Integrity Constraints Research Articles

AI-Driven Route Planning and Scheduling for Electric School Buses

This review paper explores the current state, recent advancements, challenges, and future perspectives of AI-driven approaches for route planning and scheduling of Electric School Buses (ESBs). The integration of artificial intelligence into energy management systems for electric vehicles has gained significant attention, particularly in optimizing school transportation. This study examines various AI techniques, including genetic algorithms, reinforcement learning, and game-theoretic approaches, applied to ESB management. Key focus areas include energy consumption estimation, battery capacity optimization, and Vehicle-to-Grid (V2G) strategies. The paper also addresses critical challenges such as data integration, security concerns, and operational constraints. Future perspectives highlight the potential of advanced AI techniques, smart grid integration, and personalized transportation solutions. By synthesizing current research and identifying key areas for future development, this review contributes to ongoing efforts to improve the efficiency, sustainability, and overall quality of school transportation systems through AI technologies.

Construction of a digital twin model for incremental aggregation of multi type load information in hybrid microgrids under integrity constraints

In the multi type load information of hybrid microgrids, data loss or incompleteness may occur due to network congestion, signal interference, equipment failures, and other reasons. Especially with the continuous generation of new load data, gradually incorporating these new data into the existing aggregation process to achieve continuous updating and optimization of load information. Therefore, this article proposes a digital twin model construction method for incremental aggregation of multi type load information in hybrid microgrids under integrity constraints. The Leida criterion and cubic exponential smoothing method are used to preprocess various load data of hybrid microgrids, remove abnormal data, reduce data fluctuations, and make the data more interpretable. Establish integrity constraints for multiple load data of hybrid microgrids and extract load characteristics of hybrid microgrids. Based on these, establish a digital twin model for the incremental aggregation of multiple load information in a hybrid microgrid, and solve the model using an improved K-means algorithm to achieve continuous updating and optimization of load information. The experimental results show that the data sharing delay of this method is 0.12 s, the load is basically consistent with the actual value, and the relative error of the load data is 4%.

Robust Control of Electrical Machines in Renewable Energy Systems: Challenges and Solutions

The increasing global demand for energy driven by population growth necessitates a shift towards renewable energy sources to address sustainability and environmental concerns. Renewable energy sources and how they function in tandem with electrical equipment to generate power are covered extensively in this study. Renewable sources like solar-thermal, hydro, wind, wave, tidal, geothermal, and biomass-thermal utilize electric machines to convert various forms of stored energy into electricity. The paper classifies these machines based on their design and application in renewable systems, highlighting the most common types, including DC, induction, and synchronous machines. It also evaluates their performance according to efficiency, power density, and cost-effectiveness. A primary focus is on the challenges associated with controlling electrical machines in renewable energy systems, including issues related to intermittency, grid integration, nonlinear dynamics, fault tolerance, harmonics, efficiency optimization, thermal management, scalability, real-time control, and cost constraints. The paper concludes by discussing the need for advanced control strategies and solutions to address these challenges, aiming to enhance a reliability, efficiency, and performance of renewable energy systems.

Defence sector and military cooperation between Turkey and the Central Asian Republics: limitations and prospects amidst intensified regional and global rivalry

ABSTRACT Recent Turkey-Central Asian Republic integration attempts are notable. Regular visits, Turkic World summits, economic steps to build a cooperative development bank, defense procurement, and regional policy collaboration have driven this trend. China's Bridge and Road Initiative, NATO's exit from Afghanistan, the Taliban's ascent, and the Russian elite's use of the “Russkiy Mir” after the Russo-Ukrainian War make the “Turkic world” geopolitically vital. Global and regional power struggles will make the region's natural resources and strategic location more important in coming decades. Turkey-Central Asia defense cooperation may also shape the region. This study aims to determine if Turkey-region defense cooperation improves Turkic integration. The states utilize regional military ties and diverse tools for regional and global objectives. The probe will begin with “Turkic integration” and recent Turkish defense industry achievements, then regional defense ties. Finally, a comparative analysis will reveal regional integration constraints and potential, focusing on defense cooperation.

