• Title/Summary/Keyword: step complexity measure

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The Step Complexity Measure - Its Meaning and Applications

  • Park, Jinkyun;Wondea Jung;Kim, Jaewhan;Jaejoo Ha
    • Nuclear Engineering and Technology
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    • v.35 no.1
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    • pp.80-90
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    • 2003
  • According to related studies, it was revealed that the procedural deviation plays a significant role in initiating accidents or incidents. This means that, to maximize safety, it is indispensable to be able to answer the question of “why the operators deviate from procedures\ulcorner” In this study, the SC (step complexity) measure is introduced to investigate its applicability for studying the procedural deviation, since it was shown that the change of the operators' performance is strongly correlated with the change of SC scores. This means that the SC measure could play an important role for researches related to the procedural deviation, since it is strongly believed that complicated procedures would affect both the operator' performance and the possibility of the procedural deviation. Thus, to ensure this expectation, the meaning of the SC measure is investigated through brief explanations including the necessity, theoretical basis and verification activities of the SC measure. As a result, it is confirmed that the SC measure can be used to explain the change of the operators' performance due to the task complexity implied by procedures. In addition, it seems that the SC measure nay be useful for various purposes, particularly for scrutinizing the relationship between the procedural deviation and complicated procedures.

A FULL-NEWTON STEP INFEASIBLE INTERIOR-POINT ALGORITHM FOR LINEAR PROGRAMMING BASED ON A SELF-REGULAR PROXIMITY

  • Liu, Zhongyi;Chen, Yue
    • Journal of applied mathematics & informatics
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    • v.29 no.1_2
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    • pp.119-133
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    • 2011
  • This paper proposes an infeasible interior-point algorithm with full-Newton step for linear programming. We introduce a special self-regular proximity to induce the feasibility step and also to measure proximity to the central path. The result of polynomial complexity coincides with the best-known iteration bound for infeasible interior-point methods, namely, O(n log n/${\varepsilon}$).

A Simple Tandem Method for Clustering of Multimodal Dataset

  • Cho C.;Lee J.W.;Lee J.W.
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.05a
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    • pp.729-733
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    • 2003
  • The presence of local features within clusters incurred by multi-modal nature of data prohibits many conventional clustering techniques from working properly. Especially, the clustering of datasets with non-Gaussian distributions within a cluster can be problematic when the technique with implicit assumption of Gaussian distribution is used. Current study proposes a simple tandem clustering method composed of k-means type algorithm and hierarchical method to solve such problems. The multi-modal dataset is first divided into many small pre-clusters by k-means or fuzzy k-means algorithm. The pre-clusters found from the first step are to be clustered again using agglomerative hierarchical clustering method with Kullback- Leibler divergence as the measure of dissimilarity. This method is not only effective at extracting the multi-modal clusters but also fast and easy in terms of computation complexity and relatively robust at the presence of outliers. The performance of the proposed method was evaluated on three generated datasets and six sets of publicly known real world data.

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A study on object recognition using morphological shape decomposition

  • Ahn, Chang-Sun;Eum, Kyoung-Bae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.05a
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    • pp.185-191
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    • 1999
  • Mathematical morphology based on set theory has been applied to various areas in image processing. Pitas proposed a object recognition algorithm using Morphological Shape Decomposition(MSD), and a new representation scheme called Morphological Shape Representation(MSR). The Pitas's algorithm is a simple and adequate approach to recognize objects that are rotated 45 degree-units with respect to the model object. However, this recognition scheme fails in case of random rotation. This disadvantage may be compensated by defining small angle increments. However, this solution may greatly increase computational complexity because the smaller the step makes more number of rotations to be necessary. In this paper, we propose a new method for object recognition based on MSD. The first step of our method decomposes a binary shape into a union of simple binary shapes, and then a new tree structure is constructed which ran represent the relations of binary shapes in an object. finally, we obtain the feature informations invariant to the rotation, translation, and scaling from the tree and calculate matching scores using efficient matching measure. Because our method does not need to rotate the object to be tested, it could be more efficient than Pitas's one. MSR has an intricate structure so that it might be difficult to calculate matching scores even for a little complex object. But our tree has simpler structure than MSR, and easier to calculated the matchng score. We experimented 20 test images scaled, rotated, and translated versions of five kinds of automobile images. The simulation result using octagonal structure elements shows 95% correct recognition rate. The experimental results using approximated circular structure elements are examined. Also, the effect of noise on MSR scheme is considered.

