On the optimal cooling strategy for variable‐speed continuous casting

In this paper, we consider the inverse problem of determining the optimal cooling parameters for continuous casting under changing casting speed. We rely on automatic differentiation to support different search methods for the parameter values that will minimize a given cost functional, which can include a variety of criteria: surface temperature evolution and variation, interface position, full solidification point. In the direct problem we use a fixed‐domain transformation to solve the corresponding free‐boundary problem to high accuracy. Numerical experiments are provided to illustrate and support the effectiveness of the present concept. Copyright © 2001 John Wiley & Sons, Ltd.     

Forced migration of soluble and suspended materials by freezing front in aqueous systems

Migration of soluble and suspended materials by directional freezing of aqueous systems has been studied qualitatively. Slow freezing was employed vertically as well as horizontally through solutions and suspensions. In all cases, the impurities (soluble salts as well as suspended materials) were appreciably forced out by dynamic freezing front. The phenomenon worked for concentrating/separating inorganic ions, soluble organic compounds and dyes in synthetic solutions as well as in natural streams. Various analytical techniques were employed to monitor the migrating species through the freezing media. It was found that separation efficiency depends on different factors like rate of cooling, pH and concentration. Model experiments were designed and exercised successfully to employ the technique for treatment of dye-polluted water.     

3D Model compression using Connectivity-Guided Adaptive Wavelet Transform built into 2D SPIHT

Connectivity-Guided Adaptive Wavelet Transform based mesh compression framework is proposed. The transformation uses the connectivity information of the 3D model to exploit the inter-pixel correlations. Orthographic projection is used for converting the 3D mesh into a 2D image-like representation. The proposed conversion method does not change the connectivity among the vertices of the 3D model. There is a correlation between the pixels of the composed image due to the connectivity of the 3D mesh. The proposed wavelet transform uses an adaptive predictor that exploits the connectivity information of the 3D model. Known image compression tools cannot take advantage of the correlations between the samples. The wavelet transformed data is then encoded using a zero-tree wavelet based method. Since the encoder creates a hierarchical bitstream, the proposed technique is a progressive mesh compression technique. Experimental results show that the proposed method has a better rate distortion performance than MPEG-3DGC/MPEG-4 mesh coder.     

Increasing the toughness of nylon 12 by the incorporation of functionalized graphene

The effect of functionalized graphene (FG) on the mechanical properties, especially toughness, of nylon12 was investigated. The results revealed that the incorporation of a very small amount (about 0.6 wt%) of the FG caused a significant improvement in ultimate tensile strength, elongation, impact strength and toughness. With 0.6 wt% FG ultimate tensile strength and elongation at break of the nylon 12 are improved by ∼35% and ∼200%, respectively. The K_Ic of the nylon 12 is ∼1.28 MPa m^0.5 and the incorporation of 0.6 wt% FG causes a significant increase of 72% (∼2.2 MPa m^0.5). 0.6 wt% FG also causes a significant improvement of 175% in impact failure energy of the nylon 12. The incorporation of FG resulted in an increase in amount of γ-phase of nylon12 which could be the direct reason for the increase of toughness.     

Challenges in Developing a Bessel-Beam Based Ultrafast Ablation Probe

Instruments and Experimental Techniques - With its elongated depth of focus, Bessel beams offer rapid and high aspect ratio ablation capability, in contrast to Gaussian beam counterparts. In this...     

Machine learning for post-traumatic stress disorder identification utilizing resting-state functional magnetic resonance imaging

Early detection of post-traumatic stress disorder (PTSD) is essential for proper treatment of the patients to recover from this disorder. The aligned purpose of this study was to investigate the performance deviations in regions of interest (ROI) of PTSD than the healthy brain regions, to assess interregional functional connectivity and applications of machine learning techniques to identify PTSD and healthy control using resting-state functional magnetic resonance imaging (rs-fMRI). The rs-fMRI data of 10 ROI was extracted from 14 approved PTSD subjects and 14 healthy controls. The rs-fMRI data of the selected ROI were used in ANOVA to measure performance level and Pearson's correlation to investigate the interregional functional connectivity in PTSD brains. In machine learning approaches, the logistic regression, K-nearest neighbor (KNN), support vector machine (SVM) with linear, radial basis function, and polynomial kernels were used to classify the PTSD and control subjects. The performance level in brain regions of PTSD deviated as compared to the regions in the healthy brain. In addition, significant positive or negative functional connectivity was observed among ROI in PTSD brains. The rs-fMRI data have been distributed in training, validation, and testing group for maturity, implementation of machine learning techniques. The KNN and SVM with radial basis function kernel were outperformed for classification among other methods with high accuracies (96.6%, 94.8%, 98.5%) and (93.7%, 95.2%, 99.2%) to train, validate, and test datasets, respectively. The study's findings may provide a guideline to observe performance and functional connectivity of the brain regions in PTSD and to discriminate PTSD subject using only the suggested algorithms.     

Characterization of a Cohesive Soil Bed using a Cone Pressuremeter

A new cone pressuremeter has been developed at the University of Engineering and Technology, Lahore-Pakistan. The new device is called the Akbar Pressuremeter (APMT). This paper is based on the APMT testing of a cohesive soil deposit comprised of low plastic lean clay (CL) to sandy silty clay (CL-ML). The APMT testing, using a full-displacement technique, standard penetration tests and undisturbed samples, was carried out at two locations. The soil strength and type were determined using the undisturbed samples. The applied pressure-cavity strain curves of the APMT tests performed at different levels were analysed to determine soil strength and stiffness. The undrained shear strength of the undisturbed samples was determined in the laboratory by unconfined compression tests. This paper provides a comparison of the parameters interpreted from the pressuremeter and those determined from other field and laboratory methods.     

Identification of Secretory Compounds from the European Callipodidan Species <Emphasis Type="Italic">Apfelbeckia insculpta</Emphasis>

Defensive secretions of the callipodidan species Apfelbeckia insculpta contain a p-cresol as the main component and phenol in traces. This is the first identification of these compounds in a European callipodidan species. The repugnatory glands of A. insculpta are of the spirobolid type and consist of a spherical reservoir, a simple duct, and a valvular cuticular infolding that opens onto the lateral surface of the millipede via a pore.     

RETRACTED ARTICLE: Document image analysis: issues,comparison of methods and remaining problems

Image analysis is an interesting research area with a large variety of challenging applications. Researchers have worked from decades on this topic, as witnessed by the scientific literature. However, document image analysis is the special case in image analysis as their spatial properties are different from natural images. Therefore, the main focus of this paper is to describe image denoising issues in general and document image issues in particular. Since the field of document processing is relatively new, it is also dynamic, so current methods have room for improvement and innovations are still being made. Several algorithms proposed in the literature are described. Critical discussions are reported about the current status of the field and open problems are highlighted. It is also demonstrated that, there are rarely definitive techniques for all cases of a certain problem. We surveyed the state of art, analyzed recent trends and tried to identify challenges for future research in this field.