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Contains fulltext : 199890.pdf (Author’s version preprint ) (Open Access) INTERSYMP 2018: 30th International Conference on Systems Research, Informatics and Cybernetics July 30 – August 3, 2018 Markgraf-Ludwig Gymnasium, Hardstrasse 2 Baden-Baden, Germany

Organic and conventional cropping systems differ in the nature and amounts of nitrogen (N) inputs, which may affect efficiency and sustainability of N use. In the DOK (bio-Dynamic, bio-Organic, Konventionell) field experiment, organic and conventional cropping systems have been compared since 1978 at two fertilization levels (with level 2 being typical for the respective system and level 1 receiving half of this dose).

International audience; We consider the problem of reasoning from logical bases equipped with a partial order expressing relative certainty, with a view to construct a partially ordered deduc-tive closure via syntactic inference. At the syntactic level we use a language expressing pairs of related formulas and axioms describing the properties of the order. Reasoning about uncertainty using possibility theory relies on the idea that if an agent believes each among two propositions to some extent, then this agent should believe their conjunction to the same extent. This principle is known as adjunction. Adjunction is often accepted in epistemic logic but fails with probabilistic reasoning. In the latter, another principle prevails, namely the sure thing principle, that claims that the certainty ordering between propositions should be invariant to the addition or deletion of possible worlds common to both sets of models of these propositions. Pursuing our work on relative certainty logic based on possibility theory, we propose a qualitative likelihood logic that respects the sure thing principle, albeit using a likelihood relation that preserves adjunction.

This paper is a survey of the connections between three-valued logics and rough sets from the point of view of incomplete information management. Based on the fact that many three-valued logics can be put under a unique algebraic umbrella, we show how to translate three-valued conjunctions and implications into operations on ill-known sets such as rough sets. We then show that while such translations may provide mathematically elegant algebraic settings for rough sets, the interpretability of these connectives in terms of an original set approximated via an equivalence relation is very limited, thus casting doubts on the practical relevance of truth-functional logical renderings of rough sets.

The aim of this study was to develop the Language Exposure Assessment Tool (LEAT) and to examine its cross-linguistic validity, reliability, and utility. The LEAT is a computerized interview-style assessment that requests parents to estimate language exposure. The LEAT yields an automatic calculation of relative language exposure and captures qualitative aspects of early language experience.

© 2016, CEUR-WS. All rights reserved. The formal similarity between possibility theory and formal concept analysis, made ten years ago, has suggested the introduction in the latter setting of the counterpart of possibilistic operators, which were ignored before. These new operators can be related to the basic operator of formal concept analysis by a triple use of negations on the contexts, on the set-valued arguments and on the obtained results, and lead to consider new compositions worth of interest. They enable us to complete the Guigues-Duquenne basis with rules having disjunctive conclusions. Besides, the approach can be naturally generalized to incomplete contexts and then to uncertain context where uncertainty is graded.

Environmental enrichment (EE) was shown recently to accelerate brain development in rodents. Increased levels of maternal care, and particularly tactile stimulation through licking and grooming, may represent a key component in the early phases of EE. We hypothesized that enriching the environment in terms of body massage may thus accelerate brain development in infants. We explored the effects of body massage in preterm infants and found that massage accelerates the maturation of electroencephalographic activity and of visual function, in particular visual acuity. In massaged infants, we found higher levels of blood IGF-1. Massage accelerated the maturation of visual function also in rat pups and increased the level of IGF-1 in the cortex. Antagonizing IGF-1 action by means of systemic injections of the IGF-1 antagonist JB1 blocked the effects of massage in rat pups. These results demonstrate that massage has an influence on brain development and in particular on visual development and suggest that its effects are mediated by specific endogenous factors such as IGF-1. Copyright © 2009 Society for Neuroscience.

