Engineering Commons^™

Multimodal Emotion Detection In Conversations And Dialogues: A Fusion Model Approach, Abhinay Jatoth

Master's Projects

Emotion recognition is gaining traction due to its wide range of potential applications across different fields. With the rise of social media, chat platforms, and voice assistants, there is a vast increase in data through which humans implicitly and explicitly carry emotional cues. With new algorithms being developed for understanding the nuances of human language and emotion, businesses can tailor more personalized and empathetic service. Sentiment analysis, expresses a positive, negative, or neutral viewpoint laid the foundation of Emotion classification. Emotion classification in conversations represents the most advanced stage of classification. It is also challenging due to the existence and …

Economic Profitability Of Sustainable Buildings Industry, Mohanad Ibrahim Altuma, Hanadi Abdulridha Lateef, Ayad Abdulkhaleq Al-Yousuf

Al-Esraa University College Journal for Engineering Sciences

The increasing global awareness of the Earth's deteriorating condition and the unpredictable effects of climate change has given rise to worldwide phenomena that impact several elements like the economy, agricultural security, water availability, and energy supplies. Buildings contribute significantly to the generation of greenhouse gases, as well as the disposal of pollutants and energy consumption. Therefore, they play a crucial role in addressing environmental issues.

Although sustainable buildings are widely acknowledged as a potential advancement, professionals in the property market still believe that the upfront costs of creating sustainable buildings are significantly higher than those of conventional buildings. This view …

Designing A Visual Control Framework Based On Feature Point Analysis To Guide Robots In Uncharted Areas, Isam Sadiq Rasham Al-Ghadhbawi

Al-Esraa University College Journal for Engineering Sciences

Image processing may be made more accurate and efficient with the use of optical processing technologies. In order to make better design judgments early in the package design process, visual packaging art simulation aims to swiftly develop realistic packaging effects. Conventional simulation techniques frequently yield findings that are neither realistic or detailed, and they also take a lot of time and human resources. Optical processing-based machine vision technology can fully utilize computer vision and image processing techniques to simulate package designs accurately and efficiently. This research proposes a foundation for machine vision technologies based on image optical processing. Real package …

Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai

Theses and Dissertations--Electrical and Computer Engineering

Artificial Intelligence (AI) has experienced remarkable success in recent years, solving complex computational problems across various domains, including computer vision, natural language processing, and pattern recognition. Much of this success can be attributed to the advancements in deep learning algorithms and models, particularly Artificial Neural Networks (ANNs). In recent times, deep ANNs have achieved unprecedented levels of accuracy, surpassing human capabilities in some cases. However, these deep ANN models come at a significant computational cost, with billions to trillions of parameters. Recent trends indicate that the number of parameters per ANN model will continue to grow exponentially in the foreseeable …

A Novel Processor Architecture Implementing The Stacked Error Diffusion Algorithm And Its Zynq-Based Realization, Qishi Hu

Theses and Dissertations--Electrical and Computer Engineering

Digital halftoning reproduces continuous-tone images using patterns of black and white dots, while multitoning extends this concept by incorporating inks with intermediate intensities. These techniques are extensively utilized in the printing industry to accommodate the limited range of inks available in printers. Stacked error diffusion is a high-quality multitoning algorithm that adheres to the blue-noise dithering standard. This thesis research studies the potential parallelism inherent in the algorithm and introduces the design of a novel processor architecture optimized for efficient execution. The architecture is realized on an FPGA development board featuring a Zynq SoC. Additionally, the hardware prototype can also …

The Impact Of Social Media On Charitable Giving For Nonprofit Organization, Namchul Shin

Journal of International Technology and Information Management

Research has extensively studied nonprofit organizations’ use of social media for communications and interactions with supporters. However, there has been limited research examining the impact of social media on charitable giving. This research attempts to address the gap by empirically examining the relationship between the use of social media and charitable giving for nonprofit organizations. We employ a data set of the Nonprofit Times’ top 100 nonprofits ranked by total revenue for the empirical analysis. As measures for social media traction, i.e., how extensively nonprofits draw supporters on their social media sites, we use Facebook Likes, Twitter Followers, and Instagram …

How Does Digitalisation Transform Business Models In Ropax Ports? A Multi-Site Study Of Port Authorities, Yiran Chen, Anastasia Tsvetkova, Kristel Edelman, Irina Wahlström, Marikka Heikkila, Magnus Hellström

