Physical Sciences and Mathematics Commons^™

Mitigating Fine-Grained Hallucination By Fine-Tuning Large Vision-Language Models With Caption Rewrites, Lei Wang, Jiabang He, Shenshen Li, Ning Liu, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have shown remarkable performance in natural language processing (NLP) tasks. To comprehend and execute diverse human instructions over image data, instruction-tuned large vision-language models (LVLMs) have been introduced. However, LVLMs may suffer from different types of object hallucinations. Nevertheless, LVLMs are evaluated for coarse-grained object hallucinations only (i.e., generated objects non-existent in the input image). The fine-grained object attributes and behaviors non-existent in the image may still be generated but not measured by the current evaluation methods. In this paper, we thus focus on reducing fine-grained hallucinations of LVLMs. We propose ReCaption, a framework that consists …

Public Acceptance Of Using Artificial Intelligence-Assisted Weight Management Apps In High-Income Southeast Asian Adults With Overweight And Obesity: A Cross-Sectional Study, Han Shi Jocelyn Chew, Palakorn Achananuparp, Palakorn Achananuparp, Nicholas W. S. Chew, Yip Han Chin, Yujia Gao, Bok Yan Jimmy So, Asim Shabbir, Ee-Peng Lim, Kee Yuan Ngiam

Research Collection School Of Computing and Information Systems

Introduction: With in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity. Methods: 280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression. Results: 271 participant responses were …

Frameworks For Measuring Population Health: A Scoping Review, Sze Ling Chan, Clement Zhong Hao Ho, Nang Ei Ei Khaing, Ezra Ho, Candelyn Pong, Jia Sheng Guan, Calida Chua, Zongbin Li, Trudi Lim Wenqi, Sean Shao Wei Lam, Lian Leng Low, Choon How How

Research Collection School Of Computing and Information Systems

Introduction Many regions in the world are using the population health approach and require a means to measure the health of their population of interest. Population health frameworks provide a theoretical grounding for conceptualization of population health and therefore a logical basis for selection of indicators. The aim of this scoping review was to provide an overview and summary of the characteristics of existing population health frameworks that have been used to conceptualize the measurement of population health. Methods We used the Population, Concept and Context (PCC) framework to define eligibility criteria of frameworks. We were interested in frameworks applicable …

Hgprompt: Bridging Homogeneous And Heterogeneous Graphs For Few-Shot Prompt Learning, Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang

Research Collection School Of Computing and Information Systems

Graph neural networks (GNNs) and heterogeneous graph neural networks (HGNNs) are prominent techniques for homogeneous and heterogeneous graph representation learning, yet their performance in an end-to-end supervised framework greatly depends on the availability of task-specific supervision. To reduce the labeling cost, pre-training on selfsupervised pretext tasks has become a popular paradigm, but there is often a gap between the pre-trained model and downstream tasks, stemming from the divergence in their objectives. To bridge the gap, prompt learning has risen as a promising direction especially in few-shot settings, without the need to fully fine-tune the pre-trained model. While there has been …

Imitate The Good And Avoid The Bad: An Incremental Approach To Safe Reinforcement Learning, Minh Huy Hoang, Mai Anh Tien, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

A popular framework for enforcing safe actions in Reinforcement Learning (RL) is Constrained RL, where trajectory based constraints on expected cost (or other cost measures) are employed to enforce safety and more importantly these constraints are enforced while maximizing expected reward. Most recent approaches for solving Constrained RL convert the trajectory based cost constraint into a surrogate problem that can be solved using minor modifications to RL methods. A key drawback with such approaches is an over or underestimation of the cost constraint at each state. Therefore, we provide an approach that does not modify the trajectory based cost constraint …

Simple Image-Level Classification Improves Open-Vocabulary Object Detection, Ruohuan Fang, Guansong Pang, Xiao Bai

