bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Monotonic Ontology-based Abstractions of Data Services
Authors: Cima Gianluca , Lenzerini Maurizio , Poggi Antonella
Published: August 2020

In Ontology-Based Data Access (OBDA), a domain ontology is linked to the data sources of an organization in order to query, integrate and manage data through the concepts and relations of the domain of interest, thus abstracting from the technical details of the data layer implementation. While the great majority of contributions in OBDA in the last decade have been concerned with the issue of computing the answers of queries expressed over the ontology, recent papers address a different problem, namely the one of providing suitable abstractions of data services, i.e., characterizing or explaining the semantics of queries over the sources in terms of queries over the domain ontology. Current works on this subject are based on expressing abstractions in terms of unions of conjunctive queries (UCQs) over the ontology. In this paper we advocate the use of a non-monotonic language for this task. As a first contribution, we present a simple extension of UCQs with non-monotonic features, and show that non-monotonicity provides more expressive power in characterizing the semantics of data services. A second contribution is to prove that, similarly to the case of monotonic abstractions, depending on the expressive power of the languages used to specify the various components of the OBDA system, there are cases where neither perfect nor approximated abstractions exist for a given data service. As a third contribution, we single out interesting special cases where the existence of abstractions is guaranteed, and we present algorithms for computing such abstractions in these cases.
Lightweight Parallel Multi-Agent Epistemic Planning
Authors: Cooper Martin , Herzig Andreas , Maris Frédéric , Perrotin Elise , Vianey Julien
Published: August 2020

We study a simple version of multi-agent epistemic planning where the number of parallel steps has to be minimized. We prove that this extension of classical planning is in PSPACE. We propose an encoding in PDDL and present some experiments providing evidence that this encoding allows us to solve practical problems. The types of problems we can encode include problems in which one agent can teach another agent how to perform a task and communication problems where some information must not be revealed to some agents.
Strategy Synthesis for Data-Aware Dynamic Systems with Multiple Actors
Authors: de Leoni Massimiliano , Felli Paolo , Montali Marco
Published: August 2020

The integrated modeling and analysis of dynamic systems and the data they manipulate has been long advocated, on the one hand, to understand how data and corresponding decisions affect the system execution, and on the other hand to capture how actions occurring in the systems operate over data. KR techniques proved successful in handling a variety of tasks over such integrated models, ranging from verification to online monitoring. In this paper, we consider a simple, yet relevant model for data-aware dynamic systems (DDSs), consisting of a finite-state control structure defining the executability of actions that manipulate a finite set of variables with an infinite domain. On top of this model, we consider a data-aware version of reactive synthesis, where execution strategies are built by guaranteeing the satisfaction of a desired linear temporal property that simultaneously accounts for the system dynamics and data evolution.
Finite Controllability for Ontology-Mediated Query Answering of CRPQ
Authors: Figueira Diego , Figueira Santiago , Pin Baque Edwin
Published: August 2020

Finite ontology mediated query answering (FOMQA) is the variant of ontology mediated query answering (OMQA) where the represented world is assumed to be finite, and thus only finite models of the ontology are considered. We study the property of finite-controllability, that is, whether FOMQA and OMQA are equivalent, for fragments of C2RPQ.
C2RPQ is the language of conjunctive two-way regular path queries, which can be regarded as the result of adding simple recursion to Conjunctive Queries. For graph classes S, we consider fragments C2RPQ(S) of C2RPQ as the queries whose underlying graph structure is in S.
We completely classify the finitely controllable and non-finitely controllable fragments under: inclusion dependencies, (frontier-)guarded rules, frontier-one rules (either with or without constants), and more generally under guarded-negation first-order constraints.
For the finitely controllable fragments, we show a reduction to the satisfiability problem for guarded-negation first-order logic, yielding a 2EXPTIME algorithm (in combined complexity) for the corresponding (F)OMQA problem.
Explainable Acceptance in Probabilistic Abstract Argumentation: Complexity and Approximation
Authors: Alfano Gianvincenzo , Calautti Marco , Greco Sergio , Parisi Francesco , Trubitsyna Irina
Published: August 2020

Recently there has been an increasing interest in probabilistic abstract argumentation, an extension of Dung's abstract argumentation framework with probability theory. In this setting, we address the problem of computing the probability that a given argument is accepted. This is carried out by introducing the concept of probabilistic explanation for a given (probabilistic) extension. We show that the complexity of the problem is FP^#P-hard and propose polynomial approximation algorithms with bounded additive error for probabilistic argumentation frameworks where odd-length cycles are forbidden. This is quite surprising since, as we show, such kind of approximation algorithm does not exist for the related FP^#P-hard problem of computing the probability of the credulous acceptance of an argument, even for the special class of argumentation frameworks considered in the paper.
Entity Type Recognition – Dealing with the Diversity of Knowledge
Authors: Giunchiglia Fausto , Fumagalli Mattia
Published: August 2020

