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Articles 33961 - 33990 of 294560
Full-Text Articles in Physical Sciences and Mathematics
Clearspeech: Improving Voice Quality Of Earbuds Using Both In-Ear And Out-Ear Microphones, Dong Ma, Ting Dang, Ming Ding, Rajesh Krishna Balan
Clearspeech: Improving Voice Quality Of Earbuds Using Both In-Ear And Out-Ear Microphones, Dong Ma, Ting Dang, Ming Ding, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Wireless earbuds have been gaining increasing popularity and using them to make phone calls or issue voice commands requires the earbud microphones to pick up human speech. When the speaker is in a noisy environment, speech quality degrades significantly and requires speech enhancement (SE). In this paper, we present ClearSpeech, a novel deep-learningbased SE system designed for wireless earbuds. Specifically, by jointly using the earbud’s in-ear and out-ear microphones, we devised a suite of techniques to effectively fuse the two signals and enhance the magnitude and phase of the speech spectrogram. We built an earbud prototype to evaluate ClearSpeech under …
A Comparative Study Of Cationic Copper(I) Reagents Supported By Bipodal Tetramethylguanidinyl-Containing Ligands As Nitrene-Transfer Catalysts, Suraj Kumar Sahoo, Brent Harfmann, Himanshu Bhatia, Harish Singh, Srikanth Balijapelly, Amitava Choudhury, Pericles Stavropoulos
A Comparative Study Of Cationic Copper(I) Reagents Supported By Bipodal Tetramethylguanidinyl-Containing Ligands As Nitrene-Transfer Catalysts, Suraj Kumar Sahoo, Brent Harfmann, Himanshu Bhatia, Harish Singh, Srikanth Balijapelly, Amitava Choudhury, Pericles Stavropoulos
Chemistry Faculty Research & Creative Works
The Bipodal Compounds [(TMG2biphenN-R)CuI-NCMe](PF6) (R = Me, Ar (4-CF3Ph-)) And [(TMG2biphenN-Me)CuI-I] Have Been Synthesized With Ligands That Feature A Diarylmethyl- And Triaryl-Amine Framework And Superbasic Tetramethylguanidinyl Residues (TMG). The Cationic Cu(I) Sites Mediate Catalytic Nitrene-Transfer Reactions Between The Imidoiodinane PhI = NTs (Ts = Tosyl) And A Panel Of Styrenes In MeCN, To Afford Aziridines, Demonstrating Comparable Reactivity Profiles. The Copper Reagents Have Been Further Explored To Execute C-H Amination Reactions With A Variety Of Aliphatic And Aromatic Hydrocarbons And Two Distinct Nitrene Sources PhI = NTs And PhI = NTces (Tces = 2,2,2-Trichloroethylsulfamate) In Benzene/HFIP (10:2 V/v). Good Yields …
Perfect Polar Alignment Of Parallel Beloamphiphile Layers: Improved Structural Design Bias Realized In Ferroelectric Crystals Of The Novel “Methoxyphenyl Series Of Acetophenone Azines”, Harmeet Bhoday, Nathan Knotts, Rainer Glaser
Perfect Polar Alignment Of Parallel Beloamphiphile Layers: Improved Structural Design Bias Realized In Ferroelectric Crystals Of The Novel “Methoxyphenyl Series Of Acetophenone Azines”, Harmeet Bhoday, Nathan Knotts, Rainer Glaser
Chemistry Faculty Research & Creative Works
An Improved Design Is Described For Ferroelectric Crystals And Implemented With The "Methoxyphenyl Series" Of Acetophenone Azines, (MeO−Ph, Y)-Azines With Y=F (1), Cl (2), Br (3), Or I (4). The Crystal Structures Of These Azines Exhibit Polar Stacking Of Parallel Beloamphiphile Monolayers (PBAMs). Azines 1, 3, And 4 Form True Racemates Whereas Chloroazine 2 Crystallizes As A Kryptoracemate. Azines 1–4 Are Helical Because Of The N−N Bond Conformation. In True Racemates The Molecules Of Opposite Helicity (M And P) Are Enantiomers A(M) And A*(P) While In Kryptoracemates They Are Diastereomers A(M) And B*(P). The Stacking Mode Of PBAMs Is Influenced …
Solar Enhanced Oxygen Evolution Reaction With Transition Metal Telluride, Harish Singh, Taishi Higuchi-Roos, Fabrice Roncoroni, David Prendergast, Manashi Nath
Solar Enhanced Oxygen Evolution Reaction With Transition Metal Telluride, Harish Singh, Taishi Higuchi-Roos, Fabrice Roncoroni, David Prendergast, Manashi Nath
