Automatic generation of meta classifiers with large levels for distributed computing and networking

This paper is devoted to a case study of a new construction of classifiers. These classifiers are called automatically generated multi-level meta classifiers, AGMLMC. The construction combines diverse meta classifiers in a new way to create a unified system. This original construction can be generated automatically producing classifiers with large levels. Different meta classifiers are incorporated as low-level integral parts of another meta classifier at the top level. It is intended for the distributed computing and networking. The AGMLMC classifiers are unified classifiers with many parts that can operate in parallel. This make it easy to adopt them in distributed applications. This paper introduces new construction of classifiers and undertakes an experimental study of their performance. We look at a case study of their effectiveness in the special case of the detection and filtering of phishing emails. This is a possible important application area for such large and distributed classification systems. Our experiments investigate the effectiveness of combining diverse meta classifiers into one AGMLMC classifier in the case study of detection and filtering of phishing emails. The results show that new classifiers with large levels achieved better performance compared to the base classifiers and simple meta classifiers classifiers. This demonstrates that the new technique can be applied to increase the performance if diverse meta classifiers are included in the system.

Statistical analysis of synthetic earthquake catalogs generated by models with various levels of fault zone disorder

The stress release model, a stochastic version of the elastic rebound theory, is applied to the large events from four synthetic earthquake catalogs generated by models with various levels of disorder in distribution of fault zone strength (Ben-Zion, 1996) They include models with uniform properties (U), a Parkfield-type asperity (A), fractal brittle properties (F), and multi-size-scale heterogeneities (M). The results show that the degree of regularity or predictability in the assumed fault properties, based on both the Akaike information criterion and simulations, follows the order U, F, A, and M, which is in good agreement with that obtained by pattern recognition techniques applied to the full set of synthetic data. Data simulated from the best fitting stress release models reproduce, both visually and in distributional terms, the main features of the original catalogs. The differences in character and the quality of prediction between the four cases are shown to be dependent on two main aspects: the parameter controlling the sensitivity to departures from the mean stress level and the frequency-magnitude distribution, which differs substantially between the four cases. In particular, it is shown that the predictability of the data is strongly affected by the form of frequency-magnitude distribution, being greatly reduced if a pure Gutenburg-Richter form is assumed to hold out to high magnitudes.

Phylogeographic reconstruction of a bacterial species with high levels of lateral gene transfer

Background Phylogeographic reconstruction of some bacterial populations is hindered by low diversity coupled with high levels of lateral gene transfer. A comparison of recombination levels and diversity at seven housekeeping genes for eleven bacterial species, most of which are commonly cited as having high levels of lateral gene transfer shows that the relative contributions of homologous recombination versus mutation for Burkholderia pseudomallei is over two times higher than for Streptococcus pneumoniae and is thus the highest value yet reported in bacteria. Despite the potential for homologous recombination to increase diversity, B. pseudomallei exhibits a relative lack of diversity at these loci. In these situations, whole genome genotyping of orthologous shared single nucleotide polymorphism loci, discovered using next generation sequencing technologies, can provide very large data sets capable of estimating core phylogenetic relationships. We compared and searched 43 whole genome sequences of B. pseudomallei and its closest relatives for single nucleotide polymorphisms in orthologous shared regions to use in phylogenetic reconstruction. Results Bayesian phylogenetic analyses of >14,000 single nucleotide polymorphisms yielded completely resolved trees for these 43 strains with high levels of statistical support. These results enable a better understanding of a separate analysis of population differentiation among >1,700 B. pseudomallei isolates as defined by sequence data from seven housekeeping genes. We analyzed this larger data set for population structure and allele sharing that can be attributed to lateral gene transfer. Our results suggest that despite an almost panmictic population, we can detect two distinct populations of B. pseudomallei that conform to biogeographic patterns found in many plant and animal species. That is, separation along Wallace's Line, a biogeographic boundary between Southeast Asia and Australia. Conclusion We describe an Australian origin for B. pseudomallei, characterized by a single introduction event into Southeast Asia during a recent glacial period, and variable levels of lateral gene transfer within populations. These patterns provide insights into mechanisms of genetic diversification in B. pseudomallei and its closest relatives, and provide a framework for integrating the traditionally separate fields of population genetics and phylogenetics for other bacterial species with high levels of lateral gene transfer.

