• Annual Conference of KIPS
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• 2023.05a
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• pp.642-643
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• 2023

피트니스 분야 인공지능 서비스의 성능 개선을 AI모델 개발이 아닌 데이터셋의 품질 개선을 통해 접근하는 방식을 제안하고, 데이터품질의 성능을 평가하는 것을 목적으로 한다. 데이터 설계는 각 분야 전문가 10명이 참여하였고, 단일 시점 영상을 이용한 운동동작 자동 분류에 사용된 모델은 Google의 MediaPipe 모델을 사용하였다. 팔굽혀펴기의 운동동작인식 정확도는 100%로 나타났으나 팔꿉치의 각도 15° 이하였을 때 동작의 횟수를 인식하지 않았고 이 결과 값에 대해 피트니스 전문가의 의견과 불일치하였다. 향후 연구에서는 동작인식의 분류뿐만 아니라 운동량을 연결하여 분석할 수 있는 시스템이 필요하다.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.341-348
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• 2016

Because VPN(Virtual Private Network) uses internet network, the security technique should support it and evaluation technique based on standard should support it. Therefore the method should be organized that can evaluate the security of VPN based on the related standard. In this study, we intended to construct the security evaluation model through combining CC(Common Criteria) which is a evaluation standard and a part of security(Confidentiality, Integrity, Non-repudiation, Accountability, Authenticity) evaluation of ISO which is the standard of software quality evaluation. For this, we analyzed the quality requirements about intra-technology and security of VPN and constructed the evaluation model related to the quality characteristics of two international standard. Through this, we are able to construct a convergence model for security evaluation of VPN. Through accumulating the evaluation practices for VPN in the future, the suitability and validity of the evaluation model must be improved.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.441-448
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• 2023

The quality of the casting process generates the largest source of defects in the manufacturing process, so its management is a key factor in productivity and quality evaluation. Based on the results of factor analysis, correlation analysis, and regression analysis with process data, this study aims to optimize the machine learning model to reduce the defect rate and verify the data suitability for smart factories.

• Journal of the Korea Convergence Society
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• v.8 no.10
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• pp.37-43
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• 2017

In this paper, we propose a method for estimation software quality in terms of software test data, and it is necessary to predict the period of time required for software test evaluation. We need a model to understand of estimation of software quality. In this paper, we propose a model to estimate the number of days for software test using the data obtained through the tester's sex, and present a model for analysing the number of errors according to six quality characteristics by software type.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.157-168
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• 2024

The frequent occurrence of structural failures at building construction sites in Korea has underscored the critical role of rigorous oversight in the inspection and management of construction projects. As mandated by prevailing regulations and standards, onsite supervision by designated supervisors encompasses thorough documentation of construction quality, material standards, and the history of any reconstructions, among other factors. These reports, predominantly consisting of unstructured data, constitute approximately 80% of the data amassed at construction sites and serve as a comprehensive repository of quality-related information. This research introduces the SL-QPA model, which employs text mining techniques to preprocess supervision reports and establish a sentiment dictionary, thereby enabling the quantification of quality performance. The study's findings, demonstrating a statistically significant Pearson correlation between the quality performance scores derived from the SL-QPA model and various legally defined indicators, were substantiated through a one-way analysis of variance of the correlation coefficients. The SL-QPA model, as developed in this study, offers a supplementary approach to evaluating the quality performance of building construction projects. It holds the promise of enhancing quality inspection and management practices by harnessing the wealth of unstructured data generated throughout the lifecycle of construction projects.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.31-39
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• 2013

Recently, integration between social media and the industry has been expended, and as the usage of Internet through various smart devices of not only the existing PC but also smart phone, tablet PC and so on, a lot of unstructured data has occurred, leading to increased interest on big data system. According to the institutes which specialize in market research, the data amount is predicted to increase by 9 folds in the next 5 years when compared to the present, and the big data market is also expected to grow bigger. This dissertation evaluates the efficiency test of big data through analysis on the requirements by identifying and fragmenting the items of efficiency quality evaluation that big data should be equipped with.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.1
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• pp.113-119
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• 2014

Recently, R.O.K. Navy is increasing re-usability of design data and application of M&S(Modeling and Simulation) through the establishment of collaborative product development environment focused on Naval Ship Product Model(NSPM). As a result, the reliability of the result of design is getting better, and furthermore, a study to improve quality of construction through simulation of production/operation is in progress. Accordingly, the database construction of design data and the DB(Database) quality become important, but there was not research related to those or it was just initial state. This paper conducted research about system of the quality verification process of shape elements which compose NSPM based on the quality verification guideline of NSPM as the result of the precedent study. The hull surface was limited as verification object. The study to verify two things that application of basic drawing by the cad model of hull surface, and whether there is error in the geometric quality of cad model was progressed. To achieve this goal, the verification criteria and algorithm were defined and the prototype system which is based on was developed.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.293-298
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• 2013

We consider about software quality nowadays. The company considers about software quality more and more compare to software development. We analyze the software testing data in this paper. We find the software effect according to the number of testing, the number of testing date, the number of fault according to characteristics. Also, we analyze the result by regression. Also, we propose the testing effect by sex.

• Journal of the Korean Society for Library and Information Science
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• v.41 no.4
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• pp.315-329
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• 2007

The objective of this study is to identify key dimensions of e-service quality and explore their relations to user satisfaction at Public libraries. This research used a modified e-service quality model and surveyed Internet service users for measuring and assessing Internet users' service satisfaction at 'A' public library in Seoul region. Using an exploratory factor analysis. the study identified three factors, named Service Affect, Information Access, and Tangibles as key dimensions for public library e-service quality. Also it was found that users' satisfaction was strongly positively correlated to their intention to refer others to the service.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.293-310
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• 2022

In this study, we analyzed the performance of the BERT-based document classification model by automatically classifying documents in the field of library and information science based on the KoBERT. For this purpose, abstract data of 5,357 papers in 7 journals in the field of library and information science were analyzed and evaluated for any difference in the performance of automatic classification according to the size of the learned data. As performance evaluation scales, precision, recall, and F scale were used. As a result of the evaluation, subject areas with large amounts of data and high quality showed a high level of performance with an F scale of 90% or more. On the other hand, if the data quality was low, the similarity with other subject areas was high, and there were few features that were clearly distinguished thematically, a meaningful high-level performance evaluation could not be derived. This study is expected to be used as basic data to suggest the possibility of using a pre-trained learning model to automatically classify the academic documents.