• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.1
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• pp.76-82
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• 2010

Experiments were conducted to investigate seed persistence of Chinese milk vetch(CMV) in naturally reseeded rice field in 2007~2009. The seed and pods with seeds were buried in rice field at 0, 5 and 10 cm depths and retrieved from the field at one to three month intervals from July to the following year March and determined change of seed dormancy and viability. In the second experiment, persistence of the CMV seeds in the naturally reseeded rice field at different tillage methods and soil depths were also investigated after rice harvest in autumn. Burial depths and durations affected recovery rate, dormancy and viability of CMV seed. The viability loss was faster and greater in the seed than the pod with seeds and on the soil surface than the 5 or 10 cm burial depths. The recovery rate of CMV seed was decreased starting from one month as seed burial and it was significantly decreased to 52~65% for the seed in September. However, unlike the seed burial, the nearly 100% CMV seeds were recovered for burial as pod with seeds even after four months burial in both 0 and 5 cm depths. However, the recovery rate was sharply declined to below 30% at October in 2007 in both seed and pods with seeds and in the 2008/2009 experiment. the 15~47% of CMV seeds still remained even after October. The CMV had high seed dormancy of 95%, showing only 4~5% germination at the beginning in June but the seed germination increased to 25 to 35% in seed and 55 to 61% in pod with seeds in September due to breakage of hard seed dormancy. The viability loss was faster in the seed than in the pod with seeds regardless of depths of placement in the soil base on decayed seeds. Also the seed placed on the soil surface lost viability faster than the 5~10 burial depths. On the other hand, field observation in the naturally reseeded CMV rice field showed that as many as 917~2,185 CMV seeds $m^2$ were from the 0~15 cm soil depth in the rotary tillage and 250~10,105 CMV seeds in minimum tillage treatmints. The recovered seed germinated 25~33%, 23~43% but still had high percentage of hard seed having 64~72% and 51~77% even after rice harvest in autumn. These results indicate that freshly harvested CMV seeds had high level of primary dormancy and the dormancy was gradually broken in soil with time during rice cultivation periods and appreciable number of CMV seeds remained even 4 month after burial in soil. CMV plant regenerated naturally from the remained seed bank at rice harvest time in autumn. The CMV seedling still emerged even after 2 years of continuous destructive killing of emerged CMV plant by rotary tillage in naturally reseeded CMV plant in rice field, indicating that CMV seeds do persistent as least two years in soil.

• Journal of the Korean Society for Marine Environment & Energy
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• v.9 no.1
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• pp.1-13
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• 2006

A field survey on the spatio-temporal distribution characteristics and origins of organic matter in surface sediments was carried out monthly at six stations in Gamak Bay, South Korea from April 2000 to March 2002. The range of ignition loss(IL) was $4.6{\sim}11.6%(7.1{\pm}1.6%)$, while chemical oxygen demand(CODs) ranged from $12.25{\sim}99.26mgO_2/g-dry(30.98{\pm}19.09mgO_2/g-dry)$, acid volatile sulfide(AVS) went from no detection(ND)${\sim}10.29mgS/g-dry(1.02{\pm}0.58mgS/g-dry)$, and phaeopigment was $6.84{\sim}116.18{\mu}g/g-dry(23.72{\pm}21.16{\mu}g/g-dry)$. The ranges of particulate organic carbon(POC) and particulate organic nitrogen(PON) were $5.45{\sim}23.24 mgC/g-dty(10.34{\pm}4.40C\;mgC/g-dry)$ and $0.71{\sim}2.99mgN/g-dry(1.37{\pm}0.58mgN/g-dry)$, respectively. Water content was in the range of $43.1{\sim}77.6%(55.8{\pm}5.6%)$, and mud content(silt+clay) was higher than 95% at all stations. The spatial distribution of organic matter in surface sediments was greatly divided between the northwestern, central and eastern areas, southern entrance area from the distribution characteristic of their organic matters. The concentrations of almost all items were greater at the northwestern and southern entrance area than at the other areas in Gamak Bay. In particular, sedimentary pollution was very serious at the northwestern area, because the area had an excessive supply of organic matter due to aquaculture activity and the inflow of sewage from the land. These materials stayed longer because of the topographical characteristics of such as basin and the anoxic conditions in the bottom seawater environment caused by thermocline in the summer. The tendency of temporal change was most prominently in the period of high-water temperatures than low-water ones at the northwestern and southern entrance areas. On the other hand, the central and eastern areas did not show a regular trend for changing the concentrations of each item but mainly showed a higher tendency during the low-water temperatures. This was observed for all but AVS concentrations which were higher during the period of high-water temperature at all stations. Especially, the central and eastern areas showed a large temporal increase of AVS concentration during those periods of high-water temperature where the concentration of CODs was in excess of $20mgO_2/g-dry$. The results show that the organic matters in surface sediments in Gamak Bay actually originated from autochthonous organic matters with eight or less in average C/N ratio including the organic matters generated by the use of ocean, rather than terrigenous organic matters. However, the formation of autochthonous organic matter was mainly derived from detritus than living phytoplankton, indicated the results of the POC/phaeopigment ratio. In addition, the CODs/IL ratio results demonstrate that the detritus was the product of artificial activities such as dregs feeding and fecal pellets of farm organisms caused by aquaculture activities rather than the dynamic of natural ocean activities.

