• Title/Summary/Keyword: Korea human scale

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An data classification and application of psychophyscial scale (Psychophyscial scale에 의한 자료 분류 및 적용)

  • 곽효연;제종식
    • Journal of the Korea Society of Computer and Information
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    • v.1 no.1
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    • pp.139-146
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    • 1996
  • The estimation technique of psychophysical magnitude Is useful tool which measures to subjective feeling or opinion of human. This paper Introduces properties of the measured data, scales(nominal. ordinal. Interval. and ratio scale). and right analyzing methods of the measured data.

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A case study on misuse of psychophysical scales (Psychophysical Scale 적용시 오류에 관한 사례조사)

  • 곽지영;박성준;한성호
    • Proceedings of the ESK Conference
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    • 1993.10a
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    • pp.133-144
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    • 1993
  • Psychophysical data, in general, belong to one of the four scale categories : Nominal, Ordinal, Interval, and Ratio Scale. This paper introduces properties of the four scale categories and describes some psychophysical scales that attempt to measure subjective feeling or opinion of human. In addition, guidelines of analyzing and interpreting measured data are suggested. Some examples of analyzing and interpreting paychophysical data inappropriately are presented especially with category scales which have been used most widely in measuring subjective information.

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The Empirical Study on Relation between R&D Innovation Capability and Performance in Knowledge-Based Service Firms (R&D 혁신역량과 기업성과 간의 관계 연구)

  • Kim, Moon Sun;Kim, Soo Jung;Nam, Kyung H.
    • Journal of Korean Society for Quality Management
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    • v.40 no.4
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    • pp.631-640
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    • 2012
  • Purpose: This empirical study is focused on the relationship between innovation capability (R&D and Human Resource innovation) and performance in knowledge-based service firms. Methods: We build research model to test how each of innovation capability on technology and human resource is influenced on their financial and non-financial performance in the knowledge-based service industries. Based on the previous research, we hypothesized the factors are regarded innovation capabilities of the firms as the scale of R&D and human resources. Because this study is especially targeted to the performance of knowledge-based service firms. With the survey on 424 main knowledge-based service firms, the multi-regression analysis was performed. Results: The result showed that the scale of R&D and human resources capabilities are main factors for knowledge-based service firms' performance, which reflects the current industrial structure. Conclusion: This study empirically demonstrated that human resources are most important to the growth of knowledge-based service firms.

Development and Evaluation of Shared Medical Decision-Making Scale for End-of-Life Patients in Korea (한국형 공유 의료적 의사 결정 측정도구 개발 및 평가)

  • Jo, Kae-Hwa
    • Journal of Korean Academy of Nursing
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    • v.42 no.4
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    • pp.453-465
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    • 2012
  • Purpose: The study was done to develop a shared decision-making scale for end-of-life patients in Korea. Methods: The process included construction of a conceptual framework, generation of initial items, verification of content validity, selection of secondary items, preliminary study, and extraction of final items. The participants were 388 adults who lived in one of 3 Korean metropolitan cities: Seoul, Daegu, or Busan. Item analysis, factor analysis, criterion related validity, and internal consistency were used to analyze the data. Data collection was done from July to October 2011. Results: Thirty-four items were selected for the final scale, and categorized into 7 factors explaining 61.9% of the total variance. The factors were labeled as sharing information (9 items), constructing system (7 items), explanation as a duty (5 items), autonomy (4 items), capturing time (3 items), participation of family (3 items), and human respect (3 items). The scores for the scale were significantly correlated among shared decision-making scale, terminating life support scale, and dignified dying scale. Cronbach's alpha coefficient for the 34 items was .94. Conclusion: The above findings indicate that the shared decision-making scale has a good validity and reliability when used for end-of-life patients in Korea.

Detection of Single Nucleotide Polymorphism in Human IL-4 Receptor by PCR Amplification of Specific Alleles

