The Universe of Approximations

AbstractThe idea of approximate entailment has been in [13] as a way of modeling the reasoning of an agent with limited resources. They proposed a system in which a family of logics, parameterized by a set of propositional letters, approximates classical logic as the size of the set increases.In this paper, we take the idea further, extending two of their systems to deal with full propositional logic, giving them semantics and sound and complete proof methods based on tableaux. We then present a more general system of which the two previous systems are particular cases and show how it can be used to formalize heuristics used in theorem proving

Iterated belief change: the case of expansion into inconsistency

Constructing models that allow iterated changes is one of the most studied problems in the literature on belief change. However, up to now, iteration of expansion was only studied as a special case of consistent revision and, as far we know, there is no work in the literature that deals with expansions into inconsistency in a supraclassical framework. In this paper, we provide a semantics for iterated expansion, as well as its axiomatic characterization. We extend the model to two well-known families of iterated belief change (natural and lexicographic). Iteration of expansion can be combined with existent models of iteration of revision and contraction. Since we are able to accommodate different inconsistent belief states, iteration of expansion allows us to define new belief change functions that are currently only defined for belief bases: semi revision, external revision, as well as consolidation.info:eu-repo/semantics/publishedVersio

Semantic Data Integration for Public Health in Brazil

International audienceThe lack of semantic information is a big challenge, even in context-driven areas like Healthcare, characterized by established terminologies. Here, semantic data integration is the solution to provide precise information and answers to questions like: What is the care pathway of newborns diagnosed with a congenital anomaly in consequence of congenital syphilis in the city of São Paulo? This project will use a semantic data integration technique, ontology based data integration, to integrate three health databases from the city of São Paulo - Brazil: mortality, live births and hospital information system. It is expected that the integration of public health databases will help to map patient care pathways, predict public resource needs and minimize unnecessary spending

Expressivity and control in limited reasoning

Abstract. Real agents (natural or artificial) are limited in their reasoning capabilities. In this paper, we present a general framework for modeling limited reasoning based on approximate reasoning and discuss its properties. We start from Cadoli and Schaerf's approximate entailment. We first extend their system to deal with the full language of propositional logic. A tableau inference system is proposed for the extended system together with a sub-classical semantics; it is shown that this new approximate reasoning system is sound and complete with respect to this semantics. We show how this system can be incrementally used to move from one approximation to the next until the reasoning limitation is reached. We note that although the extension is more expressive than the original system, it offers less control over the approximation process. We then suggest how we can recover control while keeping the increased expressivity

Semantic Data Integration for Public Health in Brazil

International audienceThe lack of semantic information is a big challenge, even in context-driven areas like Healthcare, characterized by established terminologies. Here, semantic data integration is the solution to provide precise information and answers to questions like: What is the care pathway of newborns diagnosed with a congenital anomaly in consequence of congenital syphilis in the city of São Paulo? This project will use a semantic data integration technique, ontology based data integration, to integrate three health databases from the city of São Paulo-Brazil: mortality, live births and hospital information system. It is expected that the integration of public health databases will help to map patient care pathways, predict public resource needs and minimize unnecessary spending

Choosing What to Believe - New Results in Selective Revision

Selective Revision was proposed by Ferme and Hansson as ´ a belief revision operation in which it is possible to accept only a part of the input information. In this paper, we extend Selective Revision to belief bases and also to logics not closed under negation.info:eu-repo/semantics/publishedVersio

Pseudo-contractions as Gentle Repairs

Updating a knowledge base to remove an unwanted consequence is a challenging task. Some of the original sentences must be either deleted or weakened in such a way that the sentence to be removed is no longer entailed by the resulting set. On the other hand, it is desirable that the existing knowledge be preserved as much as possible, minimising the loss of information. Several approaches to this problem can be found in the literature. In particular, when the knowledge is represented by an ontology, two different families of frameworks have been developed in the literature in the past decades with numerous ideas in common but with little interaction between the communities: applications of AGM-like Belief Change and justification-based Ontology Repair. In this paper, we investigate the relationship between pseudo-contraction operations and gentle repairs. Both aim to avoid the complete deletion of sentences when replacing them with weaker versions is enough to prevent the entailment of the unwanted formula. We show the correspondence between concepts on both sides and investigate under which conditions they are equivalent. Furthermore, we propose a unified notation for the two approaches, which might contribute to the integration of the two areas

Lightweight, General Inference of Streaming Video Quality from Encrypted Traffic

Accurately monitoring application performance is becoming more important for Internet Service Providers (ISPs), as users increasingly expect their networks to consistently deliver acceptable application quality. At the same time, the rise of end-to-end encryption makes it difficult for network operators to determine video stream quality-including metrics such as startup delay, resolution, rebuffering, and resolution changes-directly from the traffic stream. This paper develops general methods to infer streaming video quality metrics from encrypted traffic using lightweight features. Our evaluation shows that our models are not only as accurate as previous approaches , but they also generalize across multiple popular video services, including Netflix, YouTube, Amazon Instant Video, and Twitch. The ability of our models to rely on lightweight features points to promising future possibilities for implementing such models at a variety of network locations along the end-to-end network path, from the edge to the core

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049