• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.207-216
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• 2000

Due to recent growing interest in autonomous software agents and their potential application in areas such as electronic commerce, the autonomous negotiation become more important. Evidence from both theoretical analysis and observations of human interactions suggests that if decision makers have prior information on opponents and furthermore learn the behaviors of other agents from interaction, the overall payoff would increase. We propose a new methodology for a strategy finding process using data mining in autonomous negotiation system ; ANSIA (Autonomous Negotiation System using Intelligent Agent). ANSIA is a strategy based negotiation system. The framework of ANSIA is composed of following component layers : 1) search agent layer, 2) data mining agent layer and 3) negotiation agent layer. In the data mining agent layer, that plays a key role as a system engine, extracts strategy from the historic negotiation is extracted by competitive learning in neural network. In negotiation agent layer, we propose the autonomous negotiation process model that enables to estimate the strategy of opponent and achieve interactive settlement of negotiation. ANISIA is motivated by providing a computational framework for negotiation and by defining a strategy finding model with an autonomous negotiation process.

• Asian Journal of Innovation and Policy
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• v.9 no.1
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• pp.36-55
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• 2020

Climate change is one of the most discussed issues in international for a today. Evaluating the effect of climate change at a regional level and setting up an appropriate policy to address the issues associated with climate change require a proper evaluation process on the climate change and adaptation projects already implemented. Although various evaluation approaches to climate change adaptation programs have been proposed, it is rare to find a proper systematic approach to evaluating the reliability of those climate change adaptation programs. In the current situation regarding the system to evaluate climate change adaptation programs, the purpose of this study is to suggest a theoretical and standardized evaluation system on the reliability of climate change adaptation schemes. The new approach suggested in this paper will be appropriate when requiring a confidence level for adaptation programs that are specially localized and categorized. Using various quantitative and qualitative evaluation methods with the inherent reality mechanism, we provide a conceptual framework to measure the reliability of climate change adaptation programs with a flexible adjustment process. With the proposed framework, it is possible to provide the level of confidence on the results collected from the evaluation systems and construct a standardized, system-wide assessment procedure toward climate change adaptation policies. By applying this approach based on scientific evidence on the reliability of climate change adaptation policies, appropriate and efficient climate change adaptation programs will be properly designed for and implemented in Korea.

• Archives of Plastic Surgery
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• v.33 no.1
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• pp.53-60
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• 2006

The current authors performed two-stage ear reconstruction of microtia using autogenous costal cartilage combined with canaloplasty of the acoustic meatus in a team approach. In the first stage, lobule transposition, fabrication of the cartilage framework, and implantation of the framework were peformed. In the second stage, elevation of the auricle, cartilage graft for posterior auricular sulcus, coverage with the mastoid fascia flap and skin graft, and concha excavation were performed. The canaloplasty was combined simultaneously in patients with radiologic and audiometric evidence of cochlear function in the second stage. A total of 36 consecutive patients with congenital microtia were treated from 1998 to 2003. Among them, 27 patients(male: 18, female: 9) ranging from 7 to 43 years old were combined with canaloplasty. The follow-up period was one year to 5 years. Thirteen patients exhibited improved hearing over 30 dB PTA(pure tone average), 9 patients below 30 dB, and 5 patients with no improvement. Complications related to the canaloplasty were chronic drainages of the auditory meatus and meatal stenosis. Lobule type deformity combined with the canaloplasty showed higher complications than concha type. Therefore, in the lobule type, meticulous manipulation is necessary to reduce complications after the canaloplasty.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.327-348
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• 2008

A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.40.4-41
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• 2018