Research Collection School Of Computing and Information Systems

Open-Vocabulary Object Detection (OVOD) aims to detect novel objects beyond a given set of base categories on which the detection model is trained. Recent OVOD methods focus on adapting the image-level pre-trained vision-language models (VLMs), such as CLIP, to a region-level object detection task via, eg., region-level knowledge distillation, regional prompt learning, or region-text pre-training, to expand the detection vocabulary. These methods have demonstrated remarkable performance in recognizing regional visual concepts, but they are weak in exploiting the VLMs' powerful global scene understanding ability learned from the billion-scale image-level text descriptions. This limits their capability in detecting hard objects of …

Recommendations With Minimum Exposure Guarantees: A Post-Processing Framework, Ramon Lopes, Rodrigo Alves, Antoine Ledent, Rodrygo L. T. Santos, Marius Kloft

Research Collection School Of Computing and Information Systems

Relevance-based ranking is a popular ingredient in recommenders, but it frequently struggles to meet fairness criteria because social and cultural norms may favor some item groups over others. For instance, some items might receive lower ratings due to some sort of bias (e.g. gender bias). A fair ranking should balance the exposure of items from advantaged and disadvantaged groups. To this end, we propose a novel post-processing framework to produce fair, exposure-aware recommendations. Our approach is based on an integer linear programming model maximizing the expected utility while satisfying a minimum exposure constraint. The model has fewer variables than previous …

What Does One Billion Dollars Look Like?: Visualizing Extreme Wealth, William Mahoney Luckman

Dissertations, Theses, and Capstone Projects

The word “billion” is a mathematical abstraction related to “big,” but it is difficult to understand the vast difference in value between one million and one billion; even harder to understand the vast difference in purchasing power between one billion dollars, and the average U.S. yearly income. Perhaps most difficult to conceive of is what that purchasing power and huge mass of capital translates to in terms of power. This project blends design, text, facts, and figures into an interactive narrative website that helps the user better understand their position in relation to extreme wealth: https://whatdoesonebilliondollarslooklike.website/

The site incorporates …

When Evolutionary Computation Meets Privacy, Bowen Zhao, Wei-Neng Chen, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Jun Zhang

Research Collection School Of Computing and Information Systems

Recently, evolutionary computation (EC) has experienced significant advancements due to the integration of machine learning, distributed computing, and big data technologies. These developments have led to new research avenues in EC, such as distributed EC and surrogate-assisted EC. While these advancements have greatly enhanced the performance and applicability of EC, they have also raised concerns regarding privacy leakages, specifically the disclosure of optimal results and surrogate models. Consequently, the combination of evolutionary computation and privacy protection becomes an increasing necessity. However, a comprehensive exploration of privacy concerns in evolutionary computation is currently lacking, particularly in terms of identifying the object, …

Handling Long And Richly Constrained Tasks Through Constrained Hierarchical Reinforcement Learning, Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Safety in goal directed Reinforcement Learning (RL) settings has typically been handled through constraints over trajectories and have demonstrated good performance in primarily short horizon tasks. In this paper, we are specifically interested in the problem of solving temporally extended decision making problems such as robots cleaning different areas in a house while avoiding slippery and unsafe areas (e.g., stairs) and retaining enough charge to move to a charging dock; in the presence of complex safety constraints. Our key contribution is a (safety) Constrained Search with Hierarchical Reinforcement Learning (CoSHRL) mechanism that combines an upper level constrained search agent (which …

Foodmask: Real-Time Food Instance Counting, Segmentation And Recognition, Huu-Thanh Nguyen, Yu Cao, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Food computing has long been studied and deployed to several applications. Understanding a food image at the instance level, including recognition, counting and segmentation, is essential to quantifying nutrition and calorie consumption. Nevertheless, existing techniques are limited to either category-specific instance detection, which does not reflect precisely the instance size at the pixel level, or category-agnostic instance segmentation, which is insufficient for dish recognition. This paper presents a compact and fast multi-task network, namely FoodMask, for clustering-based food instance counting, segmentation and recognition. The network learns a semantic space simultaneously encoding food category distribution and instance height at pixel basis. …

A Computational Profile Of Invasive Lionfish In Belize: A New Insight On A Destructive Species, Joshua E. Balan

