90 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    A Cyclic Proof System for Full Computation Tree Logic

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    Full Computation Tree Logic, commonly denoted CTL*, is the extension of Linear Temporal Logic LTL by path quantification for reasoning about branching time. In contrast to traditional Computation Tree Logic CTL, the path quantifiers are not bound to specific linear modalities, resulting in a more expressive language. We present a sound and complete hypersequent calculus for CTL*. The proof system is cyclic in the sense that proofs are finite derivation trees with back-edges. A syntactic success condition on non-axiomatic leaves guarantees soundness. Completeness is established by relating cyclic proofs to a natural ill-founded sequent calculus for the logic

    Wissensintegration von generischem und fallbasiertem Wissen, uniforme Repräsentation, Verwendung relationaler Datenbanksysteme sowie Problemlösen mit Concept Based und Case Based Reasoning sowie Bayesschen Netzen in medizinischen wissensbasierten Systemen

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    Ein wissensbasiertes System soll den Mediziner im Rahmen der Diagnosestellung unterstützen, indem relevante Informationen bereitgestellt werden. Aus komplexen Symptomkonstellationen soll eine zuverlässige Diagnose und damit verbundene medizinische Maßnahmen abgeleitet werden. Grundlage dafür bildet das im System adäquat repräsentierte Wissen, das effizient verarbeitet wird. Dieses Wissen ist in der medizinischen Domäne sehr heterogen und häufig nicht gut strukturiert. In der Arbeit wird eine Methodik entwickelt, die die begriffliche Erfassung und Strukturierung der Anwendungsdomäne über Begriffe, Begriffshierarchien, multiaxiale Komposition von Begriffen sowie Konzeptdeklarationen ermöglicht. Komplexe Begriffe können so vollständig, eindeutig und praxisrelevant abgebildet werden. Darüber hinaus werden mit der zugrunde liegenden Repräsentation Dialogsysteme, fallbasierte und generische Problemlösungsmethoden sowie ihr Zusammenspiel mit relationalen Datenbanken in einem System vorgestellt. Dies ist vor allem im medizinischen Diskursbereich von Bedeutung, da zur Problemlösung generisches Wissen (Lehrbuchwissen) und Erfahrungswissen (behandelte Fälle) notwendig ist. Die Wissensbestände können auf relationalen Datenbanken uniform gespeichert werden. Um das vorliegende Wissen effizient verarbeiten zu können, wird eine Methode zur semantischen Indizierung vorgestellt und deren Anwendung im Bereich der Wissensrepräsentation beschrieben. Ausgangspunkt der semantischen Indizierung ist das durch Konzepthierarchien repräsentierte Wissen. Ziel ist es, den Knoten (Konzepten) Schlüssel zuzuordnen, die hierarchisch geordnet und syntaktisch sowie semantisch korrekt sind. Mit dem Indizierungsalgorithmus werden die Schlüssel so berechnet, dass die Konzepte mit den spezifischeren Konzepten unifizierbar sind und nur semantisch korrekte Konzepte zur Wissensbasis hinzugefügt werden dürfen. Die Korrektheit und Vollständigkeit des Indizierungsalgorithmus wird bewiesen. Zur Wissensverarbeitung wird ein integrativer Ansatz der Problemlösungsmethoden des Concept Based und Case Based Reasoning vorgestellt. Concept Based Reasoning kann für die Diagnose-, Therapie- und Medikationsempfehlung und -evaluierung über generisches Wissen verwendet werden. Mit Hilfe von Case Based Reasoning kann Erfahrungswissen von Patientenfällen verarbeitet werden. Weiterhin werden zwei neue Ähnlichkeitsmaße (Kompromissmengen für Ähnlichkeitsmaße und multiaxiale Ähnlichkeit) für das Retrieval ähnlicher Patientenfälle entwickelt, die den semantischen Kontext adäquat berücksichtigen. Einem ausschließlichen deterministischen konzeptbasiertem Schließen sind im medizinischen Diskursbereich Grenzen gesetzt. Für die diagnostische Inferenz unter Unsicherheit, Unschärfe und Unvollständigkeit werden Bayessche Netze untersucht. Es können so die gültigen allgemeinen Konzepte nach deren Wahrscheinlichkeit ausgegeben werden. Dazu werden verschiedene Inferenzmechanismen vorgestellt und anschließend im Rahmen der Entwicklung eines Prototypen evaluiert. Mit Hilfe von Tests wird die Klassifizierung von Diagnosen durch das Netz bewertet.:1 Einleitung 2 Medizinische wissensbasierte Systeme 3 Medizinischer