Software defect prediction based on association rule classification.

In software defect prediction, predictive models are estimated based on various code attributes to assess the likelihood of software modules containing errors. Many classification methods have been suggested to accomplish this task. However, association based classification methods have not been investigated so far in this context. This paper assesses the use of such a classification method, CBA2, and compares it to other rule based classification methods. Furthermore, we investigate whether rule sets generated on data from one software project can be used to predict defective software modules in other, similar software projects. It is found that applying the CBA2 algorithm results in both accurate and comprehensible rule sets.Software defect prediction; Association rule classification; CBA2; AUC;

Five-year mortality and related prognostic factors after inpatient stroke rehabilitation : A European multi-centre study

Objective: To determine 5-year mortality and its association with baseline characteristics and functional status 6 months post-stroke for patients who received inpatient rehabilitation. Design: A prospective rehabilitation-based cohort study. Subjects: A total of 532 consecutive stroke patients from 4 European rehabilitation centres. Methods: Predictors were recorded on admission. Barthel Index was assessed at 6 months (BI6mths) and patients were followed for 5 years post-stroke. Survival probability was computed using Kaplan-Meier analysis and compared across 3 BI6mths-classes (0-60, 65-90, 95-100) (log-rank test). Significant independent predictors were determined using multivariate Cox regression analysis (hazard ratio (HR)). Results: Five-year cumulative risk of death was 29.12% (95% confidence interval (CI): 22.86-35.38). Age (HR = 1.06, 95% CI: 1.04-1.09), cognitive impairment (HR = 1.77, 95% CI: 1.21-2.57), diabetes mellitus (HR = 1.68, 95% CI: 1.16- 2.41) and atrial fibrillation (HR = 1.52, 95% CI: 1.08-2.14) were independent predictors of increased mortality. Hyperlipidaemia (HR = 0.66, 95% CI: 0.46-0.94), and higher BI6mths (HR = 0.98, 95% CI: 0.97-0.99) were independent predictors of decreased mortality. Five-year survival probability was 0.85 (95% CI: 0.80-0.89) for patients in BI6mthsclass: 95-100, 0.72 (95% CI: 0.63-0.79) in BI6mths-class: 65-90 and 0.50 (95% CI: 0.40-0.60) in BI6mths-class: 0-60 (p < 0.0001). Conclusion: Nearly one-third of rehabilitation patients died during the first 5 years following stroke. Functional status at 6 months was a powerful predictor of long-term mortality. Maximum functional independence at 6 months post-stroke should be promoted through medical interventions and rehabilitation. Future studies are recommended to evaluate the direct effect of rehabilitation on long-term survival

Variations in follow-up services after inpatient stroke rehabilitation: A multicentre study

Background: Care after discharge from inpatient stroke rehabilitation units varies across Europe. The aim of this study was to compare service delivery after discharge. Methods: A total of 532 consecutive patients after stroke were recruited from 4 European rehabilitation centres in Germany, Switzerland, Belgium and the UK. At 2-month intervals, clinical assessments and structured interviews were carried out to document functional status and delivery of services after discharge. Significant factors for receiving follow-up services were analysed using a logistic generalized estimating equation model. Results: After controlling for case-mix, the results showed that Belgian patients were most likely to receive physical therapy but least likely to receive occupational therapy. German patients were least likely to receive nursing care. UK patients were less likely to receive medical care from their general practitioner compared with the other patient groups. Conclusion: Clinical characteristics did not explain the variations in service delivery after discharge from inpatient stroke rehabilitation. The decision-making processes involved in the provision of follow-up services need to be better documented. To improve our understanding of events post-discharge, the influence of non-clinical factors, such as healthcare regulations, should be explored further

Objective Prediction of Pharyngeal Swallow Dysfunction in Dysphagia through Artificial Neural Network Modelling

