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Muhlenberg Magic, Lehigh Valley Health Network

LVHN documents

No abstract provided.

Camelira: An Arabic Multi-Dialect Morphological Disambiguator, Ossama Obeid, Go Inoue, Nizar Habash

Computer Vision Faculty Publications

We present Camelira, a web-based Arabic multi-dialect morphological disambiguation tool that covers four major variants of Arabic: Modern Standard Arabic, Egyptian, Gulf, and Levantine. Camelira offers a user-friendly web interface that allows researchers and language learners to explore various linguistic information, such as part-of-speech, morphological features, and lemmas. Our system also provides an option to automatically choose an appropriate dialect-specific disambiguator based on the prediction of a dialect identification component. Camelira is publicly accessible at http://camelira.camel-lab.com.

Professional Development Newsletter, December 2022, Odu Career Pathways Program, Old Dominion University

Career Pathways

December 2022 issue of ODU Career Pathways Professional Development Newsletter.

Facilitating Role Understanding And Collaboration Between Aspiring School Counselors And Principals, Shelby K. Gonzales, Dodie Limberg, Kathleen M. W. Cunningham

Counselor Education Faculty Publications and Presentations

Using a convergent mixed-methods design, we investigated role understanding and collaboration between school counselors and principals. Specifically, this study situated aspiring school counselors and principals in a curriculum intervention on the role of their counterpart and then brought the two professions together in a collaborative powerful learning experience. The results of our pilot study demonstrate that both school counselor and educational leadership graduate students benefit from and value a presentation on roles of their opposite counterpart and the opportunity to practice collaboration in their graduate preparation programs.

State Digital Services Taxes: A Good And Permissible Idea (Despite What You Might Have Heard), Young Ran (Christine) Kim, Darien Shanske

Notre Dame Law Review

Tax systems have been struggling to adapt to the digitalization of the economy. At the center of the struggles is taxing digital platforms, such as Google or Facebook. These immensely profitable firms have a business model that gives away “free” services, such as searching the web. The service is not really free; it is paid for by having the users watch ads and tender data. Traditional tax systems are not designed to tax such barter transactions, leaving a gap in taxation.

One response, pioneered in Europe, has been the creation of a wholly new tax to target digital platforms: the …

Pasta: Table-Operations Aware Fact Verification Via Sentence-Table Cloze Pre-Training, Zihui Gu, Ju Fan, Nan Tang, Preslav Nakov, Xiaoman Zhao, Xiaoyong Du

Natural Language Processing Faculty Publications

Fact verification has attracted a lot of research attention recently, e.g., in journalism, marketing, and policymaking, as misinformation and disinformation online can sway one's opinion and affect one's actions. While fact-checking is a hard task in general, in many cases, false statements can be easily debunked based on analytics over tables with reliable information. Hence, table-based fact verification has recently emerged as an important and growing research area. Yet, progress has been limited due to the lack of datasets that can be used to pre-train language models (LMs) to be aware of common table operations, such as aggregating a column …

Greener: Graph Neural Networks For News Media Profiling, Panayot Panayotov, Utsav Shukla, Husrev T. Sencar, Mohamed Nabeel, Preslav Nakov

Natural Language Processing Faculty Publications

We study the problem of profiling news media on the Web with respect to their factuality of reporting and bias. This is an important but under-studied problem related to disinformation and “fake news” detection, but it addresses the issue at a coarser granularity compared to looking at an individual article or an individual claim. This is useful as it allows to profile entire media outlets in advance. Unlike previous work, which has focused primarily on text (e.g., on the articles published by the target website, or on the textual description in their social media profiles or in Wikipedia), here we …

Interview With Maria Andrade, Daniel Lane

Immigrant Leaders

An interview with Maria Andrade, an immigrant leader from Latino Action Network. The interview covers life before immigrating, arrival and integration, and political participation.

