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Articles 2221 - 2250 of 297955

Full-Text Articles in Physical Sciences and Mathematics

Numerical Simulations For Fractional Differential Equations Of Higher Order And A Wright-Type Transformation, Mariana Nacianceno, Tamer Oraby, Hansapani Rodrigo, Y. Sepulveda, Josef A. Sifuentes, Erwin Suazo, T. Stuck, J. Williams Mar 2024

Numerical Simulations For Fractional Differential Equations Of Higher Order And A Wright-Type Transformation, Mariana Nacianceno, Tamer Oraby, Hansapani Rodrigo, Y. Sepulveda, Josef A. Sifuentes, Erwin Suazo, T. Stuck, J. Williams

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this work, a new relationship is established between the solutions of higher fractional differential equations and a Wright-type transformation. Solutions could be interpreted as expected values of functions in a random time process. As applications, we solve the fractional beam equation, fractional electric circuits with special functions as external sources, and derive d’Alembert’s formula for the fractional wave equation. Due to this relationship, we present two methods for simulating solutions of fractional differential equations. The two approaches use the interpretation of the Caputo derivative of a function as a Wright-type transformation of the higher derivative of the function. In …


Open-Inquiry Opens Doors To Intriguing Optics Experiments At Home: A Case Study, Paul R. Destefano, Ralf Widenhorn Mar 2024

Open-Inquiry Opens Doors To Intriguing Optics Experiments At Home: A Case Study, Paul R. Destefano, Ralf Widenhorn

Physics Faculty Publications and Presentations

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] This manuscript presents a case study of an introductory physics student who, during the remote learning conditions imposed during the COVID-19 pandemic, found inspiration within a new, openinquiry, project-based, laboratory curriculum designed at Portland State University. The phenomenon investigated by the study subject was intriguing to both the student and the lab instructors for its unfamiliar and instructive optical effect: a ring-shaped pattern or halo created by a laser diffusely reflected in a shallow body of water. Drawing on classwork and interview responses, this …


3F4 Hypergeometric Functions As A Sum Of A Product Of 2F3 Functions, Jack C. Straton Mar 2024

3F4 Hypergeometric Functions As A Sum Of A Product Of 2F3 Functions, Jack C. Straton

Physics Faculty Publications and Presentations

This paper shows that certain 3F4 hypergeometric functions can be expanded in sums of pair products of 2F3 functions, which reduce in special cases to 2F3 functions expanded in sums of pair products of 1F2 functions. This expands the class of hypergeometric functions having summation theorems beyond those expressible as pair-products of generalized Whittaker functions, 2F1 functions, and 3F2 functions into the realm of pFq functions where p < q for both the summand and terms in the series. In addition to its intrinsic value, this result has a specific application in calculating the response of the atoms to laser stimulation in the Strong Field Approximation.


Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan Mar 2024

Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel optimal trajectory tracking scheme is introduced for nonlinear continuous-time systems in strict feedback form with uncertain dynamics by using neural networks (NNs). The method employs an actor-critic-based NN back-stepping technique for minimizing a discounted value function along with an identifier to approximate unknown system dynamics that are expressed in augmented form. Novel online weight update laws for the actor and critic NNs are derived by using both the NN identifier and Hamilton-Jacobi-Bellman residual error. A new continual lifelong learning technique utilizing the Fisher Information Matrix via Hamilton-Jacobi-Bellman residual error is introduced to obtain the significance of weights in …


Future-Proofing The Past: Artificial Intelligence In The Restoration Of Andalusian Architectural Heritage: A Case Study Of The Alhambra Palace, Granada, Spain, Kholoud Bader Hasan Ghaith Mar 2024

Future-Proofing The Past: Artificial Intelligence In The Restoration Of Andalusian Architectural Heritage: A Case Study Of The Alhambra Palace, Granada, Spain, Kholoud Bader Hasan Ghaith

Theses

This thesis explains the contribution of artificial intelligence in heritage restoration as an icon of Andalusian architecture by using the Alhambra as an example. The task of sustaining heritage is increasing dramatically due to the accumulation of heritage assets and the need for modern and innovative operations to cope with preservation tasks. Therefore, this thesis reviews the role of artificial intelligence in improving the restoration operation to improve accuracy and efficiency. I applied the case study as a scientific methodology to explain this work to overcome scientific and subjective obstacles, such as scarce data and software integration while explaining the …


