The application of FEL-EXPERT system in the interpretation of boron compounds toxicity

1990 ◽  
Vol 55 (1) ◽  
pp. 317-329
Author(s):  
Oldřich Štrouf ◽  
Vladimír Mařík
Keyword(s):  
Expert System ◽  
Boron Atom ◽  
High Toxicity ◽  
Production Rules ◽  
Boron Compounds ◽  
Low Toxicity ◽  
Technical University ◽  
Medium Toxicity

The influence of substructural features on boron compounds toxicity (LD50, mice, i.p.) has been studied by FEL-EXPERT system developed at the Czech Technical University of Prague. A set of 108 compounds containing one or two boron atoms in their molecule has been arbitrarily divided into three classes: the compounds with a high toxicity (LD50 < 100 mg/kg), with a medium toxicity (100 mg/kg ⪬ LD50 < 1 000 mg/kg) and with a low toxicity (LD50 ≥ 1 000 mg/kg). The compounds have been represented by 70 substructural fragments, 27 of them being "central substructures" containing boron atom(s). The inference net consists of 118 nodes (74 of the Bayesian type), 362 production rules and 74 context links. The total classification correctness has been 98%. As a case-study, the classification of p-tolylboronic acid (LD50 = 520 mg/kg) and 4-carboxyphenylboronic acid (LD50 = 3 838 mg/kg) has been discussed.

scholarly journals Incorporation of the Method of Ranking the Hazards of Abandoned Mine Entries into a Rule-Based Expert System

Minerals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 600 ◽  
Author(s):  
Mhlongo ◽  
Amponsah-Dacosta ◽  
Kadyamatimba
Keyword(s):  
Expert System ◽  
Limpopo Province ◽  
Abandoned Mines ◽  
Abandoned Mine ◽  
Production Rules ◽  
Web Based ◽  
Rule Based ◽  
Ranking Problems ◽  
The Web

The work of quantifying the problems of abandoned mines is the first step towards the rehabilitation of these mines. As the result, in all countries that have many abandoned mines, researchers and different organizations have been making efforts to develop decision-making tools, methods, and techniques for rehabilitation of abandoned mines. This paper describes the work conducted to incorporate the method for ranking the problems of abandoned mine entries into a rule-based expert system. This is done using the web-based expert system platform provided by expert system (ES)-Builder Shell. The ES is tested by applying it to the case study of the problems of abandoned mine entries in the areas of Giyani and Musina, Limpopo Province of South Africa. This paper gives details of the procedure followed in creating the production rules of the ES for ranking problems of abandoned mine entries (ES-RAME), its attributes, and the results of its application to the selected case study. The use of the ES-RAME is found to be important for setting the objectives and priorities of the rehabilitation of abandoned mine entries. In addition, the incorporation of the ranking method into the expert system ensured that the procedure of the tanking method is clearly communicated and preserved as the rules of the ES. The expert system also has the advantages of being consistent in its guidance, and it gives the user an opportunity to go through the ranking process of the system using any possible fictitious information; this gives the user a feel for the ranking process and the data required when using the ES-RAME.

scholarly journals Subjectivity Reducing In Software Version Criticity Classification With The Support Of An Expert System

2020 ◽  
Author(s):  
Dacyr Gatto ◽  
Renato José Sassi
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Problem Solving ◽  
Confidence Level ◽  
Management Process ◽  
Production Rules ◽  
Artificial Intelligence Technique ◽  
Release Management ◽  
Intelligence Technique

<p>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. In order to reduce subjectivity in the process, an Artificial Intelligence technique called the Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. <a>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. </a>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 in order 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.</p>

scholarly journals Subjectivity reducing in software version criticality classification with the support of an expert system

2022 ◽  
Vol 11 (1) ◽  
pp. e37811125132
Author(s):  
Dacyr Dante de Oliveira Gatto ◽  
Renato José Sassi
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Problem Solving ◽  
Confidence Level ◽  
Management Process ◽  
Production Rules ◽  
Artificial Intelligence Technique ◽  
Release Management ◽  
Intelligence Technique

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.

scholarly journals Subjectivity Reducing In Software Version Criticity Classification With The Support Of An Expert System

2020 ◽  
Author(s):  
Dacyr Gatto ◽  
Renato José Sassi
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Problem Solving ◽  
Confidence Level ◽  
Management Process ◽  
Production Rules ◽  
Artificial Intelligence Technique ◽  
Release Management ◽  
Intelligence Technique

<p>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. In order to reduce subjectivity in the process, an Artificial Intelligence technique called the Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. <a>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. </a>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 in order 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.</p>

ANALYSIS OF PLANT FRAGARIA XANANASSA DISEASE DIAGNOSES USING PRODUCTION RULES BASE ON EXPERT SYSTEM

2020 ◽  
Vol 16 (1) ◽  
pp. 25-32
Author(s):  
Basiroh Basiroh ◽  
Wiji Lestari
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
General Public ◽  
Insect Pests ◽  
Fruit Rot ◽  
Proper Treatment ◽  
Harvest Time ◽  
Production Rules

