Unparticle Physics in Single Top Signals

We study the single production of top quarks in $e^+e^-, ep$ and $pp$ collisions in the context of unparticle physics through the Flavor Violating (FV) unparticle vertices and compute the total cross sections for single top production as functions of scale dimension d_{\U}. We find that among all, LHC is the most promising facility to probe the unparticle physics via single top quark production processes.Comment: 14 pages, 10 figure

Hidden Spoor, Ruan Xiaoxu, And His Treatise On Reclusion

In early medieval China great attention was paid to compiling accounts of men in reclusion, yet the prefaces to these compilations often contain only vague or stale reasoning concerning the nature of reclusion itself. A preface by Shen Yue (441-513) is a notable exception: Shen differentiated between disengagement and reclusion. A slightly later contemporary of Shen, Ruan Xiaoxu (479-536), took issue with him in a unique and tightly constructed disquisition on what Ruan saw as a basic dichotomy in the Way of man: the root and overt traces. Ruan\u27s overlooked treatise is examined here, as are some relevant facets of his life

Synthetic-Neuroscore: Using A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. Arguably the most striking results have been in the area of image synthesis. However, evaluating the performance of GANs is still an open and challenging problem. Existing evaluation metrics primarily measure the dissimilarity between real and generated images using automated statistical methods. They often require large sample sizes for evaluation and do not directly reflect human perception of image quality. In this work, we describe an evaluation metric we call Neuroscore, for evaluating the performance of GANs, that more directly reflects psychoperceptual image quality through the utilization of brain signals. Our results show that Neuroscore has superior performance to the current evaluation metrics in that: (1) It is more consistent with human judgment; (2) The evaluation process needs much smaller numbers of samples; and (3) It is able to rank the quality of images on a per GAN basis. A convolutional neural network (CNN) based neuro-AI interface is proposed to predict Neuroscore from GAN-generated images directly without the need for neural responses. Importantly, we show that including neural responses during the training phase of the network can significantly improve the prediction capability of the proposed model. Materials related to this work are provided at https://github.com/villawang/Neuro-AI-Interface

International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome