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A Comprehensive Review On Shale Studies With Emphasis On Nuclear Magnetic Resonance (Nmr) Technique, Yujie Yuan, Reza Rezaee, Mei-Fu Zhou, Stefan Iglauer Dec 2023

A Comprehensive Review On Shale Studies With Emphasis On Nuclear Magnetic Resonance (Nmr) Technique, Yujie Yuan, Reza Rezaee, Mei-Fu Zhou, Stefan Iglauer

Research outputs 2022 to 2026

Multi-scale shale studies put a significant emphasis on high-resolution investigations from nanometer to decametre scales. Despite that multiple advanced techniques have been used in shale studies, they are mostly limited to the detection scopes and have restricted capacity for high-resolution characterization of shale nanopores with substantial heterogeneity. Therefore, it remains a challenge for accurate resource estimation in unconventional shales. The nuclear magnetic resonance (NMR) is an advanced technique enabling non-destructive and fast measurements, and has the advantage of high-resolution evaluation of shale formations and nanopore structure. Petrophysical studies using NMR have made breakthroughs in shale studies. However, multi-scale shale investigations …

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Global Dataset Of Soil Organic Carbon In Tidal Marshes, Tania L. Maxwell, André S. Rovai, Maria F. Adame, Janine B. Adams, José Álvarez-Rogel, William E. N. Austin, Kim Beasy, Francesco Boscutti, Michael E. Böttcher, Tjeerd J. Bouma, Richard H. Bulmer, Annette Burden, Shannon A. Burke, Saritta Camacho, Doongar R. Chaudhary, Gail L. Chmura, Margareth Copertino, Grace M. Cott, Christopher Craft, John Day, Carmen B. De Los Santos, Lionel Denis, Weixin Ding, Joanna C. Ellison, Carolyn J. E. Lewis, Luise Giani, Maria Gispert, Swanne Gontharet, José A. González-Pérez, M. Nazaret González-Alcaraz, Connor Gorham, Anna E. L. Graversen, Anthony Grey, Roberta Guerra, Qiang He, James R. Holmquist, Alice R. Jones, José A. Juanes, Brian P. Kelleher, Karen E. Kohfeld, Dorte Krause-Jensen, Anna Lafratta, Paul S. Lavery, Edward A. Laws, Carmen Leiva-Dueñas, Pei S. Loh, Catherine E. Lovelock, Carolyn J. Lundquist, Peter I. Macreadie, Inés Mazarrasa, J. Patrick Megonigal, Joao M. Neto, Juliana Nogueira, Michael J. Osland, Jordi F. Pagès, Nipuni Perera, Eva-Maria Pfeiffer, Thomas Pollmann, Jacqueline L. Raw, María Recio, Ana C. Ruiz-Fernández, Sophie K. Russell, John M. Rybczyk, Marek Sammul, Christian Sanders, Rui Santos, Oscar Serrano, Matthias Siewert, Craig Smeaton, Zhaoliang Song, Carmen Trasar-Cepeda, Robert R. Twilley, Marijn Van De Broek, Stefano Vitti, Livia V. Antisari, Baptiste Voltz, Christy N. Wails, Raymond D. Ward, Melissa Ward, Jaxine Wolfe, Renmin Yang, Sebastian Zubrzycki, Emily Landis, Lindsey Smart, Mark Spalding, Thomas A. Worthington Dec 2023

