Data Storage Systems Commons^™

Investigating Consumer Satisfaction Towards Mobile Marketing, Dr Surabhi Singh

Journal of International Technology and Information Management

The extensive applications of mobile phones are visible in global companies for the marketing of their products. The popularity of mobile marketing is increasing considerably. This paper has provided insights into the perspectives of consumer attitude towards mobile marketing in India. The companies will develop an understanding of how mobile marketing influence consumer attitudes. The scale of measurement used for Attitudes was Likert scale and explained the consumer's behavior towards mobile marketing. The factors identified through the study will provide insights into Consumer buying behavior via mobile platforms. The analytical tool SPSS has been used for analysis by using methods …

R2gan: Cross-Modal Recipe Retrieval With Generative Adversarial Network, Bin Zhu, Chong-Wah Ngo, Jingjing Chen, Yanbin Hao

Research Collection School Of Computing and Information Systems

Representing procedure text such as recipe for crossmodal retrieval is inherently a difficult problem, not mentioning to generate image from recipe for visualization. This paper studies a new version of GAN, named Recipe Retrieval Generative Adversarial Network (R2GAN), to explore the feasibility of generating image from procedure text for retrieval problem. The motivation of using GAN is twofold: learning compatible cross-modal features in an adversarial way, and explanation of search results by showing the images generated from recipes. The novelty of R2GAN comes from architecture design, specifically a GAN with one generator and dual discriminators is used, which makes the …

Adversarial Contract Design For Private Data Commercialization, Parinaz Naghizadeh, Arunesh Sinha

Research Collection School Of Computing and Information Systems

The proliferation of data collection and machine learning techniques has created an opportunity for commercialization of private data by data aggregators. In this paper, we study this data monetization problem as a mechanism design problem, specifically using a contract-theoretic approach. Our proposed adversarial contract design framework provides a fundamental extension to the classic contract theory set-up in order to account for the heterogeneity in honest buyers’ demands for data, as well as the presence of adversarial buyers who may purchase data to compromise its privacy. We propose the notion of Price of Adversary (PoAdv) to quantify the effects of adversarial …

Your Internet Data Is Rotting, Paul Royster

University of Nebraska-Lincoln Libraries: Faculty Publications

The internet is growing, but old information continues to disappear daily.

Many MySpace users were dismayed to discover earlier this year that the social media platform lost 50 million files uploaded between 2003 and 2015. The failure of MySpace to care for and preserve its users’ content should serve as a reminder that relying on free third-party services can be risky. MySpace has probably preserved the users’ data; it just lost their content. The data was valuable to MySpace; the users’ content less so.

Preserving content or intellectual property on the internet presents a conundrum. If it’s accessible, then it …

Crude Oil Price Prediction With Decision Tree Based Regression Approach, Engu Chen, Xin James He

Journal of International Technology and Information Management

Crude oil is an essential commodity for industry and the prediction of its price is crucial for many business entities and government organizations. While there have been quite a few conventional statistical models to forecast oil prices, we find that there is not much research using decision tree models to predict crude oil prices. In this research, we develop decision tree models to forecast crude oil prices. In addition to historical crude oil price time series data, we also use some predictor variables that would potentially affect crude oil prices, including crude oil demand and supply, and monthly GDP and …

College Choice Criteria Utilizing Conjoint Analysis Enabled On A Saas Platform, Alison Munsch

Journal of International Technology and Information Management

College enrollments and low to moderate household incomes are stagnating while tuition costs are increasing. The New York State Legislature enacted the nation’s first tuition-free degree program, the Excelsior Scholarship, designed to make a college education more affordable to middle class families. This legislation can impact what institution of higher education students will choose upon high school graduation. In order to understand the choice criteria for selecting an institution of higher education, a research study was conducted among a representative sample of high school upper classmen and parents of this respondent segment. The data collection and analysis were accomplished using …

Designated-Server Identity-Based Authenticated Encryption With Keyword Search For Encrypted Emails, Hongbo Li, Qiong Huang, Jian Shen, Guomin Yang, Willy Susilo

