• Title/Summary/Keyword: Gaussian distribution model

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Analysis of Drain Induced Barrier Lowering for Double Gate MOSFET Using Gaussian Distribution (가우스분포를 이용한 이중게이트 MOSFET의 드레인유기장벽감소 분석)

  • Jung, Hak-Kee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.2
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    • pp.325-330
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    • 2012
  • In this paper, drain induced barrier lowering(DIBL) has been analyzed as one of short channel effects occurred in double gate(DG) MOSFET to be next-generation devices. Since Gaussian function been used as carrier distribution for solving Poisson's equation to obtain analytical solution of potential distribution, we expect our results using this model agree with experimental results. DIBL has been investigated according to projected range and standard projected deviation as variables of Gaussian function, and channel structure and channel doping intensity as device parameter. Since the validity of this analytical potential distribution model derived from Poisson's equation has already been proved in previous papers, DIBL has been analyzed using this model. Resultly, DIBL has been greatly changed for channel structure and doping concentration.

Study on Image Processing Techniques Applying Artificial Intelligence-based Gray Scale and RGB scale

  • Lee, Sang-Hyun;Kim, Hyun-Tae
    • International Journal of Advanced Culture Technology
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    • v.10 no.2
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    • pp.252-259
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    • 2022
  • Artificial intelligence is used in fusion with image processing techniques using cameras. Image processing technology is a technology that processes objects in an image received from a camera in real time, and is used in various fields such as security monitoring and medical image analysis. If such image processing reduces the accuracy of recognition, providing incorrect information to medical image analysis, security monitoring, etc. may cause serious problems. Therefore, this paper uses a mixture of YOLOv4-tiny model and image processing algorithm and uses the COCO dataset for learning. The image processing algorithm performs five image processing methods such as normalization, Gaussian distribution, Otsu algorithm, equalization, and gradient operation. For RGB images, three image processing methods are performed: equalization, Gaussian blur, and gamma correction proceed. Among the nine algorithms applied in this paper, the Equalization and Gaussian Blur model showed the highest object detection accuracy of 96%, and the gamma correction (RGB environment) model showed the highest object detection rate of 89% outdoors (daytime). The image binarization model showed the highest object detection rate at 89% outdoors (night).

Analysis of Subthreshold Swing for Oxide Thickness and Doping Distribution in DGMOSFET (산화막두께 및 도핑분포에 대한 DGMOSFET의 문턱전압이하 스윙분석)

  • Jung, Hak-Kee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.10
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    • pp.2217-2222
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    • 2011
  • In this paper, the relationship of potential and charge distribution in channel for double gate(DG) MOSFET has been derived from Poisson's equation using Gaussian function. The relationship of subthreshold swing and oxide thickness has been investigated according to variables of doping distribution using Gaussian function, i.e. projected range and standard projected deviation, The analytical potential distribution model has been derived from Poisson's equation, and subthreshold swing has been obtained from this model for the change of oxide thickness. The subthreshold swing has been defined as the derivative of gate voltage to drain current and is theoretically minimum of 60 mS/dec, and very important factor in digital application. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the relationship of subthreshold swing and oxide thickness have been analyzed according to the shape of doping distribution.

Analysis of Subthreshold Current Deviation for Channel Doping of Double Gate MOSFET (이중게이트 MOSFET의 채널도핑에 다른 문턱전압이하 전류 변화 분석)

  • Jung, Hakkee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.6
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    • pp.1409-1413
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    • 2013
  • This paper analyzed the change of subthreshold current for channel doping concentration of double gate(DG) MOSFET. Poisson's equation had been used to analyze the potential distribution in channel, and Gaussian function had been used as carrier distribution. The potential distribution was obtained as the analytical function of channel dimension, using the boundary condition. The subthreshold current had been analyzed for channel doping concentration, and projected range and standard projected deviation of Gaussian function. Since this analytical potential model was verified in the previous papers, we used this model to analyze the subthreshold current. As a result, we know the subthreshold current was influenced on parameters of Gaussian function and channel doping concentration for DGMOSFET.

Analysis of Channel Doping Profile Dependent Threshold Voltage Characteristics for Double Gate MOSFET (이중게이트 MOSFET에서 채널도핑분포의 형태에 따른 문턱전압특성분석)

  • Jung, Hak-Kee;Han, Ji-Hyung;Lee, Jae-Hyung;Jeong, Dong-Soo;Lee, Jong-In;Kwon, Oh-Shin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.6
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    • pp.1338-1342
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    • 2011
  • In this paper, threshold voltage characteristics have been analyzed as one of short channel effects occurred in double gate(DG)MOSFET to be next-generation devices. The Gaussian function to be nearly experimental distribution has been used as carrier distribution to solve Poisson's equation, and threshold voltage has been investigated according to projected range and standard projected deviation, variables of Gaussian function. The analytical potential distribution model has been derived from Poisson's equation, and threshold voltage has been obtained from this model. Since threshold voltage has been defined as gate voltage when surface potential is twice of Fermi potential, threshold voltage has been derived from analytical model of surface potential. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the threshold voltage characteristics have been considered according to the doping profile of DGMOSFET.

