Denoising and Dehazing an Image in a Cascaded Pattern for Continuous Casting

Automatic vision systems have been widely used in the continuous casting of the steel industry, which improve efficiency and reduce labor. At present, high temperatures with evaporating fog cause images to be noisy and hazy, impeding the usage of advanced machine learning algorithms in this task. Instead of considering denoising and dehazing separately like previous papers, we established that by taking advantage of deep learning in a modeling complex formulation, our proposed algorithm, called Cascaded Denoising and Dehazing Net (CDDNet) reduces noise and hazy in a cascading pattern. Experimental results on both synthesized images and a pragmatic video from a continuous casting factory demonstrate our method’s superior performance in various metrics. Compared with existing methods, CDDNet achieved a 50% improvement in terms of peak signal-to-noise ratio on the validation dataset, and a nearly 5% improvement on a dataset that has never seen before. Besides, our model generalizes so well that processing a video from an operating continuous casting factory with CDDNet resulted in high visual quality.

Improvising Improperly

Chapter 8 is attentive to the innovation that women writers from around the world are introducing into their work in French. It explores how certain books depict inappropriate behavior in inventive textual turns that are transgressive but also transformative, ultimately allowing for the complex formulation of truths that are so often elided in euphemistic writings. Many of the writers who have come to France have encountered prejudice in various forms that they address in their work. They portray racial discrimination and gender bias, and they contemplate the plight of migrants in Europe at a time of political change. Theatrical metaphors frequently emerge in the work of authors who describe encounters in performative terms, emphasizing how the script their characters are assigned appears to preclude all forms of improvisation. Despite the difficulties of this vocation, many women writers describe a compulsion to compose literary works, an irresistible pressure to take up the pen that propels them to write, even when their texts meet with criticism and misunderstandings. The role of generic categorizations often predetermines textual interpretations in ways that mirror the confining societal categorizations these authors represent in their writing. The fictional space of literary creations nonetheless allows for the creative staging of unacceptable actions in which characters from elsewhere who have experienced trauma effectively act out, demonstrating the pent-up frustration and releasing the tension that has accumulated in a setting where they are often not afforded the opportunity to express themselves verbally.

Stein interpolation for the real interpolation method

We prove a complex formulation of the real interpolation method, showing that the real and complex interpolation methods are not inherently real or complex. Using this complex formulation, we prove Stein interpolation for the real interpolation method. We apply this theorem to interpolate weighted $$L^p$$ L p -spaces and the sectoriality of closed operators with the real interpolation method.

Exact Path Synthesis of RCCC linkages for a Maximum of Nine Prescribed Positions

This paper addresses the path synthesis of RCCC linkages, a problem that has not given due attention in the literature. Compared with planar and spherical four-bar linkages, a RCCC linkage has many more design parameters, which leads to a complex formulation of the path-synthesis problem and, consequently, to a quite challenging system of algebraic equations. In this paper, the problem is solved with a novel formulation of path synthesis for visiting a number of prescribed positions. This is achieved by means of an alternative coordinate system, with which point coordinates are expressed with the aid of two vectors fixed to the same body. By this means, the rotation matrix used to represent the coupler-link attitude is obviated. The synthesis equations are then formulated in a simple form. The new formulation confirms that path synthesis admits exact solutions for up to nine prescribed positions, which proves a landmark claim submitted by Burmester. Examples are included to demonstrate the path-synthesis procedure with the method thus developed.

Anti-vibrio effects of the precious Tibetan pill, Rinchen Drangjor Rilnag Chenmo (RDRC)

Tibetan precious pills are an integral part of TTM (Traditional Tibetan Medicine). Among them, Rinchen Drangjor Rilnag Chenmo (RDRC) has been named “King of Precious Pills” due to its efficacy in treating a multitude of human disorders. RDRC has a complex formulation with about 140 ingredients, mostly from medicinal plants and a few precious stones and metals. Not many studies have been done on the experimental validation of antimicrobial properties of this important pill. The current study investigated the antimicrobial activity of the extracts of RDRC. Both aqueous and chloroform extracts were evaluated for their antibacterial potential against a total of seven different bacterial species, which are pathogenic, including three species of Vibrio, viz. V. vulnificus, V. parahaemolyticus and V. harveyi using the well-diffusion method and also by assessing MIC and MBC values. Its antifungal potential was also studied against two fungal strains Aspergillus niger and Talaromyces islandicus. It was found that the chloroform extract of RDRC exerted a positive antibacterial effect on all the Vibrio species tested, and the least MIC of 3.33 mg/ml was observed for V. parahaemolyticus. This is the first study of its kind on the anti-Vibrio effect of the Tibetan precious pill, Rinchen Drangjor Rilnag Chenmo.

