Computer Sciences Commons^™

Employee Retention Strategies In The Information Technology Industry, Corey Harris

Walden Dissertations and Doctoral Studies

Productivity declines when employees voluntarily leave an organization. The purpose of this case study was to explore strategies that business leaders use to reduce turnover among their skilled information technology (IT) professionals in the Dallas-Fort Worth area. Six business leaders were selected because they had implemented strategies to retain skilled IT professionals. Herzberg's 2-factor theory was the conceptual framework for this doctoral study. Data were collected from semistructured interviews and review of the organization's policies, procedures, and personnel handbook. Data analysis consisted of assembling the data, organizing the data into codes, compiling the data into themes, and interpreting and disclosing …

Initiating Factors Affecting Information Systems Project Success, Jonathan Olubunmi Afolabi

Walden Dissertations and Doctoral Studies

Information systems (IS) projects are complex and costly, but only a 3rd of IS projects are successful; the Standish Group reported that 32% of IS projects were successful in 2012. Although investments in research have led to improvements in practice, there is a general perception that management failures are responsible for the low rate of IS project success. The effects of initiating factors on project outcome had not been sufficiently explored; few IS researchers have explored the initiation phase. The purpose of this grounded theory study was to explore project initiation factors, including relational, as well as decision-making aspects, and …

Swimming In A Sea Of Javascript Or: How I Learned To Stop Worrying And Love High-Fidelity Replay, John A. Berlin, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

[First paragraph] Preserving and replaying modern web pages in high-fidelity has become an increasingly difficult task due to the increased usage of JavaScript. Reliance on server-side rewriting alone results in live-leakage and or the inability to replay a page due to the preserved JavaScript performing an action not permissible from the archive. The current state-of-the-art high fidelity archival preservation and replay solutions rely on handcrafted client-side URL rewriting libraries specifically tailored for the archive, namely Webrecoder's and Pywb's wombat.js [12]. Web archives not utilizing client-side rewriting rely on server-side rewriting that misses URLs used in a manner not accounted for …

A Survey Of Archival Replay Banners, Sawood Alam, Mat Kelly, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

We surveyed various archival systems to compare and contrast different techniques used to implement an archival replay banner. We found that inline plain HTML injection is the most common approach, but prone to style conflicts. Iframe-based banners are also very common and while they do not have style conflicts, they suffer from screen real estate wastage and limited design choices. Custom Elements-based banners are promising, but due to being a new web standard, these are not yet widely deployed.

Strategies For Applying Electronic Health Records To Achieve Cost Saving Benefits, Daniel Kanyi Ngunyu

Walden Dissertations and Doctoral Studies

The American Recovery and Reinvestment Act (ARRA) of 2009 authorized the distribution of about $30 billion incentive funds to accelerate electronic health record (EHR) applications to improve the quality of care, safety, privacy, care coordination, and patients' involvement in healthcare. EHR use has the potential of saving $731 in costs for hospitals per patient admission; however, most hospitals are not applying EHR to reach the level at which cost savings are possible. The purpose of this single case study was to explore strategies that IT leaders in hospitals can use to apply EHR to achieve the cost saving benefits. The …

Organizational Information Security: Strategies To Minimize Workplace Cyberloafing For Increased Productivity, Hawazin Al Abbasi

Walden Dissertations and Doctoral Studies

Productivity loss occurs in organizations that experience high levels of personal Internet use by employees on company time, which includes employees using smartphones to surf without needing the firm's Internet connection. The purpose of this qualitative phenomenological study was to explore reliable ways for organizational leaders to monitor or limit their employees' use of smartphone technology for personal use (cyberloafing) while on the job to minimize wasted work time. Social cognitive theory, which includes an emphasis on human behavioral changes based upon the environment, people, and behavior, served as the conceptual framework. The general research question was as follows: How …

Social Media Policy To Support Employee Productivity In The Finance Industry, David Shaun Rogers

Walden Dissertations and Doctoral Studies

Business leaders may see social media as a distraction for their workers; however, blocking access could lead to a reduction in productivity. Using social media technologies with knowledge workers could achieve cost reductions for payroll of 30% to 35%. The purpose of this multiple case study was to explore how business leaders used a social media policy to support employee productivity. The conceptual framework for this study was social exchange theory, which supports the notion that dyad and small group interactions make up most interactions, and such interactions enhance employees' productivity. The research question was to explore how finance industry …

Evaluating A Cluster Of Low-Power Arm64 Single-Board Computers With Mapreduce, Daniel Mcdermott

