A two-phase framework for quality-aware Web service selection

Service-oriented computing is gaining momentum as the next technological tool to leverage the huge investments in Web application development. The expected large number of Web services poses a set of new challenges for efficiently accessing these services. We propose an integrated service query framework that facilitates users in accessing their desired services. The framework incorporates a service query model and a two-phase optimization strategy. The query model defines service communities that are used to organize the large and heterogeneous service space. The service communities allow users to use declarative queries to retrieve their desired services without worrying about the underlying technical details. The two-phase optimization strategy automatically generates feasible service execution plans and selects the plan with the best user-desired quality. In particular, we present an evolutionary algorithm that is able to “co-evolve” multiple feasible execution plans simultaneously and allows them to compete with each other to generate the best plan. We conduct a set of experiments to assess the performance of the proposed algorithms.     

New aspect-oriented constructs for security hardening concerns

In this paper, we present new pointcuts and primitives to Aspect-Oriented Programming (AOP) languages that are needed for systematic hardening of security concerns. The two proposed pointcuts allow to identify particular join points in a program's control-flow graph (CFG). The first one is the GAFlow, Closest Guaranteed Ancestor, which returns the closest ancestor join point to the pointcuts of interest that is on all their runtime paths. The second one is the GDFlow, Closest Guaranteed Descendant, which returns the closest child join point that can be reached by all paths starting from the pointcut of interest. The two proposed primitives are called ExportParameter and ImportParameter and are used to pass parameters between two pointcuts. They allow to analyze a program's call graph in order to determine how to change function signatures for passing the parameters associated with a given security hardening. We find these pointcuts and primitives to be necessary because they are needed to perform many security hardening practices and, to the best of our knowledge, none of the existing ones can provide their functionalities. Moreover, we show the viability and correctness of the proposed pointcuts and primitives by elaborating and implementing their algorithms and presenting the result of explanatory case studies.     

Reliability of lightning-resistant overhead lines

Lightning continues to be the major cause of outages on overhead power distribution lines. Through laboratory testing and field observations and measurements, the properties of a lightning stroke and its effects on electrical distribution system components are fairly well-understood phenomena. A meticulous compilation of 32 years of historical records has been kept for outage causes, duration, and locations for eight distribution feeders at the Oak Ridge National Laboratory (ORNL). Due to the limited growth of ORNL, the number, length, and location of the 13.8 kV overhead lines have remained the same between 1960 and 1992. Except for noted differences (voltage construction class, length, age, and maximum elevation above a reference level), other factors that could influence the reliability of an overhead line have remained nearly the same. This allowed a meaningful reliability study to be performed on the entire ORNL electrical distribution system. In this article, the main findings of the reliability assessment as it relates to lightning-resistant overhead line construction techniques are out-lined, and a simple and cost-effective method to reduce lightning caused outages is offered. In addition, comparisons are made between the failure rates and causes experienced at ORNL and those in industry surveys. Where large discrepancies exist between survey data and experiences at ORNL, evidence is presented to explain the differences between ORNL's distribution system and those typical of industry     

Postischemic Neuroprotection of Aminoethoxydiphenyl Borate Associates Shortening of Peri-Infarct Depolarizations

Brain stroke is a highly prevalent pathology and a main cause of disability among older adults. If not promptly treated with recanalization therapies, primary and secondary mechanisms of injury contribute to an increase in the lesion, enhancing neurological deficits. Targeting excitotoxicity and oxidative stress are very promising approaches, but only a few compounds have reached the clinic with relatively good positive outcomes. The exploration of novel targets might overcome the lack of clinical translation of previous efficient preclinical neuroprotective treatments. In this study, we examined the neuroprotective properties of 2-aminoethoxydiphenyl borate (2-APB), a molecule that interferes with intracellular calcium dynamics by the antagonization of several channels and receptors. In a permanent model of cerebral ischemia, we showed that 2-APB reduces the extent of the damage and preserves the functionality of the cortical territory, as evaluated by somatosensory evoked potentials (SSEPs). While in this permanent ischemia model, the neuroprotective effect exerted by the antioxidant scavenger cholesteronitrone F2 was associated with a reduction in reactive oxygen species (ROS) and better neuronal survival in the penumbra, 2-APB did not modify the inflammatory response or decrease the content of ROS and was mostly associated with a shortening of peri-infarct depolarizations, which translated into better cerebral blood perfusion in the penumbra. Our study highlights the potential of 2-APB to target spreading depolarization events and their associated inverse hemodynamic changes, which mainly contribute to extension of the area of lesion in cerebrovascular pathologies.     