Global Dataset Of Soil Organic Carbon In Tidal Marshes, Tania L. Maxwell, André S. Rovai, Maria F. Adame, Janine B. Adams, José Álvarez-Rogel, William E. N. Austin, Kim Beasy, Francesco Boscutti, Michael E. Böttcher, Tjeerd J. Bouma, Richard H. Bulmer, Annette Burden, Shannon A. Burke, Saritta Camacho, Doongar R. Chaudhary, Gail L. Chmura, Margareth Copertino, Grace M. Cott, Christopher Craft, John Day, Carmen B. De Los Santos, Lionel Denis, Weixin Ding, Joanna C. Ellison, Carolyn J. E. Lewis, Luise Giani, Maria Gispert, Swanne Gontharet, José A. González-Pérez, M. Nazaret González-Alcaraz, Connor Gorham, Anna E. L. Graversen, Anthony Grey, Roberta Guerra, Qiang He, James R. Holmquist, Alice R. Jones, José A. Juanes, Brian P. Kelleher, Karen E. Kohfeld, Dorte Krause-Jensen, Anna Lafratta, Paul S. Lavery, Edward A. Laws, Carmen Leiva-Dueñas, Pei S. Loh, Catherine E. Lovelock, Carolyn J. Lundquist, Peter I. Macreadie, Inés Mazarrasa, J. Patrick Megonigal, Joao M. Neto, Juliana Nogueira, Michael J. Osland, Jordi F. Pagès, Nipuni Perera, Eva-Maria Pfeiffer, Thomas Pollmann, Jacqueline L. Raw, María Recio, Ana C. Ruiz-Fernández, Sophie K. Russell, John M. Rybczyk, Marek Sammul, Christian Sanders, Rui Santos, Oscar Serrano, Matthias Siewert, Craig Smeaton, Zhaoliang Song, Carmen Trasar-Cepeda, Robert R. Twilley, Marijn Van De Broek, Stefano Vitti, Livia V. Antisari, Baptiste Voltz, Christy N. Wails, Raymond D. Ward, Melissa Ward, Jaxine Wolfe, Renmin Yang, Sebastian Zubrzycki, Emily Landis, Lindsey Smart, Mark Spalding, Thomas A. Worthington

Research outputs 2022 to 2026

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this …

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Numerical Investigation Of Lead Free Cs2tibr6 Based Perovskite Solar Cell With Optimal Selection Of Electron And Hole Transport Layer Through Scaps-1d Simulation, Hironmoy Karmaker, Ayesha Siddique, Barun K. Das Dec 2023

Numerical Investigation Of Lead Free Cs2tibr6 Based Perovskite Solar Cell With Optimal Selection Of Electron And Hole Transport Layer Through Scaps-1d Simulation, Hironmoy Karmaker, Ayesha Siddique, Barun K. Das

Research outputs 2022 to 2026

Halide-based perovskite has several advantages, including high efficiency, ease of manufacture, and low cost. In general, hazardous lead (Pb) is used in perovskite solar cells as an absorber layer, while polymer, which is unstable in nature used as the electron/hole transport layer. Despite its appealing characteristics, the device uses of lead and degradable components must be addressed. Lead-free titanium-based inorganic perovskite solar cells (PSCs) have drawn strong scientific interest in recent years in order to reduce the possibly detrimental effects of lead on the environment. Titanium is non-toxic, robust, inexpensive, and widely available when compared to other elements. The performance …

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A New Approach To Predicting Vertical Permeability For Carbonate Rocks In The Southern Mesopotamian Basin, Emad A. Al-Khdheeawi, Raed H. Allawi, Wisam I. Al-Rubaye, Stefan Iglauer Dec 2023

A New Approach To Predicting Vertical Permeability For Carbonate Rocks In The Southern Mesopotamian Basin, Emad A. Al-Khdheeawi, Raed H. Allawi, Wisam I. Al-Rubaye, Stefan Iglauer

Research outputs 2022 to 2026

Reservoir performance depends on many factors, and the most important one is permeability anisotropy. In addition, with high heterogeneity, it is essential to find unique relationships to predict permeability. Therefore, this study aims to predict vertical permeability based on horizontal permeability and porosity and to find new equations for carbonate reservoirs. This work relied on the 398 measured points of cores data collected from several wells in carbonate reservoirs. A new correlation for predicting vertical permeability for the whole data (369 samples) as a function of horizontal permeability and porosity has been developed. The results indicate that this new correlation …

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Capillary-Sealing Efficiency Of Mica-Proxy Caprock For Co2/H2 Geologic Storage In The Presence Of Organic Acids And Nanofluids, Amer Alanazi, Muhammad Ali, Mahmoud Mowafi, Saleh Bawazeer, Ziyad K K. Kaidar, Hussein Hoteit Dec 2023

