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

DoubleAUG: Single-domain Generalized Object Detector in Urban via Color Perturbation and Dual-style Memory

Object detection in urban scenarios is crucial for autonomous driving in intelligent traffic systems. However, unlike conventional object detection tasks, urban-scene images vary greatly in style. For example, images taken on sunny days differ significantly from those taken on rainy days. Therefore, models trained on sunny day images may not generalize well to rainy day images. In this paper, we aim to solve the single-domain generalizable object detection task in urban scenarios, meaning that a model trained on images from one weather condition should be able to perform well on images from any other weather conditions. To address this challenge, we propose a novel Double AUGmentation (DoubleAUG) method that includes image- and feature-level augmentation schemes. In the image-level augmentation, we consider the variation in color information across different weather conditions and propose a Color Perturbation (CP) method that randomly exchanges the RGB channels to generate various images. In the feature-level augmentation, we propose to utilize a Dual-Style Memory (DSM) to explore the diverse style information on the entire dataset, further enhancing the model's generalization capability. Extensive experiments demonstrate that our proposed method outperforms state-of-the-art methods. Furthermore, ablation studies confirm the effectiveness of each module in our proposed method. Moreover, our method is plug-and-play and can be integrated into existing methods to further improve model performance.Comment: Accepted by ACM Transactions on Multimedia Computing, Communications, and Application

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

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

Optomechanically-induced transparency in parity-time-symmetric microresonators

Optomechanically-induced transparency (OMIT) and the associated slowing of light provide the basis for storing photons in nanoscale devices. Here we study OMIT in parity-time (PT)-symmetric microresonators with a tunable gain-to-loss ratio. This system features a sideband-reversed, non-amplifying transparency, i.e., an inverted-OMIT. When the gain-to-loss ratio is varied, the system exhibits a transition from a PT-symmetric phase to a broken-PT-symmetric phase. This PT-phase transition results in the reversal of the pump and gain dependence of the transmission rates. Moreover, we show that by tuning the pump power at a fixed gain-to-loss ratio, or the gain-to-loss ratio at a fixed pump power, one can switch from slow to fast light and vice versa. These findings provide new tools for controlling light propagation using nanofabricated phononic devices

Observation of topological flat bands in the kagome semiconductor Nb3_3Cl8_8

The destructive interference of wavefunctions in a kagome lattice can give rise to topological flat bands (TFBs) with a highly degenerate state of electrons. Recently, TFBs have been observed in several kagome metals, including Fe$_3$Sn$_2$, FeSn, CoSn, and YMn$_6$Sn$_6$. Nonetheless, kagome materials that are both exfoliable and semiconducting are lacking, which seriously hinders their device applications. Herein, we show that Nb$_3$Cl$_8$, which hosts a breathing kagome lattice, is gapped out because of the absence of inversion symmetry, while the TFBs survive because of the protection of the mirror reflection symmetry. By angle-resolved photoemission spectroscopy measurements and first-principles calculations, we directly observe the TFB and a moderate band gap in Nb$_3$Cl$_8$. By mechanical exfoliation, we successfully obtain monolayers of Nb$_3$Cl$_8$ and confirm that they are stable under ambient conditions. In addition, our calculations show that monolayers of Nb$_3$Cl$_8$ have a magnetic ground state, thus providing opportunities to study the interplay between geometry, topology, and magnetism.Comment: 6 pages, 4 figure

Tunable Magnetocaloric Effect in Ni-Mn-Ga Microwires

Abstract Magnetic refrigeration is of great interest due to its high energy efficiency, environmental friendliness and low cost. However, undesired hysteresis losses, concentrated working temperature interval (WTI) and poor mechanical stability are vital drawbacks that hinder its practical application. Off-stoichiometric Ni-Mn-Ga Heusler alloys are capable of giant magnetocaloric effect (MCE) and tunable transformation temperatures. Here, by creating Ni-Mn-Ga microwires with diameter of 35–80 μm using a melt-extraction technique, negligible hysteresis and relatively good mechanical stability are found due to the high specific surface area (SSA) that reduces incompatibility between neighboring grains. The high SSA also favors the element evaporation at high temperatures so that the transformation temperatures can be feasibly adjusted. Tunable magnetocaloric effect owing to different magneto-structural coupling states is realized by (i) composition design and subsequent tuning, which adjusts the temperature difference between the martensite transformation (MT) and the magnetic transition, and (ii) creation of gradient composition distribution state, which manipulates the MT range. Magnetic entropy change ΔS m ~−18.5 J kg−1 K−1 with relatively concentrated WTI and WTI up to ~60 K with net refrigeration capacity ~240 J kg−1 at 50 kOe are demonstrated in the present Ni-Mn-Ga microwires. This criterion is also applicable for other small-sized materials