  • Hwang, Sue Yun;Kim, Seung Hoon;Hwang, Sung Hee;Cho, Chul Soo;Kim, Ho Youn
    • Animal cells and systems
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    • v.5 no.2
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    • pp.153-156
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    • 2001
  • A key aspect of genomic research in the “post-genome era”is to associate sequence variations with heritable phenotypes. The most common variations in the human genome are single nucleotide polymorphisms (SNPs) that occur approximately once in every 500 to 1,000 bases. Although analyzing the phenotypic outcome of these SNPs is crucial to facilitate large-scale association studies of genetic diseases, detection of SNPs from an extended number of human DNA samples is often difficult, labor-intensive and time-consuming. Recent development in SNP detection methods using DNA microarrays and mass spectrophotometry has allowed automated high throughput analyses, but such equipments are not accessible to many scientists. In this study, we demonstrate that a simple PCR-based method using primers with a mismatched base at the 3'-end provides a fast and easy tool to identify known SNPs from human genomic DNA in a regular molecular biology laboratory. Results from this PCR amplification of specific alleles (PASA) analysis efficiently and accurately typed the Q576R polymorphism of human IL4 receptor from the genomic DNAs of 29 Koreans, including 9 samples whose genotype could not be discerned by the conventiona1 PCR-SSCP (single strand conformation polymorphism) method. Given the increasing attention to disease-associated polymorphisms in genomic research, this alternative technique will be very useful to identify SNPs in large-scale population studies.

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Emotion Recognition Using The Color Image Scale in Clothing Images (의류 영상에서 컬러 영상 척도를 이용한 감성 인식)

  • Lee, Seul-Gi;Woo, Hyo-Jeong;Ryu, Sung-Pil;Kim, Dong-Woo;Ahn, Jae-Hyeong
    • The Journal of the Korea Contents Association
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    • v.14 no.11
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    • pp.1-6
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    • 2014
  • Emotion recognition is defined as that machines automatically recognize human emotions. Because the human emotions is very subjective, it is impossible to measure objectively. Therefore, the goal of emotion recognition is to obtain a measure that is agreed by as many people as possible. Emotion recognition in a image is implemented as the method that matches human emotions to the various features of the image. In the paper, we propose an emotion recognition system using color features of clothing image based on the Kobayashi's image scale. The proposed system stores colors of image scale into a database. And extracted major colors from a input clothing image are compared with those in the database. The proposed system can obtain three emotions maximally. In order to evaluate the system performance 70 observers are tested. The test results shows that recognized emotions of the proposed system are very similar to the observers emotions.

Automatic Vowel Onset Point Detection Based on Auditory Frequency Response (청각 주파수 응답에 기반한 자동 모음 개시 지점 탐지)

  • Zang, Xian;Kim, Hag-Tae;Chong, Kil-To
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.1
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    • pp.333-342
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    • 2012
  • This paper presents a vowel onset point (VOP) detection method based on the human auditory system. This method maps the "perceptual" frequency scale, i.e. Mel scale onto a linear acoustic frequency, and then establishes a series of Triangular Mel-weighted Filter Bank simulate the function of band pass filtering in human ear. This nonlinear critical-band filter bank helps greatly reduce the data dimensionality, and eliminate the effect of harmonic waves to make the formants more prominent in the nonlinear spaced Mel spectrum. The sum of mel spectrum peaks energy is extracted as feature for each frame, and the instinct at which the energy amplitude starts rising sharply is detected as VOP, by convolving with Gabor window. For the single-word database which contains 12 vowels articulated with different kinds of consonants, the experimental results showed a good average detection rate of 72.73%, higher than other vowel detection methods based on short-time energy and zero-crossing rate.

Methods to Improve Fire Suppression Capability by Forest Fire Simulation Analysis (산불화재 시뮬레이션분석에 의한 화재진압능력 개선방안)

  • Jeong-Il, Lee;Sung-bae, Cho
    • Journal of the Korea Safety Management & Science
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    • v.24 no.4
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    • pp.125-134
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    • 2022
  • Forest fires in Korea usually start in the fall and occur every year until spring. Most wildfires are human resources that combine topographical characteristics and carelessness, and failure to respond in the initial stage and lack of cleanup are spreading to large-scale wildfires. In order to prevent these wildfires, active cooperation from the public is essential. As can be seen from recent wildfires, the attention of the public is needed above all else because large-scale wildfires in Korea are occurring due to the people's negligence. If a wildfire spreads and becomes large, it causes damage to life and property, and the damage is irreversible. In this study, various methods were used to prevent forest fires and improve initial suppression ability. In order to minimize damage, the model analyzed by the 119 Special Rescue Team in Gangwon, Chungcheong and nearby forest fires was analyzed on the combustion progress and wind direction by time period. The propagation speed by the wind direction was simulated. Until now, most of the wildfires have been extinguished by firefighting, but I hope that the Forest Service will take the lead and maintain coordination with related organizations.

Multi-resolution Fusion Network for Human Pose Estimation in Low-resolution Images

  • Kim, Boeun;Choo, YeonSeung;Jeong, Hea In;Kim, Chung-Il;Shin, Saim;Kim, Jungho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.7
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    • pp.2328-2344
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    • 2022
  • 2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.