The Journal of Purdue Undergraduate Research

Since their discovery in the region in 2009, invasive Indonesian-native lionfish have been taking over the Belize Barrier Reef. As a result, populations of local species have dwindled as they are either eaten or outcompeted by the invaders. This has led to devastating losses ecologically and economically; massive industries in the local nations, such as fisheries and tourism, have suffered greatly. Attempting to combat this, local organizations, from nonprofits to ecotourism companies, have been manually spear-hunting them on scuba dives to cull the population. One such company, Reef Conservation Institute (ReefCI), operating out of Tom Owens Caye outside of Placencia, …

Strategic Research On Information Technology Promoting National Governance Modernization—Review On The S70th Xiangshan Science Conferences, Chao Zhang, Weiyu Duan, Kaihua Chen, Xiaoguang Yang, Yuntao Long

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study systematically summarizes the reports and speeches of the S70th Xiangshan Science Conferences on the theme of “Strategic Research on Information Technology Promoting the National Governance Modernization” and summarizes the consensus of the conference in the following three aspects. (1) Important progress and achievements have been made in the four typical areas, i.e., smart justice, internet governance, data governance, and emergency management. (2) Using information technology to promote the modernization of national governance is confronted with unprecedented opportunities and challenges. And (3) it is necessary to take a series of effective measures to promote information technology to facilitate the …

Quantifying The Competitiveness Of A Dataset In Relation To General Preferences, Kyriakos Mouratidis, Keming Li, Bo Tang

Research Collection School Of Computing and Information Systems

Typically, a specific market (e.g., of hotels, restaurants, laptops, etc.) is represented as a multi-attribute dataset of the available products. The topic of identifying and shortlisting the products of most interest to a user has been well-explored. In contrast, in this work we focus on the dataset, and aim to assess its competitiveness with regard to different possible preferences. We define measures of competitiveness, and represent them in the form of a heat-map in the domain of preferences. Our work finds application in market analysis and in business development. These applications are further enhanced when the competitiveness heat-map is used …

Predicting Viral Rumors And Vulnerable Users With Graph-Based Neural Multi-Task Learning For Infodemic Surveillance, Xuan Zhang, Wei Gao

Research Collection School Of Computing and Information Systems

In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be more susceptible to spreading such misinformation. This proactive approach allows for timely preventive measures to be taken, mitigating the negative impact of false information on society. We propose a novel approach to predict viral rumors and vulnerable users using a unified graph neural network model. We pre-train network-based user embeddings and leverage a cross-attention mechanism between users and posts, together with a community-enhanced vulnerability propagation (CVP) …

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

Electronic Theses and Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …

Creation Of A Digital Storage System For Genome Sequencing Metadata, Jacquelin W. Olexa

Undergraduate Theses, Professional Papers, and Capstone Artifacts

As the field of computational genomics continues to expand in both potential and application, it is now more imperative than ever to ensure that massive genetic sequencing datasets are properly stored in an accessible manner. This project sought to establish a practical, user-friendly, secure system for a genomics research lab (the Good Lab; thegoodlab.org) at the University of Montana. A MySQL database and connected web application was ruled the best configuration to maximize utility and accessibility for the lab’s researchers. Building the logical framework for the database, creating the server, and sourcing data occurred over several months. The dataset ranged …

Student Attitudes And Intentions To Use Continuous Authentication Methods Applied To Mitigate Impersonation Attacks During E-Assessments, Andrea E. Green

CCE Theses and Dissertations

No solution can ultimately eliminate cheating in online courses. However, universities reserve funding for authentication systems to minimize the threat of cheating in online courses. Most higher education institutions use a combination of authentication methods to secure systems against impersonation attacks during online examinations. Authentication technologies ensure that an online course is protected from impersonation attacks. However, it is important that authentication methods secure systems against impersonation attacks with minimal disruption during an examination. Authentication methods applied to secure e-assessments against impersonation attacks may impact a student’s attitude and intentions to use the e-examination system.