High levels of BACH2 associated with lower levels of BCL2 transcript abundance in t(14;18)(q21;q34) translocation positive non-Hodgkin’s lymphoma

The t(14;18)(q21;q34) BCL2 translocation is a common genetic alteration in follicular and diffuse large B-cell lymphoma. However, it is not invariably associated with BCL2 gene overexpression due to undefined mechanisms that regulate expression from the proximal immunoglobulin heavy-chain (IgH) promoter. The BACH2 transcriptional repressor is able to modulate activity of this promoter. Here we have shown that, in tumor samples with BCL2 translocation, those with high levels of BACH2 had significantly lower BCL2 transcript abundance compared to those with low levels of BACH2. This indicates that BACH2 may be partially responsible for regulation of BCL2 expression from the t(14;18)(q21;q34) translocation.

A Protocol for Authentication with Multiple Levels of Anonymity (AMLA) in VANETs

The basic requirements for secure communication in a vehicular ad hoc network (VANET) are anonymous authentication with source non-repudiation and integrity. The existing security protocols in VANETs do not differentiate between the anonymity requirements of different vehicles and the level of anonymity provided by these protocols is the same for all the vehicles in a network. To provide high level of anonymity, the resource requirements of security protocol would also be high. Hence, in a resource constrained VANET, it is necessary to differentiate between the anonymity requirements of different vehicles and to provide the level of anonymity to a vehicle as per its requirement. In this paper, we have proposed a novel protocol for authentication which can provide multiple levels of anonymity in VANETs. The protocol makes use of identity based signature mechanism and pseudonyms to implement anonymous authentication with source non-repudiation and integrity. By controlling the number of pseudonyms issued to a vehicle and the lifetime of each pseudonym for a vehicle, the protocol is able to control the level of anonymity provided to a vehicle. In addition, the protocol includes a novel pseudonym issuance policy using which the protocol can ensure the uniqueness of a newly generated pseudonym by checking only a very small subset of the set of pseudonyms previously issued to all the vehicles. The protocol cryptographically binds an expiry date to each pseudonym, and in this way, enforces an implicit revocation for the pseudonyms. Analytical and simulation results confirm the effectiveness of the proposed protocol.

Contributions to Ensemble Classifiers with Image Analysis Applications

134 p.

Band crossing in isovalent semiconductor alloys with large size mismatch: First-principles calculations of the electronic structure of Bi and N incorporated GaAs

For large size- and chemical-mismatched isovalent semiconductor alloys, such as N and Bi substitution on As sites in GaAs, isovalent defect levels or defect bands are introduced. The evolution of the defect states as a function of the alloy concentration is usually described by the popular phenomenological band anticrossing (BAC) model. Using first-principles band-structure calculations we show that at the impurity limit the N-(Bi)-induced impurity level is above (below) the conduction- (valence-) band edge of GaAs. These trends reverse at high concentration, i.e., the conduction-band edge of GaAs1-xNx becomes an N-derived state and the valence-band edge of GaAs1-xBix becomes a Bi-derived state, as expected from their band characters. We show that this band crossing phenomenon cannot be described by the popular BAC model but can be naturally explained by a simple band broadening picture.

An ensemble of classifiers with genetic algorithmBased Feature Selection

Different data classification algorithms have been developed and applied in various areas to analyze and extract valuable information and patterns from large datasets with noise and missing values. However, none of them could consistently perform well over all datasets. To this end, ensemble methods have been suggested as the promising measures. This paper proposes a novel hybrid algorithm, which is the combination of a multi-objective Genetic Algorithm (GA) and an ensemble classifier. While the ensemble classifier, which consists of a decision tree classifier, an Artificial Neural Network (ANN) classifier, and a Support Vector Machine (SVM) classifier, is used as the classification committee, the multi-objective Genetic Algorithm is employed as the feature selector to facilitate the ensemble classifier to improve the overall sample classification accuracy while also identifying the most important features in the dataset of interest. The proposed GA-Ensemble method is tested on three benchmark datasets, and compared with each individual classifier as well as the methods based on mutual information theory, bagging and boosting. The results suggest that this GA-Ensemble method outperform other algorithms in comparison, and be a useful method for classification and feature selection problems.

