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By simulating the change process of the inventory of scientific papers according to a mathematical model of the publishing process, we find that publication delay would cause statistical error of the scientific paper output indicator, i.e. the quantity of published papers. Based on a simulation model and the average publication delay, we construct an optimization algorithm of the actual scientific paper output using a nonlinear least squares algorithm and validate its accuracy. To simplify the solution process, we propose an approximate algorithm of the actual scientific paper output indicator which would help science and technology managers practically deduce an approximation of the actual indicator. This has implications for strategy decision making and allocation of resources for science and technology research by policy makers. [ABSTRACT FROM AUTHOR]

Oil reservoir history matching is a well-known inverse problem for predicting production by optimizing enormous unknown parameters with numerical simulation. Typically it can be formulated in a Bayesian framework with geological priors. Instead of gradient-based optimization with the possibility of converging to a local minimum, evolutionary algorithms have been introduced to globally find optimal parameters. Due to the high-dimensional parameters, the optimization could become inefficient; therefore, many dimensionality reduction algorithms have been applied in history matching. However, these methods suffer from the linear assumption or the pre-image problem, which could affect the model optimization. In this paper, based on the evolutionary algorithm termed Multi-objective Evolutionary Algorithm Based on Decomposition, which is capable of simultaneously optimizing the parameters with respect to the data of several oil wells, we propose history matching with dimensionality reduction by explicitly utilizing the nonlinear dimensionality reduction model Auto-Encoder to reduce the number of unknown parameters, which can naturally handle the pre-image problem and then improve model performance in terms of precision and complexity. Experimental results based on PUNQ-S3 data verify the efficiency of the newly proposed methods. [ABSTRACT FROM AUTHOR]

Time Petri nets (TPNs) have been widely used for modeling discrete event systems such as manufacturing, supply chain, and military systems. However, TPNs still have many drawbacks in some scenarios where an operation or process is associated with probability, and also lack appropriate simulation algorithms for analyzing different types of systems. In this paper, we address these two issues by proposing a class of extended time Petri nets (ETPNs) and presenting an appropriate simulation algorithm. We illustrate and validate our approach using a hypothetic command and control system, which shows that this approach could be a powerful tool for modeling and analyzing discrete event systems. [ABSTRACT FROM AUTHOR]

This paper considers the problems of unknown input observer (UIO) designs when the so-called observer matching condition (OMC) is not satisfied. Firstly, the system left-invertibility (SLI) concept is investigated in detail and some new criteria are given. Secondly, based on the SLI concept, an augmented output vector formed partly by the original measurable output and partly by the auxiliary output is obtained. By this constructed output vector, the new system is allowed to be transformed into an equivalent linear dynamic system which contains no unknown input, and thus a simple Luenberger observer can be constructed to simultaneously estimate the original states and unknown inputs. Compared with the existing results, the present UIO design can be taken under the single strong detectability condition and the OMC is not needed any more. Finally, the simulations of a single-link flexible joint robotic model and a linearized vertical take-off and landing helicopter model are given to show the effectiveness of our method and its superiority over existing ones. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of maximizing the utilization of operating rooms, which is translated to jobs scheduling in an identical parallel machine environment with sequence-dependent setup times and an objective of minimizing the makespan. The jobs' processing times and setup times are stochastic for better depiction of the real world. This is a non-deterministic polynomial time (NP)-hard problem, and in this paper a new heuristic is developed and compared to existing ones using simulation and optimization. The results and analysis obtained from the computational experiments proved the superiority of the proposed algorithm Longest Expected Processing with Setup Time (LEPST) over the other algorithms presented. [ABSTRACT FROM AUTHOR]