Journal of International Technology and Information Management

This article investigates the relationship between digitalisation and business model changes in RoPax ports. The study is based on six RoPax ports in Northern Europe, examining their digitalisation efforts and the resulting changes in their business models, leading to further digital transformation. The paper offers insights by reviewing relevant literature on digitalisation’s role in business model innovation and its application in ports. The findings reveal that digitalisation supports relevant business model changes concerning port operation integration within logistics chains, communication, documentation flow, and cargo flow optimisation. However, exploring digitalisation’s potential for diversifying value propositions is still limited. Most digitalisation efforts …

Key Issues Of Predictive Analytics Implementation: A Sociotechnical Perspective, Leida Chen, Ravi Nath, Nevina Rocco

Journal of International Technology and Information Management

Developing an effective business analytics function within a company has become a crucial component to an organization’s competitive advantage today. Predictive analytics enables an organization to make proactive, data-driven decisions. While companies are increasing their investments in data and analytics technologies, little research effort has been devoted to understanding how to best convert analytics assets into positive business performance. This issue can be best studied from the socio-technical perspective to gain a holistic understanding of the key factors relevant to implementing predictive analytics. Based upon information from structured interviews with information technology and analytics executives of 11 organizations across the …

Does Personality Traits And Security Habits Influence Security Of Personal Identification Numbers? The Context Of Mobile Money Services In Tanzania., Daniel Ntabagi Koloseni

Journal of International Technology and Information Management

Security is an important ingredient in financial transactions; as such, it is imperative that attention should be paid to enhancing the security habits and user behaviours of mobile payment services. Establishing a link between security habits, personality characteristics, and security behaviours provides a new dimension to studying security behaviours regarding mobile money services. Therefore, this study investigates how personality traits affect security behaviours and habits and how security habits mediate the link between personality traits and PIN security practices. The study found that conscientiousness, openness to experience, extroversion and security habits influence PIN security practices, while conscientiousness, agreeableness, and neuroticism …

Media And Internet Censorship In India: A Study Of Its History And Political-Economy, Ramesh Subramanian

Journal of International Technology and Information Management

The Indian Constitution, which came into force on January 26, 1950, guarantees various fundamental rights, such as the freedom of speech and expression, freedom of religion, rights to form association, as well as rights to privacy. Yet, since the adoption of the Constitution, the Indian citizen has been subject to varying degrees of media censorship and surveillance. This paper seeks to delve into the historical evolution of media and Internet censorship and surveillance in India. It shows how media censorship of varying types have existed since the British colonists introduced restrictive laws in order to expand and control the native …

Activities Tailoring Within Agile Scrum Roles: A Case Of Nigerian Healthcare Information Systems Development, Yazidu Salihu, Julian Bass, Gloria Iyawa

Journal of International Technology and Information Management

Developing quality agile healthcare information systems requires understanding regulatory compliance and evolving healthcare needs through activities tailored within agile scrum roles. Agile scrum, a widely adopted philosophy, offers significant advantages in managing software development processes. This research explores how activities within the agile scrum roles are tailored to agile healthcare information systems development within the Nigerian context. This study adopted a qualitative case study methodology and interviewed 12 agile practitioners developing healthcare information systems within Nigeria using semi-structured open-ended interview guide questions. The practitioners were selected based on a snowballing process, a sunset of purposive sampling techniques from our network …

Classification Of Sow Postures Using Convolutional Neural Network And Depth Images, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The United States swine industry reports an average preweaning mortality of approximately 16% where approximately 6% of them are attributed to piglets overlayed by sows. Detecting postural transitions and estimating sows’ time budgets for different postures are valuable information for breeders and engineering design of farrowing facilities to eventually reduce piglet death. Computer vision tools can help monitor changes in animal posture accurately and efficiently. To create a more robust system and eliminate varying lighting issues within a day including daytime/ nighttime differences, there is an advantage to using depth cameras over digital cameras. In this study, a computer vision …

A Fully Automated Global Post-Hoc Method Based On Abstract Argumentation For Explainable Artificial Intelligence And Its Application On Fully Connected Dense Deep Neural Networks, Giulia Vilone

Dissertations

Explainable Artificial Intelligence (XAI) has rapidly grown in the past decade due to the prevalence of machine learning, especially deep learning, in fields like healthcare and finance. While these models excel in accuracy, their complexity hampers transparency and interpretability. Ensuring understandable explanations for AI predictions fosters trust, prevents errors, complies with regulations, and enhances model refinement. The research project outlined in this thesis unfolds in phases. It commences with a comprehensive review of existing XAI studies, contributing to the field’s knowledge by proposing a taxonomy that organises theories and notions related to explainability, the evaluation approaches for XAI methods, and …

Privacy-Preserving Pedestrian Movement Analysis In Complex Public Spaces, Kunchala Anil

Doctoral

Every journey starts and ends with a walking phase. As a fundamental mode of transportation, it plays a crucial role in the functioning of urban societies. Cities should strive to create public spaces that promote walking by designing pedestrian-friendly infrastructure that is accessible, safe, and convenient for all. An essential step in designing pedestrian-friendly infrastructure is understanding pedestrian usage patterns and behaviour in existing public spaces and infrastructure.

