• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.472-489
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• 2023

This study was conducted to derive the optimal estimation equations for deriving the green and dry weights of Larix kaempferi (Japanese larch) and Pinus rigida (Rigida pine), which are major coniferous tree species in South Korea. The equations were then used to develop weight tables. Table development began with the sampling of 150 L. kaempferi and 90 P. rigida trees distributed throughout the national scale, after which green weights were measured on-site. Samples from each stand were then collected, and their dry weights were measured in a laboratory. The equation used to calculate green and dry weights was divided into a one-variable formula that uses only the diameter at breast height (DBH) and a two-variable equation that employs DBH and height. The equations used to estimate the green and dry weights of logs were divided into one- and two-variable equations using DBH. Statistical data, such as the fitness index (FI), root mean square error, standard error of estimation, and residual diagram, were used to verify the suitability of the estimation equations. Applicability was examined by calculating weights using the derived optimal equations. The equation W = bD+cD² was used in measurements involving only DBH, whereas the equation W = aD^bH^c was employed in cases involving both diameter and height at breast height. The FI of W = bD+cD² was 0.91, while that of W = aD^bH^c was 0.95, both of which are high values. With these estimation formulas, weight tables for the green and dry weights of L. kaempferi and P. rigida were prepared and compared with weight tables created 20 years ago. The green and dry weight tables of both species were larger.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.4
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• pp.158-164
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• 2006

Yongdam Lake is the fifth largest artificial lake in Korea newly formed by the first impounding the Yongdam Multi-purpose Dam on December, 2002. Yongdam Lake, with her total water storage of 820 million M/T, is located at the roof-top region of the streams flowing into the just-constructed new Saemankeum Lake. Seasonal succession of phytoplakton in Yongdam Lake might affect cyanobacterial blooms in Saemankeum Lake by inoculating seasonal dominants. During 2002-2003 when the first impounding after the construction of Yongdam Multi-purpose Dam was still undergoing, summer cyanobacterial blooms by Anabaena, Microcystis, and Aphanizomenon were observed. Among these three, filamentous Anabaena is well known to have its species with $N_2-fixing$ ability and special cells such as heterocysts and akinetes as well as the vegetative cells. We established a clonal culture of Anabaena spiroides v. crasse (KNU-YD0310) from the live water samples collected at the bloom site of Yongdam Lake. The N- and P-nutrient requirement of the KNU-YD0310 was explored by the experimental cultivation of the laboratory strain. Ratio of heterocysts to vegetative cells increased as N-deficiency extended with its maximum at $N_2-fixing$ condition. The strain KNU-YD0310 exhibited considerable growth under N-limiting conditions while its growth was proportional to the initial phosphate-P concentration under P-deficient conditions. Under P-limiting conditions akinete density increased, which could be interpreted as an adaptation strategy to survive severe environment by transforming into resting stage. The above eco-physiological characteristics of Anabaena spiroides v. crassa might be useful as an ecological criterion in controlling cyanobacterial blooms at Shaemankeum Lake in near future.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.110-126
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• 2024

This study conducted a classification of small-scale biological habitats created in Seoul to analyze and synthesize location characteristics, habitat structure, biological habitat functions, and threat factors of representative sites, as well as derive creation and management problems according to the ecological characteristics. The aim was to suggest improvement measures and management items. Data collected through a field survey was used to categorize 39 locations, and 8 representative sites were selected by dividing them into location, water system, and size as classification criteria for typification. Due to the characteristics of each type, the site was created in an area where amphibian movement was disadvantageous due to low or disconnected connectivity with the hinterland forest, and the water supply was unstable in securing a constant flow and maintaining a constant water depth. The habitat structure has a small area, an artificial habitat structure that is unfavorable for amphibians, having the possibility of sediment inflow, and damage to the revetment area. The biological habitat function is a lack of wetland plants and the distribution of naturalized grasses, and threats include the establishment of hiking trails and decks in the surrounding area. Artificial disturbances occur adjacent to facilities. When creating habitats according to the characteristics of each type, it was necessary to review the possibility of an artificial water supply and introduce a water system with a continuous flow in order to connect the hinterland forest for amphibian movement and locate it in a place where water supply is possible. The habitat structure should be as large as possible, or several small-scale habitats should be connected to create a natural waterfront structure. In addition, additional wetland plants should be introduced to provide shelter for amphibians, and facilities such as walking paths should be installed in areas other than migration routes to prevent artificial disturbances. After construction, the management plan is to maintain various water depths for amphibians to inhabit and spawn, stabilize slopes due to sediment inflow, repair damage to revetments, and remove organic matter deposits to secure natural grasses and open water. Artificial management should be minimized. This study proposed improvement measures to improve the function of biological habitats through the analysis of problems with previously applied techniques, and based on this, in the future, small-scale biological habitat spaces suitable for the urban environment can be created for local governments that want to create small-scale biological habitat spaces, including Seoul City. It is significant in that it can provide management plans.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

