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Controlling the spread of infectious diseases in large populations is animportant societal challenge. Mathematically, the problem is best captured as acertain class of reaction-diffusion processes (referred to as contagionprocesses) over appropriate synthesized interaction networks. Agent-basedmodels have been successfully used in the recent past to study such contagionprocesses. We describe EpiSimdemics,...
Cooperative sensing enables secondary users to combine individual sensing results in order to attain sensing accuracies beyond those achieved by consumer RF devices. However, due to sensing costs, secondary users may prefer not to cooperate to the sensing task, leading to higher false alarm probability. In this paper, we study how information about the presence of cooperators affects the dynamics...
The neurocomputational model described here proposes that two dimensions involved in computation of reward prediction errors i.e magnitude and time could be computed separately and later combined unlike traditional reinforcement learning models. The model is built on biological evidences and is able to reproduce various aspects of classical conditioning, namely, the progressive cancellation of the...
Axial compressor systems are predisposed to instability near their optimum operating point. Instabilities include surge or stall, leading to severe consequences to the operational health and integrity of compressor system. The Moore-Greitzer (MG) model has been commonly recognized as a standard when characterizing the dynamics within an axial compressor and is advantageous for the development of a...
We develop an abstract approximation and convergence framework for the estimation of random parameters in infinite dimensional dynamical systems governed by regularly dissipative operators in a Gelfand triple setting. Our results are motivated by a problem involving the development of a data analysis system for a transdermal alcohol biosensor. Our approach combines some recent results for random abstract...
Deep brain stimulation (DBS) is a widespread method of combating tremors associated with Parkinson's disease, but whose mechanisms are not fully understood. One hypothesis, supported experimentally, is that some symptoms of Parkinson's are associated with pathological synchronization of neurons in the basal ganglia. For this reason, there has been interest in recent years in finding efficient ways...
Employing impedance control during manipulation of an object provides a mean to control its dynamic interactions with the environment. This paper presents a decentralized algorithm to achieve a desired multi-dimensional impedance behavior of the object during a collective manipulation without inter-agent communication. The proposed algorithm introduces the concept of “virtual coordination” arising...
The immune evolutionary algorithm (IEA) is a new type of soft algorithm, it is based on the theory of biological immune system and evolved on the basis of evolutionary algorithm. This paper first introduces the theoretical basis of immune evolutionary algorithm, and obtains the general expression of immune evolutionary algorithm. On this basis, the application of immune evolutionary algorithm has...
The planning of maintenance activities can hinder manufacturing operations in term of cost, quality and time, but it is necessary to ensure the availability of the production equipment to meet customer demands. We propose to model the function of maintenance tasks and production operations by the sum of the two costs under a set of constraints. As a method of resolution, we use genetic algorithms...
Markov chains are extensively used in the modeling and analysis of engineering and scientific problems. Usually, paper-and-pencil proofs, simulation or computer algebra software are used to analyze Markovian models. However, these techniques either are not scalable or do not guarantee accurate results, which are vital in safety-critical systems. Probabilistic model checking has been proposed to formally...
SEIR model has been utilized to represent the behavior of various epidemic systems. Several kinds of diseases have been proposed and studied based on this model. The design of the vaccine law or policies to regulate the infection system is one of the important areas of studies. The vaccine policies can be determined based on the knowledge of the nonlinear control theory as seen in literature. The...
A new class of Multi-Objective Evolutionary Algorithms (MOEAs) has emerged recently that uses the concept of decomposition to overcome the challenges faced by the current state-of-the-art MOEAs in undertaking optimization problems with more than three objectives. This new class of MOEAs employs a set of reference points to decompose the objective space into multiple scalar problems and to generate...
Action recognition systems have the potential to support clinicians, coaches and physical therapists in identifying important adopted movement patterns which could aid injury detection potential or inform rehabilitation strategies. Currently, motion capture systems, structured light pattern and time-of-flight sensors have utilization limitations that place constraints on their use outside of the laboratory...
The continuous population growth of Bangkok has been the main cause of numerous pollution issues, including the significant accumulation of municipal solid waste (MSW). This form of waste has currently been underutilized, as little is used for the production of compost fertilizers, while a there exists no implementation of a bioenergy recovery system. In order to fully utilize MSW, long-term planning...
In this paper, we propose a hybrid genetic algorithm to solve assembly line balancing problem type E. There are two objectives to be achieved: Maximizing line efficiency balancing the workstation simultaneously. The model provide more realistic situation of assembly line balancing problem with station restriction and zoning constraints. The genetic algorithm may lack the capability of exploring the...
This paper explores how the semi-analytical solutions have been applied on delayed diffusive food-limited models. The Galerkin technique has been used to determine partial differential equations through ordinary differential equations. Steady-state solutions, limit cycles and Hopf bifurcation points are considered. In addition, comparisons between semi-analytical and numerical results show good agreement...
Several technical and management disciplines are involved with complex system development and product life cycle management. Often they work in isolation leading to inconsistencies in product specifications, information, and challenges in decision-making. Differences across disciplines in their respective practices, techniques, tools, system metrics, and lack of a common platform for exchanging information...
For high speed rolling bearing, the bubble flow calculation model is constructed based upon two-body fluid model and liquid phase turbulent flow model, in which effect of bubble diameter and size of the bubble, and the bubble breakup and coalescence model are considered. The numerical study reveals the relationship between cavitation ratio of bubbles, inlet speed of lubricant, bearing speed and pressure...
The rapid development of information technologies give rise to the big data era. In this age, large amounts of unlabeled software defect metric data at a significantly lower cost is collected. It is how to exploit the unlabeled data to predict software defect has become a hot topic during the past few years. In this paper, a novel method called chaotic and immune spectral clustering (CISC) is proposed...
Transmission losses are of major distress in fossil fuel fired conventional centralized methods of power generation. Distributed generation (DG) decreases the transmission losses as it generates power near the load centers. Maintenance of low reactive power level and a good voltage profile at all buses are big concern now-a-days. In this work, optimal allocation and sizing of DG and reactive power...
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