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Articles 4111 - 4140 of 6727

Full-Text Articles in Physical Sciences and Mathematics

Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao Aug 2013

Learning To Name Faces: A Multimodal Learning Scheme For Search-Based Face Annotation, Dayong Wang, Steven C. H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao

Research Collection School Of Computing and Information Systems

Automated face annotation aims to automatically detect human faces from a photo and further name the faces with the corresponding human names. In this paper, we tackle this open problem by investigating a search-based face annotation (SBFA) paradigm for mining large amounts of web facial images freely available on the WWW. Given a query facial image for annotation, the idea of SBFA is to first search for top-n similar facial images from a web facial image database and then exploit these top-ranked similar facial images and their weak labels for naming the query facial image. To fully mine those information, …


Understanding User Resistance To Information Technology: Toward A Comprehensive Model In Health Information Technology, Madison N. Ngafeeson Aug 2013

Understanding User Resistance To Information Technology: Toward A Comprehensive Model In Health Information Technology, Madison N. Ngafeeson

Theses and Dissertations - UTB/UTPA

The successful implementation of health information systems is expected to increase legibility, reduce medical errors, boost the quality of healthcare and shrink costs. Yet, evidence points to the fact that healthcare professionals resist the full use of these systems. Physicians and nurses have been reported to resist the system. Even though resistance to technology has always been identified as key issue in the successful implementation of information technology, the subject remains largely under-theorized and deficient of empirical testing. Only two proposed model have been tested so far. Hence, though user resistance is clearly identified and defined in literature, not very …


Has Safeer Improved Sacm's Work And Helped Saudi Students In The Usa Resolve Their Needs Quickly, Faisal M. Alzomily Aug 2013

Has Safeer Improved Sacm's Work And Helped Saudi Students In The Usa Resolve Their Needs Quickly, Faisal M. Alzomily

Masters Theses & Specialist Projects

This study examined efficiency of the Safeer by gathering and analyzing the perception of 131 Saudi students from Bowling Green, KY. The purpose of the study was to ensure that the system is able to perform its function as the bridge between different institutions and Saudi students studying in the US who require assistance in processing their academic requirements. A self-administered survey using five scale points was employed. Results were summarized using descriptive statistics at 95% confidence level. The result confirmed the hypothesis that the use of the Safeer program provides quality service delivery within SACM, which in turn benefits …


Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk Aug 2013

Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk

Research Collection School Of Computing and Information Systems

In political contexts, it is known that people act as "motivated reasoners", i.e., information is evaluated first for emotional affect, and this emotional reaction influences later deliberative reasoning steps. As social media becomes a more and more prevalent way of receiving political information, it becomes important to understand more completely the interaction between information, emotion, social community, and information-sharing behavior. In this paper, we describe a high-precision classifier for politically-oriented tweets, and an accurate classifier of a Twitter user's political affiliation. Coupled with existing sentiment-analysis tools for microblogs, these methods enable us to systematically study the interaction of emotion and …


Computing Immutable Regions For Subspace Top-K Queries, Kyriakos Mouratidis, Hwee Hwa Pang Aug 2013

Computing Immutable Regions For Subspace Top-K Queries, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Given a high-dimensional dataset, a top-k query can be used to shortlist the k tuples that best match the user’s preferences. Typically, these preferences regard a subset of the available dimensions (i.e., attributes) whose relative significance is expressed by user-specified weights. Along with the query result, we propose to compute for each involved dimension the maximal deviation to the corresponding weight for which the query result remains valid. The derived weight ranges, called immutable regions, are useful for performing sensitivity analysis, for finetuning the query weights, etc. In this paper, we focus on top-k queries with linear preference functions over …


Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis Aug 2013

Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In this paper, we consider a new problem in the context of road network databases, named Resource Constrained Best Upgrade Plan computation (BUP, for short). Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in G, and a budget (resource constraint) B, the BUP problem is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …


Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu Aug 2013

Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. Unlike the regular budget kernel online learning scheme that usually uses different strategies to bound the number of support vectors, our framework explores a functional approximation approach to approximating a kernel function/matrix in order to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) the Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) the …


Making Sense Of Software Development And Personality Types, Luiz Fernando Capretz, Faheem Ahmed Dr. Jul 2013

Making Sense Of Software Development And Personality Types, Luiz Fernando Capretz, Faheem Ahmed Dr.

