production rules
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2022 ◽  
Vol 11 (1) ◽  
pp. e37811125132
Author(s):  
Dacyr Dante de Oliveira Gatto ◽  
Renato José Sassi

In the software version release management process, there is a need, on the part of human specialists, to classify the criticality of each software version. However, the subjectivity of this classification may be present according to the experience acquired by specialists over the years. To reduce subjectivity in the process, an Artificial Intelligence technique called Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. Thus, the aim of this paper was to reduce the subjectivity in the criticality classification of the software version with the support of the Expert System. To this end, a questionnaire was developed with the objective of obtaining the criticality opinions classified as High, Medium and Low in each specialist's software version to assist in the preparation of the ES production rules.  ES generated 17 production rules with a 100% confidence level applied to a production database. The results of the classification carried out by the ES corresponded to the classification carried out by the specialists in the production base, that is, the ES was able to represent their knowledge. Then, another questionnaire was applied to the specialists to verify the perception of satisfaction regarding the use of the ES with a result obtained of 4.8, considered satisfactory. It was concluded, then, that the ES supported the reduction of subjectivity in the classification of the criticality of software version.


Author(s):  
Daniel Ashlock

Human knowledge was regarded as a transfer process into an applied knowledge base in the early 1980s as the creation of a Knowledge-Based Systems (KBS). The premise behind this transfer was that the KBS-required information already existed and only needed to be gathered and applied. Most of the time, the necessary information was gleaned through talking to professionals about how they handle particular problems. This knowledge was usually put to use in production rules, which were then carried out by a rule interpreter linked to them. Here, we demonstrate a number of new ideas and approaches that have emerged during the last few years. This paper presents MIKE, PROTÉGÉ-II, and Common KADS as three different modeling frameworks that may be used together or separately.


2021 ◽  
Author(s):  
Michael Chimento ◽  
Brendan J. Barrett ◽  
Anne Kandler ◽  
Lucy M. Aplin

Culture is an outcome of the acquisition of knowledge about behaviour through social transmission, and its subsequent production. Transmission and production are often discussed interchangeably or modeled separately, yet to date, no study has accounted for both processes and explored their interaction. We present a generative model that integrates the two in order to explore how variation in either might shape cultural diffusion dynamics. Agents make behavioural choices that change as they learn from their behavioural productions. Their repertoires also change over time, and the social transmission of behaviours depends on their frequency. We diffuse a novel behaviour through social networks across a large parameter space to demonstrate how accounting for both transmission and production reveals dependencies between individual-level behavioural production rules and population-level diffusion dynamics. We then investigate how such dependencies might affect the performance of two commonly used inferential models for social learning; Network-based Diffusion Analysis (NBDA), and Experienced Weighted Attraction models (EWA). By clarifying the distinction between acquisition and usage, we illuminate often-overlooked theoretical differences between social learning and social influence. These distinctions yield consequences and new considerations for how inferential methods are applied to empirical studies of culture.


Author(s):  
Анастасия Сергеевна Бизюкина ◽  
Юлия Сергеевна Данилова

В статье рассматриваются вопросы диагностики заболеваний органов зрения и его придаточного аппарата. Медико-социальное значение болезней органов зрения и его придаточного аппарата в современных условиях велико и определяется, прежде всего, их крайне высокой частотой среди различных контингентов населения. Так как зрение является для человека важнейшим из всех органов чувств, без которого невозможна полноценная жизнь, необходимо вовремя выявлять различные патологии и применять незамедлительные меры лечения. Одним из средств повышения эффективности диагностики заболеваний глаз является автоматизация обработки диагностических данных с использованием современных технологий, а именно компьютерной системы поддержки принятия решений. Данная статья посвящена разработке автоматизированной системы диагностики заболеваний глаза на основе продукционных правил. Следует отметить, что процесс медицинского офтальмологического исследования занимает значительное время на различного рода лабораторные анализы, инструментальную диагностику, опрос больного или физического исследования. Автоматизированная компьютерная система диагностики глазных заболеваний предназначена для автоматического установления по характерным признакам таких диагнозов как острый конъюнктивит, острый ирит, острый приступ глаукомы и катаракта. Разработанная программа, реализованная в системе визуального объектно-ориентированного программирования С++, представляется пользователям как консультант для автоматизации работы, что позволит повысить эффективность процесса диагностики заболеваний органов зрения и его придаточного аппарата The article deals with the diagnosis of diseases of the organs of vision and its accessory apparatus. The medical and social significance of diseases of the organs of vision and its accessory apparatus in modern conditions is great and is determined, first of all, by their extremely high frequency among various contingents of the population. Since vision is the most important of all sense organs for a person, without which a full life is impossible, it is necessary to identify various pathologies in time and apply immediate treatment measures. One of the means to increase the effectiveness of the diagnosis of eye diseases is the automation of diagnostic data processing using modern technologies, namely a computer decision support system. This article is devoted to the development of an automated system for diagnosing eye diseases based on production rules. It should be noted that the process of medical ophthalmological examination takes considerable time for various kinds of laboratory tests, instrumental diagnostics, patient interview or physical examination. The automated computer system for the diagnosis of eye diseases is designed to automatically establish the characteristic signs of such diagnoses as acute conjunctivitis, acute iritis, acute attack of glaucoma and cataract. The developed program, implemented in the C++ visual object-oriented programming system, is presented to users as a consultant for automating work, which will increase the efficiency of the process of diagnosing diseases of the visual organs and its accessory apparatus