SOCIAL NETWORKS USER CLASSIFICATION FOR PROFESSIONAL ORIENTATION

The article deals with a complex formulation of the topic social networks users classification to determine professional orientation.

Synergic effect of metallic fillers as heat dissipaters in the tribological performance of a nonasbestos disk brake pad

Brake friction linings are made of materials with a highly complex formulation that helps in improving the braking performance. The selection of friction materials with good physical, mechanical, and thermal properties is vital, which will decide the braking performance. Apart from giving good physio-mechanical properties, metallic fillers act as heat dissipaters. The objective of this work is to study the synergetic effect of prominent heat dissipaters, namely copper fibers, brass fibers, and zinc powders. Three simplified formulations were developed with 10, 14, and 18 wt.% of these heat dissipaters and named DB1, DB2, and DB3, respectively. It was observed that the addition of heat dissipaters increased the thermal properties. Tribological properties are tested based on SAE J661 standards. It was observed that DB2 had a consistent and higher coefficient of friction of 0.503 with a higher wear rate (7.6%) while DB3 had adequate μ and lower wear rate. The same batches of brake pads were tested in an inertia brake dynamometer following JASO C406 and a wear test was carried out. It was observed that % fade and % recovery were better for DB2 in both cycles. The wear rate in terms of thickness was lesser for DB2 followed by DB1 and DB3. The wear mechanism was analyzed using a scanning electron microscope. The preference selection index method of optimization was used to evaluate the overall performance parameters of the brake friction composites. Heat dissipaters with 14 wt.% have proved to be the better performers, followed by 10 and 18 wt.%.

Modelling surface evolution in abrasive jet micromachining using level set methods

The time dependent surface evolution in abrasive jet micromachining (AJM) is described by a partial differential equation which is difficult to solve using analytical or traditional numerical techniques. These techniques can yield incorrect predicted profile evolution or fail altogether under certain conditions. More recently developed particle tracking cellular automaton simulations can address some of these limitations but are difficult to implement and are computationally expensive. In this work, level set methods (LSM) were introduced to develop novel surface evolution models to predict resulting feature shapes in AJM. Initially, a LSM-based numerical model was developed to predict the surface evolution of unmasked channels machined at normal and oblique jet impact angles (incidence), as well as masked micro-channels and micro-holes at normal incidence, in both brittle and ductile targets. This model was then extended to allow the prediction of: surface evolution of inclined masked micro-channels made using AJM at oblique incidence, where the developing profiles rapidly become multi-valued necessitating a more complex formulation; mask erosive wear by permitting surface evolution of both the mask and target micro-channels simultaneously at any jet incidence; and surface damage due to secondary particle strikes in brittle target micro-channels resulting from particle mask-to-target and target-to-target ricochets at any jet incidence. For all the models, a general ‘masking’ function was developed by applying previous concepts to model the adjustment to abrasive mass flux incident to the target or mask surfaces to reflect the range of particle sizes that are ‘visible’ to these surfaces. The models were also optimized for computational efficiency using an adaptive Narrow Band LSM scheme. All models were experimentally verified and, where possible, compared against existing models. Generally, good predictive capabilities and improvements over previous attempts in terms of feature prediction or execution time, were observed. The time dependent surface evolution in abrasive jet micromachining (AJM) is described by a partial differential equation which is difficult to solve using analytical or traditional numerical techniques. These techniques can yield incorrect predicted profile evolution or fail altogether under certain conditions. More recently developed particle tracking cellular automaton simulations can address some of these limitations but are difficult to implement and are computationally expensive.In this work, level set methods (LSM) were introduced to develop novel surface evolution models to predict resulting feature shapes in AJM. Initially, a LSM-based numerical model was developed to predict the surface evolution of unmasked channels machined at normal and oblique jet impact angles (incidence), as well as masked micro-channels and micro-holes at normal incidence, in both brittle and ductile targets.This model was then extended to allow the prediction of: surface evolution of inclined masked micro-channels made using AJM at oblique incidence, where the developing profiles rapidly become multi-valued necessitating a more complex formulation; mask erosive wear by permitting surface evolution of both the mask and target micro-channels simultaneously at any jet incidence; and surface damage due to secondary particle strikes in brittle target micro-channels resulting from particle mask-to-target and target-to-target ricochets at any jet incidence. For all the models, a general ‘masking’ functionwas developed by applying previous concepts to model the adjustment to abrasive mass flux incident to the target or mask surfaces to reflect the range of particle sizes that are ‘visible’ to these surfaces. The models were also optimized for computational efficiency using an adaptive Narrow Band LSM scheme.All models were experimentally verified and, where possible, compared against existing models. Generally, good predictive capabilities and improvements over previous attempts in terms of feature prediction or execution time, were observed.The proposed LSM-based models can be practical assistive tools during the micro-fabrication of complex MEMS and microfluidic devices using AJM.