Phenotypic Characterization and Genotypic Subtyping of Salmonella enterica Serovars Enteritidis and Gallinarum Isolated from Human and Poultry-Related Samples

This study aimed to assess the serotypes, antibiotic susceptibility, and molecular subtyping of Salmonella enterica isolated from food products and human patients with gastroenteritis. A total of 59 isolates were investigated, and the results revealed a predominance of S. Enteritidis with 57.63% (34/59) S. Gallinarum held second with 15.62% (5/32) of total food borne. While, isolates from humans showed 18.51% (5/27) of S. Typhimurium. High level of resistance to nalidixic acid was noted among food strains and 35.29% of human isolates were found to be multidrug resistant. Eight representative isolates were subtyping using three molecular approaches, ribotyping, Multilocus sequence typing (MLST) and Multiple-locus variable number tandem repeat analysis (MLVA). MLST showed three sequence types corresponding to two clonal complexes, (ST-78, CC-4) for S. Gallinarum, (ST-11, CC-4) for S. Enteritidis and (S-367, CC-37) for S. Cerro. While, MLVA generated six different profiles targeting nine loci for S. Enteritidis and S. Gallinarum.     

Fault diagnosis using partial syndromes: a modified Hopfield neural network approach

This paper presents a modified Hopfield neural network (HNN) for solving the system-level fault diagnosis problem which aims at identifying the set of faulty nodes. This problem has been extensively studied in the last three decades. Nevertheless, identifying the set of all faulty nodes using only partial syndromes, i.e. when some of the testing or comparison outcomes are missing prior to initiating the diagnosis phase, remains an outstanding research issue. The new HNN-based diagnosis algorithm does not require any prior learning or knowledge about the system, nor about any faulty situation, hence providing a better generalisation performance. Results from a thorough simulation study demonstrate the effectiveness of the HNN-based fault diagnosis algorithm in terms of diagnosis correctness, diagnosis latency and diagnosis scalability, for randomly generated diagnosable systems of different sizes and under various fault scenarios. We have also conducted extensive simulations using partial syndromes. Simulations showed that the HNN-based diagnosis performed efficiently, i.e. diagnosis correctness was around 99% when at most half of the test or comparison outcomes are missing, making it a viable alternative to existing diagnosis algorithms.     

Fitting Time Series Models for Prediction

The mathematical theory of the best linear prediction of stationary time series presumes that the model generating the series, which can be specified by either the autocovariance function or the spectral density, is known. The true model is, of course, not known in practice, and the procedure is to fit a model and predict as if this fitted model were the truth. The question then is one of deciding whether the resulting predictions are about as good as could be gotten if the truth were known. This paper describes a method for assessing the predictions of the fitting model by an analysis of residuals. In particular, it is argued that the traditional tests of hypothesis for white noise are inappropriate if prediction is the goal, and a method is described for determining whether or not the mean square errors of the predictions arising from the fitted model can be measurably reduced.     

Rapid and efficient hand gestures recognizer based on classes discriminator wavelet networks

Multimedia Tools and Applications - The vision based on hand gesture recognition is one of the key challenges in behavior understanding and computer vision. It offers to machines the possibility of...     

Bioconversion of shrimp shell waste for the production of antioxidant and chitosan used as fruit juice clarifier

The pH, proteolytic activity, extent of demineralisation and deprotenisation of shrimp waste were studied during 7 days of fermentation using Pseudomonas aeruginosa A2. After 3 days, pH dropped from 7.0 to 4.4 and then remained constant. Simultaneously, a demineralisation of 92% was achieved. However, protease activity reached its highest level (1230 U mL^?1) after 1 day of incubation, and a protein removal of 90% was achieved. Chitin obtained was converted to chitosan. This chitosan, with 73% deacetylation, was tested for clarification of different fruit juices. It was observed that low concentrations of chitosan (below to 1%) greatly increase the clarity of juices without affecting the nutritional value. The antioxidant activity of the hydrolysates produced during fermentation was tested. Hydrolysate obtained after 3 days showed the strongest scavenging activity (90%), which was comparable to the positive control BHA; however, that obtained after 1 day exhibited the highest ferric‐reducing antioxidant power (OD 700 nm = 1.7).