Physical Sciences and Mathematics Commons^™

Risk Spillover Effect Of China-Asean Supply Chains: Insights Of Industrial Transfer, Zeyang Bian, Yuning Zhang, Keng Siau, Yaqian Zhang, Jianjia He

Research Collection School Of Computing and Information Systems

As labour costs in China increase, labour-intensive industries are migrating to ASEAN countries, attracted by lower labour costs and market potential. This shift not only affects the economies of China and ASEAN but also reshapes the global manufacturing landscape. This paper investigates the correlation and spillover of supply chain risks using production exposure indicators derived from inter-country input-output data and the R-Vine Copula model. We assess the risk spillover of each country within the global supply chain. Our findings indicate that industrial relocation can significantly alter supply chain structures, thereby affecting the concentration and direction of risks. While China's role …

An Agent-Based Computational Finance Simulation Model To Study Market Efficiency, Wei Feng, Keng Siau, Wee-Yeap Lau, Lim-Thye Goh, Haonan Chen

Research Collection School Of Computing and Information Systems

The advancement of computational modeling, data systems, and digital infrastructure has enabled the rise of agent-based computational finance (ACF). This study models interactions among heterogeneous investors. By embedding behavioral logics such as environmental, social, and governance (ESG) preferences and volatility thresholds, the model captures microstructural dynamics under different trading rules. Using ACF, the authors compare transaction plus 0 day (T+0) to transaction plus 1 day (T+1). Results show that T+0 improves price discovery, deepens liquidity, and reduces transaction costs. From a computational perspective, this research contributes to ACF by showing how policy logic and investor heterogeneity can be encoded and …

More Effective Javascript Breaking Change Detection Via Dynamic Object Relation Graph, Dezhen Kong, Jiakun Liu, Chao Ni, David Lo, Lingfeng Bao

Research Collection School Of Computing and Information Systems

JavaScript libraries are characterized by their widespread use, frequent code changes, and a high tolerance for backward incompatible changes. Awareness of such breaking changes can help developers adapt to version updates and avoid negative impacts. Several tools have been targeted to or can be used to detect breaking change detection in the JavaScript community. However, these tools detect breaking changes using different ways, and there are currently no systematic reviews of these approaches. From a preliminary study on popular JavaScript libraries, we find that existing approaches, including simple regression testing, model-based testing and type differencing cannot detect many breaking changes …

Don’T Complete It! Preventing Unhelpful Code Completion For Productive And Sustainable Neural Code Completion Systems, Zhensu Sun, Xiaoning Du, Fu Song, Shangwen Wang, Mingze Ni, Li Li, David Lo

Research Collection School Of Computing and Information Systems

Currently, large pre-trained language models are widely applied in neural code completion systems. Though large code models significantly outperform their smaller counterparts, around 70% of displayed code completions from Github Copilot are not accepted by developers. Being reviewed but not accepted, their help to developer productivity is considerably limited and may conversely aggravate the workload of developers, as the code completions are automatically and actively generated in state-of-the-art code completion systems as developers type out once the service is enabled. Even worse, considering the high cost of the large code models, it is a huge waste of computing resources and …

Financial Named Entity Recognition: How Far Can Llm Go?, Yi-Te Lu, Yintong Huo

Research Collection School Of Computing and Information Systems

The surge of large language models (LLMs) has revolutionized the extraction and analysis of crucial information from a growing volume of financial statements, announcements, and business news. Recognition for named entities to construct structured data poses a significant challenge in analyzing financial documents and is a foundational task for intelligent financial analytics. However, how effective are these generic LLMs and their performance under various prompts are yet need a better understanding. To fill in the blank, we present a systematic evaluation of state-of-the-art LLMs and prompting methods in the financial Named Entity Recognition (NER) problem. Specifically, our experimental results highlight …

Privacy-Preserving User Recruitment With Sensing Quality Evaluation In Mobile Crowdsensing, Jieying An, Yanbing Ren, Xinghua Li, Man Zhang, Bin Luo, Yinbin Miao, Ximeng Liu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Recruiting users in mobile crowdsensing (MCS) can make the platform obtain high-quality data to provide better services. Although the privacy leakage during the process of user recruitment has received a lot of research attention, none of the existing work considers the evaluation of the sensing quality of privacy-preserving data submitted by users, which makes the platform incapable of recruiting users suitably to obtain high-quality sensing data, thereby reducing the reliability of MCS services. To solve this problem, we first propose a sensing quality evaluation method based on the deviation and variance of sensing data. According to it, the platform can …

