Physical Sciences and Mathematics Commons^™

Nonrigid Shape Recovery By Gaussian Process Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Liu

Research Collection School Of Computing and Information Systems

Most state-of-the-art nonrigid shape recovery methods usually use explicit deformable mesh models to regularize surface deformation and constrain the search space. These triangulated mesh models heavily relying on the quadratic regularization term are difficult to accurately capture large deformations, such as severe bending. In this paper, we propose a novel Gaussian process regression approach to the nonrigid shape recovery problem, which does not require to involve a predefined triangulated mesh model. By taking advantage of our novel Gaussian process regression formulation together with a robust coarse-to-fine optimization scheme, the proposed method is fully automatic and is able to handle large …

Information Sharing And Strategic Signaling In Supply Chains, Robert J. Kauffman, Hamid Mohtadi

Research Collection School Of Computing and Information Systems

Information sharing in procurement occurs in rich and varied industry contexts in which managerial decisions are made and organizational strategy is formulated. We explore how information sharing ought to work in procurement contexts that involve investments in inter-organizational information systems (IOS) and collaborative planning, forecasting and replenishment (CPFR) practices. How and under what circumstances does a firm that plays the role of a supply chain buyer decide to share information on key variables, such as point-of-sale consumer demand data with its supplier, up the supply chain? This is a key issue that crosses the boundary between supply chain management and …

A Revisit Of Generative Model For Automatic Image Annotation Using Markov Random Fields, Yu Xiang, Xiangdong Zhou, Tat-Seng Chua, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many well designed and sophisticated methods. However, when considering semantic context for annotation, the model suffers from the weak learning ability. This is mainly due to the lack of parameter setting and appropriate learning strategy for characterizing the semantic context in the traditional generative model. In this paper, we present a new approach based on Multiple Markov Random Fields (MRF) for semantic context modeling and learning. Differing from previous MRF related AIA approach, we …

Cyber Attacks: Cross-Country Interdependence And Enforcement, Qiu-Hong Wang, Seung Hyun Kim

Research Collection School Of Computing and Information Systems

This study empirically characterizes the interdependence in cyber attacks and examines theimpact from the first international treaty against cybercrimes (Convention on Cybercrimes:Europe Treaty Series No. 185). With the data covering 62 countries over the period from year2003 to 2007, we find that, international cooperation in enforcement as measured by theindicator of joining the Convention on Cybercrimes, deterred cyber attacks originating from anyparticular country by 15.81% ~ 24.77% (in 95% confidence interval). Second, joining theConvention also affected the interdependence in cyber attacks from two angels. First, for anypair of country, closer status in joining or not joining the Convention was associated …

Intentional Learning Agent Architecture, Budhitama Subagdja, Liz Sonenberg, Iyad Rahwan

Research Collection School Of Computing and Information Systems

Dealing with changing situations is a major issue in building agent systems. When the time is limited, knowledge is unreliable, and resources are scarce, the issue becomes more challenging. The BDI (Belief-Desire-Intention) agent architecture provides a model for building agents that addresses that issue. The model can be used to build intentional agents that are able to reason based on explicit mental attitudes, while behaving reactively in changing circumstances. However, despite the reactive and deliberative features, a classical BDI agent is not capable of learning. Plans as recipes that guide the activities of the agent are assumed to be static. …

Enterprise Information Technology Organizational Flexibility : Managing Uncertainty And Change, Karen Prast Patten

Dissertations

Chief Information Officers (CIOs) lead enterprise information technology organizations (EITOs) in today's dynamic competitive business environment. CIOs deal with external and internal environmental changes, changing internal customer needs, and rapidly changing technology. New models for the organization include flexibility and suggest that CIOs should create and manage an enterprise IT organization that is more flexible in order to manage change and prepare for uncertainty, but they do not define what is meant by flexibility.

The first objective of this exploratory and ethnographic research study was to understand how uncertainty and unexpected change are currently managed by CIOs. The second was …

Leadership In Partially Distributed Teams, Linda Plotnick

Dissertations

Inter-organizational collaboration is becoming more common. When organizations collaborate they often do so in partially distributed teams (PDTs). A PDT is a hybrid team that has at least one collocated subteam and at least two subteams that are geographically distributed and communicate primarily through electronic media. While PDTs share many characteristics with both traditionally collocated and fully distributed teams, they also have unique characteristics and issues.

