scholarly journals Classification of Actions or Inheritance also for Methods

1987 ◽  
Vol 16 (231) ◽  
Author(s):  
Bent Bruun Kristensen ◽  
Ole Lehrmann Madsen ◽  
Birger Møller-Pedersen ◽  
Kristen Nygaard
Keyword(s):  
General Class ◽  
Object Oriented ◽  
Wide Range ◽  
Language Classes ◽  
Virtual Classes ◽  
Main Thing

<p>The main thing with the sub-class mechanism as found in languages like C++, SIMULA and Smalltalk is its possibility to express <em>specializations</em>. A general class, covering a wide range of objects, may be specialized to cover more specific objects. This is obtained by three properties of sub-classing: An object of a sub-class inherits the attributes of the super-class, virtual procedure/method attributes (of the super-class) may be specialized in the sub-class, and (in SIMULA only) it inherits the actions of the super-class.</p><p>In the languages mentioned above, virtual procedures/methods of a super-class are specialized in sub-classes in a very primitive manner: they are simply <em>re-defined</em> and need not bear any resemblance of the virtual in the super-class. In BETA, a new object-oriented language, classes and methods are unified into one concept, and by an extension of the virtual concept, virtual procedures/methods in sub-classes are defined as <em>specializations of the virtuals</em> in the super-class. The virtual procedures/methods of the sub-classes thus inherit the attributes (e.g. parameters) and actions from the ''super-procedure/method''.</p><p>In the languages mentioned above only procedures/methods may be virtual. As classes and procedures/methods are unified in BETA this gives also <em>virtual classes</em>. The paper demonstrates, how this may be used to parameterize types and enforce constraints on types.</p>

scholarly journals Functional capacity of audio guides

2021 ◽  
pp. 1-9
Author(s):  
Aleksandra Vladimirovna Urazmetova
Keyword(s):  
Foreign Language ◽  
Effective Means ◽  
Educational Activity ◽  
Wide Range ◽  
Language Classes ◽  
The Subject ◽  
Historical Heritage ◽  
Multimedia Product ◽  
Favorable Conditions

The subject of this research is the audio guide as a relatively new multimedia product used in the sphere of tourism and education. The author determines the key advantages of using audio guide, as well as functional-linguistic peculiarities of organizing this genre of tourism discourse. Classification of audio guides is carried out based on their target audience and content. Special attention is given to examination of the prospects of using audio guides in teaching foreign languages. The author outlines the functions performed by audio guides in foreign language classes, such as entertainment, promotional, scientific-enlightening, scientific research, and educational. The scientific novelty lies in consideration of the type of educational activity that used audio guide as a modern and highly effective means of mastering foreign language skills. Audio guide not only creates favorable conditions for the implementation of educational-pedagogical activity, but also has a wide range of variations for solution of educational tasks. The use of audio guides is particularly relevant in studying the disciplines related to cultural-historical heritage of the country of origin of the language taught; they can also be used in expanding vocabulary, learning grammar, phonetics, etc. The article describes the most popular software and services for working with audio materials, as well as the examples of using a multimedia product in the classes of English phonetics.

scholarly journals ИССЛЕДОВАНИЕ ЭФФЕКТИВНОСТИ МЕТОДОВ ПОСТ-КЛАССИФИКАЦИОННОЙ ОБРАБОТКИ ЗАШУМЛЕННЫХ МНОГОКАНАЛЬНЫХ ИЗОБРАЖЕНИЙ

2019 ◽  
pp. 45-59
Author(s):  
Ирина Карловна Васильева ◽  
Владимир Васильевич Лукин
Keyword(s):  
Signal To Noise Ratio ◽  
Decision Rules ◽  
Object Oriented ◽  
Correct Recognition ◽  
Likelihood Method ◽  
Noise Variance ◽  
Post Processing ◽  
Noisy Images ◽  
Wide Range

The subject matter of the article are the methods of local spatial post-processing of images obtained as a result of statistical per-pixel classification of multichannel satellite images distorted by additive Gaussian noise. The aim is to investigate the effectiveness of some variants of post-classification image processing methods over a wide range of signal-to-noise ratio; as a criterion of effectiveness, observed objects classification reliability indicators have been taken. The tasks to be solved are: to generate random values of the noise components brightness, ensuring that they coincide with the adopted probabilistic model; to implement a procedure of statistical controlled classification by the maximum likelihood method for images distorted by noise; to evaluate the results of the objects selection in noisy images by the criterion of the empirical probability of correct recognition; to implement procedures for local object-oriented post-processing of images; to investigate the effect of noise variance on the effectiveness of post-processing procedures. The methods used are: methods of stochastic simulation, methods of approximation of empirical dependencies, statistical methods of recognition, methods of probability theory and mathematical statistics, methods of local spatial filtering. The following results have been obtained. Algorithms of rank and weighted median post-processing with considering the results of classification by k-nearest neighbors in the filter window were implemented. The developed algorithms efficiency analysis that based on estimates of the correct recognition probability for objects on noisy images was carried out. Empirical dependences of the estimates of the overall recognition errors probability versus the additive noise variance were obtained. Conclusions. The scientific novelty of the results obtained is as follows: combined approaches to building decision rules, taking into account destabilizing factors, have been further developed – it has been shown that the use of methods of local object-oriented filtering of segmented images reduces the number of point errors in the element-based classification of objects, as well as partially restores the connectedness and spatial distribution of image structure elements.

