• Journal of Korea Foresty Energy
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• v.21 no.1
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• pp.65-75
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• 2002

The study was carried out to determine the growth and biomass production of major deciduous trees including Betula platyphylla var. japonica, Betula schmidtii, Zelkova serrata, Acer mono, Prunes sargentii, and Ligustrum obtusifolium subjected to artificial shade treatment in nursery field. The six deciduous trees seedlings grow for 2 years under different light intensity of 100%, 38-62%, 22-28%, 7-20%, and 2-6% of the full sun light intensity. The results were as follows; In the seedling heights and root collar diameters of shade intolerant species like Betula platyphylla var. japonica and Betula schmidtii, the relative growth rates of seedlings grown in full sun showed 2 times as compared with those subjected to the shade treatment of 2-6% light intensities of full sun. In the shade tolerant species like Acer mono ant Ligustrum obtusifolium, the growth performances were better in the seedlings grown in 38-62% light intensities of full sun. Total dry mass including the dry mass of leaves, shoot and root were as a whole decreased with shade treatment. The ratio of the dry mass of leaves and stem increased the dry mass of root. T/R ratio of the seedlings increased by decreasing the relative light intensity. And the T/R ratio of 2-6% light intensities of full sun was ranged from 1.1~5.0 were greater in the full sun light was ranged from 0.6~3.2. Light intensity by artificial shade treatment decreased in deciduous trees when compared on the whole, it showed tendency that SLA increases, increased that seeing resemblant tendency in LAR and LWR and changed of light intensity is strong, it increased that showed difference as statistical. But, LWR of Betula platyphylla var. japonica increased gradually and showed tendency that decreases rapidly in the shade treatment of 2-6% light intensities of full sun. This result is thought that biomass production decreased by shading treatment influenced in physiological characteristics such as leaf area and decrease of the leaf amount.

• Journal of the Korean earth science society
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• v.24 no.3
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• pp.205-215
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• 2003

A precise and dense Bouguer anomaly is one of the most important data to improve the knowledge of our environment in the aspect of geophysics and physical geodesy. Besides the precise absolute gravity station net, we should consider two parts; one is to improve the precision in gravity measurement and correction of it, and the other is the density of measurement both in number and distribution. For the precise positioning, we have tested how we could use the GPS properly in gravity measurement, and deduced that the GPS measurement for 5 minutes would be effective when we used DGPS with two geodetic GPS receivers and the baseline was shorter than 40km. In this case we should use a precise geoid model such as PNU95. By applying this method, we are able to reduce the cost, time, and number of surveyors, furthermore we also get the benefit of improving in quality. Two kind of computer programs were developed to correct crossover errors and to calculate terrain effects more precisely. The repeated measurements on the same stations in gravity surveying are helpful not only to correct the drifts of spring but also to approach the results statistically by applying network adjustment. So we can find out the blunders of various causes easily and also able to estimate the quality of the measurements. The recent developments in computer technology, digital elevation data, and precise positioning also stimulate us to improve the Bouguer anomaly by more precise terrain correction. The gravity data of various sources, such as land gravity data (by Choi, NGI, etc.), marine gravity data (by NORI), Bouguer anomaly map of North Korea, Japanese gravity data, altimetry satellite data, and EGM96 geopotential model, were collected and processed to get a precise and dense Bouguer anomaly in and around the Korean Peninsula.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.488-495
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• 2005