© 2014 The Authors and IOS Press. Generalized possibilistic logic (GPL) is a logic for reasoning about the revealed beliefs of another agent. It is a two-tier propositional logic, in which propositional formulas are encapsulated by modal operators that are interpreted in terms of uncertainty measures from possibility theory. Models of a GPL theory represent weighted epistemic states and are encoded as possibility distributions. One of the main features of GPL is that it allows us to explicitly reason about the ignorance of another agent. In this paper, we study two types of approaches for reasoning about ignorance in GPL, based on the idea of minimal specificity and on the notion of guaranteed possibility, respectively. We show how these approaches naturally lead to different flavours of the language of GPL and a number of decision problems, whose complexity ranges from the first to the third level of the polynomial hierarchy.

If an agent desires that ψ and desires that φ this agent often also desires that ψ and φ hold at the same time (ψ φ). However, there are cases where ψ φ may be found less satisfactory for the agent than each of ψ or φ alone. This paper is a first attempt at modeling such nonmonotonic desires. The approach is developed in the setting of possibility theory, since it has been recently pointed out that guaranteed (or strong) possibility measures are a good candidate for modeling graded desires. Although nonmonotonic reasoning has been studied extensively for knowledge, and that preferential nonmonotonic consequence relations can be faithfully represented in the possibilistic setting, nonmonotonic desires appear to require a different approach.

BACKGROUND & AIMS: This study examined the prevalence of upper gastrointestinal (GI) symptoms and symptom groupings and determined impact on disability days in a nationally representative US sample. METHODS: A telephone survey of 21,128 adults was conducted including questions about the presence of upper GI symptoms during the past 3 months. Respondents were categorized as symptomatic (ie, reported GI symptoms once per month) or asymptomatic. The survey included questions about missed work, leisure activity, or household activity days. Symptom groupings were identified by using factor analysis, and cluster analysis was used to assign respondents into distinct groups on the basis of these symptom groupings. RESULTS: The prevalence of an average of 1 or more upper GI symptoms during the past 3 months was 44.9%. The most common symptoms experienced during the past 3 months were early satiety, heartburn, and postprandial fullness. Factor analysis identified 4 symptom groupings: (1) heartburn/regurgitation; (2) nausea/vomiting; (3) bloating/abdominal pain; and (4) early satiety/loss of appetite. Five respondent clusters were identified; the largest clusters were primarily early satiety/fullness (44%) and gastroesophageal reflux disease-like symptoms (28%). Two small clusters reflected nausea and vomiting (7%) and a heterogeneous symptom profile (4%). Symptomatic respondents reported significantly more missed work, leisure, and household activity days than asymptomatic respondents (all P < .0001). CONCLUSIONS: Factor analysis separated GI symptoms into groupings reflecting gastroesophageal reflux disease and dyspepsia: early satiety, postprandial fullness, and loss of appetite; bloating and abdominal pain/discomfort; and nausea and vomiting. These upper GI symptoms were associated with significant loss of work and activity days.

The modeling of conditional/implicative rules of the form "if A then B" plays a crucial role in any attempt at formalizing reasoning. Starting from the expression of different forms of rules that have been identified in the setting of possibility theory, we study their counterparts in the framework of extensions of possibilistic logic. A distinction between rules and meta-rules is especially emphasized. The former contribute to the partial specification of a unique epistemic state, while the latter relate partially specified epistemic states, as in Answer Set Programming (ASP). The contribution of Pascal Nicolas to bridging the gap between possibilistic logic and ASP is discussed in this perspective. © 2012 Lavoisier.

