Fabrication and Characterisation of Rutile-TiO_2 Coatings on Metallic Alloy Substrates

RUTILE-TJO2is a versatile material possessing manyinteresting physical,chemical,optical and dielectricproperties[l].It is also a good tribological material thatcan offer low friction and low wear rate[2,3].However,the application of rutile in the tribological field hasbeen limited to titanium alloys only so far,for example,by thermal oxidation of titanium alloys[4,5].Very fewinvestigations have been directed to the tribologicalapplications of rutile films on substrates other thantitanium al…     

The pitting corrosion of sputtered Fe base alloy films

Predominantly single phase Fe base alloy films were prepared by a DC sputtering method. The compositions of the alloy films, as determined by Auger electron spectroscopy (AES) were Fe-7 at% Cr and Fe-18 at% Cr, Fe-11 at% W and Fe-19 at% W, Fe-9, −13 and −27 at% Ta. The pitting potential of the sputtered alloys determined in chloride solutions was found to be strongly dependent on the nature and the concentration of the alloying element. The pitting potential of sputtered Fe-18 at% Cr and Fe-27 at% Ta alloy films were approximately 0.9 V higher than that of bulk Fe and 0.6 V higher than that of Fe-19 at% W alloy film. A very good correlation was found between the pitting potential of Fe alloy films and the solubility of an alloying element oxide in acidic solutions with a pH corresponding to that within the stable pits of pure Fe (pH = 2). The pitting potential of the Fe alloy was found to increase with a decrease in the solubility of the alloying element oxide in acidic solutions. The pitting potentials of the sputtered Fe-7 at% Cr and Fe-18 at% Cr alloy films were were significantly higher than those of the bulk materials with the same composition. The higher pitting potentials of these alloy films are tentatively attributed to the presence of very fine particles of the oxide phase that are homogeneously distributed in the sputtered alloys.     

Combining the evidences of temporal and spectral enhancement techniques for improving the performance of Indian language identification system in the presence of background noise

Language Identification has gained significant importance in recent years, both in research and commercial market place, demanding an improvement in the ability of machines to distinguish between languages. Although methods like Gaussian mixture models, hidden Markov models and neural networks are used for identifying languages the problem of language identification in noisy environments could not be addressed so far. This paper addresses the performance of automatic language identification system in noisy environments. A comparative performance analysis of speech enhancement techniques like minimum mean squared estimation, spectral subtraction and temporal processing, with different types of noise at different SNRs, is presented here. Though these individual enhancement techniques may not yield good performance with different types of noise at different SNRs, it is proposed to combine the evidences of all these techniques to improve the overall performance of the system significantly. The language identification studies are performed using IITKGP-MLILSC (IIT Kharagpur-Multilingual Indian Language Speech Corpus) databases which consists of 27 languages.     

Accuracy vs Efficiency Trade-offs in Optical Flow Algorithms

There have been two thrusts in the development of optical flow algorithms. One has emphasized higher accuracy; the other faster implementation. These two thrusts, however, have been independently pursued, without addressing the accuracy vs efficiency trade-offs. Although the accuracy–efficiency characteristic is algorithm dependent, an understanding of a general pattern is crucial in evaluating an algorithm as far as real-world tasks are concerned, which often pose various performance requirements. This paper addresses many implementation issues that have often been neglected in previous research, including temporal filtering of the output stream, algorithms' flexibility, and robustness to noise, subsampling, etc. Their impacts on accuracy and/or efficiency are emphasized. We present a survey of different approaches toward the goal of higher performance and present experimental studies on accuracy vs efficiency trade-offs. A detailed analysis of how this trade-off affects algorithm design is manifested in a case study involving two state-of-the-art optical flow algorithms: a gradient and a correlation-based method. The goal of this paper is to bridge the gap between the accuracy- and the efficiency-oriented approaches.     

Aligned texture map creation for pose invariant face recognition

In last years, Face recognition based on 3D techniques is an emergent technology which has demonstrated better results than conventional 2D approaches. Using texture (180° multi-view image) and depth maps is supposed to increase the robustness towards the two main challenges in Face Recognition: Pose and illumination. Nevertheless, 3D data should be acquired under highly controlled conditions and in most cases depends on the collaboration of the subject to be recognized. Thus, in applications such as surveillance or control access points, this kind of 3D data may not be available during the recognition process. This leads to a new paradigm using some mixed 2D-3D face recognition systems where 3D data is used in the training but either 2D or 3D information can be used in the recognition depending on the scenario. Following this concept, where only part of the information (partial concept) is used in the recognition, a novel method is presented in this work. This has been called Partial Principal Component Analysis (P²CA) since they fuse the Partial concept with the fundamentals of the well known PCA algorithm. This strategy has been proven to be very robust in pose variation scenarios showing that the 3D training process retains all the spatial information of the face while the 2D picture effectively recovers the face information from the available data. Furthermore, in this work, a novel approach for the automatic creation of 180° aligned cylindrical projected face images using nine different views is presented. These face images are created by using a cylindrical approximation for the real object surface. The alignment is done by applying first a global 2D affine transformation of the image, and afterward a local transformation of the desired face features using a triangle mesh. This local alignment allows a closer look to the feature properties and not the differences. Finally, these aligned face images are used for training a pose invariant face recognition approach (P²CA).     