Batch-sizing and machinability data systems for milling operations: An optimal sustainable cost of quality approach

Nowadays, manufacturers make every effort to achieve a higher quality of their products at an attractive cost. With all the introduced legislation and incentives in the developed world to address global warming, machining shops in the West also strive to cut greenhouse emissions. This article offers an optimal approach to the micro Computer-Aided Process Planning (CAPP) problem to optimize the internal quality cost and buffering effect while keeping the environmental impact low. To optimize the machining parameters, the mathematical model is developed for different milling operations, face, side, and peripheral. cutting speed, feed rate, axial depth of cut, radial depth of cut, nose radius, and batch sizing while maximizing profit and meeting customer demand. A Mixed-Integer Nonlinear Programming (MINLP) model is formulated and solved using Classical Constrained Nonlinear Optimization (CCNO) and Genetic Algorithms (GAs). Surface roughness, used as a metric to evaluate the desired quality level of a finished machined part type, is modeled as a Gaussian random variable to model the surface roughness of the machined part utilizing a cumulative normal distribution. The ratio of rework and scrap is calculated in terms of the surface roughness of the machined part shifting away from the target and exceeding upper and lower specification limits. The internal failure cost model, addressing both scrap and rework, is developed based on Taguchi’s quadratic loss function. CCNO is employed to validate the results obtained by GAs, relaxing the lot-sizing integrality constraint and, thus, the convexity of the produced relaxed model. An iterative method employing a developed multi-regression model is used to solve for the expended power consumption (an inherent highly nonlinear environmental criterion of the developed model) within both GAs and CCNO. This study reveals that the machining parameters substantially impact the cost components of the objective function as well as the scrap and rework quantities. A stringent quality cost target can force the model to optimize the feed rate and nose radius to minimize the internal failure quality cost while improving the environmental impact, including direct and indirect power consumption and CO2 emissions considerations.

Mass minimization using the reaction-diffusion level set method by considering local stress constraints in an integral form

Research in topology optimization with stress constraints has shown that defining the stress constraint locally yields better performance compared to global methods. However, an examination of the formulas for local stress constraints reveals a limitation - the constraint is only satisfied at points where it is explicitly defined, failing to guarantee satisfaction across the entire design domain. To address this shortcoming, this paper proposes utilizing an integral form of the stress constraint. The integral formulation theoretically ensures that the stress constraint is satisfied over whole design domain. The objective is to minimize the mass of plane stress structures using reaction-diffusion level set method while incorporating local stress constraints in this integral form. The methodology utilizes finite element approximations for geometry and displacements, defining local stress constraints through an integral formulation. A Lagrangian function combines objective and constraint functions, with sensitivity analysis performed during optimization based on level set function changes. Structural boundaries are updated using the Hamilton-Jacobi equation. The paper presents numerical examples with varying loads and support conditions to demonstrate the effectiveness of this integral stress constraint approach. Results illustrate the capability of the proposed method to generate optimal topologies while satisfying stress constraints across the entire design space.

Some Results on Pursuit Games for an Infinite System of Ternary Differential Equations

This paper aims to study a one-pursuer, one evader pursuit differential game for a higher level of infinite system that is an infinite system of first order ternary differential equations, and prove completion of pursuit in the game. Both integral constraints and geometric constraints are subjected on the players' control functions, thus two separate cases of pursuit games are examined. In the game, the pursuer wants to take the state of the system into the origin of l2 space at some finite time interval, whereas evader avoids this from happening. For every case, we solve the control problem by establishing the admissible control function. In order to achieve the pursuer's objective, we then construct an admissible strategy for the pursuer and develop an equation for the guaranteed pursuit time of the game.

A Multi-Sized Unit Cell Method for the Design of LPBF Lattice Support Structures Concerning Complex Geometries

Abstract Composed of individual unit cells strategically arranged to achieve a desired function, lattices are a promising solution for laser powder bed fusion (LPBF) support structure design in additive manufacturing. Despite their many advantages (e.g., multifunctionality and reduced material cost), prior work in lattice support structure design primarily focuses on horizontal support domains that are not translatable to support domains for complex geometries, thereby limiting their application. This work introduces a multi-sized unit cell design optimization (MSO) method to create lattice support structures (LSS) for parts with complex geometries. The proposed method utilizes voxelization to generate LSS using box-like unit cells of different sizes. It also allows for efficient, high-dimensional design optimization for the types and locations of user-specified unit cells through a modified simulated annealing-based optimization algorithm. The effectiveness and efficiency of the MSO method are demonstrated through the case study of an adapter pipe for a high-temperature heat exchanger. For this demonstration, LSS using multi-sized unit cells are designed to increase heat transfer rate while satisfying structural integrity and material cost constraints. The case study results indicate that the design of the LSS derived from the MSO method fulfills all constraints, including the design constraint of 50% material cost reduction, compared to the solid support structure. In contrast, the lattice support structure designs derived from equal-sized unit cell methods either cannot satisfy all design constraints or have a lower heat transfer rate than the design of the MSO method.