This study was conducted to understand the influences of forest structure on throughfall, stemflow and interception loss. The study plots included the natural old-growth deciduous, Pinus koraiensis and Abies holophylla forests in Gwangneung and the rehabilitated young mixed forest in Yangju, Gyeonggido. The Pinus koraiensis and Abies hotophylla had been planted in 1976. The rehabilitated young mixed forest had been established to control erosion in 1974. Total and net rainfall were monitored from March, 2003 to October, 2004. Tipping bucket rain gauge recorded total rainfall. Throughfall and stemflow were measured by custom-made tipping bucket and CR10X data logger at each $10m{\times}10m$ plots at intervals of 30 minutes. Interception loss in the Pinus koraiensis plot were most as 37.2% of total rainfall and least as 22.6% in the rehabilitated young mixed forest. Stemflow in the rehabilitated young mixed forest was 10.7% of total rainfall and stemflow in the Pinus koraiensis plot was 2.4%. The average throughfall ratio ranged from 66% to 77% depending on the canopy coverage. The relationship of stemflow and total rainfall represented in a linear regression equation though the variation of data was large. The ratio of stemflow-conversion was 2% of total rainfall in the Pinus koraiensis plot and 12% in the rehabilitated young mixed forest, respectively. The stem storage of the natural old-growth deciduous was the largest of 0.21 mm whereas that of the Pinus koraiensis plot was the least of 0.003 mm. A deciduous forest produced stemflow more than a coniferous forest due to a smooth bark and steeply angled branches. Interception loss of all study plots increased linearly as total rainfall increased. The distribution of interception loss data related in total rainfall became wider in a deciduous forest than a coniferous. It resulted from seasonality of leaf area index in a deciduous forest. As considered above results, it was confirmed that there were great differences of throughfall, stemflow and interception loss depending on forest stand structures. The simulation model for predicting interception loss must have parameters such as forest stand characteristics and LAI in order to describe the influence of forest structure on interception loss.

• Journal of Korean Society of Forest Science
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• v.87 no.4
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• pp.519-527
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• 1998

An economic study of vegetation control to increase production of Songyi (Korean name far pine mushroom, matsutake, Tracholoma matsutake (S. Ito & Imai) Sing.) in red pine (Panes densiflora) stands in Korea was undertaken. In Korea, Songyi grows only in red pine stands. Harvest of this mushroom provides a significant income source to rural people in Korea yielding exports of US$20 million to US$80 million per year. However, hypogeous Songyi colonies and the mushroom production are declining, partly because shade tolerant species are succeeding the shade intolerant red pine. Past research says that it is possible to deep Songyi production increasing by controlling under-story vegetation. But few people are wilting to invest in the necessary control. Our analysis found that the economics of vegetation control appear to be quite favorable, showing an internal rate of return (IRR) of 20.7 percent in 15 years. However, positive returns do not occur for at least eight years and even then, the returns may not appear to the landowner to be a result of vegetation control efforts only because the mushroom production has been greatly variable depending on weather conditions. In a sensitivity analysis, it was found that the number of circular mushroom colonies was critically important for the cash flow. Results of this analysis are also sensitive to assumptions about annual growth length(0.16m radial growth=1.0m/circular length growth) of Songyi colony. However, the primary goal of vegetation control should be to keep the young colonies growing. Further research in the behavior of hypogeous Songyi colonies after vegetation control would help to improve our confidence in the results.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.239-240
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• 2008

