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Articles 31 - 60 of 225044

Full-Text Articles in Physical Sciences and Mathematics

Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng Xia, Reshika P. Velumani, Yong Wang, Huamin Qu, Xiaojuan Ma Oct 2021

Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng Xia, Reshika P. Velumani, Yong Wang, Huamin Qu, Xiaojuan Ma

Research Collection School Of Computing and Information Systems

With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultivate their problem-solving skills. To guarantee the high quality of such learning materials, question designers need to inspect how students’ problem-solving processes unfold step by step to infer whether students’ problem-solving logic matches their design intent. They also need to compare the behaviors of different groups (e.g., students from different grades) to distribute questions to students with the right level of knowledge. The availability of fine-grained interaction data, such as mouse movement trajectories ...


Tradao: A Visual Analytics System For Trading Algorithm Optimization, Ka Wing Tsang, Haotian Li, Fuk Ming Lam, Yifan Mu, Yong Wang, Huamin Qu Oct 2021

Tradao: A Visual Analytics System For Trading Algorithm Optimization, Ka Wing Tsang, Haotian Li, Fuk Ming Lam, Yifan Mu, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

With the wide applications of algorithmic trading, it has become critical for traders to build a winning trading algorithm to beat the market. However, due to the lack of efficient tools, traders mainly rely on their memory to manually compare the algorithm instances of a trading algorithm and further select the best trading algorithm instance for the real trading deployment. We work closely with industry practitioners to discover and consolidate user requirements and develop an interactive visual analytics system for trading algorithm optimization. Structured expert interviews are conducted to evaluateTradAOand a representative case study is documented for illustrating the system ...


Visual Analysis Of Discrimination In Machine Learning, Qianwen Wang, Zhenghua Xu, Zhutian Chen, Yong Wang, Yong Wang, Huamin Qu Oct 2021

Visual Analysis Of Discrimination In Machine Learning, Qianwen Wang, Zhenghua Xu, Zhutian Chen, Yong Wang, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set ...


Stay Calm And Focus On The Learning Outcomes: Tools For Taking Biophysical Chemistry Online, Maria Ballester, Brian L. Van Hoozen Jr., Arthur Sikora Aug 2021

Stay Calm And Focus On The Learning Outcomes: Tools For Taking Biophysical Chemistry Online, Maria Ballester, Brian L. Van Hoozen Jr., Arthur Sikora

Chemistry and Physics Faculty Articles

Course specific learning outcomes are an important tool to define the scope of a course and can be very helpful when designing experiments and assessments. With slight modification, these learning outcomes can serve as a guide when transitioning to the distance learning format especially in courses with a traditional lab. Here we present such an example for the biophysical chemistry course.


Splash: Learnable Activation Functions For Improving Accuracy And Adversarial Robustness, Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi Aug 2021

Splash: Learnable Activation Functions For Improving Accuracy And Adversarial Robustness, Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi

Publications

We introduce SPLASH units, a class of learnable activation functions shown to simultaneously improve the accuracy of deep neural networks while also improving their robustness to adversarial attacks. SPLASH units have both a simple parameterization and maintain the ability to approximate a wide range of non-linear functions. SPLASH units are: (1) continuous; (2) grounded (f(0)=0"); (3) use symmetric hinges; and (4) their hinges are placed at fixed locations which are derived from the data (i.e. no learning required). Compared to nine other learned and fixed activation functions, including ReLU and its variants, SPLASH units show superior performance ...


The Food Truck Problem, Supply Chains And Extensions Of The Newsvendor Problem, Dennis Quayesam Aug 2021

The Food Truck Problem, Supply Chains And Extensions Of The Newsvendor Problem, Dennis Quayesam

Electronic Theses and Dissertations

Inventory control is important to ensuring sufficient quantities of items are available tomeet demands of customers. The Newsvendor problem is a model used in Operations Research to determine optimal inventory levels for fulfilling future demands. Our study extends the newsvendor problem to a food truck problem. We used simulation to show that the food truck does not reduce to a newsvendor problem if demand depends on exogenous factors such temperature, time etc. We formulate the food truck problem as a multi-product multi-period linear program and found the dual for a single item. We use Discrete Event Simulation to solve the ...


Logbert: Log Anomaly Detection Via Bert, Haixuan Guo Aug 2021

Logbert: Log Anomaly Detection Via Bert, Haixuan Guo

All Graduate Theses and Dissertations

When systems break down, administrators usually check the produced logs to diagnose the failures. Nowadays, systems grow larger and more complicated. It is labor-intensive to manually detect abnormal behaviors in logs. Therefore, it is necessary to develop an automated anomaly detection on system logs. Automated anomaly detection not only identifies malicious patterns promptly but also requires no prior domain knowledge. Many existing log anomaly detection approaches apply natural language models such as Recurrent Neural Network (RNN) to log analysis since both are based on sequential data. The proposed model, LogBERT, a BERT-based neural network, can capture the contextual information in ...