• The Journal of Dong Guk Oriental Medicine
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• v.10
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• pp.119-145
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• 2008

Through a simple study of the medical classics in the '$\bar{A}yurveda$', we have summarized them as follows. 1) Traditional Indian medicine started in the Ganges river area at about 1500 B. C. E. and traces of medical science can be found in the "Rigveda" and "Atharvaveda". 2) The "Charaka(閣羅迦集)" and "$Su\acute{s}hruta$(妙聞集)", ancient texts from India, are not the work of one person, but the result of the work and errors of different doctors and philosophers. Due to the lack of historical records, the time of Charaka(閣羅迦) or $Su\acute{s}hruta$(妙聞)s' lives are not exactly known. So the completion of the "Charaka" is estimated at 1st$\sim$2nd century C. E. in northwestern India, and the "$Su\acute{s}hruta$" is estimated to have been completed in 3rd$\sim$4th century C. E. in central India. Also, the "Charaka" contains details on internal medicine, while the "$Su\acute{s}hruta$" contains more details on surgery by comparison. 3) '$V\bar{a}gbhata$', one of the revered Vriddha Trayi(triad of the ancients, 三醫聖) of the '$\bar{A}yurveda$', lived and worked in about the 7th century and wrote the "$Ast\bar{a}nga$ $Ast\bar{a}nga$ hrdaya $samhit\bar{a}$ $samhit\bar{a}$(八支集) and "$Ast\bar{a}nga$ Sangraha $samhit\bar{a}$(八心集)", where he tried to compromise and unify the "Charaka" and "$Su\acute{s}hruta$". The "$Ast\bar{a}nga$ Sangraha $samhit\bar{a}$" was translated into Tibetan and Arabic at about the 8th$\sim$9th century, and if we generalize the medicinal plants recorded in each the "Charaka", "$Su\acute{s}hruta$" and the "$Ast\bar{a}nga$ Sangraha $samhit\bar{a}$", there are 240, 370, 240 types each. 4) The 'Madhava' focused on one of the subjects of Indian medicine, '$Nid\bar{a}na$' ie meaning "the cause of diseases(病因論)", and in one of the copies found by Bower in 4th century C. E. we can see that it uses prescriptions from the "BuHaLaJi(布唅拉集)", "Charaka", "$Su\acute{s}hruta$". 5) According to the "Charaka", there were 8 branches of ancient medicine in India : treatment of the body(kayacikitsa), special surgery(salakya), removal of alien substances(salyapahartka), treatment of poison or mis-combined medicines(visagaravairodhikaprasamana), the study of ghosts(bhutavidya), pediatrics(kaumarabhrtya), perennial youth and long life(rasayana), and the strengthening of the essence of the body(vajikarana). 6) The '$\bar{A}yurveda$', which originated from ancient experience, was recorded in Sanskrit, which was a theorization of knowledge, and also was written in verses to make memorizing easy, and made medicine the exclusive possession of the Brahmin. The first annotations were 1060 for the "Charaka", 1200 for the "$Su\acute{s}hruta$", 1150 for the "$Ast\bar{a}nga$ Sangraha $samhit\bar{a}$", and 1100 for the "$Nid\bar{a}na$". The use of various mineral medicines in the "Charaka" or the use of mercury as internal medicine in the "$Ast\bar{a}nga$ Sangraha $samhit\bar{a}$", and the palpation of the pulse for diagnosing in the '$\bar{A}yurveda$' and 'XiZhang(西藏)' medicine are similar to TCM's pulse diagnostics. The coexistence with Arabian 'Unani' medicine, compromise with western medicine and the reactionism trend restored the '$\bar{A}yurveda$' today. 7) The "Charaka" is a book inclined to internal medicine that investigates the origin of human disease which used the dualism of the 'Samkhya', the natural philosophy of the 'Vaisesika' and the logic of the 'Nyaya' in medical theories, and its structure has 16 syllables per line, 2 lines per poem and is recorded in poetry and prose. Also, the "Charaka" can be summarized into the introduction, cause, judgement, body, sensory organs, treatment, pharmaceuticals, and end, and can be seen as a work that strongly reflects the moral code of Brahmin and Aryans. 8) In extracting bloody pus, the "Charaka" introduces a 'sharp tool' bloodletting treatment, while the "$Su\acute{s}hruta$" introduces many surgical methods such as the use of gourd dippers, horns, sucking the blood with leeches. Also the "$Su\acute{s}hruta$" has 19 chapters specializing in ophthalmology, and shows 76 types of eye diseases and their treatments. 9) Since anatomy did not develop in Indian medicine, the inner structure of the human body was not well known. The only exception is 'GuXiangXue(骨相學)' which developed from 'Atharvaveda' times and the "$Ast\bar{a}nga$ Sangraha $samhit\bar{a}$". In the "$Ast\bar{a}nga$ Sangraha $samhit\bar{a}$"'s 'ShenTiLun(身體論)' there is a thorough listing of the development of a child from pregnancy to birth. The '$\bar{A}yurveda$' is not just an ancient traditional medical system but is being called alternative medicine in the west because of its ability to supplement western medicine and, as its effects are being proved scientifically it is gaining attention worldwide. We would like to say that what we have researched is just a small fragment and a limited view, and would like to correct and supplement any insufficient parts through more research of new records.

