• Journal of Information Technology Services
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• v.15 no.1
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• pp.245-253
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• 2016

Background in a novel is most important elements with characters and events, and means time, place and situation that characters appeared. Among the background, spatial background can help conveys topic of a novel. So, it may be helpful for choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels. In case of English text, It can be recognize spatial background easily because it use upper and lower case and words used with the spatial information such as Bank, University and City. But, in case Korean text, it is difficult to recognize that spatial background because there is few information about usage of letter. In the previous studies, they use machine learning or dictionaries and rules to recognize about spatial information in text such as news and text messages. In this paper, we build a nation dictionaries that refer to information such as 'Korean history' and 'Google maps.' We Also propose a method for recognizing spatial background based on patterns of postposition in Korean sentences comparing to previous works. We are grasp using of postposition with spatial background because Korean characteristics. And we propose a method based on result of morpheme analyze and frequency in a novel text for raising accuracy about recognizing spatial background. The recognized spatial background can help readers to grasp the atmosphere of a novel and to understand the events and atmosphere through recognition of the spatial background of the scene that characters appeared.

• Korean Journal of Cognitive Science
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• v.13 no.2
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• pp.47-59
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• 2002

Three experiments were conducted to investigate whether different types (common vs. uncommon) of prior-examples entail different effects in creative problem solving, and whether types/levels (rich or lean. common or uncommon) of background knowledge interact with types of prior-examples. It was found that the example types and the types/levels of background knowledge do interact and have some differential effects on generating novel and useful ideas. In Experiment 1 and 2. uncommon examples had a positive effect - generating many novel and useful ideas. regardless of background knowledge types. while common examples had positive effects, only when the background knowledge was somewhat uncommon In Experiment 3 it was also found that types (irrelevant,. single common. single uncommon, or multiple common + uncommon) of background knowledge seemed to influence differently on the ease of finding solutions: when background knowledge is diverse or not directly related to the task problem, uncommon prior examples produced much greater number of novel ideas than it was with single common or sin91e uncommon background knowledge. Implications of the present study were discussed. in relation to mental sets and fixation.

• English Language & Literature Teaching
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• v.11 no.1
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• pp.225-243
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• 2005

Korean students in English novel class read presentable papers about a novel, but if asked about some parts of the novel, they are helpless. How do they know the whole novel without knowing its parts? Because most Korean students cannot read through an English novel in a short time, they are awfully pressed with preparation for papers to be presented in the class. That makes their papers composed entirely of appropriated ideas from references. Being conscious of students' inability to read through a novel, some teachers select and read only some important parts or chapters of the novel. That makes students take a novel not as literary art, but as a prose work for abstract ideas. In order to solve the problem, I propose chapter analysis. Attentive reading new critics applied to poetry and short story is applicable to the chapter of a novel. Because no critic or scholar analyzes a novel chapter by chapter in his/her articles or books, students cannot wholly mosaic their papers with ideas from references. Chapter analysis will enable Korean students to interpret a novel with their own view point. This paper includes such sections as the theoretical background of fictional chapters, some items to be considered for chapter analysis in the class, and examples of analysis of a short story and two chapters from a novel.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.159-161
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• 2004

Many motion object detection algorithms rely on the process of background subtraction, an important technique that is used for detecting changes from a model of the background scene. This paper propose a novel method to update the background model image of a visual surveillance system which is not stationary. In order to do this, we use a background model based on statistical qualities of monitored images and another background model that excluded motions. By comparing each changed area computed from the two background model images and current monitored image, the areas that will be updated are decided.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.625-633
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• 2023

In this paper, we will examine the theoretical background and educational methodological basis of Novel engineering class cases published to date. For this purpose, we selected and investigated 30 Novel engineering-related academic papers and dissertations published from 2016 to 2023. As a result, the theoretical background is Seymour Papert's constructionism and Vygotsky's socio-cultural constructivism, and the educational methodological basis is creative problem-solving learning, problem-based learning, interdisciplinary convergence class, action learning, associating reading and writing education, possibility with integrated curriculum. We hope that this study will solidify the theoretical value of the Nobel Engineering convergence teaching model and serve as an alternative for teachers preparing for future education.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.63-66
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• 2009

Automatic segmentation of foreground from background in video sequences has attracted lots of attention in computer vision. This paper proposes a novel framework for the background subtraction that the foreground is segmented from the background by directly subtracting a background image from each frame. Most previous works focus on the extraction of more reliable seeds with threshold, because the errors are occurred by noise, weak color difference and so on. Our method has good segmentations from the approximate seeds by using the Random Walks with Restart (RWR). Experimental results with live videos demonstrate the relevance and accuracy of our algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.782-804
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• 2011

In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.255-274
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• 2006

Moving object boundary is very important for the accurate segmentation of moving object. We extract the moving object boundary from the moving object edge. But the object boundary shows broken boundaries so we develop a novel boundary linking algorithm to link the broken boundaries. The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundaries and searches for other terminating pixels to link in concentric circles clockwise within a search radius in the forward direction. The boundary linking algorithm guarantees the shortest distance linking. We register the background from the image sequence using the stationary background filtering. We construct two object masks, one object mask from the boundary linking and the other object mask from the initial moving object, and use these two complementary object masks to segment the moving objects. The main contribution of the proposed algorithms is the development of the novel object boundary linking algorithm for the accurate segmentation. We achieve the accurate segmentation of moving object, the segmentation of multiple moving objects, the segmentation of the object which has a hole within the object, the segmentation of thin objects, and the segmentation of moving objects in the complex background using the novel object boundary linking and the background automatically. We experiment the algorithms using standard MPEG-4 test video sequences and real video sequences of indoor and outdoor environments. The proposed algorithms are efficient and can process 70.20 QCIF frames per second and 19.7 CIF frames per second on the average on a Pentium-IV 3.4GHz personal computer for real-time object-based processing.

• The Journal of Natural Sciences
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• v.16 no.1
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• pp.39-48
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• 2005

Many researchers consider the totality of Babylonian mathematics was profoundly elementary, but some of their mathematical knowledge achieved a novel comparable to the Greeks. The aim of this article is to provide a brief overview of the environmental and social background which made mathematical development. Historically, mathematics is always a product of society. So it is valuable to study historical background which have produced mathematics.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.