This paper presents a combined finite/discrete element method for 2D/3D modeling of composite specimens subjected to dynamic/impact loadings. Simulation of various composite failure modes, such as delamination and layer cracking, requires a sophisticated numerical approach capable of handling anisotropic behavior of individual layers as well as potential interaction phenomena. The combined finite/discrete element (FE/DE) methodology has proved to be an efficient approach for the simulation of progressive fracture in brittle and quasibrittle media. Therefore, an existing FE/DE approach has been adopted and modified in this study for the simulation of delamination and fracture in composites subjected to impact loadings. The paper comprises a section on fundamental aspects of adopted FE/DE algorithm and discusses the basics of a general node to face nonlinear frictional contact algorithm. It is followed by details of formulation for composite failure mechanisms, including the Hoffman material model and the 3D Hashin interface model. Several numerical simulations are then discussed to assess the performance of the proposed approach. Full progressive fracture and fragmentation behavior as well as potential post-cracking interactions caused by the newly created crack sides and segments are automatically controlled. The same procedure is capable of modeling the application of fiber reinforced polymer (FRP) layers to other engineering structures in order to improve their flexible behavior in static and dynamic loading conditions. [ABSTRACT FROM AUTHOR]

Weld line is aesthetically unpleasant and affects the mechanical strength of injection molded parts. Because of the ever-increasing requirements for parts performance, lots of researchers have performed various studies related to the weld lines optimization. However, research about the computer determination of weld lines in injection molding remains scarce. In this paper, a weld line computer determination method based on filling simulation with surface model is proposed, from which the positions and lengths of the weld lines can be predicted. According to the characteristics of the surface model, all weld lines are classified into two different types. Initial welding node searching and revision algorithms for the two different types of weld lines are first developed. Starting from initial welding nodes, weld lines are then extended by a pre-extension algorithm and an extension algorithm. In the weld line extension algorithm, 135° is set as a welding angle threshold for forming weld lines. Finally, the effects of cavity thickness, process parameters, and mesh densities have been investigated. Moreover, Moldflow simulation results and real parts in production have been conducted to verify the proposed determination method, which demonstrate that the proposed method is correct and effective in actual production. [ABSTRACT FROM PUBLISHER]

This paper presents the dynamic modeling and the stator-voltage-aligned control (SVAC) strategies of the doubly fed induction generator (DFIG)-based wind energy generation system (WEGS). The state-space dynamic model of the DFIG is derived in the synchronous d-q reference frame. The control strategies of the DFIG-based WEGS includes three parts, namely, the network-side converter (NSC) control, the rotor-side converter (RSC) control and the maximum power-point tracking (MPPT) algorithm. The NSC and RSC control algorithms are implemented based on the internal model control principle. The SVAC algorithm is devised for the RSC, where the positions of the stator and rotor voltage-vectors are referenced to the stator-frame to simplify the controller. The hill-climbing method is adopted for the MPPT algorithm, and the iteration procedure for searching the optimal operation point is discussed. The simulation results obtained from the electromagnetic transient program (EMTP-ATP) are provided, which validates the effectiveness of the control algorithms. The theoretical analysis and EMTP-based digital simulation can be widely applied for the grid-connected converters in renewable generation and smart grid applications. [ABSTRACT FROM PUBLISHER]

Automatic extraction of time plane features is extremely important for the diagnosis of cardiac diseases. This paper introduces an effective technique based on a second-generation wavelet transform for the denoising of electrocardiogram (ECG) signals. An improved half-soft threshold based on the lifting wavelet is used to overcome the drawbacks of thresholds applied in the classic wavelet. As ECG signals are corrupted by non-stationary noises, after the threshold point of denoising, Hilbert transform and an improved approximate envelope are applied to the ECG signals to enhance the QRS complexes and suppress unwanted P/T waves and noises. A detection algorithm based on the slope threshold is then used for feature detection. The results of simulation demonstrated that the proposed method allows for the detection of the locations of the R peak, P peak, T peak, start and end of the QRS complex, and premature ventricular contraction. The performance of the algorithm was evaluated against the MIT-BIH Arrhythmia Database, and the numerical results indicated that it could function reliably even under poor signal quality and with long P and T peaks. The R peak detection error rate for tape 105 was only 0.27%. [ABSTRACT FROM PUBLISHER]

Agent-based modeling and simulation play an important role in sociological analysis for complex phenomena. The social communication behaviors can be reproduced by interactive agents, who can behave like human beings. In this paper, we propose a simulation framework of multilayer social networks to model high-resolution interaction between agents. The agent model contains three components: social networks, a demographic-based population and a schedule-based behavior. A common description of multilayer heterogeneous networks is presented. To evaluate the performance of the proposed framework, we reproduce the transmission of influenza H1N1 in an artificial classroom, and compare the simulation results with a real outbreak of influenza H1N1 at one university in Langfang, 2009. The simulation results show high correlation between social networks and the transmission of influenza, and demonstrate that individual-based social network models can well reproduce and analyze complex interacting behavior. Furthermore, experiments under controlled conditions are carried out to analyze the sensitivity of alternative parameters. The framework is able to model high-resolution, social communications from multiple aspects. [ABSTRACT FROM AUTHOR]

