Hasil untuk "Logic"

Nicholaos Galatos, P. Jipsen, T. Kowalski et al.

H. Marcuse

Lawrence Charles Paulson, T. Nipkow

Athanassios Tzouvaras

We approach the sorites paradox (SP) through an observer-based and time-dependent approach to truth of vague assertions. Formally the approach gives rise to a semantics, called fluxing-object semantics (FOS), because it involves models that contain ``fluxing objects'', that is, entities changing with time and observer. The models are equipped with agents (observers) and a linear and discrete time axis for time. The changing entities are represented by partial functions of time and agent, and this partiality causes truth-value gaps. If we interpret a truth-value gap as a third truth value, then FOS becomes a three-valued logic, which, quite interestingly, is proved identical to strong Kleene three-valued logic. The sorites phenomena can be represented in a structure of FOS as special objects that change imperceptibly with respect to an observer and with respect to a particular attribute. In this account the key point that eliminates the paradoxical character of sorites is the partiality of functions. When the observer is fixed the partiality corresponds to interrupted watching on his part. The interruption creates watching gaps during which the attributed property of the object as understood by the observer may change, without violating the imperceptibility condition. Interrupted watching has, according to experts on visual attention and focusing capabilities of humans, a firm physiological justification. The relationship of watching gaps with horizon crossing is also discussed.

Takao Inoué

We introduce \emph{TAPO-Structured Description Logic} (TAPO--DL), a formal extension of classical description logic designed to model \emph{information behavior} as a structured, dynamic process. TAPO--DL extends the standard T--Box/A--Box architecture with two additional layers: a \emph{Procedural Box} (P--Box), which supports concept-driven, imperative-style programs such as conditional and iterative actions, and an \emph{Oracle Box} (O--Box), which formalizes controlled interaction with external information sources. While the terminological and assertional components capture static conceptual and factual knowledge, the procedural and oracle-based components enable the explicit representation of information-generating actions and external validation. We provide a unified semantic framework for TAPO--DL based on a co-generative, sheaf-theoretic interpretation, in which local informational states are modeled as sections and informational stability corresponds to the existence of coherent global structures. Within this setting, informational truth is characterized as stability under repeated agentive interaction rather than correspondence to a fixed global state. By integrating description logic with procedural dynamics, oracle-based reasoning, and sheaf-theoretic semantics, TAPO--DL offers a principled formal framework for analyzing information behavior in contexts involving interaction, uncertainty, and contextuality.

W. Labov

Mª Ángeles Caraballo, Oksana Liashenko

Background Institutional quality is a critical determinant of development outcomes, yet the role of social attitudes in shaping institutions remains underexplored. This study examines the impact of public attitudes toward gender equality, environmental protection, and immigration on institutional strength and socioeconomic development. Method Using data from Wave 7 of the World Values Survey, we apply a classification of attitudes based on a combination of set theory and ordinal preference logic. Respondents are grouped into 27 attitude combinations and then aggregated into eight categories. Country-level proportions are computed. We apply Bayesian Network Analysis (BNA) to uncover complex dependencies, identifying relationships and central institutional nodes such as the rule of law, democratic stability, and market organisation. Latent institutional quality and development outcomes variables are derived using Principal Component Analysis. We then use Structural Equation Modelling (SEM) to test a mediation model, estimating direct and indirect effects of attitudes on development outcomes. Bootstrapping with 5,000 replications ensures statistical robustness. Results BNA reveals that institutional quality is a key bridge between social attitudes and development outcomes. SEM confirms that institutional quality mediates these effects in most cases. Neutral-positive and mixed-neutral attitudes yield the most potent positive indirect effects, underscoring their role in consensus building. Negative attitudes are associated with institutional weakening and lower development performance. Interestingly, moderately negative views may drive democratic reform when linked to institutional accountability. Conclusion Social attitudes affect development primarily through their influence on institutions. Contrary to common assumptions, moderate and neutral positions are not passive; they foster institutional adaptability and stability. These findings underscore the importance of targeting centrist groups in policy design to reinforce inclusive governance and long-term development.

Zeyin Chen, Siying Li, Tao Wu et al.

