Exclusion Constraints Research Articles

Monitor-based synthesis in enforcing disjunctive generalised mutual exclusion constraints

This paper focuses on enforcing disjunctive generalised mutual exclusion constraints, referred to as OR-GMEC, on Petri net models. In this case, the legal marking set is non-convex, while the admissible marking set can either be convex or non-convex. The study presents a necessary condition for the existence of a monitor-based solution for a non-convex admissible marking set. Subsequently, the disjunctive constraints are developed to derive an optimal supervisory controller, and an algorithm is proposed for solution computation. The design procedure includes off-line computation mechanisms, yielding an optimal (maximally permissive) supervisor with only a few monitors. The key advantage of the suggested approach is that, unlike the current techniques, the number of monitors in the supervisor’s structure does not rise as the number of constraints increases.

Educational exclusion and socio-cultural constraints for tribal women in the Ganderbal district

Using a phenomenological approach, this study aims at understanding tribal females' educational deprivation due to socio-cultural limitations. The study, conducted in the Ganderbal district of Kashmir in 2022, included 30 women. A semi-structured interview schedule and observation method was used to collect data, which was analyzed with Moustakas' modified Stevick-Colaizzi-Keen phenomenological approach. We identified four themes associated with women's challenges in their communities: (a) poverty, domestic duties, and co-education challenges, (b) cultural and structural barriers, (c) economic exploitation, early marriage, and gender bias and (d) intersection of marginality. Deep-seated cultural norms favoring men's education and relegating women to domestic roles hampered tribal women's access to education. These norms, in turn, resulted in detrimental practices such as child marriage, forced labor, child labor, exclusion from the market, social alienation, exploitation and backwardness, poor decision-making power, and increasing school dropouts. To promote educational inclusion among tribal members, it is necessary to implement National Education Policy (NEP)-2020 fully and make both tribal men and women aware of the impact of socioeconomic and cultural exclusion on their mobility.

Algebraic Control Strategy for Solving the Mutual Exclusion Constraint Problem in a Network of Timed Event Graphs With Disturbance Inputs: Application to an Assembly Process

Algebraic Control Strategy for Solving the Mutual Exclusion Constraint Problem in a Network of Timed Event Graphs With Disturbance Inputs: Application to an Assembly Process

Re-decoupling the classification branch in object detectors for few-class scenes

Few-class object detection is a critical task in numerous scenes, such as autonomous driving and intelligent surveillance. The current researches mainly focus on the correlation or decoupling between classification and regression subtasks in object detection. However, they rarely take advantage of the potential of re-decoupling the classification subtask. In this paper, we propose to re-decouple the classification branch in object detection for few-class scenes by reducing multi-classification features to multiple binary-classification features. Since multi-classification losses cannot supervise the network to learn decoupled binary-classification features, we introduce a single-class loss to supervise decoupled multiple binary-classification branches. In particular, we propose a basic feature degradation head (FD-Head) structure that decouples the classification branches and applies binary-classification loss to encourage each branch to learn only the degraded single-class features. In addition, based on the mutual exclusion between classes, we propose a mutual exclusion constraint (FD-Head-M) module to constrain the scores of all classes, promoting the detector performance. Finally, we replace the original convolution with more powerful feature extraction modules to form the enhanced FD-Head (FD-Head-E). Notably, our method can be used as a universal module and embedded into the existing object detectors to boost their performance. When applying our method to typical object detectors, it experimentally achieves performance gains of 1.2–2.2%, 1.7–2.5% on the KITTI-3, SeaShips datasets respectively. When using ResNet50 as the backbone network, our method gains an accuracy of 45.9% on the MS COCO dataset.