Optimisation of stir bar sorptive extraction and liquid desorption combined with large volume injection-gas chromatography–quadrupole mass spectrometry for the determination of volatile compounds in wines

Stir bar sorptive extraction and liquid desorption followed by large volume injection coupled to gas chromatography–quadrupole mass spectrometry (SBSE–LD/LVI-GC–qMS) had been applied for the determination of volatiles in wines. The methodology was optimised in terms of extraction time and influence of ethanol in the matrix; LD conditions, and instrumental settings. The optimisation was carried out by using 10 standards representative of the main chemical families of wine, i.e. guaiazulene, E,E-farnesol, β-ionone, geranylacetone, ethyl decanoate, β-citronellol, 2-phenylethanol, linalool, hexyl acetate and hexanol. The methodology shows good linearity over the concentration range tested, with correlation coefficients higher than 0.9821, a good reproducibility was attained (8.9–17.8%), and low detection limits were achieved for nine volatile compounds (0.05–9.09 μg L−1), with the exception of 2-phenylethanol due to low recovery by SBSE. The analytical ability of the SBSE–LD/LVI-GC–qMS methodology was tested in real matrices, such as sparkling and table wines using analytical curves prepared by using the 10 standards where each one was applied to quantify the structurally related compounds. This methodology allowed, in a single run, the quantification of 67 wine volatiles at levels lower than their respective olfactory thresholds. The proposed methodology demonstrated to be easy to work-up, reliable, sensitive and with low sample requirement to monitor the volatile fraction of wine.

DIAGNOSIS of REGIONAL CEREBRAL BLOOD FLOW ABNORMALITIES USING SPECT: AGREEMENT BETWEEN INDIVIDUALIZED STATISTICAL PARAMETRIC MAPS and VISUAL INSPECTION BY NUCLEAR MEDICINE PHYSICIANS WITH DIFFERENT LEVELS of EXPERTISE IN NUCLEAR NEUROLOGY

INTRODUCTION: Visual analysis is widely used to interpret regional cerebral blood flow (rCBF) SPECT images in clinical practice despite its limitations. Automated methods are employed to investigate between-group rCBF differences in research Studies but have rarely been explored in individual analyses.OBJECTIVES: To compare visual inspection by nuclear physicians with the automated statistical parametric mapping program using a SPECT dataset of patients with neurological disorders and normal control images.METHODS: Using statistical parametric mapping, 14 SPECT images from patients with various neurological disorders were compared individually with a databank of 32 normal images using a statistical threshold of p<0.05 (corrected for multiple comparisons at the level of individual voxels or clusters). Statistical parametric mapping results were compared with Visual analyses by a nuclear physician highly experienced in neurology (A) as well as a nuclear physician with a general background of experience (B) who independently classified images as normal or altered, and determined the location of changes and the severity.RESULTS: of the 32 images of the normal databank, 4 generated maps showing rCBF abnormalities (p<0.05, corrected). Among the 14 images from patients with neurological disorders, 13 showed rCBF alterations. Statistical parametric mapping and physician A completely agreed on 84.37% and 64.28% of cases from the normal databank and neurological disorders, respectively. The agreement between statistical parametric mapping and ratings of physician B were lower (71.18% and 35.71%, respectively).CONCLUSION: Statistical parametric mapping replicated the findings described by the more experienced nuclear physician. This finding suggests that automated methods for individually analyzing rCBF SPECT images may be a valuable resource to complement visual inspection in clinical practice.

