2,289 research outputs found

    Deformation of Pipelines Induced by the Construction of Underlying Twin-Tunnel

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    The soil displacement load induced by the metro tunneling is applied to the adjacent pipelines, which leads to the deformation of the pipelines, and affects the safe use of the pipeline. According to the displacement of the soil caused by the excavation of the twin-tunnel, considering the shear deformation of the soil and the angle between the tunnel and the pipeline, the analysis method of the Pasternak foundation beam for the longitudinal displacement of the pipeline caused by tunneling was established. The calculation result was relatively close to that of the numerical simulation based on displacement controlled method (DCM) and the field measured data. The influences of the angle, the distance between tunnel axes, the soil volume loss rate and the relative bending stiffness on the pipeline deformation were analyzed. Finally, the influence of the shearing stiffness of the pipeline was researched based on the Timoshenko beam model

    On the spectrum of operators concerned with the reduced singular Cauchy integral

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    We investigate spectrums of the reduced singular Cauchy operator and its real and imaginary components

    Fast Depth and Inter Mode Prediction for Quality Scalable High Efficiency Video Coding

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    International audienceThe scalable high efficiency video coding (SHVC) is an extension of high efficiency video coding (HEVC), which introduces multiple layers and inter-layer prediction, thus significantly increases the coding complexity on top of the already complicated HEVC encoder. In inter prediction for quality SHVC, in order to determine the best possible mode at each depth level, a coding tree unit can be recursively split into four depth levels, including merge mode, inter2Nx2N, inter2NxN, interNx2N, interNxN, in-ter2NxnU, inter2NxnD, internLx2N and internRx2N, intra modes and inter-layer reference (ILR) mode. This can obtain the highest coding efficiency, but also result in very high coding complexity. Therefore, it is crucial to improve coding speed while maintaining coding efficiency. In this research, we have proposed a new depth level and inter mode prediction algorithm for quality SHVC. First, the depth level candidates are predicted based on inter-layer correlation, spatial correlation and its correlation degree. Second, for a given depth candidate, we divide mode prediction into square and non-square mode predictions respectively. Third, in the square mode prediction, ILR and merge modes are predicted according to depth correlation, and early terminated whether residual distribution follows a Gaussian distribution. Moreover, ILR mode, merge mode and inter2Nx2N are early terminated based on significant differences in Rate Distortion (RD) costs. Fourth, if the early termination condition cannot be satisfied, non-square modes are further predicted based on significant differences in expected values of residual coefficients. Finally, inter-layer and spatial correlations are combined with residual distribution to examine whether to early terminate depth selection. Experimental results have demonstrated that, on average, the proposed algorithm can achieve a time saving of 71.14%, with a bit rate increase of 1.27%

    Differentially Private Multi-Agent Planning for Logistic-like Problems

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    Planning is one of the main approaches used to improve agents' working efficiency by making plans beforehand. However, during planning, agents face the risk of having their private information leaked. This paper proposes a novel strong privacy-preserving planning approach for logistic-like problems. This approach outperforms existing approaches by addressing two challenges: 1) simultaneously achieving strong privacy, completeness and efficiency, and 2) addressing communication constraints. These two challenges are prevalent in many real-world applications including logistics in military environments and packet routing in networks. To tackle these two challenges, our approach adopts the differential privacy technique, which can both guarantee strong privacy and control communication overhead. To the best of our knowledge, this paper is the first to apply differential privacy to the field of multi-agent planning as a means of preserving the privacy of agents for logistic-like problems. We theoretically prove the strong privacy and completeness of our approach and empirically demonstrate its efficiency. We also theoretically analyze the communication overhead of our approach and illustrate how differential privacy can be used to control it

    Searching for bidirectional promoters in Arabidopsis thaliana

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    <p>Abstract</p> <p>Background</p> <p>A "bidirectional gene pair" is defined as two adjacent genes which are located on opposite strands of DNA with transcription start sites (TSSs) not more than 1000 base pairs apart and the intergenic region between two TSSs is commonly designated as a putative "bidirectional promoter". Individual examples of bidirectional gene pairs have been reported for years, as well as a few genome-wide analyses have been studied in mammalian and human genomes. However, no genome-wide analysis of bidirectional genes for plants has been done. Furthermore, the exact mechanism of this gene organization is still less understood.</p> <p>Results</p> <p>We conducted comprehensive analysis of bidirectional gene pairs through the whole <it>Arabidopsis thaliana </it>genome and identified 2471 bidirectional gene pairs. The analysis shows that bidirectional genes are often coexpressed and tend to be involved in the same biological function. Furthermore, bidirectional gene pairs associated with similar functions seem to have stronger expression correlation. We pay more attention to the regulatory analysis on the intergenic regions between bidirectional genes. Using a hierarchical stochastic language model (HSL) (which is developed by ourselves), we can identify intergenic regions enriched of regulatory elements which are essential for the initiation of transcription. Finally, we picked 27 functionally associated bidirectional gene pairs with their intergenic regions enriched of regulatory elements and hypothesized them to be regulated by bidirectional promoters, some of which have the same orthologs in ancient organisms. More than half of these bidirectional gene pairs are further supported by sharing similar functional categories as these of handful experimental verified bidirectional genes.</p> <p>Conclusion</p> <p>Bidirectional gene pairs are concluded also prevalent in plant genome. Promoter analyses of the intergenic regions between bidirectional genes could be a new way to study the bidirectional gene structure, which may provide a important clue for further analysis. Such a method could be applied to other genomes.</p

    Translational medical bioengineering research of traumatic brain injury among Chinese and American pedestrians caused by vehicle collision based on human body finite element modeling

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    Based on the average human body size in China and the THUMS AM50 finite element model of the human body, the Kriging interpolation algorithm was used to model the Chinese 50th percentile human body, and the biological fidelity of the model was verified. We built three different types of passenger vehicle models, namely, sedan, sports utility vehicle (SUV), and multi-purpose vehicle (MPV), and used mechanical response analysis and finite element simulation to compare and analyze the dynamic differences and head injury differences between the Chinese 50th percentile human body and the THUMS AM50 model during passenger vehicle collisions. The results showed that there are obvious differences between the Chinese mannequin and THUMS in terms of collision time, collision position, invasion speed, and angle. When a sedan collided with the mannequins, the skull damage to the Chinese human body model was more severe, and when a sedan or SUV collided, the brain damage to the Chinese human body was more severe. The abovementioned results suggest that the existing C-NCAP pedestrian protection testing regulations may not provide the best protection for Chinese human bodies, and that the regulations need to be improved by combining collision damage mechanisms and the physical characteristics of Chinese pedestrians. This thorough investigation is positioned to shed light on the fundamental biomechanics and injury mechanisms at play. Furthermore, the amalgamation of clinically rooted translational and engineering research in the realm of traumatic brain injury has the potential to establish a solid foundation for discerning preventive methodologies. Ultimately, this endeavor holds the potential to introduce effective strategies aimed at preventing and safeguarding against traumatic brain injuries

    DP-Image: Differential Privacy for Image Data in Feature Space

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    The excessive use of images in social networks, government databases, and industrial applications has posed great privacy risks and raised serious concerns from the public. Even though differential privacy (DP) is a widely accepted criterion that can provide a provable privacy guarantee, the application of DP on unstructured data such as images is not trivial due to the lack of a clear qualification on the meaningful difference between any two images. In this paper, for the first time, we introduce a novel notion of image-aware differential privacy, referred to as DP-image, that can protect user's personal information in images, from both human and AI adversaries. The DP-Image definition is formulated as an extended version of traditional differential privacy, considering the distance measurements between feature space vectors of images. Then we propose a mechanism to achieve DP-Image by adding noise to an image feature vector. Finally, we conduct experiments with a case study on face image privacy. Our results show that the proposed DP-Image method provides excellent DP protection on images, with a controllable distortion to faces
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