One model to use them all: training a segmentation model with complementary datasets

PurposeUnderstanding surgical scenes is crucial for computer-assisted surgery systems to provide intelligent assistance functionality. One way of achieving this is via scene segmentation using machine learning (ML). However, such ML models require large amounts of annotated training data, containing examples of all relevant object classes, which are rarely available. In this work, we propose a method to combine multiple partially annotated datasets, providing complementary annotations, into one model, enabling better scene segmentation and the use of multiple readily available datasets.MethodsOur method aims to combine available data with complementary labels by leveraging mutual exclusive properties to maximize information. Specifically, we propose to use positive annotations of other classes as negative samples and to exclude background pixels of these binary annotations, as we cannot tell if a positive prediction by the model is correct.ResultsWe evaluate our method by training a DeepLabV3 model on the publicly available Dresden Surgical Anatomy Dataset, which provides multiple subsets of binary segmented anatomical structures. Our approach successfully combines 6 classes into one model, significantly increasing the overall Dice Score by 4.4% compared to an ensemble of models trained on the classes individually. By including information on multiple classes, we were able to reduce the confusion between classes, e.g. a 24% drop for stomach and colon.ConclusionBy leveraging multiple datasets and applying mutual exclusion constraints, we developed a method that improves surgical scene segmentation performance without the need for fully annotated datasets. Our results demonstrate the feasibility of training a model on multiple complementary datasets. This paves the way for future work further alleviating the need for one specialized large, fully segmented dataset but instead the use of already existing datasets.

Control Laws for Partially Observable Min-Plus Systems Networks With Disturbances and Under Mutual Exclusion Constraints

Control Laws for Partially Observable Min-Plus Systems Networks With Disturbances and Under Mutual Exclusion Constraints

Control laws synthesis to satisfy generalized mutual exclusion constraints for timed event graphs networks using min-plus algebra

The paper focuses on the Generalized Mutual Exclusion Constraints (GMECs) problem in the Network of Timed Event Graphs (NTEGs). A new formal method for state feedback control using Min-Plus algebra formalisms is proposed. For this purpose, the dynamic behavior of the NTEGs and GMECs are respectively described by linear equations and weighted inequalities in Min-Plus algebra. Based on these mathematical tools, control laws are computed to satisfy the constraints that are imposed on the NTEGs in case sufficient conditions are verified. The established controllers are represented by monitor places which supervise the system to ensure all GMECs. Finally, a case study of an AGV network is carried out to illustrate theoretical results and demonstrate the efficiency of developed approaches.

A GIS-based method for assessing the economics of utility-scale photovoltaic systems

Solar photovoltaic capacities have experienced remarkable gains worldwide. The accelerated deployment of photovoltaic (PV) systems has emphasized the need for methods and tools that can assist in planning and investment decisions of utility-scale photovoltaic systems to ensure a sustainable energy transition. This study bridges the gap between research and current solar PV project evaluation practices by proposing a geographic information system (GIS)-based approach for analyzing land eligibility and performing techno-economic assessments of utility-scale photovoltaic systems. To tackle the issue of country-specific cost elements, the model incorporates a levelized cost of electricity (LCOE) breakdown often used by governmental and intergovernmental organizations. The proposed GIS-based model can assist in mapping the distribution of eligible land for utility-scale solar systems while considering exclusion constraints, estimating PV capacity and generation potentials, as well as determining the average LCOE of utility-scale solar photovoltaic systems at a spatial resolution of 100 m. The GIS-based approach is demonstrated through the case study of Poland. The model estimates that 3.61% of the total area of Poland is suitable for the installation of utility-scale solar PV systems. Implementing PV installations in these areas would result in solar capacities ranging from 394.64 to 563.77 GW. Furthermore, the findings of the case study indicate that the LCOE would range from €0.043/kWh to €0.049/kWh, with a national average of €0.045/kWh. The proposed approach can be utilized to develop national and regional strategies focused on large-scale PV installations, facilitating the attainment of renewable energy goals. The study fills a significant gap in the literature as it provides a GIS-based tool for planning the sustainable development of utility-scale PV systems at the regional scale. In addition, it is the first to comprehensively assess the capacity and generation potential of utility-scale solar photovoltaics in Poland at the NUTS-2 level.

