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Author(s):  
Qianlong Dang ◽  
Weifeng Gao ◽  
Maoguo Gong

AbstractMultiobjective multitasking optimization (MTO) is an emerging research topic in the field of evolutionary computation, which has attracted extensive attention, and many evolutionary multitasking (EMT) algorithms have been proposed. One of the core issues, designing an efficient transfer strategy, has been scarcely explored. Keeping this in mind, this paper is the first attempt to design an efficient transfer strategy based on multidirectional prediction method. Specifically, the population is divided into multiple classes by the binary clustering method, and the representative point of each class is calculated. Then, an effective prediction direction method is developed to generate multiple prediction directions by representative points. Afterward, a mutation strength adaptation method is proposed according to the improvement degree of each class. Finally, the predictive transferred solutions are generated as transfer knowledge by the prediction directions and mutation strengths. By the above process, a multiobjective EMT algorithm based on multidirectional prediction method is presented. Experiments on two MTO test suits indicate that the proposed algorithm is effective and competitive to other state-of-the-art EMT algorithms.


Author(s):  
Gerardo Javier Marin-Tellez ◽  
Víctor López-Garza ◽  
Paulina Marin-Tellez ◽  
Adrián Santibañez-Maldonado

This work shows the computational simulation of the fluid dynamics of inductor discs (patent pending reception number MX/E/2021/002395) applied to vertical axis wind turbines (VAWT). These inductor discs have a unique and innovative design that can be classified as wind concentrators. The purpose of these devices is to increase wind velocity at the wind turbine entrance; this increase in velocity exponentially boosts the mechanical power of the turbine, according to Betz's theory, increasing the electrical energy production of the turbine and, at the same time, reducing its dimensions. The objective of this investigation is to carry out the fluid dynamic simulation (CFD) of two of the inductor disc geometries: an elliptical one and a truncated conical one, varying the entrance wind velocities of the VAWT from 3 m/s to 12 m/s. The proposed methodology consists of employing a CFD software (ANSYS) to model the two inductor disc geometries and extract them from a static control volume. Mesh this volume, establish boundary conditions, and vary wind velocities to carry out the fluid dynamic analysis. Finally, the obtained velocities are compared at different representative points of both geometries.


Author(s):  
Olena Musiyenko ◽  
Roman Chopyk ◽  
Nataliya Kizlo

By measuring the electrical conductivity of different meridians of the human body data can be obtained to demonstrate the meridian energies. Such non-invasive methods are used to stimulate acupuncture points on the meridians. There is a need to confirm the effectiveness of mechanisms of acupuncture for the human body using scientific methods. Measuring the electrical conductivity of different meridians provides indicators for interpretation. The aim of our study is to establish the possibility of using the method of studying the effect of exercise on the body by means of acupuncture diagnostics according to J.Nakatani’s method on the example of static exercise, which is performed similarly to Dhanurasana (outside the bow in Hatha Yoga). Ten female students were examined. Measurements were taken before the exercise, during and after the exercise after 6 minutes. The results of the research showed significant changes in the indicators of electrical activity in the representative points of the meridians of the body. An increase in electrical activity in the meridians of the human body, which are responsible for the functions of the respiratory, cardiovascular systems, kidneys and adrenal glands, gallbladder, small and large intestines, spleen, pancreas, liver and bladder, and its decrease in the meridian of the stomach. The method of acupuncture diagnostics chosen allows determining the electrical activity of the meridians of the human body during static exercise. It is possible to offer use of this technique of research of influence of physical exercises on a human body along with other generally accepted scientific methods.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yang Yan ◽  
Xiaohong Yu

With the increasing load and speed of trains, the problems caused by various random excitations (such as safety and passenger comfort) have become more prominent and thus arises the necessity to analyze stochastic dynamical systems, which is important in both academic and engineering circles. The existing analysis methods are inadequate in terms of computational accuracy, computational efficiency, and applicability in solving complex problems. For that, a new efficient and accurate method is used in this paper, suitable for linear and nonlinear random vibration analysis of large structures as well as static and dynamic reliability assessment. It is the direct probability integration method, which is extended and applied to the random vibration reliability analysis of dynamical systems. Dynamical models of the dynamic system and coupled system “three-car vehicle-rail-bridge” are established, the time-varying differential equations of motion are derived in detail, and the dynamic response of the system is calculated using the explicit Newmark algorithm. The simulation results show the influence of the number of representative points on the smoothness of the image of the probability density function and the accuracy of the calculation results.


Information ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 392
Author(s):  
Sinead A. Williamson ◽  
Jette Henderson

Understanding how two datasets differ can help us determine whether one dataset under-represents certain sub-populations, and provides insights into how well models will generalize across datasets. Representative points selected by a maximum mean discrepancy (MMD) coreset can provide interpretable summaries of a single dataset, but are not easily compared across datasets. In this paper, we introduce dependent MMD coresets, a data summarization method for collections of datasets that facilitates comparison of distributions. We show that dependent MMD coresets are useful for understanding multiple related datasets and understanding model generalization between such datasets.


