Ann Christine Catlin

PYTHIA-II: a knowledge/database system for managing performance data and recommending scientific software

Often scientists need to locate appropriate software for their problems and then select from among many alternatives. We have previously proposed an approach for dealing with this task by processing performance data of the targeted software. This approach has been tested using a customized implementation referred to as PYTHIA. This experience made us realize the complexity of the algorithmic discovery of knowledge from performance data and of the management of these data together with the discovered knowledge. To address this issue, we created PYTHIA-II—a modular framework and system which combines a general knowledge discovery in databases (KDD) methodology and recommender system technologies to provide advice about scientific software/hardware artifacts. The functionality and effectiveness of the system is demonstrated for two existing performance studies using sets of software for solving partial differential equations. From the end-user perspective, PYTHIA-II allows users to specify the problem to be solved and their computational objectives. In turn, PYTHIA-II (i) selects the software available for the users problem (ii) suggests parameter values, and (iii) assesses the recommendation provided. PYTHIA-II provides all the necessary facilities to set up database schemas for testing suites and associated performance data in order to test sets of software. Moreover, it allows easy interfacing of alternative data mining and recommendation facilities. PYTHIA-II is an open-ended system implemented on public domain software and has been used for performance evaluation in several different problem domains.

InsightVideo: toward hierarchical video content organization for efficient browsing, summarization and retrieval

Hierarchical video browsing and feature-based video retrieval are two standard methods for accessing video content. Very little research, however, has addressed the benefits of integrating these two methods for more effective and efficient video content access. In this paper, we introduce InsightVideo, a video analysis and retrieval system, which joins video content hierarchy, hierarchical browsing and retrieval for efficient video access. We propose several video processing techniques to organize the content hierarchy of the video. We first apply a camera motion classification and key-frame extraction strategy that operates in the compressed domain to extract video features. Then, shot grouping, scene detection and pairwise scene clustering strategies are applied to construct the video content hierarchy. We introduce a video similarity evaluation scheme at different levels (key-frame, shot, group, scene, and video.) By integrating the video content hierarchy and the video similarity evaluation scheme, hierarchical video browsing and retrieval are seamlessly integrated for efficient content access. We construct a progressive video retrieval scheme to refine user queries through the interactions of browsing and retrieval. Experimental results and comparisons of camera motion classification, key-frame extraction, scene detection, and video retrieval are presented to validate the effectiveness and efficiency of the proposed algorithms and the performance of the system.

The NEEShub Cyberinfrastructure for Earthquake Engineering

The US Network for Earthquake Engineering Simulation (NEES) operates a shared network of civil engineering experimental facilities aimed at facilitating research on mitigating earthquake damage and loss of life. The NEEShub gateway was created in response to the NEES communitys needs, combining data, simulation, and analysis functionality with collaboration tools.

Development of the International Thymic Malignancy Interest Group International Database: An Unprecedented Resource for the Study of a Rare Group of Tumors

Background: Our knowledge of thymic malignancies has largely been derived from small, single-institution series. Recognition of the need for broad collaboration led to the creation of the International Thymic Malignancy Interest Group (ITMIG) and the development of a large, centralized database to advance knowledge of these rare tumors. Methods: A multidisciplinary Database Committee was convened to define a common set of data elements a priori. Retrospective data were solicited from ITMIG members and collated using standardized fields. Patients with thymoma, thymic carcinoma, or thymic carcinoid were included. Results: Over a 6-month period, 47 institutions spanning 15 countries contributed a total of 6097 cases (mean, 129 [range, 10–1209]). The sex distribution was equal for thymomas, but there was a greater proportion of men with thymic carcinoma and thymic carcinoid (p < 0.0001). Nearly all cases (99%) were treated surgically. WHO type B2 was the most frequent histologic classification among thymomas, whereas squamous was the most common among thymic carcinomas. In total, 38% of patients with thymoma had myasthenia gravis compared with less than or equal to 5% for thymic carcinoma and thymic carcinoid. Median overall survival was 18.9 years (95% confidence interval [CI], 17.4–20.3) for thymoma, 6.8 years (95% CI, 5.5–7.9) for thymic carcinoma, and 7.5 years (95% CI, 6.5–8.5) for thymic carcinoid. Conclusions: The rapid creation of the ITMIG database demonstrates the feasibility of international collaboration for this rare set of malignancies and attests to the engagement of its membership. This database represents the largest collective data set ever assembled and provides an unprecedented resource for research of these tumors.

Medical video mining for efficient database indexing, management and access

To achieve more efficient video indexing and access, we introduce a video database management framework and strategies for video content structure and events mining. The video shot segmentation and representative frame selection strategy are first utilized to parse the continuous video stream into physical units. Video shot grouping, group merging, and scene clustering schemes are then proposed to organize the video shots into a hierarchical structure using clustered scenes, scenes, groups, and shots, in increasing granularity from top to bottom. Then, audio and video processing techniques are integrated to mine event information, such as dialog, presentation and clinical operation, from the detected scenes. Finally, the acquired video content structure and events are integrated to construct a scalable video skimming tool which can be used to visualize the video content hierarchy and event information for efficient access. Experimental results are also presented to evaluate the performance of the proposed framework and algorithms.

