Search results for "Machine"
showing 10 items of 2592 documents
Dataset related to article "Development and external validation of a clinical prediction model for functional impairment after intracranial tumor sur…
2021
Anonymised clinical database containing information (Age, sex, prior surgery, tumor histology and maximum diameter, expected major brain vessel or cranial nerve manipulation, resection in eloquent areas and the posterior fossa, and surgical approach were recorded) about patients of Fondazione IRCCS Istituto Besta analysed for the article “Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery”
Interactively Learning the Preferences of a Decision Maker in Multi-objective Optimization Utilizing Belief-rules
2020
Many real life problems can be modelled as multiobjective optimization problems. Such problems often consist of multiple conflicting objectives to be optimized simultaneously. Multiple optimal solutions exist to these problems, and a single solution cannot be said to be the best without preferences given by a domain expert. Preferences can be used to find satisfying solutions: optimal solutions, which best match the expert’s preferences. To model the preferences of the expert, and aid him/her in finding satisfying solutions, a novel method is proposed. The method utilizes machine learning combined with belief-rule based systems to adaptively train a belief rule based system to learn a domai…
Numerical and Experimental Study of a Novel Concept for Hydraulically Controlled Negative Loads
2016
This paper presents a numerical and experimental investigation of a novel concept that eliminates oscillations in hydraulic systems containing a counterbalance valve in series with a pressure compensated flow supply. The concept utilizes a secondary circuit where a low-pass filtered value of the load pressure is generated and fed back to the compensator of the flow supply valve. The novel concept has been implemented on a single boom actuated by a cylinder. A nonlinear model of the system has been developed and an experimental verification shows good correspondence between the model and the real system. The model is used for a parameter study on the novel concept. From the study it is found…
The role of Artificial intelligence in architectural design: conversation with designer and researchers
2020
The proliferation of data together with the increase of computing power in the last decade has triggered a new interest in artificial intelligence methods. Machine learning and in particular deep learning techniques, inspired by the topological structure of neurons network in brains, are omnipresent in the IT discourse, and generated new enthusiasms and fears in our society. These methods have already shown great effectiveness in fields far from architecture and have long been exploited in software that we use every day. Many computing libraries are available for anyone with some programming skills and allow them to "train" a neural network based on several types of data. The world of archi…
Enhancing identification of causal effects by pruning
2018
Causal models communicate our assumptions about causes and effects in real-world phe- nomena. Often the interest lies in the identification of the effect of an action which means deriving an expression from the observed probability distribution for the interventional distribution resulting from the action. In many cases an identifiability algorithm may return a complicated expression that contains variables that are in fact unnecessary. In practice this can lead to additional computational burden and increased bias or inefficiency of estimates when dealing with measurement error or missing data. We present graphical criteria to detect variables which are redundant in identifying causal effe…
Radiomics Analysis of Brain [18F]FDG PET/CT to Predict Alzheimer’s Disease in Patients with Amyloid PET Positivity: A Preliminary Report on the Appli…
2022
Background: Early in-vivo diagnosis of Alzheimer’s disease (AD) is crucial for accurate management of patients, in particular, to select subjects with mild cognitive impairment (MCI) that may evolve into AD, and to define other types of MCI non-AD patients. The application of artificial intelligence to functional brain [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography(CT) aiming to increase diagnostic accuracy in the diagnosis of AD is still undetermined. In this field, we propose a radiomics analysis on advanced imaging segmentation method Statistical Parametric Mapping (SPM)-based completed with a Machine-Learning (ML) application to predict the diagnosi…
Biological and Mechanical Characterization of the Random Positioning Machine (RPM) for Microgravity Simulations
2021
The rapid improvement of space technologies is leading to the continuous increase of space missions that will soon bring humans back to the Moon and, in the coming future, toward longer interplanetary missions such as the one to Mars. The idea of living in space is charming and fascinating; however, the space environment is a harsh place to host human life and exposes the crew to many physical challenges. The absence of gravity experienced in space affects many aspects of human biology and can be reproduced in vitro with the help of microgravity simulators. Simulated microgravity (s-μg) is applied in many fields of research, ranging from cell biology to physics, including cancer biology. In…
Improvements and applications of the elements of prototype-based clustering
2018
Clustering or cluster analysis is an essential part of data mining, machine learning, and pattern recognition. The most popularly applied clustering methods are partitioning-based or prototype-based methods. Prototype-based clustering methods usually have easy implementability and good scalability. These methods, such as K-means clustering, have been used for different applications in various fields. On the other hand, prototype-based clustering methods are typically sensitive to initialization, and the selection of the number of clusters for knowledge discovery purposes is not straightforward. In the era of big data, in high-velocity, ever-growing datasets, which can also be erroneous, outl…
The manipulation of Euribor: An analysis with machine learning classification techniques
2022
The manipulation of the Euro Interbank Offered Rate (Euribor) was an affair which had a great impact on in ternational financial markets. This study tests whether advanced data processing techniques are capable of classifying Euribor panel banks as either manipulating or non-manipulating on the basis of patterns found in quotes submissions. For this purpose, panel banks’ daily contributions have been studied and monthly variables obtained that denote different contribution patterns for Euribor panel banks. Thus, in accordance with the court verdict, banks are categorized as manipulating and non-manipulating and Machine Learning classification techniques such as Supervised Learning, Anomaly …
De la sauvagerie à la violence créatrice : regards sur les bris de machines dans la France du XIXe siècle
2013
International audience