• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.418-421
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• 2003

Surfactant enhanced in-situ soil flushing was peformed to remediate the soil and groundwater at an oil contaminated site, and the effluent solution was treated by the chemical treatment process including DAF(Dissolved Air Flotation). A section from the contaminated site(4.5m$\times$4.5m$\times$6.0m) was selected for the research, which was composed of heterogeneous sandy and silt-sandy soils with average Hydraulic conductivity of 2.0$\times$10$^{-4}$ cm/sec. Two percent of sorbitan monooleate(POE 20) and 0.07% of iso-prophyl alcohol were mixed for the surfactant solution and 3 pore volumes of surfactant solution were injected to remove oil from the contaminant section. Four injection wells and two extraction wells were built in the section to flush surfactant solution. Water samples taken from extraction wells and the storage tank were analyzed by GC(gas-chromatography) for TPH concentration with different time. Five pore volumes of solution were extracted while TPH concentration in soil and groundwater at the section were below the Waste Water Discharge Limit(WWDL). Total 18.5kg of oil (TPH) was removed from the section. The concentration of heavy metals in the effluent solution also increased with the increase of TPH concentration, suggesting that the surfactant enhanced in-situ flushing be available to remove not only oil but heavy metals from contaminated sites. Results suggest that in-situ soil flushing and chemical treatment process including DAF could be a successful process to remediate contaminated sites distributed in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2815-2839
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• 2020

In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1238-1249
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• 2020

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1913-1934
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• 2022

The emergence of technologies like Big data analytics, Industrial Internet of Things, Internet of Things, and applicability of these technologies in various domains leads to increased demand in the underlying execution environment. The demand may be for compute, storage, and network resources. These demands cannot be effectively catered by the conventional cloud environment, which requires an integrated environment. The task of finding an appropriate service provider is tedious for a service consumer as the number of service providers drastically increases and the services provided are heterogeneous in the specification. A service broker is essential to find the service provider for varying service consumer requests. Also, the service broker should be smart enough to make the service providers best fit for consumer requests, ensuring that both service consumer and provider are mutually beneficial. A service broker in an integrated environment named Global Manager is proposed in the paper, which can find an appropriate service provider for every varying service consumer request. The proposed Global Manager is capable of identification of parameters for service negotiation with the service providers thereby making the providers the best fit to the maximum possible extent for every consumer request. The paper describes the architecture of the proposed Global Manager, workflow through the proposed algorithms followed by the pilot implementation with sample datasets retrieved from literature and synthetic data. The experimental results are presented with a few of the future work to be carried out to make the Manager more sustainable and serviceable.

• Journal of Life Science
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• v.30 no.8
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• pp.672-679
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• 2020

Distal myopathy is a clinically and genetically heterogeneous group of degenerative diseases of the distal muscle. Glycogen storage disease type IXD (GSD9D) is a metabolic distal myopathy characterized by muscle deficiency of phosphorylase kinase, a key regulatory enzyme in glycogen metabolism. Affected individuals may develop muscle weakness, degeneration, and cramps, as well as abnormal muscle pain and stiffness after exercise. It has been reported that mutations in the PHKA1 gene which encodes the alpha subunit of muscle phosphorylase kinase cause GSD9D. In this study, we examined a Korean GSD9D family with a c.3314T>C (p.I1105T) mutation in the PHKA1 gene. This mutation has not been previously reported in any mutation database nor was it found in 500 healthy controls. The mutation region is well conserved in various other species, and in silico analysis predicts that it is likely to be pathogenic. To date, only seven mutations in the PHKA1 gene have been documented, and this is the first report of Korean GSD9D patients. This study also describes and compares the clinical symptoms and pathological conditions of previously reported cases and these Korean patients. We believe that our findings will be useful for the molecular diagnosis of GSD9D.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.819-822
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• 2008

The demand against the contents service which is various with improvement capability of the mobile device. But the capability of heterogeneous mobile device to display contents has a difference from the side of the hardware, software, network conditions so the adaptation of contents is a solution to overcome this difference. This adaptation of contents is based on profile(DDL : Device Description Language) but there is no system which manages the profile efficiently. In this paper, we designed independent DDR(Device Description Repository) system that offers storage and optimized profiles processed by searching and recombination with request conditions.

• Journal of KIISE:Information Networking
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• v.32 no.4
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• pp.471-482
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• 2005

The high-speed network permits Grid computing to handle large problem of management areas and share various computational resources. As there are many resources and changes of them in Grid computing, the resources should be detected effectively and matched correctly with tasks to provide high performance. In this paper, we propose a mechanism that maximizes the performance of Grid computing systems. According to a priority, grade and site of heterogeneous resources, we assign tasks to those resources. Initially, a volunteer's priority and ranking are determined by static information like as CPU speed, RAM size, storage size and network bandwidth. And then, the rank of resources is decided by considering dynamic information such as correctness, response time, and error rate. We find that overall Grid system performance is improved and high correctness using resource reallocation mechanism is achieved.

• Journal of The Korean Association of Information Education
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• v.9 no.1
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• pp.79-86
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• 2005

With the rapid advance of computer and communication technology, the amount of data transferred is also increasing more than ever. The recent trend of education systems is connecting related information semantically in different systems in order to improve the utilization of computerized information Therefore, Web-based teaching-learning is developing in the ubiquitous learning direction that learners select and organize the contents, time and order of learning by themselves. That is, it is evolving to provide teaching-learning environment adaptive to individual learners' characteristics (their level of knowledge, pattern of study, areas of interest). This paper proposes the efficient evaluation method of learning contents in a mediator for the integration of heterogeneous information resources. This means that the autonomy of a remote server can be preserved to the highest degree. In addition, this paper proposes the adaptive optimization of learning contents such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a learning content from the past, the accumulated usage frequency of a learning content decays as time goes by.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.227-248
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• 2017

This paper introduces an integrated model for systematically constructing a linguistic resource database that can be used by machine learning-based biomedical information extraction systems. The proposed method suggests an orderly process of collecting and constructing dictionaries and training sets for both named-entity recognition and relation extraction. Multiple heterogeneous structures for the resources which are collected from diverse sources are analyzed to derive essential items and fields for constructing the integrated database. All the collected resources are converted and refined to build an integrated linguistic resource storage. In this paper, we constructed entity dictionaries of gene, protein, disease and drug, which are considered core linguistic elements or core named entities in the biomedical domains and conducted verification tests to measure their acceptability.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.769-778
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• 2002

The LEX system is a XML-based framework for medical information consolidation. The Lex makes it possible for heterogeneous HISs(Hospital Information Systems) exchange and share HL7 messages by storing the messages into a single Central Clinical Database. In this paper, we propose a HL7 message server independently interoperable from existing HIS to generate HL7 messages, and design an XML database schema suitable for storing and manipulating such data. We also propose a new DTD for efficient transformation of HL7 messages to XML documents for storage saving as well as supporting patient-oriented information retrieval.