Contextualism

2020 ◽  
pp. 108-127
Author(s):  
Alastair Norcross

Although consequentialism is not fundamentally concerned with such staples of moral theory as rightness, duty, obligation, goodness of actions, and harm, such notions may nonetheless be of practical significance. A contextualist approach to all these notions makes room for them in ordinary moral discourse, but also illustrates why there is no room for them at the level of fundamental moral theory. Roughly, to say that an act is right is to say that it is at least as good as the appropriate alternative, to say an act is good is to say that it is better than the appropriate alternative, to say an act harms someone is to say that it makes them worse off than they would have been on the appropriate alternative. In each case, “appropriate” is an indexical, whose referent is fixed by the context of utterance. This approach also makes room for an account of supererogation.

2010 ◽  
Vol 108-111 ◽  
pp. 1070-1074
Author(s):  
Li Ying Wang ◽  
Wei Guo Zhao ◽  
Jian Min Hou

The cascade correlation algorithm that is CC algorithms, CC network structure and CC network weights learning algorithm are introduced, based on the operation data of Wanjiazhai hydropower station, considering the pressure fluctuation, the network model of vibration characteristics is established based on CC algorithm, and the applications of CC and BP algorithm in vibration characteristics of turbine are compared. The results show that the CC algorithm is better than BP neural network, the results can be used in the optimal operation of hydropower, and it has a practical significance.


2021 ◽  
Vol 16 ◽  
Author(s):  
Haohao Zhou ◽  
Hao Wang ◽  
Yijie Ding ◽  
Jijun Tang

Background: Antifungal peptides (AFP) have been found to be effective against many fungal infections. Objective: However, it is difficult to identify AFP. Therefore, it is great practical significance to identify AFP via machine learning methods (with sequence information). Method: In this study, a Multi-Kernel Support Vector Machine (MKSVM) with Hilbert-Schmidt Independence Criterion (HSIC) is proposed. Proteins are encoded with five types of features (188-bit, AAC, ASDC, CKSAAP, DPC), and then construct kernels using Gaussian kernel function. HSIC are used to combine kernels and multi-kernel SVM model is built. Results: Our model performed well on three AFPs datasets and the performance is better than or comparable to other state-of-art predictive models. Conclusion: Our method will be a useful tool for identifying antifungal peptides.


Author(s):  
Lee Spector ◽  
Jon Klein

AbstractWe demonstrate the use of genetic programming in the automatic invention of quantum computing circuits that solve problems of potential theoretical and practical significance. We outline a developmental genetic programming scheme for such applications; in this scheme the evolved programs, when executed, build quantum circuits and the resulting quantum circuits are then tested for “fitness” using a quantum computer simulator. Using the PushGP genetic programming system and the QGAME quantum computer simulator we demonstrate the invention of a new, better than classical quantum circuit for the two-oracle AND/OR problem.


2003 ◽  
Vol 12 (4) ◽  
pp. 447-454
Author(s):  
TUIJA TAKALA

I think that utilitarianism is a good moral theory, and definitely better than its rivals, deontology and teleology. For practical purposes in multicultural contexts, at least, I think that no one should overlook a theory that is able to take into account a variety of ethical views and accommodate the ever-changing facts of the material world. But utilitarianism has a bad reputation in bioethics. It is often seen as the inhumane theory that allows the sacrifice of minorities, the killing of the innocent, and simplistic calculations on the value of life. Hardly anyone cares to remember that most formulations of the theory do not allow these actions. The economic doctrine sometimes labeled as utilitarianism could be guilty as charged, but ethics and economy are not interchangeable words. Also as a theory that can actually propose answers to no-win situations, utilitarianism has been an easy target for criticism.


