Use of Dynamic Technologies for Web-enabled Database Management Systems

In this paper we consider two computer systems and the dynamic Web technologies they are using. Different contemporary dynamic web technologies are described in details and their advantages and disadvantages have been shown. Specific applications are developed, clinic and studying systems, and their programming models are described. Finally we implement these two applications in the students education process: Online studying has been tested in the Technical University – Varna, Web based clinic system has been used for practical education of the students in the Medical College - Sofia, branch V. Tarnovo

ImageSpace: An Environment for Image Ontology Management

More and more researchers have realized that ontologies will play a critical role in the development of the Semantic Web, the next generation Web in which content is not only consumable by humans, but also by software agents. The development of tools to support ontology management including creation, visualization, annotation, database storage, and retrieval is thus extremely important. We have developed ImageSpace, an image ontology creation and annotation tool that features (1) full support for the standard web ontology language DAML+OIL; (2) image ontology creation, visualization, image annotation and display in one integrated framework; (3) ontology consistency assurance; and (4) storing ontologies and annotations in relational databases. It is expected that the availability of such a tool will greatly facilitate the creation of image repositories as islands of the Semantic Web.

The Wide-Field Plate Database: Development and Access via Internet

ACM Computing Classification System (1998): J.2.

Adaptive Document Image Binarization with Application in Processing Astronomical Logbooks

ACM Computing Classification System (1998): I.7, I.7.5.

When is an image a health claim? A false-recollection method to detect implicit inferences about products' health benefits

Objective: Images on food and dietary supplement packaging might lead people to infer (appropriately or inappropriately) certain health benefits of those products. Research on this issue largely involves direct questions, which could (a) elicit inferences that would not be made unprompted, and (b) fail to capture inferences made implicitly. Using a novel memory-based method, in the present research, we explored whether packaging imagery elicits health inferences without prompting, and the extent to which these inferences are made implicitly. Method: In 3 experiments, participants saw fictional product packages accompanied by written claims. Some packages contained an image that implied a health-related function (e.g., a brain), and some contained no image. Participants studied these packages and claims, and subsequently their memory for seen and unseen claims were tested. Results: When a health image was featured on a package, participants often subsequently recognized health claims that—despite being implied by the image—were not truly presented. In Experiment 2, these recognition errors persisted despite an explicit warning against treating the images as informative. In Experiment 3, these findings were replicated in a large consumer sample from 5 European countries, and with a cued-recall test. Conclusion: These findings confirm that images can act as health claims, by leading people to infer health benefits without prompting. These inferences appear often to be implicit, and could therefore be highly pervasive. The data underscore the importance of regulating imagery on product packaging; memory-based methods represent innovative ways to measure how leading (or misleading) specific images can be. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

LCME Acreditation Database Draft - March 2007

A Draft of the LCME Accreditation Database prepared for the College of Medicine's Second Accreditation Planning Weekend, March 10, 2007.

Database/Knowledge Base Development

Document detialing plans to develop the Medical Library's knowledge base collection. Provides an overview of databases and knowledge bases, as well as recommended databases.

A multimedia indexing and retrieval framework for multimedia database systems

The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval, by which a robust video shot/scene segmentation method is developed based on low-level visual feature comparison, object tracking, and audio analysis. Based on shot boundaries, a novel data mining framework is further proposed to detect events in soccer videos, while fully utilizing the multi-modality features and object information obtained through video shot/scene detection. ^ Another contribution of this dissertation is the potential of the above techniques to be tailored and applied to other multimedia applications. This is demonstrated by their utilization in traffic video surveillance applications. The enhanced image segmentation algorithm, coupled with an adaptive background learning algorithm, improves the performance of vehicle identification. A sophisticated object tracking algorithm is proposed to track individual vehicles, while the spatial and temporal relationships of vehicle objects are modeled by an abstract semantic model. ^

DIMUSE: An integrated framework for distributed multimedia system with database management and security support

With the recent explosion in the complexity and amount of digital multimedia data, there has been a huge impact on the operations of various organizations in distinct areas, such as government services, education, medical care, business, entertainment, etc. To satisfy the growing demand of multimedia data management systems, an integrated framework called DIMUSE is proposed and deployed for distributed multimedia applications to offer a full scope of multimedia related tools and provide appealing experiences for the users. This research mainly focuses on video database modeling and retrieval by addressing a set of core challenges. First, a comprehensive multimedia database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) is proposed to model high dimensional media data including video objects, low-level visual/audio features, as well as historical access patterns and frequencies. The associated retrieval and ranking algorithms are designed to support not only the general queries, but also the complicated temporal event pattern queries. Second, system training and learning methodologies are incorporated such that user interests are mined efficiently to improve the retrieval performance. Third, video clustering techniques are proposed to continuously increase the searching speed and accuracy by architecting a more efficient multimedia database structure. A distributed video management and retrieval system is designed and implemented to demonstrate the overall performance. The proposed approach is further customized for a mobile-based video retrieval system to solve the perception subjectivity issue by considering individual user's profile. Moreover, to deal with security and privacy issues and concerns in distributed multimedia applications, DIMUSE also incorporates a practical framework called SMARXO, which supports multilevel multimedia security control. SMARXO efficiently combines role-based access control (RBAC), XML and object-relational database management system (ORDBMS) to achieve the target of proficient security control. A distributed multimedia management system named DMMManager (Distributed MultiMedia Manager) is developed with the proposed framework DEMUR; to support multimedia capturing, analysis, retrieval, authoring and presentation in one single framework.

Comparison of medical and forensic profiling potential of volatile biomarkers from different biological specimens from individuals and across populations

There is limited scientific knowledge on the composition of human odor from different biological specimens and the effect that physiological and psychological health conditions could have on them. There is currently no direct comparison of the volatile organic compounds (VOCs) emanating from different biological specimens collected from healthy individuals as well as individuals with certain diagnosed medical conditions. Therefore the question of matching VOCs present in human odor across various biological samples and across health statuses remains unanswered. The main purpose of this study was to use analytical instrumental methods to compare the VOCs from different biological specimens from the same individual and to compare the populations evaluated in this project. The goals of this study were to utilize headspace solid-phase microextraction gas chromatography mass spectrometry (HS-SPME-GC/MS) to evaluate its potential for profiling VOCs from specimens collected using standard forensic and medical methods over three different populations: healthy group with no diagnosed medical or psychological condition, one group with diagnosed type 2 diabetes, and one group with diagnosed major depressive disorder. The pre-treatment methods of collection materials developed for the study allowed for the removal of targeted VOCs from the sampling kits prior to sampling, extraction and analysis. Optimized SPME-GC/MS conditions has been demonstrated to be capable of sampling, identifying and differentiating the VOCs present in the five biological specimens collected from different subjects and yielded excellent detection limits for the VOCs from buccal swab, breath, blood, and urine with average limits of detection of 8.3 ng. Visual, Spearman rank correlation, and PCA comparisons of the most abundant and frequent VOCs from each specimen demonstrated that each specimen has characteristic VOCs that allow them to be differentiated for both healthy and diseased individuals. Preliminary comparisons of VOC profiles of healthy individuals, patients with type 2 diabetes, and patients with major depressive disorder revealed compounds that could be used as potential biomarkers to differentiate between healthy and diseased individuals. Finally, a human biological specimen compound database has been created compiling the volatile compounds present in the emanations of human hand odor, oral fluids, breath, blood, and urine.

Florida Board of Governors Meeting Florida International University Medical School Approval

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FIU Medical Library Stacks and Computers

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FIU Medical Library Computers

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