• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.722-725
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• 2013

In this work, we have been analyzed the characteristics of ReRAM with different annealing condition and temperature. The ReRAM devices with top electrode=150nm, bottom electrode=150nm, oxide thickness=70nm and annealing temperature=$500^{\circ}C$, $850^{\circ}C$ have been used in characterization. The Set/Reset voltage, sensing window and resistivity have been characterized. From the measurement results, the Set/Reset voltage and sensing window have been enhanced as the annealing temperature has been increased. But it has been decreased as the temperature performance has been increased. In case of the annealing temperature=$850^{\circ}C$, the variation of Set/Reset voltage was lower than that of other condition. But the variation of sensing window was the lowest when the annealing temperature was $500^{\circ}C$. With considering the variation of Set/Reset voltage and sensing window, the devices annealed at $850^{\circ}C$ showed the best performance to ReRAM.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.554-556
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• 2005

Meteorological imager on the Multi-functional Transport Satellite (MTSAT-IR), which has been operating formally since 28 June 2005, was intercalibrated with a polar orbit satellite [Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS)] as a well-calibrated instrument. The intercalibration method used in this study was developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS). This was done for the infrared window channels. The differences of MTSAT-IR and MODIS were are -0.26 K for $11\;\mu m-IR$ window channel, 0.40 K for $12\;\mu m-IR$, window channel, and -0.67 K for $6.7\;\mu m-water$ vapor channel.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.78-86
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• 2010

The Spectrum Sensing Technology is the core technology of the Cognitive Radio (CR) System that is one of the future wireless communication technologies. In this paper, we proposed the efficient Spectrum Sensing Method using the Short Time Fourier Transform (STFT) that is the algorithm for Time-Frequency analysis of the raw data. Applied window function to STFT algorithm is a Kaiser window, it is piled up its 50% range. For the simulation, the DVB-H signal with the 6MHz bandwidth is used as the Input Signal. And we confirm the Spectrum Sensing result using Modified Periodogram Method, Welch's Method for compared with Short Time Fourier Transform Algorithm. And also, Spectrum Sensing Module is implemented using embedded board.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.221-221
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• 2009

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1105-1116
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• 2008

Cognitive radio is one of the most effective techniques to improve the spectrum utilization efficiency. To implement the cognitive radio, spectrum sensing is considered as the key functionality because only counting on it, can the secondary users identify the spectrum holes and utilize them efficiently without causing interference to primary users. Generally, there are several spectrum sensing methods; the most common and simplest method is energy detection. However, the conventional energy detection has some disadvantages, which are caused by noise, especially, uncertain noise power leads to degradation of energy detector. In this paper, to solve this problem, we proposed sliding window-based energy detection method which can devide the frequency band of primary signal and noise using sliding window to estimate the power of primary user without the noise effect and achieve the better performance. It can calculate the energy of primary user only and can detect the primary signal. The simulation result shows that our proposed method outperforms conventional one.

• Korean Journal of Remote Sensing
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• v.11 no.1
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• pp.31-45
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• 1995

The values of brightness temperature difference (BTD) between 11um and 12um infrared channels may reflect amounts of low-level water vapor and cloud types due to the different absorptivity for water vapor between two channels. A simple method of classifying cloud types at night was proposed. Two-dimensional histograms of brightness temperature of the 11um channel and the BTD between the split window data over subareas around characteristic clouds such as Cb(cumulonimbus), Ci(cirrus), and Sc(stratocumulus) was constructed. Cb, Ci and Sc can be classified by seleting appropriate thresholds in the two-dimensional histograms. And we can see amounts of low-level water vapor in clear area as well as cloud types in cloudy area in the BTD image. The map of cloud types and low-level water vapor generated by this method was compared with 850hPa and 1000hPa relative humidity(%) of numerical analysis data and nephanalysis chart. The comparisons showed reasonable agreement.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.18-21
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• 2005

The impact of the interannual climatic variability on the vegetation sensitively appears in the timing of phenological events such as green-up, mature, and senescence. Therefore, an accurate and temporally high-resolution NDVI dataset will be required for analysis on the interannual variability of the climate-vegetation relationship. We constructed a daily 8km NDVI dataset over Eurasia based on the 8km tiled data of Pathfinder A VHRR Land (PAL) Global daily product. Cloud contamination was successfully reduced by Temporal Window Operation (TWO), which is a method to find optimized upper envelop line of the NDVI seasonal change. Based on the daily NDVI time series from 1982 to 2000, an accurate (daily) interannual change of the phenological events will be analyzed.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.601-612
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• 2006

This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1657-1662
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• 2014

In this paper, the impact of substrate bias($V_{BS}$) on the zero capacitor RAM(Z-RAM) in n-channel junctionless multiple gate MOSFET(MuGFET) has been analyzed experimentally. Junctionless transistors with fin width of 50nm and 1 fin exhibits a memory window of 0.34V and a sensing margin of $1.8{\times}10^4$ at $V_{DS}=3.5V$ and $V_{BS}=0V$. As the positive $V_{BS}$ is applied, the memory window and sensing margin were improved due to an increase of impact ionization. When $V_{BS}$ is increased from 0V to 10V, not only the memory window is increased from 0.34V to 0.96V but also sensing margin is increased slightly. The sensitivity of memory window with different $V_{BS}$ in junctionless transistor was larger than that of inversion-mode transistor. A retention time of junctionless transistor is better than that of inversion-mode transistor due to low Gate Induced Drain Leakage(GIDL) current. To evaluate the device reliability of Z-RAM, the shifts in the Set/Reset voltages and current were measured.

• Korean Journal of Remote Sensing
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• v.8 no.1
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• pp.15-26
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• 1992

This paper describes an implementation of adaptive stereo matching for DBM generation. The matching method of two stereo satellite images to find corresponding points used in this paper is area-based matching, which is usually used in the field of making DBM. Same window size and search area used as in the conventional matching methods and we propose adaptive stereo matching algorithm in this paper. We cluster three areas which are consist of mountainous areas, cultivated areas and cities, and rivers and lakes by using proposed linear feature extracting method. These classified areas are matched by adaptive window size and search area, but rivers and lakes is excluded in this experiment. The matching time is three times faster than conventional methods.