Computer Sciences Commons^™

Hristudio: A Framework For Wizard-Of-Oz Experiments In Human-Robot Interaction Studies, Luiz Felipe Perrone, Sean O'Connor

Faculty Conference Papers and Presentations

Human-robot interaction (HRI) research plays a pivotal role in shaping how robots communicate and collaborate with humans. However, conducting HRI studies, particularly those employing the Wizard-of-Oz (WoZ) technique, can be challenging. WoZ user studies can have complexities in technical and methodological level that may render the results irreproducible. We propose to address these challenges with HRIStudio, a novel web-based platform designed to streamline the design, execution, and analysis of WoZ experiments. HRIStudio offers an intuitive interface for experiment creation, real-time control and monitoring during experimental runs, and comprehensive data logging and playback tools for analysis and reproducibility. By lowering technical …

Ai And Academic Integrity, Max Sparkman Research Instruction Librarian, Milne Library, Brandon West Head Of Research & Instruction, Milne Library

Artificial Intelligence, 2024-25

This short module introduces students to important concepts regarding the use of AI and academic integrity. Concepts covered include a brief overview of generative AI, whether or not their use is considered plagiarism, how to use generative AI tools responsibly, and potential use cases. The module ends with a quiz where students can apply concepts from the module to three scenarios.

Module: Ai And Value-Neutrality, Jonathan Auyer Ph.D., Department Of Philosophy

Artificial Intelligence, 2024-25

Artificial Intelligence is on the tips of everyone’s tongues these days – What exactly is it? What will can it be used for? What will it be used for in the future? What problems will it create or solve or exacerbate? This learning module aims to look at a specific facet of AI — the issue of value-neutrality — by having students look inward at capabilities necessary for human flourishing and then ask whether AI can cultivate (or inhibit) those capabilities. This will lead to a discussion of what values underlie AI and what this says about whether or not …

Chatgpt Can Write My Class Assignments, Right?: A Guided Classroom Activity For Teaching The Strengths And Weaknesses Of Generative-Ai Tools, Dr. Peter J. Kalenda Assistant Professor, Elementary Science & Math, School Of Education

Artificial Intelligence, 2024-25

This module is designed to support your undergraduate or graduate students with developing an understanding of:

• How to use generative-AI tools, like ChatGPT,
• The strengths and weaknesses of generative-AI tools for completing different tasks,
• How to design and revise a classroom presentation that is aligned with course topics and objectives by using generative-AI tools as a resource, and
• How to engage in prompt engineering and prompt revision for generative-AI tools.

Your students are being tasked with creating an engaging presentation they will deliver to their peers that aligns with the topics and learning objectives of your course. However, they will …

As Soon As [A]I Speak[S], Lytton Smith Professor Of Poetry, Department Of English

Artificial Intelligence, 2024-25

This guide facilitates the delivery of a two-workshop sequence allowing students to understand how an Artificial Intelligence (AI) Large Language Model (LLM) composes poetry, and to use that knowledge to compose their own poem for optional display in both electronic and physical form. Students may participate in either/both workshops, and in each will engage in reflective work to understand how AI impacts them and vice versa. This guide and curriculum aligns with the "Contemporary Global Challenges, Creativity and Innovation" Participation in a Global Society outcome within the Geneseo GLOBE Curriculum.

Creating A Business In 50 Minutes With Ai, Mark A. Rider Vanarsdale Chair In Entrepreneurship, School Of Business

Artificial Intelligence, 2024-25

This lesson plan explores using artificial intelligence (AI) to enhance the process of business idea generation and validation. Over a dynamic 50-minute workshop, students will engage with AI tools, particularly Microsoft's Copilot, to develop viable business concepts aligned with their personal interests and market needs.

The session begins with the Ikigai exercise, guiding students to identify their passions, strengths, and potential economic opportunities. Following this, students will use AI to engage in divergent thinking, generating a wide range of business ideas and refining them through iterative prompts until they find promising concepts.