Artificial Intelligence In Education: Mathematics Teachers’ Perspectives, Practices And Challenges, Mohammad A. Tashtoush, Yousef Wardat, Rommel Al Ali, Shoeb Saleh

Iraqi Journal for Computer Science and Mathematics

Efforts have been made to include artificial intelligence (AI) in teaching and learning; nevertheless, the successful deployment of new instructional technology depends on the attitudes of the teachers who conduct the lesson. Few scholars have researched teachers' perspectives on AI use due to a general lack of expertise on how it can be used in the classroom, as well as a lack of specific knowledge about what AI-adopted tools would be like. This study investigated mathematics teachers’ perceptions of implemented AI systems and applications in Abu Dhabi Emirate schools. The sample study consists of 580 male and female math teachers …

Context-Free Grammar Framework For Automatic Shooting Game Enemy Pattern Generation, Nitit Kaweeratanakit

Chulalongkorn University Theses and Dissertations (Chula ETD)

This research proposes a framework for generating enemy patterns for SHMUPs game. It is directly based on a grammar derived from the enemy behavior of existing commercial SHMUPs, and implemented using a new description language called "Enemy Pattern Description Language" (EPDL). EPDL contains all information required to construct the enemy, with no requirement of external data content. The language is human-readable and can be connected to any game engine of choice using an EPDL interpreter. The interpreter itself consists of lexer and recursive descent parser. The results shown in this research is implemented in. "rdnh", a private fork of Touhou …

การพยากรณ์การจ่ายยาของโรงพยาบาลโดยการเรียนรู้ของเครื่องและวิธีการวิเคราะห์เชิงสถิติ, วริศ ปุณณะหิตานนท์

Chulalongkorn University Theses and Dissertations (Chula ETD)

ในปัจจุบันการพยากรณ์การจ่ายยาของโรงพยาบาลถือเป็นหัวใจสำคัญต่อการจัดการคลังยาและการสั่งซื้อยาเป็นอย่างมาก เนื่องจากการพยากรณ์ที่น้อยเกินไปทำให้ยาไม่เพียงพอส่งผลให้เกิดความล่าช้าภายในโรงพยาบาล ในขณะที่การพยากรณ์ที่มากเกินไปทำให้เปลืองพื้นที่ใช้สอยและอาจทำให้ยาเสื่อมสภาพหรือหมดอายุซึ่งส่งผลให้โรงพยาบาลสูญเสียรายได้ การมีแบบจำลองที่สามารถพยากรณ์ปริมาณการจ่ายยาให้ใกล้เคียงกับค่าจริงจะสามารถลดปัญหาการขาดแคลนยาในแต่ละห้องจ่ายยาหรือการที่ห้องจ่ายยามีการกักตุนตัวยาเกินความจำเป็น จากปัญหาที่กล่าวมาข้างต้น โครงงานมหาบัณฑิตนี้จึงถูกจัดทำขึ้นเพื่อนำเสนอแบบจำลองที่จะมาแทนค่าเฉลี่ยเคลื่อนที่แบบทั่วไปซึ่งจะช่วยให้โรงพยาบาลสามารถพยากรณ์ปริมาณการจ่ายยาแต่ละวันได้แม่นยำมากขึ้น โดยจะนำเทคนิคสำหรับพยากรณ์ข้อมูลที่อยู่ในรูปแบบของอนุกรมเวลามาประยุกต์ใช้กับข้อมูลการจ่ายยาย้อนหลังและข้อมูลการนัดหมายแพทย์ย้อนหลัง หลังจากนั้นจะนำผลลัพธ์ที่ได้มาคำนวณค่าเคลาดเคลื่อนด้วยค่าเฉลี่ยของเปอร์เซ็นต์ความคลาดเคลื่อนสัมบูรณ์และค่าเฉลี่ยสมมาตรของเปอร์เซ็นต์ความคลาดเคลื่อนสัมบูรณ์และนำผลที่ได้มาใช้ในการเลือกว่าแบบจำลองไหนให้ค่าคลาดเคลื่อนต่ำที่สุด ผลการทดลองพบว่าแบบจำลองซัพพอร์ตเวกเตอร์รีเกรสชันให้ค่าความคลาดเคลื่อนที่ต่ำกว่าค่าเฉลี่ยเคลื่อนที่แบบทั่วไป แบบจำลองที่ผู้จัดทำโครงงานนำเสนอสามารถนำไปประยุกต์ใช้กับการพยากรณ์การจ่ายยาเพื่อให้แต่ละห้องจ่ายยามียาสำหรับให้บริการในปริมาณที่เพียงพอต่อความต้องการ

