Entrainment-enhanced neural oscillator for rhythmic motion control

We propose a new neural oscillator model to attain rhythmic movements of robotic arms that features enhanced entrainment property. It is known that neural oscillator networks could produce rhythmic commands efficiently and robustly under the changing task environment. However, when a quasi-periodic or non-periodic signal is inputted into the neural oscillator, even the most widely used Matsuoka’s neural oscillator (MNO) may not be entrained to the signal. Therefore, most existing neural oscillator models are only applicable to a particular situation, and if they are coupled to the joints of robotic arms, they may not be capable of achieving human-like rhythmic movement. In this paper, we perform simulations of rotating a crank by a two-link planar arm whose joints are coupled to the proposed entrainment-enhanced neural oscillator (EENO). Specifically, we demonstrate the excellence of EENO and compare it with that of MNO by optimizing their parameters based on simulated annealing (SA). In addition, we show an impressive capability of self-adaptation of EENO that enables the planar arm to make adaptive changes from a circular motion into an elliptical motion. To the authors’ knowledge, this study seems to be the first attempt to enable the oscillator-coupled robotic arm to track a desired trajectory interacting with the environment.     

Dynamic frequency and voltage scaling for a multiple-clock-domain microprocessor

Multiple clock domains is one solution to the increasing problem of propagating the clock signal across increasingly larger and faster chips. The ability to independently scale frequency and voltage in each domain creates a powerful means of reducing power dissipation. A multiple clock domain (MCD) microarchitecture, which uses a globally asynchronous, locally synchronous (GALS) clocking style, permits future aggressive frequency increases, maintains a synchronous design methodology, and exploits the trend of making functional blocks more autonomous. In MCD, each processor domain is internally synchronous, but domains operate asynchronously with respect to one another. Designers still apply existing synchronous design techniques to each domain, but global clock skew is no longer a constraint. Moreover, domains can have independent voltage and frequency control, enabling dynamic voltage scaling at the domain level.     

Kernel duration and modulation gain in a coupled oscillator model and their implications on the progression of seizures

The coupled oscillator model has previously been used for the simulation of neuronal activities in in?vitro rat hippocampal slice seizure data and the evaluation of seizure suppression algorithms. Each model unit can be described as either an oscillator which can generate action potential spike trains without inputs, or a threshold-based unit. With the change of only one parameter, each unit can either be an oscillator or a threshold-based spiking unit. This would eliminate the need of a new set of equations for each type of unit. Previous analysis has suggested that long kernel duration and imbalance of inhibitory feedback can cause the system to intermittently transition into and out of ictal activities. The state transitions of seizure-like events were investigated here; specifically, how the system excitability may change when the system underwent transitions in the preictal and postictal processes. Analysis showed that the area of the excitation kernel is positively correlated with the mean firing rate of ictal activity. The kernel duration is also correlated to the amount of ictal activity. The transition into ictal involved the escape from the saddle point foci in the state space trajectory identified using Newton's method.     

Application of the modified frequency formulation to a nonlinear oscillator

He’s frequency formulation is used to obtain the relationship between the frequency and amplitude of a nonlinear oscillator. The general approach is to choose two linear oscillators; in this paper, however, one linear oscillator and the Duffing oscillator are chosen as trial equations. The solution procedure is of utter simplicity, while the result is of high accuracy.     

A feedback oscillator model for circulatory autoregulation

Circulatory autregulation is the phenomenon whereby an isolated organ can maintain a constant or almost-constant blood flow rate over a range of perfusion pressures. A mathematical model is developed, based on work reported in the physiological literature, and tuned to show that autoregulation can be accomplished by pressure-induced oscillations in arteriolar radius. Various features known lo be exhibited by skeletal muscle and by stretch receptors are incorporated in the model of smooth muscle surrounding the arterioles.     

A scaling model for electrowetting-on-dielectric microfluidic actuators

A hydrodynamic scaling model of droplet actuation in an electrowetting-on-dielectric (EWD) actuator is presented that takes into account the effects of contact angle hysteresis, drag from the filler fluid, drag from the solid walls, and change in the actuation force while a droplet traverses a neighboring electrode. Based on this model, the threshold voltage, V _T, for droplet actuation is estimated as a function of the filler medium of a scaled device. It is shown that scaling models of droplet splitting and liquid dispensing all show a similar scaling dependence on [t/ε_r(d/L)]^1/2, where t is insulator thickness and d/L is the aspect ratio of the device. It is also determined that reliable operation of a EWD actuator is possible as long as the device is operated within the limits of the Lippmann–Young equation. The upper limit on applied voltage, V _sat, corresponds to contact-angle saturation. The minimum 3-electrode splitting voltages as a function of aspect ratio d/L < 1 for an oil medium are less than V _sat. However, for an air medium the minimum voltage for 3-electrode droplet splitting exceeds V _sat for d/L ≥ 0.4. EWD actuators were fabricated to operate with droplets down to 35pl. Reasonable scaling results were achieved.

