Search results for "TSE"
showing 10 items of 1193 documents
Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability
2020
Despite significant effort, building models that are both interpretable and accurate is an unresolved challenge for many pattern recognition problems. In general, rule-based and linear models lack accuracy, while deep learning interpretability is based on rough approximations of the underlying inference. Using a linear combination of conjunctive clauses in propositional logic, Tsetlin Machines (TMs) have shown competitive performance on diverse benchmarks. However, to do so, many clauses are needed, which impacts interpretability. Here, we address the accuracy-interpretability challenge in machine learning by equipping the TM clauses with integer weights. The resulting Integer Weighted TM (…
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…
Proving The Power Of Postselection
2011
It is a widely believed, though unproven, conjecture that the capability of postselection increases the language recognition power of both probabilistic and quantum polynomial-time computers. It is also unknown whether polynomial-time quantum machines with postselection are more powerful than their probabilistic counterparts with the same resource restrictions. We approach these problems by imposing additional constraints on the resources to be used by the computer, and are able to prove for the first time that postselection does augment the computational power of both classical and quantum computers, and that quantum does outperform probabilistic in this context, under simultaneous time an…
Low-Power Audio Keyword Spotting using Tsetlin Machines
2021
The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current Neural Network (NN) powered AI-KWS pipelines has remained ever present. This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM). Through significant reduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining high learning efficacy. In this paper we explore a TM based keyword spotting (KWS) pipe…
The Multi-States (MuSt) Theory for Emotion- and Action-regulation in Sports
2020
Feeling states – including emotional experiences – are fundamental to human adaptation, as they influence effort, attention, decision making, memory, and behavioural responses of individuals, as well as their interpersonal interactions. Thus, the ability to self-regulate is crucial for athletic success. This chapter presents the multi-states (MuSt) theory as a holistic approach for both emotion- and action-centred self-regulation for performance enhancement and optimisation. Central to the MuSt theory is the notion that a combination of emotion- and action-regulation strategies is more effective than focusing on one aspect alone. In this chapter, we describe psychobiosocial feeling states a…
De novo SMARCA2 variants clustered outside the helicase domain cause a new recognizable syndrome with intellectual disability and blepharophimosis di…
2020
International audience; Purpose: Nontruncating variants in SMARCA2, encoding a catalytic subunit of SWI/SNF chromatin remodeling complex, cause Nicolaides-Baraitser syndrome (NCBRS), a condition with intellectual disability and multiple congenital anomalies. Other disorders due to SMARCA2 are unknown.Methods: By next-generation sequencing, we identified candidate variants in SMARCA2 in 20 individuals from 18 families with a syndromic neurodevelopmental disorder not consistent with NCBRS. To stratify variant interpretation, we functionally analyzed SMARCA2 variants in yeasts and performed transcriptomic and genome methylation analyses on blood leukocytes.Results: Of 20 individuals, 14 showed…
Effectiveness of the Influence of Selected Essential Oils on the Growth of Parasitic Fusarium Isolated from Wheat Kernels from Central Europe
2021
The aim of the study was to determine the effectiveness of selected seven commercial essential oils (EsO) (grapefruit, lemongrass, tea tree (TTO), thyme, verbena, cajeput, and Litsea cubeba) on isolates of common Central European parasitic fungal species of Fusarium obtained from infected wheat kernels, and to evaluate the oils as potential natural fungicides. The study was conducted in 2 stages. At each stage, the fungicidal activity of EsO (with concentrations of 0.025
Evaluation of Fungistatic Activity of Eight Selected Essential Oils on Four Heterogeneous Fusarium Isolates Obtained from Cereal Grains in Southern P…
2020
The aim of the study was to determine the relationship between the chemical composition of eight commercial essential oils (EsO) (garlic, grapefruit, lemon grass, tea tree, thyme, verbena, cajeput, and Litsea cubeba) and their fungistatic activity in relation to four species of Fusarium: F. avenaceum, F. culmorum, F. graminearum, and F. oxysporum. The species identification of Fusarium isolates was confirmed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer. The determination of qualitative and quantitative chemical composition of the EsO was carried out using the gas chromatography&ndash
The potential of temporal analysis: Combining log data and lag sequential analysis to investigate temporal differences between scaffolded and non-sca…
2020
This paper contributes to the ongoing discussion about analysing the temporal aspects of learning processes in the educational technology research field. Our main aim was to advance methods for analysing temporal aspects of technology-enhanced learning (TEL) processes by introducing the temporal lag sequential analysis (TLSA) technique and by combining TLSA with temporal log data analysis (TLDA). Our secondary aim was to illustrate the potential of these two analysis techniques to reveal the differences between the face-to-face technology-enhanced collaborative inquiry-based learning (CIBL) processes of three different conditions (non-scaffolded, writing scaffolded and script scaffolded gro…
Metabolic Networks of Sodalis glossinidius: A Systems Biology Approach to Reductive Evolution
2012
BackgroundGenome reduction is a common evolutionary process affecting bacterial lineages that establish symbiotic or pathogenic associations with eukaryotic hosts. Such associations yield highly reduced genomes with greatly streamlined metabolic abilities shaped by the type of ecological association with the host. Sodalis glossinidius, the secondary endosymbiont of tsetse flies, represents one of the few complete genomes available of a bacterium at the initial stages of this process. In the present study, genome reduction is studied from a systems biology perspective through the reconstruction and functional analysis of genome-scale metabolic networks of S. glossinidius.ResultsThe functiona…