• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.538-546
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• 2008

It has limits that system administrator deals with many problems occurred in systems because computing environments are increasingly complex. It is issued that systems have an ability to recognize system's situations and adapt them by itself in order to resolve these limits. But it requires much experiences and knowledge to build the Self-Adaptive System. The difficulty that builds the Self-Adaptive System has been problems. This paper proposes a technique that generates automatically the codes of the Self-Adaptive System in order to make the system to be built more easily. This Self-Adaptive System resolves partially the problems about ineffectiveness of the exceeded usage of the system resource that was previous research's problem and incorrect operation that is occurred by external factors such as virus. In this paper, we applied the proposed approach to the file transfer module that is in the video conferencing system in order to evaluate it. We compared the length of the codes, the number of Classes that are created by the developers, and development time. We have confirmed this approach to have the effectiveness.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.480-487
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• 2012

In Busan, the structural limitations of the road, is causing severe traffic congestion and low speed of the vehicle. So the existing traffic control system needs improvements to its structure. A study on Optimal Traffic Signal System and Improvement for User Oriented Public Transit Service are required. U-city is a city or region with ubiquitous information technology. All information systems are linked, and virtually everything is linked to an information technologies. U-Traffic goal is to maximize of traffic information services based on advanced information technology to integrate of transportation infrastructure. The objectives of this research are : a vehicle detection method through a variety of sensors, an algorithm of the traffic signal system, a design and implementation a simulator to compare between the fixed traffic signal and adaptive traffic signal system. This simulator will have allowed analysis techniques for the study of traffic control. Results of simulator test shows that traffic congestion can be some reduce.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.34-40
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• 2018

This paper presents a new method to estimate the pose of a moving object accurately using a monocular camera and a low-end GPS+IMU sensor system. For this goal, we adopted a deep neural network for the semantic segmentation of input images and compared the results with a semantic map of a neighborhood. In this map matching, we use weight tables to deal with label inconsistency effectively. Signals from a low-end GPS+IMU sensor system are used to limit search spaces and minimize the proposed function. For the evaluation, we added noise to the signals from a high-end GPS-IMU system. The results show that the pose can be recovered from the noisy signals. We also show that the proposed method is effective in handling non-open-sky situations.

• Proceedings of the KSRS Conference
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• v.1
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• pp.29-33
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• 2006

The potential impact of past Caribbean tsunamis generated by earthquakes and/or massive submarine slides/slumps, as well as the tsunamigenic potential and population distribution within the Intra-Americas Sea (IAS) was examined to help define the optimal location for coastal sea level gauges intended to serve as elements of a regional tsunami warning system. The goal of this study was to identify the minimum number of sea level gauge locations to aid in tsunami detection and provide the most warning time to the largest number of people. We identified 12 initial, prioritized locations for coastal sea level gauge installation. Our study area approximately encompasses $7^{\circ}N$, $59^{\circ}W$ to $36^{\circ}N$, $98^{\circ}$ W. The results of this systematic approach to assess priority locations for coastal sea level gauges will assist in developing a tsunami warning system (TWS) for the IAS by the National Oceanic and Atmospheric Administration (NOAA) and the Intergovernmental Oceanographic Commission's Regional Sub-Commission for the Caribbean and Adjacent Regions (IOCARIBE-GOOS).

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2042-2047
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• 2005

Many service robots which is interacting with human at home and in buildings have been developed. Few of them are shown in of the United States and of Japan. These robots are supposed to have a powerful indoor navigation performance in places where human beings live and work. The overall capability of service robots to move around in this environment is called environment correspondence, in which localization problem to find the accurate position and orientation is the most critical problem. While users set up a proper or a best environment for industrial robots, but for services robots at home and in buildings, it is very difficult to change the environment for robots. The expanded workspace due to mobility is difficult to be covered by means of those used for industrial robots because the cost increases and human beings do not want their environment to be changed for robots. This fact has made many researchers study efficient and effective environment correspondence problems. Among these problems, localization is the most difficult. Goal of localization study includes (1) Accurate detection of position and orientation (2) Minimum cost of the additional devices (3) Minimum change of human environment. In this study, as a solution of the above, we propose "Artificial Stars" which are attached on room ceiling as landmarks. In addition, we solve an adoption problem raised when a robot is delivered to a customer site and before it can perform its full navigation capability. We call this as "Initialization Problem" of service robots. We solve the initialization problem for both cases of environment with the map and without map. The proposed system is experimented and has shown how well it handles the initialization problem.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.61-72
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• 2020

