Physical Sciences and Mathematics Commons^™

A Content-Driven Reputation System For The Wikipedia, B. Thomas Adler, Luca De Alfaro

Luca de Alfaro

On-line forums for the collaborative creation of bodies of information are a phenomenon of rising importance; the Wikipedia is one of the best-known examples. The open nature of such forums could benefit from a notion of reputation for its authors. Author reputation could be used to flag new contributions from low-reputation authors, and it could be used to allow only authors with good reputation to contribute to controversial or critical pages. A reputation system for the Wikipedia would also provide an incentive to give high-quality contributions.

We present in this paper a novel type of content-driven reputation system for Wikipedia …

Creating Custom Containers With Generative Techniques, Gabriel A. Moreno

Gabriel A. Moreno

Component containers are a key part of mainstream component technologies, and play an important role in separating nonfunctional concerns from the core component logic. This paper addresses two different aspects of containers. First, it shows how generative programming techniques, using AspectC++ and metaprogramming, can be used to generate stubs and skeletons without the need for special compilers or interface description languages. Second, the paper describes an approach to create custom containers by composing different non-functional features. Unlike component technologies such as EJB, which only support a predefined set of container types, this approach allows different combinations of non-functional features to …

What Users Say They Want In Documentation, David G. Novick, Karen Ward

David G. Novick

While earlier work provided a partial view of users’ preferences about manuals, for most users in most work contexts the important question remains open: What do users want in documentation? This paper presents the results of a study in which a diverse cross-section of 25 users was interviewed in depth about their needs and preferences with respect to software help systems, whether printed or on-line, that they use at work. The study’s participants indicated that they preferred documentation, whether online or printed, that is easy to navigate, provides explanations at an appropriate level of technical detail, enables finding as well …

Magnifying-Lens Abstraction For Markov Decision Processes, Luca De Alfaro, Pritam Roy

Luca de Alfaro

We present a novel abstraction technique which allows the analysis of reachability and safety properties of Markov decision processes with very large state spaces. The technique, called magnifying-lens abstraction, copes with the state-explosion problem by partitioning the state-space into regions, and by computing upper and lower bounds for reachability and safety properties on the regions, rather than on the states. To compute these bounds, magnifying-lens abstraction iterates over the regions, considering the concrete states of each region in turn, as if one were sliding across the abstraction a magnifying lens which allowed viewing the concrete states. The algorithm adaptively refines …

An Open Framework Supporting Multimedia Web Services, Jia Zhang, Jen-Yao Chung

Jia Zhang

No abstract provided.

Cryptogram Decoding For Optical Character Recognition, Gary Huang, Erik G. Learned-Miller, Andrew Mccallum

Erik G Learned-Miller

OCR systems for printed documents typically require large numbers of font styles and character models to work well. When given an unseen font, performance degrades even in the absence of noise. In this paper, we perform OCR in an unsupervised fashion without using any character models by using a cryptogram decoding algorithm. We present results on real and artificial OCR data.

The Umass Mobile Manipulator Uman: An Experimental Platform For Autonomous Mobile Manipulation, Dov Katz, Emily Horrell, Yuandong Yang, Brendan Burns, Thomas Buckley, Anna Grishkan, Volodymyr Zhylkovskyy, Oliver Brock, Erik G. Learned-Miller

Erik G Learned-Miller

Object identification is the task of identifying specific objects belonging to the same class such as cars. We often need to recognize an object that we have only seen a few times. In fact, we often observe only one example of a particular object before we need to recognize it again. Thus we are interested in building a system which can learn to extract distinctive markers from a single example and which can then be used to identify the object in another image as “same ” or “different”. Previous work by Ferencz et al. introduced the notion of hyper-features, which …

Bi-Level Clustering Of Mixed Categorical And Numerical Biomedical Data, Bill Andreopoulos, Aijun An, Xiaogang Wang

William B. Andreopoulos

Economics Of Information Security Investment In The Case Of Simultaneous Attacks, C. Derrick Huang, Qing Hu, Ravi S. Behara

Qing Hu

With billions of dollars being spent on information security related products and services each year, the economics of information security investment has become an important area of research, with significant implications for management practices. Drawing on recent studies that examine optimal security investment levels under various attack scenarios, we propose an economic model that considers simultaneous attacks from multiple external agents with distinct characteristics, and derive optimal investments based on the principle of benefit maximization. The relationships among the major variables, such as systems vulnerability, security breach probability, potential loss of security breach, and security investment levels, are investigated via …

A Research Capability On Management Of Engineering And Technology, Arcot Desai Narasimhalu

