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Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis 2015 Singapore Management University

Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis

Research Collection School Of Information Systems

The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and enhance them with elaborate optimizations. Finally, we use real social network data to empirically verify the efficiency and efficacy of our solutions.


Automated Detection Of Puffing And Smoking With Wrist Accelerometers, Qu Tang 2015 Northeastern University

Automated Detection Of Puffing And Smoking With Wrist Accelerometers, Qu Tang

Electrical and Computer Engineering Master's Theses

Real-time, automatic detection of smoking behavior could lead to novel measurement tools for smoking research and "just-in-time" interventions that may help people quit, reducing preventable deaths. This paper discusses the use of machine learning with wrist accelerometer data for automatic puffing and smoking detection. A two-layer smoking detection model is proposed that incorporates both low-level time domain features and high-level smoking topography such as inter-puff intervals and puff frequency to detect puffing then smoking. On a pilot dataset of 6 individuals observed for 11.8 total hours in real-life settings performing complex tasks while smoking, the model obtains a cross ...


Resource Management In Enterprise Cluster And Storage Systems, Jianzhe Tai 2015 Northeastern University

Resource Management In Enterprise Cluster And Storage Systems, Jianzhe Tai

Computer Engineering Dissertations

In this thesis, we present our works on resource management in large scale systems, especially for enterprise cluster and storage systems. Large-scale cluster systems become quite popular among a community of users by offering a variety of resources. Such systems require complex resource management schemes for multi-objective optimizations and should be specific to different system requirements. In addition, burstiness has often been found in enterprise workloads, being a key factor in performance degradation. Therefore, it is an extremely challenging problem of managing heterogeneous resources (e.g., computing, networking and storage) for such a large scale system under bursty conditions while ...


Measuring Privacy Disclosures In Url Query Strings, Andrew G. West, Adam J. Aviv 2014 SelectedWorks

Measuring Privacy Disclosures In Url Query Strings, Andrew G. West, Adam J. Aviv

Andrew G. West

Publicly posted URLs may contain a wealth of information about the identities and activities of the users who share them. URLs often utilize query strings (i.e., key-value pairs appended to the URL path) as a means to pass session parameters and form data. While often benign and necessary to render the web page, query strings sometimes contain tracking mechanisms, user names, email addresses, and other information that users may not wish to publicly reveal. In isolation this is not particularly problematic, but the growth of Web 2.0 platforms such as social networks and micro-blogging means URLs (often copy-pasted ...


An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak 2014 Wright State University

An Analysis Of Mayo Clinic Search Query Logs For Cardiovascular Diseases, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak

Kno.e.sis Publications

Increasingly, individuals are taking active participation in learning and managing their health by leveraging online resources. Understanding online health information searching behavior can help us to study what health topics users search for and how search queries are formulated. In this work, we analyzed 10 million cardiovascular diseases (CVD) related search queries from MayoClinic.com. We performed semantic analysis on the queries using UMLS MetaMap and analyzed structural and textual properties as well as linguistic characteristics of the queries.


Online Information Searching For Cardiovascular Diseases: An Analysis Of Mayo Clinic Search Query Logs, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak 2014 Wright State University

Online Information Searching For Cardiovascular Diseases: An Analysis Of Mayo Clinic Search Query Logs, Ashutosh Sopan Jadhav, Amit P. Sheth, Jyotishman Pathak

Kno.e.sis Publications

Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 ...


"Be Our Guest:" Crafting A Magical Client Experience, Rebecca Klein, Kevin Steele 2014 Valparaiso University

"Be Our Guest:" Crafting A Magical Client Experience, Rebecca Klein, Kevin Steele

Information Technology Faculty and Staff Publications

The Client Services team of Valparaiso University’s IT department found inspiration in Disney’s guest service models and has been building a culture of superior service throughout IT. Come along on a magic carpet ride to discover how this new world is transforming delivery of technological services to the campus. From Help Desk to training to assessment, we are increasing satisfaction levels among campus constituents as we meet their needs. We will show how we created a guest service compass that guides our decision-making and service delivery. Further, we will share areas where we learned we were creating our ...


Infographics: The New 5-Paragraph Essay, Brittany Ann Kos, Elizabeth Sims 2014 University of Colorado, Boulder

Infographics: The New 5-Paragraph Essay, Brittany Ann Kos, Elizabeth Sims

ATLAS Institute Graduate Contributions

The STEM Career Infographic Project (SCIP) was a 5-week exploratory project deployed in an 8th grade classroom at Mountain Vista Middle School (MVMS) in the spring of 2014. Students were required to research a STEM career in-depth, then report on their careers using infographics, in lieu of a standard 5- paragraph essay. SCIP was broken down into 9 days of instruction: introduction, research, three days of design lecture, three work days, and a final presentation day. The students were in the lab working on their infographics every day. We observed that infographics were better suited than traditional essays in areas ...