In the validation phase, students will employ AI …

Using Ai In Higher Ed: Is It Cheating?, David Levy Associate Professor & Chair Of Philosophy

Artificial Intelligence, 2024-25

Students generate a course-based or college-wide policy regarding the use of Generative AI, based on assigned readings, discussion, practice using the tools on writing assignments.

Psychology And The Digital Everywhere: Artificial Intelligence, Cassie Van Stolk Assistant Professor Of Psychology, Department Of Psychology

Artificial Intelligence, 2024-25

This module within the PSYC 390: Psychology and the Digital Everywhere course investigates the the implications of AI on human experiences using a biopsychosocial lens. Topics covered include an exploration of AI as a tool versus as an autonomous mind, ethical considerations of AI usage, and the promises and pitfalls of AI as a tool within the field of psychology. This module aligns with the "Contemporary Global Challenges, Creativity and Innovation" Participation in a Global Society outcome within the Geneseo GLOBE Curriculum.

Real Time Pii Scanning, John David

Electronic Theses and Dissertations

The increased amount of web applications and internet software solutions utilizing cloud frameworks has contributed to large data sets of system log messages being generated constantly. These messages may contain sensitive data, creating an additional security risk for the systems and contributing to the need for analysis of such large volumes of data in real time. Large commercial data monitoring systems can solve for these analysis requirements, but they can be costly. We present a solution to analyzing web application log data which ingests it, processes it and visualizes sensitive data found within in real time. Our solution utilizes an …

Heterogeneous Multi-Robot Person-Following In Constrained Environments, Ori A. Miller

Electronic Theses and Dissertations

Maintaining visibility of a person requires effective systems. Security cameras or ground robots might be ideal, but they often fail in uncontrolled or unknown environments. A single ground robot struggles to navigate and track an agent at the same time. This work addresses the challenge by developing a multi-robot system with a slow ground robot and an agile aerial robot. Three methods are evaluated: FORWARD-PF, RL-Person Following (RL), and a baseline closed-loop method. FORWARD-PF proved the most reliable, completing all nine paths and reaching targets nearly twice as fast as RL. Despite completing seven paths, RL faltered on complex tasks. …

Integrating Authentication Schemes In Augmented And Virtual Reality Classrooms, Naheem Noah

Electronic Theses and Dissertations

Augmented Reality and Virtual Reality (AR/VR) technologies are revolutionizing educational experiences, but their widespread adoption hinges on addressing critical security and usability challenges, particularly in the domain of user authentication. This research presents an investigation into the security landscape of AR/VR and explores a graphical authentication scheme called “Things” that enhances both security and usability in immersive learning environments. Through a systematic evaluation of popular AR/VR devices and applications, potential vulnerabilities and limitations were identified, such as high usage of pin/passwords which are susceptible to shoulder-surfing attacks, lack of multi-factor authentication, and unclear data-sharing practices. A review of existing knowledge-based …

Supervised Classification Modeling On Louisiana Medicaid Data: A Comparative Study, Yead Rahman

Master's Theses

This thesis systematically optimizes and compares state-of-the-art supervised classification models for Louisiana Medicaid data targeting clinical services, COVID-19 infection, and tobacco use. These target variables are critically important as they represent key health outcomes and behaviors among Medicaid enrollees in Louisiana, a population often characterized by poverty and limited access to education. This study applies advanced machine learning techniques to identify the best model for multinomial and binary classification tasks. These include models such as Logistic Regression, XGBoost, AdaBoost, Random Forest, Decision Tree, Artificial Neural Networks, and Naïve Bayes. Extensive tuning of the hyperparameters and optimization of each classifier were …

Robotic Odor Source Localization Using Vision And Olfaction Sensing, Sunzid Hassan

