40 research outputs found
Outlier Robust Adversarial Training
Supervised learning models are challenged by the intrinsic complexities of
training data such as outliers and minority subpopulations and intentional
attacks at inference time with adversarial samples. While traditional robust
learning methods and the recent adversarial training approaches are designed to
handle each of the two challenges, to date, no work has been done to develop
models that are robust with regard to the low-quality training data and the
potential adversarial attack at inference time simultaneously. It is for this
reason that we introduce Outlier Robust Adversarial Training (ORAT) in this
work. ORAT is based on a bi-level optimization formulation of adversarial
training with a robust rank-based loss function. Theoretically, we show that
the learning objective of ORAT satisfies the -consistency in
binary classification, which establishes it as a proper surrogate to
adversarial 0/1 loss. Furthermore, we analyze its generalization ability and
provide uniform convergence rates in high probability. ORAT can be optimized
with a simple algorithm. Experimental evaluations on three benchmark datasets
demonstrate the effectiveness and robustness of ORAT in handling outliers and
adversarial attacks. Our code is available at
https://github.com/discovershu/ORAT.Comment: Accepted by The 15th Asian Conference on Machine Learning (ACML 2023
Differentially Private SGDA for Minimax Problems
Stochastic gradient descent ascent (SGDA) and its variants have been the
workhorse for solving minimax problems. However, in contrast to the
well-studied stochastic gradient descent (SGD) with differential privacy (DP)
constraints, there is little work on understanding the generalization (utility)
of SGDA with DP constraints. In this paper, we use the algorithmic stability
approach to establish the generalization (utility) of DP-SGDA in different
settings. In particular, for the convex-concave setting, we prove that the
DP-SGDA can achieve an optimal utility rate in terms of the weak primal-dual
population risk in both smooth and non-smooth cases. To our best knowledge,
this is the first-ever-known result for DP-SGDA in the non-smooth case. We
further provide its utility analysis in the nonconvex-strongly-concave setting
which is the first-ever-known result in terms of the primal population risk.
The convergence and generalization results for this nonconvex setting are new
even in the non-private setting. Finally, numerical experiments are conducted
to demonstrate the effectiveness of DP-SGDA for both convex and nonconvex
cases
Clinical Outcomes of Hematopoietic Cell Transplantation in Patients with Diffuse Large B Cell Lymphoma Transformed From Follicular Lymphoma
Seaweed polysaccharide relieves hexavalent chromium-induced gut microbial homeostasis
Heavy metals released in the environment pose a huge threat to soil and water quality, food safety and public health. Additionally, humans and other mammals may also be directly exposed to heavy metals or exposed to heavy metals through the food chain, which seriously threatens the health of animals and humans. Chromium, especially hexavalent chromium [Cr (VI)], as a common heavy metal, has been shown to cause serious environmental pollution as well as intestinal damage. Thus, increasing research is devoted to finding drugs to mitigate the negative health effects of hexavalent chromium exposure. Seaweed polysaccharides have been demonstrated to have many pharmacological effects, but whether it can alleviate gut microbial dysbiosis caused by hexavalent chromium exposure has not been well characterized. Here, we hypothesized that seaweed polysaccharides could alleviate hexavalent chromium exposure-induced poor health in mice. Mice in Cr and seaweed polysaccharide treatment group was compulsively receive K2Cr2O7. At the end of the experiment, all mice were euthanized, and colon contents were collected for DNA sequencing analysis. Results showed that seaweed polysaccharide administration can restore the gut microbial dysbiosis and the reduction of gut microbial diversity caused by hexavalent chromium exposure in mice. Hexavalent chromium exposure also caused significant changes in the gut microbial composition of mice, including an increase in some pathogenic bacteria and a decrease in beneficial bacteria. However, seaweed polysaccharides administration could ameliorate the composition of gut microbiota. In conclusion, this study showed that seaweed polysaccharides can restore the negative effects of hexavalent chromium exposure in mice, including gut microbial dysbiosis. Meanwhile, this research also lays the foundation for the application of seaweed polysaccharides
Methods to match high-intensity interval exercise intensity in hypoxia and normoxia – a pilot study
Objectives: The aim of this study was to compare high-intensity interval exercise (HIIE) sessions prescribed on the basis of a maximal value (peak power output, PPO) and a submaximal value (lactate threshold, LT) derived from graded exercise tests (GXTs) in normoxia and hypoxia. Methods: A total of ten males (aged 18–37) volunteered to participate in this study. The experimental protocol consisted of a familiarization procedure, two GXTs under normoxia (FiO2 = 0.209) and two GXTs under normobaric hypoxia (FiO2 = 0.140), and three HIIE sessions performed in a random order. The HIIE sessions included one at hypoxia (HY) and two at normoxia (one matched for the absolute intensity in hypoxia, designated as NA, and one matched for the relative intensity in hypoxia, designated as NR). Results: The data demonstrated that there was significant lower peak oxygen uptake (V̇O2peak), peak heart rate (HRpeak), PPO, and LT derived from GXTs in hypoxia, with higher respiratory exchange ratio (RER), when compared to those from GXTs performed in normoxia (p < 0.001). Among the three HIIE sessions, the NA session resulted in lower percentage of HRpeak (85.0 ± 7.5% vs 94.4 ± 5.0%; p = 0.002) and V̇O2peak (74.1 ± 9.1% vs 88.7 ± 7.7%; p = 0.005), when compared to the NR session. HIIE sessions in HY and NR resulted in similar percentage of HRpeak and V̇O2peak, as well as similar rating of perceived exertion and RER. The blood lactate level increased immediately after all the three HIIE sessions (p < 0.001), while higher blood lactate concentrations were observed immediately after the HY (p = 0.0003) and NR (p = 0.014) sessions when compared with NA. Conclusion: Combining of PPO and LT derived from GXTs can be used to prescribe exercise intensity of HIIE in hypoxia