Topology optimization with geometric constraints for additive manufacturing based on coupled fictitious physical model

The combination of topology optimization and laser powder bed fusion (LPBF), a kind of metal additive manufacturing, has attracted attention because of its ability to manufacture complex optimal structures with metal materials. However, LPBF must satisfy geometric constraints, e.g., overhang constraint and closed cavity exclusion constraint. Several previous studies proposed the fictitious physics model (FPM) to describe and consider these constraints. However, there exists a problem where the objective of the mechanical model (MM) describing physical phenomena conflicts with that of the FPM, resulting in poor convergence. To solve the convergence problem, we propose a coupled fictitious physics model (CFPM) in this paper. In the CFPM, the material constant in the MM is varied in the regions that violate the geometric constraints defined by the FPM such that the objective function of the MM worsens. Then, the objective of the FPM is integrated into that of the MM, potentially improving convergence. This paper formulates the CFPM and performs sensitivity analysis on representative optimization problems considering geometric constraints for LPBF. In addition, we verify through numerical examples whether the CFPM can lead to an optimal structure that satisfies the geometric constraints and can improve convergence. The proposed method to couple the two models can also be applied to topology optimization considering various geometric constraints in other manufacturing requirements.

Multi-camera multi-object tracking: A review of current trends and future advances

The nascent applicability of multi-camera tracking (MCT) in numerous real-world applications makes it a significant computer vision problem. While visual tracking of objects, especially in video obtained from single camera setup, has drawn huge research attention, the constant identification and tracking of targets as they transit across multiple cameras remains an open research problem. In addition to the linking of target appearance and trajectory information across frames, effective association of such data across multiple cameras is also very critical in MCT. Occlusion, appearance variability, camera motion, as well as nonrigid object structure and motion are widely recognized constraints and major sources of concerns in MCT. In recent years, several literatures have been contributed suggesting a variety of approaches to addressing various problems in MCT. However, studies that critically review and report the advances and trends of research in MCT are still limited. This current study presents a comprehensive and up-to-date review of visual object tracking in multi-camera settings. In this paper, we analyze and categorize existing works based on six crucial facets: problem formulation, adopted problem solving approach, data association requirements, mutual exclusion constraints, benchmark datasets, and performance metrics. Furthermore, the study summarizes the outcomes of 30 state-of-the-art MCT algorithms on common datasets to allow quantitative comparison and analysis of their experimental results. Finally, we examine recent advances in MCT and suggest some promising future research directions.

Impact analysis of innovation and gendered constraints in the fisheries sector of southern Ghana

This paper adopts the multinomial endogenous treatment effect approach to analyze the impact of innovation choices on the income of 230 fish workers in the Greater Accra and Central regions of Ghana, while the Kendall’s ranking technique is applied to analyze the constraints to innovation. Findings show that technological and non-technological innovations available to fish workers have positive impacts on their income. Specifically, savings, credit access, and support service are identified to have positive impacts on income while gender and membership of a fish workers’ association have negative impacts on income. The most pressing constraints to innovation faced by female fish workers are cultural/ethnic restrictions, social exclusion, and time constraints. On the other hand, a high dependency ratio and discrimination in access to resources are the most pressing constraints faced by male fish workers. The paper recommends that stakeholders should continue to offer support services to fish workers. In addition, lending institutions should make credit accessible at lower interest rates. Interventions by the Ministry of Fisheries and Aquaculture Development and development agencies that aim to solve constraints of fish workers should be approached from a gender dimension.

Feedback control laws to ensure generalized mutual exclusion constraints in a network of partially observable timed event graphs

This paper deals with the control problem of partially-observable Discrete Event Systems (DESs) which are modelled by Networks of Timed Event Graphs (NTEGs) and subject to Generalized Mutual Exclusion Constraints (GMECs). A new mathematical methodology based on the use of Min-Plus formalisms to synthesize control laws that guarantee the concerned constraints is suggested. For this, the dynamic behavior of the NTEGs is described by linear equations in Min-Plus algebra and the GMECs are represented by weighted inequalities in Min-Plus algebra too. Sufficient conditions are supplied to verify the existence of feedback gains guaranteeing the satisfaction of GMECs. Eventually, to verify the analytical results, it is important to examine a real case study of manufacturing systems.

