天气雷达低噪声放大器的仿真设计

The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper. The two areas are brought together in establishing an interdisciplinary interface that contributes to advancing the field of system autonomy, and pushes the engineering boundaries beyond the existing techniques. The present research adopts the experimental aspects of quantum entanglement and quantum cryptography, and integrates these established quantum capabilities into distributed robotic platforms, to explore the possibility of achieving increased autonomy for the control of multi-agent robotic systems engaged in cooperative tasks. Experimental quantum capabilities are realized by producing single photons (using spontaneous parametric down-conversion process), polarization of photons, detecting vertical and horizontal polarizations, and single photon detecting/counting. Specifically, such quantum aspects are implemented on network of classical agents, i.e., classical aerial and ground robots/unmanned systems. With respect to classical systems for robotic applications, leveraging quantum technology is expected to lead to guaranteed security, very fast control and communication, and unparalleled quantum capabilities such as entanglement and quantum superposition that will enable novel applications.     

Bistable Piezoelectric Flutter Energy Harvesting with Uncertainty

The analytical formulation of piezoelectric flutter energy harvesting using a bistable material, while considering uncertainties in the model is presented in this paper. Bistable laminates provide the advantage of large deflection due to the nonlinear snap-through characteristics when exposed to external loading, and can therefore provide a suitable base for piezoelectric material in energy harvesting applications. A piezoelectric material that is bounded on the surface of bistable laminates, subjected to external loading, generates large strains and hence relatively higher electrical output energy, in comparison with the case where piezoelectric material is bonded on a regular surface, with analogous loading conditions. Although information regarding the external loading, material characteristics of the bistable laminate and the piezoelectric material, boundary conditions, and overall electrical circuit efficiency can be defined for analytical purposes, the exact model of the system is not readily accessible. The unavoidable uncertainties in the material, loading, and efficiency of a complex system call for a probabilistic approach. Hence, this paper provides a formulation that considers uncertainty bounds in obtaining a realistic model. Optimal Uncertainty Quantification (OUQ) is used in this paper, which takes into account uncertainty measures with optimal bounds and incomplete information about the system, as a well-defined optimization problem according to maximum probabilities, subjected to the imposed constraints. The OUQ allows the inspection of the solution for a span of uncertain input parameters, as a reliable and realistic model.     

Antimicrobial properties of treated cotton fabrics with non-toxic biopolymers and their dyeing with safflower and walnut hulls

Novel results were obtained by selection of chitosan treatment parameters on cotton fabrics to obtain antimicrobial properties against E. coli, gram-negative bacteria. Taguchi experimental design was used in this study and microbial reduction rate was considered as the response. The signal-to-noise and the analysis of variance (ANOVA) were used to find the optimum levels to indicate the impact of treatment parameters on antimicrobial properties. The antimicrobial behavior of the fabric against bacterium as a function of each parameter was plotted. A verification test was also performed to prove the validity of Taguchi technique for this study after the determination of parameters’ optimum levels. Also the effect of chitosan and the mordanting on the dyeing properties of cotton fabrics with natural dyes such as walnut hull and safflower was investigated by measuring the color strength (K/S values) of the treated and untreated substrates at various concentrations. The results revealed that the K/S of dyed chitosan-treated cottons increased compared to untreated samples. In addition, antimicrobial properties of natural-dyed treated and untreated fabrics were determined. Walnut hull and safflower have shown antimicrobial properties. Although dyeing the chitosan-treated fabric reduced its antimicrobial effects but the results showed that chitosan-treated cotton fabrics had excellent antimicrobial properties against E. coli. Applying Taguchi experimental design for treating cotton fabrics with chitosan and utilizing these native natural dyes have never been used elsewhere.     

An evolutionary decoding method for HMM-based continuous speech recognition systems using particle swarm optimization

The main recognition procedure in modern HMM-based continuous speech recognition systems is Viterbi algorithm. Viterbi algorithm finds out the best acoustic sequence according to input speech in the search space using dynamic programming. In this paper, dynamic programming is replaced by a search method which is based on particle swarm optimization. The major idea is focused on generating initial population of particles as the speech segmentation vectors. The particles try to achieve the best segmentation by an updating method during iterations. In this paper, a new method of particles representation and recognition process is introduced which is consistent with the nature of continuous speech recognition. The idea was tested on bi-phone recognition and continuous speech recognition workbenches and the results show that the proposed search method reaches the performance of the Viterbi segmentation algorithm ; however, there is a slight degradation in the accuracy rate.     

