• Journal of the Korean Vacuum Society
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• v.18 no.4
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• pp.302-309
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• 2009

We fabricated a Si nano floating gate memory with Schottky barrier tunneling transistor structure. The device was consisted of Schottky barriers of Er-silicide at source/drain and Si nanoclusters in the gate stack formed by LPCVD-digital gas feeding method. Transistor operations due to the Schottky barrier tunneling were observed under small gate bias < 2V. The nonvolatile memory properties were investigated by measuring the threshold voltage shift along the gate bias voltage and time. We obtained the 10/50 mseconds for write/erase times and the memory window of $\sim5V$ under ${\pm}20\;V$ write/erase voltages. However, the memory window decreased to 0.4V after 104seconds, which was attributed to the Er-related defects in the tunneling oxide layer. Good write/erase endurance was maintained until $10^3$ write/erase times. However, the threshold voltages moved upward, and the memory window became small after more write/erase operations. Defects in the LPCVD control oxide were discussed for the endurance results. The experimental results point to the possibility of a Si nano floating gate memory with Schottky barrier tunneling transistor structure for Si nanoscale nonvolatile memory device.

• Korean Journal of Heritage: History & Science
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• v.47 no.1
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• pp.164-179
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• 2014

The Buddhas of the Three Words in a form of arranging Bhaiṣajyaguru and $Amit{\bar{a}}bha$ at its side based on ${\acute{S}}{\bar{a}}kyamuni$ at the center is enshrined in Daeungbojeon Hall of Daeheungsa Temple located at Haenam. So far, this Buddhas of the Three Words has been known as a wooden Buddha statue. However, as a result of X-ray screening, in left/right Buddha statues excepting main Buddha, wood and molding clay layer were observed at the same time. Therefore, this study intended to observe its internal structure, grafting method and to clarify making technique of Buddha statue during Joseon era based on image information being obtained through X-ray screening of The Buddhas of the Three Words of Daeheungsa Temple. As its result, it was revealed that form of ${\acute{S}}{\bar{a}}kyamuni$ was completed by mainly grafting 5 pieces of timber and this statue shows a typical wood grafted Buddha statue during Joseon era. Form of Bhaiṣajyaguru and $Amit{\bar{a}}bha$ were completed based on molding technique by applying clay on sculpture similar to its appearance after sculpturing more than 10 pieces of timber through its grafting. In other words, internal timber is considered to play a role of its core and grafting method of timber is more close to a technique of molding Buddha statue than to that of wooden Buddha statue during Joseon era. However, clay was directly applied on timber thinly, not applying clay thickly on it after winding straw rope on wooden core and its characteristic is that its facial area was completely composed of wooden construction only. Therefore, it is hard to rule out a possibility that the original sculpturing intention of an artist might be a wooden Buddha statue but in view of the fact that a word, 'molding' was used in a record of relics buried in statue, it could be seen that this Buddha statue might have been recognized as a molding statue at the time when creation of this statue was completed. It is considered that number of case of making statue based on this technique would be more increased when more results of X-ray screening should be accumulated and if more data should be collected, it would provide a significant evidence for identifying chronological, regional aspects of making technique of Buddha statue.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of agriculture & life science
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• v.50 no.1
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• pp.105-115
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• 2016

This study was carried out to establish the optimum forest management plan for the Cryptomeria japonica plantations in southern inland and Jeju island in Korea. Sixty seven circular sample plots of 0.04ha were established and we surveyed vegetation structure and growth characteristics from three layers(upper, middle, and lower). As a result of cluster analysis obtained by importance values of each tree species, the community type of C. japonica stands were classified into C. japonica group(C1) and C. japonica-C obtusa group. C. obtusa community were also sbudivided into P. thunbergii-Q. serrata group(C2) and Q. serrata-C obtusa group(C3). In tree layers importance value(IV) of C. japonica were 97.2% in C1, 80.7% in C2, and 47.6% in C3 and in sub-tree layers IV were 8.9% in C1, 15.2% in C2, and 5.7% in C3. Especially in C3 there are bamboo species (Smilacina japonica var. lutecarpa and Pseudosasa japonica) it is necessary for us to control them. In shrub layers C. japonica were found in C1(9.2%) and C2(7.0%), but except for C3. In tree layer species diversity indices of each community ranged from the lowest 0.059 in C1 to the highest 0.548 in C3. Dominance ranged from 0.958 in C1 to 0.393 in C3 which may caused by interspecific competition. Current annual increment of diameter growth ranged from 7.01mm/yr to 8.04mm/yr. As a result of our study we recommend the application of proper thinning and pruning for C1 and C2.