Capillary-Sealing Efficiency Of Mica-Proxy Caprock For Co2/H2 Geologic Storage In The Presence Of Organic Acids And Nanofluids, Amer Alanazi, Muhammad Ali, Mahmoud Mowafi, Saleh Bawazeer, Ziyad K K. Kaidar, Hussein Hoteit

Research outputs 2022 to 2026

Toward a diversified low-carbon future, the geological storage of carbon dioxide (CO2) and hydrogen (H2) is regarded as a key enabler for an industrial-scale implementation. However, many geological formations, such as depleted oil and gas reservoirs, can contain inherent traces of organic molecules that dramatically affect their storage capacities and caprock sealing efficiency. Hence, using the right analysis to accurately determine the caprock sealing efficiency and storage capacity in the presence of organics is crucial for a secure and safe storage process. This study analyzed the sealing potential of a proxy caprock (mica) by calculating the capillary entry pressure and …

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Parapapillary Βbm And Γ Zones Played Different Roles In Axial Elongation Among Young Adolescents Using Optical Coherence Tomography, Yin Guo, Jiayan Li, Feifei Tian, Rui Hou, Lijuan Liu, Jiali Duan, Ang Ji, Youxin Wang, Xiuhua Guo, Deqiang Zheng, Wei Wang, Lijuan Wu Dec 2023

Parapapillary Βbm And Γ Zones Played Different Roles In Axial Elongation Among Young Adolescents Using Optical Coherence Tomography, Yin Guo, Jiayan Li, Feifei Tian, Rui Hou, Lijuan Liu, Jiali Duan, Ang Ji, Youxin Wang, Xiuhua Guo, Deqiang Zheng, Wei Wang, Lijuan Wu

Research outputs 2022 to 2026

Purpose: To evaluate the influencing factors of parapapillary BM and zones incidence in young adolescents and to explore their associations with axial length progression. Methods: In this prospective cohort study, 976 seventh-grade students from nine secondary schools in Beijing, China, were enrolled and followed up 1 year later. Parapapillary BM zone was defined as retinal pigment epithelium loss while Bruch's membrane was present. Parapapillary zone was defined as the absence of retinal pigment epithelium and Bruch's membrane. Logistic regression model was used to analyze the influencing factors of BM and zone incidence. A linear mixed model was used to analyze …

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Innovative Multi-Criteria Decision-Making Approach For Supplier Evaluation: Combining Tlf, Fuzzy Bwm, And Vikor, Ikhwan Arief, Dicky Fatrias, Ferry Jie, Armijal Armijal Dec 2023

Innovative Multi-Criteria Decision-Making Approach For Supplier Evaluation: Combining Tlf, Fuzzy Bwm, And Vikor, Ikhwan Arief, Dicky Fatrias, Ferry Jie, Armijal Armijal

Research outputs 2022 to 2026

Addressing the performance issues of underperforming suppliers necessitates a thorough evaluation, serving as a catalyst for initiating supplier development efforts. However, the inherent inaccuracies in information introduce complexity, especially when human judgment is involved in the supplier evaluation process. Associated with such problem, this study presents a novel methodology for supplier performance evaluation in the crumb rubber industry, integrating the Taguchi Loss Function (TLF), fuzzy Best-Worst Method (BWM), and VIKOR technique in group decision-making environment. Aimed at addressing the challenges in industries with variable supplier quality and performance, such as the crumb rubber industry in Indonesia, the methodology was empirically …

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Waterbody Size Influences Chemical And Community Characteristics Of North Dakota Prairie Wetlands And Lakes, Julia Renee Hampton Dec 2023

Waterbody Size Influences Chemical And Community Characteristics Of North Dakota Prairie Wetlands And Lakes, Julia Renee Hampton

Theses and Dissertations

The Prairie Pothole Region (PPR) of North America is home to dynamic glacier-formed lakes and wetlands that range in size from small intermittent wetlands to large permanently filled basins. Predicting water-related shifts in environmental conditions and biological community responses within these systems has been challenging due to non-linear, scale-specific changes. Furthermore, landscape-level changes in the quantity and distribution of surface water are becoming more frequent. This thesis contributes to our understanding of how waterbody size, and potential size fluctuations, influence chemical and community dynamics of complex PPR glacial lakes and wetlands. We paired remote sensing and discontinuity methods with US …

