Karpjoo Jeong

Deploying Scientific Applications to the PRAGMA Grid Testbed: Strategies and Lessons

Recent advances in grid infrastructure and middleware development have enabled various types of applications in science and engineering to be deployed on the grid. The characteristics of these applications and the diverse infrastructure and middleware solutions developed, utilized or adapted by PRAGMA member institutes are summarized. The applications include those for climate modeling, computational chemistry, bioinformatics and computational genomics, remote control of instruments, and distributed databases. Many of the applications are deployed to the PRAGMA grid testbed in routine basis experiments. Strategies for deploying applications without modifications, and those taking advantage of new programming models on the grid are explored and valuable lessons learned are reported. Comprehensive end to end solutions from PRAGMA member institutes that provide important grid middleware components and generalized models of integrating applications and instruments on the grid are also described.

Emotion-Based textile indexing using colors and texture

For a given product or object, predicting human emotions is very important in many business, scientific and engineering applications. There has been a significant amount of research work on the image-based analysis of human emotions in a number of research areas because human emotions are usually dependent on human vision. However, there has been little research on the computer image processing-based prediction, although such approach is naturally very appealing. In this paper, we discuss challenging issues in how to index images based on human emotions and present a heuristic approach to emotion-based image indexing. The effectiveness of image features such as colors, textures, and objects (or shapes) varies significantly depending on the types of emotion or image data. Therefore, we propose adaptive and selective techniques. With respect to six adverse pairs of emotions such as weak-strong, we evaluated the effectiveness of those techniques by applying them to the set of about 160 images in a commercial curtain pattern book obtained from the Dongdaemoon textile shopping mall in Seoul. Our preliminary experimental results showed that the proposed adaptive and selective strategies are effective and improve the accuracy of indexing significantly depending on the type of emotion.

Emotion-based textile indexing using colors, texture and patterns

We propose a textile indexing system which can classify textile images based on human emotions. The emotions can be regarded as emotional reactions of human beings when they view specific textile images. The evaluation system starts with extracting features of textile images such as colors, texture and patterns using various image processing techniques. The proposed system utilizes both fuzzy rules and neural networks. The fuzzy rules are determined for six emotional features which can be formulated with respect to color and texture. On the other hand, the neural network is used for recognizing patterns which can be used in classifying textile images based on the 4 other emotional features. For the machine learning component of the system, we selected 70 subjects so that they could view and annotate 160 textile images using ten pairs of emotional features. The fuzzy rule based component of the system uses color features and texture features in order to predict six pairs of emotional features such as (warm, cold), (gay, sober), (cheerful, dismal), (light, dark), (strong, weak), and (hard, soft). The neural-network based component of the system can predict four pairs of emotional features such as (natural, unnatural), (dynamic, static), (unstable, stable) and (gaudy, plain). Our experimental results showed that the proposed system was effective for predicting human emotions based on textile images and improving the accuracy of indexing the textile images based on emotional features.

Molecular dynamics simulation of cyclosophoroheptadecaose (Cys-A)

The conformational preferences of cyclosophoroheptadecaose (Cys-A), which is a member of a class of cyclic (1→2)-β-D-glucan, were characterized by molecular dynamics simulations. Simulated annealing and constant temperature molecular dynamics simulations were performed on the Cys-A. The simulations produced various types of compact and asymmetrical conformations of Cys-A. Excellent agreement was found between experimental data and corresponding values predicted by molecular modeling. Most glycosidic linkages were concentrated in the lowest energy region of φ-ψ energy map, and the values of radius of gyration (RG) and the nuclear Overhauser effect (NOE) distance data derived from our simulations were finely consistent with the reported experimental values. This result will also give novel insights for the molecular complexation mechanism of Cys-A with various guest chemicals.

An XML Schema-based Semantic Data Integration

Cyber-infrastructures for scientific and engineering applications require integrating heterogeneous legacy data in different formats and from various domains. Such data integration raises challenging issues: (1) Support for multiple independently-managed schemas, (2) Ease of schema evolution, and (3) Simple schema mappings. In order to address these issues, we propose a novel approach to semantic integration of scientific data which uses XML schemas and RDF-based schema mappings. In this approach, XML schema allows scientists to manage data models intuitively and to use commodity XML DBMS tools. A simple RDF-based ontological representation scheme is used for only structural relations among independently-managed XML schemas from different institutes or domains. We present the design and implementation of a prototype system developed for the national cyber-environments for civil engineering research activities in Korea (similar to the NEES project in USA) which is called KOCEDgrid

X-SIGMA: XML Based Simple Data Integration System for Gathering, Managing, and Accessing Scientific Experimental Data in Grid Environments

Effective scientific data management is crucial for e-Science applications. Scientific data management raises challenging requirements: (1) support for not only experimental data but also context data, (2) both schema evolution and integration, (3) and compatibility with legacy data management conventions or environments. In this paper, we present a scientific data management system (called XSIGMA) which is designed to address those issues. X-SIGMA is a Grid-based integrated system for managing, integrating, and accessing scientific experimental data. A prototype system is implemented and has been being used to develop the scientific data management system for the national cyberinfrastructure project called KOCED in Korea.

AirScope: A Micro-Scale Urban Air Quality Management System

In this paper, we present a framework for micro-scale air quality monitoring and sensor management system. The developed system is validated in a preliminary test environment. The test result shows that it is feasible to adopt sensor networks for micro-scale monitoring. In the future, enhancements on the VR core modules will also be investigated such as enhanced interaction devices, mobile sensors, and display devices. Finally, we will also build web-based information portal to be used by citizens whenever the information is needed.

A Web-Based Interactive Monitoring System for Molecular Simulation

Molecular simulation such as molecular dynamics requires high computing capacity of large scale clusters or supercomputers to complete its experiment. Since it is hard to calculate with general computer, high computing power such as grid computing is required through the Web. After the simulation, the result file is created and replicated to the Web. To analysis the experiment, biologist has to download it, but large amount of file takes many times to download and analysis the result. We propose a Web-based interactive monitoring system for molecular simulation. The grid system is used for computing equations of molecular simulations. The results can be viewed through 3D animations and manipulated by interactive manners. The operations can be performed through Web browsers over the Internet. The proposed system was evaluated in performance in comparison with previous approaches. The proposed system enable biologist to analysis the simulation results five times faster than previous tools.

A workflow management and grid computing approach to molecular simulation-based bio/nano experiments

In this paper, we propose an approach to molecular simulation-based experiments which combines workflow management and grid computing techniques to address both the computing issue due to the challenging computation requirement from molecular simulation and the management issue due to distributed, heterogeneous computing platforms. We present a workflow management system customized for such experiments and explain how this workflow system can be integrated with computational grids.

Systematic probing of an atomic charge set of sialic acid disaccharides for the rational molecular modeling of avian influenza virus based on molecular dynamics simulations

A systematic searching approach for an atomic charge set through molecular dynamics simulations is introduced to calculate a reasonable sialic acid carbohydrate conformation with respect to the experimentally observed structures. The present molecular dynamics simulation study demonstrated that B3LYP/6-31G is the most suitable basis set for the sialic acid disaccharides, attaining good agreement with experimental data.