Supporting business intelligence usage: an integrated framework with automatic weighting

This paper presents an integrated framework that comprises an automatic weighting method for assessing data quality (DQ) of the framework so as to better support the business intelligence (BI) usage. Specifically, we utilize business process modeling (BPM) notation and information product map and frame them into a hierarchical mapping structure. Furthermore, we develop and demonstrate an automatic weight-assignment method for evaluating critical dimensions (i.e., completeness and accuracy) of DQ of the integrated framework. Through a design science paradigm, the effectiveness of the framework and the associated DQ weighting method has been rigorously validated by faculty management users of a university. The framework together with the DQ weighting method builds user confidence by enhancing the traceability of a BI product. The automatic DQ weight assignment also provides better time efficiency because the weight of each data attribute is determined automatically based on its usage on the BI dashboard.

an empirical study on bug assignment automation using chinese bug data

Univ SE Calif, Ctr Syst & Software Engn, ABB, Microsoft Res, IEEE, ACMSIGSOFT, N Carolina State Univ Comp Sci

Rapid protein domain assignment from amino acid sequence using predicted secondary structure

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (±20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed

Identification of intersectional Corymbia hybrids based on seedling morphology improves with parental divergence

Differences in morphology have provided a basis for detecting natural interspecific hybridisation in forest trees for decades but have come to prominence again more recently as a means for directly measuring gene flow from planted forests. Here we examined the utility of seedling morphology for hybrid discrimination in three hybrid groups relevant to the monitoring of gene flow from plantings of Corymbia (L.D. Pryor & L.A.S. Johnson ex Brooker) taxa in subtropical Australia. Thirty leaf and stem characters were assessed on 907 8-month old seedlings from four parental and six hybrid taxa grown in a common garden. Outbred F1 hybrids between spotted gums (Corymbia citriodora subspecies variegata, C. citriodora subspecies citriodora and Corymbia henryi) tended to more closely resemble their maternal Corymbia torelliana parent and the most discriminating characters were the ratio of blade length to maximum perpendicular width, the presence or absence of a lignotuber, and specific leaf weight. Assignment of individuals into genealogical classes based on a multivariate model limited to a set of the more discriminating and independent characters was highest in the hybrid group, where parental taxa were genetically most divergent. Overall power to resolve among outbred F1 hybrids from both parental taxa was low to moderate, but this may not be a limitation to its likely major application of identifying hybrids in seedlots from native spotted gum stands. Advanced generation hybrids (outbred F2 and outbred backcrosses) were more difficult to resolve reliably due to the higher variances of hybrid taxa and the tendency of backcrosses to resemble their recurrent parents. Visual assessments of seedling morphology may provide a filter allowing screening of the large numbers needed to monitor gene flow, but will need to be combined with other hybrid detection methods to ensure hybrids are detected.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Validity of Charlson Comorbidity Index in patients hospitalised with acute coronary syndrome. Insights from the nationwide AMIS Plus registry 2002-2012

OBJECTIVE This study aimed to assess the impact of individual comorbid conditions as well as the weight assignment, predictive properties and discriminating power of the Charlson Comorbidity Index (CCI) on outcome in patients with acute coronary syndrome (ACS). METHODS A prospective multicentre observational study (AMIS Plus Registry) from 69 Swiss hospitals with 29 620 ACS patients enrolled from 2002 to 2012. The main outcome measures were in-hospital and 1-year follow-up mortality. RESULTS Of the patients, 27% were female (age 72.1±12.6 years) and 73% were male (64.2±12.9 years). 46.8% had comorbidities and they were less likely to receive guideline-recommended drug therapy and reperfusion. Heart failure (adjusted OR 1.88; 95% CI 1.57 to 2.25), metastatic tumours (OR 2.25; 95% CI 1.60 to 3.19), renal diseases (OR 1.84; 95% CI 1.60 to 2.11) and diabetes (OR 1.35; 95% CI 1.19 to 1.54) were strong predictors of in-hospital mortality. In this population, CCI weighted the history of prior myocardial infarction higher (1 instead of -0.4, 95% CI -1.2 to 0.3 points) but heart failure (1 instead of 3.7, 95% CI 2.6 to 4.7) and renal disease (2 instead of 3.5, 95% CI 2.7 to 4.4) lower than the benchmark, where all comorbidities, age and gender were used as predictors. However, the model with CCI and age has an identical discrimination to this benchmark (areas under the receiver operating characteristic curves were both 0.76). CONCLUSIONS Comorbidities greatly influenced clinical presentation, therapies received and the outcome of patients admitted with ACS. Heart failure, diabetes, renal disease or metastatic tumours had a major impact on mortality. CCI seems to be an appropriate prognostic indicator for in-hospital and 1-year outcomes in ACS patients. CLINICALTRIALSGOV IDENTIFIER NCT01305785.