Abstract In rapidly urbanizing cities, historical neighborhoods often experience drastic spatial transformation, leading to the erosion of urban form, memory, and identity. This study examines the morphological transformation of the Siwenli Lilong neighborhood in central Shanghai, tracing its evolution from 1948 to 2021. Drawing on a 70-year fine-scale GIS dataset at the lane-block level which is a rare longitudinal resolution in related urban research, the study integrates historical cartography, urban morphology, and heritage interpretation to identify three key phases: wartime densification, socialist consolidation, and market-driven redevelopment. Each phase reflects distinct governance rationales, cumulatively producing a shift from spatial continuity to fragmentation. The research introduces the concept of “interface rupture” to capture the disjunction between old and new typologies, particularly in façade logic and public–private transitions. Rather than treating transformation as incidental, it proposes a conceptual model linking governance regimes, development logics, and spatial consequences. While symbolic heritage elements are selectively retained, most morphological memory is weakened or erased. By integrating urban morphology with the Historic Urban Landscape (HUL) framework, the study contributes to heritage-led urbanism by moving beyond site-specific diagnosis toward transferable explanatory mechanisms. It calls for adaptive conservation frameworks that recognize spatial memory as a planning asset, promoting continuity during inevitable change. The Siwenli case thus serves as both empirical evidence and a theoretical lens for understanding structural dynamics behind morphological rupture in East Asian cities.

P. A. Rezvy, Venkata Lakshmi Narayana Komanapalli

When transmitters measure process variables like temperature, pressure, flow, level, and quality in process industries, due to wear and tear, ambient conditions, process variations and electromagnetic interference, measured values always deviate from their actual value, and controlled variables will start to oscillate near setpoint. This review paper investigates artificial intelligence impacts on measurement system to improve characteristics of transmitters like linearity, accuracy, sensitivity, resolution, repeatability. Soft computation using artificial neural networks and deep learning for linearization, compensation and error reduction, machine learning for estimation levaraging different algorithms like levenberg marquardt, scaled conjugate gradient, bayesian regularization, are assessed for training, testing and validation in real time and simulation. Hardware approach with soft computation has reduced non linearity error by 84.63% for thermocouple linearization, meanwhile novel hybrid approach using genetic algorithm (GA) and particle swarm optimization (PSO) combined with back propagation neural network (BPNN) have reduced mean absolute percentage error to 1.2 % for industrial weir than conventional hardware approaches using sensors and signal conditioning circuits but at higher computational cost. Challenges like integration to distributed control system via programmable logic controller, huge amount of training data for estimation, real time implementation in measurement systems, overfitting, underfitting, implementation cost are analyzed. Application of artificial intelligence methods and hybrid approaches in measurement systems can drastically improve the operation, maintenance, cost, safety of plant and personnel in real time, where artificial intelligence is still in its nascent stage in instrumentation and control.

Hanamantagouda P. Sankappanavar

This paper grew out of our investigation into a simple, but natural, question: Can 'F implies T' be distinct from F and T? To this end, we introduce five 'unorthodox' algebras that will play a major role, not only in providing a positive answer to the question, but also in their similarity to the 2-element Boolean algebra 2. Yet, they are remarkably dissimilar from 2 in many respects. In this paper, we will examine these five algebras both algebraically and logically. We define, and initiate an investigation into, a subvariety, called RUNO1, of the variety of De Morgan semi-Heyting algebras and show that RUNO1 is, in fact, the variety generated by the five algebras. Then several applications of this theorem are given. It is shown that RUNO1 is a discriminator variety and that all five algebras are primal. It is also shown that every subvariety of RUNO1 satisfies the Strong Amalgamation Property and the property that epimorphisms are surjective (ES). It is shown that the lattice of subvarieties of RUNO1 is a Boolean lattice of 32 elements. The bases for all the subvarieties of RUNO1 are also given. We introduce a new logic called mathcal{RUNO1} and show that it is algebraizable with the variety RUNO1 as its equivalent algebraic semantics. We then present axiomatizations for all 32 axiomatic extensions of mathcal{RUNO1} and deduce that all the axiomatic extensions are decidable. The paper ends with some open problems.

Lea Kaftan

Elected leaders increasingly undermine liberal democratic institutions with the support of their voters, openly challenging liberal democratic institutions in election campaigns. However, political scientists thus far have lacked the theoretical and empirical tools to study the role of elections in democratic backsliding. This article theorizes the degree to which democracy in general and liberal democracy more specifically can and should be conceptualized as valence and positional issues in multiparty electoral competitions of established liberal democracies. By investigating how German citizens and parties of the postwar period spoke about democracy per se and liberal democracy in their regional and national election manifestos, this article shows that democracy per se and liberal democracy, in particular, have been issues of different qualities in German postwar elections. While parties have used references to democracy in general as a mixed issue, showing both signs of valence and positional issues, parties’ emphasis on liberal democracy is shaped by a positional logic. Social and direct democracy have also been positional issues. Studying democracy and its various conceptions as electoral issues will help us address many important questions concerning the stability of democracies, shifting researchers’ focus to the competition of parties over citizens’ support for reforms that undermine or stabilize liberal democracy.

Nana Yaw Asiedu, Peter Paul Bamaalabong, Jesse Essuman Johnson et al.

