• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.41-49
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• 2017

The 'NIST Framework and Road Map for Smart Grid Interoperability Standards' proposes an architecture framework to secure the direction of development and standard interoperability of smart grid and provides a list of identified standard, standard cyber security strategies, and certification framework. In particular, SEP 2.0 and OpenADR 2.0 are the examples. SEP 2.0 and OpenADR 2.0 can functionally link HEMS and Smart Grid, but interoperability standards between the two protocols are not planned in above document. The OpenADR Alliance also announced that work is underway to define mapping tables for interoperability between OpenADR 2.0 and SEP 2.0, but no information is yet available. Therefore, In this paper, in developing energy efficiency improvement HEMS, we propose a mapping model that supports syntactic and semantic founded interoperability between SEP 2.0 and OpenADR 2.0b for ICT grid convergence based on the standard specification document of each protocol and confirmed through an example of the semantic mapping function based on the demand response service scenario.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.4
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• pp.41-49
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• 2010

This paper proposes a new high speed SHA-1 architecture using multiple unfolding and pre-computation techniques. We unfolds iterative hash operations to 2 continuos hash stage and reschedules computation timing. Then, the part of critical path is computed at the previous hash operation round and the rest is performed in the present round. These techniques reduce 3 additions to 2 additions on the critical path. It makes the maximum clock frequency of 118 MHz which provides throughput rate of 5.9 Gbps. The proposed architecture shows 26% higher throughput with a 32% smaller hardware size compared to other counterparts. This paper also introduces a analytical model of multiple SHA-1 architecture at the system level that maps a large input data on SHA-1 block in parallel. The model gives us the required number of SHA-1 blocks for a large multimedia data processing that it helps to make decision hardware configuration. The hs fospeed SHA-1 is useful to generate a condensed message and may strengthen the security of mobile communication and internet service.

• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.77-85
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• 2018

Purpose - The purpose of this study is to subdivide trade transaction-centered structure in a logistics/distribution industry system to apply blockchain, to establish and resolve with which types of technology, and to provide policy direction of government institution and technology to apply blockchain in this kind of industry. Research design, data, and methodology - This study was conducted with previous researches centered on cases applied in various industry sectors on the basis of blockchain technology. Results - General fields of blockchain application include digital contents distribution, IoT platform, e-Commerce, real-estate transaction, decentralized app. development(storage), certification service, smart contract, P2P network infrastructure, publication/storage of public documents, smart voting, money exchange, payment/settlement, banking security platform, actual asset storage, stock transaction and crowd funding. Blockchain is being applied in various fields home and abroad and its application cases can be explained in the banking industry, public sector, e-Commerce, medical industry, distribution and supply chain management, copyright protection. As examined in the blockchain application cases, it is expected to establish blockchain that can secure safety through distributed ledger in trade transaction because blockchain is established and applied in various sectors of industries home and abroad. Parties concerned of trade transaction can secure visibility even in interrupted specific section when they provide it as a base for distributed ledger application in trade and establish trade transaction model by applying blockchain. In case of interrupted specific section by using distributed ledger, blockchain model of trade transaction needs to be formed to make it possible for parties concerned involved in trade transaction to secure visibility and real-time tracking. Additionally, management should be possible from the time of contract until payment, freight transfer to buyers through land, air and maritime transportation. Conclusions - In order to boost blockchain-based logistics/distribution industry, the government, institutionally, needs to back up adding legal plan of shipping, logistics and distribution, reviewing standardization of electronic switching system and coming up with blockchain-based industrial road maps. In addition, the government, technologically, has to support R&D for integration with other high technology, standardization of distribution industry's blockchain technology and manpower training to expand technology development.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.834-843
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• 2023

Purpose: The Serious Civil Accidents consist of the public use facilities, the public transports, and the material and its products. According to the Serious Civil Accidents of the Serious Accidents Punishment Act, it must be constructed the safety and health management framework and execution system. In this study. we are design the model of the Serous Civil Accidents management and action system. Method: Firstly, we review from 8^th article to 11^th article of the enforcement ordinance of the Serious Accidents Punishment Act. From the articles, we design the visual and structural management system supporting the Act. Result: The Serious Civil Accidents apply to the system is consisted of 6 monitoring modules and 4 kinds DB modules. Conclusion: The Serious Civil Accidents are managed by the private enterprises, local governments, and public institutions. Specially, the CEO of restaurants, cafes, et al, do not know the detail information related to the Act. Also in case of the local governments, there are many facilities related the Act. It is not easy to the construct the management framework of the Act. This study provides the simple management structure for the Act.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• International Commerce and Information Review
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• v.15 no.4
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• pp.457-479
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• 2013

