A Perspective On The Challenges And Issues In Developing Biomarkers For Human Allergic Risk Assessments,
2017
U.S. Food and Drug Administration
A Perspective On The Challenges And Issues In Developing Biomarkers For Human Allergic Risk Assessments, Ying Mu, Dianne E. Godar, Stephen Merrill
Mathematics, Statistics and Computer Science Faculty Research and Publications
No abstract provided.
Obesity-Induces Organ And Tissue Specific Tight Junction Restructuring And Barrier Deregulation By Claudin Switching,
2017
University of Nebraska Medical Center
Obesity-Induces Organ And Tissue Specific Tight Junction Restructuring And Barrier Deregulation By Claudin Switching, Rizwan Ahmad, Bilal Rah, Dhundy Bastola, Punita Dhawan, Amar B. Singh
Interdisciplinary Informatics Faculty Publications
Obesity increases susceptibility to multiple organ disorders, however, underlying mechanisms remain unclear. The subclinical inflammation assisted by obesity-induced gut permeability may underlie obesity-associated co-morbidities. Despite eminent clinical significance of the obesity led gut barrier abnormalities, its precise molecular regulation remains unclear. It is also unknown whether barrier deregulations, similar to the gut, characterize other vital organs in obese individuals. The claudin family of proteins is integral to the tight junction (TJ), the apical cell-cell adhesion and a key regulator of the epithelial barrier. Using comprehensive physiological and biochemical analysis of intestinal and renal tissues from high-fat diet fed mice, critical …
Conflict-Free Vertex Coloring Of Planar Graphs,
2017
University of Minnesota, Morris
Conflict-Free Vertex Coloring Of Planar Graphs, Shawn Seymour
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
The conflict-free coloring problem is a variation of the vertex coloring problem, a classical NP-hard optimization problem. The conflict-free coloring problem aims to color a possibly proper subset of vertices such that there is a unique color within the closed neighborhood (a vertex and its neighbors) of every vertex. This paper presents recent findings and heuristics to solve the conflict-free coloring problem on both general graphs and planar graphs.
Touchscreen Smartphone User Interfaces For Older Adults,
2017
University of Minnesota, Morris
Touchscreen Smartphone User Interfaces For Older Adults, Ai Sano
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Today the world is experiencing the rapid growth of the older population. The number of older adults who own digital devices such as smartphones is increasing as well. The current smartphone user interfaces, however, appear not optimized for older adults. When designing smartphone user interfaces for older adults, we must consider their age-related physical and cognitive changes, which most likely affect their user experience. The present paper explores smartphone user interface guidelines for older adults and heuristics for evaluating the usability of Android launchers for older adults as well as a research study that developed an Android launcher for older …
Identifying Twitter Spam By Utilizing Random Forests,
2017
University of Minnesota, Morris
Identifying Twitter Spam By Utilizing Random Forests, Humza S. Haider
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
The use of Twitter has rapidly grown since the first tweet in 2006. The number of spammers on Twitter shows a similar increase. Classifying users into spammers and non-spammers has been heavily researched, and new methods for spam detection are developing rapidly. One of these classification techniques is known as random forests. We examine three studies that employ random forests using user based features, geo-tagged features, and time dependent features. Each study showed high accuracy rates and F-measures with the exception of one model that had a test set with a more realistic proportion of spam relative to typical testing …
An Overview Of Modern Global Illumination,
2017
University of Minnesota, Morris
An Overview Of Modern Global Illumination, Skye A. Antinozzi
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Advancements in graphical hardware call for innovative solutions, which can improve the realism of computer generated lighting. These innovative solutions aim to generate state of the art computer generated lighting through a combination of intelligent global illumination models and the use of modern hardware. The solution described in this paper achieves global illumination by ray tracing over geometry within a 3D scene from distributed light field probes and proceeds to shade the scene with a deferred renderer. Such a solution provides the flexibility and robustness that many other global illumination models have previously lacked while still achieving realistic lighting that …
Essays On Crowdfunding: Exploring The Funding And Post-Funding Phases And Outcomes,
2017
University of South Florida
Essays On Crowdfunding: Exploring The Funding And Post-Funding Phases And Outcomes, Onochie Fan-Osuala
USF Tampa Graduate Theses and Dissertations
In the recent years, crowdfunding (a phenomenon where individuals collectively contribute money to back different goals and projects through the internet) has been gaining a lot of attention especially for its socio-economic impact. This dissertation explores this phenomenon in three distinct but related essays. The first essay explores the nature and dynamics of backers’ contributions and uses the insights generated to develop a forecasting model that can predict crowdfunding campaign outcomes. The second essay investigates how creators’ crowdfunding campaign design decisions impact their funding and post-funding outcomes. Interestingly, the essay highlights that certain crowdfunding campaign design decisions have differential effects …
High-Performance Complex Event Processing For Decision Analytics,
