Northeastern University (China)

About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).

Universal Domain Adaptation in Fault Diagnostics With Hybrid Weighted Deep Adversarial Learning

Abstract: In the past years, the practical cross-domain machinery fault diagnosis problems have been attracting growing attention, where the training and testing data are collected from different operating conditions. The recent advances in closed-set domain adaptation have well addressed the basic problem where the fault mode sets are identical in the source and target domains. While some attempts have also been made on the partial and open-set domain adaptations, no prior information of the target-domain fault modes can be usually available in the real industries, that forms a challenging problem in transfer learning. This article proposes a universal domain adaptation method for fault diagnosis, where no explicit assumption is made on the target label set. A hybrid approach with source class-wise and target instance-wise weighting mechanism is proposed for selective adaptation. By using additional outlier identifier, the proposed method can automatically recognize the unknown fault modes while achieving class-level alignments for the shared health states, without knowing the target label set. Experiments on two rotating machine datasets validate the proposed method, which is promising for practical applications under strong data uncertainties.

Iron and Alzheimer's Disease: From Pathogenesis to Therapeutic Implications.

Abstract: As people age, iron deposits in different areas of the brain may impair normal cognitive function and behavior. Abnormal iron metabolism generates hydroxyl radicals through the Fenton reaction, triggers oxidative stress reactions, damages cell lipids, protein and DNA structure and function, and ultimately leads to cell death. There is an imbalance in iron homeostasis in Alzheimer's disease (AD). Excessive iron contributes to the deposition of β-amyloid and the formation of neurofibrillary tangles, which in turn, promotes the development of AD. Therefore, iron-targeted therapeutic strategies have become a new direction. Iron chelators, such as desferoxamine, deferiprone, deferasirox, and clioquinol, have received a great deal of attention and have obtained good results in scientific experiments and some clinical trials. Given the limitations and side effects of the long-term application of traditional iron chelators, alpha-lipoic acid and lactoferrin, as self-synthesized naturally small molecules, have shown very intriguing biological activities in blocking Aβ-aggregation, tauopathy and neuronal damage. Despite a lack of evidence for any clinical benefits, the conjecture that therapeutic chelation, with a special focus on iron ions, is a valuable approach for treating AD remains widespread.

Observer-Based Fuzzy Adaptive Event-Triggered Control Codesign for a Class of Uncertain Nonlinear Systems

Abstract: This paper is concerned with the simultaneous design of a fuzzy-based output feedback control law and an adaptive event-triggering condition for a class of single-input and single-output uncertain nonlinear systems in the presence of a communication channel between the plant and the controller. To this aim, a Lyapunov-based technique is adopted in an impulsive dynamic system framework to ensure local stability and tracking performance. The proposed Lyapunov formulation yields an event-triggered algorithm to update the control input and fuzzy weights based on conditions involving the closed-loop state, which are aperiodically updated only at the event-sampled instants. Furthermore, a positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. Different from the existing traditional time-triggered control schemes, the developed method samples the state and updates the controller and fuzzy weights only when it is necessary. Clearly, this can largely decrease the communication burden of the communication network. Finally, the effectiveness of the proposed method is illustrated using simulation examples.

A novel image encryption–compression scheme using hyper-chaos and Chinese remainder theorem

Abstract: Hyper-chaos has more than one positive Lyapunov exponents and it has more complex dynamical characteristics than chaos Hence it becomes a better choice for secure image encryption schemes In this paper, we propose a new image encryption scheme integrated with compression simultaneously Specifically, we first use 2D hyper-chaos discrete nonlinear dynamic system to shuffle the plain image, and then we apply Chinese remainder theorem (well known in number theory) to diffuse and compress the shuffled image, simultaneously This new scheme can be used to change the plain image information drastically and compress the plain image with a given compression ratio k , which is most crucial in multimedia transmission Theoretical and experimental analyses both confirm the security and the validity of the proposed algorithm