Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- China Simulation Federation (3305)
- TÜBİTAK (3006)
- Wright State University (1766)
- University of Nebraska - Lincoln (1099)
- University of Texas at El Paso (843)
-
- Selected Works (836)
- Washington University in St. Louis (717)
- Technological University Dublin (654)
- Brigham Young University (642)
- California Polytechnic State University, San Luis Obispo (602)
- Embry-Riddle Aeronautical University (522)
- Singapore Management University (483)
- Universitas Indonesia (435)
- Old Dominion University (395)
- Marquette University (387)
- Air Force Institute of Technology (374)
- Santa Clara University (303)
- University of South Carolina (278)
- SelectedWorks (275)
- University of Central Florida (249)
- Portland State University (246)
- California State University, San Bernardino (243)
- Purdue University (212)
- Western University (192)
- Nova Southeastern University (171)
- New Jersey Institute of Technology (166)
- University of Arkansas, Fayetteville (165)
- University of Dayton (165)
- University of Massachusetts Amherst (165)
- University of Nevada, Las Vegas (164)
- Keyword
-
- Machine learning (353)
- Computer Science (329)
- Department of Computer Science and Engineering (272)
- Engineering (260)
- Deep learning (247)
-
- Simulation (230)
- Robotics (206)
- Machine Learning (200)
- Security (187)
- College of Engineering and Computer Science (157)
- Newsletters (157)
- Optimization (157)
- Science news (157)
- Technical writing (157)
- Classification (148)
- Artificial intelligence (130)
- Deep Learning (126)
- Computer Science and Engineering (121)
- Computer Engineering (117)
- Cybersecurity (114)
- Genetic algorithm (108)
- Internet (106)
- Computer vision (105)
- Data mining (96)
- Computer science (93)
- Privacy (93)
- Artificial Intelligence (88)
- Blockchain (87)
- Particle swarm optimization (87)
- Clustering (86)
- Publication Year
- Publication
-
- Journal of System Simulation (3305)
- Turkish Journal of Electrical Engineering and Computer Sciences (3006)
- Computer Science & Engineering Syllabi (1312)
- Departmental Technical Reports (CS) (760)
- All Computer Science and Engineering Research (683)
-
- International Congress on Environmental Modelling and Software (630)
- Theses and Dissertations (560)
- Department of Electrical and Computer Engineering: Faculty Publications (483)
- Research Collection School Of Computing and Information Systems (451)
- Makara Journal of Technology (433)
- Electrical and Computer Engineering Faculty Research and Publications (367)
- Electronic Theses and Dissertations (352)
- Faculty Publications (317)
- Dissertations (310)
- Journal of Digital Forensics, Security and Law (299)
- Browse all Theses and Dissertations (295)
- Computer Engineering (273)
- Electrical and Computer Engineering Faculty Publications (209)
- Masters Theses (207)
- Computer Science and Engineering Senior Theses (201)
- Department of Computer Science and Engineering: Dissertations, Theses, and Student Research (191)
- Doctoral Dissertations (187)
- Master's Theses (187)
- Conference papers (163)
- BITs and PCs Newsletter (157)
- College of Engineering and Computing Course Catalogs (152)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (149)
- USF Tampa Graduate Theses and Dissertations (133)
- Publications (131)
- Articles (130)
- Publication Type
Articles 271 - 300 of 23840
Full-Text Articles in Entire DC Network
Mechanism Design For Optimizing On-Chain Sell Order In Market Without Market Maker, Nico Pei
Mechanism Design For Optimizing On-Chain Sell Order In Market Without Market Maker, Nico Pei
CMC Senior Theses
The absence of market makers alters the microstructure of the market. It’s difficult to get exposed to time-weighted prices in markets without market makers. In this paper, we delve into three mechanism designs – discrete gradual dutch auction, continuous gradual dutch auction, and variable rate gradual dutch auction – to study how to execute time-weighted sell orders on blockchain in a market without market makers. To make it simpler for readers to understand, we imagine an example of helping a close friend of Picasso to sell his 100 Picasso paintings in the next 10 years since 1970, with the private …
