• Journal of the Korean Society of Costume
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• v.36
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• pp.139-148
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• 1998

In order to know what sorts of features of neck form may be required to make plans for tight collars, the neck form of young japanese women were measured three demension-ally using GRASP(Grating Projection System for Profiling) and plaster torso. By the BASIC language in NEC computer and EXCEL program in MACINTOSHI computer, it became possible to draft a number of neck surface auomatically, therefore, we got analysis of a mass of subjects. Thed following results were obtained: 1. There was a large individual difference in the shape of neck, in particular, on the front and side curves of the neck base line, where the undulation of clavicular part of neck and inclination of shoulder are refracted. 2. When designing a stand collar, from the viewpoint of clothing strcture, it is important to grasp exactly the shapes of the neck, such as the line of the neck base, the neck gradient, back neck length, back neck width & girth. 3. According to the somatotypes(turing-over, standard, bending type), there were different the method of the basic collar pattern making.

• The Mathematical Education
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• v.57 no.2
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• pp.75-92
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• 2018

Based on Perceptions about Mathematics Teachers (PMT) perceived by high school students, measured by 2189 students from Seoul Educational Longitudinal Study 2014 (SELS 2014), latent profile analysis (LPA) identified five distinct types of student groups (positive, partial positive, middle, negative, extreme negative). These student of positive, middle, and negative groups are positive, moderate and negative perceptions about math teachers. Partial positive group generally had a positive perception about mathematics teachers, extremely negative group was very negative about mathematics teachers. Both of these groups had peculiarly inconsistent trends and several anomalies. The Multinomial logistic regression analyses also indicated that individual factors (gender, major, self-concept, resilience, self-assessment, career maturity), school factors (friendship, relationship with school teachers) and parental factors (academic-relationship, emotional-relationship) were significant predictors of PMT profile groups. The Analysis of variance also indicated that mathematics class (attitude, satisfaction and atmosphere), Mathematics achievement were significant predictors of PMT profile groups. The profiling of perceptions about mathematics teachers resulted in enhanced understanding of the complex range of processes students employed. During mathematics class, implementation of smooth interactions and communications between students and teachers added in the teaching and learning of mathematics.

• Journal of Home Health Care Nursing
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• v.22 no.1
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• pp.59-68
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• 2015

Purpose: The purpose of this study was to analyze nursing research using data envelopment analysis and suggest directions for future research. Methods: We established -criteria literature search. e reviewed 45 from RISS, KISS, National assembly library and NDSL DB. Data were collected on December 17, 2013. developed analytic framework of literature reviews using Yun's study. This framework had 8 items related to approach of data envelopment analysis. Results: literature established -criteria. Average numbers of input and output variables were 2.4 and 4.2, respectively. All selected research conducted efficiency analysis, analysis, and inefficiency analysis. However only 3 research. Conclusion: he results of studysuggest that data envelopment are needed to enhance efficiencies of nursing organization as follows individual nurse's profiling to develop customized performance management plans; patient centered nursing interventions; and financial performance financial reports.

• Genomics & Informatics
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• v.6 no.3
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• pp.126-129
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• 2008

The robust identification and comprehensive profiling of copy number alterations (CNAs) is highly challenging. The amount of data obtained from high-throughput technologies such as array-based comparative genomic hybridization is often too large and it is required to develop a comprehensive and versatile tool for the detection and visualization of CNAs in a genome-wide scale. With this respective, we introduce a software framework, CGHscape that was originally developed to explore the CNAs for the study of copy number variation (CNV) or tumor biology. As a standalone program, CGHscape can be easily installed and run in Microsoft Windows platform. With a user-friendly interface, CGHscape provides a method for data smoothing to cope with the intrinsic noise of array data and CNA detection based on SW-ARRAY algorithm. The analysis results can be demonstrated as log2 plots for individual chromosomes or genomic distribution of identified CNAs. With extended applicability, CGHscape can be used for the initial screening and visualization of CNAs facilitating the cataloguing and characterizing chromosomal alterations of a cohort of samples.

• Food Science and Industry
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• v.54 no.3
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• pp.145-159
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• 2021

Conventional nutrition services involve producer-oriented approaches without considering the differences in the characteristics and circumstances of each individual, whereas personalized nutrition services are consumer-oriented concepts that provide products and services for maintaining optimal health conditions based on the genetic, physiological, and metabolic characteristics of individuals, with these products based on balanced nutrition and healthy living. Currently, methods for evaluating dietary habits, monitoring dietary behaviors, deep phenotyping, and metabotyping via microbiota profiling, as well as methods for predicting big data by using machine learning, have been previously studied in Korea and abroad. With the development of medical technology and the improvement of hygiene, the demand for personalized nutrition and health services for healthier, happier, and more satisfying lives is rapidly increasing. Therefore, based on scientific technologies, attempts are needed to advance these services into global personalized markets and to boost the global competitiveness of countries and companies.

