Computer Sciences Commons^™

Analyzing Sensor Based Human Activity Data Using Time Series Segmentation To Determine Sleep Duration, Yogesh Deepak Lad

Masters Theses

"Sleep is the most important thing to rest our brain and body. A lack of sleep has adverse effects on overall personal health and may lead to a variety of health disorders. According to Data from the Center for disease control and prevention in the United States of America, there is a formidable increase in the number of people suffering from sleep disorders like insomnia, sleep apnea, hypersomnia and many more. Sleep disorders can be avoided by assessing an individual's activity over a period of time to determine the sleep pattern and duration. The sleep pattern and duration can be …

Exploring Management Practices Of The Health Care System For Contractors, Gary L. Williams

Walden Dissertations and Doctoral Studies

Researchers have found that military members serving in war experienced changes in physical and mental health. Military members' healthcare is managed by the Department of Defense. The problem was that management practices of the system for providing long-term healthcare for employees of a contracting company working in foreign combat zones is either minimal or nonexistent. The purpose of this case study was to explore ways that contractor managers and government managers can work together to provide healthcare for those contract employees who will be deployed with the U.S. military. The primary research question was to determine what managers of contractors …

Strategies To Manage Cloud Computing Operational Costs, Frankie Nii A Sackey

Walden Dissertations and Doctoral Studies

Information technology (IT) managers worldwide have adopted cloud computing because of its potential to improve reliability, scalability, security, business agility, and cost savings; however, the rapid adoption of cloud computing has created challenges for IT managers, who have reported an estimated 30% wastage of cloud resources. The purpose of this single case study was to explore successful strategies and processes for managing infrastructure operations costs in cloud computing. The sociotechnical systems (STS) approach was the conceptual framework for the study. Semistructured interviews were conducted with 6 IT managers directly involved in cloud cost management. The data were analyzed using a …

Complexity Theory Of Leadership And Management Information, Mark Aloysius Simpson

Walden Dissertations and Doctoral Studies

Implementing effective leadership strategies in management of information systems (MIS) can positively influence overall organizational performance. This study was an exploration of the general problem of failure to lead effectively in the current knowledge-based economy and the resulting deleterious effects on organizational performance and threats to continuing organizational viability. The specific problem was the lack of understanding regarding the interaction of leadership processes with MIS functions and the impact on organizational success. Managers' and employees' lived experiences of leadership in small- to medium-sized enterprises were explored, as well as how those experiences influenced the organization's adaptive responses regarding technology and …

Small Business Owners' Search For Profitability Under The Affordable Care Act, Alton Simpson

Walden Dissertations and Doctoral Studies

Health care costs for small businesses have been rising annually for the past few decades. Congress voted to pass the Affordable Care Act (ACA) to lower the cost of health care in 2010. The purpose of this phenomenological study was to explore small business owners' experiences in implementing ACA requirements and how the ACA affects small businesses as their owners work to make these organizations profitable. Complex adaptive systems theory formed the conceptual framework for this study Data were gathered during face-to-face and telephone interviews with a sample of 20 small business owners in the Philadelphia region. The research questions …

A Recurrent Neural Network Architecture For Biomedical Event Trigger Classification, Jeevith Bopaiah

Theses and Dissertations--Computer Science

A “biomedical event” is a broad term used to describe the roles and interactions between entities (such as proteins, genes and cells) in a biological system. The task of biomedical event extraction aims at identifying and extracting these events from unstructured texts. An important component in the early stage of the task is biomedical trigger classification which involves identifying and classifying words/phrases that indicate an event. In this thesis, we present our work on biomedical trigger classification developed using the multi-level event extraction dataset. We restrict the scope of our classification to 19 biomedical event types grouped under four broad …

Deep Probabilistic Models For Camera Geo-Calibration, Menghua Zhai

Theses and Dissertations--Computer Science

The ultimate goal of image understanding is to transfer visual images into numerical or symbolic descriptions of the scene that are helpful for decision making. Knowing when, where, and in which direction a picture was taken, the task of geo-calibration makes it possible to use imagery to understand the world and how it changes in time. Current models for geo-calibration are mostly deterministic, which in many cases fails to model the inherent uncertainties when the image content is ambiguous. Furthermore, without a proper modeling of the uncertainty, subsequent processing can yield overly confident predictions. To address these limitations, we propose …

Software Safety And Security Risk Mitigation In Cyber-Physical Systems, Miklos Biro, Atif Mashkoor, Johannes Sametinger, Remzi Seker

Publications

Cyber-physical systems (CPSs) offer many opportunities but pose many challenges--especially regarding functional safety, cybersecurity, and their interplay, as well as the systems' impact on society. Consequently, new methods and techniques are needed for CPS development and assurance. This article [and issue] aims to address some of these challenges.