Regional Sea Level Rise Prediction In Monterey Bay With Lstms And Vertical Land Motion, Branden Lopez
Regional Sea Level Rise Prediction In Monterey Bay With Lstms And Vertical Land Motion, Branden Lopez
Master's Projects
Earth system data is vast in volume and variety, and is used to forecast weather,
hurricanes, floods, and sea level. Sea Level Rise (SLR) impacts various sectors, espe- cially ecosystems, food production, industry, population, health, and the availability of
clean water. Because of its broad impact, describing the behavior and forecasting SLR is an important topic. Traditional Machine Learning (ML) models vary in use, but many are not capable of capturing all the non-linear spatial and temporal properties of SLR factors. Deep learning models efficaciously handle complex time series data, noise, and high dimensional spaces, making them a focus of …
Factors Affecting The Adoption Of Information Technology In Medium And Small Enterprises: A Case Study In Mekong Delta, Vietnam, Thy-Lieu Nguyen-Thi, Duy-Dong Le, Kieu-Chinh Nguyen-Ly, Trung-Tien Nguyen, Mohamed Saleem Haja Nazmudeen
Factors Affecting The Adoption Of Information Technology In Medium And Small Enterprises: A Case Study In Mekong Delta, Vietnam, Thy-Lieu Nguyen-Thi, Duy-Dong Le, Kieu-Chinh Nguyen-Ly, Trung-Tien Nguyen, Mohamed Saleem Haja Nazmudeen
ASEAN Journal on Science and Technology for Development
This research endeavors to discern the determinants influencing the adoption of information technology in the management practices of small and medium-sized enterprises (SMEs) situ-ated within the Mekong Delta region of Vietnam. Leveraging the Unified Theory of Ac-ceptance and Use of Technology (UTAUT), PLS-SEM, and ANN models, this study ranks the pivotal factors that impact the decision to integrate information technology into SME management. The identified factors, in order of significance, encompass (1) Support from State Agencies, (2) Managerial Qualifications, (3) Competitive Landscape, (4) Enterprise Scale, and (5) Employee Qualifications. The investigation encompasses 496 SMEs across the Mekong Delta and evaluates …
A New Cache Replacement Policy In Named Data Network Based On Fib Table Information, Mehran Hosseinzadeh, Neda Moghim, Samira Taheri, Nasrin Gholami
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 …
Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie
Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie
Electrical and Computer Engineering Faculty Publications
Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel …
Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu
Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu
Electrical and Computer Engineering Faculty Publications
Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can …
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
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
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
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 …
Applications Of Predictive And Generative Ai Algorithms: Regression Modeling, Customized Large Language Models, And Text-To-Image Generative Diffusion Models, Suhaima Jamal
Electronic Theses and Dissertations
The integration of Machine Learning (ML) and Artificial Intelligence (AI) algorithms has radically changed predictive modeling and classification tasks, enhancing a multitude of domains with unprecedented analytical capabilities. Predictive modeling leverages ML and AI to forecast future trends or behaviors based on historical data, while classification tasks categorize data into distinct classes, from email filtering to medical diagnosis. Concurrently, text-to-image generation has emerged as a transformative potential, allowing visual content creation directly from textual descriptions. These advancements are pivotal in design, art, entertainment, and visual communication, as well as enhancing creativity and productivity. This work explores three significant studies in …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
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 …
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Publications
Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance1.