Investigation Of A Busemann Intake At Negative Angle Of Attack, Mark E. Noftz, Andrew N. Bustard, Nicholas J. Bisek, Thomas J. Juliano, Joseph S. Jewell

Publications

A high-speed, shape-transitioned, inward-turning intake was tested in Purdue’s Boeing/AFOSR Mach 6 Quiet Tunnel. The inlet model, called the Indiana Inlet (INlet), had a total contraction ratio of 4.68:1 and a design point of Mach 6 at 0° angle of attack. The model was outfitted with a suite of high-frequency pressure transducers, and the external flowfield was imaged with high-speed schlieren photography. The INlet was tested under low freestream disturbance levels for a variety of freestream unit Reynolds numbers and at-4° angle of attack. An unsteady shockwave near the leading edge of the inlet forebody, indicative of boundary layer separation, …

A Systematic Review On Mental Health Chatbots: Trends, Design Principles, Evaluation Methods, And Future Research Agenda, Mohammad Amin Kuhail, Ons Al-Shamaileh, Shahbano Farooq, Hana Shahin, Fatema Abdelzaher, Justin Thomas

All Works

Recent decades have witnessed a rise in the prevalence of common mental health problems coupled with an increasing demand for talk‐based psychological therapies. This has coincided with the rise of mental health chatbots (MHCs), a corollary of which is the use of MHCs, AI‐driven, conversational agents, to provide interactive support, guidance, and therapeutic engagement for persons experiencing mental health challenges. There has been a growing research interest in MHCs, and this study provides a much‐needed systematic review that examines this expanding research literature, identifying themes, trends, and areas worthy of further exploration. This review identified and systematically explored 97 published …

Navigating Copyright In Ai-Enhanced Game Design: Legal Challenges In Multimodal And Dynamic Content Creation, Andrew Begemann, James Hutson

Faculty Scholarship

The integration of artificial intelligence (AI) in video game design has transformed traditional workflows, allowing for the generation of text, images, music, videos, and code at unprecedented scales. However, this advancement presents complex challenges for copyright law, traditionally rooted in human originality and authorship. This article examines recent case law that underscores the evolving legal landscape, exploring landmark cases such as Zarya of the Dawn and Andersen v. Stability AI. These cases reveal the tensions between AI-generated outputs and copyright eligibility, especially in the dynamic, multimodal compositions inherent to video games. The review analyzes how various AI tools are employed …

Explicit Inverse Of Symmetric, Tridiagonal Near Toeplitz Matrices With Strictly Diagonally Dominant Toeplitz Part, Bakytzhan Kurmanbek, Yogi Erlangga, Yerlan Amanbek

All Works

Let T n = tridiag ( - 1 , b , - 1 ) , an n x n symmetric, strictly diagonally dominant tridiagonal matrix ( divided by b divided by > 2 ). This article investigates tridiagonal near-Toeplitz matrices T n & colone; [ t i , j ] , obtained by perturbing the ( 1 , 1 ) and ( n , n ) entry of T n . Let t 1 , 1 = t n , n = b not equal b . We derive exact inverses of T n . Furthermore, we demonstrate that these results …

Resource Assessment Report No. 01: Mid-West Scallop Resource 2024 Assessment, Jason How, Arani Chandrapavan, Rachel Marks

Resource Assessment Reports

The Mid-West Scallop Resource (Resource) is only accessed by the Abrolhos Islands Mid-West Trawl Managed Fishery (AIMWTMF). The AIMWTMF is the second largest scallop fishery in Western Australia. Access is limited to the 10 licences granted to access the Resource, which are managed through a range of, gear controls, catch rates and seasonal closures. They access saucer scallops, Ylistrum balloti (formerly Amusium balloti) using otter trawls fished over predominantly sand. The fishery was certified by the Marine Stewardship Council in 2021, with the fishery entering re-certification in 2026.

