• Title/Summary/Keyword: reliability improvement

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A Study on Factors Influencing the Severity of Autonomous Vehicle Accidents: Combining Accident Data and Transportation Infrastructure Information (자율주행차 사고심각도의 영향요인 분석에 관한 연구: 사고데이터와 교통인프라 정보를 결합하여)

  • Changhun Kim;Junghwa Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.200-215
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    • 2023
  • With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

A Research on Applicability of Drone Photogrammetry for Dam Safety Inspection (드론 Photogrammetry 기반 댐 시설물 안전점검 적용성 연구)

  • DongSoon Park;Jin-Il Yu;Hojun You
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.5
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    • pp.30-39
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    • 2023
  • Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

Analysis of the Effectiveness of Big Data-Based Six Sigma Methodology: Focus on DX SS (빅데이터 기반 6시그마 방법론의 유효성 분석: DX SS를 중심으로)

  • Kim Jung Hyuk;Kim Yoon Ki
    • KIPS Transactions on Software and Data Engineering
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    • v.13 no.1
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    • pp.1-16
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    • 2024
  • Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.

An Exploratory Study on the Trustworthiness Analysis of Generative AI (생성형 AI의 신뢰도에 대한 탐색적 연구)

  • Soyon Kim;Ji Yeon Cho;Bong Gyou Lee
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.79-90
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    • 2024
  • This study focused on user trust in ChatGPT, a generative AI technology, and explored the factors that affect usage status and intention to continue using, and whether the influence of trust varies depending on the purpose. For this purpose, the survey was conducted targeting people in their 20s and 30s who use ChatGPT the most. The statistical analysis deploying IBM SPSS 27 and SmartPLS 4.0. A structural equation model was formulated on the foundation of Bhattacherjee's Expectation-Confirmation Model (ECM), employing path analysis and Multi-Group Analysis (MGA) for hypothesis validation. The main findings are as follows: Firstly, ChatGPT is mainly used for specific needs or objectives rather than as a daily tool. The majority of users are cognizant of its hallucination effects; however, this did not hinder its use. Secondly, the hypothesis testing indicated that independent variables such as expectation- confirmation, perceived usefulness, and user satisfaction all exert a positive influence on the dependent variable, the intention for continuance intention. Thirdly, the influence of trust varied depending on the user's purpose in utilizing ChatGPT. trust was significant when ChatGPT is used for information retrieval but not for creative purposes. This study will be used to solve reliability problems in the process of introducing generative AI in society and companies in the future and to establish policies and derive improvement measures for successful employment.

A Study on the Measurement Method for Improvement of Reliability for Heavy-Weight Floor Impact Sound Measurement (중량 바닥충격음 측정의 신뢰성 향상을 위한 측정방법 검토)

  • Joo, Moon-Ki;Park, Jong-Young;Yang, Kwan-Seop;Oh, Yang-Ki
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.4
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    • pp.163-170
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    • 2008
  • Most of receiving rooms for the measurement of floor impact sound have rectangular shapes with couple of meters of dimension, with reflective finishing, no furniture, no curtains. Modal overlaps in those condition are the major reason for the low reproducibility, and as a matter of course, the low credibility. It is the major purpose of this study that searching for a better measurement method which mitigate the effect of modal overlap on measurement. Two ways of methods are tested. One is the way described in ISO standards which enables controlling the room modes of receiving rooms, the other is the way which enables to get more precise spatial averages in receiving rooms with room modes. It is not easy maintaining the reverberation time of low frequency bands in the range between 1s and 2s, though it is proven to be effective controlling the room modes with base traps. Space-time average SPL's through combinations of rotating microphones are easy to measure, and have good consistencies with average SPL of entire receiving room.

