• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.140-143
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• 2017

Lately, the three mobile telecom companies in Korea are competing for the launch of internet of things services for using home. Typical launched services are in the smart home related fields. However, internet of things as mobile telecom based are at an early stage, expected that various services will be started continuously. At this point, we have been planning to analyze the preference of Internet of things for objects based on the services already launched. In order to apply the AHP (analytic hierarchy process) analysis method, the first stage factors were designed as safety, security, health care, intelligence and home appliances. In addition, the second stage factors were organized into 18 detailed services presented in the conceptual model. Thus, we present the theoretical and practical implications of these results.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.327-334
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• 2017

For enhancing network efficiency, various applications/services like CDN and P2P try to utilize content which have previously been cached somewhere. Content-centric networking (CCN) also utilizes data caching functionality. However, dislike CDN/P2P, CCN implements such a function on network nodes. Then, any intermediated nodes can directly respond to request messages for cached data. Hence, it is essential which content is cached as well as which nodes cache transmitted content. Basically, CCN propose for every nodes on the path from the content publisher of transmitted object to a requester to cache the object. However, such an approach is inefficient considering the utilization of cached objects as well as the storage overhead of each node. Hence, various caching mechanisms are proposed to enhance the storage efficiency of a node. In this paper, we analyze the performance of such mechanisms and compare the characteristics of such mechanisms. Also, we analyze content utilization patterns and apply such pattern to caching mechanisms to analyze the practicalism of the caching mechanisms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.9
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• pp.614-619
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• 2014

In WSN (Wireless Sensor Networks) based surveillance system, it needs to know the occurrence of events or objects and their locations, because the data have no meaning without location information. Using traditional 2D localization mechanisms provide good accuracy where altitude is fixed. But the mapping the position estimated by 2D localization to the real world can cause an error. Even though 3D localization mechanisms provide better accuracy than 2D localization, they need four reference nodes at least and high processing overhead. In our surveillance system, it is needed to estimate the height of the detected object in order to determine if the object is human. In this paper, we propose a height estimation mechanism which does not require many reference nodes and high complexity. Finally, we verify the performance of our proposed mechanism through various experiments.

• Korean Institute of Interior Design Journal
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• v.25 no.3
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• pp.51-59
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• 2016

The technique for Eye-tracking is to trace the movements of pupils so that the eye's exploration response to be digitized. The procedure of Observation Experiment shows a mutual environmental characteristics between men and measuring devices. In order to improve the reliability and to secure the objectivity of the data acquired from eye-tracking, it is very important to analyze the procedures for the experiment to be prepared and the test data to be saved. Based on this viewpoint, the convergent exploration activities at the observation experiment with the objects of sport images were examined to find out what influences the context effect given by experimental environments have on this experiment. In addition, the starting time of attention affecting the reliability of observation data has been estimated. When the observation time is to be subdivided by the unit of second. The attention disperses for the individual characteristics to be appreciated. However, in case of analysis by the overall average, there was the problem that the section of attention dispersed to make it difficult to analyze the subjects' observation features. The study results made it possible to understand the physiological characteristics which were near unconsciousness, when there was an intensive attention for the first 3 seconds and the observation data were shown to be in ordinary range after 4 seconds. The analysis of observation with the focus of the intensive attention enabled the analysis with the first 3 seconds excepted so that it might approach the ordinary range of observation data. The distribution of attention for the first 3 seconds showed the intensive attention, which was on the center. The emergence of intensive attention and the overlapping of the centers can be considered as a context effect due to the correction for the preparing process of experiment. Accordingly, it is thought to be helpful to the security of objectivity and the construction of reliability of eye-tracking data to analyze the observation features shown after the deletion of the data for the first 3 seconds.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.153-165
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• 2010

In this paper, we proposed a Proactive Application Service Engine (PASE) supporting tailor-made distributed application services based on the Distributed Object Group Framework (DOGF) efficiently managing distributed objects, in the viewpoint of distributed application, composed application on network. The PASE consists of 3 layers which are the physical layer, the middleware layer, and the application layer. With the supporting services of the PASE, the grouping service manages the data gathered from H/W devices and the object's properties for application by user's request as a group. And the security service manages the access of gathered data and the object according to user's right. The data filtering service executes the filtering function to provide application with gathered data. The statistics service analysis past data. The diagnostic service diagnoses a present condition by using the gathered data. And the prediction service predicts a future's status based on the statistics service and the diagnostic service. For verifying the executability of the PASE's services, we applied to a greenhouse automatic control application in ubiquitous agriculture field.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.192-198
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• 2018

Recently, the use of drone has been increasing rapidly in many ways. A drone can capture remote objects efficiently so it is suitable for surveillance and security systems. This paper discusses three methods for detecting moving vehicles using a drone. We compare three target detection methods using a background frame, preceding frames, or moving average frames. They are subtracted from a current frame. After the frame subtraction, morphological filters are applied to increase the detection rate and reduce the false alarm rate. In addition, the false alarm region is removed based on the true size of targets. In the experiments, three moving vehicles were captured by a drone, and the detection rate and the false alarm rate were obtained by three different methods and the results are compared.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.311-318
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• 2021

Research has been ongoing to detect ships from offshore photographs for a variety of reasons, including maritime security, identifying international trends, and social scientific research. Due to the development of artificial intelligence, R-CNN models for object detection in photographs and images have emerged, and the performance of object detection has risen dramatically. Ship detection in offshore photographs using the R-CNN model has also begun to apply to satellite photography. However, satellite images project large areas, so various objects such as vehicles, landforms, and buildings are sometimes recognized as ships. In this paper, we propose a novel methodology to improve the performance of ship detection in satellite photographs using R-CNN series models. We separate land and sea via marker-based watershed algorithm and perform morphology operations to specify RoI one more time, then detect vessels using R-CNN family models on specific RoI to reduce typology. Using this method, we could reduce the misdetection rate by 80% compared to using only the Fast R-CNN.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.771-780
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• 2021

The space Debris laser ranging system is called to be a definite type of satellite laser ranging system that measures the distance to satellites. It is a system that performs POD (Precise Orbit Determination) by measuring time of flight by firing a laser. Distance precision can be measured in mm-level units, and it is the most precise system among existing systems. Currently, KASI has built SLR in Sejong and Geochang, and utilized SLR data to verify the precise orbits of the STSAT-2C and KOMASAT-5. In recent years, due to the fall or collision of space debris, its satellites have been threatened, and in terms of security, laser tracking of space objects is receiving great interest in order to protect their own space assets and protect the safety of the people. In this paper, a 1.5m-class main mirror was applied for the system design of a multipurpose laser tracking system that considers satellite laser ranging and space object laser tracking. System preliminary performance analysis was performed based on Link Budget analysis considering specifications of major components.

• Journal of the Korea Society for Simulation
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• v.31 no.2
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• pp.11-20
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• 2022

There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.169-171
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• 2021

Image processing through cameras such as self-driving, CCTV, mobile phone security, and parking facilities is being used to solve many real-life problems. Simple classification is solved through image processing, but it is difficult to find images or in-image features of complexly mixed objects. To solve this feature point, we utilize deep learning techniques in classification, detection, and segmentation of image data so that we can think and judge closely. Of course, the results are better than just image processing, but we confirm that the results judged by the method of image segmentation using deep learning have deviations from the real object. In this paper, we study how to perform accuracy improvement through simple image processing just before outputting the output of deep learning image segmentation to increase the precision of image segmentation.