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In this paper I aim to explain the approach to the nature and aims of logic in the work of Isaac Watts (1674–1748): Logick: Or, the Right Use of Reason in the Enquiry after Truth (1725). I discuss Watts's notion that the guidance and regulation of the acts and powers of the mind is the proper province of logic, as well as the pedagogical ambitions of his logical works. I focus on the cure of the imagination, which is one member of the more general cure of the intellectual powers that logic under this description seeks. I also provide the historical contexts that are apt to illuminate these features of an early Enlightenment logic: I situate Watts within the early modern development of an approach to logic as a therapeutic art of thinking; and I suggest that the pedagogical nature of Watts's work is indebted to a specific tradition of Protestant practical divinity that fed into the pedagogical practices of early eighteenth-century English religious dissent, which Watts embraced. [ABSTRACT FROM AUTHOR]

IoT devices produce a vast amount of data ranging from personal to sensitive information. Usually, these devices remain connected to the internet so protecting the information produced by them is crucial. Since most of the IoT devices are resource-constrained, they must be supported with lightweight encryption standards to protect information. Recent research has used the concept of context awareness to select the most suitable data encryption standard based on the device resources along with the required information confidentiality level. However, to effectively use the context information, it is required to be organized explicitly while considering the dynamic nature of IoT systems. In this regard, ontology-based systems effectively reduce the volume of manual work while recommending solutions. Currently, these systems cannot work with precision due to multiple uncertain factors of IoT sensory data. To overcome this challenge, this research proposes a fuzzy ontology-based context-aware system to protect IoT device information with the help of an encryption algorithm that considers device capabilities and user priorities regarding the data confidentiality. In order to automate the recommendation process, Semantic Web Rule Language (SWRL) rules and fuzzy logic are used, whereas, Description Logic and RDF Query Language is used to evaluate the results. The evaluation results confirm that the proposed method can produce results according to human perception by significantly increasing the accuracy of prediction. [ABSTRACT FROM AUTHOR]

This article examines the influence of Alfred Tennyson's poem "The Lady of Shalott" on Herman Melville's poem "The Portent." The author argues that Melville's poem shows clear signs of being influenced by Tennyson's work, particularly in terms of its syntax and metaphorical logic. The article provides evidence from Melville's personal library and compares the two poems to support this claim. Additionally, the article discusses Melville's interest in English poetry during the Civil War and how he used Tennyson's poetry to shape his own aesthetic beliefs. It also explores the themes of history, poetry, and the Civil War in Melville's work. [Extracted from the article]

The internet of things (IoT) has seen rapid expansion, but this growth brings significant privacy challenges due to the large amounts of data generated by myriad IoT devices. To address these challenges, this study introduces Smart Anonymity, a method that determines the optimal data anonymization algorithm for a dataset by assessing its unique features. The solution leverages OWL ontologies grounded in description logic (DL), which facilitates inconsistency checks and the discovery of new facts for data validation. Additionally, machine learning (ML) is incorporated to improve the accuracy of these classifications. ML is also instrumental in recommending suitable anonymization algorithms, with the random forest algorithm being employed explicitly for this purpose. The findings from this research indicate that Smart Anonymity effectively improves user privacy. [ABSTRACT FROM AUTHOR]

Non-Tarskian interpretations of many-valued logics have been widely explored in the logic literature. The development of non-tarskian conceptions of logical consequence set the theoretical foundations for rediscovering well-known (Tarskian) many-valued logics. One may find in distinct authors many novel interpretations of many-valued systems. They are produced through a type of procedure which consists in altering the semantic structure of Tarskian many-valued logics in order to output a non-Tarskian interpretation of these logics. Through this type of transformation the paper explores a uniform way of transforming finitely many-valued Tarskian logics into their non-Tarskian interpretation. Some general properties of carrying out this type of procedure are studied, namely the dualities between these logics and the conditions under which negation-explosive and negation-complete Tarskian logics become non-explosive. [ABSTRACT FROM AUTHOR]

Background: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. The heterogeneity of cancer vaccine data significantly impedes effective integration and analysis. While CanVaxKB serves as a pioneering database for over 670 manually annotated cancer vaccines, it is important to distinguish that a database, on its own, does not offer the structured relationships and standardized definitions found in an ontology. Recognizing this, we expanded the Vaccine Ontology (VO) to include those cancer vaccines present in CanVaxKB that were not initially covered, enhancing VO's capacity to systematically define and interrelate cancer vaccines. Results: An ontology design pattern (ODP) was first developed and applied to semantically represent various cancer vaccines, capturing their associated entities and relations. By applying the ODP, we generated a cancer vaccine template in a tabular format and converted it into the RDF/OWL format for generation of cancer vaccine terms in the VO. '12MP vaccine' was used as an example of cancer vaccines to demonstrate the application of the ODP. VO also reuses reference ontology terms to represent entities such as cancer diseases and vaccine hosts. Description Logic (DL) and SPARQL query scripts were developed and used to query for cancer vaccines based on different vaccine's features and to demonstrate the versatility of the VO representation. Additionally, ontological modeling was applied to illustrate cancer vaccine related concepts and studies for in-depth cancer vaccine analysis. A cancer vaccine-specific VO view, referred to as "CVO," was generated, and it contains 928 classes including 704 cancer vaccines. The CVO OWL file is publicly available on: http://purl.obolibrary.org/obo/vo/cvo.owl, for sharing and applications. Conclusion: To facilitate the standardization, integration, and analysis of cancer vaccine data, we expanded the Vaccine Ontology (VO) to systematically model and represent cancer vaccines. We also developed a pipeline to automate the inclusion of cancer vaccines and associated terms in the VO. This not only enriches the data's standardization and integration, but also leverages ontological modeling to deepen the analysis of cancer vaccine information, maximizing benefits for researchers and clinicians. Availability: The VO-cancer GitHub website is: https://github.com/vaccineontology/VO/tree/master/CVO. [ABSTRACT FROM AUTHOR]

