Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

Denoising of LSFCM images with compensation for the photoblinking/photobleaching effects

Fluorescence confocal microscopy images present a low signal to noise ratio and a time intensity decay due to the so called photoblinking and photobleaching effects. These effects, together with the Poisson multiplicative noise that corrupts the images, make long time biological observation processes very difficult.

On the analysis of compensation correctness

One fundamental idea of service-oriented computing is that applications should be developed by composing already available services. Due to the long running nature of service interactions, a main challenge in service composition is ensuring correctness of transaction recovery. In this paper, we use a process calculus suitable for modelling long running transactions with a recovery mechanism based on compensations. Within this setting, we discuss and formally state correctness criteria for compensable processes compositions, assuming that each process is correct with respect to transaction recovery. Under our theory, we formally interpret self-healing compositions, that can detect and recover from faults, as correct compositions of compensable processes. Moreover, we develop an automated verification approach and we apply it to an illustrative case study.

The impact of SFAS 123R on CEO equity compensation

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Consumption and emotional compensation in economic crisis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Measurement of the correlation between flow harmonics of different order in lead-lead collisions at root S-NN=2.76 TeV with the ATLAS detector

Correlations between the elliptic or triangular flow coefficients vm (m=2 or 3) and other flow harmonics vn (n=2 to 5) are measured using sNN−−−−√=2.76 TeV Pb+Pb collision data collected in 2010 by the ATLAS experiment at the LHC, corresponding to an integrated lumonisity of 7 μb−1. The vm-vn correlations are measured in midrapidity as a function of centrality, and, for events within the same centrality interval, as a function of event ellipticity or triangularity defined in a forward rapidity region. For events within the same centrality interval, v3 is found to be anticorrelated with v2 and this anticorrelation is consistent with similar anticorrelations between the corresponding eccentricities ϵ2 and ϵ3. On the other hand, it is observed that v4 increases strongly with v2, and v5 increases strongly with both v2 and v3. The trend and strength of the vm-vn correlations for n=4 and 5 are found to disagree with ϵm-ϵn correlations predicted by initial-geometry models. Instead, these correlations are found to be consistent with the combined effects of a linear contribution to vn and a nonlinear term that is a function of v22 or of v2v3, as predicted by hydrodynamic models. A simple two-component fit is used to separate these two contributions. The extracted linear and nonlinear contributions to v4 and v5 are found to be consistent with previously measured event-plane correlations.

Exercise and heart failure. Relation of the severity of the disease to the anaerobic threshold and the respiratory compensation point

OBJECTIVE - To identify, the anaerobic threshold and respiratory compensation point in patients with heart failure. METHODS - The study comprised 42 Men,divided according to the functional class (FC) as follows: group I (GI) - 15 patients in FC I; group II (GII) - 15 patients in FC II; and group III (GIII) - 12 patients in FC III. Patients underwent a treadmill cardiopulmonary exercise test, where the expired gases were analyzed. RESULTS - The values for the heart rate (in bpm) at the anaerobic threshold were the following: GI, 122±27; GII, 117±17; GIII, 114±22. At the respiratory compensation point, the heart rates (in bpm) were as follows: GI, 145±33; GII, 133±14; GIII 123±22. The values for the heart rates at the respiratory compensation point in GI and GIII showed statistical difference. The values of oxygen consumption (VO2) at the anaerobic threshold were the following (in ml/kg/min): GI, 13.6±3.25; GII, 10.77±1.89; GIII, 8.7±1.44 and, at the respiratory compensation point, they were as follows: GI, 19.1±2.2; GII, 14.22±2.63; GIII, 10.27±1.85. CONCLUSION - Patients with stable functional class I, II, and III heart failure reached the anaerobic threshold and the respiratory compensation point at different levels of oxygen consumption and heart rate. The role played by these thresholds in physical activity for this group of patients needs to be better clarified.

Computer-assisted motion compensation and analysis of perfusion ultrasound data

Magdeburg, Univ., Fak. für Informatik, Diss., 2014

Motion compensation strategies in magnetic resonance imaging.

Image quality in magnetic resonance imaging (MRI) is considerably affected by motion. Therefore, motion is one of the most common sources of artifacts in contemporary cardiovascular MRI. Such artifacts in turn may easily lead to misinterpretations in the images and a subsequent loss in diagnostic quality. Hence, there is considerable research interest in strategies that help to overcome these limitations at minimal cost in time, spatial resolution, temporal resolution, and signal-to-noise ratio. This review summarizes and discusses the three principal sources of motion: the beating heart, the breathing lungs, and bulk patient movement. This is followed by a comprehensive overview of commonly used compensation strategies for these different types of motion. Finally, a summary and an outlook are provided.

The Recovery of Health Service Costs in Cases Involving Personal Injury Compensation (205KB)

A Consultation Document

Report of the State Claims Agency on Compensation for Thalidomide Survivors

Report of the State Claims Agency on Compensation for Thalidomide Survivors Click here to download PDF 279KB

Does metabolic compensation explain the majority of less-than-expected weight loss in obese adults during a short-term severe diet and exercise intervention?

Objective:We investigated to what extent changes in metabolic rate and composition of weight loss explained the less-than-expected weight loss in obese men and women during a diet-plus-exercise intervention.Design:In all, 16 obese men and women (41±9 years; body mass index (BMI) 39±6 kg m(-2)) were investigated in energy balance before, after and twice during a 12-week very-low-energy diet(565-650 kcal per day) plus exercise (aerobic plus resistance training) intervention. The relative energy deficit (EDef) from baseline requirements was severe (74%-87%). Body composition was measured by deuterium dilution and dual energy X-ray absorptiometry, and resting metabolic rate (RMR) was measured by indirect calorimetry. Fat mass (FM) and fat-free mass (FFM) were converted into energy equivalents using constants 9.45 kcal per g FM and 1.13 kcal per g FFM. Predicted weight loss was calculated from the EDef using the '7700 kcal kg(-1) rule'.Results:Changes in weight (-18.6±5.0 kg), FM (-15.5±4.3 kg) and FFM (-3.1±1.9 kg) did not differ between genders. Measured weight loss was on average 67% of the predicted value, but ranged from 39% to 94%. Relative EDef was correlated with the decrease in RMR (R=0.70, P<0.01), and the decrease in RMR correlated with the difference between actual and expected weight loss (R=0.51, P<0.01). Changes in metabolic rate explained on average 67% of the less-than-expected weight loss, and variability in the proportion of weight lost as FM accounted for a further 5%. On average, after adjustment for changes in metabolic rate and body composition of weight lost, actual weight loss reached 90% of the predicted values.Conclusion:Although weight loss was 33% lower than predicted at baseline from standard energy equivalents, the majority of this differential was explained by physiological variables. Although lower-than-expected weight loss is often attributed to incomplete adherence to prescribed interventions, the influence of baseline calculation errors and metabolic downregulation should not be discounted.