• Title/Summary/Keyword: Collection development

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A Study on the Development of FRACAS-based Failure Analysis Workflow for Military weapon system (FRACAS에 기반한 군 무기체계의 고장분석 워크플로우 구축에 대한 연구)

  • Lee, Min-Young;Kim, Wan-Gul;Kim, Kyung-Soo
    • Journal of Applied Reliability
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    • v.10 no.2
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    • pp.93-105
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    • 2010
  • The following thesis provides an explanation for the definition of the MIL-HDBK-2155 : Failure Reporting, Analysis and Corrective Action System (FRACAS), which systemizes the collection and analysis of failure data and the feedback process of the results. It also presents a plan based on MIL-HDBK-2155 for the collection and analysis of operating specifications on weapon systems. The collection and analysis of failure data and the feedback process utilizing FRACAS contributes to identifying improvement requirements during equipment operation as well as finding and eliminating the root cause of the failures. The objective of applying FRACAS to weapon systems is to receive source data feedback for reliability enhancements and performance improvements during operation. This is done by recognizing weaknesses in the design or operation by identifying the type of failures that might occur, and by performing Failure Modes, Effects and Criticality Analysis(FMECA) and Failure Tree Analysis(FTA).

A Study on the Analysis of Circulation and Usage of Law Library Collection: A Case Study of Law Library in S University (법학도서관 장서의 대출현황 분석 및 이용에 관한 연구 - S 대학 법학도서관을 중심으로 -)

  • Ahn, Jooyeon;Kim, Seonghee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.4
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    • pp.255-274
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    • 2019
  • In this study, we analyzed Circulation data of Law library in the S university for one year in 2018 and analyzed whether the Library holdings are actually used for education and research. First of all, this study analyzed user patterns by analyzing subjects, languages, and publication years for books that were circulated for one year from the ALMA system which is an S university library system. In addition, we analyzed how the current library holdings were used or cited in course syllabi and research papers written by members in S university. The results from this study can be used as an important basic data for effective collection development.

Integrated Solid Waste Management for the Environmentally Sound and Sustainable Development (환경적으로 지속가능한 개발을 위한 폐기물의 통합적 관리 방안)

  • Hong, Sang-Pyo;Nam, Kie-Chang
    • Journal of Environmental Impact Assessment
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    • v.9 no.1
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    • pp.87-98
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    • 2000
  • The costs of solid waste management have continued to increase. Stricter environmental regulations have been applied to waste management units. Future integrated solid waste management should be balanced between source reduction, recycling, energy recovery, and land disposal. To achieve more balanced solid waste management programs, more local governments must adopt diversion and recycling goals and finance to meet those goals. The hierarchy of integrated solid waste management must be enforced in a manner that is flexible enough to allow local governments to implement waste management facilities that match the communities' ability to pay for them. In establishing a hierarchy of integrated solid waste management, local governements have difficulties in implementing source reduction and recycling because of a lack of local control and inability to pay for new facilities. Integrated solid waste management involves selecting compatible options for facilities to manage the collection, recovery of energy and materials(transformation), and disposal of solid wastes efficiently. Waste Collection, transformation, and disposal must support source reduction and recycling activities.

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Development Status of Crowdsourced Ground Vibration Data Collection System Based on Micro-Electro-Mechanical Systems (MEMS) Sensor (MEMS 센서 기반 지반진동 정보 크라우드소싱 수집시스템 개발 현황)

  • Lee, Sangho;Kwon, Jihoe;Ryu, Dong-Woo
    • Tunnel and Underground Space
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    • v.28 no.6
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    • pp.547-554
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    • 2018
  • Using crowdsourced sensor data collection technique, it is possible to collect high-density ground vibration data which is difficult to obtain by conventional methods. In this study, we have developed a crowdsourced ground vibration data collection system using MEMS sensors mounted on small electronic devices including smartphones, and implemented client and server based on the proposed infrastructure system design. The system is designed to gather vibration data quickly through Android-based smartphones or fixed devices based on Android Things, minimizing the usage of resource like power usage and data transmission traffic of the hardware.

