• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Progress in Medical Physics
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• v.18 no.1
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• pp.48-54
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• 2007

This study is to develope a phantom for MOSFET (Metal Oxide Semiconductors Field Effect Transistors) dosimetry and compare the dosimetric properties of standard MOSFET and microMOSFET with the phantom. In this study, the developed phantom have two shape: one is the shape of semi-sphere with 10cm diameters and the other one is the flat slab of $30{\times}30cm$with 1 cm thickness. The slab phantom was used for calibration and characterization measurements of reproducibility, linearity and dose rate dependency. The semi-sphere phantom was used for angular and directional dependence on the types of MOSFETs. The measurements were conducted under $10{\times}10cm^2$ fields at 100cm SSD with 6MV photon of Clinac (21EX, Varian, USA). For calibration and reproducibility, five standard MOSFETS and microMOSFETs were repeatedly Irradiated by 200cGy five times. The average calibration factor was a range of $1.09{\pm}0.01{\sim}1.12{\pm}0.02mV/cGy$ for standard MOSFETS and $2.81{\pm}0.03{\sim}2.85{\pm}0.04 mV/cGy$ for microMOSFETs. The response of reproducibility in the two types of MOSFETS was found to be maximum 2% variation. Dose linearity was evaluated In the range of 5 to 600 cGy and showed good linear response with $R^2$ value of 0.997 and 0.999. The dose rate dependence of standard MOSFET and microMOSFET was within 1% for 200 cGy from 100 to 500MU/min. For linearity, reproducibility and calibration factor, two types of MOSFETS showed similar results. On the other hand, the standard MOSFET and microMOSFET were found to be remarkable difference in angular and directional dependence. The measured angular dependence of standard MOSFET and microMOSFET was also found to be the variation of 13%, 10% and standard deviation of ${\pm}4.4%,\;{\pm}2.1%$. The directional dependence was found to be the variation of 5%, 2% and standard deviation of ${\pm}2.1%,\;{\pm}1.5%$. Therefore, dose verification of radiation therapy used multidirectional X-ray beam treatments allows for better the use of microMOSFET which has a reduced angular and directional dependence than that of standard MOSFET.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.2
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• pp.197-205
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• 2015

Offshore structures for the gas production are exposed to the risk of gas leaks, and gas explosions can result in fatal damages to the primary structures as well as secondary structures. To minimize the damage from the critical accidents, the study of the dynamic response of structural members subjected to blast loads must be conducted. Furthermore, structural dynamic analysis has to be performed considering relationships between the natural frequency of structural members and time duration of the explosion loading because the explosion pressure tends to increase and dissipate within an extremely short time. In this paper, the numerical model based on time history data were proposed considering the negative phase pressure in which considerable negative phase pressures were observed in CFD analyses of gas explosions. The undamped single degree of freedom(SDOF) model was used to characterize the dynamic response under the blast loading. A blast wall of FPSO topside was considered as an essential structure in which the wall prevents explosion pressures from the process area to utility and working areas. From linear/nonlinear transient analyses using LS-DYNA, it was observed that dynamic responses of structures were influenced by significantly the negative time duration.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.293-300
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• 2021

In this study, the microstructure and thermal conductivity correlation was investigated for concrete materials used in concrete thermal energy storage (CTES) among real-time energy storage devices. Graphite was used as admixture to increase the thermal conductivity performance of the CTES. Concrete specimens of 10% and 15% substitution of cement by mass with graphite, as well as ordinary portland cement (OPC) specimens were prepared, and the microstructural changes and effects on thermal conductivity were analyzed. Porosities of OPC and concrete with graphite were compared using micro-CT, and the microstructural characteristics were quantified using probability functions. Three-dimensional virtual specimens were constructed for thermal analysis, to confirm the effect of microstructural characteristics on thermal conductivity, and the results were compared with the measured conductivity obtained using the hot-disc method. To identify thermal conductivity of graphite for thermal analysis, solid phase conductivity was inversely determined based on simulation and experimental results, and the effect of graphite on thermal conductivity was analyzed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.1021-1028
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• 2018

As entering the international construction market became more difficult than the past, ODA projects can be a breakthrough for domestic engineering companies to enter the international market. However, since many companies compete for limited projects, it is necessary to reinforce the competitiveness of bidding success. The competitiveness is the result of accumulating experience, reputation, and networking through partnering. Therefore, depending on which partnering strategy has been taken over a long period, the bidding success is decided. The objective of this study is to identify the effective partnering strategy for bidding success. For this, the World Bank bid results, focusing on consulting projects in Vietnam, are collected. Using the bid results, inter-firm network representing the partnering relationship is constructed and the Social Network Analysis is conducted. After then, by conducting the Logistic Regression Analysis, effective partnering strategies are suggested. The result shows that the diversification strategy is advantageous for transportation and city development projects and the concentration strategy is advantageous for water projects. The partnering strategy for the consulting project proposed in this study will be used as a reference for the domestic engineering companies to enter the Vietnam construction market in the future.