This dissertation reports on a field study of PDTs conducted over two semesters with student participants, This research was conducted as part of a larger series of studies investigating PDTs, In these studies, participants …

The Influence Of Organizational And Information Systems Factors On The Effectiveness Of Post-Merger Technology Integration, Gianilda A. Morsell

Dissertations

This dissertation explores how ten specific organizational and information systems factors influence post-merger IS integration success, and the role that degree of IS integration plays in moderating the influence these factors may have on IS integration success. Data were gathered, using a self-administered survey instrument, from senior IS executives at firms that experienced a U.S. public merger greater than $25 million between 2004 and 2007. Support is found for the study's Conceptual Model, indicating that all ten factors in unison influence post-merger IS integration success. The data support the hypotheses that quality of merger planning, quality of communication of merger …

My Guild, My Team: Applying The Technology Capabilities Of Massively Multiplayer Online Games To Virtual Project Teams, Dawn Owens, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Millions of people are playing Massively Multiplayer Online Games (MMOGs), a computer game genre where thousands of players interact daily in highly complex virtual world environments. These players self-organize, develop skills, and acquire various roles. MMOGs appear to mirror the complexity of the business context while offering unique technology capabilities that appear to encourage group participation and emergent leadership. Managing a remote workforce across different time zones, geography and culture requires effective virtual collaboration and management of communication, coordination challenges and control issues. Therefore, the purpose of this paper is to explore the unique technology capabilities of MMOGs and propose …

Situation Awareness Via Abductive Reasoning For Semantic Sensor Data: A Preliminary Report, Krishnaprasad Thirunarayan, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Semantic sensor Web enhances raw sensor data with spatial, temporal, and thematic annotations to enable high-level reasoning. In this paper, we explore how abductive reasoning framework can benefit formalization and interpretation of sensor data to garner situation awareness. Specifically, we show how abductive logic programming techniques, in conjunction with symbolic knowledge rules, can be used to detect inconsistent sensor data and to generate human accessible description of the state of the world from consistent subset of the sensor data. We also show how trust/belief information can be incorporated into the interpreter to enhance reliability. For concreteness, we formalize weather domain …

Semsos: Semantic Sensor Observation Service, Cory Andrew Henson, Josh Pschorr, Amit P. Sheth, Krishnaprasad Thirunarayan

Kno.e.sis Publications

Sensor observation service (SOS) is a Web service specification defined by the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) group in order to standardize the way sensors and sensor data are discovered and accessed on the Web. This standard goes a long way in providing interoperability between repositories of heterogeneous sensor data and applications that use this data. Many of these applications, however, are ill equipped at handling raw sensor data as provided by SOS and require actionable knowledge of the environment in order to be practically useful. There are two approaches to deal with this obstacle, make the …

Semisupervised Svm Batch Mode Active Learning With Applications To Image Retrieval, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learning is popular for its application to relevance feedback in CBIR. However, the regular SVM active learning has two main drawbacks when used for relevance feedback. First, SVM often suffers from learning with a small number of labeled examples, which is the case in relevance feedback. Second, SVM active learning usually does not take into account the redundancy among examples, and therefore could select multiple examples in relevance feedback that are similar (or even identical) to …

Zeros And Ones, M. Thulasidas

Research Collection School Of Computing and Information Systems

Computers are notorious for their infuriatingly literal obedience. I am sure anyone who has ever worked with a computer has come across the lack of empathy on its part – it follows our instructions to the dot, yet ends up accomplishing something altogether different from what we intend. Let’s spare a thought for the way your glorified adding machine makes sense of things

Predicting Outcome For Collaborative Featured Article Nomination In Wikipedia, Meiqun Hu, Ee Peng Lim, Ramayya Krishnan

Research Collection School Of Computing and Information Systems

In Wikipedia, good articles are wanted. While Wikipedia relies on collaborative effort from online volunteers for quality checking, the process of selecting top quality articles is time consuming. At present, the duty of decision making is shouldered by only a couple of administrators. Aiming to assist in the quality checking cycles so as to cope with the exponential growth of online contributions to Wikipedia, this work studies the task of predicting the outcome of featured article (FA) nominations. We analyze FA candidate (FAC) sessions collected over a period of 3.5 years, and examine the extent to which consensus has been …