This paper considers a specification rewriting meachanism for a specific fragment of Linear Temporal Logic for Finite traces, DECLAREd, working through an equational logic and rewriting mechanism under customary practitioner assumptions from the Business Process Management literature. By rewriting the specification into an equivalent formula which might be easier to compute, we aim to streamline current state-of-the-art temporal artificial intelligence algorithms working on temporal logic. As this specification rewriting mechanism is ultimately also able to determine with the provided specification is a tautology (always true formula) or a formula containing a temporal contradiction, by detecting the necessity of a specific activity label to be both present and absent within a log, this implies that the proved mechanism is ultimately a SAT-solver for DECLAREd. We prove for the first time, to the best of our knowledge, that this fragment is a polytime fragment of LTLf, while all the previously-investigated fragments or extensions of such a language were in polyspace. We test these considerations over formal synthesis (Lydia), SAT-Solvers (AALTAF) and formal verification (KnoBAB) algorithms, where formal verification can be also run on top of a relational database and can be therefore expressed in terms of relational query answering. We show that all these benefit from the aforementioned assumptions, as running their tasks over a rewritten equivalent specification will improve their running times, thus motivating the pressing need of this approach for practical temporal artificial intelligence scenarios. We validate such claims by testing such algorithms over a Cybersecurity dataset. [ABSTRACT FROM AUTHOR]

The twentieth-century logical mainstream, derived from works by Łukasiewicz and Scholz, pictures the history of logic for the most part as the prehistory of Boolean–Fregean mathematical logic. Particularly, with respect to classical propositional calculus, the Stoic logic has been pictured as an early stage of it and Aristotle's or the Peripatetics' logic as a theory that assumes it. Although it was not emphasised, it follows that the ancient logics contain the principle of explosion. In the endmost quarter of the twentieth century, a competitive view began to spread to the effect that the ancient systems of logic were paraconsistent or relevantistic. In the twenty-first century, the latter view prevails and has every chance of becoming a new orthodoxy. It is claimed that although in Łukasiewicz's argument for the classicality of ancient logics, there are gaps, it may be demonstrated that the ancient logics contain the principle of explosion. [ABSTRACT FROM AUTHOR]

The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized or rejected entirely. Because uncertainty is omnipresent in the real world, knowledge engineers are often faced with the dilemma of performing prohibitively labor-intensive research or running the risk of rejecting correct information and accepting incorrect information. It would be preferable if ontologies could explicitly model real-world uncertainty and incorporate it into reasoning. We present an ontology framework which is based on a seamless synthesis of description logic and probabilistic semantics. This synthesis is powered by a link between ontology assertions and random variables that allows for automated construction of a probability distribution suitable for inferencing. Furthermore, our approach defines how to represent stochastic, uncertain, or incomplete subject matter. Additionally, this paper describes how to fuse multiple conflicting ontologies into a single knowledge base that can be reasoned with using the methods of both description logic and probabilistic inferencing. This is accomplished by using probabilistic semantics to resolve conflicts between assertions, eliminating the need to delete potentially valid knowledge and perform consistency checks. In our framework, emergent inferences can be made from a fused ontology that were not present in any of the individual ontologies, producing novel insights in a given domain. [ABSTRACT FROM AUTHOR]

Inductive Logic Programming (ILP) is a research field at the intersection between machine learning and logic programming, focusing on developing a formal framework for inductively learning relational descriptions in the form of logic programs from examples and background knowledge. As an emerging method of ILP, Meta-Interpretive Learning (MIL) leverages the specialization of a set of higher-order metarules to learn logic programs. In MIL, the input includes a set of examples, background knowledge, and a set of metarules, while the output is a logic program. MIL executes a depth-first traversal search, where its program search space expands polynomially with the number of predicates in the provided background knowledge and exponentially with the number of clauses in the program, sometimes even leading to search collapse. To address this challenge, this study introduces a strategy that employs the concept of reuse, specifically through the integration of auxiliary predicates, to reduce the number of clauses in programs and improve the learning efficiency. This approach focuses on the proactive identification and reuse of common program patterns. To operationalize this strategy, we introduce MILER, a novel method integrating a predicate generator, program learner, and program evaluator. MILER leverages frequent subgraph mining techniques to detect common patterns from a limited dataset of training samples, subsequently embedding these patterns as auxiliary predicates into the background knowledge. In our experiments involving two Visual Question Answering (VQA) tasks and one program synthesis task, we assessed MILER's approach to utilizing reusable program patterns as auxiliary predicates. The results indicate that, by incorporating these patterns, MILER identifies reusable program patterns, reduces program clauses, and directly decreases the likelihood of timeouts compared to traditional MIL. This leads to improved learning success rates by optimizing computational efforts. [ABSTRACT FROM AUTHOR]

The inclusion of collective intelligence through a semantic focused affective computing can incorporate intelligence to web search and ensure its compliance with the Web 3.0. In this article, a query growth model with inclusive and exclusive ontology semantics has been proposed for diversification of query recommendation in semantic search. The ontology semantics include query augmented ontology generation, agent‐driven attractor‐distractor generation to yield a merged ontology, and endowment of merged ontology by using hybridization of a series of knowledge bases. The strategy further includes the formulation of a semantic network and entity leveraging based on description logics (DLs) to improve the quality of query recommendation. A novel hierarchical entropy cognitive similarity covariance model has been proposed for yielding the most appropriate recommendable query words. The strategy also encompasses the user‐click information for capturing the current user intents to improve the quality queries recommended in semantic search, and thereby incorporate personalization. Experimentations are conducted for the CHiC dataset and the Spring 2006 Query Log dataset and an average accuracy of 96.27% and 92.01%, respectively, with a very low false discovery rate of 0.06 and 0.1 for the respective datasets. [ABSTRACT FROM AUTHOR]

The article overviews the means for describing and formally analyzing natural-language text knowledge under uncertainty. We consider a family of classic attribute languages and logics based on them, their properties, problems, and solution tools. We also overview propositional n-valued logics and fuzzy logics, their syntax and semantics. Based on the considered logical constructions, we propose syntax and set-theoretic interpretation of n-valued description logic ALCQn that provides the means for describing concept intersection, union, complement, value restrictions, and qualitative and quantitative constraints. We consider the means for solving key problems of reasoning over such logics: executability, augmentation, equivalence, and disjunctivity. As an algorithm for calculating the executability degree, we consider an extension of the tableau algorithm often used for first-order logic with solving simple numerical constraints. We prove that the algorithm is terminal, complete, and non-contradictory. We also provide several applications for the formal representation in natural language processing, including extending results of machine learning models, combining knowledge from multiple sources and formally describing uncertain facts. [ABSTRACT FROM AUTHOR]