Uncertainty Quantification In Large Language Models Through Convex Hull Analysis, Ferhat Ozgur Catak, Murat Kuzlu

Engineering Technology Faculty Publications

Uncertainty quantification approaches have been more critical in large language models (LLMs), particularly high-risk applications requiring reliable outputs. However, traditional methods for uncertainty quantification, such as probabilistic models and ensemble techniques, face challenges when applied to the complex and high-dimensional nature of LLM-generated outputs. This study proposes a novel geometric approach to uncertainty quantification using convex hull analysis. The proposed method leverages the spatial properties of response embeddings to measure the dispersion and variability of model outputs. The prompts are categorized into three types, i.e., ’easy’, ’moderate’, and ’confusing’, to generate multiple responses using different LLMs at varying temperature settings. …

Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

Multimodal Human Action Recognition (MHAR) is an important research topic in computer vision and event recognition fields. In this work, we address the problem of MHAR by developing a novel audio-image and video fusion-based deep learning framework that we call Multimodal Audio-Image and Video Action Recognizer (MAiVAR). We extract temporal information using image representations of audio signals and spatial information from video modality with the help of Convolutional Neutral Networks (CNN)-based feature extractors and fuse these features to recognize respective action classes. We apply a high-level weights assignment algorithm for improving audio-visual interaction and convergence. This proposed fusion-based framework utilizes …

Assessing The Condition Of Pavements (Road Surfaces) Using Computer Vision & Machine Learning, Syed Ibrahim Hassam

Doctoral

Regular inspections of pavements are conducted by civil infrastructure departments to evaluate the surface condition. Pavement surfaces are subject to deterioration caused by several factors such as traffic, weather, and sunlight. This deterioration becomes evident through various distresses, including potholes, rutting, cracking, bleeding, patching, and ravelling, which gradually affects the surface layer over time. It is essential to assess the condition of pavements as it not only ensures their usability but also maximises public safety. Effective pavement maintenance requires substantial resources and capital investment to carry out the most suitable maintenance treatments at the optimal time. Furthermore, the outcomes of …

Information Access For Infrastructurally-Challenged Environments And Beyond Through Mutually Aware Spectrum Sharing Technologies, Karyn Doke

Electronic Theses & Dissertations (2024 - present)

The Radio Frequency (RF) spectrum is scarce and to make it available for new mobile wireless services, regulators are forced to re-allocate spectrum from existing services or develop mechanisms to share spectrum with new entries. Television White Space (TVWS) and Citizen Broadband Radio Service (CBRS) are two examples of recently commercialized spectrum sharing technologies. TVWS enables sharing among fixed wireless broadband technologies (secondary users) and terrestrial TV broadcast services (primary users). CBRS enables spectrum sharing among 5G/LTE (secondary users) and naval radar (primary users). With both technologies, a central database determines when it is safe for secondary users to operate …

Transformer-Enabled Deep Reinforcement Learning For Coverage Path Planning, Daniel B. Tiu

UNF Graduate Theses and Dissertations

Coverage path planning (CPP) is the problem of covering all points in an environment and is a well-researched topic in robotics due to its sheer practical relevance. This paper investigates such an offline CPP problem where the primary objective is to minimize the path length to achieve complete coverage. Furthermore, the literature suggests that taking turns leads to a higher energy use than going straight. To this end, we design a novel objective function that aims to minimize the number of turns as well. We have proposed a deep reinforcement learning (DRL)-based framework that uses a Transformer model. Unlike state-of-the-art …

Explainable Automated Inconsistency Detection In Biomedical And Health Literature, Prajwol Lamichhane

UNF Graduate Theses and Dissertations

Given the exponential growth of scientific information online, researchers often face the daunting task of detecting contradictory statements on crucial health topics. This work develops a comprehensive pipeline for automated contradiction detection that integrates an Information Retrieval (IR) system, machine learning classifiers, and Explainable AI (XAI). The Information Retrieval system is tailored for biomedical data and comprises a datastore, syntactic, and semantic components. Users can input queries, initiating a pipeline that identifies top documents through syntactic analysis and refines results via semantic examination for relevant research claims. Employing a diverse range of Large Language Models such as pre-trained Distil-BERT, BioBERT, …

Implementation Of Algorithms For Sorting By Strip Swaps Using Alternating Cycle Graphs, Harsh S. Bhakharia

UNF Graduate Theses and Dissertations

Challenges in computational biology, such as genome rearrangement, and applications in optical character recognition, like zoning techniques, often require solving optimization problems. These involve reordering scrambled sequences of numbers into a sequential arrangement known as the identity permutation.