• Korean Journal of Ecology and Environment
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• v.57 no.1
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• pp.39-50
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• 2024

In ecosystems within limited resources, interspecific competition is inevitable, often leading to the competitive exclusion of inferior species. This study aims to provide foundational information for the conservation and restoration management of Microphysogobio rapidus by evaluating species' ecological response to biological factors within its habitat. To understand this relationship, we collected food web organisms from site where M. rapidus coexist with Microphysogobio yaluensis, a specie ecologically similar to M. rapidus, and evaluated the trophic levels (TL), isotopic niche space (INS), and the overlap of INS among fishes within the habitat using stable isotope analysis. Our analysis revealed that the M. rapidus exhibited a higher TL than M. yaluensis, with TL of 2.6 and 2.4, respectively. M. yaluensis exhibited a broad INS, significantly influencing the feeding characteristics of most fish. Conversely, M. rapidus showed a narrow INS and asymmetric feeding relationships with other species, in habitats with high competition levels. This feeding characteristics of M. rapidus indicate that the increase in competitors sharing the similar resources lead to a decrease in available resources and, consequently, is expected to result in a decrease in their density.

• Industry Promotion Research
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• v.9 no.3
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• pp.57-75
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• 2024

This study examined how ESG activities of convenience stores, affect consumers' store loyalty. Using 300 valid samples of convenience store users collected through an online specialized agency (Company M), this study empirically analyzed the effects of environmental (E), social (S), and governance (G) activities among ESG on trust and store loyalty, and the mediating effects of trust and the moderating effects of eco-friendly values, social media activity, and consumer-company identification. The results of the analysis showed that, first, governance activities had a positive effect on trust, and environmental activities and trust had a positive effect on store loyalty, but social activities had no effect Second, trust had a moderating effect only on the relationship between governance activities and store loyalty, and third, in the relationship between ESG activities and trust, eco-friendly values and social media activity had moderating effects on environmental, social, and governance activities, and consumer-company identification had moderating effects on environmental and governance activities, but not on social activities. Therefore, convenience store brands should further strengthen their environmental and social activities to build consumer trust, especially environmental activities, which only directly affect store loyalty, so they should be more cautious and proactive. In addition, intensive marketing activities are needed to build trust among consumers who have high eco-friendly values, social media activity, and consumer-company identification. Therefore, this study confirms the critical view of consumers despite the social contribution activities of convenience store brands, and suggests that in order to improve them, it is necessary to strengthen social activity efforts, actively participate in ESG activities of on-site franchisees who are customer contact points, and educate employees.

• Asia Marketing Journal
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• v.14 no.2
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• pp.65-96
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• 2012

