• Economic and Environmental Geology
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• v.55 no.4
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• pp.353-366
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• 2022

Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

• Journal of the Korean Geotechnical Society
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• v.22 no.9
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• pp.45-59
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• 2006

The successful performance of any numerical geotechnical simulation depends on the accuracy and efficiency of the numerical implementation of constitutive model used to simulate the stress-strain (constitutive) response of the soil. The corner stone of the numerical implementation of constitutive models is the numerical integration of the incremental form of soil-plasticity constitutive equations over a discrete sequence of time steps. In this paper a well known two-surface soil plasticity model is implemented using a generalized implicit return mapping algorithm to arbitrary convex yield surfaces referred to as the Closest-Point-Projection method (CPPM). The two-surface model describes the nonlinear behavior of coarse-grained materials by incorporating a bounding surface concept together with isotropic and kinematic hardening as well as fabric formulation to account for the effect of fabric formation on the unloading response. In the course of investigating the performance of the CPPM integration method, it is proven that the algorithm is an accurate, robust, and efficient integration technique useful in finite element contexts. It is also shown that the algorithm produces a consistent tangent operator $\frac{d\sigma}{d\varepsilon}$ during the iterative process with quadratic convergence rate of the global iteration process.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.610-620
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• 2022

An acoustic vector sensor can simultaneously receive vector quantities, such as particle velocity and acceleration, as well as acoustic pressure at one location, and thus it can be used as a single input multiple output receiver in underwater acoustic communication systems. On the other hand, vector signals received by a single vector sensor have different channel characteristics due to the azimuth angle between the source and receiver and the difference in propagation angle of multipath in each component, producing different communication performances. In this paper, we propose a channel parameter-based weighting method to improve the performance of an acoustic communication system using a single vector sensor. To verify the proposed method, we used communication data collected from the experiment conducted during the KOREX-17 (Korea Reverberation Experiment). For communication demodulation, block-based time reversal technique which is robust against time-varying channels were utilized. Finally, the communication results showed that the effectiveness of the channel parameter-based weighting method for the underwater communication system using a single vector sensor was verified.

• Membrane Journal
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• v.32 no.1
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• pp.43-49
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• 2022

Solid-state supercapacitors with high safety and robust mechanical properties are attracting global attention as next-generation energy storage devices. As an electrode of a supercapacitor, an economical carbon-based electrode is widely used. However, when an aqueous electrolyte is introduced, the charge transfer resistance increases because the interfacial contact between the hydrophobic electrode surface and aqueous electrolyte is not good. In this regard, we propose a method to obtain higher electrochemical performance based on improved interfacial properties by treating the electrode surface with oxygen plasma. The surface hydrophilization induced by the enriched oxygen functionalities was confirmed by the contact angle measurement. As a result, the degree of hydrophilization was easily adjusted by controlling the power and duration of the oxygen plasma treatment. As the electrolyte of the supercapacitor, PVA/H₃PO₄, which is a typical solid-state aqueous electrolyte, was used. Free-standing membranes of PVA/H₃PO₄ electrolyte were prepared and then pressed onto the electrode. The optimal condition was to perform oxygen plasma treatment for 5 seconds with a low power of 15 W, and the energy density of the supercapacitor increased by about 8%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.745-752
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• 2009

Management of social infrastructure has been advanced from facility management (FM) to asset management (AM), which adopts the aggressive and proactive methods in predicting the deterioration of infrastructure, prevents failures, and eventually saves maintenance cost. Infrastructure asset management is not a simple engineering technique, but it is a new paradigm evolved from facility management practices. To implement the infrastructure asset management successfully, organizational reform is very important. This paper suggests critical success factors and key performance indicators to implement the infrastructure asset management for facility managers of government owned social infrastructures such as roads and bridges. Reorganizing the facility management group requires new vision, objectives, strategies for the paradigm-changing asset management. This paper uses Balanced Score Card (BSC) which is a proven method in measuring and setting new objectives for an organization. Once the performance indicators are reviewed repeatedly by facility managers through experts workshops, developed BSC can be used in practice. This paper discusses the development of robust BSC scoring method through in depth literature reviews and investigation of asset management practices of domestic and international cases.