This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving'. © 2016 John Wiley & Sons LtdBackground Pharyngeal pressure-flow analysis (PFA) of high resolution impedance-manometry (HRIM) with calculation of the swallow risk index (SRI) can quantify swallow dysfunction predisposing to aspiration. We explored the potential use of artificial neural networks (ANN) to model the relationship between PFA swallow metrics and aspiration and to predict swallow dysfunction. Methods Two hundred consecutive dysphagia patients referred for videofluoroscopy and HRIM were assessed. Presence of aspiration was scored and PFA software derived 13 metrics and the SRI. An ANN was created and optimized over training cycles to achieve optimal classification accuracy for matching inputs (PFA metrics) to output (presence of aspiration on videofluoroscopy). Application of the ANN returned a value between 0.00 and 1.00 reflecting the degree of swallow dysfunction. Key Results Twenty one patients were excluded due to insufficient number of swallows (<4). Of 179, 58 aspirated and 27 had aspiration pneumonia history. The SRI was higher in aspirators (aspiration 24 [9, 41] vs no aspiration 7 [2, 18], p < 0.001) and patients with pneumonia (pneumonia 27 [5, 42] vs no pneumonia 8 [3, 24], p < 0.05). The ANN Predicted Risk was higher in aspirators (aspiration 0.57 [0.38, 0.82] vs no aspiration 0.13 [0.4, 0.25], p < 0.001) and in patients with pneumonia (pneumonia 0.46 [0.18, 0.60] vs no pneumonia 0.18 [0.6, 0.49], p < 0.01). Prognostic value of the ANN was superior to the SRI. Conclusions & Inferences In a heterogeneous cohort of dysphagia patients, PFA with ANN modeling offers enhanced detection of clinically significant swallowing dysfunction, probably more accurately reflecting the complex interplay of swallow characteristics that causes aspiration

Computer simulation of glioma growth and morphology

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion

Modélisations multiphysiques, réalisation et expérimentations d'un haut-parleur digital matriciel piézoélectrique MEMS