Chemistry Faculty Research & Creative Works
The Photo-Enhanced Electrocatalytic Method of Oxygen Evolution Reaction (OER) Shows Promise for Enhancing the Effectiveness of Clear Energy Generation through Water Splitting by using Renewable and Sustainable Source of Energy. However, Despite Benefits of Photo electrocatalytic (PEC) Water Splitting, its Uses Are Constrained by its Low Efficiency as a Result of Charge Carrier Recombination, a Large overpotential, and Sluggish Reaction Kinetics. Here, We Illustrate that Nickel Telluride (NiTe) Synthesized by Hydrothermal Methods Can Function as an Extremely Effective Photo-Coupled Electrochemical Oxygen Evolution Reaction (POER) Catalyst. in This Study, NiTe Was Synthesized by Hydrothermal Method at 145°C within Just an Hour …
Polar Stacking Of Dipole Parallel-Aligned Monolayers Of Unsymmetrical 1,4-Diphenyl-1,3-Butadienes Creates Nonlinear Optical Materials: Insights From Experiments Guide Structure Assignments, Harmeet Bhoday, Justin Nulsen, Steven P. Kelley, Rainer Glaser
Polar Stacking Of Dipole Parallel-Aligned Monolayers Of Unsymmetrical 1,4-Diphenyl-1,3-Butadienes Creates Nonlinear Optical Materials: Insights From Experiments Guide Structure Assignments, Harmeet Bhoday, Justin Nulsen, Steven P. Kelley, Rainer Glaser
Chemistry Faculty Research & Creative Works
A series of 1-(4′-halophenyl)-4-(4″-methoxyphenyl) buta-1,3-dienes, (H, MeO, Y)-1,4-diphenylbutadienes with halogens Y = F (1), Cl (2), Br (3), and I (4) are described. Crystal structure analysis establishes that 1-4 present a new class of highly dipole parallel-aligned polar organic molecular materials for nonlinear optics (NLO). Building on previous studies of polar crystals of unsymmetrical acetophenone azines, (R, X, Y)-azines, X-Ph-CR═N-N═CR-Ph-Y (R = Me; X = R'O, PhO, R'OPh; Y = F, Cl, Br, I), we suspected that the all-carbon analogs (R, R'O, Y)-1,4-diphenylbutadienes, R'O-Ph-CR═CH-CH═CR-Ph-Y, could crystallize with polar lattices and feature stronger NLO effects because of their improved conjugation and …
Dna Origami-Assisted Regioselective Organization Of Anisotropic Gold Nanotriangle Clusters, Wenyan Liu, Prashant Gupta, Yuwei Zhang, Krishna Thapa, Srikanth Singamaneni, Risheng Wang
Dna Origami-Assisted Regioselective Organization Of Anisotropic Gold Nanotriangle Clusters, Wenyan Liu, Prashant Gupta, Yuwei Zhang, Krishna Thapa, Srikanth Singamaneni, Risheng Wang
Chemistry Faculty Research & Creative Works
The manipulation of anisotropic nanoparticles, such as gold nanorods and nano prisms, has attracted great attention in nanotechnology due to their sensitive geometry-dependent properties. However. traditional synthesis and assembly methods for these particles face challenges in size uniformity and higher-order structuring. To address these limitations, this study presents a strategy using DNA origami triangles, not just as templates, but as encapsulating agents for gold nanotriangles (AuNTs). This method enables the construction of diverse nanoparticle clusters with precisely controlled distance and orientation. The formed clusters exhibit unique optical characteristics, demonstrated by UV-visible spectroscopy and supported by finite-difference time domain (FDTD) simulations. …
Selected Trace Element Uptake By Rice Grain As Affected By Soil Arsenic, Water Management And Cultivar -A Field Investigation, Eric M. Farrow, Jianmin Wang, Honglan Shi, John Yang, Bin Hua, Baolin Deng
Selected Trace Element Uptake By Rice Grain As Affected By Soil Arsenic, Water Management And Cultivar -A Field Investigation, Eric M. Farrow, Jianmin Wang, Honglan Shi, John Yang, Bin Hua, Baolin Deng
Chemistry Faculty Research & Creative Works
Accumulation of arsenic (As) in rice grain was reported in many regions of the world, including the United States, which has been a threat to human health. This field research investigated the grain As accumulation and its relationship with the uptake of selenium (Se), molybdenum (Mo), and cadmium (Cd) in soils with and without monosodium methane arsonate (MSMA) amended, as effects of selected rice cultivars and water management. Results indicated that MSMA increased the accumulation of As and Se but decreased Mo for all six cultivars under four irrigation management. MSMA also increased grain-Cd in some cultivars. In no MSMA-amended …
High-Capacity Anode For Sodium-Ion Batteries Using Hard Carbons Derived From Polyurea-Cross-Linked Silica Xerogel Powders, Santhoshkumar Sundaramoorthy, Rushi U. Soni, Stephen Yaw Owusu, Sutapa Bhattacharya, A. B.M.Shaheen Ud Doulah, Vaibhav A. Edlabadkar, Chariklia Sotiriou-Leventis, Amitava Choudhury
High-Capacity Anode For Sodium-Ion Batteries Using Hard Carbons Derived From Polyurea-Cross-Linked Silica Xerogel Powders, Santhoshkumar Sundaramoorthy, Rushi U. Soni, Stephen Yaw Owusu, Sutapa Bhattacharya, A. B.M.Shaheen Ud Doulah, Vaibhav A. Edlabadkar, Chariklia Sotiriou-Leventis, Amitava Choudhury
Chemistry Faculty Research & Creative Works
In this article, we demonstrated carbon aerogel-silica composites derived from polyurea-cross-linked silica xerogel powders (C-PUA@silica) as anodes for Na-ion batteries. These xerogel-derived hard carbons with embedded silica showed a stable high capacity. Of the several hard carbon samples derived at different temperatures, the pyrolyzed sample at 800 °C (C-PUA@silica-800) showed a high capacity of 236 mAh/g at a current density of 10 mA/g and a stable cycle-life at 200 mAh/g. The galvanostatic charge-discharge curves displayed a sloping voltage profile reminiscent of the adsorption mechanism of Na+ storage. On the other hand, higher temperature-pyrolyzed samples at 1300 °C (C-PUA@silica-1300) displayed a …
Boosting The Microbial Electrosynthesis Of Formate By Shewanella Oneidensis Mr-1 With An Ionic Liquid Cosolvent, Ashwini Dantanarayana, Wassim El Housseini, Kevin Beaver, Monica Brachi, Timothy P. Mcfadden, Shelley D. Minteer
Boosting The Microbial Electrosynthesis Of Formate By Shewanella Oneidensis Mr-1 With An Ionic Liquid Cosolvent, Ashwini Dantanarayana, Wassim El Housseini, Kevin Beaver, Monica Brachi, Timothy P. Mcfadden, Shelley D. Minteer
Chemistry Faculty Research & Creative Works
Microbial electrosynthesis (MES) is a rapidly growing technology at the forefront of sustainable chemistry, leveraging the ability of microorganisms to catalyze electrochemical reactions to synthesize valuable compounds from renewable energy sources. The reduction of CO2 is a major target application for MES, but research in this area has been stifled, especially with the use of direct electron transfer (DET)-based microbial systems. The major fundamental hurdle that needs to be overcome is the low efficiency of CO2 reduction largely attributed to minimal microbial access to CO2 owing to its low solubility in the electrolyte. With their tunable physical …
Hardware-Assisted Live Kernel Function Updating On Intel Platforms, Lei Zhou, Fengwei Zhang, Kevin Leach, Xuhua Ding, Zhenyu Ning, Guojun Wang, Jidong Xiao
Hardware-Assisted Live Kernel Function Updating On Intel Platforms, Lei Zhou, Fengwei Zhang, Kevin Leach, Xuhua Ding, Zhenyu Ning, Guojun Wang, Jidong Xiao
Research Collection School Of Computing and Information Systems
Traditional kernel updates such as perfective maintenance and vulnerability patching requires shutting the system down, disrupting continuous execution of applications. Enterprises and researchers have proposed various live updating techniques to patch the kernel with lower downtime to reduce the loss of useful uptime. However, existing kernel live update techniques either rely on specific support from the target OS, or are deployed in virtualized environments (i.e., systems running in virtual machines). In this article we present KShot , a hardware-assisted live and secure kernel function update mechanism for native operating systems. By leveraging x86 SMM and Intel SGX, KShot runs in …