• Food Science and Industry
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• v.50 no.1
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• pp.2-10
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• 2017

Human have eaten various traditional fermented foods for a numbers of million years for health benefit as well as survival. The beneficial effects of fermented foods have been resulted from complex microbial communications within the fermented foods. Therefore, the holistic approaches for individual identification and complete microbial profiling involved in their communications have been of interest to food microbiology fields. Microbiome is the ecological community of microorganisms that literally share our environments including foods as well as human body. However, due to the limitation of culture-dependent methods such as simple isolations of just culturable microorganisms, the culture-independent methods have been consistently developed, resulting in new light on the diverse non-culturable and hitherto unknown microorganisms, and even microbial communities in the fermented foods. For the culture-independent approaches, the food microbiome has been deciphered by employing various molecular analysis tools such as fluorescence in situ hybridization, quantitative PCR, and denaturing gradient gel-electrophoresis. More recently, next-generation-sequencing (NGS) platform-based microbiome analysis has been of interest, because NGS is a powerful analytical tool capable of resolving the microbiome in respect to community structures, dynamics, and activities. In this overview, the development status of analysis tools for the fermented food microbiome is covered and research trend for NGS-based food microbiome analysis is also discussed.

• ETRI Journal
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• v.45 no.2
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• pp.318-328
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• 2023

Recently, embedded systems, such as mobile platforms, have multiple processing units that can operate in parallel, such as centralized processing units (CPUs) and neural processing units (NPUs). We can use deep-learning compilers to generate machine code optimized for these embedded systems from a deep neural network (DNN). However, the deep-learning compilers proposed so far generate codes that sequentially execute DNN operators on a single processing unit or parallel codes for graphic processing units (GPUs). In this study, we propose PartitionTuner, an operator scheduler for deep-learning compilers that supports multiple heterogeneous PUs including CPUs and NPUs. PartitionTuner can generate an operator-scheduling plan that uses all available PUs simultaneously to minimize overall DNN inference time. Operator scheduling is based on the analysis of DNN architecture and the performance profiles of individual and group operators measured on heterogeneous processing units. By the experiments for seven DNNs, PartitionTuner generates scheduling plans that perform 5.03% better than a static type-based operator-scheduling technique for SqueezeNet. In addition, PartitionTuner outperforms recent profiling-based operator-scheduling techniques for ResNet50, ResNet18, and SqueezeNet by 7.18%, 5.36%, and 2.73%, respectively.

• The Korean Journal of Physiology and Pharmacology
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• v.28 no.5
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• pp.403-411
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• 2024

The global spread of flaviviruses has triggered major outbreaks worldwide, significantly impacting public health, society, and economies. This has intensified research efforts to understand how flaviviruses interact with their hosts and manipulate the immune system, underscoring the need for advanced research tools. RNA-sequencing (RNA-seq) technologies have revolutionized our understanding of flavivirus infections by offering transcriptome analysis to dissect the intricate dynamics of virus-host interactions. Bulk RNA-seq provides a macroscopic overview of gene expression changes in virus-infected cells, offering insights into infection mechanisms and host responses at the molecular level. Single-cell RNA sequencing (scRNA-seq) provides unprecedented resolution by analyzing individual infected cells, revealing remarkable cellular heterogeneity within the host response. A particularly innovative advancement, virus-inclusive single-cell RNA sequencing (viscRNA-seq), addresses the challenges posed by non-polyadenylated flavivirus genomes, unveiling intricate details of virus-host interactions. In this review, we discuss the contributions of bulk RNA-seq, scRNA-seq, and viscRNA-seq to the field, exploring their implications in cell line experiments and studies on patients infected with various flavivirus species. Comprehensive transcriptome analyses from RNA-seq technologies are pivotal in accelerating the development of effective diagnostics and therapeutics, paving the way for innovative treatments and enhancing our preparedness for future outbreaks.

• Atmosphere
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• v.34 no.3
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• pp.325-336
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• 2024

Radiosonde is an important in-situ profiling instrument that measures atmospheric temperature, moisture, and wind structure from the surface to the middle stratosphere. The operational radiosonde measurements are carried out more than twice (at 0000 UTC and 1200 UTC) daily at approximately 1,300 World Meteorological Organization (WMO) stations and play a pivotal role in daily weather forecasts. It also contributes to the monitoring of atmospheric structure by providing the key physical information like temperature and pressure, forming the backbone of atmospheric (re)analyses and numerical weather forecasts. Additionally, high-resolution radiosonde profiles are used for calibration and evaluation of satellite products. Despite these advantages, radiosonde measurements are mostly limited to operational uses due to the high initial cost of ground instrument setup required for data transmission and reception. This study outlines a cost-effective (roughly one-tenth of the operational cost) method for establishing the ground station and the necessary radiosonde measurement procedures, offering guidance for individual researchers or university-level instructors.

• Geophysics and Geophysical Exploration
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• v.18 no.4
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• pp.181-196
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• 2015

A 3.5 kHz or chirp sub-bottom profiling survey is widely used in the marine geological and engineering purpose exploration. However, swells in the sea degrade the quality of the survey data. The horizontal continuity of profiler data can be enhanced and the quality can be improved by correcting the influence of the swell. Accurate detection of sea bottom location is important in correcting the swell effect. In this study, we tried to pick sea bottom locations by finding the position of crossing a threshold of the maximum value for the raw data and transformed data of envelope or energy ratio. However, in case of the low-quality data where the sea bottom signals are not clear due to sea wave noise, automatic sea bottom detection at the individual traces was not successful. We corrected the mispicks for the low quality data and obtained satisfactory results by picking a sea bottom within a range considering the previous average of sea bottom, and excluding unreliable big-difference picks. In case of trace by trace picking, fewest mispicks were found when using energy ratio data. In case of picking considering the previous average, the correction result was relatively satisfactory when using raw data.