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Residual Trapping Of Co2, N2, And A Co2-N2 Mixture In Indiana Limestone Using Robust Nmr Coreflooding: Implications For Co2 Geological Storage, Amer Alanazi, Auby Baban, Muhammad Ali, Alireza Keshavarz, Stefan Iglauer, Hussein Hoteit Dec 2023

Residual Trapping Of Co2, N2, And A Co2-N2 Mixture In Indiana Limestone Using Robust Nmr Coreflooding: Implications For Co2 Geological Storage, Amer Alanazi, Auby Baban, Muhammad Ali, Alireza Keshavarz, Stefan Iglauer, Hussein Hoteit

Research outputs 2022 to 2026

Carbon capture and sequestration (CCS) in geological formations is a prominent solution for reducing anthropogenic carbon emissions and mitigating climate change. The capillary trapping of CO2 is a primary trapping mechanism governed by the pressure difference between the wetting and nonwetting phases in a porous rock, making the latter a key input parameter for dynamic simulation models. During the CCS operational process, however, the CO2 is prone to contamination by impurities from various sources such as surfaces (e.g., pipelines and tanks) and the subsurface (e.g., existing natural gas). Such contamination can strongly influence the overall CO2 wettability, storage capacity, and …

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Substantial Blue Carbon Sequestration In The World’S Largest Seagrass Meadow, Chuancheng Fu, Sofia Frappi, Michelle N. Havlik, Wells Howe, S. David Harris, Elisa Laiolo, Austin J. Gallagher, Pere Masqué, Carlos M. Duarte Dec 2023

Substantial Blue Carbon Sequestration In The World’S Largest Seagrass Meadow, Chuancheng Fu, Sofia Frappi, Michelle N. Havlik, Wells Howe, S. David Harris, Elisa Laiolo, Austin J. Gallagher, Pere Masqué, Carlos M. Duarte

Research outputs 2022 to 2026

Seagrass meadows are important sinks for organic carbon and provide co-benefits. However, data on the organic carbon stock in seagrass sediments are scarce for many regions, particularly The Bahamas, which accounts for up to 40.7% of the documented global seagrass area, limiting formulation of blue carbon strategies. Here, we sampled 10 seagrass meadows across an extensive island chain in The Bahamas. We estimate that Bahamas seagrass meadows store 0.42–0.59 Pg organic carbon in the top-meter sediments with an accumulation rate of 2.1–2.9 Tg annually, representing a substantial global blue carbon hotspot. Autochthonous organic carbon in sediments decreased from ~1980 onwards, …

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Time Reduction For Slm Ofdm Papr Based On Adaptive Genetic Algorithm In 5g Iot Networks, Esam A. A. Hagras, Sameh F. Desouky, Saad Aldosary, Haitham Khaled, Tarek M. Hassan Dec 2023

Time Reduction For Slm Ofdm Papr Based On Adaptive Genetic Algorithm In 5g Iot Networks, Esam A. A. Hagras, Sameh F. Desouky, Saad Aldosary, Haitham Khaled, Tarek M. Hassan

Research outputs 2022 to 2026

In this paper, a new peak average power and time reduction (PAPTR) based on the adaptive genetic algorithm (AGA) strategy is used in order to improve both the time reduction and PAPR value reduction for the SLM OFDM and the conventional genetic algorithm (GA) SLM-OFDM. The simulation results demonstrate that the recommended AGA technique reduces PAPR by about 3.87 dB in comparison to SLM-OFDM. Comparing the suggested AGA SLM-OFDM to the traditional GA SLM-OFDM using the same settings, a significant learning time reduction of roughly 95.56% is achieved. The PAPR of the proposed AGA SLM-OFDM is enhanced by around 3.87 …

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Exploring Teachers’ Reflections And Narratives Of Negative Language, Maya Khemlani David, Ameer Ali, Francisco Perlas Dumanig, Muhammad Hassan Abbasi Dec 2023

