Using solidification parameters to predict porosity distributions in alloy castings

Quality criteria used in the computer-aided design and analysis of casting processes typically relate geometric, thermal, or solidification parameters to structural features such as centerline shrinkage and microporosity. Quality criteria for the prediction of porosity in castings have been used successfully in steel, but the application of criteria functions to nonferrous alloys has been less successful. Recent work suggests that the dominating mechanism that determines the amount and distribution of porosity in castings is strongly dependent on the solidification mode of the alloy and the solidification conditions. Accordingly, casting processes and alloy types are divided into four groups, and a different set of criteria functions are obtained for each group.     

Model driven middleware: A new paradigm for developing distributed real-time and embedded systems

Distributed real-time and embedded (DRE) systems have become critical in domains such as avionics (e.g., flight mission computers), telecommunications (e.g., wireless phone services), tele-medicine (e.g., robotic surgery), and defense applications (e.g., total ship computing environments). These types of system are increasingly interconnected via wireless and wireline networks to form systems of systems. A challenging requirement for these DRE systems involves supporting a diverse set of quality of service (QoS) properties, such as predictable latency/jitter, throughput guarantees, scalability, 24x7 availability, dependability, and security that must be satisfied simultaneously in real-time. Although increasing portions of DRE systems are based on QoS-enabled commercial-off-the-shelf (COTS) hardware and software components, the complexity of managing long lifecycles (often ∼15-30 years) remains a key challenge for DRE developers and system integrators. For example, substantial time and effort is spent retrofitting DRE applications when the underlying COTS technology infrastructure changes.This paper provides two contributions that help improve the development, validation, and integration of DRE systems throughout their lifecycles. First, we illustrate the challenges in creating and deploying QoS-enabled component middleware-based DRE applications and describe our approach to resolving these challenges based on a new software paradigm called Model Driven Middleware (MDM), which combines model-based software development techniques with QoS-enabled component middleware to address key challenges faced by developers of DRE systems — particularly composition, integration, and assured QoS for end-to-end operations. Second, we describe the structure and functionality of CoSMIC (Component Synthesis using Model Integrated Computing), which is an MDM toolsuite that addresses key DRE application and middleware lifecycle challenges, including partitioning the components to use distributed resources effectively, validating software configurations, assuring multiple simultaneous QoS properties in real-time, and safeguarding against rapidly changing technology.     

Mycobacterial infection in guinea pigs

We described published reports of the chaos which exists in research concerning laboratory animal models for assay of tuberculosis (TB) vaccines and proposed a "rational animal model" as a solution to the problem. This animal model, an aerosol challenge model in guinea pigs, was recently applied to the problem of differences in growth characteristics of sputum isolates of low and high virulence. The same model was used to investigate the protective effect of high dose BCG given aerogenically. Based on studies in the guinea pig model of experimental airborne TB, and a review of the literature on pathogenesis of human TB, we described an "integrated model" for the pathogenesis of TB, a model which includes a role for both the endogenous reactivation and the exogenous reinfection pathways. Our hypothesis is that tubercle bacilli must be able to gain access to the "vulnerable region" in the lung apex in order to survive the effects of the CMI response. In endogenous reactivation TB (virulent tubercle bacilli), this access occurs via the bloodstream. Whereas in exogenous reinfection TB, access to the vulnerable region occurs via multiple exposures via the respiratory tract. Central to our perspective is the acceptance of the evidence that during first infection with virulent organisms, tubercle bacilli enter the bloodstream via the efferent lymphatics. We believe the hypotheses we have proposed have the potential to lead to a further increase in our knowledge of these mechanisms and are a prerequisite to studies aimed at the development of new vaccines.     

Biosynthesised silver and copper nanoformulation as foliar spray to control bird's eye spot disease in tea plantations

