• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.216-219
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• 2004

In this study, the concept and techniques to generate the level lA, lB and 2A image products have been reviewed. In particular, radiometric and geometric corrections and bands registration used to generate level lA, lB and 2A products have been focused in this study. Radiometric correction is performed to take into account radiometric gain and offset calculated by compensating the detector response non-uniformity. And, in order to compensate satellite altitude, attitude, skew effects, earth rotation and earth curvature, some geometric parameters for geometric corrections are computed and applied. Bands registration process using the matching function between a geometry, which is called 'reference geometry', and another one which is corresponds to the image to be registered is applied to images in case of multi-spectral imaging mode. In order to generate level-lA image products, a simple radiometric processing is applied to a level-0 image. Level-lB image has the same radiometry correction as a level-lA image, but is also issued from some geometric corrections in order to compensate skew effects, Earth rotation effects and spectral misregistration. Level-2A image is generated using some geo-referencing parameters computed by ephemeris data, orbit attitudes and sensor angles. Level lA image is tested by visual analysis. The difference between distances calculated level 1 B image and distances of real coordinate is tested. Level 2A image is tested Using checking points.

• Proceedings of the KSRS Conference
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• v.2
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• pp.892-895
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• 2006

The atmospheric effects on the retrieval of sea ice concentration from passive microwave sensors are examined using simulated data typical for the Arctic summer. The simulation includes atmospheric contributions of cloud liquid water and water vapor and surface wind on surface emissivity on the microwave signatures. A plane parallel radiative transfer model is used to compute brightness temperatures at SSM/I frequencies over surfaces that contain open water, first-year (FY) ice and multi-year (MY) ice and their combinations. Synthetic retrievals in this study use the NASA Team (NT) algorithm for the estimation of sea ice concentrations. This study shows that if the satellite sensor’s field of view is filled with only FY ice the retrieval is not much affected by the atmospheric conditions due to the high contrast between emission signals from FY ice surface and the signals from the atmosphere. Pure MY ice concentration is generally underestimated due to the low MY ice surface emissivity that results in the enhancement of emission signals from the atmospheric parameters. Simulation results in marginal ice areas also show that the atmospheric and surface effects tend to degrade the accuracy at low sea ice concentration. FY ice concentration is overestimated and MY ice concentration is underestimated in the presence of atmospheric water and surface wind at low ice concentration. In particular, our results suggest that strong surface wind is more important than atmospheric water in contributing to the retrieval errors of total ice concentrations over marginal ice zones.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.86-101
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• 2019

Remote sensing technology has been continuously developed both quantitatively and qualitatively, including platform development, exploration area, and exploration functions. Recently, the use cases and related researches in the agricultural field are increasing. Also, since it is possible to detect and quantify the condition of cropland and establish management plans and policy support for cropland and agricultural environment, it is being studied in various fields such as crop growth abnormality determination and crop estimation based on time series information. The purpose of this study was to analyze the vegetation index for agricultural land reclamation area using a UAV equipped with a multi-spectral sensor. In addition, field surveys were conducted to evaluate the accuracy of vegetation indices calculated from multispectral image data obtained using UAV. The most appropriate vegetation index was derived by evaluating the correlation between vegetation index calculated by field survey and vegetation index calculated from UAV multispectral image, and was used to analyze vegetation index of the entire area.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.153-160
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• 2010

We optimized the Si(substrate)/$SiO_2$(cladding)/$Si_3N_4$(antiresonant cladding)/$SiO_2$(core)/air multi-layers rib-optical waveguides of antiresonant reflecting optical waveguide (ARROW) for integrated optical biosensor structure utilizing beam propagation method (BPM). Thickness of anti-resonant cladding was derived to minimize the propagation loss and leaky field mode deeply related with evanescent mode was theoretically derived. Depth, width, refractive index and cladding thickness of anti-resonant cladding were numerically calculated into 2.3${\mu}m$, 5${\mu}m$, 1.488, and 0.11${\mu}m$ respectively to minimize propagation loss using the BPM simulation tool. Finally one- and two-dimensional propagation characteristics of ARROW was confirmed.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.186-191
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• 2003

