Lattice Boltzmann method simulation of electroosmotic stirring in a microscale cavity

The suitable surface modification of microfluidic channels can enable a neutral electrolyte solution to develop an electric double layer (EDL). The ions contained within the EDL can be moved by applying an external electric field, inducing electroosmotic flows (EOFs) that results in associated stirring. This provides a solution for the rapid mixing required for many microfluidic applications. We have investigated EOFs generated by applying a steady electric field across a square cavity that has homogenous electric potentials along its walls. The flowfield is simulated using the lattice Boltzmann method. The extent of mixing is characterized for different electrode configurations and electric field strengths. We find that rapid mixing can be achieved by using this simple configuration which increases with increasing electric field strength. The mixing time for water-soluble organic molecules can be decreased by four orders of magnitude by suitable choice of wall zeta potential and electric field. We dedicate this paper to the memory of our colleagues Professors Kevin Granata and Liviu Librescu who fell tragically on April 16, 2007 while answering their call to serve higher education. They continue to inspire us. AM gratefully acknowledges support from Jadavpur University under the World Bank funded Technical Education Quality Improvement Programme of the Government of India and the hospitality of the Virginia Tech ESM Department where he conducted a portion of this work.     

Expressions Recognition of North-East Indian (NEI) Faces

Facial expression is one of the major distracting factors for face recognition performance. Pose and illumination variations on face images also influence the performance of face recognition systems. The combination of three variations (facial expression, pose and illumination) seriously degrades the recognition accuracy. In this paper, three experimental protocols are designed in such a way that the successive performance degradation due to the increasing variations (expressions, expressions with illumination effect and expressions with illumination and pose effect) on face images can be examined. The whole experiment is carried out using North-East Indian (NEI) face images with the help of four well-known classification algorithms namely Linear Discriminant Analysis (LDA), K-Nearest Neighbor algorithm (KNN), combination of Principal Component Analysis and Linear Discriminant Analysis (PCA + LDA), combination of Principal Component Analysis and K-Nearest Neighbor algorithm (PCA + KNN). The experimental observations are analyzed through confusion matrices and graphs. This paper also describes the creation of NEI facial expression database, which contains visual static face images of different ethnic groups of the North-East states. The database is useful for future researchers in the area of forensic science, medical applications, affective computing, intelligent environments, lie detection, psychiatry, anthropology, etc.     

On robustness against JPEG2000: a performance evaluation of wavelet-based watermarking techniques

With the emergence of new scalable coding standards, such as JPEG2000, multimedia is stored as scalable coded bit streams that may be adapted to cater network, device and usage preferences in multimedia usage chains providing universal multimedia access. These adaptations include quality, resolution, frame rate and region of interest scalability and achieved by discarding least significant parts of the bit stream according to the scalability criteria. Such content adaptations may also affect the content protection data, such as watermarks, hidden in the original content. Many wavelet-based robust watermarking techniques robust to such JPEG2000 compression attacks are proposed in the literature. In this paper, we have categorized and evaluated the robustness of such wavelet-based image watermarking techniques against JPEG2000 compression, in terms of algorithmic choices, wavelet kernel selection, subband selection, or watermark selection using a new modular framework. As most of the algorithms use a different set of parametric combination, this analysis is particularly useful to understand the effect of various parameters on the robustness under a common platform and helpful to design any such new algorithm. The analysis also considers the imperceptibility performance of the watermark embedding, as robustness and imperceptibility are two main watermarking properties, complementary to each other.     

Visual requirements analytics: a framework and case study

For many software projects, keeping requirements on track needs an effective and efficient path from data to decision. Visual analytics creates such a path that enables the human to extract insights by interacting with the relevant information. While various requirements visualization techniques exist, few have produced end-to-end value to practitioners. In this paper, we advance the literature on visual requirements analytics by characterizing its key components and relationships in a framework. We follow the goal–question–metric paradigm to define the framework by teasing out five conceptual goals (user, data, model, visualization, and knowledge), their specific operationalizations, and their interconnections. The framework allows us to not only assess existing approaches, but also create tool enhancements in a principled manner. We evaluate our enhanced tool support through a case study where massive, heterogeneous, and dynamic requirements are processed, visualized, and analyzed. Working together with practitioners on a contemporary software project within its real-life context leads to the main finding that visual analytics can help tackle both open-ended visual exploration tasks and well-structured visual exploitation tasks in requirements engineering. In addition, the study helps the practitioners to reach actionable decisions in a wide range of areas relating to their project, ranging from theme and outlier identification, over requirements tracing, to risk assessment. Overall, our work illuminates how the data-to-decision analytical capabilities could be improved by the increased interactivity of requirements visualization.     

Thermal,morphological, and mechanical characterization of novel carbon nanofiber‐filled bismaleimide composites

Novel carbon nanofiber (CNF) ‐filled bismalemide composites were fabricated by a thermokinetic mixing method. The thermal and mechanical properties of composites containing 1 wt % and 2 wt % CNFs were investigated. Thermogravimetric analysis demonstrated that minimal improvement in thermal stability of the nanocomposites was obtained by the addition of CNFs. Dynamic mechanical analysis showed an increase in storage modulus (E′) and glass transition temperature (T_g) upon incorporation of nanofibers. Limiting oxygen index (LOI) has also been found to increase with incorporation of CNFs. Morphological studies of fractured surfaces of the composites has been carried out by scanning electron microscopy to determine the effect of fiber content and dispersion on the failure mechanism. In general, good dispersion was observed, along with agglomeration at some points and some fiber matrix interfacial debonding. A decrease in mechanical strength has been observed and debonding was found as the main failure mechanism. Further research outlook is also presented. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Sensitivity importance‐based robust optimization of structures with incomplete probabilistic information

Robust design optimization (RDO) is usually performed by minimizing the nominal value of a performance function and its dispersion considering equal importance to each individual gradient of the performance function. However, it is well known that all gradients are not equally important. An efficient sensitivity importance‐based RDO technique is proposed in the present study for optimum design of structures characterized by bounded uncertain input parameters. The basic idea of the proposed RDO formulation is to improve the robustness of a performance function by using a new gradient index that utilizes the importance factors proportional to the importance of the gradients of the performance function. The same concept is also extended to the constraints. To enhance the robustness of the constraints, the constraint functions are also modified by using the importance factor proportional to the importance of the associated gradient of the constraint. Because all the variables are not equally important to capture the presence of uncertainty, an improved robust solution is obtained by the proposed approach compared with the conventional RDO approach. The present formulation is illustrated with the help of three informative examples. The results are compared with the conventional RDO results to study the effectiveness of the proposed RDO approach. Copyright © 2012 John Wiley & Sons, Ltd.