• 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.

• Tuberculosis and Respiratory Diseases
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• v.42 no.5
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• pp.744-751
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• 1995

Background: Asthma is an inflammatory disease because there are many inflammatory changes in the asthmatic airways. Axon reflex mechanisms may be involved in the pathogenesis of asthma. Sensory neuropeptides are involved in this inflammation, which is defined as neurogenic inflammation. Substance p, neurokinin A, and neurokinin B may be main neuropeptides of neurogenic inflammation in airways. These tachykinins act on neurokinin receptors. Three types of neurokinin receptors, such as $NK_1$, $NK_2$, and $NK_3$, are currently recognized, at which substance p, neurokinin A, and neurokinin B may be the most relevant natural agonist of neurogenic inflammation in airways. The receptor subtypes present in several tissues have been characterized on the basis of differential sensitivity to substance p, neurokinin A, and neurokinin B. Plasma extravasation and vasodilation are induced by substance p more potently than by neurokinin A, indicating NK1 receptors on endothelial cells mediate the response. But airway contraction is induced by neurokinin A more potently than by substance P, indicating the $NK_2$ receptors in airway smooth muscles. These receptors are used to evaluate the pathogenesis of brochial asthma. FK224 was identified from the fermentation products of Streptomyces violaceoniger. FK224 is a dual antagonist of both $NK_1$ and $NK_2$ receptors. Purpose: For a study of pathogenesis of bronchial asthma, the effect of FK224 on plasma extravasation induced by vagal NANC electrical stimulation was evaluated in rat airway. Method: Male Sprague-Dawley rats weighing 180~450gm were anesthetized by i.p. injection of urethane. Plasma extravasation was induced by electrical stimulation of cervical vagus NANC nerves with 5Hz, 1mA, and 5V for 2 minutes(NANC2 group) and for sham operation without nerve stimulation(control group). To evaluate the effect of FK224 on plasma extravasation in neurogenic inflammation, FK224(1mg/kg, Fujisawa Pharmaceutical Co., dissolved in dimethylsulphoxide; DMSO, Sigma Co.) was injected 1 min before nerve stimulation(FK224 group). To assess plasma exudation, Evans blue dye(20mg/kg, dissolved in saline) was used as a plasma marker and was injected before nerve stimulation. After removal of intravascular dye, the evans blue dye in the tissue was extracted in formamide($37^{\circ}C$, 24h) and quantified spectrophotometrically by measuring dye absorbance at 629nm wavelength. Tissue dye content was expressed as ng of dye per mg of wet weight tissue. The amount of plasma extravasation was measured on the part of airways in each groups. Results: 1) Vagus nerve(NANC) stimulation significantly increased plasma leakage in trachea, main bronchus, and peripheral bronchus compared with control group, $14.1{\pm}1.6$ to $49.7{\pm}2.5$, $17.5{\pm}2.0$ to $38.7{\pm}2.8$, and $12.7{\pm}2.2$ to $19.1{\pm}1.6ng$ of dye per mg of tissue(mean ${\pm}$ SE), respectively(p<0.05). But there was not significantly changed in lung parenchyma(p>0.05) 2) FK224 had significant inhibitory effect upon vagal nerve stimulation-induced airway plasma leakage in any airway tissues of rat,such as trachea, main bronchus, and peripheral bronchus compared with vagus nerve stimulation group, 49%, 58%, and 70%, respectively(p<0.05). Inhibitory effect of FK224 on airway plasma leakage in neurogenic inflammation was revealed the more significant in peripheral bronchus, but no significant in lung parenchyma. Conclusion: These results suggest that FK224 is a selective NK receptor antagonist which effectively inhibits airway plasma leakage induced by the endogenous neurotransmitters relased by neurogenic inflammation in rat airway. Tachykinin receptor antagonists may be useful in the treatment of brochial asthma.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.2
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• pp.27-34
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• 2016