Effects Of Mindfulness And Emotion Regulation On Aesthetics: A Theoretical Model From Hedonic Perspective Of Processing Fluency, Geng-Bao Lin, Fiona Fui-Hoon Nah, Choon Ling Sia
Effects Of Mindfulness And Emotion Regulation On Aesthetics: A Theoretical Model From Hedonic Perspective Of Processing Fluency, Geng-Bao Lin, Fiona Fui-Hoon Nah, Choon Ling Sia
Research Collection School Of Computing and Information Systems
Research has shown that processing fluency positively impacts perceived aesthetics, with pleasure mediating the relationship. Considering the important role of pleasure, we propose studying the role of emotion regulation in moderating the mediated relationship from processing fluency to perceived aesthetics. Based on our hypotheses, individuals’ emotion regulation strategies are expected to have moderating effects on the relationship between processing fluency and perceived aesthetics such that cognitive reappraisal positively moderates the relationship from processing fluency to pleasure, and expressive suppression negatively moderates the relationship from pleasure to perceived aesthetics. Trait mindfulness is also expected to influence perceived aesthetics through emotion regulation …
Continual Learning, Fast And Slow, Quang Anh Pham, Chenghao Liu, Steven C. H. Hoi
Continual Learning, Fast And Slow, Quang Anh Pham, Chenghao Liu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
According to the Complementary Learning Systems (CLS) theory (McClelland et al. 1995) in neuroscience, humans do effective continual learning through two complementary systems: a fast learning system centered on the hippocampus for rapid learning of the specifics, individual experiences; and a slow learning system located in the neocortex for the gradual acquisition of structured knowledge about the environment. Motivated by this theory, we propose DualNets (for Dual Networks), a general continual learning framework comprising a fast learning system for supervised learning of pattern-separated representation from specific tasks and a slow learning system for representation learning of task-agnostic general representation via …
Investigating Drought Response And Paleoclimate Potential Of A New Network Of White Oak Chronologies In Western Kentucky, Usa, Audrey J. Heichelbech, Maegen L. Rochner, Megan Gibson
Investigating Drought Response And Paleoclimate Potential Of A New Network Of White Oak Chronologies In Western Kentucky, Usa, Audrey J. Heichelbech, Maegen L. Rochner, Megan Gibson
Undergraduate Research Events
In Kentucky, historic and paleo-climate data are limited, and current understanding of long-term climate change in the state relies on instrumental data spanning only 1895-present. Proxy data are necessary to extend the temporal and spatial span of climate information. One potential proxy source for Kentucky is tree ring data, but currently, only four such datasets are publicly available on the International Tree Ring Data Bank (ITRDB). Archaeological and archival timber sources may help to fill in this gap. In the 1940s, Florence Hawley-Ellis, the first woman dendrochronologist, collected samples of white oak (Quercus alba L.) from four counties in western …
The Attitudes And Practices Of United Arab Emirates Consumers Towards Food Waste: A Nationwide Cross-Sectional Study, Lynne Kennedy, Samir Safi, Tareq M. Osaili, Ala Al Rajabi, Ayesha Alblooshi, Dima Al Jawarneh, Ahmed Al Kaabi, Fakhra Al Rubaei, Maitha Albreiki, Maryam Alfadli, Aseilah Alhefeiti, Moez Al Islam Ezzat Faris, Kholoud Allaham, Sameeha Junaidi, Moien A.B. Khan
