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Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 80
Author(s):  
Siva Kumar Pathuri ◽  
N. Anbazhagan ◽  
Gyanendra Prasad Joshi ◽  
Jinsang You

The COVID-19 pandemic has spread to almost all countries of the World and affected people both mentally and economically. The primary motivation of this research is to construct a model that takes reviews or evaluations from several people who are affected with COVID-19. As the number of cases has accelerated day by day, people are becoming panicked and concerned about their health. A good model may be helpful to provide accurate statistics in interpreting the actual records about the pandemic. In the proposed work, for sentimental analysis, a unique classifier named the Sentimental DataBase Miner algorithm (SADBM) is used to categorize the opinions and parallel processing, and is applied on the data collected from various online social media websites like Twitter, Facebook, and Linkedin. The accuracy of the proposed model is validated with trained data and compared with basic classifiers, such as logistic regression and decision tree . The proposed algorithm is executed on CPU as well as GPU and calculated the acceleration ratio of the model. The results show that the proposed model provides the best accuracy compared with the other two models, i.e., 96% (GPU).


2021 ◽  
pp. 104973232110540
Author(s):  
Alicia VandeVusse ◽  
Jennifer Mueller ◽  
Sebastian Karcher

Expectations to share data underlying studies are increasing, but research on how participants, particularly those in qualitative research, respond to requests for data sharing is limited. We studied research participants’ willingness to, understanding of, and motivations for data sharing. As part of a larger qualitative study on abortion reporting, we conducted interviews with 64 cisgender women in two states in early 2020 and asked for consent to share de-identified data. At the end of interviews, we asked participants to reflect on their motivations for agreeing or declining to share their data. The vast majority of respondents consented to data sharing and reported that helping others was a primary motivation for agreeing to share their data. However, a substantial number of participants showed a limited understanding of the concept of “data sharing.” Additional research is needed on how to improve participants’ understanding of data sharing and thus ensure fully informed consent.


2021 ◽  
Vol 18 (6) ◽  
Author(s):  
Catherine Simpson Bueker

Citizenship acquisition is viewed as the key indicator of political incorporation into US society and one motivated by the desire to formally engage in the civic realm, but we know naturalization is undertaken for many reasons. What we know less about is what motivates particular groups. Through surveying 74 lower socio-economic immigrants of color initiating the naturalization process at free citizenship clinics in the Boston, Massachusetts area in the northeastern United States in fall 2019, we examine the stated motivations to naturalize. The survey data reveal that the desire to engage politically is the most commonly cited primary motivation to naturalize (44%), followed by a desire to feel safer in the US (29%). When looking at primary and secondary motivations, 66% cite the ability to vote, and 59% cite the desire to feel safer. The combined motivations of security and political engagement suggest a “threat-opportunity” model of citizenship acquisition, whereby immigrants assess the external socio-political threats and seek to neutralize them through both naturalizing and then engaging politically to change the environment. At the same time, statistically significant relationships between motivations and ethno-racial group and country of origin suggest additional factors must be examined.


Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7218
Author(s):  
Manaram Gnanasekera ◽  
Jay Katupitiya ◽  
Andrey V. Savkin ◽  
A.H.T. Eranga De De Silva

This paper proposes an algorithm that will allow an autonomous aerial drone to approach and follow a steady or moving herd of cattle using only range measurements. The algorithm is also insensitive to the complexity of the herd’s movement and the measurement noise. Once arrived at the herd of cattle, the aerial drone can follow it to a desired destination. The primary motivation for the development of this algorithm is to use simple, inexpensive and robust sensing hence range sensors. The algorithm does not depend on the accuracy of the range measurements, rather the rate of change of range measurements. The proposed method is based on sliding mode control which provides robustness. A mathematical analysis, simulations and experimental results with a real aerial drone are presented to demonstrate the effectiveness of the proposed method.


Author(s):  
MATT DUNCAN

Abstract One increasingly popular view in the philosophy of perception is externalism about sensible qualities, according to which sensible qualities such as colors, smells, tastes, and textures are features, not of our minds, but of mind-independent, external objects in the world. The primary motivation for this view is that perceptual experience seems to be transparent—that is, when we attend to sensible qualities, it seems like what we are attending to are features of external objects, not our own minds. Most (if not all) externalists are either naïve realists or externalist representationalists. However, in this article, I argue that those who are moved by the primary motivation for externalism should instead be sense-datum theorists, for externalists’ primary motivation supports the sense-datum theory, not their actually favored views. I argue that externalists should focus on different motivations, get new ones, or become sense-datum theorists.