Rearranging any given permutation into the identity permutation with the minimum number of specific operations related to strips gives rise to various combinatorial optimization scenarios. Operations such as strip moves, transpositions, reversals, and block interchanges have been extensively researched.

This thesis builds on the foundational work of Roy et al., targeting the refinement of their cycle graph algorithm for sorting by strip …

Large Language Models For Multimodal User Interaction In A Virtual Environment, Ahmed A. Sayed

UNF Graduate Theses and Dissertations

Virtual Reality (VR) is increasingly popular, but many barriers exist for individuals with little experience in coding, 3D modeling, or creating their own virtual experiences. The current tools used for content creation are often viewed as complex or frustrating, and they exhibit a steep learning curve. This problem presents an opportunity to develop tools incorporating Natural User Interfaces that better support end users. One such possible tool to assist users is Large Language Models (LLM), which can, extract a user's intention through speech or text. We posit how using LLMs can better support novice and expert developers alike, and using …

Expanding Australia's Defence Capabilities For Technological Asymmetric Advantage In Information, Cyber And Space In The Context Of Accelerating Regional Military Modernisation: A Systemic Design Approach, Pi-Shen Seet, Anton Klarin, Janice Jones, Michael N. Johnstone, Violetta Wilk, Stephanie Meek, Summer O'Brien

Research outputs 2022 to 2026

Introduction. The aim of the project was to conduct a systemic design study to evaluate Australia'sopportunities and barriers for achieving a technological advantage in light of regional military technological advancement. It focussed on the three domains of (1) cybersecurity technology, (2) information technology, and (3) space technology.

Research process. Employing a systemic design approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding of the interdisciplinary nature of defence technologies, identifying key areas for further exploration. The subsequent survey study, engaging 828 …

A Review Of Textmining Techniques: Trends, And Applications In Various Domains, Hiba J. Aleqabie, Mais Saad Sfoq, Rand Abdulwahid Albeer, Enaam Hadi Abd

Iraqi Journal for Computer Science and Mathematics

Text mining, a subfield of natural language processing (NLP), has received considerable attention in recent years due to its ability to extract valuable insights from large volumes of unstructured textual data. This review aims to provide a comprehensive evaluation of the applicability of text mining techniques across various domains and industries. The reviewstarts off with a dialogue of the basic ideas and methodologies that are concerned with textual content mining together with preprocessing, feature extraction, and machine learning algorithms. Furthermore, this survey highlights the challenges faced at some stage in implementing textual content mining strategies. Additionally, the review explores emerging …

Applications For The Groups , Where Prime Upper Than 9, Lemya Abd Alameer Hadi, Mahmood S. Fiadh, Niran Sabah Jasim, Jabbar Abed Eleiwy

Iraqi Journal for Computer Science and Mathematics

The problem of finding the cyclic decomposition (c.d.) for the groups ), where prime upper than 9 is determined in this work. Also, we compute the Artin characters (A.ch.) and Artin indicator (A.ind.) for the same groups, we obtain that after computingthe conjugacy classes, cyclic subgroups, the ordinary character table (o.ch.ta.) and the rational valued character table for each group.

Magnetometer-Less State-Estimation Of A Mobile Robot Using Cascaded Kalman Filters, Tommy Le

Graduate Research Theses & Dissertations

Localization, or state-estimation algorithms, are one of the most important aspects inthe development of autonomous mobile robots. Typical localization requires an IMU (Inertial Measurement Unit) along with an external reference, such as GPS (Global Positioning System) for outdoor applications. In indoor applications, the GPS data is not accessible so many mobile robot implementations turn to magnetometers to provide additional pose information. However, in the context of miniaturizing robotic systems, magnetometers are not always reliable due to their proximity to motors and other electronics, causing magnetic distortion and in turn, incorrect pose information. To address this issue, this thesis proposes a …

The Impact Of Ai In Gaming Industry, Huang Xiaorong

MA Theses

With the rapid development of artificial intelligence (AI) technology, the application
of AI art in game development is becoming increasingly popular. AI art can not only help game developers speed up the creative process but also improve the visual quality and user experience of games. This paper provides an overview of the application of AI art in games, including character design, scene generation, animation production, and more. It also discusses the challenges and future directions of AI art. Through comprehensive analysis of existing research and practices, we find that AI art has tremendous potential in game development but still faces …