Search Results (10)

In this study, we demonstrate that the Sn₂Se₂P₄ monolayer exhibits intrinsic anisotropic electronic characteristics with the strain-synergistic modulation of carrier transport and optoelectronic properties, as revealed by various levels of density functional theory calculations combined with the non-equilibrium Green’s function method. The calculations reveal that a-axis uniaxial compression of the Sn₂Se₂P₄ monolayer induces an indirect-to-direct bandgap transition (from 1.73 eV to 0.97 eV, as calculated by HSE06), reduces the hole effective mass by ≥70%, and amplifies current density by 684%. Conversely, a-axis uniaxial expansion (+8%) boosts ballistic transport (a/b-axis current ratio > 10⁵), rivaling black phosphorus. Notably, a striking negative differential conductance arises with the maximum I_peak/I_valley in the order of 10⁵ under the 2% uniaxial compression along the b-axis of the Sn₂Se₂P₄ monolayer. Visible-range anisotropic absorption coefficients (~10⁵ cm⁻¹) are achieved, where −4% a-axis strain elevates the photocurrent density (6.27 μA mm⁻² at 2.45 eV) and external quantum efficiency (39.2%) beyond many 2D materials benchmarks. Non-monotonic strain-dependent photocurrent density peaks at 2.00 eV correlate with hole effective mass reduction patterns, confirming the carrier mobility of the Sn₂Se₂P₄ monolayer as the governing parameter for photogenerated charge separation. These results establish Sn₂Se₂P₄ as a multifunctional material enabling strain-tailored anisotropy for logic transistors, negative differential resistors, and photovoltaic devices, while guiding future investigations on environmental stabilization and heterostructure integration toward practical applications. Full article

Non-axiomatic logic (NAL) is a term-based, non-monotonic, multi-valued logic with evidence-based formal semantics. All those characteristics position NAL as an excellent candidate for modeling natural language expressions and supporting artificial agents while performing knowledge discovery and commonsense reasoning tasks. In this article, we propose a set of rules for the automatic translation of natural language (NL) text into the formal language of non-axiomatic logic (NAL). Several free available tools are used to support a previous linguistic analysis, and a common sense ontology is used to populate a background knowledge base that helps to delimit the scope and the semantics of logical formulas translated. Experimentation shows our set to be the most comprehensive NL-to-NAL translation rule set known so far. Furthermore, we included an extensive set of examples to show how our proposed set of rules can be used for translating a wide range of English statements with varying grammatical structures. Full article

Ferroelectric ceramic materials based on the (1-x-y) NaNbO₃-xKNbO₃-yCd_0.5NbO₃ system (x = 0.05–0.65, y = 0.025–0.30, Δx = 0.05) were obtained by a two-stage solid-phase synthesis followed by sintering using conventional ceramic technology. It was found that the region of pure solid solutions extends to x = 0.70 at y = 0.05 and, with increasing y, it narrows down to x ≤ 0.10 at y = 0.25. Going out beyond the specified concentrations leads to the formation of a heterogeneous region. It is shown that the grain landscape of all studied ceramics is formed during recrystallization sintering in the presence of a liquid phase, the source of which is unreacted components (Na₂CO₃ with T_melt. = 1126 K, K₂CO₃ with T_melt. = 1164 K, KOH with T_melt. = 677 K) and low-melting eutectics in niobate mixtures (NaNbO₃, T_melt. = 1260 K, KNbO₃, T_melt. = 1118 K). A study of the electrophysical properties at room temperature showed the nonmonotonic behavior of all dependences with extrema near symmetry transitions, which corresponds to the logic of changes in the electrophysical parameters in systems with morphotropic phase boundaries. An analysis of the evolution of dielectric spectra made it possible to distinguish three groups of solid solutions: classical ferroelectrics (y = 0.05–0.10), ferroelectrics with a diffuse phase transition (y = 0.30), and ferroelectrics relaxors (y = 0.15–0.25). A conclusion about the expediency of using the obtained data in the development of materials and devices based on such materials has been made. Full article

Default logic is one of the basic formalisms for nonmonotonic reasoning, a well-established area from logic-based artificial intelligence dealing with the representation of rational conclusions, which are characterised by the feature that the inference process may require to retract prior conclusions given additional premisses. This nonmonotonic aspect is in contrast to valid inference relations, which are monotonic. Although nonmonotonic reasoning has been extensively studied in the literature, only few works exist dealing with a proper proof theory for specific logics. In this paper, we introduce sequent-type calculi for two variants of default logic, viz., on the one hand, for three-valued default logic due to Radzikowska, and on the other hand, for disjunctive default logic, due to Gelfond, Lifschitz, Przymusinska, and Truszczyński. The first variant of default logic employs Łukasiewicz’s three-valued logic as the underlying base logic and the second variant generalises defaults by allowing a selection of consequents in defaults. Both versions have been introduced to address certain representational shortcomings of standard default logic. The calculi we introduce axiomatise brave reasoning for these versions of default logic, which is the task of determining whether a given formula is contained in some extension of a given default theory. Our approach follows the sequent method first introduced in the context of nonmonotonic reasoning by Bonatti, which employs a rejection calculus for axiomatising invalid formulas, taking care of expressing the consistency condition of defaults. Full article