Errors that occur in solving problems in strawberry plants (Fragaria Xananassa) such as the presence of leaf patches, fruit rot, perforated leaves, and insect pests can be the cause of not maximum in harvest time. The farmers and the general public who planted strawberry (Fragaria Xananassa) need to know the proper treatment of diseases and pests so that future yields as expected. Therefore, it takes an application as a solution in the delivery of information related to the problems that are often encountered in strawberry plants (Fragaria Xananassa). Methods of production rules can be used to diagnose the disease strawberry (Fragaria Xananassa) based on signs or symptoms that occur in the parts of plants and strawberry, the results of diagnosis using this method are the same as we do Consultation on experts.  The purpose of this study was to determine the early diagnosis of disease in strawberry plants (Fragaria Xananassa) based on signs or symptoms that occur in the plant and fruit parts. The results of the analysis of this study showed that the validation of disease and symptom data in strawberry plants (Fragaria Xananassa) reached 99%, meaning that between the data of symptoms and disease understudy the accuracy was guaranteed with the experts.

scholarly journals Assessment of health/functioning of older adults who consume psychoactive substances

2018 ◽  
Vol 71 (3) ◽  
pp. 942-950
Author(s):  
Vania Dias Cruz ◽  
Silvana Sidney Costa Santos ◽  
Jamila Geri Tomaschewski-Barlem ◽  
Bárbara Tarouco da Silva ◽  
Celmira Lange ◽  
...  
Keyword(s):  
Older Adults ◽  
Qualitative Case Study ◽  
International Classification Of Functioning ◽  
Psychoactive Substances ◽  
Systematic Observation ◽  
Health Functioning ◽  
Final Consideration ◽  
Theory Of Complexity

ABSTRACT Objective: To assess the health/functioning of the older adult who consumes psychoactive substances through the International Classification of Functioning, Disability and Health, considering the theory of complexity. Method: Qualitative case study, with 11 older adults, held between December 2015 and February 2016 in the state of Rio Grande do Sul, using interviews, documents and non-systematic observation. It was approved by the ethics committee. The analysis followed the propositions of the case study, using the complexity of Morin as theoretical basis. Results: We identified older adults who consider themselves healthy and show alterations - the alterations can be exacerbated by the use of psychoactive substances - of health/functioning expected according to the natural course of aging such as: systemic arterial hypertension; depressive symptoms; dizziness; tinnitus; harmed sleep/rest; and inadequate food and water consumption. Final consideration: The assessment of health/functioning of older adults who use psychoactive substances, guided by complex thinking, exceeds the accuracy limits to risk the understanding of the phenomena in its complexity.

scholarly journals Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhe Yang ◽  
Dejan Gjorgjevikj ◽  
Jianyu Long ◽  
Yanyang Zi ◽  
Shaohui Zhang ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Supervised Classification ◽  
Deep Neural Networks ◽  
Activation Function ◽  
Reconstruction Error ◽  
Fine Tuning ◽  
Fault Diagnostics ◽  
Sparse Autoencoder

AbstractSupervised fault diagnosis typically assumes that all the types of machinery failures are known. However, in practice unknown types of defect, i.e., novelties, may occur, whose detection is a challenging task. In this paper, a novel fault diagnostic method is developed for both diagnostics and detection of novelties. To this end, a sparse autoencoder-based multi-head Deep Neural Network (DNN) is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring data. The detection of novelties is based on the reconstruction error. Moreover, the computational burden is reduced by directly training the multi-head DNN with rectified linear unit activation function, instead of performing the pre-training and fine-tuning phases required for classical DNNs. The addressed method is applied to a benchmark bearing case study and to experimental data acquired from a delta 3D printer. The results show that its performance is satisfactory both in detection of novelties and fault diagnosis, outperforming other state-of-the-art methods. This research proposes a novel fault diagnostics method which can not only diagnose the known type of defect, but also detect unknown types of defects.

scholarly journals Neither a Novel Tau Proteinopathy nor an Expansion of a Phenotype: Reappraising Clinicopathology-Based Nosology

2021 ◽  
Vol 22 (14) ◽  
pp. 7292
Author(s):  
Luca Marsili ◽  
Jennifer Sharma ◽  
Alberto J. Espay ◽  
Alice Migazzi ◽  
Elhusseini Abdelghany ◽  
...  
Keyword(s):  
Spinocerebellar Ataxia Type ◽  
Niemann Pick Disease ◽  
Whole Exome ◽  
Heterozygous Variant ◽  
History Of ◽  
Ataxia Syndrome ◽  
Niemann Pick

The gold standard for classification of neurodegenerative diseases is postmortem histopathology; however, the diagnostic odyssey of this case challenges such a clinicopathologic model. We evaluated a 60-year-old woman with a 7-year history of a progressive dystonia–ataxia syndrome with supranuclear gaze palsy, suspected to represent Niemann–Pick disease Type C. Postmortem evaluation unexpectedly demonstrated neurodegeneration with 4-repeat tau deposition in a distribution diagnostic of progressive supranuclear palsy (PSP). Whole-exome sequencing revealed a new heterozygous variant in TGM6, associated with spinocerebellar ataxia type 35 (SCA35). This novel TGM6 variant reduced transglutaminase activity in vitro, suggesting it was pathogenic. This case could be interpreted as expanding: (1) the PSP phenotype to include a spinocerebellar variant; (2) SCA35 as a tau proteinopathy; or (3) TGM6 as a novel genetic variant underlying a SCA35 phenotype with PSP pathology. None of these interpretations seem adequate. We instead hypothesize that impairment in the crosslinking of tau by the TGM6-encoded transglutaminase enzyme may compromise tau functionally and structurally, leading to its aggregation in a pattern currently classified as PSP. The lessons from this case study encourage a reassessment of our clinicopathology-based nosology.

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