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A Time-Parameterized Data-Centric Storage Method for Storage Utilization and Energy Efficiency in Sensor Networks (센서 네트워크에서 저장 공간의 활용성과 에너지 효율성을 위한 시간 매개변수 기반의 데이타 중심 저장 기법)

  • Park, Yong-Hun;Yoon, Jong-Hyun;Seo, Bong-Min;Kim, June;Yoo, Jae-Soo
    • Journal of KIISE:Databases
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    • v.36 no.2
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    • pp.99-111
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    • 2009
  • In wireless sensor networks, various schemes have been proposed to store and process sensed data efficiently. A Data-Centric Storage(DCS) scheme assigns distributed data regions to sensors and stores sensed data to the sensor which is responsible for the data region overlapping the data. The DCS schemes have been proposed to reduce the communication cost for transmitting data and process exact queries and range queries efficiently. Recently, KDDCS that readjusts the distributed data regions dynamically to sensors based on K-D tree was proposed to overcome the storage hot-spots. However, the existing DCS schemes including KDDCS suffer from Query Hot-Spots that are formed if the query regions are not uniformly distributed. As a result, it causes reducing the life time of the sensor network. In this paper, we propose a new DCS scheme, called TPDCS(Time-Parameterized DCS), that avoids the problems of storage hot-spots and query hot-spots. To decentralize the skewed. data and queries, the data regions are assigned by a time dimension as well as data dimensions in our proposed scheme. Therefore, TPDCS extends the life time of sensor networks. It is shown through various experiments that our scheme outperform the existing schemes.

Automatic Classification by Land Use Category of National Level LULUCF Sector using Deep Learning Model (딥러닝모델을 이용한 국가수준 LULUCF 분야 토지이용 범주별 자동화 분류)

  • Park, Jeong Mook;Sim, Woo Dam;Lee, Jung Soo
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1053-1065
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    • 2019
  • Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

Learning-based Super-resolution for Text Images (글자 영상을 위한 학습기반 초고해상도 기법)

  • Heo, Bo-Young;Song, Byung Cheol
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.4
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    • pp.175-183
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    • 2015
  • The proposed algorithm consists of two stages: the learning and synthesis stages. At the learning stage, we first collect various high-resolution (HR)-low-resolution (LR) text image pairs, and quantize the LR images, and extract HR-LR block pairs. Based on quantized LR blocks, the LR-HR block pairs are clustered into a pre-determined number of classes. For each class, an optimal 2D-FIR filter is computed, and it is stored into a dictionary with the corresponding LR block for indexing. At the synthesis stage, each quantized LR block in an input LR image is compared with every LR block in the dictionary, and the FIR filter of the best-matched LR block is selected. Finally, a HR block is synthesized with the chosen filter, and a final HR image is produced. Also, in order to cope with noisy environment, we generate multiple dictionaries according to noise level at the learning stage. So, the dictionary corresponding to the noise level of the input image is chosen, and a final HR image is produced using the selected dictionary. Experimental results show that the proposed algorithm outperforms the previous works for noisy images as well as noise-free images.

The Publicity of Reasons and the Requirement of Non-Interference (이유의 공지성과 방해하지 않음의 요구조건)

  • Sung, Changwon
    • Journal of Korean Philosophical Society
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    • v.117
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    • pp.113-136
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    • 2011
  • According to the thesis of the publicity of reasons, practical reasons are public in their nature: the normative force of reasons may extend across different agents. Wallace argues that the normative mode of public reasons can be exhausted by what he calls the requirement of non-interference. I argue that the publicity thesis as he presents it equally applies to both (non-special) interpersonal relations and special relationships. At first, Wallace's version of the publicity thesis may seem incompatible with the fact that there exists reasons of positive aid. He says that when these reasons obtain in the case of interpersonal relations, they are accommodated by relevant specific moral principles. I defend this claim by showing that there is a kind of internal relation between the publicity thesis and moral principles in question. It is true that the reasons of positive aid obtain in the case of special relationships as well. I show that in this case such reasons are grounded by the requirements of the given special relationships themselves. I argue that the logical consequence of these claims is what I call the dualistic conception of our practical reasoning about what to do and that this dualism does not raise a serious challenge to the publicity thesis. The overall arguments of this paper, I believe, make us to be "realistic" about the philosophical significance of the thesis in question in moral discourses.