If A caused B and B caused C, did A cause C? Although laypersons commonly perceive causality as being transitive, some philosophers have questioned this assumption, and models of causality in artificial intelligence are often agnostic with respect to transitivity. We consider two formal models of causation that differ in the way they represent uncertainty. The quantitative model uses a crude probabilistic definition, arguably the common core of more sophisticated quantitative definitions; the qualitative model uses a definition based on nonmonotonic consequence relations. Different sufficient conditions for the transitivity of causation are laid bare by the two models: The Markov condition on events for the quantitative model, and a so-called saliency condition (A is perceived as a typical cause of B) for the qualitative model. We explore the formal and empirical relations between these sufficient conditions, and between the underlying definitions of perceived causation. These connections shed light on the range of applicability of each model, contrasting commonsense causal reasoning (supposedly qualitative) and scientific causation (more naturally quantitative). These speculations are supported by a series of three behavioral experiments. © 2012 Springer Science+Business Media B.V.

Although εL is a popular logic used in large existing knowledge bases, to the best of our knowledge no procedure has yet been proposed that computes uniform εL interpolants of general εL terminologies. Up to now, also the bounds on the size of uniform εL interpolants remain unknown. In this paper, we propose an approach based on proof theory and the theory of formal tree languages to computing a finite uniform interpolant for a general εL terminology if it exists. Further, we show that, if such a finite uniform εL interpolant exists, then there exists one that is at most triple exponential in the size of the original TBox, and that, in the worst-case, no shorter interpolants exist, thereby establishing the triple exponential tight bounds on their size. © 2012 The Author(s).

In spite of variable grain protein contents, baking quality of organic wheat was found to be acceptable to good. Mycotoxin (DON) infestation was generally low on tested grain samples. Choice of wheat cultivar was the most efficient way to obtain higher grain quality. Fertilization with readily available nitrogen and, to a lower extent, association with legumes and green manures with mixtures containing fodder legumes also improved grain quality. Reduced tillage affected soil quality and wheat yield but had little effects on grain quality.

We propose an analysis of the impossibility results in judgement aggregation by means of a proof-theoretical approach to collective rationality. In particular, we use linear logic in order to analyse the group inconsistencies and to show possible ways to circumvent them.

Agronomical ways for better quality and safety Choice of cultivar is an efficient way to obtain higher grain quality. Intercropping legumes (grain or forage) improves weed competition and N availability for wheat crop or succeeding crop. Green manure can be an effective alternative to farmyard manure. Fertilization with readily available nitrogen improves yield and quality when water is available. Reduced tillage affects soil fertility and wheat yield but has little effects on grain quality. Technological ways for better quality and safety Milling process strongly influences flour characteristics. Stone milling improves nutritive value; characteristics remain very stable independent of the milling yield. Flour characteristics from roller milling appear very susceptible to the milling yield. Increasing the milling yield in the aim of enriching nutritional quality has a detrimental effect either on safety (DON) or on bread-making quality (bread volume).

Reduction of acids to molecular hydrogen as a means of storing energy is catalyzed by platinum, but its low abundance and high cost are problematic. Precisely controlled delivery of protons is critical in hydrogenase enzymes in nature that catalyze hydrogen (H2) production using earth-abundant metals (iron and nickel). Here, we report that a synthetic nickel complex, [Ni(PPh2NPh)2](BF4)2, (PPh2NPh = 1,3,6-triphenyl-1-aza-3,6-diphosphacycloheptane), catalyzes the production of H2 using protonated dimethylformamide as the proton source, with turnover frequencies of 33,000 per second (s−1) in dry acetonitrile and 106,000 s−1 in the presence of 1.2 M of water, at a potential of –1.13 volt (versus the ferrocenium/ferrocene couple). The mechanistic implications of these remarkably fast catalysts point to a key role of pendant amines that function as proton relays. Precisely shaped basic ligands protect highly reactive protons and electrons to help accelerate catalytic hydrogen formation. Precisely shaped basic ligands protect highly reactive protons and electrons to help accelerate catalytic hydrogen formation.