Master's Theses

Robotic Odor Source Localization (ROSL) technology allows autonomous agents like robots to find an odor source in unknown environments. A successful odor source location depends crucially on an effective navigation algorithm that directs the robot towards the odor source. This thesis is a combination of three projects. First, we detail development of a versatile multi-modal robotic platform for ROSL real-world ROSL experimentation and discussed real-world validation of a traditional olfactionbased ROSL algorithm. Secondly, we introduced vision in ROSL by proposing a fusion navigation algorithm that integrates deep-learning enabled vision and olfaction-based navigation. This hybrid approach tackles challenges such as turbulent …

Democratization Of Custom, High Quality Large Language Models, Pablo Lopez

College of Computing and Digital Media Dissertations

Large Language Models (LLMs) have shown exceptional performance in several natural language processing (NLP) tasks. Customizing LLMs boosts their performance in domain specific tasks but typically requires substantial resources and effort for training, such as supervised fine-tuning. This research proposes methods to achieve significant accuracy improvements given minimal resources, particularly focusing on open-ended question answering with a given piece of context. We utilize an LLM’s self-generated training data to fine-tune the LLM and partial fine-tuning with on-demand GPU to reduce practitioner training costs. The research shows that these methods give significant performance gains in a Retrieval Augmented Generation (RAG) based …

It Strategies For Social Media Implementation In Liberian Enterprises, Romeo Yleah

Walden Dissertations and Doctoral Studies

The rapid proliferation of social media platforms has globally transformed organizational operations, creating unique opportunities for direct consumer engagement. However, some Liberian organizations face challenges regarding effective social media implementation. Addressing this issue is critical for enabling Liberian businesses to compete internationally and maximize the potential of social media platforms. Grounded in the diffusion of innovations theory, the purpose of this qualitative pragmatic study was to explore effective IT strategies for integrating social media into Liberian enterprises. Data were collected using semi-structured interviews, observations, and field notes from eight IT managers in Monrovia who had integrated social media within the …

The Impact Of Model Variations On The Robustness Of Deep Learning Models In Adversarial Settings, Firuz Juraev, Mohammed Abuhamad, Simon S. Woo, George K. Thiruvathukal, Tamer Abuhmed

Computer Science: Faculty Publications and Other Works

Rapid advancements of deep learning are accelerating adoption in a wide variety of applications, including safety-critical applications such as self-driving vehicles, drones, robots, and surveillance systems. These advancements include applying variations of sophisticated techniques that improve the performance of models. However, such models are not immune to adversarial manipulations, which can cause the system to misbehave and remain unnoticed by experts. The frequency of modifications to existing deep learning models necessitates thorough analysis to determine the impact on models’ robustness. In this work, we present an experimental evaluation of the effects of model modifications on deep learning model robustness using …

Molecular Docking, Pharmacological Profiling, And Molecular Dynamics Simulation Of Potential Antihyperuricemic Agent From Secondary Metabolites Of Dillenia Philippinensis Rolfe (Dilleniaceae), Louie Rince C. Suyo, John P. Paulin, Nicole Clarence Louise L. Gapaz, Markus Brent S. Arevalo, Vince Tyrell P. Yongco, Librado A. Santiago

Karbala International Journal of Modern Science

Crystal accumulation in the joints due to increased serum uric acid (sUA) may lead to an inflammatory condition called gout. Increased sUA is caused by the excessive reabsorption of the urate anion transporter-1 (URAT-1). Therefore, URAT-1 inhibition will promote uric acid excretion and reduce the risk of having gout. Dillenia philippinensis Rolfe, often known as katmon, is an endemic plant in the Philippines with bioactive compounds associated with several therapeutic benefits. The present study represents the first scientific inquiry into the antihyperuricemic potential of compounds isolated from D. philippinensis. This study aimed to assess the interaction of URAT-1 with …

