• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2246-2255
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• 2023

Evacuation time estimation (ETE) is crucial for the effective implementation of resident protection measures as well as planning, owing to its applicability to nuclear emergencies. However, as confirmed in the Fukushima case, the ETE performed by nuclear operators does not reflect behavioral features, exposing thus, gaps that are likely to appear in real-world situations. Existing research methods including surveys and interviews have limitations in extracting highly feasible behavioral features. To overcome these limitations, we propose a VR-based immersive experiment system. The VR system realistically simulates nuclear emergencies by structuring existing disasters and human decision processes in response to the disasters. Evacuation behavioral features were quantitatively extracted through the proposed experiment system, and this system was systematically verified by statistical analysis and a comparative study of experimental results based on previous research. In addition, as part of future work, an application method that can simulate multi-level evacuation dynamics was proposed. The proposed experiment system is significant in presenting an innovative methodology for quantitatively extracting human behavioral features that have not been comprehensively studied in evacuation. It is expected that more realistic evacuation behavioral features can be collected through additional experiments and studies of various evacuation factors in the future.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.61-68
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• 2008

This paper presents a spam filter system using co-training with spamminess features and URL features based on the maximum entropy model. Spamminess features are the emphasizing patterns or abnormal patterns in spam messages used by spammers to express their intention and to avoid being filtered by the spam filter system. Since spammers use URLs to give the details and make a change to the URL format not to be filtered by the black list, normal and abnormal URLs can be key features to detect the spam messages. Co-training with spamminess features and URL features uses two different features which are independent each other in training. The filter system can learn information from them independently. Experiment results on TREC spam test collection shows that the proposed approach achieves 9.1% improvement and 6.9% improvement in accuracy compared to the base system and bogo filter system, respectively. The result analysis shows that the proposed spamminess features and URL features are helpful. And an experiment result of the co-training shows that two feature sets are useful since the number of training documents are reduced while the accuracy is closed to the batch learning.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.23-40
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• 1993

In this paper, we developed a prototype part recognition system for FMS (Flexible Manufacturing System) by comparing the features extracted from CAD data and the features obtained from the image through a single camera, Good or distinct features with high recognition efficiency for a specific part are obtained automatically and intelligently according to the rules from CAD data. Since the selection of distinct features are done automatically without any human interference, the developed system seems to be quite robust. Fourther, since it uses only a few distinct features on-line among many features and all the time-consuming calculations are done off-line, it is possible to recognize each part quickly and accurately. In order to evaluate the performance and the effectiveness of the developed system, two example(L and T shaped parts) are tested and the results are reported.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.298-309
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• 2001

This research aims to unravel the significant features of the human immune system, which would be successfully employed for a novel network intrusion detection model. Several salient features of the human immune system, which detects intruding pathogens, are carefully studied and the possibility and the advantages of adopting these features for network intrusion detection are reviewed and assessed.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.119-129
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• 2007

To recognition a human motion, in this paper, we propose a neural approach using silhouettes in video frames captured by two cameras placed at the front and side of the human body. To extract features of the silhouettes for motion estimation, the proposed system computes both global and local features and then groups these features into static and dynamic features depending on whether features are in a static frame. Extracted features are in a static frame. Extracted features are used to train a RBF network. The neural system uses static features as the input of the neural network and dynamic features as additional features for recognition. In this paper, the proposed method was applied to movement education for young children. The basic movements for such education consist of locomotor movements, such as walking, jumping, and hopping, and non-locomotor movements, including bending, stretching, balancing and turning. The system demonstrated the effectiveness of motion recognition for movement education generated by the proposed neural network. The proposed system dan be extended to the system for movement education which develops the spatial sense of young children.

• Journal of Mechanical Science and Technology
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• v.18 no.12
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• pp.2095-2103
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• 2004

A macro-level CAPP system is proposed to plan the complicated mechanical prismatic parts efficiently. The system creates the efficient machining sequence of the features in a part by analyzing the feature information. Because the planning with the individual features is very complicated, feature groups are formed for effective planning using the nested relations of the features of a part, and special feature groups are determined for sequencing. The process plan is generated based on the sequences of the feature groups and features. When multiple machines are required, efficient machine assignment is performed. A series of heuristic rules are developed to accomplish it.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.265-271
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• 2001

It is highly for the research in artificial intelligence area to be able to manage knowledge as human beings do. One of the fantastic natures that human knowledge management systems have is being active. Human beings actively manage their knowledge, solve conflicts and make inference. It makes a major difference from artificial intelligent systems. This paper focuses on the discussion of the features of that human knowledge systems, which underlies the active nature. With the features extracted, further research can be done to construct a suitable infrastructure to facilitate these features to build a man-made active knowledge management system. This paper proposed 10 features that human beings follow to maintain their knowledge. We believe it will advance the evolution of active knowledge management systems by realizing these features with suitable knowledge representation/decision models and software agent technology.

• Journal of Biosystems Engineering
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• v.19 no.4
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• pp.380-396
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• 1994

A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.60-69
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• 1996

To retrieve complex data such as images in multimedia information, we need the content-based retrieval methods based on the visual properties rather than keywords. In this paper, a contrent-based image retrieval system is desinged and implemented to retrieve images using the features of images such as colors, lines and intensity vetor features when a visual query inputs. The contents for image retrievals are the color features extracted from the color component of 16 blocks of the image, th eline features extracted form 4 lines in the image and the shape features extracted from the intensity vectors of the 16 blocks. We can either use a whole image or a sketch image for query. As the experimental results demonstrate the precision 91% the recall 33% and the average rank 3.1 the retrieval performance is found to be high. The experimental results indicate that the retrieval using the weighted features have led to substantial improvement in the percision and performance of system.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.85-96
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• 2001

In this paper, part features are classified and then its coding system is constructed by the considered characteristics of features in assemble process. Analyzing the characteristics of features, code values about part features are determined. Assembly process is divided into five functions such as transporting, handing, approaching, alignment and joining, and then the detail parameters of each functions such as determined. Code values about assembly process are determined according to detail parameters. The detail parameters are kinds of available working method and assembly tools when each assembly function is going on. By the coding system, available assembly process can be grasped and perceived for the part that it is difficult to assemble.