Abstract Transfer of laboratory-scale experiments to production-scale ethanol fermentation is time-consuming and involves expensive prototype systems from complex experimental designs that determine optimal operating conditions for minimal substrate and product inhibitions. The study developed and validated a Simulink-based model for optimal pH and temperature control using fuzzy logic and PID controllers respectively and taking advantage of 2D and 1D substrate and product inhibition models from which suitable ethanol fermentation reaction rates models were selected. Temperature and pH levels and substrate, product, and biomass concentrations were measured. Selected inhibition models were linear-product, linear substrate-sudden stop product, and linear substrate for cassava, maize, and sorghum, respectively. Fuzzy logic controller ascertained optimal flow rate of acid and base as 0.000196 ml/s and 0.000204 ml/s, respectively, and pH error and rate of pH error as 0.00334 and 0.00368, respectively. F-test two-sample for variances showed no significant difference between model and experimental curves (cassava: F critical = 0.9704, F calculated = 0.1905; maize: F critical 0.9704, F calculated = 0.2149; sorghum: F critical = 0.9704, F calculated = 0.2488). PID logic controller showed model curves and experimental curves with good fit. F-test two-sample for variances showed no significant difference between model and experimental curves (cassava: F critical = 0.9704, F calculated = 0.1288; maize: F critical = 0.9704, F calculated = 0.2083; sorghum: F critical = 0.9704, F calculated = 0.2016). The study provided an improved approach as solution for optimal pH and temperature conditions in order to mitigate substrate and product inhibitions during ethanol fermentation. It illustrated that the application of artificial intelligence-based controllers provides satisfactory outcomes that are desirable for implementation in the industrial space. Graphical Abstract

K. Segerberg

Paola Cappanera, Marco Gavanelli, Maddalena Nonato et al.

In Answer Set Programming (ASP), the user can define declaratively a problem and solve it with efficient solvers; practical applications of ASP are countless and several constraint problems have been successfully solved with ASP. On the other hand, solution time usually grows in a superlinear way (often, exponential) with respect to the size of the instance, which is impractical for large instances. A widely used approach is to split the optimization problem into sub-problems that are solved in sequence, some committing to the values assigned by others, and reconstructing a valid assignment for the whole problem by juxtaposing the solutions of the single sub-problems. On the one hand this approach is much faster, due to the superlinear behavior; on the other hand, it does not provide any guarantee of optimality: committing to the assignment of one sub-problem can rule out the optimal solution from the search space. In other research areas, Logic-Based Benders Decomposition (LBBD) proved effective; in LBBD, the problem is decomposed into a Master Problem (MP) and one or several Sub-Problems (SP). The solution of the MP is passed to the SPs, that can possibly fail. In case of failure, a no-good is returned to the MP, that is solved again with the addition of the new constraint. The solution process is iterated until a valid solution is obtained for all the sub-problems or the MP is proven infeasible. The obtained solution is provably optimal under very mild conditions. In this paper, we apply for the first time LBBD to ASP, exploiting an application in health care as case study. Experimental results show the effectiveness of the approach. We believe that the availability of LBBD can further increase the practical applicability of ASP technologies.

N. Rescher

Tao Lei, Yanbo Wang, Xianqiu Jin et al.

With the development of high-altitude and long-endurance unmanned aerial vehicles (UAVs), optimization of the coordinated energy dispatch of UAVs’ energy management systems has become a key target in the research of electric UAVs. Several different energy management strategies are proposed herein for improving the overall efficiency and fuel economy of fuel cell/battery hybrid electric power systems (HEPS) of UAVs. A rule-based (RB) energy management strategy is designed as a baseline for comparison with other strategies. An energy management strategy (EMS) based on fuzzy logic (FL) for HEPS is presented. Compared with classical rule-based strategies, the fuzzy logic control has better robustness to power fluctuations in the UAV. However, the proposed FL strategy has an inherent defect: the optimization performances will be determined by the heuristic method and the past experiences of designers to a great extent rather than a specific cost function of the algorithm itself. Thus, the paper puts forward an improved fuzzy logic-based strategy that uses particle swarm optimization (PSO) to track the optimal thresholds of membership functions, and the equivalent hydrogen consumption minimization is considered as the objective function. Using a typical 30 min UAV mission profile, all the proposed EMS were verified by simulations and rapid controller prototype (RCP) experiments. Comprehensive comparisons and analysis are presented by evaluating hydrogen consumption, system efficiency and voltage bus stability. The results show that the PSO-FL algorithm can further improve fuel economy and achieve superior overall dynamic performance when controlling a UAV’s fuel-cell powertrain.