Semantic Heterogeneity is the problem that arises when multiple resources present differences in how they represent the same real-world phenomenon. In KR, an early approach was the development of ontologies and, later on, when ontologies showed at the knowledge level the same semantic heterogeneity that they were meant to fix at the data level, to compute mappings among them. In this paper we acknowledge the impossibility of avoiding semantic heterogeneity, this being a consequence of the more general phenomenon of the diversity of the world and of the world descriptions. In this perspective, the heterogeneity of ontologies is a feature (and not a bug to be fixed by aligning them) which gives the possibility to use the most suitable ontology in any given application context. The main contributions of this paper are: (i) a novel articulation of the problem of semantic heterogeneity, as it appears at the knowledge level, as contextuality, (ii) its qualitative and quantitative formalization in terms of a set of diversity and unity metrics and (iii) an Entity Type Recognition algorithm which selects the contextually most appropriate ontology and exploits it to solve the current problem, e.g., the alignment and integration of a set of input schemas. The experimental results show the validity of the approach.
Datalog Rewritability and Data Complexity of ALCHOIF with Closed Predicates
Authors: Gogacz Tomasz , Lukumbuzya Sanja , Ortiz Magdalena , Šimkus Mantas
Published: August 2020

We study the relative expressiveness of ontology-mediated queries (OMQs) formulated in the expressive Description Logic ALCHOIF extended with closed predicates. In particular, we present a polynomial-time translation from OMQs into Datalog with negation under the stable model semantics, the formalism that underlies Answer Set Programming. This is a novel and non-trivial result: the considered OMQs are not only non-monotonic but also feature a tricky combination of nominals, inverse roles, and role functionality. We start with atomic queries and then lift our approach to a large class of first-order queries where quantification is “guarded” by closed predicates. Our translation is based on a characterization of the query answering problem via integer programming, and a specially crafted program in Datalog with negation that finds solutions to dynamically generated systems of integer inequalities. As an important by-product of our translation, we get that the query answering problem is co-NP-complete in data complexity for the considered class of OMQs. Thus, answering these OMQs in the presence of closed predicates is not harder than answering them in the standard setting. This is not obvious as closed predicates are known to increase data complexity for some existing ontology languages.
Multi-head Guarded Existential Rules Over Fixed Signatures
Authors: Gottlob Georg , Manna Marco , Pieris Andreas
Published: August 2020

Guarded existential rules form a robust rule-based language for modelling ontologies. The central problem of ontology-based query answering, as well as the notion of polynomial combined rewritability, have been extensively studied during the last years for this formalism. However, the relevant setting where the underlying signature is considered to be fixed is far from being well understood. All the existing results on ontology-based query answering and polynomial combined rewritability assume rule heads with one atom, while existential rules in real ontologies are typically coming with multi-heads consisting of several atoms. We aim to fill this gap.
Syntax Splitting for Iterated Contractions
Authors: Haldimann Jonas Philipp , Kern-Isberner Gabriele , Beierle Christoph
Published: August 2020

Parikh developed the notion of syntax splitting to describe belief sets with independent parts. He also formulated a postulate demanding that belief revisions respect syntax splittings in belief sets. The concept of syntax splitting was later transferred to epistemic states with total preorders and ranking functions by Kern-Isberner and Brewka along with corresponding postulates for belief revisions. Besides revision, contraction is also a central operation in the field of general belief change. In this paper, we analyse belief contractions with respect to syntax splitting. Based on the work on syntax splitting for revision, we develop syntax splitting postulates for contractions on ranking functions, on epistemic states with total preorder, and on belief sets. Finally, we evaluate different contractions from the literature, namely moderate contraction, natural contraction, lexicographic contraction, and c-contractions with respect to the newly developed contraction postulates.
Dynamic Awareness
Authors: Halpern Joseph Y. , Piermont Evan
Published: August 2020

We investigate how to model the beliefs of an agent who becomes more aware. We use the framework of Halpern and Rego (2013) by adding probability, and define a notion of a model transition that describes constraints on how, if an agent becomes aware of a new formula φ in state s of a model M, she transitions to state s* in a model M*. We then discuss how such a model can be applied to information disclosure.
Answer Set Programming with Composed Predicate Names
Authors: Alviano Mario
Published: August 2020

Mainstream systems for Answer Set Programming implement intelligent grounding to eliminate object variables from the input program, often obtaining a propositional program of reasonable size. However, non-stratified negation may inhibit the simplification of some rule bodies due to the lack of knowledge on the truth of recursive atoms. Frustration is greatest when the program is clearly locally stratified, such as in case of numerical arguments in rule heads obtained by increasing some body arguments; common examples are minimal distances in graphs and time arguments in planning scenarios. This paper suggests to move some arguments in predicate names, so that the declarative semantics of Answer Set Programming is preserved, but non-stratified negation is possibly avoided thanks to symbolic rule instantiation. A proof of concept is given in terms of Jinja templates for arguments with a clear range.
Plausible Reasoning about EL-Ontologies using Concept Interpolation
Authors: Ibáñez-García Yazmín , Gutiérrez-Basulto Víctor , Schockaert Steven
Published: August 2020

