This paper describes the forecast of power plant construction in a competitive korean electricity market. In Korea, KEPCO (Korea Electric Power Corporation, fully controlled by government) was responsible for from the production of the electricity to the sale of electricity to customer. However, the generation part is separated from KEPCO and six generation companies were established for whole sale competition from April 1st, 2001. The generation companies consist of five fossil power companies and one nuclear power company in Korea at present time. Fossil power companies are scheduled to be sold to private companies including foreign investors. Nuclear power company is owned and controlled by government. The competition in generation market will start from 2003. ISO (Independence System Operator will purchase the electricity from the power exchange market. The market price is determined by the SMP(System Marginal Price) which is decided by the balance between demand and supply of electricity in power exchange market. Under this uncertain circumstance, the energy policy planners such as government are interested to the construction of the power plant in the future. These interests are accelerated due to the recent shortage of electricity supply in California. In the competitive market, investors are no longer interested in the investment for the capital intensive, long lead time generating technologies such as nuclear and coal plants. Large unclear and coal plants were no longer the top choices. Instead, investors in the competitive market are interested in smaller, more efficient, cheaper, cleaner technologies such as CCGT(Combined Cycle Gas Turbine). Electricity is treated as commodity in the competitive market. The investors behavior in the commodity market shows that the new investment decision is made when the market price exceeds the sum of capital cost and variable cost of the new facility and the existing facility utilization depends on the marginal cost of the facility. This investors behavior can be applied to the new investments for the power plant. Under these postulations, there is the potential for power plant construction to appear in waves causing alternating periods of over and under supply of electricity like commodity production or real estate production. A computer model was developed to sturdy the possibility that construction will appear in waves of boom and bust in Korean electricity market. This model was constructed using System Dynamics method pioneered by Forrester(MIT, 1961) and explained in recent text by Sternman (Business Dynamics, MIT, 2000) and the recent work by Andrew Ford(Energy Policy, 1999). This model was designed based on the Energy Policy results(Ford, 1999) with parameters for loads and resources in Korea. This Korea Market Model was developed and tested in a small scale project to demonstrate the usefulness of the System Dynamics approach. Korea electricity market is isolated and not allowed to import electricity from outsides. In this model, the base load such as unclear and large coal power plant are assumed to be user specified investment and only CCGT is selected for new investment by investors in the market. This model may be used to learn if government investment in new unclear plants could compensate for the unstable actions of private developers. This model can be used to test the policy focused on the role of unclear investments over time. This model also can be used to test whether the future power plant construction can meet the government targets for the mix of generating resources and to test whether to maintain stable price in the spot market.
Genomics is providing targets faster than we can validate them and combinatorial chemistry is providing new chemical entities faster than we can screen them. Historically, the drug discovery cascade has been established as a sequential process initiated with a potency screening against a selected biological target. In this sequential process, pharmacokinetics was often regarded as a low-throughput activity. Typically, limited pharmacokinetics studies would be conducted prior to acceptance of a compound for safety evaluation and, as a result, compounds often failed to reach a clinical testing due to unfavorable pharmacokinetic characteristics. A new paradigm in drug discovery has emerged in which the entire sample collection is rapidly screened using robotized high-throughput assays at the outset of the program. Higher-throughput pharmacokinetics (HTPK) is being achieved through introduction of new techniques, including automation for sample preparation and new experimental approaches. A number of in vitro and in vivo methods are being developed for the HTPK. In vitro studies, in which many cell lines are used to screen absorption and metabolism, are generally faster than in vivo screening, and, in this sense, in vitro screening is often considered as a real HTPK. Despite the elegance of the in vitro models, however, in vivo screenings are always essential for the final confirmation. Among these in vivo methods, cassette dosing technique, is believed the methods that is applicable in the screening of pharmacokinetics of many compounds at a time. The widespread use of liquid chromatography (LC) interfaced to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) allowed the feasibility of the cassette dosing technique. Another approach to increase the throughput of in vivo screening of pharmacokinetics is to reduce the number of sample analysis. Two common approaches are used for this purpose. First, samples from identical study designs but that contain different drug candidate can be pooled to produce single set of samples, thus, reducing sample to be analyzed. Second, for a single test compound, serial plasma samples can be pooled to produce a single composite sample for analysis. In this review, we validated the issue whether the second method can be applied to practical screening of in vivo pharmacokinetics using data from seven of our previous bioequivalence studies. For a given drug, equally spaced serial plasma samples were pooled to achieve a 'Pooled Concentration' for the drug. An area under the plasma drug concentration-time curve (AUC) was then calculated theoretically using the pooled concentration and the predicted AUC value was statistically compared with the traditionally calculated AUC value. The comparison revealed that the sample pooling method generated reasonably accurate AUC values when compared with those obtained by the traditional approach. It is especially noteworthy that the accuracy was obtained by the analysis of only one sample instead of analyses of a number of samples that necessitates a significant man-power and time. Thus, we propose the sample pooling method as an alternative to in vivo pharmacokinetic approach in the selection potential lead(s) from combinatorial libraries.