Through a Chinese rise, Chinese dream is actualizing as the world's great power. According to outlook of World Bank and IMF, Around 2030 China will be a great power bigger than America's economic power. The rise of China will give a huge impact to the whole world. China expands her influence through a global manufacturing base and a global market. To actualize 'Peaceful Rise' Strategy, China has many constraints. Chinese society is facing many difficult social problem due to side effects of a rapid development. Such as the spread of corruption, the severity of wealth gap, environmental degradation and energy shortage. Internationally there are containment from hegemon so-called 'China threat' dispute, Taiwan issue and territorial disputes. Western countries are hostile to China for two reasons. Based on expectations, one is China's socialist system and the other is the rising China which will compete for supremacy with Europe and America. Recent emergence of Chinese nationalism and the containment of the neighboring countries are also serious limiting factors. Domestically they have the rampant corruption in the bureaucracy, weakened capacity of Communist rule, wealth disparity due to the discriminatory economic development strategy, seriousness of rural problem, social instability, lack of social security systems and the development gap between the eastern coastal areas and western inland areas, ethnic minorities problems, the constraint of sustainable development issues due to lack of resources, environmental pollution and energy constraints. Like the former Soviet Union, China may face a dismantlement. After the rise, China may encounter possibilities of a war between great powers or a collapse of Chinese society caused by deepening internal conflict. Serious economic polarization would make peasants and urban workers, who are social vulnerable people, to turn their back to communist party and threaten the justification and the appropriateness of the ruling communist party. Chinese government will think internal system security threat is more formidable risk factor than a system security threat from the hegemon. The decline of great country comes from internal reasons rather than external reasons. To achieve peaceful rise, unification with Taiwan is an essential prerequisite. Taiwan issues are complex problems which equipped with international and domestic factors. Lack of energy resources, environmental pollution in China will bring economic crisis to Korean enterprises. Important influence to Korean economy will be a changeover of the method in economic development. It will turn the balance of investment and consumption, GDP-centered growth to consumption and environment-centered growth. Services industries including finance, environment, culture, education, health care and social welfare will grow. Change in China's growth model will give a great challenge upon the intermediate goods industry in Korea. Korea should reduce the portion of machinery, automotive, semiconductor, steel and chemical-centered export industry to China, and should increase the proportion of the service industry.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Journal of Preventive Medicine and Public Health
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• v.26 no.4 s.44
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• pp.599-613
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• 1993

To study the pattern of prenatal care utilization and its determinants in rural Korea, 976 mothers (65.5%) out of 1,489 living mothers in Chinyang, Sachon and Hapchon Counties in Kyongsangnam Province who had delivered a baby between July 1, 1990 and June 30, 1991 were interviewed by the Myon health workers from January 3 through February 15, 1992. The Anderson's behavioral model for health service utilization was applied to develop the frames for analysis. The dependent variable was a number of prenatal care visits. And the independent variables included In the model were the variables pertaining to the predisposing, enabling, medical need and other components. The proportion of mother who had ever received the prenatal care service for the index pregnancy was 97.3%. However, the proportion of mothers who had made more than 10 visits was only 20.6%, which indicated that majority of mothers had paid far less visits than recommended $10{\sim}12$ visits for each normal pregnancy. The low utilization of prenatal care services (none or less than 4 visits) was related to mother's low educational level, the high birth order, beneficiary of the medical aid, the absence of clinic in the community, no diagnosed disease of mother during pregnancy, and mothers engaged in farming. Inequity of access seemed to exist because social structure variables and the variables of enabling component were important predictors. And there seemed to be high mutability in equalizing the distribution of prenatal care services because the variables of enabling component such as type of medical security and whether there was a clinic or not in the community were substantially important.