Specifying and Monitoring Interactions and Commitments in Open Business Processes

Business processes are increasingly complex and open because they rely on services that are distributed geographically and across organizations. So, they're prone to several points of failure. Monitoring, therefore, remains an important concern. A new approach specifies and monitors interactions among heterogeneous services by tracking their commitments. This approach extends recent research that views business process design as a composition of interaction protocols. It specifies and monitors policies and commitments as a way to monitor service-level agreements and recover from process failures.     

Design patterns for open tool integration

Design tool integration is a highly relevant area of software engineering that can greatly improve the efficiency of development processes. Design patterns have been widely recognized as important contributors to the success of software systems. This paper describes and compares two large-grain, architectural design patterns that solve specific design tool integration problems. Both patterns have been implemented and used in real-life engineering processes.     

A Functional Programming Framework for Latency Insensitive Protocol Validation

Latency insensitive protocols (LIPs) have been proposed as a viable means to connect synchronous IP blocks via long interconnects in a system-on-chip. The reason why one needs to implement LIPs on long interconnects stems from the fact that with increasing clock frequencies, the signal delay on some interconnects exceeds the clock period. Correctness of a system composed of synchronous blocks communicating via LIPs is established by showing latency equivalence between a completely synchronous composition of the blocks, and the LIP based composition. A design flow based on a synchronous composition specification, and stepwise refinement to LIP composition can be easily conceived, and a proof obligation to show latency equivalence between the synchronous specification and the refinement needs to be discharged. In this work, we propose a functional programming based framework for modeling and simulating LIP, and implement the semantics of various refinement steps in the programming model, so we can validate the LIP model against the original system within this functional programming framework. Such validation becomes easier due to the inherent denotational model of functional languages. We specifically use Standard ML to model the original system implementation as well as its latency insensitive version and compare the two by creating a model that contains both, giving them the same inputs and checking their outputs to be latency equivalent.     

Si nanocolumns as novel nanostructured supports for enzyme immobilization

Silicon nanocolumns have been used as novel supports for the high-density immobilization of enzymes. Silicon nanocolumns with diameters of ca. 50-100 nm and a height of 1 micron were constructed using glancing angle deposition. The surfaces were successively treated with 3-aminopropyltriethoxysilane (APTES) and then with an amine reactive polymer, poly(ethylene-alt-maleic anhydride), to attach soybean peroxidase (SBP) to the support. Optimal coverage of APTES, polymer, and SBP was obtained for incorporation of enzyme onto the sidewalls of the nanocolumns. SBP immobilized on the silicon nanocolumns demonstrated an enhancement in biocatalytic activity of 160% over that of the enzyme immobilized on flat silicon wafers with the same projected area. The enzymatic activity decreased with progressive washes for both supports. This decrease in the activity of enzyme was found to be primarily due to the intrinsic deactivation of immobilized enzyme on the silicon surface. Designing nanocolumns with optimal dimensions, spacing, and surface chemistry may lead to the development of high-density arrays of proteins for applications in biotechnology.     

Towards a verifiable real-time, autonomic, fault mitigation framework for large scale real-time systems

Designing autonomic fault responses is difficult, particularly in large-scale systems, as there is no single ‘perfect’ fault mitigation response to a given failure. The design of appropriate mitigation actions depend upon the goals and state of the application and environment. Strict time deadlines in real-time systems further exacerbate this problem. Any autonomic behavior in such systems must not only be functionally correct but should also conform to properties of liveness, safety and bounded time responsiveness. This paper details a real-time fault-tolerant framework, which uses a reflex and healing architecture to provide fault mitigation capabilities for large-scale real-time systems. At the heart of this architecture is a real-time reflex engine, which has a state-based failure management logic that can respond to both event- and time-based triggers. We also present a semantic domain for verifying properties of systems, which use this framework of real-time reflex engines. Lastly, a case study, which examines the details of such an approach, is presented.     