Weighted knowledge bases for description logics with typicality provide a logical interpretation of MultiLayer Perceptrons, based on a "concept-wise" multi-preferential semantics. On the one hand, in the finitely many-valued case, Answer Set Programming (ASP) has been shown to be suitable for addressing defeasible reasoning from weighted knowledge bases for the boolean fragment of ALC. On the other hand, the semantics of weighted knowledge bases with typicality, in their different variants, have suggested some new gradual argumentation semantics, as well as an approach for defeasible reasoning over a weighted argumentation graph, building on the gradual semantics and, specifically on the φ-coherent semantics. In this paper, we explore the relationships between weighted knowledge bases and weighted argumentation graphs, to develop proof methods for defeasible reasoning over an argumentation graph under the φ-coherent semantics, in the finitely-valued case. We establish a mapping from a weighted argumentation graph to a weighted knowledge base as well as a lower bound on the complexity of the problem of verifying graded implications over an argumentation graph in the φ-coherent semantics. We also consider a mapping from weighted knowledge bases to weighted argumentation graphs, and provide an ASP implementation and some experimental results. [ABSTRACT FROM AUTHOR]

The paper addresses academic adultcentrism from the perspective of the pre-service instruction and practice of philosophy teachers, based on the experience we have gained while leading a Didactic of Philosophy seminar for a Philosophy and Letters academic program where students are engaged in the designing, implementation and evaluation of academic material and class performance for K-12 schools. After giving a brief presentation of the context in which philosophy teaching takes place, and a description of the logic and horizon that set the basis of our seminar, we define and discuss four particular ways in which adultcentrism permeates the preparation and performance of philosophy classes for classrooms with students ranging from 8 to 15 years old: cognitive, epistemic, pedagogical and disciplinary adultcentrism. As well as some of the ways in which, as part of the seminar, the students and the instructor have devised to address and overcome the adultcentrism problems. At the end of the discussion, an auto-critical note is included in order to show the limits of our own practices and base ground, as well as a way to define new necessary approaches and perspectives required to address both the problems we found to be at the bottom of current teaching practices. As well as n our own expectations, methods and ways to deal with those issues with our pre-service young colleagues. [ABSTRACT FROM AUTHOR]

At a commercial gallery in London in 2019 I'm listening to audio recordings of Rose English's 1980s performance Plato's Chair, while a video of the show is projected on the wall ahead. The effect is of the performer describing what she is doing as she does it, the description displaced from one medium or occasion to another. Although, what she appears to be doing – for all her constant motion – is enacting a kind of hiatus while she ponders her next move, alone with herself, removed from her audience, thinking it all through and using words to do so. Description attempts to move things along. At play here, a certain – or uncertain – mimetics. Pleasures, for sure, for those who were there, or are placed there now. And a theatrical know-how – comedy, melodrama, opera-dance, and dressage all get a try-out – which is rooted in repertoire, but which ponders how to proceed. She is at once, she says, a comedian and philosopher. Which is to say also, ironist. In her book-length study of our ordinary acts of self-description, The Words of Selves (2000), Denise Riley locates in irony a 'political astringency' that corrodes 'excessively vaunted' categories, such as the human. But she finds irony also arising spontaneously within injury, compelled into intensities of self-contemplation. The injury, for instance, of one – as human as they come – who describes to me, on the phone, a tree outside her window. 'I don't know what to call it'. Description goes around. [ABSTRACT FROM AUTHOR]

Fuzzy spatiotemporal reasoning is extensively used in various application fields such as Geographic Information Systems, Geospatial Artificial Intelligence, and Remote Sensing Systems. However, providing a tractable reasoning mechanism for fuzzy spatiotemporal knowledge is a challenging research problem. Description logics (DLs) are a type of logic-based tractable knowledge representation formalism that allow for describing knowledge structure of an application domain, but they are limited in their ability to express fuzzy spatiotemporal knowledge. To address this limitation, we propose a tractable temporal DL named f- ALC (S) -LTL, which expands linear temporal logic (LTL) by utilizing fuzzy spatial DL f- ALC (S) . In this article, we first define the syntax and formal-semantic model of our logic and investigate a tableau rule-based reasoning procedure to verify satisfiability. We further show the correctness and computational complexity of the reasoning procedure and demonstrate a running example of its application. Finally, we implement a prototype reasoning tool that can determine the satisfiability problem. Our case studies show that our logic f- ALC (S) -LTL is feasible and the prototype reasoning tool actually works. The logic f- ALC (S) -LTL enables tractable reasoning about the dynamic evolution of fuzzy RCC relations over time. [ABSTRACT FROM AUTHOR]

This study aimed to identify research on different Qur'anic ontologies by providing a clear picture of the existing reality, activities, and progress in developing Qur'anic ontologies. Therefore, the present scoping review attempts to overview the breadth and scope of the research conducted around Qur'anic ontologies during 2017-2022. The methodological framework of Arksey and O'Malley (2005), who suggested five steps for conducting domain review, was used. The search strategy was conducted in 6 databases, including Emerald, Science Direct, IEEE Xplore Digital Library, Google Scholar, Web of Science, and Scopus, in April 2022. As a result, 811 studies were identified. The EndNote ver. 9 reference management tool was used to organize the studies. Three hundred and seventeen duplicate articles and 362 unrelated articles were excluded. Maximum research has considered specific Qur'anic themes in creating Qur'anic ontologies, even though some studies have tried to construct an ontology of the entire Qur'an. English and Arabic were the most common languages used in developing existing Qur'anic ontologies. In addition, most of the research constructed monolingual thematic ontology, and limited studies have applied multilingual translation of the Qur'an to their ontology. Developing tools, programming languages, and methods used in most studies are Protégé, W3C Web Ontology Language (OWL), and Resource Description Framework (RDF), and the concept classification is the up-down approach. SPARQL Protocol and RDF Query Language (SPARQL) have been the proper evaluation tools and methods used in previous research. In contrast, Description Logic (DL) queries and human experts have only been used in a few studies. This study provided a practical indication of the shortcomings, problems, and suggestions in constructing and developing existing Qur'anic ontologies leading to comprehensive Qur'an ontology to disseminating correct knowledge of the Qur'an with the help of semantic technologies. In this way, creating a comprehensive Qur'anic ontology in Persian is suggested to overcome the limitations raised in previous research. [ABSTRACT FROM AUTHOR]