• The Korean Journal of Rheology
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• v.11 no.1
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• pp.18-27
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• 1999

Predicting the deformation behaviors of sheets in thermoforming processes has been a daunting challenge due to the strong nonlinearities arising from very large deformations, mold-polymer contact condition and hyperelasticity constitutive equations. Nonlinear numerical analysis is always required to face this challenge especially for realistic processing conditions. In this study a 3-D algorithm and the membrane approximation are developed for thermoforming processes. The constitutive equation is expressed in terms of the 2nd Piola-Kirchhoff stress tensor and the Cauchy-Green deformation tensor. The 2-term Mooney-Rivlin model is used for the material model equation. The algorithm is established by the finite element formulation employing the total Lagrangian coordinate. The deformation behavior and the stress distribution results of 3-D algorithm with various point boundary conditions are compared to those of the membrane approximation algorithm. Also, the slip boundary condition and the no-slip boundary condition are applied for the systems that have molds. Finally, the effect of sheet temperatures on the final thickness distribution is investigated for the ABS material.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.97-106
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• 2014

The development of big data technology was to more accurately predict diversified contemporary society and to more efficiently operate it, and to enable impossible technique in the past. This technology can be utilized in various fields such as the social science, economics, politics, cultural sector, and science technology at the national level. It is a prerequisite to find valuable information by data mining techniques in order to analyze big data. Data mining techniques associated with big data involve text mining, opinion mining, cluster analysis, association rule mining, and so on. The most widely used data mining technique is to explore association rules. This technique has been used to find the relationship between each set of items based on the association thresholds such as support, confidence, lift, similarity measures, etc.This paper proposed cosine net confidence as association thresholds, and checked the conditions of interestingness measure proposed by Piatetsky-Shapiro, and examined various characteristics. The comparative studies with basic confidence and cosine similarity, and cosine net confidence were shown by numerical example. The results showed that cosine net confidence are better than basic confidence and cosine similarity because of the relevant direction.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.759-769
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• 2008

Convergence technology stimulating participation sharing openness to the public of web 2.0 such as Open-API, Mash-Up, Syndication gives diversity to education field. The convergence in education field means the revolution toward education 2.0 and new education reflecting web 2.0 stream is called 'education 2.0'. Education environment can be the space of social network intimately linked between learners, educators and educational organization. Network technology developed in ontology language makes it possible to educate semantically which understands privatized education service and connection. Especially, filtering system by the reputation system of Amazon and the collective intelligence of Wikipedia are the best samples. Education area can adopt actively because learners as educational main body can broaden their role of participation and communicate bilaterally in the equal position. In this paper, new network architecture in contents linkage is introduced and researched for utilization and analysis of the architecture for web 2.0 technology and educational contents are to be converged. Education 2.0 service utilizing convergence technology and network architecture for realizing education 2.0 is introduced and analyzed so that the research could be a preceding research to the education 2.0 platform foundation.

• The Korean Journal of Mycology
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• v.26 no.1 s.84
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• pp.1-7
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• 1998

In order to find relationship within and between entomopathogenic species, analysis of protein band pattern in mycelia of 25 isolates was conducted by UPGMA. The results allowed differentiation of three groups on 85% similarity coefficient. Similarity coefficient within C. militaris was $0.787{\sim}1.000$, C. kyushuensis was 0.958-1.000 and C. pruinosa was 0.993-1.000. C210 and C298 isolates which had somewhat immersed perithecia, comparable to other C. militaris isolates, had 91% similarity. C108, C225-1 and C228 isolates pathogenic on Lepidopterous larvae had 89% similarity. Closely related species to C. militaris were C. kyushuensis and C. pruinosa. And similarity between C. pruinosa and C. kyushuensis was 88%. Similarity between C. bifusispora formed conidia on media and Paecilomyces tenuipes was 89%. C. scarabaeicola pathogenic specifically on adult Scarabaeidae had 82% similarity with above two species. C118 identified as C. militaris showed different protein banding patterns.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.123-140
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• 2023

Maritime transportation is one of the oldest means of transportation utilized by mankind, and it has significantly contributed to the advancement of civilization by efficiently transporting bulk cargo at a low cost. The study aim to identify the factors influencing the selection of shipping companies in the bulk shipping market and provide insights for improving the competitiveness of shipping-related companies. To achieve this goal, the Analytic Hierarchy Process (AHP) was employed. For the empirical analysis, previous research, interviews, and a pilot test were conducted to identify five top-level factors such as companies, vessels, operations, services, and transaction factors. Each top-level factor has four sub-factors. The results of the analysis, based on 80 valid questionnaires, are as follows: Firstly, in the selection of shipping companies, the priority of factors influencing the choice of shipping companies was as follows: vessel factors were the most important, followed by company, operations, relationship, and service factors. Secondly, when investigating the priority of sub-factors, the availability/appropriateness of vessels was the most crucial factor, followed by company characteristics, financial soundness, and the company's reputation in order. The implications of these findings suggest that shipowners should focus on securing more suitable vessels and enhancing their reputation in response to shippers' demand. Shippers, on the other hand, should consider maintaining a healthy financial structure as a crucial task in securing competitive shipping service providers.