• Radiation Oncology Journal
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• v.31 no.2
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• pp.88-96
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• 2013

Purpose: This study identifies accident sequences from the past accidents in order to help the risk analysis application to the external radiotherapy. Materials and Methods: This study reviews 59 accidental cases in two retrospective safety analyses that have collected the incidents in the external radiotherapy extensively. Two accident analysis reports that accumulated past incidents are investigated to identify accident sequences including initiating events, failure of safety measures, and consequences. This study classifies the accidents by the treatments stages and sources of errors for initiating events, types of failures in the safety measures, and types of undesirable consequences and the number of affected patients. Then, the accident sequences are grouped into several categories on the basis of similarity of progression. As a result, these cases can be categorized into 14 groups of accident sequence. Results: The result indicates that risk analysis needs to pay attention to not only the planning stage, but also the calibration stage that is committed prior to the main treatment process. It also shows that human error is the largest contributor to initiating events as well as to the failure of safety measures. This study also illustrates an event tree analysis for an accident sequence initiated in the calibration. Conclusion: This study is expected to provide sights into the accident sequences for the prospective risk analysis through the review of experiences.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.415-425
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• 2007

In this study, we generated an orthophoto with both LIDAR data and aerial images and compared it with that generated from only the images. For the accuracy assessment of these orthophotos, we performed not only qualitative analysis based on visual inspection but also quantitative analysis by measuring horizontal inconsistency, boundary coordinates and similarity measures on buildings. Based on the visual inspection and horizontal inconsistency, the orthophoto based on LIDAR DSM appeared to be more closer to a true-orthophoto. However, the analysis on measurements of boundary coordinates and similarity measures indicates that the orthophoto based on LIDAR DSM is more vulnerable to double mapping on occluded areas. Accordingly, if we apply an effective solution on double mapping or use only the central areas of the aerial images where occluded areas are rarely founded, we can generate automatically true-orthophotos based on a LIDAR DSM.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1188-1193
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• 2013

In content based image retrieval (CBIR) system, the images are represented based upon its feature such as color, texture, shape, and spatial relationship etc. In this paper, we propose a MRI Image Retrieval using wavelet transform with mahalanobis distance measurement. Wavelet transformation can also be easily extended to 2-D (image) or 3-D (volume) data by successively applying 1-D transformation on different dimensions. The proposed algorithm has tested using wavelet transform and performance analysis have done with HH and $H^*$ elimination methods. The retrieval image is the relevance between a query image and any database image, the relevance similarity is ranked according to the closest similar measures computed by the mahalanobis distance measurement. An adaptive similarity synthesis approach based on a linear combination of individual feature level similarities are analyzed and presented in this paper. The feature weights are calculated by considering both the precision and recall rate of the top retrieved relevant images as predicted by our enhanced technique. Hence, to produce effective results the weights are dynamically updated for robust searching process. The experimental results show that the proposed algorithm is easily identifies target object and reduces the influence of background in the image and thus improves the performance of MRI image retrieval.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.438-447
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• 2006

Fuzzy controller's design depends mainly on the rule base and membership functions over the controller's input and output ranges. This paper presents two different approaches to deal with these design issues. A simple and efficient approach; namely, Fuzzy Subtractive Clustering is used to identify the rule base needed to realize Fuzzy PI and PD type controllers. This technique provides a mechanism to obtain the reduced rule set covering the whole input/output space as well as membership functions for each input variable. But it is found that some membership functions projected from different clusters have high degree of similarity. The number of membership functions of each input variable is then reduced using a similarity measure. In this paper, the fuzzy subtractive clustering approach is shown to reduce 49 rules to 8 rules and number of membership functions to 4 and 6 for input variables (error and change in error) maintaining almost the same level of performance. Simulation on a wide range of linear and nonlinear processes is carried out and results are compared with fuzzy PI and PD type controllers without clustering in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error (IAE) and integral-of-time multiplied absolute error (ITAE) and in each case the proposed schemes shows an identical performance.

• Journal of the Korean Society for Library and Information Science
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• v.31 no.1
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• pp.153-184
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• 1997

The importance of WWW search services is increasing as Internet information resources explode. An evaluation of current 9 search services was first conducted by comparing descriptively the features concerning indexing, searching, and ranking of search results. Secondly, a couple of search queries were used to evaluate search performance of those services by the measures of retrieval effectiveness. the degree of overlap in searching sites, and the degree of similarity between services. In this experiment, Alta Vista, HotBot and Open Text Index showed better results for the retrieval effectiveness. The level of similarity among the 9 search services was extremely low.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.37-40
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• 2021