In 2024, 95.7 t meat weight (478.5 t whole weight) of saucer …

การศึกษารูปแบบความร่วมมือของภาครัฐและภาคเอกชนในการบริหารจัดการเหตุวิกฤติฉุกเฉินและนโยบายการรักษาความปลอดภัยย่านศูนย์กลางธุรกิจของกรุงเทพมหานคร, ปัญจรัตน์ เดชกุญชร

Chulalongkorn University Theses and Dissertations (Chula ETD)

ภัยพิบัติเป็นสิ่งที่ทั่วโลกเล็งเห็นความสำคัญและให้ความตระหนักในการบริหารจัดการ ด้วยการเปลี่ยนแปลงของโลกเป็นปัจจัยกระตุ้นให้เกิดเหตุขึ้นบ่อยครั้ง เป็นเหตุวิกฤติที่เกินการรับมือ การศึกษาเรื่อง รูปแบบความร่วมมือของภาครัฐและภาคเอกชนในการบริหารจัดการเหตุวิกฤติฉุกเฉินและนโยบายการรักษาความปลอดภัยย่านศูนย์กลางธุรกิจของกรุงเทพมหานคร เป็นการศึกษาในภาคการขับเคลื่อนนโยบายการบริหารระหว่างหน่วยงานภาครัฐและเครือข่ายภาคประชาชนในพื้นที่ย่านราชประสงค์ เขตปทุมวัน ภายใต้กรอบแนวคิดการร่วมมือทำงานกันระหว่างภาครัฐและภาคเอกชนแบบเครือข่าย Networking มีวัตถุประสงค์เพื่อทราบถึง 1) รูปแบบความร่วมมือเชิงนโยบายของภาครัฐและภาคเอกชนในการบริหารจัดการเหตุวิกฤติ 2) นโยบายการรักษาความปลอดภัยของภาครัฐและภาคเอกชนในพื้นที่ย่านราชประสงค์ 3) การออกแบบแผนการรับมือเหตุวิกฤติ และ 4) เพื่อดูแนวโน้มการเป็นต้นแบบนำร่องไปใช้ในพื้นที่ชุมชนเมืองอื่นในกรุงเทพมหานคร เป็นการวิจัยเชิงคุณภาพแบบกรณีศึกษา โดยการสัมภาษณ์ผู้บริหารกลุ่มภาคเอกชนกลุ่มผู้ประกอบวิสาหกิจในย่านราชประสงค์ จำนวน 10 องค์กร และหน่วยงานภาครัฐในพื้นที่อีก 2 องค์กร ใช้แบบสัมภาษณ์กึ่งโครงสร้าง วิเคราะห์ข้อมูลเชิงเนื้อหา พรรณนา พัฒนาแก่นสาระ ตรวจสอบด้วยวิธีเทคนิคสามเส้า ร่วมกับการศึกจากข้อมูลเอกสารและการลงพื้นที่เพื่อสังเกตการณ์ ผลการวิจัยพบว่า (1) รูปแบบความร่วมมือเชิงนโยบายของภาครัฐและภาคเอกชนในการบริหารจัดการเหตุวิกฤติฉุกเฉินในย่านราชประสงค์ ขับเคลื่อนด้วยแนวคิดการจัดการปกครองสาธารณะแนวใหม่แบบเครือข่าย ระหว่างภาครัฐกับเครือข่ายภาคเอกชน บวกกับ Disaster Management และ Crisis Management (2) นโยบายการรักษาความปลอดภัยใช้การร่วมออกแบบ ร่วมคิด และขับเคลื่อนกลไกเชิงนโยบายมีปฏิสัมพันธ์ในระดับองค์กร และระดับบุคคลต่อบุคคล (3) การออกแบบแผนการรับมือเหตุวิกฤติฉุกเฉินจากภัยพิบัติในย่านราชประสงค์ ใช้วิธีการเตรียมความพร้อม ตามหลักการของ Disaster Management ร่วมกับ Crisis Management (4) แนวโน้มการเป็นต้นแบบนำไปใช้ในพื้นที่ชุมชนเมืองอื่นในกรุงเทพมหานคร ต้องพิจารณาร่วมด้วยกับความเข้มแข็งของความร่วมมือของรัฐและเอกชนที่มีวิสัยทัศน์ แนวทางในการขับเคลื่อนไปในทิศทางเดียวกัน ระบบการเงินส่วนกลางที่น่าเชื่อถือ มีการจัดปรับการใช้รูปแบบให้เหมาะสมกับทรัพยากรที่มีอยู่ในพื้นที่ของตนเอง

