MATEX: A Distributed Framework for Transient Simulation of Power Distribution Networks

We proposed MATEX, a distributed framework for transient simulation of power distribution networks (PDNs). MATEX utilizes matrix exponential kernel with Krylov subspace approximations to solve differential equations of linear circuit. First, the whole simulation task is divided into subtasks based on decompositions of current sources, in order to reduce the computational overheads. Then these subtasks are distributed to different computing nodes and processed in parallel. Within each node, after the matrix factorization at the beginning of simulation, the adaptive time stepping solver is performed without extra matrix re-factorizations. MATEX overcomes the stiff-ness hinder of previous matrix exponential-based circuit simulator by rational Krylov subspace method, which leads to larger step sizes with smaller dimensions of Krylov subspace bases and highly accelerates the whole computation. MATEX outperforms both traditional fixed and adaptive time stepping methods, e.g., achieving around 13X over the trapezoidal framework with fixed time step for the IBM power grid benchmarks.Comment: ACM/IEEE DAC 2014. arXiv admin note: substantial text overlap with arXiv:1505.0669

Factors influencing consumers’ purchase intention on organic foods via a Theory of Planned Behaviour approach

Even though Asian countries are expected to become a dominant market for organic foods in the coming years, there are few studies which focused on young Asian consumers’ organic food purchase behaviour. This study aims to investigate how attitude, subjective norm, perceived behavioural control, and health concerns influence consumers’ intention to purchase and consume organic foods. A purposive sampling method was adopted for this study and a total of 289 usable questionnaires were collected for empirical testing of the postulated hypotheses using SPSS and structural equation modelling (SEM). The results showed that attitude, subjective norm, perceived behavioural control and health concern positively influenced intention. In addition, subjective norm positively influenced attitude while attitude played a partial mediation effect on the relationship between subjective norm and intention. Lastly, the theoretical and practical implications as well as the limitations of the study are discussed

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

Distribution of KEGG pathway annotations for S-sulfenylated proteins. (DOCX 15 kb

Enhanced Boundary Learning for Glass-like Object Segmentation

Glass-like objects such as windows, bottles, and mirrors exist widely in the real world. Sensing these objects has many applications, including robot navigation and grasping. However, this task is very challenging due to the arbitrary scenes behind glass-like objects. This paper aims to solve the glass-like object segmentation problem via enhanced boundary learning. In particular, we first propose a novel refined differential module that outputs finer boundary cues. We then introduce an edge-aware point-based graph convolution network module to model the global shape along the boundary. We use these two modules to design a decoder that generates accurate and clean segmentation results, especially on the object contours. Both modules are lightweight and effective: they can be embedded into various segmentation models. In extensive experiments on three recent glass-like object segmentation datasets, including Trans10k, MSD, and GDD, our approach establishes new state-of-the-art results. We also illustrate the strong generalization properties of our method on three generic segmentation datasets, including Cityscapes, BDD, and COCO Stuff. Code and models is available at \url{https://github.com/hehao13/EBLNet}.Comment: ICCV-2021 Code is availabe at https://github.com/hehao13/EBLNe

TransTIC: Transferring Transformer-based Image Compression from Human Visualization to Machine Perception

This work aims for transferring a Transformer-based image compression codec from human vision to machine perception without fine-tuning the codec. We propose a transferable Transformer-based image compression framework, termed TransTIC. Inspired by visual prompt tuning, we propose an instance-specific prompt generator to inject instance-specific prompts to the encoder and task-specific prompts to the decoder. Extensive experiments show that our proposed method is capable of transferring the codec to various machine tasks and outshining the competing methods significantly. To our best knowledge, this work is the first attempt to utilize prompting on the low-level image compression task

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

Aerial Image Segmentation is a particular semantic segmentation problem and has several challenging characteristics that general semantic segmentation does not have. There are two critical issues: The one is an extremely foreground-background imbalanced distribution, and the other is multiple small objects along with the complex background. Such problems make the recent dense affinity context modeling perform poorly even compared with baselines due to over-introduced background context. To handle these problems, we propose a point-wise affinity propagation module based on the Feature Pyramid Network (FPN) framework, named PointFlow. Rather than dense affinity learning, a sparse affinity map is generated upon selected points between the adjacent features, which reduces the noise introduced by the background while keeping efficiency. In particular, we design a dual point matcher to select points from the salient area and object boundaries, respectively. Experimental results on three different aerial segmentation datasets suggest that the proposed method is more effective and efficient than state-of-the-art general semantic segmentation methods. Especially, our methods achieve the best speed and accuracy trade-off on three aerial benchmarks. Further experiments on three general semantic segmentation datasets prove the generality of our method. Code will be provided in (https: //github.com/lxtGH/PFSegNets).Comment: accepted by CVPR202

Left Bundle Branch Ablation Guided by a Three-Dimensional Mapping System: A Novel Method for Establishing a Heart Failure Animal Model

Objective: Few studies have been conducted to establish animal models of left bundle branch block by using three-dimensional mapping systems. This research was aimed at creating a canine left bundle branch block model by using a three-dimensional mapping system. Materials and Methods: We used a three-dimensional mapping system to map and ablate the left bundle branch in beagles. Results: Ten canines underwent radiofrequency ablation, among which left bundle branch block was successfully established in eight, one experienced ventricular fibrillation, and one developed third-degree atrioventricular block. The maximum HV interval measured within the left ventricle was 29.00 ± 2.93 ms, and the LBP-V interval at the ablation site was 20.63 ± 2.77 ms. The LBP-V interval at the ablation target was 71.08% of the maximum HV interval. Conclusion: This three-dimensional mapping system is a reliable and effective guide for ablation of the left bundle branch in dogs

Factors influencing consumers' purchase intention on organic foods via a theory of planned behaviour approach

Even though Asian countries are expected to become a dominant market for organic foods in the coming years, there are few studies which focused on young Asian consumers’ organic food purchase behaviour. This study aims to investigate how attitude, subjective norm, perceived behavioural control, and health concerns influence consumers’ intention to purchase and consume organic foods. A purposive sampling method was adopted for this study and a total of 289 usable questionnaires were collected for empirical testing of the postulated hypotheses using SPSS and structural equation modelling (SEM). The results showed that attitude, subjective norm, perceived behavioural control and health concern positively influenced intention. In addition, subjective norm positively influenced attitude while attitude played a partial mediation effect on the relationship between subjective norm and intention. Lastly, the theoretical and practical implications as well as the limitations of the study are discussed