• Korean Journal of Environment and Ecology
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• v.37 no.2
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• pp.163-178
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• 2023

This study was conducted to understand the vegetation characteristics of Cheongwansan Provincial Park through the analysis of the plant community structure and to build data necessary for the continuous management and protection of Cheongwansan Provincial Park. The TWINSPAN and DCS analyses of the plant community structure of 63 survey districts in Cheongwansan Provincial Park identified eight colonies, including Cryptomeria japonica Community (I), Chamaecyparis obtusa-Pinus densiflora Commuity (II), P. rigida-P. densiflora Community (III), mixed coniferous and broad-leaved Community (IV), P. densiflora Community (V), deciduous broad-leaved such as Quercus spp. Community (VI), Q. mongolica-P. densiflora Community (VII) and P. thunbergii Community (VIII). The colonies can be grouped into afforestation communities (I, II, and III) dominated by C. obtusa, C. japonica, and P. rigida and natural forest communities (IV, V, VI, VII, and VIII) dominated by native species. Although Cheongwansan Provincial Park is a provincial park area that can represent natural ecosystems and landscapes, the rate of artificial forests is higher than that of other provincial parks. Most of the artificial forest communities are expected to maintain their current state, but since native species such as Machilus thunbergii, Neolitsea sericea, and deciduous broad-leaved, which are warm-temperate trees introduced through surrounding natural forests, appear in the lower layer, it is determined that it is possible to induce succession to natural forests suitable for climatic characteristics through management, and monitoring for continuous management is also necessary. Deciduous broad-leaved such as Quercus spp. Copete with P. densiflora in most natural forest communities. The vegetation series in the warm-temperate region of Korea appears to be in the early stages, and it is believed that the succession to Q. serrata or Q. mongolica, which appears next to coniferous in the series, is in progress. However, M. thunbergii and N. sericea, which appear in the middle stage of the succession in the warm-temperate region, have started to appear, and since Jangheung-gun belongs to the warm-temperate region considering the climate characteristics, the eventual succession to the warm-temperate forests dominated by evergreen broad-leaved is also expected. In this study, we built vegetation data from Cheongwansan Provincial Park, which lacks research on vegetation. However, since vegetation research in Cheongwansan Provincial Park is still insufficient, it is believed that further research should be continuously conducted to establish forest vegetation data and observe vegetation changes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.924-942
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• 2021

The expansion of the Changjiang Diluted Water (CDW) plume during summer is known to be a major factor influencing phytoplankton diversity, community structure, and the regional marine environment of the northern East China Sea (ECS). The discharge of the CDW plume was very high in the summer of 2020, and cruise surveys and stationary monitoring were conducted to understand the dynamics of changes in environmental characteristics and the impact on phytoplankton diversity and community structure. A cruise survey was conducted from August 16 to 17, 2020, using R/V Eardo, and a stay survey at the Ieodo Ocean Research Station (IORS) from August 15 to 21, 2020, to analyze phytoplankton diversity and community structure. The southwestern part of the survey area exhibited low salinity and high chlorophyll a fluorescence under the influence of the CDW plume, whereas the southeastern part of the survey area presented high salinity and low chlorophyll a fluorescence under the influence of the Tsushima Warm Current (TWC). The total chlorophyll a concentrations of surface water samples from 12 sampling stations indicated that nano-phytoplankton (20-3 ㎛) and micro-phytoplankton (> 20 ㎛) were the dominant groups during the survey period. Only stations strongly influenced by the TWC presented approximately 50% of the biomass contributed by pico-phytoplankton (< 3 ㎛). The size distribution of phytoplankton in the surface water samples is related to nutrient supplies, and areas where high nutrient (nitrate) supplies were provided by the CDW plume displayed higher biomass contribution by micro-phytoplankton groups. A total of 45 genera of nano- and micro-phytoplankton groups were classified using morphological analysis. Among them, the dominant taxa were the diatoms Guinardia flaccida and Nitzschia spp. and the dinoflagellates Gonyaulax monacantha, Noctiluca scintillans, Gymnodinium spirale, Heterocapsa spp., Prorocentrum micans, and Tripos furca. The sampling stations affected by the TWC and low in nitrate concentrations presented high concentrations of photosynthetic pico-eukaryotes (PPE) and photosynthetic pico-prokaryotes (PPP). Most sampling stations had phosphate-limited conditions. Higher Synechococcus concentrations were enumerated for the sampling stations influenced by low-nutrient water of the TWC using flow cytometry. The NGS analysis revealed 29 clades of Synechococcus among PPP, and 11 clades displayed a dominance rate of 1% or more at least once in one sample. Clade II was the dominant group in the surface water, whereas various clades (Clades I, IV, etc.) were found to be the next dominant groups in the SCM layers. The Prochlorococcus group, belonging to the PPP, observed in the warm water region, presented a high-light-adapted ecotype and did not appear in the northern part of the survey region. PPE analysis resulted in 163 operational taxonomic units (OTUs), indicating very high diversity. Among them, 11 major taxa showed dominant OTUs with more than 5% in at least one sample, while Amphidinium testudo was the dominant taxon in the surface water in the low-salinity region affected by the CDW plume, and the chlorophyta was dominant in the SCM layer. In the warm water region affected by the TWC, various groups of haptophytes were dominant. Observations from the IORS also presented similar results to the cruise survey results for biomass, size distribution, and diversity of phytoplankton. The results revealed the various dynamic responses of phytoplankton influenced by the CDW plume. By comparing the results from the IORS and research cruise studies, the study confirmed that the IORS is an important observational station to monitor the dynamic impact of the CDW plume. In future research, it is necessary to establish an effective use of IORS in preparation for changes in the ECS summer environment and ecosystem due to climate change.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47
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• pp.15-32
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• 2002

