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

Exploring Diverse In-Context Configurations for Image Captioning

After discovering that Language Models (LMs) can be good in-context few-shot learners, numerous strategies have been proposed to optimize in-context sequence configurations. Recently, researchers in Vision-Language (VL) domains also develop their few-shot learners, while they only use the simplest way, ie., randomly sampling, to configure in-context image-text pairs. In order to explore the effects of varying configurations on VL in-context learning, we devised four strategies for image selection and four for caption assignment to configure in-context image-text pairs for image captioning. Here Image Captioning is used as the case study since it can be seen as the visually-conditioned LM. Our comprehensive experiments yield two counter-intuitive but valuable insights, highlighting the distinct characteristics of VL in-context learning due to multi-modal synergy, as compared to the NLP case. Furthermore, in our exploration of optimal combination strategies, we observed an average performance enhancement of 20.9 of CIDEr scores compared to the baseline. The code is given in https://github.com/yongliang-wu/ExploreCfg.Comment: Accepted by NeurIPS202

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 the expression pattern of the BCL11B gene and its relatives in patients with T-cell acute lymphoblastic leukemia

<p>Abstract</p> <p>Background</p> <p>In a human T-cell acute lymphoblastic leukemia (T-ALL) cell line (Molt-4), siRNA-mediated suppression of <it>BCL11B </it>expression was shown to inhibit proliferation and induce apoptosis, functions which may be related to genes involved in apoptosis (such as <it>TNFSF10 </it>and <it>BCL2L1</it>) and TGF-β pathways (such as <it>SPP1</it>and <it>CREBBP</it>).</p> <p>Methods</p> <p>The expression levels of the above mentioned genes and their correlation with the <it>BCL11B </it>gene were analyzed in patients with T-ALL using the TaqMan and SYBR Green I real-time polymerase chain reaction technique.</p> <p>Results</p> <p>Expression levels of <it>BCL11B, BCL2L1</it>, and <it>CREBBP </it>mRNA in T-ALL patients were significantly higher than those from healthy controls (<it>P <</it>0.05). In T-ALL patients, the <it>BCL11B </it>expression level was negatively correlated with the <it>BCL2L1 </it>expression level (<it>r</it>_s= -0.700; <it>P </it><it><</it>0.05), and positively correlated with the <it>SPP1 </it>expression level (<it>r</it>_s= 0.683; <it>P </it><it><</it>0.05). In healthy controls, the <it>BCL11B </it>expression level did not correlate with the <it>TNFSF10</it>, <it>BCL2L1</it>, <it>SPP1</it>, or <it>CREBBP </it>expression levels.</p> <p>Conclusions</p> <p>Over-expression of <it>BCL11B </it>might play a role in anti-apoptosis in T-ALL cells through up-regulation of its downstream genes <it>BCL2L1 </it>and <it>CREBBP</it>.</p

An Improved Method to Knock Out the asd Gene of Salmonella enterica Serovar Pullorum

An asd-deleted (Δasd) mutant of Salmonella enterica serovar Pullorum (SP) was constructed using an improved method of gene knockout by combining the π-suicide plasmid system with the Red Disruption system. The asd gene was efficiently knocked out by the recombinant suicide vector, which replaced the asd gene with the CmR gene. Based on the balanced lethal host-vector system, the phenotype of the Δasd mutant was further defined. The improved method was simpler and more effective than previously reported conventional methods

Online Cooperative Promotion and Cost Sharing Policy under Supply Chain Competition

This paper studies online cooperative promotion and cost sharing decisions in competing supply chains. We consider a model of one B2C e-commerce platform and two supply chains each consisting of a supplier and an online retailer. The problem is studied using a multistage game. Firstly, the e-commerce platform carries out the cooperative promotion and sets the magnitude of markdown (the value of e-coupon). Secondly, each retailer and his supplier determine the fraction of promotional cost sharing when they have different bargaining power. Lastly, the retailers decide whether to participate in the cooperative promotion campaign. We show that the retailers are likely to participate in the promotion if consumers become more price-sensitive. However, it does not imply that the retailers can benefit from the price promotion; the promotion decision game resembles the classical prisoner’s dilemma game. The retailers and suppliers can benefit from the cooperative promotion by designing an appropriate cost sharing contract. For a supply chain, the bargaining power between supplier and retailer, consumer price sensitivity, and competition intensity affect the fraction of the promotional cost sharing. We also find that equilibrium value of e-coupon set by the e-commerce platform is not optimal for all the parties

Expression and distribution of PPP2R5C gene in leukemia

<p>Abstract</p> <p>Background</p> <p>Recently, we clarified at the molecular level novel chromosomal translocation t(14;14)(q11;q32) in a case of Sézary syndrome, which caused a rearrangement from TRAJ7 to the <it>PPP2R5C </it>gene. <it>PPP2R5C </it>is one of the regulatory B subunits of protein phosphatase 2A (PP2A). It plays a crucial role in cell proliferation, differentiation, and transformation. To characterize the expression and distribution of five different transcript variants of the <it>PPP2R5C </it>gene in leukemia, we analyzed the expression level of <it>PPP2R5C </it>in peripheral blood mononuclear cells from 77 patients with <it>de novo </it>leukemia, 26 patients with leukemia in complete remission (CR), and 20 healthy individuals by real-time PCR and identified the different variants of <it>PPP2R5C </it>by RT-PCR.</p> <p>Findings</p> <p>Significantly higher expression of <it>PPP2R5C </it>was found in AML, CML, T-ALL, and B-CLL groups in comparison with healthy controls. High expression of <it>PPP2R5C </it>was detected in the B-ALL group; however, no significant difference was found compared with the healthy group. The expression level of <it>PPP2R5C </it>in the CML-CR group decreased significantly compared with that in the <it>de novo </it>CML group and was not significantly different from the level in the healthy group. By using different primer pairs that covered different exons, five transcript variants of <it>PPP2R5C </it>could be identified. All variants could be detected in healthy samples as well as in all the leukemia samples, and similar frequencies and distributions of <it>PPP2R5C </it>were indicated.</p> <p>Conclusions</p> <p>Overexpression of <it>PPP2R5C </it>in T-cell malignancy as well as in myeloid leukemia cells might relate to its proliferation and differentiation. Investigation of the effect of target inhibition of this gene might be beneficial to further characterization of molecular mechanisms and targeted therapy in leukemia.</p