• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1050-1061
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• 2000

This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.119-126
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• 2024

The volume of genomic data is constantly increasing in various modern industries and research fields. This growth presents new challenges and opportunities in terms of the quantity and diversity of genetic data. In this paper, we propose a distributed cloud system for integrating and managing large-scale gene databases. By introducing a distributed data storage and processing system based on the Hadoop Distributed File System (HDFS), various formats and sizes of genomic data can be efficiently integrated. Furthermore, by leveraging Spark on YARN, efficient management of distributed cloud computing tasks and optimal resource allocation are achieved. This establishes a foundation for the rapid processing and analysis of large-scale genomic data. Additionally, by utilizing BigQuery ML, machine learning models are developed to support genetic search and prediction, enabling researchers to more effectively utilize data. It is expected that this will contribute to driving innovative advancements in genetic research and applications.

• Journal of Korea Water Resources Association
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• v.37 no.11
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• pp.969-978
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• 2004

According to the report of hydrologic modeling study, from a quantitative point of view, a lumped model is more efficient than a distributed model. A distributed model has to simplify geospatial characteristics for the shake of restricted application on computer calculation and field observation. In this reason, a distributed model can not help having some errors of water quantity modelling. However, considering a distribution of rainfall-runoff reflected spatial characteristics, a distributed model is more efficient to simulate a flow of surface water, The purpose of this study is modeling of spatial rainfall-runoff of surface water using grid based distributed model, which is consisted of storage function model and essential basin-channel parameters( slope, flow direction & accumulation), and that procedure is able to be executed at a personal computer. The prototype of this model is developed in Heongseong Multipunose Dam basin and adapted in Hapchon Multipurpose Dam basin, which is larger than the former about five times. The efficiency coefficients in result of two dam basin simulations are more than about 0.9, but ones at the upstream water level gauge station meet with bad result owing to overestimated rating curves in high water level. As a result of this study, it is easily implemented that spatially distributed rainfall-runoff model using GIS, and geophysical characteristics of the catchment, hereafter it is anticipated that this model is easily able to apply rainfall data by real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3794-3820
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• 2019

In recent years, a cloud environment with the ability to detect illegal behaviours along with a secured data storage capability is much needed. This study presents a cloud storage framework, wherein a 128-bit encryption key has been generated by combining deoxyribonucleic acid (DNA) cryptography and the Hill Cipher algorithm to make the framework unbreakable and ensure a better and secured distributed cloud storage environment. Moreover, the study proposes a DNA-based encryption technique, followed by a 256-bit secure socket layer (SSL) to secure data storage. The 256-bit SSL provides secured connections during data transmission. The data herein are classified based on different qualitative security parameters obtained using a specialized fuzzy-based classification technique. The model also has an additional advantage of being able to decide on selecting suitable storage servers from an existing pool of storage servers. A fuzzy-based technique for order of preference by similarity to ideal solution (TOPSIS) multi-criteria decision-making (MCDM) model has been employed for this, which can decide on the set of suitable storage servers on which the data must be stored and results in a reduction in execution time by keeping up the level of security to an improved grade.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1483-1493
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• 2018

Recently, more power facilities are needed to cope with the increasing electric demand. However, the additional construction of generators, transmission and distribution installations is not easy because of environmental problems and citizen's complaints. Under this circumstance, a microgrid system with distributed renewable resources emerges as an alternative of the traditional power systems. Moreover, the configuration of power system changes with more DC loads and more DC installations. This paper is written to introduce an idea of a genetic algorithm-based solution to determine the optimal capacity of the distributed generators depending on the types of system configuration: AC-link, DC-link and Hybrid-link types. In this paper, photovoltaic, wind turbine, energy storage system and diesel generator are considered as distributed generators and the feasibility of the proposed algorithm is verified by comparing the calculated capacity of each distributed resource with HOMER simulation results for 3 types of system configuration.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.99-111
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• 2009

In wireless sensor networks, various schemes have been proposed to store and process sensed data efficiently. A Data-Centric Storage(DCS) scheme assigns distributed data regions to sensors and stores sensed data to the sensor which is responsible for the data region overlapping the data. The DCS schemes have been proposed to reduce the communication cost for transmitting data and process exact queries and range queries efficiently. Recently, KDDCS that readjusts the distributed data regions dynamically to sensors based on K-D tree was proposed to overcome the storage hot-spots. However, the existing DCS schemes including KDDCS suffer from Query Hot-Spots that are formed if the query regions are not uniformly distributed. As a result, it causes reducing the life time of the sensor network. In this paper, we propose a new DCS scheme, called TPDCS(Time-Parameterized DCS), that avoids the problems of storage hot-spots and query hot-spots. To decentralize the skewed. data and queries, the data regions are assigned by a time dimension as well as data dimensions in our proposed scheme. Therefore, TPDCS extends the life time of sensor networks. It is shown through various experiments that our scheme outperform the existing schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2521-2530
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• 1997

