Search results for "Machine"

Non Linear Fitting Methods for Machine Learning

2017

This manuscript presents an analysis of numerical fitting methods used for solving classification problems as discriminant functions in machine learning. Non linear polynomial, exponential, and trigonometric models are mathematically deduced and discussed. Analysis about their pros and cons, and their mathematical modelling are made on what method to chose for what type of highly non linear multi-dimension problems are more suitable to be solved. In this study only deterministic models with analytic solutions are involved, or parameters calculation by numeric methods, which the complete model can subsequently be treated as a theoretical model. Models deduction are summarised and presented a…

A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Popu…

2021

Objective: We explored the risk factors for intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) and constructed a prediction model based on machine learning algorithms.Methods: A retrospective study including 1,398 KD patients hospitalized in 7 affiliated hospitals of Chongqing Medical University from January 2015 to August 2020 was conducted. All patients were divided into IVIG-responsive and IVIG-resistant groups, which were randomly divided into training and validation sets. The independent risk factors were determined using logistic regression analysis. Logistic regression nomograms, support vector machine (SVM), XGBoost and LightGBM prediction models wer…

Power dispatching techniques as a finite state machine for a standalone photovoltaic system with a hybrid energy storage

2020

Standalone photovoltaic system (SPVS) is usually embedded with an energy storage unit to overcome the intermittency of photovoltaic (PV) generation as well as to address load variations in off-grid operation. In SPVS energy systems, batteries can serve as the long term energy storage and contributing to the large portion of the energy demand but to overcome the load intermittency, it necessitates a fast response energy storage embedded with the battery as a hybrid energy storage (HES) for dynamic loads (e.g., Electric Vehicle loads, emergency power management). In this work, Lead-Acid (LA) battery and supper capacitor (SC) array are used as the HES. HES helps not only in increasing more uti…

Mobile Edge Computing: Architetture ed Analisi della Live Migration

2020

Con l'ormai prossima rete mobile 5G entreranno a far parte della nostra quotidianità nuovi servizi applicativi, mai prima possibili, grazie all'avvicinamento di risorse di calcolo e di memoria nei pressi dell'utente in mobilità. Un’architettura abilitante i futuri servizi è quella di Mobile Edge Computing (MEC) in cui cloud di capacità inferiori rispetto a quelli presenti nella core della rete sono dislocati nei pressi della stazioni radio e metteranno a disposizione risorse di calcolo tali da permettere, tramite la tecnica di offloading, la fruizione di servizi quali realtà aumentata, gaming online, contenuti streaming ad alta risoluzione ed operazioni di data analytics. Ogni nuovo paradig…

Process specification and verification

1996

Graph grammars provide a very convenient specification tool for distributed systems of processes. This paper addresses the problem how properties of such specifications can be proven. It shows a connection between algebraic graph rewrite rules and temporal (trace) logic via the graph expressions of [2]. Statements concerning the global behavior can be checked by local reasoning.

Machine Learning: WEKA

2015

Cada vez más se utilizan ingentes cantidades de datos lo que conlleva la necesidad de extraer información útil para la toma de decisiones. La minería de datos es una tarea dentro de este proceso que utiliza la estadística como herramienta fundamental.

CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease

2023

AbstractThis study was aimed to investigate the predictive value of the radiomics features extracted from pericoronaric adipose tissue — around the anterior interventricular artery (IVA) — to assess the condition of coronary arteries compared with the use of clinical characteristics alone (i.e., risk factors). Clinical and radiomic data of 118 patients were retrospectively analyzed. In total, 93 radiomics features were extracted for each ROI around the IVA, and 13 clinical features were used to build different machine learning models finalized to predict the impairment (or otherwise) of coronary arteries. Pericoronaric radiomic features improved prediction above the use of risk factors alon…

Coding Sequences with Constraints

1990

In this paper we consider the following problem: given all bi-infinite sequences of symbols satisfying certain constraints, search for a set X of words such that i): any concatenation of elements of X satisfies these constraints and ii): any sequence verifying the constraints can be “parsed” in elements of X.

Codes and automata

2006

Magnetic Stochastic Resonance in systems described by Dynamic Preisach Model

2008

Stochastic resonance (SR) is generally considered as an enhancement of the system response for certain finite values of the noise strength. In particular the signal to noise ratio (SNR) and the signal amplification show a maximum as a function of the noise intensity. This effect has been experimentally observed in many physical systems and also in magnetic systems. However, as far as magnetic systems are concerned, the dynamic features of the systems have been neglected and it has been assumed that the typical relaxation time is negligible. However this is clearly a rough approximation. In order to clarify this relation, in this paper we numerically study magnetic stochastic resonance in se…