• Imaging Science in Dentistry
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• v.54 no.1
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• pp.81-91
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• 2024

Purpose: The objective of this study was to propose a deep-learning model for the detection of the mandibular canal on dental panoramic radiographs. Materials and Methods: A total of 2,100 panoramic radiographs (PANs) were collected from 3 different machines: RAYSCAN Alpha (n=700, PAN A), OP-100 (n=700, PAN B), and CS8100 (n=700, PAN C). Initially, an oral and maxillofacial radiologist coarsely annotated the mandibular canals. For deep learning analysis, convolutional neural networks (CNNs) utilizing U-Net architecture were employed for automated canal segmentation. Seven independent networks were trained using training sets representing all possible combinations of the 3 groups. These networks were then assessed using a hold-out test dataset. Results: Among the 7 networks evaluated, the network trained with all 3 available groups achieved an average precision of 90.6%, a recall of 87.4%, and a Dice similarity coefficient (DSC) of 88.9%. The 3 networks trained using each of the 3 possible 2-group combinations also demonstrated reliable performance for mandibular canal segmentation, as follows: 1) PAN A and B exhibited a mean DSC of 87.9%, 2) PAN A and C displayed a mean DSC of 87.8%, and 3) PAN B and C demonstrated a mean DSC of 88.4%. Conclusion: This multi-device study indicated that the examined CNN-based deep learning approach can achieve excellent canal segmentation performance, with a DSC exceeding 88%. Furthermore, the study highlighted the importance of considering the characteristics of panoramic radiographs when developing a robust deep-learning network, rather than depending solely on the size of the dataset.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.28-35
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• 2024

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.83-93
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• 2002

To improve the performance of estimation, the research that uses additional information addition to traffic count and target OD with additional survey cost have been studied. The purpose of this paper is to improve the performance of OD estimation by reducing the feasible solutions with cost-efficiently additional information addition to traffic counts and target OD. For this purpose, we Propose the OD estimation method with sample link use proportion as additional information. That is, we obtain the relationship between OD trip and link flow from sample link use proportion that is high reliable information with roadside survey, not from the traffic assignment of target OD. Therefore, this paper proposes OD estimation algorithm in which the conservation of link flow rule under the path-based non-equilibrium traffic assignment concept. Numerical result with test network shows that it is possible to improve the performance of OD estimation where the precision of additional data is low, since sample link use Proportion represented the information showing the relationship between OD trip and link flow. And this method shows the robust performance of estimation where traffic count or OD trip be changed, since this method did not largely affected by the error of target OD and the one of traffic count. In addition to, we also propose that we must set the level of data precision by considering the level of other information precision, because "precision problem between information" is generated when we use additional information like sample link use proportion etc. And we Propose that the method using traffic count as basic information must obtain the link flow to certain level in order to high the applicability of additional information. Finally, we propose that additional information on link have a optimal counting location problem. Expecially by Precision of information side it is possible that optimal survey location problem of sample link use proportion have a much impact on the performance of OD estimation rather than optimal counting location problem of link flow.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.39-59
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• 2007

