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RISS 인기검색어
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- 저자 : Maria Wolters (검색결과 4 건)
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자동 범주유창성검사 평가를 향하여: 단어 군집화를 활용한 그룹간 구별
이용재(Yong-Jae Lee),Maria Wolters,이희진(Hee-Jin Lee),박종철(Jong C. Park) 한국정보과학회 2012 한국정보과학회 학술발표논문집 Vol.39 No.1B
The Category Fluency Test (CFT) is a widely used verbal fluency test. The standard measure of scoring the test is the number of distinct words that a subject generates during the test. Recently, other measures have also been proposed to evaluate performance, such as clustering and switching. In this study, we examine clusters and switches can be assessed using word similarity measures. Based on these measures, we can distinguish between subject groups.
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Blog Corpus-based Clustering Scheme for Category Fluency Test (CFT) Data Clustering
Yong-Jae Lee(이용재),Maria Wolters,Hee-Jin Lee(이희진),Jong C. Park(박종철) 한국HCI학회 2013 한국HCI학회 학술대회 Vol.2013 No.1
치매 진단 도구의 하나인 범주유창성검사는 치매 환자의 의미기억과 언어 유창성 수행 능력을 평가하는데 널리 사용되고 있다. 범주유창성검사의 수행 결과는 피험자가 검사 중 나열하는 항목들의 총갯수를 바탕으로 평가되는데, 최근에는 검사 데이터의 군집 및 전이 패턴을 고려하여 수행 결과를 평가하려는 연구들과 이에 대한 자동화 기법들이 제안되고 있다. 본 연구에서는 범주유창성검사 데이터의 군집 및 전의 패턴을 계산학적으로 분석하기 위해 블로그 코퍼스 기반 군집 계획을 제안하고 기존의 범주유창성검사 군집 자동화 연구와의 비교를 통해 블로그 코퍼스 기반 군집 계획 구성의 필요성을 보인다. Category Fluency Test (CFT) is one of the most popular methods to screen dementia and is used in particular to evaluate the organization of the semantic memory and verbal fluency of a patient with dementia. The CFT performance is assessed according to the number of items each patient produces during the test. Recently, however, researchers have also proposed to evaluate the performance by considering the pattern of clusters and switches of the CFT data, with efforts to figure out the clusters and switches on the CFT data computationally. In this work, we propose a novel blog corpus-based clustering scheme to analyze the clusters and switches of the CFT data in a computational manner. In addition, we will argue for the need of the blog corpus-based clustering scheme by comparing it with the previous work on automatic CFT data clustering.
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Xu, Jun,Chen, Lie-Wen,Tsang, ManYee Betty,Wolter, Hermann,Zhang, Ying-Xun,Aichelin, Joerg,Colonna, Maria,Cozma, Dan,Danielewicz, Pawel,Feng, Zhao-Qing,Le Fè,vre, Arnaud,Gaitanos, Theodoros,Hartn American Physical Society 2016 Physical Review C Vol.93 No.4
<P>Transport simulations are very valuable for extracting physics information from heavy-ion-collision experiments. With the emergence of many different transport codes in recent years, it becomes important to estimate their robustness in extracting physics information from experiments. We report on the results of a transport-code-comparison project. Eighteen commonly used transport codes were included in this comparison: nine Boltzmann-Uehling-Uhlenbeck-type codes and nine quantum-molecular-dynamics-type codes. These codes have been asked to simulate Au + Au collisions using the same physics input for mean fields and for in-medium nucleon-nucleon cross sections, as well as the same impact parameter, the similar initialization setup, and other calculational parameters at 100 A and 400 A MeV incident energy. Among the codes we compare one-body observables such as rapidity and transverse flow distributions. We also monitor nonobservables such as the initialization of the internal states of colliding nuclei and their stability, the collision rates, and the Pauli blocking. We find that not completely identical initializations may have contributed partly to different evolutions. Different strategies to determine the collision probabilities and to enforce the Pauli blocking also produce considerably different results. There is a substantial spread in the predictions for the observables, which is much smaller at the higher incident energy. We quantify the uncertainties in the collective flow resulting from the simulation alone as about 30% at 100 A MeV and 13% at 400 A MeV, respectively. We propose further steps within the code comparison project to test the different aspects of transport simulations in a box calculation of infinite nuclear matter. This should, in particular, improve the robustness of transport model predictions at lower incident energies, where abundant amounts of data are available.</P>
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Analyzing the Patterns of Switching and Clustering on CFT data using Hidden Markov Model
이용재(Yong-Jae Lee),이희진(Hee-Jin Lee),Maria Wolters,박종철(Jong C. Park) 한국HCI학회 2012 한국HCI학회 학술대회 Vol.2012 No.1
치매의 조기 진단은 환자들과 그들의 보호자들이 치매에 대비할 수 있는 더많은 시간을 가질 수 있게 한다. 치매를 진단하는 방법들 중 하나인 범주유창성검사는 치매 환자의 의미기억과 언어 유창성 수행 능력을 평가하는데 사용된다. 최근 들어 범주유창성검사의 수행능력을 평가하는 다양한 척도들이 연구되고 있는데, 특히 범주유창성검사 데이터의 군집과 전이가 중요한 요소로 고려되고 있다. 본 연구에서는 은닉 마르코프 모델을 사용하여 범주유창성검사 데이터의 군집과 전이 패턴을 분석하고 이들에 대한 종합적인 분석이 언어 유창성 수행 능력의 중요한 특징을 드러낸다는 점을 보인다. Early detection of dementia allows people to have more time to prepare themselves for the symptom. As one of the methods to screen dementia, Category Fluency Test (CFT) is used to evaluate the organization of semantic memory and to assess the verbal fluency performance of patients with dementia. Recently, various measures to evaluate their CFT performance have been studied and, in particular, clusters and switches of the CFT data are considered as important factors. In this work, we analyze the clusters and switches of the CFT data by using Hidden Markov Model (HMM) to verify the hypothesis that a comprehensive pattern analysis of their switches and clusters can reveal important characteristics of verbal fluency performance.
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