scholarly journals Modes of Interaction in Naturally Occurring Medical Encounters With General Practitioners: The “One in a Million” Study

2021 ◽  
pp. 104973232199379
Author(s):  
Olaug S. Lian ◽  
Sarah Nettleton ◽  
Åge Wifstad ◽  
Christopher Dowrick
Keyword(s):  
General Practitioners ◽  
Narrative Analysis ◽  
Mode Competition ◽  
General Applicability ◽  
Naturally Occurring ◽  
Wide Range ◽  
The One ◽  
Narrative Mode ◽  
Modes Of Interaction

In this article, we qualitatively explore the manner and style in which medical encounters between patients and general practitioners (GPs) are mutually conducted, as exhibited in situ in 10 consultations sourced from the One in a Million: Primary Care Consultations Archive in England. Our main objectives are to identify interactional modes, to develop a classification of these modes, and to uncover how modes emerge and shift both within and between consultations. Deploying an interactional perspective and a thematic and narrative analysis of consultation transcripts, we identified five distinctive interactional modes: question and answer (Q&A) mode, lecture mode, probabilistic mode, competition mode, and narrative mode. Most modes are GP-led. Mode shifts within consultations generally map on to the chronology of the medical encounter. Patient-led narrative modes are initiated by patients themselves, which demonstrates agency. Our classification of modes derives from complete naturally occurring consultations, covering a wide range of symptoms, and may have general applicability.

scholarly journals Uncertainty-Aware Deep Learning-Based Cardiac Arrhythmias Classification Model of Electrocardiogram Signals

Computers ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 82
Author(s):  
Ahmad O. Aseeri
Keyword(s):  
Deep Learning ◽  
Cardiac Arrhythmias ◽  
Large Scale ◽  
Clinical Decision Making ◽  
Probabilistic Approach ◽  
Classification Model ◽  
Gating Mechanism ◽  
Uncertainty Estimates ◽  
Wide Range

Deep Learning-based methods have emerged to be one of the most effective and practical solutions in a wide range of medical problems, including the diagnosis of cardiac arrhythmias. A critical step to a precocious diagnosis in many heart dysfunctions diseases starts with the accurate detection and classification of cardiac arrhythmias, which can be achieved via electrocardiograms (ECGs). Motivated by the desire to enhance conventional clinical methods in diagnosing cardiac arrhythmias, we introduce an uncertainty-aware deep learning-based predictive model design for accurate large-scale classification of cardiac arrhythmias successfully trained and evaluated using three benchmark medical datasets. In addition, considering that the quantification of uncertainty estimates is vital for clinical decision-making, our method incorporates a probabilistic approach to capture the model’s uncertainty using a Bayesian-based approximation method without introducing additional parameters or significant changes to the network’s architecture. Although many arrhythmias classification solutions with various ECG feature engineering techniques have been reported in the literature, the introduced AI-based probabilistic-enabled method in this paper outperforms the results of existing methods in outstanding multiclass classification results that manifest F1 scores of 98.62% and 96.73% with (MIT-BIH) dataset of 20 annotations, and 99.23% and 96.94% with (INCART) dataset of eight annotations, and 97.25% and 96.73% with (BIDMC) dataset of six annotations, for the deep ensemble and probabilistic mode, respectively. We demonstrate our method’s high-performing and statistical reliability results in numerical experiments on the language modeling using the gating mechanism of Recurrent Neural Networks.

scholarly journals Classification of unlabeled online media

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sakthi Kumar Arul Prakash ◽  
Conrad Tucker
Keyword(s):  
Social Media ◽  
Real World ◽  
Graphical Model ◽  
Ground Truth ◽  
Classification Problem ◽  
Machine Learning Algorithms ◽  
Social Media Networks ◽  
Online Social Media ◽  
Wide Range