In this regard, the research …

A New Cache Replacement Policy In Named Data Network Based On Fib Table Information, Mehran Hosseinzadeh, Neda Moghim, Samira Taheri, Nasrin Gholami

VMASC Publications

Named Data Network (NDN) is proposed for the Internet as an information-centric architecture. Content storing in the router’s cache plays a significant role in NDN. When a router’s cache becomes full, a cache replacement policy determines which content should be discarded for the new content storage. This paper proposes a new cache replacement policy called Discard of Fast Retrievable Content (DFRC). In DFRC, the retrieval time of the content is evaluated using the FIB table information, and the content with less retrieval time receives more discard priority. An impact weight is also used to involve both the grade of retrieval …

Development Of A Collaborative Research Platform For Efficient Data Management And Visualization Of Qubit Control, Devanshu Brahmbhatt

Computer Science and Engineering Theses

This thesis introduces QubiCSV, a pioneering open-source platform for quantum computing field. With an emphasis on collaborative research, QubiCSV addresses the critical need for specialized data management and visualization tools in qubit control. The platform is crafted to overcome the challenges posed by the high costs and complexities associated with quantum experimental setups. It emphasizes efficient utilization of resources through shared ideas, data, and implementation strategies. One of the primary obstacles in quantum computing research has been the ineffective management of extensive calibration data and the inability to visualize complex quantum experiment outcomes effectively. QubiCSV fills this gap by offering …

Design And Development Of Industrial Practice Monitoring And Assessment Systems Using Tsukamoto Fuzzy Logic, Tri Yuli Pahtoni, Fatchul Arifin

Elinvo (Electronics, Informatics, and Vocational Education)

Vocational high schools are given flexibility for their students to carry out direct learning in the industry as part of the practical education activities of implementing student skills. The implementation of industrial practice requires a special way to find out and monitor each student's activities so that the achievements of the implementation of industrial practice can be carried out properly. The implementation of industrial work practice assessment has several assessment criteria. These criteria include attendance, neatness, attitude, skills, and knowledge. The problems found in the assessment system are still done manually so that the effectiveness is minimal. This study aims …

Implementation Of Fdss (Fuzzy Decision Support System) Sugeno Model In Optimizing Bandwidth Requirement Management Of Web-Based Networks, Indah Wardati Lahiya, Fatchul Arifin

Elinvo (Electronics, Informatics, and Vocational Education)

To increase the efficacy of bandwidth allocation at PT. Digdaya Monokrom Group, this study describes the development of a Fuzzy Decision Support System (FDSS) utilizing the Sugeno methodology. The Waterfall development process is employed for the purposes of system planning, construction, and maintenance. The study consists of three primary stages: the creation of fuzzy sets, the development of fuzzy rules, and the process of defuzzification. The study findings demonstrate that the utilization of FDSS has effectively improved the distribution of bandwidth. The distribution has shifted from a uniform one to a more optimized allocation, focusing on the Execution, Content Creator, …

The Determination Of A Place Of Popular Tourism On The Island Of Madura Using Weighted Product (Wp), Sigit Susanto Putro, Eka Malasari Rochman, Aery Rachmad

Elinvo (Electronics, Informatics, and Vocational Education)

This research explored the diverse aspects of Madura Island, including its cultural, societal, and touristic facets. The primary focus was on developing a recommendation system to identify Madura's most popular tourist destinations. Utilizing the Weighted Product (WP) method, a decision support system model, this study assessed the popularity of various tourist attractions in Madura, aiding tourists in selecting destinations through a multi-criteria weighting process. Key parameters included the number of both foreign and local visitors, proximity to the city center, and visitor ratings. The study encompassed 62 tourist sites across four districts in Madura, evaluating the most popular attractions in …

Visitor Decision System In Selection Of Tourist Sites Based On Hybrid Of Chi-Square And K-Nn Methods, Devie Rosa Anamisa, Fifin Ayu Mufarroha, Achmad Jauhari

Elinvo (Electronics, Informatics, and Vocational Education)

