Hasil untuk "Logic"

J. Alamo

R. Brayton, A. Mishchenko

S. Vargo, R. Lusch

A. Andrew

W. Quine

A. R. Turquette, A. Tarski, J. H. Woodger

C. A. Middelburg

A paradefinite logic is a logic that can serve as the underlying logic for theories that are inconsistent or incomplete. A well-known paradefinite logic is Belnap-Dunn logic. Various expansions of Belnap-Dunn logic have been studied in the literature. In this note, it is argued that the most natural paradefinite logic relative to classical logic is the expansion of Belnap-Dunn logic with a falsity connective and an implication connective for which the standard deduction theorem holds.

Metin Deder, Simay Sahin, Merve Yilmazer et al.

Automated unit testing methods in the software development process are crucial for reducing costs, improving product quality, and ensuring system reliability. While current Large Language Models (LLMs) are highly successful in general-purpose code generation, they may fall short in ensuring structural integrity and producing executable code in industrial fields such as C++ and ROS 2, where memory management is critical and external dependencies are frequently used. The proposed method fills this gap by focusing not only on high-level languages, unlike existing studies in the literature, but also on industrial embedded system architectures. The proposed method developed in this study aims to create high-accuracy unit tests by reducing the hallucination rate for systems without existing test scope, and to develop systems with existing test scope using developer logic. Recently distinguished by its success in code generation, the 7-billion-parameter Qwen 2.5 Coder model was selected as the base model. A multilingual dataset consisting of over 13,000 unique code-test pairs was created to reduce the model's computational costs and improve test code generation speed. The model was trained using QLoRA (Quantized Low-Rank Adaptation) and LLM fine-tuning methods. The proposed method has contributed to time savings and increased efficiency by accelerating test code generation speed by approximately 4 times compared to existing cloud-based approaches. Furthermore, unlike functionality-focused black-box testing and raw text-based approaches in the literature, the model's understanding of the project context is ensured by using Abstract Syntax Trees (AST), and the hallucination problem is significantly reduced by employing white-box and structural testing principles that examine the internal structure and dependencies of the source code. The proposed method addresses the limitations of leveraging large language models when generating unit test code and the key points in producing effective unit test code for industrial applications.

A. Newell, H. Simon

Kanta Takahata, Jonas Schöpf, Naoki Nishida et al.

Logically constrained term rewriting is a rewriting framework that supports built-in data structures such as integers and bit vectors. Recently, constrained terms play a key role in various analyses and applications of logically constrained term rewriting. A fundamental question on constrained terms arising there is how to characterize equivalence between them. However, in the current literature only limited progress has been made on this. In this paper, we provide several sound and complete solutions to tackle this problem. Our key idea is the introduction of a novel concept, namely existentially constrained terms, into which the original form of constrained terms can be embedded. We present several syntactic characterizations of equivalence between existentially constrained terms. In particular, we provide two different kinds of complete characterizations: one is designed to facilitate equivalence checking, while the other is intended for theoretical analysis.

Fella Boucetta, Mohamed Toufik Benchouia, Amel Benmouna et al.

This paper introduces a novel fractional-order fuzzy logic controller (FOFLC) designed for stator voltage control in standalone doubly fed induction generator (DFIG) systems used in wind energy applications. Unlike traditional fuzzy logic controllers (FLCs), which are limited by integer-order dynamics, the FOFLC leverages the advanced principles of fractional-order (FO) calculus. By integrating fuzzy logic with fractional-order operators, the FOFLC enhances system precision, adaptability, and interpretability while addressing the inherent limitations of conventional proportional-integral (PI) controllers and integer-order FLCs. A key innovation of the FOFLC is its dual-mode architecture, enabling it to operate seamlessly as either a traditional FLC or a fractional-order FOFLC controller. This versatility allows for independent tuning of fractional parameters, optimizing the system’s response to transients, steady-state errors, and disturbances. The controller’s flexibility makes it particularly well-suited for nonlinear and dynamically complex stand-alone renewable energy systems. The FOFLC is experimentally validated on a 3-kW DFIG test bench using the dSPACE-1104 platform under various operating conditions. Compared to a conventional PI controller, the FOFLC demonstrated superior performance, achieving 80% reduction in response time, eliminating voltage overshoot and undershoot, reducing stator power and torque ripples by over 46%, and decreasing total harmonic distortion (THD) of both stator voltage and current by more than 50%. These results confirm the FOFLC’s potential as a robust and adaptive control solution for stand-alone renewable energy systems, ensuring high-quality power output and reliable operation.