Marketing Video Games To Aging Demographics: A Generational Profile Analysis, Brinna Louise Ball Mar 2024

Marketing Video Games To Aging Demographics: A Generational Profile Analysis, Brinna Louise Ball

Theses

Marketing video games to aging demographics like Baby Boomers, Generation X, and Millennials requires a unique approach by video game studios and consumer products divisions alike. The strategies employed for younger generations such as Generation Z and Generation Alpha differ from conventional methods, requiring a fresh outlook and a need for more innovative and inventive approaches. To comprehend the current aging audience more effectively, it's essential to examine four crucial factors: accessibility, exposure, media habits, and motivations to play video games. Examining these factors by generation, we can better grasp how to effectively market video games to these demographics. It's …


Improving Automatic Transcription Using Natural Language Processing, Anna Kiefer Mar 2024

Improving Automatic Transcription Using Natural Language Processing, Anna Kiefer

Master's Theses

Digital Democracy is a CalMatters and California Polytechnic State University initia-
tive to promote transparency in state government by increasing access to the Califor-
nia legislature. While Digital Democracy is made up of many resources, one founda-
tional step of the project is obtaining accurate, timely transcripts of California Senate
and Assembly hearings. The information extracted from these transcripts provides
crucial data for subsequent steps in the pipeline. In the context of Digital Democracy,
upleveling is when humans verify, correct, and annotate the transcript results after
the legislative hearings have been automatically transcribed. The upleveling process
is done with the …


Automated Tree Mortality Detection Using Ubiquitously Available Public Data, Michael T. Huggins Mar 2024

Automated Tree Mortality Detection Using Ubiquitously Available Public Data, Michael T. Huggins

Master's Theses

Understanding the dynamic interplay between fire severity, topography, and tree mortality, is crucial for predicting future forest dynamics and enhancing resilience against climate change-induced wildfire regimes. This thesis develops a multi-sensor approach for automated estimation of tree mortality, then applies it to examine trends in tree mortality over a six-year period across a fire affected study site in the Trinity River basin in Northern California. The Random Forest model uses publicly available USGS 3D Elevation Program Lidar (3DEP) and NAIP imagery as inputs and is likely to be easily adaptable to other landscapes. The model had a Receiver Operating Characteristic …


The Effect Of Internet Firms’ Data Analytics Capability On Their Innovation Speed And Innovation Quality: A Dynamic Capability Perspective, Yeyu Hua Mar 2024

The Effect Of Internet Firms’ Data Analytics Capability On Their Innovation Speed And Innovation Quality: A Dynamic Capability Perspective, Yeyu Hua

Dissertations and Theses Collection (Open Access)

With the advent of big data era, data plays a pivotal role in sustainingfirms’ competitive advantages. Although a few studies have shown that data analytics capability contributes to firms’ innovative performance, these studies either focus on general innovative performance or specific types of innovation, such as incremental innovation, radical innovation, and supply chaininnovation. In this thesis, I enrich this stream of literature by conducting twostudies to further examine the relationship between data analytics capabilityand innovation speed as well as innovation quality. This thesis consists of twostudies. Study 1 is a survey study, in which I investigate the relationshipbetween data analytics …


Mask2former With Improved Query For Semantic Segmentation In Remote-Sensing Images, Shichen Guo, Qi Wang, Shiming Xiang, Shuwen Wang, Xuezhi Wang Mar 2024

Mask2former With Improved Query For Semantic Segmentation In Remote-Sensing Images, Shichen Guo, Qi Wang, Shiming Xiang, Shuwen Wang, Xuezhi Wang

Computer Science Faculty Publications and Presentations

Semantic segmentation of remote sensing (RS) images is vital in various practical applications, including urban construction planning, natural disaster monitoring, and land resources investigation. However, RS images are captured by airplanes or satellites at high altitudes and long distances, resulting in ground objects of the same category being scattered in various corners of the image. Moreover, objects of different sizes appear simultaneously in RS images. For example, some objects occupy a large area in urban scenes, while others only have small regions. Technically, the above two universal situations pose significant challenges to the segmentation with a high quality for RS …