AbstractThis work investigates the ability to classify misinformation in online social media networks in a manner that avoids the need for ground truth labels. Rather than approach the classification problem as a task for humans or machine learning algorithms, this work leverages user–user and user–media (i.e.,media likes) interactions to infer the type of information (fake vs. authentic) being spread, without needing to know the actual details of the information itself. To study the inception and evolution of user–user and user–media interactions over time, we create an experimental platform that mimics the functionality of real-world social media networks. We develop a graphical model that considers the evolution of this network topology to model the uncertainty (entropy) propagation when fake and authentic media disseminates across the network. The creation of a real-world social media network enables a wide range of hypotheses to be tested pertaining to users, their interactions with other users, and with media content. The discovery that the entropy of user–user and user–media interactions approximate fake and authentic media likes, enables us to classify fake media in an unsupervised learning manner.

scholarly journals Sequence data from isolated lichen-associated melanized fungi enhance delimitation of two new lineages within Chaetothyriomycetidae

2021 ◽  
Vol 20 (7) ◽  
pp. 911-927
Author(s):  
Lucia Muggia ◽  
Yu Quan ◽  
Cécile Gueidan ◽  
Abdullah M. S. Al-Hatmi ◽  
Martin Grube ◽  
...  
Keyword(s):  
Sequence Data ◽  
Single Species ◽  
Sister Group ◽  
Asexual Propagation ◽  
Dna Sequence Data ◽  
Wide Range ◽  
The Family ◽  
Rock Inhabiting Fungi ◽  
Stable Habitat

AbstractLichen thalli provide a long-lived and stable habitat for colonization by a wide range of microorganisms. Increased interest in these lichen-associated microbial communities has revealed an impressive diversity of fungi, including several novel lineages which still await formal taxonomic recognition. Among these, members of the Eurotiomycetes and Dothideomycetes usually occur asymptomatically in the lichen thalli, even if they share ancestry with fungi that may be parasitic on their host. Mycelia of the isolates are characterized by melanized cell walls and the fungi display exclusively asexual propagation. Their taxonomic placement requires, therefore, the use of DNA sequence data. Here, we consider recently published sequence data from lichen-associated fungi and characterize and formally describe two new, individually monophyletic lineages at family, genus, and species levels. The Pleostigmataceae fam. nov. and Melanina gen. nov. both comprise rock-inhabiting fungi that associate with epilithic, crust-forming lichens in subalpine habitats. The phylogenetic placement and the monophyly of Pleostigmataceae lack statistical support, but the family was resolved as sister to the order Verrucariales. This family comprises the species Pleostigma alpinum sp. nov., P. frigidum sp. nov., P. jungermannicola, and P. lichenophilum sp. nov. The placement of the genus Melanina is supported as a lineage within the Chaetothyriales. To date, this genus comprises the single species M. gunde-cimermaniae sp. nov. and forms a sister group to a large lineage including Herpotrichiellaceae, Chaetothyriaceae, Cyphellophoraceae, and Trichomeriaceae. The new phylogenetic analysis of the subclass Chaetothyiomycetidae provides new insight into genus and family level delimitation and classification of this ecologically diverse group of fungi.

Introduction of a new AAC symbol classification system: the multidimensional quaternary symbol continuum (MQSC)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Eliada Pampoulou ◽  
Donald R. Fuller
Keyword(s):  
Peer Review ◽  
Classification System ◽  
Augmentative And Alternative Communication ◽  
Social Issues ◽  
Content Type ◽  
Design Attributes ◽  
Wide Range ◽  
Current Classification ◽  
Symbol Classification

PurposeWhen the augmentative and alternative communication (ACC) model (Lloyd et al., 1990) was proposed, these components of symbols were not considered, nor were they contemplated when superordinate (Lloyd and Fuller, 1986) and subordinate levels (Fuller et al., 1992) of AAC symbol taxonomy were developed. The purpose of this paper is to revisit the ACC model and propose a new symbol classification system called multidimensional quaternary symbol continuum (MQSC)Design/methodology/approachThe field of AAC is evolving at a rapid rate in terms of its clinical, social, research and theoretical underpinnings. Advances in assessment and intervention methods, technology and social issues are all responsible to some degree for the significant changes that have occurred in the field of AAC over the last 30 years. For example, the number of aided symbol collections has increased almost exponentially over the past couple of decades. The proliferation of such a large variety of symbol collections represents a wide range of design attributes, physical attributes and linguistic characteristics for aided symbols and design attributes and linguistic characteristics for unaided symbols.FindingsTherefore, it may be time to revisit the AAC model and more specifically, one of its transmission processes referred to as the means to represent.Originality/valueThe focus of this theoretical paper then, is on the current classification of symbols, issues with respect to the current classification of symbols in terms of ambiguity of terminology and the evolution of symbols, and a proposal for a new means of classifying the means to represent.Peer reviewThe peer review history for this article is available at: https://publons.com/publon10.1108/JET-04-2021-0024

Sign in / Sign up

Export Citation Format

Share Document