2017
University of Massachusetts Amherst
High-Performance Complex Event Processing For Decision Analytics, Haopeng Zhang
Doctoral Dissertations
Complex Event Processing (CEP) systems are becoming increasingly popular in do- mains for decision analytics such as financial services, transportation, cluster monitoring, supply chain management, business process management, and health care. These systems collect or create high volumes event streams, and often require such event streams to be processed in real-time. To this end, CEP queries are applied for filtering, correlation, ag- gregation, and transformation, to derive high-level, actionable information. Tasks for CEP systems fall into two categories: passive monitoring and proactive monitoring. For passive monitoring, users know their exact needs and express them in CEP queries, then CEP engines …
Belief-Space Planning For Resourceful Manipulation And Mobility,
2017
University of Massachusetts Amherst
Belief-Space Planning For Resourceful Manipulation And Mobility, Dirk Ruiken
Doctoral Dissertations
Robots are increasingly expected to work in partially observable and unstructured environments. They need to select actions that exploit perceptual and motor resourcefulness to manage uncertainty based on the demands of the task and environment. The research in this dissertation makes two primary contributions. First, it develops a new concept in resourceful robot platforms called the UMass uBot and introduces the sixth and seventh in the uBot series. uBot-6 introduces multiple postural configurations that enable different modes of mobility and manipulation to meet the needs of a wide variety of tasks and environmental constraints. uBot-7 extends this with the use …
Automatic Derivation Of Requirements For Components Used In Human-Intensive Systems,
2017
University of Massachusetts Amherst
Automatic Derivation Of Requirements For Components Used In Human-Intensive Systems, Heather Conboy
Doctoral Dissertations
Human-intensive systems (HISs), where humans must coordinate with each other along with software and/or hardware components to achieve system missions, are increasingly prevalent in safety-critical domains (e.g., healthcare). Such systems are often complex, involving aspects such as concurrency and exceptional situations. For these systems, it is often difficult but important to determine requirements for the individual components that are necessary to ensure the system requirements are satisfied. In this thesis, we investigated an approach that employs interface synthesis methods developed for software systems to automatically derive such requirements for components used in HISs. In previous work, we investigated a requirement …
Problems In Graph-Structured Modeling And Learning,
2017
University of Massachusetts Amherst
Problems In Graph-Structured Modeling And Learning, James Atwood
Doctoral Dissertations
This thesis investigates three problems in graph-structured modeling and learning. We first present a method for efficiently generating large instances from nonlinear preferential attachment models of network structure. This is followed by a description of diffusion-convolutional neural networks, a new model for graph-structured data which is able to outperform probabilistic relational models and kernel-on-graph methods at node classification tasks. We conclude with an optimal privacy-protection method for users of online services that remains effective when users have poor knowledge of an adversary's behavior.
Method For Enabling Causal Inference In Relational Domains,
2017
University of Massachusetts Amherst
Method For Enabling Causal Inference In Relational Domains, David Arbour
Doctoral Dissertations
The analysis of data from complex systems is quickly becoming a fundamental aspect of modern business, government, and science. The field of causal learning is concerned with developing a set of statistical methods that allow practitioners make inferences about unseen interventions. This field has seen significant advances in recent years. However, the vast majority of this work assumes that data instances are independent, whereas many systems are best described in terms of interconnected instances, i.e. relational systems. This discrepancy prevents causal inference techniques from being reliably applied in many real-world settings.
In this thesis, I will present three contributions to …
Knowledge Extraction From Metacognitive Reading Strategies Data Using Induction Trees,
2017
University of Texas at Tyler
Knowledge Extraction From Metacognitive Reading Strategies Data Using Induction Trees, Christopher Taylor, Arun D. Kulkarni, Kouider Mokhtari
Arun Kulkarni
The assessment of students’ metacognitive knowledge and skills about reading is critical in determining their ability to read academic texts and do so with comprehension. In this paper, we used induction trees to extract metacognitive knowledge about reading from a reading strategies dataset obtained from a group of 1636 undergraduate college students. Using a C4.5 algorithm, we constructed decision trees, which helped us classify participants into three groups based on their metacognitive strategy awareness levels consisting of global, problem-solving and support reading strategies. We extracted rules from these decision trees, and in order to evaluate accuracy of the extracted rules, …
Signet: A Neural Network Architecture For Predicting Protein-Protein Interactions,
2017
The University of Western Ontario
Signet: A Neural Network Architecture For Predicting Protein-Protein Interactions, Muhammad S. Ahmed
Electronic Thesis and Dissertation Repository
The study of protein-protein interactions (PPI) is critically important within the field of Molecular Biology, as proteins facilitate key organismal functions including the maintenance of both cellular structure and function. Current experimental methods for elucidating PPIs are greatly hindered by large operating costs, lengthy wait times, as well as low accuracy. The recent development of computational PPI predicting techniques has worked to address many of these issues. Despite this, many of these methods utilize over-engineered features and naive learning algorithms. With the recent advances in Machine Learning and Artificial Intelligence, we attempt to view this problem through a novel, deep …
Harmonic Distortion Minimization In Power Grids With Wind And Electric Vehicles,
2017
Midcontinent Independent System Operator
Harmonic Distortion Minimization In Power Grids With Wind And Electric Vehicles, Ritam Misra, Sumit Paudyal, Oguzhan Ceylan, Paras Mandal
Michigan Tech Publications
Power-electronic interfacing based devices such as wind generators (WGs) and electrical vehicles (EVs) cause harmonic distortions on the power grid. Higher penetration and uncoordinated operation of WGs and EVs can lead to voltage and current harmonic distortions, which may exceed IEEE limits. It is interesting to note that WGs and EVs have some common harmonic profiles. Therefore, when EVs are connected to the grid, the harmonic pollution EVs impart onto the grid can be reduced to some extent by the amount of wind power injecting into the grid and vice versa. In this context, this work studies the impact of …
Signal Processing On Graphs Using Kron Reduction And Spline Interpolation,
2017
University of Berkeley, California
Signal Processing On Graphs Using Kron Reduction And Spline Interpolation, Michael Dennis, Enrico Au-Yeung
DePaul Discoveries
In applications such as image processing, the data is given in a regular pattern with a known structure, such as a grid of pixels. However, it is becoming increasingly common for large datasets to have some irregular structure. In image recognition, one of the most successful methods is wavelet analysis, also commonly known as multi-resolution analysis. Our project is to develop and explore this powerful technique in the setting where the data is not stored in the form of a rectangular table with rows and columns of pixels. While the data sets will still have a lot of structure to …
Multiple Attributes Decision Fusion For Wireless Sensor Networks Based On Intuitionistic Fuzzy Set,
2017
Beijing Jiaotong University, China
Multiple Attributes Decision Fusion For Wireless Sensor Networks Based On Intuitionistic Fuzzy Set, Zhenjiang Zhang, Ziqi Hao, Sherali Zeadally, Jing Zhang, Bowen Han, Han-Chieh Chao
Information Science Faculty Publications
Decision fusion is an important issue in wireless sensor networks (WSN), and intuitionistic fuzzy set (IFS) is a novel method for dealing with uncertain data. We propose a multi-attribute decision fusion model based on IFS, which includes two aspects: data distribution-based IFS construction algorithm (DDBIFCA) and the category similarity weight-based TOPSIS intuitionistic fuzzy decision algorithm (CSWBT-IFS). The DDBIFCA is an IFS construction algorithm that transforms the original attribute values into intuitionistic fuzzy measures, and the CSWBT-IFS is an intuitionistic fuzzy aggregation algorithm improved by the traditional TOPSIS algorithm, which combines intuitionistic fuzzy values of different attributes and obtains a final …
A First Look At The Year In Computing,
2017
University of Kent
A First Look At The Year In Computing, Sebastian Dziallas, Sally Fincher, Colin G. Johnson, Ian Utting
All Faculty Presentations - School of Engineering and Computer Science
In this paper, we discuss students' expectations and experiences in the first term of the Year in Computing, a new programme for non-computing majors at the University of Kent, a public research university in the UK. We focus on the effect of students' home discipline on their experiences in the programme and situate this work within the context of wider efforts to make the study of computing accessible to a broader range of students. Copyright is held by the owner/author(s).
Cnn Based 3d Facial Expression Recognition Using Masking And Landmark Features,
2017
Missouri University of Science and Technology
Cnn Based 3d Facial Expression Recognition Using Masking And Landmark Features, Huiyuan Yang, Lijun Yin
Computer Science Faculty Research & Creative Works
Automatically recognizing facial expression is an important part for human-machine interaction. In this paper, we first review the previous studies on both 2D and 3D facial expression recognition, and then summarize the key research questions to solve in the future. Finally, we propose a 3D facial expression recognition (FER) algorithm using convolutional neural networks (CNNs) and landmark features/masks, which is invariant to pose and illumination variations due to the solely use of 3D geometric facial models without any texture information. The proposed method has been tested on two public 3D facial expression databases: BU-4DFE and BU-3DFE. The results show that …
Soft Sides Of Software,
2017
University of Western Ontario
Soft Sides Of Software, Luiz Fernando Capretz, Faheem Ahmed, Fabio Queda Silva
Electrical and Computer Engineering Publications
Software is a field of rapid changes: the best technology today becomes obsolete in the near future. If we review the graduate attributes of any of the software engineering programs across the world, life-long learning is one of them. The social and psychological aspects of professional development is linked with rewards. In organizations, where people are provided with learning opportunities and there is a culture that rewards learning, people embrace changes easily. However, the software industry tends to be short-sighted and its primary focus is more on current project success; it usually ignores the capacity building of the individual or …