The Attitudes And Practices Of United Arab Emirates Consumers Towards Food Waste: A Nationwide Cross-Sectional Study, Lynne Kennedy, Samir Safi, Tareq M. Osaili, Ala Al Rajabi, Ayesha Alblooshi, Dima Al Jawarneh, Ahmed Al Kaabi, Fakhra Al Rubaei, Maitha Albreiki, Maryam Alfadli, Aseilah Alhefeiti, Moez Al Islam Ezzat Faris, Kholoud Allaham, Sameeha Junaidi, Moien A.B. Khan
All Works
Background: Reducing global food waste is an international environmental, health, and sus-tainability priority. Although significant reductions have been achieved across the food chain, progress by UAE households and consumers remain inadequate. This study seeks to understand the association between consumer attitudes, knowledge, and awareness relating to food waste practice of residents living in the UAE. to help inform policy and action for addressing this national priority. Methods: A cross-sectional study was conducted using a validated semi-structured online questionnaire through stratified sampling (n =1052). The Spearman correlation coefficient was performed to determine the correlations. Two independent regression analysis were used to …
Petrologic And Geochemical Constraints On The Pre-Eruptive Storage Conditions Of Magmas Erupted During The ~12.5 Ka Flare Up Of Medicine Lake Volcano, Ca, Regina M. Khoury
Petrologic And Geochemical Constraints On The Pre-Eruptive Storage Conditions Of Magmas Erupted During The ~12.5 Ka Flare Up Of Medicine Lake Volcano, Ca, Regina M. Khoury
Cal Poly Humboldt theses and projects
The Medicine Lake Volcano (MLV) system in the California Cascades is composed of a large shield volcano with numerous basaltic to rhyolitic vents on and around the flanks, many of which are aligned with N-S trending normal faults. A significant portion of the post-glacial volcanic activity at MLV is comprised of the ~12.5 ka “flare up” eruptions of basalt and basaltic andesite magmas from seven discrete flank vents. Prior work documented surface areas (0.02-198 km2), volumes (0.0001-4.35 km3), and eruption styles (Hawaiian to Strombolian; Donnelly-Nolan, 2010) of the ~12.5 ka deposits. This study uses new geologic …
Enhancing Security And Performance In Vehicular Adhoc Networks: A Machine Learning Approach To Combat Adversarial Attacks, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Ahmed Raheem Abdulnabi
Enhancing Security And Performance In Vehicular Adhoc Networks: A Machine Learning Approach To Combat Adversarial Attacks, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Ahmed Raheem Abdulnabi
Mesopotamian Journal of Computer Science
Integrating Machine Learning (ML) techniques into Vehicular Adhoc Networks (VANETs) provides promising features in autonomous driving and ITS applications. In this paper, DSRC data is used to evaluate the effectiveness of different ML models, including Naive Bayes, Random Forest, KNN, and Gradient Boosting, in normal and adversarial scenarios. Since the dataset is relatively imbalanced, the Synthetic Minority Over-sampling Technique (SMOTE) is employed for sampling, and defensive distillation for improving model resilience to adversarial perturbations. From the results, it is clear that models such as Gradient Boosting and Random Forest show high accuracy in both cases, thus showing the potential of …
Using Unsupervised Learning Methods In Extracting Features For Classifying Rice Varieties From Rice Grains Images., Kevin Anthony Martinez
Using Unsupervised Learning Methods In Extracting Features For Classifying Rice Varieties From Rice Grains Images., Kevin Anthony Martinez
ICT
Rice, a staple food for nearly half of the global population, requires accurate classification of its varieties to ensure food quality, support agricultural trade, and enhance yield optimisation. Traditional manual classification methods are time-intensive and error-prone, prompting this study's exploration of unsupervised learning for feature extraction from rice grain images. The research tested classifiers on 75,000 rice samples across five classes, with 15,000 samples per class.