Distributed evolutionary multi-objective mesh-partitioning algorithm for parallel finite element computations

Majority of the mesh-partitioning algorithms attempt to optimise the interprocessor communications, while balancing the computational load among the processors. However, it is desirable to simultaneously optimise the submesh aspect ratios in order to significantly improve the convergence characteristics of the domain decomposition based Preconditioned-conjugate-gradient algorithms, being used extensively in the state-of-the-art parallel finite element codes. Keeping this in view, a new distributed multi-objective mesh-partitioning algorithm using evolutionary computing techniques is proposed in this paper. Effectiveness of the proposed distributed mesh-partitioning algorithm is demonstrated by solving several unstructured meshes of practical-engineering problems and also benchmark problems.     

ILP-assisted de novo drug design

The accurate and early detection of epileptic seizures in continuous electroencephalographic (EEG) data has a growing role in the management of patients with epilepsy. Early detection allows for therapy to be delivered at the start of seizures and for caregivers to be notified promptly about potentially debilitating events. The challenge to detecting epileptic seizures, however, is that seizure morphologies exhibit considerable inter-patient and intra-patient variability. While recent work has looked at addressing the issue of variations across different patients (inter-patient variability) and described patient-specific methodologies for seizure detection, there are no examples of systems that can simultaneously address the challenges of inter-patient and intra-patient variations in seizure morphology. In our study, we address this complete goal and describe a multi-task learning approach that trains a classifier to perform well across many kinds of seizures rather than potentially overfitting to the most common seizure types. Our approach increases the generalizability of seizure detection systems and improves the tradeoff between latency and sensitivity versus false positive rates. When compared against the standard approach on the CHB–MIT multi-channel scalp EEG data, our proposed method improved discrimination between seizure and non-seizure EEG for almost 83 % of the patients while reducing false positives on nearly 70 % of the patients studied.     

On the formation of the diamond grain configuration during high temperature creep and fatigue

A study has been made of the influence of test variables on the formation of the diamond grain configuration during high temperature creep and fatigue deformation of a wide variety of metals. The proposed mechanisms for the formation of this interesting grain morphology are reviewed. It is concluded that the diamond grain configuration arises from a balance between grain-boundary sliding, grain-boundary mobility, intragranular deformation and defect imbalance across the grain boundaries and that it tends to be stabilized by intergranular cavitation. While the phenomenon occurs during high temperature fatigue in a variety of metals irrespective of their crystal structure, during creep it has been observed only in to h c p metals. It is surmised that the occurrence of the diamond array of grain boundaries during creep deformation in h c p metals is aided by the limited number of slip systems which leads to high defect imbalances in adjacent grains and consequently high driving forces for grain-boundary migration. On the basis of quantitative metallography involving measurements of the number of edges per grain section, the number of grains meeting at vertices, angular distribution histograms and grain-boundary lengths in different angular orientations with respect to the stress axis in "annealed" and "diamond" microstructures, it is concluded that the shape of the "diamond" grain is essentially the same as that of the "annealed" grain but in a distorted form.     

A blur-robust descriptor with applications to face recognition

Understanding the effect of blur is an important problem in unconstrained visual analysis. We address this problem in the context of image-based recognition by a fusion of image-formation models and differential geometric tools. First, we discuss the space spanned by blurred versions of an image and then, under certain assumptions, provide a differential geometric analysis of that space. More specifically, we create a subspace resulting from convolution of an image with a complete set of orthonormal basis functions of a prespecified maximum size (that can represent an arbitrary blur kernel within that size), and show that the corresponding subspaces created from a clean image and its blurred versions are equal under the ideal case of zero noise and some assumptions on the properties of blur kernels. We then study the practical utility of this subspace representation for the problem of direct recognition of blurred faces by viewing the subspaces as points on the Grassmann manifold and present methods to perform recognition for cases where the blur is both homogenous and spatially varying. We empirically analyze the effect of noise, as well as the presence of other facial variations between the gallery and probe images, and provide comparisons with existing approaches on standard data sets.     

Neutral shift [five years of continuous operation with adjustable frequency drives]

The combined efforts of the AFD supplier and end-user have resulted in an extremely reliable electrical adjustable speed drive system. Almost three years into the run of the first unit, all parties are confident of the ability to meet the five-year run target that was identified at the outset. The redundancy of the power cells in this particular design, together with the neutral shift control has practically eliminated the power components as a source of operational failure. Future development efforts will include applying redundancy and fault tolerance to the drive control processor to further enhance system reliability.