• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.348-359
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• 2017

Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.60-74
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• 2007

For quantitative analysis of spatio-temporal distribution pattern on marine environment, spatial autocorrelation statistics on the both global and local aspects was applied to the observed data obtained from Gwangyang Bay in South Sea of Korea. Global indexes such as Moran's I and General G were used for understanding environmental distribution pattern in the whole study area. LISAs (local indicators of spatial association) such as Moran's I ($I_i$) and $G_i{^*}$ were considered to find similarity between a target feature and its neighborhood features and to detect hot spot and/or cold spot. Additionally, the significance test on clustered patterns by Z-scores was carried out. Statistical results showed variations of spatial patterns quantitatively in the whole year. Then all of general water quality, nutrients, chlorophyll-a and phytoplankton had strong clustered pattern in summer. When global indexes showed strong clustered pattern, the front region with a negative $I_i$ which means a strong spatial variation was observed. Also, when global indexes showed random pattern, hot spot and/or cold spot were/was found in the small local region with a local index $G_i{^*}$. Therefore, global indexes were useful for observing the strength and time series variations of clustered patterns in the whole study area, and local indexes were useful for tracing the location of hot spot and/or cold spot. Quantification of both spatial distribution pattern and clustering characteristics may play an important role to understand marine environment in depth and to find the reasons for spatial pattern.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.114-120
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• 2013

Recently, navigation systems based on wireless communication have been applied to the internal structures such as building or ship. If a stable azimuth information is obtained, these systems can effectively guide the direction of the user's progress through the information and then can improve the performance of guidance. Since conventional method which has acquired an azimuth information using geomagnetic and acceleration sensor(azimuth sensor hereafter) is sensitive to the effects of the magnetic field, it has unstable error range according to the surrounding environment. In order to improve these problems, this paper presents a new relative azimuth estimation algorithm using the displacement of a mobile node and its rotation angle based on Wireless communication. For the performance assessment of the proposed algorithm, experiments using rotating arm are performed and the results are confirmed that the proposed system can estimate the relative azimuth without using additional sensors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2293-2302
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• 2012

New optical transmission links technique for compensating of the distorted wavelength division multiplexed (WDM) signals due to group velocity dispersion (GVD) and self phase modulation (SPM) in single mode fiber (SMF) are proposed. The proposed optical links have optical phase conjugator (OPC) placed at nearby WDM transmitter or receiver and repeater spans with artificial distribution of SMF length and residual dispersion per span (RDPS). It is confirmed that optimal link configuration expanding effective launching power range and effective net residual dispersion (NRD) by improving system performance is that having OPC closely placed at WDM receiver and the gradually descended distribution of SMF length and RDPS of each repeater spans, related with the gradually increased optical link length. And, it is also confirmed that NRD is controlled by postcompensation in optimal optical link with OPC closely placed at WDM receiver.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.687-690
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• 2015

Forward collision warning systems(FCWS) and lane change assist systems(LCAS) need regions of interest for detecting lanes and objects as road regions. Watershed segmentation is effective algorithm that classify the road. That algorithm is split results appear differently depending on Watershed line with local minimum in the early part of the seed. If not road regions or vehicles combined the road's seed, It segment road with the others. For compensate the that defect, It has to adaptive change by road environment. The method is that image segmentate the several of regions of interest. Then It is set in a straight line that is detected in regions of interest. If It was detected cars on seed, seed is adjusted the location. And If It wasn't include the line, seed is adjusted the length for final decision the seed. We can detect the road region using the final seed that selected according to the road environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.519-521
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• 2022

As appearance of diverse electric power supplies and fuel cells have been emerging, UAVs have capacity to prolong their flight missions. Nowadays, the rotary based UAVs that are commonly distributed on the open market, adapt rechargeable batteries and have around 50 centimeters in width and generally within 30 minutes in hovering flight capacities. UAV's flight time highly depends on the capacity and the weight of its batteries. To cope with the flight time, recharging methods are also being researched. their researches are mainly divided into coupled and decoupled in manner. In this article, we propose the method to refine the position more effectivly and precisely adapting QR Code and 3-D position estimation so that UAVs enable to land on the recharging system successfully.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.224-238
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• 2004

Multi-modality image registration is a widely used image processing technique to obtain composite information from two different kinds of image sources. This study proposes an image registration method based on moment information and surface distance, which improves the previous surface-based registration method. The proposed method ensures stable registration results with low registration error without being subject to the initial position and direction of the object. In the preprocessing step, the surface points of the object are extracted, and then moment information is computed based on the surface points. Moment information is matched prior to fine registration based on the surface distance, in order to ensure stable registration results even when the initial positions and directions of the objects are very different. Moreover, surface comer sampling algorithm has been used in extracting representative surface points of the image to overcome the limits of the existed random sampling or systematic sampling methods. The proposed method has been applied to brain MRI(Magnetic Resonance Imaging) and PET(Positron Emission Tomography), and its accuracy and stability were verified through registration error ratio and visual inspection of the 2D/3D registration result images.

• Journal of Digital Contents Society
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• v.8 no.2
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• pp.213-225
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• 2007

This study confirms Busan area medium and small enterprises' position and analyzed present condition and actual conditions of swing Korea measure and consumer's attitude about measure in general circumstance that our country medium and small enterprises is placed in information. According to result that analyze Busan area medium and small enterprises' information level, Busan was expose by whole country average low including the electron commercial transaction rate. When consider weight that Busan economy occupies in gross domestic product, information differential of medium and small enterprises of Busan area is subject that must improve urgently and seriousness point is true that information differential of manufacturing industry is main factor more. Therefore, urgent agenda should be the activation of manufacturing industry information assistance measure and extension of current manufacturing technique information assistance business for Busan economy. Also, at problem solution progress, Busan is thought that must come looking for seat role actively.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.641-646
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• 2010

This paper presents algorithms for real-time navigation of a humanoid robot with a stereo vision but no other sensors. Using the algorithms, a robot can recognize its 3D environment by retrieving SIFT features from images, estimate its position through the Kalman filter, and plan its path to reach a destination avoiding obstacles. Our approach focuses on estimating the robot’s central walking path trajectory rather than its actual walking motion by using an approximate model. This strategy makes it possible to apply mobile robot localization approaches to humanoid robot localization. Simple collision free path planning and motion control enable the autonomous robot navigation. Experimental results demonstrate the feasibility of our approach.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.148-155
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• 2017

In this paper, we develop a new system to estimate the step count for a smartphone user. The system analyzes data obtained from the accelerometer, magnetic sensor, and gyroscope of an android smartphone to extract pattern information of human steps. We conduct an experiment and evaluation to confirm that the proposed system successfully estimates the number of steps with 96% accuracy when hand-held and 95.5% accuracy when in-pocket. In addition, we found that detection errors were caused by human motions such as touching the screen, shaking the device up and down, sitting up and sitting down, and waving the phone around.