2021 ◽  
Vol 325 ◽  
pp. 86-91
Author(s):  
Pavla Bauerová ◽  
Pavel Reiterman ◽  
Magdalena Kracík Štorkánová ◽  
Martin Keppert

Mortars containing linseed oil as admixture to lime were identified in several mosaics found in Czech Republic. These mosaics were made around 1900 and the composition of their bedding mortar was likely influenced by publication La Mosaïque by E. Gerspach [1], published in Paris, 1880. The recipe for lime mortar with linseed oil and stand oil has been reproduced within the present paper. Four mixes were prepared with varying oil/stand oil content (below, above and according to Gerspach’s recommendation). The primary motivation of mosaic artists to use oil admixture was to keep the mortar’s plasticity for longer time, what is beneficial for the mosaic tesseraes (stones) adjustment. This effect was quantified by help of Vicat apparatus. The influence of oils on mechanical properties and carbonation was evaluated at 28 days. It was found by XRD, that the rate of carbonation is reduced due to the oil presence. It is caused by fact that the oil acts also as water-repealing admixture what reduces the ability of aerial CO2 to dissolve in pore solution and react with lime. The deformation behavior of material has been modified by oil toward the higher toughness, but lower compressive strength, due to polymeration of oil in mortar.


2021 ◽  
Vol 11 (19) ◽  
pp. 9055
Author(s):  
Ce Guo ◽  
Pengming Zhu ◽  
Zhiqian Zhou ◽  
Lin Lang ◽  
Zhiwen Zeng ◽  
...  

This paper focuses on generating distributed flocking strategies via imitation learning. The primary motivation is to improve the swarm robustness and achieve better consistency while respecting the communication constraints. This paper first proposes a quantitative metric of swarm robustness based on entropy evaluation. Then, the graph importance consistency is also proposed, which is one of the critical goals of the flocking task. Moreover, the importance-correlated directed graph convolutional networks (IDGCNs) are constructed for multidimensional feature extraction and structure-related aggregation of graph data. Next, by employing IDGCNs-based imitation learning, a distributed and scalable flocking strategy is obtained, and its performance is very close to the centralized strategy template while considering communication constraints. To speed up and simplify the training process, we train the flocking strategy with a small number of agents and set restrictions on communication. Finally, various simulation experiments are executed to verify the advantages of the obtained strategy in terms of realizing the swarm consistency and improving the swarm robustness. The results also show that the performance is well maintained while the scale of agents expands (tested with 20, 30, 40 robots).


2021 ◽  
Vol 1 (10) ◽  
Author(s):  
Patrick Dunlop ◽  
Erica E. F. Ballantyne

AbstractIn an industry that has experienced rapid growth for a number of years, where product differentiation is minimal, the marketing tactics of online sports gambling (OSG) bookmakers are likely to push the boundaries of what can be considered responsible, as companies seek to stand out from competitors and take advantage of industry growth. This research aims to explore how the marketing tactics of OSG companies shape the gambling habits of young adult consumers, and whether this demographic considers these tactics responsible. Recommendations are made on how online bookmakers can remain responsible in their marketing to young adults. Findings revealed that the primary motivation behind young adults’ recreational gambling was the excitement induced through participation. Further, young adults’ OSG bookmaker preference is influenced by promotional offers for existing customers. Results from the study indicate that in general, young adults do not deem the varied marketing techniques employed by OSG companies as irresponsible practices. However there were concerns regarding the potential impact of the continued increase in OSG marketing on problem gamblers and children (under 18).


2021 ◽  
Vol 12 (5) ◽  
pp. 1
Author(s):  
Elnivan Moreira de Souza ◽  
Sergio Henrique Arruda Cavalcante Forte

The micro-foundations research agenda's primary motivation in strategy is to dissect macro-level constructs in terms of actions and organizational members' interactions to the micro-level. This work seeks to evolve the understanding of these micro-foundations to explain the relationship between Managerial Cognitive Capabilities and Dynamic Managerial Capabilities. We conducted a laboratory experiment with a sample of 111 participants, divided into two groups, containing 57 and 54 participants, each one. The results revealed that Sensing Opportunity and Seizing Opportunity, components of the Dynamic Managerial Capability, and the Language and Communication, which are part of the Cognitive Managerial Capability, can be predictive of the ability to Reconfigure Tangible and Intangible Assets. Our research contributes by extending central literature on micro-foundations through an experiment. We empirically show that managerial and cognitive dynamic capabilities can be a preeminent field to improve the comprehension of dynamic capabilities' micro-foundations.


Author(s):  
Suma G

Agribusiness is the core of numerous nations and soil is the primary significant component of horticulture. There are diverse soil sorts and every sort has various highlights for various yields. In this field, presently a day's various techniques and models are utilized to build the amount of the harvests. So the primary motivation behind this of this task is to make a model that assists ranchers with realizing which harvest should take in a specific kind of soil. In this task, we measure the dirt pictures to produce an advanced soil characterization framework for rustic ranchers for minimal price. Tensorflow climate is utilized from this we can download the necessary bundles. We are utilizing two datasets, that is preparing set comprises of four sorts of soil Alluvial, Red, Dark, Earth and train set. Soil surface is the principle factor to be considered prior to doing development. In this methodology, we can gather 50 examples from the various areas of our country. The examples are shot under light condition utilizing an any camera. Soil pictures are handled through the various stages like Convolution layer is to separate highlights from the info picture, Max pool layer is to decrease the spatial component of the information volume for next layers, Drop out layer is arbitrarily sets input units to 0 with a recurrence of rate at each progression during preparing time, which forestalls over fitting, and different layers.


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