A Study On Ethical Hacking In Cybersecurity Education Within The United States, Jordan Chew Mar 2024

A Study On Ethical Hacking In Cybersecurity Education Within The United States, Jordan Chew

Master's Theses

As the field of computer security continues to grow, it becomes increasingly important to educate the next generation of security professionals. However, much of the current education landscape primarily focuses on teaching defensive skills. Teaching offensive security, otherwise known as ethical hacking, is an important component in the education of all students who hope to contribute to the field of cybersecurity. Doing so requires a careful consideration of what ethical, legal, and practical issues arise from teaching students skills that can be used to cause harm. In this thesis, we first examine the current state of cybersecurity education in the …


Seasonal Variability And Predictability Of Monsoon Precipitation In Southern Africa, Matthew F. Horan, Fred Kucharski, Moetasim Ashfaq Mar 2024

Seasonal Variability And Predictability Of Monsoon Precipitation In Southern Africa, Matthew F. Horan, Fred Kucharski, Moetasim Ashfaq

Faculty Publications

Rainfed agriculture is the mainstay of economies across Southern Africa (SA), where most precipitation is received during the austral summer monsoon. This study aims to further our understanding of monsoon precipitation predictability over SA. We use three natural climate forcings, El Niño–Southern Oscillation, Indian Ocean Dipole (IOD), and the Indian Ocean Precipitation Dipole (IOPD)—the dominant precipitation variability mode—to construct an empirical model that exhibits significant skill over SA during monsoon in explaining precipitation variability and in forecasting it with a five-month lead. While most explained precipitation variance (50%–75%) comes from contemporaneous IOD and IOPD, preconditioning all three forcings is key …


Transiam: Aggregating Multi-Modal Visual Features With Locality For Medical Image Segmentation, Xuejian Li, Shiqiang Ma, Junhai Xu, Jijun Tang, Shengfeng He, Fei Guo Mar 2024

Transiam: Aggregating Multi-Modal Visual Features With Locality For Medical Image Segmentation, Xuejian Li, Shiqiang Ma, Junhai Xu, Jijun Tang, Shengfeng He, Fei Guo

Research Collection School Of Computing and Information Systems

Automatic segmentation of medical images plays an important role in the diagnosis of diseases. On single-modal data, convolutional neural networks have demonstrated satisfactory performance. However, multi-modal data encompasses a greater amount of information rather than single-modal data. Multi-modal data can be effectively used to improve the segmentation accuracy of regions of interest by analyzing both spatial and temporal information. In this study, we propose a dual-path segmentation model for multi-modal medical images, named TranSiam. Taking into account that there is a significant diversity between the different modalities, TranSiam employs two parallel CNNs to extract the features which are specific to …


Non-Monotonic Generation Of Knowledge Paths For Context Understanding, Pei-Chi Lo, Ee-Peng Lim Mar 2024

Non-Monotonic Generation Of Knowledge Paths For Context Understanding, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Knowledge graphs can be used to enhance text search and access by augmenting textual content with relevant background knowledge. While many large knowledge graphs are available, using them to make semantic connections between entities mentioned in the textual content remains to be a difficult task. In this work, we therefore introduce contextual path generation (CPG) which refers to the task of generating knowledge paths, contextual path, to explain the semantic connections between entities mentioned in textual documents with given knowledge graph. To perform CPG task well, one has to address its three challenges, namely path relevance, incomplete knowledge graph, and …


Ditmos: Delving Into Diverse Tiny-Model Selection On Microcontrollers, Xiao Ma, Shengfeng He, Hezhe Qiao, Dong Ma Mar 2024

Ditmos: Delving Into Diverse Tiny-Model Selection On Microcontrollers, Xiao Ma, Shengfeng He, Hezhe Qiao, Dong Ma