This paper relates two interesting paradigms in fuzzy logic programming from a semantical approach: core fuzzy answer set programming and multi-adjoint normal logic programming. Specifically, it is shown how core fuzzy answer set programs can be translated into multi-adjoint normal logic programs and vice versa, preserving the semantics of the starting program. This translation allows us to combine the expressiveness of multi-adjoint normal logic programming with the compactness and simplicity of the core fuzzy answer set programming language. As a consequence, theoretical properties and results which relate the answer sets to the stable models of the respective logic programming frameworks are obtained. Among others, this study enables the application of the existence theorem of stable models developed for multi-adjoint normal logic programs to ensure the existence of answer sets in core fuzzy answer set programs. Full article

There is a fairly widespread belief that the problem of existence is not an essential issue for logic. Logic, though formal, must deal with the problem of existence. However, logic should be limited to describing “formal existence” or “existence of a formal system”. However, the logical problem of existence and how to treat and resolve this problem differ completely from the corresponding metaphysical problem. It is possible to deduce that formal existence is nothing other than belonging to the universe of discourse, so proposing a solution to the logical problem of existence in an epistemological, rather than a metaphysical, context. In this paper, we conclude, from a formal point of view, no universe of discourse is given in advance; any universe of discourse that satisfies the necessary conditions can be used. The extended epistemological belief that there is a universe of discourse defined rigorously, which would be the true and should be “the universe of discourse of logic”, cannot be justified. Full article

The diagnosis method for a weak-fault model with only normal behaviors of each component has evolved over decades. However, many systems now demand a strong-fault models, the fault modes of which have specific behaviors as well. It is difficult to diagnose a strong-fault model due to its non-monotonicity. Currently, diagnosis methods usually employ conflicts to isolate possible fault and the process can be expedited when some observed output is consistent with the model’s prediction where the consistency indicates probably normal components. This paper solves the problem of efficiently diagnosing a strong-fault model by proposing a novel Logic-based Truth Maintenance System (LTMS) with two search approaches based on conflict and consistency. At the beginning, the original a strong-fault model is encoded by Boolean variables and converted into Conjunctive Normal Form (CNF). Then the proposed LTMS is employed to reason over CNF and find multiple minimal conflicts and maximal consistencies when there exists fault. The search approaches offer the best candidate efficiency based on the reasoning result until the diagnosis results are obtained. The completeness, coverage, correctness and complexity of the proposals are analyzed theoretically to show their strength and weakness. Finally, the proposed approaches are demonstrated by applying them to a real-world domain—the heat control unit of a spacecraft—where the proposed methods are significantly better than best first and conflict directly with A* search methods. Full article

This article is an overview of the SP theory of intelligence, which aims to simplify and integrate concepts across artificial intelligence, mainstream computing and human perception and cognition, with information compression as a unifying theme. It is conceived of as a brain-like system that receives "New" information and stores some or all of it in compressed form as "Old" information; and it is realised in the form of a computer model, a first version of the SP machine. The matching and unification of patterns and the concept of multiple alignment are central ideas. Using heuristic techniques, the system builds multiple alignments that are "good" in terms of information compression. For each multiple alignment, probabilities may be calculated for associated inferences. Unsupervised learning is done by deriving new structures from partial matches between patterns and via heuristic search for sets of structures that are "good" in terms of information compression. These are normally ones that people judge to be "natural", in accordance with the "DONSVIC" principle—the discovery of natural structures via information compression. The SP theory provides an interpretation for concepts and phenomena in several other areas, including "computing", aspects of mathematics and logic, the representation of knowledge, natural language processing, pattern recognition, several kinds of reasoning, information storage and retrieval, planning and problem solving, information compression, neuroscience and human perception and cognition. Examples include the parsing and production of language with discontinuous dependencies in syntax, pattern recognition at multiple levels of abstraction and its integration with part-whole relations, nonmonotonic reasoning and reasoning with default values, reasoning in Bayesian networks, including "explaining away", causal diagnosis, and the solving of a geometric analogy problem. Full article

In semantic policy infrastructure, a Trusted Legal Domain (TLD), designated as a Super-Peer Domain (SPD), is a legal cage model used to circumscribe the legal virtual boundary of data disclosure and usage in the cloud. Semantic legal policies in compliance with the law are enforced at the super-peer within an SPD to enable Law-as-a-Service (LaaS) for cloud service providers. In addition, cloud users could query fragmented but protected outsourcing cloud data from a law-aware super-peer, where each query is also compliant with the law. Semantic legal policies are logic-based formal policies, which are shown to be a combination of OWL-DL ontologies and stratified Datalog rules with negation, i.e., so-called non-monotonic cq-programs, for policy representation and enforcement. An agent at the super-peer is a unique law-aware guardian that provides protected data integration services for its peers within an SPD. Furthermore, agents at the super-peers specify how law-compliant legal policies are unified with each other to provide protected data exchange services across SPDs in the semantic data cloud. Full article

Sensor networks are estimated to drive the formation of the future Internet, with stream reasoning responsible for analysing sensor data. Stream reasoning is defined as real time logical reasoning on large, noisy, heterogeneous data streams, aiming to support the decision process of large numbers of concurrent querying agents. In this research we exploited non-monotonic rule-based systems for handling inconsistent or incomplete information and also ontologies to deal with heterogeneity. Data is aggregated from distributed streams in real time and plausible rules fire when new data is available. The advantages of lazy evaluation on data streams were investigated in this study, with the help of a prototype developed in Haskell. Full article