Evaluating Audio-Compression Techniques, Thien Tuong Duong

Theses and Dissertations

Perceptual quality of audio is the aural accuracy and fidelity perceived by the listener. It is how humans respond to the accuracy, intelligibility, or fidelity of aural media. High-fidelity audio represents high accuracy and minimal distortion and is the standard against which compression algorithms are assessed. We argue that maintaining high-fidelity audio is not just a technical requirement but is also about respecting the artistry of music production. The primary goal of this thesis is to compare the performance of popular audio codecs including file size and conversion speed of each codec when encoding the same file. A secondary goal …

Evaluation Of Business-Driven Reference Architecture For Big Data Analytics Implementation By Public Sector Organizations In Resource-Constrained Setting: A Case Study Of Uganda, Matendo Didas

Tanzania Journal of Engineering and Technology (TJET)

Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) …

Challenges And Recommendations For Building Open Source Innovation Ecosystem For Large-Models In China, Xin Wen, Chao Zhang, Rui Guo, Kaihua Chen, Ze Feng, Qigang Zhu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Addressing the current technological development issues that constrain the development of China’s large-scale model industry is needed to promote the continuous prosperity and development of the industry and enhance its international competitiveness. The study analyzes the significance of the open-source innovation ecosystem for the development of large-scale models in China. Based on reviewing the international experience of constructing the open-source innovation ecosystem, it further dissects the problems and challenges faced by the construction of the open-source innovation ecosystem for large-scale models in China and puts forward targeted suggestions. The study finds that the open-source innovation ecosystem for large-scale models in …

Research And Practice Of Digital Institute And Its System Framework, Jianjun Yu, Yue Wang, Kongmin Wang, Zhuomin Shi

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the era of the digital economy, digital scientific research and digital government are both crucial components, serving as application scenarios enabled by new information technologies. Currently, the new generation of information technologies, especially artificial intelligence and big data, is instrumental in modernizing governance at scientific research institutions within Chinese Academy of Sciences (CAS). They notably drive paradigm shifts in scientific activities and accelerate the digital transformation of these institutions. The digital system formed by the digital transformation of management processes in scientific activities at research institutes is defined as the digital institute. This study analyzes the impact of digital …

Engineering Ecological Analysis Of Rise Of Huawei’S Harmonyos And Its Implications, Dazhou Wang, Yishi Lyu, Zhihuan Fu

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study aims to explore the rise of the Harmony operating system from the perspective of engineering ecology. In the face of increasingly fierce global technological competition, Huawei, as a leading Chinese information technology enterprise, launched its self-developed HarmonyOS and has progressively built the Harmony ecosystem, providing foundational support for the development of all sectors. The development path of HarmonyOS can be divided into three main phases based on its strategic goals, technological and product characteristics, and ecological construction: the initial phase, the acceleration phase, and the transformation phase. It is revealed that, throughout this development, various construction strategies for …

Developing Green Design, Leading Green And Low-Carbon Society, Yongxiang Lu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Green design refers to a design principle and method that comprehensively considers energy and resource conservation, emission reduction, and environmental impact during the product manufacturing and operation process in the product design stage. It strives to reduce greenhouse gas emissions throughout the entire product lifecycle. In the era of information networks, green design is supported by big data, AI network collaborative design, network detection and monitoring, etc. It involves selecting energy-saving processes, green and low-carbon materials, and optimizing product geometry design and surface treatment to achieve efficient resource utilization and minimize waste. For example, selecting environmentally friendly materials through networked …

Research And Implications Of The Us Clean Energy Strategy, Lanchun Li, Qing Liu, Wei Chen, Yun Tang, Jun Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

As the world enters a new period of carbon neutrality, the US government is actively building a clean energy innovation ecosystem through both internal and external measures. Systematically tracking and in-depth analysis of the intent, structure, approach, and other characteristics of the new phase of the US clean energy strategy is of practical significance to Chinese energy revolution. The US focuses on the strategic objectives of science and technology innovation, energy security, and infrastructure, and has constructed an innovation ecology characterized by technology lists, planning blueprints, full-chain research, and innovative subjects from the perspective of whole-government coordination, cross-institutional decision-making, deep …