A Bert-Based Two-Stage Model For Chinese Chengyu Recommendation, Minghuan Tan, Jing Jiang, Bingtian Dai Aug 2021

A Bert-Based Two-Stage Model For Chinese Chengyu Recommendation, Minghuan Tan, Jing Jiang, Bingtian Dai

Research Collection School Of Computing and Information Systems

In Chinese, Chengyu are fixed phrases consisting of four characters. As a type of idioms, their meanings usually cannot be derived from their component characters. In this paper, we study the task of recommending a Chengyu given a textual context. Observing some of the limitations with existing work, we propose a two-stage model, where during the first stage we re-train a Chinese BERT model by masking out Chengyu from a large Chinese corpus with a wide coverage of Chengyu. During the second stage, we fine-tune the retrained, Chengyu-oriented BERT on a specific Chengyu recommendation dataset. We evaluate this method on ...


Hierarchical Mapping For Crosslingual Word Embedding Alignment, Ion Madrazo Azpiazu, Maria Soledad Pera Jul 2021

Hierarchical Mapping For Crosslingual Word Embedding Alignment, Ion Madrazo Azpiazu, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

The alignment of word embedding spaces in different languages into a common crosslingual space has recently been in vogue. Strategies that do so compute pairwise alignments and then map multiple languages to a single pivot language (most often English). These strategies, however, are biased towards the choice of the pivot language, given that language proximity and the linguistic characteristics of the target language can strongly impact the resultant crosslingual space in detriment of topologically distant languages. We present a strategy that eliminates the need for a pivot language by learning the mappings across languages in a hierarchicalway. Experiments demonstrate that ...


Membrane Inlet Mass Spectrometry Method (Reox/Mims) To Measure 15n-Nitrate In Isotope-Enrichment Experiments, Xianbiao Lin, Kaijun Lu, Amber K. Hardison, Et Al Jul 2021

Membrane Inlet Mass Spectrometry Method (Reox/Mims) To Measure 15n-Nitrate In Isotope-Enrichment Experiments, Xianbiao Lin, Kaijun Lu, Amber K. Hardison, Et Al

VIMS Articles

Using 15N stable isotope as a tracer to quantify N transformation rates in isotope-enrichment experiments improves understanding of the N cycle in various ecosystems. However, measuring 15N-nitrate (15NO3) in small volumes of water for these experiments is a major challenge due to the inconvenience of preparing samples by traditional techniques. We developed a “REOX/MIMS” method by applying membrane inlet mass spectrometry (MIMS) to determining 15NO3 concentrations in a small volumes of water from isotope-enrichment experiments after converting the dissolved inorganic N to N2. The nitrates (NO3 + NO2) were reduced to ...


On-Chip Nanoscale Plasmonic Optical Modulators, Abdalrahman Mohamed Nader Abdelhamid Jun 2021

On-Chip Nanoscale Plasmonic Optical Modulators, Abdalrahman Mohamed Nader Abdelhamid

Theses and Dissertations

In this thesis work, techniques for downsizing Optical modulators to nanoscale for the purpose of utilization in on chip communication and sensing applications are explored. Nanoscale optical interconnects can solve the electronics speed limiting transmission lines, in addition to decrease the electronic chips heat dissipation. A major obstacle in the path of achieving this goal is to build optical modulators, which transforms data from the electrical form to the optical form, in a size comparable to the size of the electronics components, while also having low insertion loss, high extinction ratio and bandwidth. Also, lap-on-chip applications used for fast diagnostics ...


Mechanistic And Synthetic Studies Of Oxidopyrylium Cycloaddition Reactions, Lauren P. Bejcek Jun 2021

Mechanistic And Synthetic Studies Of Oxidopyrylium Cycloaddition Reactions, Lauren P. Bejcek

Dissertations, Theses, and Capstone Projects

Cycloaddition chemistry has historically served as a robust route to stereo-rich and highly functionalized cyclic and heterocyclic compounds. Herein we describe our examination of 3-hydroxy-4-pyrone-derived oxidopyrylium cycloadditions in both mechanistic considerations as well as the unique synthetic advancements of their corresponding cycloadducts. Chapter 1 is a literature review where we specifically outline the use of oxidopyrylium cycloadditions in the synthesis of natural products. This includes the mention of previous syntheses prior to 2008, and a more thorough examination of the natural products synthesized from 2008 to present. The work exploits this chemistry as a facile route to highly complex 7-membered ...