Background: SNOMED CT is a large terminology system designed to represent all aspects of healthcare. Its current form and content result from decades of bottom-up evolution. Due to SNOMED CT's formal descriptions, it can be considered an ontology. The Basic Formal Ontology (BFO) is a foundational ontology that proposes a small set of disjoint, hierarchically ordered classes, supported by relations and axioms. In contrast, as a typical top-down endeavor, BFO was designed as a foundational framework for domain ontologies in the natural sciences and related disciplines. Whereas it is mostly assumed that domain ontologies should be created as extensions of foundational ontologies, a post-hoc harmonization of consolidated domain ontologies in use, such as SNOMED CT, is known to be challenging. Methods: We explored the feasibility of harmonizing SNOMED CT with BFO, with a focus on the SNOMED CT Clinical Finding hierarchy. With more than 100,000 classes, it accounts for about one third of SNOMED CT's content. In particular, we represented typical SNOMED CT finding/disorder concepts using description logics under BFO. Three representational patterns were created and the logical entailments analyzed. Results: Under a first scrutiny, the clinical intuition that diseases, disorders, signs and symptoms form a homogeneous ontological upper-level class appeared incompatible with BFO's upper-level distinction into continuants and occurrents. The Clinical finding class seemed to be an umbrella for all kinds of entities of clinical interest, such as material entities, processes, states, dispositions, and qualities. This suggests the conclusion that Clinical finding would not be a suitable upper-level class from an BFO perspective. On closer inspection of the taxonomic links within this hierarchy and the implicit meaning derived thereof, it became clear that Clinical finding classes do not characterize the entity (e.g. a fracture, allergy, tumor, pain, hemorrhage, seizure, fever) in a literal sense but rather the condition of a patient having that fracture, allergy, pain etc. This gives sense to the current characteristic of the Clinical Finding hierarchy, in which complex classes are modeled as subclasses of their constituents. Most of these taxonomic links are inferred, as the consequence of the 'role group' design pattern, which is ubiquitous in SNOMED CT and has often been subject of controversy regarding its semantics. Conclusion: Our analyses resulted in the proposal of (i) equating SNOMED CT's 'role group' property with the reflexive and transitive BFO relation 'has occurrent part'; and (ii) reinterpreting Clinical Findings as Clinical Occurrents, i.e. temporally extended entities in an organism, having one or more occurrents as temporal parts that occur in continuants. This re-interpretation was corroborated by a manual analysis of classes under Clinical Finding, as well as the identification of similar modeling patterns in other ontologies. As a result, SNOMED CT does not require any content redesign to establish compatibility with BFO, apart from this re-interpretation, and a suggested re-labeling. Regarding the feasibility of harmonizing terminologies with principled foundational ontologies post-hoc, our results provide support to the assumption that this does not necessarily require major redesign efforts, but rather a careful analysis of the implicit assumptions of terminology curators and users. [ABSTRACT FROM AUTHOR]

Many ΙΤ applications rely on the operationalisation of terminologies, such as multilingual semantic search engines. By operationalisation of terminology, we mean a computational representation of the conceptual system as an ontology of knowledge engineering. This conceptual approach of terminology is close to the ISO principles on terminology as defined by the core standards ISO 1087:2019 and ISO 704:2022. The question then is to study what contribution these standards can make to the construction of ontologies for terminological purposes. In other words, are the terminology principles of ISO soluble in the ontology of knowledge engineering? In this article, we will attempt to provide some answers on the feasibility of implementing ISO principles in description logic, the dominant model in knowledge representation. We will illustrate our proposition with Protégé, the most popular environment for building ontologies. Facing the issues raised by this approach, the article will end with the ontoterminology building environment Tedi directly linked to the ISO principles. [ABSTRACT FROM AUTHOR]

Objectives: Buffer analysis is a common tool of spatial analysis, which deals with the problem of proximity. Due to numerous and complex operations in the algorithm, the computational efficiency needs to be optimized. Methods: To process large scale point features, a graph-based representation model is pro⁃ posed, which establishes the spatial computational domain for data and analysis, and develops a well-balanced task-partitioning method by partitioning the graph. First, the proposed model defines processing functions of point features and their spatial relationships from the perspectives of graph nodes and graph edges, and provides a logic description for buffer zone generation around point features. Second, the computational weights of graph nodes and graph edges are obtained by fitting the time complexity of the above processing functions. Finally, graph partitioning is adopted to divide the buffer task, which contributes to multiple parallel tasks matching with the computational resources. Results: The experimental results show that graphbased buffer analysis can achieve better load balance and overall efficiency, which is superior to the main⁃ stream partitioning methods, regular-grid and quadtree. Conclusions: The proposed method can provide a reference for optimization of spatial analysis methods when processing large scale vector data. [ABSTRACT FROM AUTHOR]

In Pietroski (2018) a simple representation language called SMPL is introduced, construed as a hypothesis about core conceptual structure. The present work is a study of this system from a logical perspective. In addition to establishing a completeness result and a complexity characterization for reasoning in the system, we also pinpoint its expressive limits, in particular showing that the fourth corner in the square of opposition ("Some_not") eludes expression. We then study a seemingly small extension, called SMPL+, which allows for a minimal predicate-binding operator. Perhaps surprisingly, the resulting system is shown to encode precisely the concepts expressible in first-order logic. However, unlike the latter class, the class of SMPL+ expressions admits a simple procedural (context-free) characterization. Our contribution brings together research strands in logic—including natural logic, modal logic, description logic, and hybrid logic—with recent advances in semantics and philosophy of language. [ABSTRACT FROM AUTHOR]

In this paper I argue that in Map to the Door of No Return, Dionne Brand is an ethnographer of Black interiority and gives us a poetics of Black psychoanalysis rejoining our slaveness to a less alienated geo-environmental social. I argue that we might read Brand alongside Saidiya Hartman and Paule Marshall as writers coming to terms with Black being as one consecrated in disruption and producing a "tribe of the Middle Passage." I further suggest that they do so without a demand for a common unity beyond the logic of survival, and without a demand for an official or proper name. [ABSTRACT FROM AUTHOR]