Recent collapses of Session Initiation Protocol (SIP) servers indicate that the built-in SIP overload control mechanism cannot mitigate overload effectively. In this paper, we propose a new SIP overload control algorithm by introducing a novel analytical approach to model the dynamic behavior of a SIP network where each server has a finite buffer. Three key breakthroughs of our modeling approach are the formulations of the message loss process, message retransmission process, and the complex departure process through detailed analysis. Our modeling results indicate that retransmissions triggered by the queuing delay are redundant, thus we propose a feedback control mechanism that regulates the retransmission message rate to mitigate the overload. We then demonstrate how to extend our analytical approach to the modeling of our overload control solution. Simulation based on this analytical model runs much faster than event-driven simulation, which needs to track thousands of retransmission timers for outstanding messages and may crash a simulator due to limited computation resources. Performance evaluation demonstrates that: (1) without the control algorithm applied, the overload at a downstream server may propagate to its upstream servers and cause widespread network failure; (2) in the case of short-term overload, our feedback control solution can mitigate the overload effectively without rejecting calls intentionally or reducing network utilization, thus avoiding the disadvantages of existing overload control solutions. In addition, compared with the pushback solution, our retransmission-based solution achieves a better trade-off between the speed to cancel the overload and the call rejection rate when an overload lasts a short period. [ABSTRACT FROM PUBLISHER]

Data Distribution Management (DDM) is one of the High-level Architecture (HLA) services that reduce message traffic over the network. The major purpose of DDM is to filter and route the exchange of data between federates during a federation. However, this traffic reduction usually results in a significant computational overhead, which is caused by calculating the intersection between update regions and subscription regions in a matching process. To reduce the computational overhead for the matching process, this paper proposes a binary partition-based matching algorithm for DDM in a HLA-based distributed simulation. The new matching algorithm is fundamentally based on a divide-and-conquer approach. The proposed algorithm recursively performs binary partitioning that divides the regions into two partitions that entirely cover those regions. This approach promises low computational overhead, since it does not require unnecessary comparisons within regions in different partitions. The experimental results show that the proposed algorithm performs the existing DDM-matching algorithms better and improves the scalability of the DDM. [ABSTRACT FROM PUBLISHER]

In this paper we present the design and implementation of a parallel network simulator to manipulate the shared-memory packet buffer in a network interface card (NIC) for a network terminal. The proposed simulator consists of two components, input generator and buffer management simulator. The simulator flexibly accommodates either a dynamic or a static packet buffer management algorithm for a high-speed Ethernet to deliver fast and accurate clock-cycle level data analysis. In addition, it is transparent to trace and analyze the concurrent operations in the packet buffer and, thus, the simulator contributes to developing efficient buffer management algorithms. [ABSTRACT FROM AUTHOR]

One of the main issues in distributed computing systems is to determine an optimal task-scheduling method. In this paper, we present an effective algorithm to schedule a directed acyclic graph onto a heterogeneous distributed system, called the Earliest Starting and Finishing time Duplication based (ESFD) algorithm. Our proposed algorithm considers all parameters associated with the processors, the task, and its immediate predecessors to perform an effective task allocation. The ESFD algorithm is a three-phase algorithm with a dynamic phase to assign a priority to each task. Simulation results on both random graphs and real application graphs show that the network storage link, speedup, and efficiency generated by ESFD algorithm are better than those generated by the well-known Heterogeneous Critical Parent Trees, Heterogeneous Earliest Finish Time, and Levelized Heavily Communicating Node First algorithms. [ABSTRACT FROM PUBLISHER]