Stock Price Trend Prediction Using Emotion Analysis Of Financial Headlines With Distilled Llm Model, Rithesh H. Bhat
Stock Price Trend Prediction Using Emotion Analysis Of Financial Headlines With Distilled Llm Model, Rithesh H. Bhat
Computer Science and Engineering Theses
Capturing the volatility of stock prices helps individual traders, stock analysts, and institutions alike increase their returns in the stock market. Financial news headlines have been shown to have a significant effect on stock price mobility. Lately, many financial portals have restricted web scraping of stock prices and other related financial data of companies from their websites. In this study we demonstrate that emotion analysis of financial news headlines alone can be sufficient in predicting stock price movement, even in the absence of any financial data. We propose an approach that eliminates the need for web scraping of financial data. …
Development Of A Collaborative Research Platform For Efficient Data Management And Visualization Of Qubit Control, Devanshu Brahmbhatt
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 …
Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora
Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora
Computer Science and Engineering Theses
This thesis delves into the intricate symbiosis between machine learning (ML) methodologies and embedded hardware systems, with a primary focus on augmenting efficiency and real-time processing capabilities across diverse application domains. It confronts the formidable challenge of deploying sophisticated ML algorithms on resource-constrained embedded hardware, aiming not only to optimize performance but also to minimize energy consumption. Innovative strategies are explored to tailor ML models for streamlined execution on embedded platforms, with validation conducted across various real-world application domains. Notable contributions include the development of a deep-learning framework leveraging a variational autoencoder (VAE) for compressing physiological signals from wearables while …
Joint Learning Of Unknown Safety Constraints And Control Policies In Reinforcement Learning, Lunet Abiye Yifru
Joint Learning Of Unknown Safety Constraints And Control Policies In Reinforcement Learning, Lunet Abiye Yifru
Graduate Theses, Dissertations, and Problem Reports
Reinforcement learning (RL) has revolutionized decision-making across a wide range of domains over the past few decades. Yet, deploying RL policies in real-world scenarios presents the crucial challenge of ensuring safety. Traditional safe RL approaches have predominantly focused on incorporating predefined safety constraints into the policy learning process. However, this reliance on predefined safety constraints poses limitations in dynamic and unpredictable real-world settings where such constraints may not be available or sufficiently adaptable. Bridging this gap, we propose a novel approach that concurrently learns a safe RL control policy and identifies the unknown safety constraint parameters of a given environment. …
On The Performance Of A Photonic Reconfigurable Electromagnetic Band Gap Antenna Array For 5g Applications, Taha A. Elwi, Fatma Taher, Bal S. Virdee, Mohammad Alibakhshikenari, Ignacio J.Garcia Zuazola, Astrit Krasniqi, Amna Shibib Kamel, Nurhan Turker Tokan, Salahuddin Khan, Naser Ojaroudi Parchin, Patrizia Livreri, Iyad Dayoub, Giovanni Pau, Sonia Aissa, Ernesto Limiti, Mohamed Fathy Abo Sree
On The Performance Of A Photonic Reconfigurable Electromagnetic Band Gap Antenna Array For 5g Applications, Taha A. Elwi, Fatma Taher, Bal S. Virdee, Mohammad Alibakhshikenari, Ignacio J.Garcia Zuazola, Astrit Krasniqi, Amna Shibib Kamel, Nurhan Turker Tokan, Salahuddin Khan, Naser Ojaroudi Parchin, Patrizia Livreri, Iyad Dayoub, Giovanni Pau, Sonia Aissa, Ernesto Limiti, Mohamed Fathy Abo Sree
All Works
In this paper, a reconfigurable Multiple-Input Multiple-Output (MIMO) antenna array is presented for 5G portable devices. The proposed array consists of four radiating elements and an Electromagnetic Band Gap (EBG) structure. Planar monopole radiating elements are employed in the array with Coplanar Waveguide Ports (CWPs). Each CWP is grounded on one side to a reflecting L-shaped structure that has an effect of improving the antenna's directivity. It is shown that by inductively connecting Minkowski fractal structure of 1^{st} order to the radiating element, the impedance matching is improved that results in enhancement in the array's bandwidth performance. The EBG structure …
The Effects Of Ai Image Synthesis On Graphic Design, Ji Ren
The Effects Of Ai Image Synthesis On Graphic Design, Ji Ren
MA Theses
From 1763 when Thomas Bayes developed a framework to infer event probabilities, to the end of 2022 when the world-renowned AI research laboratory Open AI launched Chat GPT, a language model based on AI technology, statistical computing-based AI has revolutionized human life. AI image synthesis can simulate the processes and methods of human painting through machine learning, deep learning, and other methods, thereby generating high-fidelity images. There is growing concern about how AI image synthesis will affect the art world as it advances. The art market could be reimagined, authorship and creativity concepts challenged, and traditional artistic practices disrupted by …