Blockchain: A New Type Of Database, Brent Marshall

A with Honors Projects

The blockchain is a new technology that seems to have people all over the world talking about it. But what is it? And what can it do? This paper will explore both the current uses of block chain technology and its potential uses. We will begin with definitions, followed by the history and uses of blockchains.

Structurally Defined Conditional Data-Flow Static Analysis, Elena Sherman, Matthew B. Dwyer

Computer Science Faculty Publications and Presentations

Data flow analysis (DFA) is an important verification technique that computes the effect of data values propagating over program paths. While more precise than flow-insensitive analyses, such an analysis is time-consuming.

This paper investigates the acceleration of DFA by structural decomposition of the underlying control flow graph. Specifically, we explore the cost and effectiveness of dividing program paths into subsets by partitioning path suffixes at conditional statements, applying a DFA on each subset, and then combining the resulting invariants. This yields a family of independent DFA problems that are solved in parallel and where the partial results of each problem …

The Lkpy Package For Recommender Systems Experiments, Michael D. Ekstrand

Computer Science Faculty Publications and Presentations

Since 2010, we have built and maintained LensKit, an open-source toolkit for building, researching, and learning about recommender systems. We have successfully used the software in a wide range of recommender systems experiments, to support education in traditional classroom and online settings, and as the algorithmic backend for user-facing recommendation services in movies and books. This experience, along with community feedback, has surfaced a number of challenges with LensKit’s design and environmental choices. In response to these challenges, we are developing a new set of tools that leverage the PyData stack to enable the kinds of research experiments and educational …

Monte Carlo Estimates Of Evaluation Metric Error And Bias: Work In Progress, Mucun Tian, Michael D. Ekstrand

Computer Science Faculty Publications and Presentations

Traditional offline evaluations of recommender systems apply metrics from machine learning and information retrieval in settings where their underlying assumptions no longer hold. This results in significant error and bias in measures of top-N recommendation performance, such as precision, recall, and nDCG. Several of the specific causes of these errors, including popularity bias and misclassified decoy items, are well-explored in the existing literature. In this paper we survey a range of work on identifying and addressing these problems, and report on our work in progress to simulate the recommender data generation and evaluation processes to quantify the extent of …

Retrieving And Recommending For The Classroom: Stakeholders, Objectives, Resources, And Users, Michael D. Ekstrand, Ion Madrazo Azpiazu, Katherine Landau Wright, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

In this paper, we consider the promise and challenges of deploying recommendation and information retrieval technology to help teachers locate resources for use in classroom instruction. The classroom setting is a complex environment presenting a number of challenges for recommendation, due to its inherent multi-stakeholder nature, the multiple objectives that quality educational resources and experiences must simultaneously satisfy, and potential disconnect between the direct user of the system and the end users of the resources it provides. In this paper, we outline these challenges, highlight opportunities for new research, and describe our work in progress in this area including insights …

Inverse Tree-Olap: Definition, Complexity And First Solution, Domenico Saccà, Edoardo Serra, Alfredo Cuzzocrea

Computer Science Faculty Publications and Presentations

Count constraint is a data dependency that requires the results of given count operations on a relation to be within a certain range. By means of count constraints a new decisional problem, called the Inverse OLAP, has been recently introduced: given a flat fact table, does there exist an instance satisfying a set of given count constraints? This paper focus on a special case of Inverse OLAP, called Inverse Tree-OLAP, for which the flat fact table key is modeled by a Dimensional Fact Model (DFM) with a tree structure.

From Recommendation To Curation: When The System Becomes Your Personal Docent, Nevena Dragovic, Ion Madrazo Azpiazu, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Curation is the act of selecting, organizing, and presenting content. Some applications emulate this process by turning users into curators, while others use recommenders to select items, seldom achieving the focus or selectivity of human curators. We bridge this gap with a recommendation strategy that more closely mimics the objectives of human curators. We consider multiple data sources to enhance the recommendation process, as well as the quality and diversity of the provided suggestions. Further, we pair each suggestion with an explanation that showcases why a book was recommended with the aim of easing the decision making process for the …

Broncovote: Secure Voting System Using Ethereum’S Blockchain, Gaby G. Dagher, Praneeth Babu Marella, Matea Milojkovic, Jordan Mohler

Computer Science Faculty Publications and Presentations

Voting is a fundamental part of democratic systems; it gives individuals in a community the faculty to voice their opinion. In recent years, voter turnout has diminished while concerns regarding integrity, security, and accessibility of current voting systems have escalated. E-voting was introduced to address those concerns; however, it is not cost-effective and still requires full supervision by a central authority. The blockchain is an emerging, decentralized, and distributed technology that promises to enhance different aspects of many industries. Expanding e-voting into blockchain technology could be the solution to alleviate the present concerns in e-voting. In this paper, we propose …

