• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.39-60
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• 2011

Since the introduction of web 2.0 technology, social network service has been recognized as the foundation of an important future information technology. The advent of web 2.0 has led to the change of content creators. In the existing web, content creators are service providers, whereas they have changed into service users in the recent web. Users share experiences with other users improving contents quality, thereby it has increased the importance of social network. As a result, diverse forms of social network service have been emerged from relations and experiences of users. Social network is a network to construct and express social relations among people who share interests and activities. Today's social network service has not merely confined itself to showing user interactions, but it has also developed into a level in which content generation and evaluation are interacting with each other. As the volume of contents generated from social network service and the number of connections between users have drastically increased, the social network extraction method becomes more complicated. Consequently the following problems for the social network extraction arise. First problem lies in insufficiency of representational power of object in the social network. Second problem is incapability of expressional power in the diverse connections among users. Third problem is the difficulty of creating dynamic change in the social network due to change in user interests. And lastly, lack of method capable of integrating and processing data efficiently in the heterogeneous distributed computing environment. The first and last problems can be solved by using FOAF, a tool for describing ontology-based user profiles for construction of social network. However, solving second and third problems require a novel technology to reflect dynamic change of user interests and relations. In this paper, we propose a novel method to overcome the above problems of existing social network extraction method by applying FOAF (a tool for describing user profiles) and RSS (a literary web work publishing mechanism) to OLAP system in order to dynamically innovate and manage FOAF. We employed data interoperability which is an important characteristic of FOAF in this paper. Next we used RSS to reflect such changes as time flow and user interests. RSS, a tool for literary web work, provides standard vocabulary for distribution at web sites and contents in the form of RDF/XML. In this paper, we collect personal information and relations of users by utilizing FOAF. We also collect user contents by utilizing RSS. Finally, collected data is inserted into the database by star schema. The system we proposed in this paper generates OLAP cube using data in the database. 'Dynamic FOAF Management Algorithm' processes generated OLAP cube. Dynamic FOAF Management Algorithm consists of two functions: one is find_id_interest() and the other is find_relation (). Find_id_interest() is used to extract user interests during the input period, and find-relation() extracts users matching user interests. Finally, the proposed system reconstructs FOAF by reflecting extracted relationships and interests of users. For the justification of the suggested idea, we showed the implemented result together with its analysis. We used C# language and MS-SQL database, and input FOAF and RSS as data collected from livejournal.com. The implemented result shows that foaf : interest of users has reached an average of 19 percent increase for four weeks. In proportion to the increased foaf : interest change, the number of foaf : knows of users has grown an average of 9 percent for four weeks. As we use FOAF and RSS as basic data which have a wide support in web 2.0 and social network service, we have a definite advantage in utilizing user data distributed in the diverse web sites and services regardless of language and types of computer. By using suggested method in this paper, we can provide better services coping with the rapid change of user interests with the automatic application of FOAF.

• Horticultural Science & Technology
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• v.33 no.4
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• pp.605-617
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• 2015

The ultimate goal of this research is to develop a botanical biofiltration system that combines a green interior, biofiltering, and automatic irrigation to purify indoor air pollutants according to indoor space and the size of biofilter. This study was performed to compare the stability of air flow characteristics and removal efficiency (RE) of fine dust within a wall-typed (vertical) botanical biofilter depending on humidifying cycle and to investigate RE of volatile organic compounds (VOCs) by the biofilter. The biofilter used in this experiment was designed as an integral form of water metering pump, water tank, blower, humidifier, and multi-level planting space in order to be suitable for indoor space utilization. As a result, relative humidity, air temperature, and soil moisture content (SMC) within the biofilter showed stable values regardless of three different humidifying cycles operated by the metering pump. In particular, SMCs were consistently maintained in the range of 27.1-29.7% during all humidifying cycles; moreover, a humidifying cycle of operating for 15 min and pausing for 45 min showed the best horizontal linear regression (y = 0.0008x + 29.09) on SMC ($29.0{\pm}0.2%$) during 120 hour. REs for number of fine dust (PM10) and ultra-fine dust (PM2.5) particles passed through the biofilter were in the range of 82.7-89.7% and 65.4-73.0%, respectively. RE for weight of PM10 passed through the biofilter was in the range of 58.1-78.9%, depending on humidifying cycle. REs of xylene, ethyl benzene, total VOCs (TVOCs), and toluene passed through the biofilter were in the range of 71.3-75.5%, while REs of benzene and formaldehyde (HCHO) passed through the biofilter were 39.7% and 44.9%, respectively. Hence, it was confirmed that the wall-typed botanical biofilter suitable for indoor plants was very effective for indoor air purification.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of Animal Environmental Science
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• v.18 no.2
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• pp.99-110
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• 2012

The purpose of the study is to collect basis data for to establish standard administrative processes of liquid fertilizer treatment. From this survey we could make out the key point of each step through a case of effective liquid manure treatment system in pig house. It is divided into six step; 1. piggery slurry management step, 2. Solid-liquid separation step, 3. liquid fertilizer treatment (aeration) step, 4. liquid fertilizer treatment (microorganism, recirculation and internal return) step, 5. liquid fertilizer treatment (completion) step, 6. land application step. From now on, standardization process of liquid manure treatment technologies need to be develop based on the six steps process.