Research Collection School Of Computing and Information Systems

In encrypted email system, how to search over encrypted cloud emails without decryption is an important and practical problem. Public key encryption with keyword search (PEKS) is an efficient solution to it. However, PEKS suffers from the complex key management problem in the public key infrastructure. Its variant in the identity-based setting addresses the drawback, however, almost all the schemes does not resist against offline keyword guessing attacks (KGA) by inside adversaries. In this work we introduce the notion of designated-server identity-based authenticated encryption with keyword search (dIBAEKS), in which the email sender authenticates the message while encrypting so that …

Cure: Flexible Categorical Data Representation By Hierarchical Coupling Learning, Songlei Jian, Guansong Pang, Longbing Cao, Kai Lu, Hang Gao

Research Collection School Of Computing and Information Systems

The representation of categorical data with hierarchical value coupling relationships (i.e., various value-to-value cluster interactions) is very critical yet challenging for capturing complex data characteristics in learning tasks. This paper proposes a novel and flexible coupled unsupervised categorical data representation (CURE) framework, which not only captures the hierarchical couplings but is also flexible enough to be instantiated for contrastive learning tasks. CURE first learns the value clusters of different granularities based on multiple value coupling functions and then learns the value representation from the couplings between the obtained value clusters. With two complementary value coupling functions, CURE is instantiated into …

Modeling Sequential And Basket-Oriented Associations For Top-K Recommendation, Duc-Trong Le Duc Trong

Dissertations and Theses Collection (Open Access)

Top-K recommendation is a typical task in Recommender Systems. In traditional approaches, it mainly relies on the modeling of user-item associations, which emphasizes the user-specific factor or personalization. Here, we investigate another direction that models item-item associations, especially with the notions of sequence-aware and basket-level adoptions . Sequences are created by sorting item adoptions chronologically. The associations between items along sequences, referred to as “sequential associations”, indicate the influence of the preceding adoptions on the following adoptions. Considering a basket of items consumed at the same time step (e.g., a session, a day), “basket-oriented associations” imply correlative dependencies among these …

Examining Effectiveness Of Web-Based Internet Of Things Honeypots, Lukas A. Stafira

Theses and Dissertations

The Internet of Things (IoT) is growing at an alarming rate. It is estimated that there will be over 25 billion IoT devices by 2020. The simplicity of their function usually means that IoT devices have low processing power, which prevent them from having intricate security features, leading to vulnerabilities. This makes IoT devices the prime target of attackers in the coming years. Honeypots are intentionally vulnerable machines that run programs which appear as a vulnerable device to a would-be attacker. They are placed on a network to entice and trap an attacker and then gather information on them, including …

Graph-Based Temporal Analysis In Digital Forensics, Nikolai A. Adderley

Theses and Dissertations

Establishing a timeline as part of a digital forensics investigation is a vital part of understanding the order in which system events occurred. However, most digital forensics tools present timelines as histogram or as raw artifacts. Consequently, digital forensics examiners are forced to rely on manual, labor-intensive practices to reconstruct system events. Current digital forensics analysis tools are at their technological limit with the increasing storage and complexity of data. A graph-based timeline can present digital forensics evidence in a structure that can be immediately understood and effortlessly focused. This paper presents the Temporal Analysis Integration Management Application (TAIMA) to …

Machine Learning Models Of C-17 Specific Range Using Flight Recorder Data, Marcus Catchpole

Theses and Dissertations

Fuel is a significant expense for the Air Force. The C-17 Globemaster eet accounts for a significant portion. Estimating the range of an aircraft based on its fuel consumption is nearly as old as flight itself. Consideration of operational energy and the related consideration of fuel efficiency is increasing. Meanwhile machine learning and data-mining techniques are on the rise. The old question, "How far can my aircraft y with a given load cargo and fuel?" has given way to "How little fuel can I load into an aircraft and safely arrive at the destination?" Specific range is a measure of …

Making Personal Goals More Achievable, Adam Carlson

ENGS 86 Independent Projects (AB Students)

Achieving long-term goals has a large impact on one’s life. However, this success requires focused, consistent work even when the achievement is not imminent. Presently, we turn to calendars and task management applications for help. But, these tools quickly become cluttered making it difficult to visualize progress. I created an iPhone application which emphasizes long-term thinking. First-time users must provide three long-term goals with deadlines. Then, they have the opportunity to add smaller, to-do items to their week. For each item, the user must specify a long-term goal to which it is associated. The long-term association ensures users stay focused.