Research Collection School Of Computing and Information Systems

Enabling efficient and accurate deep neural network (DNN) inference on microcontrollers is non-trivial due to the constrained on-chip resources. Current methodologies primarily focus on compressing larger models yet at the expense of model accuracy. In this paper, we rethink the problem from the inverse perspective by constructing small/weak models directly and improving their accuracy. Thus, we introduce DiTMoS, a novel DNN training and inference framework with a selectorclassifiers architecture, where the selector routes each input sample to the appropriate classifier for classification. DiTMoS is grounded on a key insight: a composition of weak models can exhibit high diversity and the …


Harnessing The Advances Of Meda To Optimize Multi-Puf For Enhancing Ip Security Of Biochips, Chen Dong, Xiaodong Guo, Sihuang Lian, Yinan Yao, Zhenyi Chen, Yang Yang, Zhanghui Liu Mar 2024

Harnessing The Advances Of Meda To Optimize Multi-Puf For Enhancing Ip Security Of Biochips, Chen Dong, Xiaodong Guo, Sihuang Lian, Yinan Yao, Zhenyi Chen, Yang Yang, Zhanghui Liu

Research Collection School Of Computing and Information Systems

Digital microfluidic biochips (DMFBs) have a significant stride in the applications of medicine and the biochemistry in recent years. DMFBs based on micro-electrode-dot-array (MEDA) architecture, as the next-generation DMFBs, aim to overcome drawbacks of conventional DMFBs, such as droplet size restriction, low accuracy, and poor sensing ability. Since the potential market value of MEDA biochips is vast, it is of paramount importance to explore approaches to protect the intellectual property (IP) of MEDA biochips during the development process. In this paper, an IP authentication strategy based on the multi-PUF applied to MEDA biochips is presented, called bioMPUF, consisting of Delay …


Knowledge Generation For Zero-Shot Knowledge-Based Vqa, Rui Cao, Jing Jiang Mar 2024

Knowledge Generation For Zero-Shot Knowledge-Based Vqa, Rui Cao, Jing Jiang

Research Collection School Of Computing and Information Systems

Previous solutions to knowledge-based visual question answering (K-VQA) retrieve knowledge from external knowledge bases and use supervised learning to train the K-VQA model. Recently pre-trained LLMs have been used as both a knowledge source and a zero-shot QA model for K-VQA and demonstrated promising results. However, these recent methods do not explicitly show the knowledge needed to answer the questions and thus lack interpretability. Inspired by recent work on knowledge generation from LLMs for text-based QA, in this work we propose and test a similar knowledge-generation-based K-VQA method, which first generates knowledge from an LLM and then incorporates the generated …


Monocular Bev Perception Of Road Scenes Via Front-To-Top View Projection, Wenxi Liu, Qi Li, Weixiang Yang, Jiaxin Cai, Yuanhong Yu, Yuexin Ma, Shengfeng He, Jia Pan Mar 2024

Monocular Bev Perception Of Road Scenes Via Front-To-Top View Projection, Wenxi Liu, Qi Li, Weixiang Yang, Jiaxin Cai, Yuanhong Yu, Yuexin Ma, Shengfeng He, Jia Pan

Research Collection School Of Computing and Information Systems

HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need to perform road segmentation and view transformation separately, which often causes distortion and missing content. To push the limits of the technology, we present a novel framework that reconstructs a local map formed by road layout and vehicle occupancy in the bird's-eye view given a front-view monocular image only. We propose a front-to-top view projection (FTVP) module, which takes the constraint of cycle consistency between views into account and makes full use of their correlation to strengthen …


Strongly Magnetized Accretion In Two Ultracompact Binary Systems, Thomas J. Maccarone, Thomas Kupfer, Edgar Najera Casarrubias, Liliana E. Rivera Sandoval, Aarran W. Shaw, Christoper T. Britt, Jan Van Roestel, David R. Zurek Mar 2024

Strongly Magnetized Accretion In Two Ultracompact Binary Systems, Thomas J. Maccarone, Thomas Kupfer, Edgar Najera Casarrubias, Liliana E. Rivera Sandoval, Aarran W. Shaw, Christoper T. Britt, Jan Van Roestel, David R. Zurek