Modelling surface evolution in abrasive jet micromachining using level set methods

The time dependent surface evolution in abrasive jet micromachining (AJM) is described by a partial differential equation which is difficult to solve using analytical or traditional numerical techniques. These techniques can yield incorrect predicted profile evolution or fail altogether under certain conditions. More recently developed particle tracking cellular automaton simulations can address some of these limitations but are difficult to implement and are computationally expensive. In this work, level set methods (LSM) were introduced to develop novel surface evolution models to predict resulting feature shapes in AJM. Initially, a LSM-based numerical model was developed to predict the surface evolution of unmasked channels machined at normal and oblique jet impact angles (incidence), as well as masked micro-channels and micro-holes at normal incidence, in both brittle and ductile targets. This model was then extended to allow the prediction of: surface evolution of inclined masked micro-channels made using AJM at oblique incidence, where the developing profiles rapidly become multi-valued necessitating a more complex formulation; mask erosive wear by permitting surface evolution of both the mask and target micro-channels simultaneously at any jet incidence; and surface damage due to secondary particle strikes in brittle target micro-channels resulting from particle mask-to-target and target-to-target ricochets at any jet incidence. For all the models, a general ‘masking’ function was developed by applying previous concepts to model the adjustment to abrasive mass flux incident to the target or mask surfaces to reflect the range of particle sizes that are ‘visible’ to these surfaces. The models were also optimized for computational efficiency using an adaptive Narrow Band LSM scheme. All models were experimentally verified and, where possible, compared against existing models. Generally, good predictive capabilities and improvements over previous attempts in terms of feature prediction or execution time, were observed. The time dependent surface evolution in abrasive jet micromachining (AJM) is described by a partial differential equation which is difficult to solve using analytical or traditional numerical techniques. These techniques can yield incorrect predicted profile evolution or fail altogether under certain conditions. More recently developed particle tracking cellular automaton simulations can address some of these limitations but are difficult to implement and are computationally expensive.In this work, level set methods (LSM) were introduced to develop novel surface evolution models to predict resulting feature shapes in AJM. Initially, a LSM-based numerical model was developed to predict the surface evolution of unmasked channels machined at normal and oblique jet impact angles (incidence), as well as masked micro-channels and micro-holes at normal incidence, in both brittle and ductile targets.This model was then extended to allow the prediction of: surface evolution of inclined masked micro-channels made using AJM at oblique incidence, where the developing profiles rapidly become multi-valued necessitating a more complex formulation; mask erosive wear by permitting surface evolution of both the mask and target micro-channels simultaneously at any jet incidence; and surface damage due to secondary particle strikes in brittle target micro-channels resulting from particle mask-to-target and target-to-target ricochets at any jet incidence. For all the models, a general ‘masking’ functionwas developed by applying previous concepts to model the adjustment to abrasive mass flux incident to the target or mask surfaces to reflect the range of particle sizes that are ‘visible’ to these surfaces. The models were also optimized for computational efficiency using an adaptive Narrow Band LSM scheme.All models were experimentally verified and, where possible, compared against existing models. Generally, good predictive capabilities and improvements over previous attempts in terms of feature prediction or execution time, were observed.The proposed LSM-based models can be practical assistive tools during the micro-fabrication of complex MEMS and microfluidic devices using AJM.

A Systematic Approach in the Development of the Morphologically-Directed Raman Spectroscopy Methodology for Characterizing Nasal Suspension Drug Products

Demonstrating bioequivalence (BE) of nasal suspension sprays is a challenging task. Analytical tools are required to determine the particle size of the active pharmaceutical ingredient (API) and the structure of a relatively complex formulation. This study investigated the utility of the morphologically-directed Raman spectroscopy (MDRS) method to investigate the particle size distribution (PSD) of nasal suspensions. Dissolution was also investigated as an orthogonal technique. Nasal suspension formulations containing different PSD of mometasone furoate monohydrate (MFM) were manufactured. The PSD of the MFM batches was characterized before formulation manufacture using laser diffraction and automated imaging. Upon formulation manufacture, the droplet size, single actuation content, spray pattern, plume geometry, the API dissolution rate, and the API PSD by MDRS were determined. A systematic approach was utilized to develop a robust method for the analysis of the PSD of MFM in Nasonex® and four test formulations containing the MFM API with different particle size specifications. Although the PSD between distinct techniques cannot be directly compared due to inherent differences between these methodologies, the same trend is observed for three out of the four batches. Dissolution analysis confirmed the trend observed by MDRS in terms of PSD. For suspension-based nasal products, MDRS allows the measurement of API PSD which is critical for BE assessment. This approach has been approved for use in lieu of a comparative clinical endpoint BE study [1]. The correlation observed between PSD and dissolution rate extends the use of dissolution as a critical analytical tool demonstrating BE between test and reference products.