A Case Study on Minimizing Contract Amount Adjustments due to Design Changes in Defense and Military Facility Projects (국방·군사시설 사업의 설계변경 계약금액조정 최소화를 위한 사례연구)

  • Cho, Sung-joon;Lee, Kyoung-han;Lee, Myung-sik;Park, Bong-gyu
    • Korean Journal of Construction Engineering and Management
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    • v.25 no.4
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    • pp.34-44
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    • 2024
  • In defense and military facility projects, adjustments to contract amounts due to design changes directly or indirectly affect factors such as increased construction costs and extended construction periods. Moreover, they can lead to differences of opinion and conflicts between the military and contracting parties. This case study analyzed the integrated management of defense and military facility projects by the Gyeonggi Southern Facilities Division, which oversees projects in Seoul and the southern Gyeonggi Province region for the Army, Navy, Marine Corps, and Air Force. Out of 388 completed projects, 103 cases with design changes were selected for analysis, aiming to ensure the reliability of data regarding the proportion of design changes in project completion. The study classified samples by the causes of design changes specified in the Ministry of Planning and Finance's contract regulations, assigning rankings based on the occurrence rates of each cause. Furthermore, it analyzed detailed factors for each cause of design change and derived implications to propose improvement measures. Considering the limited access to military primary data, this case study is expected to contribute to minimizing design changes in defense and military facility projects. Additionally, it is anticipated to be practically useful for subsequent research on contract amount adjustments resulting from design changes.

Evaluation of Quality Standards of Bio-Diesel (BD100, BD20) Manufactured Using Waste Frying Oil (폐식용유를 이용하여 제조한 바이오디젤(BD100, BD20)의 품질기준 평가)

  • Na, Seong-Joo;Jeon, Byung-Gwan
    • Journal of the Korea Organic Resources Recycling Association
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    • v.17 no.1
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    • pp.39-48
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    • 2009
  • Biodiesel is estimated to be the best recycling energy source as an alternative fuel for transportation vehicles which represents the biggest share of greenhouse effect gas exhausts. Thus, in order to widely expand use of biodiesel and to enhancement its reliability, studies on quality improvement of biodiesel is needed. In this study, we have produced biodiesel(BD100, BD20) through esterification reaction using raw material of waste frying oil and analyzed compatibility with 24 items of quality criteria. As waste frying oil has high contents of unsaturated fatty acid such as Oleic acid, Linoleic acid and Linolenic acid, it is confirmed that there is no problem in using the same as a raw material of biodiesel. The result of analyzing the quality criteria items of biodiesel showed that it satisfied all the quality criteria except the oxidation stability of BD100, which was 2 hours, fatty acid methyl ester of BD20, which was 18.6w% and the filter plugging point, which was $-5^{\circ}C$. We believe that it will contribute to improved utilization of waste resources as alternative energy if studies on technology to improve quality of some items are provided.

A Multimodal Profile Ensemble Approach to Development of Recommender Systems Using Big Data (빅데이터 기반 추천시스템 구현을 위한 다중 프로파일 앙상블 기법)

  • Kim, Minjeong;Cho, Yoonho
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.93-110
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    • 2015
  • The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

A Study on Qulity Perceptions and Satisfaction for Medical Service Marketing (의료서비스 마케팅을 위한 품질지각과 만족에 관한 연구)