Clustering And Halo Abundances In Early Dark Energy Cosmological Models, A. Klypin, V. Poulin, F. Prada, J. Primack, M. Kamionkowski, V. Avila-Reese, A. Rodriguez-Puebla, P. Behroozi, D. Hellinger, Tristan L. Smith Jun 2021

Clustering And Halo Abundances In Early Dark Energy Cosmological Models, A. Klypin, V. Poulin, F. Prada, J. Primack, M. Kamionkowski, V. Avila-Reese, A. Rodriguez-Puebla, P. Behroozi, D. Hellinger, Tristan L. Smith

Physics & Astronomy Faculty Works

Cold Dark Matter with cosmological constant (ΛCDM) cosmological models with early dark energy (EDE) have been proposed to resolve tensions between the Hubble constant H0=100h km ṡ−1Ṁpc−1 measured locally, giving h ≈ 0.73, and H0 deduced from Planck cosmic microwave background (CMB) and other early-Universe measurements plus ΛCDM, giving h ≈ 0.67. EDE models do this by adding a scalar field that temporarily adds dark energy equal to about 10 per cent of the cosmological energy density at the end of the radiation-dominated era at redshift z ∼ 3500. Here, we compare linear and non-linear predictions of a ...


Learn Biologically Meaningful Representation With Transfer Learning, Di He Jun 2021

Learn Biologically Meaningful Representation With Transfer Learning, Di He

Dissertations, Theses, and Capstone Projects

Machine learning has made significant contributions to bioinformatics and computational biol­ogy. In particular, supervised learning approaches have been widely used in solving problems such as bio­marker identification, drug response prediction, and so on. However, because of the limited availability of comprehensively labeled and clean data, constructing predictive models in super­ vised settings is not always desirable or possible, especially when using data­hunger, red­hot learning paradigms such as deep learning methods. Hence, there are urgent needs to develop new approaches that could leverage more readily available unlabeled data in driving successful machine learning ap­ plications in this ...


Energy On Spheres And Discreteness Of Minimizing Measures, Dmitriy Bilyk, Alexey Glazyrin, Ryan Matzke, Josiah Park, Oleksandr Vlasiuk Jun 2021

Energy On Spheres And Discreteness Of Minimizing Measures, Dmitriy Bilyk, Alexey Glazyrin, Ryan Matzke, Josiah Park, Oleksandr Vlasiuk

Mathematical and Statistical Sciences Faculty Publications and Presentations

In the present paper we study the minimization of energy integrals on the sphere with a focus on an interesting clustering phenomenon: for certain types of potentials, optimal measures are discrete or are supported on small sets. In particular, we prove that the support of any minimizer of the p-frame energy has empty interior whenever p is not an even integer. A similar effect is also demonstrated for energies with analytic potentials which are not positive definite. In addition, we establish the existence of discrete minimizers for a large class of energies, which includes energies with polynomial potentials.


Synthetic And Biological Studies On Benzazepine Derivatives As Dopamine Receptor Ligands, Rajan Giri Jun 2021

Synthetic And Biological Studies On Benzazepine Derivatives As Dopamine Receptor Ligands, Rajan Giri

Dissertations, Theses, and Capstone Projects

Dopamine (DA) receptors, members of the G-protein coupled receptors (GPCRs) family, are divided in two groups based on their transmembrane structural homology domains: D1R-like (D1R, D5R sub-types) and D2R-like DA receptors (D2R, D3R and D4R sub-types). Disturbances in dopaminergic neurotransmission are associated with several CNS disorders. Hence, DA receptor selective ligands have been sought as pharmacological agents to normalize perturbations in the dopaminergic system. Despite several notable efforts, the discovery of highly selective ligands for dopamine receptor sub-types has proved challenging due to close transmembrane structural similarity, especially between DA receptor sub-types within the same group.

The 1-phenylbenzazepine scaffold is ...


Waste To Phosphorus: A Transdisciplinary Solution To P Recovery From Wastewater Based On The Triz Approach, Anna Jama-Rodzeńska, Andrzej Białowiec, Jacek A. Koziel, Józef Sowiński Jun 2021

Waste To Phosphorus: A Transdisciplinary Solution To P Recovery From Wastewater Based On The Triz Approach, Anna Jama-Rodzeńska, Andrzej Białowiec, Jacek A. Koziel, Józef Sowiński

Agricultural and Biosystems Engineering Publications

Phosphorus (P) is a limited yet essential resource. P cannot be replaced, but it can be recovered from waste. We proposed the TRIZ approach (Teoria reszenija izobretatielskich zadacz - Rus., Theory of Inventive Problem Solving - Eng.) to identify a feasible solution. We aimed at minimizing the environmental impact and, by eliminating contradictions, proposed viable technical solutions. P recovery can be more sustainable based on circular economy and 4Rs (reduction, recovery, reuse, and recycling). The TRIZ approach identified sewage sludge (SS) as waste with a large potential for P recovery (up to 90%). Successful selection and application of SS management and P ...