As semiconductor devices are scaled down for better performance and more functionality, the Cu-based interconnects suffer from the increase of the resistivity of the Cu wires. The resistivity increase, which is attributed to the electron scattering from grain boundaries and interfaces, needs to be addressed in order to further scale down semiconductor devices [1]. The increase in the resistivity of the interconnect can be alleviated by increasing the grain size of electroplating (EP)-Cu or by modifying the Cu surface [1]. Another possible solution is to maximize the portion of the EP-Cu volume in the vias or damascene structures with the conformal diffusion barrier and seed layer by optimizing their deposition processes during Cu interconnect fabrication, which are currently ionized physical vapor deposition (IPVD)-based Ta/TaN bilayer and IPVD-Cu, respectively. The use of in-situ etching, during IPVD of the barrier or the seed layer, has been effective in enlarging the trench volume where the Cu is filled, resulting in improved reliability and performance of the Cu-based interconnect. However, the application of IPVD technology is expected to be limited eventually because of poor sidewall step coverage and the narrow top part of the damascene structures. Recently, Ru has been suggested as a diffusion barrier that is compatible with the direct plating of Cu [2-3]. A single-layer diffusion barrier for the direct plating of Cu is desirable to optimize the resistance of the Cu interconnects because it eliminates the Cu-seed layer. However, previous studies have shown that the Ru by itself is not a suitable diffusion barrier for Cu metallization [4-6]. Thus, the diffusion barrier performance of the Ru film should be improved in order for it to be successfully incorporated as a seed layer/barrier layer for the direct plating of Cu. The improvement of its barrier performance, by modifying the Ru microstructure from columnar to amorphous (by incorporating the N into Ru during PVD), has been previously reported [7]. Another approach for improving the barrier performance of the Ru film is to use Ru as a just seed layer and combine it with superior materials to function as a diffusion barrier against the Cu. A RulTaN bilayer prepared by PVD has recently been suggested as a seed layer/diffusion barrier for Cu. This bilayer was stable between the Cu and Si after annealing at $700^{\circ}C$ for I min [8]. Although these reports dealt with the possible applications of Ru for Cu metallization, cases where the Ru film was prepared by atomic layer deposition (ALD) have not been identified. These are important because of ALD's excellent conformality. In this study, a bilayer diffusion barrier of Ru/TaCN prepared by ALD was investigated. As the addition of the third element into the transition metal nitride disrupts the crystal lattice and leads to the formation of a stable ternary amorphous material, as indicated by Nicolet [9], ALD-TaCN is expected to improve the diffusion barrier performance of the ALD-Ru against Cu. Ru was deposited by a sequential supply of bis(ethylcyclopentadienyl)ruthenium [Ru$(EtCp)_2$] and $NH_3$plasma and TaCN by a sequential supply of $(NEt_2)_3Ta=Nbu^t$ (tert-butylimido-trisdiethylamido-tantalum, TBTDET) and $H_2$ plasma. Sheet resistance measurements, X-ray diffractometry (XRD), and Auger electron spectroscopy (AES) analysis showed that the bilayer diffusion barriers of ALD-Ru (12 nm)/ALD-TaCN (2 nm) and ALD-Ru (4nm)/ALD-TaCN (2 nm) prevented the Cu diffusion up to annealing temperatures of 600 and $550^{\circ}C$ for 30 min, respectively. This is found to be due to the excellent diffusion barrier performance of the ALD-TaCN film against the Cu, due to it having an amorphous structure. A 5-nm-thick ALD-TaCN film was even stable up to annealing at $650^{\circ}C$ between Cu and Si. Transmission electron microscopy (TEM) investigation combined with energy dispersive spectroscopy (EDS) analysis revealed that the ALD-Ru/ALD-TaCN diffusion barrier failed by the Cu diffusion through the bilayer into the Si substrate. This is due to the ALD-TaCN interlayer preventing the interfacial reaction between the Ru and Si.

• Korean Chemical Engineering Research
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• v.50 no.2
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• pp.365-370
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• 2012

In this study, Economic analysis of supercritical coal-fired power plant with $CO_2$ capture process was performed. For this purpose, chemical absorption method using amine solvent, which is commercially available and most suitable for existing thermal power plant, was studied. For the evaluation of the economic analysis of coal-fired power plant with post-combustion $CO_2$ capture process in Korea, energy penalty after $CO_2$ capture was calculated using the power equivalent factor suggested by Bolland et al. And the overnight cost of power plant (or cost of plant construction) and the operation cost reported by the IEA (International Energy Agency) were used. Based on chemical absorption method using a amine solvent and 3.31 GJ/$tonCO_2$ as a regeneration energy in the stripper, the net power efficiency was reduced from 41.0% (without $CO_2$ capture) to 31.6% (with $CO_2$ capture) and the levelized cost of electricity was increased from 45.5 USD/MWh (Reference case, without $CO_2$ capture) to 73.9 USD/MWh (With $CO_2$ capture) and the cost of $CO_2$ avoided was estimated as 41.3 USD/$tonCO_2$.

