• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.302-307
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• 1990

An automatic visual classification system is introduced which provides for measuring the length and diameter of coilform cores and dividing them into 5 different classes in terms of how far their length be from the desired length. This task is fully automated by controlling two STEP motors and by using image processing techniques. The classification procedure is broken into three logical parts. Fist, cores in the form of randomly stacked bundle are lined up one by one so as to be well captured by a cameras. The second part involves capturing core image. Then, it enters the measuring process. Finally, this machine would retain all tire information relating to the length. According to the final result, cores are sent to the corresponding bin. This considerably simplifies the selecting task and facilitates a greatly improved reliability in precision. The average classifying capability about 2 pieces per second.

• The Journal of Information Systems
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• v.23 no.3
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• pp.127-142
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• 2014

Plagiarism occurs when the content is copied without permission or citation, and the problem of plagiarism has rapidly increased because of the digital era of resources available on the World Wide Web. An important task in plagiarism detection is measuring and determining similar text portions between a given pair of documents. One of the main difficulties of this task is that not all similar text fragments are examples of plagiarism, since thematic coincidences also tend to produce portions of similar text. In order to handle this problem, this paper proposed association analysis in data mining to detect plagiarism. This method is able to detect common actions performed by plagiarists such as word deletion, insertion and transposition, allowing to obtain plausible portions of plagiarized text. Experimental results employing an unsupervised document classification strategy showed that the proposed method outperformed traditionally used approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.580-584
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• 2006

Material information for environment may be useful to accomplish mobile robot localization. A procedure to classify a set of indoor materials (glass, steel, wood, aluminum and concrete) with the reflected signal of ultrasonic sensor is proposed in this paper. The main idea is to use material-specific reflection characteristics for the recognition of material type. To achieve the classification task, we modeled reflected signal as a maximum amplitude with respect to distance. In this way, we can generate echo signal models for the given materials and these models are used to compare with the current sensor reading. The experimental results show that the proposed method may give material information during map building task of mobile robot.

• Journal of Korean Society for Quality Management
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• v.30 no.1
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• pp.152-161
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• 2002

The analysis of large data sets with hundreds of thousands observations and thousands of independent variables is a formidable computational task. A less parametric method, capable of identifying important independent variables and their interactions, is a tree structured approach to regression and classification. It gives a graphical and often illuminating way of looking at data in classification and regression problems. In this paper, we have reviewed and summarized tile methodology used to construct a tree, multiple trees and the sequential strategy for identifying active compounds in large chemical databases.

• Phonetics and Speech Sciences
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• v.2 no.4
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• pp.109-118
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• 2010

Using a speeded classification task (Garner, 1978), we investigated the perceptual interaction of distinctive features in Korean consonants. The main questions of this study were whether listeners can perceptually identify the component features that make up complex consonant sounds, whether these features are processed independently or dependently and whether there is a systematic hierarchy in their dependency. Participants were asked to classify syllables based on their difference in distinctive features in the task. Reaction times for this task were also gathered. For example, participants classified spoken syllables /ta/ and /pa/ as one category and /$t^ha$/ and /$p^ha$/ as another in terms of aspiration condition. In terms of articulation, participants classified /ta/ and /$t^ha$/ as one category and /pa/ and /$p^ha$/ as another. We assumed that the difference between their RTs represents their interdependency. We compared the laryngeal features and place features (Experiment 1), resonance features and place features (Experiment 2), and manner features and laryngeal features (Experiment 3). The results showed that distinctive features were not perceived in a completely independent way, but they had an asymmetric and hierarchical interdependency. The laryngeal features were found to be more independent compared to place and manner features. We discuss these results in the context of perceptual basis in phonology.

