• Cartoon and Animation Studies
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• s.36
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• pp.553-572
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• 2014

In this paper, for the evaluation of the ease of a particular Web site (www.appbelt.net), insert the log tracking code for Google Analytics in a page of the Web site to collect behavioral data of visitor and has studied the improvement measures for the problems of the Web site, after the evaluation of the overall quality of the Web site through the evaluation of Coolcheck. These findings set the target value of the company's priority (importance) companies want to influence the direction of the business judgment are set up correctly, and the user's needs and behavior will be appropriate for the service seems to help improvement.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.109-121
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• 1999

플랜트 및 설비가 대규모, 정교화, 복잡화 될수록 이로 인한 고장 및 오류에 의한 피해가 막대하기 때문에, 시스템의 신뢰성, 보전성 및 안전성 향상과 제품 품질 향상을 추구 및 안전성 유지에 대한 관심이 고조되고 있다. 고장진단은 잠재적으로 노이즈를 가지고 있다고 생각되는 데이터의 해석에 근거하여 시스템의 고장을 찾는 일련의 체계적이고 통합된 방법이다. 그러나 대부분의 방법들이 이진 논리에 기초를 둔 추론으로 불확실성을 제대로 결과에 반영하지 못하고 있다. 본 논문에서는 예방정비의 관점에서 시스템에 내재된 다양한 불확실성을 효율적으로 처리하기 위해 전문가의 직관과 경험등을 기초로 하여 언어학적 변량을 취하고, 이를 퍼지 기법을 이용하여 정량화 함으로써 불확실성을 고려한 판단이 가능하게 하는 퍼지 전문가 시스템을 제안한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.548-556
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• 2018

NMS (Network Management System) is a system that is used for a small or large networks management. As the size of network becomes larger and the configuration information become complicated, it becomes more difficult to grasp the network status and it takes much time to diagnose the failure of the network equipment. In this paper, to alleviate the problems of NMS we implement web-based network topology automatically using JavaScript, Python, HTML5 based TWaver. The detailed implementation of the system include the automatic collection of the connection information based on the equipment information registered in the NMS system, the implementation of the web-based network topology and the remote fault diagnosis. In the network topology, we can expect to improve the quality of the NMS system through structured data management by adding the configuration management, fault management and performance management functions in a comprehensive manner.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2396-2402
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• 2015

Air compressor, as an essential equipment used in the factory and plant operations, accounts for around 30% of the total electricity consumption in U.S.A, thereby being proposed advanced technologies to reduce electricity consumption. When the fluctuation of the compressed airflow rate is small, the system stability is increased followed by the reduction of the electricity consumption which results in the efficient design of the energy system. In the statistical analysis, the normal distribution, log normal distribution, gamma distribution or the like are generally used to identify system characteristics. However a single distribution may not fit well the data with long tail, representing sudden air flow rate especially in extremes. In this paper, authors decouple the compressed airflow rate into two parts to present a mixture of distribution function and suggest a method to reduce the electricity consumption. This reduction stems from the fact that a general pareto distribution estimates more accurate quantile value than a gaussian distribution when an airflow rate exceeds over a large number.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.483-486
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• 2021

With the explosive increase in data, the 'big data era' has arrived, focusing on deriving new values and insights through data. With the development of data analysis technology, the importance of data analysis and utilization in the field of diagnosis and treatment as well as prevention is expanding, while the use of big data is emerging in the healthcare field. Moreover, as the three data-related laws (Personal Information Protection Act, Information and Communication Network Act, and Credit Information Act) were passed in January 2020, it became possible to use a wide range of big data through pseudonym information. However, the use of healthcare big data is still struggling due to various policies and regulations, inconsistent data quality, and the absence of specialized personnel. Therefore, in this study, examines the current state of use of big data in the healthcare field, and analyzes the challenges, overseas cases, plans, and expected effects for activation of healthcare big data.

