40 research outputs found
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning
Federated Learning (FL) has received increasing attention due to its privacy
protection capability. However, the base algorithm FedAvg is vulnerable when it
suffers from so-called backdoor attacks. Former researchers proposed several
robust aggregation methods. Unfortunately, many of these aggregation methods
are unable to defend against backdoor attacks. What's more, the attackers
recently have proposed some hiding methods that further improve backdoor
attacks' stealthiness, making all the existing robust aggregation methods fail.
To tackle the threat of backdoor attacks, we propose a new aggregation
method, X-raying Models with A Matrix (XMAM), to reveal the malicious local
model updates submitted by the backdoor attackers. Since we observe that the
output of the Softmax layer exhibits distinguishable patterns between malicious
and benign updates, we focus on the Softmax layer's output in which the
backdoor attackers are difficult to hide their malicious behavior.
Specifically, like X-ray examinations, we investigate the local model updates
by using a matrix as an input to get their Softmax layer's outputs. Then, we
preclude updates whose outputs are abnormal by clustering. Without any training
dataset in the server, the extensive evaluations show that our XMAM can
effectively distinguish malicious local model updates from benign ones. For
instance, when other methods fail to defend against the backdoor attacks at no
more than 20% malicious clients, our method can tolerate 45% malicious clients
in the black-box mode and about 30% in Projected Gradient Descent (PGD) mode.
Besides, under adaptive attacks, the results demonstrate that XMAM can still
complete the global model training task even when there are 40% malicious
clients. Finally, we analyze our method's screening complexity, and the results
show that XMAM is about 10-10000 times faster than the existing methods.Comment: 23 page
MonoOcc: Digging into Monocular Semantic Occupancy Prediction
Monocular Semantic Occupancy Prediction aims to infer the complete 3D
geometry and semantic information of scenes from only 2D images. It has
garnered significant attention, particularly due to its potential to enhance
the 3D perception of autonomous vehicles. However, existing methods rely on a
complex cascaded framework with relatively limited information to restore 3D
scenes, including a dependency on supervision solely on the whole network's
output, single-frame input, and the utilization of a small backbone. These
challenges, in turn, hinder the optimization of the framework and yield
inferior prediction results, particularly concerning smaller and long-tailed
objects. To address these issues, we propose MonoOcc. In particular, we (i)
improve the monocular occupancy prediction framework by proposing an auxiliary
semantic loss as supervision to the shallow layers of the framework and an
image-conditioned cross-attention module to refine voxel features with visual
clues, and (ii) employ a distillation module that transfers temporal
information and richer knowledge from a larger image backbone to the monocular
semantic occupancy prediction framework with low cost of hardware. With these
advantages, our method yields state-of-the-art performance on the camera-based
SemanticKITTI Scene Completion benchmark. Codes and models can be accessed at
https://github.com/ucaszyp/MonoOccComment: Accepted by ICRA 202
Study on surface integrity of DD5 nickel-based single crystal super-alloy in creep-feed grinding
In order to control the forming surface quality of signal crystal turbine blade tenon teeth in the creep feed grinding, the influence of the creep feed grinding parameters on the grinding surface integrity of DD5 nickel-based single crystal superalloy was investigated via orthogonal experiment. The results showed that the surface roughness along vertical grinding direction was ranged at 0.56-0.74 μm at the grinding wheel speed range of 15-30 m/s, feeding velocity range of 120-210 mm/min and grinding depth range of 0.1-0.7 mm, and the surface roughness in the grinding direction is about 1/5 of that in the vertical grinding direction. The surface topography and texture results showed that there were the obvious grooves and ridges on the grinding surface caused by the grain ploughing and scratching, the length and height of grooves and ridges on the grinding surface changed obviously under different processing parameters, and the three-dimensional topography of the grinding surface fluctuated obviously. The length of grooves and ridges along the grinding direction were sensitive to the speed of grinding wheel, waviness of grooves and ridges along the vertical grinding direction were sensitive to the grinding depth and workpiece feed rate. The different degrees of work hardening effect were presented at the grinding surface, the biggest work hardening effect achieved at 11.6%, and the maximum depth of work hardening effect was 110 μm. The distinct plastic deformation appeared at the grinding surface. The γ phase presented slip deformation along the grinding direction with various degrees, and the γ' phase presented skewing, twisting, broken and fracture, the maximum depth of plastic deformation was 2.92 μm. The work hardening effect of DD5 creep feed grinding mainly due to the plastic deformation degree at the grinding surface. The experimental conclusions provided theoretical guidance for DD5 signal crystal turbine blade tenon teeth
The Impact of Mentoring Relationships on Innovation Performance of Post-90s Employees: A Dual-Path Model of Cognition and Affect
(1) Background: In recent years, post-90s employees have emerged as the driving force behind enterprise innovation, presenting unique challenges for innovation management. Their distinct characteristics and attitudes towards work require a thoughtful and adaptable approach from businesses to harness their potential effectively; (2) Methods: through empirical analysis of 518 valid samples in the Chinese context, with SPSS 26.0 and PROCESS V4.1 being used for the analysis, and to test the moderated mediation model; (3) Results: a. Mentoring relationships positively predict innovation performance; b. This relationship is mediated by role stress (cognition) and job vigor (affect); c. Innovative self-efficacy negatively moderates the impact of role stress on innovation performance and positively moderates the impact of job vigor on innovation performance; d. Moreover, innovative self-efficacy significantly moderates the mediating effect of role stress and job vigor, and the moderated mediating model is established; (4) Conclusions: Our findings reveal the “black box” of mentoring relationships in the process of influencing the innovation performance of post-90s employees, an area that has received limited research attention. This study further reveals the boundary effect of innovative self-efficacy
