Physical Sciences and Mathematics | Open Access Articles

Using The Census Bureau's Public Use Microdata For Migration Analysis, Mark Salling, Ellen Cyran

Ellen Cyran

Using the Census Bureau's Public Use Microdata for Migration Analysis, Proceedings of the annual conference of the Urban and Regional Information Systems Association, Vancouver, BC, Canada, September 2006, pp.336-348.

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From Cyber Terrorism To State Actors’ Covert Cyber Operations, Jan Kallberg, Bhavani Thuraisingham

Jan Kallberg

Historically, since the Internet started to become a common feature in our lives, hackers have been seen as a major threat. This view has repeatedly been entrenched and distributed by media coverage and commentaries through the years. Instead the first twenty year of the Internet was acceptably secure, due to the limited abilities of the attackers, compared to the threat generated from a militarized Internet with state actors conducting cyber operations. In reality, the Internet have a reversed trajectory for its security where it has become more unsafe over time and moved from a threat to the individual to a …

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Spatial Search Techniques For Mobile 3d Queries In Sensor Web Environments, Junjun Yin, James Carswell

Articles

Developing mobile geo-information systems for sensor web applications involves technologies that can access linked geographical and semantically related Internet information. Additionally, in tomorrow’s Web 4.0 world, it is envisioned that trillions of inexpensive micro-sensors placed throughout the environment will also become available for discovery based on their unique geo-referenced IP address. Exploring these enormous volumes of disparate heterogeneous data on today’s location and orientation aware smartphones requires context-aware smart applications and services that can deal with “information overload”. 3DQ (Three Dimensional Query) is our novel mobile spatial interaction (MSI) prototype that acts as a next-generation base for human interaction within …

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Nuclear Deterrence In A Second Obama Term, Adam Lowther, Jan Kallberg

Jan Kallberg

In the months prior to the 2012 presidential election in the United States, members of the Obama administration and sympathetic organizations inside the Beltway began floating the idea that the administration would pursue – after an Obama victory – further reductions in the US nuclear arsenal. With the ink still wet on the New ST ART Treaty, efforts to reduce the American arsenal to 1000 operationally deployed strategic nuclear weapons or, as some suggest, 500, is certainly premature. These efforts illustrate a poor understanding of nuclear deterrence theory and practice and the ramifications of a United States that lacks a …

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Session F-4: Using Web Tools And Strategies To Enhance Student Engagement, Jackie Naughton, Frank Tomsic

Professional Learning Day

Web tools and strategies will be introduced and modeled. Teachers will leave this session able to immediately implement the tools and strategies in their classrooms. Participants must bring their own devices.

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Predicting Parkinson's Disease Progression With Smartphone Data, Pramod Anantharam, Krishnaprasad Thirunarayan, Vahid Taslimi, Amit P. Sheth

Kno.e.sis Publications

Most of the existing approaches for detecting diseases/risk score form observations (sensor and textual) ignore the presence of any prior knowledge of the disease. In this work, we start top-down by enumerating the symptoms of Parkinson's Disease (PD) and map the symptoms to its possible manifestations in sensor observations (bottom-up). We show such manifestations and further use these manifestations as features to build classifiers to differentiate between the PD patients and the control group.

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Robust Image Analysis With Sparse Representation On Quantized Visual Features, Bingkun Bao, Guangyu Zhu, Jialie Shen, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Recent techniques based on Sparse Representation (SR) have demonstrated promising performance on high-level visual recognition, exemplified by the high-accuracy face recognition under occlusions and other sparse corruptions [1]. Most research in this area has focused on classification algorithms using raw image pixels, and very few have been proposed to utilize the quantized visual features, such as the popular Bagof- Words (BOW) feature abstraction. In such cases, besides the inherent quantization errors, ambiguity associated with visual word assignment and mis-detection of feature points due to factors such as visual occlusions and noises, constitutes the major causes to the dense corruptions of …

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Data Visualization On Interactive Surfaces: A Research Agenda, Petra Isenberg, Tobias Isenberg, Tobias Hesselmann, Bongshin Lee, Ulrich Von Zadow, Anthony Tang