Physics and Astronomy Faculty Publications and Presentations

We present the discoveries of two of AM CVn systems, Gaia14aae and SDSS J080449.49+161624.8, which show X-ray pulsations at their orbital periods, indicative of magnetically collimated accretion. Both also show indications of higher rates of mass transfer relative to the expectations from binary evolution driven purely by gravitational radiation, based on existing optical data for Gaia14aae, which show a hotter white dwarf temperature than expected from standard evolutionary models, and X-ray data for SDSS J080449.49+161624.8 which show a luminosity 10−100 times higher than those for other AM CVn at similar orbital periods. The higher mass transfer rates could be driven …


Math Word Problem Generation Via Disentangled Memory Retrieval, Wei Qin, Xiaowei Wang, Zhenzhen Hu, Lei Wang, Yunshi Lan, Richang Hong Mar 2024

Math Word Problem Generation Via Disentangled Memory Retrieval, Wei Qin, Xiaowei Wang, Zhenzhen Hu, Lei Wang, Yunshi Lan, Richang Hong

Research Collection Lee Kong Chian School Of Business

The task of math word problem (MWP) generation, which generates an MWP given an equation and relevant topic words, has increasingly attracted researchers’ attention. In this work, we introduce a simple memory retrieval module to search related training MWPs, which are used to augment the generation. To retrieve more relevant training data, we also propose a disentangled memory retrieval module based on the simple memory retrieval module. To this end, we first disentangle the training MWPs into logical description and scenario description and then record them in respective memory modules. Later, we use the given equation and topic words as …


Artificial Intelligence And/Or Machine Learning (Ai &| Ml), George K. Thiruvathukal Mar 2024

Artificial Intelligence And/Or Machine Learning (Ai &| Ml), George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

These slides are from an invited panel presentation at my home institution, Loyola University Chicago, organized by the Loyola University Chicago Retiree Association (LUCRA). I was asked to give a broad historical overview of AI and ML and speak about its societal impacts.

"The Loyola University Chicago Retiree Association embraces the Vision of Loyola University Chicago and will assist students, faculty, and administrators as they strive to serve humanity. The group values freedom of inquiry, the pursuit of truth, and care of others and embraces a commitment to excellence, service that promotes social justice, values based leadership, and global awareness."


Ionization Cross Sections Of Hydrogen Molecule By Electron And Positron Impact, Károly Tőkési, Robert D. Dubois Mar 2024

Ionization Cross Sections Of Hydrogen Molecule By Electron And Positron Impact, Károly Tőkési, Robert D. Dubois

Physics Faculty Research & Creative Works

We Present Ionization Cross Sections of Hydrogen Molecules by Electron and Positron Impact for Impact Energies between 20 and 1000 EV. a Three-Body Classical Trajectory Monte Carlo Approximation is Applied to Mimic the Collision System. in This Approach, the H2 Molecule is Modeled by a Hydrogen-Type Atom with One Active Electron Bound to a Central Core of Effective Charge with an Effective Binding Energy. Although This Model is Crude for Describing a Hydrogen Molecule, We Found that the Total Cross Sections for Positron Impact Agree Reasonably Well with the Experimental Data. for the Electron Impact, Our Calculated Cross Sections Are …


Universality Class Of A Spinor Bose–Einstein Condensate Far From Equilibrium, Seung Jung Huh, Koushik Mukherjee, Kiryang Kwon, Jihoon Seo, Junhyeok Hur, Simeon I. Mistakidis, H. R. Sadeghpour, Jae Yoon Choi Mar 2024

Universality Class Of A Spinor Bose–Einstein Condensate Far From Equilibrium, Seung Jung Huh, Koushik Mukherjee, Kiryang Kwon, Jihoon Seo, Junhyeok Hur, Simeon I. Mistakidis, H. R. Sadeghpour, Jae Yoon Choi