Power and choice represent two fundamental forces that govern human behavior. Scholars have largely treated power as an interpersonal construct involving control over other individuals, whereas choice has largely been treated as an intrapersonal construct that concerns the ability to select a preferred course of action. Although these constructs have historically been studied separately, we propose that they share a common foundation—that both are rooted in an individual’s sense of personal control. Because of this common underlying basis, we hypothesized that power and choice are substitutable; that is, we predicted that the absence of one would increase the desire for the other, which, when acquired, would serve to satisfy the broader need for control. We also predicted that choice and power would exhibit a threshold effect, such that once one source of control had been provided (e.g., power), the addition of the other (e.g., choice) would yield diminishing returns. Six experiments provide evidence supporting these predictions.

Two important ideas at the core of Zadeh's seminal contributions to fuzzy logic and approximate reasoning are the notions of granulation and of possibilistic uncertainty. In this short paper, elaborating a bit on the basis of some mathematical analogy, recently made by the authors, between possibility theory and formal concept analysis, we suggest another bridge between the notion of extensional fuzzy set with respect to a similarity relation, and formal concept analysis. Thus, we point out some fruitful interactions between the possibilistic representation of information and two views of granulation emphasizing the idea of clusters of points that can be identified respectively on the basis of their closeness, or of their common labeling in terms of properties.

Nowadays, chemical tankers are transporting a wide variety of chemical products. These products have different characteristics, and some are toxic. In literature several studies suggest an increased incidence of various forms of cancer for crew members on tankers. Most of these studies are based on medical statistics, rather than on effective measurements on board. The aim of this study is to monitor the average concentrations of toxic vapours on board of chemical tankers. Therefore we went on board of two chemical tankers for a 14-day trip and performed measurements during the normal operation of the vessel, in order to find out whether cargo vapours are traceable in the atmosphere in and around the vessel. The concentrations measured clearly show that there is a relationship between the cargoes transported and the concentration of the cargo vapour in the atmosphere in and around the vessel. The results further show an elevated concentration of the analyzed substances in the engine room and an important influence of the relative wind direction. Tank vents situated in the gas-safe zone influenced the results as well.

Programme SASUPHII - Séminaires sur les Ambiances Sonores Urbaines : Pratiques et Habitudes de l’Interdisciplinarité pour l’Intersectoriel

Intelligent agents require methods to revise their epistemic state as they acquire new information. Jeffrey's rule, which extends conditioning to uncertain inputs, is currently used for revising probabilistic epistemic states when new information is uncertain. This paper analyses the expressive power of two possibilistic counterparts of Jeffrey's rule for modeling belief revision in intelligent agents. We show that this rule can be used to recover most of the existing approaches proposed in knowledge base revision, such as adjustment, natural belief revision, drastic belief revision, revision of an epistemic by another epistemic state. In addition, we also show that that some recent forms of revision, namely improvement operators, can also be recovered in our framework. © 2009 Springer Berlin Heidelberg.

Relationships between geographically referenced variables are usually spatially heterogeneous and, to account for such variations, local models are necessary. This paper compares the Geographically Weighted Regression (GWR) model, usually used to integrate and examine the spatial heterogeneity of a relationship, and the Fuzzy Clustering-Based Least Squares (FCBLS) model for the analysis of spatially varying relationships. Both models use the same model parameters and bandwidth values derived from the Akaike Information Criterion. The results show that FCBLS outperforms the GWR model.

Optimism or pessimism of investors is one of the important characteristics that determine the investment behavior in financial markets. In this paper, we propose a model of investor optimism based on a fuzzy connective. The advantage of the proposed approach is that the influence of different levels of optimism can be studied by varying a single parameter. We implement our model in an artificial financial market based on the LLS model. We find that more optimistic investors create more pronounced booms and crashes in the market, when compared to the unbiased efficient market believers of the original model. In the case of extreme optimism, the optimistic investors end up dominating the market, while in the case of extreme pessimism, the market reduces to the benchmark model of rational informed investors.