River flood forecasting and assessment are crucial for reducing flood risks, as they offer early alerts and allow for proactive actions to safeguard individuals from possible flood-related damage. Effective modeling in this field often multiple interconnected aspects of the hydrologic cycle, such as precipitation, infiltration, runoff, and evaporation, requiring collaboration among hydrology experts. Such collaboration enables experts to handle and manage their specialized processes more effectively, thereby enhancing the efficiency of the development of integrated flood forecasting models. Tight integration and loose integration are two common strategies for integrating different hydrologic cycle process models in river flood forecasting. However, most integration strategies rely on centralized models, necessitating experts to configure models and data on local computers. Currently, there is a deficiency in the capacity for effective collaboration in the integrated modeling of river flood forecasts. This issue arises from multiple obstacles: the complexity of understanding heterogeneous data and hydrologic cycle process models; the difficulty of integrating models with diverse runtime environments; and the challenge of synchronizing forecasting model changes among experts in real time. Therefore, we propose a web-based collaborative integrated modeling method, designed to support both tightly and loosely integrated modes, to enhance collaborative river flood forecasting and assessment. This method includes three core modules: (1) data and model description for providing a structured description of the execution logic of forecasting models and the internal structure of forecast data for expert understanding; (2) model access and integration for access and integration of data and multi-source heterogeneous models of hydrologic cycle processes; and (3) modeling scenario configuration for collaborative development of forecasting models and the execution of simulation tasks. Finally, we illustrate the application of the proposed method by utilizing the GEFS v12 (Global Ensemble Forecast System) rainfall ensemble forecasting dataset with the CREST (Coupled Routing and Excess STorage) hydrologic model. The results show enhanced efficiency in the collaborative development of river flood forecasts by hydrology experts, particularly in model accessibility, data processing, simulation, and evaluation, thereby potentially aiding decision-making. • A collaborative integrated modeling method is proposed for river flood forecasting. • The method can help integrating diverse water cycle models and data. • The method facilitates the collaboration of experts in model development. [ABSTRACT FROM AUTHOR]

The ontology knowledge base (KB) can be divided into two parts: TBox and ABox, where the former models schema-level knowledge within the domain, and the latter is a set of statements of assertions or facts about instances. ABox reasoning is a process of discovering implicit knowledge in ABox based on the existing KB, which is of great value in KB applications. ABox reasoning is influenced by both the complexity of TBox and scale of ABox. The traditional logic-based ontology reasoning methods are usually designed to be provably sound and complete but suffer from long algorithm runtimes and do not scale well for ontology KB represented by OWL DL (Description Logic). In some application scenarios, the soundness and completeness of reasoning results are not the key constraints, and it is acceptable to sacrifice them in exchange for the improvement of reasoning efficiency to some extent. Based on this view, an approximate reasoning method for large-scale ABox in OWL DL KBs was proposed, which is named the ChunfyReasoner (CFR). The CFR introduces neural-symbolic learning into ABox reasoning and integrates the advantages of symbolic systems and neural networks (NNs). By training the NN model, the CFR approximately compiles the logic deduction process of ontology reasoning, which can greatly improve the reasoning speed while ensuring higher reasoning quality. In this paper, we state the basic idea, framework, and construction process of the CFR in detail, and we conduct experiments on two open-source ontologies built on OWL DL. The experimental results verify the effectiveness of our method and show that the CFR can support the applications of large-scale ABox reasoning of OWL DL KBs. [ABSTRACT FROM AUTHOR]

Featured Application: Potential applications of the work are systems for objective artificial-intelligent performance assessment in healthy individuals (including athletes) and patients with various injuries and conditions, including within the eHealth paradigm, including future wearable devices (e.g., e-shoes). The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf soccer players, 19 hearing soccer players and 46 deaf untraining male). A fuzzy computational model of different levels of physical activity with a focus on the lower limbs was constructed. The proposed fuzzy model assessing lower limb peak torque in an isokinetic mode demonstrated its effectiveness. The novelty of our research lies in the use of hierarchical fuzzy logic to extract computational rules from data provided explicitly and then to determine the corresponding physiological and pathological mechanisms. The contribution of our research lies in complementing the methods for describing physiology, pathology and rehabilitation with fuzzy parameters, including the so-called dynamic norm embedded in the model. [ABSTRACT FROM AUTHOR]

We study a sound verification method for parametric component-based systems. The method uses a resource logic, a new formal specification language for distributed systems consisting of a finite yet unbounded number of components. The logic allows the description of architecture configurations coordinating instances of a finite number of types of components, by means of inductive definitions similar to the ones used to describe algebraic data types or recursive data structures. For parametric systems specified in this logic, we show that decision problems such as reaching deadlock or violating critical section are undecidable, in general. Despite this negative result, we provide for these decision problems practical semi-algorithms relying on the automatic synthesis of structural invariants allowing the proof of general safety properties. The invariants are defined using the WS κ S fragment of the monadic second order logic, known to be decidable by a classical automata-logic connection, thus reducing a verification problem to checking satisfiability of a WS κ S formula. • We introduce a logic-based language for describing sets of configurations of parameterized distributed systems. • The language uses predicate symbols to hierarchically decompose the system architecture into specific patterns. • We address a parametric safety problem i.e., checking that reachable configurations stay clear of error configurations. • We show that deadlock freedom and critical section violation problems are undecidable, even for simple architectures. • We develop a verification method that synthesizes parametric invariants described using a decidable fragment of MSO. [ABSTRACT FROM AUTHOR]

We present DEGARI 2.0 (Dynamic Emotion Generator And ReclassIfier): an explainable, affective-based, art recommender relying on the commonsense reasoning framework T CL and exploiting an ontological model formalizing the Plutchik's theory of emotions. The main novelty of this system relies on the development of diversity-seeking affective recommendations obtained by exploiting the spatial structure of the Plutchik's 'wheel of emotion'. In particular, such development allows to classify and to suggest, to museum users, cultural items able to evoke not only the very same emotions of already experienced or preferred objects (e.g. within a museum exhibition), but also novel items sharing different emotional stances. The system's goal, therefore, is to break the filter bubble effect and open the users' view towards more inclusive and empathy-based interpretations of cultural content. The system has been tested, in the context of the EU H2020 SPICE project, on the community of deaf people and on the collection of the GAM Museum of Turin. We report the results and the lessons learnt concerning both the acceptability and the perceived explainability of the received diversity-seeking recommendations. [ABSTRACT FROM AUTHOR]

