Aligning Crystal Orientation of Poly-Crystalline Bi-Te With a High Magnetic Field

We investigated the effect of aligning crystal orientation in the microstructures containing sub micro-sized grains on the thermoelectric properties for polycrystalline Bi-Te materials.Bi-Te powder,prepared through the conventional pulverization process,was sufficiently dispersed in an appropriate solvent,and then was formed into c-axis aligned green bodies under a designated high magnetic field.The green bodies were sintered with spark-plasma-sintering machine.The degree of crystal alignment of sintered bodies was examined with the electron-back-scatter-diffraction SEM and the X-ray diffraction patterns.It was observed that for both p and n type thermoelectric Bi-Te materials,aligning crystal orientation properly made electrical resistivity decreased with keeping Seebeck coefficient and thermal conductivity remained unchanged.As a typical result,the aligned Bi-Te material with the magnetic field of 10 tesla showed 30%enhancement of the thermoelectric performance.     

Modification of Solidification Structure Under DC Pulse Magnetic Field

A new process using direct cunent pulsed magnetic field for modification of solidification structure of pure aluminium has been investigated.The experimental results show that the fine equiaxed crystal zone exists at the bottom of ingots with pulse magnetic,and with the increase of rated output current the equiaxed grains are more finer.     

Microstructural Factors Controlling Blunt- and Sharp-Notch Toughness in La-Added 8Ni-13Co Secondary Hardening Steel

Toughness variations of sharp and blunt notches were studied. For the quantitative analysis of various particles, small-angle neutron scattering was conducted. Under the 1323 K (1050 °C), and the 1473 K/1323 K and 1473 K/1173 K (1200 °C/1050 °C and 1200 °C/900 °C) (high-temperature initial step and low-temperature final step) austenitizing conditions, the impact toughness underwent changes as follows: 30→30→43 J. In contrast, the fracture toughness underwent variations as follows: 90.5→120→114 MPa $ \sqrt {\text{m}} $ m . Blunt- and sharp-notch toughness parameters were found to be mainly dependent on grain size and primary particles, respectively. The microstructural dependence of toughness with notch acuity is discussed in detail.     

A multi-director formulation for nonlinear elastic-viscoelastic layered shells

A C⁰ finite element formulation for nonlinear analysis of multi-layered shells comprised of elastic and viscoelastic layers is presented for applications involving small strains but finite rotations. The elastic and viscoelastic layers may occupy arbitrary layer locations and the formulation is applicable to thick and thin shells. The formulation utilizes a three-dimensional variational approach in which the layered shell is represented as a multi-director field. The incorporated kinematic theory describes, within individual layers, the effects of transverse shear and transverse normal strain to arbitrary orders in the layer thickness coordinate. Stresses are computed through the three-dimensional constitutive equations and the usual “zero normal stress” shell hypothesis is not employed. Sufficiently general constitutive equations for the viscoelastic layers are proposed in objective rate form and a product algorithm, based on an operator split in the complete set of constitutive equations, is used for the temporal integration of the rate equations. The definition of the tangent operator, used in Newton's method for the solution of the nonlinear equations, is derived consistently from the product algorithm. Observations on the use of reduced/selective integration in the presence of high order kinematics are made and a number of numerical examples are presented to illustrate the capability of the formulation.     

Improving Korean verb-verb morphological disambiguation using lexical knowledge from unambiguous unlabeled data and selective web counts

This paper deals with verb-verb morphological disambiguation of two different verbs that have the same inflected form. The verb-verb morphological ambiguity (VVMA) is one of the critical Korean parts of speech (POS) tagging issues. The recognition of verb base forms related to ambiguous words highly depends on the lexical information in their surrounding contexts and the domains they occur in. However, current probabilistic morpheme-based POS tagging systems cannot handle VVMA adequately since most of them have a limitation to reflect a broad context of word level, and they are trained on too small amount of labeled training data to represent sufficient lexical information required for VVMA disambiguation.In this study, we suggest a classifier based on a large pool of raw text that contains sufficient lexical information to handle the VVMA. The underlying idea is that we automatically generate the annotated training set applicable to the ambiguity problem such as VVMA resolution via unlabeled unambiguous instances which belong to the same class. This enables to label ambiguous instances with the knowledge that can be induced from unambiguous instances. Since the unambiguous instances have only one label, the automatic generation of their annotated corpus are possible with unlabeled data.In our problem, since all conjugations of irregular verbs do not lead to the spelling changes that cause the VVMA, a training data for the VVMA disambiguation are generated via the instances of unambiguous conjugations related to each possible verb base form of ambiguous words. This approach does not require an additional annotation process for an initial training data set or a selection process for good seeds to iteratively augment a labeling set which are important issues in bootstrapping methods using unlabeled data. Thus, this can be strength against previous related works using unlabeled data. Furthermore, a plenty of confident seeds that are unambiguous and can show enough coverage for learning process are assured as well.We also suggest a strategy to extend the context information incrementally with web counts only to selected test examples that are difficult to predict using the current classifier or that are highly different from the pre-trained data set.As a result, automatic data generation and knowledge acquisition from unlabeled text for the VVMA resolution improved the overall tagging accuracy (token-level) by 0.04%. In practice, 9-10% out of verb-related tagging errors are fixed by the VVMA resolution whose accuracy was about 98% by using the Naïve Bayes classifier coupled with selective web counts.     

