• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.893-914
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• 2016

This paper describes the development of an inquiry-based fieldwork program based on Yangdong village where students explore the ways that it can develop in a sustainable way. Important considerations in an inquiry-based fieldwork design include what the key inquiry questions should be, the geographical issues of fieldwork location, the potential roles of mobile technologies, design of learning activities and a final product, and the roles of a teacher. Student fieldwork activities, including mapping land-use changes at the building level, detecting what should be changed or remain the same, and conducting interview with residents to examine their perceptions of overall tourism impacts, are supported by mobile technologies (i.e., the Collector for ArcGIS and the Google Forms). Twenty one high school students participated in a field test of the program in February 2016, which allowed authors to evaluate the program. Students' pre-, in-, and post-fieldwork activities were observed and the data and final products which they gathered and producted were analyzed. The post-program survey indicated that the students deepened and expanded their understanding of Yangdong village and expressed their satisfaction with the program in general. Incorporating mobile technologies into inquiry-based geographical fieldwork can help students involved in collaborative problem solving and creative activities in real world settings and create a shareable multimodal product combining maps, photo, and text.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.590-592
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• 2018

Taxis that are illegally parked on the road to catch customer can cause traffic congestion and sometimes cause traffic accidents. Stop position of taxis is determined by the long term experience of taxi drivers. In this study, We provide information to taxi drivers and customer who visit in first time through finding stop position of taxis by time. To do this, we used the Internet of Vehicle (IoV) data collected from sensors installed in 40 taxis. Previous studies attempted by forming a cluster around a taxi. Since this method is centered on a taxi, the position of the cluster changes depending on the location of the taxi. In this study, we use a road segmentation algorithm to solve these problems. Unlike the previous studies, since the cluster is formed around the road, the position of the cluster is fixed and it is not affected by the number of taxis, so it is possible to grasp the stop position in real time. The road segmentation is made up of 30m units, and map the taxi location data divided into hourly, weekday, and weekend to the nearest point. As a result of the mapping, it was difficult to see a big difference in the time of week because there were few taxis to operate on weekends, but in case of weekdays, the difference of stop position between the commute time zone and the night time zone was confirmed. The results of this study suggest that it will be possible to propose the prevention of taxi illegally driving taxi and the location of the taxi stand.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.102-109
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• 2008

In this paper, the robust hybrid modulation type classifier which use both HOS and WT key features and can recognize 10 digitally modulated signals without a priori information in multipath fading channel conditions is proposed. The proposed classifier developed using data taken field measurements in various propagation model (i,e., rural area, small town and urban area) for real world scenarios. The 9 channel data are used for supervised training and the 6 channel data are used for testing among total 15 channel data(i.e., holdout-like method). The Proposed classifier is based on HOS key features because they are relatively robust to signal distortion in AWGN and multipath environments, and combined WT key features for classifying MQAM(M=16, 64, 256) signals which are difficult to classify without equalization scheme such as AMA(Alphabet Matched Algorithm) or MMA(Multi-modulus Algorithm. To investigate the performance of proposed classifier, these selected key features are applied in SVM(Support Vector Machine) which is known to having good capability of classifying because of mapping input space to hyperspace for margin maximization. The Pcc(Probability of correct classification) of the proposed classifier shows higher than those of classifiers using only HOS or WT key features in both training channels and testing channels. Especially, the Pccs of MQAM 3re almost perfect in various SNR levels.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.117-130
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• 2011

The purpose of this study is to produce a better way to detect crossroad accidents, which involves an efficient method to produce background images in consideration of object movement and preserve/demonstrate the candidate accident region. One of the prior studies proposed an employment of traffic signal interval within crossroad to detect accidents on crossroad, but it may cause a failure to detect unwanted accidents if any object is covered on an accident site. This study adopted inverse perspective mapping to control the scale of object, and proposed different ways such as producing robust background images enough to resist surrounding noise, generating candidate accident regions through information on object movement, and by using edge information to preserve and delete the candidate accident region. In order to measure the performance of proposed algorithm, a variety of traffic images were saved and used for experiment (e.g. recorded images on rush hours via DVR installed on crossroad, different accident images recorded in day and night rainy days, and recorded images including surrounding noise of lighting and shades). As a result, it was found that there were all 20 experiment cases of accident detected and actual effective rate of accident detection amounted to 76.9% on average. In addition, the image processing rate ranged from 10~14 frame/sec depending on the area of detection region. Thus, it is concluded that there will be no problem in real-time image processing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.210-217
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• 2013

The development of collaboration among information systems in accordance with changes in enterprises' business environment brings about the problems of duplication of the existing business services and increase in costs of maintenance. Accordingly, Web service has been suggested as the standard of distributed computing to prevent the duplication of services within the same business domain and to attain the services that are already being utilized. But since the data needed for Web services are not standardized, it is difficult for the users to find services that meet diverse business purposes. In this paper, we construct an ontology-based collaboration system for service interoperability. The ontology can support fusion service by finding services which are existed interdependently under the distributed environment for collaboration processing. The role of the collaborative system includes development, registration and call of services based on ontology. A local systems request collaboration support through the service profile. Collaborative system supports the development of service using the service profiles, represents the semantic association between real data through system ontology, and infers relationship between instances contained in the services. Based on this, we applied the travel booking services for collaboration system. As a result, service can be managed effectively preventing collision in collaborative system, and we verify that the mapping between system is reduced.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.99-99
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• 2013