Suitability and Sustainability Assessment of Existing Onshore Wind Farms in Greece

Site selection for wind farm projects is a vital issue that should be considered in spatial energy planning. This study explores the deployment of onshore wind farms (OWFs) in Greece and assesses their suitability and sustainability using geographic information systems and multicriteria analysis techniques (the analytical hierarchy process—AHP and Technique for Order of Preference by Similarity to Ideal Solution—TOPSIS). Their suitability is assessed in terms of seven exclusion criteria and constraints provided in the Specific Framework for Spatial Planning and Sustainable Development for Renewable Energy Sources (SFSPSD-RES), while their sustainability is assessed in terms of nine environmental, technical-economic, and social assessment criteria in five different scenarios. The obtained results indicated that 81.4% of the existing wind farms are included within suitable areas and the highest percentage of improper siting refers to the installation of wind farms in sites that are within the boundaries of the Natura 2000 protected areas. The existing wind farms located in a part of Peloponnese, at the point bordering the Administrative Region (AR) of Attica, are characterized as more ideal in four out of five of the examined scenarios in the sustainability assessment. The proposed framework of this study is practical and effective in assessing the suitability and sustainability of existing wind farms in a country, and could contribute to spatial energy planning.

Online verification of [formula omitted]-step opacity by Petri nets in centralized and decentralized structures

This paper presents an online approach to deal with the problem of state-based K-step opacity of a discrete event system modeled with labeled Petri nets. The secret states can be described by a set of either markings or generalized mutual exclusion constraints (GMECs), which is more general than the existing approaches in which the secret states are characterized by GMECs only. We formulate an integer linear programming (ILP) model to find a marking outside the set of secret states from each of the K-delayed state estimates, avoiding a complete enumeration of reachability set. Based on the ILP model, an online algorithm is developed to verify K-step opacity of an observation (i.e., an observed sequence). As an extension of K-step opacity, we define the notion of jointK-step opacity in a decentralized structure with two local sites and extend the proposed algorithm to verify the joint K-step opacity of an observation. In addition, the relationship between joint K-step opacity and K-step opacity is formally discussed.

Short-range and long-range correlations in driven dense colloidal mixtures in narrow pores.

The system of a driven dense colloid mixture in a tube with diameter comparable to particle size is modeled by a generalization of the asymmetric simple exclusion process (ASEP) model. The generalization goes in two directions: relaxing the exclusion constraint by allowing several (but few) particles on a site and by considering two species of particles, which differ in size and transport coefficients. We calculate the nearest-neighbor correlations using a variant of the Kirkwood approximation and show by comparison with numerical simulations that the approximation provides quite accurate results. However, for long-range correlations, we show that the Kirkwood approximation is useless, as it predicts exponential decay of the density-density correlation function with distance, while simulation data indicate that the decay is algebraic. For the one-component system, we show that the decay is governed by a power law with universal exponent close to 2. In the two-component system, the correlation function behaves in a more complicated manner: Its sign oscillates but the envelope decays again very slowly and the decay is compatible with a power law with an exponent somewhat lower than 2. Therefore, our generalization of the ASEP belongs to a different universality class from the ensemble of generalized ASEP models which are mappable to zero-range processes.

Critical Observability of Discrete-Event Systems in a Petri Net Framework

This article focuses on the issue of checking critical observability for labeled Petri nets. Critical observability is a property related to the safety concern of cyber-physical systems. With the aim of checking this property of a net system, it is required to detect whether a set of markings consistent with any observed word of the net system is a subset of a set of critical states representing undesirable operations or a set of noncritical states. In this work, we prove a necessary and sufficient condition to check critical observability when the critical state set is described by an arbitrary subset of reachable markings. Then, the result is extended to the case when a critical state set is modeled by all the reachable markings that satisfy disjunctions of generalized mutual exclusion constraints. The proposed method is derived from the solutions of integer linear programming problems and is applicable to net systems with liveness and boundness. Several case studies show the performance of the presented methodology for discrete-event systems.

