Poly(butylene terephthalate)/organoclay nanocomposites prepared by in situ interlayer polymerization and its fiber (II)

Intercalated nanocomposites with poly(butylene terephthalate) (PBT) incorporated between the montmorillonite layers were synthesized from dimethyl terephthalate and 1,4-butane diol by using an in situ interlayer polymerization. The PBT nanocomposites were melt-spun at different organoclay contents to produce monofilaments. The samples were characterized by using wide angle X-ray diffraction, electron microscopy, thermal analysis, and tensile testing. The extent of the clay layer in the PBT was confirmed by using X-ray diffraction and electron microscopy, and the clay layer was found to be highly dispersed on a nanometer scale. The addition of only a small amount of organoclay was enough to improve the thermo-mechanical properties of the PBT hybrid fibers. The hybrids were extruded with various draw ratios (DRs) to examine the tensile mechanical property of the fibers. At DR=1, the ultimate tensile strength of the hybrid fibers increased with the addition of clay up to a critical content and then decreased. However, the initial modulus monotonically increased with increasing amount of organoclay in the PBT matrix. When the DR was increased from 1 to 6, for example, the strength and the initial modulus values of the hybrids containing 3 wt% organoclay decreased linearly.     

An empirical study of design-of-experiment data mining for yield-loss diagnosis for semiconductor manufacturing

To maintain competitive advantages, semiconductor industry has strived for continuous technology migrations and quick response to yield excursion. As wafer fabrication has been increasingly complicated in nano technologies, many factors including recipe, process, tool, and chamber with the multicollinearity affect the yield that are hard to detect and interpret. Although design of experiment (DOE) is a cost effective approach to consider multiple factors simultaneously, it is difficult to follow the design to conduct experiments in real settings. Alternatively, data mining has been widely applied to extract potential useful patterns for manufacturing intelligence. However, because hundreds of factors must be considered simultaneously to accurately characterize the yield performance of newly released technology and tools for diagnosis, data mining requires tremendous time for analysis and often generates too many patterns that are hard to be interpreted by domain experts. To address the needs in real settings, this study aims to develop a retrospective DOE data mining that matches potential designs with a huge amount of data automatically collected in semiconductor manufacturing to enable effective and meaningful knowledge extraction from the data. DOE can detect high-order interactions and show how interconnected factors respond to a wide range of values. To validate the proposed approach, an empirical study was conducted in a semiconductor manufacturing company in Taiwan and the results demonstrated its practical viability.     

An SDP Primal-Dual Algorithm for Approximating the Lovász-Theta Function

The Lovász ?-function (Lovász in IEEE Trans. Inf. Theory, 25:1–7, 1979) of a graph G=(V,E) can be defined as the maximum of the sum of the entries of a positive semidefinite matrix X, whose trace Tr(X) equals 1, and X _ij =0 whenever {i,j}∈E. This function appears as a subroutine for many algorithms for graph problems such as maximum independent set and maximum clique. We apply Arora and Kale’s primal-dual method for SDP to design an algorithm to approximate the ?-function within an additive error of δ>0, which runs in time $O(\frac{\vartheta ^{2} n^{2}}{\delta^{2}} \log n \cdot M_{e})$ , where ?=?(G) and M _e =O(n ³) is the time for a matrix exponentiation operation. It follows that for perfect graphs G, our primal-dual method computes ?(G) exactly in time O(? ² n ⁵logn). Moreover, our techniques generalize to the weighted Lovász ?-function, and both the maximum independent set weight and the maximum clique weight for vertex weighted perfect graphs can be approximated within a factor of (1+?) in time O(? ^?2 n ⁵logn).     

Domain Adaptation for Structured Regression

Discriminative regression models have proved effective for many vision applications (here we focus on 3D full-body and head pose estimation from image and depth data). However, dataset bias is common and is able to significantly degrade the performance of a trained model on target test sets. As we show, covariate shift, a form of unsupervised domain adaptation (USDA), can be used to address certain biases in this setting, but is unable to deal with more severe structural biases in the data. We propose an effective and efficient semi-supervised domain adaptation (SSDA) approach for addressing such more severe biases in the data. Proposed SSDA is a generalization of USDA, that is able to effectively leverage labeled data in the target domain when available. Our method amounts to projecting input features into a higher dimensional space (by construction well suited for domain adaptation) and estimating weights for the training samples based on the ratio of test and train marginals in that space. The resulting augmented weighted samples can then be used to learn a model of choice, alleviating the problems of bias in the data; as an example, we introduce SSDA twin Gaussian process regression (SSDA-TGP) model. With this model we also address the issue of data sharing, where we are able to leverage samples from certain activities (e.g., walking, jogging) to improve predictive performance on very different activities (e.g., boxing). In addition, we analyze the relationship between domain similarity and effectiveness of proposed USDA versus SSDA methods. Moreover, we propose a computationally efficient alternative to TGP (Bo and Sminchisescu 2010), and it’s variants, called the direct TGP. We show that our model outperforms a number of baselines, on two public datasets: HumanEva and ETH Face Pose Range Image Dataset. We can also achieve 8–15 times speedup in computation time, over the traditional formulation of TGP, using the proposed direct formulation, with little to no loss in performance.     