In order to maximize the efficiency of a complex distributed system such as a grid, a proper scheduling algorithm is necessary. The scheduling algorithm is responsible for allocating the available system resources to the existing jobs. In this paper, we consider scheduling gangs in a multi-cluster system in the presence of critical jobs which arrive in a sporadic manner. We examine an adaptive grid scheduler with periodic feedback which allocates the existing jobs to the available clusters. A migration scheme is implemented in order to alleviate the impact of critical sporadic jobs on the performance of gang scheduling. A simulation model is used to provide results on the performance of the system. [ABSTRACT FROM PUBLISHER]

In this paper, we present an extended Kalman filter (EKF)-based estimator for simultaneous localization and mapping (SLAM) with processing requirements that are linear in the number of features in the map. The proposed algorithm, called the Power-SLAM, is based on three key ideas. Firstly, by introducing the Global Map Postponement method, approximations necessary for ensuring linear computational complexity of EKF-based SLAM are delayed over multiple time steps. Then by employing the Power Method, only the most informative of the Kalman vectors, generated during the postponement phase, are retained for updating the covariance matrix. This ensures that the information loss during each approximation epoch is minimized. Next, linear-complexity, rank-2 updates, that minimize the trace of the covariance matrix, are employed to increase the speed of convergence of the estimator. The resulting estimator, in addition to being conservative as compared to the standard EKF, has processing requirements that can be adjusted depending on the availability of computational resources. Lastly, simulation and experimental results are presented that demonstrate the accuracy of the proposed algorithm (Power-SLAM) when compared to the standard EKF-based SLAM with quadratic computational cost and two linear-complexity competing alternatives. [ABSTRACT FROM AUTHOR]

Robots that perform complex manipulation tasks must be able to generate strategies that make and break contact with the object. This requires reasoning in a motion space with a particular multi-modal structure, in which the state contains both a discrete mode (the contact state) and a continuous configuration (the robot and object poses). In this paper we address multi-modal motion planning in the common setting where the state is high-dimensional, and there are a continuous infinity of modes. We present a highly general algorithm, Random-MMP, that repeatedly attempts mode switches sampled at random. A major theoretical result is that Random-MMP is formally reliable and scalable, and its running time depends on certain properties of the multi-modal structure of the problem that are not explicitly dependent on dimensionality. We apply the planner to a manipulation task on the Honda humanoid robot, where the robot is asked to push an object to a desired location on a cluttered table, and the robot is restricted to switch between walking, reaching, and pushing modes. Experiments in simulation and on the real robot demonstrate that Random-MMP solves problem instances that require several carefully chosen pushes in minutes on a PC. [ABSTRACT FROM AUTHOR]

In this paper, an agent-based simulation approach is applied to explore how employee behavior interacts with dynamic tasks. An assessment model for matching between employees and tasks is presented, and two algorithms to allocate tasks to employees are designed: the minimal matching and the greedy matching algorithm. The algorithms are then translated into multi-agent simulation systems, which are programmed in Java based on Repast J 3.0. The simulation experiment results showed that minimal matching is better than greedy matching for rapid task allocation. The former can reduce interface communication cost and effectively promote the use of employee capability. Moreover, with the minimal matching algorithm, the following effects are evident: (1) the different percentage of generalists and specialists have a distinct effect on completion of tasks; (2) the different preference of manager has a rarer impact on the completion of tasks than on the increase of individual capability; (3) the higher rate of individual capability is positively correlated with collaborative learning rate; and (4) the higher rate of individual capability has a marginal, significant effect when the variance of task capability distribution increases and the expectation remains constant. The increase will be significant when the expectation of the task capability requirement increases. The increase of task number has positive impact on the average rate of increase of capability of employees. [ABSTRACT FROM PUBLISHER]

From a modeling and simulation perspective, studying dynamic systems consists of focusing on changes in states. According to the precision of state changes, generic algorithms can be developed to track the activity of sub-systems. This paper aims at describing and applying this more natural and intuitive way to describe and implement dynamic systems. Activity is defined mathematically. A generic application case of diffusion is experimented with to compare the efficiency of quantized state methods using this new approach with traditional methods which do not focus computations on active areas. Our goal is to demonstrate that the concept of activity can estimate the computational effort required by a quantized state method. Specifically, when properly designed, a discrete-event simulator for such a method achieves a reduction in the number of state transitions that more than compensates for the overhead it imposes. [ABSTRACT FROM PUBLISHER]