The results of investigation on the spatial composition and landscape characteristics of Shimwon-pavilion garden built and enjoyed by Jo Byeong-sun in 1937 during the period of Japanese colonialism based on 'Shimwon-pavilion Soosukgii(水石記)' and 'Shimwon-pavilion Poem of 25 Sceneries(二十五詠)' contained in 'Anthology of Giheon(寄軒)' are as follows. 1. Shimwon-pavilion garden is assumed as Byeol-Seo garden based on the planning background and contents of Gimun and the observations on spot. By its location, it is classified as 'Planted forest' with a pine forest in the north and 'Byeol-Seo of mooring type' with Guyacheon flowing in the garden. It is about 400m away from the main house in the straight-line distance. 2. The meaning and attributes of reclusiveness are well represented in the 'screening structures' all around Shimwon-pavilion garden with Hakrimsan, a Gasan(假山) in the north, vines on Chwibyeong(翠屛) in the east and west, Eunbyeong(隱屛) of stone walls along with Guyacheon in the south, which shows the spirit of Giheon who adored the Taoistic life. 3. Shimwon-pavilion garden, located in the Songrimsa, a temple of thousand years, is a place of consilience where Buddhism was accepted, Taoistic life was pursued with Tao Yuan-ming's philosophy regarding rural areas and romantic sensibilities of Li Po, called poem master(詩仙), the confucian values of Zhu Xi were realized. Giheon intended to build and enjoy this place as a microcosm and shelther where he unfolded his own view of learning and cultivated his mind. 4. 25 sceneries on Shimwon-pavilion consist of 5 sceneries in the space of pavilion(architecture) and 20 sceneries in the outer garden. First, 5 sceneries consist of ancillary rooms for various uses, including Jeongunru, Amsushil, Wiryujae, Iyeoldang, and Jeong-Gak Shimwon-pavilion embracing them, which shows that Shimwon-pavilion is a place to foster younger students. And 20 scenary is divided into 9 sceneries on the natural spaces and 11 artificially created facilities. 9 sceneries are engraved on the rocks as described in 'Seokgyeonggi'. 5. 4 sceneries of the indoor scenery lexemes(亭閣 心遠亭 怡悅堂 停雲樓 闇修室) were intended to be recognized by the framed pictures, 5 places among the scenery lexemes in garden(龜巖 醒石 隱屛 兩忘臺 東槃) by letters carved on the rocks, and 8 places(君子沼 杞泉 天光雲影橋 芳園 槐岡 柳堤 石扉 東翠屛) by sign stones, but signs of 8 sceneries are not currently identified because they have been be swept away and demolished. 6. A variety of plant landscapes with various meanings and water landscape with various types are contained in 25 sceneries - Sophora symbolizing a tree for scholar in Gehgang(槐岡), Willow symbolizing Tao Yuanming and continued vitality in Yooje(柳堤), Boxthorn symbolizing family togetherness in spring(杞泉), vines and herbal plants and waterfalls(隱瀑), shallow pond(君子沼), pond(湯池), water hole(杞泉), water flowing in the middle of rock(盤陀石), water flowing between the rocks(水口巖). 7. While Shimwon-pavilion garden is a garden near the water, the active involvements with 11 sceneries directly built is distinguished. The other pavilion gardens are faithful in engraving the names by setting the scenery lexemes of the nature-oriented Gyeong(景) and Gok(曲) near and far, but Shimwon-pavilion garden is a garden for active learning(修景) with the spaces built to match with the beautiful nature and to show the depths of space off.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.171-196
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• 2018

