81 research outputs found

    Decentralized Narrowband and Wideband Spectrum Sensing with Correlated Observations

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    This dissertation evaluates the utility of several approaches to the design of good distributed sensing systems for both narrowband and wideband spectrum sensing problems with correlated sensor observations

    Improved Real-time Post-Processing for quantum Random Number Generators

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    Randomness extraction is a key problem in cryptography and theoretical computer science. With the recent rapid development of quantum cryptography, quantum-proof randomness extraction has also been widely studied, addressing the security issues in the presence of a quantum adversary. In contrast with conventional quantum-proof randomness extractors characterizing the input raw data as min-entropy sources, we find that the input raw data generated by a large class of trusted-device quantum random number generators can be characterized as the so-called reverse block source. This fact enables us to design improved extractors. Specifically, we propose two novel quantum-proof randomness extractors for reverse block sources that realize real-time block-wise extraction. In comparison with the general min-entropy randomness extractors, our designs achieve a significantly higher extraction speed and a longer output data length with the same seed length. In addition, they enjoy the property of online algorithms, which process the raw data on the fly without waiting for the entire input raw data to be available. These features make our design an adequate choice for the real-time post-processing of practical quantum random number generators. Applying our extractors to the raw data of the fastest known quantum random number generator, we achieve a simulated extraction speed as high as 374 Gbps.Comment: 11 pages, 3 figure

    Performance of XOR Rule for Decentralized Detection of Deterministic Signals in Bivariate Gaussian Noise

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    In this paper, we consider the performance of exclusive-OR (XOR) rule in detecting the presence or absence of a deterministic signal in bivariate Gaussian noise. Signals, when present at the two sensors, are assumed unequal, whereas the noise components have identical marginal distribution but are correlated. The sensors send their one-bit quantized data to a fusion center, which then employs the XOR rule to arrive at the final decision. Here we prove that, in the limit as the correlation coefficient r approaches 1, the optimum fusion rule for both parallel and tandem topologies is XOR with identical, alternating partitions (XORAP) of the observations at the sensors. We further quantify the asymptotic decrease of the Bayes error of XORAP towards zero as a constant multiplied by \sqrt 1-r , as r approaches 1. When compared to the asymptotic Bayes error of CLRT, which decreases to zero exponentially fast, as a function of 1/(1-r) , the Bayes error of XORAP decreases to zero much slower

    Dynamic output-feedback passivity control for fuzzy systems under variable sampling

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    This paper concerns the problem of dynamic output-feedback control for a class of nonlinear systems with nonuniform uncertain sampling via Takagi-Sugeno (T-S) fuzzy control approach. The sampling is not required to be periodic, and the state variables are not required to be measurable. A new type fuzzy dynamic output-feedback sampled-data controller is constructed, and a novel time-dependent Lyapunov-Krasovskii functional is chosen for fuzzy systems under variable sampling. By using Lyapunov stability theory, a sufficient condition for very-strict passive analysis of fuzzy systems with nonuniformuncertain sampling is derived. Based on this condition, a novel fuzzy dynamic output-feedback controller is designed such that the closed-loop system is very-strictly passive. The existence condition of the controller can be solved by convex optimization approach. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method

    Certifying randomness in quantum state collapse

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    The unpredictable process of state collapse caused by quantum measurements makes the generation of quantum randomness possible. In this paper, we explore the quantitive connection between the randomness generation and the state collapse and provide a randomness verification protocol under the assumptions: (I) independence between the source and the measurement devices and (II) the L\"{u}ders' rule for collapsing state. Without involving heavy mathematical machinery, the amount of genereted quantum randomness can be directly estimated with the disturbance effect originating from the state collapse. In the protocol, we can employ general measurements that are not fully trusted. Equipped with trusted projection measurements, we can further optimize the randomness generation performance. Our protocol also shows a high efficiency and yields a higher randomness generation rate than the one based on uncertainty relation. We expect our results to provide new insights for understanding and generating quantum randomnes

    Transient magneto-optical spectrum of photoexcited electrons in the van der Waals ferromagnet Cr2Ge2Te6

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    Femtosecond optical control of magnetic materials shows promise for future ultrafast data storage devices. To date, most studies in this area have relied on quasimonochromatic light in magneto-optical pump-probe experiments, which limited their ability to probe semiconducting and molecule-based materials with structured optical spectra. Here, we demonstrate the possibility of extracting the magneto-optical spectrum of the electrons in the conduction band in the two-dimensional van der Waals ferromagnet Cr2Ge2Te6 (CGT), which is made possible due to broadband probing in the visible spectrum. The magneto-optical signal is a sum of contributions from electrons in the conduction and valence bands, which are of opposite sign for CGT. Depending on the probe wavelength used, this difference could lead to an erroneous interpretation that the magnetization direction is reversed after excitation, which has important consequences for understanding spin toggle switching phenomena