Representing uncertain information is crucial for modeling real world domains. This has been fully recognized both in the field of Logic Programming and of Description Logics (DLs), with the introduction of probabilistic logic languages and various probabilistic extensions of DLs respectively. Several works have considered the distribution semantics as the underlying semantics of Probabilistic Logic Programming (PLP) languages and probabilistic DLs (PDLs), and have then targeted the problem of reasoning and learning in them. This paper is a survey of inference, parameter and structure learning algorithms for PLP languages and PDLs based on the distribution semantics. A few of these algorithms are also available as web applications. [ABSTRACT FROM AUTHOR]

We answer the question of which conjunctive queries are uniquely characterized by polynomially many positive and negative examples and how to construct such examples efficiently. As a consequence, we obtain a new efficient exact learning algorithm for a class of conjunctive queries. At the core of our contributions lie two new polynomial-time algorithms for constructing frontiers in the homomorphism lattice of finite structures. We also discuss implications for the unique characterizability and learnability of schemamappings and of description logic concepts. [ABSTRACT FROM AUTHOR]

The aim of the present paper is to prove that concept validity and positive satisfiability with an empty ontology in the Fuzzy Description Logic I ALE , under standard product semantics and with respect to quasi-witnessed models, are decidable. In our framework we are not considering reasoning tasks over ontologies. The proof of our result consists in reducing the problem to a finitary consequence problem in propositional product logic with Monteiro-Baaz delta operator, which is known to be decidable. Product FDL and first order logic are known not to enjoy the finite model property, so we cannot restrict to finite interpretations. Thus, in order to obtain our result, we need to codify infinite interpretations using a finite number of propositional formulas. Such result was conjectured in [10] , but the proof given was subsequently found incorrect. In the present work an improved reduction algorithm is proposed and a proof of the same result is provided. [ABSTRACT FROM AUTHOR]

This paper is a survey of standards being used in the domain of digital cultural heritage with focus on the Metadata Encoding and Transmission Standard (METS) created by the Library of Congress in the United States of America. The process of digitization of cultural heritage requires silo breaking in a number of areas—one area is that of academic disciplines to enable the performance of rich interdisciplinary work. This lays the foundation for the emancipation of the second form of silo which are the silos of knowledge, both traditional and born digital, held in individual institutions, such as galleries, libraries, archives and museums. Disciplinary silo breaking is the key to unlocking these institutional knowledge silos. Interdisciplinary teams, such as developers and librarians, work together to make the data accessible as open data on the "semantic web". Description logic is the area of mathematics which underpins many ontology building applications today. Creating these ontologies requires a human–machine symbiosis. Currently in the cultural heritage domain, the institutions' role is that of provider of this open data to the national aggregator which in turn can make the data available to the trans-European aggregator known as Europeana. Current ingests to the aggregators are in the form of machine readable cataloguing metadata which is limited in the richness it provides to disparate object descriptions. METS can provide this richness. [ABSTRACT FROM AUTHOR]

Controlled Query Evaluation (CQE) is a framework for the protection of confidential data, where a policy given in terms of logic formulae indicates which information must be kept private. Functions called censors filter query answering so that no answers are returned that may lead a user to infer data protected by the policy. The preferred censors, called optimal censors, are the ones that conceal only what is necessary, thus maximizing the returned answers. Typically, given a policy over a data or knowledge base, several optimal censors exist. Our research on CQE is based on the following intuition: confidential data are those that violate the logical assertions specifying the policy, and thus censoring them in query answering is similar to processing queries in the presence of inconsistent data as studied in Consistent Query Answering (CQA). In this paper, we investigate the relationship between CQE and CQA in the context of Description Logic ontologies. We borrow the idea from CQA that query answering is a form of skeptical reasoning that takes into account all possible optimal censors. This approach leads to a revised notion of CQE, which allows us to avoid making an arbitrary choice on the censor to be selected, as done by previous research on the topic. We then study the data complexity of query answering in our CQE framework, for conjunctive queries issued over ontologies specified in the popular Description Logics DL-Lite R and EL ⊥. In our analysis, we consider some variants of the censor language, which is the language used by the censor to enforce the policy. Whereas the problem is in general intractable for simple censor languages, we show that for DL-Lite R ontologies it is first-order rewritable, and thus in AC0 in data complexity, for the most expressive censor language we propose. [ABSTRACT FROM AUTHOR]

The advent of the Semantic Web and Linked Data initiative has contributed to new perspectives and opportunities regarding cultural heritage conservation. Museums have extensive collections of Chinese ceramic vases in China. Although some data sources have been digitized, the vision of cultural heritage institutions is not only to display objects and simple descriptions (drawn from metadata), but also to allow for understanding relationships between objects (created by semantically interrelated metadata). The key to achieving this goal is to utilize the technologies of the Semantic Web, whose core is Ontology. The focus of this paper is to describe the construction of the TAO CI ("ceramics" in Chinese) ontology and terminology of the domain of ceramic vases of the Ming (1368–1644) and Qing (1644–1911) dynasties. The theoretical framework relies on the notion of essential characteristics. This notion is compliant with the ISO principles on Terminology (ISO 1087 and 704), according to which a concept is defined as a combination of essential characteristics, and with the Aristotelian definition in terms of genus and differentia. This approach is intuitive for domain experts and requires identifying essential characteristics, combining them into concepts, and translating the result into a Semantic Web language. This article proposes an approach based on a morphological analysis of the Chinese terms for vases to identify essential characteristics and a term-guided method for defining concepts. Such a term-and-characteristic guided approach makes ontology engineering less dependent on formal languages and does not require a background in Description Logics. The research presented in this article aims to publish the resulting structured data on the Semantic Web for the use of anybody interested, including museums hosting collections of these vessels, and enrich existing domain ontology building methodologies. To our knowledge, there are no comprehensive ontologies for Chinese ceramic vases. TAO CI ontology remedies this gap and provides a reference for ontology building in other domains of Chinese cultural heritage. The TAO CI ontology is openly accessible here: http://www.dh.ketrc.com/otcontainer/data/otc.owl. [ABSTRACT FROM AUTHOR]