The Digital Loudspeaker Array (DLA) is an electroacoustic transducer which receives as input a digital signal and performs the analog conversion directly into the air. It consists of a plurality of radiating elements arranged in a matrix. These elements will be designated by the term “speaklet” when they are reduced in size. The acoustic radiation of a DLA is indeed very sensitive to the size of the matrix due to differences in path length, which makes it especially suitable for MEMS technology. This thesis is on the study of a piezoelectric MEMS DLA. After an introduction that is increasingly focused on the subject, the thesis addresses the multiphysics modeling of the DLA, dimensioning of the speaklets and experimental tests. Analytical formulas, numerical simulations and finite element models are developed and used to predict the mechanical behavior of the presented speaklets, the pressure radiated by the DLA and the electrical power consumption. The speaklet are then dimensioned from the technological stack (set in advance) in order to maximize the pressure level. Experimental tests involving the use of an anechoic chamber, an optical interferometer, a vibrometer and an impedancemeter validate most of the models. Otherwise, these tests are usefull for improving some of them or for showing their limitations. The results have shown the importance of the residual stresses, which cause an initial deformation of the speaklets and modify their resonance frequencies, thus rendering ineffective the use of large radii. In accordance with the models, the static deflection of the speaklets is nonlinear but their dynamic behavior is linear. This enables characterizations using transfer functions. Theory and sound recordings show that a DLA made of such speaklets can produce in the best case the same pressure to that generated by the same matrix driven in an analog way. In our case, more distortions were obtained in digital reconstructions because of non-uniform responses of the speaklets, due to different access resistances. However, the presented DLA has other advantages, the most important being the very low power consumption it is theoretically possible to achieve using the adiabatic charge principle. The piezoelectric MEMS DLA thus appears as a promising technology. The optimization of our first prototype using the developed tools should indeed lead to a DLA able to generate an equivalent presure to that obtained with analog control, but with a far greater electroacoustic efficiency. Future work should then focus on the design of nonlinear speaklets and on the shaping of the pulse of pressure they generate, in order to increase the total pressure level.Le Haut-Parleur Digital Matriciel (HPDM) est un moyen de transduction électroacoustique qui reçoit comme entrée un signal numérique et qui effectue la conversion vers l'analogique directement dans l'air. Il est constitué de plusieurs éléments rayonnants disposés au sein d'une matrice. Ces éléments seront désignés par le terme «speaklet» lorsqu'ils sont de tailles réduites. Le rayonnement acoustique du HPDM est en effet très sensible à la taille de la matrice, ce qui le rend tout particulièrement adapté à la technologie MEMS. Cette thèse porte sur l'étude de HPDM MEMS piézoélectriques. Après une introduction qui débute par certaines généralités jusqu'à se focaliser sur le sujet, la thèse aborde les modélisations multiphysiques des HPDM étudiés, le dimensionnement des speaklets puis les tests expérimentaux. Des modèles analytiques ainsi que des simulations numériques et par éléments finis sont mis en place et permettent de prédire le comportement mécanique des speaklets présentés, les pressions rayonnées par les HPDM et les puissances électriques consommées. Les speaklets sont ensuite dimensionnés à partir de l'empilement technologique afin de maximiser le niveau de pression qu'ils génèrent. Des tests expérimentaux permettent alors de valider la majorité des modèles ou au contraire de revenir sur certains d'entre eux pour les optimiser ou montrer leurs limitations. Les résultats ont en effet montré l'importance de la prise en compte des contraintes résiduelles, qui provoquent une déformée initiale des speaklets et modifient leurs fréquences propres, rendant alors l'utilisation de grands rayons inefficaces. En accord avec les modèles, les speaklets possèdent un comportement dynamique linéaire, ce qui permet de les caractériser à l'aide de fonctions de transfert. La théorie et les enregistrements sonores montrent alors qu'un HPDM composé de tels speaklets permet dans le meilleur des cas de produire une pression identique à celle générée par la même matrice pilotée en analogique. Dans notre cas, des taux de distorsions supérieurs ont été obtenus lors des reconstructions digitales, à cause des réponses non uniformes des speaklets, dues à des résistances d'accès différentes. Le HPDM présenté possède cependant d'autres avantages, le plus important étant la très faible consommation électrique qu'il est théoriquement possible d'atteindre en utilisant les méthodes de charges et de décharges adiabatiques. Le HPDM piézoélectrique MEMS apparait donc comme étant une technologie prometteuse. L'optimisation de notre premier prototype à l'aide des outils développés doit en effet conduire à un HPDM capable de générer une pression équivalente à celle obtenue en mode analogique, mais avec un rendement électroacoustique beaucoup plus important. Les futurs travaux devront ensuite se concentrer sur la conception de speaklets non-linéaires et sur la forme du pulse de pression qu'ils génèrent, afin de gagner en niveau sonore

Vermindert een heupprotector het risico op een heupfractuur?

bespreking artikel Douglas P. Kiel, MD, MPH; et al. Efficacy of a Hip Protector to Prevent Hip Fracture in Nursing Home Residents. JAMA 2007, 298 (4): 413-422

Is the metabolic cost of walking higher in people with diabetes?

People with diabetes walk slower and display biomechanical gait alterations compared with controls, but it remains unknown whether the metabolic cost of walking (CoW) is elevated. The aim of this study was to investigate the CoW and the lower limb concentric joint work as a major determinant of the CoW, in patients with diabetes and diabetic peripheral neuropathy (DPN). Thirty-one nondiabetic controls (Ctrl), 22 diabetic patients without peripheral neuropathy (DM), and 14 patients with moderate/severe DPN underwent gait analysis using a motion analysis system and force plates and treadmill walking using a gas analyzer to measure oxygen uptake. The CoW was significantly higher particularly in the DPN group compared with controls and also in the DM group (at selected speeds only) compared with controls, across a range of matched walking speeds. Despite the higher CoW in patients with diabetes, concentric lower limb joint work was significantly lower in DM and DPN groups compared with controls. The higher CoW is likely due to energetic inefficiencies associated with diabetes and DPN reflecting physiological and biomechanical characteristics. The lower concentric joint work in patients with diabetes might be a consequence of kinematic gait alterations and may represent a natural strategy aimed at minimizing the CoW