The level of domestic greenhouse complex environmental control technology is a hardware-oriented automation steps that mechanically control the environments of greenhouse, such as temperature, humidity and
Basic research have contributed to technological growth or economic growth in U.S. Specially recent studies say that universities also contribute to economic development through scientific activities like science research, education, technology transfers. But we can not assure whether scientific knowledge was connected to real technology or economic performance, and it is difficult to figure out the effect of scientific output. "What is the exact performance of scientific knowledge?" It is still obscure. In this context, this paper analyzes characteristics of the linkage of science and technology. Data are U.S. R&D expenditure, scientific articles, citation of articles in U.S. patents by fields and sectors. As a result, university sector has the most weight of the linkage of science and technology. But, in relative connection rate analysis, industrial sector's is stronger than any other sectors. In the field analysis, linkage of science and technology is very strong in Chemistry, Physics, Biological sciences fields. And recently the linkage was increased in the fields of Computer science, Agricultural science, Engineering. Finally, this paper supports funding policy or estimation policy of government to product of scientific knowledge. University sector is still important because it has the most weight of the linkage. Scientific knowledge of industrial sector is also important. The connection rate of industrial science is the strongest in all sectors. And this research classify the R&D type by science fields. Considering the differences of science fields is needed to product science knowledge effectively.
This study aims to conduct a quantitative assessment of potential economic impacts on the Korean economy of the concessions of the Korea-U.S. FTA (KORUS FTA) which was signed on April 1, 2007 using a dynamic computable general equilibrium (CGE) model, with all sectors, including agriculture, manufacturing sectors and services industry, considered for simulations. In addition, the timing of trade liberalization based on the concessions agreed on in the KORUS FTA talks for all sectors is explicitly considered. Major findings of this study are that Korea' real GDP would rise by 4.67%~4.99% by 2023 and the contribution of liberalization of services trade to Korea's economic growth would be 0.3%~0.62% points. Trade liberalization in service sectors would lead to lowered import prices and an increase in FDI, which are to contribute to an higher output and exports of sectors which make an intensive use of imported inputs and finally a higher economic growth of the Korean economy as a whole. For that to happen, a ratification of the KORUS FTA by the National Assembly of Korea and the U.S. Congress is required.
As exhibition industry, which is a part of 17 new growth engines of the government, is related to other industries such as tourism, transportation and financial industries. So it has a significant ripple effect on other industries. Exhibition is a knowledge-intensive, eco-friendly and high value-added Industry. Over 13,000 exhibitions are held every year around the world which contributes to getting foreign currency. Exhibition industry is closely related with culture and tourism and could be utilized as local and national development strategies and improve national brand image as well. Many countries try various efforts to invigorate exhibition industry by arranging related laws and support system. In Korea, more than 200 exhibitions are being held every year, but only 2~3 exhibitions are hosted with over 400 exhibitors and except these exhibitions most exhibitions have few foreign exhibitors. The main reason of weakness of domestic trade show is that there are no agencies managing exhibitionrelated statistics and there is no specific and reliable evaluation. This might cause impossibility of providing buyer or seller with reliable data, poor growth of exhibitions in terms of quality and thus service quality of trade shows cannot be improved. Hosting a lot of visitors (Public/Buyer/Exhibitor) is very crucial to the development of domestic exhibition industry. In order to attract many visitors, service quality of exhibition and visitor's satisfaction should be enhanced. For this purpose, a variety of real-time customized services through digital media and the services for creating new customers and retaining existing customers should be provided. In addition, by providing visitors with personalized information services they could manage their time and space efficiently avoiding the complexity of exhibition space. Exhibition industry can have competitiveness and industrial foundation through building up exhibition-related statistics, creating new information and enhancing research ability. Therefore, this paper deals with customized service with visitor's smart-phone at the exhibition space and designing mobile framework which enables exhibition devices to interact with other devices. Mobile server framework is composed of three different systems; multi-server interaction, server, client, display device. By making knowledge pool of exhibition environment, the accumulated data for each visitor can be provided as personalized service. In addition, based on the reaction of visitors each of all information is utilized as customized information and so the cyclic chain structure is designed. Multiple interaction server is designed to have functions of event handling, interaction process between exhibition device and visitor's smart-phone and data management. Client is an application processed by visitor's smart-phone and could be driven on a variety of platforms. Client functions as interface representing customized service for individual visitors and event input and output for simultaneous participation. Exhibition device consists of display system to show visitors contents and information, interaction input-output system to receive event from visitors and input toward action and finally the control system to connect above two systems. The proposed mobile framework in this paper provides individual visitors with customized and active services using their information profile and advanced Knowledge. In addition, user participation service is suggested as well by using interaction connection system between server, client, and exhibition devices. Suggested mobile framework is a technology which could be applied to culture industry such as performance, show and exhibition. Thus, this builds up the foundation to improve visitor's participation in exhibition and bring about development of exhibition industry by raising visitor's interest.
Personalization is user oriented dynamic method based on user preferences for easy access to what users want to view or get. It has become more important in mobile domain with rapid growth of wireless Internet and mobile phone market after success of web based market and therefore, it can be applied to service of spatial analysis result. In this paper, spatial analysis using user profile and notification service methods are proposed as one of personalized spatial data service methods for mobile users. A service system for spatial analysis with user profile is designed to prove possibility of spatial analysis based on user preferences and notification service is also designedto show generated output can be sent to user's mobile devices efficiently to make users informed of preferred information. Prototype system is implemented and it is applied to real estate data that has many selectable conditions by users. Information service based on user preferences can be applied to spatial data by using proposed system and it is efficient when cache module is used to shorten response time. Various user models for application domains and performance evaluation methods need to be developed in the future.
In franchise business, exclusive sales territory (sometimes EST in table) protection is a very important issue from an economic, social and political point of view. It affects the growth and survival of both franchisor and franchisee and often raises issues of social and political conflicts. When franchisee is not familiar with related laws and regulations, franchisor has high chance to utilize it. Exclusive sales territory protection by the manufacturer and distributors (wholesalers or retailers) means sales area restriction by which only certain distributors have right to sell products or services. The distributor, who has been granted exclusive sales territories, can protect its own territory, whereas he may be prohibited from entering in other regions. Even though exclusive sales territory is a quite critical problem in franchise business, there is not much rigorous research about the reason, results, evaluation, and future direction based on empirical data. This paper tries to address this problem not only from logical and nomological validity, but from empirical validation. While we purse an empirical analysis, we take into account the difficulties of real data collection and statistical analysis techniques. We use a set of disclosure document data collected by Korea Fair Trade Commission, instead of conventional survey method which is usually criticized for its measurement error. Existing theories about exclusive sales territory can be summarized into two groups as shown in the table below. The first one is about the effectiveness of exclusive sales territory from both franchisor and franchisee point of view. In fact, output of exclusive sales territory can be positive for franchisors but negative for franchisees. Also, it can be positive in terms of sales but negative in terms of profit. Therefore, variables and viewpoints should be set properly. The other one is about the motive or reason why exclusive sales territory is protected. The reasons can be classified into four groups - industry characteristics, franchise systems characteristics, capability to maintain exclusive sales territory, and strategic decision. Within four groups of reasons, there are more specific variables and theories as below. Based on these theories, we develop nine hypotheses which are briefly shown in the last table below with the results. In order to validate the hypothesis, data is collected from government (FTC) homepage which is open source. The sample consists of 1,896 franchisors and it contains about three year operation data, from 2006 to 2008. Within the samples, 627 have exclusive sales territory protection policy and the one with exclusive sales territory policy is not evenly distributed over 19 representative industries. Additional data are also collected from another government agency homepage, like Statistics Korea. Also, we combine data from various secondary sources to create meaningful variables as shown in the table below. All variables are dichotomized by mean or median split if they are not inherently dichotomized by its definition, since each hypothesis is composed by multiple variables and there is no solid statistical technique to incorporate all these conditions to test the hypotheses. This paper uses a simple chi-square test because hypotheses and theories are built upon quite specific conditions such as industry type, economic condition, company history and various strategic purposes. It is almost impossible to find all those samples to satisfy them and it can't be manipulated in experimental settings. However, more advanced statistical techniques are very good on clean data without exogenous variables, but not good with real complex data. The chi-square test is applied in a way that samples are grouped into four with two criteria, whether they use exclusive sales territory protection or not, and whether they satisfy conditions of each hypothesis. So the proportion of sample franchisors which satisfy conditions and protect exclusive sales territory, does significantly exceed the proportion of samples that satisfy condition and do not protect. In fact, chi-square test is equivalent with the Poisson regression which allows more flexible application. As results, only three hypotheses are accepted. When attitude toward the risk is high so loyalty fee is determined according to sales performance, EST protection makes poor results as expected. And when franchisor protects EST in order to recruit franchisee easily, EST protection makes better results. Also, when EST protection is to improve the efficiency of franchise system as a whole, it shows better performances. High efficiency is achieved as EST prohibits the free riding of franchisee who exploits other's marketing efforts, and it encourages proper investments and distributes franchisee into multiple regions evenly. Other hypotheses are not supported in the results of significance testing. Exclusive sales territory should be protected from proper motives and administered for mutual benefits. Legal restrictions driven by the government agency like FTC could be misused and cause mis-understandings. So there need more careful monitoring on real practices and more rigorous studies by both academicians and practitioners.
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.
The country with a relative abundance of human capital conducts relatively more R&D in the steady state than its partner. This country acquires the know-how to produce a relatively wider range of innovative goods. High technology comprises a large share of the national economy in the human-capital rich country and real output growth is faster. This prediction would seem to accord weakly with empirical observation of Korean economy.
The role of pension plans in the macroeconomy has been a subject of much interest for some years. It has come to be recognized that pension plans may alter basic macroeconomic behavior patterns. The net effects on both savings and labor supply are thus matters for speculation. The aim of the present paper is to provide quantitative results which may be helpful in attaching orders of magnitude to some of the possible effects. We are not concerned with the providing empirical evidence relating to actual behavior, but rather with deriving the macroeconomic implications for a alternative possibilities. The pension plan interacts with the economy and the population in a number of ways. Demographic variables may thus affect both the economic burden of a national pension plan and the ability of the economy to sustain the burden. The tax transfer process associated with the pension plan may have implications for national patterns of saving and consumption. The existence of a pension plan may have implications also for the size of the labor force, inasmuch as labor force participation rates may be affected. Changes in technology and the associated changes in average productivity levels bear directly on the size of the national income, and hence on the pension contribution base. The vehicle for the analysis is a hypothetical but broadly realistic simulation model of an economic- demographic system into which is inserted a national pension plan. All income, expenditure, and related aggregates are in real terms. The economy is basically neoclassical; full employment is assumed, output is generated by a Cobb-Douglas production process, and factors receive their marginal products. The model was designed for use in computer simulation experiments. The simulation results suggest a number of general conclusions. These may be summarized as follows; - The introduction of a national pension plan (funded system) tends to increase the rate of economic growth until cost exceeds revenue. - A scheme with full wage indexing is more expensive than one in which pensions are merely price indexed. - The rate of technical progress is not a critical element in determining the economic burden of the pension scheme. - Raising the rate of benefits affects its economic burden, and raising the age of eligibility may decrease the burden substantially. - The level of fertility is an element in determining the long-run burden. A sustained low fertility rate increases the proportion of the aged in total population and increases the burden of the pension plan. High fertility has inverse effects.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70