This paper presents a design of a speech to sign language converter for deaf and hard of hearing people. The device is low-cost, low-power consumption, and it can be able to work entirely offline. The speech recognition is implemented using an open-source API, Pocketsphinx library. In this work, we proposed a context-oriented language model, which measures the similarity between the recognized speech and the predefined speech to decide the output. The output speech is selected from the recommended speech stored in the database, which is the best match to the recognized speech. The proposed context-oriented language model can improve the speech recognition rate by 21% for working entirely offline. A decision module based on determining the similarity between the two texts using Levenshtein distance decides the output sign language. The output sign language corresponding to the recognized speech is generated as a set of sequential images. The speech to sign language converter is deployed on a Raspberry Pi Zero board for low-cost deaf assistive devices.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.365-371
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• 2014

Association rule of the well-studied techniques in data mining is the exploratory data analysis for understanding the relevance among the items in a huge database. This method has been used to find the relationship between each set of items based on the interestingness measures such as support, confidence, lift, similarity measures, etc. By typical association rule technique, we generate association rule that satisfy minimum support and confidence values. Support and confidence are the most frequently used, but they have the drawback that they can not determine the direction of the association because they have always positive values. In this paper, we compared support, basic confidence, and three kinds of confidence measures useful for classification model building to overcome this problem. The result confirmed that the causal confirmed confidence was the best confidence in view of the association mining because it showed more precisely the direction of association.

• Physical Therapy Korea
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• v.30 no.2
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• pp.120-127
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• 2023

Background: In general, measurement qualities of cross-culturally adapted quality of life (QOL) measures are altered in many aspects, although versions of them are well-validated measures. The latent trait and measurement qualities of the QOL measures for cancer-related samples should be considered when developing cross-culturally adapted measures. Objects: To investigate the latent trait of the translated into Korean World Health Organization Quality of Life-BREF (WHOQOL-BREF) administered to different cancer survivors who had palliative rehabilitation care service (PRCS). Methods: A cross-sectional study with 139 cancer survivors who had an experience of cancer survivorship with PRCS were conducted with a two-step analytic procedure including exploratory factor analysis (EFA) to confirm the latent trait and Rasch rating scale modeling to investigate the measurement qualities of the cross-culturally adapted WHOQOL-BREF measure. Results: While the original WHOQOL-BREF measure constitutes a 4-latent trait, the EFA reveals that 24 items constitute six substantial factors. The item loadings are predominantly spread over factors 1 through 4 in a mixed manner of the latent traits, while the loadings of 'physical health' and 'environmental health' latent traits show similarity to what the original measure intended to assess. The latent trait of the cross-culturally adapted WHOQOL-BREF measure administered to different cancer survivors is likely to reveal more dimensions than the original WHOQOL-BREF measure. Person reliability (i.e., analogous to Cronbach's alpha) and separation are measured with 0.92 and 3.48, respectively. All items except the one item (medical treatment item) fit the Rasch rating model. Conclusion: Findings suggest that the latent trait and the measurement qualities of the cross-culturally adapted WHOQOL-BREF measure should be taken into consideration when applying versions of it to various populations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.45-52
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• 2004

According tothe development of digital media technologies various algorithms for video sequence matching have been proposed to match the video sequences efficiently. A large number of video sequence matching methods have focused on frame-wise query, whereas a relatively few algorithms have been presented for video sequence matching or video shot matching. In this paper, we propose an efficientalgorithm to index the video sequences and to retrieve the sequences for video sequence query. To improve the accuracy and performance of video sequence matching, we employ the Cauchy function as a similarity measure between histograms of consecutive frames, which yields a high performance compared with conventional measures. The key frames extracted from segmented video shots can be used not only for video shot clustering but also for video sequence matching or browsing, where the key frame is defined by the frame that is significantly different from the previous fames. Several key frame extraction algorithms have been proposed, in which similar methods used for shot boundary detection were employed with proper similarity measures. In this paper, we propose the efficient algorithm to extract key frames using the cumulative Cauchy function measure and. compare its performance with that of conventional algorithms. Video sequence matching can be performed by evaluating the similarity between data sets of key frames. To improve the matching efficiency with the set of extracted key frames we employ the Cauchy function and the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed method yields the high matching performance and accuracy with a low computational load compared with conventional algorithms.

• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.95-116
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• 2009

Ontologies have provided supports in integrating heterogeneous and distributed information. More and more ontologies and tools have been developed in various domains. However, building ontologies requires much time and effort. Therefore, ontologies need to be shared and reused among users. Specifically, finding the desired ontology from an ontology repository will benefit users. In the past, most of the studies on retrieving and ranking ontologies have mainly focused on lexical level supports. In those cases, it is impossible to find an ontology that includes concepts that users want to use at the semantic level. Most ontology libraries and ontology search engines have not provided semantic matching capability. Retrieving an ontology that users want to use requires a new ontology selection and ranking mechanism based on semantic similarity matching. We propose an ontology selection and ranking model consisting of selection criteria and metrics which are enhanced in semantic matching capabilities. The model we propose presents two novel features different from the previous research models. First, it enhances the ontology selection and ranking method practically and effectively by enabling semantic matching of taxonomy or relational linkage between concepts. Second, it identifies what measures should be used to rank ontologies in the given context and what weight should be assigned to each selection measure.