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Improvement of Component Design using Component Metrics (컴포넌트 메트릭스를 이용한 컴포넌트 설계 재정비)

  • 고병선;박재년
    • Journal of KIISE:Software and Applications
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    • v.31 no.8
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    • pp.980-990
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    • 2004
  • The component-based development methodology aims at the high state of abstraction and the reusability with components larger than classes. It is indispensible to measure the component so as to improve the quality of the component-based system and the individual component. And, the quality of the component should be improved through putting the results into the process of the development. So, it is necessary to study the component metric which can be applied in the stage of the component analysis and design. Hence, in this paper, we propose component cohesion, coupling, independence metrics reflecting the information extracted in the step of component analysis and design. The proposed component metric bases on the similarity information about behavior patterns of operations to offer the component's service. Also, we propose the redesigning process for the improvement of component design. That process uses the techniques of clustering and is for the thing that makes the component as the independent functional unit having the low complexity and easy maintenance. And, we examine that the component design model can be improved by the component metrics and the component redesigning process.

Patterns of Restricted and Repetitive Behaviors in Toddlers and Young Children with Autism Spectrum Disorder

  • Song, Da-Yea;Kim, Dabin;Lee, Hannah J.;Bong, Guiyoung;Han, Jae Hyun;Yoo, Hee Jeong
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.33 no.2
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    • pp.35-40
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    • 2022
  • Objectives: Restricted and repetitive behaviors (RRBs) are a core symptom in the diagnosis of autism spectrum disorder (ASD). The complexity of behavioral patterns has called for the creation of phenotypically homogeneous subgroups among individuals with ASD. The purpose of this study was 1) to investigate the different types of RRBs and 2) to explore whether subgroups created by RRBs would show unique levels of functioning in toddlers and young children with ASD. Methods: A total of 313 children with ASD, aged 12-42 months were included in the analysis. The Autism Diagnostic Interview-Revised was used to obtain information on the different types of RRBs by grouping 15 items into six categories. The Vineland Adaptive Behaviors Scale, a parent-reported questionnaire, was used to measure adaptive functioning. A portion of the children were analyzed separately for verbal-related RRBs based on their expressive language level. Two-step cluster analysis using RRB groups as features was used to create subgroups. Analysis of covariance while covarying for age and language was performed to explore the clinical characteristics of each cluster group. Results: Sensory-related RRBs were the most prevalent, followed by circumscribed interests, interest in objects, resistance to change, and repetitive body movements. A subset of the children was analyzed separately to explore verbal-related RRBs. Four cluster groups were created based on reported RRBs, with multiple RRBs demonstrating significant delays in adaptive functioning. Conclusion: Heterogeneity of RRBs emerges at a young age. The different patterns of RRBs can be used as valuable information to determine developmental trajectories with better implications for treatment approaches.

Development of a Tool to Measure Suffering in Patients with Cancer (암환자의 고통 측정도구 개발에 관한 연구)

  • 강경아
    • Journal of Korean Academy of Nursing
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    • v.29 no.6
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    • pp.1365-1378
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    • 1999
  • This study is a methodological research study to develop an instrument to measure in patients with cancer and to test the validity and reliability of the instrument. The research procedure was as follows : 1) The first step was to develop conceptual framework based on a comprehensive review of the literature and in-depth interviews with patients with cancer. This conceptual framework was organized in to three dimensions (the intrapersonal dimension, the significant-other and context related dimension, the transcendental dimension). Initially 59 items were adopted. 2) These items were analyzed through the index of content validity(CVI) and 53 items were selected which met more than 80% on the CVI. 3) The pretest was carried out with 87 patients with cancer. After the pretest results were analyzed by item analysis, 44 items were selected. A second test of content validity was conducted and 6 items were eliminated considering the 80% CVI. 4) To test for reliability and validity, data collection was done during the period from January 25, 1999, to February 26, 1999. The subjects for the test were 160 patients with cancer and 185 healthy persons. analysis, item analysis and multitrait-multimethod method to analyze validity. The findings are as follows : 1) The Cronbach's alpha coefficient for internal consistency was .92 for the total 38 items and .79, .82, .85, for the three dimensions in that order. 2) The item analysis was based on the corrected item to total correlation coefficient( .30 or more) and information about the alpha estimate if this item was dropped from the scale. 3) As a result of the initial factor analysis using principal component analysis and varimax rotation, one item was deleted because of factor complexity (indiscriminate factor loadings). In the secondary factor analysis, 7 factors with eigenvalue of more than 1.0 were extracted and these factors explained 56 percents of the total variance. The seven factors were labeled as 'family relationship', 'emotional condition', 'physical discomfort', 'meaning and goal of life', 'contextual stimuli', 'change of body image', 'guilt feelings'. 4) The convergence effect between this instrument and the life satisfaction scale was identified and there was significant positive correlation(r= .52, p= .00). The discriminant validity between this instrument and the depression scale(CES-D) was tested and there was significant negative correlation(r= -.50, p= .00). The instrument for accessing the suffering of patients with cancer developed in this study was identified as a tool with a high degree of reliability and validity. In this sense, this tool can be effectively utilized for assessment in caring for patients with cancer.

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