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어린이집 재원 만 3, 4, 5세 유아의 문제행동에 대한 부모와 교사의 인식 비교
유세영,조윤경 한국유아교육ㆍ보육복지학회 2019 유아교육·보육복지연구 Vol.23 No.3
This study is designed to find out the differences in recognition on the child's challenging behaviors between parents and teachers as first solution to challenging behaviors. The child's behavioral checklist for parents(K-CBCL, 1.5-5), the child's behavior evaluation scale for the teachers(C-TRF) were used to rate the behaviors. The questionnaires were distributed to 160 teachers and 160 parents of children of 3, 4, 5 years old at the public child care and education centers located in Incheon and Gyeonggi-do. The results of the study are as follows. First, the parents and teachers groups showed the significant differences in total challenging behaviors. The teachers group rated higher than the parents group at the challenging behaviors of the children except the physical symptom subcategory. Second, the parents and teachers groups showed the significant differences at withdrawal subcategory only in the internalized challenging behaviors. The teachers group rated higher than the parents group, too. Third, the parents and teachers groups showed the significant differences at attention problem and aggressive behavior subcategory in the externalized challenging behaviors. The teachers group also rated higher than the parent group. Based on these results, parents and teachers should acknowledge the differences between two groups on recognizing the challenging behaviors, for intervening appropriately on preschoolers' challenging behaviors. And needs of program development and education for lessening the differences between two groups were discussed. 본 연구는 교사와 부모의 유아 문제행동에 대한 인식을 비교해보고, 가정과 유아교육기관의 연계를 통해 유아의 문제행동을 올바르게 인식하고 부모와 교사의 협력적 접근의 토대를 마련하고자 진행되었다. 이를 위해 인천시와 경기도에 소재한 32개 국공립어린이집에 재원 중인 만 3, 4, 5세 유아의 부모와 담당교사 각 160명, 총 320명을 대상으로, 유아행동평가척도 부모용(K-CBCL. 1.5-5)과 한국판 유아행동 평가척도 교사용(C-TRF) 도구를 포함하는 설문조사를 실시하였다. 연구결과 첫째, 동일한 유아에 대한 전체 문제행동 인식에서 부모와 교사 집단은 유의미한 차이를 나타냈다. 내재화의 신체증상을 제외하고 전 하위 영역에서 부모집단에 비해 교사집단이 높게 평정하였다. 둘째, 동일한 유아에 대한 내재화된 문제행동 인식에서는 위축에서 부모와 교사 두 집단 간에 차이가 있는 것으로 나타났으며, 부모집단에 비해 교사집단이 높게 평정하였다. 셋째, 동일한 유아에 대한 외현화 문제행동 인식 차이에서 주의 집중 문제와 공격행동에서 부모와 교사 집단은 차이를 보였으며, 부모집단에 비해 교사집단이 높게 평정하였다. 이러한 결과에 의거하여 유아의 문제행동에 대한 적합한 조기 중재를 위해 유아 문제행동에 대한 부모와 교사 간 인식의 차이가 있음을 인지하고, 부모와 교사가 인식하는 문제행동의 차이를 줄여나가기 위한 프로그램 개발과 교육이 필요함을 논의되었다.
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Performance of NVMe and NVMe-over-Fabrics in NUMA System with High-Performance Network
유세영 한국지식정보기술학회 2021 한국지식정보기술학회 논문지 Vol.16 No.6
To find a common bottleneck in Data Transfer Nodes using modern NUMA systems, we need to investigate many components in the system. Even efficient modern data transfer systems suffer from performance degradation when used in high-speed data transfer because of the large amount of process load on the system, especially on the CPU and the storage devices. Many efficient storage systems provide a particular benefit in a specific situation. However, there is no comprehensive study of these protocols. There are proposed techniques to optimize CPU load on data transfer and configure storage systems, such as using different CPU core affinity bindings in their Non-Uniform Memory Access (NUMA) system NVMe-over-Fabrics to avoid CPU bottleneck in high-speed data transfer. Such techniques limit the user processes to specific NUMA nodes to reduce foreign memory access overhead. However, this results from a smaller number of available CPU cores in the NUMA system, which is counter-intuitive to run a large workload accessing multiple storage devices. To evaluate the performance of local file systems in high-speed data transfer and CPU affinity binding in a high-speed data transfer system, we performed an analysis of storage and CPU affinity binding in a 100 Gbps network. We achieved the maximum SSD performance threshold using 32 transfer processes with traditional file transfer while using one process per NVMe with NVMe-over-Fabrics and reduced CPU utilization. We could not find significant evidence that binding processes to the local processor or cores improve the file transfer performance with NVMe-over-Fabrics.
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유세영 한국지식정보기술학회 2021 한국지식정보기술학회 논문지 Vol.16 No.3
Big data science collaboration enables science research to discover deeper knowledge of technology human behavior and the universe. To better utilize the big data for science collaboration we need to enable efficient data sharing between remote sites that generate scientific data and analyze it. There have been numerous studies on optimizing data sharing in modern research infrastructure using high-speed networks and DTNs. However, the optimization has been limited to heuristics and manual optimization to find suitable configurations for specific collaboration environments due to a large configuration space and heterogeneous set of hardwares, softwares, and network connections. We present a dynamic optimization system for DTNs that can explore available configuration space in specific environments and automatically adjust to the dynamic environment. We build a next-generation data transfer system that can monitor existing data transfer and use various techniques to find out available resources in the system and tries to utilize them. Our focus in this research is to provide an environment for the infrastructure administrator to examine their existing infrastructure and find an optimal configuration for each environment without minimal human intervention. Our system can find optimal storage configuration and apply transfer parameters in the DTNs in a science infrastructure in real-time to maximize available resources.
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