A 2.4-GHz Dual-Mode CMOS Power Amplifier with a Bypass Structure Using Three-Port Transformer to Improve Efficiency (3-포드 변압기를 이용한 바이패스 구조를 적용하여 효율이 개선된 이중 모드 2.4-GHz CMOS 전력 증폭기)

  • Jang, Joseph;Yoo, Jinho;Lee, Milim;Park, Changkun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.6
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    • pp.719-725
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    • 2019
  • We propose a 2.4-GHz CMOS power amplifier (PA) with a bypass structure to improve the power-added efficiency (PAE) in the low-power region. The primary winding of the output transformer is split into two parts. One of the primary windings is connected to the output of the power stage for high-power mode. The other primary winding is connected to the output of the driver stage for low-power mode. Operation of the high power mode is similar to conventional PAs. On the other hand, the output power of the driver stage becomes the output power of the overall PA in the low power mode. Owing to a turning-off of the power stage, the power consumption is decreased in low-power mode. We designed the CMOS PA using a 180-nm RFCMOS process. The measured maximum output power is 27.78 dBm with a PAE of 20.5%. At a measured output power of 16 dBm, the PAE is improved from 2.5% to 12.7%.

Characteristics of Wave Response in a 'Y' Shape Water Channel Resonator Using Resonance of Internal Fluid (내부유체 공진을 이용한 'Y'자 수로형 공명구조물내 파도응답 특성)

  • Kim, Jeongrok;Cho, Il Hyoung
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.31 no.3
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    • pp.170-179
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    • 2019
  • In this study, the wave responses in a 'Y'shape water channel resonator for amplifying wave energy of a low density has been investigated. A water channel resonator is composed of the long channel and wave guider installed at the entrance. If the period of the incident waves coincides with the natural period of the fluid in a water channel resonator, resonance occurs and the internal fluid amplifies highly to a standing wave form. In order to analyze the wave response in a water channel resonator, we used the matched asymptotic expansion method and boundary element method. The both results were in good agreement with the results of the model test carried out in the two-dimensional wave tank of Jeju National University. Wave guider has an optimum length and installation angle according to the period of the incident wave, and especially effective in enhancing the amplification factor in a period range deviated from the resonance period. It is expected that the wave energy can be effectively extracted by placing the point absorber wave energy converter at the position of anti-node where the maximum wave height is formed by the internal fluid resonance.

Watermarking for Digital Hologram by a Deep Neural Network and its Training Considering the Hologram Data Characteristics (딥 뉴럴 네트워크에 의한 디지털 홀로그램의 워터마킹 및 홀로그램 데이터 특성을 고려한 학습)

  • Lee, Juwon;Lee, Jae-Eun;Seo, Young-Ho;Kim, Dong-Wook
    • Journal of Broadcast Engineering
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    • v.26 no.3
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    • pp.296-307
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    • 2021
  • A digital hologram (DH) is an ultra-high value-added video content that includes 3D information in 2D data. Therefore, its intellectual property rights must be protected for its distribution. For this, this paper proposes a watermarking method of DH using a deep neural network. This method is a watermark (WM) invisibility, attack robustness, and blind watermarking method that does not use host information in WM extraction. The proposed network consists of four sub-networks: pre-processing for each of the host and WM, WM embedding watermark, and WM extracting watermark. This network expand the WM data to the host instead of shrinking host data to WM and concatenate it to the host to insert the WM by considering the characteristics of a DH having a strong high frequency component. In addition, in the training of this network, the difference in performance according to the data distribution property of DH is identified, and a method of selecting a training data set with the best performance in all types of DH is presented. The proposed method is tested for various types and strengths of attacks to show its performance. It also shows that this method has high practicality as it operates independently of the resolution of the host DH and WM data.