2nd Fatrec Workshop: Responsible Recommendation, Toshihiro Kamishima, Pierre-Nicolas Schwab, Michael D. Ekstrand

Computer Science Faculty Publications and Presentations

The second Workshop on Responsible Recommendation (FATREC 2018) was held in conjunction with the 12th ACM Conference on Recommender Systems on October 6th, 2018 in Vancouver, Canada. This full-day workshop brought together researchers and practitioners to discuss several topics under the banner of social responsibility in recommender systems: fairness, accountability, transparency, privacy, and other ethical and social concerns.

Predicting Perceived Age: Both Language Ability And Appearance Are Important, Sarah Plane, Ariel Marvasti, Tyler Egan, Casey Kennington

Computer Science Faculty Publications and Presentations

When interacting with robots in a situated spoken dialogue setting, human dialogue partners tend to assign anthropomorphic and social characteristics to those robots. In this paper, we explore the age and educational level that human dialogue partners assign to three different robotic systems, including an un-embodied spoken dialogue system. We found that how a robot speaks is as important to human perceptions as the way the robot looks. Using the data from our experiment, we derived prosodic, emotional, and linguistic features from the participants to train and evaluate a classifier that predicts perceived intelligence, age, and education level.

A Certificateless One-Way Group Key Agreement Protocol For End-To-End Email Encryption, Jyh-Haw Yeh, Srisarguru Sridhar, Gaby G. Dagher, Hung-Min Sun, Ning Shen, Kathleen Dakota White

Computer Science Faculty Publications and Presentations

Over the years, email has evolved into one of the most widely used communication channels for both individuals and organizations. However, despite near ubiquitous use in much of the world, current information technology standards do not place emphasis on email security. Not until recently, webmail services such as Yahoo's mail and Google's gmail started to encrypt emails for privacy protection. However, the encrypted emails will be decrypted and stored in the service provider's servers. If the servers are malicious or compromised, all the stored emails can be read, copied and altered. Thus, there is a strong need for end-to-end (E2E) …

Field-Verified Integrated Eaf-Svc-Electrode Positioning Model Simulation And Anovel Hybrid Series Compensation Control For Eaf, Ahmed Hassan, Amr Abou-Ghazala, Ashraf Megahed

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, modeling and simulation of a typical steel-making network are realized using MATLAB Simulink environment and validated using trends collected from an actual steel plant. The models integrate different reactions between an electric arc furnace (EAF), a static Var compensator, and electrode positioning systems according to a previously introduced theory of operations. In addition, the conventional electrode positioning control performance is compared with the new hybrid series compensation control method to demonstrate the superiority of the new method regarding system response. With help of the proposed series compensation, the reference resistance value was restored 2.5 s faster than …

A Novel Efficient Tsv Built-In Test For Stacked 3d Ics, Badi Guibane, Belgacem Hamdi, Brahim Ben Salem, Abdellatif Mtibaa

Turkish Journal of Electrical Engineering and Computer Sciences

A through-silicon via (TSV) is established as the main enabler for a three-dimensional integrated circuit (3D IC) that increases system density and compactness. The exponential increase in TSV density led to TSV-induced catastrophic and parametric faults. We propose an original architecture that detects errors caused by TSV manufacturing defects. The proposed design for testability is a built-in technique that detects errors in an early manufacturing stage and is hence very economically attractive. The proposal is capable of testing each and every TSV in the network. The technique achieves high fault coverage and high observability.

New Trends In Second Language Learning And Teaching Through The Lens Of Ict, Networked Learning, And Artificial Intelligence, Jaya Kannan, Pilar Munday

Languages Faculty Publications

In the last few decades, Information and Communications Technology (ICT) applications have been shaping the field of Computer Assisted Language Learning (CALL). Mobile Assisted Language Learning (MALL) paved the way for ubiquitous learning. The advent of new technologies in the early 21st century also added a social dimension to ICT that allowed for Networked Learning (NL). Given that language learning is fundamentally a socio-cultural experience, networked learning capabilities have provided the potential for language learning in community settings. This has revitalized the earlier frameworks provided by CALL. NL has empowered language learners today to connect globally, to access Open Educational …

A Bi-Level Heuristic Solution For The Nurse Scheduling Problem Based On Shift-Swapping, Ahmed Youssef, Samah Senbel

