—The demand for high-performance anomaly detection techniques of IoT data becomes urgent, especially in industry field. The anomaly identification and explanation in time series data is one essential task in IoT data...
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In this work, we devote ourselves to the challenging task of Unsupervised Multi-view Representation Learning (UMRL), which requires learning a unified feature representation from multiple views in an unsupervised mann...
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The extraction of building contour line is an important computer-aided design work for the layout of building climbing frame walkway plates. So a study is conducted on the identification of building components and the...
The extraction of building contour line is an important computer-aided design work for the layout of building climbing frame walkway plates. So a study is conducted on the identification of building components and their characteristics for planar CAD drawings, and an algorithm for searching building contour line by line segment is proposed. Import CAD building plan data in Revit, read CAD drawing geometric information through Teigha class library, identify the walls forming the building frame, analyze the geometric features of the walls forming the building contour, the algorithm of searching the building contour line is proposed by line segment, which can effectively solve the problem of identifying the corner contour of wall break and inward depression, and can automatically extract the whole building contour from the plan CAD drawing data, laying the foundation for the optimized layout of the auxiliary climbing frame walkway plates. The experimental results show that the line segment search algorithm can effectively extract the contour of buildings from existing CAD drawing data, improving the efficiency of building climbing frame BIM modeling.
In the realm of cybersecurity, the evolution of network attacks necessitates innovative approaches for threat prediction and mitigation. Traditional methods often fall short in identifying novel attack patterns or ada...
In the realm of cybersecurity, the evolution of network attacks necessitates innovative approaches for threat prediction and mitigation. Traditional methods often fall short in identifying novel attack patterns or adapting swiftly to emerging threats. This study explores the application of Domain Generative Algorithms (DGAs) in the context of network attack prediction. DGAs leverage advanced machine learning techniques to generate synthetic data samples representing various network attack scenarios. By training generative models on diverse and large-scale datasets comprising both historical attack data and benign network traffic, the algorithms learn intricate patterns intrinsic to different types of attacks. Through, systematic analysis of these synthetic attack instances, IDS and IPS algorithms can be fine-tuned to recognize subtle attack patterns that might elude conventional signature-based detection methods. This research underscores the pivotal role of DGAs in revolutionizing the landscape of network attack prediction. By harnessing the power of generative algorithms, organizations can proactively strengthen their cybersecurity posture, effectively mitigating the risks posed by an ever-evolving spectrum of network attacks.
Chance constrained programming (CCP) refers to a type of optimization problem with uncertain constraints that are satisfied with at least a prescribed probability level. In this work, we study the sample average appro...
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In order to realize intelligent processing of drawings in building construction, improve the accuracy of drawings and provide more security for construction personnel, this paper proposes a layout algorithm of all ste...
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In order to realize intelligent processing of drawings in building construction, improve the accuracy of drawings and provide more security for construction personnel, this paper proposes a layout algorithm of all steel attached wall climbing frame walkway boards, which can read and process the building contour data. Based on the building contour data, the layout drawing of building peripheral climbing frame walkway boards can be generated by one click in Revit and the walkway board data can be obtained Read and process the recognized building contour in the database, analyze the coordinate change and summarize the law by using the processed data, and obtain the walkway board contour map, walkway board partition map and walkway board data. The implementation of this algorithm greatly improves the work efficiency of technicians and lays the foundation for the layout of other parts. It has great application value in the field of computer- aided building construction design.
This paper proposes an ocean front database and a method for its construction tailored for studying the dynamic evolution of ocean fronts. Ocean fronts play a crucial role in the interactions between the ocean and atm...
This paper proposes an ocean front database and a method for its construction tailored for studying the dynamic evolution of ocean fronts. Ocean fronts play a crucial role in the interactions between the ocean and atmosphere, affecting the transfer of heat and matter in the ocean. In recent years, research on ocean fronts has emerged as a significant and rapidly evolving area within oceanography. With the development of ocean remote sensing technology, the amount of available ocean remote sensing data has been increasing. However, the potential of this expanding volume of ocean front data remains largely untapped. The lag in data processing technology has hindered research progress in understanding ocean fronts despite the growing amount of data available. To bridge this gap, this paper proposes an ocean front dynamic evolution database along with a method for its construction to further promote research into the variations and interactions of ocean fronts. This is especially relevant for studies utilizing deep learning to explore the dynamic evolution of ocean fronts. Specifically, the proposed database is designed to capture the variation processes of ocean front enhancement and attenuation, as well as the interactions during ocean front splitting and merging. The proposed database construction method allows for the segmentation and extraction of specific ocean fronts of interest from ocean front images. The proposed method is beneficial for analyzing the dynamic evolution between multiple ocean fronts on the same timeline.
Recently, the task of contactless physiological signal monitoring based on deep learning technologies has attracted a large number of scholars. However, few studies focus on the application of real-world scenarios, es...
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