Skills in tracing of the MR divide into following, approaching, avoiding and warning and so on. It is difficult to have all these skills learned as neural network. To make this up for, skills consisted of each module, and Mobile Robot was controlled by the output of module adequate for the situation. A mobile Robot was equipped multi-ultrasonic sensor and a USB Camera, which can be in place of human sense, and the measured environment information data is learned through Modular Neural Network. MNN consisted of optimal combination of activation function in the Expert Network and its structure seemed to improve learning time and errors. The Gating Network(GN) used to control output values of the MNN by switching for angle and speed of the robot. In the paper, EN of Modular Neural network was designed optimal combination. Traveling with a real MR was performed repeatedly to verity the usefulness of the MNN which was proposed in this paper. The robot was properly controlled and driven by the result value and the experimental is rewarded with good fruits.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.19-28
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• 2017

In this paper, we propose a method to reduce the difference in image characteristics when multiple camera images are captured for virtual space production. Sixty-four images were used by cross-mounting eight bodies and lenses, respectively. Image analysis compares and analyzes the standard deviation of the histogram and pixel distribution values. As a result of the analysis, it shows different image characteristics depending on the lens or image sensor, though it is a camera of the same model. In this paper, we have adjusted the distribution of the overall brightness value of the image to compensate for this difference. As a result, the average deviation was the maximum of (Indoor: 6.89, outdoor: 24.23), we obtained images with almost no deviation (Indoor: maximum 0.42, outdoor: maximum: 2.73). In the future, we will study and apply more accurate image analysis methods than image brightness distribution.

• Composites Research
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• v.23 no.2
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• pp.24-30
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• 2010

Interfacial evaluation and hydrophobicity of Ni-nanopowder/epoxy composites were investigated for self-sensing and actuation. Contact resistance and resistivity were measured using gradient micro-specimens. The actuation of the composites in the electromagnetic field was studied with three wave functions, i.e., sine, triangle and square functions. Due tothe presence of hydrophobic domains on the heterogeneous surface, the static contact angle of Ni-nanopowder/epoxy nanocomposite wasabout $100^{\circ}$, which was rather lower than that for super-hydrophobicity. The dynamic contact angle showed the similar trend of static contact angle. Ni-nanopowder/epoxy composite was responded wellfor both self-sensing and actuation in electromagnetic field due to the intrinsic metal property of Ni-nanopowder. Displacement of the actuator of Ni-nanopowder/epoxy composite was evaluated to obtain the maximum and the optimum performance using laser displacement sensor as functions of the wave type, frequency, and voltage. Actuation of Ni-nanopowder/epoxy composites also increased as functions of applied frequency and voltage. Actuated strain increased more rapidly at sine wave with increasing voltage compared to those of triangle or rectangular waves.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.17-23
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• 2012

In this paper, we were proposed a new LED light device lighting control algorithm for optimal energy saving. The propose lighting control algorithm be to the LED lights devices lighting control by measuring illuminance into multi sensors. And it be to lighting control by inverting of octagon pattern during set-up time. All the LED is lighting when detecting motion by the motion sensor. And, it was designed enable remote management control by communicate with central monitoring center using Zigbee wireless network to measured data from sensors at real time. In this paper, a proposed lighting control algorithm was measured power consumption about the lighting status of LED lighting device using the lighting control program for demonstrate of energy savings effect. The measured result, the lighting method applying proposed algorithm were proved energy savings effect of more 40% more compared to the existing lighting method.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.89-98
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• 2012

In this paper, we proposed the efficient addressing scheme for improving the performance of routing algorithm by using ZigBee in Smart Grid environment. In a 16-bit address space and the network size of a few thousands, it is very unlikely to suffer from frequent address collisions. In response, we propose an elegant (x, y, z) coordinate axes addressing scheme from divided address space of 16 bit and its routing algorithm. One of disadvantages of (x, y) coordinate axes addressing, however, is that any router may not hold as many children as proposed, since sensor nodes tend to be connected to a geographically nearby router. We also present an adaptive routing algorithm for location-aware routing algorithms, using our addressing scheme. As a result, each node was reduced not only bitwise but also multi hop using the coordinate axes while routing and the effective address assignment and routing is to minimize the average energy consumption of each node in the network.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.