Fat-simulating and accelerating solvents for polyolefins and MWD of solvent extracts of polyethylenes

Migration kinetics of straight-chain oligomers and antioxidants from several polyolefins at different temperatures into various solvents have been studied by radioactive tracer techniques. Anhydrous ethanol appears to be a well suited food-oil or liquid-fat simulant for extracting different types of migrants from polyolefins. Pure and mixed triglycerides are also good oil or fat simulants, but the triglycerides offer no simpler analytical procedures than the use of oil or fat themselves. n-Octanol may also be considered as a reasonable oil or fat simulant; however, its action depends somewhat on the choice of migrants. The accelerating action of n-heptane over that of oil or simulants is quantitatively demonstrated. The accelerating effects are greater for migration systems with lower diffusion coefficients. The diffusion coefficients for migration into n-heptane are about 20 times greater than the diffusion coefficients into ethanol or oil for otherwise identical migration systems yielding diffusion coefficients of about 10^?7 cm²s^?1 into oil or ethanol. For systems yielding diffusion coefficients into oil or ethanol of about 10^?12 cm²s^?1, the corresponding diffusion coefficients into n-heptane are about 1000 times greater. The molecular weight distributions (MWDs) of the n-heptane and ethanol extracts of polyolefins have been analysed. n-Heptane can not only accelerate the migration of the individual migrant but also remove oligomer species that are slightly soluble or present at low levels in the oil or simulant extracts.     

Dependence of properties of liquid crystalline aromatic copolyesters on monomer sequence-copolyesters derived from terephthalic acid, 2,7-naphthalenediol and p-hydroxybenzoic acid

Summary An aromatic copolyester with the ordered sequence of terephthalic acid (TA)-p-hydroxybenzoic acid (HB)-2,7-naphthalenediol (ND)-p-hydroxybenzoic acid (HB) was prepared and its properties were compared with those of the corresponding random copolyester having the same overall monomer composition. Thermal and crystallizing properties of the two polymers are quite different. The former exhibits significantly higher glass transition and melting temperatures than the latter. The former's degree of crystallinity also is much higher than the latter's. Both polymers are thermotropic and form nematic melts.     

A study on security strategy in ICT convergence environment

In the knowledge and information society, the value of utilizing ICT technology in companies is being newly interpreted upon the convergence of business and information technology of companies. Accordingly, companies are ensuring corporate competitiveness by improving product productivity and reducing the consumption of human/physical resources through the change of strategic management environment using ICT technology. On the other hand, companies’ core information is being leaked outside of company from the convergence with ICT technology and its scale is increasing each year. Accordingly, the need for improving the level of security according to companies’ informatization level is increasing. However, studies are lacking on the composition of security strategy in suitable forms according to the scale of company and level of retaining resources. Accordingly, this study examined the security advancement steps to verify the present condition of companies’ security and design security strategy from a macroscopic perspective by improving the level of security according to the scale of company and present condition of resources.     

Simulation Estimation of Dynamic Panel Discrete Choice Models Using the t Distributions

In this paper a practical robust simulation estimator is proposed for the dynamic panel data discrete choice models using the $t$ distribution. The maximum simulated likelihood estimators are obtained through a recursive algorithm formulated by Geweke–Hajivassiliou–Keane simulators. Monte Carlo experiments indicate that the proposed robust simulation estimators perform well under the errors with longer than normal tails for a small simulation size, even with the initial conditions problem.     

Measurement of the rheological properties of polymer melts with annular rheometer

An annular die has been designed having a very thin gap distance between two coaxial cylinders. The die was then used to measure wall normal stresses along the longitudinal direction of polymer melts flowing through the thin annulus. The materials investigated were high-density polyethylene, low-density polyethylene, polypropylene, and polystyrene. Also investigated were blends of polystyrene and polypropylene, and blends of polystyrene and high-density polyethylene The measurements of wall normal stresses were used to determine the rheological properties of the melts, namely, the melt viscosity from the slope of axial wall normal stress profiles and the melt elasticity from exit pressures. The interpretation of the experimental data was made possible by the fact that the narrow-gap annular die can be considered as a substitute for a thin slit die. It has been found that the results obtained in the present study are consistent with those reported earlier by the author, who at that time used both capillary and slit dies.     

Collaborative representation with reduced residual for face recognition

Collaboration representation-based classification (CRC) was proposed as an alternative approach to the sparse representation method with similar efficiency. The CRC is essentially a competition scheme for the training samples to compete with each other in representing the test sample, and the training class with the minimum representation residual from the test sample wins the competition in the classification. However, the representation error is usually calculated based on the Euclidean distance between a test sample and the weighted sum of all the same-class samples. This paper exploits alternative methods of calculating the representation error in the CRC methods to reduce the representation residual in a more optimal way, so that the sample classes compete with each other in a closer range to represent the test sample. A large number of face recognition experiments on three face image databases show that the CRC methods with optimized presentation residual achieve better performance than the original CRC, and the maximum improvement in classification accuracy is up to 12 %.