Vocal and territorial behavior in the Smith frog (Hypsiboas faber): Relationships with plasma levels of corticosterone and testosterone

The possible trade-off between the roles of glucocorticoids as facilitators of energy substrate mobilization and neural inhibitors of sexual behavior during breeding season is under debate. We studied the relationship between calling and territorial behavior with plasma levels of corticosterone (CORT) and plasma levels of testosterone (T) across the breeding season of Hypsiboas faber, a large and territorial Neotropical treefrog. We investigated these relationships through focal observations of males calling naturally, followed by blood sampling for hormonal radioimmunoassay. We additionally used an experimental approach, which consisted of broadcasting recorded advertisement calls for 10 min to simulate an invasion in the territory of the focal subjects, followed by behavioral observation and blood sampling for hormonal radioimmunoassay. Results showed a pattern of co-variation between CORT and T across the breeding season. Furthermore, individual variation in CORT and T was related to different aspects of behavior: individuals with higher CORT showed higher calling rates, and individuals with higher steroid levels, mainly T, showed higher responsivity to social stimulation by other males in the chorus. Experimental simulation of territorial intrusion by using playback of advertisement calls of this species did not elicit consistent changes in agonistic behavior and CORT, but decreased T in focal males. (C) 2012 Elsevier Inc. All rights reserved.

Specific and Nonspecific Psychological Interventions for PTSD Symptoms: A Meta-Analysis With Problem Complexity as a Moderator

CONTEXT The necessity of specific intervention components for the successful treatment of patients with posttraumatic stress disorder is the subject of controversy. OBJECTIVE To investigate the complexity of clinical problems as a moderator of relative effects between specific and nonspecific psychological interventions. METHODS We included 18 randomized controlled trials, directly comparing specific and nonspecific psychological interventions. We conducted moderator analyses, including the complexity of clinical problems as predictor. RESULTS Our results have confirmed the moderate superiority of specific over nonspecific psychological interventions; however, the superiority was small in studies with complex clinical problems and large in studies with noncomplex clinical problems. CONCLUSIONS For patients with complex clinical problems, our results suggest that particular nonspecific psychological interventions may be offered as an alternative to specific psychological interventions. In contrast, for patients with noncomplex clinical problems, specific psychological interventions are the best treatment option.

Tailored instructional methods for students with diverse levels of computer knowledge and skills

The purpose of this online course is to ensure new nursing graduate students know how to use computer technologies required to complete academic and research activities. Powerful computers, high speed internet, digitalized resources and databases are widely available in educational institutes. New renovation and updates are being released at faster pace than ever. All these developments are necessary for a student to utilize computer programs and synthesize large amount of data in a limited time for any given academic research project. [See PDF for complete abstract]

No evidence for an association of posttraumatic stress disorder with circulating levels of CRP and IL-18 in a population-based study.

Several studies have shown associations of posttraumatic stress disorder (PTSD) with the development of cardiometabolic diseases. The underlying psychopathological mechanisms, including potential links to inflammatory processes, have been discussed but remain elusive. Therefore, the aim of the present study was to evaluate the association of PTSD symptoms with the inflammatory biomarkers C-reactive protein (CRP) and interleukin-18 (IL-18). The study population consisted of 3012 participants aged 32-81years drawn from the population-based KORA F4 study conducted in 2006-08 in the Augsburg region (Southern Germany). PTSD symptoms were measured by the Impact of Event Scale, the Posttraumatic Diagnostic Scale and interview data and classified as no, partial or full PTSD. The associations of PTSD with CRP and IL-18 concentrations were estimated by multiple regression analyses with adjustments for age, sex and cardiometabolic risk factors. Linear regression analyses showed no significant association between PTSD and CRP or IL-18 concentration: adjusted for age and sex, the geometric mean concentrations in participants with full PTSD was for CRP 9% lower and for IL-18 1% higher than in participants with no PTSD (p values 0.53 and 0.89). However, further analyses indicated that individuals with partial PTSD had an increased chance of belonging to the highest quartile of the IL-18 concentration. No significant association was observed for any of the three subscales intrusion, avoidance or hyperarousal with CRP or IL-18 concentration. This large, population-based study could not find an association of full PTSD with CRP and IL-18 concentrations. Further research is needed to analyse these relationships.