• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.97-106
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• 2003

When a route choice is done under uncertainty, a driver has some expectation of traffic conditions that will occur according to the route chosen. This study tries to build a framework in which we can observe the learning behavior of the drivers' expectations of the travel time under nonstationary environment. In order to investigate how drivers have their subjective expectations on traffic conditions in response to public information, a numerical experiment is carried out. We found that rational expectations(RE) formation about the route travel time can be expressed by the adaptive expectation model when the travel time changes in accordance with the nonstationary process which consists of permanent shock and transient shock. Also, we found that the adaptive parameter of the model converges to the fixed value corresponding to the route conditions.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.19-24
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• 2010

The number of automobiles are continuously increasing in Korea since 1990's and it causes frustrating commuting traffic and holyday traffic. Meanwhile, the obsolete traffic signal control system is still under static control based on the aggregated traffic statistics thus it is not sufficiently adaptive in real world traffic situation that changes in real time. Thus, in this paper, we propose an adaptive signal control system using fuzzy control technology that can react to real time traffic situations. The method computes the priority of signal phases based on the number of waiting automobiles and occupying time on intersection using fuzzy membership functions. The phase with highest priority obtains "proceed" signal. Also, the duration of this "proceed" signal is determined based on the ratio of number of waiting automobiles of given phase and total number of waiting automobiles on intersection. In experiment, we show that the proposed fuzzy control system is better than the static control system for all sorts of traffic congestion situations by simulation.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.97-103
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• 2020

Wireless sensor networks collect and analyze sensing data in a variety of environments without human intervention. The sensor network changes its lifetime depending on routing protocols initially installed. In addition, it is difficult to modify the routing path during operating the network because sensors must consume a lot of energy resource. It is important to measure the network performance through simulation before building the sensor network into the real field. This paper proposes a WSN model for a low-energy adaptive clustering hierarchy protocol using DEVS kernel models. The proposed model is implemented with the sub models (i.e. broadcast model and controlled model) of the kernel model. Experimental results indicate that the broadcast model based WSN model showed lower CPU resource usage and higher message delivery than the broadcast model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.852-860
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• 2019

In this paper, we proposed a new trilateration technique based on exponential moving average (EMA) filter with adaptive signal model which enhances accuracy of positioning system even if the RSSI changes randomly due to movement of obstacles or blind node in indoor environment. In the proposed scheme, three fixed transmitters sent out the signal to blind node. The transmitter decides the location of the blind node based on RSSI and it estimates the cause of RSSI fluctuation which is interference of obstacle or movement of blind node. When the path between blind node and transmitter has become NLOS path because of obstacles, the transmitter ignores the measured RSSI in NLOS path and replace estimated RSSI in LOS environment. In the other case, the transmitter updated the new RSSI to represent of movement of blind node. The proposed scheme has been verified on a ZigBee testbed and we proved the improved positioning accuracy compared to the existing indoor position system.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.57-69
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• 2022

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.

• The Journal of Korean Society for Radiation Therapy
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• v.20 no.1
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• pp.45-53
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• 2008

Purpose: We are trying to analyze 130 patients' conditions by using our Helical Tomotherapy, which was installed in our center in Oct. 2007. We will be statistically approach this examination and analyze so that we will be able to figure out adaptive plans according to the change in place of the tumor, GTV (gross tumor volume), total amount of time it took, vector (${\upsilon}=\surd$x2+y2+z2) and the change in size of the tumor. Materials and Methods: Objectives were the patients who were medicated with Tomotherapy in our medical center since Oct. 2007 August 2008. The Average age of the patients were 53 years old (Minimum 25 years old, Maximum 83 years old). The parts of the body we operated were could be categorized as Head&neck (n=22), Chest (n=47), Abdomen (n=25), Pelvis (n=11), Bone (n=25). MVCT had acted on 2702 times, and also had acted on our adaptive plan toward patients who showed big difference in the size of tumor. Also, after equalizing our gained MVCT and kv-CT we checked up on the range of possible mistake, using x, y, z, roll and vector. We've also investigated on Set-up, MVCT, average time of operation and target volume. Results: Mean time on table was 22.8 minutes. Mean treatment time was 13.26 minutes. Mean correction (mm) was X=-0.7, Y=-1.4, Z=5.77, roll=0.29, vector=8.66 Head&neck patients had 2.96 mm less vector value in movement than patients of Chest, Abdomen, Bone. In increasing order, Head&neck, Bone, Abdomen, Chest, Pelvis showed the vector value in movement. Also, there were 27 patients for adaptive plan, 39 patients, who had long or multiple tumor. We could know that When medical treatment is one cure plan, it takes 32 minutes, and when medical treatment is two cure plan, it takes 40 minutes that one medical treatment takes 21 minutes, and the other medical treatment takes 19 minutes. Conclusion:With our basic tools, we could bring more accurate IMRT with MVCT. Also, through our daily image, we checked up on the change in tumor so that adaptive plan could work. It was made it possible to take the cure of long or multiple tumor, the cure in a nearby OAR, and the complicated cure that should make changes of gradient dose distribution.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1579-1590
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• 2020