Research Collection School Of Computing and Information Systems

Interactive tabletops and surfaces (ITSs) provide rich opportunities for data visualization and analysis and consequently are used increasingly in such settings. A research agenda of some of the most pressing challenges related to visualization on ITSs emerged from discussions with researchers and practitioners in human-computer interaction, computer-supported collaborative work, and a variety of visualization fields at the 2011 Workshop on Data Exploration for Interactive Surfaces (Dexis 2011)

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A Self-Training Framework For Automatic Identification Of Exploratory Dialogue, Zhongyu Wei, Yulan He, Simon Shum, Rebecca Ferguson, Wei Gao, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

The dramatic increase in online learning materials over the last decade has made it difficult for individuals to locate information they need. Until now, researchers in the field of Learning Analytics have had to rely on the use of manual approaches to identify exploratory dialogue. This type of dialogue is desirable in online learning environments, since training learners to use it has been shown to improve learning outcomes. In this paper, we frame the problem of exploratory dialogue detection as a binary classification task, classifying a given contribution to an online dialogue as exploratory or non-exploratory. We propose a self-training …

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Semi-Supervised Heterogeneous Fusion For Multimedia Data Co-Clustering, Lei Meng, Ah-Hwee Tan, Dong Xu

Research Collection School Of Computing and Information Systems

Co-clustering is a commonly used technique for tapping the rich meta-information of multimedia web documents, including category, annotation, and description, for associative discovery. However, most co-clustering methods proposed for heterogeneous data do not consider the representation problem of short and noisy text and their performance is limited by the empirical weighting of the multi-modal features. In this paper, we propose a generalized form of Heterogeneous Fusion Adaptive Resonance Theory, called GHF-ART, for co-clustering of large-scale web multimedia documents. By extending the two-channel Heterogeneous Fusion ART (HF-ART) to multiple channels, GHF-ART is designed to handle multimedia data with an arbitrarily rich …

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Spoons: Netflix Outage Detection Using Microtext Classification, Eriq A. Augusitne

Master's Theses

Every week there are over a billion new posts to Twitter services and many of those messages contain feedback to companies about their services. One company that recognizes this unused source of information is Netflix. That is why Netflix initiated the development of a system that lets them respond to the millions of Twitter and Netflix users that are acting as sensors and reporting all types of user visible outages. This system enhances the feedback loop between Netflix and its customers by increasing the amount of customer feedback that Netflix receives and reducing the time it takes for Netflix to …

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Image Collection Summarization Via Dictionary Learning For Sparse Representation, Chunlei Yang, Jialie Shen, Jinye Peng, Jianping Fan

Research Collection School Of Computing and Information Systems

In this paper, a novel approach is developed to achieve automatic image collection summarization. The effectiveness of the summary is reflected by its ability to reconstruct the original set or each individual image in the set. We have leveraged the dictionary learning for sparse representation model to construct the summary and to represent the image. Specifically we reformulate the summarization problem into a dictionary learning problem by selecting bases which can be sparsely combined to represent the original image and achieve a minimum global reconstruction error, such as MSE (Mean Square Error). The resulting “Sparse Least Square” problem is NP-hard, …

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Confidence Weighted Mean Reversion Strategy For Online Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan

Research Collection School Of Computing and Information Systems

Online portfolio selection has been attracting increasing attention from the data mining and machine learning communities. All existing online portfolio selection strategies focus on the first order information of a portfolio vector, though the second order information may also be beneficial to a strategy. Moreover, empirical evidence shows that relative stock prices may follow the mean reversion property, which has not been fully exploited by existing strategies. This article proposes a novel online portfolio selection strategy named Confidence Weighted Mean Reversion (CWMR). Inspired by the mean reversion principle in finance and confidence weighted online learning technique in machine learning, CWMR …

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Conditional Random Fields: An Introduction, Hanna M. Wallach

Hanna M. Wallach

No abstract provided.