The international involvement of a firm has been described as a gradual development process "a process in which the enterprise gradually increases its international involvement in many studies. This process evolves in the interplay between the development of knowledge about foreign markets and operations on one hand and increasing commitment of resources to foreign markets on the other." On the basis of Uppsala internationalization model, many studies strengthen strong theoretical and empirical support. According to the predictions of the classic stages theory, the internationalization process of firms have been recognized and characterized gradual evolution to foreign markets, so called stage theory: indirect & direct export, strategic alliance and foreign direct investment. However, termed "international new ventures" (McDougall, Shane, and Oviatt 1994), "born globals" (Knight 1997; Knight and Cavusgil 1996; Madsen and Servais 1997), "instant internationals" (Preece, Miles, and Baetz 1999), or "global startups" (Oviatt and McDougall 1994) have been used and come into spotlight in internationalization study of technology intensity venture companies. Recent researches focused on venture company have suggested the phenomenons of 'born global' firms as a contradiction to the stages theory. Especially the article by Oviatt and McDougall threw the spotlight on international entrepreneurs, on international new ventures, and on their importance in the globalising world economy. Since venture companies have, by definition. lack of economies of scale, lack of resources (financial and knowledge), and aversion to risk taking, they have a difficulty in expanding their market to abroad and pursue internalization gradually and step by step. However many venture companies have pursued 'Born Global Strategy', which is different from process strategy, because corporate's environment has been rapidly changing to globalization. The existing studies investigate that (1) why the ventures enter into overseas market in those early stage, even in infancy, (2) what make the different international strategy among ventures and the born global strategy is better to the infant ventures. However, as for venture's performance(growth and profitability), the existing results do not correspond each other. They also, don't include marketing strategy (differentiation, low price, market breadth and market pioneer) that is important factors in studying of BGV's performance. In this paper I aim to delineate the appearance of international new ventures and the phenomenons of venture companies' internationalization strategy. In order to verify research problems, I develop a resource-based model and marketing strategies for analyzing the effects of the born global venture firms. In this paper, I suggested 3 research problems. First, do the korean venture companies take some advantages in the aspects of corporate's performances (growth, profitability and overall market performances) when they pursue internationalization from inception? Second, do the korean BGV have firm specific assets (foreign experiences, foreign orientation, organizational absorptive capacity)? Third, What are the marketing strategies of korean BGV and is it different from others? Under these problems, I test then (1) whether the BGV that a firm started its internationalization activity almost from inception, has more intangible resources(foreign experience of corporate members, foreign orientation, technological competences and absorptive capacity) than any other venture firms(Non_BGV) and (2) also whether the BGV's marketing strategies-differentiation, low price, market diversification and preemption strategy are different from Non_BGV. Above all, the main purpose of this research is that results achieved by BGV are indeed better than those obtained by Non_BGV firms with respect to firm's growth rate and efficiency. To do this research, I surveyed venture companies located in Seoul and Deajeon in Korea during November to December, 2005. I gather the data from 200 venture companies and then selected 84 samples, which have been founded during 1999${\sim}$2000. To compare BGV's characteristics with those of Non_BGV, I also had to classify BGV by export intensity over 50% among five or six aged venture firms. Many other researches tried to classify BGV and Non_BGV, but there were various criterion as many as researchers studied on this topic. Some of them use time gap, which is time difference of establishment and it's first internationalization experience and others use export intensity, ration of export sales amount divided by total sales amount. Although using a mixed criterion of prior research in my case, I do think this kinds of criterion is subjective and arbitrary rather than objective, so I do mention my research has some critical limitation in the classification of BGV and Non_BGV. The first purpose of research is the test of difference of performance between BGV and Non_BGV. As a result of t-test, the research show that there are statistically efficient difference not only in the growth rate (sales growth rate compared to competitors and 3 years averaged sales growth rate) but also in general market performance of BGV. But in case of profitability performance, the hypothesis that is BGV is more profit (return on investment(ROI) compared to competitors and 3 years averaged ROI) than Non-BGV was not supported. From these results, this paper concludes that BGV grows rapidly and gets a high market performance (in aspect of market share and customer loyalty) but there is no profitability difference between BGV and Non_BGV. The second result is that BGV have more absorptive capacity especially, knowledge competence, and entrepreneur's international experience than Non_BGV. And this paper also found BGV search for product differentiation, exemption strategy and market diversification strategy while Non_BGV search for low price strategy. These results have never been dealt with other existing studies. This research has some limitations. First limitation is concerned about the definition of BGV, as I mentioned above. Conceptually speaking, BGV is defined as company pursue internationalization from inception, but in empirical study, it's very difficult to classify between BGV and Non_BGV. I tried to classify on the basis of time difference and export intensity, this criterions are so subjective and arbitrary that the results are not robust if the criterion were changed. Second limitation is concerned about sample used in this research. I surveyed venture companies just located in Seoul and Daejeon and also use only 84 samples which more or less provoke sample bias problem and generalization of results. I think the more following studies that focus on ventures located in other region, the better to verify the results of this paper.