• Journal of Intelligence and Information Systems
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• v.1 no.1
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• pp.61-72
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• 1995

Dynamic and explicit ordering of strategies is a key process in modeling knowledge-level problem-solving behavior. This paper addressed the important problem of howl to make the scheduler more knowledge-intensive in a way that facilitates the acquisition, integration, and maintenance of the scheduler control knowledge. The solution a, pp.oach described in this paper involved formulating the scheduler task as a heuristic classification problem, and then implementing it as a classification expert system. By doing this, the wide spectrum of known methods of acquiring, refining, and maintaining the knowledge of a classification expert system are a, pp.icable to the scheduler control knowledge. One important innovation of this research is that of recursive heuristic classification : this paper demonstrates that it is possible to formulate and solve a key subcomponent of heuristic classification as heuristic classification problem. Another key innovation is the creation of a method of dynamic heuristic classification : the classification alternatives that are selected among are dynamically generated in real-time and then evidence is gathered for and aginst these alternatives. In contrast, the normal model of heuristic classification is that of structured selection between a set of preenumerated fixed alternatives.

• Safety and Health at Work
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• v.11 no.3
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• pp.335-346
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• 2020

Background: Nursing service is a nonroutine work with an excessive physical load and diverse tasks. This study derived representative common tasks based on the frequently occurring tasks with a high physical load in the nursing workers' daily work and developed indicators to evaluate the work risk by reflecting the characteristics of nonroutine work. Methods: Common tasks were classified through the following stages: literature review, first focus group interview (FGI) with experts, first classification of common tasks, second FGI with hospital health managers, a survey of nursing service workers, and the final classification of common tasks for each task type. To develop an objective risk index for physical load assessment, we investigated the frequency and duration of the derived common tasks via survey. Results: Nursing common tasks were categorized into six task types and 56 subtasks. To evaluate the risks of various tasks in nonroutine works, three frequencies and three working time levels were defined by examining the task frequency and working hours. Exposure time was defined to reflect the characteristics of a nonroutine job. The final risk assessment was the product of the exposure time level and job intensity level. From this, four risk action levels were derived. Conclusion: This study has the advantage of solving the problem of focusing on some tasks in evaluating the physical load. It was meaningful in that a new risk assessment index based on exposure time was proposed based on the development of an evaluation scale for frequency and time by reflecting the characteristics of nonroutine work.

• Journal of Science Education
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• v.34 no.2
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• pp.185-192
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• 2010

The purpose of this study was to develope the negative-emotion prediction model by hormonal changes during the scientific inquiry. For this study, biological classification task was developed that are suitable for comprehensive scientific inquiry. Forty-seven 2nd grade secondary school students (boy 18, girl 29) were participated in this study. The students are healthy for measure hormonal changes. The students performed the feathers classification task individually. Before and after the task, the strength of negative emotion was measured using adjective emotion check lists and they extracted their saliva sample for salivary hormone analysis. The results of this study, student's change of negative emotion during the feathers classification process was significant positive correlation(R=0.39, P<0.001) with student's salivary cortisol concentration. According to this results, we developed the negative emotion prediction model by salivary cortisol changes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.525-528
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• 2009

Recently, image classification has been an important task in various fields. Generally, the performance of image classification is not good without the adjustment of image features. Therefore, it is desired that the way of automatic feature extraction. In this paper, we propose an image classification method which adjusts image features automatically. We assume that texture features are useful in image classification tasks because natural images are composed of several types of texture. Thus, the classification accuracy rate is improved by using distribution of texture features. We obtain texture features by calculating image features from a current considering pixel and its neighborhood pixels. And we calculate image features from distribution of textures feature. Those image features are adjusted to image classification tasks using Genetic Algorithm. We apply proposed method to classifying images into "head" or "non-head" and "male" or "female".

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.76-85
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• 2007

This paper addresses a task of opinion extraction from given documents and its positive/negative classification. We propose a sentence classification method using a notion of syntactic piece. Syntactic piece is a minimum unit of structure, and is used as an alternative processing unit of n-gram and whole tree structure. We compute its semantic orientation, and classify opinion sentences into positive or negative. We have conducted an experiment on more than 5000 opinion sentences of multiple domains, and have proven that our approach attains high performance at 91% precision.