Computer Sciences Commons^™

Interpretable Multimodal Retrieval For Fashion Products, Lizi Liao, Xiangnan He, Bo Zhao, Chong-Wah Ngo, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Deep learning methods have been successfully applied to fashion retrieval. However, the latent meaning of learned feature vectors hinders the explanation of retrieval results and integration of user feedback. Fortunately, there are many online shopping websites organizing fashion items into hierarchical structures based on product taxonomy and domain knowledge. Such structures help to reveal how human perceive the relatedness among fashion products. Nevertheless, incorporating structural knowledge for deep learning remains a challenging problem. This paper presents techniques for organizing and utilizing the fashion hierarchies in deep learning to facilitate the reasoning of search results and user intent. The novelty of …

Malware Analysis On Android Using Supervised Machine Learning Techniques, Md Shohel Rana, Andrew H. Sung

Faculty Publications

In recent years, a widespread research is conducted with the growth of malware resulted in the domain of malware analysis and detection in Android devices. Android, a mobile-based operating system currently having more than one billion active users with a high market impact that have inspired the expansion of malware by cyber criminals. Android implements a different architecture and security controls to solve the problems caused by malware, such as unique user ID (UID) for each application, system permissions, and its distribution platform Google Play. There are numerous ways to violate that fortification, and how the complexity of creating a …

Ideating Mobile Health Behavioral Support For Compliance To Therapy For Patients With Chronic Disease: A Case Study Of Atrial Fibrillation Management, Mor Peleg, Wojtek Michalowski, Szymon Wilk, Enea Parimbelli, Silvia Bonaccio, Dympna O'Sullivan, Martin Michalowski, Silvana Quaglini, Marc Carrier

Articles

Poor patient compliance to therapy results in a worsening condition that often increases healthcare costs. In the MobiGuide project, we developed an evidence-based clinical decision-support system that delivered personalized reminders and recommendations to patients, helping to achieve higher therapy compliance. Yet compliance could still be improved and therefore building on the MobiGuide project experience, we designed a new component called the Motivational Patient Assistant (MPA) that is integrated within the MobiGuide architecture to further improve compliance. This component draws from psychological theories to provide behavioral support to improve patient engagement and thereby increasing patients' compliance. Behavior modification interventions are delivered …

Evaluating Annual Fixed Wing Maintenance Costs, Kirsten Bunecke, Edward D. White, Jonathan D. Ritschel, Brett A. Bush

Faculty Publications

This article serves two purposes: first, to empirically model the annual percentage increase of operations and support (O&S) costs for fixed wing aircraft; and second, to place into the archival realm another reference for other researchers to consider when investigating other O&S topics. For this study of 21 different airframes grouped together at the Mission- Design Series (MDS), maintenance subcategories 3.1 Consumable Materials and Repair Parts, 3.2 Depot Level Repairables (DLR), and 3.4 Depot Maintenance accounted for an average 91.5% of annual organic maintenance costs. For contractor-maintained MDS, subcategory 3.7, Contractor Logistics Support (CLS) accounted for 96.6% of annual maintenance …

Back Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Sharia Law And Digital Forensics In Saudi Arabia, Fahad Alanazi, Andrew Jones, Catherine Menon

Journal of Digital Forensics, Security and Law

These days, digital crime is one of the main challenges for law enforcement and the judicial system. Many of the laws which are used to protect the users of current technologies were derived from legislation and laws that are utilized in the control of crimes that are based in the physical realm. This applies not only in Western countries, but in countries that adopt Sharia law. There is a need to establish specific legislation and accepted best practice to deal with digital crimes that is compatible with Sharia law, which affects more than one billion Muslims. This paper presents a …

Ontologies And The Semantic Web For Digital Investigation Tool Selection, Hayden Wimmer, Lei Chen, Thomas Narock

Journal of Digital Forensics, Security and Law

The nascent field of digital forensics is heavily influenced by practice. Much digital forensics research involves the use, evaluation, and categorization of the multitude of tools available to researchers and practitioners. As technology evolves at an increasingly rapid pace, the digital forensics field must constantly adapt by creating and evaluating new tools and techniques to perform forensic analysis on many disparate systems such as desktops, notebook computers, mobile devices, cloud, and personal wearable sensor devices, among many others. While researchers have attempted to use ontologies to classify the digital forensics domain on various dimensions, no ontology of digital forensic tools …