Energy loss rate of an electron in three-dimensional tilting Dirac semimetals

We have computed the energy loss rate (ELR) of an intruding electron in three-dimensional tilting Dirac semimetals in the light of the excitation process. In contrast to two-dimensional electron gas, ELRs contributed by single-particle excitation (${\mathrm{ELRs}}^{(\mathrm{SP})}$) show a nondecreasing tendency as the incidence velocity increases, and tend to replicate the behavior of the untilt intrinsic ${\mathrm{ELR}}^{(\mathrm{SP})}$, which is described by a cubic polynomial coupling with a logarithm velocity term. In comparison, ELRs contributed by the plasmon excitation (${\mathrm{ELRs}}^{(\mathrm{P})}$) first reach a maximum in the small velocity region followed by a slow discrepancy. As the contribution of plasmon excitation is restricted by the vanishing imaginary part of the dielectric function, the ${\mathrm{ELRs}}^{(\mathrm{P})}$ also manifest as an opposite counterpart to the corresponding ${\mathrm{ELRs}}^{(\mathrm{SP})}$ with different tilts. In addition, the threshold velocities in both ELRs are tilt and chemical potential dependent, and governed by the interplay of the Pauli exclusion constraints and the conservation law concealed in the energy loss function. Finally, we briefly discuss the inelastic mean scattering time. Our results may be verified by investigating the femtosecond electron dynamics in the time-resolved two-photon photoemission.

Rectification in a mixture of active and passive particles subject to a ratchet potential

We study by simulation a mixture of active (run-and-tumble) and passive (Brownian) particles with repulsive exclusion interactions in one dimension, subject to a ratchet (smoothed sawtooth) potential. Such a potential is known to rectify active particles at one-body level, creating a net current in the ‘easy direction’. This is the direction in which one encounters the lower maximum force en route to the top of a potential barrier. The exclusion constraint results in single-file motion, so the mean velocities of active and passive particles are identical; we study the effects of activity level, Brownian diffusivity, particle size, initial sequence of active and passive particles, and active/passive concentration ratio on this mean velocity (i.e. the current per particle). We show that in some parameter regimes the sign of the current is reversed. This happens when the passive particles are at high temperature and so would cross barriers relatively easily, and without rectification, except that they collide with ‘cold’ active ones, which would otherwise be localized near the potential minima. In this case, the reversed current arises because hot passive particles push cold active ones preferentially in the direction with the lower spatial separation between the bottom and top of the barrier. A qualitatively similar mechanism operates in a mixture containing passive particles of two very different temperatures, although there is no quantitative mapping between that case and the systems studied here.

Topology optimization with a closed cavity exclusion constraint for additive manufacturing based on the fictitious physical model approach

This paper proposes a topology optimization method that considers the geometric constraint of no closed cavities to improve the effectiveness of additive manufacturing based on the fictitious physical model approach. First, the basic topology optimization concept and level set-based method are introduced. Next, the fictitious physical model for a geometric constraint in the topology optimization framework is discussed. Then, a model for the geometric constraint of no closed cavities for additive manufacturing is proposed. Numerical examples are provided to validate the proposed model. In addition, topology optimization considering the geometric constraint is formulated, and topology optimization algorithms are constructed using the finite element method. Finally, optimization examples are provided to validate the proposed topology optimization method.

On the Feedback Control for Networks of Partially Observable Timed Event Graphs Subject to Mutual Exclusion Constraints in Dioid Algebra

On the Feedback Control for Networks of Partially Observable Timed Event Graphs Subject to Mutual Exclusion Constraints in Dioid Algebra