Madura Island is one of the islands with a lot of tourism spread over four districts, such as natural, religious, and cultural tourism. And every year, various visitors visit various tourist sites in Madura, so an increase in the number of visitors has been found in multiple places. This is influenced in addition to the type of tourist attraction but also changes in tourist behavior in making decisions to visit tourist objects. Most of the researchers have applied the right decision-making with intelligence-based measurement. However, the accuracy obtained has not yet reached the optimal solution. Therefore, this study uses the …

Decision Support System For Major Selection In Higher Education For Multimedia Graduate Students Using Fuzzy Mamdani Logic, Khasna Nur Fauziah, Fatchul Arifin

Elinvo (Electronics, Informatics, and Vocational Education)

Students at the vocational high school level are indeed prepared to be able to work directly, but it does not rule out the possibility that vocational high school students can continue higher education such as universities. But the problem that will be faced again if students who graduate from vocational high schools choose to continue their education in college is what major they will take. One of the vocational high school majors, namely Multimedia, has a wide scope, so grade 3 vocational high school students who want to go to college have a dilemma in deciding on a major. This …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Movie Recommendation System Using Content Based Filtering, Sribhashyam Rakesh

Al-Bahir Journal for Engineering and Pure Sciences

The movie recommendation system plays a crucial role in assisting movie enthusiasts in finding movies that match their interests, saving them from the overwhelming task of sifting through countless options. In this paper, we present a content-grounded movie recommendation system that leverages an attribute-based approach to offer personalized movie suggestions to users. The proposed method focuses on attributes such as cast, keywords, crew, and genres of movies to predict users' preferences accurately. Through extensive evaluation, our content-grounded recommendation system demonstrated significant improvements in performance compared to conventional methods. The precision and recall scores increased by an average of 20% and …

A Conceptual Decentralized Identity Solution For State Government, Martin Duclos

Theses and Dissertations

In recent years, state governments, exemplified by Mississippi, have significantly expanded their online service offerings to reduce costs and improve efficiency. However, this shift has led to challenges in managing digital identities effectively, with multiple fragmented solutions in use. This paper proposes a Self-Sovereign Identity (SSI) framework based on distributed ledger technology. SSI grants individuals control over their digital identities, enhancing privacy and security without relying on a centralized authority. The contributions of this research include increased efficiency, improved privacy and security, enhanced user satisfaction, and reduced costs in state government digital identity management. The paper provides background on digital …

Unmasking Shadows: Unraveling Crime Patterns In Nyc's Boroughs, Jack Hachicho, Muhammad Hassan Butt

Publications and Research

New York City's crime dynamics have been on the rise for decades. Brooklyn and The Bronx have been disproportionately affected. This research aims to understand the crime landscape in these boroughs to formulate effective policies. Using crime data from official sources, statistical analyses, and data visualizations, the study identifies patterns and trends. The data encompasses over 400,000 reported incidents collected over the past 10 years, meticulously categorized by borough, crime type, and demographic information. Brooklyn has the highest overall crime rate, followed by The Bronx. Most shooting victims are Black. This highlights the need for holistic community programs to address …

Les Expositions Turnus, Une Page D’Histoire Transnationale Des Beaux-Arts En Suisse À La Fin Du Xixe Siècle. Et Comment Découvrir Les Humanités Numériques, Béatrice Joyeux-Prunel

Artl@s Bulletin

Cet article présente le travail de la classe d’introduction aux humanités numériques de l’Université de Genève sur les expositions Turnus en Suisse à partir des années 1840. Près de 50 catalogues ont été retranscrits, décrits et structurés à l’aide de scripts Python, puis géolocalisés. Les données ont été ajoutées à BasArt, le répertoire mondial de catalogues d’expositions d’Artl@s (https://artlas.huma-num.fr/map). Elles permettent de mieux comprendre les premières années de ces expositions et leurs dynamiques locales, fédérales et internationales. Le Turnus fut une plaque tournante pour les artistes suisses, voire un tremplin vers le marché européen de l’art.