In this paepr, we present a video-on-demand (VOD) system design model that address and integrates a number of inter-related issues. Then with analysis and performance evaluation, we investigate various aspects of disk and buffer managements in the given model. Based on the analysis results, we suggest that a distributed buffering scheme with intermediate buffers may te useful to transform bursty disk accesses into a continuous stream for for glitch-free performance of VOD systems. Also, through simulation, we illustrate that massive multimedia information storage design techniques such as prefetching, clustered striping, and real-time disk scheduling integrated with the distributed buffering mechanism may enhance end-to-end real-time performance of VOD systems under wide-area networks.

• Journal of Plant Biology
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• v.34 no.3
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• pp.201-213
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• 1991

This study has been carried out to investigate the ultrastructural changes, formation of storage materials in endosperm cells with electron microscope during the seed formation of Panax ginseng C.A. Meyer. In the early stage of seed formation with green seed coat, the endosperm was cellular type. Cell plate was largely composed of dictyosome vesicles in early stage of wall formation after mitosis. Central vacuole was gradually subdivided into several small-sized vacuoles. During the differentiation of plastids, some proplastid was replaced by amyloplast with starch grains and lamellar structure. A number of mitochondria with well developed cristae were distributed in cytoplasm. Rough endoplasmc reticulum, dictyosome, microbody, free ribosomes and polysomes were evenly distributed in cytoplasm. Spherical spherosomes were formed from dictyosome containing the lipid materials of even electron density. Protein bodies were formed by interfusing between vacuoles and vesicles derived from rough endoplasmic reticulum which contained the amorphous protein of high electron density.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.128-134
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• 2023

The widespread usage of blockchain technology in cryptocurrencies has led to the adoption of the blockchain concept in data storage management systems for secure and effective data storage and management. Several innovative studies have proposed solutions that integrate blockchain with distributed databases. In this article, we review current blockchain databases, then focus on two well-known blockchain databases-BigchainDB and FalconDB-to illustrate their architecture and design aspects in more detail. BigchainDB is a distributed database that integrates blockchain properties to enhance immutability and decentralization as well as a high transaction rate, low latency, and accurate queries. Its architecture consists of three layers: the transaction layer, consensus layer, and data model layer. FalconDB, on the other hand, is a shared database that allows multiple clients to collaborate on the database securely and efficiently, even if they have limited resources. It has two layers: the authentication layer and the consensus layer, which are used with client requests and results. Finally, a comparison is made between the two blockchain databases, revealing that they share some characteristics such as immutability, low latency, permission, horizontal scalability, decentralization, and the same consensus protocol. However, they vary in terms of database type, concurrency mechanism, replication model, cost, and the usage of smart contracts.

• Journal of Hydrogen and New Energy
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• v.24 no.6
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• pp.550-557
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• 2013

A glucose hydrothermal method is described for preparing hollow carbon spheres (HCS), which have a regular morphology and a high Brunauer-Emmett-Teller surface area of 28.6 m2/g. Scanning electron microscopy shows that they have thin shells and diameter between 2 and 8 ${\mu}m$. The HCSs were modified for the enhanced room temperature hydrogen storage by employing Ni nanoparticles on their surface. The Ni-decorated HCSs were characterized by X-ray diffraction, transmission electron microscopy coupled with an energy dispersive spectroscope, and an inductively coupled plasma spectrometer, indicating that fine and well-distributed Ni nanoparticles can be accomplished on the HCSs. The hydrogen uptake capacity in HCSs with and without Ni loading was evaluated using a high-pressure microbalance at room temperature under a hydrogen pressure upto 9 MPa. As much as 1.23wt.% of hydrogen can be stored when uniformly distributed Ni nanoparticles are formed on the HCSs, while the hydrogen uptake capacity of as-received HCSs was 0.41 wt.%. For Ni nanoparticle-loaded HCSs, hydrogen molecules could be easily dissociated into atomic hydrogen and then chemically adsorbed by the sorbents, leading to an enhanced capacity for storing hydrogen.