University of Windsor

About: University of Windsor is a education organization based out in Windsor, Ontario, Canada. It is known for research contribution in the topics: Population & Argumentation theory. The organization has 10654 authors who have published 22307 publications receiving 435906 citations. The organization is also known as: UWindsor & Assumption University of Windsor.

Stability and change among high-functioning children with pervasive developmental disorders: a 2-year outcome study.

Abstract: This study prospectively compared the 2-year outcome of children diagnosed with autism or Asperger syndrome at age 6–8 years in terms of symptoms from the Autism Diagnostic Interview. Significant differences were seen in the three-domain summary scores of social interaction, communication, and repetitive activities, with the Asperger syndrome group demonstrating fewer and/or less severe symptoms at both times. There was a trend for the trajectories to come together over time on the socialization and communication domains, but not the repetitive activities domain. Differences were not attributable to IQ. Analysis of individual items indicated that the autism group improved over time on seven items and showed increased symptom severity on three items. On the other hand, the Asperger syndrome group improved on only two items and showed increased symptom severity on six items. Results suggest that the two PDD subtypes represent similar developmental trajectories, although the Asperger syndrome group maintains its advantage. Educational and clinical implications of the results are discussed.

Crude oil price shocks, monetary policy, and China's economy

Abstract: This paper develops a time‐varying parameter vector autoregressive model to examine the dynamic effects of crude oil prices and monetary policy on China's economy during January 1996 to June 2017. The empirical results indicate that (a) in general, international crude oil price shocks have positive effect on China's economic growth and inflation in the short run, but the long‐run effect appears diverse; (b) China's monetary policy shocks have positive effect on the economic growth and inflation overall; specifically, an increase in monetary supply can partly offset crude oil prices' negative effect on China's economic growth; (c) China's monetary policy has positive effect on crude oil prices and plays an important role in the relationship between crude oil price shocks and economy; and (d) during the recent global financial crisis, crude oil price shocks produce greater negative effect on China's economic growth, whereas the long‐run effect of monetary policy on China's economic growth proves weaker, compared with other periods.

DeepEDN: A Deep-Learning-Based Image Encryption and Decryption Network for Internet of Medical Things

Abstract: Internet of Medical Things (IoMT) can connect many medical imaging equipment to the medical information network to facilitate the process of diagnosing and treating doctors. As medical image contains sensitive information, it is of importance yet very challenging to safeguard the privacy or security of the patient. In this work, a deep-learning-based image encryption and decryption network (DeepEDN) is proposed to fulfill the process of encrypting and decrypting the medical image. Specifically, in DeepEDN, the cycle-generative adversarial network (Cycle-GAN) is employed as the main learning network to transfer the medical image from its original domain into the target domain. The target domain is regarded as “hidden factors” to guide the learning model for realizing the encryption. The encrypted image is restored to the original (plaintext) image through a reconstruction network to achieve image decryption. In order to facilitate the data mining directly from the privacy-protected environment, a region of interest (ROI)-mining network is proposed to extract the interesting object from the encrypted image. The proposed DeepEDN is evaluated on the chest X-ray data set. Extensive experimental results and security analysis show that the proposed method can achieve a high level of security with a good performance in efficiency.