1,721,619 research outputs found
Immunogenicity of Haemophilus influenzae b conjugate vaccine (HibTITER) and safety of HibTITER and a combination vaccine of diphtheria, tetanus, pertussis and HibTITER in infants two months of age: a preliminary report.
No full textClinical manifestations and molecular epidemiology of necrotizing pneumonia and empyema caused by Streptococcus pneumoniae in children in Taiwan.
No full textEffect of Cr and Si additions on the continuous-cooling-transformation kinetics of gamma-based Ti-45 at.% Al alloy
No full textThe effect of Cr and Si additions on the continuous-cooling-transformation (CCT) kinetics of Ti45Al alloy has been studied at cooling rates from about 0.5 to 500 degreesC s(-1) using our recently constructed in-situ real-time resistivity-temperature measurement apparatus. The alpha --> gamma (L) lamellar reaction occurs at slow cooling rates and only the alpha --> alpha (2) ordering reaction occurs at fast cooling rates; no massive reaction occurs at intermediate cooling rates. The addition of Cr results in a simple decrease in the reaction temperatures for the alpha --> gammaL lamellar reaction without a change in the critical cooling rate for the ordering reaction only, in partial agreement with the depression of the alpha transus temperature. The ordering start temperature was measured to be slightly higher. The addition of Si, on the other hand, significantly accelerates the kinetics of alpha-->gamma (L) lamellar reaction by shifting its CCT curve towards a higher temperature and a shorter time. This is because silicides formed at high temperatures on grain boundaries raise the gamma -phase nucleation temperature and also because Si enhances its growth rate, probably by increasing the chemical diffusivity of alpha phase. The addition of Cr to a Si-containing Ti-45 at.% Al alloy significantly refines its lamellar spacing either by suppressing the Si segregation to grain boundaries or by reducing the alpha-gamma interfacial energy. The antiphase domain size in the alpha (2) phase is distinctively small in the Si-containing alloy probably owing to its interfacial segregation tendency
Multiple neuro-adaptive control of robot manipulators using visual cues
Full text linkA new adaptive controller based on multiple neural networks (NNs) for an uncertain robot manipulator system is developed in this paper. The proposed multiple neuro-adaptive controller (MNAC) switches to a memorized control skill or blends multiple skills by using visual information on the given job to improve the transient response at the time of task variation like a change of manipulating object. MNAC is a type of adaptive feedback controller where system nonlinearity terms are approximated with multiple NNs. The proposed controller is effective for a job where some tasks are repeated but information on the load cannot be scheduled before the operation. During the learning phase, MNAC memorizes a control skill for each load with each NN. For a new task, most similar existing control skills may be used as a starting point of adaptation, which improves the performance of learning. Lyapunov-function-based design of MNAC guarantees the stability of the closed-loop system to be independent of switching or blending law. Simulation results on a two-link manipulator for changing the mass of the given load were illustrated to show the effectiveness of the proposed control scheme by comparison with the conventional neuro-adaptive controller
Adaptive control for uncertain nonlinear systems based on multiple neural networks
Full text linkA new adaptive multiple neural network controller (AMNNC) with a supervisory controller for a class of uncertain nonlinear dynamic systems was developed in this paper. The AMNNC is a kind of adaptive feedback linearizing controller where nonlinearity terms are approximated with multiple neural networks. The weighted sum of the multiple neural networks was used to approximate system nonlinearity for the given task. Each neural network represents the system dynamics for each task. For a job where some tasks are repeated but information on the load is not defined and unknown or varying, the proposed controller is effective because of its capability to memorize control skill for each task with each neural network. For a new task, most similar existing control skills may be used as a starting point of adaptation. With the help of a supervisory controller, the resulting closed-loop system is globally stable in the sense that all signals involved are uniformly bounded. Simulation results on a cartpole system for the changing mass of the pole were illustrated to show the effectiveness of the proposed control scheme for the comparison with the conventional adaptive neural network controller (ANNC)
Experimental Study of the Hybrid Reburn/SNCR Process for NOx and CO Reduction in LPG Flame
No full textInfluence of Interfacial Tensions on Transition of Two-Phase Flow Pattern in Mini-channels
No full textCharacteristics of granular sludge in a single upflow sludge blanket reactor treatm\ing high level of nitrate and simple organic compound
No full textHybrid Effects of Reburning and Selective Non-Catalytic Reaction on Thermal Characteristics and NOx Reduction in Oxygen-Enriched LPG Flame
No full textHealth Workers’ Mindfulness-Based Stress Reduction and Resilience During COVID-19 Pandemic [Corrigendum]
No full textMa HY, Chiang NT, Kao RH, Lee CY. J Multidiscip Healthc. 2024;17:3691–3713.
Page 3701, second paragraph, fourth sentence, the text “The study was approved by the Ethics Committee of National Quemoy University (Approval Number: NQU-CHSS-111-0630)” should read “The study was approved by the Ethics Committee of The College of Humanities and Social Sciences, National Quemoy University (Ethics Approval Number: NQU-CHSS-111-0630)”.
The authors apologize for this error
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