Competence Assessment And Automated Feedback For Ultrasound-Guided Intervention Training, Matthew Holden

Link Foundation Modeling, Simulation and Training Fellowship Reports

There is an ongoing shift in the medical education community from a time-based model of medical education to a competency-based model. In the competency-based model, trainees’ performance must be continually monitored. But due to constraints on expert scheduling, this is infeasible for expert preceptors. Moreover, despite the advent of structured assessment rubrics, expert assessment remains subjective. This motivates the development of automated assessment methods. This can be complemented by methods for automatic feedback and instruction, which can be used to improve the training process and acceleration learning curves without the presence of an expert preceptor. Ultrasound-guided interventions are particularly challenging …

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

A Forensic Enabled Data Provenance Model For Public Cloud, Shariful Haque, Travis Atkison

Journal of Digital Forensics, Security and Law

Cloud computing is a newly emerging technology where storage, computation and services are extensively shared among a large number of users through virtualization and distributed computing. This technology makes the process of detecting the physical location or ownership of a particular piece of data even more complicated. As a result, improvements in data provenance techniques became necessary. Provenance refers to the record describing the origin and other historical information about a piece of data. An advanced data provenance system will give forensic investigators a transparent idea about the data's lineage, and help to resolve disputes over controversial pieces of data …

Masthead

Journal of Digital Forensics, Security and Law

No abstract provided.

From Tag To Protect: A Tag-Driven Policy Recommender System For Image Sharing, Anna Cinzia Squicciarini, Andrea Novelli, Dan Lin, Cornelia Caragea, Haoti Zhong

Computer Science Faculty Research & Creative Works

Sharing images on social network sites has become a part of daily routine for more and more online users. However, in face of the considerable number of images shared online, it is not a trivial task for a person to manually configure proper privacy settings for each of the images that he/she uploaded. The lack of proper privacy protection during image sharing could raise many potential privacy breaches of people's private lives that they are not aware of. In this work, we propose a privacy setting recommender system to help people effortlessly set up the privacy settings for their online …

Cmaps: A Chess-Based Multi-Facet Password Scheme For Mobile Devices, Ye Zhu, Jonathan Gurary, George Corser, Jared Oluoch, Nahed Alnahash, Huirong Fu, Junhua Tang

Electrical and Computer Engineering Faculty Publications

It has long been recognized, by both security researchers and human-computer interaction researchers, that no silver bullet for authentication exists to achieve security, usability, and memorability. Aiming to achieve the goals, we propose a Multi-fAcet Password Scheme (MAPS) for mobile authentication. MAPS fuses information from multiple facets to form a password, allowing MAPS to enlarge the password space and improve memorability by reducing memory interference, which impairs memory performance according to psychology interference theory. The information fusion in MAPS can increase usability, as fewer input gestures are required for passwords of the same security strength. Based on the idea of …

Evaluating Prose Style Transfer With The Bible, Keith Carlson, Allen Riddell, Daniel Rockmore

Dartmouth Scholarship

In the prose style transfer task a system, provided with text input and a target prose style, produces output which preserves the meaning of the input text but alters the style. These systems require parallel data for evaluation of results and usually make use of parallel data for training. Currently, there are few publicly available corpora for this task. In this work, we identify a high-quality source of aligned, stylistically distinct text in different versions of the Bible. We provide a standardized split, into training, development and testing data, of the public domain versions in our corpus. This corpus is …

Using Chronicling America’S Images To Explore Digitized Historic Newspapers & Imagine Alternative Futures, Elizabeth Lorang, Leen-Kiat Soh

University of Nebraska-Lincoln Libraries: Presentations

This presentation situates the work of the Aida team broadly as well as hinges this work on some very specific challenges for digital libraries. In doing so demonstrate the many types of questions and domains to be explored in digitized newspapers.

