• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Management & Information Systems Review
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• v.35 no.3
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• pp.57-79
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• 2016

It is required to derive various conclusions by identifying the type of power and the relationship between SCMs and presenting practical implications. Thus, we can identify the differential effects of each type of power on SCM performance. We can contribute to develop the practical implications at more sophisticated multi-dimension by comparing results of this study with various SCM theories. Through previous studies, the source of power is largely divided into binding power and non-binding power. Binding power is classified into behavior coercion, binding reward and relationship legitimacy. Non-binding power is classified into work expertise, information superiority and value compliance. Enterprises should fully understand and recognize partners within supply chains including understanding of the source of power, imbalance and results. Thus, we look into types of power and effects on trust and commitment, and identify a causal relationship leading to collaboration and SCM performance. Specific research results are as follows. First, the binding power did not give a significant effect to the trust. However, the binding power gave a positively(+) significant effect to the commitment. Second, non-binding power showed a significant effect on both trust and commitment. As a result of analysis on total effects, it was shown that non-binding power gave indirect effects to collaboration and SCM performance. Third, it was shown that both trust and commitment significantly affected collaboration. From the perspectives of social exchange theory and trading cost theory among inter-organizational relationship theory, it may lead to SCM performance of trust, commitment and collaboration. Moreover, it was found that association of each attribute of power led to the significant result. Fourth, it was shown that trust and collaboration significantly affected SCM performance. However, commitment did not directly affect SCM performance, but it indirectly significantly affected SCM performance through collaboration. Proper use of this power can firmly build partnerships between members of the supply chain and induce the improvement on supply chain performance and satisfaction of members.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.665-673
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• 2011

In order to estimate the hydrocarbon reserves, the porosity of the reservoir must be determined. The porosity of the area without a well is generally calculated by extrapolating the porosity logs measured at wells. However, if not only well logs but also seismic data exist on the same site, the more accurate pseudo porosity log can be obtained through artificial neural network technique by extracting the relations between the seismic data and well logs at the site. In this study, we have developed a module which creates pseudo porosity logs by using the polynomial neural network method. In order to obtain more accurate pseudo porosity logs, we selected the seismic attributes which have high correlation values in the correlation analysis between the seismic attributes and the porosity logs. Through the training procedure between selected seismic attributes and well logs, our module produces the correlation weights which can be used to generate the pseudo porosity log in the well free area. To verify the reliability and the applicability of the developed module, we have applied the module to the field data acquired from F3 Block in the North Sea and compared the results to those from the probabilistic neural network method in a commercial program. We could confirm the reliability of our module because both results showed similar trend. Moreover, since the pseudo porosity logs from polynomial neural network method are closer to the true porosity logs at the wells than those from probabilistic method, we concluded that the polynomial neural network method is effective for the data sets with insufficient wells such as F3 Block in the North Sea.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.191-204
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• 2010

