Various effects of silicidation on shallow p+ junctionsformed by BF2+ implantation into thin poly-Sifilms on Si substrates

Various effects of silicidation on shallow p⁺ n junctions formed by the scheme that implants BF₂⁺ ions into thin poly-Si films on Si substrates are described. A post-Ni silicidation just slightly improves the preformed junctions of the annealed sample. However, as the sample is first deposited with thin Ni films after the implantation and then annealed, the resulting junctions are much better than the preformed ones. Moreover, as the sample is deposited with Ti films, the resultant junctions are just slightly better the preformed ones     

The role of coping in the relationship between perceived racism and racism-related stress for Asian Americans: Gender differences.

On the basis of stress and coping theory, the authors examined coping as a mediator of the relationship between perceptions of racism and racism-related stress with a sample of Asian American college students (N = 336). Results indicated that coping mediated the relationship between racism and racism-related stress differentially by gender. The more that men perceived racism, the more likely they were to use support-seeking coping strategies that were associated with higher levels of racism-related stress. The more that women perceived racism, the more they used active coping strategies that were associated with higher levels of racism-related stress. The findings demonstrate how coping with racism differs for Asian Americans on the basis of gender. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Recurrent type-2 fuzzy neural network using Haar wavelet energy and entropy features for speech detection in noisy environments

This paper proposes a new method to detect the boundary of speech in noisy environments. This detection method uses Haar wavelet energy and entropy (HWEE) as detection features. The Haar wavelet energy (HWE) is derived by using the robust band that shows the most significant difference between speech and nonspeech segments at different noise levels. Similarly, the wavelet energy entropy (WEE) is computed by selecting the two wavelet energy bands whose entropy shows the most significant speech/nonspeech difference. The HWEE features are fed as inputs to a recurrent self-evolving interval type-2 fuzzy neural network (RSEIT2FNN) for classification. The RSEIT2FNN is used because it uses type-2 fuzzy sets, which are more robust to noise than type-1 fuzzy sets. The recurrent structure in the RSEIT2FNN helps to remember the context information of a test frame. The RSEIT2FNN outputs are compared with a parameter threshold to determine whether it is a speech or nonspeech period. The HWEE-based RSEIT2FNN detection was applied to speech detection in different noisy environments with different noise levels. Comparisons with different detection methods verified the advantage of the proposed method of using HWEE.     

Parameter optimization of continuous sputtering process based on Taguchi methods,neural networks,desirability function,and genetic algorithms

To combat climate change, many industries have participated in the research on alternative energies. Industrial Technology Research Institute in Taiwan has developed techniques for the solar energy selective absorption film continuous sputtering process. For this extremely complicated process, plenty of parameters would influence the output quality. If parameters settings simply rely on the experience of engineers, the defect rate may increase due to instability. A more reliable approach is desirable to optimize the condition of manufacturing process parameters, thus improving the quality.The present study applies a systematic procedure for the parameter optimization of the absorption film continuous sputtering process. First, possible variables are determined based on collected data and engineering knowledge. Second, Taguchi methods are utilized to search for the significant factors and the optimal level combination of parameters. Finally, the integration of back-propagation neural network, desirability function, and genetic algorithms is used to obtain the optimal parameters setting. According to the experiment results, the performance of the integrated procedure is better than that of Taguchi methods and traditional approach. Furthermore, if applying the integrated method, the saving energy would achieve 9770.53 kiloliter of oil equivalent (kLOE) per year, which is 11.2 times the saving kLOE of the traditional paint process.     

Effects of insulin therapy on non-insulin-dependent diabetics with secondary oral hypoglycemic agent failure

A recent trend among physicians is the categorisation of lung scans as normal [excludes pulmonary embolism (PE)], high probability (confirms PE) and non-diagnostic (no judgement on PE risk). The low probability scan is therefore being eliminated as a functional category. This occasional survey contends that such an approach is misguided. Correction of the original PIOPED data with certain assumptions provides a more reproducible, albeit restricted, low probability scan category which excludes PE in 97% of cases in the low pre-test clinical category. Patients with a low probability scan with risk factors for PE (i.e. medium clinical risk) will require further investigation. More important, the very low probability scan category excludes PE in 98% of patients with low and more than 92% of patients with medium pre-test clinical likelihood. The demise of "low probability" is premature.     

