Microstructural Characterization and Role of Glassy Layer Developed on Inconel 690 During a Nuclear High-Level Waste Vitrification Process

The interaction of Inconel 690 metallic components with borosilicate melt leads to development of a partially amorphous and a partially crystalline layer within borosilicate melt adjacent to the interface. Such a heterogeneous layer is referred to here as a glassy layer. In the present investigation, the glassy layer is constituted of several phases, e.g. a Cr₂O₃ layer, a Ni₂CrO₄ needle, and NiCr₂O₄ cubic phases. Incorporation of such a glassy layer within the melt pool can lead to significant microstructural changes in the melt. Formation of barium chromate and nickel silicate has been observed in a sodium barium borosilicate melt with excess amount of Cr₂O₃ and NiO, respectively.     

Location and time do matter: A long tail study of website requests

There has been a tremendous growth in the amount and range of information available on the Internet. The users' requests for online information can be captured by a long tail model. A few popular websites enjoy a high number of visitations while the majority of the rest are less frequently requested. In this study we use real world data to investigate this phenomenon and show that both users' physical location and time of access affect the heterogeneity of website requests. The effect can partially be explained by differences in demographic characteristics at locations and diverse user browsing behavior in weekdays and weekends. These results can be used to design better online marketing strategies, affiliate advertising models, and Internet caching algorithms with sensitivities to user location and time of access differences.     

Teaching Real-World Issues through Case Studies*

Engineering students are expected to be not only technically proficient, but, also to exhibit a sound awareness of real-world issues such as marketing, finance, communications, and interpersonal relations. We found that this is best learned by participating in a case study method of instruction. This paper describes the results of a research undertaken by the authors to develop a teaching methodology to bring real-world issues into engineering classrooms. It describes the steps taken in developing an engineering-management case study, administering this case study in a classroom, and results of evaluating the effectiveness of this method of instruction. In particular, it focuses on the students' and professional engineers' perceptions on the utility of the case study method of instruction in engineering classes. The results of the research lead to recommendations to funding agencies and educators on the need to develop interdisciplinary technical case studies so that the innovations happening in the engineering world can be communicated to the students in the classrooms.     

Seamless live migration of virtual machines over the MAN/WAN

The “VM Turntable” demonstrator at iGRID 2005 pioneered the integration of Virtual Machines (VMs) with deterministic “lightpath” network services across a MAN/WAN. The results provide for a new stage of virtualization—one for which computation is no longer localized within a data center but rather can be migrated across geographical distances, with negligible downtime, transparently to running applications and external clients. A noteworthy data point indicates that a live VM was migrated between Amsterdam, NL and San Diego, USA with just 1–2 s of application downtime. When compared to intra-LAN local migrations, downtime is only about 5–10 times greater despite 1000 times higher round-trip times.     

Dynamic pricing of call rates: Bayesian approach

In this paper, we present different cases and their possible solutions in the telecommunications market by incorporating dynamically changing call rates over the channel depending upon the network congestion. Since dynamic pricing of call rates is beneficial from both the perspectives of subscribers and service providers, our solution can significantly help to adapt this pricing mechanism in real market scenario. In order to deploy this scheme, we have incorporated the competing network provider's strategy into the mechanism of deciding dynamic price. Establishment of Nash equilibrium with the competing network provider has stabilized our pricing mechanism.     

3D segmentation of abdominal CT imagery with graphical models,conditional random fields and learning

Probabilistic graphical models have had a tremendous impact in machine learning and approaches based on energy function minimization via techniques such as graph cuts are now widely used in image segmentation. However, the free parameters in energy function-based segmentation techniques are often set by hand or using heuristic techniques. In this paper, we explore parameter learning in detail. We show how probabilistic graphical models can be used for segmentation problems to illustrate Markov random fields (MRFs), their discriminative counterparts conditional random fields (CRFs) as well as kernel CRFs. We discuss the relationships between energy function formulations, MRFs, CRFs, hybrids based on graphical models and their relationships to key techniques for inference and learning. We then explore a series of novel 3D graphical models and present a series of detailed experiments comparing and contrasting different approaches for the complete volumetric segmentation of multiple organs within computed tomography imagery of the abdominal region. Further, we show how these modeling techniques can be combined with state of the art image features based on histograms of oriented gradients to increase segmentation performance. We explore a wide variety of modeling choices, discuss the importance and relationships between inference and learning techniques and present experiments using different levels of user interaction. We go on to explore a novel approach to the challenging and important problem of adrenal gland segmentation. We present a 3D CRF formulation and compare with a novel 3D sparse kernel CRF approach we call a relevance vector random field. The method yields state of the art performance and avoids the need to discretize or cluster input features. We believe our work is the first to provide quantitative comparisons between traditional MRFs with edge-modulated interaction potentials and CRFs for multi-organ abdominal segmentation and the first to explore the 3D adrenal gland segmentation problem. Finally, along with this paper we provide the labeled data used for our experiments to the community.     

POST: a scalable optical data center network

In this paper, we propose a wavelength division multiplexing-based power efficient data center interconnect called Passive Optical Scalable Tree data center network (POST). POST is a highly scalable tree structured network that interconnects thousands of servers and provides low hop count transmission paths among all the servers connected. In POST, we introduced two new switching components that help in routing data passively and efficiently within a POST network. Additionally, we have provided architectural modification to POST, which enhances the reliability of POST in a cost-effective manner. Our simulation results prove that POST provides a low average delay compared with traditional data center networks and the scalability of POST increases as the north–south traffic in the data center increases.     

Trichoderma harzianum‐based novel formulations: potential applications for management of Next‐Gen agricultural challenges

Fungi of the Trichoderma spp. genus, notably Trichoderma harzianum, are commonly used for biological management of deleterious seed‐ and soil‐borne pathogens. The global biopesticides market is booming with a major share of various commercial formulations of T. harzianum. However, there are some major drawbacks associated with these commercial formulations including short shelf life, low on‐field stability and irregular performance in different agro‐climatic regions. For effectively resolving these issues, new strategies are urgently required for efficient management of pathogens. The present review provides an overview of the use of Trichoderma spp., with special emphasis on T. harzianum, and discusses future trends for biological control. Technologies are described for the microencapsulation of fungi and for the biogenic synthesis of nanoparticles, with the aim of improving the biological control of pathogens and contributing to sustainable agricultural practices. © 2018 Society of Chemical Industry     

Predictive topography model for shape adaptive grinding of metal matrix composites

Compliant finishing (e.g. shape adaptive grinding) can routinely achieve nanoscale roughness on diverse metal and ceramic materials. However, when processing multiphase materials consisting of distinct phases with different mechanical properties, non-uniform material removal often occurs and the inherent mechanism remains unclear. Here, a deterministic and stochastic model to predict processed surface topography is derived from the different material removal behaviours across phases. Experimental topographies, profiles and roughness on three selected Si-SiC samples show high consistency with theoretical predictions. Both model and experiments indicate that improved and stable surface finish can be achieved on metal matrix composites with small grain size.