Behandlungsablauf und erweiterter wissensbasierter Agent 4 Methoden zur Wissensrepräsentation 5 Uniforme Repräsentation mit Begriffshierachien, Konzepten, generischem und fallbasierten Schließen 6 Semantische Indizierung 7 Medizinisches System als Beispielanwendung 8 Ähnlichkeitsmaße, Kompromissmengen, multiaxiale Ähnlichkeit 9 Inferenzen mittels Bayesscher Netze 10 Zusammenfassung und Ausblick A Ausgewählte medizinische wissensbasierte Systeme zur Entscheidungsunterstützung aus der Literatur B Realisierung mit Softwarewerkzeugen C Causal statistic modeling and calculation of distribution functions of classification featuresA knowledge-based system is designed to support the medical professionals in the diagnostic process by providing relevant information. A reliable diagnosis and associated medical measures are to be derived from complex symptom constellations. It is based on the knowledge adequately represented in the system, which is processed efficiently. This knowledge is very heterogeneous in the medical domain and often not well structured. In this work, a methodology is developed that enables the conceptual capture and structuring of the application domain via concepts, conecpt hierarchies, multiaxial composition of concepts as well as concept declarations. Complex concepts can thus be mapped completely, clearly and with practical relevance. Furthermore, the underlying representation introduces dialogue systems, \acrlong{abk:CBR} and generic problem solving methods as well as their interaction with relational databases in one system. This is particularly important in the field of medical discourse, since generic knowledge (textbook knowledge) and experiential knowledge (treated cases) are necessary for problem solving. The knowledge can be stored uniformly on relational databases. In order to be able to process the available knowledge efficiently, a method for semantic indexing is presented and its application in the field of knowledge representation is described. The starting point of semantic indexing is the knowledge represented by concept hierarchies. The goal is to assign keys to the nodes (concepts) that are hierarchically ordered and syntactically and semantically correct. With the indexing algorithm, the keys are calculated in such a way that the concepts are unifiable with the more specific concepts and only semantically correct concepts may be added to the knowledge base. The correctness and completeness of the indexing algorithm is proven. An integrative approach of the problem-solving methods of Concept Based and \acrlong{abk:CBR} is presented for knowledge processing. Concept Based Reasoning can be used for diagnosis, therapy and medication recommendation and evaluation via generic knowledge. Case Based Reasoning can be used to process experiential knowledge of patient cases. Furthermore, two new similarity measures (compromise sets for similarity measures and multiaxial similarity) are developed for the retrieval of similar patient cases that adequately consider the semantic context. There are limits to an exclusively deterministic Concept Based Reasoning in the medical domain. For diagnostic inference under uncertainty, vagueness and incompleteness Bayesian networks are investigated. The method is based on an adequate uniform representation of the necessary knowledge. Thus, the valid general concepts can be issued according to their probability. To this end, various inference mechanisms are introduced and subsequently evaluated within the context of a developed prototype. Tests are employed to assess the classification of diagnoses by the network.:1 Einleitung 2 Medizinische wissensbasierte Systeme 3 Medizinischer Behandlungsablauf und erweiterter wissensbasierter Agent 4 Methoden zur Wissensrepräsentation 5 Uniforme Repräsentation mit Begriffshierachien, Konzepten, generischem und fallbasierten Schließen 6 Semantische Indizierung 7 Medizinisches System als Beispielanwendung 8 Ähnlichkeitsmaße, Kompromissmengen, multiaxiale Ähnlichkeit 9 Inferenzen mittels Bayesscher Netze 10 Zusammenfassung und Ausblick A Ausgewählte medizinische wissensbasierte Systeme zur Entscheidungsunterstützung aus der Literatur B Realisierung mit Softwarewerkzeugen C Causal statistic modeling and calculation of distribution functions of classification feature