Emergent Photophyiscs In Diketopyrrolopyrrole Superstructures, Andrew Levine Jun 2021

Emergent Photophyiscs In Diketopyrrolopyrrole Superstructures, Andrew Levine

Dissertations, Theses, and Capstone Projects

Organic semiconductors have received substantial attention as active components in optoelectronic devices because of their processability and customizable electronic properties. Tailoring the organic active layer in these devices to exhibit desirable optoelectronic properties requires understanding the complex and often subtle structure-property relationships governing their photophysical response to light. Both structural organization and frontier molecular orbitals (FMO) play pivotal roles in energy relaxation processes, and complex interplay between organization and orbital energies are difficult to anticipate based upon the molecular structure of the components alone, especially in systems comprised of multiple components. In pursuit of design rules, there is a need ...


Skyrmions And Biskyrmions In Magnetic Films, Daniel Capic Jun 2021

Skyrmions And Biskyrmions In Magnetic Films, Daniel Capic

Dissertations, Theses, and Capstone Projects

Skyrmions have garnered significant attention in condensed matter systems in recent years. In principle, they are topologically protected, so there is a large energy barrier preventing their annihilation. Furthermore, they can exist at the nanoscale, be manipulated with very small currents, and be created by a number of different methods. This makes them attractive for use in potential computing applications. This work studies ferromagnetic skyrmions. In particular, it highlights our small contributions to the field of skyrmions in condensed matter systems, specifically in thin-film ferromagnets.


Blockchain For Automotive: An Insight Towards The Ipfs Blockchain-Based Auto Insurance Sector, Nishara Nizamuddin, Ahed Abugabah Jun 2021

Blockchain For Automotive: An Insight Towards The Ipfs Blockchain-Based Auto Insurance Sector, Nishara Nizamuddin, Ahed Abugabah

All Works

The advancing technology and industrial revolution have taken the automotive industry by storm in recent times. The auto sector’s constantly growing demand has paved the way for the automobile sector to embrace new technologies and disruptive innovations. The multi-trillion dollar, complex auto insurance sector is still stuck in the regulations of the past. Most of the customers still contact the insurance company by phone to buy new policies and process existing insurance claims. The customers still face the risk of fraudulent online brokers, as policies are mostly signed and processed on papers which often require human supervision, with a ...


Towards A Machine Learning Based Generalizable Framework For Detecting Covid-19 Misinformation On Social Media, Yuanzhi Chen May 2021

Towards A Machine Learning Based Generalizable Framework For Detecting Covid-19 Misinformation On Social Media, Yuanzhi Chen

Computer Science and Engineering: Theses, Dissertations, and Student Research

Since the beginning of the COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, online social media has become a conduit for the rapid propagation of misinformation. The misinformation is a type of fake news that is created inadvertently without the intention of causing harm. Yet COVID-19 misinformation has caused serious social disruptions including accidental death and destruction of public property. Timely prevention of the propagation of online misinformation requires the development of automated detection tools. Machine learning (ML) based models have been used to automate techniques for identifying fake news. These techniques involve converting text data ...


An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja May 2021

An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi T. Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja

Publications and Research

Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today’s data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed ...


Using An Integrative Machine Learning Approach To Study Microrna Regulation Networks In Pancreatic Cancer Progression, Roland Madadjim May 2021

Using An Integrative Machine Learning Approach To Study Microrna Regulation Networks In Pancreatic Cancer Progression, Roland Madadjim

Computer Science and Engineering: Theses, Dissertations, and Student Research

With advances in genomic discovery tools, recent biomedical research has produced a massive amount of genomic data on post-transcriptional regulations related to various transcript factors, microRNAs, lncRNAs, epigenetic modifications, and genetic variations. In this direction, the field of gene regulation network inference is created and aims to understand the interactome regulations between these molecules (e.g., gene-gene, miRNA-gene) that take place to build models able to capture behavioral changes in biological systems. A question of interest arises in integrating such molecules to build a network while treating each specie in its uniqueness. Given the dynamic changes of interactome in chaotic ...