Recently, the CO2 emission and energy consumption have become critical global issues to decide the future of nations. Especially, the spread of IT products and the increased use of internet and web applications result in the energy consumption and CO2 emission of IT industry though information technologies drive global economic growth. EU, the United States, Japan and other developed countries are using IT related environmental regulations such as WEEE(Waste Electrical and Electronic Equipment), RoHS(Restriction of the use of Certain Hazardous Substance), REACH(Registration, Evaluation, Authorization and Restriction of CHemicals) and EuP(Energy using Product), and have established systematic green business/IT strategies to enhance the competitiveness of IT industry. For example, the Japan government proposed the "Green IT initiative" for being compatible with economic growth and environmental protection. Not only energy saving technologies but energy saving systems have been developed for accomplishing sustainable development. Korea's CO2 emission and energy consumption continuously have grown at comparatively high rates. They are related to its industrial structure depending on high energy-consuming industries such as iron and steel Industry, automotive industry, shipbuilding industry, semiconductor industry, and so on. In particular, export proportion of IT manufacturing is quite high in Korea. For example, the global market share of the semiconductor such as DRAM was about 80% in 2008. Accordingly, Korea needs to establish a systematic strategy to respond to the global environmental regulations and to maintain competitiveness in the IT industry. However, green competitiveness of Korea ranked 11th among 15 major countries and R&D budget for green technology is not large enough to develop energy-saving technologies for infrastructure and value chain of low-carbon society though that grows at high rates. Moreover, there are no concrete action plans in Korea. This research aims to deduce the priorities of the Korean green business/IT strategies to use multi attribute weighted average method. We selected a panel of 19 experts who work at the green business related firms such as HP, IBM, Fujitsu and so on, and selected six assessment indices such as the urgency of the technology development, the technology gap between Korea and the developed countries, the effect of import substitution, the spillover effect of technology, the market growth, and the export potential of the package or stand-alone products by existing literature review. We submitted questionnaires at approximately weekly intervals to them for priorities of the green business/IT strategies. The strategies broadly classify as follows. The first strategy which consists of the green business/IT policy and standardization, process and performance management and IT industry and legislative alignment relates to government's role in the green economy. The second strategy relates to IT to support environment sustainability such as the travel and ways of working management, printer output and recycling, intelligent building, printer rationalization and collaboration and connectivity. The last strategy relates to green IT systems, services and usage such as the data center consolidation and energy management, hardware recycle decommission, server and storage virtualization, device power management, and service supplier management. All the questionnaires were assessed via a five-point Likert scale ranging from "very little" to "very large." Our findings show that the IT to support environment sustainability is prior to the other strategies. In detail, the green business /IT policy and standardization is the most important in the government's role. The strategies of intelligent building and the travel and ways of working management are prior to the others for supporting environment sustainability. Finally, the strategies for the data center consolidation and energy management and server and storage virtualization have the huge influence for green IT systems, services and usage This research results the following implications. The amount of energy consumption and CO2 emissions of IT equipment including electrical business equipment will need to be clearly indicated in order to manage the effect of green business/IT strategy. And it is necessary to develop tools that measure the performance of green business/IT by each step. Additionally, intelligent building could grow up in energy-saving, growth of low carbon and related industries together. It is necessary to expand the affect of virtualization though adjusting and controlling the relationship between the management teams.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.134-138
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• 2006

Depression is the most common and widespread mood disorder. About 20% of the population might suffer a major, incapacitating episode of depression during their lifetime. This disorder can be classified into two types: major depressive disorders and bipolar disorder. Since pharmaceutical treatments are different according to types of depression disorders, correct and fast classification is quite critical for depression patients. Yet, classical statistical method, such as minnesota multiphasic personality inventory (MMPI), have some difficulties in applying to depression patients, because the patients suffer from concentration. We used electroencephalogram (EEG) analysis method fer classification of depression. We extracted nonlinearity of information flows between channels and estimated approximate entropy (ApEn) for the EEG at each channel. Using these attributes, we applied two types of data mining classification methods: decision tree and possibilistic support vector machines (PSVM). We found that decision tree showed 85.19% accuracy and PSVM exhibited 77.78% accuracy for classification of depression, 30 patients with major depressive disorder and 24 patients having bipolar disorder.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.481-488
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• 2008

This study examined the relationship of what kind of creative thinking has related factors for emotion design products in order to let consumers focusing on the successful cases of emotion products. For the design creativity attribute used in this experiment, the design evaluation creativity tools revealed by Kim Eun-Ju's 2007 design creativity evaluation tool development were used mostly and of the 12 most common emotion products and general product, MP3s, which have various forms, functions and sizes were selected as the target for experiment. Results of the experiment showed that for design creativeness items of all emotional products, vision creation, favorableness, convenience, practicality and being purchasable were relevant, while for MP3, uniqueness, favorableness and convenience were relevant. Accordingly, the common features of design creativeness items for emotional products were identified. When summing up the contents of the two experiments above, for emotional designs, the interest level of uniqueness for the design creativity evaluation items and the functional items for practicality had a high level of relativity. Therefore, there is a need to examine the common features between the design creativity items for general products other than MP3s in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.381-392
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• 2011