Chatter: Classifying Malware Families Using System Event Ordering, Aziz Mohaisen, Andrew G. West, Allison Mankin, Omar Alrawi 2014 SelectedWorks

Chatter: Classifying Malware Families Using System Event Ordering, Aziz Mohaisen, Andrew G. West, Allison Mankin, Omar Alrawi

Andrew G. West

Using runtime execution artifacts to identify malware and its associated "family" is an established technique in the security domain. Many papers in the literature rely on explicit features derived from network, file system, or registry interaction. While effective, use of these fine-granularity data points makes these techniques computationally expensive. Moreover, the signatures and heuristics this analysis produces are often circumvented by subsequent malware authors.

To this end we propose CHATTER, a system that is concerned only with the order in which high-level system events take place. Individual events are mapped onto an alphabet and execution traces are captured via terse ...


Fuzzy Mathematical Models For The Analysis Of Fuzzy Systems With Application To Liver Disorders, R.W. W. Hndoosh 2014 SelectedWorks

Fuzzy Mathematical Models For The Analysis Of Fuzzy Systems With Application To Liver Disorders, R.W. W. Hndoosh

R. W. Hndoosh

The main objective of this model is to focus on how to use the model of fuzzy system to solve fuzzy mathematics problems. Some mathematical models based on fuzzy set theory, fuzzy systems and neural network techniques seem very well suited for typical technical problems. We have proposed an extension model of a fuzzy system to N-dimension, using Mamdani's minimum implication, the minimum inference system, and the singleton fuzzifier with the center average defuzzifier. Here construct two different models namely a fuzzy inference system and an adaptive fuzzy system using neural network. We have extended the theorem for accuracy ...


Fuzzy Mathematical Models Of Type-1 And Type-2 For Computing The Parameters And Its Applications, R.W. W. Hndoosh 2014 SelectedWorks

Fuzzy Mathematical Models Of Type-1 And Type-2 For Computing The Parameters And Its Applications, R.W. W. Hndoosh

R. W. Hndoosh

This work provides mathematical formulas and algorithm in order to calculate the derivatives that being necessary to perform Steepest Descent models to make T1 and T2 FLSs much more accessible to FLS modelers. It provides derivative computations that are applied on different kind of MFs, and some computations which are then clarified for specific MFs. We have learned how to model T1 FLSs when a set of training data is available and provided an application to derive the Steepest Descent models that depend on trigonometric function (SDTFM). This work, also focused on an interval type-2 non-singleton type-2 FLS (IT2 NS-T2 ...


Vast 2014, Challenge One: Event Analysis Within Big Data, Isaac C. Sheeley, Jieqiong Zhao, Jing Xia, Shehzad Afzal, Joseph Christopher, David Ebert Dr. 2014 Purdue University

Vast 2014, Challenge One: Event Analysis Within Big Data, Isaac C. Sheeley, Jieqiong Zhao, Jing Xia, Shehzad Afzal, Joseph Christopher, David Ebert Dr.

The Summer Undergraduate Research Fellowship (SURF) Symposium

News articles and email conversation data could be very useful in the analysis of developing and ongoing events, such as preventing a potential threat or possibly even locating a missing person. There is currently no “one-size-fits-all” solution to visualizing diverse forms of datasets and their sheer sizes are far too great to efficiently analyze by brute force methods. However, using principles of Visual Analytics, it is possible to take this information overload and transform it into a useful tool to help increase the efficiency of event analysis. A visualization system was developed for email conversation networks using web technologies. An ...


Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert 2014 Purdue University

Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

There has been a rise in the use of visual analytic techniques to create interactive predictive environments in a range of different applications. These tools help the user sift through massive amounts of data, presenting most useful results in a visual context and enabling the person to rapidly form proactive strategies. In this paper, we present one such visual analytic environment that uses historical crime data to predict future occurrences of crimes, both geographically and temporally. Due to the complexity of this analysis, it is necessary to find an appropriate statistical method for correlative analysis of spatiotemporal data, as well ...


Reconstructing A Large-Scale Attribute-Based Social Network, Weijia Luo, Mario Ventresca 2014 Purdue University

Reconstructing A Large-Scale Attribute-Based Social Network, Weijia Luo, Mario Ventresca

The Summer Undergraduate Research Fellowship (SURF) Symposium

An epidemic occurs when a disease rapidly infects substantially more people than expected compared to past experience of similar diseases. If an epidemic is not contained, it could turn into a pandemic, which will cause a worldwide crisis. Therefore, it is critical to determine and implement epidemic policies that are promising and effective within a short period of time. In this paper, we will develop tools that will allow us to recreate large-scale real-world social networks. Using such networks will enable us to simulate disease spread and determine critical personal and social factors that will be the key to containing ...


