Adversarially Robust Neural Architectures

Deep Neural Network (DNN) are vulnerable to adversarial attack. Existing methods are devoted to developing various robust training strategies or regularizations to update the weights of the neural network. But beyond the weights, the overall structure and information flow in the network are explicitly determined by the neural architecture, which remains unexplored. This paper thus aims to improve the adversarial robustness of the network from the architecture perspective with NAS framework. We explore the relationship among adversarial robustness, Lipschitz constant, and architecture parameters and show that an appropriate constraint on architecture parameters could reduce the Lipschitz constant to further improve the robustness. For NAS framework, all the architecture parameters are equally treated when the discrete architecture is sampled from supernet. However, the importance of architecture parameters could vary from operation to operation or connection to connection, which is not explored and might reduce the confidence of robust architecture sampling. Thus, we propose to sample architecture parameters from trainable multivariate log-normal distributions, with which the Lipschitz constant of entire network can be approximated using a univariate log-normal distribution with mean and variance related to architecture parameters. Compared with adversarially trained neural architectures searched by various NAS algorithms as well as efficient human-designed models, our algorithm empirically achieves the best performance among all the models under various attacks on different datasets.Comment: 9 pages, 3 figures, 5 table

Increasing Capacity of Intersections with Transit Priority

Dedicated bus lane (DBL) and transit signal priority (TSP) are two effective and low cost ways in improving the reliability of transits. On the contrary, these strategies reduce the capacity of general traffic. This paper presents an integrated optimization (IO) model to improve the performance of intersections with dedicated bus lanes. The IO model integrated geometry layout, main-signal timing, pre-signal timing and transit priority. The optimization problem is formulated as a Mix-Integer-Non-Linear-Program (MINLP) that can be transformed into a Mix-Integer-Linear-Program (MILP) and then solved by the standard branch-and-bound technique. The applicability of the IO model is tested through numerical experiment under different intersection layouts and traffic demands. A VISSIM microsimulation model was developed and used to evaluate the performance of the proposed IO model. The test results indicate that the proposed model can increase capacity and reduce delay of general traffic when providing priority to buses

Optimal and near-optimal frequency-hopping sequences based on Gaussian period

Frequency-hopping sequences (FHSs) have a decisive influence on the whole frequency-hopping communication system. The Hamming correlation function plays an important role in evaluating the performance of FHSs. Constructing FHS sets that meet the theoretical bounds is crucial for the research and development of frequency-hopping communication systems. In this paper, three new classes of optimal FHSs based on trace functions are constructed. Two of them are optimal FHSs and the corresponding periodic Hamming autocorrelation value is calculated by using the known Gaussian period. It is shown that the new FHSs are optimal according to the Lempel-Greenberger bound. The third class of FHSs is the near-optimal FHSs

Electrotunable liquid sulfur microdroplets.

Manipulating liquids with tunable shape and optical functionalities in real time is important for electroactive flow devices and optoelectronic devices, but remains a great challenge. Here, we demonstrate electrotunable liquid sulfur microdroplets in an electrochemical cell. We observe electrowetting and merging of sulfur droplets under different potentiostatic conditions, and successfully control these processes via selective design of sulfiphilic/sulfiphobic substrates. Moreover, we employ the electrowetting phenomena to create a microlens based on the liquid sulfur microdroplets and tune its characteristics in real time through changing the shape of the liquid microdroplets in a fast, repeatable, and controlled manner. These studies demonstrate a powerful in situ optical battery platform for unraveling the complex reaction mechanism of sulfur chemistries and for exploring the rich material properties of the liquid sulfur, which shed light on the applications of liquid sulfur droplets in devices such as microlenses, and potentially other electrotunable and optoelectronic devices

