• The KIPS Transactions:PartC
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• v.15C no.6
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• pp.513-522
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• 2008

Efficient data dissemination is one of the important subjects for sensor networks. High accessibility of the sensed data can be kept by deploying the data centric storage approach in which data is stored over the nodes in the sensor network itself rather than external storages or systems. The advantage of this approach is its direct accessibility in a real-time without the severe burden on delay and power dissipation on the data path to the external storages or systems. However, if the queries from many users are concentrated to the few nodes with data, then the response time could be increased and it could lead to the reduction of network life time by rapid energy dissipation caused by concentrated network load. In this paper, we propose a adaptive data centric storage scheme based on proxy trajectory (APT) mechanism. We highlight the data centric storage mechanism by taking account of supporting large number of users, and make it feasible to provide high-performance accessibility when a non-uniform traffic pattern is offered. Storing data around the localized users by considering spatial data-access locality, the proxy trajectory of APT provides fast response for the users. The trajectory, furthermore, may help the mobile users to roams freely within the area they dwell.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.74-80
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• 2008

Spatio-temporal filters are capable of reducing noise from moving pictures, which cannot be dealt with by spatial filters. However, the algorithm is too complicated to be realized as hardware. We implemented a real-time spatio-temporal noise reduction system, using at most three frames, based upon adaptive mean filter algorithm. Some factors which interfere with hardware implementation were modified. Noise estimated from the previous frame was used to filter the current frame so that filtering could be conducted in parallel with noise estimation. This speeds up the system thereby enabling real-time execution. The form of filtering windows was also modified to facilitate synchronization. The proposed structure was implemented on Virtex 4 XC4VLX60, occupying 66% of total slices with 80MHz of the maximum operation frequency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.825-840
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• 2015

Adaptive bitrate (ABR) streaming technology has become an important and prevalent feature in many multimedia delivery systems, with content providers such as Netflix and Amazon using ABR streaming to increase bandwidth efficiency and provide the maximum user experience when channel conditions are not ideal. Where such systems could see improvement is in the delivery of live video with a closed loop cognitive control of video encoding. In this paper, we present streaming camera system which provides spatially and temporally adaptive video streams, learning the user's preferences in order to make intelligent scaling decisions. The system employs a hardware based H.264/AVC encoder for video compression. The encoding parameters can be configured by the user or by the cognitive system on behalf of the user when the bandwidth changes. A cognitive video client developed in this study learns the user's preferences(i.e. video size over frame rate) over time and intelligently adapts encoding parameters when the channel conditions change. It has been demonstrated that the cognitive decision system developed has the ability to control video bandwidth by altering the spatial and temporal resolution, as well as the ability to make scaling decisions.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.101-107
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• 2020

We propose a realistic seeing through visualization methods in mixed reality environment. When a user wants to see specific location beyond a wall in indoor environment. The proposed system recognizes and registers the selected area using environment modelling and feature-based tracking. Then the selected area is diminished and the specific location is visualized in real-time. With the proposed seeing through methods, a user can understand spatial relationship of the building and can easily find the target location. We conducted a user study comparing the seeing through method to conventional indoor navigation service in order to investigate the potential of the proposed seeing through method. The proposed seeing through method was evaluated in navigation time in comparison with conventional approach. The proposed method enable users to navigate target locations 30% faster than the conventional approach.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.41-46
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• 2018

The context of innovation in which we evolve today, subtracts us in a spacial reality and virtuality (digital) that aimed less and less to interact with natural processes which could converge to new possible relationships in the world. We constantly live in presence of fluctuations and imperceptible natural energies (wind, solar radiation, etc.) defined by flows, their own physicality, which remains without being virtual, elusive. This study first outlines how these energies already exploited within the framework of production, could be thought as interactive of our habitat's space dimension, as a prolongation of a physical and material environment built by men and for men, giving rise to new social, cultural dynamics, and making natural complexity of our space vivid, comprehensible with new visual and physical clues. In recent days, where lifestyles are changing, architecture no longer needs to limit its scope of creation to only built structures. Based on a deeper understanding of human and through new potential advanced technologies (kinetic system, etc), it is time to fundamentally diagnose what environments or devices contribute to our lives. Architecture becomes ${\ll}interface{\gg}$, step up its fundamental role, and newly defines the sturdy image and tectonics of existing environment, establishing a stance to search for a new typology. In the end, building will show two simultaneous and distinctive connections related to its physical existence: reality in its function and irreductibility, in its ability to forge new dynamic connections with its environment, hybridizing the spatial dimension to a new form of physicality, adaptive and incessantly flexible in the dimension time, becoming a vessel for ever changing contemporary lifestyles.

• Spatial Information Research
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• v.20 no.2
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• pp.13-24
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• 2012

To prevent the damage to human health by climate change, vulnerability assessment should be conducted for establishment of adaptation strategies. In this study, vulnerability assessment was conducted to provide information about vulnerable area for making adaptation policy. vulnerability assessment for human health was divided into three categories; extreme heat, ozone, and epidemic disease. To assess vulnerability, suitable indicators were selected by three criteria; sensitivity, adaptive capacity, and exposure, spatial data of indicators were prepared and processed using GIS technique. As a result, high vulnerability to extreme heat was shown in the low land regions of southern part. And vulnerability to harmful ozone was high in the surrounding area of Dae-gu basin and metropolitan area with a number of automobiles. Vulnerability of malaria and tsutsugamushi disease have a region-specific property. They were high in the vicinity of the Dimilitarized zone and south-western plain, respectively. In general, vulnerability of human health was increased in the future time. Vulnerable area was extended from south to central regions and from plain to low mountainous regions. For assessing vulnerability with high accuracy, it is necessary to prepare more related indicators and consider weight of indicators and use climate prediction data based on the newly released scenario when assessing vulnerability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.26-35
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• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1292-1299
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• 2014

Weather radar systems can provide weather information of the ground, sea, and air in extensive spatial coverage in near real time. However, it becomes problematic when ground clutter signal exists around precipitation because strong signals of ground can cause a false precipitation report. A large percentage of land coverage of Korea consists of mountainous regions where ground clutter needs to be mitigated for more accurate prediction. Thus, it is considered necessary to introduce a new suitable ground clutter removal technique specifically adequate for Korea. In this paper, the C-Map(Clutter Map) method using raw radar signals is proposed for removing ground clutter using a terrain-adaptive clutter map. A clutter map is generated using raw radar signals(I/Q) of clear days, then it is subtracted from received radar signals in frequency domain. The proposed method is applied to the radar data acquired from Sobaeksan rain radar and the result shows that the clutter rejection ratio is about 91.17 %.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.666-673
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• 2019

In the immersive virtual reality environment, we can select and manipulate various virtual objects. in order to select a virtual object, we generally use Ray-casting method that fires a virtual line in user's view and selects an object when the line and the object match, or Cone-casting method that is widely used to select multiple objects at the same time. However, since the virtual objects used in CAD are composed of small and complex objects in detail, when selecting an object in the user's view by existing methods, there occurs a ambiguity problem that needs additional realignment operation even though an object is selected as a group. in this paper, even if a virtual object is composed of several small virtual objects, it calculates the spatial and logical relationship among objects and expands or shrinks desired objects, so that the user can quickly and accurately select a desired object. in order to evaluate the proposed method, performance comparison were performed using Our and Ray-Casting and Cone-Casting methods. Experimental results show that the proposed method has the fastest speed and the highest accuracy when selecting the desired objects.