Electro chemical characteristics of $(MnX)O_2$ electrode prepared by thermal decomposition method (열분해법으로 제조된 $(MnX)O_2$ 전극의 전기화학적 특성)

  • Kim, Hyun-Sik;Lee, Hae-Yon;Huh, Jeoung-Sub;Kim, Jong-Ryung;Lee, Dong-Yoon
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.11a
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    • pp.348-351
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    • 2003
  • 산소 과전압이 낮은 $MnO_2$를 촉매로 사용하여 반도체 산화물계의 산소선택성 전극을 제조하고 산화물 coating층의 미세구조와 전기화학적 특성을 분석하였다. Ti 기판에 열분해 법을 이용하여 $MnO_2$ 피막을 형성하였고, 또한 PVDF : $MnO_2$의 함량비를 1 : 1에서 1 : 40까지 정량적으로 변화시키고 DMF의 함량을 각각의 고정된 PVDF : $MnO_2$의 함량비에서 변화시켜 Pb전극에 1.5 mm/sec의 속도로 5회 dipping하여 $MnO_2$ 피막층을 형성 하였다. $450^{\circ}C$에서 1시간 열분해하여 약 $1\;{\mu}m$$MnO_2$ 피막층이 형성되었으나 Ti 기판과의 접착력이 약하여 피막자체에 대한 전기화학적 특성을 관찰할 수 없었다. PVDF : DMF = 4 : 96인 경우 pb 전극의 피막층이 얇기 때문에 박리현상이 일어났으며 이는 산화물 용제의 낮은 점도 때문인 것으로 판단된다. 또한 PVDF : DMF = 10 : 90의 경우는 5회 dipping 하여 약 $150\;{\mu}m$의 피막층을 형성하였다. PVDF : $MnO_2$의 함량비가 1:1에서 1:6 까지는 DMF의 함량에 무관하게 전극 특성이 나타나지 않았지만 $MnO_2$의 양이 상대적으로 증가하면 cycle이 증가하더라도 거의 일정한 전류 값을 갖고 $MnO_2$와 PVDF의 비가 20:1 이상의 조성에서는 균일한 CV 특성을 나타냈다. 이는 $MnO_2$가 효과적으로 촉매 작용을 한 것으로 판단되며 anodic polarization에 의한 산소 발생 과전압도 약 1.4V 정도로 감소되었다.동등한 MSIL 코드를 생성하도록 시스템을 컴파일러 기법을 이용하여 모듈별로 구성하였다.적용하였다.n rate compared with conventional face recognition algorithms. 아니라 실내에서도 발생하고 있었다. 정량한 8개 화합물 각각과 총 휘발성 유기화합물의 스피어만 상관계수는 벤젠을 제외하고는 모두 유의하였다. 이중 톨루엔과 크실렌은 총 휘발성 유기화합물과 좋은 상관성 (톨루엔 0.76, 크실렌, 0.87)을 나타내었다. 이 연구는 톨루엔과 크실렌이 총 휘발성 유기화합물의 좋은 지표를 사용될 있고, 톨루엔, 에틸벤젠, 크실렌 등 많은 휘발성 유기화합물의 발생원은 실외뿐 아니라 실내에도 있음을 나타내고 있다.>10)의 $[^{18}F]F_2$를 얻었다. 결론: $^{18}O(p,n)^{18}F$ 핵반응을 이용하여 친전자성 방사성동위원소 $[^{18}F]F_2$를 생산하였다. 표적 챔버는 알루미늄으로 제작하였으며 본 연구에서 연구된 $[^{18}F]F_2$가스는 친핵성 치환반응으로 방사성동위원소를 도입하기 어려운 다양한 방사성의 약품개발에 유용하게 이용될 수 있을 것이다.었으나 움직임 보정 후 영상을 이용하여 비교한 경우, 결합능 변화가 선조체 영역에서 국한되어 나타나며 그 유의성이 움직임 보정 전에 비하여 낮음을 알 수 있었다. 결론: 뇌활성화 과제 수행시에 동반되는 피험자의 머리 움직임에 의하여 도파민 유리가 과대평가되었으며 이는 이 연구에서 제안한 영상정합을 이용한 움직임 보정기법에 의해서 개선되었다. 답이 없는 문제, 문제 만들기, 일반화가 가능한 문제 등으로 보고, 수학적 창의성 중 특히 확산적 사고에 초점을 맞추어 개방형 문제가 확산적 사고의 요소인 유창성, 독창성, 유연성 등에 각각 어떤 영향을 미치는지 20주의 프로그램을 개발, 진행하여 그 효과를 검증하고자

