Mutual Constraints Research Articles

A hybrid game theory and mathematical programming model for solving trans-boundary water conflicts

In this research, a hybrid game theory and mathematical programming model (HGT-MPM) is proposed for solving trans-boundary water conflicts in Guanting reservoir basin (GRB) between two cities (i.e., Zhangjiakou and Beijing) in north China. A water allocation model, which considers both water quality and quantity, is developed for optimizing water use and pollutant discharge in the two cities, maximizing the net aggregate benefits from these activities and reducing the costs for water supply and pollution removal. The initial rights of water use and pollutant discharge are allocated to the cities of Beijing and Zhangjiakou, as two players based on the incorporation of a negotiation method for ill-defined water rights within the watershed. At this stage, equal treatment of every player’s benefit claim can be addressed. The strategy spaces of the two players are delineated through solving the proposed HGT-MPM with mutual benefit claim constraints. The Rubinstein bargaining solution method is employed to identify the equilibrium of bargaining. To achieve maximal benefits for the two players, starting from allocating the results of the second step, the concepts of Core and Nash solutions of cooperative games are used to generate stable basin-wide cooperative solutions. Both players find it beneficial to cooperate with side payment from the downstream to upstream. At this stage, the principle of maximum economic benefits is mainly considered. The results indicate that unclear initial water rights and pollutant discharge rights can be fairly defined through bilateral negotiations between upstream and downstream. Without side payment, the initial water rights and pollutant discharge allocation will be the final outcome, which is suboptimal, although it is better than the status quo in term of both total and individual benefits. Full cooperation with side payment leads to the greatest total net benefits and the greatest benefits to each individual city. The results not only provide a basis to allocate trans-jurisdictional water rights and pollutant discharge rights in an equal and efficient way but also provide certain inspirations for management policy improvement, such as establishing a water right trading system.

A method for parallel scheduling of multi-rate co-simulation on multi-core platforms

The design of cyber-physical systems is a complex process and relies on the simulation of the system behavior before its deployment. Such is the case, for instance, of joint simulation of the different subsystems that constitute a hybrid automotive powertrain. Co-simulation allows system designers to simulate a whole system composed of a number of interconnected subsystem simulators. Traditionally, these subsystems are modeled by experts of different fields using different tools, and then integrated into one tool to perform simulation at the system-level. This results in complex and compute-intensive co-simulations and requires the parallelization of these co-simulations in order to accelerate their execution. The simulators composing a co-simulation are characterized by the rates of data exchange between the simulators, defined by the engineers who set the communication steps. The RCOSIM approach allows the parallelization on multi-core processors of co-simulations using the FMI standard. This approach is based on the exploitation of the co-simulation parallelism where dependent functions perform different computation tasks. In this paper, we extend RCOSIM to handle additional co-simulation requirements. First, we extend the co-simulation to multi-rate, i.e. where simulators are assigned different communication steps. We present graph transformation rules and an algorithm that allow the execution of each simulator at its respective rate while ensuring correct and efficient data exchange between simulators. Second, we present an approach based on acyclic orientation of mixed graphs for handling mutual exclusion constraints between functions that belong to the same simulator due to the non-thread-safe implementation of FMI. We propose an exact algorithm and a heuristic for performing the acyclic orientation. The final stage of the proposed approach consists in scheduling the co-simulation on a multi-core architecture. We propose an algorithm and a heuristic for computing a schedule which minimizes the total execution time of the co-simulation. We evaluate the performance of our proposed approach in terms of the obtained execution speed. By applying our approach on an industrial use case, we obtained a maximum speedup of 2.91 on four cores.

Time-Varying Automated Manufacturing Systems and Their Invariant-Based Control: A Petri Net Approach

As an important branch of production facilities, automated manufacturing systems are a promising perspective of modern factories which become increasingly complex and flexible. From the perspective of development, time variable is a significant concern. In this paper, we propose a class of time-varying systems, Tv-S4R. After involving a global time information loop, it can represent realistic system whose manufacturing process varies with time variables. Event-based control is introduced for serving two important purposes. First, it exerts time-varying specifications on the system, i.e., different processes are executed at different time stages. Second, it prevents the system from reaching any first-met bad marking which will eventually result in deadlocks. We will show that the event-based control can enhance our specifications' expressivity capability compared to their state-based counterparts in terms of generalized mutual exclusion constraints. At last, supervisors are simplified according to the identification of dependence and independence of inequalities. An experimental study illustrates the application of Tv-S4R and the effectiveness of event-based control method.