Physics Faculty Research & Creative Works

Scale Invariance And Self-Similarity In Physics Provide A Unified Framework For Classifying Phases Of Matter And Dynamical Properties Near Equilibrium In Both Classical And Quantum Systems. This Paradigm Has Been Further Extended To Isolated Many-Body Quantum Systems Driven Far From Equilibrium, For Which The Physical Observables Exhibit Dynamical Scaling With Universal Scaling Exponents. Universal Dynamics Appear In A Wide Range Of Scenarios, Including Cosmology, Quark–gluon Matter, Ultracold Atoms And Quantum Spin Magnets. However, How The Universal Dynamics Depend On The Symmetry Of The Underlying Hamiltonian In Non-Equilibrium Systems Remains An Outstanding Challenge. Here We Report On The Classification Of Universal …


Singular Cr Structures Of Constant Webster Curvature And Applications, Chiara Guidi, Ali Maalaoui, Vittorio Martino Mar 2024

Singular Cr Structures Of Constant Webster Curvature And Applications, Chiara Guidi, Ali Maalaoui, Vittorio Martino

Mathematics

We consider the sphere (Formula presented.) equipped with its standard contact form. In this paper, we construct explicit contact forms on (Formula presented.), which are conformal to the standard one and whose related Webster metrics have constant Webster curvature; in particular, it is positive if (Formula presented.). As main applications, we provide two perturbative results. In the first one, we prove the existence of infinitely many contact forms on (Formula presented.) conformal to the standard one and having constant Webster curvature, where (Formula presented.) is a small perturbation of (Formula presented.). In the second application, we show that there exist …


A Social-Aware Gaussian Pre-Trained Model For Effective Cold-Start Recommendation, Siwei Liu, Xi Wang, Craig Macdonald, Iadh Ounis Mar 2024

A Social-Aware Gaussian Pre-Trained Model For Effective Cold-Start Recommendation, Siwei Liu, Xi Wang, Craig Macdonald, Iadh Ounis

Machine Learning Faculty Publications

The use of pre-training is an emerging technique to enhance a neural model's performance, which has been shown to be effective for many neural language models such as BERT. This technique has also been used to enhance the performance of recommender systems. In such recommender systems, pre-training models are used to learn a better initialisation for both users and items. However, recent existing pre-trained recommender systems tend to only incorporate the user interaction data at the pre-training stage, making it difficult to deliver good recommendations, especially when the interaction data is sparse. To alleviate this rcommon data sparsity issue, we …


Using Flipped Classroom Modules To Facilitate Higher Order Learning In Undergraduate Organic Chemistry, Lauren R. Holloway, Tabitha Miller, Bryce Da Camara, Paul M. Bogie, Briana L. Hickey, Jack Barbera, Angie L. Lopez, Multiple Additional Authors Mar 2024

Using Flipped Classroom Modules To Facilitate Higher Order Learning In Undergraduate Organic Chemistry, Lauren R. Holloway, Tabitha Miller, Bryce Da Camara, Paul M. Bogie, Briana L. Hickey, Jack Barbera, Angie L. Lopez, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

In an ongoing effort to incorporate active learning and promote higher order learning outcomes in undergraduate organic chemistry, a hybrid (“flipped”) classroom structure has been used to facilitate a series of collaborative activities in the first two courses of the lower division organic chemistry sequence. An observational study of seven classes over a five-year period reveals there is a strong correlation between performance on the in-class activities and performance on the final exam across all classes; however, a significant number of students in these courses continue to struggle on both the in-class activities and final exam. The Activity Engagement Survey …


Dna-Based Assay For Calorimetric Determination Of Protein Concentrations In Pure Or Mixed Solutions, Matthew W. Eskew, Patrick Reardon, Albert S. Benight Mar 2024

Dna-Based Assay For Calorimetric Determination Of Protein Concentrations In Pure Or Mixed Solutions, Matthew W. Eskew, Patrick Reardon, Albert S. Benight

Chemistry Faculty Publications and Presentations

It was recently reported that values of the transition heat capacities, as measured by differential scanning calorimetry, for two globular proteins and a short DNA hairpin in NaCl buffer are essentially equivalent, at equal concentrations (mg/mL). To validate the broad applicability of this phenomenon, additional evidence for this equivalence is presented that reveals it does not depend on DNA sequence, buffer salt, or transition temperature (Tm). Based on the equivalence of transition heat capacities, a calorimetric method was devised to determine protein concentrations in pure and complex solutions. The scheme uses direct comparisons between the thermodynamic stability of a short …


