• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.205-214
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• 2019

This paper aims to discover factors and their influences degree to repurchase organic cosmetic in Vietnam. In addition, this research also discloses the main segments that have high demand re-buying intention based on demographic groups of gender, age, income, educational level, job, type of products, and place of production. Twenty-eight scale was designed based on previous studies and adjusted to match the 5-point Likert scale to conduct measurement. By using survey method to test hypotheses and set up conceptual models to collect 295 Vietnamese consumers who have experience in consuming organic cosmetic by explain the results through Smart PLS software. The findings show that there is positive attitude of customers to the intention of acquiring organic cosmetics, green perceived and customer satisfaction. In addition, customer satisfaction, knowledge of products, safety values, and environmental protection consciousness also play important roles to form a positive attitude of customers for products. Moreover, the consciousness of green living of consumers accounts for a high proportion in creating customer satisfaction for organic products. The results show useful information for current premises to determine the factors that influence the decision to repurchase organic cosmetic product, that provide business strategies.

• Korean System Dynamics Review
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• v.7 no.2
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• pp.57-80
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• 2006

Nuclear technology made a great contribution to the national economy and society by localization of nuclear power plant design, and by stabilization of electricity price, etc. It is very important to conduct the retrospective analysis for the nuclear technology contribution to the national economy and society, but it is more important to conduct prospective analysis for the nuclear technology contribution. The term "technology value" is often used in the prospective analysis to value the result of technology development. There are various definitions of technology value, but generally it means the increment of future revenue or the reduction of future cost by technology development. These technology valuation methods are widely used in various fields (information technology or energy technology, etc). The main objective of this research is to develop valuation methodology that represents unique characteristics of nuclear power technology. The valuation methodology that incorporates market share changes of generation technologies was developed. The technology valuation model which consists of five modules (electricity demand forecast module, technology development module, market share module, electricity generation module, total cost module) to incorporate market share changes of generation technologies was developed. The nuclear power technology value assessed by this technology valuation model was 3 times more than the value assessed by the conventional method. So it was confirmed that it is very important to incorporates market share changes of generation technologies. The valuation results of nuclear power technology in this study can be used as policy data for ensuring the benefits of nuclear power R&D (Research and Development) investment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.10-19
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• 2003

As the technical demand for biometrics is increasing, users expect that fingerprint recognition systems are operable with various fingerprint readers. However, current commercial off-the-shelf fingerprint recognition systems are no interoperable due to the lack of standardization in application program interfaces for fingerprint readers. A cross-matching fingerprint recognition system is a person authentication system based on fingerprints and utilizing different types of fingerprint readers. It should be able to overcome variations in fingerprint images acquired by different readers, such as the size, resolution, contrast of images. The purpose of this research is to develop across-matching fingerprint recognition system for fingerprint research of different sensing mechanism. The fingerprint readers tested in this study are optical, semiconductor and thermal sensor modules, and the prpoposed cross-matching system utilizes both a minutiae-based similarity and a ridge count-based similarity in matching fingerprint images acquired by different sensors.

• Earthquakes and Structures
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• v.4 no.3
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• pp.299-324
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• 2013

The current research focuses on the seismic vulnerability assessment of typical Southern Europe buildings, based on processing of a large set of observational damage data. The presented study constitutes a sequel of a previous research. The damage statistics have been enriched and a wider damage database (178578 buildings) is created compared to the one of the first presented paper (73468 buildings) with Damage Probability Matrices (DPMs) after the elaboration of the results from post-earthquake surveys carried out in the area struck by the 7-9-1999 near field Athens earthquake. The dataset comprises buildings which developed damage in several degree, type and extent. Two different parameters are estimated for the description of the seismic demand. After the classification of damaged buildings into structural types they are further categorized according to the level of damage and macroseismic intensity. The relative and the cumulative frequencies of the different damage states, for each structural type and each intensity level, are computed and presented, in terms of damage ratio. Damage Probability Matrices (DPMs) are obtained for typical structural types and they are compared to existing matrices derived from regions with similar building stock and soil conditions. A procedure is presented for the classification of those buildings which initially could not be discriminated into structural types due to restricted information and hence they had been disregarded. New proportional DPMs are developed and a correlation analysis is fulfilled with the existing vulnerability relations.

• Journal of Distribution Science
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• v.13 no.6
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• pp.11-15
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• 2015

Purpose - Robot path planning, a constrained optimization problem, has been an active research area with many methods developed to tackle it. This study proposes the use of a Rapidly-exploring Random Tree and Particle Swarm Optimizer algorithm for path planning. Research design, data, and methodology - The grid method is built to describe the working space of the mobile robot, then the Rapidly-exploring Random Tree algorithm is applied to obtain the global navigation path and the Particle Swarm Optimizer algorithm is adopted to obtain the best path. Results - Computer experiment results demonstrate that this novel algorithm can rapidly plan an optimal path in a cluttered environment. Successful obstacle avoidance is achieved, the model is robust, and performs reliably. The effectiveness and efficiency of the proposed algorithm is demonstrated through simulation studies. Conclusions - The findings could provide insights to the validity and practicability of the method. This method makes it is easy to build a model and meet real-time demand for mobile robot navigation with a simple algorithm, which results in a certain practical value for distribution environments.