A Novel Framework For Efficient Automated Singer Identification In Large Music Databases, Jialie Shen, John Shepherd, Bin Cui, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

Over the past decade, there has been explosive growth in the availability of multimedia data, particularly image, video, and music. Because of this, content-based music retrieval has attracted attention from the multimedia database and information retrieval communities. Content-based music retrieval requires us to be able to automatically identify particular characteristics of music data. One such characteristic, useful in a range of applications, is the identification of the singer in a musical piece. Unfortunately, existing approaches to this problem suffer from either low accuracy or poor scalability. In this article, we propose a novel scheme, called Hybrid Singer Identifier (HSI), for …

A Study Of Relevance Feedback In Vector Space Model, Deepthi Katta

UNLV Theses, Dissertations, Professional Papers, and Capstones

Information Retrieval is the science of searching for information or documents based on information need from a huge set of documents. It has been an active field of research since early 19^th century and different models of retrieval came in to existence to cater the information need.

This thesis starts with understanding some of the basic information retrieval models, followed by implementation of one of the most popular statistical retrieval model known as Vector Space Model. This model ranks the documents in the collection based on the similarity measure calculated between the query and the respective document. The user …

A Self-Organizing Neural Network Architecture For Intentional Planning Agents, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic representation in developing agents. Some novel techniques are introduced that enables the neural network to process and manipulate sequential and hierarchical structures of information. It is suggested that by incorporating intentional agent model which relies on explicit symbolic description with self-organizing neural networks that are good at learning and recognizing patterns, the best from both sides can be exploited. This paper demonstrates that plans can be represented as weighted connections and reasoning processes can …

Sharing Hierarchical Mobile Multimedia Content Using The Mobitop System, Quang Minh Nguyen, Thi Nhu Quynh Kim, Dion Hoe-Lian Goh, Ee-Peng Lim, Yin-Leng Theng, Kalyani Chatterjea, Chew-Hung Chang, Aixin Sun, Khasfariyati Razikin

Research Collection School Of Computing and Information Systems

We introduce MobiTOP (Mobile Tagging of Objects and People), a map-based application which allows users to contribute and share geo-referenced multimedia annotations via mobile devices. An important feature of MobiTOP is that annotations are hierarchical, allowing annotations to be annotated to an arbitrary depth. MobiTOP's interface was designed using a participatory design methodology to ensure that the user interface meets the needs of potential users. In an evaluation, a group of student-teachers involved in a geographical field study were tasked to collaboratively identify rock formations using the MobiTOP system. The students who were in the field were guided by their …

On Mining Rating Dependencies In Online Collaborative Rating Networks, Hady W. Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

The trend of social information processing sees e-commerce and social web applications increasingly relying on user-generated content, such as rating, to determine the quality of objects and to generate recommendations for users. In a rating system, a set of reviewers assign to a set of objects different types of scores based on specific evaluation criteria. In this paper, we seek to determine, for each reviewer and for each object, the dependency between scores on any two given criteria. A reviewer is said to have high dependency between a pair of criteria when his or her rating scores on objects based …

Open Library, William Osei-Poku

William Osei-Poku

No abstract provided.

Mind Map, William Osei-Poku

William Osei-Poku

No abstract provided.

Encoded Archival Description, William Osei-Poku

William Osei-Poku

No abstract provided.

Joint Ranking For Multilingual Web Search, Wei Gao, Cheng Niu, Ming Zhou, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s language. Existing approaches are focused on combining relevance scores of different retrieval settings, but do not learn the ranking function directly. We approach Web MLIR ranking within the learning-to-rank (L2R) framework. Besides adopting popular L2R algorithms to MLIR, a joint ranking model is created to exploit the correlations among documents, and induce the joint relevance probability for all the documents. Using this method, the relevant documents of one language can be leveraged to improve …

Using Gis To Locate Areas For Growing Quality Coffee In Honduras, Ellen Mickle

Department of Environmental Studies: Undergraduate Student Theses

Abstract Small-scale coffee producers worldwide remain vulnerable to price fluctuations after the 1999-2003 coffee crisis. One way to increase small-scale farmer economic resilience is to produce a more expensive product, such as quality coffee. There is growing demand in coffee-producing and coffee-importing countries for user-friendly tools that facilitate the marketing of quality coffee. The purpose of this study is to develop a prototypical quality coffee marketing tool in the form of a GIS model that identifies regions for producing quality coffee in a country not usually associated with quality coffee, Honduras. Maps of areas for growing quality coffee were produced …

Opaque: Protecting Path Privacy In Directions Search, Ken C. K. Lee, Wang-Chien Lee, Hong Va Leong, Baihua Zheng

Research Collection School Of Computing and Information Systems

Directions search returns the shortest path from a source to a destination on a road network. However, the search interests of users may be exposed to the service providers, thus raising privacy concerns. For instance, a path query that finds a path from a resident address to a clinic may lead to a deduction about "who is related to what disease". To protect user privacy from accessing directions search services, we introduce the OPAQUE system, which consists of two major components: (1) an obfuscator that formulates obfuscated path queries by mixing true and fake sources/destinations; and (2) an obfuscated path …

An Incremental Threshold Method For Continuous Text Search Queries, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

A text filtering system monitors a stream of incoming documents, to identify those that match the interest profiles of its users. The user interests are registered at a server as continuous text search queries. The server constantly maintains for each query a ranked result list, comprising the recent documents (drawn from a sliding window) with the highest similarity to the query. Such a system underlies many text monitoring applications that need to cope with heavy document traffic, such as news and email monitoring. In this paper, we propose the first solution for processing continuous text queries efficiently. Our objective is …

Exploring Hierarchically Organized Georeferenced Multimedia Annotations In The Mobitop System, Thi Nhu Quynh Kim, Khasfariyati Razikin, Dion Hoe-Lian Goh, Yin Leng Theng, Quang Minh Nguyen, Ee-Peng Lim, Aixin Sun, Chew Hung Chang, Kalyani Chatterjea

Research Collection School Of Computing and Information Systems

We introduce MobiTOP, a map-based interface for accessing hierarchically organized georeferenced annotations. Each annotation contains multimedia content associated with a location, and users are able to annotate existing annotations, in effect creating a hierarchy. MobiTOPs interface was designed using a participatory design methodology to ensure that the user interface meets the needs of potential users. A pilot study to compare the MobiTOP interface with a space-filling thumbnail (SFT) interface suggested that participants preferred the MobiTOP design for accessing annotations even though the SFT interface was conceptually easier to understand resources.

Efficient Evaluation Of Multiple Preference Queries, Hou U Leong, Nikos Mamaoulis, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Consider multiple users searching for a hotel room, based on size, cost, distance to the beach, etc. Users may have variable preferences expressed by different weights on the attributes of the searched objects. Although individual preference queries can be evaluated by selecting the object in the database with the highest aggregate score, in the case of multiple requests at the same time, a single object cannot be assigned to more than one users. The challenge is to compute a fair 1-1 matching between the queries and a subset of the objects. We model this as a stable-marriage problem and propose …

Mitigating Insider Sabotage And Espionage: A Review Of The United States Air Force's Current Posture, Erika C. Leach

Theses and Dissertations

The security threat from malicious insiders affects all organizations. Mitigating this problem is quite difficult due to the fact that (1) there is no definitive profile for malicious insiders, (2) organizations have placed trust in these individuals, and (3) insiders have a vast knowledge of their organization’s personnel, security policies, and information systems. The purpose of this research is to analyze to what extent the United States Air Force (USAF) security policies address the insider threat problem. The policies are reviewed in terms of how well they align with best practices published by the Carnegie Mellon University Computer Emergency Readiness …

Gis Hub For Pace Community Service, Collaborative Project

Dyson College- Seidenberg School of CSIS : Collaborative Projects and Presentations

This entry adheres to the use of the quad chart template to provide a succinct description only of the current research project undertaken by the participants. It provides for the folowing information

1. Participants and Affiliations
2. Overall Project Goals
3. Illustrative picture
4. Specific research/artistic/pedagogic foci