2017 ◽  
Vol 1 (1) ◽  
pp. 54-86 ◽  
Author(s):  
DAN M. KAHAN ◽  
ELLEN PETERS ◽  
ERICA CANTRELL DAWSON ◽  
PAUL SLOVIC

AbstractWhy does public conflict over societal risks persist in the face of compelling and widely accessible scientific evidence? We conducted an experiment to probe two alternative answers: the ‘science comprehension thesis’ (SCT), which identifies defects in the public's knowledge and reasoning capacities as the source of such controversies; and the ‘identity-protective cognition thesis’ (ICT), which treats cultural conflict asdisablingthe faculties that members of the public use to make sense of decision-relevant science. In our experiment, we presented subjects with a difficult problem that turned on their ability to draw valid causal inferences from empirical data. As expected, subjects highest in numeracy – a measure of the ability and disposition to make use of quantitative information – did substantially better than less numerate ones when the data were presented as results from a study of a new skin rash treatment. Also as expected, subjects’ responses became politically polarized – and even less accurate – when the same data were presented as results from the study of a gun control ban. But contrary to the prediction of SCT, such polarization did not abate among subjects highest in numeracy; instead, itincreased. This outcome supported ICT, which predicted that more numerate subjects would use their quantitative-reasoning capacity selectively to conform their interpretation of the data to the result most consistent with their political outlooks. We discuss the theoretical and practical significance of these findings.


2019 ◽  
Vol 6 (11) ◽  
pp. 256-260
Author(s):  
Li Diao ◽  
Ning Wang

As one of the four financial pillars, insurance has the functions of risk diversification, loss compensation, financing and social management. It is of great practical significance to predict the level of premium income in the new normal of economy. In this paper, long short-term memory (LSTM) neural network was innovatively applied to the study of premium income prediction. The monthly data of China's premium income from January 1999 to October 2019 was selected for prediction, and the prediction results were compared with BP neural network. The results show that LSTM model can accurately predict premium income, and its performance is better than BP neural network.


2014 ◽  
Vol 526 ◽  
pp. 362-366 ◽  
Author(s):  
Jian Xiao Cao ◽  
Ye Cao ◽  
Jian Hua Fu ◽  
Jing Pei

On the basis of two test results of safety belt from national spot check. This paper analyzes safety belt products in domestic market and data bases from each testing center. Searching and studying the existing problem with safety belt products. The results showed the quality of safety belt in market is good expecting two batches. And the test data is better than the standard value. This research has important practical significance on analysis of safety belt quality.


2013 ◽  
Vol 821-822 ◽  
pp. 1381-1385
Author(s):  
Tian Zhai ◽  
Hui Di Hao ◽  
Jian Yong Lei

The research of the flow simulation in the inner stirring tank with the single pipe and dual pipe was studied by CFD, which has demonstrated the fluid simulation effect of the single pipe and dual pipe. It has found that the effect is better in the single pipe stirring tank than the dual pipe one. Basing on this result, the flow simulation effect of dual pipe is better than the single one, and the result has a certain practical significance effect on industry.


2021 ◽  
Author(s):  
RG Negri ◽  
Alejandro Frery

© 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd. part of Springer Nature. The Earth’s environment is continually changing due to both human and natural factors. Timely identification of the location and kind of change is of paramount importance in several areas of application. Because of that, remote sensing change detection is a topic of great interest. The development of precise change detection methods is a constant challenge. This study introduces a novel unsupervised change detection method based on data clustering and optimization. The proposal is less dependent on radiometric normalization than classical approaches. We carried experiments with remote sensing images and simulated datasets to compare the proposed method with other unsupervised well-known techniques. At its best, the proposal improves by 50% the accuracy concerning the second best technique. Such improvement is most noticeable with uncalibrated data. Experiments with simulated data reveal that the proposal is better than all other compared methods at any practical significance level. The results show the potential of the proposed method.


2021 ◽  
Author(s):  
RG Negri ◽  
Alejandro Frery

© 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd. part of Springer Nature. The Earth’s environment is continually changing due to both human and natural factors. Timely identification of the location and kind of change is of paramount importance in several areas of application. Because of that, remote sensing change detection is a topic of great interest. The development of precise change detection methods is a constant challenge. This study introduces a novel unsupervised change detection method based on data clustering and optimization. The proposal is less dependent on radiometric normalization than classical approaches. We carried experiments with remote sensing images and simulated datasets to compare the proposed method with other unsupervised well-known techniques. At its best, the proposal improves by 50% the accuracy concerning the second best technique. Such improvement is most noticeable with uncalibrated data. Experiments with simulated data reveal that the proposal is better than all other compared methods at any practical significance level. The results show the potential of the proposed method.


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