Search results for "550"

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications

2019

Medical applications challenge today's text categorization techniques by demanding both high accuracy and ease-of-interpretation. Although deep learning has provided a leap ahead in accuracy, this leap comes at the sacrifice of interpretability. To address this accuracy-interpretability challenge, we here introduce, for the first time, a text categorization approach that leverages the recently introduced Tsetlin Machine. In all brevity, we represent the terms of a text as propositional variables. From these, we capture categories using simple propositional formulae, such as: if "rash" and "reaction" and "penicillin" then Allergy. The Tsetlin Machine learns these formulae from a labelled tex…

Environment Sound Classification using Multiple Feature Channels and Attention based Deep Convolutional Neural Network

2020

In this paper, we propose a model for the Environment Sound Classification Task (ESC) that consists of multiple feature channels given as input to a Deep Convolutional Neural Network (CNN) with Attention mechanism. The novelty of the paper lies in using multiple feature channels consisting of Mel-Frequency Cepstral Coefficients (MFCC), Gammatone Frequency Cepstral Coefficients (GFCC), the Constant Q-transform (CQT) and Chromagram. Such multiple features have never been used before for signal or audio processing. And, we employ a deeper CNN (DCNN) compared to previous models, consisting of spatially separable convolutions working on time and feature domain separately. Alongside, we use atten…

Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation

2019

Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environment is a promising tool which would revolutionize video and image analysis for a wide range of applications in marine ecology. However, classifying fish from images captured by underwater cameras is in general very challenging due to noise and illumination variations in water. Previous classification methods in the literature relies on filtering the images to separate the fish from the background or sharpening the images by removing background noise. This pre-filtering process may negatively impact the classificat…

Word-level human interpretable scoring mechanism for novel text detection using Tsetlin Machines

2021

Recent research in novelty detection focuses mainly on document-level classification, employing deep neural networks (DNN). However, the black-box nature of DNNs makes it difficult to extract an exact explanation of why a document is considered novel. In addition, dealing with novelty at the word-level is crucial to provide a more fine-grained analysis than what is available at the document level. In this work, we propose a Tsetlin machine (TM)-based architecture for scoring individual words according to their contribution to novelty. Our approach encodes a description of the novel documents using the linguistic patterns captured by TM clauses. We then adopt this description to measure how …

Expert Q-learning: Deep Reinforcement Learning with Coarse State Values from Offline Expert Examples

2022

In this article, we propose a novel algorithm for deep reinforcement learning named Expert Q-learning. Expert Q-learning is inspired by Dueling Q-learning and aims at incorporating semi-supervised learning into reinforcement learning through splitting Q-values into state values and action advantages. We require that an offline expert assesses the value of a state in a coarse manner using three discrete values. An expert network is designed in addition to the Q-network, which updates each time following the regular offline minibatch update whenever the expert example buffer is not empty. Using the board game Othello, we compare our algorithm with the baseline Q-learning algorithm, which is a…

Dynamics of inertial pair coupled via frictional interface

2022

Understanding the dynamics of two inertial bodies coupled via a friction interface is essential for a wide range of systems and motion control applications. Coupling terms within the dynamics of an inertial pair connected via a passive frictional contact are non-trivial and have long remained understudied in system communities. This problem is particularly challenging from a point of view of modeling the interaction forces and motion state variables. This paper deals with a generalized motion problem in systems with a free (of additional constraints) friction interface, assuming the classical Coulomb friction with discontinuity at the velocity zero crossing. We formulate the dynamics of mot…

Inventario de robbe de la guardarrobba de lo illustrissimo signore Don Ferrante de Aragona Duca de Callabria

Ms Títol obtingut del títol (f. 1r) Col·lació: Paper, f. i (paper) i (pergamí actual) + 217 (en blanc els f. 1v, 14v, 15, 19r, 56r, 154r, 194v, 195-197) + i (paper) ; numeració antiga i moderna a llapis Composició: Escrit a línia tirada Escriptura: Humanística cursiva Enquadernació: Restaurada, pergamí sobre cartó. Títol al llom: "Inventario del Duca de Calabria. Ferrara 1527" Origen: Escrit a Ferrara, Itàlia, on residia la mare del duc, Isabel Del Balzo en l'any 1527 (f. 1r) Signatura anterior: Ms. 947 Signatura actual: València, Universitat de València. Biblioteca Històrica, BH Ms. 947 Títol del f. 1r: "Inventario de robbe de la guardarrobba de lo illustrissimo signore Don Ferrante de Ara…

Indigent consumers’ protection at the financial services market

2016

Opracowanie stanowi próbę odpowiedzi na pytanie, czy ochrona osób niezamożnych na rynku usług finansowych powinna być realizowana odrębnie w stosunku do powszechnie obowiązujących zasad oraz jakie elementy powinna obejmować ta ochrona? Ponadto – jakie podmioty powinny jej udzielać – czy te, które już istnieją na rynku, czy inne, nowe? Problem ochrony osób niezamożnych wynika stąd, że w dużej mierze osoby te są wykluczone z rynku podstawowego (mainstream market), objętego ochroną prawną. Część osób korzysta z oferty rynku alternatywnego, czy wręcz nieformalnego. Wydaje się więc, że dodatkowa ochrona osób niezamożnych powinna być ukierunkowana na te właśnie obszary rynku usług finansowych. Th…

A two-armed bandit collective for hierarchical examplar based mining of frequent itemsets with applications to intrusion detection

2014

Published version of a chapter in the book: Transactions on Computational Collective Intelligence XIV. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-662-44509-9_1 In this paper we address the above problem by posing frequent item-set mining as a collection of interrelated two-armed bandit problems. We seek to find itemsets that frequently appear as subsets in a stream of itemsets, with the frequency being constrained to support granularity requirements. Starting from a randomly or manually selected examplar itemset, a collective of Tsetlin automata based two-armed bandit players - one automaton for each item in the examplar - learns which items should be included in …

Scenario-based Serious Game to Teach about Healthcare

2019

Author's accepted manuscript (postprint). © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Available from 29/10/2021. In this paper, we explore the concept of a scenario-based serious game for healthcare solutions. The complexity of the interactions and the multitude of actors is captured in a scenario, which is then played with the help of an additional game pl…