• Journal of Korea Technology Innovation Society
• /
• v.17 no.3
• /
• pp.449-466
• /
• 2014

There have been various researches on the relationship between a company's R&D investment and the outcome from innovation. However, these studies failed to effectively analyze the decision-making process followed by companies in relation to knowledge production. Especially, in analyzing the patent of companies, the Poisson model has been commonly used, but its limitations have been pointed out. In recent years, many studies have adopted negative binomial models, but they still pose limitations in analyzing the selection process. This paper proposed a hurdle negative binomial model to effectively reflect the company's decision embedded within patent information and conduct an empirical analysis on a survey of businesses' activities. In particular, the study analyzed the selection process of companies in determining the number of patents. As a result of estimation, the presence of over-dispersion was identified. In addition, the Wald-test confirmed that setting up of hurdles was valid, and there was a difference between the results of hurdle models and those of general negative binomial settings.

• Journal of Korea Society of Industrial Information Systems
• /
• v.26 no.6
• /
• pp.81-96
• /
• 2021

This study examines the importance of factors that influence the online platform selection decision to support operational optimization strategies. For the research purpose, we first reviewed previous studies on service encounters and identified those factors that have been proven important for using online platforms. Second, this study analyzed the factors that customers perceived as important based on analytical hierarchy process (AHP) of the data we collected from 10 mobile or computer-based Internet users. The study results revealed that the important factors for the online platform selection were in the following order: product diversity (27.4%), ease of use (21.5%), brand credibility (18.1%), interactions with the service provider (17.7%), and ease of accessibility (15.3%). The study provides useful insights to online platform service providers in developing strategies for customer-focused value creation.

• International Journal of Computer Science & Network Security
• /
• v.24 no.7
• /
• pp.108-117
• /
• 2024

The selection and recommendation of a suitable job applicant from the pool of thousands of applications are often daunting jobs for an employer. The recommendation and selection process significantly increases the workload of the concerned department of an employer. Thus, Resume Classification System using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process and ease the job of an employer. Moreover, the automation of this process can significantly expedite and transparent the applicants' selection process with mere human involvement. Nevertheless, various Machine Learning approaches have been proposed to develop Resume Classification Systems. However, this study presents an automated NLP and ML-based system that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of Resume Classification Systems and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP & ML techniques for processing & classification of Resumes, the extracted features were tested on nine machine learning models Support Vector Machine - SVM (Linear, SGD, SVC & NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN) and Logistic Regression (LR). The Term-Frequency Inverse Document (TF-IDF) feature representation scheme proven suitable for Resume Classification Task. The developed models were evaluated using F-Score_M, Recall_M, Precission_M, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume Classification task, the SVM class of Machine Learning algorithms performed better on the study dataset with over 96% overall accuracy. The promising results suggest that NLP & ML techniques employed in this study could be used for the Resume Classification task.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.453-456
• /
• 2000

This paper presents experimental results on selecting optimal process parameters for UV-Vaccum casting. The UV-Vacuum casting is a relatively new process that allows very rapid mold preparation and part duplication via UV curing. Effect of various process variables such as pressure and temperature on mold strength and part accuracy was evaluated by using Taguchi method.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1241-1241
• /
• 2001

We propose a new calibration method, which uses the linearization method for spectral responses and the repetitive adoptions of the linearization weight matrices to construct a frature. Weight matrices are estimated through multiple linear regression (or principal component regression or partial least squares) with forward variable selection. The proposed method is applied to three data sets. The first is FTIR spectral data set for FeO content from sinter process and the second is NIR spectra from trans-alkylation process having two constituent variables. The third is NIR spectra of crude oil with three physical property variables. To see the calibration performance, we compare the new method with the PLS. It is found that the new method gives a little better performance than the PLS and the calibration result is stable in spite of the collinearity among each selected spectral responses. Furthermore, doing the repetitive adoptions of linearization matrices in the proposed methods, uninformative variables are disregarded. That is, the new methods include the effect of variables subset selection, simultaneously.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1611-1611
• /
• 2001

