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Magnetic nanoparticles functionalized with carboxyl-group have considerable potential to be used as bio-labels due to their conjugation abilities with proteins. Here, we synthesized the iron oxide nanoparticles functionalized with carboxyl groups through self-assembled monolayer coating using citric acid and self-assembled bilayer coating using fatty acids. Their dimension, hydrodynamic size, surface property, and magnetic behavior were characterized through transmission electron microscopy, dynamic light scattering, Fourier transform infrared spectroscopy, thermal gravimetric analysis, and vibrating sample magnetometry. We also confirmed the binding ability of these nanoparticles with bovine serum albumin on thin gold film. [ABSTRACT FROM AUTHOR]

A concept of using planar circuit resonance to disable 3D cavity resonance inside a rectangular waveguide filter is demonstrated. Switchable RF MEMS planar resonators are introduced inside the resonant cavities of a high Q-factor iris bandpass filter to turn the filter ON and OFF. The measurement confirms that this high Q-factor filter with insertion loss better than 0.1 dB can be converted to a bandstop filter with an isolation better than 30 dB for the same frequency and bandwidth. [ABSTRACT FROM PUBLISHER]

A new class of TE10 mode waveguide switch is proposed in this letter. The concept is based on switching planar bandstop filters with monolithically integrated RF MEMS that are placed inside, onto the sidewall, of conventional rectangular waveguides. The design allows electrical switching off a waveguide in specific bands. To illustrate the principle, simulation and measured results are presented for waveguide switches employing 3-pole and 5-pole planar filters. An insertion loss better than 0.3 dB and an isolation better than 14 dB are achieved over a bandwidth of 500 MHz at Ku-band. [ABSTRACT FROM PUBLISHER]

An improved hybrid particle swarm optimization (PSO)-based wavelet neural network (WNN) for Modeling the development of Fluid Dispensing for Electronic Packaging (MFD-EP) is presented in this paper. In modeling the fluid dispensing process, it is important to understand the process behavior as well as determine the optimum operating conditions of the process for a high-yield, low-cost, and robust operation. Modeling the fluid dispensing process is a complex nonlinear problem. This kind of problem is suitable to be solved by applying a neural network. Among the different kinds of neural networks, the WNN is a good choice to solve the problem. In the proposed WNN, the translation parameters are variables depending on the network inputs. Due to the variable translation parameters, the network becomes an adaptive one that provides better performance and increased learning ability than conventional WNNs. An improved hybrid PSO is applied to train the parameters of the proposed WNN. The proposed hybrid PSO incorporates a wavelet-theory-based mutation operation. It applies the wavelet theory to enhance the PSO in more effectively exploring the solution space to reach a better solution. A case study of MFD-EP is employed to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Uncertainty in manufacturing processes is caused both by randomness, as in material properties, and by fuzziness, as in the inexact knowledge. Previous research has seldom considered these two types of uncertainty when modeling manufacturing processes. In this paper, a hybrid fuzzy least-squares regression (HFLSR) approach to modeling manufacturing processes, which does take into consideration these two types of uncertainty, is proposed and described, and a new form of weighted fuzzy arithmetic is introduced to develop the hybrid fuzzy least-squares regression method. The proposed HFLSR approach not only features the capability of dealing with the two types of uncertainty, but also addresses the consideration of replication of responses in experiments. To investigate the effectiveness of the proposed approach to process modeling, it was applied to the modeling solder paste dispensing process. Modeling results were compared with those based on statistical regression and fuzzy linear regression. It was found that the accuracy of prediction based on the HFLSR is slightly better than that based on statistical regression and much better than that based on the Peters fuzzy regression. [ABSTRACT FROM AUTHOR]

A new hybrid particle swarm optimization (PSO) that incorporates a wavelet-theory-based mutation operation is proposed. It applies the wavelet theory to enhance the PSO in exploring the solution space more effectively for a better solution. A suite of benchmark test functions and three industrial applications (solving the load flow problems, modeling the development of fluid dispensing for electronic packaging, and designing a neural- network-based controller) are employed to evaluate the performance and the applicability of the proposed method. Experimental results empirically show that the proposed method significantly outperforms the existing methods in terms of convergence speed, solution quality, and solution stability. [ABSTRACT FROM AUTHOR]