Privacy-preserving matrix product based static mutual exclusive roles constraints violation detection in interoperable role-based access control

Secure interoperation is an important technology to protect shared data in multi-domain environments. IRBAC (Interoperable Role-based Access Control) 2000 model has been proposed to achieve security interoperation between two or more RBAC administrative domains. Static Separation of Duties (SSoD) is an important security policy in RBAC, but it has not been enforced in the IRBAC 2000 model. As a result, some previous works have studied the problem of SMER (Statically Mutually Exclusive Roles) constraints violation between two RBAC domains in the IRBAC 2000 model. However all of them do not enforce how to preserve privacy of RBAC policies, such as roles, roles hierarchies and user-role assignment while detecting SMER constraints violation, if the two interoperable domains do not want to disclose them each other and to others. In order to enforce privacy-preserving detection of SMER constraints violation, we first introduce a solution without privacy-preserving mechanism using matrix product. Then a privacy-preserving solution is proposed to securely detect SMER constraints violation without disclosing any RBAC policy based on a secure three-party protocol to matrix product computation. By efficiency analysis and experimental results comparison, the secure three-party computation protocol to matrix product based on the Paillier cryptosystem is more efficient and practical.

INDEPENDENT ON-ORBIT GEOMETRIC CALIBRATION OF OPTICAL SATELLITE BASED ON WEIGHTED VIRTUAL OBSERVATION

Abstract. On-orbit geometric calibration is an essential technology to improve the initial geometric accuracy of the optical satellite images. The presented methods usually take the absolute constraint from calibration site data into the imaging model to deduce exact systematic error parameters. However, the characteristic of strong dependence on the high-accuracy calibration site data leads to limitations such as high cost and poor efficiency of these conventional methods. In order to make better use of the mutual constraints among the images, and to get rid of the dependence of calibration site, we conduct an investigation on the on-orbit geometric calibration using the mutual constraints of overlapped images instead of absolute constraint from calibration site for optical satellite. To ensure the stable solution of calibration equation, a weighted virtual observation is introduced into calibration model to improve its condition. The method is verified with a pair of simulated images, and the satisfactory results indicate that the method is effective and reasonable.

Categorizing relational facts from the web with fuzzy rough sets

Significant advances have been made in automatically constructing knowledge bases of relational facts derived from web corpora. These relational facts are linguistic in nature and are represented as ordered pairs of nouns (Winnipeg, Canada) belonging to a category (City_Country). One major problem is that these facts are abundant but mostly unlabeled. Hence, semi-supervised learning approaches have been successful in building knowledge bases where a small number of labeled examples are used as seed (training) instances and a large number of unlabeled instances are learnt in an iterative fashion. In this paper, we propose a novel fuzzy rough set-based semi-supervised learning algorithm (FRL) for categorizing relational facts derived from a given corpus. The proposed FRL algorithm is compared with a tolerance rough set-based learner (TPL) and the coupled pattern learner (CPL). The same ontology derived from a subset of corpus from never ending language learner system was used in all of the experiments. This paper has demonstrated that the proposed FRL outperforms both TPL and CPL in terms of precision. The paper also addresses the concept drift problem by using mutual exclusion constraints. The contributions of this paper are: (i) introduction of a formal fuzzy rough model for relations, (ii) a semi-supervised learning algorithm, (iii) experimental comparison with other machine learning algorithms: TPL and CPL, and (iv) a novel application of fuzzy rough sets.

Cardiophenomenology: a refinement of neurophenomenology

Cardiophenomenology aims at refining the neuro-phenomenological approach created by F. Varela as a new paradigm, jointly based on Husserl’s a priori dynamics of the living present and an experiment on anticipatory time-dynamics of visual motor perception. In order to do so, we will situate the paradigm of neurophenomenology at the cardio-vascular level, focusing on the emotional dynamics of lived experience and thus refining the dialogue, more precisely, the generative mutual constraints between first- and third-person analysis. In this article we present the theoretical hypothesis of cardiophenomenology, which places the bodily-emotional heartsystem at its core, as an intrinsic part of the cognitive system. The latter therefore needs to be enlarged in order to include an enactive embodied cardiac-affective dimension. Here we present five main arguments for the necessary inclusion of the bodily-emotional heartsystem in the cognitive system: first, two pragmatic operational arguments (experiential and methodological), then three theoretical ones (cognitive, homological and ontological-laden). A direct methodological-pragmatic consequence is the actual operativity of the generative mutual constraints based on an experiential (lived)-experimental (organic) continuity of the embodied cardiac-affective fold inherent in the subject.

Liveness-Enforcing Supervision in AMS-Oriented HAMGs: An Approach Based on New Characterization of Siphons Using Petri Nets

In the context of automated manufacturing systems, flexibility and synchronization are two main representative formations. Supervisory control techniques for flexibility have gained increasing attention, but those for synchronization operations have received little notice. Based on their comparison, our work makes threefold contributions. First, we propose a novel characterization of siphons, i.e., type I and type II, based on a special kind of Petri nets, namely, hierarchical augmented marked graphs (HAMGs), which integrate multilevel synchronization into a system. This characterization of siphons is further proved to be a crucial and essential description for both synchronization and flexibility. Second, event circular-wait is proposed to describe the occurrence of deadlocks in HAMGs. Its counterpart is resource circular-wait in flexibility. Ours is a more general and accurate characterization of deadlocks. The liveness of HAMGs can be attributed to the absence of undermarked siphons. Third, a unified liveness-enforcing supervisory control is established based on new characterization of siphons with the aid of generalized mutual exclusion constraints. Supervisor simplification based on inequality analysis is provided for structure simplicity. An experimental study illustrates the correctness of such characterization and the effectiveness of our proposed control method.

Hypothesis Testing Under Mutual Information Privacy Constraints in the High Privacy Regime

Hypothesis testing is a statistical inference framework for determining the true distribution among a set of possible distributions for a given dataset. Privacy restrictions may require the curator of the data or the respondents themselves to share data with the test only after applying a randomizing privacy mechanism. This work considers mutual information (MI) as the privacy metric for measuring leakage. In addition, motivated by the Chernoff-Stein lemma, the relative entropy between pairs of distributions of the output (generated by the privacy mechanism) is chosen as the utility metric. For these metrics, the goal is to find the optimal privacy-utility trade-off (PUT) and the corresponding optimal privacy mechanism for both binary and m-ary hypothesis testing. Focusing on the high privacy regime, Euclidean information-theoretic approximations of the binary and m-ary PUT problems are developed. The solutions for the approximation problems clarify that an MI-based privacy metric preserves the privacy of the source symbols in inverse proportion to their likelihoods.

Coordinate alignment of combined measurement systems using a modified common points method

The co-ordinate metrology has been extensively researched for its outstanding advantages in measurement range and accuracy. The alignment of different measurement systems is usually achieved by integrating local coordinates via common points before measurement. The alignment errors would accumulate and significantly reduce the global accuracy, thus need to be minimized. In this thesis, a modified common points method (MCPM) is proposed to combine different traceable system errors of the cooperating machines, and optimize the global accuracy by introducing mutual geometric constraints. The geometric constraints, obtained by measuring the common points in individual local coordinate systems, provide the possibility to reduce the local measuring uncertainty whereby enhance the global measuring certainty. A simulation system is developed in Matlab to analyze the feature of MCPM using the Monto-Carlo method. An exemplary setup is constructed to verify the feasibility and efficiency of the proposed method associated with laser tracker and indoor iGPS systems. Experimental results show that MCPM could significantly improve the alignment accuracy.

Beyond the evoked/intrinsic neural process dichotomy.

