Encoding Lexicographical Ordering Constraints in SAT

Symmetry occurs in many constraint satisfaction problems, and it is important to deal with it efficiently and effectively, as it often leads to an exponential number of isomorphic assignments. Symmetric rows and columns in matrices are an important class of symmetries in constraint programming. In this work, we develop a new SAT encoding for partial lexicographical ordering constraints to break symmetries in such places. We also survey all the previous complete lex-leader encodings in literature and translate them into SAT encodings. We perform experimental analysis on how these lex-leader constraints impact the solving of Balanced Incomplete Block Design (BIBD) instances. Each encoding is able to outperform the other encodings on some instances, and they all perform close to each other; no clear winner can be drawn. Finally, the result shows that though using any lex-leader constraints is detrimental to finding a single BIBD, they are necessary in enumerating all BIBDs and proving non-existing designs

Contact Angle Measurement

The Contact angle, where a liquid/vapor interface meets a solid surface[wiki], has been widely used to measure the wettability of a surface in physics and chemistry. Scientists place a drop on a surface of interest, take an image of the drop in profile, and measure the angle the drop makes with the surface. We have developed a Contact Angle Measurement plugin for the ImageJ image analysis framework, which provides researchers a easier way to access experiment data. The major goal of our algorithm is to automatically detect drops and surfaces via image analysis, so that we can calculate the contact angle. Firstly, we filter the image by detecting edges and randomly sample a collection of three points on edges to get a collection of circles (note that three points define a circle)which could potentially fit the drop; then we apply various mathematical analyses to adjust the radius and position of the circle to gain a better fit. After the circle detection, we apply linear regression analysis to determine where the surface is. This approach turns out to be very reliable when the input drop region chosen by users is fairly small

Parallel Infeasibility Analysis

Oral presentation abstract

Self-Calibrated Cross Attention Network for Few-Shot Segmentation

The key to the success of few-shot segmentation (FSS) lies in how to effectively utilize support samples. Most solutions compress support foreground (FG) features into prototypes, but lose some spatial details. Instead, others use cross attention to fuse query features with uncompressed support FG. Query FG could be fused with support FG, however, query background (BG) cannot find matched BG features in support FG, yet inevitably integrates dissimilar features. Besides, as both query FG and BG are combined with support FG, they get entangled, thereby leading to ineffective segmentation. To cope with these issues, we design a self-calibrated cross attention (SCCA) block. For efficient patch-based attention, query and support features are firstly split into patches. Then, we design a patch alignment module to align each query patch with its most similar support patch for better cross attention. Specifically, SCCA takes a query patch as Q, and groups the patches from the same query image and the aligned patches from the support image as K&V. In this way, the query BG features are fused with matched BG features (from query patches), and thus the aforementioned issues will be mitigated. Moreover, when calculating SCCA, we design a scaled-cosine mechanism to better utilize the support features for similarity calculation. Extensive experiments conducted on PASCAL-5^i and COCO-20^i demonstrate the superiority of our model, e.g., the mIoU score under 5-shot setting on COCO-20^i is 5.6%+ better than previous state-of-the-arts. The code is available at https://github.com/Sam1224/SCCAN.Comment: This paper is accepted by ICCV'2

Study on Barriers and Countermeasures of Technological Innovation of Ecological Service Function Assessment of Urban Greenbelt

AbstractAs the main body of the natural productivity, the urban greenbelt, an irreplaceable comprehensive ecological service system, plays a leading role in beautifying the urban appearance, improving the quality of the urban ecological environment, adjusting the urban ecological balance. The research of ecological service function assessment is a hot research of many domains in recent times, such as ecology, environmental science, sociology, science of culture, economics, etc. Technological innovation is not only the urgent need and significant support system of technological development, but also the urgent need of solving the existing problems of the ecological service function assessment of urban greenbelt. This paper analyzes the main barriers and corresponding countermeasures of the technological innovation, such as unsound innovation mechanism, dated technological means, fault information transform, unsound assessment system, etc., which provides enlightenment and reference for the assessment, planning, construction, management and sustainable development of the ecological service function of urban greenbelt