. It was hypothesized that …

Towards Efficient Privacy-Preserving Deep Learning: He-Friendly Structures, Flexible Pruning, He-Efficient Architectures, And Secure Transformer Token Drop, Yifei Cai

Electrical & Computer Engineering Theses & Dissertations

Deep learning (DL) has become a powerful tool for solving complex problems, but developing DL models typically requires vast datasets, high computational resources, and expert knowledge—barriers that limit accessibility. Machine Learning as a Service (MLaaS) addresses this challenge by allowing resource-rich providers to deliver pre-trained DL models as services. However, privacy concerns arise: clients hesitate to share sensitive data, while providers protect their proprietary models. To address this, privacy-preserving MLaaS integrates cryptographic techniques into DL computations, as seen in frameworks like Cryptonets, SecureML, GAZELLE, CrypTFlow2, Cheetah, and BOLT. Among them, Homomorphic Encryption (HE) enables computation on encrypted data but remains …

Connecting Children With Artists Through A Children's Art History Book, Katie Meyer

Theses

This project is a children’s art history book that is set in an art museum. The goal of the book is to help children connect with Contemporary artists and their art. A museum setting is utilized to introduce children to museums and as an appropriate environment for viewing art. The theme of the exhibit that will be presented in the book is titled the “Innovators Exhibit.” This exhibit features six Contemporary artists from different art styles/mediums. The artists come from diverse backgrounds to expose children to a variety of cultures. Thought provoking questions will also be asked throughout the book …

Ms4 Swmpp 2025, National Technology & Engineering Solutions Of Sandia, Llc (Ntess) And Department Of Energy (Doe)

Municipal Separate Storm Sewer System (MS4) Permit

Stormwater discharges from Sandia National Laboratories/New Mexico (SNL/NM) are eligible for coverage under the National Pollutant Discharge Elimination System (NPDES) Municipal Separate Storm Sewer System (MS4) Permit. This Stormwater Management Plan (SWMP) was prepared by National Technology and Engineering Solutions of Sandia (NTESS) for the Department of Energy (DOE) National Nuclear Security Administration (NNSA) Sandia Field Office (SFO), owner of SNL/NM, located in Albuquerque, NM.

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Ziad Khalifa, Kyrillos Selim, Amira Ali, Sameh Abdellatif

Chemical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)- based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a …

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Ziad Khalifa

Chemical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)- based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a …

Evaluation Of Snap-Ed New Mexico’S Pilot “I Choose H2o” Campaign To Increase Water Consumption, Theresa H. Cruz, Mahtab Soleimani, Camille R. Velarde, Belinda E. Vicuna

Reports & Documents

The “I Choose H2O” campaign is a school-based pilot initiative developed by the University of New Mexico Prevention Research Center with SNAP-Ed NM funding from the USDA. Designed as a three-week social marketing effort, the campaign aimed to increase daily water consumption and reduce intake of sugar-sweetened beverages (SSBs) among middle school students. The campaign engaged students and staff through activities such as water challenges, events, tastings, and prize incentives, while also encouraging broader school-level policy, systems, and environmental (PSE) changes.

This evaluation used direct observation before and after implementation to assess changes in water fountain usage and lunchtime beverage …