In this talk, I will present two research works in progress, which are: i) mapping of piezoelectric polarization and associated charge density distribution in the heteroepitaxial InGaN/GaN multi-quantum well (MQW) structure of a light emitting diode (LED) by using inline electron holography and ii) in-situ observation of the polarization switching process of an ferroelectric Pb(Zr1-x,Tix)O3 (PZT) thin film capacitor under an applied electric field in transmission electron microscope (TEM). In the first part, I will show that strain as well as total charge density distributions can be mapped quantitatively across all the functional layers constituting a LED, including n-type GaN, InGaN/GaN MQWs, and p-type GaN with sub-nm spatial resolution (~0.8 nm) by using inline electron holography. The experimentally obtained strain maps were verified by comparison with finite element method simulations and confirmed that not only InGaN QWs (2.5 nm in thickness) but also GaN QBs (10 nm in thickness) in the MQW structure are strained complementary to accommodate the lattice misfit strain. Because of this complementary strain of GaN QBs, the strain gradient and also (piezoelectric) polarization gradient across the MQW changes more steeply than expected, resulting in more polarization charge density at the MQW interfaces than the typically expected value from the spontaneous polarization mismatch alone. By quantitative and comparative analysis of the total charge density map with the polarization charge map, we can clarify what extent of the polarization charges are compensated by the electrons supplied from the n-doped GaN QBs. Comparison with the simulated energy band diagrams with various screening parameters show that only 60% of the net polarization charges are compensated by the electrons from the GaN QBs, which results in the internal field of ~2.0 MV cm-1 across each pair of GaN/InGaN of the MQW structure. In the second part of my talk, I will present in-situ observations of the polarization switching process of a planar Ni/PZT/SrRuO3 capacitor using TEM. We observed the preferential, but asymmetric, nucleation and forward growth of switched c-domains at the PZT/electrode interfaces arising from the built-in electric field beneath each interface. The subsequent sideways growth was inhibited by the depolarization field due to the imperfect charge compensation at the counter electrode and preexisting a-domain walls, leading to asymmetric switching. It was found that the preexisting a-domains split into fine a- and c-domains constituting a $90^{\circ}$ stripe domain pattern during the $180^{\circ}$ polarization switching process, revealing that these domains also actively participated in the out-of-plane polarization switching. The real-time observations uncovered the origin of the switching asymmetry and further clarified the importance of charged domain walls and the interfaces with electrodes in the ferroelectric switching processes.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.649-657
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• 2006

Reinforcement Learning is a computational approach to learning whereby an agent take an action which maximize the total amount of reward it receives among possible actions within current state when interacting with a uncertain environment. Q-learning, one of the most active algorithm in Reinforcement Learning, is consist of rewards which is obtained when an agent take an action. But it has the problem with mapping real world to discrete states. When state spaces are very large, Q-learning suffers from time for learning. In constant, when the state space is reduced, many state spaces map to single state space. Because an agent only learns single action within many states, an agent takes an action monotonously. In this paper, to reduce time for learning and complement simple action, we propose the Q-learning using influence map(QIM). By using influence map and adjacent state space's learning result, an agent could choose proper action within uncertain state where an agent does not learn. When this paper compares simulation results of QIM and Q-learning, we show that QIM effects as same as Q-learning even thought QIM uses 4.6% of the Q-learning's state spaces. This is because QIM learns faster than Q-learning about 2.77 times and the state spaces which is needed to learn is reduced, so the occurred problem is complemented by the influence map.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.67-76
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• 2010

This paper proposes a image-based water level measurement method, which adapt to the ruler's surface condition. When the surface of a ruler is deteriorated by mud, drifts, or strong light reflection, the proposed method judges the pollution of ruler by comparing distance between two levels: the first one is the end position of horizontal edge region which keeps the pattern of ruler's marking, and the second one is the position where the sharpest drop occurs in the histogram which is construct using image density based on the axis of image height. If the ruler is polluted, the water level is a position of local valley of the section having a maximum difference between the local peak and valley around the second level. If the ruler is not polluted, the water level is detected as the position having horizontal edges more than 30% of histogram's maximum value around the first level. The detected water level is converted to the actual water level by using the mapping table which is construct based on the making of ruler in the image. The proposed method is compared to the ultrasonic based method to evaluate its accuracy and efficiency on the real situation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• Composites Research
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• v.33 no.6
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• pp.365-370
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• 2020

The icing formation at aircraft occur problems such as increasing weight of the body, fuel efficiency reduction, drag reduction, the error of sensor, and etc. The viscosity of polyurethane (PU) topcoat was measured at 60℃ in real time to set the pre-curing time. SiO2 nanoparticles were dispersed in ethanol using ultra-sonication method. The SiO2/ethanol solution was sprayed on PU topcoat that was not cured fully with different pre-curing conditions. Surface roughness of SiO2/PU nanocomposites were measured using surface roughness tester and the surface roughness data was visualized using 3D mapping. The adhesion property between SiO2 and PU topcoat was evaluated using adhesion pull-off test. The static contact angle was measured using distilled water to evaluate the hydrophobicity. Finally, the pre-curing time of PU topcoat was optimized to exhibit the hydrophobicity of SiO2/PU topcoat.