NeSSi (network security simulator) is a novel network simulation tool which incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Its capabilities such as profile-based automated attack generation, traffic analysis and support for detection algorithm plug-ins allow it to be used for security research and evaluation purposes. NeSSi has been successfully used for testing intrusion detection algorithms, conducting network security analysis and developing overlay security frameworks. NeSSi is built upon the agent framework JIAC, resulting in a distributed and extensible architecture. In this paper, we provide an overview of the NeSSi architecture as well as its distinguishing features and briefly demonstrate its application to current security research projects. [ABSTRACT FROM AUTHOR]

In this paper, we study the behaviour of the slotted Aloha multiple access scheme with a finite number of users under different traffic loads and optimize the retransmission probability qr for various settings, cost objectives and policies. First, we formulate the problem as a parameter optimization problem and use certain efficient smoothed functional algorithms for finding the optimal retransmission probability parameter. Next, we propose two classes of multi-level closed-loop feedback policies (for finding in each case the retransmission probability qr that now depends on the current system state) and apply the above algorithms for finding an optimal policy within each class of policies. While one of the policy classes depends on the number of backlogged nodes in the system, the other depends on the number of time slots since the last successful transmission. The latter policies are more realistic as it is difficult to keep track of the number of backlogged nodes at each instant. We investigate the effect of increasing the number of levels in the feedback policies. We also investigate the effects of using different cost functions (with and without penalization) in our algorithms and the corresponding change in the throughput and delay using these. Both of our algorithms use two-timescale stochastic approximation. One of the algorithms uses one simulation while the other uses two simulations of the system. The two-simulation algorithm is seen to perform better than the other algorithm. Optimal multi-level closed-loop policies are seen to perform better than optimal open-loop policies. The performance further improves when more levels are used in the feedback policies. [ABSTRACT FROM AUTHOR]

In this paper the authors propose a modification to the known force identification procedure based on modal filtration. The modification consists of replacing the modal vectors with the Ritz vectors. The latter seem to be more accurate because they take into account the static deformation of the structure and are less sensitive to truncation error. After the main idea- the algorithm modification- is presented, it is verified and then compared with the original solution. Two sets of data are used for this purpose, firstly simulation data from the numerical model, and then physical data recorded during a laboratory experiment. [ABSTRACT FROM AUTHOR]

Dynamic structure Discrete Event System Specification (DSDEVS) is an advanced modeling formalism that allows DEVS models and their couplings to be dynamically changed. The modeling power and advantages of DSDEVS have been well studied, however, the performance aspect is generally overlooked. This paper provides a comprehensive performance measurement of DSDEVS for a large-scale cellular space model. We consider the modeling and simulation layers for performance analysis, and carry out performance measurement based on a token ring model and a fire spread model. The results show that DS modeling can improve simulation performance for large-scale cellular space models, due to the fact that it makes the simulation focus only on those active models, and thus is more efficient than when the entire cellular space is loaded. On the other hand, the DS overhead cannot be ignored and can become significant and even dominant when a large number of cells are dynamically added/deleted. [ABSTRACT FROM AUTHOR]

This paper describes a new approach for modelling of a distribution transformer and automatic voltage regulator in forward/backward sweep-based algorithms for unbalanced radial distribution systems. For the transformer modelling a symmetrical components model is used and zero sequence voltage and current updating for the sweep-based methods are demonstrated. The validity and effectiveness of the proposed method is demonstrated in a simple two-bus system for grounded wye-delta and delta-grounded wye transformer connections. The automatic voltage regulators (AVRs) are included into the sweep-based methods and tested by using two distribution test systems. From the systems, all results are in agreement, the proposed model is valid and reliable, and the performance of the algorithms is less affected from the inclusion of regulator modelling. [ABSTRACT FROM AUTHOR]

A common problem in statistical modelling is to distinguish between finite mixture distribution and a homogeneous non-mixture distribution. Finite mixture models are widely used in practice and often mixtures of normal densities are indistinguishable from homogenous non-normal densities. This paper illustrates what happens when the EM algorithm for normal mixtures is applied to a distribution that is a homogeneous non-mixture distribution. In particular, a population-based EM algorithm for finite mixtures is introduced and applied directly to density functions instead of sample data. This algorithm is used to find finite mixture approximations to common homogeneous distributions. An example regarding the nature of a placebo response in drug treated depressed subjects is used to illustrate ideas. [ABSTRACT FROM AUTHOR]