The latest movement in live video streaming service is mobile personal broadcasting (MPB), which refers to consumers accessing the service through social media with mobile devices, such as smartphones and tablet PCs. This service is possible through the advancements in mobile video technology and platforms. Features such as enhanced user interaction, personalization, and real-time broadcasting, combined with a greater variety of content, have led to the development of MPB. The increase in MPB users calls for research, including that on the hedonic motivational angle. This study aims to assess MPB users' intrinsic motives through the hedonic-motivation system adoption model (HMSAM) using seven factors: joy, temporal dissociation, escapism, focused immersion, perceived ease of use, perceived usefulness and intention to watch. Survey data collected from 154 samples were analyzed with statistical techniques, such as structural equation modeling. Results showed that time dissociation, escapism, and perceived ease of use have a positive relationship with heightened enjoyment. Joy significantly affects focused immersion and intention to watch. Escapism also had a statistically significant influence on focused immersion. This study contributes to the advancement of the MPB study under the HMSAM theoretical framework and offers practical suggestions to managers to enhance MPB content viewership.
We analyzed the international comovements and structural changes in the quarterly real GDP by the Markov-switching vector autoregressive model (MS-VAR) from 1971(1) to 2016(1). The main results of this study were as follows. First, the business cycle phenomenon that occurs in the models or individual time series in real GDP has been grasped through the MS-VAR models. Unlike previous studies, this study showed the significant comovements, asymmetry and structural changes in the MS-VAR model using a real GDP across countries. Second, even if there was a partial difference, there were remarkable structural changes in the economy contraction regime(recession), such as 1988(2) ending the global oil shock crisis and 2007(3) starting the global financial crisis by the MS-VAR model. Third, large-scale structural changes were generated in the economic expansion and/or contraction regime simultaneously among countries. We found that the second world oil shocks that occurred after the first global oil shocks of 1973 and 1974 were the main reasons that caused the large-scale comovements of the international real GDP among countries. In addition, the spillover between Korea and 5 countries has been weak during the Asian currency crisis from 1997 to 1999, but there was strong transmission between Korea and 5 countries at the end of 2007 including the period of the global financial crisis. Fourth, it showed characteristics that simultaneous correlation appeared to be high due to the country-specific shocks generated for each country with the regime switching using real GDP since 1973. Thus, we confirmed that conclusions were consistent with a number of theoretical and empirical evidence available, and the macro-economic changes were mainly caused by the global shocks for the past 30 years. This study found that the global business cycles were due to large-scale asymmetric shocks in addition to the general changes, and then showed the main international comovements and/or structural changes through country-specific shocks.
Severe mine disasters have continued to occur around the world. To ensure worker's health and safety and enhance the productivity, a number of studies have been conducted for the development of wireless sensor network (WSN), environmental monitoring, and communication system in underground mines. An increase in development and application of these systems has just begun with the introduction of information and communication technology into the mining industry in Korea, and yet there have been only a few studies that considered the underground mine ventilation system. This study presented the literature review on the development of WSN and environmental monitoring in underground mines, and especially, on 7 subjects in terms of underground mine ventilation. Moreover, studies that especially conducted real-time environmental monitoring were reviewed and categorized by each commercial software commonly utilized for the ventilation network analysis. For the application in domestic underground mines, further issues were discussed regarding research subjects that may be needed in the future and domestic environmental standards that has been used in the underground mine operation. This paper is expected to be useful for the development of WSN-based environmental monitoring and communication system, as well as for related studies in the future.