Development of Big-data Management Platform Considering Docker Based Real Time Data Connecting and Processing Environments (도커 기반의 실시간 데이터 연계 및 처리 환경을 고려한 빅데이터 관리 플랫폼 개발)

  • Kim, Dong Gil;Park, Yong-Soon;Chung, Tae-Yun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.16 no.4
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    • pp.153-161
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    • 2021
  • Real-time access is required to handle continuous and unstructured data and should be flexible in management under dynamic state. Platform can be built to allow data collection, storage, and processing from local-server or multi-server. Although the former centralize method is easy to control, it creates an overload problem because it proceeds all the processing in one unit, and the latter distributed method performs parallel processing, so it is fast to respond and can easily scale system capacity, but the design is complex. This paper provides data collection and processing on one platform to derive significant insights from various data held by an enterprise or agency in the latter manner, which is intuitively available on dashboards and utilizes Spark to improve distributed processing performance. All service utilize dockers to distribute and management. The data used in this study was 100% collected from Kafka, showing that when the file size is 4.4 gigabytes, the data processing speed in spark cluster mode is 2 minute 15 seconds, about 3 minutes 19 seconds faster than the local mode.

Nucleic acid-based molecular diagnostic testing of SARS-CoV-2 using self-collected saliva specimens

  • Hwang, Eurim C.;Kim, Jeong Hee
    • International Journal of Oral Biology
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    • v.46 no.1
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    • pp.1-6
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    • 2021
  • Since the outbreak of coronavirus disease 2019 (COVID-2019), the infection has spread worldwide due to the highly contagious nature of severe acute syndrome coronavirus (SARS-CoV-2). To manage SARS-CoV-2, the development of diagnostic assays that can quickly and accurately identify the disease in patients is necessary. Currently, nucleic acid-based testing and serology-based testing are two widely used approaches. Of these, nucleic acid-based testing with quantitative reverse transcription-PCR (RT-qPCR) using nasopharyngeal (NP) and/or oropharyngeal (OP) swabs is considered to be the gold standard. Recently, the use of saliva samples has been considered as an alternative method of sample collection. Compared to the NP and OP swab methods, saliva specimens have several advantages. Saliva specimens are easier to collect. Self-collection of saliva specimens can reduce the risk of infection to healthcare providers and reduce sample collection time and cost. Until recently, the sensitivity and accuracy of the data obtained using saliva specimens for SARS-CoV-2 detection was controversial. However, recent clinical research has found that sensitive and reliable data can be obtained from saliva specimens using RT-qPCR, with approximately 81% to 95% correspondence with the data obtained from NP and OP swabs. These data suggest that self-collected saliva is an alternative option for the diagnosis of COVID-19.

DISEASE FORECAST USING MACHINE LEARNING ALGORITHMS

  • HUSSAIN, MOHAMMED MUZAFFAR;DEVI, S. KALPANA
    • Journal of applied mathematics & informatics
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    • v.40 no.5_6
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    • pp.1151-1165
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    • 2022
  • Key drive of information quarrying is to digest liked information starting possible information. With the colossal amount of realities kept in documents, information bases, and stores, in the medical care area, it's inexorably significant, assuming excessive, arising compelling resources aimed at examination besides comprehension like information on behalf of the withdrawal of gen that might assistance in independent direction. Classification is method in information mining; it's characterized as per private, passing on item toward a specific course established happening it is likeness toward past instances of different substances trendy the data collection. In pre-owned recycled four Classification algorithm that incorporate Multi-Layer perception, KSTAR, Bayesian Network and PART to fabricate the grouping replicas arranged the malaria data collection and analyze the replicas, degree their exhibition through Waikato Environment for Knowledge Analysis introduced to Java Development Kit 8, then utilizations outfit's technique trendy promoting presentation of the arrangement methodology. The outcome perceived that Bayesian Network return most elevated exactness of 50.05% when working on followed by Multi-Layer perception, with 49.9% when helping is half, then, at that point, Kstar with precision of 49.44%, 49.5% when supporting individually and PART have lesser precision of 48.1% when helping, The exploration recommended that Bayesian Network is awesome toward remain utilized on Malaria data collection in our sanatoriums.

A numerical fluid dynamic study of a high temperature operating cyclone (고온 작동 싸이클론 유체역학적 거동 전산 연구)

  • Shin, Mi-Soo;Kim, Hey-Suk;Jang, Dong-Soon
    • Journal of Korean Society of Environmental Engineers
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    • v.31 no.11
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    • pp.1033-1040
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    • 2009
  • One thing to note in cyclone operation and design is to minimize the pressure drop with the enhancement of the efficiency of dust collection. This can be facilitated by the detailed resolution of complex fluid flow occurring inside a cyclone. To this end, the main objective of this study was to obtain the detailed fluid dynamics by the development of a reliable computation method and thereby to figure out the physics of dust collection mechanism for more extreme environment caused by high temperature and pressure condition. First of all, the computer program developed was evaluated against experimental result. That is, the numerical calculation predicts well the data of experimental pressure drop as a function of flow rate for the elevated pressure and temperature condition employed in this study. The increase of pressure and temperature generally affects significantly the collection efficiency of fine particle but the effect of pressure and temperature appears contrary each other. Therefore, the decrease of collection efficiency caused by the high operating temperature mainly due to the decrease of gaseous density can be remedied by increase of operating pressure. After the evaluation of the program, a series of parametric investigations are performed in terms of major cyclone design or operating parameters such as tangential velocity and vortex finder diameter for dusts of a certain range of particle diameters, etc. As expected, tangential velocity plays the most important effect on the collection efficiency. And the efficiency was not affected significantly by the change of the length of vortex finder but the diameter of vortex finder plays an important role for the enhancement of collection efficiency.