การประเมินผลการใช้น้ำเสียบำบัดในระบบไฮโดรพอนิกส์ : การเปลี่ยนแปลงของไนโตรเจน การเติบโตของผักกาดหอม และกลุ่มชุมชนของจุลินทรีย์บริเวณราก, พชร ป่ากว้าง

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้ศึกษาการนำน้ำเสียที่ผ่านการบำบัดจากระบบเติมอากาศของอาคารหอสมุดกลาง จุฬาลงกรณ์มหาวิทยาลัย กลับมาใช้ในระบบไฮโดรพอนิกส์เพาะปลูกผักกาดหอม (Lactuca sativa) เพื่อส่งเสริมการจัดการน้ำอย่างยั่งยืนและการใช้ทรัพยากรหมุนเวียน การทดลองออกเป็น 3 ระยะตามอัตราส่วนน้ำเสียบำบัด ได้แก่ 50% (ระยะที่ 1), 100% (ระยะที่ 2) และ 75% (ระยะที่ 3) เปรียบเทียบกับระบบควบคุมที่ใช้สารละลายปุ๋ยไฮโดรพอนิกส์ ศึกษาการเปลี่ยนแปลงของไนโตรเจน ได้แก่ แอมโมเนียม (NH4+), ไนไตร์ท (NO2-), ไนเตรต (NO3-), และ ไนโตรเจนคเจดาลห์ (TKN) และประเมินผลต่อการเจริญเติบโตและปริมาณไนโตรเจนของผักกาดหอม ตลอดระยะเวลาเพาะปลูก 28 วัน มีการเก็บตัวอย่างน้ำเพื่อวิเคราะห์คุณภาพน้ำ และสุ่มเก็บตัวอย่างรากเพื่อศึกษาความหลากหลายของชุมชนจุลินทรีย์ ผลการทดลองพบว่าอัตราส่วนของน้ำเสียบำบัดมีผลต่อการเจริญเติบโตของผักกาดหอมอย่างมีนัยสำคัญทางสถิติ โดยระบบที่ใช้น้ำเสียบำบัด 100% ให้ผลผลิตสูงสุดทั้งในด้านน้ำหนักสด น้ำหนักแห้ง และปริมาณไนโตรเจน ซึ่งแนวโน้มนี้สอดคล้องกับความเข้มข้นไนเตรตและ TKN ในน้ำ แสดงถึงความเพียงพอของธาตุอาหาร โดยเฉพาะไนโตรเจน ขณะเดียวกันการวิเคราะห์ชุมชนจุลินทรีย์บริเวณรากพบว่าระบบน้ำเสียบำบัดมีความหลากหลายสูงกว่าระบบควบคุม โดยพบแบคทีเรียเด่นใน สกุล Altererythrobacter รวมถึงสกุล midas_g_859 ซึ่งอยู่ในอันดับ Thermomicrobiales และสกุลของแบคทีเรียในไฟลัม Armatimonadotaซึ่งเกี่ยวข้องกับการย่อยสลายอินทรียวัตถุและการเปลี่ยนรูปไนโตรเจน ส่วนระบบควบคุมพบแบคทีเรียเด่นในสกุลของวงศ์ Rhizobiaceae และสกุล Bosea ซึ่งมีบทบาทสำคัญในการตรึงไนโตรเจนและช่วยเพิ่มความสามารถในการดูดซึมสารอาหารของพืช ดังนั้นการนำน้ำเสียบำบัดกลับมาใช้ในระบบไฮโดรพอนิกส์จึงมีศักยภาพในการส่งเสริมการเจริญเติบโตของผักกาดหอมได้อย่างมีประสิทธิภาพ แต่การปรับสมดุลธาตุอาหารและคุณภาพน้ำก่อนใช้งานจริงยังเป็นสิ่งจำเป็น ผลการศึกษานี้จึงสามารถเป็นแนวทางพัฒนาระบบบำบัดน้ำเสียแบบบูรณาการร่วมกับการเพาะปลูกไฮโดรพอนิกส์ภายในมหาวิทยาลัยต่อไป

