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2024

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Articles 2101 - 2130 of 3700

Full-Text Articles in Computer Sciences

Gc-84 Owl Cyber Defense Systems, Randolph S Gilstrap, Christopher Dunbar, Stephanie Aguirre, Ryan M Leblanc, Justin Place Apr 2024

Gc-84 Owl Cyber Defense Systems, Randolph S Gilstrap, Christopher Dunbar, Stephanie Aguirre, Ryan M Leblanc, Justin Place

C-Day Computing Showcase

Owl Cyber Defense Systems is a fictitious (for now?) start-up offering comprehensive cybersecurity solutions for small and medium businesses. Our premier flagship product is an AI Chatbot that answers security related questions and provides vetted code and security settings to secure and harden a variety of systems. Starting with the initial concept, we methodically progressed through the business planning process, carefully considering technology usage and design. This comprehensive approach ultimately enabled us to develop a robust set of client offerings. We used a hybrid approach combining Agile Scrum and traditional Waterfall methodologies to complete the project. We utilized Jira Project …

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Gmr-107 An Integrated Architecture For Maintaining Security In Cloud Computing Using Blockchain, Namratha Tavva, Ashrith Kumar Devara, Gar H Lock Apr 2024

Gmr-107 An Integrated Architecture For Maintaining Security In Cloud Computing Using Blockchain, Namratha Tavva, Ashrith Kumar Devara, Gar H Lock

C-Day Computing Showcase

Cloud services are vulnerable to assaults because of their widespread availability. Since cloud computing is still a relatively new service, there is a real risk that sensitive information might be altered while in transit. Because of this, bad actors may gain an edge by manipulating data. Clients using the cloud for a wide range of use cases want to know that their data is reliable and secure. Blockchain, on the other hand, is an immutable digital ledger that may be used with cloud computing to provide an immutable cloudbased data storage and processing system. In this work, we present a …

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Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati Apr 2024

Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati

C-Day Computing Showcase

With the quick rise of Artificial Intelligence (AI), generative AI models have greatly increased the volume and velocity of data creation. Among that data, AI-generated images have become a highly discussed topic, especially when discussing the potential dangers of these AI models. Due to these dangers, being able to distinguish AI-generated art from human-made art is becoming a necessity. Additionally, as these AI-models improve, it is becoming increasingly difficult for humans to determine whether art is AI-generated or human-made. This paper proposes the further exploration of the effectiveness of a current state of the art AI-image identification model.

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Gmr-59 Customer Segmentation For Marketing Campaigns Using K-Means Clustering, Jaswanthi Vellanki, Hrithik Singh Chandel, Vyghni Sudha Kommineni, Priyanka A Bagal, Rutvikkumar K Ramani Apr 2024

Gmr-59 Customer Segmentation For Marketing Campaigns Using K-Means Clustering, Jaswanthi Vellanki, Hrithik Singh Chandel, Vyghni Sudha Kommineni, Priyanka A Bagal, Rutvikkumar K Ramani

C-Day Computing Showcase

The objective of this project is to use K-means clustering an unsupervised machine learning algorithm to categorize customers based on characteristics such as demograp hics, purchasing history and interaction behavior. The purpose is to discover different client segments that can be targeted with specialized marketing techniques that improve marketing campaign efficiency and increase consumer satisfaction and engagement.

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Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam Apr 2024

Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam

C-Day Computing Showcase

In the rapidly evolving fields of Artificial Intelligence and Natural Language Processing, significant opportunities have emerged to transform educational practices. Discourse analysis, particularly in science education, plays a critical role in fostering scientific thinking among students. However, the manual application of tools like the Classroom Discourse Analysis Tool is resource-intensive and impractical on a large scale. This abstract proposes the development of an AI-based Discourse Analysis System tailored for educational settings, designed to automate and enrich the analysis of classroom discourse. Leveraging the latest in Artificial Intelligence and Natural Language Processing, this web-based application will provide teachers nationwide with the …

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Gmr-90 Digimindready: Enhancing Military Readiness With Edge Ai-Driven Wellness, Education, And Digital Discipline Through Mhealth Innovation., Md Mehedi Hasan, Nafisa Anjum Apr 2024

