放射光励起半導体素子作製プロセスに関する研究

名古屋大学Nagoya University博士(工学)名古屋大学博士学位論文 学位の種類:博士(工学) (論文) 学位授与年月日:平成9年3月12日doctoral thesi

幼児教育の質を探求する : 「子ども暮らし」を中心とした実践から<教育科学>

Recently, more attention is being paid to improving the quality of Early Childhood Education (ECE) from an international viewpoint. The challenge, however, is the difficulty in quantifying what ‘progress’ in ECE means. Measuring children’s progress in ECE is difficult because they are influenced both by their experiences in school and their daily life experiences. Further, there are significant differences in individual children’s development. However, assessment is important in ECE to ensure that programs are meeting the needs of children. This study examined how to measure the ‘quality of progress’ in ECE using participant observation of two activities on a spring picnic of a Certified Children Centre and the interactions between nursery children and kindergarten children. The results show that it is necessary to define the quality of nursery education in terms of the emotional richness and true nature of individual children, while limiting assessment on ‘quality of progress’ to a self-assessment by teachers. Quality assessment is best achieved through a ‘parallel-run’ observation method, while maintaining a reasonable distance from the children. There is a strong possibility, however, that the self-assessment will end up in complacency. Therefore, I suggest that self-assessments should be paired with conversations with other practitioners and researchers about the results of their ‘parallel-run’ observations and self-assessments.textapplication/pdfdepartmental bulletin pape

Observation of B+→pp̅π+, B0→pp̅K0, and B+→pp̅K*+

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SOME VARIANTS OF A STRICT-SET-CONTRACTION

application/pdfdepartmental bulletin pape

2008 BBSRC Tools and Resources Development Fund Application - pubmed2ensembl: a resource for linking biological literature to genome sequences

<p>2008 BBSRC Tools and Resources Development Fund application. Awarded.</p

Identification of transcription factor contexts in literature using machine learning approaches-1

Del; BM = biological model)<p><b>Copyright information:</b></p><p>Taken from "Identification of transcription factor contexts in literature using machine learning approaches"</p><p>http://www.biomedcentral.com/1471-2105/9/S3/S11</p><p>BMC Bioinformatics 2008;9(Suppl 3):S11-S11.</p><p>Published online 11 Apr 2008</p><p>PMCID:PMC2352869.</p><p></p

Identification of transcription factor contexts in literature using machine learning approaches-2

; BM = biological model)<p><b>Copyright information:</b></p><p>Taken from "Identification of transcription factor contexts in literature using machine learning approaches"</p><p>http://www.biomedcentral.com/1471-2105/9/S3/S11</p><p>BMC Bioinformatics 2008;9(Suppl 3):S11-S11.</p><p>Published online 11 Apr 2008</p><p>PMCID:PMC2352869.</p><p></p

Term features were extracted through several steps, including extraction of term candidates and acronyms, their inflectional and orthographic normalisation, and estimation of termhoods for synterms

<p><b>Copyright information:</b></p><p>Taken from "Mining protein function from text using term-based support vector machines"</p><p></p><p>BMC Bioinformatics 2005;6(Suppl 1):S22-S22.</p><p>Published online 24 May 2005</p><p>PMCID:PMC1869015.</p><p></p

Additional file 1: of Modelling and extraction of variability in free-text medication prescriptions from an anonymised primary care electronic medical record research database

Table S1. Examples of commonly used Latin abbreviations in medication. Table S2. Dictionaries used for the identification of dosage information. Table S3. System errors from the test dataset (220 prescriptions). (DOCX 25 kb

Clinical record data with injected outbreaks annotated with MPC and topic number.

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