Variations of pH, EC and anion of stemflow and throughfall in Quercus mongolica and Q. variabilis (신갈나무와 굴참나무 수간류, 임내우의 pH, 전기전도도 및 음이온 변화)
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- Journal of Forest and Environmental Science
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- v.16 no.1
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- pp.82-92
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- 2000
The pH, EC and anion of stemflow in Quercus mongolica and Q. variabilis were surveyed and analyzed in order to examine the relationship between watershed conservation function and flood control function of forest in quality and quantity in the Experiment Forests. College of Forest Sciences, Kangwon National University. The results were as follows: 1. pH values of rainfall ranged from 4.47 to 6.55(average: 5.39), and pH values of throughfall ranged from 4.07 to 6.25(average 5.45) for Q. mongolica and from 4.34 to 6.57(average : 5.62) for Q. variabilis, and thus pH values were not different between these two species. Also, pH values of stemflow from Q. mongolica ranged from 4.08 to 6.13(average 5.17) and those of stemflow from Q. variabilis ranged from 3.62 to 6.11(average : 4.68), and pH values of rainfall gave little influence on pH values of stemflow. But, pH values of stemflow in Q. mongolica and Q. variabilis appeard significantly lower in spring and than those in summer and autumn. 2. EC of rainfall was
Objectives. This study was conducted to evaluate the association between upper extremity musculoskeletal symptoms and Rapid Upper Limb Assessment(RULA) in vehicle assembly line workers. The goal of this study is to show the feasibility of RULA as a checklist for work related musculoskeletal symptoms (WMSDs) in Korean workers. Methods. The total number of 199 people from the department of assembly and 115 people from the department of Quality Control(QC) in automotive plant were subjects for this cross sectional study. A standard symptom questionnaire survey has been used for the individual characteristics, work history, musculosketal symptoms and non-occupational covariates. The data were obtained by applying one-on-one interview for the all subjects. RULA has been applied for ergonomic work posture analysis and the primary ergonomic risk sure was computed by RULA method. Association between upper extremity musculoskeletal symptoms and RULA were assessed by multiple logistic regression analysis. Results. A total of 314 workers was examined. The prevalence of musculoskeletal symptoms by NIOSH case definition was 62.4%. The distribution of musculoskeletal symptoms by the part of the body turned out to be following; back:41.4%, neck: 32.8%, shoulder: 26.4%, arm: 10.5% and hand:29.3%. The relationship of the individual RULA scores were statistically significant for the prevalence of musculoskeletal symptoms. As the result of the multiple logistic regressioin analysis, grand final score (OR=2.250 95% CI: 1.402-3.612) was associated with musculoskeletal symptoms in any part of the body.; upper arm score(OR=1.786 95% CI: 1.036-3.079) and posture score A(OR=1.634 95% CI: 1.016-2.626) in neck; muscel use score(OR=3.076 95% CI:1.782-5.310) and posture score A(OR=1.798 95% CI: 1.072-3.017) in shoulder; upper arm score(OR=1.715 95% CI: 1.083-2.715) and muscel use score(OR=2.057 95% CI:1.303-3.248) in neck & shoulder; muscle use score(OR=10.662 95% CI: 3.180-35.742) in arm; writst/wist score(OR=2.068 95% CI: 1.130-3.786) and muscle use score(OR=2.215 95% CI: 1.284-3.819) in hand & wrist.; muscle use score of trunk (OR=2.601 95% CI: 1.147-5.901) in back. Conclusions. Musculoskeletal symptoms of the extremities were strongly associated with individual RULA body score. These results show that RULA can be used as a useful assessment tool for the evaluation of musculoskeletal loading which is known to contribute to work-related musculoskeletal disorders. RULA also can be used as a screening tool or incorporated into a wider ergonomic assessment of epidemiological, physical, mental, environmental and organizational factors. As shown in this study, complement of the analysis system for the other risk factors and characterizing between the upper limb and back part will be needed for future work.
Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors,
KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.
This study attempts to examine the influence that negative WOM (NWOM) has in an online context. It specifically focuses on the impact of the service failure description and the perceived intention of the communication provider on consumer evaluations of firm competence, attitude toward the firm, positive word of mouth and behavioral intentions. Studies of communication persuasiveness focus on "who says what; to whom; in which channel; with what effect (Chiu 2007)." In this research study, we examine electronic web posting, particularly focusing on two aspects of "what": the level of service failure communicated and perceived intention of the individual posting. It stands to reason electronic NWOM that appears to be trying to damage a product’s or firm's reputation will be viewed as more biased and will thus be considered as less credible. According to attribution theory, people search for the causes of events especially those that are negative and unexpected (Weiner 2006). Hennig-Thurau and Walsh (2003) state "since the reader has only limited knowledge and trust of the author of an online articulation the quality of the contribution could be expected to serve as a potent moderator of the articulation-behavior relationship. We therefore posit the following hypotheses: H1. Subjects exposed to electronic NWOM describing a high level of service failure will provide lower scores on measures of (a) firm competence, (b) attitude toward the firm, (c) positive word of mouth, and (d) behavioral intention than will subjects exposed to electronic NWOM describing a low level of service failure. H2. Subjects exposed to electronic NWOM with a warning intent will provide lower scores on measures of (a) firm competence, (b) attitude toward the firm, (c) positive word of mouth, and (d) behavioral intention than will subjects exposed to electronic NWOM with a vengeful intent. H3. Level of service failure in electronic NWOM will interact with the perceived intention of the electronic NWOM, such that there will be a decrease in mean response on measures of (a) firm competence, (b) attitude toward the firm, (c) positive word of mouth, and (d) behavioral intention from electronic NWOM with a warning intent to a vengeful intent. The main study involved a2 (service failure severity) x2 (NWOM with warning versus vengeful intent) factorial experiment. Stimuli were presented to subjects online using a mock online web posting. The scenario described a service failure associated with non-acceptance of a gift card in a brick-and-mortar retail establishment. A national sample was recruited through an online research firm. A total of 113 subjects participated in the study. A total of 104 surveys were analyzed. The scenario was perceived to be realistic with 92.3% giving the scenario a greater than average response. Manipulations were satisfactory. Measures were pre-tested and validated. Items were analyzed and found reliable and valid. MANOVA results found the multivariate interaction was not significant, allowing our interpretation to proceed to the main effects. Significant main effects were found for post intent and service failure severity. The post intent main effect was attributable to attitude toward the firm, positive word of mouth and behavioral intention. The service failure severity main effect was attributable to all four dependent variables: firm competence, attitude toward the firm, positive word of mouth and behavioral intention. Specifically, firm competence for electronic NWOM describing high severity of service failure was lower than electronic NWOM describing low severity of service failure. Attitude toward the firm for electronic NWOM describing high severity of service failure was lower than electronic NWOM describing low severity of service failure. Positive word of mouth for electronic NWOM describing high severity of service failure was lower than electronic NWOM describing low severity of service failure. Behavioral intention for electronic NWOM describing high severity of service failure was lower for electronic NWOM describing low severity of service failure. Therefore, H1a, H1b, H1c and H1d were all supported. In addition, attitude toward the firm for electronic NWOM with a warning intent was lower than electronic NWOM with a vengeful intent. Positive word of mouth for electronic NWOM with a warning intent was lower than electronic NWOM with a vengeful intent. Behavioral intention for electronic NWOM with a warning intent was lower than electronic NWOM with a vengeful intent. Thus, H2b, H2c and H2d were supported. However, H2a was not supported though results were in the hypothesized direction. Otherwise, there was no significant multivariate service failure severity by post intent interaction, nor was there a significant univariate service failure severity by post intent interaction for any of the three hypothesized variables. Thus, H3 was not supported for any of the four hypothesized variables. This study has research and managerial implications. The findings of this study support prior research that service failure severity impacts consumer perceptions, attitude, positive word of mouth and behavioral intentions (Weun et al. 2004). Of further relevance, this response is evidenced in the online context, suggesting the need for firms to engage in serious focused service recovery efforts. With respect to perceived intention of electronic NWOM, the findings support prior research suggesting reader's attributions of the intentions of a source influence the strength of its impact on perceptions, attitude, positive word of mouth and behavioral intentions. The implication for managers suggests while consumers do find online communications to be credible and influential, not all communications are weighted the same. A benefit of electronic WOM, even when it may be potentially damaging, is it can be monitored for potential problems and additionally offers the possibility of redress.
To prepare for the complicated international relationship regarding Korean Peninsula after reunification, this thesis started off with the awareness that Unified Korea should build its international posture and national security at an early stage by determining its appropriate military strength for independent defense and military strategies that Unified Korea should aim. The main theme of this thesis is 'The research on appropriate military strength of the Unified Korean military'. To derive appropriate military strength of Unified Korea, this research focuses on conflict scenario and relative balance strategy based on potential threats posed by neighboring countries, and this is the part that differentiates this research from other researches. First of all, the main objective of the research is to decide appropriate military strength for Unified Korea to secure defense sufficiency. For this, this research will decide efficient military strategy that Unified Korea should aim. Than by presuming the most possible military conflict scenario, this research will judge the most appropriate military strength for Unified Korea to overcome the dispute. Second, after deciding appropriate military strength, this research will suggest how to operate presumed military strength in each armed force. The result of this thesis is as in the following. First, Unified Korea should aim 'relative balance strategy'. 'Relative balance strategy' is a military strategy which Unified Korea can independently secure defense sufficiency by maintaining relative balance when conflicts occur between neighboring countries. This strategy deters conflicts in advance by relative balance of power in certain time and place. Even if conflict occurs inevitably, this strategy secures initiative. Second, when analyzing neighboring countries interest and strategic environment after unification, the possibility of all-out war will be low in the Korean Peninsula because no other nation wants the Korean Peninsula to be subordinated to one single country. Therefore appropriate military strength of the Unified Korean military would be enough when Unified Korea can achieve relative balance in regional war or limited war. Third, Northeast Asia is a region where economic power and military strength is concentrated. Despite increasing mutual cooperation in the region, conflicts and competition to expand each countries influence is inherent. Japan is constantly enhancing their military strength as they aim for normal statehood. China is modernizing their military strength as they aspire to become global central nation. Russia is also enhancing their military strength in order to hold on to their past glory of Soviet Union as a world power. As a result, both in quality and quantity, the gap between military strength of Unified Korea and each neighboring countries is enlarged at an alarming rate. Especially in the field of air-sea power, arms race is occurring between each nation. Therefore Unified Korea should be equipped with appropriate military strength in order to achieve relative balance with each threats posed by neighboring countries. Fourth, the most possible conflicts between Unified Korea and neighboring countries could be summarized into four, which are Dokdo territorial dispute with Japan, Leodo jurisdictional dispute with China, territorial dispute concerning northern part of the Korea Peninsula with China and disputes regarding marine resources and sea routes with Russia. Based on those conflict scenarios, appropriate military strength for Unified Korea is as in the following. When conflict occurs with Japan regarding Dokdo, Japan is expected to put JMSDF Escort Flotilla 3, one out of four of its Japan Maritime Self-Defense Force Escort Fleet, which is based in Maizuru and JMSDF Maizuru District. To counterbalance this military strength, Unified Korea needs one task fleet, comprised with three task flotilla. In case of jurisdictional conflict with China concerning Leodo, China is expected to dispatch its North Sea fleet, one out of three of its naval fleet, which is in charge of the Yellow Sea. To response to this military action, Unified Korea needs one task fleet, comprised with three task flotilla. In case of territorial dispute concerning northern part of the Korean Peninsula with China, it is estimated that out of seven Military Region troops, China will dispatch two Military Region troops, including three Army Groups from Shenyang Military Region, where it faces boarder with the Korean Peninsula. To handle with this military strength, Unified Korea needs six corps size ground force strength, including three corps of ground forces, two operational reserve corps(maneuver corps), and one strategic reserve corps(maneuver corps). When conflict occurs with Russia regarding marine resources and sea routes, Russia is expected to send a warfare group of a size that includes two destroyers, which is part of the Pacific Fleet. In order to balance this strength, Unified Korea naval power requires one warfare group including two destroyers. Fifth, management direction for the Unified Korean military is as in the following. Regarding the ground force management, it would be most efficient to deploy troops in the border area with china for regional and counter-amphibious defense. For the defense except the border line with china, the most efficient form of force management would be maintaining strategic reserve corps. The naval force should achieve relative balance with neighboring countries when there is maritime dispute and build 'task fleet' which can independently handle long-range maritime mission. Of the three 'task fleet', one task fleet should be deployed at Jeju base to prepare for Dokdo territorial dispute and Leodo jurisdictional dispute. Also in case of regional conflict with china, one task fleet should be positioned at Yellow Sea and for regional conflict with Japan and Russia, one task fleet should be deployed at East Sea. Realistically, Unified Korea cannot possess an air force equal to neither Japan nor China in quantity. Therefore, although Unified Korea's air force might be inferior in quantity, they should possess the systematic level which Japan or China has. For this Unified Korea should build air base in island areas like Jeju Island or Ullenong Island to increase combat radius. Also to block off infiltration of enemy attack plane, air force needs to build and manage air bases near coastal areas. For landing operation forces, Marine Corps should be managed in the size of two divisions. For island defense force, which is in charge of Jeju Island, Ulleung Island, Dokdo Island and five northwestern boarder island defenses, it should be in the size of one brigade. Also for standing international peace keeping operation, it requires one brigade. Therefore Marine Corps should be organized into three divisions. The result of the research yields a few policy implications when building appropriate military strength for Unified Korea. First, Unified Korea requires lower number of ground troops compared to that of current ROK(Republic of Korea) force. Second, air-sea forces should be drastically reinforced. Third, appropriate military strength of the Unified Korean military should be based on current ROK military system. Forth, building appropriate military strength for Unified Korea should start from today, not after reunification. Because of this, South Korea should build a military power that can simultaneously prepare for current North Korea's provocations and future threats from neighboring countries after reunification. The core of this research is to decide appropriate military strength for Unified Korea to realize relative balance that will ensure defense sufficiency from neighboring countries threats. In other words, this research should precisely be aware of threats posed by neighboring countries and decide minimum level of military strength that could realize relative balance in conflict situation. Moreover this research will show the path for building appropriate military strength in each armed force.