Pollutant loads calculated with unit factor method can not identity seasonal variations of pollutant inputs. Estimation of pollutant loads considering rainfall runoff can overcome these limits. SCS curve number method was applied to estimate runoff of each event of Koeup watershed of Koheung estuary lake. SCS curve numbers were calculated based upon land use, soil types of the catchment using GIS. Point and nonpoint source pollutant loads were summed up for total loads estimation. Those from nonpoint source were estimated by multiplying the calculated runoff and expected mean concentrations (EMC) presented by the Minister of Environment of Korea. DEM can present three dimensional views of a terrain, identity stream networks and flow accumulation. Furthermore, it can examine accumulated pollutant loads of specific point of a catchment. Therefore, cell based pollutant load estimation was attempted using DEM. ArcView was utilized to collect, store and manipulate spatial and attribute data of pollutant sources and features of the catchment. Cell-based DEM which was established by the GRID module of ARC/INFO was employed to estimate flows and pollutant loads.

• Analytical Science and Technology
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• v.26 no.6
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• pp.401-406
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• 2013

Oxygen($O_2$) consumption and carbon dioxide($CO_2$) excretion of a fertile chicken egg during incubation were measured by a gas mass spectrometer. A closed sample chamber was developed to collect gas samples during the 20 days of artificial incubation of both a fertile and an infertile egg. After leaving an egg in the sample chamber for an hour, using a gas-tight syringe, samples of 2 mL of gas were collected from the closed sample chamber and analyzed using a gas mass spectrometer in 2~4 day intervals. The $O_2$ consumption and $CO_2$ excretion of chicken embryos increased rapidly after 10 days from the starting point of incubation. After 20 days, 23 mL of $O_2$ was consumed and 16 mL of $CO_2$ was excreted per hour. Throughout the whole period of incubation, concentration of $O_2$ decreased 4.3 mol% and $CO_2$ increased only 3.1 mole%, i.e., the mole of consumed $O_2$ and the mole of excreted $CO_2$ were not the same. On the other hand, during the same period, concentration of $N_2$ increased about 1.3 mol% and the increased mole fraction of $N_2$ was comparable with the difference (1.2 mol%) between the mole fraction of consumed $O_2$ and excreted $CO_2$. Therefore, we can attribute the increase of $N_2$ mole% to the difference of mole fraction between consumed $O_2$ and excreted $CO_2$. In this study, through the analysis of gas, we could explain the respiration of a fertile chicken egg during incubation.

• Spatial Information Research
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• v.11 no.1
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• pp.41-60
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• 2003

It is noted that the paper mapping system for University Building Facility has many limitations in terms of data maintenance, real-time GIS data acquisition, and economic efficiency. The aim of this research was to evaluate an operational potential of an on site real-time mobile GIS technique to resolve the problem faced in the university. The idea is based upon the recent trends in the field of 'Telecommunication and Information Technology' that uses a PDA (personal Digital Assistants), wireless network computing, mobile computing, etc. A real time mobile GIS approach has been adopted, in which a PDA is linked to a wireless internet and field workers record data on the computer at the site and analyse data on site. While there should be a considerable number and variety of factors associated with real-time mobile GIS quality, this research focuses on three criteria that are identified as fundamental to customer requirements; (1) data quarry (2) spatial analysis (3) real-time GIS database building. 'Art--empirical study for a case study facility has been conducted to confirm the validity for the system. The system has been checked experimentally, enabled the field users to quarry the data required simply and execute spatial analysis (buffer, overlay etc.,) accommodating versatile alternatives on the site. Detailed visual maps can be generated over large areas quickly and easily. The PDA interface, in particular, were ideally suited for field users to interactively displaying positional information with attribute data. This system has shown to be quite convenient to maintaining a highly reliable database since it could playa crucial role in documenting at real-time basis temporal and spatial changes occurred in the facilities. It is anticipated that this research output will greatly serve to introduce the reliable and cost-effective facility mapping system in the university by overcoming serious constraints suffered from the past non-real time mobile GIS approach.