Description logics (DLs) are standard knowledge representation languages for modelling ontologies, i.e. knowledge about concepts and the relations between them. Unfortunately, DL ontologies are difficult to learn from data and time-consuming to encode manually. As a result, ontologies for broad domains are almost inevitably incomplete. In recent years, several data-driven approaches have been proposed for automatically extending such ontologies. One family of methods rely on characterizations of concepts that are derived from text descriptions. While such characterizations do not capture ontological knowledge directly, they encode information about the similarity between different concepts that can be exploited for filling in the gaps in existing ontologies. To this end, several inductive inference mechanisms have already been proposed, but these have been defined and used in a heuristic fashion. In this paper, we instead propose an inductive inference mechanism which is based on a clear model-theoretic semantics, and can thus be tightly integrated with standard deductive reasoning. We particularly focus on interpolation, a powerful commonsense reasoning mechanism which is closely related to cognitive models of category-based induction. Apart from the formalization of the underlying semantics, as our main technical contribution we provide computational complexity bounds for reasoning in EL with this interpolation mechanism.
Logical Separability of Incomplete Data under Ontologies
Authors: Jung Jean Christoph , Lutz Carsten , Pulcini Hadrien , Wolter Frank
Published: August 2020

Finding a logical formula that separates positive and negative examples given in the form of labeled data items is fundamental in applications such as concept learning, reverse engineering of database queries, and generating referring expressions. In this paper, we investigate the existence of a separating formula for incomplete data in the presence of an ontology. Both for the ontology language and the separation language, we concentrate on first-order logic and three important fragments thereof: the description logic ALCI, the guarded fragment, and the two-variable fragment. We consider several forms of separability that differ in the treatment of negative examples and in whether or not they admit the use of additional helper symbols to achieve separation. We characterize separability in a model-theoretic way, compare the separating power of the different languages, and determine the computational complexity of separability as a decision problem.
SAT-Based ATL Satisfiability Checking
Authors: Kacprzak Magdalena , Niewiadomski Artur , Penczek Wojciech
Published: August 2020

Synthesis of models and strategies is a very important task in software engineering. The main problem here consists in checking the satisfiability of formulae expressing the specification of a system to be implemented. This paper puts forward a novel method for deciding the satisfiability of formulae of Alternating-time Temporal Logic (ATL) under perfect and imperfect information. The synthesised models of strategic games are often minimal. The method expands the one for CTL exploiting SAT Modulo Monotonic Theories (SMMT) solvers. Our tool MsATL combines SMMT solvers with two existing ATL model checkers: MCMAS and STV. This is the first ever tool for checking the satisfiability of imperfect information ATL. The experimental results show that, similarly to the CTL case, our approach appears to be very efficient and can quickly check the satisfiability of large ATL formulae that have been out of reach of the existing approaches.
Changing Beliefs about Domain Dynamics in the Situation Calculus
Authors: Klassen Toryn Q. , McIlraith Sheila A. , Levesque Hector J.
Published: August 2020

Agents change their beliefs about the plausibility of various aspects of domain dynamics -- effects of physical actions, results of sensing, and action preconditions -- as a consequence of their interactions with the world. In this paper we propose a way to conveniently represent domain dynamics in the situation calculus to support such belief change. Furthermore, we suggest patterns to follow when writing the axioms that describe the effects of actions, and prove how these patterns can control the extent to which observations change the agent's beliefs about action effects. We also discuss the relation of our work to the AGM postulates for belief revision. Finally, we show how beliefs about domain dynamics can be incorporated into a form of regression rewriting to support reasoning.
Boolean Role Inclusions in DL-Lite With and Without Time
Authors: Kontchakov Roman , Ryzhikov Vladislav , Wolter Frank , Zakharyaschev Michael
Published: August 2020

Traditionally, description logic has focused on representing and reasoning about classes rather than relations (roles), which has been justified by the deterioration of the computational properties if expressive role inclusions are added. The situation is even worse in the temporalised setting, where monodicity is viewed as an almost necessary condition for decidability. We take a fresh look at the description logic DL-Lite with expressive role inclusions, both with and without a temporal dimension. While we confirm that full Boolean expressive power on roles leads to FO^2-like behaviour in the atemporal case and undecidability in the temporal case, we show that, rather surprisingly, the restriction to Krom and Horn role inclusions leads to much lower complexity in the atemporal case and to decidability (and ExpSpace-completeness) in the temporal case, even if one admits full Booleans on concepts. The latter result is one of very few instances breaking the monodicity barrier in temporal FO. This is also reflected on the data complexity level, where we obtain new rewritability results into FO with relational primitive recursion and FO with unary divisibility predicates.
Computing Cores for Existential Rules with the Standard Chase and ASP
Authors: Krötzsch Markus
Published: August 2020

To reason with existential rules (a.k.a. tuple-generating dependencies), one often computes universal models. Among the many such models of different structure and cardinality, the core is arguably the “best”. Especially for finitely satisfiable theories, where the core is the unique smallest universal model, it has advantages in query answering, non-monotonic reasoning, and data exchange. Unfortunately, computing cores is difficult and not supported by most reasoners. We therefore propose ways of computing cores using practically implemented methods from rule reasoning and answer set programming. Our focus is on cases where the standard chase algorithm produces a core. We characterise this desirable situation in general terms that apply to a large class of cores, derive concrete approaches for decidable special cases, and generalise these approaches to non-monotonic extensions of existential rules.
An Answer Set Programming Approach to Argumentative Reasoning in the ASPIC+ Framework
Authors: Lehtonen Tuomo , Wallner Johannes P. , Järvisalo Matti
Published: August 2020

