• Journal of Korean Academy of Nursing
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• v.11 no.2
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• pp.55-68
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• 1981

The prime object of the study is to evaluate how much all the students of the Nursing Schools throughout the nation are in comprehension toward the application of nursing process to clinical experience as means of systematic solution of nursing problems. An effort has been made to find out the actual state whether they are in practice of clinical experience in accordance with application of nursing process, over the period of four weeks managing from December 1st to 28th, 1980 and centering on 36 nursing schools, and meanwhile and evaluation, employing the assessment tool used by Bertuccietal, has been made on the nursing process notes recorded by 200 senions out of 21 nursing schools where application of nursing process to clinical experience being in practice. The assessment tool is composed of 5 different criteria in view of patient nursing and authors made an attempt to find out the result of clinical experience on application students in accordance with 5 different scoring criteria and further evaluating all the findings thereof. The findings were disposed of accordance with practice duration and criteria of the specific sudents subject to this finding as to verify the scoring difference in significance and of which the results are as follows: 1) as of now, in 21 (58.2%) out of 36 nursing Schools nursing process in being appliced in clinical experience. 2) Schools that started the application of nursing process to clinical experience amount to - for more than 4 yrs -6 (28.6％) - for 2 to 3 yrs-11s(52.4％) - for 1 yr -4 (19.0％) 3) As for the response upon application of nursing process. To clinical etperience, the largest voice (61.9%) heard was that it is rather difficult beyond the lecturing thereof, to practically apply it outs patients and the second voice (19.1%) turned out to be that it is hard to put in practice owing to uninformed nurses of the process serving in the clinical field. 4) The response. Of the processors assigned to instruction as to the most difficult problem in criteria of nursing process, the largest voice (38.2%) centered on the problem assessment while the second voice (17.7%) on the indirect nursing activity and the objective data respectively and considered to be the easiest was the indirect nursing activity (11.7%). 5) In order for a satisfactory. application of nursing process to clinical experience hence-forth, it has been pointed out that sufficient number of nurses should be supplemented in clinical field (44.1%) and at the same time supplementory education (35.3%) centered around professors be necessary. 6) Of the criteria that record result of nursing process, a significant difference in comprehension of subjective and objective data has been revealed according to the degree of the practice duration of application to clinical experience. For instance, while although poor it may seen, only 74.9% in subjective data and 71.1% in objective data represent the student group in practice for more than 4 years and only 56.3% in subjective data and 66.8% in objective data represent the student group in practice for 2 to 3 years but they still surpass in comprehension over the student group in practice for 1 year attaning only 19.6% in subjective data and 16.8% in objective data (P < 0.005). 7) As for problem assessment, the student group who started application of nursing process for 4 years stand for 37,7% the group for 2 to 3 years started for 25.3% and the group for 1 year started for 5.4%, revealing no significant difference according to duration (P < 0.5) and as poor as to indicate only 22.8% on an overage is in comprehension. 8) On direct and indirect nursing activity, the student group of for more than 4 years in appling nursing process (representing 49.5% in direct nursing activity, 21.4% in indirect nursing activity). Know more about it than the student group of for 2 to 3 years (representing 36.3% in direct nursing activity, 20.8% in indirect nursing activity) but revealed no significant difference. (P ＜ 0.5) 9) The student group applying nursing process for more than 4 years subjective data (74.9%) comprehend were more than objective data (71.1%) but shown no significant difference (P < 0.5). 10) However, the student group applying nursing process for 2 to 3 years comprehend objective data (66.8%) well ever subjective data (55.5%) indicating that 40.9% in average is in comprehension, thereby revealing a significant difference (P < 0.005). 11) On the other hand, the student group applying nursing process to clinical experience for 1 year had revealed themselves as poorly as to comprehend only 11.7% are an average of it, revealing no significant difference (P < 0.5). In consequence of the fore going, I the conductor of the present study, hereby suggest the following points: 1) Application of nursing process to clinical experience be practiced in all the Nursing Schools all over the nation at the earliest possible date in order that scientific nursing be prevailed (as of now only 58.0%), 2) In teaching nursing process, it is desirable to teach specific method of applying to practical clinical situations. 3) In order to meet the end of satisfactory application of nursing process to clinical experience, sufgecient nursing man power be sysplemented in clinical field and at the save time supplementary education by professors is necessary. 4) Sinces the students whose application duration of nursing process to clinical experience is longer comprehend more about it, it is reguired that the schools not yet in practice of the application be promptlyurged to follow. 5) Of the criteria recording nursing process, since it is comparatively hard to comprehend“assessment”and“Direct and indirect nursing activity”, a concentrated instruction is desirable. 6) The students whose duration of application of nursing process to clinical experience falls short of 1 years be put in a concentrated guidance program on individual criterion.

• Journal of Distribution Research
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• v.16 no.4
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• pp.1-27
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• 2011

Introduction: Sales of private labels(PU have been growing m recent years. Globally, PLs have already achieved 20% share, although between 25 and 50% share in most of the European markets(AC. Nielson, 2005). These products are aimed to have comparable quality and prices as national brand(NB) products and have been continuously eroding manufacturer's national brand market share. Stores have also started introducing premium PLs that are of higher-quality and more reasonably priced compared to NBs. Worldwide, many retailers already have a multiple-tier private label architecture. Consumers as a consequence are now able to have a more diverse brand choice in store than ever before. Since premium PLs are priced higher than regular PLs and even, in some cases, above NBs, stores can expect to generate higher profits. Brand extensions and private label have been extensively studied in the marketing field. However, less attention has been paid to the private label extension. Therefore, this research focuses on private label extension using the Multi-Attribute Attitude Model(Fishbein and Ajzen, 1975). Especially there are few studies that consider the hierarchical effect of the PL's two parent brands: store brand and the original PL. We assume that the attitude toward each of the two parent brands affects the attitude towards the extended PL. The influence from each parent brand toward extended PL will vary according to the perceived fit between each parent brand and the extended PL. This research focuses on how these two parent brands act as reference points to one another in the consumers' choice consideration. Specifically we seek to understand how store image and attitude towards original PL affect consumer perceptions of extended premium PL. How consumers perceive extended premium PLs could provide strategic suggestions for retailer managers with specific suggestions on whether it is more effective: to position extended premium PL similarly or dissimilarly to original PL especially on the quality dimension and congruency with store image. There is an extensive body of research on branding and brand extensions (e.g. Aaker and Keller, 1990) and more recently on PLs(e.g. Kumar and Steenkamp, 2007). However there are no studies to date that look at the upgrading and influence of original PLs and attitude towards store on the premium PL extension. This research wishes to make a contribution to this gap using the perceived fit difference between parent brands and extended premium PL as the context. In order to meet the above objectives, we investigate which factors heighten consumers' positive attitude toward premium PL extension. Research Model and Hypotheses: When considering the attitude towards the premium PL extension, we expect four factors to have an influence: attitude towards store; attitude towards original PL; perceived congruity between the store image and the premium PL; perceived similarity between the original PL and the premium PL. We expect that all these factors have an influence on consumer attitude towards premium PL extension. Figure 1 gives the research model and hypotheses. Method: Data were collected by an intercept survey conducted on consumers at discount stores. 403 survey responses were attained (total 59.8% female, across all age ranges). Respondents were asked to respond to a series of Questions measured on 7 point likert-type scales. The survey consisted of Questions that measured: the trust towards store and the original PL; the satisfaction towards store and the original PL; the attitudes towards store, the original PL, and the extended premium PL; the perceived similarity of the original PL and the extended premium PL; the perceived congruity between the store image and the extended premium PL. Product images with specific explanations of the features of premium PL, regular PL and NB we reused as the stimuli for the Question response. We developed scales to measure the research constructs. Cronbach's alphaw as measured each construct with the reliability for all constructs exceeding the .70 standard(Nunnally, 1978). Results: To test the hypotheses, path analysis was conducted using LISREL 8.30. The path analysis for verification of the model produced satisfactory results. The validity index shows acceptable results(${\chi}^2=427.00$(P=0.00), GFI= .90, AGFI= .87, NFI= .91, RMSEA= .062, RMR= .047). With the increasing retailer use of premium PLBs, the intention of this research was to examine how consumers use original PL and store image as reference points as to the attitude towards premium PL extension. Results(see table 1 & 2) show that the attitude of each parent brand (attitudes toward store and original pL) influences the attitude towards extended PL and their perceived fit moderates these influences. Attitude toward the extended PL was influenced by the relative level of perceived fit. Discussion of results and future direction: These results suggest that the future strategy for the PL extension needs to consider that positive parent brand attitude is more strongly associated with the attitude toward PL extensions. Specifically, to improve attitude towards PL extension, building and maintaining positive attitude towards original PL is necessary. Positioning premium PL congruently to store image is also important for positive attitude. In order to improve this research, the following alternatives should also be considered. To improve the research model's predictive power, more diverse products should be included in study. Other attributes of product should also be included such as design, brand name since we only considered trust and satisfaction as factors to build consumer attitudes.

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

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

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.13
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• pp.869-895
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• 2000

The US supports the Information and Communication (IC) industry as a strategic one to wield a complete power over the World Market. However, several other countries are also eager to have the support for the IC industry because the industry produces a high added value and has a significant effect on other industries. Korea is not an exception. Korea recently succeeded in the commercialization of CDMA for the first time in the world, after the successful development of TDX. Hence, it is highly likely to get tracked by the US. Although the IC industry is a specific sector of IT, there is a concern that there might be a trade friction between the US and Korea due to a possible competition. It will be very important to prepare a solution in advance so that Korea could prevent the friction and at the same time increase its share domestically and globally. It will be our important task to solve the problem with the minimum cost if the conflict arises unfortunately in the IT area. The parties that have a strong influence on the US trade policy are the think tank group and the IT-related interest group. Therefore, it would be important to have a close relationship with them. We found some implications by analyzing the case of Japan, which has experienced trade frictions with the US over the long period of time in the high tech industry. In order to get rid of those conflicts with the US, the Japanese did the following things : (1) The Japanese government developed supporting theories and also resorted to international support so that the world could support the Japanese theories. (2) Through continual dialogue with the US business people, the Japanese business people sought after solutions to share profits among the Japanese and the US both in the domestic and in the worldwide markets. They focused on lobbying activities to influence the US public opinion to support the Japanese. The specific implementation plan was first to open culture lobby toward opinion leaders who were leaders about the US opinion. The institution, Japan Society, were formed to deliver a high quality lobbying activities. The second plan is economic lobby. They have established Japanese Economic Institute at Washington. They provide information about Japan regularly or irregularly to the US government, research institution, universities, etc., that are interested in Japan. The main objective behind these activities though is to advertise the validity of Japanese policy. Japanese top executives, practical interest groups on international trade, are trying to justify their position by direct contact with the US policy makers. The third one is political lobby. Japan is very careful about this political lobby. It is doing its best not to give impression that Japan is trying to shape the US policy making. It is collecting a vast amount of information to make a correct judgment on situation. It is not tilted toward one political party or the other, and is rather developing a long-term network of people who understand and support the Japanese policy. The following implications were drawn from the experience of Japan. First, the Korean government should develop a long-term plan and execute it to improve the Korean image perceived by American people. Second, the Korean government should begin public relation activities toward the US elite group. It is inevitable to make an effort to advertise Korea to this elite group because this group leads public opinion in the USA. Third, the Korean government needs the development of a relevant policy to elevate the positive atmosphere for advertising toward the US. For example, we need information about to whom and how to about lobbying activities, personnel network who immediately respond to wrong articles about Korea in the US press, and lastly the most recent data bank of Korean support group inside the USA. Fourth, the Korean government should create an atmosphere to facilitate the advertising toward the US. Examples include provision of incentives in tax on the expenses for the advertising toward the US and provision of rewards to those who significantly contribute to the advertising activities. Fifth, the Korean government should perform the role of a bridge between Korean and the US business people. Sixth, the government should promptly analyze the policy of IT industry, a strategic area, and timely distribute information to industries in Korea. Since the Korean government is the only institution that has formal contact with the US government, it is highly likely to provide information of a high quality. The followings are some implications for business institutions. First, Korean business organization should carefully analyze and observe the business policy and managerial conditions of US companies. It is very important to do so because all the trade frictions arise at the business level. Second, it is also very important that the top management of Korean firms contact the opinion leaders of the US. Third, it is critically needed that Korean business people sent to the USA do their part for PR activities. Fourth, it is very important to advertise to American employees in Korean companies. If we cannot convince our American employees, it would be a lot harder to convince regular American. Therefore, it is very important to make the American employees the support group for Korean ways. Fifth, it should try to get much information as early as possible about the US firms policy in the IT area. It should give an enormous effort on early collection of information because by doing so it has more time to respond. Sixth, it should research on the PR cases of foreign enterprise or non-American companies inside the USA. The research needs to identify the success factors and the failure factors. Finally, the business firm will get more valuable information if it analyzes and responds to, according to each medium.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of the Mineralogical Society of Korea
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• v.21 no.3
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• pp.227-237
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• 2008

Arsenic has recently become of the most serious environmental concerns, and the worldwide regulation of arsenic fur drinking water has been reinforced. Arsenic contaminated groundwater and soil have been frequently revealed as well, and arsenic contamination and its treatment and measures have been domestically raised as one of the most important environmental issues. Arsenic behavior in geo-environment is principally affected by oxides and clay minerals, and particularly iron (oxy)hydroxides have been well known to be most effective in controlling arsenic. Among a number of iron (oxy)hydroxides, for this reason, 2-line ferrihydrite was selected in this study to investigate its effect on arsenic behavior. Adsorption of 2-line ferrihydrite was characterized and compared between As(III) and As(V) which are known to be the most ubiquitous species among arsenic forms in natural environment. Two-line ferrihydrite synthesized in the lab as the adsorbent of arsenic had $10\sim200$ nm for diameter, $247m^{2}/g$ for specific surface area, and 8.2 for pH of zero charge, and those representative properties of 2-line ferrihydrite appeared to be greatly suitable to be used as adsorbent of arsenic. The experimental results on equilibrium adsorption indicate that As(III) showed much stronger adsorption affinity onto 2-line ferrihydrite than As(V). In addition, the maximum adsorptions of As(III) and As(V) were observed at pH 7.0 and 2.0, respectively. In particular, the adsorption of As(III) did not show any difference between pH conditions, except for pH 12.2. On the contrary, the As(V) adsorption was remarkably decreased with increase in pH. The results obtained from the detailed experiments investigating pH effect on arsenic adsorption show that As(III) adsorption increased up to pH 8.0 and dramatically decreased above pH 9.2. In case of As(V), its adsorption steadily decreased with increase in pH. The reason the adsorption characteristics became totally different depending on arsenic species is attributed to the fact that chemical speciation of arsenic and surface charge of 2-line ferrihydrite are significantly affected by pH, and it is speculated that those composite phenomena cause the difference in adsorption between As(III) and As(V). From the view point of adsorption kinetics, adsorption of arsenic species onto 2-line ferrihydrite was investigated to be mostly completed within the duration of 2 hours. Among the kinetic models proposed so for, power function and elovich model were evaluated to be the most suitable ones which can simulate adsorption kinetics of two kinds of arsenic species onto 2-line ferrihydrite.

• Journal of Preventive Medicine and Public Health
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• v.29 no.4 s.55
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• pp.785-799
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• 1996

We investigated the 1,004 workers who worked in a automobile factory to study the epidemiologic characterists of dermatoses due to cutting oils. Among the workers, 667(66.4%) answered the questionaire. They are belong to 5 departments of the factory-the Engine-Work(258 workers), Gasoline engine Assembly(210), Diesel engine Assembly(96), Power train Work(86), Power train Assembly(17). We measured the oil mist concentration in air of the departments and examined the workers who had dermatologic symptoms. The results were follows; 1) Oil mist concentration ; Of all measured points(52),9 points(17.2%) exeeded $5mg/m^3$- the time-weighed PEL-and one department had a upper confidence limit(95%) higher than $5mg/m^3$. 2) Dermatologists examined 213 workers. 172 of them complained any skin symptoms at that time - itching(32.5%), papule(21.6%), scale(15.7%), vesicle(12.5%) in order. The abnormal skin site found by dermatologist were palm(29.3%), finger & nail(24.6%), forearm(16.2%), back of hand(8.4%) in order. 3) As the result of physical examination, we found that 160 workers had skin diseases. Contact dermatitis was the most common; 69 workers had contact dermatitis alone(43.1%), 11 had contact dermatitis with acne(6.9%), 10 had contact dermatitis with folliculitis(6.3%), 1 had contact dermatitis with acne & folliculitis, and 1 had contact dermatitis with abnormal pigmentation. Others were folliculitis(9 workers, 5.6%), acne(8, 5.0%), folliculitis & acne (2, 1.2%), keratosis(1, 0.6%), abnormal pigmentation (1, 0.6%), and non-specific hand eczema (47, 29.3%). 4) The prevalence of any skin diseases was 34.0 pet 100 in cutting oil users, and 13.3 per 100 in non- users. Especially, the prevalence of contact dermatitis was 23.0 per 100 in cutting oil users and 23.0 per 100 in non-users. 5) We tried patch test(standard serise, oil serise, organic solvents) on 49 patients to differentiate allergic contact dermatitis from irritant contact dermatitis and found 20 were positive. 6) In a multivariate analysis(independant=age, tenure, kinds of cutting oil), the risk of skin diseases was higher in the water-based cutting oil user and both oil user than non-user or neat oil user(odds ratio were 2.16 and 2.78, respectively). And the risk of contact dermatitis was much higher at the same groups(odds ratio were 5.16 and 6.82, respectively).