This study develops and improves the EZ Touch App of the scorecard application (app) using the smartphone and the pad, and works with the customer management system (C/S). The research was conducted as follows. First, how do you handle the EZ Touch input method on a scorecard? Second, how to configure the platform of customer (member) management system (C/S) and data server system? Third, does EZ Touch App work organically with customer management system (C/S)? The developed EZ Touch is entered into the scorecard as an input method using the gesture as a result of this research, and it is linked with the C/S system to organize the review function, hall information function, field coaching function through score, It can be used for applications such as information management functions and statistics through differentiated statistics. However, there are some problems and improvements in user convenience in real time use. I think there is a need to study to solve this problem in the future. EZ Touch input method is input to the scorecard by inputting gesture of the finger as a result of this study, and it is linked with this, and it is possible to use differentiated statistics such as review function, hall information function, field coaching function, It is the purpose of the study to improve the technical competitiveness of the product by developing the application.
Journal of the Korea Society of Computer and Information
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v.20
no.4
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pp.131-138
/
2015
One of the most conspicuous characteristics of a business model that pursues expanding customer relationship is that it tries to lock in customers by encouraging them to repeat purchase in the long-term with the help of "Follow" function in Social Networking Service (SNS), which enables producers to automatically register the customers as potentially important ones and to offer them customized marketing services. In the value chain of the agriculture sector, producers of agricultural products can use SNS functions to provide loyal customers with valuable information and experiences such as the real-time information of their farm and products, hidden stories about the whole process from seeding to harvesting, and the storage and cooking methods of their products. These activities help the producers invoke customers' desire to live in the farm and to grow the products themselves. They also raise the accessibility of the producers' websites as customers are able to share a variety of news and knowledge such as the release of new products. This means that the producers's websites are now functioning to enable the producers to perform sales and promotion related activities. It is a big leap from the traditional e-commerce business model where sales and promotion of a product were separated and could be connected only through outside links. This two-way, viral characteristics of marketing services using SNS facilitate customers to share product information and their purchase experience with each other, which leads to more effective and efficient communication within the customer community.
KIPS Transactions on Computer and Communication Systems
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v.9
no.12
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pp.291-306
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2020
Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.
Journal of the Korean BIBLIA Society for library and Information Science
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v.34
no.1
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pp.209-238
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2023
This study aims to propose the main learning contents, functions and activation plans for building an e-learning platform for libraries through a literature review, case analysis and expert survey. Through the literature review, it was found that libraries must play a role in providing high-quality online education for users in the e-learning ecosystem. Based on the previous studies, a learning function analysis tool was developed for the analysis of the library's e-learning platform. Based on this, the learning contents, learning functions and characteristics of library e-learning platforms were analyzed, and expert surveys and interviews were conducted. As a results, the construction of a platform for effectively applying learning processes and technology is essential for the library's sustainable e-learning services. The contents that should be provided for characteristics of library education, reading guidance, information literacy instruction, library usage instruction, and the latest IT technologies. And The main learning functions include the ability to conduct video lectures and real-time classes among learning types, and learning activity support functions, a cloud platform support function and a personalized environment support function. Additionally, suggested re-education for library staff to improve their technical skills and the formation of an e-learning team.
Journal of the Korean Society for Marine Environment & Energy
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v.16
no.1
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pp.17-24
/
2013
In order to have market competitiveness in local and global areas, Domestic Marine Leisure Industry business, which is a latecomer in the Marine Leisure industry, should retain a strong market adaptability by reducing time and cost that are required for work of planning, designing, and preparation for product development. To meet above requirements, it is essential that integrated system control extensive marine leisure industry. After ensuring integrated information by figuring out the systematic link between related-industries, the core of this research is to secure information classifications that are not just in the flow of simple serial order, but in that of integration and object-oriented information classifications. For this end, we examine other similar cases in industries using real information system applied to industrial production and Product Lifecycle Management (PLM), Product Data Management (PDM), Digital Manufacturing (DM) and applying the same methodology to review practical application in order to construct the information system, and Work Breakdown Structure (WBS), compared with the case studies. Through this basic task for the marine leisure industry classification system configuration (Work Breakdown Structure, WBS) and utilizing information of driving real companies of marine leisure industry, a unique area of MLWBS (Marine Leisure Work Breakdown Structure, MLWBS) is configured. This Marine Leisure Work Breakdown Structure can be used in various areas of applications like products, design information, engineering, production, purchasing, sales, marketing, AS, utilizing various forms of customer support.
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