• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.513-521
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• 2022

This study deals with an AI architecture model for collecting battlefield data using the tactical C4I system. Based on this model, the artificial staff can be utilized in tactical echelon. In the current structure of the Army's tactical C4I system, Servers are operated by brigade level and above and divided into an active and a standby server. In this C4I system structure, the AI server must also be installed in each unit and must be switched when the C4I server is switched. The tactical C4I system operates a server(DB) for each unit, so data matching is partially delayed or some data is not matched in the inter-working process between servers. To solve these issues, this study presents an operation concept so that all of alternate server can be integrated based on virtualization technology, which is used as an source data for AI Meta DB. In doing so, this study can provide criteria for the AI architectural model of the ground tactical echelon.

• Journal of Korean Society of Forest Science
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• v.106 no.3
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• pp.340-352
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• 2017

In This study, we examined the gap between supply and demand of forest policy by year through big data analysis for macroscopic evaluation of the 5th Basic Forest Plan. We collected unstructured data based on keywords related to the projects mentioned in the news, SNS and so on in the relevant year for the policy demand side; and based on the documents published by the Korea Forest Service for the policy supply side. based on the collected data, we specified the network structure through the social network analysis technique, and identified the gap between supply and demand of the Korea Forest Service's policies by comparing the network of the demand side and that of the supply side. The results of big data analysis indicated that the network of the supply side is less radial than that of the demand side, implying that various keywords other than forest could considerably influence on the network. Also we compared the trends of supply and demand for 33 keywords related to 27 major projects. The results showed that 7 keywords shows increasing demand but decreasing supply: sustainable, forest management, forest biota, forest protection, forest disease and pest, urban forest, and North Korea. Since the supply-demand gap is confirmed for the 7 keywords, it is necessary to strengthen the forest policy regarding the 7 keywords in the 6th Basic Plan.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.467-475
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• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.851-858
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• 2021

Due to the increase in renewable energy and distributed resources, not only traditional data but also various energy-related data are being generated in the new energy industry. In other words, there are various renewable energy facilities and power generation data, system operation data, metering and rate-related data, as well as weather and energy efficiency data necessary for new services and analysis. Energy big data processing technology can systematically analyze and diagnose data generated in the first half of the power production and consumption infrastructure, including distributed resources, systems, and AMI. Through this, it will be a technology that supports the creation of new businesses in convergence between the ICT industry and the energy industry. To this end, research on the data analysis system, such as itemized characteristic analysis of the collected data, correlation sampling, categorization of each feature, and element definition, is needed. In addition, research on data purification technology for data loss and abnormal state processing should be conducted. In addition, it is necessary to develop and structure NIFI, Spark, and HDFS systems so that energy data can be stored and managed in real time. In this study, the overall energy data processing technology and system for various power transactions as described above were proposed.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• 재활복지
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• v.22 no.3
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• pp.23-39
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• 2018

The fourth industrial revolution and technological innovation will make the job factor of people with disabilities complicated and difficult. Thus, this study analyzed the technical factors influencing the job structure and tried to find a way to develop the job of the people with disabilities in response to the 4th Industrial Revolution by changing the labor market and changing the trend of the employment by industry. The methods for this study are literature research and FGI. First, technological factors affecting the job structure of the Fourth Industrial Revolution are artificial intelligence, Internet and networking of things, 3D printing, big data, Second, technological innovation due to the industrial revolution was a major factor in the job structure. As the industrial revolution and technological innovation progressed, the job structure shifted rapidly from the manufacturing industry to the service industry, Third, as the measures of the 4th Industrial Revolution and the change of the job structure, it is necessary to make preemptive investment for the development of competency to cope with technological innovation, Finally, in order to respond to the Fourth Industrial Revolution and the rapidly changing technological innovation, the basic data of people with disabilities should be able to be big data.

• Ocean and Polar Research
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• v.44 no.2
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• pp.113-126
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• 2022

This study was carried out to investigate the benthic polychaetous community and benthic ecosystem quality status on the adjacent continental shelf of Jeju Island, and field surveys were conducted at 31 stations in July and August, 2020. The surface sediment was generally composed of muddy sand facies and sandy mud facies, and the average particle size was medium silt (6.1±1.6∅). The benthic polychaetous community revealed a total of 73 species with a mean density of 242 ind./m². The major dominant species were Notomastus latericeus, Ampharete arctica and Onuphis shirikishinaiensis. By the cluster analysis and nMDS results based on species composition of the benthic polychaetous community, the study area was divided into three station groups arranged from east to west by the water depth and sedimentary facies. The station group located in the west was subdivided into two station groups from south to north. From results of correlation analysis and PCA, it was found that the benthic polychaetous community in the study area had a strong correlation with the sedimentary environment and water depth. The benthic faunal community (or ecosystem) on the adjacent continental shelf of Jeju Island was assessed to be in a healthy state by biotic indices such as AMBI and BPI.

• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.116-122
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• 2019

In recent years, small and medium-sized businesses are rapidly changing to an industrial structure where process/quality/energy data aggregates can be automatically or real-time to achieve global competitiveness. In particular, real-time information analysis produced in the production process of small businesses is evolving into a new process process that analyzes, predicts, prescribes and implements significant performance of small businesses. In this paper, we propose a platform-building model that can transform the automated production information system of small businesses into big data so that they can upgrade data that is generated by small businesses. The proposed model has the capability to support operational efficiency (consulting and training) and strategic decision making of small businesses by utilizing a variety of data on the basic information of products produced by small businesses for data collection by smart SMEs. In addition, the proposed model is characterized by close cooperation between small and medium-sized businesses with different regional characteristics and areas of information sharing and system linkage.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1191-1195
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• 2006

Now days, heavy storm occur to be continue. It is hard to use before frequency based on flood discharge for decision that design water pocket structure. We need to estimation of frequency based on flood discharge on the important basin likely city or basin that damage caused by flood recurrence. In this paper flood discharge calculated by Clark watershed method and SCS synthetic unit hydrograph method about upside during each minute of among time distribution method of rainfall, Huff method choosing Bocheong Stream basin that is representative basin of International Hydrologic Project (IHP) about time distribution of rainfall that exert big effect at flood discharge estimate to research target basin because of and the result is as following. Relation between probability flood discharge that is calculated through frequency analysis about flood discharge data and rainfall - runoff that is calculated through outward flow model was assumed about $48.1{\sim}95.9%$ in the case of $55.8{\sim}104.0%$, SCS synthetic unit hydrograph method in case of Clark watershed method, and Clark watershed method has big value overly in case of than SCS synthetic unit hydrograph method in case of basin that see, but branch of except appeared little more similarly with frequency flood discharge that calculate using survey data. In the case of Critical duration, could know that change is big area of basin is decrescent. When decide time distribution type of rainfall, apply upside during most Huff 1-ST because heavy rain phenomenon of upsides appears by the most things during result 1-ST about observation recording of target area about Huff method to be method to use most in business, but maximum value of peak flood discharge appeared on Huff 3-RD too in the case of upside, SCS synthetic unit hydrograph method during Huff 3-RD incidental of this research and case of Clark watershed method. That is, in the case of Huff method, latitude is decide that it is decision method of reasonable design floods that calculate applying during all $1-ST{\sim}4-TH$.

• Bulletin of the Korean Chemical Society
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• v.23 no.11
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• pp.1527-1530
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• 2002

1,12-diazacyclodocosane-2,11-dione was first isolated from a plant Phyllanthus niruri Linn. Its structure has been determined by means of spectroscopy methods and X-ray crystallography. Two peptide groups in the big ring (lactam) are the main factors influencing intermolecular contacts. The hydrogen-bond interaction of these hydrophilic groups is observed in the crystal structure. Meanwhile, C-H···O hydrogen bonds in molecules contribute to the formation of the whole crystal. These two kinds of hydrogen-bond form six- member rings among molecules. This compound crystallizes in the triclinic space group P-1 with a= 9.588(1) $\AA$, b= $9.850(1)\AA$, c = $11.810(1)\AA$, $\alpha=$ 68.18(1)$^{\circ}C$ , $\beta=$ 84.98(1), $\gamma$ = 86.03(1)$^{\circ}C$ , V = $1030.66(17)\AA3$ , Z = 2. A disorder of five-member carbon chain in the whole ring is observed in the title compound. The bond angle 105.8(4) is determined for a extreme configuration C(14)-C(15)-C(16), and 117.7(10) for another extreme configuration C(14')-C(15')-C(16'). In this crystal, two molecules are tied each other by short intermolecular hydrogen bonds, the oxygen atom being tied by hydrogen bond to nitrogen atom of another two molecules. The NMR and IR spectral data coincides to the structure of the compound.