Asdot: Any-Shot Data-To-Text Generation With Pretrained Language Models, Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu

Machine Learning Faculty Publications

Data-to-text generation is challenging due to the great variety of the input data in terms of domains (e.g., finance vs sports) or schemata (e.g., diverse predicates). Recent end-to-end neural methods thus require substantial training examples to learn to disambiguate and describe the data. Yet, real-world data-to-text problems often suffer from various data-scarce issues: one may have access to only a handful of or no training examples, and/or have to rely on examples in a different domain or schema. To fill this gap, we propose Any-Shot Data-to-Text (ASDOT), a new approach flexibly applicable to diverse settings by making efficient use of …

Hand In Hand, Winter, 2022

Hand in Hand

A newsletter published for Deaf Catholics in Milwaukee, WI

Hand in Hand Finding Aid

Understanding And Improving The Activity Of Oxygen Evolution Reaction Catalysts In Alkaline And Chloride-Containing Electrolytes, Prajwal Adiga

Link Foundation Energy Fellowship Reports

Hydrogen is a feedstock in many chemical processes and can also be used as an energy carrier to store, move, and deliver energy produced from other sources. Recently, hydrogen is of interest for storing renewable electricity and helping address the intermittent nature of electricity generation from renewable sources.1 Water electrolysis plays a pivotal role in achieving a green hydrogen economy by sourcing electricity from intermittent renewable sources. However, the efficiency of the electrolysis process is limited by the sluggish oxygen evolution reaction (OER) kinetics,2-5 whereas the kinetics of the hydrogen evolution reaction (HER) are more facile. My work focused on …

Electric Reliability, Distributed Energy Resources (Ders), And Opportunities For Customer-Sited Solar And Storage In Modern Electric Systems, Will Gorman

Link Foundation Energy Fellowship Reports

At the turn of the 21st century, the electricity system started to transform. Regulators opened up electric generation to competition and renewable electricity, particularly wind and solar, entered a period of rapid cost decline (Borenstein and Bushnell, 2015). At the same time the popularity of distributed, rather than centralized, supply of electricity grew, giving end consumers new options to meet their electricity demand locally. The dramatic cost decline of solar technologies made it more economic to install solar generators at individual households (Barbose et al., 2021a), and technological development of battery storage has led to even more options for the …

Zero-Defect Manufacturing Utilizing Autonomation In Aerospace, Quinton L. Marks, Abeni El-Amin Ph.D.

Management Faculty Publications

Multifunctional manufacturing processes are comprised of zero-defect manufacturing (ZDM), which is inherently a complex process because of the simultaneous operations needed to accomplish zero defects. The application of the ZDM philosophy, together with autonomation, presents significant challenges and opportunities for the implementation of new processes that contribute to innovative manufacturing production processes. An emphasis must be on developing fully integrated, operative solutions, employing many quality systems, digitization, data analytics, and industry standards such as AS9100, ISO 9001, and Advanced Product Quality Planning.

Novel Techniques For Quantifying Secondhand Smoke Diffusion Into Children's Bedroom, Sunil Ramchandani

Computational and Data Sciences (PhD) Dissertations

The impact of secondhand smoking to health of general population, and specifically children, is a well-known phenomenon that researchers have studied for years. In this dissertation, I extend work done within a secondhand smoke intervention to understand and quantity the impact of intervention on flow of smoke air particle concentration from the main room where smoking generates air particle contamination to a room where a child living in the home sleeps. The paper also explores potential modelling techniques to proactively identify and the impact of the smoke air particles with the intent to discourage adults from smoking in the home …

Ethical And Moral Imperatives Of 2022, Sheila P. Davis Phd

Journal of Health Ethics

Editor's introduction to the Journal of Health Ethics vol. 18, no. 2

(R1953) M-Regression Estimation With The K Nearest Neighbors Smoothing Under Quasi-Associated Data In Functional Statistics, Bellatrach Nadjet, Bouabsa Wahiba, Attouch Mohammed Kadi, Fetitah Omar

Applications and Applied Mathematics: An International Journal (AAM)

The main goal of this paper is to study the non parametric M-estimation under quasi-associated sequence with the k Nearest Neighbor’s method shortly (kNN). We construct an estimator of this nonparametric function and we study its asymptotic properties. Furthermore, a comparison study based on simulated data is also provided to illustrate the highly sensitive of the kNN approach to the presence of even a small proportion of outliers in the data.

