Recently, the environmental problem has become a global issue. The air to fuel ratio (AFR) in the combustion of thermal power plants directly influences pollutants and thermal efficiency. A research result was published showing that the AFR control performance of thermal power plants can be improved through supplementary control using dynamic matrix control (DMC). However, online optimization of DMC needs an extra computer server in implementation. This paper proposes a practical AFR control with one-step ahead control which does not use online optimization and can be implemented directly in existing distributed control system (DCS) of thermal power plants. Closed-loop transfer function models at three operating points are independently developed offline. Then, an online transfer function using interpolation of offline models is applied at each sampling step. A simple one-step ahead control with online transfer function is applied as a supplementary control of AFR. Simulations with two different type power plants, a 600 MW oil-fired drum-type power plant and a 1000 MW ultra supercritical (USC) coal-fired once-through type power plant, are performed to show the effectiveness of the proposed control structure. Simulation results show that the proposed supplementary control can effectively improve the conventional AFR control performance of power plants.

Recently, the environmental problem has become a global issue. The air to fuel ratio (AFR) in the combustion of thermal power plants directly influences pollutants and thermal efficiency. A research result was published showing that the AFR control performance of thermal power plants can be improved through supplementary control using dynamic matrix control (DMC). However, online optimization of DMC needs an extra computer server in implementation. This paper proposes a practical AFR control with one-step ahead control which does not use online optimization and can be implemented directly in existing distributed control system (DCS) of thermal power plants. Closed-loop transfer function models at three operating points are independently developed offline. Then, an online transfer function using interpolation of offline models is applied at each sampling step. A simple one-step ahead control with online transfer function is applied as a supplementary control of AFR. Simulations with two different type power plants, a 600 MW oil-fired drum-type power plant and a 1000 MW ultra supercritical (USC) coal-fired once-through type power plant, are performed to show the effectiveness of the proposed control structure. Simulation results show that the proposed supplementary control can effectively improve the conventional AFR control performance of power plants.

The intermittence of renewable energy sources increases the importance of the effective load-tracking ability of power plants. Coordinated control between boiler and turbine systems is the uppermost layer of a thermal power plant control to follow the load demand. In this paper, a supplementary controller is proposed based on the One-Step Ahead strategy for coordinated control of thermal power plants. After a plant model is developed offline from a step response test, the optimized control of the One-Step Ahead strategy is applied to the boiler feed-forward (BFF) signal to control the electric power output and the main steam pressure simultaneously. Simulation with a 1000 MW ultra-supercritical (USC) once-through type power plant is performed. The results show that the error of Mega-Watt Output (MWO) was reduced to 78~95%, and settling time was reduced to 64~79% from conventional coordinated control by adding the proposed supplementary controller.

In this paper, a transformer based 2-stage fully differential power amplifier is proposed for mmWave 5G applications. To improve the linearity of the power amplifier, a 2ndharmonic tap and diode linearization bias circuit are added to the gate of each stages, and a cross coupling capacitor is applied to increase the gain. Using 65-nm CMOS technology, the simulated PA achieves maximum gain of 32.1dB, 20.5dBm saturated output power, 17.9% power added efficiency (PAE) at 1dB compression point (OP1dB) of 16.5dBm, at 28GHz

깊이 영상 기반 렌더링은 깊이 정보를 활용하여 가상 시점의 영상을 생성하는 기술로 다양한 3차원 영상시스템에서 필요로 하는 기술이다. 깊이 영상 기반 렌더링에서 가장 어려운 과제는 가상 시점 영상에서 새롭게 드러나는 부분을 채우는 과정이다. 영상 인페인팅은 이 과정에서 보편적으로 활용되는 방법이다. 본 논문에서는 홀을 채우는 과정에서 발생하는 오류를 줄이고 자연스럽게 채우는 방법을 제안한다. 먼저 색상 영상의 정보와 깊이 정보를 활용하여 지역적으로 적응적 패치 크기를 선택하도록 하였다. 또한 패치 간 유사도에 따라 홀을 채우는 방법을 한 번에 채우는 경우와 부분적으로 채우는 경우로 구분하였다. 이를 통해 오류의 발생을 줄이고 깊이 영상 기반 렌더링에서 가장 큰 문제가 되는 오류의 전파를 억제하였다. 실험을 통해 제안한 방법이 기존의 방법보다 시각적으로 자연스러운 가상 시점 영상을 생성하는 것을 확인하였다.

