Parameter determination of support vector machine and feature selection using simulated annealing approach

Support vector machine (SVM) is a novel pattern classification method that is valuable in many applications. Kernel parameter setting in the SVM training process, along with the feature selection, significantly affects classification accuracy. The objective of this study is to obtain the better parameter values while also finding a subset of features that does not degrade the SVM classification accuracy. This study develops a simulated annealing (SA) approach for parameter determination and feature selection in the SVM, termed SA-SVM.To measure the proposed SA-SVM approach, several datasets in UCI machine learning repository are adopted to calculate the classification accuracy rate. The proposed approach was compared with grid search which is a conventional method of performing parameter setting, and various other methods. Experimental results indicate that the classification accuracy rates of the proposed approach exceed those of grid search and other approaches. The SA-SVM is thus useful for parameter determination and feature selection in the SVM.     

Synthesis of bio-functionalized copolymer particles bearing carboxyl groups via a microfluidic device

Monodisperse copolymer particles carrying surface carboxyl groups in the range of 50–200 μm were prepared by in situ UV polymerization of ethyleneglycol dimethacrylate (EGDMA) with acrylic acid (AA) via a microfluidic flow-focusing device (MFFD). The design of the coaxial orifices in the MFFD enables the confinement of the comonomer liquid thread to the central axis of the microchannel, which can avoid the wetting problem of comonomer liquid with the microchannel and can successfully produce monodisperse copolymer microspheres with coefficient of variance below 5%. The effects of concentration of EGDMA and AA on droplet diameters and the distribution of carboxyl group on particle surfaces were examined. It has been found that, increasing the concentration of AA would decrease particle sizes, but increase the distribution of carboxyl group on particle surfaces. Bioconjugation of the carboxylated copolymer particles with the anti-rabbit IgG–Cy3 conjugates was successfully demonstrated. By increasing the concentration of AA accompanied with decreasing the particle sizes, high efficiency of bioconjugation on carboxylated copolymer particles was achieved. The rapid continuous synthesis of carboxylated copolymer particles via a microfluidic device provides a reliable control of particle sizes and composition for massive production in biotechnological applications.     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Noise of He-Cd laser and its suppression

Linear relations have been observed between the reciprocal of the noise ratio and the reciprocal of the output power of the He-Cd laser as well as between the noise ratio and the net gain within the laser cavity. By a feedback method with an acoustooptic modulator in the laser cavity at the Brewster angle for low optical loss, a stable laser with high power output and low noise has been obtained. The noise ratio and the output power are 0.8% and 33 mW, respectively, at 4416 A     

From immediate agreement to eventual agreement: early stopping agreement protocol for dynamic networks with malicious faulty processors

With the rapid advancement of wireless networking technology, networks have evolved from static to dynamic. Reliability of dynamic networks has virtually become an important issue. Fortunately, a solution to the above issue can be derived from solutions to the Byzantine Agreement (BA) problem. BA problem can be solved by protocols that make processors reach an agreement through message exchange. Protocols used to solve the problem can be divided into Immediate Byzantine Agreement (IBA) protocols and Eventual Byzantine Agreement (EBA) protocols. In IBA protocols, the number of rounds of message exchange is determined by the total number of processors in the network. Even if no faulty processor is present in the network, IBA protocols still require a fixed number of rounds of message exchange, causing a waste of time. In contrast, EBA protocols dynamically adjust the number of rounds of message exchange according to the interference of faulty processors. In terms of efficiency, EBA protocols certainly outperform IBA protocols. Due to the fact that the existing EBA protocols have been designed for static networks, they cannot work on dynamic networks. In this paper, we revisit the EBA problem in dynamic networks to increase the reliability of dynamic networks. Simulations will be conducted to validate that the proposed protocol requires the minimum rounds of message exchange and can tolerate the maximum number of malicious faulty processors compared to other existing protocols.     

Deformation Behavior of Duplex Zircaloy-4-Oxygen Alloys

The mechanical properties of two-phase Zircaloy-4-oxygen alloys at thermal equilibrium have been determined. The strength of these alloys depends to a large extent on their microstructure. The strengthening behavior for alloys having isolateda grains in the softer β matrix is similar to the dispersed particle strengthening. The yield strength of these alloys is found to obey the Petch relationship, (MPa), whereλ _β is the mean free path of β phase inμm. As the volume fraction ofa phase increases, its aspect ratio also increases. This allows more effective load transfer from the matrix to the hardera phase. It has been shown that the strength of these alloys obeys a modified rule of mixtures. The alloys having equiaxeda grains in the β matrix show large strain rate sensitivities at low strain rate. The deformation behavior is interpreted in terms of dislocation slip in the β matrix and diffusion assisted climb near the interphase boundary.     

Synthesis of BaTi4O9 ceramics by reaction-sintering process

Synthesis of BaTi₄O₉ ceramics by a reaction-sintering process was investigated. The mixture of raw materials for stoichiometric BaTi₄O₉ were pressed and sintered into ceramics without any calcination stage involved. Pure BaTi₄O₉ phases were obtained at 1150-1280 °C. High-sintered density, 98.2-99.5% of theoretical value (4.533 g/cm³), can be obtained for pellets sintered at 1200-1280 °C for 2-6 h. Some rod-shaped grains 3-7 μm in the longitudinal axis appear in pellets sintered at 1230 °C. Both the size and the amount of these rod-shaped grains increase at higher sintering temperature.     

Diverse reasoning in automated model formulation

Diverse reasoning supports a dynamic integration of various reasoning methods in a computerized system. This paper describes a control blackboard approach to simulate the control features observed in the expert's model formulation protocols. The diverse reasoning concept is incorporated so that the model formulation process is dynamically in a plan-directed, action-directed, or data-directed fashion. The diverse reasoning concept facilitates the control features simulation. By analyzing the diverse reasoning behavior in the proposed system, this paper contributes to a better understanding of and support to the modeling process for the design of intelligent decision support systems. The usefulness of the prototype system is also evaluated using an empirical experiment.     

Product family modeling for mass customization

With growing reliance on modeling in product development, it is imperative to describe product families in a cohesive way. In particular, mass customization calls for a close integration of product life cycle from customer recognition to delivery and services. This paper proposes a triple-view scheme for modeling product families. Technical challenges are discussed by comparing product family modeling with modeling single products. Individual modeling formalisms for different views are discussed. An example of product family modeling in power supply design is presented to illustrate the feasibility and potential of the proposed approach.