• Journal of the Korean Ceramic Society
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• v.55 no.5
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• pp.407-418
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• 2018

Increasing demand for portable and wireless electronic devices with high power and energy densities has inspired global research to investigate, in lieu of scarce rare-earth and expensive ruthenium oxide-like materials, abundant, cheap, easily producible, and chemically stable electrode materials. Several potential electrode materials, including carbon-based materials, metal oxides, metal chalcogenides, layered metal double hydroxides, metal nitrides, metal phosphides, and metal chlorides with above requirements, have been effectively and efficiently applied in electrochemical supercapacitor energy storage devices. The synthesis of self-grown, or in-situ, nanostructured electrode materials using chemical processes is well-known, wherein the base material itself produces the required phase of the product with a unique morphology, high surface area, and moderate electrical conductivity. This comprehensive review provides in-depth information on the use of self-grown electrode materials of different morphologies in electrochemical supercapacitor applications. The present limitations and future prospects, from an industrial application perspectives, of self-grown electrode materials in enhancing energy storage capacity are briefly elaborated.

• Asia Pacific Journal of Business Review
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• v.5 no.2
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• pp.19-44
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• 2021

Sub Saharan Africa (SSA) is receiving increased investments in the energy sector under the belt and road initiative (BRI) project since its inception in 2013. SSA has a worse energy efficiency ratio coupled with deficient electricity access, through analysis showed varied impacts on the SSA countries due to the BRI initiative. This study dilves into the influencing factors for Energy Efficiency (EE) in 38 SSA countries, applying the probit and logit approach for 2000-2018. The Multiple-regression model shows significant results of some variables such as foreign direct investment, gross domestic product, and port infrastructure quality being significant on EE under BRI initiative countries. However, the logit and probit models produce similar results and the marginal effect for the entire variable, except energy imports that do not likely impact EE. Furthermore, the interaction of quality of port infrastructure and foreign direct investment variables produces significant results, highlighting the increased investments SSA receives under the BRI initiative in the energy and transport sectors. The model Percent correctly predicted (PCP) value was about 84%, indicating it correctly classified the variables and about 16% not classified. The study recommends EE performance standards should be incorporated on energy projects in SSA to ensure that these projects are energy efficient and decouple SSA's energy demand from economic growth. The research proffers suggestions for policy regarding the BRI initiative in SSA and the implications on sustainable energy and building a community with a shared future.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1-7
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• 2007

New Zealand is a hydrologically diverse and active country. This paper presents an overview of the major hydrological issues and problems facing New Zealand and provides examples of some the research being undertaken to solve the problems. Fundamental to any environmental decision making is the provision of good quality hydrometric data. Reduced funding for the national hydrometric network has meant a reduction in the number of monitoring sites, the decision on how to redesign the network was made using information on geographic coverage and importance of each site. New Zealand faces a major problem in understanding the impacts of rapid land use change on water quantity and quality. On top of the land use change is overlain the issue of agricultural intensification. The transfer of knowledge about impacts of change at the small watershed scale to much larger, more complex watersheds is one that is attracting considerable research attention. There is a large amount of research currently being undertaken to understand the processes of water and nutrient movement through the vadose zone into groundwater and therefore understanding the time taken for leached nutrients to reach receiving water bodies. The largest water management issue of the past 5 years has been based around fair and equitable water allocation when there is increasing demand for irrigation water. Apart from policy research into market trading for water there has been research into water storage and transfer options and improving irrigation efficiency. The final water management issue discussed concerns the impacts of hydrological extremes (floods and droughts). This is of particular concern with predictions of climate change for New Zealand suggesting increased hydrological extremes. Research work has concentrated on producing predictive models. These have been both detailed inundation models using high quality LIDAR data and also flood models for the whole country based on a newly interpolated grid network of rainfall.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.87-100
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• 2016

The acquisition of the forest resource information has depended on a partial sampling method or aerial photographs which demand a lot of effort and time because of the vast areas and the difficult approach. For the acquisition of the forest resource information, there have been the optical remote-sensing and the multi-spectrum image to offer only horizontal distributions of trees, but a new technological approach, such as Airborne LiDAR, is more necessary to acquire directly three dimensional information related to the forest terrains and trees' features. This paper proposes an algorithm for the forest information extraction such as trees' individual numbers and the heights of trees by using LiDAR data. Especially, this proposed algorithm adopts a region growing method for the extraction of the vegetation-point and extracts the forest information using morphological features of trees.