Dp-Smote: Integrating Differential Privacy And Oversampling Technique To Preserve Privacy In Smart Homes, Amr Tarek Elsayed, Almohammady Sobhi Alsharkawy, Mohamed Sayed Farag, Shaban Ebrahim Abu Yusuf
Dp-Smote: Integrating Differential Privacy And Oversampling Technique To Preserve Privacy In Smart Homes, Amr Tarek Elsayed, Almohammady Sobhi Alsharkawy, Mohamed Sayed Farag, Shaban Ebrahim Abu Yusuf
Al-Azhar Bulletin of Science
Smart homes represent intelligent environments where interconnected devices gather information, enhancing users’ living experiences by ensuring comfort, safety, and efficient energy management. To enhance the quality of life, companies in the smart device industry collect user data, including activities, preferences, and power consumption. However, sharing such data necessitates privacy-preserving practices. This paper introduces a robust method for secure sharing of data to service providers, grounded in differential privacy (DP). This empowers smart home residents to contribute usage statistics while safeguarding their privacy. The approach incorporates the Synthetic Minority Oversampling technique (SMOTe) and seamlessly integrates Gaussian noise to generate synthetic data, …
Machine Learning For Environmental Sustainability, Syeda Nyma Ferdous
Machine Learning For Environmental Sustainability, Syeda Nyma Ferdous
Graduate Theses, Dissertations, and Problem Reports
This research proposes a comprehensive approach to address pressing challenges in environmental sustainability, agricultural residue management, using machine learning based approaches. Machine learning (ML) techniques have emerged as powerful tools for addressing environmental sustainability challenges by facilitating the analysis and prediction of ecological phenomena, and optimization of resource management strategies. The study explores the synergies between environmental sustainability and machine learning to develop a framework that leverages artificial intelligence techniques covering a wide range of tasks including crop residue management, soil CO2 flux prediction, and forest carbon system prediction for sustainable development. The study analyze various ML models, such as, …
Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
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 …
Midi Recorder And Learning Tool, Caden Dees, Saikishore Gowrishankar, Cameron Johnson, Benjamin Bolyard
Midi Recorder And Learning Tool, Caden Dees, Saikishore Gowrishankar, Cameron Johnson, Benjamin Bolyard
Williams Honors College, Honors Research Projects
The project's goal is to create a device that can record MIDI files from any standard 88-key piano as well as teach piano learners how to play songs.
Children's Hospital Animatronic, Erin Keller, Wesley Cunningham, Dylan Mueller, Carl Richter
Children's Hospital Animatronic, Erin Keller, Wesley Cunningham, Dylan Mueller, Carl Richter
Williams Honors College, Honors Research Projects
This senior project explores the development of a pediatric-oriented animatronic designed to enhance the hospital experience for children. Recognizing the importance of alleviating the anxiety and fear that often accompany hospital visits, the project focuses on creating an engaging and interactive companion to soothe children.
Key components of this project include:
-
Creative Design: The animatronic character's design prioritizes child-friendliness, employing research into child psychology and preferences to ensure an appealing and approachable aesthetic.
-
Electrical and Mechanical Engineering: A robust mechanical and electronic system was engineered to enable lifelike movements, gestures, and responses.
-
Interactive Features: A simple, user-friendly app will be …
Smart Dog Door, Andrew Shetler, William Boissoneault, Jacob Stump, Benjamin Charlson
Smart Dog Door, Andrew Shetler, William Boissoneault, Jacob Stump, Benjamin Charlson
Williams Honors College, Honors Research Projects
With modern life getting busier and more complex, many have turned to autonomous assistance for taking care of pets. The objective of this project is to design and prototype a device and application that will allow only certain dogs to enter and exit through a dog door while making the owners aware of their dog's activity. The dog door will utilize wireless communication from the dog to the door to control the status of the door’s lock and update the database that will send updates to the application. The application will keep track of when the dog enters and exits …
Autonomous Damage And Structure Scanning Drone, Natasha Ninan, Amber Long, Lee Nestor, Emmanuel Jensen
Autonomous Damage And Structure Scanning Drone, Natasha Ninan, Amber Long, Lee Nestor, Emmanuel Jensen
Williams Honors College, Honors Research Projects
Remote damage analysis plays a crucial role in lowering the risk associated with human presence at dangerous sites. This project focuses on developing a system for remote structural examination using photogrammetric techniques and analysis. The system utilizes a drone equipped with cameras for photogrammetry, and LiDARs for navigation. This setup can enable efficient structural model generation with the collection of images from multiple points. A novel structural analysis is performed to detect potential damage or points of failure in the structure.