The
As the world becomes more globalized, business competition becomes fiercer, while consumers' needs for less expensive quality products are on the increase. Business operations make an effort to secure a competitive edge in costs and services, and the logistics industry, that is, the industry operating the storing and transporting of goods, once thought to be an expense, begins to be considered as the third cash cow, a source of new income. Logistics centers are central to storage, loading and unloading of deliveries, packaging operations, and dispensing goods' information. As hubs for various deliveries, they also serve as a core infrastructure to smoothly coordinate manufacturing and selling, using varied information and operation systems. Logistics centers are increasingly on the rise as centers of business supply activities, growing beyond their previous role of primarily storing goods. They are no longer just facilities; they have become logistics strongholds that encompass various features from demand forecast to the regulation of supply, manufacturing, and sales by realizing SCM, taking into account marketability and the operation of service and products. However, despite these changes in logistics operations, some centers have been unable to shed their past roles as warehouses. For the continuous development of logistics centers, various measures would be needed, including a revision of current supporting policies, formulating effective management plans, and establishing systematic standards for founding, managing, and controlling logistics centers. To this end, the research explored previous studies on the use and effectiveness of logistics centers. From a theoretical perspective, an evaluation of the overall introduction, purposes, and transitions in the use of logistics centers found issues to ponder and suggested measures to promote and further advance logistics centers. First, a fact-finding survey to establish demand forecast and standardization is needed. As logistics newspapers predicted that after 2012 supply would exceed demand, causing rents to fall, the business environment for logistics centers has faltered. However, since there is a shortage of fact-finding surveys regarding actual demand for domestic logistic centers, it is hard to predict what the future holds for this industry. Accordingly, the first priority should be to get to the essence of the current market situation by conducting accurate domestic and international fact-finding surveys. Based on those, management and evaluation indicators should be developed to build the foundation for the consistent advancement of logistics centers. Second, many policies for logistics centers should be revised or developed. Above all, a guideline for fair trade between a shipper and a commercial logistics center should be enacted. Since there are no standards for fair trade between them, rampant unfair trades according to market practices have brought chaos to market orders, and now the logistics industry is confronting its own difficulties. Therefore, unfair trade cases that currently plague logistics centers should be gathered by the industry and fair trade guidelines should be established and implemented. In addition, restrictive employment regulations for foreign workers should be eased, and logistics centers should be charged industry rates for the use of electricity. Third, various measures should be taken to improve the management environment. First, we need to find out how to activate value-added logistics. Because the traditional purpose of logistics centers was storage and loading/unloading of goods, their profitability had a limit, and the need arose to find a new angle to create a value added service. Logistic centers have been perceived as support for a company's storage, manufacturing, and sales needs, not as creators of profits. The center's role in the company's economics has been lowering costs. However, as the logistics' management environment spiraled, along with its storage purpose, developing a new feature of profit creation should be a desirable goal, and to achieve that, value added logistics should be promoted. Logistics centers can also be improved through cost estimation. In the meantime, they have achieved some strides in facility development but have still fallen behind in others, particularly in management functioning. Lax management has been rampant because the industry has not developed a concept of cost estimation. The centers have since made an effort toward unification, standardization, and informatization while realizing cost reductions by establishing systems for effective management, but it has been hard to produce profits. Thus, there is an urgent need to estimate costs by determining a basic cost range for each division of work at logistics centers. This undertaking can be the first step to improving the ineffective aspects of how they operate. Ongoing research and constant efforts have been made to improve the level of effectiveness in the manufacturing industry, but studies on resource management in logistics centers are hardly enough. Thus, a plan to calculate the optimal level of resources necessary to operate a logistics center should be developed and implemented in management behavior, for example, by standardizing the hours of operation. If logistics centers, shippers, related trade groups, academic figures, and other experts could launch a committee to work with the government and maintain an ongoing relationship, the constraint and cooperation among members would help lead to coherent development plans for logistics centers. If the government continues its efforts to provide financial support, nurture professional workers, and maintain safety management, we can anticipate the continuous advancement of logistics centers.
Festivals are an indispensable feature of cultural tourism(Formica & Uysal, 1998). Cultural tourism festivals are increasingly being used as instruments promoting tourism and boosting the regional economy. So much research related to festivals is undertaken from a variety of perspectives. Plans to revisit a particular festival have been viewed as an important research topic both in academia and the tourism industry. Therefore festivals have frequently been leveled as cultural events. Cultural tourism festivals have become a crucial component in constituting the attractiveness of tourism destinations(Prentice, 2001). As a result, a considerable number of tourist studies have been carried out in diverse cultural tourism festivals(Backman et al., 1995; Crompton & Mckay, 1997; Park, 1998; Clawson & Knetch, 1996). Much of previous literature empirically shows the close linkage between tourist satisfaction and behavioral intention in festivals. The main objective of this study is to investigate the effects of evaluation attributes of cultural tourism festivals on satisfaction and behavioral intention. accomplish the research objective, to find out evaluation items of cultural tourism festivals through the literature study an empirical study. Using a varimax rotation with Kaiser normalization, the research obtained four factors in the 18 evaluation attributes of cultural tourism festivals. Some empirical studies have examined the relationship between behavioral intention and actual behavior. To understand between tourist satisfaction and behavioral intention, this study suggests five hypotheses and hypothesized model. In this study, the analysis is based on primary data collected from visitors who participated in '2006 Gwangju Kimchi Festival'. In total, 700 self-administered questionnaires were distributed and 561 usable questionnaires were obtained. Respondents were presented with the 18 satisfactions item on a scale from 1(strongly disagree) to 7(strongly agree). Dimensionality and stability of the scale were evaluated by a factor analysis with varimax rotation. Four factors emerged with eigenvalues greater than 1, which explained 66.40% of the total variance and Cronbach' alpha raging from 0.876 to 0.774. And four factors named: advertisement and guides, programs, food and souvenirs, and convenient facilities. To test and estimate the hypothesized model, a two-step approach with an initial measurement model and a subsequent structural model for Structural Equation Modeling was used. The AMOS 4.0 analysis package was used to conduct the analysis. In estimating the model, the maximum likelihood procedure was used.In this study Chi-square test is used, which is the most common model goodness-of-fit test. In addition, considering the literature about the Structural Equation Modeling, this study used, besides Chi-square test, more model fit indexes to determine the tangibility of the suggested model: goodness-of-fit index(GFI) and root mean square error of approximation(RMSEA) as absolute fit indexes; normed-fit index(NFI) and non-normed-fit index(NNFI) as incremental fit indexes. The results of T-test and ANOVAs revealed significant differences(0.05 level), therefore H1(Tourist Satisfaction level should be different from Demographic traits) are supported. According to the multiple Regressions analysis and AMOS, H2(Tourist Satisfaction positively influences on revisit intention), H3(Tourist Satisfaction positively influences on word of mouth), H4(Evaluation Attributes of cultural tourism festivals influences on Tourist Satisfaction), and H5(Tourist Satisfaction positively influences on Behavioral Intention) are also supported. As the conclusion of this study are as following: First, there were differences in satisfaction levels in accordance with the demographic information of visitors. Not all visitors had the same degree of satisfaction with their cultural tourism festival experience. Therefore it is necessary to understand the satisfaction of tourists if the experiences that are provided are to meet their expectations. So, in making festival plans, the organizer should consider the demographic variables in explaining and segmenting visitors to cultural tourism festival. Second, satisfaction with attributes of evaluation cultural tourism festivals had a significant direct impact on visitors' intention to revisit such festivals and the word of mouth publicity they shared. The results indicated that visitor satisfaction is a significant antecedent of their intention to revisit such festivals. Festival organizers should strive to forge long-term relationships with the visitors. In addition, it is also necessary to understand how the intention to revisit a festival changes over time and identify the critical satisfaction factors. Third, it is confirmed that behavioral intention was enhanced by satisfaction. The strong link between satisfaction and behavioral intentions of visitors areensured by high quality advertisement and guides, programs, food and souvenirs, and convenient facilities. Thus, examining revisit intention from a time viewpoint may be of a great significance for both practical and theoretical reasons. Additionally, festival organizers should give special attention to visitor satisfaction, as satisfied visitors are more likely to return sooner. The findings of this research have several practical implications for the festivals managers. The promotion of cultural festivals should be based on the understanding of tourist satisfaction for the long- term success of tourism. And this study can help managers carry out this task in a more informed and strategic manner by examining the effects of demographic traits on the level of tourist satisfaction and the behavioral intention. In other words, differentiated marketing strategies should be stressed and executed by relevant parties. The limitations of this study are as follows; the results of this study cannot be generalized to other cultural tourism festivals because we have not explored the many different kinds of festivals. A future study should be a comparative analysis of other festivals of different visitor segments. Also, further efforts should be directed toward developing more comprehensive temporal models that can explain behavioral intentions of tourists.
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.