With the development of the web, two-way communication and evaluation became possible and marketing paradigms shifted. In order to meet the needs of consumers, web design trends are continuously responding to consumer feedback. As the web becomes more and more important, both academics and businesses are studying consumer emotions and satisfaction on the web. However, some consumer characteristics are not well considered. Demographic characteristics such as age and sex have been studied extensively, but few studies consider psychological characteristics such as regulatory focus (i.e., emotional regulation). In this study, we analyze the effect of web style on consumer emotion. Many studies analyze the relationship between the web and regulatory focus, but most concentrate on the purpose of web use, particularly motivation and information search, rather than on web style and design. The web communicates with users through visual elements. Because the human brain is influenced by all five senses, both design factors and emotional responses are important in the web environment. Therefore, in this study, we examine the relationship between consumer emotion and satisfaction and web style and design. Previous studies have considered the effects of web layout, structure, and color on emotions. In this study, however, we excluded these web components, in contrast to earlier studies, and analyzed the relationship between consumer satisfaction and emotional indexes of web-style only. To perform this analysis, we collected consumer surveys presenting 40 web style themes to 204 consumers. Each consumer evaluated four themes. The emotional adjectives evaluated by consumers were composed of 18 contrast pairs, and the upper emotional indexes were extracted through factor analysis. The emotional indexes were 'softness,' 'modernity,' 'clearness,' and 'jam.' Hypotheses were established based on the assumption that emotional indexes have different effects on consumer satisfaction. After the analysis, hypotheses 1, 2, and 3 were accepted and hypothesis 4 was rejected. While hypothesis 4 was rejected, its effect on consumer satisfaction was negative, not positive. This means that emotional indexes such as 'softness,' 'modernity,' and 'clearness' have a positive effect on consumer satisfaction. In other words, consumers prefer emotions that are soft, emotional, natural, rounded, dynamic, modern, elaborate, unique, bright, pure, and clear. 'Jam' has a negative effect on consumer satisfaction. It means, consumer prefer the emotion which is empty, plain, and simple. Regulatory focus shows differences in motivation and propensity in various domains. It is important to consider organizational behavior and decision making according to the regulatory focus tendency, and it affects not only political, cultural, ethical judgments and behavior but also broad psychological problems. Regulatory focus also differs from emotional response. Promotion focus responds more strongly to positive emotional responses. On the other hand, prevention focus has a strong response to negative emotions. Web style is a type of service, and consumer satisfaction is affected not only by cognitive evaluation but also by emotion. This emotional response depends on whether the consumer will benefit or harm himself. Therefore, it is necessary to confirm the difference of the consumer's emotional response according to the regulatory focus which is one of the characteristics and viewpoint of the consumers about the web style. After MMR analysis result, hypothesis 5.3 was accepted, and hypothesis 5.4 was rejected. But hypothesis 5.4 supported in the opposite direction to the hypothesis. After validation, we confirmed the mechanism of emotional response according to the tendency of regulatory focus. Using the results, we developed the structure of web-style recommendation system and recommend methods through regulatory focus. We classified the regulatory focus group in to three categories that promotion, grey, prevention. Then, we suggest web-style recommend method along the group. If we further develop this study, we expect that the existing regulatory focus theory can be extended not only to the motivational part but also to the emotional behavioral response according to the regulatory focus tendency. Moreover, we believe that it is possible to recommend web-style according to regulatory focus and emotional desire which consumers most prefer.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.50-63
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• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.