An Analysis of Alternative Materials Collection Evaluation Using a National Alternative Materials Union Catalog (국가대체자료종합목록을 이용한 시각장애인 대체자료 장서 평가 연구)

  • Jang, Boseong
    • Journal of the Korean Society for information Management
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    • v.39 no.3
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    • pp.51-67
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    • 2022
  • The purpose of this study is to diagnose the current status of alternative materials in Korea and to suggest directions and goals for the development of alternative materials. The comprehensive list of national alternative materials and the list of popular and new books were analyzed using the collection evaluation method. Results first the percentage of alternative material collections based on the popular book list for 10 years is 90.1%. The production rate of alternative materials is low in the subjects of 'Language', 'Art' and 'Technology and Science'. Most of the service formats were 'text only daisy'. Second, the CCHR(Common Collection Holding Ratio) and CUI(Collection Uniqueness index) of alternative materials were analyzed using the union catalog. Libraries with a large volume of books have a high proportion of CCHR and CUI. Topics with the highest CCHR are 'Literature' and 'Social Science'. The subjects with the highest collection uniqueness index are 'religion', 'art', and 'language'. Third, the replacement ratio of new books for 3 years is 5.09%. During the same period, the average book purchase rate of public libraries was 8.83%. The average book purchase rate in public libraries is 8.83%, and it is necessary to increase the collection rate of alternative materials based on this ratio.

Development Study of a Predictive Model for the Possibility of Collection Delinquent Health Insurance Contributions (체납된 건강보험료 징수 가능성 예측모형 개발 연구)

  • Young-Kyoon Na
    • Health Policy and Management
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    • v.33 no.4
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    • pp.450-456
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    • 2023
  • Background: This study aims to develop a "Predictive Model for the Possibility of Collection Delinquent Health Insurance Contributions" for the National Health Insurance Service to enhance administrative efficiency in protecting and collecting contributions from livelihood-type defaulters. Additionally, it aims to establish customized collection management strategies based on individuals' ability to pay health insurance contributions. Methods: Firstly, to develop the "Predictive Model for the Possibility of Collection Delinquent Health Insurance Contributions," a series of processes including (1) analysis of defaulter characteristics, (2) model estimation and performance evaluation, and (3) model derivation will be conducted. Secondly, using the predictions from the model, individuals will be categorized into four types based on their payment ability and livelihood status, and collection strategies will be provided for each type. Results: Firstly, the regression equation of the prediction model is as follows: phat = exp (0.4729 + 0.0392 × gender + 0.00894 × age + 0.000563 × total income - 0.2849 × low-income type enrollee - 0.2271 × delinquency frequency + 0.9714 × delinquency action + 0.0851 × reduction) / [1 + exp (0.4729 + 0.0392 × gender + 0.00894 × age + 0.000563 × total income - 0.2849 × low-income type enrollee - 0.2271 × delinquency frequency + 0.9714 × delinquency action + 0.0851 × reduction)]. The prediction performance is an accuracy of 86.0%, sensitivity of 87.0%, and specificity of 84.8%. Secondly, individuals were categorized into four types based on livelihood status and payment ability. Particularly, the "support needed group," which comprises those with low payment ability and low-income type enrollee, suggests enhancing contribution relief and support policies. On the other hand, the "high-risk group," which comprises those without livelihood type and low payment ability, suggests implementing stricter default handling to improve collection rates. Conclusion: Upon examining the regression equation of the prediction model, it is evident that individuals with lower income levels and a history of past defaults have a lower probability of payment. This implies that defaults occur among those without the ability to bear the burden of health insurance contributions, leading to long-term defaults. Social insurance operates on the principles of mandatory participation and burden based on the ability to pay. Therefore, it is necessary to develop policies that consider individuals' ability to pay, such as transitioning livelihood-type defaulters to medical assistance or reducing insurance contribution burdens.