Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness

Evaluating the robustness of a defense model is a challenging task in adversarial robustness research. Obfuscated gradients, a type of gradient masking, have previously been found to exist in many defense methods and cause a false signal of robustness. In this paper, we identify a more subtle situation called Imbalanced Gradients that can also cause overestimated adversarial robustness. The phenomenon of imbalanced gradients occurs when the gradient of one term of the margin loss dominates and pushes the attack towards to a suboptimal direction. To exploit imbalanced gradients, we formulate a Margin Decomposition (MD) attack that decomposes a margin loss into individual terms and then explores the attackability of these terms separately via a two-stage process. We also propose a MultiTargeted and an ensemble version of our MD attack. By investigating 17 defense models proposed since 2018, we find that 6 models are susceptible to imbalanced gradients and our MD attack can decrease their robustness evaluated by the best baseline standalone attack by another 2%. We also provide an in-depth analysis of the likely causes of imbalanced gradients and effective countermeasures.Comment: 19 pages, 7 figue

A review of diamond synthesis, modification technology, and cutting tool application in ultra-precision machining

Diamond is the hardest natural material, boasting a variety of remarkable properties. However, due to increased demand and technological advancements, natural diamond has struggled to meet the specialized requirements of various industries. This paper offers a comprehensively critical review of diamond synthesis, modification, and cutting tool in ultra-precision machining based on the remarkable properties of diamond. Firstly, the paper outlines the outstanding properties of diamonds and breakthroughs in the original performance achieved by doping elements. Secondly, the paper focuses on recent progress in high temperature high pressure (HTHP), specifically those involving solvent-catalysts and element catalysts. The advancements in chemical vapor deposition (CVD) for diamond synthesis, emphasizing improvements in growth rate and quality, are thoroughly reviewed and summarized. Thirdly, the mechanisms of boron doping and interface modification are analyzed. Finally, the paper presents the fabrication of diamond tools and their wear mechanisms during the machining of difficult-to-cut materials and explores assisted-machining methods. Notably, the future direction of diamond synthesis will emphasize producing large-sized diamond with high growth rates, as well as doping and the preparation of diamond/metal composite materials. This critical review provides a comprehensive review of diamond preparation, modification, and cutting tools in ultra-precision machining. It serves as a valuable reference for relevant research endeavors

A New Approach for Assessing Heat Balance State along a Water Transfer Channel during Winter Periods

Ice problems in channels for water transfer in cold regions seriously affect the capacity and efficiency of water conveyance. Sometimes, ice problems such as ice jams in water transfer channels create risk during winter periods. Recently, water temperature and environmental factors at various cross-sections along the main channel of the middle route of the South-to-North Water Transfer Project in China have been measured. Based on these temperature data, the heat balance state of this water transfer channel has been investigated. A principal component analysis (PCA) method has been used to analyze the complex factors influencing the observed variations of the water temperature, by reducing eigenvector dimension and then extracting the principal component as the input feature. Based on the support vector machine (SVM) theory, a new approach for judging the heat loss or heat gain of flowing water in a channel during winter periods has been developed. The Gaussian radial basis is used as the kernel function in this new approach. Then, parameters have been optimized by means of various methods. Through the supervised machine learning process toward the observed water temperature data, it is found that the air–water temperature difference and thermal conditions are the key factors affecting the heat loss or heat absorption of water body. Results using the proposed method agree well with those of measurements. The changes of water temperature are well predicted using the proposed method together with the state of water heat balance