• Korean Journal of Environmental Biology
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• v.39 no.3
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• pp.259-265
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• 2021

A diagnostic test for viral hemorrhagic septicemia virus (VHSV), which infects more than 80 species of freshwater and marine fish at home and abroad, causing mass mortality, was conducted to provide quantitative data on the amount of virus expression in various tissues of flounder in chronological order. The tissues were collected in chronological order after the intraperitoneal injection of 3.0E+07 tissue culture infective dose₅₀ (TCID₅₀) per 0.1mL per fish of VHSV to randomly selected flounder. As a result of relative quantification through real-time PCR, the highest levels of virus expression were found in the spleen, kidney, gill, and liver on day 5. This study proved that the spleen was an appropriate site for the final diagnosis of VHSV in the early stages of infection and will provide important information for the diagnosis of legal infectious diseases in Korea.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.6
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• pp.255-266
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• 2022

The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.4
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• pp.37-47
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• 2024

This study proposes a track maintenance quantity estimation model that considers evolution of rail fatigue damage and ballast settlement based on actual maintenance data from the Gyeongbu high-speed railway, and revises the existing life cycle cost (LCC) model for railway track. Using this model, maintenance quantities and life cycle costs based on different track quality levels are evaluated and discussed. According to the results, it is confirmed that applying the track maintenance quantity estimation model that accounts for rail fatigue damage and ballast settlement allows us to reasonably estimate maintenance costs close to the actual data. The track quality coefficient significantly influences both rail and ballast maintenance quantities, with ballast maintenance having a greater impact than rail maintenance. Additionally, as train speed increases, both rail and ballast maintenance quantities rise. Moreover, a higher track quality coefficient leads to a steeper increase in maintenance quantities with increasing train speed. Consequently, LCC also exhibits a faster growth rate over time with higher track quality coefficients and faster train speeds, resulting from an increased proportion of maintenance costs.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.667-668
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• 2008

현대 산업사회의 특징은 대용량화와 고속화에 있다. 전력부분에 있어서도 예외는 아니어서 초고층빌딩, 대단지 아파트, 공장, 위락시설, 병원 등 대용량 전력부하가 급격한 속도로 증가하고 있다. 특히 전력부분에 있어서는 대용량화와 동시에 경량 및 부피감소의 요구가 증대되면서도 신뢰성 높은 전력 품질 또한 요구되고 있다. 전기안전의 측면에 있어서 발전소의 안전불량은 전력수용가의 수급 차질로 인한 데이터 전산망, 생산설비의 막대한 재산 피해 뿐 아니라 병원 등에서의 인명피해도 발생시킬 수 있으므로 이에 대한 대책이 꼭 강구되어야 한다. 본 논문은 소용량 2극 동기발전기의 공극자속 파형 특성연구를 통하여 발전기 회전자 권선의 단락고장진단을 위한 예측진단기술을 개발하는 과정의 일환으로 진행되었으며 우선 정상상태의 공극자속을 컴퓨터 시뮬레이션 방법으로 계산하고 이를 시험치와 비교하여 해석 결과의 신뢰성을 평가하였다. 본 연구의 결과를 바탕으로 발전기의 모의 고장으로 발생하는 공극 자속의 특성을 연구하여 발전설비의 안전 확대에 기여할 것이다.

• Journal of the Korean Society of Radiology
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• v.10 no.4
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• pp.247-253
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• 2016

Ultrasound devices diagnose many disease, which is widely used, can not be standardized quantitative evaluated in order to evaluate sonography image of quality. Therefore, in this papers, aims to get correct image in order to accurate diagnosis by figuring out the appropriate parameter based on each target by measuring distortion which results in the analyzation of the sensitivity of SNR and the histogram of signal by manipulating parameter of 8 mm target in ATS-539 multipurpose phantom. Equipment using Acuson sequoia 512, convex probe and utilizes multi-objective phantom. experiment method is that first you put the phantom on the flat and acquire 85 sheets of image, changing frequency(2,3,4 MHz, harmonic 3, 4, 4.5 MHz), Focus(2, 4, 6 unit), and Dynamic Range(58, 68, 78, 88, 98) for a 8 mm structure. through the Image J program. The sensitivity angle of 8mm target through Image J program is gauged by each separate target SNR and the distorted angle subtract and measure Histogram of background from Histogram of signal and take top 40% from the given result value above. According to parameter variation we found out proper parameter by acquiring SNR of sensitivity and distortion data for aspect of transition. The more this findings have Focus, the lower distortion value and at 4 MHz frequency this result have high SNR and low distortion value. Dynamic Range got an appropriate image on 88 and 98. It is considered on the basis of the experimental data, the probability of disease diagnosis will get higher.