Formal thought disorder (FTD) is a clinical mental condition that is typically diagnosable by the speech productions of patients. However, this has been a vexing condition for the clinical community, as it is not at all easy to determine what "formal" means in the plethora of symptoms exhibited. We present a logic-based model for the syntax–semantics interface in semantic networking that can not only explain, but also diagnose, FTD. Our model is based on description logic (DL), which is well known for its adequacy to model terminological knowledge. More specifically, we show how faulty logical form as defined in DL-based Conception Language (CL) impacts the semantic content of linguistic productions that are characteristic of FTD. We accordingly call this the dyssyntax model. [ABSTRACT FROM AUTHOR]

A new IoT authentication protocol is presented to address the security deficiencies in the Z-Wave protocol. The new protocol is based on Diameter and includes authentication/authorization module, billing module, and secure communication module. According to the characteristics of IoT devices, the relevant algorithms are optimized, and the key agreement scheme based on elliptic curve algorithm and the symmetric encryption scheme based on AES and RC4 are introduced, which enhances the security of the protocol and also improves the system performance. The speed of response reduces the energy consumption of the system. Aiming at solving the problem that the existing polynomial-based key predistribution management scheme is limited by the key sharing rate between the nodes and the network connectivity rate, a quadratic-based wireless sensor key management scheme is proposed. The scheme breaks through the existing idea of building a shared key with a binary t-order symmetric polynomial, introduces a multivariate asymmetric quadratic polynomial, and utilizes the relationship between the quadratic eigenvalues and eigenvectors. The analysis proves that the quadratic form can be orthogonally diagonalized and uses it to generate key information, and nodes realize identity authentication by exchanging key information. The establishment of an independent and unique session key with the neighbor node is completed. The security performance analysis and simulation results show that, compared with the existing key management schemes, the scheme has great improvements in anti-capture property, connectivity, scalability, communication overhead, and storage overhead. After a series of functional tests, the enterprise information system based on the SaaS platform in this paper basically met the design requirements and finally realized the networking of the enterprise information management process and the sharing of information. Each functional module of the system can be used normally. When the input and output are wrong, the system will have a correct prompt. The buttons and various controls of the system can work normally, meeting the requirements of functional testing. Each document of the system is correct and complete, and the language description and logic meet the needs of users and meet the requirements of document testing. The test results show that the interface of the system is friendly and easy to operate and the performance of the system is stable, which is basically in line with the needs of users and achieves the design goal of this system. [ABSTRACT FROM AUTHOR]

Based on a formalization of open formulas as statements in context, the paper presents a freshly new and abstract view of logics and specification formalisms. Generalizing concepts like sets of generators in Group Theory, underlying graph of a sketch in Category Theory, sets of individual names in Description Logic and underlying graph-based structure of a software model in Software Engineering, we coin an abstract concept of context. We show how to define, in a category independent way, arbitrary first-order statements in arbitrary contexts. Examples of those statements are defining relations in Group Theory, commutative, limit and colimit diagrams in Category Theory, assertional axioms in Description Logic and constraints in Software Engineering. To validate the appropriateness of the newly proposed abstract framework, we prove that our category independent definitions and constructions give us a very broad spectrum of Institutions of Statements at hand. For any Institution of Statements, a specification (presentation) is given by a context together with a set of first-order statements in that context. Since many of our motivating examples are variants of sketches, we will simply use the term sketch for those specifications. We investigate exhaustively different kinds of arrows between sketches and their interrelations. To pave the way for a future development of category independent deduction calculi for sketches, we define arbitrary first-order sketch conditions and corresponding sketch constraints as a generalization of graph conditions and graph constraints, respectively. Sketch constraints are the crucial conceptual tool to describe and reason about the structure of sketches. We close the paper with some vital observations, insights and ideas related to future deduction calculi for sketches. Moreover, we outline that our universal method to define sketch constraints enables us to establish and to work with conceptual hierarchies of sketches. [ABSTRACT FROM AUTHOR]

There are two kinds of bisimulation, namely crisp and fuzzy , between fuzzy structures such as fuzzy automata, fuzzy labeled transition systems, fuzzy Kripke models and fuzzy interpretations in description logics. Fuzzy bisimulations between fuzzy automata over a complete residuated lattice have been introduced by Ćirić et al. in 2012. Logical characterizations of fuzzy bisimulations between fuzzy Kripke models (respectively, fuzzy interpretations in description logics) over the residuated lattice [ 0 , 1 ] with the Gödel t-norm have been provided by Fan in 2015 (respectively, Nguyen et al. in 2020). There was the lack of logical characterizations of fuzzy bisimulations between fuzzy graph-based structures over a general residuated lattice, as well as over the residuated lattice [ 0 , 1 ] with the Łukasiewicz or product t-norm. In this article, we provide and prove logical characterizations of fuzzy bisimulations in fuzzy modal logics over residuated lattices. The considered logics are the fuzzy propositional dynamic logic and its fragments. Our logical characterizations concern invariance of formulas under fuzzy bisimulations and the Hennessy-Milner property of fuzzy bisimulations. They can be reformulated for other fuzzy structures such as fuzzy labeled transition systems and fuzzy interpretations in description logics. [ABSTRACT FROM AUTHOR]

Ontologies are logical theories that are used in computer science for describing different items such as web services, agents in multi-agent systems, or domain knowledge. Many ontologies exist, expressing various domains of knowledge with different abstraction levels (domain ontologies, top-level ontologies, and task ontologies are the usual categories). The conceptualization of the knowledge contained in an ontology is subject to change, whether because the context of its use changes, because the domain evolves, or because an ontology needs to interoperate with other elements using other ontologies. Change in logical theories is a form of defeasible reasoning, in which some formulas need to be added or removed from a knowledge base. Adaptive Logics (AL) is a logic managing defeasible reasoning that we investigate in this paper for managing change in ontologies expressed with Description Logics (DL). The adaptation of AL for DL will help express the context in which formulas remain valid or can be added to a DL knowledge base, and ease the interoperability between ontologies. [ABSTRACT FROM AUTHOR]