A Process of Notch Wavy Rolling for Strengthening Metal Sheets

Wavy roll design was employed for strengthening 1 mm thin austenitic stainless steel coil sheet by cold rolling without further reduction in thickness. This steel possesses high corrosion resistance and high ductility. Initially, the sheets were rolled into sine wave shape (wave amplitude <2 mm) and then flattened using conventional cold rolling mill. Such a process cycle was repeated for four times successfully and the mechanical properties were measured after each cycle. The yield strength increased from 255 to 931 MPa with corresponding decrease in elongation from 45% to only 17% after the fourth cycle of severe cold working. Tensile strength and hardness values increased from 753 MPa and 185 HV to 973 MPa and 371 HV, respectively. The micro-to-nano-scale resolution structures, obtained by optical and atomic force microscope (AFM), were used to explain the variation in properties during this manufacturing process and to propose schematically the deformation mechanism.     

Neotectonic study of Ganga and Yamuna tear faults,NW Himalaya,using remote sensing and GIS

The Ganga and Yamuna rivers emerge from the Himalayas along two major faults known as the Ganga and Yamuna Tear Faults respectively. The two major strike-slip faults transverse to the Siwalik range are clearly seen in satellite imagery of the Dehradun area. Earthquake records, landslide and recent changes in geomorphological features indicate that the area between the Main Boundary Thrust and the Main Frontal Thrust is tectonically active. An effort has been made to study the tectonic evolution and neotectonism of the Ganga and Yamuna tear faults. Spectral and spatial enhancement techniques have been employed to the digital data of IRS-1B LISS-I to delineate the lineaments and major faults of the area. Based on Mohr's theory, failure criteria and statistical analysis of remotely sensed lineament data, horizontal compressive stress values (S_Hmax) have been estimated at various sites of the study area. These data are found to be consistent with the published S_Hmax orientation determined from earthquake focal mechanism solutions. Active faults and lineaments have been extracted from the remotely sensed lineament data. Past earthquake data and depth to basement contour data have been used in an integrated approach with available Geographic Information System (GIS) techniques to reconstruct a present-day regional geodynamic model. Attempts have been made to investigate the genesis of Ganga and Yamuna Tear Faults and possible causes of recent tectonic activities of the area with the help of the proposed geodynamic model.     

The impact of assimilation of AMSU data for the prediction of a tropical cyclone over India using a mesoscale model

Tropical cyclones form over the seas: a typical data‐sparse region for conventional observations. Therefore, satellites, especially with microwave sensors, are ideal for cyclone studies. The advanced microwave sounding unit (AMSU) , in addition to providing very valuable data over non‐precipitating cloudy regions, can provide very high horizontal resolution of the temperature and humidity soundings. Such high‐resolution microwave data can improve the poorly analysed cyclone. The objective of this study is to investigate the impact of ingesting and assimilating the AMSU data together with conventional upper air and surface meteorological observations over India on the prediction of a tropical cyclone which formed over the Arabian Sea during November 2003 using analysis nudging. The impact of assimilating the AMSU‐derived temperature and humidity vertical profiles in a mesoscale model has not been tested yet over the Indian region. Such studies are important as most weather systems over India form over the seas. The present study is unique in the sense that it addresses the impact of ingesting and assimilating microwave sounding data (together with conventional India Meteorological Department data) on the prediction of a tropical cyclone, which formed over the Arabian Sea during November 2003 using analysis nudging. Two sets of numerical experiments are designed in this study. While the first set utilizes the National Center for Environmental Prediction (NCEP) reanalysis (for the initial and lateral boundary conditions) only in the fifth‐generation mesoscale model simulation, the second set utilized the AMSU satellite and conventional meteorological upper air and surface data to provide an improved analysis through analysis nudging. The results of the two sets of model simulations are compared with one another as well as with the NCEP reanalysis and the observations.