Martin Grohe, Peter Lindner

Probabilistic databases (PDBs) model uncertainty in data in a quantitative way. In the established formal framework, probabilistic (relational) databases are finite probability spaces over relational database instances. This finiteness can clash with intuitive query behavior (Ceylan et al., KR 2016), and with application scenarios that are better modeled by continuous probability distributions (Dalvi et al., CACM 2009). We formally introduced infinite PDBs in (Grohe and Lindner, PODS 2019) with a primary focus on countably infinite spaces. However, an extension beyond countable probability spaces raises nontrivial foundational issues concerned with the measurability of events and queries and ultimately with the question whether queries have a well-defined semantics. We argue that finite point processes are an appropriate model from probability theory for dealing with general probabilistic databases. This allows us to construct suitable (uncountable) probability spaces of database instances in a systematic way. Our main technical results are measurability statements for relational algebra queries as well as aggregate queries and Datalog queries.

Roberto Peña Luna, Gregorio Garza Rodríguez, Liliana Angélica Guerrero Ramos et al.

Organizations consider human capital as one of their most important assets. Experts in the field have focused on the research and development of human talent management skills. At present, companies are giving high importance to the management of this intangible resource. Management by competencies and skills is basic in the selection and development of the most valuable asset the organization has: its human capital. A conceptual framework of the intelligent management of human capital and some more advanced knowledge discovery techniques are presented in this paper. A methodology for smart detection of core competencies based on fuzzy logic predicates and business analytics is proposed. The proposed methodology allows: (1) the evaluation of the importance of competencies, (2) the identification of competencies achievement level of each employee, (3) the identification of competencies with difficulties, (4) the identification of competencies that have influence on others, and (5) a hierarchization of the competencies to select the most appropriated for the employee recruitment plan. Furthermore, an analysis is proposed using knowledge discovery, which allows one to identify which competences have influence on a specific one. All of the above is useful to build an ideal profile for a position. A case study was carried out in order to show the implementation and interpretation of our proposal.

Ivony Hari, Elita Rahmarestya, Harsono Harsono

Smart irrigation system is an automatic irrigation and monitoring system on agricultural land with a sensor, automation, and control technology based on the Internet of Things (IoT). This system can reduce the agricultural activities that were previously performed manually into an automatic system with a reduced human supervision. Smart Irrigation systems that are widely developed used Arduino as the controller. Arduino still lacks in response, low durability, and sensitivity to temperature change, hence requiring frequent maintenance to avoid weather disturbances, insects, and others. This paper presents a development of a smart irrigation system using a Programmable Logic Controller (PLC) as the controller and a soil moisture sensor as a humidity condition measurement tool. The advantage of using PLC as a controller is more stable and has sensor compatibility with higher accuracy. Hence the results are more consistent and accurate. The PLC system is expandable, allowing for the inclusion of more channels for sensors and other measurement instruments. The developed system can collect data on soil moisture conditions, trigger valves, and perform auto irrigation using sprinklers, reducing or even eliminating the need for human intervention. The IoT collects data from sensors and updates the data into a database system, allowing users to monitor the land conditions in real-time. The developed system was predicted to save manpower (20%) and water usage (42.47%) compared to the conventional method.   Keywords: Smart Irrigation; IoT; PLC; Moisture Sensor; Sprinkler

M. Benassi, F. Ambrosini, R. Raggini et al.

Introduction Literature showed that patients suffering from disorders belonging to the schizophrenic (SZ) and bipolar (DB) spectrum have a qualitatively similar but quantitatively different neurocognitive impairment that correlates with the outcomes. However, the majority of former studies are conducted on patients in remission phase. Objectives This study aims to compare cognitive functions between SZ and DB in the acute phase and their possible correlations with treatment outcomes. Methods In a prospective longitudinal study conducted at the SPDC Ausl unit of Romagna - Cesena, 57 SZ and 82 DB took part in the study. The diagnosis was based on the SCID5 CV and SCID5 DP. Symptom severity was assessed with BPRS and HONOS both at the beginning and at the end of hospitalization. Executive functions were measured with Tower of London (ToL) and Modified Wisconsin Card Sorting Test (MCST), attention with Attentive Matrices (MA) and Stroop Test (ST), non-verbal logic skills with Colored Matrices by Raven (PM47). The statistical analyzes applied are ANOVA and logistic regression. Results The cognitive tests did not reveal significant differences between SZ and DB. The logistic regression analysis showed that the scores obtained at the MCST and MA positively correlate with the efficacy of the treatment for both groups. Conclusions Cognition in DB and SZ patients was similarly impaired, supporting recent theories that placed diagnoses on a continuum of severity. Moreover, the results indicated that also in the acute phase the best predictors of the outcome were flexibility in problem solving strategies and visuospatial attention. Disclosure No significant relationships.