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Offensive Cyber: Superiority Or Stuck In Legal Hurdles?, Jan Kallberg

Jan Kallberg

In recent years, offensive cyber operations have attracted significant interest from the non-Defense Department academic legal community, prompting numerous articles seeking to create a legal theory for cyber conflicts. Naturally, cyber operations should be used in an ethical way, but the hurdles generated by the legal community are staggering. At a time when the United States has already lost an estimated $4 trillion in intellectual property as a result of foreign cyber espionage, not to mention the loss of military advantage, focusing on what the United States cannot do in cyberspace only hinders efforts to defend the country from future …

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Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …

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Synthetic Controllable Turbulence Using Robust Second Vorticity Confinement, Shengfeng He, Rynson W. H. Lau

Research Collection School Of Computing and Information Systems

Capturing fine details of turbulence on a coarse grid is one of the main tasks in real-time fluid simulation. Existing methods for doing this have various limitations. In this paper, we propose a new turbulence method that uses a refined second vorticity confinement method, referred to as robust second vorticity confinement, and a synthesis scheme to create highly turbulent effects from coarse grid. The new technique is sufficiently stable to efficiently produce highly turbulent flows, while allowing intuitive control of vortical structures. Second vorticity confinement captures and defines the vortical features of turbulence on a coarse grid. However, due to …

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K-Pop Live: Social Networking & Language Learning Platform, Thomas Chua, Chin Leng Ong, Kian Ming Png, Aloysius Lau, Houston Toh, Feida Zhu, Kyong Jin Shim, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

K-Pop live is a social networking and language learning platform developed by an undergraduate student team from Singapore Management University. K-Pop live aims to combine social media together with gamification to promote Korean culture. It consolidates all relevant Tweets from Twitter as well as videos from YouTube. The platform allows the user to connect with his friends who share similar interests in terms of K-pop artists and music.

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Guest Editorial: Selected Papers From Icimcs 2011, Chong-Wah Ngo, Changsheng Xu, Xiao Wu, Abdulmotaleb El Saddik

Research Collection School Of Computing and Information Systems

International Conference on Internet Multimedia Computing and Services (ICIMCS) is an annual conference sponsored by ACM SIGMM China Chapter. The conference is especially interested in the latest technologies and applications that deal with the web-scale processing and management of heterogeneous data from the Internet for multimedia computing and service. ICIMCS 2011 held in Chengdu, China— the ancient hometown of lovely panda. The conference has attracted around 80 participants, including researchers from academia and industries across ten countries/regions, for sharing their recent works in the topics ranging from visual information analysis and mining, query processing and search, multimedia privacy and security.

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Online Multiple Kernel Classification, Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang

Research Collection School Of Computing and Information Systems

Although both online learning and kernel learning have been studied extensively in machine learning, there is limited effort in addressing the intersecting research problems of these two important topics. As an attempt to fill the gap, we address a new research problem, termed Online Multiple Kernel Classification (OMKC), which learns a kernel-based prediction function by selecting a subset of predefined kernel functions in an online learning fashion. OMKC is in general more challenging than typical online learning because both the kernel classifiers and the subset of selected kernels are unknown, and more importantly the solutions to the kernel classifiers and …

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Online Multi-Modal Distance Learning For Scalable Multimedia Retrieval, Hao Xia, Pengcheng Wu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In many real-word scenarios, e.g., multimedia applications, data often originates from multiple heterogeneous sources or are represented by diverse types of representation, which is often referred to as "multi-modal data". The definition of distance between any two objects/items on multi-modal data is a key challenge encountered by many real-world applications, including multimedia retrieval. In this paper, we present a novel online learning framework for learning distance functions on multi-modal data through the combination of multiple kernels. In order to attack large-scale multimedia applications, we propose Online Multi-modal Distance Learning (OMDL) algorithms, which are significantly more efficient and scalable than the …

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Human Resource Information Systems: Information Security Concerns For Organizations, Humayun Zafar

Humayun Zafar

We explore HRIS and e-HR security by presenting information security fundamentals and how they pertain to organizations. With increasing use of enterprise systems such as HRIS and e-HR, security of such systems is an area that is worthy of further exploration. Even then, there is surprisingly little research in this area, albeit that extensive work is present in regard to HRIS privacy. While focusing on HRIS and e-HR security, we introduce aspects of HRIS and e-HR security and how it can be enhanced in organizations. A research model is also presented along with propositions that can guide future research.

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A Qualitative Review Of Differential Diagnosis Generators, William Bond Md, Ms, Linda M. Schwartz Mde, Ahip, Cm, Kevin R. Weaver Do, Donald Levick Md, Mba, Michael Guliano Md, Med, Mhpe, Mark L. Graber Md

Linda Matula Schwartz MDE, AHIP, CM

No abstract provided.

