• Journal of Korean Society of Forest Science
• /
• v.70 no.1
• /
• pp.91-102
• /
• 1985

Growth and biomass production of natural stands of Quercus variabilis in relation to tree density were studied to obtain basic guide lines for future tending operation. Two natural stands of Quercus variabilis located at 900m (A stand: 6,600trees/ha, $15.84m^2/ha$, $\frac{19}{17-20}$) and 800m (B stand: 4,300trees/ha, $16.65m^2/ha$, $\frac{20}{17-21}$) elevation in Sancheong, Kyongnam Province were selected for the comparative study and following results were obtained through a sample plot method. After diameter of individual trees in the sample plots was measured, twelve average trees from each diameter class were cut felled to measure dry weight of $W_S$, $W_B$, $W_L$, $W_{Ba}$, and standing biomass and biomass production rates by a allometrior regressions related to $D^2H$. Vertical distribution of leaves along the stems indicated that photosynthesis was carried out 2.2m above the ground in Stand A and 1.2m in Stand B. Maximum photosynthesis was located 4.2m and 6.2m above the ground in Stand A and B, respectively. Leaf area index was 4.25ha/ha for Stand A, and 3.89ha/ha for Stand B. Above-ground standing biomass was 49.51 ton/ha for Stand A and 59.20 ton/ha and net annual production was 6.75 ton/ha/yr. for Stand A and 8.99 ton/ha/yr. for Stand B. The ratio of net annual production to standing biomass was 17.5% for Stand A and 16.7% for Stand B. Net assimilation rate was 2.75kg/kg/yr. for Stand A and 3.58kg/kg/yr. for Stand B. Stem wood production rate was 1.46kg/kg/yr. for Stand A and 2.09kg/kg/yr. for Stand B. Bark production rate was 0.60 kg/kg/yr. for Stand A and 0.34kg/kg/yr. for Stand B. Above data indicated that Stand B utilized growing spaces and sites more efficiently than Stand A. It is concluded chat productivity of natural stands of Quercus variabilis can be enhanced through optimization of basal areas and number of tree per hectare and that sound management of natural oak stands should be based on systematic sampling of the area for periodic productivity estimation.

• Food Science of Animal Resources
• /
• v.27 no.2
• /
• pp.171-178
• /
• 2007

This study was conducted to investigate the effect of ageing temperature(0 and $4^{\circ}C$) and time(2, 7, 14, 21, 28, and 49 days) on the meat quality of longissimus muscle from Hanwoo steer. The pH, Warner-Bratzler shear force(WBSF), myofibrillar fragmentation index(MFI), cooking and purge loss, sensory, morphological changes, and amino acid composition were assessed. The pH of longissimus muscle increased significantly(p<0.05) for 21 days at $0^{\circ}C$ and 14 days at $4^{\circ}C$, but decreased thereafter. Longissimus muscle aged from 14 days to 28 days at $4^{\circ}C$ had a lower WBSF than longissimus muscle aged at $0^{\circ}C$(p<0.05). The WBSF of longissimus muscle decreased significantly(p<0.05) with ageing time. The MFI, cooking and purge loss, tenderness, and juiciness scores were higher for longissimus muscle aged at $4^{\circ}C$ than at $0^{\circ}C$. As ageing time increased, the MFI, cooking and purge loss, tenderness, juiciness, and amino acid composition of longissimus muscle increased significantly(p<0.05) with ageing at 0 or $4^{\circ}C$. Transmission electron microscopy showed Z-disk degradation and morphological changes of the myofibrils correlating with increased tenderness during the ageing time. Based on these results, the proper ageing conditions of longissimus muscle of Hanwoo steer were 14 days of ageing at $0^{\circ}C$ or 7 days of ageing at $4^{\circ}C$. However, further study on the application of ageing technology to this industry is necessary for the optimization of ageing conditions for the sub-primals or muscles from Hanwoo beef.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.20 no.12
• /
• pp.844-861
• /
• 2008

The papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during the year of 2007 have been reviewed. Focus has been put on current status of research in the aspect of heating, cooling, ventilation, sanitation and building environments. The conclusions are as follows. (1) The research trends of fluid engineering have been surveyed as groups of general fluid flow, fluid machinery and piping, etc. New research topics include micro nano fluid, micropump and fuel cell. Traditional CFD was still popular and widely used in research and development. Studies about fans and pumps were performed in the field of fluid machinery. Characteristics of flow and fin shape optimization are studied in the field of piping system. (2) The research works on heat transfer have been reviewed in the field of heat transfer characteristics, heat exchangers, and desiccant cooling systems. The research on heat transfer characteristics includes thermal transport in pulse tubes, high temperature superconductors, ground heat exchangers, fuel cell stacks and ice slurry systems. For the heat 'exchangers, the research on pin-tube heat exchanger, plate heat exchanger, condensers and gas coolers has been cordially implemented. The research works on heat transfer augmenting tubes have been also reported. For the desiccant cooling systems, the studies on the design and operating conditions for desiccant rotors as well as performance index are noticeable. (3) In the field of refrigeration, many papers were presented on the air conditioning system using CO2 as a refrigerant. The issues on the two-stage compression, the oil selection, and the appropriate oil charge were treated. The subjects of alternative refrigerants were also studied steadily. Hydrocarbons, DME and their mixtures were considered and various heat transfer correlations were proposed. (4) Research papers have been reviewed in the field of building facilities by grouping into the researches on heat and cold sources, air conditioning and air cleaning, ventilation and fire research including tunnel ventilation, flow control of piping system, and sound research with drain system. Main focuses have been addressed to the promotion of efficient or effective use of energy, which helps to save energy and results in reduced environmental pollution and operating cost. (5) Studies were mostly focused on analyzing the indoor environment in various spaces like cars, old tombs, machine rooms, and etc. in an architectural environmental field. Moreover, subjects of various fields such as the evaluation of noise, thermal environment, indoor air quality and development of energy analysis program were researched by various methods of survey, simulation, and field experiment.

• Food Engineering Progress
• /
• v.21 no.4
• /
• pp.360-366
• /
• 2017

Fish skin peptide-loaded liposomes were prepared in 100 mL and 1 L solution as lab scales, and 10 L solution as a prototype scale. The particle size and zeta potential were measured to determine the optimal conditions for the production of fish skin peptide-loaded liposome. The liposome was manufactured by the following conditions: (1) primary homogenization at 4,000 rpm, 8,000 rpm, and 12,000 rpm for 3 minutes; (2) secondary homogenization at 40 watt (W), 60 W, and 80 W for 3 minutes. From this experimental design, the optimal conditions of homogenization were selected as 4,000 rpm and 60 W. For the next step, fish peptides were prepared as the concentrations of 3, 6, and 12% at the optimum manufacturing conditions of liposome and stored at $4^{\circ}C$. Particle size, polydispersion index (pdI), and zeta potential of peptide-loaded liposome were measured for its stability. Particle size increased significantly as manufacture scale and peptide concentration increased, and decreased over storage time. The zeta potential results increased as storage time increased at 10 L scale. In addition, 12% peptide showed the formation of a sediment layer after 3 weeks, and 6% peptide was considered to be the most suitable for industrial application.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.1-21
• /
• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.149-161
• /
• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.