Granular Matter: Microstructural Evolution And Mechanical Response, Aashish Ghimire, Ishan Srivastava, Timothy S. Fisher 2014 Purdue University

Granular Matter: Microstructural Evolution And Mechanical Response, Aashish Ghimire, Ishan Srivastava, Timothy S. Fisher

The Summer Undergraduate Research Fellowship (SURF) Symposium

Heterogeneous (nano) composites, manufactured by the densification of variously sized grains, represent an important and ubiquitous class of technologically relevant materials. Typical grain sizes in such materials range from macroscopic to a few nanometers. The morphology exhibited by such disordered materials is complex and intricately connected with its thermal and electrical transport properties. It is important to quantify the geometric features of these materials and simulate the fabrication process. Additionally, granular materials exhibit complex structural and mechanical properties that crucially govern their reliability during industrial use. In this work, we simulate the densification of soft deformable grains from a low-density ...


Earth History Visualization System, Xinjie Lei, James G. Ogg 2014 Purdue University

Earth History Visualization System, Xinjie Lei, James G. Ogg

The Summer Undergraduate Research Fellowship (SURF) Symposium

Time Scale Creator (TSCreator), a geological chart generator, displays any portion of Earth history including chemo- magneto-, and other aspects. TSCreator is used by many universities, petroleum companies, and international geological surveys. In order to improve the quality of Time Scale Creator, tools were developed to provide users with more friendly graphical user interfaces (GUIs), accurate scaling of specific isotope, internationalization of data input and output, and smart depth scaling in wells to age conversion. To implement such tools, research for algorithm and common methods was basically done by searching articles online and reading posts on forums for Java developers ...


Improved Microrobotic Control Through Image Processing And Automated Hardware Interfacing, Archit R. Aggarwal, Wuming Jing, David J. Cappelleri 2014 Purdue University

Improved Microrobotic Control Through Image Processing And Automated Hardware Interfacing, Archit R. Aggarwal, Wuming Jing, David J. Cappelleri

The Summer Undergraduate Research Fellowship (SURF) Symposium

Untethered submilliliter-sized robots (microrobots) are showing potential use in different industrial, manufacturing and medical applications. A particular type of these microrobots, magnetic robots, have shown improved performance in power and control capabilities compared to the other thermal and electrostatic based robots. However, the magnetic robot designs have not been assessed in a robust manner to understand the degree of control in different environments and their application feasibility. This research project seeks to develop a custom control software interface to provide a holistic tool for researchers to evaluate the microrobotic performance through advance control features. The software deliverable involved two main ...


Bayesian Calibration Tool, Sveinn Palsson, Martin Hunt, Alejandro Strachan 2014 Purdue University

Bayesian Calibration Tool, Sveinn Palsson, Martin Hunt, Alejandro Strachan

The Summer Undergraduate Research Fellowship (SURF) Symposium

Fitting a model to data is common practice in many fields of science. The models may contain unknown parameters and often, the goal is to obtain good estimates of them. A variety of methods have been developed for this purpose. They often differ in complexity, efficiency and accuracy and some may have very limited applications. Bayesian inference methods have recently become popular for the purpose of calibrating model's parameters. The way they treat unknown quantities is completely different from any classical methods. Even though the unknown quantity is a constant, it is treated as a random variable and the ...


Energy Based Multi-Model Fitting And Matching Problems, Hossam N. Isack 2014 Western University

Energy Based Multi-Model Fitting And Matching Problems, Hossam N. Isack

University of Western Ontario - Electronic Thesis and Dissertation Repository

Feature matching and model fitting are fundamental problems in multi-view geometry. They are chicken-&-egg problems: if models are known it is easier to find matches and vice versa. Standard multi-view geometry techniques sequentially solve feature matching and model fitting as two independent problems after making fairly restrictive assumptions. For example, matching methods rely on strong discriminative power of feature descriptors, which fail for stereo images with repetitive textures or wide baseline. Also, model fitting methods assume given feature matches, which are not known a priori. Moreover, when data supports multiple models the fitting problem becomes challenging even with known ...


A Study Of The N-D-K Scalability Problem In Large-Scale Image Classification, Carlos E. del-Castillo-Negrete, Sreenivas R. Sukumar 2014 Yale University

A Study Of The N-D-K Scalability Problem In Large-Scale Image Classification, Carlos E. Del-Castillo-Negrete, Sreenivas R. Sukumar

Yale Day of Data

Image classification is a extensively studied problem that lies at the heart of computer vision. However, the challenge remains to develop a system that can identify and classify thousands of objects like the human visual system. The accumulation of massive image data sets has permitted the study of this problem at a big-data scale. However current algorithms have been shown to fall short of being practical and accurate at scale. To further understand how these algorithms scale, we developed a library of functions to explore the scalability of the support vector machine (SVM) linear classification algorithm when applied to problems ...


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