EWU Masters Thesis Collection

With the meteoric rise of enormous data collection in science, industry, and the cloud, methods for processing massive datasets have become more crucial than ever. MapReduce is a restricted programing model for expressing parallel computations as simple serial functions, and an execution framework for distributing those computations over large datasets residing on clusters of commodity hardware. MapReduce abstracts away the challenging low-level synchronization and scalability details which parallel and distributed computing often necessitate, reducing the concept burden on programmers and scientists who require data processing at-scale. Typically, MapReduce clusters are implemented using inexpensive commodity hardware, emphasizing quantity over quality due …

Determining Vulnerability Using Attach Graphs: An Expansion Of The Current Fair Model, Beth M. Anderson

EWU Masters Thesis Collection

Factor Analysis of Information Risk (FAIR) provides a framework for measuring and understanding factors that contribute to information risk. One such factor is FAIR Vulnerability; the probability that an event involving a threat will result in a loss. An asset is vulnerable if a threat actor’s Threat Capability is higher than the Resistance Strength of the asset. In FAIR scenarios, Resistance Strength is currently estimated for entire assets, oversimplifying assets containing individual systems and the surrounding environment. This research explores enhancing estimations of FAIR Vulnerability by modeling interactions between threat actors and assets through attack graphs. By breaking down the …

Client-Assisted Memento Aggregation Using The Prefer Header, Mat Kelly, Sawood Alam, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

[First paragraph] Preservation of the Web ensures that future generations have a picture of how the web was. Web archives like Internet Archive's Wayback Machine, WebCite, and archive.is allow individuals to submit URIs to be archived, but the captures they preserve then reside at the archives. Traversing these captures in time as preserved by multiple archive sources (using Memento [8]) provides a more comprehensive picture of the past Web than relying on a single archive. Some content on the Web, such as content behind authentication, may be unsuitable or inaccessible for preservation by these organizations. Furthermore, this content may be …

Anatomy Of Online Hate: Developing A Taxonomy And Machine Learning Models For Identifying And Classifying Hate In Online News Media, Joni Salminen, Hind Almerekhi, Milica Milenkovic, Soon-Gyu Jung, Haewoon Kwak, Haewoon Kwak, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

Online social media platforms generally attempt to mitigate hateful expressions, as these comments can be detrimental to the health of the community. However, automatically identifying hateful comments can be challenging. We manually label 5,143 hateful expressions posted to YouTube and Facebook videos among a dataset of 137,098 comments from an online news media. We then create a granular taxonomy of different types and targets of online hate and train machine learning models to automatically detect and classify the hateful comments in the full dataset. Our contribution is twofold: 1) creating a granular taxonomy for hateful online comments that includes both …

Skylens: Visual Analysis Of Skyline On Multi-Dimensional Data, Xun Zhao, Yanhong Wu, Weiwei Cui, Xinnan Du, Yuan Chen, Yong Wang, Dik Lun Lee, Huamin Qu

Research Collection School Of Computing and Information Systems

Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e.. the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points …

Estimating The Optimal Cutoff Point For Logistic Regression, Zheng Zhang

Open Access Theses & Dissertations

Binary classification is one of the main themes of supervised learning. This research is concerned about determining the optimal cutoff point for the continuous-scaled outcomes (e.g., predicted probabilities) resulting from a classifier such as logistic regression. We make note of the fact that the cutoff point obtained from various methods is a statistic, which can be unstable with substantial variation. Nevertheless, due partly to complexity involved in estimating the cutpoint, there has been no formal study on the variance or standard error of the estimated cutoff point.

In this Thesis, a bootstrap aggregation method is put forward to estimate the …

Breadcrumbs: Privacy As A Privilege, Prachi Bhardwaj

Capstones

Breadcrumbs: Privacy as a Privilege Abstract

By: Prachi Bhardwaj

In 2017, the world saw more data breaches than in any year prior. The count was more than the all-time high record in 2016, which was 40 percent more than the year before that.

That’s because consumer data is incredibly valuable today. In the last three decades, data storage has gone from being stored physically to being stored almost entirely digitally, which means consumer data is more accessible and applicable to business strategies. As a result, companies are gathering data in ways previously unknown to the average consumer, and hackers are …

Introduction To The Usu Library Of Solutions To The Einstein Field Equations, Ian M. Anderson, Charles G. Torre

Tutorials on... in 1 hour or less

This is a Maple worksheet providing an introduction to the USU Library of Solutions to the Einstein Field Equations. The library is part of the DifferentialGeometry software project and is a collection of symbolic data and metadata describing solutions to the Einstein equations.