Relevance Analysis For Document Retrieval, Eric Labouve

Master's Theses

Document retrieval systems recover documents from a dataset and order them according to their perceived relevance to a user’s search query. This is a difficult task for machines to accomplish because there exists a semantic gap between the meaning of the terms in a user’s literal query and a user’s true intentions. Even with this ambiguity that arises with a lack of context, users still expect that the set of documents returned by a search engine is both highly relevant to their query and properly ordered. The focus of this thesis is on document retrieval systems that explore methods of …

Analogies And Comparisons For Stm Data Bodies, Phillip M. Cunio, Brien Flewelling

Space Traffic Management Conference

Space Traffic Management (STM) has already demonstrated its potential to be extremely data-intensive. The large number of objects on orbit today, if observed constantly throughout their lifetimes, could produce a staggeringly large number of observations that might in turn generate large numbers of orbits. Orbit data with a lengthy time history can be used to produce estimates of maneuver frequency, susceptibility to natural forces such as drag, and (if combined with photometric data) assessments of behavioral patterns of life.

A future of mega-constellations and a growing number of nations and organizations with assets on orbit would make it likely that …

Chip-Off Success Rate Analysis Comparing Temperature And Chip Type, Choli Ence, Joan Runs Through, Gary D. Cantrell

Journal of Digital Forensics, Security and Law

Throughout the digital forensic community, chip-off analysis provides examiners with a technique to obtain a physical acquisition from locked or damaged digital device. Thermal based chip-analysis relies upon the application of heat to remove the flash memory chip from the circuit board. Occasionally, a flash memory chip fails to successfully read despite following similar protocols as other flash memory chips. Previous research found the application of high temperatures increased the number of bit errors present in the flash memory chip. The purpose of this study is to analyze data collected from chip-off analyses to determine if a statistical difference exists …

Two-Stage Bagging Pruning For Reducing The Ensemble Size And Improving The Classification Performance, Hua Zhang, Yujie Song, Bo Jiang, Bi Chen, Guogen Shan

Environmental & Global Health Faculty Research

Ensemble methods, such as the traditional bagging algorithm, can usually improve the performance of a single classifier. However, they usually require large storage space as well as relatively time-consuming predictions. Many approaches were developed to reduce the ensemble size and improve the classification performance by pruning the traditional bagging algorithms. In this article, we proposed a two-stage strategy to prune the traditional bagging algorithm by combining two simple approaches: accuracy-based pruning (AP) and distance-based pruning (DP). These two methods, as well as their two combinations, “AP+DP” and “DP+AP” as the two-stage pruning strategy, were all examined. Comparing with the single …

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …

Annual Report 2018-2019, Depaul University College Of Computing And Digital Media

CDM Annual Reports

LETTER FROM THE DEAN

I am pleased to share with you the 2018-19 College of Computing and Digital Media (CDM) annual report, highlighting the important work done by our faculty, students, and staff. We’ve said this before, and we’ll say it again: it was a big year. In 2018-19, programs across all three of our schools (Computing, Cinematic Arts, and Design) were ranked nationally. Our faculty were published in dozens of scholarly journals, screened their films over 100 times, and had their work exhibited globally. Student and alumni accomplishments included an Emmy nomination, a first place win in a Department …

Metadata-Based Image Collecting And Databasing For Sharing And Analysis, Xi Wu

Theses and Dissertations--Computer Science

Data collecting and preparing is generally considered a crucial process in data science projects. Especially for image data, adding semantic attributes when preparing image data provides much more insights for data scientists. In this project, we aim to implement a general-purpose central image data repository that allows image researchers to collect data with semantic properties as well as data query. One of our researchers has come up with the specific challenge of collecting images with weight data of infants in least developed countries with limited internet access. The rationale is to predict infant weights based on image data by applying …

Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell

International Journal of Applied Management and Technology

Agencies from various disciplines supporting law enforcement functions and processes have integrated, shared, and communicated data through ad hoc methods to address crime, terrorism, and many other threats in the United States. Data integration in law enforcement plays a critical role in the technical, business, and intelligence processes created by users to combine data from various sources and domains to transform them into valuable information. The purpose of this qualitative phenomenological study was to explore the current conditions of data integration frameworks through user and system interactions among law enforcement organizational processes. Further exploration of critical success factors used to …

Procure-To-Pay Software In The Digital Age: An Exploration And Analysis Of Efficiency Gains And Cybersecurity Risks In Modern Procurement Systems, Drew Lane

MPA/MPP/MPFM Capstone Projects

Procure-to-Pay (P2P) softwares are an integral part of the payment and procurement processing functions at large-scale governmental institutions. These softwares house all of the financial functions related to procurement, accounts payable, and often human resources, helping to facilitate and automate the process from initiation of a payment or purchase, to the actual disbursal of funds. Often, these softwares contain budgeting and financial reporting tools as part of the offering. As such an integral part of the financial process, these softwares obviously come at an immense cost from a set of reputable vendors. In the case of government, these vendors mainly …

Curricular Optimization: Solving For The Optimal Student Success Pathway, William G. Thompson-Arjona

Theses and Dissertations--Electrical and Computer Engineering

Considering the significant investment of higher education made by students and their families, graduating in a timely manner is of the utmost importance. Delay attributed to drop out or the retaking of a course adds cost and negatively affects a student’s academic progression. Considering this, it becomes paramount for institutions to focus on student success in relation to term scheduling.

Often overlooked, complexity of a course schedule may be one of the most important factors in whether or not a student successfully completes his or her degree. More often than not students entering an institution as a first time full …

A Systematic Review Of Process Modelling Methods And Its Application For Personalised Adaptive Learning Systems, Kingsley Okoye

Journal of International Technology and Information Management

This systematic review work investigates current literature and methods that are related to the application of process mining and modelling in real-time particularly as it concerns personalisation of learning systems, or yet still, e-content development. The work compares available studies based on the domain area of study, the scope of the study, methods used, and the scientific contribution of the papers and results. Consequently, the findings of the identified papers were systematically evaluated in order to point out potential confounding variables or flaws that might have been overlooked or missing in the current literature. In turn, a critical structured analysis …

Table Of Contents Jitim Vol 27 Issue 4, 2018-2019

Journal of International Technology and Information Management

ToC JITIM - Special Issue on ICT4D

Table Of Contents Jitim Vol 28 Issue 1, 2019

Journal of International Technology and Information Management

Table of contents

A Multilayer Secured Messaging Protocol For Rest-Based Services, Idongesit Efaemiode Eteng

Journal of International Technology and Information Management

The lack of descriptive language and security guidelines poses a big challenge to implementing security in Representational State Transfer (REST) architecture. There is over reliance on Secure Socket Layer/Transport Layer Security (SSL/TLS), which in recent times has proven to be fallible. Some recent attacks against SSL/TLS include: POODLE, BREACH, CRIME, BEAST, FREAK etc. A secure messaging protocol is implemented in this work. The protocol is further compiled into a reusable library which can be called by other REST services. Using Feature Driven Development (FDD) software methodology, a two layer security protocol was developed. The first layer is a well hardened …

Table Of Contents Jitim Vol 28 Issue 4, 2019

Journal of International Technology and Information Management

Table of Contents

Big Data Investment And Knowledge Integration In Academic Libraries, Saher Manaseer, Afnan R. Alawneh, Dua Asoudi

Copyright, Fair Use, Scholarly Communication, etc.

Recently, big data investment has become important for organizations, especially with the fast growth of data following the huge expansion in the usage of social media applications, and websites. Many organizations depend on extracting and reaching the needed reports and statistics. As the investments on big data and its storage have become major challenges for organizations, many technologies and methods have been developed to tackle those challenges.

One of such technologies is Hadoop, a framework that is used to divide big data into packages and distribute those packages through nodes to be processed, consuming less cost than the traditional storage …

Integrating Multi-Source Weather Data For Deep Learning, Haidar A. Alanbari Mr

Dissertations and Theses

Big Data has been playing a major role in the domain of Deep Learning applications as many companies and institutions continue to find solutions and extract certain trends in fields of climate change, weather forecasting and meteorology. This project extracts weather events data from multiple data sources that are supported by National Centers for Environmental information (NCEI) [1] and Amazon Web Services (AWS) [2]. Data sources include Next-Generation NEXRAD [3] Doppler radar reflectivity, GOES-16 [4] multi-channel satellite imagery and NCEI [1] storm events. Then, it integrates and refines data in proper formats to be fed to the open-source Detectron [5] …