The Chapman Bone Algorithm: A Diagnostic Alternative For The Evaluation Of Osteoporosis, Elise Levesque, Anton Ketterer, Wajiha Memon, Cameron James, Noah Barrett, Cyril Rakovski, Frank Frisch

Mathematics, Physics, and Computer Science Faculty Articles and Research

Osteoporosis is the most common metabolic bone disease and goes largely undiagnosed throughout the world, due to the inaccessibility of DXA machines. Multivariate analyses of serum bone turnover markers were evaluated in 226 Orange County, California, residents with the intent to determine if serum osteocalcin and serum pyridinoline cross-links could be used to detect the onset of osteoporosis as effectively as a DXA scan. Descriptive analyses of the demographic and lab characteristics of the participants were performed through frequency, means and standard deviation estimations. We implemented logistic regression modeling to find the best classification algorithm for osteoporosis. All calculations and …

A Tool For Optimizing Java 8 Stream Software Via Automated Refactoring, Raffi Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed

Publications and Research

Streaming APIs are pervasive in mainstream Object-Oriented languages. For example, the Java 8 Stream API allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we describe the engineering aspects of an open source automated refactoring tool called Optimize Streams that assists developers in writing optimal stream software in …

Research Innovation And Institutional Growth: Digital Humanities, Usm, And The University Of Maine System, Janet M. Billson, Katherine Bessey

Research Innovation and Institutional Growth

No abstract provided.

Minutes & Seconds: The Scientists, Patrick Aievoli

Zea E-Books Collection

Minutes & Seconds, is a captivating intelligible read for those who strive to understand where the “what if” moment has gone. Succeeding his other captivating books, Aievoli’s deep introspective lens dials his readers in to awaken the proverbial sleeping giant inside of our consciousness. He designs an insightful exciting romp through the surreal landscape of our society and illustrates how various pioneers have lead us to a crossroads. I’m truly impressed with Aievoli’s perspicacious comprehension of where digital has taken us through the hands of these select individuals. --Sequoyah Wharton

In creating Minutes & Seconds, Aievoli has assembled an interesting …

An Outlier Detection Algorithm Based On Cross-Correlation Analysis For Time Series Dataset, Hui Lu, Yaxian Liu, Zongming Fei, Chongchong Guan

Computer Science Faculty Publications

Outlier detection is a very essential problem in a variety of application areas. Many detection methods are deficient for high-dimensional time series data sets containing both isolated and assembled outliers. In this paper, we propose an Outlier Detection method based on Cross-correlation Analysis (ODCA). ODCA consists of three key parts. They are data preprocessing, outlier analysis, and outlier rank. First, we investigate a linear interpolation method to convert assembled outliers into isolated ones. Second, a detection mechanism based on the cross-correlation analysis is proposed for translating the high-dimensional data sets into 1-D cross-correlation function, according to which the isolated outlier …

Tourism Review Sentiment Classification Using A Bidirectional Recurrent Neural Network With An Attention Mechanism And Topic-Enriched Word Vectors, Qin Li, Shaobo Li, Jie Hu, Sen Zhang, Jianjun Hu

Faculty Publications

Sentiment analysis of online tourist reviews is playing an increasingly important role in tourism. Accurately capturing the attitudes of tourists regarding different aspects of the scenic sites or the overall polarity of their online reviews is key to tourism analysis and application. However, the performances of current document sentiment analysis methods are not satisfactory as they either neglect the topics of the document or do not consider that not all words contribute equally to the meaning of the text. In this work, we propose a bidirectional gated recurrent unit neural network model (BiGRULA) for sentiment analysis by combining a topic …

A Nonlinear Systems Framework For Cyberattack Prevention For Chemical Process Control Systems, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent cyberattacks against industrial control systems highlight the criticality of preventing future attacks from disrupting plants economically or, more critically, from impacting plant safety. This work develops a nonlinear systems framework for understanding cyberattack-resilience of process and control designs and indicates through an analysis of three control designs how control laws can be inspected for this property. A chemical process example illustrates that control approaches intended for cyberattack prevention which seem intuitive are not cyberattack-resilient unless they meet the requirements of a nonlinear systems description of this property.