Two-Term Asymptotics of the Exchange Energy of the Electron Gas on Symmetric Polytopes in the High-Density Limit

We derive a two-term asymptotic expansion for the exchange energy of the free electron gas on strictly tessellating polytopes and fundamental domains of lattices in the thermodynamic limit. This expansion comprises a bulk (volume-dependent) term, the celebrated Dirac exchange, and a novel surface correction stemming from a boundary layer and finite-size effects. Furthermore, we derive analogous two-term asymptotic expansions for semi-local density functionals. By matching the coefficients of these asymptotic expansions, we obtain an integral constraint for semi-local approximations of the exchange energy used in density functional theory.

Technological Integration in CRM: A Case Study of Madurai's Hospitality Sector

This study examines the role of technological integration in Customer Relationship Management (CRM) within Madurai's hospitality sector, focusing on how digital tools and software solutions enhance customer engagement and service delivery. As the tourism and hospitality industry in Madurai continues to grow, driven by its cultural significance and heritage, effective CRM practices have become essential for maintaining competitive advantage. This case study investigates how hotels, restaurants, and tour operators in Madurai leverage CRM technologies to streamline operations, personalize guest experiences, and foster long-term relationships. The research analyses the adoption of CRM software, mobile applications, and data analytics in enhancing customer satisfaction, increasing retention rates, and improving operational efficiency. Findings reveal that while the use of technology in CRM has significantly improved service standards and customer interactions, challenges such as system integration, staff training, and cost constraints remain. This study offers insights into the potential of technological CRM solutions to transform the hospitality landscape in Madurai, contributing to both academic literature and practical applications in the tourism and hospitality industries.

Abstract argumentation frameworks with strong and weak constraints

Dealing with controversial information is an important issue in several application contexts. Formal argumentation enables reasoning on arguments for and against a claim to decide on an outcome. Dung's abstract Argumentation Framework (AF) has emerged as a central formalism in argument-based reasoning. Key aspects of the success and popularity of Dung's framework include its simplicity and expressiveness. Integrity constraints help to express domain knowledge in a compact and natural way, thus keeping easy the modeling task even for problems that otherwise would be hard to encode within an AF. In this paper, we first explore two intuitive semantics based on Kleene and Lukasiewicz logics, respectively, for AF augmented with (strong) constraints—the resulting argumentation framework is called Constrained AF (CAF). Then, we propose a new argumentation framework called Weak constrained AF (WAF) that enhances CAF with weak constraints. Intuitively, these constraints can be used to find “optimal” solutions to problems defined through CAF. We provide a detailed complexity analysis of CAF and WAF, showing that strong constraints do not increase the expressive power of AF in most cases, while weak constraints systematically increase the expressive power of CAF (and AF) under several well-known argumentation semantics.

Novel efficient iterative schemes for linear finite element approximations of elliptic optimal control problems with integral constraint on the state

Centering on a distributed optimal control problem governed by elliptic equations with a unilateral integral constraint on the state, we recall the first-order optimality conditions to explore variational formulations. The classical linear finite element method is employed to approximate the equivalent formulae. Taking into account the distinctive structural characteristics of discretized schemes, we divide the discretized optimal conditions into two equivalent matrix schemes. Subsequently, we introduce an efficient iterative algorithm designed to solve the approximation schemes. We demonstrate the convergence of our iterative algorithm and investigate its robustness and uniform optimality under a specified constraint, particularly focusing on small regularization parameters. Finally, numerical tests are conducted using various h and α to illustrate the efficiency of our proposed algorithm. These tests also validate a tremendous reduction in the number of required iterations.