Development Of A Diamond Defect Quantum Sensing Platform For Probing Novel Quantum Magnetic Phases, Jeffrey Ahlers May 2021

Development Of A Diamond Defect Quantum Sensing Platform For Probing Novel Quantum Magnetic Phases, Jeffrey Ahlers

Senior Honors Papers / Undergraduate Theses

Nitrogen vacancy centers in diamond are highly effective quantum sensors due to their high spatial resolution and high magnetic field sensitivity. We present the construction of an optically detected magnetic resonance platform in order to facilitate the probing of magnetic phases in two-dimensional heterostructures. This includes the characterization of the required microwave voltage controlled oscillator and amplifier. In the presence of crystal strain, we measure ensemble nitrogen vacancy spin transitions with and without an applied magnetic field, and observe frequency shifts consistent with sample heating.


Theranostic Applications Of Sirna Bioconjugates In Cancer Detection And Treatment, Sunil S. Shah May 2021

Theranostic Applications Of Sirna Bioconjugates In Cancer Detection And Treatment, Sunil S. Shah

Seton Hall University Dissertations and Theses (ETDs)

Abstract

The emerging field of RNA nanotechnology has led to rapid advances in the applications of RNA in chemical biology, medicinal chemistry, and biotechnology. At the forefront of its utility is the ability to self-assemble multiple siRNAs into nanostructure formulations capable of targeting selected oncogenes and potentiating the gene therapy of malignant tumors. Self-assembled siRNA integrates multiple siRNAs within a single molecular platform for silencing multiple oncogenic mRNA targets with high precision and efficacy to potentially induce cancer cell apoptosis through the RNA interference (RNAi) pathway. Furthermore, the conjugation of siRNA self-assemblies with bio-active probes results in multi-functional theranostic (therapy ...


Variability Of Usa East Coast Surface Total Alkalinity Distributions Revealed By Automated Instrument Measurements, Christopher W. Hunt, Joseph Salisbury, Douglas Vandemark, Steffen Aßmann, Christopher Melrose, Rik Wanninkhof, Kumiko Azetsu-Scott May 2021

Variability Of Usa East Coast Surface Total Alkalinity Distributions Revealed By Automated Instrument Measurements, Christopher W. Hunt, Joseph Salisbury, Douglas Vandemark, Steffen Aßmann, Christopher Melrose, Rik Wanninkhof, Kumiko Azetsu-Scott

Faculty Publications

Seawater total alkalinity (TA) is one important determinant used to monitor the ocean carbon cycle, whose spatial distributions have previously been characterized along the United States East Coast via discrete bottle samples. Using these data, several regional models for TA retrievals based on practical salinity (S) have been developed. Broad-scale seasonal or interannual variations, however, are not well resolved in these models and existing data are highly seasonally biased. This study reports findings from the first long duration deployment of a new, commercially available TA titrator aboard a research vessel and the continuous underway surface TA measurements produced. The instrument ...


Effects Of Phenological Stages On Forage Quality In Nine Range Species In Alborz Rangelands, N. Charehsaz, Hossein Arzani, A. A. Jafari May 2021

Effects Of Phenological Stages On Forage Quality In Nine Range Species In Alborz Rangelands, N. Charehsaz, Hossein Arzani, A. A. Jafari

International Grassland Congress Proceedings

No abstract provided.


Study On Optimum Cultivation Techniques Of Alfalfa On Songnen Plain, Fengjiu Chai, Zedong Liu May 2021

Study On Optimum Cultivation Techniques Of Alfalfa On Songnen Plain, Fengjiu Chai, Zedong Liu

International Grassland Congress Proceedings

No abstract provided.


Fermentation Quality Of Silage Prepared With Bacteriocin‐Producing Probiotic Lactic Acid Bacteria, Yimin Cai, Saïd Ennahar, Ramli Mohd Noor, Chuncheng Xu, Ryuichi Uegaki, Norio Yoshida May 2021

Fermentation Quality Of Silage Prepared With Bacteriocin‐Producing Probiotic Lactic Acid Bacteria, Yimin Cai, Saïd Ennahar, Ramli Mohd Noor, Chuncheng Xu, Ryuichi Uegaki, Norio Yoshida

International Grassland Congress Proceedings

No abstract provided.


Chemical Composition Of Range Plants Of Vital Fodder Value For Livestock‐Based Economy In Uttarakhand Himalaya, India, Babita Bohra, Vir Singh, R. D. Gaur May 2021

Chemical Composition Of Range Plants Of Vital Fodder Value For Livestock‐Based Economy In Uttarakhand Himalaya, India, Babita Bohra, Vir Singh, R. D. Gaur

International Grassland Congress Proceedings

No abstract provided.