• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1779-1785
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• 2018

In this paper, we propose an error correction method to improve the accuracy of human activity recognition using sensor event data obtained by smart devices such as wearable and smartphone. In the context awareness through the smart device, errors inevitably occur in sensing the necessary context information due to the characteristics of the device, which degrades the prediction performance. In order to solve this problem, we apply Kalman filter's error correction algorithm to compensate the signal values obtained from 3-axis acceleration sensor of smart device. As a result, it was possible to effectively eliminate the error generated in the process of the data which is detected and reported by the 3-axis acceleration sensor constituting the time series data through the Kalman filter. It is expected that this research will improve the performance of the real-time context-aware system to be developed in the future.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.627-634
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• 2016

In this paper, an augmented video generation method to evaluate the performance of lane departure warning system is proposed. In our system, the input is a video which have road scene with general clean lane, and the content of output video is the same but the lane is synthesized with contamination image. In order to synthesize the contamination lane image, two approaches were used. One is example-based image synthesis, and the other is background-based image synthesis. Example-based image synthesis is generated in the assumption of the situation that contamination is applied to the lane, and background-based image synthesis is for the situation that the lane is erased due to aging. In this paper, a new contamination pattern generation method using Gaussian function is also proposed in order to produce contamination with various shape and size. The contamination lane video can be generated by shifting synthesized image as lane movement amount obtained empirically. Our experiment showed that the similarity between the generated contamination lane image and real lane image is over 90 %. Futhermore, we can verify the reliability of the video generated from the proposed method through the analysis of the change of lane recognition rate. In other words, the recognition rate based on the video generated from the proposed method is very similar to that of the real contamination lane video.

• Journal of the Society of Disaster Information
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• v.9 no.2
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• pp.220-230
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• 2013

In this study, we investigated the recognition of the first aid of guard major college students are trained to deal well and flexibly to the situation of unforeseen circumstances, you are trying to present the teaching methods and effective importance of first aid. Analysis of data collected in this study is as follows: The results obtained using the statistical program SPSS18.0. First, education has not been done properly, there is no difference between the average score of people who did not receive the people who received the fact of first aid veritable we are specialized in, the second education systematic is needed, training of first aid has not been properly implemented, problems of education there were many. Third, because there is no difference in the level of knowledge by training institutions of first aid, the places where there is training of first aid, there is no effect on the knowledge level. Therefore, it can be the need training first aid practical to enhance the ability to proactively address the situation of contingencies.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.804-809
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• 2013

The current state monitoring system at a semiconductor manufacturing process is based on the manually collected sensor data, which involves limitations when it comes to complex malfunction detection and real time monitoring. This study aims to design a situation recognition algorithm to form a network over time by creating a domain ontology and to suggest a system to provide users with services by generating events upon finding risk factors in the semiconductor process. To this end, a multiple sensor node for situational inference was designed and tested. As a result of the experiment, events to which the rule of time inference was applied occurred for the contents formed over time with regard to a quantity of collected data while the events that occurred with regard to malfunction and external time factors provided log data only.

• Journal of Science Education
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• v.45 no.2
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• pp.201-218
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• 2021

The purpose of this study is to investigate qualitatively two cases of general citizens' scientific participation and activities responding to fine dust problem. The processes of their scientific actions were investigated and categorized inductively based on three stages: problem recognition stage, information collection and analysis stage, and sharing and spreading stage. As a result, in the 'problem recognition' stage, two participants recognized the seriousness of the fine dust problem as they felt a threat to their health and began to act practically by questioning the accuracy of public data. In the 'information collection and analysis' stage, a participant collected as much information as possible and compared them in order to obtain more accurate information for her situation. On the other hand, another participant conducted various experiments in person to get the information which is appropriate to his situation. Finally, in the 'Sharing and Spreading' stage, both participants created and shared various materials based on online environment, and continued their activities with a sense of contribution through others assistance. Educational implications are discussed in terms of civic science education and scientific literacy.