  • Yoo, Dong-Keun
    • Journal of Korean Academy of Nursing Administration
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    • v.2 no.1
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    • pp.97-114
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    • 1996
  • INSTRODUCTION Service quality is, unlike goods quality, an abstract and elusive constuct. Service quality and its requirements are not easily understood by consumers, and also present some critical research problems. However, quality is very important to marketers and consumers in that it has many strategic benefits in contributing to profitability of marketing activities and consumers' problem-solving activities. Moreover, despite the phenomenal growth of medical service sector, few researchers have attempted to define and model medical service quality. Especially, little research has focused on the evaluation of medical service quality and patient satisfaction from the perspectives of both the provider and the patient. As competition intensifies and patients are demanding higher quality of medical service, medical service quality and patient satisfaction has emerged as a critical research topic. The major purpose of this article is to explore the concept of medical service quality and its evaluation from both nurse and patient perspectives. This article attempts to achieve its purpose by (1)classfying critical service attibutes into threecategories(satisfiers, hygiene factors, and performance factors). (2)measuring the relative importance of need criteria, (3)evaluating SERVPERF model and SERVQUAL model in medical service sector, and (4)identifying the relationship between perceived quality and overall patient satisfaction. METHOD Data were gathered from a sample of 217 patients and 179 nurses in Seoul-area general hospitals. From the review of previous literature, 50 survey items representing various facets of the medical service quality were developed to form a questionnaire. A five-point scale ranging from "Strongly Agree"(5) to "Strongly Disagree"(1) accompanied each statement(expectation statements, perception statements, and importance statements). To measure overall satisfaction, a seven-point scale was used, ranging from "Very Satisfied"(7) to "Very Dissatisfied"(1) with no verbal labels for scale points 2 through 6 RESULTS In explaining the relationship between perceived performance and overall satisfaction, only 31 variables out of original 50 survey items were proven to be statistically significant. Hence, a penalty-reward analysis was performed on theses 31 critical attributes to find out 17 satisfiers, 8 hygiene factors, and 4 performance factors in patient perspective. The role(category) of each service quality attribute in relation to patient satisfaction was com pared across two groups, that is, patients and nurses. They were little overlapped, suggesting that two groups had different sets of 'perceived quality' attributes. Principal components factor analyses of the patients' and nurses' responses were performed to identify the underlying dimensions for the set of performance(experience) statements. 28 variables were analyzed by using a varimax rotation after deleting three obscure variables. The number of factors to be extracted was determined by evaluating the eigenvalue scores. Six factors wereextracted, accounting for 57.1% of the total variance. Reliability analysis was performed to refine the factors further. Using coefficient alpha, scores of .84 to .65 were obtained. Individual-item analysis indicated that all statements in each of the factors should remain. On 26 attributes of 31 critical service quality attributes, there were gaps between actual patient's importance of need criteria and nurse perceptions of them. Those critical attributes could be classified into four categories based on the relative importance of need criteria and perceived performance from the perspective of patient. This analysis is useful in developing strategic plans for performance improvement. (1) top priorities(high importance and low performance) (in this study)- more health-related information -accuracy in billing - quality of food - appointments at my convenience - information about tests and treatments - prompt service of business office -adequacy of accommodations(elevators, etc) (2) current strengths(high importance and high performance) (3)unnecessary strengths(low importance and high performance) (4) low priorities(low importance and low performance) While 26 service quality attributes of SERPERF model were significantly related to patient satisfation, only 13 attributes of SERVQUAL model were significantly related. This result suggested that only experience-based norms(SERVPERF model) were more appropriate than expectations to serve as a benchmark against which service experiences were compared(SERVQUAL model). However, it must be noted that the degree of association to overall satisfaction was not consistent. There were some gaps between nurse percetions and patient perception of medical service performance. From the patient's viewpoint, "personal likability", "technical skill/trust", and "cares about me" were most significant positioning factors that contributed patient satisfaction. DISCUSSION This study shows that there are inconsistencies between nurse perceptions and patient perceptions of medical service attributes. Also, for service quality improvement, it is most important for nurses to understand what satisfiers, hygiene factors, and performance factors are through two-way communications. Patient satisfaction should be measured, and problems identified should be resolved for survival in intense competitive market conditions. Hence, patient satisfaction monitoring is now becoming a standard marketing tool for healthcare providers and its role is expected to increase.

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Quality Dimensions Affecting the Effectiveness of a Semantic-Web Search Engine (검색 효과성에 영향을 미치는 시맨틱웹 검색시스템 품질요인에 관한 연구)

  • Han, Dong-Il;Hong, Il-Yoo
    • Asia pacific journal of information systems
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    • v.19 no.1
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    • pp.1-31
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    • 2009
  • This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.