290 research outputs found

    Pointwise equidistribution for almost smooth functions with an error rate and Weighted L\'evy-Khintchin theorem

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    The purpose of this article is twofold: to prove a pointwise equidistribution theorem with an error rate for almost smooth functions, which strengthens the main result of Kleinbock, Shi and Weiss (2017); and to obtain a L\'evy-Khintchin theorem for weighted best approximations, which extends the main theorem of Cheung and Chevallier (2019). To do so, we employ techniques from homogeneous dynamics and the methods developed in the work of Cheung-Chevallier (2019) and Shapira-Weiss (2022).Comment: 32 page

    TasselNet: Counting maize tassels in the wild via local counts regression network

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    Accurately counting maize tassels is important for monitoring the growth status of maize plants. This tedious task, however, is still mainly done by manual efforts. In the context of modern plant phenotyping, automating this task is required to meet the need of large-scale analysis of genotype and phenotype. In recent years, computer vision technologies have experienced a significant breakthrough due to the emergence of large-scale datasets and increased computational resources. Naturally image-based approaches have also received much attention in plant-related studies. Yet a fact is that most image-based systems for plant phenotyping are deployed under controlled laboratory environment. When transferring the application scenario to unconstrained in-field conditions, intrinsic and extrinsic variations in the wild pose great challenges for accurate counting of maize tassels, which goes beyond the ability of conventional image processing techniques. This calls for further robust computer vision approaches to address in-field variations. This paper studies the in-field counting problem of maize tassels. To our knowledge, this is the first time that a plant-related counting problem is considered using computer vision technologies under unconstrained field-based environment.Comment: 14 page

    Life Cycle Assessment of a Coke Cleaning Agent

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    The life cycle assessment of the coke cleaning agent developed by a university-enterprise cooperation project was conducted. This cleaning agent has the characteristics of phosphorus-free, environmentally friendly, and broad market prospects. The life cycle assessment of the established model showed that the GWP of producing 1kg of coke cleaning agent is 1.19 kg CO2 eq, PED is 13.17 MJ, WU is 186.74 kg, AP is 3.63E-03 kg SO2 eq, ADP is 7.75E-05 kg antimony eq, EP is 1.30E-03 kg PO43-eq, RI is 1.16E-03 kg PM2.5 eq, ODP is 4.63E-06 kg CFC-11 eq, and POFP is 1.85E-03 kg NMVOC eq .The uncertainty of the results is between 4.20% and 24.05%. The carbon footprint (GWP) analysis showed that the production process of isotridecanol polyoxyethylene ether, isopropanol, fatty alcohol polyoxyethylene ether M and isodecanol polyoxyethylene ether contributed significantly. The average sensitivity analysis showed that the most influential processes were sodium lauryl amphoacetate, isopropanol, and tripropylene glycol methyl ether. Citation: Gong, Y., Yang, C., Qu, Y., Li, J., Yang, B., Ding, Y., and Zhang, B. (2022). Life Cycle Assessment of a Coke Cleaning Agent. Trends in Renewable Energy, 8(1), 67-83. DOI: 10.17737/tre.2022.8.1.0014

    Modal-Graph 3D Shape Servoing of Deformable Objects with Raw Point Clouds

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    Deformable object manipulation (DOM) with point clouds has great potential as non-rigid 3D shapes can be measured without detecting and tracking image features. However, robotic shape control of deformable objects with point clouds is challenging due to: the unknown point-wise correspondences and the noisy partial observability of raw point clouds; the modeling difficulties of the relationship between point clouds and robot motions. To tackle these challenges, this paper introduces a novel modal-graph framework for the model-free shape servoing of deformable objects with raw point clouds. Unlike the existing works studying the object's geometry structure, our method builds a low-frequency deformation structure for the DOM system, which is robust to the measurement irregularities. The built modal representation and graph structure enable us to directly extract low-dimensional deformation features from raw point clouds. Such extraction requires no extra point processing of registrations, refinements, and occlusion removal. Moreover, to shape the object using the extracted features, we design an adaptive robust controller which is proved to be input-to-state stable (ISS) without offline learning or identifying both the physical and geometric object models. Extensive simulations and experiments are conducted to validate the effectiveness of our method for linear, planar, tubular, and solid objects under different settings

    On-chip jitter measurement for true random number generators

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    Applications of true random number generators (TRNGs) span from art to numerical computing and system security. In cryptographic applications, TRNGs are used for generating new keys, nonces and masks. For this reason, a TRNG is an essential building block and often a point of failure for embedded security systems. One type of primitives that are widely used as source of randomness are ring oscillators. For a ring-oscillator-based TRNG, the true randomness originates from its timing jitter. Therefore, determining the jitter strength is essential to estimate the quality of a TRNG. In this paper, we propose a method to measure the jitter strength of a ring oscillator implemented on an FPGA. The fast tapped delay chain is utilized to perform the on-chip measurement with a high resolution. The proposed method is implemented on both a Xilinx FPGA and an Intel FPGA. Fast carry logic components on different FPGAs are used to implement the fast delay line. This carry logic component is designed to be fast and has dedicated routing, which enables a precise measurement. The differential structure of the delay chain is used to thwart the influence of undesirable noise from the measurement. The proposed methodology can be applied to other FPGA families and ASIC designs