Automatic 3d free form shape matching using the graduated assignment algorithm.

Liu, Yonghuai. Automatic 3d free form shape matching using the graduated assignment algorithm. Pattern Recognition, vol. 38, no. 10, pp. 1615-1631, 2005.

Efficient -tensor determination and NH assignment of paramagnetic proteins

Anisotropic magnetic susceptibility tensors chi of paramagnetic metal ions are manifested in pseudocontact shifts, residual dipolar couplings, and other paramagnetic observables that present valuable long-range information for structure determinations of protein-ligand complexes. A program was developed for automatic determination of the chi-tensor anisotropy parameters and amide resonance assignments in proteins labeled with paramagnetic metal ions. The program requires knowledge of the three-dimensional structure of the protein, the backbone resonance assignments of the diamagnetic protein, and a pair of 2D N-15-HSQC or 3D HNCO spectra recorded with and without paramagnetic metal ion. It allows the determination of reliable chi-tensor anisotropy parameters from 2D spectra of uniformly N-15-labeled proteins of fairly high molecular weight. Examples are shown for the 185-residue N-terminal domain of the subunit epsilon from E. coli DNA polymerase III in complex with the subunit theta and La3+ in its diamagnetic and Dy3+, Tb3+, and Er3+ in its paramagnetic form.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

The interaction between exercise, appetite and food intake : implications for weight control

Exercise could indirectly affect body weight by exerting changes on various components of appetite control, including nutrient and taste preferences, meal size and frequency, and the drive to eat. This review summarizes the evidence on how exercise affects appetite and eating behavior and in particular answers the question, “Does exercise induce an increase in food intake to compensate for the increase in energy expenditure?” Evidence will be presented to demonstrate that there is no automatic increase in food intake in response to acute exercise and that the response to repeated exercise is variable. The review will also identify areas of further study required to explain the variability. One limitation with studies that assess the efficacy of exercise as a method of weight control is that only mean data are presented—the individual variability tends to be overlooked. Recent evidence highlights the importance of characterizing the individual variability by demonstrating exercise-induced changes in appetite. Individuals who experience lower than theoretically predicted reductions in body weight can be characterized by hedonic (eg, pleasure) and homeostatic (eg, hunger) features.

Energy-based motion control of marine vehicles using interconnection and damping assignment passivity-based control : a survey

This paper reviews some recent results in motion control of marine vehicles using a technique called Interconnection and Damping Assignment Passivity-based Control (IDA-PBC). This approach to motion control exploits the fact that vehicle dynamics can be described in terms of energy storage, distribution, and dissipation, and that the stable equilibrium points of mechanical systems are those at which the potential energy attains a minima. The control forces are used to transform the closed-loop dynamics into a port-controlled Hamiltonian system with dissipation. This is achieved by shaping the energy-storing characteristics of the system, modifying its interconnection structure (how the energy is distributed), and injecting damping. The end result is that the closed-loop system presents a stable equilibrium (hopefully global) at the desired operating point. By forcing the closed-loop dynamics into a Hamiltonian form, the resulting total energy function of the system serves as a Lyapunov function that can be used to demonstrate stability. We consider the tracking and regulation of fully actuated unmanned underwater vehicles, its extension to under-actuated slender vehicles, and also manifold regulation of under-actuated surface vessels. The paper is concluded with an outlook on future research.

CBCT-guided radiotherapy for locally advanced head and cancer: dosimetric impact of weight loss on VMAT and IMRT plans for selected organs at risk structures (OARs)

Purpose: It is common for head and neck patients to be affected by time trend errors as a result of weight loss during a course of radiation treatment. The objective of this planning study was to investigate the impact of weight loss on Volumetric Modulated Arc Therapy (VMAT) as well as Intensity modulated radiation therapy (IMRT) for locally advanced head and neck cancer using automatic co-registration of the CBCT. Methods and Materials: A retrospective analysis of previously treated IMRT plans for 10 patients with locally advanced head and neck cancer patients was done. A VMAT plan was also produced for all patients. We calculated the dose–volume histograms (DVH) indices for spinal cord planning at risk volumes (PRVs), the brainstem PRVs (SC+0.5cm and BS+0.5cm, respectively) as well as mean dose to the parotid glands. Results: The results show that the mean difference in dose to the SC+0.5cm was 1.03% and 1.27% for the IMRT and VMAT plans, respectively. As for dose to the BS+0.5, the percentage difference was 0.63% for the IMRT plans and 0.61% for the VMAT plans. The analysis of the parotid gland doses shows that the percentage change in mean dose to left parotid was -8.0% whereas that of the right parotid was -6.4% for the IMRT treatment plans. In the VMAT plans, the percentages change for the left and the right parotid glands were -6.6% and -6.7% respectively. Conclusions: This study shows a clinically significant impact of weight loss on DVH indices analysed in head and neck organs at risk. It highlights the importance of adaptive radiotherapy in head and neck patients if organ at risk sparing is to be maintained.

A chitotetrose specific lectin from Luffa acutangula :Physico-chemical properties and the assignment of orientation of sugars in the lectin binding site

A chitooligosaccharide specific lectin (Luffa acutangula agglutinin) has been purified from the exudate of ridge gourd fruits by affinity chromatography on soybean agglutininglycopeptides coupled to Sepharose-6B. The affinity purified lectin was found homogeneous by polyacrylamide gel electrophoresis, in sodium dodecyl sulphate-polyacrylamide gels, by gel filtration on Sephadex G-100 and by sedimentation velocity experiments. The relative molecular weight of this lectin is determined to be 48,000 ± 1,000 by gel chromatography and sedimentation equilibrium experiments. The sedimentation coefficient (S20, w) was obtained to be 4·06 S. The Stokes’ radius of the protein was found to be 2·9 nm by gel filtration. In sodium dodecyl sulphate-polyacrylamide gel electrophoresis the lectin gave a molecular weight of 24,000 in the presence as well as absence of 2-mercaptoethanol. The subunits in this dimeric lectin are therefore held by non-covalent interactions alone. The lectin is not a glycoprotein and circular dichroism spectral studies indicate that this lectin has 31% α-helix and no ß-sheet. The lectin is found to bind specifically to chitooligosaccharides and the affinity of the lectin increases with increasing oligosaccharide chain length as monitored by near ultra-violetcircular dichroism and intrinsic fluorescence titration. The values of ΔG, ΔΗ and ΔS for the binding process showed a pronounced dependence on the size of the oligosaccharide. The values for both ΔΗ and ΔS show a significant increase with increase in the oligosaccharide chain length showing that the binding of higher oligomers is progressively more favoured thermodynamically than chitobiose itself. The thermodynamic data is consistent with an extended binding site in the lectin which accommodates a tetrasaccharide. Based on the thermodynamic data, blue shifts and fluorescence enhancement, spatial orientation of chitooligosaccharides in the combining site of the lectin is assigned.