A major research direction in AI argumentation is the study and development of practical computational techniques for reasoning in different argumentation formalisms. Compared to abstract argumentation, developing algorithmic techniques for different structured argumentation formalisms, such as assumption-based argumentation and the general ASPIC+ framework, is more challenging. At present, there is a lack of efficient approaches to reasoning in ASPIC+. We develop a direct declarative approach based on answer set programming (ASP) to reasoning in an instantiation of the ASPIC+ framework. We establish formal foundations for direct declarative encodings for reasoning in ASPIC+ without preferences for several central argumentation semantics, and detail ASP encodings of semantics for which reasoning about acceptance is NP-hard in ASPIC+. Empirically, the ASP approach scales up to frameworks of significant size, thereby answering the current lack of practical computational approaches to reasoning in ASPIC+ and providing a promising base for capturing further generalizations within ASPIC+.
On the Reversibility of Actions in Planning
Authors: Morak Michael , Chrpa Lukas , Faber Wolfgang , Fišer Daniel
Published: August 2020

Checking whether action effects can be undone is an important question for determining, for instance, whether a planning task has dead-ends. In this paper, we investigate the reversibility of actions, that is, when the effects of an action can be reverted by applying other actions, in order to return to the original state. We propose a broad notion of reversibility that generalizes previously defined versions and investigate interesting properties and relevant restrictions. In particular, we propose the concept of uniform reversibility that guarantees that an action can be reverted independently of the state in which the action was applied, using a so-called reverse plan. In addition, we perform an in-depth investigation of the computational complexity of deciding action reversibility. We show that reversibility checking with polynomial-length reverse plans is harder than polynomial-length planning and that, in case of unrestricted plan length, the PSPACE-hardness of planning is inherited. In order to deal with the high complexity of solving these tasks, we then propose several incomplete algorithms that may be used to compute reverse plans for a relevant subset of states.
Towards a Logic of Meta-Analysis
Authors: Peñaloza Rafael
Published: August 2020

We currently have access to a plethora of statistical analyses based on sampling limited parts of a population. Meta-analysis is the task of combining several statistical results to obtain a more precise and reliable picture of the population. By the nature of sampling, all these results are uncertain, and difficult to combine with other knowledge. In this position paper, we propose a first approach for automated reasoning in meta-analyses.
Designing Participatory Budgeting Mechanisms Grounded in Judgment Aggregation
Authors: Rey Simon , Endriss Ulle , de Haan Ronald
Published: August 2020

We introduce a new approach for designing rules for participatory budgeting, the problem of deciding on the use of public funds based directly on the views expressed by the citizens concerned. The core idea is to embed instances of the participatory budgeting problem into judgment aggregation, a powerful general-purpose framework for modelling collective decision making. Taking advantage of the possibilities offered by judgment aggregation, we enrich the familiar setting of participatory budgeting with additional constraints, namely dependencies between projects and quotas regarding different types of projects. We analyse the rules obtained both in algorithmic and in axiomatic terms.
Modelling the Polysemy of Spatial Prepositions in Referring Expressions
Authors: Richard-Bollans Adam , Gómez Álvarez Lucía , Cohn Anthony G.
Published: August 2020

In previous work exploring how to automatically generate typicality measures for spatial prepositions in grounded settings, we considered a semantic model based on Prototype Theory and introduced a method for learning its parameters from data. However, though there is much to suggest that spatial prepositions exhibit polysemy, each term was treated as exhibiting a single sense. The ability for terms to represent distinct but related meanings is unexplored in the work on grounded semantics and referring expressions, where even homonymy is rarely considered. In this paper we address this problem by analysing the issue of reference using spatial language and examining how the polysemy exhibited by spatial prepositions can be incorporated into semantic models for situated dialogue. We support our approach on theoretical developments of Prototype Theory, which suggest that polysemy may be analysed in terms of radial categories, characterised by having several prototypicality centres. After providing a brief overview of polysemy in spatial language and a review of the related work, we define the Baseline Model and discuss how polysemy may be incorporated to improve it. We introduce a method of identifying polysemes based on `ideal meanings' and a modification of the `principled polysemy' framework. In order to compare polysemes and aid typicality judgements we then introduce a notion of `polyseme hierarchy'. Subsequently, we test the performance of the extended Polysemy Model by comparing it to the Baseline Model as well as a data-driven model of polysemy which we derive with a clustering algorithm. We conclude that our method for incorporating polysemy into the Baseline Model provides significant improvement. Finally, we analyse the properties and behaviour of the generated Polysemy Model, providing some insight into the improvement in performance, as well as justification for the given methods.
Seq2KG: An End-to-End Neural Model for Domain Agnostic Knowledge Graph (not Text Graph) Construction from Text
Authors: Stewart Michael , Liu Wei
Published: August 2020

