A semiotic approach of multi-agent simulation for policy evaluation

Nowadays the changing environment becomes the main challenge for most of organizations, since they have to evaluate proper policies to adapt to the environment. In this paper, we propose a multi-agent simulation method to evaluate policies based on complex adaptive system theory. Furthermore, we propose a semiotic EDA (Epistemic, Deontic, Axiological) agent model to simulate agent's behavior in the system by incorporating the social norms reflecting the policy. A case study is also provided to validate our approach. Our research present better adaptability and validity than the qualitative analysis and experiment approach and the semiotic agent model provides high creditability to simulate agents' behavior.

Markers for nutrition studies: review of criteria for the evaluation of markers

The following criteria were identified as essential elements in the evaluation of markers: (1) the marker has a causal biological link with the endpoint, (2) there is a significant association between marker and endpoint in the target population, (3) marker changes consistently with the endpoint, e.g., in response to an intervention, and (4) change in the marker explains a substantial proportion of the change in the endpoint in response to the intervention.

Improving the evaluation of hydrological multi-model forecast performance in the Upper Danube Catchment

Medium range flood forecasting activities, driven by various meteorological forecasts ranging from high resolution deterministic forecasts to low spatial resolution ensemble prediction systems, share a major challenge in the appropriateness and design of performance measures. In this paper possible limitations of some traditional hydrological and meteorological prediction quality and verification measures are identified. Some simple modifications are applied in order to circumvent the problem of the autocorrelation dominating river discharge time-series and in order to create a benchmark model enabling the decision makers to evaluate the forecast quality and the model quality. Although the performance period is quite short the advantage of a simple cost-loss function as a measure of forecast quality can be demonstrated.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

An evaluation of the pedestrian classification in a multi-domain multi-modality setup

The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion.

Postoperative renal function evaluation, through RIFLE criteria, of elderly patients who underwent femur fracture surgery under spinal anesthesia

Introduction. The postoperative acute renal failure (ARF) incidence in different kinds of surgery has rarely been studied. Age, cardiac dysfunction, previous renal dysfunction, intraoperative hypoperfusion, and use of nephrotoxic medications are mentioned as risk factors for ARF at the postoperative period. The postoperative ARF definition was based on the creatinine increase by the RIFLE classification (R = risk, I = injury, F = failure, L = loss, E = end stage), which corresponds to a 1.5 creatinine increase, two to three times, respectively, above the basal value. This study aimed to evaluate the postoperative ARF incidence in elderly patients who underwent femur fracture surgery under subarachnoid anesthesia and stratify it by the RIFLE criteria. Methods. Ninety patients older than 65 years under spinal anesthesia with fixed dosage of 15 mg of 0.5% isobaric bupivacaine associated with morphine 50 g were studied. Immediate postoperative creatinine was considered basal and compared with maximal creatinine evaluated at 24, 48, and 72 postoperative hours. Results. The mean age of the patients was 80.27 years. ARF incidence was 24.44% and stratified this way: R = 21.11% and I = 3.33%. Conclusions. In conclusion, the postoperative ARF incidence after femur fracture surgery in patients over 65 years was 24.44%. By analyzing the stratification based on the RIFLE classification, the incidence was categorized as Risk (R) = 21.11% and Injury (I) = 3.33%.

Evaluation of alternate lines of Fe for sequential multi-element determination of Cu, Fe, Mn and Zn in soil extracts by high-resolution continuum source flame atomic absorption spectrometry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Pediatric Rheumatology International Trials Organization American-College-of-Rheumatology provisional criteria for the evaluation of response to therapy in juvenile systemic lupus erythematosus: Prospective validation of the definition of improvement

Objective. To use the Pediatric Rheumatology International Trials Organization (PRINTO) core set of outcome measures to develop a validated definition of improvement for the evaluation of response to therapy in juvenile systemic lupus erythematosus (SLE).Methods. Thirty-seven experienced pediatric rheumatologists from 27 countries, each of whom had specific experience in the assessment of juvenile SLE patients, achieved consensus on 128 patient profiles as being clinically improved or not improved. Using the physicians' consensus ratings as the gold standard measure, the chi-square, sensitivity, specificity, false-positive and false-negative rates, area under the receiver operating characteristic curve, and kappa level of agreement for 597 candidate definitions of improvement were calculated. Only definitions with a kappa value greater than 0.7 were retained. The top definitions were selected based on the product of the content validity score multiplied by its kappa statistic.Results. The definition of improvement with the highest final score was at least 50% improvement from baseline in any 2 of the 5 core set measures, with no more than 1 of the remaining worsening by more than 30%.Conclusion. PRINTO proposes a valid and reproducible definition of improvement that reflects well the consensus rating of experienced clinicians and that incorporates clinically meaningful change in core set measures in a composite end point for the evaluation of global response to therapy in patients with juvenile SLE. The definition is now proposed for use in juvenile SLE clinical trials and may help physicians to decide whether a child with SLE responded adequately to therapy.