In this paper a novel Polar Scan Matching (PSM) approach is described that works in the laser scanner's polar coordinate system, therefore taking advantage of the structure of the laser measurements and eliminating the need for an expensive search for corresponding points in other scan match approaches. PSM belongs to the family of point to point scan matching approaches with its matching bearing association rule. The performance of PSM is thoroughly evaluated in a simulated experiment, in experiments using ground truth, in experiments aimed at determining the area of convergence and in a SLAM experiment. All results are compared to results obtained using an iterated closest point (ICP) scan matching algorithm implementation. It is found that PSM is superior to the ICP implementation in processing speed and that PSM converges to a correct solution from a larger range of initial positions. [ABSTRACT FROM AUTHOR]

Dynamic task allocation is an essential requirement for multi-robot systems operating in unknown dynamic environments. It allows robots to change their behavior in response to environmental changes or actions of other robots in order to improve overall system performance. Emergent coordination algorithms for task allocation that use only local sensing and no direct communication between robots are attractive because they are robust and scalable. However a lack of formal analysis tools makes emergent coordination algorithms difficult to design. In this paper we present a mathematical model of a general dynamic task allocation mechanism. Robots using this mechanism have to choose between two types of tasks, and the goal is to achieve a desired task division in the absence of explicit communication and global knowledge. Robots estimate the state of the environment from repeated local observations and decide which task to choose based on these observations. We model the robots and observations as stochastic processes and study the dynamics of the collective behavior. Specifically, we analyze the effect that the number of observations and the choice of the decision function hove on the performance of the system. The mathematical models are validated in a in multi-robot multi-foraging scenario. The model's predictions agree very closely with results of embodied simulations. [ABSTRACT FROM AUTHOR]

In this paper we propose a vision-based stabilization and output tracking control method for a model helicopter A novel two-camera method is introduced for estimating the full six-degrees-of-freedom pose of the helicopter One of these cameras is located on-board the helicopten and the other camera is located on the ground. Unlike previous work, these two cameras are set to see each other The pose estimation algorithm is compared in simulation to other methods and is shown to be less sensitive to errors on feature detection. In order to build an autonomous helicopter two methods of control are studied: one using a series of mode-based, feedback linearizing controllers and the other using a backstepping-like control law. Various simulations demonstrate the implementation of these controllers. Finally, we present flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter [ABSTRACT FROM AUTHOR]

Actively articulated locomotion systems such as hybrid wheel-legged vehicles are a possible way to enhance the locomotion performance of an autonomous mobile robot. In this paper, we address the control of the wheel-legged robot Hylos traveling on irregular sloping terrain. The redundancy of such a system is used to optimize both the balance of traction forces and the tipover stability. The general formulation of this optimization problem is presented, and a sub- optimal but computationally efficient solution is proposed. Then, an algorithm to control the robot posture, based on a velocity model, is described. Finally, this algorithm is validated through simulations and experiments that show the capabilities of such a redundantly actuated vehicle to enhance its own safety and autonomy in critical environments. [ABSTRACT FROM AUTHOR]

This paper presents a general and efficient formulation applicable to a vast variety of rigid and flexible multibody systems. It is based on a variable-gain error correction with scaling and adaptive control of the convergence parameter. The methodology has the following distinctive features. (i) All types of holonomic and non-holonomic equality constraints as well as a class of inequalities can be treated in a plain and unified manner. (ii) Stability of the constraints is assured. (iii) The formulation has an order N computational cost in terms of both the constrained and unconstrained degrees of freedom, regardless of the system topology. (iv) Unlike the traditional recursive order N algorithms, it is quite amenable to parallel computation. (v) Because virtually no matrix operations are involved, it can be implemented to very simple general-purpose simulation programs. Noting the advantages, the algorithm has been realized as a C++ code supporting distributed processing through the Message-Passing Interface (MPI). Versatility, dynamical validity and efficiency of the approach are demonstrated through numerical studies of several particular systems including a crawler and a flexible space structure. [ABSTRACT FROM AUTHOR]