Zoned-partitioning of tree-like access methods

The performance of access methods and the underlying disk system is a significant factor in determining the performance of database applications, especially with large sets of data. While modern hard disks are manufactured with multiple physical zones, where seek times and data transfer rates vary significantly across the zones, there has been little consideration of this important disk characteristic in designing access methods (indexing schemes). Instead, conventional access methods have been developed based on a traditional disk model that comes with many simplifying assumptions such as an average seek time and a single data transfer rate. The paper proposes novel partitioning techniques that can be applied to any tree-like access methods, both dynamic and static, fully utilizing zoning characteristics of hard disks. The index pages are allocated to disk zones in such a way that more frequently accessed index pages are stored in a faster disk zone. On top of the zoned data placement, a localized query processing technique is proposed to significantly improve the query performance by reducing page retrieval times from the hard disk.     

Procedural Synthesis using Vortex Particle Method for Fluid Simulation

We propose a fast and effective technique to improve sub‐grid visual details of the grid based fluid simulation. Our method procedurally synthesizes the flow fields coming from the incompressible Navier‐Stokes solver and the vorticity fields generated by vortex particle method for sub‐grid turbulence. We are able to efficiently animate smoke which is highly turbulent and swirling with small scale details. Since this technique does not solve the linear system in high‐resolution grids, it can perform fluid simulation more rapidly. We can easily estimate the influence of turbulent and swirling effect to the fluid flow.     

Multitask bilateral learning for real‐time image enhancement

Nowadays, deep neural networks (DNNs) for image processing are becoming more complex; thus, reducing computational cost is increasingly important. This study highlights the construction of a DNN for real‐time image processing, training various image processing operators efficiently through multitask learning. For real‐time image processing, the proposed algorithm takes a joint upsampling approach through bilateral guided upsampling. For multitask learning, the overall network is based on an encoder‐decoder architecture, which consists of encoding, processing, and decoding components, in which the encoding and decoding components are shared by all the image processing operators. In the processing component, a semantic guidance map, which contains processing information for each image processing operator, is estimated using simple linear shifts of the shared deep features. Through these components, the proposed algorithm requires an increase of only 5% in the number of parameters to add another image processing operator and achieves faster and higher performance than that of deep‐learning‐based joint upsampling methods in local image processing as well as global image processing.     

Mathematical analysis of oxygen transfer through polydimethylsiloxane membrane between double layers of cell culture channel and gas chamber in microfluidic oxygenator

For successful cell culture in microfluidic devices, precise control of the microenvironment, including gas transfer between the cells and the surrounding medium, is exceptionally important. The work is motivated by a polydimethylsiloxane (PDMS) microfluidic oxygenator chip for mammalian cell culture suggesting that the speed of the oxygen transfer may vary depending on the thickness of a PDMS membrane or the height of a fluid channel. In this paper, a model is presented to describe the oxygen transfer dynamics in the PDMS microfluidic oxygenator chip for mammalian cell culture. Theoretical studies were carried out to evaluate the oxygen profile within the multilayer device, consisting of a gas reservoir, a PDMS membrane, a fluid channel containing growth media, and a cell culture layer. The corresponding semi-analytical solution was derived to evaluate dissolved oxygen concentration within the heterogeneous materials, and was found to be in good agreement with the numerical solution. In addition, a separate analytical solution was obtained to investigate the oxygen pressure drop (OPD) along the cell layer due to oxygen uptake of cells, with experimental validation of the OPD model carried out using human umbilical vein endothelial cells cultured in a PDMS microfluidic oxygenator. Within the theoretical framework, the effects of several microfluidic oxygenator design parameters were studied, including cell type and critical device dimensions.