Data Storage Systems Commons^™

Towards A Taxonomy Of Challenges In An Integrated It Governance Framework Implementation, Mathew Nicho, Suadad Muamaar

Journal of International Technology and Information Management

The rapid adoption of IT governance (ITG) frameworks in organizations worldwide, along with the subsequent need to select and integrate overlapping ITG frameworks has presented practitioners with challenges in choice and integration of frameworks. In this respect, the purpose of this study was to explore the ITG frameworks integration (ITGFI) challenges faced by organizations worldwide; develop and test a theory-based integrated ITG challenges (IIC) taxonomy model created from extant literature; and validate and compare these with those empirically extracted from three case studies in the United Arab Emirates (UAE). The results present the audience with a taxonomy of a prioritized …

Comparative Empirical Analysis On Computer Software Piracy Behaviors Between China And The United States: An Exploratory Study, Xiang Fang, Sooun Lee

Journal of International Technology and Information Management

Using the data collected from several universities in China and the United States, which have drastically different piracy rates, economic development stages, income levels, and national cultures, this study aims to identify which demographic factors affect software piracy significantly. Totally, the dataset includes 600 valid responses. Multivariate data analysis, supported by Multivariate Analysis of Variance and Turkey’s test, reveals that among various factors, country difference and gender most significantly influence software piracy. In addition, this study offers recommendations on how to curb software piracy effectively.

Outlier Detection In Complex Categorical Data By Modeling The Feature Value Couplings, Guansong Pang, Longbing Cao, Ling Chen

Research Collection School Of Computing and Information Systems

This paper introduces a novel unsupervised outlier detection method, namely Coupled Biased Random Walks (CBRW), for identifying outliers in categorical data with diversified frequency distributions and many noisy features. Existing pattern-based outlier detection methods are ineffective in handling such complex scenarios, as they misfit such data. CBRW estimates outlier scores of feature values by modelling feature value level couplings, which carry intrinsic data characteristics, via biased random walks to handle this complex data. The outlier scores of feature values can either measure the outlierness of an object or facilitate the existing methods as a feature weighting and selection indicator. Substantial …

Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu

Research Collection School Of Computing and Information Systems

Nowadays an increasing amount of data stored in the public cloud need to be searched remotely for fast accessing. For the sake of privacy, the remote files are usually encrypted, which makes them difficult to be searched by remote servers. It is also harder to efficiently share encrypted data in the cloud than those in plaintext. In this paper, we develop a searchable encryption framework called Linear Encryption with Keyword Search (LEKS) that can semi-generically convert some existing encryption schemes meeting our Linear Encryption Template (LET) to be searchable without re-encrypting all the data. For allowing easy data sharing, we …

Wearable Ekg, Cale Hopkins, Tanner Papenfuss, Travis E. Michael

Computer Engineering

No abstract provided.

Stand, Lisa Yip

Computer Engineering

With busy lives, people sometimes forget to take breaks for multiple hours at a time. The purpose of this project is to remind the user to move around every hour if they have not already. To do so, stand will be a light weight fitness tracker that will detect the number of steps made within an hour. If the step count, dependent on goals, is not met then a vibration motor will gently remind them to take a break and walk. The data throughout the day will be shown on an iOS application where the user will be able to …

Polyfs Visualizer, Paul Martin Fallon

Master's Theses

One of the most important operating system topics, file systems, control how we store and access data and form a key point in a computer scientists understanding of the underlying mechanisms of a computer. However, file systems, with their abstract concepts and lack of concrete learning aids, is a confusing subjects for students. Historically at Cal Poly, the CPE 453 Introduction to Operating Systems has been on of the most failed classes in the computing majors, leading to the need for better teaching and learning tools. Tools allowing students to gain concrete examples of abstract concepts could be used to …

Energetic Behavior Of Resistive Random-Access Memory Cells, Christopher M. Bisbee

Macalester Journal of Physics and Astronomy

In order to investigate the switching characteristics of Resistive Random Access Memory cells (ReRAM) in terms of their thermodynamic free energy properties, we need to build a number of models that replicate the system. This report contains the models used to investigate filament growth patterns based on different boundary conditions applied to the electrode-filament system. Using Comsol Multiphysics software, we determined that when a fixed voltage is applied to each electrode in the electrode-filament system, we should expect filament dissolution that resets our cells into the High Resistance State (HRS). If we instead fix a set amount of charge on …

A Study Of Three Paradigms For Storing Geospatial Data: Distributed-Cloud Model, Relational Database, And Indexed Flat File, Matthew A. Toups

LSU New Orleans Theses and Dissertations

Geographic Information Systems (GIS) and related applications of geospatial data were once a small software niche; today nearly all Internet and mobile users utilize some sort of mapping or location-aware software. This widespread use reaches beyond mere consumption of geodata; projects like OpenStreetMap (OSM) represent a new source of geodata production, sometimes dubbed “Volunteered Geographic Information.” The volume of geodata produced and the user demand for geodata will surely continue to grow, so the storage and query techniques for geospatial data must evolve accordingly.