Tea leaves have economic importance in preparation of the popular beverage of the world “tea”. Bird’s eye spot disease of tea leaves creates significant revenue loss in tea trade of many tea plant cultivating countries. Management of this disease by silver (AgNps) and copper (CuNps) nanoparticles that are biosynthesised by efficient antagonists was studied. The biocontrol agents like Pseudomonas fluorescens, Trichoderma atroviride and Streptomyces sannanensis were evaluated for nanoparticle synthesis against Cercospora theae isolates namely KC10, MC24 and VC38. Initially, the freshly prepared extracellular AgNps showed high disease control (59.42 – 79.76%), but the stability of antagonistic property in stored nanoparticles were significantly high in CuNps (58.71 – 73.81%). Greenhouse studies on various treatments imposed also showed reduced disease incidence percentage of 13.4, 7.57 and 10.11% when treated with CuNps synthesized by P. fluorescens, T. atroviride and S. sannanensis respectively. Various treatment schedule in fields suggested the use of Bionanocopper@1.5 ppm for highest yield (3743 kg/ha) with 66.1% disease prevention. The results suggest the use of biosynthesised CuNps using Streptomyces sannanensis for controlling the tea plant pathogens causing foliar disease with higher stability in releasing the antagonistic activity during sporadic disease incidence of bird’s eye spot disease in tea plants.Inspec keywords: silver, copper, crops, plant diseases, nanoparticles, air pollution, agrochemicals, nanobiotechnologyOther keywords: biosynthesised silver, biosynthesised copper, nanoformulation, foliar spray, bird eye spot disease control, tea plantations, tea leaves, economic importance, revenue loss, tea trade, tea plant cultivating countries, silver nanoparticles, AgNps, copper nanoparticles, CuNps, biocontrol agents, nanoparticle synthesis, Cercospora theae isolates, KC10, MC24, VC38, greenhouse studies, antagonistic property, P. fluorescens, T. atroviride, S. sannanensis, fungicides, synthetic nanomaterials, bionanomaterials, disease prevention, green leaf yield, BionanoCu, tea plant pathogens, foliar disease     

Managing supply systems with partial information on shipment locations

This paper studies a supply system for a retailer who orders a single product from one manufacturer. Orders filled by the manufacturer pass through multiple transportation stages before reaching the retailer. Each stage represents either a physical location or a step in the delivery process. The lead time for a new order depends on the location of shipments against prior orders in transit. Shipments are not allowed to cross over in time. Thus, the movement of each shipment depends on the movements of shipments ahead of it and the resulting congestion. The retailer is able to track shipments as they move through the transportation channel. The retailer adopts an ordering policy that minimises the sum of his one-period holding and shortage costs, using available status information of shipments already in transit. The case where practical constraints prevent the retailer from obtaining a complete status of shipments at all stages in the transportation channel is considered. The methodology developed evaluates the value of partial shipment tracking information, and uses it to determine the optimal placement of a limited number of tracking devices. The methodology can also be used to evaluate the cost–benefit of placing additional tracking devices in the supply system.     

Parallelization of a dynamic SVD clustering algorithm and its application in information retrieval

We describe an implementation of a parallel document clustering scheme based on latent semantic indexing, which uses singular value decomposition. Given a set of documents, the clustering algorithm is dynamic in the sense that it automatically infers the number of clusters to be output. The parallel version has been implemented on a LAN and on a dual‐core system. Experimental evaluation of the algorithm shows an average speed‐up of 6.22 for the LAN implementation and an average speed‐up of 3.71 for the dual‐core implementation, while still maintaining a precision and recall in the range [0.85, 1]. To put these implementations in the context of information retrieval, we use the parallel clustering algorithm and develop a document similarity search system. The similarity search system shows good performance in terms of precision and recall. Copyright © 2010 John Wiley & Sons, Ltd.     

A new robust reference watermarking scheme based on DWT-SVD

This paper presents a new semi-blind reference watermarking scheme based on discrete wavelet transform(DWT) and singular value decomposition(SVD) for copyright protection and authenticity. We are using a gray scale logo image as watermark instead of randomly generated Gaussian noise type watermark. For watermark embedding, the original image is transformed into wavelet domain and a reference sub-image is formed using directive contrast and wavelet coefficients. We embed watermark into reference image by modifying the singular values of reference image using the singular values of the watermark. A reliable watermark extraction scheme is developed for the extraction of watermark from distorted image. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks. We show that the proposed scheme also stands with the ambiguity attack also.     

Implementation of a Gaussian process-based machine learning grasp predictor

With the goal of advancing the state of automatic robotic grasping, we present a novel approach that combines machine learning techniques and physical validation on a robotic platform to develop a comprehensive grasp predictor. After collecting a large grasp sample set (522 grasps), we first conduct a statistical analysis of the predictive ability of grasp quality metrics that are commonly used in the robotics literature. We then apply principal component analysis and Gaussian process (GP) algorithms on the grasp metrics that are discriminative to build a classifier, validate its performance, and compare the results to existing grasp planners. The key findings are as follows: (i) several of the existing grasp metrics are weak predictors of grasp quality when implemented on a robotic platform; (ii) the GP-based classifier significantly improves grasp prediction by combining multiple grasp metrics to increase true positive classification at low false positive rates; (iii) The GP classifier can be used generate new grasps to improve bad grasp samples by performing a local search to find neighboring grasps which have improved contact points and higher success rate.