The endeavors enhancing the grain quality of high-yielding japonica rice were steadily continued during 1980s-1990s along with the self-sufficiency of rice production and the increasing demands of high-quality rices. During this time, considerably great progress and success was obtained in development of high-quality japonica cultivars and quality evaluation techniques including the elucidation of interrelationship between the physicochemical properties of rice grain and the physical or palatability components of cooked rice. In 1990s, some high-quality japonica rice cultivars and special rices adaptable for food processing such as large kernel, chalky endosperm, aromatic and colored rices were developed and its objective preference and utility was also examined by a palatability meter, rapid-visco analyzer and texture analyzer, Recently, new special rices such as extremely low-amylose dull or opaque non-glutinous endosperm mutants were developed. Also, a high-lysine rice variety was developed for higher nutritional utility. The water uptake rate and the maximum water absorption ratio showed significantly negative correlations with the K/Mg ratio and alkali digestion value(ADV) of milled rice. The rice materials showing the higher amount of hot water absorption exhibited the larger volume expansion of cooked rice. The harder rices with lower moisture content revealed the higher rate of water uptake at twenty minutes after soaking and the higher ratio of maximum water uptake under the room temperature condition. These water uptake characteristics were not associated with the protein and amylose contents of milled rice and the palatability of cooked rice. The water/rice ratio (in w/w basis) for optimum cooking was averaged to 1.52 in dry milled rices (12% wet basis) with varietal range from 1.45 to 1.61 and the expansion ratio of milled rice after proper boiling was average to 2.63(in v/v basis). The major physicochemical components of rice grain associated with the palatability of cooked rice were examined using japonica rice materials showing narrow varietal variation in grain size and shape, alkali digestibility, gel consistency, amylose and protein contents, but considerable difference in appearance and texture of cooked rice. The glossiness or gross palatability score of cooked rice were closely associated with the peak, hot paste and consistency viscosities of viscosities with year difference. The high-quality rice variety "IIpumbyeo" showed less portion of amylose on the outer layer of milled rice grain and less and slower change in iodine blue value of extracted paste during twenty minutes of boiling. This highly palatable rice also exhibited very fine net structure in outer layer and fine-spongy and well-swollen shape of gelatinized starch granules in inner layer and core of cooked rice kernel compared with the poor palatable rice through image of scanning electronic microscope. Gross sensory score of cooked rice could be estimated by multiple linear regression formula, deduced from relationship between rice quality components mentioned above and eating quality of cooked rice, with high probability of determination. The $\alpha$-amylose-iodine method was adopted for checking the varietal difference in retrogradation of cooked rice. The rice cultivars revealing the relatively slow retrogradation in aged cooked rice were IIpumbyeo, Chucheongyeo, Sasanishiki, Jinbubyeo and Koshihikari. A Tonsil-type rice, Taebaegbyeo, and a japonica cultivar, Seomjinbyeo, showed the relatively fast deterioration of cooked rice. Generally, the better rice cultivars in eating quality of cooked rice showed less retrogradation and much sponginess in cooled cooked rice. Also, the rice varieties exhibiting less retrogradation in cooled cooked rice revealed higher hot viscosity and lower cool viscosity of rice flour in amylogram. The sponginess of cooled cooked rice was closely associated with magnesium content and volume expansion of cooked rice. The hardness-changed ratio of cooked rice by cooling was negatively correlated with solids amount extracted during boiling and volume expansion of cooked rice. The major physicochemical properties of rice grain closely related to the palatability of cooked rice may be directly or indirectly associated with the retrogradation characteristics of cooked rice. The softer gel consistency and lower amylose content in milled rice revealed the higher ratio of popped rice and larger bulk density of popping. The stronger hardness of rice grain showed relatively higher ratio of popping and the more chalky or less translucent rice exhibited the lower ratio of intact popped brown rice. The potassium and magnesium contents of milled rice were negatively associated with gross score of noodle making mixed with wheat flour in half and the better rice for noodle making revealed relatively less amount of solid extraction during boiling. The more volume expansion of batters for making brown rice bread resulted the better loaf formation and more springiness in rice breed. The higher protein rices produced relatively the more moist white rice bread. The springiness of rice bread was also significantly correlated with high amylose content and hard gel consistency. The completely chalky and large grain rices showed better suitability far fermentation and brewing. The glutinous rice were classified into nine different varietal groups based on various physicochemical and structural characteristics of endosperm. There was some close associations among these grain properties and large varietal difference in suitability to various traditional food processing. Our breeding efforts on improvement of rice quality for high palatability and processing utility or value-adding products in the future should focus on not only continuous enhancement of marketing and eating qualities but also the diversification in morphological, physicochemical and nutritional characteristics of rice grain suitable for processing various value-added rice foods.ice foods.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.1
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• pp.93-106
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• 2014

