Critical evaluation of Śaṅkarapādabhūṣaṇam of Raghunāthasūri, presenting Advaita point of view against the Dvaita school in Hindu philosophy.

Labels provide a quick and effective solution to obtain people interesting content from large-scale social network information. The current interest label extraction method based on the subgraph stream proves the feasibility of the subgraph stream for user label extraction. However, it is extremely time-consuming for constructing subgraphs. As an effective mathematical method to deal with fuzzy and uncertain information, rough set-based representations for subgraph stream construction are capable of capturing the uncertainties of the social network. Therefore, we propose an effective (...) approach called RS_UNITE_SS, which is suitable for large-scale social network user interest label extraction. Specifically, we first propose the subgraph division algorithm to construct a subgraph stream by incorporating a rough set. Then, the algorithm for user real-time interest label extraction based on upper approximation is proposed by using sequentially characteristics of the subgraph. Empirically, we evaluate RS_UNITE_SS over real-world datasets, and experimental results demonstrate that our proposed approach is more computationally efficient than existing methods while achieving higher precision value and MRR value. (shrink)

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume and the complex modeling requirements increase the difficulty of deep learning modeling, and the classical centralized deep learning modeling scheme has encountered bottlenecks in the improvement of model performance (...) and the diversification of smart application scenarios. The parallel processing system in deep learning links the virtual information space with the physical world, although the distributed deep learning research has become a crucial concern with its unique advantages in training efficiency, and improving the availability of trained models and preventing privacy disclosure are still the main challenges faced by related research. To address these above issues in distributed deep learning, this research developed a clonal selective optimization system based on the federated learning framework for the model training process involving large-scale data. This system adopts the heuristic clonal selective strategy in local model optimization and optimizes the effect of federated training. First of all, this process enhances the adaptability and robustness of the federated learning scheme and improves the modeling performance and training efficiency. Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy. (shrink)

Online health communities have enjoyed increasing popularity in recent years, especially in the context of the COVID-19 pandemic. However, several concerns have been raised regarding the privacy of users’ personal information in OHCs. Considering that OHCs are a type of data-sharing or data-driven platform, it is crucial to determine whether users’ health information privacy concerns influence their behaviors in OHCs. Thus, by conducting a survey, this study explores the impact of users’ health information privacy concerns on their engagement and payment (...) behavior in OHCs. The empirical results show that users’ concerns about health information privacy reduce their Paid in OHCs by negatively influencing their OHC engagement. Further analysis reveals that if users have higher benefit appraisals and lower threat appraisals, the negative effect of health information privacy concerns on users’ OHC engagement will decrease. (shrink)

In the framework of transferable utility games, we modify the 2-person Davis–Maschler reduced game to ensure non-emptiness of the imputation set of the adapted 2-person reduced game. Based on the modification, we propose two new axioms: reduced game monotonicity and reduced dominance. Using RGM, RD, NE, Covariance under strategic equivalence, Equal treatment property and Pareto optimality, we are able to characterize the kernel.

This chapter contains section titled: Literary Revolution and its Meaning The Naturalistic Conception of the Universe and the Experimentalist Method History of Chinese Philosophy and Systematizing the National Heritage Political Philosophy and Liberalism Hu Shi as an Enlightenment Philosopher.

We present a stochastic theory for the nonequilibriurn dynamics of charges moving in a quantum scalar field based on the worldline influence functional and the close-time-path (CTP or in-in) coarse-grained effective action method. We summarize (1) the steps leading to a derivation of a modified Abraham-Lorentz-Dirac equation whose solutions describe a causal semiclassical theory free of runaway solutions and without pre-acceleration patholigies, and (2) the transformation to a stochastic effective action, which generates Abraham-Lorentz-Dirac-Langevin equations depicting the fluctuations of a particle’s (...) worldline around its semiclassical trajectory. We point out the misconceptions in trying to directly relate radiation reaction to vacuum fluctuations, and discuss how, in the framework that we have developed, an array of phenomena, from classical radiation and radiation reaction to the Unruh effect, are interrelated to each other as manifestations at the classical, stochastic and quantum levels. Using this method we give a derivation of the Unruh effect for the spacetime worldline coordinates of an accelerating charge. Our stochastic particle-field model, which was inspired by earlier work in cosmological backreaction, can be used as an analog to the black hole backreaction problem describing the stochastic dynamics of a black hole event horizon. (shrink)

本卷收入胡适哲学与文化方面的论文、函牍、讲演、札记80余篇。其中包括实验主义、我们对于西洋近代文明的态度等重要文章。所收文章全面反映了胡适哲学思想、学术主张和对于中西文化的态度,对于了解和研究胡适本人 以及现代中国学术史、现代中国启蒙运动等内容。.

What is the criterion of truth? This is a question that was resolved long ago by the revolutionary teachers of the proletariat. But as a result of damage done by the "Gang of Four" and a mass of distorted propaganda in the media under their control, it has become muddled beyond compare in recent years. In order to deepen the criticism of the "Gang of Four" and eradicate the remnants of their poison and influence, it is very important to clear (...) this up and sort it out. (shrink)

Awareness logic is a type of belief logic in which an agent's beliefs are restricted to those sentences that the agent is aware of. Awareness logic is a successful way to circumvent the problem of omniscience so that actual belief is modelled in a reasonable way. In this paper, we suggest a new method modelling awareness and actual belief by using two-dimensional logics. We show that the two-dimensional logics are flexible tools. Different types of concepts of awareness can be easily (...) modelled by this method. (shrink)

This book discusses qiyun aesthetics in Chinese painting formulated by leading sixth to fourteenth-century intellectual elite. In light of Kant’s account of artistic genius, it considers the role of the mind in creating a painting replete with qiyun, thereby both demystifying qiyun aesthetics and illuminating some limitations in Kant’s aesthetics.

di yi juan. Wen yi mei xue -- di er juan. Zhongguo gu dian wen yi xue -- di san juan. Bi jiao wen yi xue --di si juan. Wen hua mei xue -- di wu juan. Mei de zhui xun.