Leveraging Gpt-4o For Automated Extraction Of Neural Projections From Scientific Literature, Rashmie Abeysinghe, Gorbachev Jowah, Licong Cui, Samden D Lhatoo, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Sudden Unexpected Death in Epilepsy (SUDEP) is a major cause of death for epilepsy patients having uncontrolled seizures. Understanding the complex neural circuits within the central nervous system is crucial for understanding the mechanisms underlying cardiorespiratory regulation, particularly in the context of SUDEP. This study explores the potential of GPT-4o, a cutting-edge language model, to automate the extraction of neural projections from scientific literature. We developed prompts to extract neuroscientific structures, extract projections, and perform synonym harmonization. Applying the approach to four neuroscientific articles, the method extracted 205 projections. A random sample of 100 projections identified was handed over to …

Depletion Of Adipose Stroma-Like Cancer-Associated Fibroblasts Potentiates Pancreatic Cancer Immunotherapy, Joseph Rupert, Alexes Daquinag, Yongmei Yu, Yulin Dai, Zhongming Zhao, Mikhail G Kolonin

Faculty, Staff and Student Publications

This study shows that populations of CAFs have distinct effects on pancreatic cancer progression and shows that depletion of CAFs expressing adipose markers potentiates tumor/metastasis suppression effects of immune checkpoint blockade.

Automated Infinite Combos Detection System For Collectible Card Game, Amornpong Trakarnkulphun

Chulalongkorn University Theses and Dissertations (Chula ETD)

In Collectible Card Games, resources management is one of the most effective strategy. However, there are some combinations of cards which produce unlimited resources called infinite combos. Too-cheap infinite combos that can be played early in the game break game environment, because the player who executes the combo immediately wins. To solve the problem, game designers usually restrict a part of the combos from being played. Due to the large number of cards in the card pool, it is difficult to search for these combos and solve this problem before a release date of a card set. This research aims …

Pipeline For Non-Self-Intersecting Racetrack Generation In Racing Games, Chatrtime Chatramornrat

Chulalongkorn University Theses and Dissertations (Chula ETD)

Procedural content generation (PCG) allows racing games to supply new racetracks automatically, but straightforward generators can produce layouts with unrealistically tight bends or self-crossings that compromise playability. This thesis introduces a racetrack generation pipeline that connects chain–code–based synthesis with a dedicated post-processing stage for resolving intersections. Candidate layouts are first assembled from image–based differential chain codes and adjusted so that each forms a closed loop. Regions where the centreline crosses itself are then identified and repaired by cutting and joining overlapping branches and applying locally constrained smoothing, so that the overall course geometry is kept intact. Finally, geometric descriptors such …

Gitcofl : Design And Implementation Of A Git-Based Federated Learning Framework Utilizing Container-Based Technology, Chokchai Faroongsarng

Chulalongkorn University Theses and Dissertations (Chula ETD)

The rapid proliferation of artificial intelligence (AI) necessitates training paradigms that are both robust and privacy-preserving. Traditional centralized federated learning (CFL) suffers from single points of failure and communication bottlenecks, while decentralized federated learning (DFL) introduces communication complexities and lacks integrated version control. This paper proposes GitCoFL, a novel framework that leverages Docker containers and a Git server as an independent, external medium for model weight communication and storage. This architecture provides inherent flexibility, enabling efficient operation in both CFL and DFL settings. Using CIFAR-10 benchmarks with MobileNet and using FedAvg for federation algorithms, GitCoFL achieves competitive F1 score when …

Quality Of Life Prediction For Driving Route Planning System Using Image Recognition And Deep Learning, Intouch Prakaisak

Chulalongkorn University Theses and Dissertations (Chula ETD)

Assessing travel-related Quality of Life (QoL) is a significant challenge due to its reliance on subjective human perception, which is difficult to measure. Traditional studies are often constrained by the limited scope of costly, manual data collection. The significant contribution of this research is the introduction of a new framework that can analyze tourist perception on a large and systematic scale. The novelty of this work lies in the utilization of Google Street View (GSV) as a large-scale visual data source, coupled with the use of a sequence-based model to analyze travel routes, which allows for the simulation of the …