Technology Governance And Governance Technology: From Perspective Of Regulatory Research On Blockchain Digital Assets, Yikai Wu, Guoan Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The Outline of the 14th Five-Year Plan takes blockchain as one of the key industries of the digital economy, and a number of ministries and commissions have also made clear deployments to accelerate the innovative application of blockchain, promote the digital transformation of the industry, and promote the high-quality development of the economy and society in the policy documents related to the informatization of the industry. The regulation and governance of blockchain digital assets cannot be separated from the understanding and analysis of blockchain technology itself, and observing the development mechanism of blockchain digital assets from the scientific and technological …

Ai-Driven Innovation And Development In Manufacturing: An Overview Of Trends, Issues, And Suggestions, Rongping Mu, Jingjing Guo, Yuchen Li, Qiang Li, Chun Jiang, Ze Feng, Guowei Dong

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence technology has become a key force in driving innovation and development in global manufacturing industries, and its application in production automation, intelligent management, and other areas has become an important trend for innovation and development of manufacturing in all countries. This study comprehensively analyzes the innovation and development trend driven by artificial intelligence in global manufacturing, outlines the policies and measures of major countries in promoting the innovation and development of the manufacturing industries driven by artificial intelligence. It also points out the current situation and problems of the manufacturing’s innovation and development driven by artificial intelligence in …

Insights From Darpa’S Program Funding Layout In Artificial Intelligence, Zheng Su, Ning He, Qi Han, Qi Zhang, Xiaocheng Jiang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence, as a disruptor in the new wave of technological revolution and industrial transformation, had already become a focal point of strategic planning for the U.S. Defense Advanced Research Projects Agency (DARPA) as early as the 1960s. To explore the patterns of DARPA’s project funding allocation in the field of artificial intelligence, this study conducts an in-depth analysis of the agency’s budget reports from fiscal years from 2015 to 2025. The study identifies the following characteristics of DARPA’s project funding framework in the field of artificial intelligence: (1) distinctive application orientation; (2) highly flexible funding system; and (3) close …

Concept And Development Trend Of Novel E-Infrastructure Platform, Jing Xu, Chuan Tang, Kuangjunyu Yang, Juan Zhang, Ru Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

E-infrastructure platform has become a critical strategic asset for driving national scientific and technological innovation, and is the focus of strategic deployment by technologically advanced countries globally. This study, through the analysis of relevant strategy documents in the United States, European Union, and the United Kingdom, the relevant concepts and development changes of the novel E-infrastructure platform have been clarified. It also summarizes the planning process and development stages of e-infrastructure platform in the United States, Europe, and the United Kingdom, and analyzes that e-infrastructure platform will develop towards a new type of ecological, intelligent, diversified, and full process novel …

Predictive Filtering-Based Image Inpainting, Xiaoguang Li

Theses and Dissertations

Image inpainting is an important challenge in the computer vision field. The primary goal of image inpainting is to fill in the missing parts of an image. This technique has many real-life uses including fixing old photographs and restoring ancient artworks, e.g., the degraded Dunhuang frescoes. Moreover, image inpainting is also helpful in image editing. It has the capability to eliminate unwanted objects from images while maintaining a natural and realistic appearance, e.g., removing watermarks and subtitles. Disregarding the fact that image inpainting expects the restored result to be identical to the original clean one, existing deep generative inpainting methods …

Challenges And Practices Of Deep Learning Model Reengineering: A Case Study On Computer Vision, Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel, Nicholas Synovic, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Many engineering organizations are reimplementing and extending deep neural networks from the research community. We describe this process as deep learning model reengineering. Deep learning model reengineering — reusing, replicating, adapting, and enhancing state-of-the-art deep learning approaches — is challenging for reasons including under-documented reference models, changing requirements, and the cost of implementation and testing.