• 한국초등과학교육학회지:초등과학교육
• /
• 제35권2호
• /
• pp.194-204
• /
• 2016

The purpose of this study is to find out the relationship between types and sources of background knowledges of elementary preteachers' questions about astronomy contents in the elementary science text books. Data were extracted from the preteachers' classes established in a university of education. The results are as follows. First, right background knowledges of questions were found in about 58% questions, wrong background knowledges 15%, and no background knowledges 26%. Second, it was found that 'school' as a source of background knowledges was found in 29% questions, 'friend' 21%, 'internet' 14%, 'book reading' 12%, 'others' 9%, 'TV' 7%, 'institute' 4%. In case of the type that right background knowledges have casual relation or correlation with question contents, 'book reading' and 'TV' sources rate increased, but 'internet' and 'others' decreased when compared to total questions. In the type which background knowledges are right and did not have casual relation or correlation with question contents, 'internet' source rate increased and 'friend' decreased. In case of the type that wrong background knowledges do not have casual relation or correlation with question contents, 'friend' and 'TV' sources rate increased, but 'school' and 'book reading' decreased. The type which background knowledges are right and did not have casual relation or correlation with question contents, 'internet' source rate increased and 'friend' decreased. In case of the type of no background knowledges, 'TV' and 'institute' source rate increased, but 'internet' and 'book reading' decreased. Third, the questions in 'Earth and Moon' unit have little background knowledges. The questions in 'solar system and stars' have background knowledges with no relation to the questions. Especially, in the unit 'changes of seasons', right background knowledges were found in more than half questions, but the contents of questions and background knowledges were not connected scientifically.

• 한국IT서비스학회지
• /
• 제15권1호
• /
• pp.245-253
• /
• 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.

• 유통과학연구
• /
• 제17권9호
• /
• pp.127-131
• /
• 2019

Purpose - This study focuses on clues that can clearly amplify the effects of background music. Review which store environments have a direct and positive impact on consumer responses, such as purchases. Research design, data, and methodology - This study focuses on clues that can clearly amplify the effects of background music. The purpose of this study is to examine what kind of store environment, combined with background music, has a direct and positive effect on consumer reactions such as purchase, and suggest future research directions. Results - The manager decides to use background music in the store because it is relatively inexpensive and easy to identify the emotional response of the consumer. In addition, appropriate background music lowers the psychological purchasing barriers of consumers. Previous studies have often not conducted a basic review of whether consumers perceive background music when it is used in retail stores. For example, it is necessary to make sure that the volume of the background music is loud enough and that the noise is properly excluded despite the congestion of the store so that the pure influence of the background music on the consumer can be measured. A way for store managers to clarify and differentiate their identity is to create a unique and satisfying store atmosphere for their customers. In order to help customers focus on their purchases, store managers must use marketing elements to integrate the five senses. And they should plan background music aiming at synergy effect of these five senses. In other words, in order to make the store atmosphere positive, it is not enough to have a suitable visual design interior or background music in the store, and consumers should have the opportunity to smell, taste and touch it directly. Conclusions - In conclusion, we hope that the following issues will be studied by several scholars in the future. It should be clarified that the impact of background music on customers varies depending on the customer's movement in the store, the selection of the background music genre order, and the timing (interval) of background music exposure to the customer.

• 한국컴퓨터정보학회논문지
• /
• 제24권5호
• /
• pp.149-156
• /
• 2019

The existing subtract image based intrusion detection system for CCTV digital images has a problem that it can not distinguish intruders from moving backgrounds that exist in the natural environment. In this paper, we tried to solve the problems of existing system by designing real - time intrusion detection system for CCTV digital image by combining subtract image based intrusion detection method and background learning artificial neural network technology. Our proposed system consists of three steps: subtract image based intrusion detection, background artificial neural network learning stage, and background artificial neural network evaluation stage. The final intrusion detection result is a combination of result of the subtract image based intrusion detection and the final intrusion detection result of the background artificial neural network. The step of subtract image based intrusion detection is a step of determining the occurrence of intrusion by obtaining a difference image between the background cumulative average image and the current frame image. In the background artificial neural network learning, the background is learned in a situation in which no intrusion occurs, and it is learned by dividing into a detection window unit set by the user. In the background artificial neural network evaluation, the learned background artificial neural network is used to produce background recognition or intrusion detection in the detection window unit. The proposed background learning intrusion detection system is able to detect intrusion more precisely than existing subtract image based intrusion detection system and adaptively execute machine learning on the background so that it can be operated as highly practical intrusion detection system.

• Journal of Electrical Engineering and Technology
• /
• 제10권1호
• /
• pp.372-378
• /
• 2015

Background subtraction is the first processing stage in video surveillance. It is a general term for a process which aims to separate foreground objects from a background. The goal is to construct and maintain a statistical representation of the scene that the camera sees. The output of background subtraction will be an input to a higher-level process. Background subtraction under dynamic environment in the video sequences is one such complex task. It is an important research topic in image analysis and computer vision domains. This work deals background modeling based on modified adaptive Gaussian mixture model (GMM) with three temporal differencing (TTD) method in dynamic environment. The results of background subtraction on several sequences in various testing environments show that the proposed method is efficient and robust for the dynamic environment and achieves good accuracy.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
• /
• pp.159-161
• /
• 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.

• 상하수도학회지
• /
• 제28권3호
• /
• pp.345-358
• /
• 2014

For introducing the groundwater quality assessment using background concentration of groundwater, several methods had been studied to estimate the background concentration of groundwater and to suggest the background concentration of study area. Some methods such as Box whisker plot, Percentile and Cumulative probability distribution had been adopted to estimate background concentration, and it was evaluated that the Cumulative probability distribution method presents more reasonable background concentration because it can consider the data distribution. So we estimated the background concentration of study area using cumulative probability distribution method. We suggested the background concentration for each hydrogeology respectively in case hydrogeological water quality similarity is very low.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
• /
• pp.35-38
• /
• 2003

In this paper, I propose an automatic background extraction method and continuous background updating technique. Because there is a movement of a vehicle and a change of a background is feeble, the area moving through the time axis is looked for and a background and a vehicle image is divided. A way to give dynamically the threshold which divides the image frame into a vehicle image and the background in a space is enforced. Through the repetition of the above-mentioned process, the background pictorial image is gained. Using the karlman filter technique, the update is done so that a background image can obey a climate situation and an environmental change in day and night. A background image processed algorithm is better than the existent one. Through simulation, the feasibility of the algorithm has been verified.

• 한국멀티미디어학회논문지
• /
• 제18권2호
• /
• pp.268-276
• /
• 2015

This article analyzes the background representation of 3D animation and look at what its proper background expression. With the development of computer graphics technology, the background of the 3D animations can be expressed as The actual background. In contrast, "The Smurfs" which was released recently was created to take the actual background. However, 3D animation with real background is not appropriate in terms of creative expression space in the main role of the animation. In this Study, we analyze the character and background of the animation made in 3D graphics. Based on this, we propose a correct representation of 3D animation background.

• 한국컴퓨터정보학회논문지
• /
• 제20권9호
• /
• pp.121-128
• /
• 2015

In this paper, we proposed and implemented the effective automatic foreground motion detection algorithm that detect the foreground motion by analyzing the digital video data that captured by the network camera. We classified the background as moving background, fixed background and normal background based on the standard deviation of background and used it to detect the foreground motion. According to the result of experiment, our algorithm decreased the fault detection of the moving background and increased the accuracy of the foreground motion detection. Also it could extract foreground more exactly by using the statistic information of background in the phase of our foreground extraction.