The study's DCGAN-CNN model achieved the highest classification accuracy of 99.67%. However, the PCA-CNN model underperformed, with only 20% accuracy, due to implementation errors. Recommendations for improvement include optimising model parameters such as learning …
Deep Learning Model Compression For Resource-Constrained Environments., Stephen Burke
Deep Learning Model Compression For Resource-Constrained Environments., Stephen Burke
ICT
This study examines the effects of three Deep Neural Network compression techniques—Quantisation, Pruning, and Weight Sharing/Clustering—on CNN and ANN models trained for image classification tasks. The models were tested on the CIFAR-10 dataset for multiclass classification and a binary classification task using a dataset derived from COCO. The best validation accuracy achieved was 74.7% with a CNN on CIFAR-10 and 53% with the best ANN. On the COCO dataset, a modified CIFAR-10 CNN model achieved 75%. The models were compressed using the three techniques and benchmarked on a ThinkPad laptop and Raspberry Pi 3B+ based on metrics relevant for resource-constrained …
Applying Neural Networks To Predict Factors Affecting Harmful Algal Blooms For Timely Alerting And Implementing Preventive Measures In Ireland's Marine Ecosystem., Nikolai Potapov
ICT
This study applies neural networks to predict harmful algal blooms (HABs) along the Irish coast, addressing ecological, health, and economic risks. Using primary interviews and secondary data on HAB species like Alexandrium and Karenia mikimotoi, the research incorporated Exploratory Data Analysis and tested three neural models: LSTM, Ensemble Stacking LSTM, and CNN-LSTM. Key factors influencing HABs, such as sea surface temperature and euphotic zone depth, were identified.
Results demonstrate the potential of neural networks to improve HAB prediction and monitoring, despite limitations. Future work aims to enhance model accuracy and integrate them into HAB warning systems.
Development And Optimisation Of Convolutional Neural Networks (Cnns) To Predict The Nutrition And Sustainability Scores Of Foods From Crowd Sourced Images., Cormac Mcelhinney
Development And Optimisation Of Convolutional Neural Networks (Cnns) To Predict The Nutrition And Sustainability Scores Of Foods From Crowd Sourced Images., Cormac Mcelhinney
ICT
This research explores the use of Convolutional Neural Networks (CNNs) for the automated classification and profiling of food products based on publicly sourced data. With the vast array of food products available worldwide and the complexity of labelling regulations, food business operators face challenges in ensuring compliance, while regulators struggle to verify adherence. This study addresses the need for efficient and accurate methods for food classification and eco/nutritional profiling. It begins with a comprehensive literature review on the application of CNNs in food product classification, followed by the collection of a large-scale dataset from Open Food Facts. A CNN architecture …
Evaluation And Implementation Of Machine Learning Models To Predict Customer Churn In The Telecommunications Sector., Stephen Hasson
Evaluation And Implementation Of Machine Learning Models To Predict Customer Churn In The Telecommunications Sector., Stephen Hasson
ICT
This research addresses customer churn in the Telecom industry by utilizing Machine Learning (ML) models to predict customers at risk of leaving and provide data-driven retention strategies. The study highlights the effectiveness of ML, particularly in churn prediction, while noting the need for further exploration into the ethical implications of AI, such as potential biases towards vulnerable groups. Using the CRISP-DM framework, the study develops and compares three Supervised Learning (SL) models: Random Forests (RF), LightGBM (LGBM), and XGBoost (XGB), incorporating class resampling techniques to manage data imbalance.