In this study, Analyze environment of location, investigation into vegetation resources, survey management status and establish to classify the management area for Natural monument No.374 Pyengdae-ri Torreya nucifera forest. The results were as follows: First, Torreya nucifera forest is concerned about influence of development caused by utilization of land changes to agricultural region. Thus, establish to preservation management plan for preservation of prototypical and should be excluded development activity to cause the change of terrain that Gotjawal in the Torreya nucifera forest is factor of base for generating species diversity. Secondly, Torreya nucifera forest summarized as 402 taxa composed 91 familly 263 genus, 353 species, 41 varieties and 8 forms. The distribution of plants for the first grade & second grade appear of endangered plant to Ministry of Environment specify. But, critically endangered in forest by changes in habitat, diseases and illegal overcatching. Therefore, when establishing forest management plan should be considered for put priority on protection. Thirdly, Torreya nucifera representing the upper layer of the vegetation structure. But, old tree oriented management and conservation strategy result in poor age structure. Furthermore, desiccation of forest on artificial management and decline in Torreya nucifera habitat on ecological succession can indicate a problem in forest. Therefore, establish plan such as regulation of population density and sapling tree proliferation for sustainable characteristics of the Torreya nucifera forest. Fourth, Appear to damaged of trails caused by use. Especially, Scoria way occurs a lot of damaged and higher than the share ratio of each section. Therefore, share ratio reduction Plan should be considered through the additional development of tourism routes rather than the replacement of Scoria. Fifth, Representing high preference of the Torreya nucifera forest tourist factor confirmed the plant elements. It is sensitive to usage pressure. And requires continuous monitoring by characteristic of Non-permanent. In addition, need an additional plan such as additional development of tourism elements and active utilizing an element of high preference. Sixth, Strength of protected should be differently accordance with importance. First grade area have to maintenance of plant population and natural habitats. Set the direction of the management. Second grade areas focus on annual regeneration of the forest. Third grade area should be utilized demonstration forest or set to the area for proliferate sapling. Fourth grade areas require the introduced of partial rest system that disturbance are often found in proper vegetation. Fifth grade area appropriate to the service area for promoting tourism by utilizing natural resources in Torreya nucifera forest. Furthermore, installation of a buffer zone in relatively low ratings area and periodic monitoring to the improvement of edge effect that adjacent areas of different class.