• Journal of Navigation and Port Research
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• v.45 no.4
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• pp.204-211
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• 2021

The Maritime Domain Awareness system is a component that is necessary to enhance the awareness of all situations occurring at sea in relation to security, safety, economy, and the environment. To establish a marine situation recognition system that is currently being introduced in major maritime countries after approval by the International Maritime Organization's Maritime Safety Committee in 2010, operational measures should be established. For the purpose of establishing a technological foundation for the efficient construction of a Korean maritime situation recognition system, this study analyzed the status of each system (RADAR, VHF, and V-PASS, etc.) and proposed the application of data and communication standards.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1723-1728
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• 2021

C-ITS is an intelligent transportation system that can improve transportation convenience and traffic safety by collecting, managing, and providing traffic information between components such as vehicles, road infrastructure, drivers, and pedestrians. In Korea, road infrastructure is being built across the country through the C-ITS project, and various services such as real-time traffic information provision and bus operation management are provided. However, the current state-of-the-art road infrastructure and information linkage system are insufficient to build C-ITS. In this paper, considering the continuity of time in various spatial aspects, we proposed a group-type network-based traffic situation recognition system that can recognize traffic flows and unexpected accidents through information linkage between traffic infrastructures. It is expected that the proposed system can primarily respond to accident detection and warning in the field, and can be utilized as more diverse traffic information services through information linkage with other systems.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.968-975
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• 2023

Purpose: We would like to confirm that the false positive rate of flames/smoke is high when detecting fires. Propose a method and dataset to recognize and classify fire situations to reduce the false detection rate. Method: Using the video as learning data, the characteristics of the fire situation were extracted and applied to the classification model. For evaluation, the model performance of Yolov8 and Slowfast were compared and analyzed using the fire dataset conducted by the National Information Society Agency (NIA). Result: YOLO's detection performance varies sensitively depending on the influence of the background, and it was unable to properly detect fires even when the fire scale was too large or too small. Since SlowFast learns the time axis of the video, we confirmed that detects fire excellently even in situations where the shape of an atypical object cannot be clearly inferred because the surrounding area is blurry or bright. Conclusion: It was confirmed that the fire detection rate was more appropriate when using a video-based artificial intelligence detection model rather than using image data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3036-3044
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• 2010

With the rapid growth of video data service, demand to provide advertisements or additional information with regard to a particular video scene is increasing. However, the direct use of automated visual analysis or speech recognition on videos virtually has limitations with current level of technology; the metadata of video such as title, category information, or summary does not reflect the content of continuously changing scenes. This work presents a new video contextual advertising system that serves relevant advertisements on a given scene by leveraging the scene's situation information inferred from video scripts. Experimental results show that the use of situation information extracted from scripts leads to better performance and display of more relevant advertisements to the user.

• Journal of Dairy Science and Biotechnology
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• v.24 no.2
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• pp.11-20
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• 2006

Korea dairy industry has a long and chronic problems to consume raw milk , those are surplus milk and decline the market milk consumption continued about 10 years. This study was aim to propose and to find the solution for dairy industry problems. After WTO system, with the importation of dairy products, domestic milk production has fell into the situation of excess supply and huge inventory of dried milk, the milk powder stocks have increased since 2002. That made a chronic decline milk consumption in Korea. The core of chronic problem of Korea dairy industry is the decreasing in market milk consumption. If they have a settlement of any other way using their raw milk to process and consumption to market milk, there will be a solution to solve the chronic problems in this situation. Especially, that will be a development of small farm scale natural cheese production and consume. This may be lead a situation of increase the raw milk consumption, because natural cheese making needs much of raw milk more than market milk. But there are very low technical level of farmers cheese making status, so they need a cheese making educational program for their commercial level of cheese products. Under these situation, there are needed a way out of educational system for the dairy farmers to obtain the high level of cheese making technology from the trustable and scientific organization. The natural cheese making technique of dairy farmers should be accumulated to get the consumers' solid recognition of high quality of natural cheese as LOHAS(Lifestyle Of Health And Sustainability) foods.