The findings identified five key features as the most significant predictors of …
Data Analysis Of Twitter’S Nasdaq100 Sentiments And Topics As Indicators For News Articles Retrieval: Fine-Tuning Roberta And Rag., Kagan Timur
ICT
This study investigates the combination of sentiment analysis using the VADER lexicon and semantic analysis through Latent Dirichlet Allocation (LDA) to identify real-life events, focusing on Twitter datasets. The research shows that while sentiment analysis alone may be insufficient, combining it with semantic analysis improves the process, particularly for identifying relevant news articles and understanding brand perception on social media. The study also fine-tunes the RoBERTa model for question-answering tasks, yielding significant improvements in the SQuAD evaluation metric. The exact match (EM) score rose dramatically from 2.06% to 62%, and the F1 score improved from 9.41% to 65%. A retrieval …
Responsible Natural Language Processing To Aid Employee Performance Reviews., Grace Rubinger
Responsible Natural Language Processing To Aid Employee Performance Reviews., Grace Rubinger
ICT
This research explores the use of Natural Language Processing (NLP) techniques in assessing evaluators' written appraisals during Employee Performance Reviews (EPRs), aiming to address biases inherent in traditional methods. By integrating Responsible Artificial Intelligence (AI) and foundational Large Language Models (LLMs), the study seeks to enhance the objectivity, fairness, and ethical transparency of performance evaluations. It highlights the potential of AI systems to ensure comprehensive assessments while promoting trust, ethical standards, and employee retention.
The research also aims to advance the field of AI Ethics in practical Human Resources Management (HRM) applications, particularly through NLP-driven tools. These tools are designed …
Sticky Charters? The Surprisingly Tepid Embrace Of Officer-Protecting Waivers In Delaware, Jens Frankenreiter, Eric L. Talley
Sticky Charters? The Surprisingly Tepid Embrace Of Officer-Protecting Waivers In Delaware, Jens Frankenreiter, Eric L. Talley
Scholarship@WashULaw
This article investigates the reaction to a much-heralded 2022 legal reform in Delaware that permitted a corporation’s charter to exculpate its officers from monetary exposure for breaching their fiduciary duty of care. To isolate reactions to this statutory reform, we make extensive use of generative AI tools to identify and interpret charter amendments that introduce officer-facing waivers. We find a surprisingly tepid rate of uptake among Delaware corporations through the end of the first post-reform year, notwithstanding widespread predictions that corporate entities would quickly storm the exculpation exits once permitted to do so.
Our study makes two contributions to the …
Advancing Chronic Kidney Disease Prediction Through Machine Learning And Deep Learning With Feature Analysis, Shiddarth Dey Tusar, S. M. Ahad Ali Chowdhury, Md. Jalal Uddin Chowdhury, Rana M. Pir, H. M. Nur A. Alam, Muhammad Rezaur Rahman, Md. Nural Absar Siddiky, Muhammad Enayetur Rahman
Advancing Chronic Kidney Disease Prediction Through Machine Learning And Deep Learning With Feature Analysis, Shiddarth Dey Tusar, S. M. Ahad Ali Chowdhury, Md. Jalal Uddin Chowdhury, Rana M. Pir, H. M. Nur A. Alam, Muhammad Rezaur Rahman, Md. Nural Absar Siddiky, Muhammad Enayetur Rahman
Electrical & Computer Engineering Faculty Publications
Chronic Kidney Diesease (CKD) is a significant health issue, ranking as the fourth leading cause of mortality worldwide. The traditional diagnosis and treatment process, reliant on medical experts, is time-consuming. Therefore, thereis an urgent need for more efficient diagnostic methods to improve patient outcomes and reduce mortality rates. In this study, we employ Machine Learning (ML) and Deep Learning (DL) techniques to predict CKD based on important features. Feature analysis was performed using a correlation matrix and the LASSO algo-rithm to identify the most relevant features for model training. We evaluated several ML and DL classifiers, including Logistic Regression (LR), …
Interannual Growth-Climate Relationships Of Western Larch After Wildfire In The Northwest, Junior Burks
Interannual Growth-Climate Relationships Of Western Larch After Wildfire In The Northwest, Junior Burks
Undergraduate Theses, Professional Papers, and Capstone Artifacts
