• Journal of the Korean earth science society
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• v.38 no.7
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• pp.511-521
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• 2017

This study analyzes Two-dimensional video disdrometer (2DVD) data while summer 2011-2012 in Daegu region and compares with Marshall and Palmer (MP) distribution to find out statistical characteristics and characteristics variability about drop size distribution (DSD) of Daegu region. As the characterize DSD of Daegu region, this study uses single moment parameters such as rainfall intensity (R), reflectivity factor (Z) and double moment parameters such as generalized characteristics number concentration ($N{_0}^{\prime}$) and generalized characteristics diameter ($D{_m}^{\prime}$). Also, this study makes an assumption that DSD function can be expressed as general gamma distribution. The results of analysis show that DSD of Daegu region has ${\log}_{10}N{_0}^{\prime}=2.37$, $D{_m}^{\prime}=1.04mm$, and c =2.37, ${\mu}=0.39$ on average. When the assumption of MP distribution is used, these figures then end up with the different characteristics; ${\log}_{10}N{_0}^{\prime}=2.27$, $D{_m}^{\prime}=0.9mm$, c =1, ${\mu}=1$ on average. The differences indicate liquid water content (LWC) of Daegu distribution is generally larger than MP distribution at equal Z. Second, DSD shape of Daegu distribution is concave upward. Other important facts are the characteristics of Daegu distribution change when Z changes. DSD shape of Daegu region changes concave downward (c =2.05~2.55, ${\mu}=0.33{\sim}0.77$) to cubic function-like shape (c =3.0, ${\mu}=-0.13{\sim}-0.33$) at Z > 45 dBZ. 35 dBZ ${\leq}$ Z > 45 dBZ group of Daegu distribution has characteristics similar to maritime cluster of diverse climate DSD study. However, Z > 45 dBZ group of Daegu distribution has a difference from the cluster.

• Korean Journal of Plant Resources
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• v.26 no.1
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• pp.26-35
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• 2013

This study was conducted to select superior provenances of Scots pine (Pinus sylvestris L.) well adapted to Korean environment for timber production. In 1976, twenty-two provenances of Scots pine were introduced from Sweden and the seeds were sown in seed beds in March. After one year, the seedlings were transplanted to nursery beds. The resulting 1-1 seedlings of 22 provenances were planted at Whaseong in 1978. Randomized complete block design with 3 replications were used for test plantation. Each provenance was planted with 20-tree row plot in each block and at a spacing of $1.8{\times}1.8m$. The growth performance of each provenance was monitored up to 33-years after planting. There were significant differences among provenances in volume growth. F3001 provenance showed the best volume growth of 33-years after planting ($0.160m^3$), which was 2.2 times greater than that of the lowest provenance W2027 ($0.072m^3$). The ranking of provenances was stabilized after 14 years. Comparing to reference tree species, Japanese red pine (Pinus densiflora), all Scots pine provenances showed poor growth performance. In other words, volume growth of Japanese red pine at age 28 and 33 were 2.1 and 3.3 times greater than that of Scots pine, respectively. Moreover, survival rate of Scots pine was lower than that of Japanese red pine. Based on these results, it was suggested that Scots pine was not suitable to Korean environments. The cause of maladaptation of Scots pine and the implications of introduction breeding were discussed.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of recreation and landscape
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• v.6 no.2
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• pp.63-71
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• 2012

As the interest in rural tourism has been increasing since the late 1990s, the research associated with rural tourism has increased, including research on the classification of rural tourism resources. The research classifying these resources has proved useful to many other studies. Although such studies have been conducted for a long time, they have expressed only experts' perspectives and been supported by statistics, without reflecting on users' opinions. Given this background, this study aims to classify rural tourism resources by focusing on the rural activities for tourists who use those tourism resources. To achieve this, each study participant proceeded to collect tourism resources by using a rural amenity resources database, and a card sorting test was conducted. Thirty-two people who had previously gone sightseeing in the rural areas were chosen as participants in the card sorting test. After the card sorting test was complete, the results were reviewed by experts. These results yielded six categories: doing nature activities, eating and cooking local dishes, putting up (overnight stays), going sightseeing/appreciating the landscape, enjoying leisure activities, and doing artistic activities. In the doing nature activities category, there were four subcategories: experiencing local resources, experiencing nature, experiencing tradition, and harvesting. This study was conducted to improve the satisfaction and understanding of the tourists who visit rural areas. Thus, the classification of rural tourism resources developed by this study will be widely used to establish the framework or contents of websites, applications, and so on, for promoting rural tourism resources and local resources.