Identification of Distributed Dynamic Characteristics of Journal Bearing with Large Aspect Ratio under Shaft Bending
The classical theory of centralized dynamic characteristics with eight coefficients is adopted for traditional journal bearings. However, under cantilevered load, distributed dynamic characteristics along the axial direction will be generated for the journal bearing with a large aspect ratio (L/D). A double-section loading method simulating shaft bending and excitation was developed, a dynamic characteristic test-rig of a large-aspect-ratio bearing was set-up, the novel four-time vertical excitation method and eight-time cross excitation method were put forward, and the equations of 16 dynamic characteristic coefficients of the bearing were deduced. The dynamic characteristic test was carried out. The results showed that the four-time vertical excitation method had a small response amplitude in the horizontal direction, and was vulnerable to interference by the vibration of the test-rig. The eight-time cross excitation method had a higher SNR with more accurate identification results. When the cantilevered load was not applied, the dynamic characteristic coefficients were evenly distributed along the axial direction, the stiffness coefficients fluctuated slightly as the rotation rate increased, while the main damping coefficients decreased significantly. Shaft bending resulted in a significant increase in local dynamic characteristic coefficients, in which the relative increase in the stiffness coefficients was greater than that of the damping coefficients. Increasing the rotational speed can weaken the effect of shaft bending, and key factors that cause the axially nonuniform distribution of dynamic characteristic coefficients of the bearing are shaft bending and large aspect ratio under low speed and cantilevered load
Identification of Distributed Dynamic Characteristics of Journal Bearing with Large Aspect Ratio under Shaft Bending
The classical theory of centralized dynamic characteristics with eight coefficients is adopted for traditional journal bearings. However, under cantilevered load, distributed dynamic characteristics along the axial direction will be generated for the journal bearing with a large aspect ratio (L/D). A double-section loading method simulating shaft bending and excitation was developed, a dynamic characteristic test-rig of a large-aspect-ratio bearing was set-up, the novel four-time vertical excitation method and eight-time cross excitation method were put forward, and the equations of 16 dynamic characteristic coefficients of the bearing were deduced. The dynamic characteristic test was carried out. The results showed that the four-time vertical excitation method had a small response amplitude in the horizontal direction, and was vulnerable to interference by the vibration of the test-rig. The eight-time cross excitation method had a higher SNR with more accurate identification results. When the cantilevered load was not applied, the dynamic characteristic coefficients were evenly distributed along the axial direction, the stiffness coefficients fluctuated slightly as the rotation rate increased, while the main damping coefficients decreased significantly. Shaft bending resulted in a significant increase in local dynamic characteristic coefficients, in which the relative increase in the stiffness coefficients was greater than that of the damping coefficients. Increasing the rotational speed can weaken the effect of shaft bending, and key factors that cause the axially nonuniform distribution of dynamic characteristic coefficients of the bearing are shaft bending and large aspect ratio under low speed and cantilevered load
Study on machining performance of fixed-abrasive lap-grinding plate with random grid structure
To meet the increasing requirements on material removal efficiency, surface quality, and subsurface damage in the ultra-precision grinding process, a textured-fixed abrasive plate (T-FAP) with random grid structure based on the Voronoi Diagram is proposed. The abrasive tool is fabricated by using UV-curable resin and micro-level alumina abrasive grains. The influence of time-varying texture characteristics of surface wear on the machining performance is studied via MATLAB image analysis and numerical simulation of the grinding trajectory. The lap-grinding experiment of the aluminum workpieces is carried out to analyze the material removal efficiency and workpiece surface roughness obtained from the T-FAP grinding process. The results show that the surface roughness of the workpiece processed with the T-FAP grinding is 0.84 μm, and that the material removal rate is 3.21 μm/min. Compared with the traditional fixed abrasive grinding tool, the T-FAP grinding ensures the material removal efficiency and obtains high surface accuracy as well
A numerical study on contact condition and wear of roller in cold rolling
An accurate determination of the contact pressure and local sliding in a cold rolling process is an essential step towards the prediction of the roller’s life due to wear damage. This investigation utilized finite element analysis to quantify the local contact pressure and local sliding over the rolling bite in a plate cold rolling process. It was the first study to quantify the local sliding distance in a rolling process using the Finite Element Analysis (FEA). The numerical results indicate that the local contact pressure over the rolling bite demonstrates a hill profile, and the peak coincides with the neutral plane. The local sliding distance over the rolling bite demonstrates a double-peak profile with the two peaks appearing at the forward slip and backward slip zones respectively. The amplitude of sliding distance in the backward slip zone is larger than that in the forward slip zone. A stick zone was confirmed between the forward slip and backward slip zones. According to a parametric study, the local contact pressure and sliding distance decrease when the thickness reduction is reduced or the diameter of the roller is decreased. The location of the neutral plane always presents at the rolling exit side of the rolling bite’s center. The size of the stick zone enlarges and the sizes of slip zones shrink significantly when the friction coefficient is increased. Finally, a novel concept of wear intensity was defined to examine the wear of the roller based on the local contact pressure and local sliding distance. The results show that a two-peak wear response exists in the backward and forward slip zones. The magnitude of the wear in the backward slip zone is larger than that in the forward slip zone. For a given roller and blank material combination, using a smaller thickness reduction, a smaller diameter roller and a higher friction coefficient condition can reduce the wear of the roller for a single rolling cycle. The current paper develops an understanding of rolling contact responses to the wear of the roller in rolling process. The research method can also be applied to study other rolling or sliding wear problems