    Assuming Data Integrity and Empirical Evidence to The Contrary

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    Background: Not all respondents to surveys apply their minds or understand the posed questions, and as such provide answers which lack coherence, and this threatens the integrity of the research. Casual inspection and limited research of the 10-item Big Five Inventory (BFI-10), included in the dataset of the World Values Survey (WVS), suggested that random responses may be common. Objective: To specify the percentage of cases in the BRI-10 which include incoherent or contradictory responses and to test the extent to which the removal of these cases will improve the quality of the dataset. Method: The WVS data on the BFI-10, measuring the Big Five Personality (B5P), in South Africa (N=3 531), was used. Incoherent or contradictory responses were removed. Then the cases from the cleaned-up dataset were analysed for their theoretical validity. Results: Only 1 612 (45.7%) cases were identified as not including incoherent or contradictory responses. The cleaned-up data did not mirror the B5P- structure, as was envisaged. The test for common method bias was negative. Conclusion: In most cases the responses were incoherent. Cleaning up the data did not improve the psychometric properties of the BFI-10. This raises concerns about the quality of the WVS data, the BFI-10, and the universality of B5P-theory. Given these results, it would be unwise to use the BFI-10 in South Africa. Researchers are alerted to do a proper assessment of the psychometric properties of instruments before they use it, particularly in a cross-cultural setting

    Tools and Algorithms for the Construction and Analysis of Systems

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    This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

    Automated Reasoning

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    This volume, LNAI 13385, constitutes the refereed proceedings of the 11th International Joint Conference on Automated Reasoning, IJCAR 2022, held in Haifa, Israel, in August 2022. The 32 full research papers and 9 short papers presented together with two invited talks were carefully reviewed and selected from 85 submissions. The papers focus on the following topics: Satisfiability, SMT Solving,Arithmetic; Calculi and Orderings; Knowledge Representation and Jutsification; Choices, Invariance, Substitutions and Formalization; Modal Logics; Proofs System and Proofs Search; Evolution, Termination and Decision Prolems. This is an open access book

    Leading Towards Voice and Innovation: The Role of Psychological Contract

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    Background: Empirical evidence generally suggests that psychological contract breach (PCB) leads to negative outcomes. However, some literature argues that, occasionally, PCB leads to positive outcomes. Aim: To empirically determine when these positive outcomes occur, focusing on the role of psychological contract (PC) and leadership style (LS), and outcomes such as employ voice (EV) and innovative work behaviour (IWB). Method: A cross-sectional survey design was adopted, using reputable questionnaires on PC, PCB, EV, IWB, and leadership styles. Correlation analyses were used to test direct links within the model, while regression analyses were used to test for the moderation effects. Results: Data with acceptable psychometric properties were collected from 11 organisations (N=620). The results revealed that PCB does not lead to substantial changes in IWB. PCB correlated positively with prohibitive EV, but did not influence promotive EV, which was a significant driver of IWB. Leadership styles were weak predictors of EV and IWB, and LS only partially moderated the PCB-EV relationship. Conclusion: PCB did not lead to positive outcomes. Neither did LS influencing the relationships between PCB and EV or IWB. Further, LS only partially influenced the relationships between variables, and not in a manner which positively influence IWB

    Automated Deduction – CADE 28

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    This open access book constitutes the proceeding of the 28th International Conference on Automated Deduction, CADE 28, held virtually in July 2021. The 29 full papers and 7 system descriptions presented together with 2 invited papers were carefully reviewed and selected from 76 submissions. CADE is the major forum for the presentation of research in all aspects of automated deduction, including foundations, applications, implementations, and practical experience. The papers are organized in the following topics: Logical foundations; theory and principles; implementation and application; ATP and AI; and system descriptions
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