School of Computer Science & Engineering Faculty Publications

This paper presents a new heuristic solution to the well-known Nurse Scheduling Problem (NSP). The NSP has a lot of constraints to satisfy. Some are mandatory and specified by the hospital administration, these are known as hard constraints. Some constraints are put by the nurses themselves to produce a comfortable schedule for themselves, and these are known as soft constraints. Our solution is based on the practice of shift swapping done by nurses after they receive an unsatisfactory schedule. The constraints are arranged in order of importance. Our technique works on two levels, first we generate a schedule that satisfies …

.Net Core Kundrejt Express Js Si Framework Për Zhvillim Modern Të Web - It, Rrezon Hasani

Theses and Dissertations

Ky punim ka për qëllim të identifikoj avantazhet dhe disavantazhet e Asp.Net Core kundrejt Express js, si dhe ndryshimet dhe qasjet që kanë këta dy frameworks për zhvillim modern të web –it. Pikat ku do të krahasohen Asp.Net Core dhe Express js janë: Instalimi, Ekosistemi dhe Performanca, Komuniteti i Zhvilluesve dhe Forumet për këta frameworks. Mënyrat e krahasimit janë bërë nepërmjet zhvillimit, testimit, demonstrimit të kodit si dhe statistikave të marra nga Interneti. Rezultatet e këtijë punimi do të ndihmojnë zhvilluesit në përzgjedhjen e frameworkut ndërmjet Asp.Net Core dhe Express js në projektet e tyre në bazë të krahasimeve që …

Extensions Of The Morse-Hedlund Theorem, Eben Blaisdell

Honors Theses

Bi-infinite words are sequences of characters that are infinite forwards and backwards; for example "...ababababab...". The Morse-Hedlund theorem says that a bi-infinite word f repeats itself, in at most n letters, if and only if the number of distinct subwords of length n is at most n. Using the example, "...ababababab...", there are 2 subwords of length 3, namely "aba" and "bab". Since 2 is less than 3, we must have that "...ababababab..." repeats itself after at most 3 letters. In fact it does repeat itself every two letters. …

Old English Character Recognition Using Neural Networks, Sattajit Sutradhar

College of Graduate Studies: Theses & Dissertations

Character recognition has been capturing the interest of researchers since the beginning of the twentieth century. While the Optical Character Recognition for printed material is very robust and widespread nowadays, the recognition of handwritten materials lags behind. In our digital era more and more historical, handwritten documents are digitized and made available to the general public. However, these digital copies of handwritten materials lack the automatic content recognition feature of their printed materials counterparts. We are proposing a practical, accurate, and computationally efficient method for Old English character recognition from manuscript images. Our method relies on a modern machine learning …

Bi-Objective Optimization Of Kidney Exchanges, Siyao Xu

Theses and Dissertations--Computer Science

Matching people to their preferences is an algorithmic topic with real world applications. One such application is the kidney exchange. The best "cure" for patients whose kidneys are failing is to replace it with a healthy one. Unfortunately, biological factors (e.g., blood type) constrain the number of possible replacements. Kidney exchanges seek to alleviate some of this pressure by allowing donors to give their kidney to a patient besides the one they most care about and in turn the donor for that patient gives her kidney to the patient that this first donor most cares about. Roth et al.~first discussed …

Leveraging Overhead Imagery For Localization, Mapping, And Understanding, Scott Workman

Theses and Dissertations--Computer Science

Ground-level and overhead images provide complementary viewpoints of the world. This thesis proposes methods which leverage dense overhead imagery, in addition to sparsely distributed ground-level imagery, to advance traditional computer vision problems, such as ground-level image localization and fine-grained urban mapping. Our work focuses on three primary research areas: learning a joint feature representation between ground-level and overhead imagery to enable direct comparison for the task of image geolocalization, incorporating unlabeled overhead images by inferring labels from nearby ground-level images to improve image-driven mapping, and fusing ground-level imagery with overhead imagery to enhance understanding. The ultimate contribution of this thesis …

Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones

Theses and Dissertations--Computer Science

In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in …

Ultra-Fast And Memory-Efficient Lookups For Cloud, Networked Systems, And Massive Data Management, Ye Yu

Theses and Dissertations--Computer Science

Systems that process big data (e.g., high-traffic networks and large-scale storage) prefer data structures and algorithms with small memory and fast processing speed. Efficient and fast algorithms play an essential role in system design, despite the improvement of hardware. This dissertation is organized around a novel algorithm called Othello Hashing. Othello Hashing supports ultra-fast and memory-efficient key-value lookup, and it fits the requirements of the core algorithms of many large-scale systems and big data applications. Using Othello hashing, combined with domain expertise in cloud, computer networks, big data, and bioinformatics, I developed the following applications that resolve several major …