• Korean Journal of Environment and Ecology
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• v.26 no.1
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• pp.46-56
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• 2012

Benthic macroinvertebrates were investigated in Hoeongseong Lake region from March to October 2010, Korea. Macroinvertebrate communities, composition of the functional feeding groups, habitiat oriented groups and the biological water quality were assessed above and below Hoeongseong Dam in the lake region. Six sites, two (St.1~2) above the lake, two (St. 3~4) into the lake, and two (St. 5~6) below the dam, were selected for quantitative (Surber sampler $30cm{\times}30cm$, mesh size 0.2 mm) and qualitative (Hand net) samplings of benthic macroinvertebrates. As a result, a total of 83 species belonging to 43 families, 17 orders, 8 classes, and 5 phyla were recognized. The EPT-group (50 spp. : 60.24%) that is major taxa or EPT-group plus Diptera (61 spp. : 73.49%) occupied most of benthic macroinvertebrates community. Based on quantitative sampling, the number of benthic maroinvertebrates above the lake was 2,399 individuals including 54 species, 28 families, 11 orders, 4 classes, and 4 phyla, whereas 510 individuals including 16 species, 12 families, 7 orders, 4 classes, and 3 phyla in the lake and 626 individuals including 62 species, 33 families, 13 orders, 6 classes, and 4 phyla below the dam were collected respectively. Dominance index was the highest, with 0.82-0.93 ($0.87{\pm}0.05$) in Hoeongseong lake (St. 3-4), diversity index was 3.04-3.16 ($3.10{\pm}0.06$), evenness index was 0.79-0.85 ($0.82{\pm}0.03$), and richness index was 7.27-8.52 ($7.90{\pm}0.63$), which were relatively higher below the dam sites. In the functional feeding groups, collector-gatherers and collector-filterers were the highest in the whole sites, and predators (Micronecta sedula) was appeared highly in the lake. Moreover, swimmers, burrowers, and clingers were considerably occupied in all collecting sites. The result of the DCA, similarity analysis, and MRPP were well reflective of the composition of lake and stream macroinvertebrates. ESB indicate that the lake sites were evaluated heavily polluted under priority improvement waters. Also, Semisulcospira gottschei, Ecdyonurus kibunensis, Epeorus pellucidus, Rhoenanthus coreanus, Stenelmis sp., and Cheumatopsyche brevilineata are considered as an indicator species above and below Hoeongseong Lake, whereas Macrobrachium nipponense and Micronecta sedula are indicated in the lake.

• Korean journal of applied entomology
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• v.56 no.4
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• pp.387-394
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• 2017

Temperature-dependent oviposition model and life table parameters of Paromius exiguus (Distant), the causal agent of 'pecky' rice grain were examined at eight constant temperatures (17.5, 20, 22.5, 25, 27.5, 30, 32.5, and $35{\pm}^{\circ}C$) and a photoperiod of 14:10 (L:D) h. Unit functions of the oviposition model were developed and life table parameters were estimated. The longevity of P. exiguus adults decreased with increasing temperature (123.8 days at $17.5^{\circ}C$ and 23.6 days at $32.5^{\circ}C$). Total fecundity was highest at $30^{\circ}C$ (585.2 eggs/female) and lowest at $17.5^{\circ}C$ (21.5 eggs/female). In order to develop a temperature-dependent oviposition model, adult aging-rate, temperature-dependent fecundity, age-specific survival rate, and age-specific cumulative oviposition rate equations were estimated. All unit equations ($r^2=0.92{\sim}0.98$) except for the temperature-dependent fecundity equation ($r^2=0.83{\sim}0.85$), described oviposition characteristics of P. exiguus adequately. Life table parameters of P. exiguus were estimated at various constant temperatures. Net reproduction rate ($R_0$) was highest at $30^{\circ}C$ (118.21). Mean generation time (T) was shortest at $32.5^{\circ}C$ (32.99 days) and doubling time (Dt) was shortest at $30^{\circ}C$ (5.69 days). The highest values of intrinsic rate of increase ($r_m$) and finite rate of increase (${\lambda}$) were 0.122 and 1.129 at $30^{\circ}C$, respectively.