Search results for "computer.software_genre"

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…

The merits and limits of pooling data from nuclear power worker studies

2015

Control of dataset bias in combined Affymetrix cohorts of triple negative breast cancer

2014

AbstractHeterogenous subtypes of breast cancer need to be analyzed separately. Pooling of datasets can provide reasonable sample sizes but dataset bias is an important concern. We assembled a combined dataset of 579 Affymetrix microarrays from triple negative breast cancer (TNBC) in Gene Expression Omnibus (GEO) series GSE31519. We developed a method for selecting comparable datasets and to control for the amount of dataset bias of individual probesets.

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…

Modeling recurrent distributions in streams using possible worlds

2015

Discovering changes in the data distribution of streams and discovering recurrent data distributions are challenging problems in data mining and machine learning. Both have received a lot of attention in the context of classification. With the ever increasing growth of data, however, there is a high demand of compact and universal representations of data streams that enable the user to analyze current as well as historic data without having access to the raw data. To make a first step towards this direction, we propose a condensed representation that captures the various — possibly recurrent — data distributions of the stream by extending the notion of possible worlds. The representation en…

The choice of tradition and the tradition of choice: Habermas’ and Rorty’s interpretation of pragmatism

1999

The paper is aimed at discussing two interpretations of pragmatism in a broader framework of general rules of philosophical interpretation. J. Habermas’ and R. Rorty’s uses of pragmatism are considered in detail and confronted with general assumptions of pragmatic philosophy. It is shown that in both cases the original ideas of pragmatism are changed in order to fit the philosophies of interpreters. The paper ends with discussion of a possibility of applying the rule of interpretative charity and dialogue to philosophical analyses.

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.

Quantifying preferential trading in the e-MID interbank market

2015

Interbank markets allow credit institutions to exchange capital for purposes of liquidity management. These markets are among the most liquid markets in the financial system. However, liquidity of interbank markets dropped during the 2007-2008 financial crisis, and such a lack of liquidity influenced the entire economic system. In this paper, we analyze transaction data from the e-MID market which is the only electronic interbank market in the Euro Area and US, over a period of eleven years (1999-2009). We adapt a method developed to detect statistically validated links in a network, in order to reveal preferential trading in a directed network. Preferential trading between banks is detecte…

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.

Preoperative Planning for Guidewires Employing Shape-Regularized Segmentation and Optimized Trajectories

2019

Upcoming robotic interventions for endovascular procedures can significantly reduce the high radiation exposure currently endured by surgeons. Robotically driven guidewires replace manual insertion and leave the surgeon the task of planning optimal trajectories based on segmentation of associated risk structures. However, such a pipeline brings new challenges. While Deep learning based segmentation such as U-Net can achieve outstanding Dice scores, it fails to provide suitable results for trajectory planning in annotation scarce environments. We propose a preoperative pipeline featuring a shape regularized U-Net that extracts coherent anatomies from pixelwise predictions. It uses Rapidly-ex…