Humanoid Dynamic Controller

In the last years several investigators have focused on the development and control of humanoid robots able to acquire human behaviors and features, in order to be able to interact with humans and work together with them. The fall of a umanoid robot can lead to damages, which entail costs for repair or even human health risks, so ensuring stability is a main concern in terms of cost and safety. This document presents the implementation of a dynamic controller for humanoid robots, able to position the robot's center of mass in a certain location operating as a stability module. It is also described a precise behavior of preparing an omnidirectional kick for a humanoid robot by placing the support foot in a precise position and orientation calculated in accordance with the robot's position, the ball and the target, and by transferring the robot'scenter of mass to the desired position

New Potential Biomarkers for Chronic Kidney Disease Management—A Review of the Literature

The prevalence of chronic kidney disease (CKD) is increasing worldwide, and the mortality rate continues to be unacceptably high. The biomarkers currently used in clinical practice are considered relevant when there is already significant renal impairment compromising the early use of potentially successful therapeutic interventions. More sensitive and specific biomarkers to detect CKD earlier on and improve patients' prognoses are an important unmet medical need. The aim of this review is to summarize the recent literature on new promising early CKD biomarkers of renal function, tubular lesions, endothelial dysfunction and inflammation, and on the auspicious findings from metabolomic studies in this field. Most of the studied biomarkers require further validation in large studies and in a broad range of populations in order to be implemented into routine CKD management. A panel of biomarkers, including earlier biomarkers of renal damage, seems to be a reasonable approach to be applied in clinical practice to allow earlier diagnosis and better disease characterization based on the underlying etiologic process.info:eu-repo/semantics/publishedVersio

A Tool for Fast Development of Modular and Hierarchic Neural Network-based Systems

This paper presents PyramidNet tool as a fast and easy way to develop Modular and Hierarchic NeuralNetwork-based Systems. This tool facilitates the fast emergence of autonomous behaviors in agents becauseit uses a hierarchic and modular control methodology of heterogeneous learning modules: the pyramid.Using the graphical resources of PyramidNet the user is able to specify a behavior system even having little understanding of artificial neural networks. Experimental tests have shown that a very significant speedup is attained in the development of modular and hierarchic neural network-based systems by using this tool

Multi-strategy learning made easy

This paper presents the AFRANCI tool for the development of Multi-Strategy learning systems. Designing a Multi-Strategy system using AFRANCI is a two step process. The use interactively designs the structure of the system and then chooses the learning strategies for each module. After providing the datasets all modules as automatically trained. The system is aware and takes into consideration the inter-dependency of the modules. The tool has built-in learning algorithms but can use external programs implementing the learning algorithms. The tool has the following facilities. It allows any user to design in an interactive and easy fashion the structure of the target system. The structure of the target system is a collection of interconnected modules. The user may then choose the different learning algorithms to construct each module. The tool has several built-in Machine Learning algorithms has has interfaces that enables it to use external learning tools like WEKA and CN2. AFRANCI uses the interdependency of the modules to determine the sequence of training. For each module the system uses a wrapper to tune automatically the parameters of the learning algorithm. In the final step of the design sequence AFRANCI generates a compact and legible ready-to-use ANSI C open-source code for the final system

A tool for Multi-Strategy Learning

This paper presents the AFRANCI tool for the developmentof Multi-Strategy learning systems. AFRANCI allows users to build, inan interactive and easy way, complex systems. Systems are built using atwo step methodology: design of the structure of the system; and fill inthe modules. The structure of the target system is a collection of interconnectedmodules. The user may then choose among a variety of learningalgorithms to construct each module. The tool has several built-in MachineLearning algorithms and interfaces that enable it to use externallearning tools like WEKA or CN2. AFRANCI uses the interdependencyof the modules to determine the sequence of their training. To improveusability, the tool uses a wrapper that hides from the user the parametertuning procedure for each algorithm. In a final step of the designsequence AFRANCI generates a compact and legible ready-to-use ANSIC++ open-source code for the final system.To illustrate the concept we have empirically evaluated the tool in thecontext of the RoboCup Rescue domain. We have developed a smallsystem that uses both neural networks and rules in the same system.The experiment have shown that a very significant speed up is attainedin the development of systems when using this tool

Image quality assessment of head CT: Control charts as an useful instrument

Themain objective of this research was to determine if the diagnostic image, acquired by CT scan, meets the quality criteria previously established for head CT exams. A total of 360 Head Computed Tomography exams were analyzed, using a checklist. For data collection, quality criteria were created, organized into four criteria groups, consisting of multiple items that must appear in the images studies. After data processing, a large number of non-conformexaminations were identified in than more than 50% of the sample. We concluded the main causes of these results are: the “incorrect or incomplete positioning”, the "lack of name of the radiographer and “motion artefacts”. Therefore it is essential to implement a checklist for a systematic evaluationof procedures.info:eu-repo/semantics/publishedVersio

Fine-tuning artificial neural networks automatically

To get the most out of powerful tools expert knowledge is often required. Experts are the ones with the suitable knowledge to tune the tools parameters. In this paper we assess several techniques which can automatically fine tune ANN parameters. Those techniques include the use of GA and Stratified Sampling. The tuning includes the choice of the best ANN structure and the best network biases and their weights. Empirical resultsachieved in experiments performed using nine heterogeneous data sets show that the use of the proposed Stratified Sampling technique is advantageous

Selective laser melting (SLM) and topology optimization for lighter aerospace componentes

AbstractAdditive Manufacturing (AM) is a manufacturing process through which a 3D component is produced by consecutively adding material. One of the most promising AM processes is SLM. In SLM a laser completely melts metallic powder particles together forming a 3D component. SLM is known for its freedom of manufacturing constraints allowing complex geometries and high material efficiency. Topology Optimisation (TO) is an optimisation type that calculates the optimal material distribution for a given problem. The combination of SLM with TO is being developed to create lightweight components. In this work, the whole development process, from optimisation to design, production and testing is addressed. Initially, an aircraft bracket topology was optimised to be produced by means of SLM. The TO solution was interpreted and designed for AM. During the interpretation and design process, a design methodology was defined in order to facilitate and make more accurate the TO solution design and make it ready for AM. After the optimised component was produced, metrological and mechanical tests were performed in order to validate the final design and the computer analysis. The optimised component showed considerable weight reduction with an increase of the factor of safety. The experimental tests revealed a good relation to the computer analysis evidencing, however, room for improvement, both in the computer model and the experimental tests