• Horticultural Science & Technology
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• v.19 no.4
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• pp.521-525
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• 2001

This study investigated the effects of conventional predrying and modified atmosphere (MA) on the head quality and storability of Chinese cabbage 'Norang' cultivar. Immediately after harvest, heads were predried for 2 days and MA stored in $50{\mu}m$ PE film packages at $4^{\circ}C$. MA packaging restrained Hunter L and b values of Chinese cabbage more effectively than non-packaging during storage at $4^{\circ}C$. But there was little change between the two treatments. Fresh weight decreased less in heads treated with predrying and MA than non-treatment during storage. Predried Chinese cabbage heads kept a high level of soluble solids in 4 weeks of storage, while non-packaging maintained high contents of soluble solids for 6 weeks of storage period. Chinese cabbage heads contained 7.0 mg/gFW glucose, 6.3 mg/gFW fructose, and 0.6 mg/gFW sucrose as major soluble sugars at harvest. The content of sugars decreased immediately after predrying and increased steadily after 2 weeks storage. It was found inappropriate to assess head quality of Chinese cabbage by investigating was investigated by Hunter a, firmness, dry matters content, pH, and soluble sugars after predrying and MA package. Marketability of Chinese cabbage was lost when heads were stored at room temperature in 2 weeks. It showed poor appearance of heads stored at $4^{\circ}C$ in 7 weeks. Decay occurred in Chinese cabbage stored in MA under excessive relative humidity. Predried head showed good appearance during storage at $4^{\circ}C$ for 7 weeks. As a result, Chinese cabbage heads can be successfully stored for at least 7 weeks with predrying and MA storage.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.353-365
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• 2019

A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R², and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.534-541
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• 2009

Word recognition test (WRT) for the children can be useful for diagnosing the degree of communication disability, prescribing hearing instruments, planning aural rehabilitation and speech therapy, and determination of site of lesions. The Korean standard monosyllabic word lists for preschoolers (KS-MWL-P) were developed considering the criteria given by the literatures. However, the authors of KS-MWL-P suggested more children should be included to verify homogeneity of the lists using psychometric function curve since only 8 children participated in the developing process. The purpose of this study was to explore the homogeneity of KS-MWL-P for supplementing the limitations of the lists employing psychometric analysis. To 23 preschoolers who have normal-hearing, 100 monosyllabic KS-MWL-P words were examined with the pictures. Psychometric function curve with linear slopes of 20% and 80%'s correct rates through accounting recognition scores of each monosyllabic word at variable intensities from -10 to 40 dBHL was obtained and analyzed. As a result, s-shaped psychometric function curve was presented with increasing correct rate depending on intensity and showed no statistical significant differences among each word and list. The congruous graph shapes among lists also indicated good homogeneity and the list 1,2,3,4's average slopes were 4.48, 3.86, 4.65, 4.50. It was verified that the homogeneity was suitable because the analysis of variance showed no statistical significance among lists (p>0.05). However, KS-MWL-P's order of slope according to the order of the number of items, $1{\sim}10$, $1{\sim}20$, $1{\sim}25$ showed no difference with the p-value of 0.93, 0.59, 0.91, 0.70 for the lists 1,2,3, and 4, respectively. Although KS-MWL-P was assumed that the lower-numbered items were easy for testing younger ages, this study's results could not agree with the author's conclusion. Considering this matter, rearranging of the number of items should be performed according to the analysis of slope suggested by this study for testing younger children with easier items. Other than this, in conclusion, KS-MWL-P was proved to be useful for clinical and rehabilitative evaluating and training tools for preschoolers.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Korean Journal of Biological Psychiatry
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• v.14 no.3
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• pp.184-193
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• 2007

Objectives:There is increasing evidence that the cerebellum plays an important role in cognition and psychiatric symptoms as well as motor coordination. The concept of cognitive dysmetria has been making cerebellar function in schizophrenia the focus of current studies. In other words, disruption in the corticocerebellum-thalamic -cortical circuit could lead to disordered cognition and clinical symptoms of schizophrenia. The purposes of this study were to determine cerebellar dysfunction in male schizophrenic patients semiquantitatively with ICARS and to investigate the clinical and cognitive correlates of ICARS in patients. Methods:We compared the scores of cerebellar neurologic sign using ICARS in 47 male patients with a DSM-IV-TR diagnosis of schizophrenia with 30 gender and age-matched healthy control subjects. The semiquantitative 100-point ICARS consists of 19 items divided into 4 unequally weighted subscores:posture and gait disturbances, kinetic functions, speech disorders and oculomotor disorders. All subjects were also assessed with cognitive function test. Cognitive functions were evaluated by Korean-Mini Mental Status Examination (K-MMSE), Verbal fluency test, and Clock drawing test. The patients were administered Korea version of Positive and Negative Symptom Scale(K-PANSS) to assess the symptom severity. Results:Schizophrenic patients had significantly higher scores on the ICARS than control subjects with posture and gait disturbances, kinetic functions, and oculomotor disorders. They also showed more significant impairments in cognitive function tests than control subjects. There was a significant correlation between ICARS and negative symptoms of patients. In cognitive function test, Clock drawing test was significantly associated with negative symptoms. In addition, Clock drawing test was negatively correlated with the total score of ICARS. Conclusion:In this study, we confirmed that schizophrenic patients have significant impairments in cognitive and cerebellar function, and that those were related with negative symptoms of schizophrenic patients. These results support a role of the cerebellum in schizophrenia. It is meaningful that we used a structured, and reliable procedure for rating neurological soft signs, ICARS. We hope that future prospective studies using a similar design help that rate of neurological sign should have been visible with the progression of illness.