Brand has received much attention from considerable marketing research. When consumers consume product or services, they are exposed to a lot of brand related stimuli. These contain brand personality, brand experience, brand identity, brand communications and so on. A special kind of new crisis occasionally confronting companies' brand management today is the brand related rumor. An important influence on consumers' purchase decision making is the word-of-mouth spread by other consumers and most decisions are influenced by other's recommendations. In light of this influence, firms have reasonable reason to study and understand consumer-to-consumer communication such as brand rumor. The importance of brand rumor to marketers is increasing as the number of internet user and SNS(social network service) site grows. Due to the development of internet technology, people can spread rumors without the limitation of time, space and place. However relatively few studies have been published in marketing journals and little is known about brand rumors in the marketplace. The study of rumor has a long history in all major social science. But very few studies have dealt with the antecedents and consequences of any kind of brand rumor. Rumor has been generally described as a story or statement in general circulation without proper confirmation or certainty as to fact. And it also can be defined as an unconfirmed proposition, passed along from people to people. Rosnow(1991) claimed that rumors were transmitted because people needed to explain ambiguous and uncertain events and talking about them reduced associated anxiety. Especially negative rumors are believed to have the potential to devastate a company's reputation and relations with customers. From the perspective of marketer, negative rumors are considered harmful and extremely difficult to control in general. It is becoming a threat to a company's sustainability and sometimes leads to negative brand image and loss of customers. Thus there is a growing concern that these negative rumors can damage brands' reputations and lead them to financial disaster too. In this study we aimed to distinguish antecedents of brand rumor transmission and investigate the effects of brand rumor characteristics on rumor spread intention. We also found key components in personal acceptance of brand rumor. In contextualist perspective, we tried to unify the traditional psychological and sociological views. In this unified research approach we defined brand rumor's characteristics based on five major variables that had been found to influence the process of rumor spread intention. The five factors of usefulness, source credibility, message credibility, worry, and vividness, encompass multi level elements of brand rumor. We also selected product involvement as a control variable. To perform the empirical research, imaginary Korean 'Kimch' brand and related contamination rumor was created and proposed. Questionnaires were collected from 178 Korean samples. Data were collected from college students who have been experienced the focal product. College students were regarded as good subjects because they have a tendency to express their opinions in detail. PLS(partial least square) method was adopted to analyze the relations between variables in the equation model. The most widely adopted causal modeling method is LISREL. However it is poorly suited to deal with relatively small data samples and can yield not proper solutions in some cases. PLS has been developed to avoid some of these limitations and provide more reliable results. To test the reliability using SPSS 16 s/w, Cronbach alpha was examined and all the values were appropriate showing alpha values between .802 and .953. Subsequently, confirmatory factor analysis was conducted successfully. And structural equation modeling has been used to analyze the research model using smartPLS(ver. 2.0) s/w. Overall, R² of adoption of rumor is .476 and R² of intention of rumor transmission is .218. The overall model showed a satisfactory fit. The empirical results can be summarized as follows. According to the results, the variables of brand rumor characteristic such as source credibility, message credibility, worry, and vividness affect argument strength of rumor. And argument strength of rumor also affects rumor intention. On the other hand, the relationship between perceived usefulness and argument strength of rumor is not significant. The moderating effect of product involvement on the relations between argument strength of rumor and rumor W.O.M intention is not supported neither. Consequently this study suggests some managerial and academic implications. We consider some implications for corporate crisis management planning, PR and brand management. This results show marketers that rumor is a critical factor for managing strong brand assets. Also for researchers, brand rumor should become an important thesis of their interests to understand the relationship between consumer and brand. Recently many brand managers and marketers have focused on the short-term view. They just focused on strengthen the positive brand image. According to this study we suggested that effective brand management requires managing negative brand rumors with a long-term view of marketing decisions.

• Economic and Environmental Geology
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• v.48 no.2
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• pp.147-160
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• 2015

In 2014, on 31 August and 1 September, the emissions of $CH_4$, $CO_2$, and $O_2$ gases were measured six times using the closed chamber method from exposed tidal flat sediments in the same position relative to the low point of the tidal cycle in the Eoeun-ri, Taean-gun, on the Mid-western Coast of Korea. The concentrations of $CH_4$ in the air sample collected in the chamber were measured using gas chromatography with an EG analyzer, model GS-23, within 6 hours of collection, and the other gases were measured in real time using a multi-gas monitor. The gas emission fluxes (source (+), and sink (-)) were calculated from a simple linear regression analysis of the changes in the concentrations over time. In order to see the surrounding parameters (water content, temperature, total organic carbon, average mean size of sediments, and the temperature of the inner chamber) were measured at the study site. On the first day, across three measurements during 5 hours 20 minutes, the observed $CO_2$ flux absorption was -137.00 to $-81.73mg/m^2/hr$, and the $O_2$ absorption, measured simultaneously, was -0.03 to $0.00mg/m^2/hr$. On the second day using an identical number of measurements, the $CO_2$ absorption was -20.43 to $-2.11mg/m^2/hr$, and the $O_2$ absorption -0.18 to $-0.14mg/m^2/hr$. The $CH_4$ absorption before low tide was $-0.02mg/m^2/hr$ (first day, Pearson correlation coefficient using the SPSS statistical analysis is -0.555(n=5, p=0.332, pronounced negative linear relationship)), and $-0.15mg/m^2/hr$ (second day, -0.915(n=5, p=0.030, strong negative linear relationship)) on both measurement days. The emitted flux after low tide on both measurement days reached a minimum of $+0.00mg/m^2/hr$ (+0.713(n=5, p=0.176, linear relationship which can be almost ignored)), and a maximum of $+0.03mg/m^2/hr$ (+0.194(n=5, p=0.754, weak positive linear relationship)) after low tide. However, the absolute values of the $CH_4$ fluxes were analyzed at different times. These results suggest that rate for $CH_4$ fluxes, even the same time and area, were influenced by changes in the tidal cycle characteristics of surface sediments for understanding their correlation with these gas emissions, and surrounding parameters such as physiochemical sediments conditions.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.