December 2022: Region 10 Emerging Special Pathogen Treatment Center (Resptc) At Providence Sacred Heart Medical Center & Children’S Hospital, Providence - Special Pathogens Program

Special Pathogens Newsletters

REGION 10 SPECIAL PATHOGENS NEWSLETTER

Minutes, December 2022, University Of Dayton. College Of Arts And Sciences

Documents of the College of Arts and Sciences Academic Affairs Committee

Minutes from organizational meeting for Academic Affairs Committee

Direction, Not Detail: Progress Towards Consensus At The Fourth Intergovernmental Conference On Biodiversity Beyond National Jurisdiction, Elizabeth Mendenhall, Elizabeth De Santo, Mathias Jankila, Elizabeth Nyman, Rachel Tiller

Marine Affairs Faculty Publications

After a two year delay caused by the COVID-19 pandemic, the fourth intergovernmental conference (IGC-4) in the negotiations for a new UN treaty to address the conservation and sustainable management of biodiversity beyond national jurisdiction (BBNJ) took place in March 2022. This meeting differed substantially from previous IGCs in terms of process, with much of the discussions occurring in ‘informal informals,’ or off-the-record meetings open only to delegates and registered observers. Additionally, in-person participation was extremely limited and observers only had access to web broadcasts, i.e., no in-person interactions with delegates. A draft text of the treaty was circulated in …

How To Present Your Research Professionally And With Confidence, Mary Garofalo

General Research

Now that your research has been accepted and you have prepared your presentation, it’s time to start practicing. Public speaking is often a very daunting task. Even seasoned professionals have anxiety around speaking to a room full of people. This fear can be compounded by first-time jitters, imposter syndrome, or other invasive thoughts. Breathe. Everyone has been in your shoes. In the meantime, here are some strategies to cut down your anxiety, boost your confidence, and help you communicate your brilliant research in the most clear and articulate manner.

Abundance And Territory Location Data Of Forest Songbirds To Determine Effects Of Pipeline Collocation As A Mitigation Strategy, Lillie Langlois

All Data Sets

These data were collected for the purpose of determining potential ecological costs associated with a mitigation strategy used in shale gas development in the Appalachian basin. Collocation is the practice of siting new shale gas pipelines adjacent to existing surface disturbance such as forest roads to reduce habitat fragmentation and loss of core forest. These data result from spot mapping for species of songbird at paired forest road and shale gas corridors (expanded access roads collocated with pipelines) between May and July 2013 in north-central Pennsylvania, USA. The data file contains nine sheets that report data from different pieces of …

Interview With Wendy Keller, Utah State University Special Collections & Archives

Utah State University COVID-19 Oral History Collection

No abstract provided.

A Case Of Transverse Myelitis Secondary To Covid-19 Infection, Rahul Borra, Neal T. Patel, Raheel Shaikh, Mayur S. Parmar, Sujatha Borra

HPD Articles

Infection with COVID-19 (SARS-CoV-2) is associated with a variety of generalized and specific symptoms, including neurological complications of both the peripheral and central nervous systems. In this case report, we present the case of a previously healthy 55-year-old woman who was diagnosed with transverse myelitis following a previous infection with COVID-19. MRI showed progressive demyelination of the cervical and thoracic spinal cord, and cerebrospinal fluid (CSF) showed increased levels of protein and red blood cells and no markers of infection, including negative polymerase chain reaction (PCR) for COVID-19 antibodies. The patient was treated with a course of methylprednisolone, multiple treatments …

Impact Of Digital Twins And Metaverse On Cities: History, Current Situation, And Application Perspectives, Zhihan Lv, Wen Long Shang, Mohsen Guizani

Machine Learning Faculty Publications

To promote the expansion and adoption of Digital Twins (DTs) in Smart Cities (SCs), a detailed review of the impact of DTs and digitalization on cities is made to assess the progression of cities and standardization of their management mode. Combined with the technical elements of DTs, the coupling effect of DTs technology and urban construction and the internal logic of DTs technology embedded in urban construction are discussed. Relevant literature covering the full range of DTs technologies and their applications is collected, evaluated, and collated, relevant studies are concatenated, and relevant accepted conclusions are summarized by modules. First, the …