2021 ◽  
Author(s):  
Tadashi Sugimura ◽  
Shunsaku Matsumoto ◽  
Soichiro Inoue ◽  
Shin Terada ◽  
Satoshi Miyazaki

Abstract The industries using floating facilities such as FPSO and offshore wind turbine are increasing. Since these vessels have been fixed and operated in the installed area for a long period of time, they cannot be regularly docked, inspected and repaired as opposed to normal ship case, and limited to the inspection of the hull outer plates from under the water and the inspection of inside the tanks are conducted once every five years. These inspections involving visual inspections and thickness measurements at representative points, only examine the current state, and don’t evaluate quantitatively the future potential (remaining life) over the subsequent long operation period. To predict residual life in order to maintain the integrity of these structures, digital twin technology is proposed to realize this demand. This paper shows the method to develop digital twin assessment which solve the insufficiency of conventional monitoring and simulation method in order to utilize for risk-based inspection (RBI) and condition-based maintenance (CBM) to the operators.


2021 ◽  
Vol 81 (7) ◽  
Author(s):  
Indrani Chakraborty ◽  
Dilip Kumar Ghosh ◽  
Nivedita Ghosh ◽  
Santosh Kumar Rai

AbstractWe study the $$S_3$$ S 3 -symmetric two Higgs doublet model by adding two generations of vector like leptons (VLL) which are odd under a discrete $$Z_2$$ Z 2 -symmetry. The lightest neutral component of the VLL acts as a dark matter (DM) whereas the full VLL set belongs to a dark sector with no mixings allowed with the standard model fermions. We analyse the model in light of dark matter and collider searches. We show that the DM is compatible with the current relic density data as well as satisfying all direct and indirect dark matter search constraints. We choose some representative points in the model parameter space allowed by all aforementioned dark matter constraints and present a detailed collider analysis of multi-lepton signals viz. the mono-lepton, di-lepton, tri-lepton and four-lepton along with missing transverse energy in the final state using both the cut-based analysis and multivariate analysis respectively at the high luminosity 14 TeV LHC run.


Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Benito Zamorano González ◽  
Fabiola Peña Cárdenas ◽  
Cristián Pinto-Cortez ◽  
Yolanda Velázquez Narváez ◽  
José Ignacio Vargas Martínez ◽  
...  

BACKGROUND: The constant changes in the global economy generate instability in the markets, favoring the closing of companies, dismissals of personnel, job losses. Unemployment has been associated with adverse psychological effects, serving as a predictor of poor mental health. OBJECTIVE: The main goal was to analyze the relation between work status and mental health. METHODS: A cross-sectional, quantitative study was carried out with a sample of community population, inhabitants of the urban area of a Mexican city. The sample consisted of 1351 participants, being 577 men (43%) and 774 women (57%) with an average age of 41.46 (SD = 17.00). The participants were selected by a quota sampling, in 13 representative points of Matamoros’ city urban area. Home surveys were applied; the Spanish version of the Symptom Checklist 90 (SCL-90) was used for mental health assessment. RESULTS: The model explaining the relation between work status and mental health (GFI) was significant (p <  0.01). Unemployment was related to higher scores in all sub-scales of psychopathologies evaluated by the SCL-90, in comparison with the rest of work status categories. CONCLUSIONS: The unemployed, followed by housewives, presented indicators of poorer mental health, while the retired and those in strikes or lockouts showed the best mental health indexes.


2021 ◽  
Vol 11 (13) ◽  
pp. 5876
Author(s):  
Jinchao Wang ◽  
Libo Weng ◽  
Fei Gao

Most object detection methods use rectangular bounding boxes to represent the object, while the representative points network (RepPoints) employs a point set to describe the object. The RepPoints can provide more fine-grained localization and facilitates classification. However, it ignores the difference between localization and classification tasks. Therefore, a lightweight RepPoints with decoupling of the sampling point set (LRP-DS) is proposed in this paper. Firstly, the lightweight MobileNet-V2 and Feature Pyramid Networks (FPN) is employed as the backbone network to realize the lightweight network, rather than the Resnet. Secondly, considering the difference between classification and localization tasks, the sampling points of classification and localization are decoupled, by introducing classification free sampling method. Finally, due to the introduction of the classification free sampling method, the problem of the mismatch between the localization accuracy and the classification confidence is highlighted, so the localization score is employed to describe the localization accuracy independently. The final network structure of this paper achieves 73.3% mean average precision (mAP) on the VOC07 test dataset, which is 1.9% higher than original RepPoints with the same backbone network MobileNetV2 and FPN. Our LRP-DS has a detection speed of 20FPS for the input image of (1000, 600), on RTX2060 GPU, which is nearly twice as fast as the backbone network of ResNet50 and FPN. Experimental results show the effectiveness of our method.


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