Gmr-90 Digimindready: Enhancing Military Readiness With Edge Ai-Driven Wellness, Education, And Digital Discipline Through Mhealth Innovation., Md Mehedi Hasan, Nafisa Anjum

C-Day Computing Showcase

Military personnel often need to operate in high-stakes situations. Combating such volatile missions primarily includes control over cognitive overload, reckless mindset, and maintaining concentration amid distractions to sustain operational effectiveness. Military training significantly focuses on human performance, which benefits military readiness. However, the 21st century has introduced unanticipated challenges, such as adverse effects of excessive screen time, external distractions, and over-reliance on technology to the US military, on top of existing issues like anxiety and emotional stability, adversely impacting military readiness and decreasing quality of life. A strategic investigation into these issues and the advancement of effective tools to address …

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Gpr-63 Adaptive Attention Aware Fusion For Human-In-Loop Behavioral Health Detection, Martin Brown, Abm Adnan Azmee Apr 2024

Gpr-63 Adaptive Attention Aware Fusion For Human-In-Loop Behavioral Health Detection, Martin Brown, Abm Adnan Azmee

C-Day Computing Showcase

Identifying behavioral health is paramount for law enforcement officers to provide appropriate follow-up community care. In the current practice, law enforcement offices manually identify these behavioral health cases to allow the designation of the relevant follow-up resources. In this work, we develop a tool to automatically detect behavioral health cases from police public narrative reports by identifying behavioral health indicator signals. We propose a novel adaptive attention-aware fusion model for detecting behavioral health signals in sensitive police reports. Our model leverages contextual and semantic information from the reports and relevant behavioral health cues as keywords from a pre-trained attention-weighted keyword-based …

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Uc-100 Indy 7 - Nutrition App, Silas E Hammond, Tho Mai, Christopher P Sarzen, Michael Ehme Apr 2024

Uc-100 Indy 7 - Nutrition App, Silas E Hammond, Tho Mai, Christopher P Sarzen, Michael Ehme

C-Day Computing Showcase

This project’s objective is to develop a fully functioning and polished mobile app for keeping track of caloric intake and monitoring other aspects of one’s health. To accomplish this, we will be using React Native to develop a front end which allows users to select their goals and get active assistance in moderating what they eat. This will be done through the scanning of barcodes of any food purchased. These barcodes will then be used to query the Food Data Central API to provide the user with as much information as needed. This will include possible allergies, calorie totals, protein …

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Uc-120 Virtual Companionship Chatbot, Cesar Tortolero, Rakshak Gurung, Noah Clark, Fabritzzio A Cabrejos Apr 2024

Uc-120 Virtual Companionship Chatbot, Cesar Tortolero, Rakshak Gurung, Noah Clark, Fabritzzio A Cabrejos

C-Day Computing Showcase

Loneliness affects about 77% of college students at some point, highlighted by a Gitnuss report. Our project aims to mitigate this by introducing a personalized chatbot that serves as an emotional outlet for students. The application is built on a React Native frontend, employs a DistilGPT-2 language model using the QUAC dataset, and is backed by a Python server. We plan to deploy it on an Azure NC6s_v3 Cloud server, integrating Firebase Real-Time Database for Android and iOS compatibility.

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Uc-60 Myfoodscan, Ibrahima Gueye, Brianna J Noel, Victoria O Kuswita, Je'dae Lisbon Apr 2024

Uc-60 Myfoodscan, Ibrahima Gueye, Brianna J Noel, Victoria O Kuswita, Je'dae Lisbon

C-Day Computing Showcase

MyFoodScan is a mobile app that enables users to scan barcodes of various food and drink items to ensure they are in compliance with their specific dietary needs. Individuals utilize this application to make a customized profile based on diet, such as vegan, vegetarian, dairy-free, allergies, etc. MyFoodScan promotes compliance with dietary limitations. The application was developed with React Native, Expo Go, Google Firebase, using the React Native Camera for barcode scanning. The OpenFoodFacts API database is used for product information. The goal of this application is to enhance awareness and safety for various dietary needs and monitor dietary restrictions.