Montane and mixed-conifer forests in the northwestern United States are burning at rates greater than any time in recent decades, due to the combined impacts of global warming and historical and contemporary land use and land management. Western larch (Larix occidentalis) is a tree of high regional significance, exhibiting a variety of traits that make it resistant and resilient to fire. Because seedlings are more sensitive to environmental stressors than adults, the impacts of climate change are expected to be detectable first in juvenile trees. Recent research shows that the natural regeneration of western larch after wildfires has …
Supporting Dataset For The Influence Of Tile-Water On Groundwater Nitrate Concentrations Within A Saturated Riparian Buffer Zone, Aminat Tosin Abdulsalam, Eric Wade Peterson
Supporting Dataset For The Influence Of Tile-Water On Groundwater Nitrate Concentrations Within A Saturated Riparian Buffer Zone, Aminat Tosin Abdulsalam, Eric Wade Peterson
Faculty Publications - Geography, Geology, and the Environment
In the U.S. Midwest, where fertile soils with high water retention are prevalent, the installation of tile drainage networks have become a common practice to drain excess soil water, which enhances plant growth and increases crop productivity. However, tile drainage networks coupled with the use of inorganic fertilizers have significant implications on water quality, contributing to eutrophication, leading to harmful algal blooms, and resulting in hypoxic conditions in surface water bodies. To mitigate excess nutrient exports to surface water bodies, edge-of-field practices have been introduced. One such practice is the saturated riparian buffer (SRB), which utilizes a diversion system to …
Petrologic Relationship Between Lamprophyres, Carbonatites, And Heavy Rare-Earth Element Enriched Breccias At Hicks Dome, Jarek Trela, Jared T. Freiburg, Esteban Gazel, Laurence Nuelle, Anton H. Maria, David H. Malone, John M. Molinarolo
Petrologic Relationship Between Lamprophyres, Carbonatites, And Heavy Rare-Earth Element Enriched Breccias At Hicks Dome, Jarek Trela, Jared T. Freiburg, Esteban Gazel, Laurence Nuelle, Anton H. Maria, David H. Malone, John M. Molinarolo
Faculty Publications - Geography, Geology, and the Environment
New petrological, geochemical, and P–T modelling results from igneous samples clarify how carbonatite-lamprophyre magmatism, fluorite and rare earth element (REE) enrichment are petrogenetically related in southern Illinois. P–T modelling reveals that igneous rocks derive from a deep mantle carbonated source, that is consistent with trace element signatures for a fluorine-rich transition zone origin. Major element systematics suggests liquid-immiscibility with lamprophyric melts as the origin for Ca-carbonatites. Heavy REE (HREE) enrichments in Hicks Dome breccias likely formed through preferential partitioning and transport of HREE by brine-melts, exsolved from a deep carbonatite body. Brine-melts redistributed HREEs throughout the …
Transport And Fate Of Nitrate In A Saturated Buffer Zone As Assessed With A Chloride Tracer Test, Alhassan Sahad, Eric W. Peterson
Transport And Fate Of Nitrate In A Saturated Buffer Zone As Assessed With A Chloride Tracer Test, Alhassan Sahad, Eric W. Peterson
Faculty Publications - Geography, Geology, and the Environment
The Upper Mississippi Basin, which includes Illinois, has highly fertile soils and experiences intensive agricultural practices. Although fertile, the soils do not drain well, resulting in the installation of tile-drainage systems. The practices of tile systems coupled with the application of nitrogen-rich fertilizers have led to the excessive export of nitrate from the agricultural fields into surface waters, contributing to eutrophication and the development of hypoxic zones in aquatic environments. Saturated riparian buffer zones (SRBs) have been proposed as a means to reduce the amount of nitrate discharged from tile-drained waters into streams. Previous works show a reduction in the …
4. Developing Media And Information Literacy Through Dialogues About Ai, Rosa Thornley, Dory Rosenberg
4. Developing Media And Information Literacy Through Dialogues About Ai, Rosa Thornley, Dory Rosenberg
Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions
Inviting students to dialogue about Artificial Intelligence (Al) can help to develop media and information literacy. Instead of establishing restrictive policies, we present a method for instructor-facilitated dialogues to teach students to analyze, evaluate, and interact with generative language models. This recursive inquiry process causes students to critically think about the spectrum of AI capabilities and limitations. Practicing this inquiry habit over time directs students towards intuitively questioning the Al which leads them to govern their own choices when they become rhetorically aware of emerging technologies and how it will affect their own research and writing. For instructors in higher …