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Diabetes mellitus and obesity are becoming some of the most serious public health challenges in the world. To help researchers more quickly reveal the complex relationships existing between diabetes mellitus, obesity, and related diseases in the literature, and give them an inspiration to search the effective treatments for these diseases, we propose a novel model named as representative latent Dirichlet...
Network Functions Virtualization allows Communication Service Providers to extend their traditional service portfolio to new models of service offerings, such as Virtualized Network Functions as a Service (VNFaaS), in which network functions can be traded following the “on-demand” Cloud paradigm. Incremental deployment and interoperability with legacy infrastructure, in particular Wide Area Network...
With the fast development of the social economy and the improving diverse material life, the demand for a much higher quality of living environment is increasing, thus, the importance to design the urban landscaping for a city is superior to that of the city planning and its ecological environment. Considering the circumstances that the extensive pattern of management in urban landscaping and the...
Unlike general purpose computer architectures that are comprised of complex processor cores and sequential computation, the brain is innately parallel and contains highly complex connections between computational units (neurons). Key to the architecture of the brain is a functionality enabled by the combined effect of spiking communication and sparse connectivity with unique variable efficacies and...
Context: We investigate the different perceptions of quality provided by leading operational quality models when used to evaluate software systems from an industry perspective. Goal: To compare and evaluate the quality assessments of two competing quality models and to develop an extensible solution to meet the quality assurance measurement needs of an industry stakeholder -The Construction Engineering...
Mimicking the collaborative behavior of biological swarms, such as bird flocks and ant colonies, Swarm Intelligence algorithms provide efficient solutions for various optimization problems. On the other hand, a computational model of the human brain, spiking neural networks, has been showing great promise in recognition, inference, and learning, due to recent emergence of neuromorphic hardware for...
Purpose of this study was to develop a fall prediction model based on various variables with linear and nonlinear analysis using postural sway. The included variables in the regression model were Sample Entropy, Largest Lyapunov exponent and Hurst exponent in anterior-posterior direction, which are nonlinear variables. Accuracy of this regression model for fall prediction was 81.9%.
Many scientific experiments in Bioinformatics are executed as computational workflows. Frequently, it is necessary to re-run an experiment under the original circumstances in which it was run to recognize and validate it. Data provenance concerns the origin of data. Knowing the data source facilitates the understanding and analysis of the results, by detailing and documenting the history and the paths...
Biomedical semantic indexing refers to annotating biomedical citations with Medical Subject Headings, which is crucial for texting mining, information retrieval and other researches in the field of bioinformatics. The traditional methods ignore the relations among labels and need complicated feature engineering. In this paper, we present a novel model with a deep serial multi-task learning structure,...
There are many models for simulating infectious disease outbreaks that assist health policy officials in making better decisions about mitigation strategies in the event of an epidemic. However, none of the existing models address the need to train students and policy makers in the concepts and use of such models. In this paper, we present Flu MODELO 1.0, an implementation of a model that simulates...
Computer science solutions for molecular biology problems are often presented in the form of workflows. There is a set of activities performed by different processing entities through managed tasks. Knowledge about the data trajectory throughout a given workflow enables reproducibility by data provenance. In order to reproduce an in silico bioinformatics experiment one must consider other aspects...
Big data analysis has been pervasively adopted as a method to analyze the tremendous amount of daily generated high throughput data in an efficient and accurate manner. Among the series of tools available in the field of big biomedical data, correlation networks are one of the most powerful tools for modelling gene expression, which is important in the study of disease and ageing. With the help of...
Forecasting models that utilize multiple predictors are gaining popularity in a variety of fields. In some cases they allow constructing more precise forecasting models, leveraging the predictive potential of many variables. Unfortunately, in practice we do not know which observed predictors have a direct impact on the target variable. Moreover, adding unrelated variables may diminish the quality...
Accurate and high-resolution maps of vegetation are critical for projects seeking to understand the terrestrial ecosystem processes and land-atmosphere interactions in Arctic ecosystems, such as U.S. Department of Energy's Next Generation Ecosystem Experiment (NGEE) Arctic. However, most existing Arctic vegetation maps are at a coarse resolution and with a varying degree of detail and accuracy. Remote...
Vaccines represent nowadays one of the most efficient weapons against foreign pathogens. To be effective, vaccines need a proper administration strategy that requires multiple administrations in order to ensure the acquisition of immunological memory. Vaccination schedules are usually based on past experience, and economical, ethical and time constraints have limited the research for better combinations...
Motivation: Next-generation sequencing (NGS) technologies using DNA, RNA, or methylation sequencing are prevailing tools used in modern genome research. For DNA sequencing, whole genome sequencing (WGS) and whole exome sequencing (WES) are two typical applications with a different preference on the trade-off between sequencing depth and base coverage. Although sequencing costs have been greatly reduced,...
This paper proposes a modeling for articulated robots based in an adaptation of the Kuramotos model. In order to simplify and help new people interested in work with it, mathematical models were made for the differential equations of first and second order from these. The modeling of this problem was based on computational modeling for solving ordinary differential equations. Among the available methods,...
Handling of deformable objects with industrial robots holds many unresolved challenges. Especially, describing and predicting the deformed state is computationally expensive and therefore difficult under the requirements of manufacturing environments. A concept for a simulation-based approach towards bin picking of deformable objects, is presented in this paper. The emphasis of the approach lies on...
In this work we used time series modelling for generating synthetic sets of hourly solar irradiance for the city of Petrolina located in the northeastern region of Brazil. The models were obtained for each month and were based on 20 years of satellite data. For each month, four time series structures were investigated: auto regressive, auto regressive integrated, auto regressive moving average and...
We develop an intelligent credit rating system that can provide debtors' rating information without involving credit rating agencies. Several models are used for credit scoring in our work, including the Duffie's model, logistic regression, and random forest. We compare the performance of these models and build an in-depth understanding of the evaluation of credit rating. Furthermore, we propose a...
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