    Preparation and Tests of MR Fluids With CI Particles Coated With MWNTs

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    The magnetorheological (MR) fluid is a typical smart material, whose shear yield stress can be adjusted through changing the strength of external magnetic field, and the changing process only takes a few milliseconds. The MR fluid is composed of micro/nanometer ferromagnetic particles, carrier fluids, and some additives. Among them, the performance of ferromagnetic particles will mainly affect the sedimentation stability and the magnetic saturation of the MR fluid. Therefore, the ferromagnetic particles are expected to have characteristics of both low density and high magnetism. In this paper, the multi-walled carbon nanotubes (MWNTs) were adopted to coat on the carbonyl iron (CI) particles with grafting technology using ultrasonication and mechanical stirring. The coated CI particles with perfect core-shell structure were developed and the influence of the dosages of grafting agent and MWNTs were tested. And then, MR fluids with CI particles coated with MWNTs were established and the coating effect was studied through surface topography particle density, and magnetic properties of composite magnetic particles and stability tests of the prepared MR fluids. The results showed that although the magnetic saturation of the prepared MR fluids with CI particles coated with MWNTs would reduce slightly, the particles density and the adsorption force between the particles were decreased effectively, which are both advantageous to the improvement of the sedimentation stability of MR fluids

    Nitrogen-Doped Hierarchical Porous Activated Carbon Derived from Paddy for High-Performance Supercapacitors

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    A facile and environmentally friendly fabrication is proposed to prepare nitrogen-doped hierarchical porous activated carbon via normal-pressure popping, one-pot activation and nitrogen-doping process. The method adopts paddy as carbon precursor, KHCO3 and dicyandiamide as the safe activating agent and nitrogen dopant. The as-prepared activated carbon presents a large specific surface area of 3025 m2·g−1 resulting from the synergistic effect of KHCO3 and dicyandiamide. As an electrode material, it shows a maximum specific capacitance of 417 F·g−1 at a current density of 1 A·g−1 and very good rate performance. Furthermore, the assembled symmetric supercapacitor presents a large specific capacitance of 314.6 F·g−1 and a high energy density of 15.7 Wh·Kg−1 at 1 A·g−1, maintaining 14.4 Wh·Kg−1 even at 20 A·g−1 with the energy density retention of 91.7%. This research demonstrates that nitrogen-doped hierarchical porous activated carbon derived from paddy has a significant potential for developing a high-performance renewable supercapacitor and provides a new route for economical and large-scale production in supercapacitor application

    The effects of nano-silver loaded zirconium phosphate on antibacterial properties, mechanical properties and biosafety of room temperature curing PMMA materials

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    Polymethyl methacrylate (PMMA) frequently features in dental restorative materials due to its favorable properties. However, its surface exhibits a propensity for bacterial colonization, and the material can fracture under masticatory pressure. This study incorporated commercially available RHA-1F-II nano-silver loaded zirconium phosphate (Ag-ZrP) into room-temperature cured PMMA at varying mass fractions. Various methods were employed to characterize Ag-ZrP. Subsequently, an examination of the effects of Ag-ZrP on the antimicrobial properties, biosafety, and mechanical properties of PMMA materials was conducted. The results indicated that the antibacterial rate against Streptococcus mutans was enhanced at Ag-ZrP additions of 0%wt, 0.5%wt, 1.0%wt, 1.5%wt, 2.0%wt, 2.5%wt, and 3.0%wt, achieving respective rates of 53.53%, 67.08%, 83.23%, 93.38%, 95.85%, and 98.00%. Similarly, the antibacterial rate against Escherichia coli registered at 31.62%, 50.14%, 64.00%, 75.09%, 86.30%, 92.98%. When Ag-ZrP was introduced at amounts ranging from 1.0% to 1.5%, PMMA materials exhibited peak mechanical properties. However, mechanical strength diminished beyond additions of 2.5%wt to 3.0%wt, relative to the 0%wt group, while PMMA demonstrated no notable cytotoxicity below a 3.0%wt dosage. Thus, it is inferred that optimal antimicrobial and mechanical properties of PMMA materials are achieved with nano-Ag-ZrP (RHA-1F-II) additions of 1.5%wt to 2.0%wt, without eliciting cytotoxicity

    DFSeer: A visual analytics approach to facilitate model selection for demand forecasting

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    Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model comparison and selection with different levels of details. Besides, it shows the difference in model performance on similar products to reveal the risk of model selection and increase users' confidence in choosing a forecasting model. Two case studies and interviews with domain experts demonstrate the effectiveness and usability of DFSeer.Comment: 10 pages, 5 figures, ACM CHI 202
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