Experimental observations on the effect of added dispersing agent on phenol biodegradation in a microporous membrane bioreactor

The effect of added dispersing agent tetrasodium pyrophosphate (TSP) on the degradation of phenol by Pseudomonas putida BCRC 14365 in a microporous membrane bioreactor was experimentally studied at 30 degrees C and pH 7. The hollow fibers were pre-wetted with ethanol to make them more hydrophilic. Phenol solution was passed through the lumen of the module and the cell medium was flowed across the shell. All Experiments were carried out at a fixed initial cell density of 0.023 g/L (0.06 optical density). Phenol could be completely degraded with the help of the biofilm formed on the outer surfaces of the fibers even though its level was high up to 3 g/L. It was also shown that the presence of TSP in cell medium could improve biodegradation. The amount of added TSP was optimized to be 1 g/L under the conditions studied. In this situation, 3 g/L of phenol could be completely removed within 76 h, much shorter than the absence of TSP (within 92 h).     

Effect of formaldehyde on Cu(II) removal from synthetic complexed solutions by solvent extraction

The effect of formaldehyde (HCHO) on the extraction of Cu(II) from an equimolar EDTA (ethylenediaminetetraacetic acid, H4L) solution with Aliquat 336 in kerosene (a quaternary amine) was examined. Experiments were carried out at different initial concentrations of Cu(II) (1.57-5 mol/m3), solution pH (3.0-8.0), HCHO concentrations (0-3 vol.%), Aliquat 336 concentrations (80-400 mol/m3), and temperatures (15-35 degrees C). It was shown that the distribution ratios (D) of Cu(II), which exists in the form of complexed anions CuL2-, increased with increasing equilibrium pH (pHeq), but reached a plateau at pHeq>4 for the system without HCHO and at pHeq>4.5 for the system with 1 vol.% HCHO. The D values increased with increasing HCHO concentration, likely due to the reduction of Cu(II) to Cu(I) by HCHO in solution. A semi-empirical two-parameter model was proposed to describe the extraction equilibrium, in which the non-ideality in organic phases was considered. The thermodynamic parameters were also evaluated and discussed.     

Safe binary particle swam algorithm for an enhanced unsupervised label refinement in automatic face annotation

Mining web facial images on the internet has become as a profitable and important paradigm towards auto face annotation technique. The unsupervised label refinement (ULR) is an effective method that can fix weakly labeled facial images data which are collected from the internet and included some images with wrong label. In order to improve the correction accuracy of ULR, particle swarm optimization (PSO) and binary particle swarm optimization (BPSO) are used for solving binary constraint optimization task in this study. A novel method named safe binary particle swam optimization (SBPSO) is also proposed to improve BPSO which has the probability over range problem for using the ULR. In addition, SBPSO is also employed for an enhanced ULR (EULR) objective function which is created by modifying the original formula of ULR to improve the accuracy of labeled facial image. An experimental database is queried from IMDb website which collected the actors who were bored in 1950 to 1990. Some error flags are randomly added in the database for the correction tests by different methods. The results showed that the SBPSO Algorithm for the EULR in automatic face annotation have the better label correction rate and convergence effect.     

Calibration of imprecise and inaccurate numerical models considering fidelity and robustness: a multi-objective optimization-based approach

Traditionally, model calibration is formulated as a single objective problem, where fidelity to measurements is maximized by adjusting model parameters. In such a formulation however, the model with best fidelity merely represents an optimum compromise between various forms of errors and uncertainties and thus, multiple calibrated models can be found to demonstrate comparable fidelity producing non-unique solutions. To alleviate this problem, the authors formulate model calibration as a multi-objective problem with two distinct objectives: fidelity and robustness. Herein, robustness is defined as the maximum allowable uncertainty in calibrating model parameters with which the model continues to yield acceptable agreement with measurements. The proposed approach is demonstrated through the calibration of a finite element model of a steel moment resisting frame.