A Benchmarking Study Of Grover's Algorithm For Solving Boolean Sat With Quantum Circuits, Jirapas Unison Jipipob

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study explores how well Grover's Algorithm performs in solving the Boolean Satisfiability Problem (SAT) using quantum circuits. The algorithm is implemented with IBM's Qiskit framework and compared to classical brute-force methods. Experiments focus on 3-SAT, 4-SAT, and 5-SAT problems, using quantum simulators and IBM quantum hardware. The results show that Grover's Algorithm is more efficient, offering a theoretical quadratic speedup over classical methods. However, practical issues like limited qubit availability, hardware noise, and optimization challenges impact its current performance. The data highlights the potential for quantum computing to scale and solve NP-complete problems. This research shows how quantum computing …

Out-Of-Domain Tuberculosis Detection From Chest X-Ray Images Using Meta Learning With Soft Labels, Kanokphat Jinanarong

Chulalongkorn University Theses and Dissertations (Chula ETD)

Automated tuberculosis screening from chest x-ray images could greatly benefit regions with limited medical resources. However, currently available methods could not handle this problem well due to the difference in chest x-ray images in each region caused by the difference in machine and demographics, the possible noise in the available labels, and other reasons. We therefore propose a new machine learning algorithm that could detect tuberculosis with great accuracy on any other data sources by learning from completely different data sources. We used a model-agnostic meta-learning together with a soft label approach, utilizing the meta-gradient to dynamically adjust the soft …

Enhancing Large Language Models For Legal Question Answering : A Case Study On The Land And Building Tax Act In Thailand, Nattapat Tantapong

Chulalongkorn University Theses and Dissertations (Chula ETD)

Thailand's Land and Buildings Tax Act requires interpreting multiple legal instruments. However, general-purpose large language models often produce answers that lack both accuracy and verifiable legal citations, which are essential for legal reasoning. This study investigates whether curriculum-structured fine-tuning enables small Thai-aligned models (8B parameters) to perform comparably to large commercial models. The research constructs a domain-specific corpus of 8,410 Q&A pairs with 30,612 hard-negative triplets, then evaluates four curriculum designs and four adapter ranks using retrieval completeness and answer quality metrics. The experimental results reveal two key findings. First, hard-negative retrieval training improves Multi-HitRate@5 by 2.6% and Multi-MRR@5 by …

Diffusion Model-Based Synthetic Image Augmentation For Enhancing Vehicle Detection Model Performance, Pawaris Parnphotong

Chulalongkorn University Theses and Dissertations (Chula ETD)

A critical challenge for modern object detection models is the significant performance degradation encountered in adverse weather or poor lighting conditions. This issue primarily stems from the imbalance of training datasets, which are predominantly composed of normal daytime scenes, resulting in reduced robustness when models face challenging scenarios. Although traditional data augmentation techniques exist, they are limited to pixel-level adjustments and inherently restricted in generating data diversity. Consequently, this research proposes an approach utilizing diffusion models to generate realistic synthetic images that simulate new atmospheric and environmental conditions. To maximize the efficiency of synthetic data generation, we investigated a crucial …

Large Language Model-Based Framework For Mental Health Support Conversation In Thai, Radchaneeporn Changpun

Chulalongkorn University Theses and Dissertations (Chula ETD)

As mental health support needs continue to rise in Thailand, access to professional care remains constrained. LLM-based chatbots present a scalable alternative, though most current systems are limited to single-turn, solution-focused interactions. This thesis introduces a Large Language Model-Based Framework for Mental Health Support Conversations in Thai, organizing dialogues around five fundamental mental health counseling stages: rapport building, problem identification, goal setting, working, and termination. Drawing from Person-Centered Therapy (PCT) and Acceptance and Commitment Therapy (ACT). The framework was assessed against three single-agent baseline models using LLM-simulated users, with positive user reaction rates evaluated by LLMs. Results demonstrated a 79.01% …

Music Generation Using Large Language Models : A Case Study On Traditional Thai Music, Sutusta Kunasorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study presents a framework for music generation using Large Language Models (LLMs), focusing on the creation of symbolic compositions in the style of traditional Thai music. The framework integrates prompting techniques, retrieval-augmented generation (RAG), and multi-agent collaboration to guide the model in producing melodies that reflect Thai musical characteristics. ABC notation is used as the primary representation, allowing LLMs to process musical structure in a text-based format. The system incorporates curated Thai musical examples and theoretical knowledge to support culturally informed generation, while multiple agents work together to compose, evaluate, and refine musical ideas using rubric-based criteria adapted from …

A Hybrid Hardware Modeling, Simulation, And Generation Framework : A Case Study Of Risc-V Out-Of-Order Superscalar Cpu Design, Tanawin Devaveja

Chulalongkorn University Theses and Dissertations (Chula ETD)

We present Kathryn, a novel framework that simplifies hardware design through a hybrid design flow and an integrated hybrid simulation approach. As specialized hardware demand grows, managing design complexity, precise control flow, and parallelism control remains challenging. Kathryn alleviates these issues by abstracting control logic and still maintaining designers’ cycle-accurate control ability. Moreover, Kathryn provides hardware-aggregation features, helping designers manage complex hardware component structures. As a result, in a simple RISC-V design, the model written in Kathryn shows a 2.6x reduction in lines of code compared to those of Verilog. [1] Moreover, in an Out-of-Order design, the model on Kathryn …

Endoplanar: Deformable Planar-Based Gaussian Splatting For Surgical Scene Reconstruction, Thatphum Paonim

Chulalongkorn University Theses and Dissertations (Chula ETD)

Precise modeling of deformable anatomical structures from stereoscopic endoscopic footage plays a critical role in advancing surgical guidance and robotic automation within image-assisted medical procedures. Recent advances in Gaussian splatting have demonstrated real-time visualization capabilities with notable quality on endoscopic data; however, traditional 3D Gaussian representations introduce volumetric artifacts that compromise geometric fidelity and depth accuracy. We address these challenges through EndoPlanar, a deformable planar Gaussian framework that projects volumetric primitives onto planar surfaces. This planar formulation facilitates bias-free depth calculation and normal vector derivation—capabilities that remain elusive with standard ellipsoidal representations. We further incorporate a regularization mechanism to ensure …

Advancing Voice Spoofing Detection In Thai : A Comprehensive Dataset And Performance Analysis On Speaking Styles And Channel Effects, Ticho Urai

Chulalongkorn University Theses and Dissertations (Chula ETD)

Voice authentication is increasingly used in applications such as banking and call center verification, but it faces serious risks from spoofed voices. Recent advances in text-to-speech (TTS) and voice cloning make it possible to generate highly natural fake speech, creating an urgent need for robust anti-spoofing systems. While most prior work focuses on English, little research addresses the Thai language. To fill this gap, we present the Chula Spoofed Speech (CSS) dataset, a large-scale Thai corpus containing 1.3M utterances of both bona fide and synthetic speech. The synthetic samples are generated using five state-of-the-art TTS systems from the same utterances …

Evaluation Of User Experience And Usability Of Organization Super App, Ananya Kumhan

Chulalongkorn University Theses and Dissertations (Chula ETD)

The digital transformation of organizations in Thailand has accelerated the development of internal systems that streamline workflows and improve accessibility to organizational information. Financial institutions, which operate with multiple fragmented systems, have increasingly adopted Enterprise SuperApps as a centralized platform that combines internal services such as corporate news, leave requests, employee directories, resource information, and meeting room reservations into a single application. However, usage statistics in several organizations indicate that continuous adoption remains relatively low. Many employees rely on alternative channels or use only selected features, reflecting challenges in user experience (UX) and usability. This study aims to evaluate the …

Partial Group Divisible 3-Designs, Apiwat Peereeyaphat

Chulalongkorn University Theses and Dissertations (Chula ETD)

We introduce a generalization of group divisible 3-designs, 3-GDDs, with two groups and two indices. A partial group divisible 3-design, 3-PGDD(gı + g2, k; A, (21, 112), is an ordered pair (GrU G2, B) where G, and G2 are disjoint finite sets called groups) of size g1 and 92, respectively; and B is a collection of k-subsets (called blocks) of G, UG, such that every 3-subset of G; occurs in exactly 1 blocks in B, and every i elements of G and j elements of G2 occur together in exactly Mig blocks in B for i. i € (1,2} and …