    Life Cycle Assessment of A Hydrocarbon-based Electrified Cleaning Agent

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    The electrified cleaning agent requires a moderate volatilization rate, low ozone-depleting substances value, non-flammable, non-explosive and other characteristics. This study performed a whole life cycle assessment on a hydrocarbon-based electrified cleaning agent. The life cycle model is cradle-to-grave, and the background data sets include power grid, transportation, high-density polyethylene, chemicals, etc. The analysis shows that the global warming potential (GWP) of the life cycle of 1 kg of electrified cleaning agent is 2.08 kg CO2 eq, acidification potential (AP) is 9.49E-03 kg SO2 eq, eutrophication potential (EP) is 1.18E-03 kg PO43-eq, respirable inorganic matter (RI) is 2.13E- 03 kg PM2.5 eq, ozone depletion potential (ODP) is 4.91E-05 kg CFC-11 eq, photochemical ozone formation potential (POFP) is 2.89E-02 kg NMVOC eq, ionizing radiation-human health potential (IRP) is 3.16E-02 kg U235 eq, ecotoxicity (ET) is 2.69E-01 CTUe, human toxicity-carcinogenic (HT-cancer) is 4.32E-08 CTUh, and human toxicity-non-carcinogenic (HT-non cancer) is 2.31E-07 CTUh. The uncertainty of the results is between 3.46-9.95%.The four processes of tetrachloroethylene production, D40 solvent oil production, tetrachloroethylene environmental discharge during product use, and electricity usage during product disposal have substantial effects on each LCA indicator, so they are the focus of process improvement. Changes in power consumption during production and transportation distance of raw materials have little effect on total carbon emissions. Compared with the production process of single-solvent electrified cleaning agent tetrachloroethylene and n-bromopropane, the production of the electrified cleaning agent developed in this study has its own advantages in terms of carbon footprint and other environmental impact indicators. Carbon emissions mainly come from the power consumption of each process, natural gas production and combustion, and other energy materials for heating. It is recommended to use renewable raw materials instead of crude oil to obtain carbon credits based on geographical advantages, and try to use production processes with lower carbon emissions, while the exhaust gas from the traditional production process is strictly absorbed and purified before being discharged

    SOFIA : software and control flow integrity architecture

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    Microprocessors used in safety-critical systems are extremely sensitive to software vulnerabilities, as their failure can lead to injury, damage to equipment, or environmental catastrophe. This paper proposes a hardware-based security architecture for microprocessors used in safety-critical systems. The proposed architecture provides protection against code injection and code reuse attacks. It has mechanisms to protect software integrity, perform control flow integrity, prevent execution of tampered code, and enforce copyright protection. We are the first to propose a mechanism to enforce control flow integrity at the finest possible granularity. The proposed architectural features were added to the LEON3 open source soft microprocessor, and were evaluated on an FPGA running a software benchmark. The results show that the hardware area is 28.2% larger and the clock is 84.6% slower, while the software benchmark has a cycle overhead of 13.7% and a total execution time overhead of 110% when compared to an unmodified processor

    Model-Free 3D Shape Control of Deformable Objects Using Novel Features Based on Modal Analysis

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    Shape control of deformable objects is a challenging and important robotic problem. This paper proposes a model-free controller using novel 3D global deformation features based on modal analysis. Unlike most existing controllers using geometric features, our controller employs a physically-based deformation feature by decoupling 3D global deformation into low-frequency mode shapes. Although modal analysis is widely adopted in computer vision and simulation, it has not been used in robotic deformation control. We develop a new model-free framework for modal-based deformation control under robot manipulation. Physical interpretation of mode shapes enables us to formulate an analytical deformation Jacobian matrix mapping the robot manipulation onto changes of the modal features. In the Jacobian matrix, unknown geometry and physical properties of the object are treated as low-dimensional modal parameters which can be used to linearly parameterize the closed-loop system. Thus, an adaptive controller with proven stability can be designed to deform the object while online estimating the modal parameters. Simulations and experiments are conducted using linear, planar, and solid objects under different settings. The results not only confirm the superior performance of our controller but also demonstrate its advantages over the baseline method.Comment: Accepted by the IEEE Transactions on Robotics. The paper will appear in the IEEE Transactions on Robotics. IEEE copyrigh
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