Information ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 502
Author(s):  
Stefan Wagenpfeil ◽  
Paul Mc Kevitt ◽  
Matthias Hemmje

Multimedia feature graphs are employed to represent features of images, video, audio, or text. Various techniques exist to extract such features from multimedia objects. In this paper, we describe the extension of such a feature graph to represent the meaning of such multimedia features and introduce a formal context-free PS-grammar (Phrase Structure grammar) to automatically generate human-understandable natural language expressions based on such features. To achieve this, we define a semantic extension to syntactic multimedia feature graphs and introduce a set of production rules for phrases of natural language English expressions. This explainability, which is founded on a semantic model provides the opportunity to represent any multimedia feature in a human-readable and human-understandable form, which largely closes the gap between the technical representation of such features and their semantics. We show how this explainability can be formally defined and demonstrate the corresponding implementation based on our generic multimedia analysis framework. Furthermore, we show how this semantic extension can be employed to increase the effectiveness in precision and recall experiments.


Animals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 3352
Author(s):  
Marika Vitali ◽  
Luca Sardi ◽  
Giovanna Martelli ◽  
Eleonora Nannoni

This work provides a narrative review of the available information on the welfare of Italian heavy pigs in the pre-slaughter phase (transport, lairage, and stunning). The meat from these pigs is used for specific PDO (Protected Designation of Origin) products, and the production rules for these specialties require higher body weight (160–170 kg) and age (in general more than 9 months) at slaughter than in most other countries. This may lead to specific behavioral and physiological needs of pigs. The present paper summarizes the main research findings and knowledge gaps for each of the pre-slaughter phases. Studies are presented according to the four principles of the Welfare Quality assessment protocol (good feeding, good housing, good health, and appropriate behavior). The results of the literature review indicate a lack of knowledge on several aspects. Most of studies were carried out in a single slaughterhouse, making it difficult to identify risk factors and confounding effects. Moreover, animal-based measures were assessed using different protocols, reducing the possibility of comparison across studies. These findings may serve as a basis for the development of specific research studies and policies aimed at enhancing the animal welfare level and the ethical attributes of this renowned production, also in accordance with consumers’ expectations.


2021 ◽  
Vol 21 (2) ◽  
pp. 77
Author(s):  
Pradifta Gilang Ramdhan ◽  
Kosala D. Purnomo ◽  
Firdaus Ubaidillah

Fractal tree is simply a trunk and a number of branches, each of which looks like the tree itself. The fractal tree can be generated using the IFS and L-Systems methods. In this article, the author develops fractal tree generation using L-Systems with additional variations. The variations given are in thickness, length, and branch angle. This development is expected to produce more diverse fractal tree patterns. In generating a fractal tree using L-Systems, it begins by determining the letters and symbols to be used. Then determine which axioms should be used. Then the production rules are made together with the determination of the parametric L-Systems. And the last is to determine the probability value for the stochastic L-Systems. In the deterministic L-Systems, thickness variations, length variations, and branch angle variations are carried out. In the variation of branch thickness, if the ratio of the thickness of the left branch is greater than that of the right branch, the fractal tree is skewed to the left. Then in the variation of branch length if the ratio of the length of the left branch is smaller than the ratio of the length of the right branch, the length of the left branch is longer than the length of the right branch. Then at the angle of the branching the smaller the 𝜃 that is included causes the branches to be closer together. The use of stochastic L-Systems can produce more diverse fractal tree patterns, even though they use the same production rules and parameter values


2021 ◽  
Author(s):  
Anton Anikin ◽  
Oleg Sychev ◽  
Mikhail Denisov

Developing algorithms using control structures and understanding their building blocks are essential skills in mastering programming. Ontologies and software reasoning is a promising method for developing intelligent tutoring systems in well-defined domains (like programming languages and algorithms); it can be used for many kinds of teaching tasks. In this work, we used a formal model consisting of production rules for Apache Jena reasoner as a basis for developing a constraint-based tutor for introductory programming domain. The tutor can determine fault reasons for any incorrect answer that a student can enter. The problem the student should solve is building an execution trace for the given algorithm. The problem is a closed-ended question that requires arranging given actions in the (unique) correct order; some actions can be used several times, while others can be omitted. Using formal reasoning to check domain constraints allowed us to provide explanatory feedback for all kinds of errors students can make.


2021 ◽  
pp. 180-187
Author(s):  
Anna E. Kolodenkova ◽  
Alexander N. Guda ◽  
Svetlana S. Vereshchagina ◽  
Valeriya O. Tuvaeva

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