Output-feedback controllers with guaranteed ℒ2-gain for continuous-time Lur'e systems using noncausal Zames–Falb multipliers

This paper focuses on the problem of dynamic output feedback control for continuous-time Lur'e systems with slope-bounded nonlinearities, particularly addressing the closed-loop L 2 gain. The synthesis framework is derived using integral quadratic constraints. The following contributions are highlighted: (i) assessment of stability and L 2 gain through causal, anticausal, and noncausal Zames–Falb multipliers; (ii) technical enhancements to improve efficiency and to reduce the conservativeness of two different classes of multipliers regarding the L 1 norm evaluation; (iii) the synthesis conditions are presented in terms of an iterative procedure based on linear matrix inequalities, allowing arbitrary order for both the controller and the multipliers. The proposed achievements are validated through numerical examples, demonstrating the efficacy and flexibility of the approach compared to existing methods in the literature.

On measuring inconsistency in graph databases with regular path constraints

Real-world data are often inconsistent. Although a substantial amount of research has been done on measuring inconsistency, this research concentrated on knowledge bases formalized in propositional logic. Recently, inconsistency measures have been introduced for relational databases. However, nowadays, real-world information is always more frequently represented by graph-based structures which offer a more intuitive conceptualization than relational ones. In this paper, we explore inconsistency measures for graph databases with regular path constraints, a class of integrity constraints based on a well-known navigational language for graph data. In this context, we define several inconsistency measures dealing with specific elements contributing to inconsistency in graph databases. We also define some rationality postulates that are desirable properties for an inconsistency measure for graph databases. We analyze the compliance of each measure with each postulate and find various degrees of satisfaction; in fact, one of the measures satisfies all the postulates. Finally, we investigate the data and combined complexity of the calculation of all the measures as well as the complexity of deciding whether a measure is lower than, equal to, or greater than a given threshold. It turns out that for a majority of the measures these problems are tractable, while for the other different levels of intractability are exhibited.

A Framework for Constraining Ocean Mixing Rates and Overturning Circulation from Age Tracers

Abstract The age of seawater refers to the amount of time that has elapsed since that water encountered the surface. This age measures the ventilation rate of the ocean, and the spatial distribution of age can be influenced by multiple processes, such as overturning circulation, ocean mixing, and air–sea exchange. In this work, we aim to gain new quantitative insights about how the ocean’s age tracer distribution reflects the strength of the meridional overturning circulation and diapycnal diffusivity. We propose an integral constraint that relates the age tracer flow across an isopycnal surface to the geometry of the surface. With the integral constraint, a relationship between the globally averaged effective diapycnal diffusivity and the meridional overturning strength at an arbitrary density level can be inferred from the age tracer concentration near that level. The theory is tested in a set of idealized single-basin simulations. A key insight from this study is that the age difference between regions of upwelling and downwelling, rather than any single absolute age value, is the best indicator of overturning strength. The framework has also been adapted to estimate the strength of abyssal overturning circulation in the modern North Pacific, and we demonstrate that the age field provides an estimate of the circulation strength consistent with previous studies. This framework could potentially constrain ocean circulation and mixing rates from age-like realistic tracers (e.g., radiocarbon) in both past and present climates. Significance Statement The age of seawater—the local mean time since local water from different pathways was last at the surface—is a valuable indicator of ocean circulation and the transport time scale of heat and carbon. We introduce a novel constraint that relates total age flow across a density surface to its geometry, which provides new insights into constraining ocean circulation and mixing rates from age-like realistic tracers (e.g., radiocarbon).

On the Continuity of the Optimal Time As a Function of the Initial State for Linear Controlled Objects with Integral Constraints on Controls

On the Continuity of the Optimal Time As a Function of the Initial State for Linear Controlled Objects with Integral Constraints on Controls

Next-order correction to the Dirac exchange energy of the free electron gas in the thermodynamic limit and generalized gradient approximations

We derive the next order correction to the Dirac exchange energy for the free electron gas in a box with zero boundary conditions in the thermodynamic limit. The correction is of the order of the surface area of the box, and comes from three different contributions: (i) a real-space boundary layer, (ii) a boundary-condition-induced small shift of Fermi momentum and bulk density, and (iii) a long-range electrostatic finite-size correction. Moreover we show that the local density approximation, in addition to capturing the bulk term exactly, also produces a correction of the correct order but not the correct size. Generalized gradient approximation (GGA) corrections are found to be capable of capturing the surface term exactly, provided the gradient enhancement factor satisfies a simple explicit integral constraint. For current GGAs such as B88 and Perdew, Burke and Ernzerhof we find that the new constraint is not satisfied and the size of the surface correction is overestimated by about ten percent. The new constraint might thus be of interest for the design of future exchange functionals.