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

School of Computing: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

Altering The Expression Of Artemisinin Through Osmotic Manipulation, Tyler Friesen

Theses/Capstones/Creative Projects

Artemisinin is an anti-malarial drug used in combination therapy to treat all malarial parasites in the blood stage. The expression of artemisinin within the plant Artemisia annua is only 1% of the dry weight. Methods for increasing the level of artemisinin within the plant were proposed. This paper looks into finding homologous enzymes across multiple species in order to find species where genetic manipulations will be useful. The second part of this paper looks at the use of osmotic stress to increase the reactive oxygen species in order to increase the amount of artemisinin within the plant. The database portion …

Ethics And Bias In Machine Learning: A Technical Study Of What Makes Us “Good”, Ashley Nicole Shadowen

Student Theses

The topic of machine ethics is growing in recognition and energy, but bias in machine learning algorithms outpaces it to date. Bias is a complicated term with good and bad connotations in the field of algorithmic prediction making. Especially in circumstances with legal and ethical consequences, we must study the results of these machines to ensure fairness. This paper attempts to address ethics at the algorithmic level of autonomous machines. There is no one solution to solving machine bias, it depends on the context of the given system and the most reasonable way to avoid biased decisions while maintaining the …

Proactive Sequential Resource (Re)Distribution For Improving Efficiency In Urban Environments, Supriyo Ghosh

Dissertations and Theses Collection (Open Access)

Due to the increasing population and lack of coordination, there is a mismatch in supply and demand of common resources (e.g., shared bikes, ambulances, taxis) in urban environments, which has deteriorated a wide variety of quality of life metrics such as success rate in issuing shared bikes, response times for emergency needs, waiting times in queues etc. Thus, in my thesis, I propose efficient algorithms that optimise the quality of life metrics by proactively redistributing the resources using intelligent operational (day-to-day) and strategic (long-term) decisions in the context of urban transportation and health & safety. For urban transportation, Bike Sharing …

Online Learning With Nonlinear Models, Doyen Sahoo

Dissertations and Theses Collection (Open Access)

Recent years have witnessed the success of two broad categories of machine learning algorithms: (i) Online Learning; and (ii) Learning with nonlinear models. Typical machine learning algorithms assume that the entire data is available prior to the training task. This is often not the case in the real world, where data often arrives sequentially in a stream, or is too large to be stored in memory. To address these challenges, Online Learning techniques evolved as a promising solution to having highly scalable and efficient learning methodologies which could learn from data arriving sequentially. Next, as the real world data exhibited …

Policy Analytics For Environmental Sustainability: Household Hazardous Waste And Water Impacts Of Carbon Pollution Standards, Kustini

Dissertations and Theses Collection (Open Access)

Policy analytics are essential in supporting more informed policy-making in environmental management. This dissertation employs a fusion of machine methods and explanatory empiricism that involves data analytics, math programming, optimization, econometrics, geospatial and spatiotemporal analysis, and other approaches for assessing and evaluating current and future environmental policies.
Essay 1 discusses household informedness and its impact on the collection and recycling of household hazardous waste (HHW). Household informedness is the degree to which households have the necessary information to make utility-maximizing decisions about the handling of their waste. Such informedness seems to be influenced by HHW public education and environmental quality …

Leveraging The Trade-Off Between Accuracy And Interpretability In A Hybrid Intelligent System, Di Wang, Chai Quek, Ah-Hwee Tan, Chunyan Miao, Geok See Ng, You Zhou

Research Collection School Of Computing and Information Systems

Neural Fuzzy Inference System (NFIS) is a widely adopted paradigm to develop a data-driven learning system. This hybrid system has been widely adopted due to its accurate reasoning procedure and comprehensible inference rules. Although most NFISs primarily focus on accuracy, we have observed an ever increasing demand on improving the interpretability of NFISs and other types of machine learning systems. In this paper, we illustrate how we leverage the trade-off between accuracy and interpretability in an NFIS called Genetic Algorithm and Rough Set Incorporated Neural Fuzzy Inference System (GARSINFIS). In a nutshell, GARSINFIS self-organizes its network structure with a small …

On Modeling Sense Relatedness In Multi-Prototype Word Embedding, Yixin Cao, Juanzi Li, Jiaxin Shi, Zhiyuan Liu, Chengjiang Li

Research Collection School Of Computing and Information Systems

To enhance the expression ability of distributional word representation learning model, many researchers tend to induce word senses through clustering, and learn multiple embedding vectors for each word, namely multi-prototype word embedding model. However, most related work ignores the relatedness among word senses which actually plays an important role. In this paper, we propose a novel approach to capture word sense relatedness in multi-prototype word embedding model. Particularly, we differentiate the original sense and extended senses of a word by introducing their global occurrence information and model their relatedness through the local textual context information. Based on the idea of …

Secure Server-Aided Top-K Monitoring, Yujue Wang, Hwee Hwa Pang, Yanjiang Yang, Xuhua Ding