Arcot Desai NARASIMHALU

Companies, private and publicly funded research institutions have been engaged in research projects and research programs. This paper describes a research capability maturity model for managing technological innovations. The insights for this proposal were derived from studying a variety of research organizations for managing technological innovations in a publicly funded research institute in Singapore. The model was implemented over a period of time with different degrees of success in Kent Ridge Digital Labs, Singapore which has since been renamed Institute for Infocomm Research. The suggested maturity model has five layers – Ad-Hoc, Directed, Managed, Optimized, and Outsourced. Every research organization …

Homeland Security: Engaging The Frontlines - Symposium Proceedings, George H. Baker, Cheryl J. Elliott

George H Baker

The rise of the American homeland security endeavor under the leadership of the new Department of Homeland Security has been heralded by several major national strategy documents. These documents have served to organize efforts at top levels within the government and industry. However, the national strategy guidance is not getting to many organizations and people at the grass-roots level who can make the most difference in preventing attacks, protecting systems, and recovering from catastrophic events, viz. the general citizenry, private infrastructure owners, and local governments. To better understand grass-roots issues and solutions, James Madison University, in cooperation with the Federal …

Biochemical Characterization Of The Major Sorghum Grain Peroxidase, Mamoudou H. Dicko, Harry Gruppen, Riet Hilhorst, Alphons G. J. Voragen, Willen W. H. Van Berkel

Pr. Mamoudou H. DICKO, PhD

Functional Connectivity In A Baseline Resting-State Network In Autism, Vladimir Cherkassky, Rajesh Kana, Timothy Keller, Marcel Just

Marcel Adam Just

No abstract provided.

Service Grid For Business Computing, Zongwei Luo, Jia Zhang, Rosa Badia

Jia Zhang

In this chapter, we will introduce an advanced topic of grid computing – Web services-oriented grid for business computing. Web services represent a new concept of computing that enables diverse and distributed resources to communicate with each other based upon a set of standards. We will discuss what values the marriage of Web services and grid computing can bring to business computing and the current state of the art of the field. The layout of the chapter is as follows: Grid computing overview; Web services orientation; Service oriented grid; Integrated service platform for integration; and Challenges and considerations.

Detecting Acromegaly: Screening For Disease With A Morphable Model, Erik G. Learned-Miller, Qifeng Lung, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, Ralph Miller

Erik G Learned-Miller

Acromegaly is a rare disorder which affects about 50 of every million people. The disease typically causes swelling of the hands, feet, and face, and eventually permanent changes to areas such as the jaw, brow ridge, and cheek bones. The disease is often missed by physicians and progresses beyond where it might if it were identified and treated earlier. We consider a semi-automated approach to detecting acromegaly, using a novel combination of support vector machines (SVMs) and a morphable model. Our training set consists of 24 frontal photographs of acromegalic patients and 25 of disease-free subjects. We modelled each subject's …

Privacy Issues Of Applying Rfid In Retail Industry, Haifei Li, Patrick C.K. Hung, Jia Zhang, David Ahn

Jia Zhang

This case study describes the privacy issues of applying Radio Frequency Identification (RFID) in the retail industry. With the dramatic price drop of RFID tags, it is possible that RFID be applied to individual items sold by a retailer. However, the RFID technology poses critical privacy challenges. In this study, we analyze the potential privacy issue of RFID utilization, and we propose a privacy authorization model aiming for precisely defining RFID privacy policies for the retail industry.

Brain Correlates Of Discourse Processing: An Fmri Investigation Of Irony And Conventional Metaphor Comprehension, Zohar Eviatar, Marcel Adam Just

Marcel Adam Just

No abstract provided.

Sentence Comprehension In Autism: Thinking In Pictures With Decreased Functional Connectivity, Rajesh K. Kana, Timothy A. Keller, Vladimir L. Cherkassky, Nancy J. Minshew, Marcel Adam Just

Marcel Adam Just

No abstract provided.

Algorithms For Optimizing Bandwidth Costs On The Internet, Micah Adler, Ramesh Sitaraman, Harish Venkataramani

Ramesh Sitaraman

Content Delivery Networks (CDNs) deliver web content to end-users from a large distributed platform of web servers hosted in data centers belonging to thousands of Internet Service Providers (ISPs) around the world. The bandwidth cost incurred by a CDN is the sum of the amounts it pays each ISP for routing traffic from its servers located in that ISP out to end-users. A large enterprise may also contract with multiple ISPs to provide redundant Internet access for its origin infrastructure using technologies such as multihoming and mirroring, thereby incurring a significant bandwidth cost across multiple ISPs. This paper initiates the …

Auction-Based Pricing Model For Web Service Providers, Jia Zhang, Ning Zhang, Liang-Jie Zhang