One of the most important stages in data preprocessing for data mining is feature selection. Real-world data analysis, data mining, classification and modeling problems usually involve a large number of candidate inputs or features. Less relevant or highly correlated features decrease, in general, the classification accuracy, and enlarge the complexity of the classifier. Feature selection is a multicriteria optimization problem, with contradictory objectives, which are difficult to properly describe by conventional cost functions. The use of fuzzy decision making may improve the performance of this type of systems, since it allows an easier and transparent description of the different criteria used in the feature selection process. In previous work an ant colony optimization algorithm for feature selection was presented, which minimizes two objectives: number of features and classification error. Two pheromone matrices and two different heuristics are used for each objective. In this paper, a fuzzy objective function is proposed to cope with the difficulty of weighting the different criteria involved in the optimization algorithm.

Knowledge discovery in databases (KDD) is the process of discovering interesting knowledge from large amounts of data. However, real-world datasets have problems such as incompleteness, redundancy, inconsistency, noise, etc. All these problems affect the performance of data mining algorithms. Thus, preprocessing techniques are essential in allowing knowledge to be extracted from data. This work presents a real world application of knowledge discovery in databases, with the objective of prediction of bankruptcy. For this task fuzzy classification models based on fuzzy clustering are used, which are developed solely from numerical data. This data set has missing values, extreme values and also presents a much smaller bankruptcy class than the not bankruptcy class, which makes it a challenging problem in the scope of KDD.

International audience; The setting of formal concept analysis presupposes the existence of a relation between objects and properties. Knowing that an unspecified object has a given property induces a formal possibil-ity distribution that models the set of objects known to possess this property. This view expressed in a recent work by the authors of the present paper, has led to introduce the set-valued counterpart to the four set functions evaluating potential or actual, possibility or neces-sity that underlie bipolar possibility theory, and to study associated notions. This framework puts formal concept analysis in a new, en-larged perspective, further explored in this article. The “actual (or guaranteed) possibility” function induces the usual Galois connex-ion that defines the notion of a concept as the pair of its extent and its intent. A new Galois connexion, based on the necessity measure, partitions the relation in “orthogonal” subsets of objects having dis-tinct properties. Besides, the formal similarity between the notion of division in relational algebra and the “actual possibility” function leads to define the fuzzy set of objects having most properties in a set, and other related notions induced by fuzzy extensions of division. Generally speaking, the possibilistic view of formal concept analysis still applies when properties are a matter of degree, as discussed in the paper. Lastly, cases where the object / property relation is incom-plete due to missing information, or more generally pervaded with possibilistic uncertainty is also discussed.

During normal management of a chemical tanker, the crew will perform operations in the cargo part of the vessel, like entering tanks, cleaning lines, connecting and disconnecting of the manifold, sampling and maintenance of specific equipment. Under these circumstances there will be a higher risk of direct contact with the cargo and cargo vapors. These vapors can be taken up by ventilation intakes, bringing the cargo fumes into the accommodation and engine Radiello® passive samplers offer several advantages for this application, including no electricity use, small sizes, adjustable exposure times and especially a precise and selective measurement of air concentrations.Especially the benzene concentrations on board were relatively high. The cargo on board can explain a lot. During our stay on board benzene has been loaded in three tanks and later on these tanks have been cleaned and ventilated during our measurements. The International Maritime Organisation (IMO), recognized that chronic exposure to very low concentrations of benzene vapors in air, of the order of a few parts per million, may cause leukaemia. According to Madl, benzene exposure on board of crude oil and chemical tankers do not pose a health risk to deck crewman. interpretation of the results will soon demonstrate if we can confirm Madl’s statement on board of this type of vessels.On the other hand we measured the concentrations of toxic vapors over relatively short periods, during well specific operations on deck. Here the concentrations were measured with the ‘PAC III’ apparatus of Draeger®. The results of this investigation have to be compared with the TLV-TWA and TLV-STEL values. Conclusions here should encourage the optimization of the use of respiratory protection aids during cargo operations.

