Design of a large dynamic range readout unit for the PSD detector of DAMPE

A large dynamic range is required by the Plastic Scintillator Detector (PSD) of DArk Matter Paricle Explorer (DAMPE), and a double-dynode readout has been developed. To verify this design, a prototype detector module has been constructed and tested with cosmic rays and heavy ion beams. The results match with the estimation and the readout unit could easily cover the required dynamic range

SST: A Simplified Swin Transformer-based Model for Taxi Destination Prediction based on Existing Trajectory

Accurately predicting the destination of taxi trajectories can have various benefits for intelligent location-based services. One potential method to accomplish this prediction is by converting the taxi trajectory into a two-dimensional grid and using computer vision techniques. While the Swin Transformer is an innovative computer vision architecture with demonstrated success in vision downstream tasks, it is not commonly used to solve real-world trajectory problems. In this paper, we propose a simplified Swin Transformer (SST) structure that does not use the shifted window idea in the traditional Swin Transformer, as trajectory data is consecutive in nature. Our comprehensive experiments, based on real trajectory data, demonstrate that SST can achieve higher accuracy compared to state-of-the-art methods.Comment: Accepted by IEEE ITS

Noise-to-Norm Reconstruction for Industrial Anomaly Detection and Localization

Anomaly detection has a wide range of applications and is especially important in industrial quality inspection. Currently, many top-performing anomaly-detection models rely on feature-embedding methods. However, these methods do not perform well on datasets with large variations in object locations. Reconstruction-based methods use reconstruction errors to detect anomalies without considering positional differences between samples. In this study, a reconstruction-based method using the noise-to-norm paradigm is proposed, which avoids the invariant reconstruction of anomalous regions. Our reconstruction network is based on M-net and incorporates multiscale fusion and residual attention modules to enable end-to-end anomaly detection and localization. Experiments demonstrate that the method is effective in reconstructing anomalous regions into normal patterns and achieving accurate anomaly detection and localization. On the MPDD and VisA datasets, our proposed method achieved more competitive results than the latest methods, and it set a new state-of-the-art standard on the MPDD dataset

Truncated Laplace and Gaussian mechanisms of RDP

The Laplace mechanism and the Gaussian mechanism are primary mechanisms in differential privacy, widely applicable to many scenarios involving numerical data. However, due to the infinite-range random variables they generate, the Laplace and Gaussian mechanisms may return values that are semantically impossible, such as negative numbers. To address this issue, we have designed the truncated Laplace mechanism and Gaussian mechanism. For a given truncation interval [a, b], the truncated Gaussian mechanism ensures the same Renyi Differential Privacy (RDP) as the untruncated mechanism, regardless of the values chosen for the truncation interval [a, b]. Similarly, the truncated Laplace mechanism, for specified interval [a, b], maintains the same RDP as the untruncated mechanism. We provide the RDP expressions for each of them. We believe that our study can further enhance the utility of differential privacy in specific applications

Efficient Spatial Dataset Search over Multiple Data Sources

In this paper, we investigate a novel spatial dataset search paradigm over multiple spatial data sources, which enables users to conduct join and union searches seamlessly. Specifically, we define two search problems called Maximum Intersection Query (MIQ) and Maximum Coverage Query with a Connection constraint (MCQC). To address these problems, we propose a unified Multi-source Spatial Dataset Search (MSDS) framework. In MSDS, we design a multi-layer index to accelerate the MIQ and MCQC. In addition, we prove that the MCQC is NP-hard and design two greedy algorithms to solve the problem. To deal with the constant update of spatial datasets in each data source, we design a dynamic index updating strategy and optimize search algorithms to reduce communication costs and improve search efficiency. We evaluate the efficiency of MSDS on five real-world data sources, and the experimental results show that our framework is able to achieve a significant reduction in running time and communication cost