Distribution, characterization, and induction of CD8+ regulatory T cells and IL-17-producing CD8+ T cells in nasopharyngeal carcinoma

<p>Abstract</p> <p>Background</p> <p>CD8⁺effector cells often have an antitumor function in patients with cancer. However, CD8⁺Foxp3⁺regulatory T cells (Tcregs) and interleukin (IL)-17-producing CD8⁺T cells (Tc17 cells) also derive from the CD8⁺T cell lineage. Their role in the antitumor response remains largely unknown. In the present study, we aimed to investigate the distribution, characterization, and generation of CD8⁺Tcregs and Tc17 cells in NPC patients.</p> <p>Methods</p> <p>Peripheral blood and tumor biopsy tissues from 21 newly diagnosed patients with nasopharyngeal carcinoma (NPC) were collected, along with peripheral blood from 21 healthy donors. The biological characteristics of Tcregs and Tc17 cells from blood and tumor tissues were examined by intracellular staining, tetramer staining and fluorescence-activated cell sorting (FACS) analysis. The suppressive function of Tcregs was investigated using a proliferation assay that involved co-culture of sorted CD8⁺CD25⁺T cells with naïve CD4⁺T cells <it>in vitro</it>.</p> <p>Results</p> <p>We observed an increased prevalence of Tcregs and Tc17 cells among tumor-infiltrating lymphocytes (TILs) and different distribution among peripheral blood mononuclear cells (PBMCs) in NPC patients. Cytokine profiles showed that the Tcregs expressed a high level of IL-10 and low level of transforming growth factor β, whereas Tc17 cells expressed a high level of tumor necrosis factor α. Interestingly, both subsets expressed a high level of interferon γ in TILs, and the Tcregs suppressed naïve CD4⁺T cell proliferation by a cell contact-dependent mechanism <it>in vitro</it>. Moreover, we demonstrated the existence of Epstein-Barr virus latent membrane protein (LMP) 1 and LMP2 antigen-specific Tcregs in NPC.</p> <p>Conclusions</p> <p>Our data provide new insights into the composition and function of CD8⁺T-cell subsets in NPC, which may have an important influence on NPC immunotherapy.</p

Functional proteomic analysis reveals the involvement of KIAA1199 in breast cancer growth, motility and invasiveness.

BACKGROUND: KIAA1199 is a recently identified novel gene that is up-regulated in human cancer with poor survival. Our proteomic study on signaling polarity in chemotactic cells revealed KIAA1199 as a novel protein target that may be involved in cellular chemotaxis and motility. In the present study, we examined the functional significance of KIAA1199 expression in breast cancer growth, motility and invasiveness. METHODS: We validated the previous microarray observation by tissue microarray immunohistochemistry using a TMA slide containing 12 breast tumor tissue cores and 12 corresponding normal tissues. We performed the shRNA-mediated knockdown of KIAA1199 in MDA-MB-231 and HS578T cells to study the role of this protein in cell proliferation, migration and apoptosis in vitro. We studied the effects of KIAA1199 knockdown in vivo in two groups of mice (n = 5). We carried out the SILAC LC-MS/MS based proteomic studies on the involvement of KIAA1199 in breast cancer. RESULTS: KIAA1199 mRNA and protein was significantly overexpressed in breast tumor specimens and cell lines as compared with non-neoplastic breast tissues from large-scale microarray and studies of breast cancer cell lines and tumors. To gain deeper insights into the novel role of KIAA1199 in breast cancer, we modulated KIAA1199 expression using shRNA-mediated knockdown in two breast cancer cell lines (MDA-MB-231 and HS578T), expressing higher levels of KIAA1199. The KIAA1199 knockdown cells showed reduced motility and cell proliferation in vitro. Moreover, when the knockdown cells were injected into the mammary fat pads of female athymic nude mice, there was a significant decrease in tumor incidence and growth. In addition, quantitative proteomic analysis revealed that knockdown of KIAA1199 in breast cancer (MDA-MB-231) cells affected a broad range of cellular functions including apoptosis, metabolism and cell motility. CONCLUSIONS: Our findings indicate that KIAA1199 may play an important role in breast tumor growth and invasiveness, and that it may represent a novel target for biomarker development and a novel therapeutic target for breast cancer