Luiz Fernando Capretz

No abstract provided.


Wildfire Assessment Using Farsite Fire Modeling: A Case Study In The Chihuahua Desert Of Mexico, John Brakeall Jul 2013

Wildfire Assessment Using Farsite Fire Modeling: A Case Study In The Chihuahua Desert Of Mexico, John Brakeall

FIU Electronic Theses and Dissertations

The Chihuahua desert is one of the most biologically diverse ecosystems in the world, but suffers serious degradation because of changes in fire regimes resulting in large catastrophic fires. My study was conducted in the Sierra La Mojonera (SLM) natural protected area in Mexico. The purpose of this study was to implement the use of FARSITE fire modeling as a fire management tool to develop an integrated fire management plan at SLM.

Firebreaks proved to detain 100% of wildfire outbreaks. The rosetophilous scrub experienced the fastest rate of fire spread and lowland creosote bush scrub experienced the slowest rate of …


From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton Jul 2013

From Questions To Effective Answers: On The Utility Of Knowledge-Driven Querying Systems For Life Sciences Data, Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya S. Sahoo, Priti Parikh, Amit P. Sheth, Rick L. Tarleton

Kno.e.sis Publications

We compare two distinct approaches for querying data in the context of the life sciences. The first approach utilizes conventional databases to store the data and provides intuitive form-based interfaces to facilitate querying of the data, commonly used by the life science researchers that we study. The second approach utilizes a large OWL ontology and the same datasets associated as RDF instances of the ontology. Both approaches are being used in parallel by a team of cell biologists in their daily research activities, with the objective of gradually replacing the conventional approach with the knowledge-driven one. We describe several benefits …


Filestream Enhancement To The Courseweb Grading System, Derrick Massey Jul 2013

Filestream Enhancement To The Courseweb Grading System, Derrick Massey

All Capstone Projects

Data is sometimes unstructured, such as text documents, images, and videos. This unstructured data is regularly stored outside the database, different from its structured data. This separation can cause data management problems. Or, if the data is connected with regulated storage, the performance and the file streaming capabilities and can degrade.

FILESTREAM incorporates the SQL Server Database Engine with an NTFS file system by loading varbinary(max) BLOB data as files. And make them available to the file system. Transact-SQL statements can update, query, search, insert, and or back up FILESTREAM data. The Win32 file system interface affords streaming access to …


Video Concept Detection By Learning From Web Images: A Case Study On Cross Domain Learning, Shiai Zhu, Ting Yao, Chong-Wah Ngo Jul 2013

Video Concept Detection By Learning From Web Images: A Case Study On Cross Domain Learning, Shiai Zhu, Ting Yao, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Concept detection is probably the most important research problem in the area of multimedia. The need to model with sufficient and diverse training instances, however, makes the task computationally and resourcefully expensive. Meanwhile, the popularity of social media has generated massive amount of weakly tagged images which could be leveraged for concept model learning. Therefore, in this paper, we consider exploring weakly taggedWeb images to shed some light on video concept detection. Particularly, two sets of Web images downloaded from Flickr are utilized as training data for concept detection on two real-world large-scale video datasets released by TRECVID. Our experiments …


Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee Jul 2013

Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee

Research Collection School Of Computing and Information Systems

Real-life vehicle routing problems comprise of a number of complexities that are not considered by the classical models found in vehicle routing literature. I present, in this paper, a two-stage sweep-based heuristic to find good solutions to a real-life Vehicle Routing Problem (VRP). The problem I shall consider, will deal with some non-standard constraints beyond those normally associated with the classical VRP. Other than considering the capacity constraints for vehicles and the time windows for deliveries, I shall introduce four additional non-standard constraints: merging of customer orders, controlling the maximum number of drop points, matching orders to vehicle types, and …


Active Learning With Expert Advice, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang Jul 2013

Active Learning With Expert Advice, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang

Research Collection School Of Computing and Information Systems

Conventional learning with expert advice methods assumes a learner is always receiving the outcome (e.g., class labels) of every incoming training instance at the end of each trial. In real applications, acquiring the outcome from oracle can be costly or time consuming. In this paper, we address a new problem of active learning with expert advice, where the outcome of an instance is disclosed only when it is requested by the online learner. Our goal is to learn an accurate prediction model by asking the oracle the number of questions as small as possible. To address this challenge, we propose …


Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu Jul 2013

Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu

Research Collection School Of Computing and Information Systems

Social network users connect and interact with one another to fulfil different kinds of social and information needs. When interaction ceases between two users, we say that their tie becomes dormant. While there are different underlying reasons of dormant ties, it is important to find means to revive such ties so as to maintain vibrancy in the relationships. In this work, we thus focus on designing an online experiment to evaluate the effectiveness of personalized social messages to revive dormant ties. The experiment carefully selects users with dormant ties so that no user gets mixed treatments and be affected by …


The Impact Of Technical Innovation On Voter Registration And Turnout, Chere' Evans Jul 2013

The Impact Of Technical Innovation On Voter Registration And Turnout, Chere' Evans

Masters Theses & Doctoral Dissertations

Research on provisional ballots is nearly nonexistent and research on military and overseas civilian absentee ballots is limited. While the percentages of those voters are small, they are still substantial enough to swing close elections, so ensuring that every eligible voter has his or her vote counted is essential and research is needed in order to identify ways to improve processes for these voters.

By the 2012 Presidential General election, the Maryland State Board of Elections (SBE) had implemented Online Voter Registration (OLVR), Electronic (or paperless) Motor Voter (EMV), and Online Absentee Request (OAR). Maryland also did a redesign of …


Student Interaction With Content In Online And Hybrid Courses: Leading Horses To The Proverbial Water, Meg Murray, Jorge Perez, Debra Geist, Alison Hedrick Jul 2013

Student Interaction With Content In Online And Hybrid Courses: Leading Horses To The Proverbial Water, Meg Murray, Jorge Perez, Debra Geist, Alison Hedrick

Faculty Articles

Permutations of traditional and online learning are rapidly advancing along a blended continuum, prompting conjecture that learning and e-learning will soon be indistinguishable. As variations of blended learning evolve, educators worldwide must develop better understanding of how effective interaction with course content impacts engagement and learning. This study compares patterns of access to instructional content in online and hybrid courses offered at a regional university in the United States. Frequency counts and access rates were examined for course content in four categories: core materials, direct support, indirect support, and ancillary materials. Observed results were echoed in responses to a survey …


Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim Jul 2013

Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Social networks provide a wealth of data to study relationship dynamics among people. Most social networks such as Epinions and Facebook allow users to declare trusts or friendships with other users. Some of them also allow users to declare distrusts or negative relationships. When both positive and negative links co-exist in a network, some interesting community structures can be studied. In this work, we mine Direct Antagonistic Communities (DACs) within such signed networks. Each DAC consists of two sub-communities with positive relationships among members of each sub-community, and negative relationships among members of the other sub-community. Identifying direct antagonistic communities …


Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis Jul 2013

Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In this paper we identify a novel query type, the top-K assignment query (αTop-K). Consider a set of objects and a set of suppliers, where each object must be assigned to one supplier. Assume that there is a cost associated with every object-supplier pair. If we allocate each object to the server with the smallest cost (for the specific object), the derived overall assignment will have the minimum total cost. In many scenarios, however, runner-up assignments may be required too, like for example when a decision maker needs to make additional considerations, not captured by individual object-supplier costs. In this …


Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi Jul 2013

Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Multiple kernel learning (MKL) is a promising family of machine learning algorithms using multiple kernel functions for various challenging data mining tasks. Conventional MKL methods often formulate the problem as an optimization task of learning the optimal combinations of both kernels and classifiers, which usually results in some forms of challenging optimization tasks that are often difficult to be solved. Different from the existing MKL methods, in this paper, we investigate a boosting framework of MKL for classification tasks, i.e., we adopt boosting to solve a variant of MKL problem, which avoids solving the complicated optimization tasks. Specifically, we present …


How To Build An Rss Feed Using Asp, Umakant Mishra Jun 2013

How To Build An Rss Feed Using Asp, Umakant Mishra

Umakant Mishra

RSS is a XML based format. The Current popular version of RSS is RSS version 2.0. The purpose of adding an RSS feed to your site is to show if anything new is added to the site. For example, if a new article or blog or news item is added to your site that should automatically appear in the RSS feed so that the visitors/ RSS readers will automatically get updated about this new addition. The RSS feed is also called RSS channel.

There are two main elements of the RSS XML file, one is the header or channel element …


Indoor Positioning For Smartphones Using Asynchronous Ultrasound Trilateration, Viacheslav Filonenko, Charlie Cullen, James Carswell Jun 2013

Indoor Positioning For Smartphones Using Asynchronous Ultrasound Trilateration, Viacheslav Filonenko, Charlie Cullen, James Carswell

Articles

Modern smartphones are a great platform for Location Based Services (LBS). While outdoor LBS for smartphones has proven to be very successful, indoor LBS for smartphones has not yet fully developed due to the lack of an accurate positioning technology. In this paper we present an accurate indoor positioning approach for commercial off-the-shelf (COTS) smartphones that uses the innate ability of mobile phones to produce ultrasound, combined with Time-Difference-of-Arrival (TDOA) asynchronous trilateration. We evaluate our indoor positioning approach by describing its strengths and weaknesses, and determine its absolute accuracy. This is accomplished through a range of experiments that involve variables …


Touch: In-Memory Spatial Join By Hierarchical Data-Oriented Partitioning, Sadegh Nobari, Farhan Tauheed, Thomas Heinis, Panagiotis Karras, Stéphane Bressan, Anastasia Ailamaki Jun 2013

Touch: In-Memory Spatial Join By Hierarchical Data-Oriented Partitioning, Sadegh Nobari, Farhan Tauheed, Thomas Heinis, Panagiotis Karras, Stéphane Bressan, Anastasia Ailamaki

Sadegh Nobari

Efficient spatial joins are pivotal for many applications and particularly important for geographical information systems or for the simulation sciences where scientists work with spatial models. Past research has primarily focused on disk-based spatial joins; efficient in- memory approaches, however, are important for two reasons: a) main memory has grown so large that many datasets fit in it and b) the in-memory join is a very time-consuming part of all disk-based spatial joins.


Mixed Spatial And Nonspatial Problems In Location Based Services, Jaime Ballesteros Jun 2013

Mixed Spatial And Nonspatial Problems In Location Based Services, Jaime Ballesteros

FIU Electronic Theses and Dissertations

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial …


Brovine: Mammary Gland Gene Database, Therin C. Irwin Jun 2013

Brovine: Mammary Gland Gene Database, Therin C. Irwin

Computer Science and Software Engineering

Brovine is used by the Animal Science department at Cal Poly to catalog and analyze genetic information. Brovine, or the Mammary Gland Gene Database, is a system used to store and categorize genetic information which is gathered through experimentation and through TESS, a web application that lets users search through catalogs of similar genetic information. This document describes the purpose, use, and maintenance of Brovine.


Crisis Response Coordination In Online Communities, Hemant Purohit Jun 2013

Crisis Response Coordination In Online Communities, Hemant Purohit

Kno.e.sis Publications

During recent crises, citizens (sensors) are increasingly using social media to share variety of information- situation on the ground, emerging needs, donation offers, damage, etc. In such an evolving ad-hoc community, how can we extract actionable nuggets from the social media streams to aid relief efforts? This doctoral consortium presentation summarizes a framework to analyze social data and manage information to assist coordination by focusing on three important questions to answer: Whom to coordinate with, Why to coordinate and How to coordinate, with exemplary insights for needs and availability from the recent disaster events.


Demo: Approximate Semantic Matching In The Collider Event Processing Engine, Souleiman Hasan, Kalpa Gunaratna, Yongrui Qin, Edward Curry Jun 2013

Demo: Approximate Semantic Matching In The Collider Event Processing Engine, Souleiman Hasan, Kalpa Gunaratna, Yongrui Qin, Edward Curry

Kno.e.sis Publications

This demo presents a use case from the energy management domain. It builds upon previous work on approximate semantic matching of heterogeneous events and compares two semantic matching scenarios: exact and approximate. It illustrates how a large number of exact matching event subscriptions are needed to match heterogeneous power consumption events. It then demonstrates how a small number of approximate semantic matching subscriptions are needed but possibly with a lower true positives/negatives performance. The demo is delivered via the COLLIDER approximate event processing engine currently under development in DERI.


Preparing Detailed 3d Building Models For Google Earth Integration, Linh Truong-Hong, Thanh Thoa Pham Thi, Junjun Yin, James Carswell Jun 2013

Preparing Detailed 3d Building Models For Google Earth Integration, Linh Truong-Hong, Thanh Thoa Pham Thi, Junjun Yin, James Carswell

Conference papers

Today's spatially aware users are becoming more interested in retrieving personalised and task relevant information, requiring detailed 3D city models linked to non-spatial attribute data. However, current implementations of 3D city models are typically LoD2 that don't include geometric or attribute details about many visible features (e.g. rooms) of a building. As such, valueadded applications developed for web-based and wireless platforms are limited to querying for available non-spatial business data at the building level only. To overcome this, geometrically accurate 3D building models are necessary to enable users to visualize, interact, and query for task specific non-spatial business data. This …


T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni Jun 2013

T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni

Research Collection School Of Computing and Information Systems

Nowadays, big cities are suffering from severe traffic congestion as a result of the continuing increase in vehicles. Taxis equipped with GPS can be viewed as sensors of the traffic situation in city. However, trajectory data generated by taxi’s GPS traces are often high-dimensional and contain large spatial and temporal attributes, which pose challenges for analysts. In this paper, based on taxi trajectory data, we present an interactive visual analytics system, T-Watcher, for monitoring and analyzing complex traffic situations in big cities. Users are able to use a carefully designed interface to monitor and inspect data interactively from three levels …


Visual Tracking Via Locality Sensitive Histograms, Shengfeng He, Qingxiong Yang, Rynson W.H. Lau, Jian Wang, Ming-Hsuan Yang Jun 2013

Visual Tracking Via Locality Sensitive Histograms, Shengfeng He, Qingxiong Yang, Rynson W.H. Lau, Jian Wang, Ming-Hsuan Yang

Research Collection School Of Computing and Information Systems

This paper presents a novel locality sensitive histogram algorithm for visual tracking. Unlike the conventional image histogram that counts the frequency of occurrences of each intensity value by adding ones to the corresponding bin, a locality sensitive histogram is computed at each pixel location and a floating-point value is added to the corresponding bin for each occurrence of an intensity value. The floating-point value declines exponentially with respect to the distance to the pixel location where the histogram is computed, thus every pixel is considered but those that are far away can be neglected due to the very small weights …