Exploring Teachers’ Reflections And Narratives Of Negative Language, Maya Khemlani David, Ameer Ali, Francisco Perlas Dumanig, Muhammad Hassan Abbasi

Journal of English and Applied Linguistics

Language is used to communicate and express feelings and emotions. In the teaching context, teachers use language to share knowledge and information with students. Teachers’ use of negative language, such as duffer, stupid, and lazy, may result in students feeling mistreated, discouraged, and worthless. Such language can also negatively affect students’ cognitive processes, feelings, and emotions and blunt their curiosity, and their interest in performing better may be reduced. Although much of the previous research has demonstrated the cause-effect relation between negative teacher talk and students’ unsatisfactory performance, none of the studies, to the best of our knowledge, explored teachers’ …

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Language As The Catalyst Between The Relationship Of Subordinates' Communicative Competence And Supervisors' Communicative Behavior: A Canonical Correlation Analysis, Lindsey N. Tan Dec 2023

Language As The Catalyst Between The Relationship Of Subordinates' Communicative Competence And Supervisors' Communicative Behavior: A Canonical Correlation Analysis, Lindsey N. Tan

Journal of English and Applied Linguistics

Communicative competence could be understood as the ability to effectively use language in different contexts, and one of these contexts is the intricate framework of the supervisor-subordinate relationship (SSR). However, studies on SSR are mostly based on supervisors’ communicative behavior (SCB), and there is a scarcity of studies that investigate the role of subordinates’ organizational communication competence (SOCC) on SSR. Consequently, this study aims to investigate the relationship between SOCC and SCB in the SSR framework. Using the canonical correlation analysis, two sets of facets were used to analyze the relationship. The first set is the SOCC, which includes communicative …

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The Economics Of Financial Scams: Evidence From Initial Coin Offerings, Kenny Phua, Bo Sang, Chi Shen Wei, Gloria Yang Yu Dec 2023

The Economics Of Financial Scams: Evidence From Initial Coin Offerings, Kenny Phua, Bo Sang, Chi Shen Wei, Gloria Yang Yu

Research Collection Lee Kong Chian School Of Business

We examine the economics of financial scams by analyzing the market for initial coin offerings (ICOs). Using data snapshots of 5,873 ICOs, we find that irregularities in ICO characteristics across listing websites predict higher scam risk and are likely intentional. These patterns are consistent with a model where malicious issuers maximize profits by using irregularities to screen for naïve investors. Almost half of the ICOs in our sample may be scams, amounting to more than U.S. $6 billion in losses. Our results draw attention to the frequent use of screening mechanisms in financial scams.

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In Search Of Cryptocurrency Failure, Donglian Ma, Jun Tu, Zhaobo Zhu Dec 2023

In Search Of Cryptocurrency Failure, Donglian Ma, Jun Tu, Zhaobo Zhu

Research Collection Lee Kong Chian School Of Business

This paper explores the determinants of cryptocurrency failure and the pricing of crypto failure risk. We document different significant market- and characteristic-based predictors for coin and token failures. The introduction of Bitcoin futures and the outbreak of COVID19 affect the importance of many predictors. Investors require extra return for bearing high failure risk of crypto assets. The return difference across high and low failure risk crypto assets is not explained by the market, size and momentum factors in the cryptocurrency market. Finally, investors benefit from diversifying into high failure risk crypto assets that is little correlated with the stock market.

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Fall 2023 Issue: Authors' Biographies, Antonina Lukenchuk Nov 2023

Fall 2023 Issue: Authors' Biographies, Antonina Lukenchuk

i.e.: inquiry in education

No abstract provided.

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Conducting Participatory Research Methods Online: A How-To Guide, Brittany Arthur, Batsheva Guy, Nancy Rogers Nov 2023

Conducting Participatory Research Methods Online: A How-To Guide, Brittany Arthur, Batsheva Guy, Nancy Rogers

i.e.: inquiry in education

The pandemic challenged many of us as researchers, requiring that we reflect upon our methods and make modifications to allow for online facilitation. As researchers who traditionally use Participatory Research Methods (PRMs), we were significantly challenged, to reflect on our approach and the ways in which we may remain true to the spirit of PRMs. Through this article, we provide an overview of how we modified two PRMs, Group Level Assessment (GLA) and Photovoice. Additionally, we provide a debrief on the aspects of PRMs we intentionally reflected on as part of our modification process; in particular, how we upheld and …

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The Effect Of Gamification On Pre-Service Teachers' Technology Acceptance, İsmail Yildiz, Ersin Topçu, Esra İzmi̇r Nov 2023

The Effect Of Gamification On Pre-Service Teachers' Technology Acceptance, İsmail Yildiz, Ersin Topçu, Esra İzmi̇r

i.e.: inquiry in education

This study delves into the transformative potential of gamification within the realm of education by integrating game elements into a lesson process primarily designed for non-gaming purposes and contexts. In this study, gamification was created by incorporating game elements such as points, badges and leaderboards into a lesson process designed for a non-game purpose and context. The study investigated the effect of gamification on pre-service social studies teachers' technology acceptance. "Technology Acceptance Scale for Teachers" (T-TAM) and structured interview were used to collect data. The study utilized a quasi-experimental design with a pretest-posttest control group designed to test the cause-and-effect …

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Teachers And Leaders’ Perspectives On The Knowledge Management Of Schools Through Teachers’ Mobility, Esen Altunay, Evrim Erol Nov 2023

Teachers And Leaders’ Perspectives On The Knowledge Management Of Schools Through Teachers’ Mobility, Esen Altunay, Evrim Erol

i.e.: inquiry in education

The purpose of this study was to examine the effects of teacher mobility on the knowledge management based on the experiences of teachers and school principals of primary and secondary schools in Turkey. The mobility of teachers in Turkey is fairly high, which makes it significant to study in terms of school management. The analysis of qualitative interviews with thirty participants revealed several meaningful themes pertaining to the advantages and disadvantages of teacher mobility in terms of knowledge management, as well as the strategies to increase the contributions of teachers to knowledge management of the schools that they have to …

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Gr-405 Boosting Clickbait Detection Through Semantic Insights And Attention-Driven Neural Network, Lokesh Meesala Nov 2023

Gr-405 Boosting Clickbait Detection Through Semantic Insights And Attention-Driven Neural Network, Lokesh Meesala

C-Day Computing Showcase

The digital age has witnessed an explosion of online content, making it increasingly challenging for users to differentiate between reliable information and clickbait, which is often misleading or sensationalized. Clickbait contributes to the spread of misinformation, phishing attacks, and illegal marketing practices, and manipulates users’ decisions. Even from a business standpoint a clickbait might not lead to a conversion, A user might land on the page by following a clickbait and get frustrated and close the page. Additionally, with the increase in the usage of large language models for content writing it is even more challenging for the general user …

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Egr-490 Importance Of Food Recognition On Blood Glucose Monitoring, Afnan Crystal Nov 2023

Egr-490 Importance Of Food Recognition On Blood Glucose Monitoring, Afnan Crystal

C-Day Computing Showcase

Maintaining blood sugar under control requires eating a healthy and balanced diet, exercising, and adhering to medications. Dietary consumption must be under strict control for diabetic patients’ general health. Traditional techniques for monitoring dietary consumption include recollection and manual record-keeping, which can be tedious and prone to mistakes. However, automated technologies for maintaining records that make use of computer vision, such as food image recognition systems, can streamline chronic health management for diabetics. These solutions seek to efficiently track daily food intake and consequential calories to facilitate and encourage lifestyle improvements. With this goal in mind, we design a Machine …

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Gc-448 Project Title: Discover, Learn, And Protect: A Mobile App For Informal Stem Learning About Local Biodiversity And Environmental Issues., Elvin Mccray, David Y. Appah, Adedunmola Banu, Binh Tran, Zenya Tucker Nov 2023

Gc-448 Project Title: Discover, Learn, And Protect: A Mobile App For Informal Stem Learning About Local Biodiversity And Environmental Issues., Elvin Mccray, David Y. Appah, Adedunmola Banu, Binh Tran, Zenya Tucker