In this paper, spatially-adaptive denormalization (SPADE) based U-Net is proposed to detect changes by using high-resolution satellite images. The proposed network is to preserve spatial information using SPADE. Change detection methods using high-resolution satellite images can be used to resolve various urban problems such as city planning and forecasting. For using pixel-based change detection, which is a conventional method such as Iteratively Reweighted-Multivariate Alteration Detection (IR-MAD), unchanged areas will be detected as changing areas because changes in pixels are sensitive to the state of the environment such as seasonal changes between images. Therefore, in this paper, to precisely detect the changes of the objects that consist of the city in time-series satellite images, the semantic spatial objects that consist of the city are defined, extracted through deep learning based image segmentation, and then analyzed the changes between areas to carry out change detection. The semantic objects for analyzing changes were defined as six classes: building, road, farmland, vinyl house, forest area, and waterside area. Each network model learned with KOMPSAT-3A satellite images performs a change detection for the time-series KOMPSAT-3 satellite images. For objective assessments for change detection, we use F1-score, kappa. We found that the proposed method gives a better performance compared to U-Net and UNet++ by achieving an average F1-score of 0.77, kappa of 77.29.

• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.221-241
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• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.5
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• pp.40-52
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• 2010

A mobile ad hoc network is instant and heuristic, and it is also vulnerable and volatile. Since topology and route changes are frequent, no single routing protocol designed for a conventional network performs well. Some protocols suffer from significant performance degradation when the number of nodes increases, or when nodes become highly mobile. In this paper we investigate a way to adaptively select a routing protocol that fits to the real-time network conditions. The first phase of our study is to analyze the performances of two classes of routing protocols under various network scenarios. The second phase consists of constructing a routing protocol selection reference. All nodes continue to monitor the status of neighbor nodes and control packets exchanged. Then, the aggregated information is periodically compared against the protocol selection reference. The selected routing protocol is maintained throughout the network until the network property changes substantially. The performance of the proposed algorithm is verified by a set of computer simulations using the OPNET modeler. The experimental results show that selectively changing routing protocol adaptive to the network conditions greatly improves the efficacy of bandwidth utilization.

• Progress in Medical Physics
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• v.20 no.3
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• pp.180-190
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• 2009

Depth of prostate volume from the skin can vary due to intra-fractional and inter-fractional movements, which may result in dose reduction to the target volume. Therefore we evaluated the feasibility of automated depth determination-based adaptive proton therapy to minimize the effect of inter-fractional movements of the prostate. Based on the center of mass method, using three fiducial gold markers in the prostate target volume, we determined the differences between the planning and treatment stages in prostate target location. Thirty-eight images from 10 patients were used to assess the automated depth determination method, which was also compared with manually determined depth values. The mean differences in prostate target location for the left to right (LR) and superior to inferior (SI) directions were 0.9 mm and 2.3 mm, respectively, while the maximum discrepancies in location in individual patients were 3.3 mm and 7.2 mm, respectively. In the bilateral beam configuration, the difference in the LR direction represents the target depth changes from 0.7 mm to 3.3 mm in this study. We found that 42.1%, 26.3% and 2.6% of thirty-eight inspections showed greater than 1 mm, 2 mm and 3 mm depth differences, respectively, between the planning and treatment stages. Adaptive planning based on automated depth determination may be a solution for inter-fractional movements of the prostate in proton therapy since small depth changes of the target can significantly reduce target dose during proton treatment of prostate cancer patients.