| Title | Design and Optimization of 3D Digital Microfluidic Biochips for the Polymerase Chain Reaction |
| Author | Zipeng Li (Duke University, U.S.A.), Tsung-Yi Ho (National Chiao Tung University, Taiwan), *Krishnendu Chakrabarty (Duke University, U.S.A.) |
| Page | pp. 184 - 189 |
| Keyword | Digital Microfluidics, real-time PCR, Three-dimensional model, Layout optimization |
| Abstract | A digital microfluidic biochip (DMFB) is an attractive technology platform for revolutionizing immunoassays, clinical diagnostics, drug discovery, DNA sequencing, and other laboratory procedures in biochemistry. In most of these applications, real-time polymerase chain reaction (PCR) is an indispensable step for amplifying specific DNA segments. In recent years, three-dimensional (3D) DMFBs that integrate photodetectors (i.e., cyberphysical DMFBs) have been developed. They offer the benefits of smaller size, higher sensitivity and quicker time-to-results. However, current DMFB design methods target optimization in only two dimensions, hence they ignore the 3D two-layer structure of a DMFB. Moreover, these techniques ignore practical constraints related to the interference between on-chip device pairs, the performance-critical PCR thermal loop, and the physical size of devices. In this paper, we describe an optimization solution for a 3D DMFB, and present a three-stage algorithm to realize a compact 3D PCR chip layout, which includes: (i) PCR thermal-loop optimization; (ii) 3D global placement based on Strong-Push-Weak-Pull (SPWP) model; (iii) constraint-aware legalization. Simulation results for four laboratory protocols demonstrate that the proposed approach is effective for the design and optimization of a 3D chip for real-time PCR. |
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| Title | An Accurate and Low Cost PM2.5 Estimation Method Based on Artificial Neural Network |
| Author | *Lixue Xia, Rong Luo, Bin Zhao, Yu Wang, Huazhong Yang (Tsinghua University, China) |
| Page | pp. 190 - 195 |
| Keyword | PM2.5, Air quality, Neural network |
| Abstract | PM2.5 has already been a major pollutant in many cities in China. It is a kind of harmful pollutant which may cause several kinds of lung diseases. However, the existing methods to monitor PM2.5 with high accuracy are too expensive to popularize. The high cost also limits the further researches about PM2.5. This paper implements a method to estimate PM2.5 with low cost and high accuracy by Artificial Neural Network (ANN) technique using other pollutants and meteorological factors that are easy to be monitored. An Entropy Maximization step is proposed to avoid the over-fitting related to the data distribution of pollutant data. Also, how to choose the input attributes is abstracted to an optimization problem. An iterative greedy algorithm is proposed to solve it, which reduces the cost and increases the estimation accuracy at the same time. The experiment shows that the linear correlation coefficient between the estimated value and real value is 0.9488. Our model can also classify PM2.5 levels with a high accuracy. Additionally, the trade-off between accuracy and cost is investigated according to the price and error rate of each sensor. |
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| Title | Iterative Disparity Voting Based Stereo Matching Algorithm and Its Hardware Implementation |
| Author | Zhi Hu, *Yibo Fan, Xiaoyang Zeng (State Key Lab of ASIC & System, Fudan University, China) |
| Page | pp. 196 - 201 |
| Keyword | stereo matching, hardware-oriented, disparity voting |
| Abstract | Stereo matching is one of the key problems in computer vision. A large number of algorithms have been proposed but few of them achieve both high accuracy and short processing time on hardware. This paper presents a hardware-oriented stereo matching algorithm which is able to generate software-oriented-level results for 1920×1080 images at 48fps. Such performance prefigures new vistas of the applications of VLSI in stereo vision. |
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| Title | Obstacle-Avoiding Wind Turbine Placement for Power-Loss and Wake-Effect Optimization |
| Author | *Yu-Wei Wu (National Cheng Kung University, Taiwan), Yi-yu Shi (Missouri University of Science and Technology, U.S.A.), Sudip Roy (National Cheng Kung University, Taiwan), Tsung-Yi Ho (National Chiao Tung University, Taiwan) |
| Page | pp. 202 - 207 |
| Keyword | Placement, Wind Turbine |
| Abstract | As finite energy resources are being consumed at fast rate than they can be replaced, renewable energy resources have drawn an extensive attention. Wind power development is one such example, which is growing significantly throughout the world. The main difficulty in wind power development is that wind turbines interfere with each other and such turbulent directly affects the power produced, known as the wake effect. In addition, wirelength among wind turbines is not merely an economic factor, but also more decides the power loss occurs in the wirelength. Moreover, in reality, obstacles exist in the wind farm which is unavoidable, e.g., private land, lake and so on. Nevertheless, to the best of our knowledge, none of the existing works consider wake effect, wirelength and obstacle-avoiding at the same time in the wind turbine placement problem. In this paper, we propose an analytical method to solve obstacle-avoiding placement of wind turbines for power-loss and wake-effect optimization. Experimental results show that the wind power produced by our tool is similar to that by the industrial tool AWS OpenWind. Besides, our algorithm can reduce the wirelength and avoid obstacles successfully while finding the locations of wind turbines at the same time. |
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