Key components include a teleoperated drone, a software pipeline for photogrammetric analysis, collision protection mechanisms, and a user interface. …
Improved Portable Back Pain Relief Device With User Interface, Zachary Bobango, Samuel J. Dauterman, Benjamin Bowman
Improved Portable Back Pain Relief Device With User Interface, Zachary Bobango, Samuel J. Dauterman, Benjamin Bowman
Williams Honors College, Honors Research Projects
The objective of this project is to design and create a massage system that is user interactive, portable, safe, efficient, and comfortable. The system should allow for user feedback from an outside peripheral such as a phone to be able to modify the system. Some challenges facing the implementation of such a system include: ensuring the product can withstand substantial force without breaking or malfunctioning while simultaneously being light enough for a consumer to carry without difficulty, engineering the massage heads to be able to move in multiple different motion types, creating the software that can control the device, and …
Managing Inventory With A Database, David Bartlett
Managing Inventory With A Database, David Bartlett
Williams Honors College, Honors Research Projects
Large commercial companies often use warehouses to store and organize their product inventory. However, manually keeping track of inventory through physical means can be a tedious process and is at risk for a variety of potential issues. It is very easy for records to be inaccurate or duplicated, especially if large reorganizations are undertaken, as this can cause issues such as duplicate product ID numbers. Therefore, it was decided that an inventory management system utilizing a SQL database should be created. The system needed to have capabilities including allowing the entry of product information, the ability to search database records …
Autonomous Basketball Court Creation Robot, Bryce Haldeman, Tyler Gray, Dalon Vura
Autonomous Basketball Court Creation Robot, Bryce Haldeman, Tyler Gray, Dalon Vura
Williams Honors College, Honors Research Projects
The Autonomous Basketball Court Outlining System presents a comprehensive solution for precision court marking. Powered by a 24V lithium-ion battery and driven by a single ST microcontroller, the system autonomously marks the outline of a half basketball court using predefined algorithms. User-friendly features include easy loading of marking material, actuated by gravity or a small servo motor depending on material of choice, ensuring intuitive operation. Safety is prioritized, with the servo motor eliminating high-pressure concerns, and the system maintains a controlled speed accounting for user well-being. Two step and direction servo motors enable accurate linear displacement, facilitating straight lines, and …
Unity Two Dimensional C# Game, Nick Zajac
Unity Two Dimensional C# Game, Nick Zajac
Williams Honors College, Honors Research Projects
My project is a 2-dimensional game that is being developed in the unity engine. This project includes animating objects, having them interact with each other, and having a goal the player will want to complete in the game. It will be a game that involves the player character moving around, attacking enemies, and dodging enemies. There will also be some challenges that involve maneuvering between platforms and enemies to progress in the game. At the end of the level, the player will encounter a stronger boss character. This character will have movement and attack patterns similar to the other minor …
Constructing And Probing A Fortified Network, Maxim Davis
Constructing And Probing A Fortified Network, Maxim Davis
Williams Honors College, Honors Research Projects
Computer networking is extremely valuable and is essential to modern infrastructure and life. Due to this fact, network security is also extremely vital and is also constantly under attack due to how precious information is in the modern world. In order to set up network security and harden systems from attack, many organizations establish guidelines, standards and techniques to defend against such threats. There is also the major issue of needing to constantly test these different standards and procedures regarding network security as if these security measures are not tested, the danger of potential threats is exponential. This project seeks …