The strategical learning "how to learn" responds to improve the teaching of the architectural design, recognizing to the mental functions that intervene in this process and that are those in charge of processing, organizing, coordinating, and integrating the information interacting with the environment that surrounds us, which is part in the student's integral education. The evaluation of a teaching-learning process is vital for the effectiveness of the process, because it allows us the correction of any current error and to reinforce the successes, which is inherent to all dynamic process. This paper aims to offer an evaluative model of the architectural teaching that is represented with the support of the Description Logics. They are formed by a family of logics that allow us the representation of the knowledge on a certain domain, in a structured way and formally well-defined. The advantages offered by the proposed model, besides representing the knowledge, is that it is possible the evaluation and self-evaluation, the socialization of the knowledge, as well as to carry out logical inferences. [ABSTRACT FROM AUTHOR]

Since its inception, research in the field of I Artificial Intelligence i (AI) has had a fundamentally logical approach; therefore, discussions have taken place to establish a way of distinguishing symbolic AI from sub-symbolic AI, basing the approach instead on the statistical approaches typical of I machine learning i , I deep learning i or I Bayesian networks i . Hence, the problem is solved by forcing the following to be false: there is an edge from node I X i to node I Y i , such that I X i is colored by the same color of I Y i (named I Z i in the rule): HT ht These two rules allow us to encode the result in a sound and complete the 3-coloring problem, also offering, thanks to the symbolic approach, an almost immediate understanding for a human being of the meaning encoded in the rules. [Extracted from the article]

The need to address the challenge of vagueness across several domains of applicability of ontology is gaining research attention. The presence of vagueness in knowledge represented with description logic impairs automating reasoning and inference making. The importance of reducing this vagueness in the formalization of medical knowledge representation is rising, considering the vulnerability of this domain to the expression of vague concepts or terms. This vagueness may be addressed from the perspective of ontology modeling language application such as ontology web language (OWL). Although several attempts have been made to tackle this problem in other disease prognoses such as diabetes and cardiovascular diseases, a similar effort is missing for breast cancer. Minimizing vagueness in breast cancer ontology is necessary to enhance automated reasoning and handle knowledge representation problems. This study proposes a framework for reducing vagueness in breast cancer ontology. The approach obtained breast cancer crisp ontology and applied fuzzy ontology elements based on the Fuzzy OWL2 model to formulate breast cancer fuzzy ontology. This was achieved by extending the elements of OWL2 (a more expressive version of OWL) with annotation properties to fuzzify the breast cancer crisp ontology. Results obtained showed a significant reduction of vagueness in the domain, yielding 0.38 for vagueness spread and 1.0 for vagueness explicitness. In addition, ontology metrics such as completeness, consistency, correctness and accuracy were also evaluated, and we obtained impressive performance. The implication of this result is the reduction of vagueness in breast cancer ontology, which provides increased computational reasoning support to applications using the ontology. [ABSTRACT FROM AUTHOR]

The article explores the following question: which among the most often examined in the literature method of constructing Hilbert-type axiom systems for finite-valued propositional logics of Łukasiewicz – the Rosser-Turquette method, the Tuziak method or the Grigolia system of axiom schemata – is in fact applicable in the researches on many-valued logics? Although the method offered by Rosser and Turquette is considered to be a solution of the problem of axiomatizability of finite-valued logics of Łukasiewicz, it has a serious limitation in producing adequate axiom systems. If the Rosser-Turquette axiom schemata are expressed just in terms of the standard propositional connectives which are definable in terms of the propositional connectives of Łukasiewicz's logics, then every Rosser-Turquette axiom system for a Łukasiewicz's logic is semantically incomplete. The article also examines the Tuziak axiom systems that actually axiomatize Łukasiewicz's finite-valued logics and can be applied in the logical researches. The article compares the Tuziak axiom systems with the Grigolia set of axiom schemata, and it demonstrates that since a crucial in the Grigolia method definition of connectives is in fact invalid in Łukasiewicz's logics, the Grigolia method does not provide sound axiom systems for Łukasiewicz's logics. [ABSTRACT FROM AUTHOR]

Introduction: Currently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of the algorithm logic, often accompanied by flowcharts. A challenge with this mode of dissemination is the potential for under-specification in the algorithm definition, which leads to ambiguity and vagueness.Methods: This study examines incidents of under-specification that occurred during the implementation of 34 narrative phenotyping algorithms in the electronic Medical Record and Genomics (eMERGE) network. We reviewed the online communication history between algorithm developers and implementers within the Phenotype Knowledge Base (PheKB) platform, where questions could be raised and answered regarding the intended implementation of a phenotype algorithm.Results: We developed a taxonomy of under-specification categories via an iterative review process between two groups of annotators. Under-specifications that lead to ambiguity and vagueness were consistently found across narrative phenotype algorithms developed by all involved eMERGE sites.Discussion and Conclusion: Our findings highlight that under-specification is an impediment to the accuracy and efficiency of the implementation of current narrative phenotyping algorithms, and we propose approaches for mitigating these issues and improved methods for disseminating EHR phenotyping algorithms. [ABSTRACT FROM AUTHOR]

A variety of recent work in epistemology employs a notion of normality to provide novel theories of knowledge or justification. While such theories are commonly advertised as affording particularly strong epistemic logics, they often make substantive assumptions about the background notion of normality and its logic. This article takes recent normality-based defences of the KK principle as a case study to submit such assumptions to scrutiny. After clarifying issues regarding the natural language use of normality claims, the article isolates a number of choice points regarding the role of contingency, context-sensitivity and similarity in our theorizing with normality. It turns out that both weaker and stronger logics of normality can be motivated depending on how such choices are resolved. And yet securing logics of normality strong enough for normality to play its envisaged role in epistemology may have unwelcome downstream consequences for the resultant theories of knowledge or justification. [ABSTRACT FROM AUTHOR]

The spatial footprints, historical or acquired in real time, help to understand the dynamics of their carriers. In a context of coastal maritime navigation, the research presented details the approach of setting up a knowledge model aimed at a semantic analysis of ship footprints. This model is defined on the basis of knowledge gathered from experts in this field, supplemented by textual and graphic descriptions. After having described these navigation principles, we present the stages leading to such a knowledge model. The research is completed by the formalization of rules relating to the visibility of landmarks. Finally, a reasoning leads to infer additional navigation knowledge on which the navigation footprints are confronted in order to identify the routes having semantics for the model and those devoid of semantics. [ABSTRACT FROM AUTHOR]