Knowledge Graph Construction (KGC) from text unlocks information held within unstructured text and is critical to a wide range of downstream applications. General approaches to KGC from text are heavily reliant on the existence of knowledge bases, yet most domains do not even have an external knowledge base readily available. In many situations this results in information loss as a wealth of key information is held within "non-entities". Domain-specific approaches to KGC typically adopt unsupervised pipelines, using carefully crafted linguistic and statistical patterns to extract co-occurred noun phrases as triples, essentially constructing text graphs rather than true knowledge graphs. In this research, for the first time, in the same flavour as Collobert et al.'s seminal work of "Natural language processing (almost) from scratch" in 2011, we propose a Seq2KG model attempting to achieve "Knowledge graph construction (almost) from scratch". An end-to-end Sequence to Knowledge Graph (Seq2KG) neural model jointly learns to generate triples and resolves entity types as a multi-label classification task through deep learning neural networks. In addition, a novel evaluation metric that takes both semantic and structural closeness into account is developed for measuring the performance of triple extraction. We show that our end-to-end Seq2KG model performs on par with a state of the art rule-based system which outperformed other neural models and won the first prize of the first Knowledge Graph Contest in 2019. A new annotation scheme and three high-quality manually annotated datasets are available to help promote this direction of research.
An Answer Set Programming Framework for Reasoning about Agents' Beliefs and Truthfulness of Statements
Authors: Balduccini Marcello , Gelfond Michael , Pontelli Enrico , Son Tran Cao
Published: August 2020

The paper proposes a framework for capturing how an agent’s beliefs evolve over time in response to observations and for answering the question of whether statements made by a third party can be believed. The basic components of the framework are a formalism for reasoning about actions, changes, and observations and a formalism for default reasoning.
The paper describes a concrete implementation that leverages answer set programming for determining the evolution of an agent's ``belief state'', based on observations, knowledge about the effects of actions, and a theory about how these influence an agent's beliefs. The beliefs are then used to assess whether statements made by a third party can be accepted as truthful. The paper investigates an application of the proposed framework in the detection of man-in-the-middle attacks targeting computers and cyber-physical systems. Finally, we briefly discuss related work and possible extensions.
µ-toksia: An Efficient Abstract Argumentation Reasoner
Authors: Niskanen Andreas , Järvisalo Matti
Published: August 2020

We describe the µ-toksia argumentation reasoning system. The system supports a range of different reasoning tasks over both standard and dynamic abstract argumentation frameworks under essentially all central argumentation semantics, covering all tracks and reasoning tasks considered in the most recent International Competition on Computational Models of Argumentation (ICCMA 2019). µ-toksia ranked first in all reasoning tasks in the main track of ICCMA 2019, and has been shown to scale noticeably better on the dynamic track tasks than its current competitors. In this paper, we provide an overview of µ-toksia and its algorithmic and implementation-level details, and provide further empirical evidence beyond ICCMA 2019 on the efficiency of µ-toksia compared to related systems.
On the Approximability of Weighted Model Integration on DNF Structures
Authors: Abboud Ralph , Ceylan İsmail İlkan , Dimitrov Radoslav
Published: August 2020

Weighted model counting (WMC) consists of computing the weighted sum of all satisfying assignments of a propositional formula. WMC is well-known to be #P-hard for exact solving, but admits a fully polynomial randomised approximation scheme (FPRAS) when restricted to DNF structures. In this work, we study weighted model integration, a generalization of weighted model counting which involves real variables in addition to propositional variables, and pose the following question: Does weighted model integration on DNF structures admit an FPRAS? Building on classical results from approximate volume computation and approximate weighted model counting, we show that weighted model integration on DNF structures can indeed be approximated for a class of weight functions. Our approximation algorithm is based on three subroutines, each of which can be a weak (i.e., approximate), or a strong (i.e., exact) oracle, and in all cases, comes along with accuracy guarantees. We experimentally verify our approach over randomly generated DNF instances of varying sizes, and show that our algorithm scales to large problem instances, involving up to 1K variables, which are currently out of reach for existing, general-purpose weighted model integration solvers.
On Tractable XAI Queries based on Compiled Representations
Authors: Audemard Gilles , Koriche Frédéric , Marquis Pierre
Published: August 2020

One of the key purposes of eXplainable AI (XAI) is to develop techniques for understanding predictions made by Machine Learning (ML) models and for assessing how much reliable they are. Several encoding schemas have recently been pointed out, showing how ML classifiers of various types can be mapped to Boolean circuits exhibiting the same input-output behaviours. Thanks to such mappings, XAI queries about classifiers can be delegated to the corresponding circuits. In this paper, we define new explanation and/or verification queries about classifiers. We show how they can be addressed by combining queries and transformations about the associated Boolean circuits. Taking advantage of previous results from the knowledge compilation map, this allows us to identify a number of XAI queries that are tractable provided that the circuit has been first turned into a compiled representation.
Towards an Inductive Logic Programming Approach for Explaining Black-Box Preference Learning Systems
Authors: D'Asaro Fabio A. , Spezialetti Matteo , Raggioli Luca , Rossi Silvia
Published: August 2020