SoftLab—a virtual laboratory for computational science

We describe a newly established research project called SoftLab in the area of computational science and computational engineering. The SoftLab project attempts to link physical laboratory experimentation with computer control and simulation to provide a virtual laboratory for computational science. We describe the overall project objectives and then introduce the three focus projects of SoftLab: Two Chemical Engineering SoftLabs (bioseparation and computational electronics) and a Mechanical Engineering SoftLab (computational mechanics). Preliminary results of our efforts are also described.

Video query processing in the VDBMS testbed for video database research

The increased use of video data sets for multimedia-based applications has created a demand for strong video database support, including efficient methods for handling the content-based query and retrieval of video data. Video query processing presents significant research challenges, mainly associated with the size, complexity and unstructured nature of video data. A video query processor must support video operations for search by content and streaming, new query types, and the incorporation of video methods and operators in generating, optimizing and executing query plans. In this paper, we address these query processing issues in two contexts, first as applied to the video data type and then as applied to the stream data type. We first present the query processing functionality of the VDBMS video database management system as a framework designed to support the full range of functionality for video as an abstract data type. We describe two query operators for the video data type which implement the rank-join and stop-after algorithms. As videos may be considered streams of consecutive image frames, video query processing can be expressed as continuous queries over video data streams. The stream data type was therefore introduced into the VDBMS system, and system functionality was extended to support general data streams. From this viewpoint, we present an approach for defining and processing streams, including video, through the query execution engine. We describe the implementation of several algorithms for video query processing expressed as continuous queries over video streams, such as fast forward, region-based blurring and left outer join. We include a description of the window-join algorithm as a core operator for continuous query systems, and discuss shared execution as an optimization approach for stream query processing.

MyPYTHIA: a recommendation portal for scientific software and services

We outline the design of a recommendation system (MyPYTHIA) implemented as a Web portal. MyPYTHIAs design objectives include evaluating the quality and performance of scientific software on Grid platforms, creating knowledge about which software and computational services should be selected for solving particular problems, selecting parameters of software (or of computational services) based on user‐specified computational objectives, providing access to performance data and knowledge bases over the Web and enabling recommendations for targeted application domains. MyPYTHIA uses a combination of statistical analysis, pattern extraction techniques and a database of software performance to map feature‐based representations of problem instances to appropriate software. MyPYTHIAs open architecture allows the user to customize it for conducting individual case studies. We describe the architecture as well as several scientific domains of knowledge enabled by such case studies. Copyright

SANKOFA: a multisite collaboration on paediatric HIV disclosure in Ghana.

With the scale-up of effective antiretroviral therapy in resource-limited settings, many HIV-infected children are now able to survive into adulthood. To achieve this potential, children must navigate normative developmental processes and challenges while living with an unusually complex, stigmatizing, potentially fatal chronic illness and meeting the demands of treatment.Yet many of these children, especially preadolescents, do not know they are HIV-infected. Despite compelling evidence supporting the merits of informing children of their HIV status, there has been little emphasis on equipping the childs caregiver with information and skills to promote disclosure, particularly, when the caregiver faces a variety of sociocultural barriers and is reluctant to do so. In this study, we present the background, process and methods for a first of its kind collaboration that is examining the efficacy of an intervention developed to facilitate the engagement of caregivers in the process of disclosure in a manner suitable to the sociocultural context and developmental age and needs of the child in Ghana. We also report preliminary data that supported the design of the intervention approach and currently available domains of the data system. Finally, we discuss challenges and implications for future research.

VDBMS: A testbed facility for research in video database benchmarking

Abstract.Real-world video-based applications require database technology that is capable of storing digital video in the form of video databases and providing content-based video search and retrieval. Methods for handling traditional data storage, query, search, retrieval, and presentation cannot be extended to provide this functionality. The VDBMS research initiative is motivated by the requirements of video-based applications to search and retrieve portions of video data based on content and by the need for testbed facilities to facilitate research in the area of video database management. In this paper we describe the VDBMS video database research platform, a system that supports comprehensive and efficient database management for digital video. Our fundamental concept is to provide a full range of functionality for video as a well-defined abstract database data type, with its own description, parameters, and applicable methods. Research problems that are addressed by VDBMS to support the handling of video data include MPEG7 standard multimedia content representation, algorithms for image-based shot detection, image processing techniques for extracting low-level visual features, a high-dimensional indexing technique to access the high-dimensional feature vectors extracted by image preprocessing, multimedia query processing and optimization, new query operators, real-time stream management, a search-based buffer management policy, and an access control model for selective, content-based access to streaming video. VDBMS also provides an environment for testing the correctness and scope of new video processing techniques, measuring the performance of algorithms in a standardized way, and comparing the performance of different implementations of an algorithm or component. We are currently developing video component wrappers with well-defined interfaces to facilitate the modification or replacement of video processing components. The ultimate goal of the VDBMS project is a flexible, extensible framework that can be used by the research community for developing, testing, and benchmarking video database technologies.