D&al004; International audience; According to the current literature, there are two different approaches to the definition of the variance of a fuzzy random variable. In the first one, the variance is defined as a fuzzy interval, offering a gradual description of our incomplete knowledge about the variance of an underlying, imprecisely observed, classical random variable. In the second case, the variance of the fuzzy random variable is defined as a crisp number, that makes it easier to handle in further processing. In this work, we introduce yet another definition of the variance of a fuzzy random variable, in the context of the theory of imprecise probabilities. The new variance is not defined as a fuzzy or crisp number, but it is a real interval, which is a compromise between both previous definitions. Our main objectives are twofold: first, we show the interpretation of the new variance and, second, with the help of simple examples, we demonstrate the usefulness of all these definitions when applied to particular situations.

International audience

DestD&al003; International audience; Probability intervals are imprecise probability assignments over elementary events. They constitute a very convenient tool to model uncertain information : two common cases are confidence intervals on parameters of multinomial distributions built from sample data and expert opinions provided in terms of such intervals. In this paper, we study how probability intervals can be transformed into other uncertainty models such as possibility distributions, Ferson's p-boxes, random sets and Neumaier's clouds.

Consumers have become more aware of healthy and safe food produced with low environmental impact. Organic agriculture is of particular interest in this respect, as manifested by 5.768 million hectares managed pursuant to Council Regulation (EEC) 2092/91 in Europe. However, there can be a considerable risk that the avoidance of chemical inputs in organic farming will result in poor food quality. Here the results of a study on the quality of wheat (Triticum aestivum L.) grown in a 21 year agrosystem comparison between organic and conventional farming in central Europe are reported. Wheat was grown in a ley (grass/clover) rotation. The 71% lower addition of plant-available nitrogen and the reduced input of other means of production to the organic field plots led to 14% lower wheat yields. However, nutritional value (protein content, amino acid composition and mineral and trace element contents) and baking quality were not affected by the farming systems. Despite exclusion of fungicides from the organic production systems, the quantities ofmycotoxins detected in wheat grains were low in all systems and did not differ. In food preference tests, as an integrative method, rats significantly preferred organically over conventionally produced wheat. The findings indicate that high wheat quality in organic farming is achievable by lower inputs, thereby safeguarding natural resources. (C) 2007 Society of Chemical Industry

International audience; A general approach to practical inference with gradual implicative rules and fuzzy inputs is presented. Gradual rules represent constraints restricting outputs of a fuzzy system for each input. They are tailored for interpolative reasoning. Our approach to inference is founded on the use of well-conditioned fuzzy systems. It is based on the computation of the fuzzy output under an interval-valued input. A double decomposition of fuzzy inputs is done in terms of @-cuts and in terms of a partitioning of these cuts according to areas where only two rules apply.; Cet article propose une methode générique d'inférence avec des règles implicatives graduelles et des entrées floues. Les règles graduelles permettent de représenter des contraintes sur un ensemble de possibles et sont très intéressantes pour leur capacité d'interpolation. Nous proposons une méthode d'inférence basée sur la notion de système bien conditionné. Elle s'appuie sur l'inférence à partir d'entrées rectangulaires dont le calcul s'avère simple. Elle utilise une double décomposition : par coupes pour se ramener à des entrées rectangulaires et par partitionnement de ces coupes en regions rectangulaires où seules deux règles s'appliquent à la fois.

International audience; A model is defined that predicts an agent’s ascriptions of causality (and related notions of facilitation and justification) between two events in a chain, based on background knowledge about the normal course of the world. Background knowledge is represented by nonmonotonic consequence relations. This enables the model to handle situations of poor information, where background knowledge is not accurate enough to be represented in, e.g., structural equations. Tentative properties of causality ascriptions are explored, i.e., preference for abnormal factors, transitivity, coherence with logical entailment, and stability with respect to disjunction and conjunction. Empirical data are reported to support the psychological plausibility of our basic definitions.