Practical Applications of Intelligent Selection of Smart Beta Mutual Funds

2019 ◽  
Vol 7 (3) ◽  
pp. 1.1-4
Author(s):  
C. Edward Chang ◽  
Thomas M. Krueger ◽  
Cedric Tresor Mbanga
2019 ◽  
Vol 22 (1) ◽  
pp. 10-23
Author(s):  
C. Edward Chang ◽  
Thomas M. Krueger ◽  
Cedric Tresor Mbanga
Keyword(s):  

2018 ◽  
Vol 10 (8) ◽  
pp. 1285 ◽  
Author(s):  
Reza Attarzadeh ◽  
Jalal Amini ◽  
Claudia Notarnicola ◽  
Felix Greifeneder

This paper presents an approach for retrieval of soil moisture content (SMC) by coupling single polarization C-band synthetic aperture radar (SAR) and optical data at the plot scale in vegetated areas. The study was carried out at five different sites with dominant vegetation cover located in Kenya. In the initial stage of the process, different features are extracted from single polarization mode (VV polarization) SAR and optical data. Subsequently, proper selection of the relevant features is conducted on the extracted features. An advanced state-of-the-art machine learning regression approach, the support vector regression (SVR) technique, is used to retrieve soil moisture. This paper takes a new look at soil moisture retrieval in vegetated areas considering the needs of practical applications. In this context, we tried to work at the object level instead of the pixel level. Accordingly, a group of pixels (an image object) represents the reality of the land cover at the plot scale. Three approaches, a pixel-based approach, an object-based approach, and a combination of pixel- and object-based approaches, were used to estimate soil moisture. The results show that the combined approach outperforms the other approaches in terms of estimation accuracy (4.94% and 0.89 compared to 6.41% and 0.62 in terms of root mean square error (RMSE) and R2), flexibility on retrieving the level of soil moisture, and better quality of visual representation of the SMC map.


2021 ◽  
Vol 12 ◽  
Author(s):  
James Crum

Neuroimaging and neuropsychological methods have contributed much toward an understanding of the information processing systems of the human brain in the last few decades, but to what extent do cognitive neuroscientific findings represent and generalize to the inter- and intra-brain dynamics engaged in adapting to naturalistic situations? If it is not marked, and experimental designs lack ecological validity, then this stands to potentially impact the practical applications of a paradigm. In no other domain is this more important to acknowledge than in human clinical neuroimaging research, wherein reduced ecological validity could mean a loss in clinical utility. One way to improve the generalizability and representativeness of findings is to adopt a more “real-world” approach to the development and selection of experimental designs and neuroimaging techniques to investigate the clinically-relevant phenomena of interest. For example, some relatively recent developments to neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) make it possible to create experimental designs using naturalistic tasks that would otherwise not be possible within the confines of a conventional laboratory. Mental health, cognitive interventions, and the present challenges to investigating the brain during treatment are discussed, as well as how the ecological use of fNIRS might be helpful in bridging the explanatory gaps to understanding the cultivation of mental health.


2021 ◽  
Vol 2113 (1) ◽  
pp. 012045
Author(s):  
Chunlei Zhou ◽  
Xiangzhou Chen ◽  
Wenli Liu ◽  
Tianyu Dong ◽  
Huang Yun

Abstract With the increase in the number of traction substations year by year, manual inspections are gradually being replaced by unattended inspections. Target detection algorithms based on deep learning are more widely used in intelligent inspections of power equipment. However, in practical applications, it is found that due to the small target to be detected, the accuracy of the deep learning model will decrease when the shooting angle is inclined and the light conditions are poor. This is because the algorithm’s robustness is low, and the detection ability of the model will be seriously affected when the angle or illumination difference with the sample is large. Based on this, the feature fusion part of the YOLOv3 algorithm and the selection of the loss function and the size of the anchor frame are improved, and the improved ASFF fusion method is used to classify various images in the power equipment. Actual measurement and repeated experiments show that the proposed method can be effectively applied to image recognition of various power equipment, optimize robustness, and greatly improve the image recognition efficiency of power equipment.


BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S350-S350
Author(s):  
Lauren Shipperbottom ◽  
Ruth Scally

AimsTo assess whether patients have a good knowledge of basic nutrition compared to a group of staff. We hypothesise that the patient's knowledge will show deficits compared to the staff despite the group interventions.BackgroundThe Royal College of Psychiatrist's core standards for inpatient physical health outlines that patients should be engaged in healthy lifestyle groups. The women's secure service at Ardenleigh has developed healthy lifestyles groups to promote a better understanding of nutrition.MethodAn adapted University College London general knowledge nutrition questionnaire was used to investigate nutritional knowledge.All 22 inpatients and a random selection of staff were offered the chance to complete the questionnaire. As the groups run on a regular basis, it was presumed all patients had attended at least one group session. The staff are the comparator group.18 staff responses and 12 inpatient responses were obtained (54.5% response rate for inpatients).ResultNo participant in either group scored 100%. Both groups had a good awareness of what foods they should be eating more and less of. 83.3% of patients were aware that they should be eating breakfast everyday as opposed to 100% of staff.Poor areas of knowledge included knowledge of the number of oily fish servings per week. Staff and patients also performed poorly when estimating their recommended daily salt intake. 1/3 of patients were unable to provide an example of a serving of fruit and vegetables.The knowledge of the structure of the Eat-Well plate was poor in both groups. Only 16% of patients and 22% of staff were aware that starchy foods should make up 1/3 of the Eat-well plate. Knowledge of protein sources was poor. 25% of patients and 16.6% of staff thought that fruit and butter were good sources of proteinFurthermore, only 50% of patients were able to choose the healthiest evening meal choice from a list of 3 options compared to 100% of staff.ConclusionIn conclusion staff had better knowledge of nutrition than patients but knowledge was poor in areas amongst both groups. We conclude that groups should have more focus around practical applications of nutritional knowledge to everyday life.


2020 ◽  
Vol 8 (2) ◽  
pp. 1.9-7
Author(s):  
James White ◽  
Victor Haghani

1996 ◽  
Vol 2 (2) ◽  
pp. 132-136
Author(s):  
Hubert Roosma
Keyword(s):  

2017 ◽  
Vol 21 ◽  
pp. 3-14
Author(s):  
Juan Carlos Tiznado ◽  
Maria Paz Silva ◽  
Natalia Viejo

Current practice for seismic design of earth structures considers the use of displacement-based methods, which allow a quick and quantitative estimation of the movement of soil masses under earthquake loading. This type of procedures are aimed to establish a relationship between (i) the main earthquake parameters, (ii) the critical acceleration, and (iii) the corresponding permanent displacements of the soil structure. In this sense, based on the well-known Newmark’s sliding block method, several regression models intended for design purposes have been proposed during last decades. However, the selection of an appropriate method to predict the expected permanent displacements of a soil mass remains a difficult and somewhat arbitrary practice. In this paper, strong-motion records from four major Chilean earthquakes, grouped by soil conditions, are used to compare and evaluate the suitability of the reviewed methods for assessing the seismic performance of earth structures. From the results obtained, general conclusions and recommendations for practical applications on sites with similar characteristics to the Chilean subduction zone are elaborated.


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