Efficient Privacy Preserving Viola-Jones Type Object Detection via Random Base Image Representation

A cloud server spent a lot of time, energy and money to train a Viola-Jones type object detector with high accuracy. Clients can upload their photos to the cloud server to find objects. However, the client does not want the leakage of the content of his/her photos. In the meanwhile, the cloud server is also reluctant to leak any parameters of the trained object detectors. 10 years ago, Avidan & Butman introduced Blind Vision, which is a method for securely evaluating a Viola-Jones type object detector. Blind Vision uses standard cryptographic tools and is painfully slow to compute, taking a couple of hours to scan a single image. The purpose of this work is to explore an efficient method that can speed up the process. We propose the Random Base Image (RBI) Representation. The original image is divided into random base images. Only the base images are submitted randomly to the cloud server. Thus, the content of the image can not be leaked. In the meanwhile, a random vector and the secure Millionaire protocol are leveraged to protect the parameters of the trained object detector. The RBI makes the integral-image enable again for the great acceleration. The experimental results reveal that our method can retain the detection accuracy of that of the plain vision algorithm and is significantly faster than the traditional blind vision, with only a very low probability of the information leakage theoretically.Comment: 6 pages, 3 figures, To appear in the proceedings of the IEEE International Conference on Multimedia and Expo (ICME), Jul 10, 2017 - Jul 14, 2017, Hong Kong, Hong Kon

Doxycycline inhibits the infiltration of inflammatory cells in rat alkali burn corneas

AIM: To investigate the inhibited effect of Doxycycline on the infiltration of inflammatory cells in rat alkali burn corneas. METHODS: Corneas of 32 SD rats were injured with 1mol/L NaOH, then divided into two groups: control and doxycycline-treated. All agents were administered topically 4 times daily. Slit-lamp microscope was performed and inflammatory index was calculated at 3, 7, 14 and 21 days after injury. Then 4 rats were randomly sacrificed and each cornea was divided into two parts, one for histopathology, the other for ICAM-1 ELISA assay. RESULTS:In control group, the inflammatory index and the number of inflammatory cell was higher than the doxycycline-treated dramatically at all time points(P<0.05). Compared with control group, corneal ICAM-1 expression decreased significantly in doxycycline-treated group at all time points(P < 0.05). CONCLUSION:Doxycycline may inhibit inflammatory cell infiltration by down-regulating ICAM-1 expression

International Trade and Income Distribution in China

In this paper, we comprehensively analyze the topic related economic data to investigate the connection between International Trade and Income Distribution in China and assert that the international trade elevates the national income condition to a higher level ,however, expands the Income inequality among regions and various fields of industries in China. Coordinating the connection between international trade and income distribution is imperative to China’s development. And we assert that maintain technical innovation, cultivate skilled laborer, and promote market competition will be of essential to solve this case. This paper is a revised version based on BEcon degree thesis in June 2014. Key words：International trade; Income distribution; Income inequalit

Predicting Aesthetic Score Distribution through Cumulative Jensen-Shannon Divergence

Aesthetic quality prediction is a challenging task in the computer vision community because of the complex interplay with semantic contents and photographic technologies. Recent studies on the powerful deep learning based aesthetic quality assessment usually use a binary high-low label or a numerical score to represent the aesthetic quality. However the scalar representation cannot describe well the underlying varieties of the human perception of aesthetics. In this work, we propose to predict the aesthetic score distribution (i.e., a score distribution vector of the ordinal basic human ratings) using Deep Convolutional Neural Network (DCNN). Conventional DCNNs which aim to minimize the difference between the predicted scalar numbers or vectors and the ground truth cannot be directly used for the ordinal basic rating distribution. Thus, a novel CNN based on the Cumulative distribution with Jensen-Shannon divergence (CJS-CNN) is presented to predict the aesthetic score distribution of human ratings, with a new reliability-sensitive learning method based on the kurtosis of the score distribution, which eliminates the requirement of the original full data of human ratings (without normalization). Experimental results on large scale aesthetic dataset demonstrate the effectiveness of our introduced CJS-CNN in this task.Comment: AAAI Conference on Artificial Intelligence (AAAI), New Orleans, Louisiana, USA. 2-7 Feb. 201

Analysis of nonlinear suspension power harvest potential

Because the power consumption of a controlled suspension is huge, the power harvest potential of a nonlinear controlled suspension is analyzed. Instead of simplifying the suspension to a linear model or adopting some control strategies to solve the problem, this paper investigates the effect of the nonlinear characteristics on the power harvesting potential. A mathematic model is introduced to calculate the nonlinear vibration, and the amount of harvested power was obtained using the multi-scale method. A numerical validation is carried out at the end of this study. The results show that the investigated mechanical parameters affect both the vibration amplitude and the induced current, while the electric parameters only affect the induced current. The power harvesting potential of the nonlinear suspension is generally greater than the linear suspension because the frequency band of the actual pavement also contains bandwidth surrounding the body resonance point. The only exception occurs if the vehicle travels on a road with a particular profile, e.g. a sine curve. To optimize harvested power, it is better to consider the nonlinear characteristics rather than simplifying the suspension to a linear model