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What Kind Of #Conversation Is Twitter? Mining #Psycholinguistic Cues For Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach, Shreyansh Bhatt

Kno.e.sis Publications

The information overload created by social media messages in emergency situations challenges response organizations to find targeted content and users. We aim to select useful messages by detecting the presence of conversation as an indicator of coordinated citizen action. Using simple linguistic indicators associated with conversation analysis in social science, we model the presence of conversation in the communication landscape of Twitter in a large corpus of 1.5M tweets for various disaster and non-disaster events spanning different periods, lengths of time and varied social significance. Within Replies, Retweets and tweets that mention other Twitter users, we found that domain-independent, linguistic …

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Europe In A ‘Nato Light’ World - Building Affordable And Credible Defense For The Eu, Jan Kallberg, Adam Lowther

Jan Kallberg

From an outsider’s perspective, the Common Security and Defense Policy and the efforts of the European Defense Agency are insufficient to provide Europe with the defense it will require in coming decades. While the European Union—particularly the members of the European Monetary Union—struggle to solve prolonged fiscal challenges, viable European security alternatives to an American-dominated security architecture are conspicuously absent from the documents and discussions that are coming from the European Council and at a time when the United States is engaged in an Asia-Pacific pivot. This is not to say that no thought has been given to defense issues. …

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Stock Market Prediction Without Sentiment Analysis: Using A Web-Traffic Based Classifier And User-Level Analysis, Pierpaolo Dondio

Conference papers

This paper provides further evidence on the predictive power of online community traffic with regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we train a classifier using a set of features entirely extracted from web-traffic data of financial online communities. The classifier is shown to outperform the predictive power of a baseline classifier solely based on price time-series, and to have similar performances as the classifier built considering price and traffic features together. The best predictive performances are achieved when information about stock capitalization is coupled with …

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Cyber Operations Bridging From Concept To Cyber Superiority, Jan Kallberg, Bhavani Thuraisingham

Jan Kallberg

The United States is preparing for cyber conflicts and ushering in a new era for national security. The concept of cyber operations is rapidly developing, and the time has come to transpose the conceptual heights to a broad ability to fight a strategic cyber conflict and defend the Nation in a cohesive way. Richard M. George, a former National Security Agency official, commented on recent developments: “Other countries are preparing for a cyberwar. If we’re not pushing the envelope in cyber, somebody else will.”1 Therefore, increased budgets are allocated to cyber operations research and education. The Defense Advanced Research Projects …

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Real-Time Embodied Agent Adaptation, Ryan M. Schuetzler, David W. Wilson

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper reports on initial investigation of two emerging technologies, FaceFX and Smartbody, capable of creating life-like animations for embodied conversational agents (ECAs) such as the AVATAR agent. Real-time rendering and animation generation technologies can enable rapid adaptation of ECAs to changing circumstances. The benefits of each package are discussed.

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Information And Communication Technologies Effects On Economic Growth, Nancy Jimenez, Lotfollah Najjar, Sajda Qureshi, Dwight Haworth

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

While Information and Communication Technologies (ICTs) are seen to be drivers of economic growth, it is unclear how this change takes place, especially since social and human factors are often seen to change as a result of ICTs. This paper investigates the effects of ICTs, and social and human factors in terms of skills, education, and labor, on economic growth. An augmented production function is used to quantify the effects that infodensity levels, defined as the combination of ICT networks and skills, education, and labor, have on the economic growth of high and low-to-middle income economies. This research draws upon …

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The Role Of Human Capital In Information And Communication Technology Adoption For Development: Evidence From China, Jie Xiong, Sajda Qureshi, Lotfollah Najjar

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Emerging economies, in particular China, are powering growth in Asia. While China is seen to lead growth in the emerging markets of Asia, 98% of its manufacturing and production base is powered by small businesses. These businesses represent the majority of all businesses in emerging countries and the growth of these businesses increases with their successful adoption of Information Technology. This paper uses a well-known model in Information Systems Adoption to analyze ICT usage, the effect ICT usage and human capital in the development of the small businesses in China. The reason this model is used is to find out …

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Full-Text Articles in Physical Sciences and Mathematics

Using The Census Bureau's Public Use Microdata For Migration Analysis, Mark Salling, Ellen Cyran

Ellen Cyran

From Cyber Terrorism To State Actors’ Covert Cyber Operations, Jan Kallberg, Bhavani Thuraisingham

Jan Kallberg

Spatial Search Techniques For Mobile 3d Queries In Sensor Web Environments, Junjun Yin, James Carswell

Articles

Nuclear Deterrence In A Second Obama Term, Adam Lowther, Jan Kallberg

Jan Kallberg

Session F-4: Using Web Tools And Strategies To Enhance Student Engagement, Jackie Naughton, Frank Tomsic

Professional Learning Day

Predicting Parkinson's Disease Progression With Smartphone Data, Pramod Anantharam, Krishnaprasad Thirunarayan, Vahid Taslimi, Amit P. Sheth

Kno.e.sis Publications

Robust Image Analysis With Sparse Representation On Quantized Visual Features, Bingkun Bao, Guangyu Zhu, Jialie Shen, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Data Visualization On Interactive Surfaces: A Research Agenda, Petra Isenberg, Tobias Isenberg, Tobias Hesselmann, Bongshin Lee, Ulrich Von Zadow, Anthony Tang

Research Collection School Of Computing and Information Systems

A Self-Training Framework For Automatic Identification Of Exploratory Dialogue, Zhongyu Wei, Yulan He, Simon Shum, Rebecca Ferguson, Wei Gao, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Semi-Supervised Heterogeneous Fusion For Multimedia Data Co-Clustering, Lei Meng, Ah-Hwee Tan, Dong Xu

Research Collection School Of Computing and Information Systems

Spoons: Netflix Outage Detection Using Microtext Classification, Eriq A. Augusitne

Master's Theses

Image Collection Summarization Via Dictionary Learning For Sparse Representation, Chunlei Yang, Jialie Shen, Jinye Peng, Jianping Fan

Research Collection School Of Computing and Information Systems

Confidence Weighted Mean Reversion Strategy For Online Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan

Research Collection School Of Computing and Information Systems

Conditional Random Fields: An Introduction, Hanna M. Wallach

Hanna M. Wallach

Offensive Cyber: Superiority Or Stuck In Legal Hurdles?, Jan Kallberg

Jan Kallberg

Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

Synthetic Controllable Turbulence Using Robust Second Vorticity Confinement, Shengfeng He, Rynson W. H. Lau

Research Collection School Of Computing and Information Systems

K-Pop Live: Social Networking & Language Learning Platform, Thomas Chua, Chin Leng Ong, Kian Ming Png, Aloysius Lau, Houston Toh, Feida Zhu, Kyong Jin Shim, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Guest Editorial: Selected Papers From Icimcs 2011, Chong-Wah Ngo, Changsheng Xu, Xiao Wu, Abdulmotaleb El Saddik

Research Collection School Of Computing and Information Systems

Online Multiple Kernel Classification, Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang

Research Collection School Of Computing and Information Systems

Online Multi-Modal Distance Learning For Scalable Multimedia Retrieval, Hao Xia, Pengcheng Wu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Human Resource Information Systems: Information Security Concerns For Organizations, Humayun Zafar

Humayun Zafar

A Qualitative Review Of Differential Diagnosis Generators, William Bond Md, Ms, Linda M. Schwartz Mde, Ahip, Cm, Kevin R. Weaver Do, Donald Levick Md, Mba, Michael Guliano Md, Med, Mhpe, Mark L. Graber Md

Linda Matula Schwartz MDE, AHIP, CM

What Kind Of #Conversation Is Twitter? Mining #Psycholinguistic Cues For Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach, Shreyansh Bhatt

Kno.e.sis Publications

Europe In A ‘Nato Light’ World - Building Affordable And Credible Defense For The Eu, Jan Kallberg, Adam Lowther

Jan Kallberg

Stock Market Prediction Without Sentiment Analysis: Using A Web-Traffic Based Classifier And User-Level Analysis, Pierpaolo Dondio

Conference papers

Cyber Operations Bridging From Concept To Cyber Superiority, Jan Kallberg, Bhavani Thuraisingham

Jan Kallberg

Real-Time Embodied Agent Adaptation, Ryan M. Schuetzler, David W. Wilson

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Information And Communication Technologies Effects On Economic Growth, Nancy Jimenez, Lotfollah Najjar, Sajda Qureshi, Dwight Haworth

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

The Role Of Human Capital In Information And Communication Technology Adoption For Development: Evidence From China, Jie Xiong, Sajda Qureshi, Lotfollah Najjar

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations