Comparison and Analysis of Field Hydraulic Tests to Evaluate Hydraulic Characteristics in Deep Granite Rockmass (심부 화강암반의 수리특성 평가를 위한 현장수리시험 비교 및 해석 연구)
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- Tunnel and Underground Space
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- v.34 no.4
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- pp.393-412
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- 2024
In selecting a disposal site for high-level radioactive waste, the hydrogeological research of the site is very important, and the hydraulic conductivity and the storage coefficient are key parameters. In this study, the hydraulic conductivity obtained by two different types of field hydraulic test equipment and methods was compared and analyzed for the deep granite rockmass in the Wonju area to understand the hydraulic characteristics of the deep granite rockmass. One was to perform the lugeon test, constant pressure injection test, and slug test at a maximum depth of 602.0 m by using the auto pressure/flow injection system, and the calculated hydraulic conductivity ranged from 1.26E-9 to 4.16E-8 m/s. In the overall depth, the maximum and minimum differences of the hydraulic conductivity were found to be about 33 times, and in the same test section, the difference by test method or analysis method was 1.13 to 8.25 times. In the other, the hydraulic conductivity calculated by performing a constant pressure injection test and a pulse test at a maximum depth of 705.1 m using the deep borehole hydraulic testing system was found to be 1.60E-10 to 2.05E-8 m/s, and the maximum and minimum differences were found to be about 130 times. In the constant pressure injection test, the difference depending on the analysis method was found to be 1.02 to 2.8 times. The hydraulic conductivity calculated by the two test equipment and methods generally showed similar ranges as E-9 and E-8 m/s, and no clear trend was observed according to depth. It was found that the granite rockmass in the Wonju area where the field hydraulic test was conducted showed low or very low rockmass permeability, and although there are differences in the range of hydraulic conductivity and the depth of application that can be measured depending on the applied test equipment and test method, it is generally believed that reliable results were presented.
The purpose of this research is to construct research framework for international franchising based on existing literature and to identify research components in the framework. Franchise can be defined as management styles that allow franchisee use various management assets of franchisor in order to make or sell product or service. It can be divided into product distribution franchise that is designed to sell products and business format franchise that is designed for running it as business whatever its form is. International franchising can be defined as a way of internationalization of franchisor to foreign country by providing its business format or package to franchisee of host country. International franchising is growing fast for last four decades but academic research on this is quite limited. Especially in Korea, research about international franchising is carried out on by case study format with single case or empirical study format with survey based on domestic franchise theory. Therefore, this paper tries to review existing literature on international franchising research, providing research framework, and then stimulating new research on this field. International franchising research components include motives and environmental factors for decision of expanding to international franchising, entrance modes and development plan for international franchising, contracts and management strategy of international franchising, and various performance measures from different perspectives. First, motives of international franchising are fee collection from franchisee. Also it provides easier way to expanding to foreign country. The other motives including increase total sales volume, occupying better strategic position, getting quality resources, and improving efficiency. Environmental factors that facilitating international franchising encompasses economic condition, trend, and legal or political factors in host and/or home countries. In addition, control power and risk management capability of franchisor plays critical role in successful franchising contract. Final decision to enter foreign country via franchising is determined by numerous factors like history, size, growth, competitiveness, management system, bonding capability, industry characteristics of franchisor. After deciding to enter into foreign country, franchisor needs to set entrance modes of international franchising. Within contractual mode, there are master franchising and area developing franchising, licensing, direct franchising, and joint venture. Theories about entrance mode selection contain concepts of efficiency, knowledge-based approach, competence-based approach, agent theory, and governance cost. The next step after entrance decision is operation strategy. Operation strategy starts with selecting a target city and a target country for franchising. In order to finding, screening targets, franchisor needs to collect information about candidates. Critical information includes brand patent, commercial laws, regulations, market conditions, country risk, and industry analysis. After selecting a target city in target country, franchisor needs to select franchisee, in other word, partner. The first important criteria for selecting partners are financial credibility and capability, possession of real estate. And cultural similarity and knowledge about franchisor and/or home country are also recognized as critical criteria. The most important element in operating strategy is legal document between franchisor and franchisee with home and host countries. Terms and conditions in legal documents give objective information about characteristics of franchising agreement for academic research. Legal documents have definitions of terminology, territory and exclusivity, agreement of term, initial fee, continuing fees, clearing currency, and rights about sub-franchising. Also, legal documents could have terms about softer elements like training program and operation manual. And