This thesis compares three paradigms for systems that manage vector data. Over the past few decades …

The Utilization Of Mobile Technology For Crime Scene Investigation In The San Francisco Bay Area, Marc Logrande

Themis: Research Journal of Justice Studies and Forensic Science

The research presented aims to explore factors affecting the decision to adopt a mobile crime scene investigation application in police departments throughout the San Francisco Bay Area. To accomplish this goal, the mobile technology acceptance model was used in designing a survey for data collection. This model utilizes four categories to interpret the factors that influence a police officer’s decision to accept or reject mobile technologies: performance, security and reliability, management style, and cognitive acceptance. Nine police departments were sampled through a series of in-person and over-the-phone interviews to obtain data regarding factors affecting the adoption of a mobile crime …

Eliminating Data Redundancy: Our Solution For Database Discovery Using Alma/Primo, Jacob Kindle, Travis Clamon

ETSU Faculty Works

East Tennessee State University recently adopted Alma & Primo and was suprised by the lack of an A-Z database discovery module. Frustrated by having to maintain electronic resources separately on our library website and in Alma, we embarked on a goal to eliminate redundancy and use Alma/Primo exclusively. This presentation will cover our entire workflow in both Alma & Primo and the issues we encountered along the way. I'll first go over our process in Alma including MARC record creation, electronic collection setup, and the top level collection module. Next, I'll cover our workflow in Primo including normalization rules, scoping, …

Factors Affecting Big Data Technology Adoption, Nayem Rahman

Student Research Symposium

With the advancement of computer science, hardware and software engineering, and computing power, and later with the advent of the internet, social networking tools and other sources such as sensors data growth has increased significantly. These data are called big data which are mostly unstructured, generated in large volumes, data need to be captured in near real-time. To handle big data a completely new set of tools and technologies are being emerged. I have studied big data literature to identify the factors that might influence big data adoption. I was able to list quite a few factors or attributes that …

Uav As A Service: Providing On-Demand Access And On-The-Fly Retasking Of Multi-Tenant Uavs Using Cloud Services, Justin Yapp

Doctoral Dissertations and Master's Theses

As commercial roles for Unmanned Aerial Vehicles (UAVs) become more well-defined and demand for the services provided by them increases, UAVs rely more on new cloud computing services and co-operative coordination to provide mission planning, control, tracking and data processing. We present UAV as a Service (UAVaaS) framework, which brings features commonly found in traditional cloud services, such as Infrastructure, Platform, and Software as a Service, to the domain of UAVs. Our work aims to conceptualize and design UAVaaS for commercial applications. Specifically, a cloud-provided orchestration framework that allows multi-tenant UAVs to easily serve multiple heterogenous clients at once and …

Efspredictor: Predicting Configuration Bugs With Ensemble Feature Selection, Bowen Xu, David Lo, Xin Xia, Ashish Sureka, Shanping Li

Research Collection School Of Computing and Information Systems

The configuration of a system determines the system behavior and wrong configuration settings can adversely impact system's availability, performance, and correctness. We refer to these wrong configuration settings as configuration bugs. The importance of configuration bugs has prompted many researchers to study it, and past studies can be grouped into three categories: detection, localization, and fixing of configuration bugs. In the work, we focus on the detection of configuration bugs, in particular, we follow the line-of-work that tries to predict if a bug report is caused by a wrong configuration setting. Automatically prediction of whether a bug is a configuration …

Algorithmic Data Compression, Maliha Lubna

Research Horizons Day Posters

No abstract provided.

“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams

Senior Honors Theses

Alan Turing asked if machines can think, but intelligence is more than logic and reason. I ask if a machine can feel pain or joy, have visions and dreams, or paint a masterpiece. The human brain sets the bar high, and despite our progress, artificial intelligence has a long way to go. Studying neurology from a software engineer’s perspective reveals numerous uncanny similarities between the functionality of the brain and that of a computer. If the brain is a biological computer, then it is the embodiment of artificial intelligence beyond anything we have yet achieved, and its architecture is advanced …

Dual-Server Public-Key Encryption With Keyword Search For Secure Cloud Storage, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xiaofen Wang

Research Collection School Of Computing and Information Systems

Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this paper, we investigate the security of a well-known cryptographic primitive, namely, public key encryption with keyword search (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual-server PEKS (DS-PEKS). As another main contribution, we define a new variant of the smooth projective …

The Development Of Project Grade-Up, Dalin Glenn Williams

MS in Computer Science Theses

The university classroom has greatly evolved from a simple syllabus and in class discussion to the modern online documentation and virtual classrooms. These developments have changed the way students review their grades and balance their workloads. With the plethora of new technologies, students are often burdened with a full school schedule, work, and social events, with few tools to help them effectively understand their grades or manage their time. Current solutions addressing this issue do not present data in an organized way that allows the student to easily comprehend their past performance or up coming work load. Our solution builds …

Data Center Load Forecast Using Dependent Mixture Model, Md Riaz Ahmed Khan

Electronic Theses and Dissertations

The dependency on cloud computing is increasing day by day. With the boom of data centers, the cost is also increasing, which forces industries to come up with techniques and methodologies to reduce the data center energy use. Load forecasting plays a vital role in both efficient scheduling and operating a data center as a virtual power plant. In this thesis work a stochastic method, based on dependent mixtures is developed to model the data center load and is used for day-ahead forecast. The method is validated using three data sets from National Renewable Energy Laboratory (NREL) and one other …

In-Field Fuel Use And Load States Of Agricultural Field Machinery, Santosh Pitla, Joe D. Luck, Jared Werner, Nannan Lin, Scott A. Shearer

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The ability to define in-field tractor load states offers the potential to better specify and characterize fuel consumption rate for various field operations. For the same field operation, the tractor experiences diverse load demands and corresponding fuel use rates as it maneuvers through straight passes, turns, suspended operation for adjustments, repair and maintenance, and biomass or other material transfer operations. It is challenging to determine the actual fuel rate and load states of agricultural machinery using force prediction models, and hence, some form of in-field data acquisition capability is required. Controller Area Networks (CAN) available on the current model tractors …