Distributed generation impact evaluation using a multi-objective tabu search

Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the Distributed Generation penetration in passive networks considering different operation scenarios. Studying DG optimal siting and sizing the planner can identify the network behavior in presence of DG. Many approaches for the optimal DG allocation problem successfully used multi-objective optimization techniques. So this paper contributes to the fundamental stage of multi-objective optimization of finding the Pareto optimal solutions set. It is proposed the application of a Multi-objective Tabu Search and it was verified a better performance comparing to the NSGA-II method. © 2009 IEEE.

Performance evaluation of multi-stage filtration with use of granular activated carbon and synthetic non-woven fabrics

The multi stage filtration (MSF) is an alternative that permits to enlarge the spectrum of application of the slow sand filtration as for the effluent quality and run duration. In this research the use of MSF technology associated to a granular activated carbon (GAC) column as polishing mechanism of the final effluent was evaluated; in the slow sand filters GAC was used as an intermediate layer and non-woven synthetic fabrics were utilized as a first layer of the filter media. Five different tests were conducted, where the systems subjected to the treatment were: water from the Ipe Lake (Ilha Solteira, Sao Paulo, Brazil); water from the lake with water from a recreational fish pond; water from the lake with a phytoplankton and cyanobacteria overload simulation, with and without the use of the pre-filters as a stage of the treatment. The synthetic fabrics and GAC use resulted in the best turbidity removal and an efficient apparent and true color removal; in spite that the polishing columns reported similar results for those parameters. The utilization of GAC as an intermediate layer contributed to a better organic matter removal and the fabrics improved chlorophyll-a removal. The pre-filtration columns made an efficient algae and cyanobacteria removal, a function that was completed by the filters and reached >98% efficiency. The synthetic non-woven fabrics and GAC inclusion in MSF operation improved performance of this technology with ease of application and operation.

Online Shopping Websites: An Evaluation of User Experience and Interface Ergonomic Criteria from the Perspective of Older Users

This paper presents a user experience evaluation of two online shopping websites from the perspective of older users (those aged 50 and older). Two online shopping websites were evaluated using methodological procedures established in prior research [1]. The methodology consists of four steps: (1) heuristic interface evaluation using an ergonomic criteria checklist, (2) online identification and experience questionnaire, (3) evaluation of user experience and interface interaction, and (4) satisfaction questionnaire. Results of the study revealed the analyzed websites are not suitable for older users, who find it difficult to interact with these interfaces.

Evaluation of the temporal acoustic window for transcranial doppler in a multi-ethnic population in Brazil

The aim of this study was to relate the presence of a temporal acoustic window (TAW) to the variables sex, age and race. This observational study was conducted in patients under etiologic investigation after stroke, sickle-cell anemia and hospitalization in an intensive therapy neurologic unit. TAW presence was confirmed by bilateral assessment by two neurologists via transcranial Doppler (TCD). Multiple logistic regression was performed to explain the presence of the window as a function of sex, age and race. In 20% of the 262 patients evaluated, a TAW was not present. The incidence of TAW presence was greater in men (odds ratio [OR] = 5.4, 95% confidence interval [CI] = 2.5-11.7, p < 0.01); lower with increased age (OR = 0.9, 95% CI = 0.92-0.97, p < 0.01); and lower among those of African and Asian descent (OR = 0.32, 95% CI = 0.14-0.70, p = 0.005). On the basis of the results, more men than women had TAWs, and the decrease in TAWs was associated with increased age and African or Asian descent.

Evaluation of a multi variated analysis for the selection of t-tbar multijet events in the current CMS implemented environment at LHC

In the present study we are using multi variate analysis techniques to discriminate signal from background in the fully hadronic decay channel of ttbar events. We give a brief introduction to the role of the Top quark in the standard model and a general description of the CMS Experiment at LHC. We have used the CMS experiment computing and software infrastructure to generate and prepare the data samples used in this analysis. We tested the performance of three different classifiers applied to our data samples and used the selection obtained with the Multi Layer Perceptron classifier to give an estimation of the statistical and systematical uncertainty on the cross section measurement.