K. J. Sora, C. C. C. Wabnitz, N. S. Steiner et al.

Abstract Climate change is impacting Arctic marine ecosystems at faster rates than the global average, challenging the management and conservation of biodiversity and living marine resources. This study examined the climate risks and vulnerabilities of 21 Arctic fish species occurring in the western Canadian Arctic using a fuzzy logic approach. Identified climatic hazards to marine species and their habitats are increasing temperature, decreasing sea ice cover, freshening, decreasing oxygen concentration, and acidification. The nature of these hazards included changes in mean conditions by 2050 (2041–2060), compared to the historical period (1979–2015 average) simulated from a regional coupled ice-ocean biogeochemical model and two coupled Earth system models under low and high emissions scenarios. A spatially-explicit algorithm was used to assess the risk and vulnerability in the Beaufort Sea shelf and slope and Amundsen Gulf (BS–AG) based on the species’ biological traits, biogeography and their exposure to climatic hazards. The results indicated high to very high exposure and risk of climate impacts across the ecosystem variables. Specifically, shallow areas were projected to be simultaneously exposed to more intense warming, reduced sea ice coverage, freshening, and acidification relative to the regional averages. In addition, for species occurring in the BS–AG, low adaptability and high sensitivity to climate hazards was identified. These applied tools and evaluations can inform marine spatial planning and climate adaptation efforts to help achieve conservation objectives and sustain ecosystem and community health in a changing Arctic climate.

A. Church

J. Sklansky

J. Goguen

Alexandru-Ioan Lungu, Vlad Teodorescu, Andrei Zaborila et al.

Algorithm design courses are fundamental to computer science curricula, but fostering algorithmic thinking in students is challenging due to the diverse skills and creativity required. Dedicated teaching support tools can help both course instructors and students in this effort. We have developed the Alk platform to promote algorithmic thinking, leveraging the theoretical foundations of Matching Logic. Alk features an intuitive algorithm language that provides a flexible computational model suitable for analysis, symbolic execution, and checking properties of algorithms. In this paper, we present an overview of the Alk platform tool and demonstrate, through use cases, how it fosters various algorithmic thinking skills. We conclude that the Alk platform is a valuable tool for learning and teaching algorithms, effectively enhancing students’ understanding and skills. Future work will extend its capabilities of supporting symbolic execution, probabilistic algorithms, as well as estimation of execution time, further broadening its impact on computer science education.

J. Hintikka

Zoltan A. Kocsis

We introduce a proof-theoretic approach to showing nondefinability of second-order intuitionistic connectives by quantifier-free schemata. We apply the method to prove that Taranovsky's "realizability disjunction" connective does not admit a quantifier-free definition, and use it to obtain new results and more nuanced information about the nondefinability of Kreisel's and Połacik's unary connectives. The finitary and combinatorial nature of our method makes it resilient to changes in metatheory, and suitable even for settings with axioms that are explicitly incompatible with classical logic. Furthermore, the problem-specific subproofs arising from this approach can be readily transcribed into univalent type theory and verified using the Agda proof assistant.

Karel Hrbacek, Mikhail G. Katz

We provide choiceless proofs using infinitesimals of the global versions of Peano's existence theorem and Osgood's theorem on maximal solutions. We characterize all solutions in terms of infinitesimal perturbations. Our proofs are more effective than traditional non-infinitesimal proofs found in the literature. The background logical structure is the internal set theory SPOT, conservative over ZF.

Marek Górka

Objectives This article will attempt to analyse securitisation theory to explore the discursive features of cyber security, using a multi-actor approach that considers the role of state and non-state actors in the creation and management of cyber security discourses. Material and methods The paper aims to assess the contribution of securitization theory to the understanding of both traditional and contemporary security policy issues. More specifically, it is an attempt to reflect on the identification of the challenges facing the modern state. Results Growing dependence on digital technology is inevitable, making the future more threatening than the present. Cyber technology is inherently vulnerable and thus impossible to fully secure. The call for "greater security" becomes justified because the more a country depends on cyber technology, the more inevitable cyber threats become. They are consistently treated by government circles as a security challenge, meaning that the problem is presented as an existential threat, requiring emergency measures and justifying action beyond the normal bounds of political procedure. Conclusions As some conclusion and conclusion, it is worth reiterating observations about the multi-stakeholder nature of cyber security and observations about the co-creation of this security by a wide range of actors representing different and in some cases conflicting interests. It can be argued that there is no single discourse on cyber security or cyber threats, and it is simplistic to assume that there is even a single discourse that represents every securitization actor, be it government or the private sector. This diversity explains why the assumption and logic of securitization theory can only apply to some, but not all, cyber security discourses.