The current 'standard model' of cosmology provides a minimal theoretical framework that can explain the gaussian, nearly scale-invariant density perturbations observed in the CMB to the late time clustering of galaxies. However accepting this framework, requires that we include within our cosmic inventory a vacuum energy that is ~122 orders of magnitude lower than Quantum Mechanical predictions, or alternatively a new scalar field (dark energy) that has negative pressure. An alternative approach to adding extra components to the Universe would be to modify the equations of Gravity. Although GR is supported by many current observations there are still alternative models that can be considered. Recently there have been many works attempting to test for modified gravity using the large scale clustering of galaxies, ISW, cluster abundance, RSD, 21cm observations, and weak lensing. In this work, we compare various modified gravity models using cosmic shear data from the Deep Lens Survey as well as data from CMB, SNe Ia, and BAO. We use the Bayesian Evidence to quantify the comparison robustly, which naturally penalizes complex models with weak data support. In this talk we present our methodology and preliminary results that show f(R) gravity is mildly disfavoured by the data.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.931-941
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• 2021

The study focuses on the relationship between SB, corporate social responsibility (CSR), and the emerging economy. Thereafter it highlights the types, principles, and funding cycle of SB with the evidence from Grameen Bank, which is a globally well-recognized microfinance venture in Bangladesh established by the Nobel Laureate Dr. Muhammad Yunus. This study employs qualitative analysis to illustrate an architectural overview of the SB model by collecting secondary data from various publications related to the topic and published data of Grameen Bank. Finally, this paper illustrates the SB model along with specified characteristics, systematic framework, and main approaches for sustainable context, which could be applied as a conceptual framework for SB in any context of the emerging economy. The findings of this study suggest that the SB model is the workflow having a hierarchy of five phases namely need identification, goal setting, solution-based business plan, business plan assessment, and business plan execution. Analyzing a range of social business interventions in a developing country, Bangladesh, through the lens of five key aspects demonstrates that social business is the most efficient way to sustainably maximize the social benefits and minimize specific social issues poverty of the people affected.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.183-193
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• 2023

This paper proposes and examines the economic impact of infrastructure improvement on the San-En-Nanshin region in the Chubu area of Japan. We develop a single transportation computable general equilibrium (CGE) model for each subregion within the San-En-Nanshin region. The explicit modeling of the transportation infrastructure is defined based on interregional commuting flows and business trips, considering the spatial structure of the San-En-Nanshin economy. A CGE model is integrated with an interregional transportation network model to enhance the framework's potential for understanding the infrastructure's role in regional development. To evaluate the economic impact of transportation improvement, we analyze the interrelationship between travel time savings and regional output and income. The economic impact analysis under the CGE framework reveals how transportation facilities and systems affect firm and household behavior and therefore induce changes in the production and consumption of commodities and transportation services. The proposed theoretical model was tested by using data from the 2005 IO tables of each subregion and the 2006 transport flow dataset issued by the Ministry of Land, Infrastructure, Transport, and Tourism in Japan. As a result, the paper confirms the positive effect of transportation investment on the total output and income of the studied region. Specifically, we found that while economic benefits typically appear in urban areas, rural areas can still potentially benefit from transportation improvement projects.

• Smart Structures and Systems
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• v.29 no.2
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.65-78
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• 2023

Investigations on information security factors re- main elusive at small and medium enterprises (SMEs), es- specially for custom-made software solutions. This article aims to investigate, classify, adopt factors from recent literature addressing information security resources. SMEs al- ready have information security in place, but they are not easy to adopt through the negotiation processes between the in-house software development companies and custom-made software clients at SMEs. This article proposes a strategic framework for implementing the process of adoption of the information security factors at SMEs after conducting a systematic snapshot approach for investigating and classifying the resources. The systematic snapshot was conducted using a search strategy with inclusion and exclusion criteria to retain 128 final reviewed papers from a large number of papers within the period of 2001-2022. These papers were analyzed based on a classification schema including management, organizational, development, and environmental categories in software development lifecycle (SDLC) phases in order to define new security factors. The reviewed articles addressed research gaps, trends, and common covered evidence-based decisions based on the findings of the systematic mapping. Hence, this paper boosts the broader cooperation between in-house software development companies and their clients to elicit, customize, and adopt the factors based on clients' demands.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.1-12
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• 2023

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.