Model-based Clustering of DOA Data Using von Mises Mixture Model for Sound Source Localization

  • Dinh, Quang Nguyen;Lee, Chang-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.59-66
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    • 2013
  • In this paper, we propose a probabilistic framework for model-based clustering of direction of arrival (DOA) data to obtain stable sound source localization (SSL) estimates. Model-based clustering has been shown capable of handling highly overlapped and noisy datasets, such as those involved in DOA detection. Although the Gaussian mixture model is commonly used for model-based clustering, we propose use of the von Mises mixture model as more befitting circular DOA data than a Gaussian distribution. The EM framework for the von Mises mixture model in a unit hyper sphere is degenerated for the 2D case and used as such in the proposed method. We also use a histogram of the dataset to initialize the number of clusters and the initial values of parameters, thereby saving calculation time and improving the efficiency. Experiments using simulated and real-world datasets demonstrate the performance of the proposed method.

Power Investigation of the Entropy-Based Test of Fit for Inverse Gaussian Distribution by the Information Discrimination Index

  • Choi, Byungjin
    • Communications for Statistical Applications and Methods
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    • v.19 no.6
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    • pp.837-847
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    • 2012
  • Inverse Gaussian distribution is widely used in applications to analyze and model right-skewed data. To assess the appropriateness of the distribution prior to data analysis, Mudholkar and Tian (2002) proposed an entropy-based test of fit. The test is based on the entropy power fraction(EPF) index suggested by Gokhale (1983). The simulation results report that the power of the entropy-based test is superior compared to other goodness-of-fit tests; however, this observation is based on the small-scale simulation results on the standard exponential, Weibull W(1; 2) and lognormal LN(0:5; 1) distributions. A large-scale simulation should be performed against various alternative distributions to evaluate the power of the entropy-based test; however, the use of a theoretical method is more effective to investigate the powers. In this paper, utilizing the information discrimination(ID) index defined by Ehsan et al. (1995) as a mathematical tool, we scrutinize the power of the entropy-based test. The selected alternative distributions are the gamma, Weibull and lognormal distributions, which are widely used in data analysis as an alternative to inverse Gaussian distribution. The study results are provided and an illustrative example is analyzed.

Gaussian Model for Laser Image on Curved Surface

  • Annmarie Grant;Sy-Hung Bach;Soo-Yeong Yi
    • Current Optics and Photonics
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    • v.7 no.6
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    • pp.701-707
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    • 2023
  • In laser imaging, accurate extraction of the laser's center is essential. Several methods exist to extract the laser's center in an image, such as the geometric mean, the parabolic curve fitting, and the Gaussian curve fitting, etc. The Gaussian curve fitting is the most suitable because it is based on the physical properties of the laser. The width of the Gaussian laser beam depends on the distance from the laser source to the target object. It is assumed in general that the distance remains constant at a laser spot resulting in a symmetric Gaussian model for the laser image. However, on a curved surface of the object, the distance is not constant; The laser beam is narrower on the side closer to the focal point of the laser light and wider on the side closer to the laser source, which causes the distribution of the laser beam to skew. This study presents a modified Gaussian model in the laser imaging to incorporate the slant angle of a curved object. The proposed method is verified with simulation and experiments.

Influence of non-Gaussian characteristics of wind load on fatigue damage of wind turbine

  • Zhu, Ying;Shuang, Miao
    • Wind and Structures
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    • v.31 no.3
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    • pp.217-227
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    • 2020
  • Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

Image Deblurring Using Vibration Information From 3-axis Accelerometer (3축 가속도 센서의 흔들림 정보를 이용한 영상의 Deblurring)

  • Park, Sang-Yong;Park, Eun-Soo;Kim, Hak-Il
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.3
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    • pp.1-11
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    • 2008
  • This paper proposes a real-time method using a 3-axis accelerometer to enhance blurred images taken from a camera loaded in mobile devices. Blurring phenomenon is a smoothing effect occurring in photo images. Algorithms to cope with blurring phenomenon is essential since small-size mobile devices tremble severely by even a tiny hand-shaking of a user. In this paper, accurate sensing characteristics of the 3-axis accelerometer is acquired by applying the sensor in pendulum motion and the blurring phenomenon is modeled as a uniform distribution and Gaussian distribution. Also, non-Gaussian distributed model is observed in the experiment of real blurring phenomenon and a particular deblurring function is designed by reversing the model. It has been demonstrated that the application of trembling information to the deblurring function adequately removes the blurring phenomenon.