Contemporary functional neuroimaging research has increasingly focused on characterization of intrinsic or “spontaneous” brain activity. Analysis of intrinsic activity is often contrasted with analysis of task-evoked activity that has traditionally been the focus of cognitive neuroscience. But does this evoked/intrinsic dichotomy adequately characterize human brain function? Based on empirical data demonstrating a close functional interdependence between intrinsic and task-evoked activity, we argue that the dichotomy between intrinsic and task-evoked activity as unobserved contributions to brain activity is artificial. We present an alternative picture of brain function in which the brain’s spatiotemporal dynamics do not consist of separable intrinsic and task-evoked components, but reflect the enaction of a system of mutual constraints to move the brain into and out of task-appropriate functional configurations. According to this alternative picture, cognitive neuroscientists are tasked with describing both the temporal trajectory of brain activity patterns across time, and the modulation of this trajectory by task states, without separating this process into intrinsic and task-evoked components. We argue that this alternative picture of brain function is best captured in a novel explanatory framework called enabling constraint. Overall, these insights call for a reconceptualization of functional brain activity, and should drive future methodological and empirical efforts.

Online Fault Diagnosis in Discrete Event Systems with Partially Observed Petri Nets

This paper investigates the fault detection problem for Discrete Event Systems (DES) which can be modeled by Partially Observed Petri Nets (POPN). To overcome the problem of low diagnosability in the POPN online fault diagnoser in current use, we propose an improved online fault diagnosis algorithm that integrates Generalized Mutual Exclusion Constraints (GMEC) and Integer Linear Programming (ILP).We assume that the POPN structure and its initial markings are known, and the faults are modeled as unobservable transitions. First, the event sequence is observed and recorded. We use GMEC for elementary diagnosis of the system behavior,then the ILP problem of POPN is solved for further diagnosis. Finally, we modeled and analyzed an example of a real DES to test the new fault diagnoser. The proposed algorithm increased the diagnosability of the DES remarkably, and the effectiveness of the new algorithm integrating GMEC and ILP was verified.

Online fault diagnosis in partially observed Petri nets

This paper investigates the fault detection problem for discrete event systems (DES) which can be modelled by partially observed Petri nets (POPN). To overcome the problem of low diagnosability in the POPN online fault diagnoser in current use, we propose an improved online fault diagnosis algorithm that integrates generalised mutual exclusion constraints (GMEC) and integer linear programming (ILP). We assume that the POPN structure and its initial markings are known, and the faults are modelled as unobservable transitions. First, the event sequence is observed and recorded. Then, the ILP problem of POPN is solved for elementary diagnosis of the system behaviour. While this system diagnoses that some faults may have happened, we also use GMEC for further diagnosis. Finally, we modelled and analysed an example of a real DES to test the new fault diagnoser. The proposed algorithm increased the diagnosability of the DES remarkably, and the effectiveness of the new algorithm integrating GMEC and ILP was verified.

On the Distinct Effects of Left-Wing and Right-Wing Populism on Democratic Quality

This study examines the differences and commonalities of how populist parties of the left and right relate to democracy. The focus is narrowed to the relationship between these parties and two aspects of democratic quality, minority rights and mutual constraints. Our argument is twofold: first, we contend that populist parties can exert distinct influences on minority rights, depending on whether they are left-wing or right-wing populist parties. Second, by contrast, we propose that the association between populist parties and mutual constraints is a consequence of the populist element and thus, we expect no differences between the left-wing and right-wing parties. We test our expectations against data from 30 European countries between 1990 and 2012. Our empirical findings support the argument for the proposed differences regarding minority rights and, to a lesser extent, the proposed similarities regarding mutual constraints. Therefore we conclude that, when examining the relationship between populism and democracy, populism should not be considered in isolation from its host ideology.

Asset Pricing Implications of Your Mutual Fund Manager's Constraints

By the end of 2015, U.S. mutual funds managed $15 trillion in assets. These funds control about 25% of the equity and 40% of the commercial paper market. As a result, regulations affecting these funds have asset pricing implications. In this paper, we analyze the liquidity management constraint imposed on these funds by the Investment Company Act of 1940. Due to the Act, some funds do not trade illiquid stocks. The non-tradability of these stocks leads to sub-optimal risk sharing. In a competitive equilibrium, we show that this constraint generates the betting against beta phenomenon. Moreover, because of this constraint, alpha is non-zero in general. Adding factors to eliminate alpha is therefore a futile exercise. Lastly, we empirically corroborate the theory by offering an alternate explanation of the distress risk anomaly.