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Rear Vehicle Detection Method in Harsh Environment Using Improved Image Information (개선된 영상 정보를 이용한 가혹한 환경에서의 후방 차량 감지 방법)

  • Jeong, Jin-Seong;Kim, Hyun-Tae;Jang, Young-Min;Cho, Sang-Bok
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.1
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    • pp.96-110
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    • 2017
  • Most of vehicle detection studies using the existing general lens or wide-angle lens have a blind spot in the rear detection situation, the image is vulnerable to noise and a variety of external environments. In this paper, we propose a method that is detection in harsh external environment with noise, blind spots, etc. First, using a fish-eye lens will help minimize blind spots compared to the wide-angle lens. When angle of the lens is growing because nonlinear radial distortion also increase, calibration was used after initializing and optimizing the distortion constant in order to ensure accuracy. In addition, the original image was analyzed along with calibration to remove fog and calibrate brightness and thereby enable detection even when visibility is obstructed due to light and dark adaptations from foggy situations or sudden changes in illumination. Fog removal generally takes a considerably significant amount of time to calculate. Thus in order to reduce the calculation time, remove the fog used the major fog removal algorithm Dark Channel Prior. While Gamma Correction was used to calibrate brightness, a brightness and contrast evaluation was conducted on the image in order to determine the Gamma Value needed for correction. The evaluation used only a part instead of the entirety of the image in order to reduce the time allotted to calculation. When the brightness and contrast values were calculated, those values were used to decided Gamma value and to correct the entire image. The brightness correction and fog removal were processed in parallel, and the images were registered as a single image to minimize the calculation time needed for all the processes. Then the feature extraction method HOG was used to detect the vehicle in the corrected image. As a result, it took 0.064 seconds per frame to detect the vehicle using image correction as proposed herein, which showed a 7.5% improvement in detection rate compared to the existing vehicle detection method.

Development of Video Image-Guided Setup (VIGS) System for Tomotherapy: Preliminary Study (단층치료용 비디오 영상기반 셋업 장치의 개발: 예비연구)

  • Kim, Jin Sung;Ju, Sang Gyu;Hong, Chae Seon;Jeong, Jaewon;Son, Kihong;Shin, Jung Suk;Shin, Eunheak;Ahn, Sung Hwan;Han, Youngyih;Choi, Doo Ho
    • Progress in Medical Physics
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    • v.24 no.2
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    • pp.85-91
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    • 2013
  • At present, megavoltage computed tomography (MVCT) is the only method used to correct the position of tomotherapy patients. MVCT produces extra radiation, in addition to the radiation used for treatment, and repositioning also takes up much of the total treatment time. To address these issues, we suggest the use of a video image-guided setup (VIGS) system for correcting the position of tomotherapy patients. We developed an in-house program to correct the exact position of patients using two orthogonal images obtained from two video cameras installed at $90^{\circ}$ and fastened inside the tomotherapy gantry. The system is programmed to make automatic registration possible with the use of edge detection of the user-defined region of interest (ROI). A head-and-neck patient is then simulated using a humanoid phantom. After taking the computed tomography (CT) image, tomotherapy planning is performed. To mimic a clinical treatment course, we used an immobilization device to position the phantom on the tomotherapy couch and, using MVCT, corrected its position to match the one captured when the treatment was planned. Video images of the corrected position were used as reference images for the VIGS system. First, the position was repeatedly corrected 10 times using MVCT, and based on the saved reference video image, the patient position was then corrected 10 times using the VIGS method. Thereafter, the results of the two correction methods were compared. The results demonstrated that patient positioning using a video-imaging method ($41.7{\pm}11.2$ seconds) significantly reduces the overall time of the MVCT method ($420{\pm}6$ seconds) (p<0.05). However, there was no meaningful difference in accuracy between the two methods (x=0.11 mm, y=0.27 mm, z=0.58 mm, p>0.05). Because VIGS provides a more accurate result and reduces the required time, compared with the MVCT method, it is expected to manage the overall tomotherapy treatment process more efficiently.