In this paper we advocate the use of Inductive Logic Programming as a device for explaining black-box models, e.g. Support Vector Machines (SVMs), when they are used to learn user preferences. We present a case study where we use the ILP system ILASP to explain the output of SVM classifiers trained on preference datasets. Explanations are produced in terms of weak constraints, which can be easily understood by humans. We use ILASP both as a global and a local approximator for SVMs, score its fidelity, and discuss how its output can prove useful e.g. for interactive learning tasks and for identifying unwanted biases when the original dataset is not available. Finally, we highlight directions for further work and discuss relevant application areas.
On Tractable Representations of Binary Neural Networks
Authors: Shi Weijia , Shih Andy , Darwiche Adnan , Choi Arthur
Published: August 2020

We consider the compilation of a binary neural network’s decision function into tractable representations such as Ordered Binary Decision Diagrams (OBDDs) and Sentential Decision Diagrams (SDDs). Obtaining this function as an OBDD/SDD facilitates the explanation and formal veriﬁcation of a neural network’s behavior. First, we consider the task of verifying the robustness of a neural network, and show how we can compute the expected robustness of a neural network, given an OBDD/SDD representation of it. Next, we consider a more efﬁcient approach for compiling neural networks, based on a pseudo-polynomial time algorithm for compiling a neuron. We then provide a case study in a handwritten digits dataset, highlighting how two neural networks trained from the same dataset can have very high accuracies, yet have very different levels of robustness. Finally, in experiments, we show that it is feasible to obtain compact representations of neural networks as SDDs.
Towards a Framework for Visual Intelligence in Service Robotics: Epistemic Requirements and Gap Analysis
Authors: Chiatti Agnese , Motta Enrico , Daga Enrico
Published: August 2020

A key capability required by service robots operating in real-world, dynamic environments is that of Visual Intelligence, i.e., the ability to use their vision system, reasoning components and background knowledge to make sense of their environment. In this paper, we analyze the epistemic requirements for Visual Intelligence, both in a top-down fashion, using existing frameworks for human-like Visual Intelligence in the literature, and from the bottom up, based on the errors emerging from object recognition trials in a real-world robotic scenario. Finally, we use these requirements to evaluate current Knowledge Bases for Service Robotics and to identify gaps in the support they provide for Visual Intelligence. These gaps provide the basis of a research agenda for developing more effective knowledge representations for Visual Intelligence.
Phonon Characterization, Structural and Optical Properties of Type-II CdSe/CdTe core/shell and Type-II/type-I CdSe/CdTe/ZnS core/shell/shell Quantum Dots
Authors: Xuan Ca Nguyen , Thi Hien Nguyen
Published: August 2020

The CdSe, type-II CdSe/CdTe core/shell and type-II/type-I CdSe/CdTe/ZnS core/shell/shell  quantum dots (QDs) were successfully synthesized in a noncoordinating solvent. The phonon characterizations, optical properties and structures of the synthesized QDs were characterized by Raman scattering (RS) spectra, photoluminescence (PL) spectroscopy, PL-decay lifetime, absorption spectroscopy (Abs), and X-ray diffraction (XRD). The growth of QDs was monitored by using RS, which demonstrated the formation of correct of the core/shell and core/shell/shell structures. Observation results from XRD reveal that all QDs crystallize in the cubic phase with zinc-blende structure. The typical characteristics of spatially indirect recombination for type-II QDs were observed through Abs and PL spectroscopy. The ZnS shell significantly enhanced the PL quantum yeild (QY), the optical durability, the chemical stability and separating CdSe/CdTe QDs from the surroundings. The effect of excitation power on the PL properties of the CdSe core,  CdSe/CdTe and CdSe/CdTe/ZnS QDs has been investigated.
Synthesis and Optical Characterizations of the Fluorescence Silica Nanoparticles Containing Quantum Dots
Authors: Ha Chu Viet , Anh Tuan Chu , Thi Bich Ngoc Nguyen , Nhung Tran Hong , Liem Nguyen Quang , Kim Lien Vu Thi
Published: August 2020

The quantum dots coated by silica  is fluorescence material class with great biocompatibility, low toxicity and water-solubility, that is suitable for bioapplications. This work presents the synthesis of SiO2 coated CdTe/ZnSe (named CdTe) quantum dots (CdTe@SiO2 nanoparticles) via a wet chemmical route called modified Stöber method. The compounds tetraethylorthosilicate (TEOS) has used as precursors, aminopropyltriethoxysilane (APTES) is  as  electric neutralizer, and ammonium hydroxide is used as catalysts. The size of CdTe@SiO2 nanoparticles was estimated about 70 to 150 nm depending on the quantities of H2O, APTEOS, and catalysts. The emission behaviours of SiO2 coated quantum dots was effected by ratio of substances participating in the reaction and synthesis conditions. with the ratio (by volume) of suitable substances: TEOS:solution of QDs:NH4OH:APTES:H2O being 1.5:1.5x10-2:0.8x10-2:4x10-2:3x10-4:5x10-2, the prepared silica nanoparticles containing quantum dots show high fluorescence emission efficiency, the fluorescence intensity is higher than that of uncoated CdTe/ZnSe quantum dots. This is a positive result in the technique of manufacturing luminescent silica nanoparticles containing quantum dots. The results show an ability to use the CdTe@SiO2 nanoparticles for biological application.
Ethnographier la blanchité dans la migration: quelle éthique pour l’étude des dominants?
Authors: Cosquer Claire
Published: August 2020