Improved design of online fault diagnoser for partially observed Petri nets with generalized mutual exclusion constraints

Improved design of online fault diagnoser for partially observed Petri nets with generalized mutual exclusion constraints

A revised approach to the energy-water nexus using place-work-folk and energy balance theories of Patrick Geddes

The use of energy to transport, treat, pump, convey, cool, and heat water and the parallel use of water to extract, refine, and use energy is a relationship known as the energy-water nexus. Not only is this relationship growing in importance as population growth and increasing living standards strain both resources, but it also becomes more problematic as energy production moves towards more water intensive practices and water requires increasing more energy to use. Despite a growing awareness of this connection a lack of understanding exists across stakeholders in both fields and a significant need exists for better cross-coordination and planning.Over a century ago urban planner, Sir Patrick Geddes, provided ideas about environmental and civic planning that if employed may improve the mutual constraints between energy and water. Specifically, Geddes’ development of 1) the integrated concept of “place-work-folk” described below, and 2) his suggestion for ranking and promoting societal activities based on their dual importance to society and impact on nature, provide a balanced approach to the energy-water nexus. Representative of his holistic thinking, both ideas recognize the mutual dependence between people and their environment as a relationship necessary for life enhancement and survival of both. This analysis employs a historical review of Geddes’ theories with logical argumentation to illustrate the modern applicability of his planning concepts to just one area of sustainable development with the intent that their potential utility to other domains will become more apparent.

The Entrepreneurial Market Process-An Exposition

The title of this article embraces three implicit, distinct claims: (i) that market phenomena are governed by definite chains of cause and effect, (ii) that these chains of cause and effect constitute and generate a definite process, and (iii) that what drives this systematic process is (not the pattern of mutual constraints which reflect the maximizing decisions of market participants, but) the outside-the-box, “daring,” hunches of entrepreneurs. The first of these three claims are fully consistent with the central thrust of economic science for over two centuries. The second of these claims will require us to clarify what we mean by “process.” The third of these claims challenges, as we shall see, the conventional wisdom of mainstream micro-economic thought of the past century.

Theory of Regions for Control Synthesis without Computing Reachability Graph

This paper addresses the design of Petri net (PN) supervisor using the theory of regions for forbidden state problem with a set of general mutual exclusion constraints. In fact, as any method of supervisory control based on reachability graph, the theory of regions suffers from a technical obstacle in control synthesis, which is the necessity of computing the graph at each iteration step. Moreover, based on the reachability graph, which may contain a large number of states, with respect to the structural size of the system, the computation of PN controllers becomes harder and even impossible. The main contribution of this paper, compared to previous works, is the development of a control synthesis method in order to decrease significantly the computation cost of the PN supervisor. Thus, based on PN properties and mathematical concepts, the proposed methodology provides an optimal PN supervisor for bounded Petri nets following the interpretation of the theory of regions. Finally, case studies are solved by CPLEX software to compare our new control policy with previous works which use the theory of regions for control synthesis.

Scheduling of unit-length jobs with bipartite incompatibility graphs on four uniform machines

Abstract In the paper we consider the problem of scheduling n identical jobs on 4 uniform machines with speeds s1 ≥ s2 ≥ s3 ≥ s4, respectively. Our aim is to find a schedule with a minimum possible length. We assume that jobs are subject to some kind of mutual exclusion constraints modeled by a bipartite incompatibility graph of degree Δ, where two incompatible jobs cannot be processed on the same machine. We show that the general problem is NP-hard even if s1 = s2 = s3. If, however, Δ ≤ 4 and s1 ≥ 12s2, s2 = s3 = s4, then the problem can be solved to optimality in time O(n1.5). The same algorithm returns a solution of value at most 2 times optimal provided that s1 ≥ 2s2. Finally, we study the case s1 ≥ s2 ≥ s3 = s4 and give a 32/15-approximation algorithm running also in O(n1.5) time.