깊이 영상 기반 렌더링은 깊이 정보를 활용하여 가상 시점의 영상을 생성하는 기술로 다양한 3차원 영상시스템에서 필요로 하는 기술이다. 깊이 영상 기반 렌더링에서 가장 어려운 과제는 가상 시점 영상에서 새롭게 드러나는 부분을 채우는 과정이다. 영상 인페인팅은 이 과정에서 보편적으로 활용되는 방법이다. 본 논문에서는 홀을 채우는 과정에서 발생하는 오류를 줄이고 자연스럽게 채우는 방법을 제안한다. 먼저 색상 영상의 정보와 깊이 정보를 활용하여 지역적으로 적응적 패치 크기를 선택하도록 하였다. 또한 패치 간 유사도에 따라 홀을 채우는 방법을 한 번에 채우는 경우와 부분적으로 채우는 경우로 구분하였다. 이를 통해 오류의 발생을 줄이고 깊이 영상 기반 렌더링에서 가장 큰 문제가 되는 오류의 전파를 억제하였다. 실험을 통해 제안한 방법이 기존의 방법보다 시각적으로 자연스러운 가상 시점 영상을 생성하는 것을 확인하였다.

In three-dimensional display systems, depth image based rendering is the most commonly used technique for generating images captured from a virtual viewpoint through reference views and depth maps. However, disoccluded hole filling remain a challenging issue as newly exposed area appears in the virtual view. Image inpainting based hole filling is a popular approach for filling in the hole, but the conventional methods generate annoying artifacts along the boundaries of the foreground objects. This letter presents a robust hole filling method that generates a virtual view with high quality. First, by using the local and neighboring property of the depth map, the background region is filled prior to the foreground region. Also, in the matching step to find the data to fill in, depth homogeneity is considered. Finally, based on the boundary decision using the depth property, the boundary regions are filled with background-relevant data to reduce boundary artifacts. Experimental results show that the views synthesized by the proposed method achieve higher visual comfort than the view synthesized by the existing methods.

As the number of electronic components in the car increases, the requirement for the higher data transmission scheme among them is on the sharp rise. The control area network (CAN) has been widely adopted to support the in-car communications needs but the data rate is far below what other schemes such as Ethernet and optical fibers can offer. A new scheme for enhancing the speed of CANs has been proposed, where a carrier modulated signal is introduced on top of the existing CAN signal, whereby the data rate can be enhanced over 100 Mb/s. The proposed scheme is compatible with the existing CAN network and accordingly enables seamless upgrade of the existing network to support high-speed demand using CAN protocol.

소실점(vanishing point)이란 카메라 렌즈를 통해 3차원 공간을 2차원 영상으로 투영하는 과정에서 평행한 직선들이 수렴하는 점을 의미한다. 소실점 검출은 영상 내의 정보를 이용하여 소실점의 위치를 파악하는 것을 의미하며, 영상 내 지점들의 상대적인 거리를 파악하거나 장면 전체의 3차원 구조를 파악하는데 활용된다. 일반적으로 영상 내 평행한 직선들은 인공 구조물 내에 존재하는 경우가 많으므로 직선 검출 기반 소실점 검출 기법들은 인공 구조물 내의 직선들을 찾아 이들이 수렴하는 점을 소실점으로서검출하는 것을 목표로 한다. 이 때, 영상 내에서 직선을 검출하기 위하여 먼저 에지 검출(edge detection) 을 통해 에지 픽셀을 검출하고 그 결과를 허프 변환(Hough transform)하여 직선들을 찾아낸다. 그러나각종 텍스쳐 및 노이즈 등 여러 원인들로 인해 위 과정에서 검출된 직선들이 모두 소실점을 지나지는 않는다. 따라서 검출된 직선들로부터 소실점을 정확히 검출하기 위해서는 각 직선에 대하여 소실점을 지날가능성에 따라 다른 가중치를 부여하는 것이 필요한데 기존의 연구들은 가중치를 동일하게 부여하거나 단순한 수준의 가중치 계산을 적용해 왔다. 본 논문에서는 소실점을 지나는 직선들은 대부분 인공 구조물내의 직선들임에 착안하여 직선에 가중치를 부여하는 새로운 방법을 제안하고 이를 이용한 소실점 검출결과를 몇 가지 기존 방법들과 비교하였다. 그 결과, 기존 방법들에 비하여 소실점 추정 오류가 약 65% 감소하였다.

A vanishing point is a point where parallel lines converge, and they become evident when a camera's lenses are used to project 3D space onto a 2D image plane. Vanishing point detection is the use of the information contained within an image to detect the vanishing point, and can be utilized to infer the relative distance between certain points in the image or for understanding the geometry of a 3D scene. Since parallel lines generally exist for the artificial structures within images, line-detection-based vanishing point-detection techniques aim to find the point where the parallel lines of artificial structures converge. To detect parallel lines in an image, we detect edge pixels through edge detection and then find the lines by using the Hough transform. However, the various textures and noise in an image can hamper the line-detection process so that not all of the lines converging toward the vanishing point are obvious. To overcome this difficulty, it is necessary to assign a different weight to each line according to the degree of possibility that the line passes through the vanishing point. While previous research studies assigned equal weight or adopted a simple weighting calculation, in this paper, we are proposing a new method of assigning weights to lines after noticing that the lines that pass through vanishing points typically belong to artificial structures. Experimental results show that our proposed method reduces the vanishing point-estimation error rate by 65% when compared to existing methods.