C-Day Computing Showcase

Our team assignment for this project was to create a mobile application that offers informal STEM learning about local biodiversity and environmental issues. Dr. Ying Xie, Professor in the College of Computing and Software Engineering (CCSE) is the owner of this project, who also laid out required features and provided necessary information, guidance, and advice for the project development. The core function of this application is to empower users to explore, identify and gain insights into the plant and animal species native to their region. Leveraging the capabilities of their smartphone’s camera, users can effortlessly scan, record, or locate local …

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Gc-511 Predicting Stock Prices Using Different Machine Learning And Deep Learning Models, Afnan Crystal, Rohith Sundar Jonnalagadda, Hrithik Singh Chandel Nov 2023

Gc-511 Predicting Stock Prices Using Different Machine Learning And Deep Learning Models, Afnan Crystal, Rohith Sundar Jonnalagadda, Hrithik Singh Chandel

C-Day Computing Showcase

Our project focuses on the challenge of predicting the daily closing prices and stock movements of Amazon, one of the world's largest and most dynamic corporations. Amazon's stock prices are known for their unpredictability and are influenced by a multitude of intricate factors. Our project aims to provide accurate and reliable forecasts for Amazon's stock prices, going beyond mere predictions. The analysis employs a comprehensive approach, comparing the performance of three distinct machine learning and deep learning models: Linear Regression, Support Vector Machine (SVM), and Multi-Layered Perceptron (MLP) for financial time series data. The dataset we used spans from January …

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Uc-491 Spectrum Analysis Cli Tool, Vitor B. Santos, Trey Redden, Sam Corella, Christopher Flores Santos, Jonathan Glennon Nov 2023

Uc-491 Spectrum Analysis Cli Tool, Vitor B. Santos, Trey Redden, Sam Corella, Christopher Flores Santos, Jonathan Glennon

C-Day Computing Showcase

The Spectrum Analysis CLI Tool takes in .mp4 recordings of a Spectrum Analyzer, converts them programmatically into values the application can understand and outputs this data into a .csv file. This file can be parsed/filtered by the user with commands during upload of the .mp4 recording, or anytime after the recording has been processed.

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Gr-515 Developing A Conversational Chatbot Using Seq2seq Model With Tensorflow, Drashtee Parmar, Ruthvik R. Anugu Nov 2023

Gr-515 Developing A Conversational Chatbot Using Seq2seq Model With Tensorflow, Drashtee Parmar, Ruthvik R. Anugu

C-Day Computing Showcase

Sequence-to-Sequence (Seq2Seq) modeling, when paired with Long-Short-Term Memory (LSTM) units, has demonstrated significant potential in developing conversational chatbot capable of participating in text-based conversation and providing human-like responses.The Cornell Movie-Dialogs Corpus will be used to extract dialogues, preprocess the data, and then use the output to train the Seq2Seq model. Our contributions include exploring the application of LSTM for Natural Language Generation (NLG) and creating a comprehensive chatbot system. According to the results of the experiment, our method works well for coming up with thoughtful answers during a conversation.

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Ur-409 Enhancing Aircraft Electronic Warfare Testing With Automated Rf Spectrum Analysis, Anthony De Santiago, Matthew T. Morgan, Geonhyeong Kim, Jalon L. Bailey, Camille Reaves Nov 2023

Ur-409 Enhancing Aircraft Electronic Warfare Testing With Automated Rf Spectrum Analysis, Anthony De Santiago, Matthew T. Morgan, Geonhyeong Kim, Jalon L. Bailey, Camille Reaves

C-Day Computing Showcase

Military test ranges utilize a variety of Radio Frequency (RF) threat systems, to assess the effectiveness of Electronic Warfare (EW) systems during flight tests. A component of this process involves monitoring RF transmissions. Traditionally, system engineers at Robins Airforce Base have manually analyzed video from spectrum analyzers to confirm properties of specific threat systems. To streamline this analysis, our team's aim was to develop an automated solution for RF spectrum analysis. We employed a custom YOLO V8 model to isolate the analyzer screen and used a novel combination of frame differencing, summing, and agglomerative clustering techniques to extract relevant properties …

