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상급종합병원 간호사의 환자안전문화 인식과 환자안전관리 활동의 관계에서 조직몰입의 효과
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TRANSFORMATION OF NONLINEAR WAVE GROUPS IN DEEP WATER
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K!2uundigungsschutzgesetz : Kommentar
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전세가구에서 생애최초 자가구입으로의 전환기간에 영향을 미치는 요인에 관한 연구
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不動産學報
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Exchange Coupling Approach to the Radical Disposition of an Intermediate in Escherichia coli Ribonucleotide Reductase
- 검색키워드
- 저자 : Zhang Zhiyao (검색결과 4 건)
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Luo, Long,Zhang, Liang,Duan, Zhiyao,Lapp, Aliya S.,Henkelman, Graeme,Crooks, Richard M. American Chemical Society 2016 ACS NANO Vol.10 No.9
<P>In this paper, we show that the onset potential for CO oxidation electrocatalyzed by ∼2 nm dendrimer-encapsulated Pt nanoparticles (Pt DENs) is shifted negative by ∼300 mV in the presence of a small percentage (<2%) of Cu surface atoms. Theory and experiments suggest that the catalytic enhancement arises from a cocatalytic Langmuir–Hinshelwood mechanism in which the small number of Cu atoms selectively adsorb OH, thereby facilitating reaction with CO adsorbed to the dominant Pt surface. Theory suggests that these Cu atoms are present primarily on the (100) facets of the Pt DENs.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancac3/2016/ancac3.2016.10.issue-9/acsnano.6b04448/production/images/medium/nn-2016-04448k_0008.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/nn6b04448'>ACS Electronic Supporting Info</A></P>
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Fixed-time Fuzzy Adaptive Decentralized Control for High-order Nonlinear Large-scale Systems
Bo Kang,Zhiyao Ma,Yongming Li,Wei Zhang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.12
This paper studies a fuzzy adaptive fixed-time tracking control issue for nonlinear high-order largescale systems. Fuzzy logic systems (FLSs) are utilized to identify unknown nonlinearities. Through using adaptive backstepping and adding a power integrator technique, the fixed-time decentralized control method is presented. It is proved that the tracking errors converge to a small neighborhood of a fixed time. A simulation example is presented to confirm the validity of the developed control method.
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LIU QIAN,Zhang Zhiyao,GUO PENG,WANG YIFAN,Liang Junxin 한국CDE학회 2024 Journal of computational design and engineering Vol.11 No.1
Predicting the remaining useful life (RUL) of the aircraft engine based on historical data plays a pivotal role in formulating maintenance strategies and mitigating the risk of critical failures. None the less, attaining precise RUL predictions often encounters challenges due to the scarcity of historical condition monitoring data. This paper introduces a multiscale deep transfer learning framework via integrating domain adaptation principles. The framework encompasses three integral components: a feature extraction module, an encoding module, and an RUL prediction module. During pre-training phase, the framework leverages a multiscale convolutional neural network to extract distinctive features from data across varying scales. The ensuing parameter transfer adopts a domain adaptation strategy centered around maximum mean discrepancy. This method efficiently facilitates the acquisition of domain-invariant features from the source and target domains. The refined domain adaptation Transformer-based multiscale convolutional neural network model exhibits enhanced suitability for predicting RUL in the target domain under the condition of limited samples. Experiments on the C-MAPSS dataset have shown that the proposed method significantly outperforms state-of-the-art methods.
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Chong Chen,Shimin Zhang,Xiaoxiao Zhu,Jingyu Shen,Zhiyao Xu 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.21 No.5
Many patients with stroke are suff ering lower limb locomotor dysfunctions all over the world. Body weight supported treadmilltraining has proven to be an eff ective post-stroke rehabilitation training method for these people’s recovery. Nowadays,lower extremity rehabilitation exoskeleton composed of a pair of mechanical legs has been introduced into body weightsupported treadmill training, which can guide and assist the movements of the patient’s legs. However, active movementsof the patient are hardly to be achieved when the rehabilitation exoskeleton is controlled by a commonly utilized positionbasedpassive strategy. Considering the restriction above, a weight supported rehabilitation training exoskeleton device wasdesigned in this paper to ensure the stroke patient can participate in rehabilitation training voluntarily. To realize this goal,a patient-cooperative rehabilitation training strategy based on adaptive impedance control is adopted for the swing phase inthe training. Human–exoskeleton interaction torques are evaluated by a backpropagation neural network and a disturbanceobserver whose stability is proved by Lyapunov’s law. With no additional demand of interaction torque sensors, the complexityof this system is simplifi ed and the cost is reduced. In order to promote the involvement of patient during the rehabilitationtraining, fuzzy algorithm is used to adjust the impedance parameters according to the human–exoskeleton interaction torques. The eff ectiveness of the whole rehabilitation control strategy is demonstrated by experimental results.
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