10 Simulations III: goal-oriented error control for a phase-field slit and time control for a screw

2020 ◽  
pp. 215-226
2003 ◽  
Vol 42 (4) ◽  
pp. 1483-1508 ◽  
Author(s):  
Lijuan Wang ◽  
Gengsheng Wang

Author(s):  
G. Mackiewicz Ludtka

Historically, metals exhibit superplasticity only while forming in a two-phase field because a two-phase microstructure helps ensure a fine, stable grain size. In the U-5.8 Nb alloy, superplastici ty exists for up to 2 h in the single phase field (γ1) at 670°C. This is above the equilibrium monotectoid temperature of 647°C. Utilizing dilatometry, the superplastic (SP) U-5.8 Nb alloy requires superheating to 658°C to initiate the α+γ2 → γ1 transformation at a heating rate of 1.5°C/s. Hence, the U-5.8 Nb alloy exhibits an anomolous superplastic behavior.


2016 ◽  
Vol 15 (2) ◽  
pp. 55-65 ◽  
Author(s):  
Lonneke Dubbelt ◽  
Sonja Rispens ◽  
Evangelia Demerouti

Abstract. Women have a minority position within science, technology, engineering, and mathematics and, consequently, are likely to face more adversities at work. This diary study takes a look at a facilitating factor for women’s research performance within academia: daily work engagement. We examined the moderating effect of gender on the relationship between two behaviors (i.e., daily networking and time control) and daily work engagement, as well as its effect on the relationship between daily work engagement and performance measures (i.e., number of publications). Results suggest that daily networking and time control cultivate men’s work engagement, but daily work engagement is beneficial for the number of publications of women. The findings highlight the importance of work engagement in facilitating the performance of women in minority positions.


1995 ◽  
Vol 34 (05) ◽  
pp. 475-488
Author(s):  
B. Seroussi ◽  
J. F. Boisvieux ◽  
V. Morice

Abstract:The monitoring and treatment of patients in a care unit is a complex task in which even the most experienced clinicians can make errors. A hemato-oncology department in which patients undergo chemotherapy asked for a computerized system able to provide intelligent and continuous support in this task. One issue in building such a system is the definition of a control architecture able to manage, in real time, a treatment plan containing prescriptions and protocols in which temporal constraints are expressed in various ways, that is, which supervises the treatment, including controlling the timely execution of prescriptions and suggesting modifications to the plan according to the patient’s evolving condition. The system to solve these issues, called SEPIA, has to manage the dynamic, processes involved in patient care. Its role is to generate, in real time, commands for the patient’s care (execution of tests, administration of drugs) from a plan, and to monitor the patient’s state so that it may propose actions updating the plan. The necessity of an explicit time representation is shown. We propose using a linear time structure towards the past, with precise and absolute dates, open towards the future, and with imprecise and relative dates. Temporal relative scales are introduced to facilitate knowledge representation and access.


2020 ◽  
pp. 1-12
Author(s):  
Changxin Sun ◽  
Di Ma

In the research of intelligent sports vision systems, the stability and accuracy of vision system target recognition, the reasonable effectiveness of task assignment, and the advantages and disadvantages of path planning are the key factors for the vision system to successfully perform tasks. Aiming at the problem of target recognition errors caused by uneven brightness and mutations in sports competition, a dynamic template mechanism is proposed. In the target recognition algorithm, the correlation degree of data feature changes is fully considered, and the time control factor is introduced when using SVM for classification,At the same time, this study uses an unsupervised clustering method to design a classification strategy to achieve rapid target discrimination when the environmental brightness changes, which improves the accuracy of recognition. In addition, the Adaboost algorithm is selected as the machine learning method, and the algorithm is optimized from the aspects of fast feature selection and double threshold decision, which effectively improves the training time of the classifier. Finally, for complex human poses and partially occluded human targets, this paper proposes to express the entire human body through multiple parts. The experimental results show that this method can be used to detect sports players with multiple poses and partial occlusions in complex backgrounds and provides an effective technical means for detecting sports competition action characteristics in complex backgrounds.


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