The main selection parameters used by forage grass (rye and Italian rye grass) breeders are dry-matter yield, seasonal growth, persistency, disease resistance, heading date, and heading. These characteristics can all be identified usually in the segregating F2 population, however characteristics such as soluble carbohydrate level, protein, lipid and digestibility cannot be identified. The emphasis of this work is to introduce a quantitative selection process for characterization of herbage quality e.g. protein, water-soluble carbohydrates, fiber fractions, dry matter digestibility. NIRS calibrations are currently being developed for identifying grass genotypes to assist the selection process, thereby allowing the opportunity to actively breed improved herbage quality. The changes in fibre fractions, associated components and digestibility of a number of grass clones at different growth stages are being assessed changes taking place during a growing season. This will provide a database of the major changes taking place during a growing season. Attempts to classify quality differences between genotypes will be carried out using multivariate analysis of the spectral data. I addition changes associated with maturity of grass will be considered in order to develop robust calibrations.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.18 no.1
• /
• pp.83-88
• /
• 2010

The study is intended to help to select the pilot candidates with exceptional flight aptitude ability and to investigate the relationship between the results of the scholastic aptitude test and the flight aptitude. It is intended that the research will help to draw recommendations on the relevant fields of the scholastic aptitude test that is to be used to select the high caliber candidates with exceptional flight aptitude ability, to gauge the resulting effectiveness of its application and helping to revise the university's syllabus accordingly. From the study, korean, mathematics, english grade and the flight aptitude test results have all shown to hold mutual relationship and through simple correlation analysis, it was discovered that mathematics and English are the two factors that affect the results of the flight aptitude test, with the extent of its impact graded in descending order of English, mathematics and Korean. Lastly, the logistic regression analysis have discovered that the mathematics grade has significant effect on the classification of the flight aptitude and non aptitude category groups, and English also has significant influence close to the 0.05 p-values. It is believed that should the findings of this study be considered as part of the selection process of the university applicants of the department of aeronautical science, making discovery of candidates of higher quality is expected.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.05a
• /
• pp.698-701
• /
• 2004

In many literatures, data mining has been used as a utilization of data warehouse and data collection. The biggest utilizations of data mining are for marketing and researches. This is solely because of the data available for this field is usually in large amount. The usability of the data mining is expandable also to the production process. While the object of research of the data mining in marketing is the customers and products, data mining in the production field is object to the so called 4MlE, man, machine, materials, method (recipe) and environment. All of the elements are important to the production process which determines the quality of the product. Because the final aim of the data mining in production field is the quality of the production, this data mining is commonly recognized as quality data mining. As the variables researched in quality data mining can be hundreds or more, it could take a long time to reveal the information from the data warehouse. Feature selection methodology is proposed to help the research take the best performance in a relatively short time. The usage of available simple statistical tools in this method can help the speed of the mining.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.939-944
• /
• 2007

Generally, development of a robot capable of fast movements or high payloads is progressed by the analysis of dynamic characteristics, DOF positioning, actuator selection, structure of links, and so on. This paper highlights the design of a robot manipulator handled by a human for man-machine cooperation. The requirements of the proposed system include its having multi-DOF(Degree of Freedom)and the capacity for a high payload in the condition of its maximum reach. The primary investigation factors are motion range, performance within the motion area, and reliabilityduring the handling of heavy materials. Traditionally, the mechanical design of robots has been viewed as a problem of packaging motors and electronics into a reasonable structure. This process usually transpires with heavy reliance of designerexperience. Not surprisingly, the traditional design process contains no formally defined rules for achieving desirable results, as there is little opportunity for quantitative feedback during the formative stages. This work primarily focuses on the selection of proper joint types and link lengths, considering a specific task type and motion requirements of the heavy material handling.

• KIEAE Journal
• /
• v.8 no.3
• /
• pp.43-50
• /
• 2008

The aim of this study is to search for the meaning and direction of sound environment preservation in Korea through the concept of soundscape. In order to achieve the goals, it was analyzed the similarities and differences on the contents of "100 The beautiful sounds of Korea - 1999" and "100 Soundscapes of Japan - 1996" in view of the intents of selection, the process of selection, and the construction of the results. The result show that there are the both similarities and differences on the intent and the process of selection, types and extent of sound samples, interactions among human-sound environment-region, the identities of the regions as well as the recognized sound environment. Also, the result shows that it is very important to preserve ecological, social, and cultural sound environment of the region. In order to practice this ideology of soundscape in Korea, there is a necessity for converting people's consciousness and participating voluntary residents' movement.