Development of an adaptive fuzzy logic-based inverse dynamic model for laser cladding process

The precision, performance, and robustness of model-based controllers depend, to a large extent, on the accuracy of the inverse dynamic model which is incorporated in the design of the controller. Due to complex nature of the laser cladding process and presence of time-varying uncertainties, derivation of an accurate mathematical inverse dynamic model of the process is very difficult, and involves many unknown parameters. The inverse dynamic model of the complex nonlinear laser cladding process, which is difficult to be described mathematically, can be described by a fuzzy logic-based inverse dynamic model constructed form input–output data. In this paper, the development of an adaptive fuzzy inverse dynamic model of the laser cladding process, using a systematic fuzzy modelling approach is presented. In a closed-loop laser cladding process, the scanning speed of the substrate is required to produce a clad with desired geometry and quality. In this paper, a fuzzy inverse dynamic model that describes the scanning speed as a function of the cladding parameters in particular the clad height is developed. The developed fuzzy model is validated by comparing the model output with experimental data. The results are very promising and show that fuzzy models can accurately describe the process dynamics.     

Impact of ZnO gate interfacial layer on piezoelectric response of AlGaN/GaN C-HEMT based ring gate capacitor

We report on a piezoelectric response investigation of AlGaN/GaN circular high electron mobility transistor (C-HEMT) based ring gate capacitor as a new stress sensor device to be potentially applied for dynamic high-pressure sensing. A ring gate capacitor of C-HEMT with an additional ZnO gate interfacial layer was used to measure the changes in the piezoelectric charge induced directly by the variation of piezoelectric polarization of both gate piezoelectric layers (AlGaN, ZnO) for harmonic loading at different excitation frequences. Our experimental results show that about 10 nm thick piezoelectric ZnO layer grown on ring gate/AlGaN interface of C-HEMT can yield almost a 60% increase in the piezoelectric detection sensitivity of the device due to its higher piezoelectric coefficient. A three-dimensional CoventorWare simulation is carried out to confirm the increase in the measured piezoelectric response of ZnO based ring gate capacitor of C-HEMT.     

An expert system for automated recognition of patients with obstructive sleep apnea using electrocardiogram recordings

Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder. The traditional diagnosis methods of the disorder are cumbersome and expensive. The ability to automatically identify OSA from electrocardiogram (ECG) recordings is important for clinical diagnosis and treatment. In this study, we proposed an expert system based on discrete wavelet transform (DWT), fast-Fourier transform (FFT) and least squares support vector machine (LS-SVM) for the automatic recognition of patients with OSA from nocturnal ECG recordings. Thirty ECG recordings collected from normal subjects and subjects with sleep apnea, each of approximately 8 h in duration, were used throughout the study. The proposed OSA recognition system comprises three stages. In the first stage, an algorithm based on DWT was used to analyze ECG recordings for the detection of heart rate variability (HRV) and ECG-derived respiration (EDR) changes. In the second stage, an FFT based power spectral density (PSD) method was used for feature extraction from HRV and EDR changes. Then, a hill-climbing feature selection algorithm was used to identify the best features that improve classification performance. In the third stage, the obtained features were used as input patterns of the LS-SVM classifier. Using the cross-validation method, the accuracy of the developed system was found to be 100% for using a subset of selected combination of HRV and EDR features. The results confirmed that the proposed expert system has potential for recognition of patients with suspected OSA by using ECG recordings.     

无线光电定位网络的设计

为满足非接触化、小型化、集成化、数字化、智能化等现代检测技术的发展要求,从成本、工作原理、灵敏度等方面综合考虑,现采用以光电定位模块为核心的光电定位技术,以无线传感器网络作为数据传输与管理的技术手段,构建了无线光电定位网络,并进行了实验分析.可实现多点实时监测、异地显示测量数据、数据网络化管理等特殊需求;涵盖了多学科领...     

Micromachining of passive planar micromixer on poly (methyl methacrylate) substrate with excimer laser ablation

Excimer laser ablation technique was introduced into this work to fabricate a passive planar micromixer on the PMMA substrate. T-junction shaped and width-changed S-shaped microchannels were both designed in this micromixer to enhance mixing effect. The mixing experiment of distilled water and Rhodamine B with injection flow rate of 500 and 1,500 μm/s validates the mixing effectivity of this micromixer, and indicates the feasibility of excimer laser ablation in the microfabrication of μ-TAS device.     

A blind watermarking method using maximum wavelet coefficient quantization

This paper proposes a blind watermarking algorithm based on maximum wavelet coefficient quantization for copyright protection. The wavelet coefficients are grouped into different block size and blocks are randomly selected from different subbands. We add different energies to the maximum wavelet coefficient under the constraint that the maximum wavelet coefficient is always maximum in a block. The watermark is embedded the local maximum coefficient which can effectively resist attacks. Also, using the block-based watermarking, we can extract the watermark without using the original image or watermark. Experimental results show that the proposed method is quite robust under either non-geometry or geometry attacks.     

PSO-based single multiplicative neuron model for time series prediction

Single multiplicative neuron model is a novel neural network model introduced recently, which has been used for time series prediction and function approximation. The model is based on a polynomial architecture that is the product of linear functions in different dimensions of the space. Particle swarm optimization (PSO), a global optimization method, is proposed to train the single neuron model in this paper. An improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. The proposed CRPSO, PSO, back-propagation algorithm and genetic algorithm are employed to train the model for three well-known time series prediction problems. The experimental results demonstrate the superiority of CRPSO-based neuron model in efficiency and robustness over the other three algorithms.     

Quantum dot light emitting devices for photomedical applications

While OLEDs have struggled to find a niche lighting application that can fully take advantage of their unique form factors as thin, flexible, lightweight and uniformly large‐area luminaire, photomedical researchers have been in search of low‐cost, effective illumination devices with such form factors that could facilitate widespread clinical applications of photodynamic therapy (PDT) or photobiomodulation (PBM). Although existing OLEDs with either fluorescent or phosphorescent emitters cannot achieve the required high power density at the right wavelength windows for photomedicine, the recently developed ultrabright and efficient deep red quantum dot light emitting devices (QLEDs) can nicely fit into this niche. Here, we report for the first time the in‐vitro study to demonstrate that this QLED‐based photomedical approach could increase cell metabolism over control systems for PBM and kill cancerous cells efficiently for PDT. The perspective of developing wavelength‐specific, flexible QLEDs for two critical photomedical fields (wound repair and cancer treatment) will be presented with their potential impacts summarized. The work promises to generate flexible QLED‐based light sources that could enable the widespread use and clinical acceptance of photomedical strategies including PDT and PBM.     

A microprocessor-based precision three-channel high-speed frequency meter with a zero dead time

A microprocessor-based frequency meter with a zero dead time is described. Basic characteristics of signals obtained by the real-time processing of measurement results by using the authors’ FreqLab program are given. The new frequency meter compares favorably with its analogs by combination of its characteristics, namely, small error (10^?9/T _meas), speed of operation (1 kHz), multichanneling (three channels, with prospects of having up to six), and low production cost.     

数字水印攻击技术及对策研究*

分类论述了目前常见的一些数字水印攻击技术,并给出了相应的解决对策,对研究新型数字水印系统有一定的借鉴作用。