Computer Sciences Commons^™

A Survey On Graph Representation And Visualization Techniques, Chen Yi, Menglu Zhang, Yuchai Wan

Journal of System Simulation

Abstract: A graph consists of nodes and edges, and represents the relationship between two or more entities. Graph-based analysis can help understand the structure and nature of the entity relationships and reveal the implicit relationships in graphs. The representation and visualization methods of graphs play an important role in the graph analysis. In graph visualization research, the accuracy of knowledge transfer and people's mental map, etc. should be considered first, then the graphs beauty, the time requirement, and the computer performance. The graph representation methods, graph layout algorithms, visualization methods based on node-link-graphs, adjacency matrices, and graph embedding are reviewed, …

Deep Learning For Identifying Breast Cancer, Yihong Li

Master of Science in Computer Science Theses

Medical images are playing an increasingly important role in the prevention and diagnosis of diseases. Medical images often contain massive amounts of data. Professional interpretation usually requires a long time of professional study and experience accumulation by doctors. Therefore, the use of super storage and computing power in deep learning as a basis can effectively process a large amount of medical data. Breast cancer brings great harm to female patients, and early diagnosis is the most effective prevention and treatment method, so this project will create a new optimized breast cancer auxiliary diagnosis model based on ResNet. Analyze and process, …

Deep Learning For Identifying Lung Diseases, Lin Wang

Master of Science in Computer Science Theses

Growing health problems, such as lung diseases, especially for children and the elderly, require better diagnostic methods, such as computer-based solutions, and it is crucial to detect and treat these problems early. The purpose of this article is to design and implement a new computer vision-based algorithm based on lung disease diagnosis, which has better performance in lung disease recognition than previous models to reduce lung-related health problems and costs . In addition, we have improved the accuracy of the five lung diseases detection, which helps doctors and doctors use computers to solve this problem at an early stage.

Automatic Recognition, Segmentation, And Sex Assignment Of Nocturnal Asthmatic Coughs And Cough Epochs In Smartphone Audio Recordings: Observational Field Study, Filipe Barata, Peter Tinschert, Frank Rassouli, Claudia Steurer-Stey, Elgar Fleisch, Milo Puhan, Martin Brutsche, David Kotz, Tobias Kowatsch

Dartmouth Scholarship

Background: Asthma is one of the most prevalent chronic respiratory diseases. Despite increased investment in treatment, little progress has been made in the early recognition and treatment of asthma exacerbations over the last decade. Nocturnal cough monitoring may provide an opportunity to identify patients at risk for imminent exacerbations. Recently developed approaches enable smartphone-based cough monitoring. These approaches, however, have not undergone longitudinal overnight testing nor have they been specifically evaluated in the context of asthma. Also, the problem of distinguishing partner coughs from patient coughs when two or more people are sleeping in the same room using contact-free audio …

Human Supremacy As Posthuman Risk, Daniel Estrada

The Journal of Sociotechnical Critique

Human supremacy is the widely held view that human interests ought to be privileged over other interests as a matter of ethics and public policy. Posthumanism is the historical situation characterized by a critical reevaluation of anthropocentrist theory and practice. This paper draws on animal studies, critical posthumanism, and the critique of ideal theory in Charles Mills and Serene Khader to address the appeal to human supremacist rhetoric in AI ethics and policy discussions, particularly in the work of Joanna Bryson. This analysis identifies a specific risk posed by human supremacist policy in a posthuman context, namely the classification of …

A Data Scientist Looks At Covid19 Part Ii: Mythbusting, Anthony Breitzman

College of Science & Mathematics Departmental Research

No abstract provided.