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Gc-427 Elevating Ai Research: Creating A Website For Kennesaw State University's Ai Lab, Shashank Gadhe Nov 2023

Gc-427 Elevating Ai Research: Creating A Website For Kennesaw State University's Ai Lab, Shashank Gadhe

C-Day Computing Showcase

The project titled "Elevating AI Research: Creating a website for Kennesaw State University's AI Lab" is dedicated to developing an HTML5 Content Management System website for Kennesaw State University. This website, AILab.kennesaw.edu, serves as a dedicated platform to showcase lab facilities, ongoing projects, and cutting-edge research, with a focus on promoting global AI research and education. Our target audience encompasses university students, faculty, AI researchers, and organizations with an interest in AI innovation.Preliminary findings support our goal: engaging platforms showcasing AI Lab research effectively.The incorporation of admin access empowers university professors to customize content, thus enhancing adaptability and personalization. These …

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Gc-447 Bio-Contribute, Tejaswi Divi, Kiranmayi Tandra, Sainath Reddy Bheemireddy, Chandrasekhar Reddy Bheemireddy, Sharanya Chinthakuntla Nov 2023

Gc-447 Bio-Contribute, Tejaswi Divi, Kiranmayi Tandra, Sainath Reddy Bheemireddy, Chandrasekhar Reddy Bheemireddy, Sharanya Chinthakuntla

C-Day Computing Showcase

The "Bio-Contribute" challenge is an ambitious initiative aimed at revolutionizing the way facts are generated and shared in lifestyle sciences. Bio-Contribute encompasses various aspects, including design, development, and facts collection. It leverages Figma for innovation, ensuring a user-friendly and collaborative interface. The challenge has completed the frontend development section, permitting customers to carry out various movements, which include content advent and information seizure with the help of the GPT-3 era. This report gives an in-depth analysis of the venture's progression, strategies used, and initial outcomes, demonstrating its potential to convert statistics introduction and sharing in the discipline of lifestyles sciences.

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Gr-406 Federated Learning In Cardiac Diagnostics: Balancing Predictive Accuracy With Data Privacy In Heart Sound Classification, Sricharan Donkada Nov 2023

Gr-406 Federated Learning In Cardiac Diagnostics: Balancing Predictive Accuracy With Data Privacy In Heart Sound Classification, Sricharan Donkada

C-Day Computing Showcase

Cardiovascular diseases account for nearly a third of global deaths, posing a challenge that machine learning can help address. However, data privacy concerns hinder the direct application of conventional machine learning in this sensitive area. This paper explores Federated Learning (FL) as a decentralized strategy to mitigate these concerns by allowing for local data processing. FL's design ensures that only processed updates, not raw data, are shared with a central server, maintaining individual privacy. Our research assesses FL's practicality and effectiveness in predicting heart disease while adhering to ethical and legal norms. We build upon previous studies, such as Wanyong …

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Gr-422 Simplified Named Entity Recognition Using Context Free Grammar, Sai Chandana Koganti, Varshini Yaganti, Vinesh Babu Yaganti, Surya Kiran Katragadda, Pavani Thulluru Nov 2023

Gr-422 Simplified Named Entity Recognition Using Context Free Grammar, Sai Chandana Koganti, Varshini Yaganti, Vinesh Babu Yaganti, Surya Kiran Katragadda, Pavani Thulluru

C-Day Computing Showcase

Named Entity Recognition (NER) is a crucial component of natural language processing. Although Spacy is a popular tool for NER, it faces challenges in accurately identifying individual's names. In response, Context-Free Grammar (CFG) is introduced as a complementary solution to augment Spacy's NER functionality, with the specific objective of enhancing the precision of person name recognition. This project focuses on formulating CFG rules and applying them to a sample text, showcasing improved NER accuracy. By combining the strengths of Spacy and CFG, we aim to address the limitations of current NER systems, particularly in recognizing individual's names, and contribute to …

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