The results of the study indicated that the impact of ingesting and assimilating microwave sounding data and the conventional meteorological data through nudging resulted in an improvement in the simulation of wind asymmetries and the warm temperature anomalies. The with‐assimilation run simulated stronger wind speeds and stronger vertical velocity motion as compared with the without‐assimilation run. The time series of the minimum sea level pressure (SLP) and maximum wind speed for the simulations with the microwave sounding data and conventional meteorological data show better agreement with the observations than the simulations without the assimilation. The central minimum pressure of the simulations with the modified analysis are lower by 7 hPa as compared with the simulations without the assimilations. Even though there is not much of a difference in the maximum wind speed between the two simulations at the initial forecast time, the results indicate that the simulations with microwave sounding data and conventional meteorological data reveal a marked (9 m/s) increase in the maximum wind speed over the simulations without the assimilation. While the lowest central pressure estimated from the satellite image is 988 hPa, the simulations with microwave sounding data and conventional meteorological data show a value of 999.5 hPa for the lowest central minimum pressure. One reason for the inability of the simulation with improved analysis to achieve the observed lowest SLP is that the NCEP reanalysis had manifested an extremely weak system in the first place and, despite assimilation with microwave sounding data and conventional meteorological data, only a moderate improvement in the lowest SLP could be achieved. A proper appreciation of the impact of the microwave sounding data can be obtained by comparing with the lowest SLP obtained from the simulation without assimilation which showed a value of 1007 hPa. The initial mis‐representation in the location of the centre of the cyclone in the NCEP reanalysis with respect to the observed location has led to marked errors in the track prediction of both the model simulations. The assimilation of microwave satellite data is yet to be implemented in the current operational regional model over India and hence the results of this study may be relevant to the operational tropical cyclone forecasting community.     

Preparation and characterization of bio-nanocomposite films based on soy protein isolate and montmorillonite using melt extrusion

The non-biodegradable and non-renewable nature of plastic packaging has led to a renewed interest in packaging materials based on bio-nanocomposites (biopolymer matrix reinforced with nanoparticles such as layered silicates). Bio-nanocomposite films based on soy protein isolate (SPI) and montmorillonite (MMT) were prepared using melt extrusion. Effects of the pH of film forming solution, MMT content, and extrusion processing parameters (screw speed and barrel temperature distribution) on the structure and properties of SPI–MMT bio-nanocomposite films were investigated. X-ray diffraction (XRD), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) were used for structural characterization of the films. Properties of the films were determined by tensile testing, dynamic mechanical analysis (DMA), thermogravimetric analysis (TGA), and water vapor barrier measurement. The arrangement of MMT in the soy protein matrix ranged from exfoliated at lower MMT content (5%) to intercalated at higher MMT content (15%). There was a significant improvement in mechanical (tensile strength and percent elongation at break) and dynamic mechanical properties (glass transition temperature and storage modulus), thermal stability, and water vapor permeability of the films with the addition of MMT. The results presented in this study show the feasibility of using bio-nanocomposite technology to improve the properties of biopolymer films based on SPI.     

Incidence and genetic variability of Listeria species from three milk processing plants

The presence of Listeria in three milk processing environments as a potential source of milk contamination was assessed. Swab samples (n = 210) taken from milk processing plants were examined. Sample sites included the milk processing equipment, besides areas handling raw and pasteurized milk. The USDA Listeria-selective enrichment procedure was used to process the samples. Forty one (19.52%) Listeria isolates were recovered. The isolates were further subjected to biochemical and genotypic characterization. Out of 41 isolates, 16 (7.62%) were confirmed as Listeria monocytogenes, 2 (0.95%) as L. ivanovii, 19 (9.05%) as L. innocua. 1 (0.48%) as L. seeligeri and 3 (1.43%) as L. grayi. All the L. monocytogenes isolates were positive for the hlyA gene. PCR based serotyping revealed all L. monocytogenes to be of 1/2a, 1/2c, 3a and 3c serovar group. AscI and ApaI restriction analysis yielded four PFGE clusters for 16 L. monocytogenes isolates obtained from raw milk collector, milk silos, buttermilk mixer, cheese and other milk product processor. No predominant PFGE cluster was observed among these L. monocytogenes isolates. The main sources of L. monocytogenes were found to be raw milk collector and milk silos. In the present study L. monocytogenes was isolated from milk and milk products processing plants which could cross-contaminate the processed products and may possess a potential threat to public health.