Novel Design and Lateral Stability Tracking Control of a Four-Wheeled Rollator
Design and control of smart rollators have attracted increasing research interests in the past decades. To meet the requirements of the elderly or disabled users, this paper proposes a novel design and tracking control scheme for empowering and assisting natural human mobility with a four-wheeled rollator. Firstly, by integrating the advantages of Kano Model Analysis and the Theory of Inventive Problem Solving (TRIZ), we introduce a novel Kano-TRIZ industrial design method to design and optimize its mechanical structure. The demand and quality characteristics of the clinical rollator are analyzed according to the Kano model. The Quality Function Deployment (QFD) and TRIZ are adopted to integrate industrial product innovations and optimize the function configuration. Furthermore, a lateral stability controller based on Model Predictive Control (MPC) scheme is introduced to achieve good tracking control performance with the lateral deviation and the heading angle deviation. Finally, the feasibility of the design and control method is verified with a simulation study. The simulation results indicate that the proposed algorithm keeps the lateral position error in a reasonable range. In the co-simulation of ADAMS-MATLAB, the trajectory of the rollator is smooth with constrained position error within 0.1 m, the turning angle and speed can achieve stable tracking control within 5 s and the heading angle is accurate and the speed is stable. A compared experiment with MPC and SMC show that MPC controller has faster response, higher tracking accuracy and smoother trajectory on the novel designed rollator. With the increasing demand for rollators in the global market, the methodology proposed in this paper will attract more research and industry interests
Regional scale mapping of fractional rice cropping change using a phenology-based temporal mixture analysis
Novel Design and Adaptive Fuzzy Control of a Lower-Limb Elderly Rehabilitation
Design and control of a lower-limb exoskeleton rehabilitation of the elderly are the main challenge for health care in the past decades. In order to satisfy the requirements of the elderly or disabled users, this paper presents a novel design and adaptive fuzzy control of lower-limb empowered rehabilitation, namely MOVING UP. Different from other rehabilitation devices, this article considers active rehabilitation training devices. Firstly, a novel product design method based on user experience is proposed for the lower-limb elderly exoskeleton rehabilitation. At the same time, in order to achieve a stable operation control for the assistant rehabilitation system, an adaptive fuzzy control scheme is discussed. Finally, the feasibility of the design and control method is validated with a detailed simulation study and the human-interaction test. With the booming demand in the global market for the assistive lower-limb exoskeleton, the methodology developed in this paper will bring more research and manufacturing interests
Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator
In the past few decades, the research of assistant mobile rollators for the elderly has attracted more and more investigation attention. In order to satisfy the needs of older people or disabled patients, this paper develops a neural approximation based predictive tracking control scheme to improve and support the handicapped through the novel four-wheeled rollator. Firstly, considering the industrial product theory, a novel Kano-TRIZ-QFD engineering design approach is presented to optimize the mechanical structure combined with humanistic care. At the same time, in order to achieve a stable trajectory tracking control for the assistant rollator system, a neural approximation enhanced predictive tracking control is discussed. Finally, autonomous tracking mobility of the presented control scheme has received sufficient advantage performance in position and heading angle variations under the external uncertainties. As the market for the medical device of the elderly rollators continues to progress, the method discussed in this article will attract more investigation and industry concerns
Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR
Conventional mobile robots employ LIDAR for indoor global positioning and navigation, thus having strict requirements for the ground environment. Under the complicated ground conditions in the greenhouse, the accumulative error of odometer (ODOM) that arises from wheel slip is easy to occur during the long-time operation of the robot, which decreases the accuracy of robot positioning and mapping. To solve the above problem, an integrated positioning system based on UWB (ultra-wideband)/IMU (inertial measurement unit)/ODOM/LIDAR is proposed. First, UWB/IMU/ODOM is integrated by the Extended Kalman Filter (EKF) algorithm to obtain the estimated positioning information. Second, LIDAR is integrated with the established two-dimensional (2D) map by the Adaptive Monte Carlo Localization (AMCL) algorithm to achieve the global positioning of the robot. As indicated by the experiments, the integrated positioning system based on UWB/IMU/ODOM/LIDAR effectively reduced the positioning accumulative error of the robot in the greenhouse environment. At the three moving speeds, including 0.3 m/s, 0.5 m/s, and 0.7 m/s, the maximum lateral error is lower than 0.1 m, and the maximum lateral root mean square error (RMSE) reaches 0.04 m. For global positioning, the RMSEs of the x-axis direction, the y-axis direction, and the overall positioning are estimated as 0.092, 0.069, and 0.079 m, respectively, and the average positioning time of the system is obtained as 72.1 ms. This was sufficient for robot operation in greenhouse situations that need precise positioning and navigation