À partir d’une enquête portant sur les «migrants privilégiés» français à Abu Dhabi, qui se désignent comme «expatriés», cet article montre comment certains des principes fondamentaux de l’éthique de recherche – consentement éclairé des enquêtés et transparence de l’enquêtrice – posent problème lorsque ladite recherche porte sur des enquêtés privilégiés et dominants. L’anthropologie, comme discipline, et l’ethnographie, comme méthode, sont nées et ont grandi dans le giron colonial. Le corollaire de cette histoire coloniale est la structuration d’une «autorité ethnographique» exotisante, altérisante, elle-même cohérente avec une éthique présupposant l’altérité et la vulnérabilité des enquêtés. Si la tendance au «studying up» a engagé de nouvelles problématisations de l’éthique de recherche, celle-ci n’est véritablement repensée que dans des conditions exceptionnelles. Or cette «exceptionnalisation» protéiforme repose sur une représentation «asociologique» du pouvoir, soit par moralisme, soit par stato-centrisme.
Model Customer Satisfaction And Customer Behaviour Intention In Improving The Dimension Of Referral Marketing, Experiental Marketing, Service Marketing
Authors: Kartika Chandra , Rudiatno Rudiatno
Published: August 2020

This research aims to test and analyze customer satisfaction model and customer behaviour intention in meningkatkandimensireferral marketing, experientalMarketing, service marketing in customer user product PT. DenpooMandiri Indonesia Branch Surabayi have been respondents to the study as much as 130 people, consisting of 90 women and 40 men. This analysis uses the analysis path. Calculation of statistical analysis using SPSS aimed at calculating the significant or absence of a study. This research can contribute to the company PT. DenpooMandiri Indonesia in increasing customer satisfaction by combining the dimensions that will be researched and researchers want to help increase the sales level of Denpoo products so that the product can be felt by the customer. Findings of this research with statistical analysis calculations using SPSS Path analysis that aims to calculate the significant or absence of a study. Based on the results of the overall research of data analysis can be noted that empirically tested by Bersama–sama referral marketing variables, experiential marketing, service marketing, customer satisfaction has a significant impact to the customer behaviour intention. Customers will increase when referral marketing variables, experiental marketing, service Marketingcan be tested and can provide benefits to the community and employees of the company.
Work Productivity Through Compensation, Experiences and Welfare Benefits PT Summit Oto Finance Surabaya
Authors: Istanti Enny , Amaliyah Amaliyah , GS Achmad Daeng
Published: August 2020

ABSTRACT Competition in the business world is getting tougher. Companies must be managed dynamically, following the current trends, where the world cannot be separated from technology and the Internet. One of the basic prerequisites for creating competitive advantage is the availability of reliable and competent human resources in accordance with the characteristics of the company. The high level of employee work performance is influenced by several factors including compensation, work experience, and benefits. Compensation, work experience, and welfare benefits are seen as one of the things that can affect the work productivity of employees, because both of these things are now not viewed solely as a means of satisfying material needs but have been one of the basic needs of humans. Hypothesis testing is done based on quantitative tests with relevant statistical test tools. The results of the study state that Compensation, work experience, and welfare benefits have a significant effect on employee work productivity. This is indicated by the probability value of t-count for the variable wages, years of service, and welfare benefits. Compensation has a dominant influence on employee work productivity. This is indicated by the Beta coefficient value for the compensation variable of 0.444 greater than the value of the Beta coefficient variable work experience and welfare benefits. Keywords: Work Productivity, Compensation, Experiences, Welfare Benefits
O desenvolvimento motor e a aquisição de habilidades motoras em autistas
Authors: Vito Rossana de Vasconcelos Pugliese , Santos Darlan
Published: August 2020

O desenvolvimento motor e as habilidades motoras em crianças autistas ainda permanecem pouco compreendidas. Estudos sugerem  fortes relações entre o transtorno do espectro autista (TEA) com déficits do desenvolvimento motor e a aquisição de habilidades motoras, mas apesar disso, ainda hoje, essa questão não é considerada como critério diagnóstico. Fator intrigante entre os pesquisadores da área. A presente pesquisa realizou uma Revisão Integrativa da Literatura (RIL), com o objetivo de  relacionar estudos  sobre o  desenvolvimento motor e a aquisição das habilidades motoras em crianças com TEA quando comparadas com crianças típicas. A pesquisa foi relizada na base de dados do Pub Med, através dos descritores “autismo” e “desenvolvimento motor” e “habilidades motoras”, após a aplicação dos critérios de inclusão e exclusão foram selecionados quinze artigos para análise. Os estudos incluídos apresentam um consenso razoável sobre a existência de atrasos motores em crianças com TEA, contudo em sua quase unanimidade, apontam para a necessidade  de pesquisas mais aprofundadas por motivos diversos, seja pelo baixo número de participantes ou pelas  dificuldades de isolar as caracterísitcas autísticas, em seus diferentes níveis.
Concepções de docentes sobre o processo ensino aprendizagem em cenários de prática da graduação em nutrição
Authors: Melo Michele de Freitas , Souza Filho Luiz Euclides Coelho de , Domingues Robson José de Souza , Normando Valéria Marques Ferreira
Published: August 2020