Design Human Object Detection Yolov4-Tiny Algorithm on ARM Cortex-A72 and A53

Currently, many object detection systems still use devices with large sizes, such as using PCs, as supporting devices, for object detection. This makes these devices challenging to use as a security system in public facilities based on human object detection. In contrast, many Mini PCs currently use ARM processors with high specifications. In this research, to detect human objects will use the Mini PC Nanopi M4V2 device that has a speed in processing with the support of CPU Dual-Core Cortex-A72 (up to 2.0 GHz) + Cortex A53 (Up to 2.0 GHz) and 4 Gb DDR4 Ram. In addition, for the human object detection system, the author uses the You Only Look Once (YOLO) method with the YoloV4-Tiny type, With these specifications and methods, the detection rate and FPS score are seen which are the feasibility values for use in detecting human objects. The simulation for human object recognition was carried out using recorded video, simulation obtained a detection rate of 0,9845 or 98% with FPS score of 3.81-5.55.  These results are the best when compared with the YOLOV4 and YOLOV5 models. With these results, it can be applied in various human detection applications and of course robustness testing is needed

Improvement of oral availability of ginseng fruit saponins by a proliposome delivery system containing sodium deoxycholate

AbstractGinseng fruit saponins (GFS) extracted from the ginseng fruit are the bioactive triterpenoid saponin components. The aim of the present study was to develop a drug delivery system called proliposome using sodium deoxycholate (NaDC) as a bile salt to improve the oral bioavailability of GFS in rats. The liposomes of GFS were prepared by a conventional ethanol injection and formed the solid proliposomes (P-GFS) using spray drying method on mannitol carriers. The formulation of P-GFS was optimized using the response surface methodology. The physicochemical properties of liposome suspensions including encapsulation efficiency, in vitro drug release studies, particle size of the reconstituted liposome were tested. The solid state characterization studies using the method of Field emission-scanning electron microscope (FE-SEM), Fourier transform infrared (FT-IR) and Differential scanning colorimetric (DSC) were tested to study the molecular state of P-GFS and to indicate the interactions among the formulation ingredients. In vitro studies showed a delayed release of ginsenoside Re (GRe). In vivo studies were carried out in rats. The concentrations of GRe in plasma of rats and its pharmacokinetic behaviors after oral administration of GFS, Zhenyuan tablets (commercial dosage form of GFS) and P-GFS were studied using ultra performance liquid chromatography tandem mass spectrometry. It was founded that the GRe concentration time curves of GFS, Zhenyuan tablets and P-GFS were much more different in rats. Pharmacokinetic behaviors of P-GFS showed a second absorption peak on the concentration time curve. The pharmacokinetic parameters of GFS, Zhenyuan tablets, P-GFS in rats were separately listed as follows: T max 0.25h, C max 474.96±66.06ng/ml and AUC0−∞ 733.32±113.82ng/mlh for GFS; T max 0.31±0.043h, C max 533.94±106.54ng/ml and AUC0−∞ 1151.38±198.29ng/mlh for Zhenyuan tablets; T max 0.5h, C max 680.62±138.051ng/ml and AUC0−∞ 2082.49±408.33ng/mlh for the P-GFS. The bioavailability of P-GFS was nearly 284% and 181% of the GFS and Zhengyuan tablets respectively. In conclusion, the proliposomes significantly enhanced the drug bioavailability, absorption in the gastrointestinal tract and decreased its elimination time of GRe in rats and could be selectively applied for oral delivery of GFS

Keeping distance! How infectious disease threat lowers consumers' attitudes toward densely displayed products

AbstractInfectious diseases have been posing frequent and significant threats to us. However, research on how disease threat affects consumer behavior, especially sensory responses, is still limited. In this study, drawing on the theory of compensatory consumption, we show that consumers under disease threat are less willing to buy products presented in a dense display. This is because disease threat activates a high‐density avoidance mindset, which is carried over to the way in which products are placed. Moreover, this effect is mitigated when diseases are noninfectious or when disinfectant products are displayed. A set of four studies, which adopt lab and field settings, using different manipulations and measures, provide convergent evidence for these effects. Specifically, Study 1 examines the main effect of disease threat on product display. Study 2 tests the mediating role of high‐density avoidance mindset as well as the moderating role of disease infectiousness. Study 3 proceeds to explore product type as the other boundary condition. Finally, Study 4 provides real world evidence through a field experiment. Furthermore, in these studies, five alternative explanations were ruled out to further clarify the psychological process. These findings offer valuable insights for retailers regarding product display strategies.</jats:p