Jia Zhang

Applying auctions to Web services selection and invocation calls for examination due to the unique features of Web services, such as interoperable machine-to-machine interactions and reenterable bargaining services. In this paper we propose a formal model for Web services-based auctions. Examining one-sided sealed auction type, we prove mathematically that service requestors’ risk preferences could lead to different pricing strategies for service providers towards higher profit. We argue that Service Level Agreement (SLA) documents can be used to analyze service requestors’ preferences. On top of WS-Agreement, we propose a basic service requestor risk preference elicitation algorithm, as well as a historical …

Data Driven Image Models Through Continuous Joint Alignment, Erik G. Learned-Miller

Erik G Learned-Miller

This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar as possible by removing variability along the known axes of variation. This technique can be used to eliminate "nuisance” variables such as affine deformations from handwritten digits or unwanted bias fields from magnetic resonance images. In addition to separating and modeling the latent images—i.e., the images without the nuisance variables—we can model the nuisance variables themselves, leading to factorized generative image models. When nuisance variable distributions are …

A Hierarchical, Hmmbased Automatic Evaluation Of Ocr Accuracy For A Digital Library Of Books, Shaolei Feng, R. Manmatha

R. Manmatha

A number of projects are creating searchable digital libraries of printed books. These include the Million Book Project, the Google Book project and similar efforts from Yahoo and Microsoft. Content-based on line book retrieval usually requires first converting printed text into machine readable (e.g. ASCII) text using an optical character recognition (OCR) engine and then doing full text search on the results. Many of these books are old and there are a variety of processing steps that are required to create an end to end system. Changing any step (including the scanning process) can affect OCR performance and hence a …

Joint Feature Selection For Object Detection And Recognition, Jerod J. Weinman, Allen Hanson, Erik G. Learned-Miller

Erik G Learned-Miller

Object detection and recognition systems, such as face detectors and face recognizers, are often trained separately and operated in a feed-forward fashion. Selecting a small number of features for these tasks is important to prevent over-fitting and reduce computation. However, when a system has such related or sequential tasks, selecting features for these tasks independently may not be optimal. We propose a framework for choosing features to be shared between object detection and recognition tasks. The result is a system that achieves better performance by joint training and is faster because some features for identification have already been computed for …

Discriminative Training Of Hyper-Feature Models For Object Identification, Vidit Jain, Erik G. Learned-Miller

Erik G Learned-Miller

Object identification is the task of identifying specific objects belonging to the same class such as cars. We often need to recognize an object that we have only seen a few times. In fact, we often observe only one example of a particular object before we need to recognize it again. Thus we are interested in building a system which can learn to extract distinctive markers from a single example and which can then be used to identify the object in another image as “same ” or “different”. Previous work by Ferencz et al. introduced the notion of hyper-features, which …

A Mobile Agents-Based Approach To Test The Reliability Of Web Services, Jia Zhang

Jia Zhang

The paradigm of web services has been transforming the internet from a repository of data into a repository of services, or so-called web services. As more and more web services are published on the internet, how to opt for an appropriate and trustworthy web service poses a big challenge. In this paper we propose a mobile agents-based approach that selects reliable web service components in a cost-effective manner.

Neural Basis Of Dyslexia: A Comparison Between Dyslexic And Non-Dyslexic Children Equated For Reading Ability, Fumiko Hoeft, Arvel Hernandez, Glenn Mcmillon, Heather Taylor-Hill, Jennifer L. Martindale, Ann Meyler, Timothy A. Keller, Wai Ting Siok, Gayle K. Deutsch, Marcel Adam Just, Susan Whitfield-Gabrieli, John D. E. Gabrieli

Marcel Adam Just

No abstract provided.

Improving Recognition Of Novel Input With Similarity, Jerod J. Weinman, Erik G. Learned-Miller

Erik G Learned-Miller

Many sources of information relevant to computer vision and machine learning tasks are often underused. One example is the similarity between the elements from a novel source, such as a speaker, writer, or printed font. By comparing instances emitted by a source, we help ensure that similar instances are given the same label. Previous approaches have clustered instances prior to recognition. We propose a probabilistic framework that unifies similarity with prior identity and contextual information. By fusing information sources in a single model, we eliminate unrecoverable errors that result from processing the information in separate stages and improve overall accuracy. …

Survey Of Computer Supported Business Collaboration In Support Of Business Processes, Carl K. Chang, Jia Zhang, Kai H. Chang

Jia Zhang

No abstract provided.

Controlled Generation Of Hard And Easy Bayesian Networks: Impact On Maximal Clique Size In Tree Clustering, Ole J. Mengshoel, David C. Wilkins, Dan Roth

Ole J Mengshoel

This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. The results are relevant to research on efficient Bayesian network inference, such as computing a most probable explanation or belief updating, since they allow controlled experimentation to determine the impact of improvements to inference algorithms. The results are also relevant to research on machine learning of Bayesian networks, since they support controlled generation of a large number of data sets at a given difficulty level. Our generation algorithms, called BPART and MPART, support controlled but random construction …