Research Collection School Of Computing and Information Systems

In a data streaming model, a data owner releases records or documents to a set of users with matching interests, in such a way that the match in interest can be calculated from the correlation between each pair of document and user query. For scalability and availability reasons, this calculation is delegated to third-party servers, which gives rise to the need to protect the integrity and privacy of the documents and user queries. In this paper, we propose a server-aided data stream monitoring scheme (DSM) to address the aforementioned integrity and privacy challenges, so that the users are able to …

Using Data Analytics For Discovering Library Resource Insights: Case From Singapore Management University, Ning Lu, Rui Song, Dina Li Gwek Heng, Swapna Gottipati, Aaron Tay

Research Collection School Of Computing and Information Systems

Library resources are critical in supporting teaching, research and learning processes. Several universities have employed online platforms and infrastructure for enabling the online services to students, faculty and staff. To provide efficient services by understanding and predicting user needs libraries are looking into the area of data analytics. Library analytics in Singapore Management University is the project committed to provide an interface for data-intensive project collaboration, while supporting one of the library’s key pillars on its commitment to collaborate on initiatives with SMU Communities and external groups. In this paper, we study the transaction logs for user behavior analysis that …

D-Watch: Embracing “Bad” Multipaths For Device-Free Localization With Cots Rfid Devices, Ju Wang, Jie Xiong, Hongbo Jiang, Xiaojiang Chen, Dingyi Fang

Research Collection School Of Computing and Information Systems

Device-free localization, which does not require any device attached to the target, is playing a critical role in many applications, such as intrusion detection, elderly monitoring and so on. This paper introduces D-Watch, a device-free system built on the top of low cost commodity-off-the-shelf RFID hardware. Unlike previous works which consider multipaths detrimental, D-Watch leverages the ''bad'' multipaths to provide a decimeter-level localization accuracy without offline training. D-Watch harnesses the angle-of-arrival information from the RFID tags' backscatter signals. The key intuition is that whenever a target blocks a signal's propagation path, the signal power experiences a drop which can be …

Leveraging Auxiliary Tasks For Document-Level Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we study domain adaptationwith a state-of-the-art hierarchicalneural network for document-level sentimentclassification. We first design a newauxiliary task based on sentiment scoresof domain-independent words. We thenpropose two neural network architecturesto respectively induce document embeddingsand sentence embeddings that workwell for different domains. When thesedocument and sentence embeddings areused for sentiment classification, we findthat with both pseudo and external sentimentlexicons, our proposed methods canperform similarly to or better than severalhighly competitive domain adaptationmethods on a benchmark dataset of productreviews.

Using Teaching Cases For Achieving Bloom’S High-Order Cognitive Levels: An Application In Technically-Oriented Information Systems Course, Kar Way Tan

Research Collection School Of Computing and Information Systems

Case-teaching has been an attractive pedagogy method for bringing in real-world examples into the classroom. However, it is challenging to introduce cases to address high-order cognitive skills such as analyzing and creating new IT solutions in technically-oriented computing course. In this research, we present our experience in introducing three types of case studies -- Story-Telling case, Design-and-Problem-Solving case, and Create-Design-Implement case to a course in an undergraduate Information Systems programme. For each case study, we plan and map the learning objectives to address various cognitive levels in the revised Bloom’s Taxonomy. Using surveys conducted over two academic years, we show …

Btci: A New Framework For Identifying Congestion Cascades Using Bus Trajectory Data, Meng-Fen Chiang, Ee Peng Lim, Wang-Chien Lee, Agus Trisnajaya Kwee

Research Collection School Of Computing and Information Systems

The knowledge of traffic health status is essential to the general public and urban traffic management. To identify congestion cascades, an important phenomenon of traffic health, we propose a Bus Trajectory based Congestion Identification (BTCI) framework that explores the anomalous traffic health status and structure properties of congestion cascades using bus trajectory data. BTCI consists of two main steps, congested segment extraction and congestion cascades identification. The former constructs path speed models from historical vehicle transitions and design a non-parametric Kernel Density Estimation (KDE) function to derive a measure of congestion score. The latter aggregates congested segments (i.e., those with …

Analyzing The E-Learning Video Environment Requirements Of Generation Z Students Using Echo360 Platform, Swapna Gottipati, Venky Shankararaman

Research Collection School Of Computing and Information Systems

As with any other generational cohort,Generation Z students have their own unique characteristics that influencetheir approach to learning process. They are the future workforce and severalefforts are undertaken by Government and education institutes to consider thecharacteristics of Gen-Z in developing the curriculum and teaching environmentsuitable for these students. E-learning plays a key role in students learningprocess and has been widely adopted by many education institutions. Inparticular, videos play a major role in the learning process of Gen-Zstudents. The purpose of this paper isto focus the on requirements of Gen-Z students and to provide suggestions forhow to create a e-learning video …