harder elements like law competent court and terms of expiration. Next element in operating strategy is about product and service. Especially for business format franchising, product/service deliverable, benefit communicators, system identifiers (architectural features), and format facilitators are listed for product/service strategic elements. Another important decision on product/service is standardization vs. customization. The rationale behind standardization is cost reduction, efficiency, consistency, image congruence, brand awareness, and competitiveness on price. Also standardization enables large scale R&D and innovative change in management style. Another element in operating strategy is control management. The simple way to control franchise contract is relying on legal terms, contractual control system. There are other control systems, administrative control system and ethical control system. Contractual control system is a coercive source of power, but franchisor usually doesn't want to use legal power since it doesn't help to build up positive relationship. Instead, self-regulation is widely used. Administrative control system uses control mechanism from ordinary work relationship. Its main component is supporting activities to franchisee and communication method. For example, franchisor provides advertising, training, manual, and delivery, then franchisee follows franchisor's direction. Another component is building franchisor's brand power. The last research element is performance factor of international franchising. Performance elements can be divided into franchisor's performance and franchisee's performance. The conceptual performance measures of franchisor are simple but not easy to obtain objectively. They are profit, sale, cost, experience, and brand power. The performance measures of franchisee are mostly about benefits of host country. They contain small business development, promotion of employment, introduction of new business model, and level up technology status. There are indirect benefits, like increase of tax, refinement of corporate citizenship, regional economic clustering, and improvement of international balance. In addition to those, host country gets socio-cultural change other than economic effects. It includes demographic change, social trend, customer value change, social communication, and social globalization. Sometimes it is called as westernization or McDonaldization of society. In addition, the paper reviews on theories that have been frequently applied to international franchising research, such as agent theory, resource-based view, transaction cost theory, organizational learning theory, and international expansion theories. Resource based theory is used in strategic decision based on resources, like decision about entrance and cooperation depending on resources of franchisee and franchisor. Transaction cost theory can be applied in determination of mutual trust or satisfaction of franchising players. Agent theory tries to explain strategic decision for reducing problem caused by utilizing agent, for example research on control system in franchising agreements. Organizational Learning theory is relatively new in franchising research. It assumes organization tries to maximize performance and learning of organization. In addition, Internalization theory advocates strategic decision of direct investment for removing inefficiency of market transaction and is applied in research on terms of contract. And oligopolistic competition theory is used to explain various entry modes for international expansion. Competency theory support strategic decision of utilizing key competitive advantage. Furthermore, research methodologies including qualitative and quantitative methodologies are suggested for more rigorous international franchising research. Quantitative research needs more real data other than survey data which is usually respondent's judgment. In order to verify theory more rigorously, research based on real data is essential. However, real quantitative data is quite hard to get. The qualitative research other than single case study is also highly recommended. Since international franchising has limited number of applications, scientific research based on grounded theory and ethnography study can be used. Scientific case study is differentiated with single case study on its data collection method and analysis method. The key concept is triangulation in measurement, logical coding and comparison. Finally, it provides overall research direction for international franchising after summarizing research trend in Korea. International franchising research in Korea has two different types, one is for studying Korean franchisor going overseas and the other is for Korean franchisee of foreign franchisor. Among research on Korean franchisor, two common patterns are observed. First of all, they usually deal with success story of one franchisor. The other common pattern is that they focus on same industry and country. Therefore, international franchise research needs to extend their focus to broader subjects with scientific research methodology as well as development of new theory.
The purpose of this research is to explore differences between small and medium-sized companies and large-sized companies in the impact of human resource innovativeness(HRI), learning orientation(LO), and HRI-LO interaction on innovation effect and business performance. Although learning orientation has long been considered as a key factor influencing good performance of a business, little research was devoted to exploring the effect of HRI-LO interaction on innovation effect and business performance. In this study, it is investigated whether there is a synergy effect between innovative human workforce and learning orientation corporate culture, in addition to each by itself, to generate good business performance as well as a success of new innovations in the market. Research hypotheses were as follows, including H1) human resource innovativeness(HRI), learning orientation(LO), and interactions of HRI and LO(HRI-LO interaction) positively affect innovation effect, H2) there is a difference of the effect of HRI, LO, and HRI-LO interaction on innovation effect between large-sized and small-sized companies, H3) HRI, LO, HRI-LO interaction, innovation effect positively affect business performance, and H4) there is a difference of the effect of HRI, LO, HRI-LO interaction, and innovation effect on business performance between large-sized and small-sized companies. Data were obtained from 479 practitioners through a web survey since the web survey is an efficient method to collect a national data at a variety of fields. A single respondent from a company was allowed to participate in the study after checking whether they have more than 5-year work experiences in the company. To check whether a common source bias is existed in the sample, additional data from a convenient sample of 97 companies were gathered through the traditional survey method, and were used to confirm correlations between research variables of the original sample and the additional sample. Data were divided into two groups according to company size, such as 352 small and medium-sized companies with less than 300 employees and 127 large-sized companies with 300 or more employees. Data were analyzed through t-test and regression analyses. HRI which is the innovativeness of human resources in the company was measured with 9 items assessing the innovativenss of practitioners in staff, manager, and executive-level positions. LO is the company's effort to encourage employees' development, sharing, and utilizing of knowledge through consistent learning. LO was measured by 18 items assessing commitment to learning, vision sharing, and open-mindedness. Innovation effect which assesses a success of new products/services in the market, was measured with 3 items. Business performance was measured by respondents' evaluations on profitability, sales increase, market share, and general business performance, compared to other companies in the same field. All items were measured by using 6-point Likert scales. Means of multiple items measuring a construct were used as variables based on acceptable reliability and validity. To reduce multi-collinearity problems generated on the regression analysis of interaction terms, centered data were used for HRI, LO, and Innovation effect on regression analyses. In group comparison, large-sized companies were superior on annual sales, annual net profit, the number of new products/services in the last 3 years, the number of new processes advanced in the last 3 years, and the number of R&D personnel, compared to small and medium-sized companies. Also, large-sized companies indicated a higher level of HRI, LO, HRI-LO interaction, innovation effect and business performance than did small and medium-sized companies. The results indicate that large-sized companies tend to have more innovative human resources and invest more on learning orientation than did small-sized companies, therefore, large-sized companies tend to have more success of a new product/service in the market, generating better business performance. In order to test research hypotheses, a series of multiple-regression analysis was conducted. In the regression analysis examining the impact on innovation effect, important results were generated as : 1) HRI, LO, and HRI-LO affected innovation effect, and 2) company size indicated a moderating effect. Based on the result, the impact of HRI on innovation effect would be greater in small and medium-sized companies than in large-sized companies whereas the impact of LO on innovation effect would be greater in large-sized companies than in small and medium-sized companies. In other words, innovative workforce would be more important in making new products/services that would be successful in the market for small and medium-sized companies than for large-sized companies. Otherwise, learning orientation culture would be more effective in making successful products/services for large-sized companies than for small and medium-sized companies. Based on these results, research hypotheses 1 and 2 were supported. In the analysis of a regression examining the impact on business performance, important results were generated as : 1) innovation effect, LO, and HRI-LO affected business performance, 2) HRI by itself did not have a direct effect on business performance regardless of company size, and 3) company size indicated a moderating effect. Specifically, an effect of the HRI-LO interaction on business performance was stronger in large-sized companies than in small and medium-sized companies. It means that the synergy effect of innovative human resources and learning orientation culture tends to be stronger as company is larger. Referring to these result, research hypothesis 3 was partially supported whereas hypothesis 4 was supported. Based on research results, implications for companies were generated. Regardless of company size, companies need to develop the learning orientation corporate culture as well as human resources' innovativeness together in order to achieve successful development of innovative products and services as well as to improve sales and profits. However, the effectiveness of the HRI-LO interaction would be varied by company size. Specifically, the synergy effect of HRI-LO was stronger to make a success of new products/services in small and medium-sized companies than in large-sized companies. However, the synergy effect of HRI-LO was more effective to increase business performance of large-sized companies than that of small and medium-sized companies. In the case of small and medium-sized companies, business performance was achieved more through the success of new products/services than much directly affected by HRI-LO. The most meaningful result of this study is that the effect of HRI-LO interaction on innovation effect and business performance was confirmed. It was often ignored in the previous research. Also, it was found that the innovativeness of human workforce would not directly influence in generating good business performance, however, innovative human resources would indirectly affect making good business performance by contributing to achieving the development of new products/services that would be successful in the market. These findings would provide valuable managerial implications specifically in regard to the development of corporate culture and education program of small and medium-sized as well as large-sized companies in a variety of fields.
The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.
Digital content makes big changes to our daily lives while bringing opportunities and challenges for companies. Creative firms integrate pictures, texts, videos, audios, and data by digitalization to develop new products or services and create digital experiences to promote their brands. Most articles on digital content contribute to the basic concept or development of marketing it in literature. Actually, compared with traditional value chains for common products or services, the digital content industry seems to have more potential value. Because quite a bit of digital content is free to the consumer, price is not necessarily perceived as an indicator of the quality or value of information (Rowley 2008). It becomes evident that a current theme in digital content is the issue of "value," and research on customers' perceived value of digital content is a necessity. This article argues that experiential value has an advantage in customers' evaluations of digital content. Two different but related contributions to the understanding of "value" of digital content are made here. First, based on the comparison of digital content with products and services, the article proposes two key characteristics that make experiential strategy available for digital content: intangibility and near-zero reproduction cost. On top of that, based on the discussion of the gap between company's idealized value and customer's perceived value, this article emphasizes that digital content prices and pricing of digital content is different from products and services. As a result of intangibility, prices may not reflect customer value. Moreover, the cost of digital content in the development stage may be very high while reproduction costs shrink dramatically. Moreover, because of the value gap mentioned before, the pricing polices vary for different digital contents. For example, flat price policy is generally used for movies and music (Magiera 2001; Netherby 2002), while for continuous demand, digital content such as online games and anti-virus programs involves a more complicated matter of utility and competitive price levels. Digital content companies have to explore various kinds of strategies to overcome this gap. Rethinking marketing solutions such as advertisements, images, and word-of-mouth and their effect on customers' perceived value becomes essential. China's digital content industry is becoming more and more globalized and drawing special attention from different countries and regions that have respective competitive advantages. The 2008-2009 Annual Report on the Development of China's Digital Content Industry (CCIDConsulting 2009) indicates that, with the driven power of domestic demand and governmental policy support, the country's digital content industry maintained a fast growth of some 30 percent in 2008, obviously indicating the initial stage of industry expansion. In China, anti-virus programs and other software programs which need to be updated use a quarter-based pricing policy. Customers can download a trial version for free and use it for six months or a year. If they want to use it longer, continuous payment is needed. They examine the excellence of the digital content during this trial period and decide whether to pay for continued usage. For China’s music and movie industries, as a result of initial development, experiential strategy has not been much applied, even though firms in other countries find the trial experience and explore important strategies(such as customers listening to music for several seconds for free before downloading it). For the above reasons, anti-virus program may be a representative for digital content industry in China and an exploratory study of the advantage of experiential value in customer's perceived value of digital content is done in the anti-virus market of China. In order to enhance the reliability of the survey data, this study focused on people who were experienced users of anti-virus programs. The empirical results revealed that experiential value has a positive effect on customers' perceived value of digital content. In other words, because digital content is intangible and the reproduction costs are nearly zero, customers' evaluations are based heavily on their experience. Moreover, image and word-of-mouth do not have a positive effect on perceived value, only on experiential value. That is to say, a digital content value chain is different from that of a general product or service. Experiential value has a notable advantage and mediates the effect of image and word-of-mouth on perceived value. The results of this study help provide an understanding of why free digital content downloads exist in developing countries. Customers can perceive the value of digital content only by using and experiencing it. This is also why such governments support the development of digital content. Other developing countries whose digital content business is also in the beginning stage can make use of the suggestions here. Moreover, based on the advantage of experiential strategy, companies should make more of an effort to invest in customers' experience. As a result of the characteristics and value gap of digital content, customers perceive more value in the intangible digital content only by experiencing what they really want. Moreover, because of the near-zero reproduction costs, companies can perhaps use experiential strategy to enhance customer understanding of digital content.
Purpose: Radioiodine (I-131) therapy is an effective modality to reduce both recurrence and mortality rates in differentiated thyroid cancer. Whether higher doses shows higher therapeutic responses was still debatable. The purpose of this study was to validate curve-fitting (CF) method measuring maximum permissible dose (MPD) by a biological dosimetry using metaphase analysis of peripheral blood lymphocytes. Materials and Methods: Therapeutic effects of MPD was evaluated in 58 patients (49 females and 9 males, mean age
Purpose: Radioimmunoassay (RIA) was usually performed by the batch assay. To improve the efficiency of RIA without increase of the cost and time, random assay could be a choice. We investigated the possibility of the random assay using automatic dispenser by assessing the agreement between batch assay and random assay. Materials and Methods: The experiments were performed with four items; Triiodothyronine (T3), free thyroxine (fT4), Prostate specific antigen (PSA), Carcinoembryonic antigen (CEA). In each item, the sera of twenty patients, the standard, and the control samples were used. The measurements were done 4 times with 3 hour time intervals by random assay and batch assay. The coefficient of variation (CV) of the standard samples and patients' data in T3, fT4, PSA, and CEA were assessed. ICC (Intraclass correlation coefficient) and coefficient of correlation were measured to assessing the agreement between two methods. Results: The CVs (%) of T3, fT4, PSA, and CEA measured by batch assay were 3.2
"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."
In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.
Background: Infective endocarditis shows high surgical mortality and morbidity rates, especially for aortic endocarditis. This study attempts to investigate the clinical characteristics and operative results of isolated aortic endocarditis. Material and Method: From July 1990 to May 2005, 25 patients with isolated aortic endocarditis (Group I, male female=18 : 7, mean age