A Real-Time Feature Indexing System On Live Video Streams, Aditya Chakraborty, Akshay Pawar, Hojoung Jang, Shunqiao Huang, Sripath Mishra, Shuo-Han Chen, Yuan-Hao Chang, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

Most of the existing video storage systems rely on offline processing to support the feature-based indexing on video streams. The feature-based indexing technique provides an effec- tive way for users to search video content through visual features, such as object categories (e.g., cars and persons). However, due to the reliance on offline processing, video streams along with their captured features cannot be searchable immediately after video streams are recorded. According to our investigation, buffering and storing live video steams are more time-consuming than the YOLO v3 object detector. Such observation motivates us to propose a real-time feature indexing (RTFI) system …

Not Intelligent: Encoding Gender Bias, Cara Tenenbaum

Minnesota Journal of Law, Science & Technology

No abstract provided.

Law, Technology, And Pedagogy: Teaching Coding To Build A “Future-Proof” Lawyer, Alfredo Contreras, Joe Mcgrath

Minnesota Journal of Law, Science & Technology

No abstract provided.

Motivational Principles And Personalisation Needs For Geo-Crowdsourced Intangible Cultural Heritage Mobile Applications, Federica Lucia Vinella, Ioanna Lykourentzou, Konstantinos Papangelis

Presentations and other scholarship

Whether it’s for altruistic reasons, personal gains, or third party’s interests, users are influenced by different kinds of motivations when making use of mobile geo-crowdsourcing applications (geoCAs). These reasons, extrinsic and/or intrinsic, must be factored in when evaluating the use intention of these applications and how effective they are. A functional geoCA, particularly if designed for Volunteered Geographic Information (VGI), is the one that persuades and engages its users, by accounting for their diversity of needs across a period of time. This paper explores a number of proven and novel motivational factors destined for the preservation and collection of Intangible …

Novel Technique To Analyze The Effects Of Cognitive And Non-Cognitive Predictors On Students Course Withdrawal In College, Mohammed Ali

Technology Faculty Publications and Presentations

A novel technique was applied to a college student database to identify the cognitive and non-cognitive factors that predict college students’ course withdrawal behaviors. Predictors such as high school grade point average (HSGPA), standardized test scores (ACT–American College Test or SAT-Scholastic Aptitude Test), number of credit hours enrolled, and age were analyzed in this study. Data mining software algorithms were used to study information about undergraduate students at a west-south-central state university in the United States. The study results revealed that two factors, number of enrolled credit hours, and a student’s age have the most effect on collegiate course withdrawal …

Being Human In Stem Csc 213x, Harrison Dekker

Library Impact Statements

No abstract provided.

Exploring Covid-19 Data Csc 292, Harrison Dekker

Library Impact Statements

No abstract provided.

Deep Learning Predictive Modeling With Data Challenges (Small, Big, Or Imbalanced), Renhao Liu

USF Tampa Graduate Theses and Dissertations

In the real world, data used to build machine learning models always has different sizes and characteristics. These size and characteristic features, including small datasets, big datasets, imbalanced datasets, often lead to different challenges when training machine learning models. Models trained on a small number of observations tend to overfit the training data and produce inaccurate results. When it comes to big data, efficiently learning from "huge" size data in a short time becomes important. With an imbalanced dataset, learning is usually biased towards the majority class in the data and appropriate measurements are needed to check model performance.

As …

Satc: Core: Medium: Collaborative: Baitbuster 2.0: Keeping Users Away From Clickbait, Mahdi Nasrullah Al-Ameen

Funded Research Records

No abstract provided.

Ieee Access Special Section Editorial: Machine Learning Designs, Implementations And Techniques, Shadi A. Aljawarneh, Oguz Bayat, Juan A. Lara, Robert P. Schumaker

Computer Science Faculty Publications and Presentations

IEEE access special section editorial.

Allosteric Regulation At The Crossroads Of New Technologies: Multiscale Modeling, Networks, And Machine Learning, Gennady M. Verkhivker, Steve Agajanian, Guang Hu, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the “second secret of life.” The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of …

Appliance Energy Prediction Using Data Analysis Pipeline And Machine Learning Algorithms, Rishav Hore

Manipal Institute of Technology, Manipal Theses and Dissertations

No abstract provided.

Implementation Of Neural Network On Low Resource Environment, Movin Dsouza

Manipal Institute of Technology, Manipal Theses and Dissertations

No abstract provided.

Recent Advances In Smart Contracts: A Technical Overview And State Of The Art, Victor Youdom Kemmoe, William Stone, Jeehyeong Kim, Daeyoung Kim, Junggab Son

School of Computing Faculty Scholarship and Creative Works

Smart contracts, as an added functionality to blockchain, have received increased attention recently. They are executable programs whose instance and state are stored in blockchain. Hence, smart contracts and blockchain enable a trustable, trackable, and irreversible protocol without the need for trusted third parties which generally constitute a single point of failure. If a user creates and distributes a smart contract, others will be able to interact with it while the underlying blockchain ensures a trustable execution. In this paper, we aim to introduce state-of-the-art technologies of the smart contract protocol. We firstly introduce the history of blockchain and smart …

Atmospheric Contrail Detection With A Deep Learning Algorithm, Nasir Siddiqui

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Aircraft contrail emission is widely believed to be a contributing factor to global climate change. We have used machine learning techniques on images containing contrails in hopes of being able to identify those which contain contrails and those that do not. The developed algorithm processes data on contrail characteristics as captured by long-term image records. Images collected by the United States Department of Energy’s Atmospheric Radiation Management user facility(ARM) were used to train a deep convolutional neural network for the purpose of this contrail classification. The neural network model was trained with 1600 images taken by the Total Sky Imager(TSI) …

Earth-Like Planet In A Binary Star System, Melissa Kamrowski

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper was written as a final lab report for a computer modeling class. It uses dynamical simulations to investigate the behavior of a planet with the mass and velocity magnitude of the Earth placed in a low mass binary star system, which was loosely based on the Sirius binary. The simulations are completed using gravitational force properties along with the Verlet algorithm, then the results were observed through a modeling program, in which each set was set as an animation to determine behavior. Results came from 40 strategic starting points, which were chosen to cover a large spread of …

Summed Batch Lexicase Selection On Software Synthesis Problems, Joseph Deglman

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Lexicase selection is one of the most successful parent selection methods in evolutionary computation. However, it has the drawback of being a more computationally involved process and thus taking more time compared to other selection methods, such as tournament selection. Here, we study a version of lexicase selection where test cases are combined into several composite errors, called summed batch lexicase selection; the hope being faster but still reasonable success. Runs on some software synthesis problems show that a larger batch size tends to reduce the success rate of runs, but the results are not very conclusive as the number …

Lulling Waters: A Poetry Reading For Real-Time Music Generation Through Emotion Mapping, Ashley Muniz, Toshihisa Tsuruoka

Electronic Literature Organization Conference 2020

Through a poetic narrative, “Lulling Waters” tells the story of a whale overcoming the loss of his mother, who passed away from ingesting plastic, as he attempts to escape from the polluted oceanic world. The live performance of this poem utilizes a software system called Soundwriter, which was developed with the goal of enriching the oral storytelling experience through music. This video demonstrates how Soundwriter’s real-time hybrid system was able to analyze “Lulling Waters” through its lexical and auditory features. Emotionally salient words were given ratings based on arousal, valence, and dominance while the emotionally charged prosodic features of the …

Β-Amyloid And Tau Drive Early Alzheimer's Disease Decline While Glucose Hypometabolism Drives Late Decline, Tyler C. Hammond, Xin Xing, Chris Wang, David Ma, Kwangsik Nho, Paul K. Crane, Fanny Elahi, David A. Ziegler, Gongbo Liang, Qiang Cheng, Lucille M. Yanckello, Nathan Jacobs, Ai-Ling Lin

Sanders-Brown Center on Aging Faculty Publications

Clinical trials focusing on therapeutic candidates that modify β-amyloid (Aβ) have repeatedly failed to treat Alzheimer’s disease (AD), suggesting that Aβ may not be the optimal target for treating AD. The evaluation of Aβ, tau, and neurodegenerative (A/T/N) biomarkers has been proposed for classifying AD. However, it remains unclear whether disturbances in each arm of the A/T/N framework contribute equally throughout the progression of AD. Here, using the random forest machine learning method to analyze participants in the Alzheimer’s Disease Neuroimaging Initiative dataset, we show that A/T/N biomarkers show varying importance in predicting AD development, with elevated biomarkers of Aβ …

Quantum Criticality In Strongly Correlated Electron Systems, Samuel Obadiah Kellar

LSU Doctoral Dissertations

The study of the Hubbard model in three dimensions contains a variety of phases dependent upon the chosen parameters. This thesis shows that there is the indication of a zero temperature phase transition at a finite doping. The Hubbard model has been used to identify a similar quantum critical point in two dimensions. The presented results continue these investigations. The system demonstrates a strange metal phase at finite temperature which cannot be described in term of the conventional Fermi liquid. While there have been extensive studies over the past three decades for such materials in two dimensions, there are few …

Nobiletin Affects Circadian Rhythms And Oncogenic Characteristics In A Cell-Dependent Manner, Sujeewa S. Lellupitiyage Don, Kelly L. Robertson, Hui-Hsien Lin, Caroline Labriola, Mary E. Harrington, Stephanie R. Taylor, Michelle E. Farkas

Psychology: Faculty Publications

The natural product nobiletin is a small molecule, widely studied with regard to its therapeutic effects, including in cancer cell lines and tumors. Recently, nobiletin has also been shown to affect circadian rhythms via their enhancement, resulting in protection against metabolic syndrome. We hypothesized that nobiletin’s anti-oncogenic effects, such as prevention of cell migration and formation of anchorage independent colonies, are correspondingly accompanied by modulation of circadian rhythms. Concurrently, we wished to determine whether the circadian and anti-oncogenic effects of nobiletin differed across cancer cell lines. In this study, we assessed nobiletin’s circadian and therapeutic characteristics to ascertain whether these …

Modeling Of Monitoring Systems Of Solar Power Stations For Telecommunication Facilities Based On Wireless Nets, Ilkhomjon Xakimovich Siddikov, Khalimjon Ergashevich Khujamatov, Doston Turayevich Khasanov, Ernazar Nurjamiyevich Reypnazarov

Chemical Technology, Control and Management

In this paper described of modelling processes of the real-time remote monitoring system of solar power sources, modelled and investigated by wireless sensor nets of telecommunications devices. As a modelling environment was obtained Proteus software. In processes of modelling of the system, structure and a block diagram of the system were developed, each of elements is deleted to parts of the system and separately described. Specially created software for the research system. The structure of the system developed and software tested by modelling processes. The results of modelling of monitoring system presented in a virtual terminal, an oscillography, and a …

Poetry For Seers Or The Peruvian Visual Poetic Tradition In Front Of New Media, Michael Hurtado, Pamela Medina, Enrique García, Michael Prado

Electronic Literature Organization Conference 2020

Since the first decades of the twentieth century, Peruvian poetic tradition has been characterized by experimental uses of language. Among these possibilities, some records tensioned this medium from the link with the plastic arts, as in the case of the poetry of José María Eguren, while others opted for the playing with the spatiality and visuality of the blank sheet, such as in the case of the work of Carlos Oquendo de Amat. However, it is not until the appearance of the poetry of César Vallejo, specifically with a poems like Trilce in 1922, that these breakages force us to …

From Ai With Love: Reading Big Data Poetry Through Gilbert Simondon’S Theory Of Transduction, Andrew Klobucar

Electronic Literature Organization Conference 2020

Computation initiated a far-reaching re-imagination of language, not just as an information tool, but as a social, bio-physical activity in general. Modern lexicology provides an important overview of the ongoing development of textual documentation and its applications in relation to language and linguistics. At the same time, the evolution of lexical tools from the first dictionaries and graphs to algorithmically generated scatter plots of live online interaction patterns has been surprisingly swift. Modern communication and information studies from Norbert Weiner to the present-day support direct parallels between coding and linguistic systems. However, most theories of computation as a model of …