Resel: N-Ary Relation Extraction From Scientific Text And Tables By Learning To Retrieve And Select, Yuchen Zhuang, Yinghao Li, Jerry Junyang Cheung, Yue Yu, Yingjun Mou, Xiang Chen, Le Song, Chao Zhang

Machine Learning Faculty Publications

We study the problem of extracting N-ary relation tuples from scientific articles. This task is challenging because the target knowledge tuples can reside in multiple parts and modalities of the document. Our proposed method RESEL decomposes this task into a two-stage procedure that first retrieves the most relevant paragraph/table and then selects the target entity from the retrieved component. For the high-level retrieval stage, RESEL designs a simple and effective feature set, which captures multilevel lexical and semantic similarities between the query and components. For the low-level selection stage, RESEL designs a cross-modal entity correlation graph along with a multi-view …

Efficient (Soft) Q-Learning For Text Generation With Limited Good Data, Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu

Machine Learning Faculty Publications

Maximum likelihood estimation (MLE) is the predominant algorithm for training text generation models. This paradigm relies on direct supervision examples, which is not applicable to many emerging applications, such as generating adversarial attacks or generating prompts to control language models. Reinforcement learning (RL) on the other hand offers a more flexible solution by allowing users to plug in arbitrary task metrics as reward. Yet previous RL algorithms for text generation, such as policy gradient (on-policy RL) and Q-learning (off-policy RL), are often notoriously inefficient or unstable to train due to the large sequence space and the sparse reward received only …

Amp: Automatically Finding Model Parallel Strategies With Heterogeneity Awareness, Dacheng Li, Hongyi Wang, Eric Xing, Hao Zhang

Machine Learning Faculty Publications

Scaling up model sizes can lead to fundamentally new capabilities in many machine learning (ML) tasks. However, training big models requires strong distributed system expertise to carefully design model-parallel execution strategies that suit the model architectures and cluster setups. In this paper, we develop AMP, a framework that automatically derives such strategies. AMP identifies a valid space of model parallelism strategies and efficiently searches the space for high-performed strategies, by leveraging a cost model designed to capture the heterogeneity of the model and cluster specifications. Unlike existing methods, AMP is specifically tailored to support complex models composed of uneven layers …

Unpaired Image-To-Image Translation With Density Changing Regularization, Shaoan Xie, Qirong Ho, Kun Zhang

Machine Learning Faculty Publications

Unpaired image-to-image translation aims to translate an input image to another domain such that the output image looks like an image from another domain while important semantic information are preserved. Inferring the optimal mapping with unpaired data is impossible without making any assumptions. In this paper, we make a density changing assumption where image patches of high probability density should be mapped to patches of high probability density in another domain. Then we propose an efficient way to enforce this assumption: we train the flows as density estimators and penalize the variance of density changes. Despite its simplicity, our method …

On Pac Learning Halfspaces In Non-Interactive Local Privacy Model With Public Unlabeled Data, Jinyan Su, Jinhui Xu, Di Wang

Machine Learning Faculty Publications

In this paper, we study the problem of PAC learning halfspaces in the non-interactive local differential privacy model (NLDP). To breach the barrier of exponential sample complexity, previous results studied a relaxed setting where the server has access to some additional public but unlabeled data. We continue in this direction. Specifically, we consider the problem under the standard setting instead of the large margin setting studied before. Under different mild assumptions on the underlying data distribution, we propose two approaches that are based on the Massart noise model and self-supervised learning and show that it is possible to achieve sample …

Help Or Hindrance: How Social Media Affects The Selection And Hiring Processes Of Businesses, Alexandra Krska

Management Undergraduate Honors Theses

Continually, young people have been advised to be conscientious of the imagery they put on social media regarding their personal lives in preparation for employment selection. However, the use of social media in the selection process may cause Human Resource professionals to have inadvertent biases toward candidates among other moral and ethical issues. Through extensive research of the thoughts and actions of a plethora of different corporate professionals, I will analyze whether using social media as a tool in the selection process authentically produces positive unbiased results, or whether social media poses more ethical issues. With the hopes to create …