Objetivo: Analisar as concepções dos docentes na formação do profissional nutricionista a cerca doprocesso ensino aprendizagem, durante o estágio supervisionado em Nutrição Social. Métodos: A pesquisaexploratória com abordagem qualitativa, desenvolvida com vinte e um docentes nutricionistas da Faculdadede Nutrição de uma universidade pública do estado do Pará respondeu a um questionário semiestruturadocom o auxílio do software ALCESTE. Resultados: Cinco classes de segmentos de texto com contextossemânticos específicos foram alcançados. Destacou-se a classe 1 como a mais específica quanto aimportância do estágio como uma atividade de consolidação do conhecimento adquirido no transcorrer daformação acadêmica. Ao articular a universidade aos diversos cenários de prática, verificou-se impactos naformação e qualificação profissional. Percebeu-se que as universidades devem estreitar os vínculos com osserviços de saúde, para melhor capacitação profissional. Novas tendências pedagógicas espelhammetodologias que possibilitem o empoderamento do aluno, colocando-o como protagonista central daconstrução de seu conhecimento e corresponsável pela sua trajetória educacional e o professor, ummediador das experiências relacionadas ao processo de aprendizagem. Conclusão: Planejar e discutirestratégias acadêmicas no processo ensino-aprendizagem são motivadas pelas ações de formaçãocontinuada ao docente.
Perfil dos fisioterapeutas nas unidades de terapia intensiva adulto
Authors: Alves Francisco Antonio Dourado , De Oliveira Brena Costa , Santos Francelly Carvalho dos , Matta Rodrigo Eugenio do Nascimento , Silva Hengrid Graciely Nascimento , Silva Cibelle de Sousa e , Carvalho Ana Flávia Machado de
Published: August 2020

Objetivo: Analisar o perfil dos fisioterapeutas que atuam nas UTIs adulto da cidade de Teresina/PI. Métodos:A amostra foi composta por 53 fisioterapeutas. A coleta de dados ocorreu entre abril e junho de 2018. Foramincluídos profissionais de ambos os gêneros e excluídos aqueles que desistiram da pesquisa, nãocompletaram o questionário e as instituições que não aceitaram participar ou não responderam a solicitaçãode coparticipante em tempo razoável. Aplicou-se um questionário online disponibilizado por e-mail e poraplicativos de mensagens contendo 32 questões. Resultados: Observou-se predominância do gênerofeminino, com média de 31,7 ± 5,59 anos, pós-graduados (92,45%) com prevalência em terapia intensiva,trabalhadores do serviço privado (52,8%) e 62,3% informaram que receberam treinamento ao seremadmitidos no setor. Constatou-se que 28,3% não são exclusivos da UTI e 60,4% consideram-se muitosatisfeitos ou satisfeitos profissionalmente, observando-se maior satisfação no serviço privado. Conclusão:Os fisioterapeutas são qualificados, estão em constante aperfeiçoamento e suas atribuições ainda não estãobem definidas, a depender da equipe multidisciplinar ao qual está inserido. Observou-se uma maiorqualificação em terapia intensiva e grau de satisfação profissional no setor privado e os fisioterapeutas doserviço público parecem possuir maior autonomia e experiência no setor de UTI.
Qualidade de vida em pacientes diabéticos: revisão de literatura
Authors: Ribeiro Luana Martins Araújo , Ribeiro Tatiana Martins Araújo , Gomes Ingrid Cristiane Pereira
Published: August 2020

Objetivo: Avaliar a qualidade de vida em pacientes diabéticos. Métodos: Trata-se de uma revisão integrativa cujo tema foi pesquisado na base de dados do PubMed e Scielo, com descritores “Quality of life AND Diabetes Mellitus” e “Qualidade de vida AND Diabetes Mellitus”, respectivamente, sendo incluídos apenas artigos dos últimos três anos. Resultados: Os artigos desenvolvidos através de questionários evidenciaram que a qualidade de vida em diabéticos é menor que em pacientes não diabéticos, devido, principalmente, à mudança do estilo de vida que a doença gera. Tal fato está relacionado também às complicações presentes na ausência ou inadequação do tratamento, assim como à própria terapia farmacológica, às alterações de estilo de vida que são impostas e à ansiedade presente em grande parte desses pacientes. Assim, tais indivíduos têm que lidar com complicações físicas e mentais que a doença proporciona, causando prejuízo no modo de viver. Considerações Finais: Pacientes diabéticos possuem menor qualidade de vida, tanto no âmbito físico como no emocional, quando comparados com indivíduos que não possuem a doença.