Considering The Impact Framework To Understand The Ai-Well-Being-Complex From An Interdisciplinary Perspective, Christian Montag, Preslav Nakov, Raian Ali Mar 2024

Considering The Impact Framework To Understand The Ai-Well-Being-Complex From An Interdisciplinary Perspective, Christian Montag, Preslav Nakov, Raian Ali

Natural Language Processing Faculty Publications

Artificial intelligence (AI) is built into many products and has the potential to dramatically impact societies around the world. This short theoretical paper aims to provide a simple framework that might help us understand how the introduction and/or use of products with AI might influence the well-being of humans. It is proposed that considering the dynamic Interplay between variables stemming from Modality, Person, Area, Culture and Transparency categories will help to understand the influence of AI on well-being. The Modality category encompasses areas such as the degree of AI being interactive, informational versus actualizing, or autonomous. The Person variable contains …


Medical Image Super-Resolution For Smart Healthcare Applications: A Comprehensive Survey, Sabina Umirzakova, Shabir Ahmad, Latif U. Khan, Taegkeun Whangbo Mar 2024

Medical Image Super-Resolution For Smart Healthcare Applications: A Comprehensive Survey, Sabina Umirzakova, Shabir Ahmad, Latif U. Khan, Taegkeun Whangbo

Machine Learning Faculty Publications

The digital transformation in healthcare, propelled by the integration of deep learning models and the Internet of Things (IoT), is creating unprecedented opportunities for improving patient care. However, the utilization of low-resolution images, often generated by IoT devices, introduces biases in the deep learning models, thereby affecting the overall clinical decision-making process. While super-resolution techniques have been extensively employed to transform low-resolution images into high-resolution counterparts, the challenge of achieving highly accurate image restoration remains unresolved. This is especially critical in the medical imaging domain, where even minor inaccuracies can lead to significant biases in model training and, consequently, impact …


Synthesis And Crystal Structures Of Bis[1-Oxopyridin-2-Olato(1−)]Bis(Pentafluorophenyl)Silicon(Iv)–Tetrahydrofuran–Pentane (2/1/1), Bis[1-Oxopyridin-2-Olato(1−)]Bis(P-Tolyl)Silicon(Iv), And Dimesitylbis[1-Oxopyridin-2-Olato(1−)]Silicon(Iv), Bradley M. Kraft, William W. Brennessel, Jordan W. Andrews, Michael T. Viggiani, Nathan F. Kittrell, Matthew T. Heckman Mar 2024

Synthesis And Crystal Structures Of Bis[1-Oxopyridin-2-Olato(1−)]Bis(Pentafluorophenyl)Silicon(Iv)–Tetrahydrofuran–Pentane (2/1/1), Bis[1-Oxopyridin-2-Olato(1−)]Bis(P-Tolyl)Silicon(Iv), And Dimesitylbis[1-Oxopyridin-2-Olato(1−)]Silicon(Iv), Bradley M. Kraft, William W. Brennessel, Jordan W. Andrews, Michael T. Viggiani, Nathan F. Kittrell, Matthew T. Heckman

Chemistry Faculty/Staff Publications

The neutral organosilicon(IV) complex, (C6F5)2Si(OPO)2 (OPO = 1-oxopyridin-2-one, C5H4NO2), was synthesized from (C6F5)2Si(OCH3)2 and 2 equiv. of 1-hy­droxy­pyridin-2-one in tetra­hydro­furan (THF). Single crystals grown from the diffusion of n-pentane into a THF solution were identified as a THF hemisolvate and an n-pentane hemisolvate, (C6F5)2Si(OPO)2·0.5THF·0.5C5H12 (1). p-Tol­yl2Si(OPO)2 (2) and mesit­yl2Si(OPO)2 (3) crystallized directly from reaction mixtures of 2 equiv. of Me3Si(OPO) with p-tol­yl2SiCl2 and mesit­yl2SiCl2, respectively, in aceto­nitrile. The oxygen-bonded carbon and nitro­gen atoms of the OPO ligands in 1, 2, and 3 were modeled as disordered indicating co-crystallization …