Clonal optimization-based negative selection algorithm with applications in motor fault detection

The Negative Selection Algorithm (NSA) and clonal selection method are two typical kinds of artificial immune systems. In this paper, we first introduce their underlying inspirations and working principles. It is well known that the regular NSA detectors are not guaranteed to always occupy the maximal coverage of the nonself space. Therefore, we next employ the clonal optimization method to optimize these detectors so that the best anomaly detection performance can be achieved. A new motor fault detection scheme using the proposed NSA is also presented and discussed. We demonstrate the efficiency of our approach with an interesting example of motor bearings fault detection, in which the detection rates of three bearings faults are significantly improved.     

Retrieval of total suspended matter concentration from Gaofen-1 Wide Field Imager (WFI) multispectral imagery with the assistance of Terra MODIS in turbid water – case in Deep Bay

This study proposed a method for developing high spatial resolution Gaofen-1 satellite (GF-1) Wide Field Imager (WFI)-based total suspended matter concentration (C_TSM) retrieval model with the assistance of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using the Deep Bay in China as a case. Based on long-term calibrated C_TSM measurements of optical backscatter (OBS) 3A turbidity and temperature monitoring system of two stationary stations from January 2007 through November 2008, 33 match-ups were selected to build an exponential retrieval model for MODIS atmospherically corrected remote-sensing reflectance (R_rs) ratio (R_rs,645/R_rs,555). Validation of the MODIS model showed well agreement with the seven in situ C_TSM measurements with a root mean squared error (RMSE) of 5.06 mg l^?1 and a coefficient of determination R² of 0.80. Aided with six MODIS retrieved C_TSM products, different band combinations (single band (R_rc,660), band subtraction (R_rc,660–R_rc,560), band ratio (R_rc,660/R_rc,560), and total suspended matter index at 660 nm band (TSMI₆₆₀) were evaluated for simultaneous GF-1 WFI Rayleigh-corrected reflectance (R_rc). The results showed that the exponential model based on the Rayleigh-corrected reflectance ratio (R_rc,660/R_rc,560) could achieve acceptable accuracy, with RMSE of 14.80 mg l^?1 and R² of 0.62. The proposed method would be helpful for dynamic monitoring in the Deep Bay, and more important could also provide an alternative approach for studies when in situ measurements are unreachable.     

Monte Carlo simulations of the HP model (the "Ising model" of protein folding)

Using Wang–Landau sampling with suitable Monte Carlo trial moves (pull moves and bond-rebridging moves combined) we have determined the density of states and thermodynamic properties for a short sequence of the HP protein model. For free chains these proteins are known to first undergo a collapse “transition” to a globule state followed by a second “transition” into a native state. When placed in the proximity of an attractive surface, there is a competition between surface adsorption and folding that leads to an intriguing sequence of “transitions”. These transitions depend upon the relative interaction strengths and are largely inaccessible to “standard” Monte Carlo methods.     

Low order integral-action controller synthesis

A simple controller synthesis method is developed for certain classes of linear, time-invariant, multi-input multi-output plants. The number of poles in each entry of these controllers depends on the number of right-half plane plant zeros, and is independent of the number of poles of the plant to be stabilized. Furthermore, these controllers have integral-action so that they achieve asymptotic tracking of step input references with zero steady-state error. The designed controller’s poles and zeros are all in the stable region with the exception of one pole at the origin for the integral-action design requirement. The freedom available in the design parameters may be used for additional performance objectives, although the only goal here is stabilization and tracking of constant references.     

Adaptive fuzzy-neural-network control for maglev transportation system

A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies.     

Secretome analysis of novel IgE-binding proteins from Penicillium citrinum

The Penicillium genus of fungi is a frequently reported cause of allergic reactions. However, only a limited number of allergens have been reported. In Penicillium spp., many allergens show higher IgE-binding activity in culture filtrate extracts than in cellular extracts. In order to investigate the IgE-reactive profile of mold-sensitized patients, secreted IgE-reactive proteins from Penicillium citrinum were identified by 2-DE, serum immunoblotting, and nanoLC-MS/MS. Among the IgE-reactive spots, one known allergen, Pen c 13, and four novel allergens were identified. The cDNAs coding for Pen c 32 and Pen c 30 were cloned using designed primers based on nanoLC-MS/MS analysis. The amino acid sequences of Pen c 32 and Pen c 30 were, respectively, found to have extensive similarity with those of pectate lyases and catalases from various fungi. Native Pen c 30 was shown to have catalase activity and to bind to serum IgE from 48% of mold-allergic patients and induced immediate type skin reactions in a sensitized patient. Here, we present a proteome approach which resulted in the identification of four novel secreted allergens. These novel allergens might be useful in allergy diagnosis and in the treatment of mold-allergic disorders.     

Stream segregation algorithm for pattern matching in polyphonic music databases

As music can be represented symbolically, most of the existing methods extend some string matching algorithms to retrieve musical patterns in a music database. However, not all retrieved patterns are perceptually significant because some of them are, in fact, inaudible. Music is perceived in groupings of musical notes called streams. The process of grouping musical notes into streams is called stream segregation. Stream-crossing musical patterns are perceptually insignificant and should be pruned from the retrieval results. This can be done if all musical notes in a music database are segregated into streams and musical patterns are retrieved from the streams. Findings in auditory psychology are utilized in this paper, in which stream segregation is modelled as a clustering process and an adapted single-link clustering algorithm is proposed. Supported by experiments on real music data, streams are identified by the proposed algorithm with considerable accuracy.

On Kalman filtering over fading wireless channels with controlled transmission powers

We study stochastic stability of centralized Kalman filtering for linear time-varying systems equipped with wireless sensors. Transmission is over fading channels where variable channel gains are counteracted by power control to alleviate the effects of packet drops. We establish sufficient conditions for the expected value of the Kalman filter covariance matrix to be exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing power control policies which minimize the total sensor power budget. In deriving the optimal power control laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.     

Determination of the Superconducting Penetration Depth From Coplanar-Waveguide Measurements

We introduce a novel transmission-line method for determining the penetration depth in thin high-temperature superconducting (HTS) films. The method is based on the accurate measurement of the inductance per unit length of a superconducting coplanar-waveguide (CPW) transmission line fabricated on the HTS sample. Using the experimentally obtained inductance per unit length, we interpolate the penetration depth from a table of numerically determined values of inductance (per unit length) as a function of penetration depth, calculated from a coupled transmission-line model. A novelty of our procedure is the utilization of the multiline thru-reflect-line (TRL) method and the calibration-comparison method to accurately determine the inductance per unit length of the superconducting transmission line. By measuring different CPW geometries patterned onto the same thin-film sample, we can verify our penetration depth values. We demonstrate this technique by extracting the penetration depth for several different HTS films at 76 K. Estimated uncertainties in the extracted penetration depth are also provided. Contribution of an agency of the US government not subject to copyright.     

Plastic Injection Molding of High-Aspect Ratio Micro-Rods

Technological advancements have led to an increase in demand for fabrication of small and cheap miniature components or parts, especially in the medical and electronic fields. In this research work, micro-rods of varying lengths and diameters were molded using a specially designed tabletop injection molding machine. The main purpose was to investigate whether complete filling of the microcavities was possible and whether small cavity openings will restrict melt flow into the cavities.

Process parameters, such as injection pressure, mold temperature and melt temperature were varied. The micro-rods obtained were analyzed with Scanning Electron Micrographs (SEM). The results showed that injection pressure was the most important parameter for microinjection molding. The use of a vacuum system also yielded better results.