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Uc-85 Helpr: Helping Extrapolate Labels For Police Reports Using Large Language Models, Hailey N Walker, William A Stigall Apr 2024

Uc-85 Helpr: Helping Extrapolate Labels For Police Reports Using Large Language Models, Hailey N Walker, William A Stigall

C-Day Computing Showcase

Police officers spend many hours a week documenting their findings when reporting to a 911 call. There is so much detail in these reports that they remain an untapped resource for future data analytics by the police department. The reports are currently being analyzed by human experts and categorized into the following categories: “Substance Abuse”, “Mental Health”, “Domestic/Social”, “Nondomestic/Social”, and “Other”. To assist the experts and reduce the amount of time that is spent on reading and analyzing, we are proposing the use of large language models (LLMs) to tag police reports based on their content. Two models, Mistral-7B and …

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Uc-92 Faculty Course Analysis Report Self Service Interface, Meet Patel, Trevor Harbin, Omit Deb, Edwin Mayhew Apr 2024

Uc-92 Faculty Course Analysis Report Self Service Interface, Meet Patel, Trevor Harbin, Omit Deb, Edwin Mayhew

C-Day Computing Showcase

This project aims to enhance the efficiency of generating and submitting Faculty Course Analysis Reports (FCARs) for the faculty of CCSE in accordance with ABET accreditation requirements. The scope involves the design and implementation of a locally hosted web-based application. This application will streamline the process, allowing FCARs to be requested and generated in real time. Development will be conducted on a Linux-based platform, and security measures will be integrated based on the NetID system.

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Uc-99 Interactive Training Games - Robins Air Force Base, Sean J Tenney, Vt Nguyen, Ian Ford, Mason Farmer, Aaron Hannah Apr 2024

Uc-99 Interactive Training Games - Robins Air Force Base, Sean J Tenney, Vt Nguyen, Ian Ford, Mason Farmer, Aaron Hannah

C-Day Computing Showcase

Our project involves converting three PowerPoint training presentations on STINFO, No Fears Act, and Records Management into engaging web-based games. Commissioned by Robins Air Force Base, our team utilizes Unity WebGL for game development and React/Firebase for website hosting. The goal is to provide Air Force personnel with interactive training modules accessible from their desks, enhancing learning retention and engagement. By gamifying the content, we aim to make learning enjoyable while ensuring critical information retention. This interdisciplinary project merges game development and web technologies to modernize training methods and improve educational outcomes for military personnel.

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Uc-51 Difference Detection: Automated Defect Detection System For Modernized Display Units, Umer Aziz, Harrison Rosser, Urooj Arshad, Teonta N Pegues, Katherine Vu Apr 2024

Uc-51 Difference Detection: Automated Defect Detection System For Modernized Display Units, Umer Aziz, Harrison Rosser, Urooj Arshad, Teonta N Pegues, Katherine Vu

C-Day Computing Showcase

In today's high-stakes military environments, the reliability and accuracy of software systems are paramount. Defects within these systems not only pose significant financial risks but can also endanger lives. To ensure the utmost safety and effectiveness, military systems undergo extensive testing and validation processes. However, the lifespan of these systems is far from indefinite. Environmental changes, advancements in adversarial capabilities, evolving mission requirements, and parts obsolescence necessitate continuous improvement efforts. One critical area of focus is the modernization of display units, which are vital for providing pilots with essential mission information and ensuring their safe return. The 402 Software Engineering …

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Ur-116 Enhancing Engineering Education Through Llm-Driven Adaptive Quiz Generation, Devananda Sreekanth, Sreekanth Gopi Apr 2024

Ur-116 Enhancing Engineering Education Through Llm-Driven Adaptive Quiz Generation, Devananda Sreekanth, Sreekanth Gopi

C-Day Computing Showcase

This study aims to develop an Artificial Intelligence (AI) quiz generation system for engineering students to enhance personalized learning. In the rapidly evolving field of educational education, the emergence of AI and, more specifically, Large Language Models (LLMs) such as GPT-4, Llama, Claude, and Gemini, has marked a significant advancement. Our literature review method employs a systematic approach, analyzing peer-reviewed articles, conference papers, and authoritative reports to uncover the trends and challenges in AI-driven quiz generation. The notable gap identified in our literature review is the lack of LLM-based quiz generation methods specifically for engineering education, which incorporate interactive and …

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Ur-12 Multiple Myeloma: Increase Longevity And Quality Of Life Through Early Detection, Desyne Martinez Apr 2024

Ur-12 Multiple Myeloma: Increase Longevity And Quality Of Life Through Early Detection, Desyne Martinez

C-Day Computing Showcase

Multiple Myeloma is a rare form of bone marrow cancer where plasma cells accumulate in the blood stream attacking the skeletal system, nervous system, and kidneys of predominantly African Americans. The disease results in high mortality rates within 5 years of initial diagnosis. Multiple Myeloma has subtle symptoms of bone pain; doctors often send people to physical therapy missing the diagnosis. Current research on the International Myeloma Foundation website includes summaries of blood tests of Multiple Myeloma patients. This study seeks to identify the best blood test predictors of Stage 3, the most aggressive stage of Multiple Myeloma. The cost …

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Ur-15 Analyzing Breast Cancer Histopathology Images Using Deep Neural Network Models, Je'dae Lisbon, Michael Bolnik, Sepehr Eshaghian Apr 2024

Ur-15 Analyzing Breast Cancer Histopathology Images Using Deep Neural Network Models, Je'dae Lisbon, Michael Bolnik, Sepehr Eshaghian

C-Day Computing Showcase

Our project aims to explore human tissue cells digitized by whole slide scanners for a better understanding of complex tumor microenvironments in breast cancer histopathology images, using various deep neural network models. First, we experimented with 70% percentages of tumor cells on image classification using ResNet50, VGG16, and Inception-ResNet. Second, we performed instance image segmentation using Mask-RCNN. Third, we applied two well-known explainable artificial intelligence (AI) techniques including Gradient-weighted Class Activation Mapping (Grad-CAM) and Shapley Additive Explanations (SHAP) to determine the effectiveness of the models.

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Ur-70 Faster Inequivalence Testing Using Robustness, Emily G Jackson Apr 2024

Ur-70 Faster Inequivalence Testing Using Robustness, Emily G Jackson

C-Day Computing Showcase

We propose a new method for quickly testing the inequivalence of two Boolean functions, when one function is represented as an ordered binary decision diagram (OBDD), and the other is represented in conjunctive normal form (CNF). Our approach is based on a notion of classifier robustness from the fields of explainable AI (XAI) and adversarial machine learning. In particular, we show that two Boolean functions that are very similar in terms of their truth values, can be very different in terms of their robustness, which in turn, provides a witness to their inequivalence. A more efficient approach to inequivalence testing …

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Ur-89 Performance Analysis Of Post-Quantum Computing Key Encapsulation Mechanism Algorithms, Dillon J Horton, Jose Gutierrez, Tyler G Standard Apr 2024

Ur-89 Performance Analysis Of Post-Quantum Computing Key Encapsulation Mechanism Algorithms, Dillon J Horton, Jose Gutierrez, Tyler G Standard

C-Day Computing Showcase

Within the next twenty years or so experts predict that we will have quantum computers which will make certain kinds of encryption that we rely on ineffective and vulnerable to malicious entities. Post quantum computing (PQC) algorithms fill in that security gap that classical encryption algorithms can not. A particular category of PQC algorithms are key exchange mechanism (KEM) algorithm. The goal of these algorithms is to securely generate a shared symmetric key which can be used for encrypting future communication between the hosts. An important use case for these algorithms is in securing the Transport Layer Security protocol (TLS) …

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Ur-94 Emohydra: Multimodal Emotion Classification Using Heterogenous Modality Fusion, William A Stigall Apr 2024

Ur-94 Emohydra: Multimodal Emotion Classification Using Heterogenous Modality Fusion, William A Stigall

C-Day Computing Showcase

Affective computing is a field of growing importance, as human society becomes more integrated with machines. Human feelings are both complex and multi-modal, expressed through various methods and nuances in behavior. In this work we introduce EmoHydra, a multi-modal model created through the fusion of three top-level models fine-tuned on text, vision, and speech respectively. Despite heterogenous heads performing well on the unseen data, as well as generalizing well to other benchmarks, logit concatenation proves to be ineffective at predicting Multimodal data, therefore we implement Multi-Head Attention as our fusion mechanism.

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Gc-101 Learning Resource Finder: A Web Scraping Tool For Educational Materials, Ashrith Kumar Devara Apr 2024

Gc-101 Learning Resource Finder: A Web Scraping Tool For Educational Materials, Ashrith Kumar Devara

C-Day Computing Showcase

The Learning Resource Finder is a pioneering tool designed to alleviate the challenges associated with navigating the vast landscape of online educational content. Leveraging sophisticated web scraping techniques and API integrations, this tool empowers users to efficiently discover relevant learning materials tailored to their specific needs. Through a user-friendly Flask-based web interface, users initiate search queries, which are then encoded and utilized to fetch pertinent URLs from leading educational platforms such as JavaTPoint, W3Schools, Coursera, Udemy, and GeeksforGeeks, as well as Google search results. The core of the web scraping process lies in the meticulous extraction of URLs from HTML …

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Gmr-118 Stress Detection By Wearable Devices: Integrating Multimodal Physiological Signals And Machine Learning Techniques, Pranita Subhash Shedage Apr 2024

Gmr-118 Stress Detection By Wearable Devices: Integrating Multimodal Physiological Signals And Machine Learning Techniques, Pranita Subhash Shedage

C-Day Computing Showcase

In the medical field, the most common complaint of patients is “stress”. Stress can cause severe effects on the human body. For example, prolonged mental stress can cause serious health issues in long term such as hypertension, cardiovascular diseases, increased susceptibility to infections, and depression. These health issues can be prevented by early detection of stress and by taking preventive measures. The most common detecting stress was determined from the questionnaires or from the interactive sessions conducted to assess the people's affective state. However, this method is not highly reliable and can be biased depending on the person who is …

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Gmr-23 Jamming Signal Detection Using Extreme Gradient Boosting (Xgboost) Algorithm, Keerthana Adamana, Christian K Sao Apr 2024

Gmr-23 Jamming Signal Detection Using Extreme Gradient Boosting (Xgboost) Algorithm, Keerthana Adamana, Christian K Sao

C-Day Computing Showcase

Radar jamming involves sending intentionally disruptive radio waves toward the target radar, which might over-saturate its receiver so it can’t receive anything or deceive it into interpreting false information. Machine learning (ML) techniques increased the capability to automatically learn the experience without being explicitly programmed. Machine learning models usually require a large, labeled sample to perform. Building a robust jamming detection model will be challenging due to the wide variability of jamming signals and less available labeled samples. In this project, we developed an eXtreme Gradient Boosting(XGBoost) algorithms for radar jamming signal classification and achieved superior performance compared with Random …

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Gmr-45 Cloud Based Bus Tracking And Ticketing System, Vyghni Sudha Kommineni, Damacharla Sravani Apr 2024

Gmr-45 Cloud Based Bus Tracking And Ticketing System, Vyghni Sudha Kommineni, Damacharla Sravani

C-Day Computing Showcase

In many urban areas, public transportation systems frequently fail to fulfill passenger demand, causing aggravation owing to a lack of real-time information about bus locations, timetables and delays. Outdated ticketing processes, which are labor-intensive and prone to mistakes, compound the annoyance by failing to match current travelers' expectations. Furthermore, transportation operators encounter difficulties with fleet management, route optimisation, and issue response due to a lack of comprehensive data analytics. Reliable monitoring systems are required to prioritize passenger and bus safety, and achieving sustainability targets necessitates efficient operations to reduce fuel consumption and emissions. A scalable and customizable cloud-based bus tracking …

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Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota Apr 2024

Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota

C-Day Computing Showcase

Predicting house prices is a challenging task that researchers from various fields (economics, statistics, politics, etc.) have attempted to answer. An accurate house prediction is useful not only to policymakers to improve their policies, but also to help sellers and buyers in the real estate market make well- informed decisions. Commonly, prediction models are trained on the whole dataset. However, as Azimlu et al [1] suggested, such models might not perform very well on dispersed data. They propose a new approach which first divides the whole dataset into smaller clusters, and then each cluster would be trained with an appropriate …

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Gmr-7 A Novel Identity Verification Framework Using A Hybrid Biometric System, Namratha Tavva, Bhanu Prakash Vadlamudi, Sumanth Kunchala, Snigdha Katta Apr 2024

Gmr-7 A Novel Identity Verification Framework Using A Hybrid Biometric System, Namratha Tavva, Bhanu Prakash Vadlamudi, Sumanth Kunchala, Snigdha Katta

C-Day Computing Showcase

In recent years, the field of big data analytics has gained immense attention due to the increasing volume and complexity of data being generated from various sources. One of the key applications of big data analytics is in the field of identity verification, where it is used to process and analyze large amounts of biometric data to authenticate individuals. A hybrid biometric system that combines multiple biometric modalities has been shown to be more effective in identity verification than a single modality system. In this project, we propose an Identity Verification Framework using a Hybrid Biometric System that leverages big …

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Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla Apr 2024

Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla

C-Day Computing Showcase

The educational domain is undergoing transformation due to the incorporation of Artificial Intelligence (AI), Large Language Models (LLMs), and generative AI technologies, raising the need for educators to integrate cutting-edge technological advancements and methodologies into their teaching approaches. Pedagogical Design Patterns (PDPs) have become prominent for their role in sharing effective educational practices and narrowing the divide between academic research and actual teaching methods. Despite their potential, the lack of widely accessible resources and the scattered nature of publishing outlets pose significant barriers to the broad application of PDPS. To address this issue, we propose the application of large language …

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Gpr-13 Effect Of Noise And Topologies On Multi-Photon Quantum Protocols, Nitin Jha Apr 2024

Gpr-13 Effect Of Noise And Topologies On Multi-Photon Quantum Protocols, Nitin Jha

C-Day Computing Showcase

Quantum-augmented networks aim to use quantum phenomena to improve detection and protection against malicious actors in a classical communication network. This may include multiplexing quantum signals into classical fiber optical channels and incorporating purely quantum links alongside classical links in the network. In such hybrid networks, quantum protocols based on single photons become a bottleneck for transmission distances and data speeds, thereby reducing entire network performance. Furthermore, many of the security assumptions of the single-photon protocols do not hold up in practice because of the impossibility of manufacturing single-photon emitters. Multi-photon quantum protocols, on the other hand, are designed to …

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Gpr-16 Attention Driven Framework For Detecting Mental Illness Causes From Social Media, Abm Adnan Azmee, Dinesh Chowdary Attota, Francis E Nweke Apr 2024

Gpr-16 Attention Driven Framework For Detecting Mental Illness Causes From Social Media, Abm Adnan Azmee, Dinesh Chowdary Attota, Francis E Nweke

C-Day Computing Showcase

Mental health is a critical aspect of our overall well-being. Mental illness refers to conditions that impact an individual's psychological state, resulting in considerable distress, and limitations in functioning day-to-day tasks. Due to the progress of technology, social media has merged as the platform, for individuals to share their thoughts and emotions. The psychological state of individuals can be accessed with the help of data from these platforms. However, it is challenging for conventional machine learning models to analyze the diverse linguistic contexts of social media data. In this work, we propose a novel attention-driven deep framework to overcome these …

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Gpr-18 Case Exploration: Automatic Keyword Matching Framework For Behavioral Health, Francis E Nweke, Abm Adnan Azmee Apr 2024

Gpr-18 Case Exploration: Automatic Keyword Matching Framework For Behavioral Health, Francis E Nweke, Abm Adnan Azmee

C-Day Computing Showcase

In this demonstration, we propose a framework for exploring, identifying, and matching repeated behavioral health keywords in first-responder reports to the current set of Behavioral Health Index Terms provided by subject matter experts (SMEs). The tool incorporates behavioral health-related keywords and has a Graphical User Interface (GUI) that allows non-technical users to explore and analyze 911 first-responder reports. We utilized an inverted index, best-matching (BM25), and plain-text searching algorithms to match keywords in first-responder reports. This tool provides a comprehensive approach to report analysis by identifying indicators of mental health disorders and taking into account the assessments of humanities and …

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