Eliciting expert opinion on GIS use for surveillance and disease response in the aquatic animal health domain

Since the 1980s, Geographical Information Systems (GIS) have been integrated into animal farming technologies for purposes such as enhancing production performances and veterinary epidemiology. In aquaculture, however, there seems to be limited application of GIS, and its potential is widely overlooked, especially for aquatic animal health management. This study describes the results of a world expert opinion elicitation on the current implementation of GIS for surveillance and disease response in the aquatic animal health domain. An online survey was submitted in autumn 2023, including both closed and open questions. With a response rate of 41.2% (21 out of 51), the answer analysis highlighted that, especially when knowledge and practical skills in geomatics, information technology and remote sensing are required, a group of advanced GIS technologies is underutilized (web-based solutions, SDI, citizen science). An artificial intelligence-based inductive text analysis was performed confirming a limited exploitation of GIS mainly due to management (financial support, training, collaboration) and methodology (data suitability, modelling analyses and integration) constraints. Furthermore, despite acknowledging the importance of planning in GIS project development, most experts did not follow any written or unwritten procedures that, according to their answers, should in fact encompass sustainable principles (integration of GIS solutions into other applications or processes), and reuse of resources (guidelines and best practices, data, methods, layouts). Shared guidelines for developing GIS projects, identifying available data sources, and long-term-maintenance planning of GIS and related geospatial data, should be pursued for using GIS technologies more effectively in the aquatic animal health domain.

Inferring potential landscapes: A Schrödinger bridge approach to maximum caliber

Schrödinger bridges have emerged as an enabling framework for unveiling the stochastic dynamics of systems based on marginal observations at different points in time. The terminology “bridge” refers to a probability law that suitably interpolates such marginals. The theory plays a pivotal role in a variety of contemporary developments in machine learning, stochastic control, thermodynamics, and biology, to name a few, impacting disciplines such as single-cell genomics, meteorology, and robotics. In this work, we extend Schrödinger's paradigm of bridges to account for integral constraints along paths, in a way akin to maximum caliber—a maximum entropy principle applied in a dynamic context. The maximum caliber principle has proven useful to infer the dynamics of complex systems, e.g., model gene circuits and protein folding. We unify these two problems via a maximum likelihood formulation to reconcile stochastic dynamics with ensemble-path data. A variety of data types can be encompassed, ranging from distribution moments to average currents along paths. The framework enables inference of time-varying potential landscapes that drive the process. The resulting forces can be interpreted as the optimal control that drives the system in a way that abides by specified integral constraints. This, in turn, relates to a similarly constrained optimal mass transport problem in the zero-noise limit. Analogous results are presented in a discrete-time, discrete-space setting and specialized to steady-state dynamics. We finish by illustrating the practical applicability of the framework through paradigmatic examples, such as that of bit erasure or protein folding. In doing so, we highlight the strengths of the proposed framework, namely, the generality of the theory, its elegant analytical structure, the ease of computation, and the ability to interpret results in terms of system dynamics. This is in contrast to maximum caliber problems where the focus is typically on updating a probability law on paths. Published by the American Physical Society 2024

Optimal control of a dengue model with cross-immunity

Mathematical modelling of a dengue epidemic with two serotypes including a temporary cross-immunity yields a nonlinear system consisting of ordinary differential equations (ODEs). We investigate an optimal control problem, where the integral of the infected humans is minimised within a time interval. The controls represent human actions to decrease the number of mosquitos in the model. An integral constraint is added, which takes a limitation on the sum of the human actions into account. On the one hand, we derive and apply a direct approach to solve the optimal control problem. Therein, a discretisation of the controls is constructed using spline interpolation in time. Consequently, a finite-dimensional constrained minimisation problem can be solved. On the other hand, we employ an indirect approach, where necessary conditions for an optimal solution are considered. This technique yields a multipoint boundary value problem of a larger system of ODEs including adjoint equations. We present results of numerical computations, where the two methods are compared.