Search results for "RULE"

showing 10 items of 1403 documents

Control of indoor environments in heritage buildings: experimental measurements in an old Italian museum and proposal of a methodology

2005

Abstract This paper describes some results from an experiment carried out regarding a procedure to be adopted for temperature and R.H. monitoring of indoor spaces designed for exhibiting events, such as museums and similar institutions. The monitored data employed in this study has been collected by the Department di Ricerche Energetiche ed Ambientali of the Universita degli Studi di Palermo in co-operation with the Regional Gallery ''Palazzo Abatellis'' of Palermo. The study analyses a simple method for characterising the environmental quality of museums so as to ensure the optimal conservation of works of art. This methodology is based on the procedure (where thermal and hygrometry parame…

ArcheologyEngineeringArchitectural engineeringReactive sensorMaterials Science (miscellaneous)media_common.quotation_subjectControl (management)ConservationCivil engineeringIndoor air qualityHVACQuality (business)Indoor air qualityAir quality indexSpectroscopyEnvironmental qualitymedia_commonbusiness.industryCultural heritageItalian standard ruleWork (electrical)Chemistry (miscellaneous)Cultural heritageWorks of art conservationbusinessGeneral Economics Econometrics and FinanceJournal of Cultural Heritage
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Julien : les années parisiennes

2009

This article intends to scrutinize in what ways Julian’s stay in Gaul as a Caesar were decisive in Julian’s political and military education, and whether a specific ruling style and manner may be detected in the Parisian years of Julian’s government. Relying on a critical analysis of the documentation (Julian himself, Mamertinus, Ammianus, Libanios), the author examines the military and civilian aspects of Julian’s training as an apparently inexperienced ruler but quick learner. She carries out a prosopographical study of the Caesar’s circle and the administrative staff which was then on duty, combining friendly and hostile persons. Gaul offered him a training ground and he became even the …

ArcheologyHistoryGovernmentbusiness.product_categorymedia_common.quotation_subjectProsopographyArtTest (assessment)Style (visual arts)PoliticsRulerCapital (economics)Julian Gaul Paris Celts Caesar Emperor capitalbusinessHumanitiesDutyClassicsmedia_common
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Exploring the Background: Puzzles, Afterthoughts, and Replies

2017

In this paper I review the comments, and reply to the objections, put forward in the commentaries to my essay “Pre-conventions. A fragment of the Background”, published in issues n. 30 and 33 of Revus – Journal for Constitutional Theory and Philosophy of Law. My remarks fall under the following headings: 1. The social dimension of pre-conventions; 2. Pre-conventions and ordinary habits and dispositions; 3. Whether my examples are mistaken; 4. Reasons and causes; 5. Normative facts; 6. Whether abstract entities can be causes; 7. Are pre-conventions conditions of Lewis-conventions? 8. What can pre-conventions do for legal theory? 9. Whether I discharged my argumentative burdens. Raziskovanje …

ArgumentativeSettore IUS/20 - Filosofia Del DirittoPhilosophyprojectibility (induction)Rule followingkonvencijaSocial dimensionEpistemologyobičajConventionconvention custom rule-following projectibility (induction) the Background of intentionalityFragment (logic)conventionupoštevanje pravilOzadje intencionalnosticustomNormativerule-followingPhilosophy of lawthe Background of intentionalityLawprojiciranje (indukcija)Constitutional theory
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Using Tsetlin Machine to discover interpretable rules in natural language processing applications

2021

Tsetlin Machines (TM) use finite state machines for learning and propositional logic to represent patterns. The resulting pattern recognition approach captures information in the form of conjunctive clauses, thus facilitating human interpretation. In this work, we propose a TM-based approach to three common natural language processing (NLP) tasks, namely, sentiment analysis, semantic relation categorization and identifying entities in multi-turn dialogues. By performing frequent itemset mining on the TM-produced patterns, we show that we can obtain a global and a local interpretation of the learning, one that mimics existing rule-sets or lexicons. Further, we also establish that our TM base…

Artificial intelligenceComputer sciencebusiness.industryNatural language processingRule miningcomputer.software_genreInterpretable AITheoretical Computer ScienceSemantic analysesComputational Theory and MathematicsMulti-turn dialogue analysesArtificial IntelligenceControl and Systems EngineeringArtificial intelligencebusinesscomputerVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Natural language processing
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Constructing Interpretable Classifiers to Diagnose Gastric Cancer Based on Breath Tests

2017

Quick, inexpensive and accurate diagnosis of gastric cancer is a necessity, but at this moment the available methods do not hold up. One of the most promising possibilities is breath test analysis, which is quick, relatively inexpensive and comfortable to the person tested. However, this method has not yet been well explored. Therefore in this article the authors propose using transparent classification models to explain diagnostic patterns and knowledge, which is acquired in the process. The models are induced using decision tree classification algorithms and RIPPER algorithm for decision rule induction. The accuracy of these models is compared to neural network accuracy.