The fear of crime, discussed in the early 1960s in the United States, is a psychological response, such as anxiety or concern about crime, the potential victim of a crime. These anxiety factors lead to the burden of the individual in securing the psychological stability and indirect costs of the crime against the society. Fear of crime is not a good thing, and it is a part that needs to be adjusted so that it cannot be exaggerated and distorted by the policy together with the crime coping and resolution. This is because fear of crime has as much harm as damage caused by criminal act. Eric Pawson has argued that the popular impression of violent crime is not formed because of media reports, but by official statistics. Therefore, the police should watch and analyze news related to fear of crime to reduce the social cost of fear of crime and prepare a preemptive response policy before the people have 'fear of crime'. In this paper, we propose a deep - based news classification system that helps police cope with crimes related to crimes reported in the media efficiently and quickly and precisely. The goal is to establish a system that can quickly identify changes in security issues that are rapidly increasing by categorizing news related to crime among news articles. To construct the system, crime data was learned so that news could be classified according to the type of crime. Deep learning was applied by using Google tensor flow. In the future, it is necessary to continue research on the importance of keyword according to early detection of issues that are rapidly increasing by crime type and the power of the press, and it is also necessary to constantly supplement crime related corpus.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.87-97
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• 2004

In this paper, we propose an algorithm for interlaced-to-progressive conversion by the weighted summation of the information collected from spatial do-interlacing method, in which the weighted edge based line average is applied, and the temporal method in which the motion compensation is employed by using hi-directional BMA (block matching algorithm). We employed time-recursive and motion adaptive processing as motion detection is involved. Also, a median filter is used to deal with limitation of the linear summation in which only an intermediate of values being involved is determined. The main goal of the approach is to overcome the shortcomings of each of the do-interlacing techniques without significant increment of the computational complexity, and the proposed method is apt to implement in hardware for real-time processing.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.267-268
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• 2002

Microbeam is a new avenue of radiation research especially in radiation biology and radiation protection. Selective irradiation of an ionizing particle to a targeted cell organelle may disclose such mechanisms as signal transaction among cell organelles and cell-to-cell communication in the processes toward an endpoint observed. Bystander effect, existence of which is clearly evidenced by application of the particle microbeam to biological experiments, suggests potential underestimation in the conventional risk estimation at low particle fluence rates, such as environment of space radiations in ISS (International Space Station). To promote these studies we started the construction of our microbeam facility (named as SPICE) to our HVEE Tandem accelerator (3.4 MeV proton and 5.1 MeV $^4$He$\^$2+/). For our primary goal, "irradiation of single particle to cell organelle within a position resolution of 2 micrometer in a reasonable irradiation time", special features are considered. Usage of a triplet Q magnet for focussing the beam to submicron of size is an outstanding feature compared to facilities of other institutes. Followings are other features: precise position control of cell dish holder, design of the cell dish, data acquisition of microscopic image of a cell organelle (cell nucleus) and data processing, a reliable particle detection, soft and hard wares to integrate all these related data, to control and irradiate exactly determined number of particles to a targeted spot.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.64.4-65
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• 2018

We present a study of citizen science performed at Korean Minjok Leadership Academy (KMLA). The importance of citizen involvements in scientific studies has been increasing, with remarkable results and performances. For instance, the discovery of an impact scar near Jupiter's south polar region (A. Wesley, 2009) led to an international campaign of professional observations to understand the asteroidal collision responsible for the scar. Citizen science at KMLA has been and will be mainly conducted by members of the astronomical observation club 'Apple-Pie' through amateur telescopes. Members of 'Apple-Pie' are specialized in various fields related to astronomy, from planetary science to cosmology. The spectrum not only includes fields that are directly related to astronomy but also fields such as computer science and astrophotography. The scheduled construction of a new observatory will further enable students to participate in higher level projects such as planetary monitoring over long timescales and the observation and detection of solar system bodies and exoplanets. In addition, a new supervisor with expertise and research experience in galactic astronomy, planetary science, and meteorology has joined the school faculty. He will supplement students with fundamental theoretical backgrounds and essential research techniques to enhance astronomical research at KMLA. KMLA's ultimate goal is to deploy a remote-controlled observatory available to aspiring scientists around the world to create a network of citizen science system. The prime observational conditions of KMLA and the willingness of the students and faculty members will provide a competitive edge for KMLA over other similar institutes in Korea.

• Journal of KIISE
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• v.45 no.1
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• pp.15-21
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• 2018

Low-Rank Representation (LRR) based methods are widely used in many practical applications, such as face clustering and object detection, because they can guarantee high prediction accuracy when used to constructing graphs in graph - based semi-supervised learning. However, in order to solve the LRR problem, it is necessary to perform singular value decomposition on the square matrix of the number of data points for each iteration of the algorithm; hence the calculation is inefficient. To solve this problem, we propose an improved and faster LRR method based on the recently published Fast LRR (FaLRR) and suggests ways to introduce and optimize additional constraints on the underlying optimization goals in order to address the fact that the FaLRR is fast but actually poor in classification problems. Our experiments confirm that the proposed method finds a better solution than LRR does. We also propose Fast MLRR (FaMLRR), which shows better results when the goal of minimizing is added.