Improving the Performance of HF Radio Networks in the Presence of Interference through Automatic Link Establishment with Frequency Hopping Technique

In the cement industry, a rotary kiln is a pyro-processing device that is used to measure temperature. Measuring and maintaining a certain range of temperature in the rotary kiln is important to ensure the production of quality clinker granules. The assessment of consuming zone temperature is acquired using radiation pyrometers from the temperature of a hotspot. However, it is a difficult task to measure the burning zone temperature due to the very high temperature developed in the turning furnace sintering process. Existing pyrometer and camera based techniques are not able to provide accurate temperature and temperature variations developed in the burning zone. This research work considers flame image processing using region of interest (ROI), fuzzy logic, and neural networks for efficient temperature measurement. Various temperature measurement and control techniques are utilized in the existing conventional (Prasanna and Bojja in ESCI (helix—the scientific explorer) 4843–4849, 2019) rotary kiln control techniques. In pyrometer-based measurements, the standard of radiation may lead to errors and inaccurate readings. Hence, the consuming zone temperature estimation got from the radiation pyrometer isn't solid and it is hard to get temperature data for a particular location. A colorimetric device-based intelligent control system measures the burning temperature of a specific point, but reading fluctuations are seen because of smoke and dust developed in the combustion process. In ROI based flame image processing, many factors, such as turbulent flame, brightness of flame zone, and dust, affect identifying the boundary for ROI based flame image analysis. In neural network models, variable selection plays a crucial role in designing effective systems with learning capabilities, but it is not an easy task to accomplish without certain rules. Hence, it is highly necessary to develop an improved control system. In view of the issues in variable and feature selection, a few neuro fuzzy systems are adopted in measurement and control. The consuming zone temperature estimation needs a lot of attention due to the very high temperature developed in the rotary kiln sintering process. Existing techniques have to be improved upon using advanced algorithms and intelligent approaches. A sintering state recognition system has been developed with features of flame images and fusion methodologies. In this approach, various flame image features and texture (Ren and Wang in Int J Autom Compu 11(1):72–77, 2014) features are extracted from the burning zone region. Though these methods address a few issues in flame image processing, the acquired image is largely affected by blurring and internal parameters of the sintering process. Charge coupled device (CCD) camera images and videos are applied to many image processing algorithms for better feature extraction and region extraction. The region of interest-based analysis is mainly focused on temperature assessment in this work. Intelligent control techniques are applied to measure the burning zone temperature in a rotary kiln. Fuzzy logic-based inference systems are combined with neural network algorithms in the development of neuro-fuzzy systems. The fuzzy surmising framework in light of mathematical models is the successful manner to anticipate the temperature esteems utilizing power measures. The fire pictures caught by the CCD cameras are handled utilizing fluffy rule-based picture investigation, which estimates temperature from a fire picture by contemplating RGB power planes. The arrangement of result temperature esteems is wanted to be a participation work. The Mamdani fluffy induction model is used to give planning of fluffy fire temperature. Exact temperature planning of fire pictures is performed to control the temperature inside the going stove to make top notch clinker. The fire picture examination is completed in different edges of three unique datasets, and temperature is estimated for various crude supper feed rates and coal feed rates. However there is a slight distinction in the acquired temperature, the general temperature evaluation process doesn't show a huge contrast as per the dataset.

     

Fabrication and micromechanical characterization of polycrystalline diamond microcantilevers

The exceptional chemical, mechanical and thermal properties of diamond make this material the ideal choice for resonant MEMS. Micro-cantilevers designed for biochemical applications have been fabricated using CVD diamond. In this work, the mechanical properties of these cantilevers were investigated by two different techniques: bending test using a Contact Surface Profilometer and resonant test, using a Laser Doppler Vibrometer. The Young’s Modulus of diamond thin film was estimated by these two tests. For the resonance test, the estimated values are comprised between 930 and 1300 GPa while bending test gives values between 950 and 1030 GPa. The load–displacement characteristics and the fracture point (or ultimate stress) have also been investigated.     

Quantum Cooperative Robotics and Autonomy

The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper.The two areas are brought together in establishing an interdisci...     

Near-field and Far-field Optical Properties of Silver Nanospheres: Theoretical and Experimental Investigations of the Size,Shape, Dielectric Environment,and Composition Effects

Protection of Metals and Physical Chemistry of Surfaces - Collective oscillation of electrons in the conduction band of noble metal nanoparticles is known as localized surface plasmon resonance...