Artificial neural networkComputer sciencebusiness.industryDecision treePattern recognition02 engineering and technologyDecision rule021001 nanoscience & nanotechnologyMachine learningcomputer.software_genre03 medical and health sciencesStatistical classification0302 clinical medicine030220 oncology & carcinogenesisGeneral Earth and Planetary SciencesArtificial intelligence0210 nano-technologybusinesscomputerGeneral Environmental ScienceProcedia Computer Science
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Classical Training Methods

2006

This chapter reviews classical training methods for multilayer neural networks. These methods are widely used for classification and function modelling tasks. Nevertheless, they show a number of flaws or drawbacks that should be addressed in the development of such systems. They work by searching the minimum of an error function which defines the optimal behaviour of the neural network. Different standard problems are used to show the capabilities of these models; in particular, we have benchmarked the algorithms in a nonlinear classification problem and in three function modelling problems.

Artificial neural networkComputer sciencebusiness.industrymedia_common.quotation_subjectTraining methodsMachine learningcomputer.software_genreError functionDelta ruleMultilayer perceptronArtificial intelligenceNonlinear classificationbusinessFunction (engineering)computermedia_common
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3D Matrix-Based Visualization System of Association Rules

2017

With the growing number of mining datasets, it becomes increasingly difficult to explore interesting rules because of the large number of resultant and its nature complexity. Studies on human perception and intuition show that graphical representation could be a better illustration of how to seek information from the data using the capabilities of human visual system. In this work, we present and implement a 3D matrix-based approach visualization system of association rules. The main visual representation applies the extended matrix-based approach with rule-to-items mapping to general transaction data set. A novel method merging rules and assigning weight is proposed in order to reduce the …

Association rule learningComputer sciencevisualisointi02 engineering and technologycomputer.software_genreMachine learningassociation rulesvisualisationInformation visualizationData visualization0202 electrical engineering electronic engineering information engineeringZoom3D matrixta113business.industry020207 software engineeringdata miningVisualizationHuman visual system modelScalability020201 artificial intelligence & image processingData miningArtificial intelligencetiedonlouhintabusinesscomputerTransaction data2017 IEEE International Conference on Computer and Information Technology (CIT)
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Discovering representative models in large time series databases

2004

The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical observations could allow to perform diagnosis and/or prognosis. Moreover, the efficient discovery of frequent patterns may play an important role in several data mining tasks such as association rule discovery, clustering and classification. However, in order to identify interesting repetitions, it is necessary to allow errors in the matching patterns; in this context, it is difficult to select one pattern particularly suited to represent the set of similar ones, whereas modelling this set with a single model could…

Association rule learningDiscretizationComputer scienceContext (language use)Correlation and dependencecomputer.software_genreSet (abstract data type)CardinalityKnowledge extractionMotif extraction Pattern discoveryPattern matchingData miningCluster analysisTime complexitycomputer
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Predicting hospital associated disability from imbalanced data using supervised learning.

2019

Hospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to such adverse effects is an active area of medical research. The purpose of the current paper is to show the potential of artificial intelligence in the form of machine learning to complement the existing medical research. This is accomplished by studying the outcome of hospitalization of elderly patients as a supervised learning task. A rich set of features characterizing the medical and social situation of elderly patients is leveraged and using confusion matrices, association rule mining, and two different classes of supervised learning algo…

Association rule learningmedicine.medical_treatmentvanhuksetMedicine (miscellaneous)sairaalahoitoOutcome (game theory)Task (project management)03 medical and health sciences0302 clinical medicineArtificial IntelligenceMedicineHumanstoimintarajoitteetDisabled PersonsSet (psychology)Adverse effectFinlandta316030304 developmental biologyAgedta1130303 health sciencesRehabilitationbusiness.industrySupervised learningennusteetta3142medicine.diseaseMedical researchHospitalizationmachine learningkoneoppiminenhospital associated disabilityMedical emergencySupervised Machine Learningtiedonlouhintabusiness030217 neurology & neurosurgeryrandom forestArtificial intelligence in medicine
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Awareness and Partitional Informational Structures

1997

We begin with an example to motivate the introduction of the concept of unawareness in models of information. There are a subject and two possible states of the world, σ and τ. At σ a certain fact p happens — it is true — and the subject sees it or hears it or anyhow perceives it, so that he knows it is true (in Geanakoplos [5] the subject is Sherlock Holmes’ assistant and fact p is ‘the dog barks’). At state τ fact p does not occur (it is false), and the subject not only does not see it or hear it etc.; but what is more, he does not even think of the possibility that it might: fact p is not present to the subject’s mind. What is an appropriate formal model for this story?

Atomic sentenceEpistemic modal logicbusiness.industryCanonical modelSubject (philosophy)Modal logicState (computer science)Artificial intelligenceRule of inferencePsychologybusinessEpistemology
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