A Framework For Detecting Injected Influence Attacks On Microblog Websites Using Change Detection Techniques, Vishnu S. Pendyala, Yuhong Liu, Silvia M. Figueira

Faculty Research, Scholarly, and Creative Activity

Presidential elections can impact world peace, global economics, and overall well-being. Recent news indicates that fraud on the Web has played a substantial role in elections, particularly in developing countries in South America and the public discourse, in general. To protect the trustworthiness of the Web, in this paper, we present a novel framework using statistical techniques to help detect veiled Web fraud attacks in Online Social Networks (OSN). Specific examples are used to demonstrate how some statistical techniques, such as the Kalman Filter and the modified CUSUM, can be applied to detect various attack scenarios. A hybrid data set, …

Left Ventricular Mechanical Dyssynchrony For Cad Diagnosis: Does It Have Incremental Clinical Values?, Zhixin Jiang, Weihua Zhou

Faculty Publications

No abstract provided.

Cultivating Third Party Development In Platform-Centric Software Ecosystems: Extended Boundary Resources Model, Brown C. Msiska

The African Journal of Information Systems

Software ecosystems provide an effective way through which software solutions can be constructed by composing software components, typically applications, developed by internal and external developers on top of a software platform. Third party development increases the potential of a software ecosystem to effectively and quickly respond to context-specific software requirements. The boundary resources model gives a theoretical account for cultivation of third party development premised on the role of platform boundary resources such as application programming interfaces (API). However, from a longitudinal case study of the DHIS2 software ecosystem, this paper observes that no matter how good the boundary resources …

Programming For The Web: From Soup To Nuts: Implementing A Complete Gis Web Page Using Html5, Css, Javascript, Node.Js, Mongodb, And Open Layers., Charles W. Kann Iii

Open Educational Resources

This book is designed to be used as a class text but should be easily accessible to programmers interested in Web Programming. It should even be accessible to an advanced hobbyist.

The original goal behind this text was to help students doing research with me in Web based mapping applications, generally using Open Layers. The idea was to provide persistent storage using REST and simple http request from JavaScript to store the data on a server.

When teaching this class, I became painfully aware of just how little students know about Web Programming. They did not know how to format …

2018 September 12 - Computation And Research In Data Science (Cards) Minutes, Computation And Research In Data Science, East Tennessee State University

Computation and Research in Data Science (CaRDS) Board Meeting Minutes

No abstract provided.

Authenticating Smart Device Users With Behavioral Biometrics, Yanyan Li

Theses and Dissertations

Designed as personal smart assistant, smartphones and smartwatches have dramatically changed people's lives in every aspect from social network communication, navigation to both online and offline shopping. A large amount of personal data such as messages, emails and payment information is stored in such a device. Such data, if lost, can lead to privacy leakage and financial loss. Therefore, protecting such devices from unauthorized access is crucial. Despite the existence of personal identification numbers (PIN) and unlock patterns for user authentication, they have well known drawbacks. Although physiological biometrics such as fingerprints and facial recognition has become popular, they suffer …

A Circular Planetarium As A Spatial Visual Musical Instrument, Dale E. Parson Ph.D.

Computer Science and Information Technology Faculty

Planetariums have been home to spatial visual music for over sixty years. Advanced technology in spatial sound such as sound field and wave field systems are superseding channel-based systems as areas for research. Nevertheless, there is room for invention in immersive spatial visual music in a channel-based planetarium. Circular seating minimizes problems with sonic reflections from circular walls suffered by unidirectional theatre seating arrangements. Circular seating supports dynamic permutation of channel-to-speaker routing as a corrective and compositional measure. Full dome projection of visuals gives inherent support for graphics-to-music spatial correlation and related immersive effects. This paper is a case study …

End-To-End Convolutional Neural Network Model For Gear Fault Diagnosis Based On Sound Signals, Yong Yao, Honglei Wang, Shaobo Li, Zhongnhao Liu, Gui Gui, Yabo Dan, Jianjun Hu

Faculty Publications

Currently gear fault diagnosis is mainly based on vibration signals with a few studies on acoustic signal analysis. However, vibration signal acquisition is limited by its contact measuring while traditional acoustic-based gear fault diagnosis relies heavily on prior knowledge of signal processing techniques and diagnostic expertise. In this paper, a novel deep learning-based gear fault diagnosis method is proposed based on sound signal analysis. By establishing an end-to-end convolutional neural network (CNN), the time and frequency domain signals can be fed into the model as raw signals without feature engineering. Moreover, multi-channel information from different microphones can also be fused …