Chirp scaling algorithm for bi-static SAR using a precise range model

Among the currently available chirp scaling algorithms for bi-static SAR, some compromise with approximation in the range model, while some others use the equivalent method by first changing bi-static SAR into mono-static SAR then apply chirp scaling algorithm of mono-static SAR. Consequently, as the squint angles get large, the performance of focusing will deteriorate significantly. This paper, however, abandons those traditional solutions to the bi-static imaging problems and introduces a novel method, based on the space model of bi-static platforms. First, a precise range model is established. Then, a new chirp scaling algorithm for bi-static SAR using the precise range model is advanced. It is theoretically proven that this is an analytic solution of the bi-static chirp scaling algorithm. Images can be focused accurately even with large squint angles. At last simulations with large squint angles are made to verify the validity of the algorithm. Supported by the National Basic Research Program of China     

Self-consistent compensated microfield model for a strongly coupled plasma

A compensated microfield model of plasma nonideality is proposed as an improvement of the traditional microfield models. In this model, a double contribution of a microfield to the truncation of statistical sums removed. The new method of truncation of the statistical sums of atoms or ions is compared with the results of experiments and computations performed by well-known Debye-type and other models. It is shown that only the microfield model correctly describes experiments. Ionization of Li and Hg atoms is calculated. The effect of metallization of plasma—an abrupt increase of ionization from zero to a single ionization at low temperatures and nearly normal densities—is qualitatively described. The results of calculation of Hg vapor ionization qualitatively agree with known experimental results on the measurement of electric conductivity of this vapor.     

Universal scaling functions of a dissipative Manna model

This study uses a losing probability f to measure the magnitude of the bulk dissipation of a dissipative Manna model where P(s;r,L,f), the probability distribution of toppling size s, on a L×(L/r) square lattice is calculated. This approach assumes that the bulk dissipation corresponds to a characteristic length ξ. The finding ξ∼f−ν leads to P(s;r,L,f)=s−τH(s/D[L/Ar],[L/Ar]fν) where H is a two-variable universal scaling function, τ, D, and ν are exponents, and Ar is a nonuniversal metric factor determined by the calculation of moment.     

Bi-level model reduction for coupled problems

In this work a methodology is proposed for the optimization of coupled problems, and applied to a 3D flexible wing. First, a computational fluid dynamics code coupled with a structural model is run to obtain the pressures and displacements for different wing geometries controlled by the design variables. Secondly, the data are reduced by Proper Orthogonal Decomposition (POD), allowing to expand any field as a linear combination of specific modes; finally, a surrogate model based on Moving Least Squares (MLS) is built to express the POD coefficients directly as functions of the design variables. After the validation of this bi-level model reduction strategy, the approximate models are used for the multidisciplinary optimization of the wing. The proposed method leads to a reduction of the weight by 6.6%, and the verification of the solution with the accurate numerical solvers confirms that the solution is feasible.     

Energy measurement,modeling, and prediction for processors with frequency scaling

The energy consumption is an important aspect of today’s processors and a large variety of research approaches deal with reducing the energy consumption for specific application codes on different platforms under certain constraints. These research approaches are based on energy information acquired by very different means, such as hardware settings with power-meters, software methods with hardware counters available for more recent CPUs, or simulations based on theoretical models. In this article, all of these energy acquisition methods are investigated and compared. As application programs, we consider the SPEC CPU2006 integer and floating-point benchmark collections, which represent a large variety of applications from different areas. The investigations are done for single multicore CPUs with the goal to get more insight into their energy consumption behavior. An experimental evaluation is performed on three recent processor types with dynamic voltage–frequency scaling. The article compares the measured energy and the energy provided by hardware counters with the energy predicted by simulation models. The comparison shows that the simulation models are able to capture the energy consumption quite accurately.     

Primal-dual method for the coupled variational model

Total variation method has been widely used in image processing, however, it produces undesirable staircase effect. Recently, the two-step method has been used to alleviate the staircase effect successfully. Combined with a new vector field and an edge indicator function, a novel variational model is proposed in this paper. Unlike the two-step method, the proposed model contains only one energy functional, that is to say, the new vector field and the reconstructed image are interwoven. Due to using the information of the restored image fully, the new vector field is more accurate than the normal vector field, and the reconstructed image is also better than that in the two-step method. To solve the new model, we design a primal-dual method to simulate the minimization problem. The numerical experiments show that the new model can obtain significant improvement not only in noise removal but also in avoiding staircase effect.     

Learning model for coupled neural oscillators.

Neurophysiological experiments have shown that many motor commands in living systems are generated by coupled neural oscillators. To coordinate the oscillators and achieve a desired phase relation with desired frequency, the intrinsic frequencies of component oscillators and coupling strengths between them must be chosen appropriately. In this paper we propose learning models for coupled neural oscillators to acquire the desired intrinsic frequencies and coupling weights based on the instruction of the desired phase pattern or an evaluation function. The abilities of the learning rules were examined by computer simulations including adaptive control of the hopping height of a hopping robot. The proposed learning rule takes a simple form like a Hebbian rule. Studies on such learning models for neural oscillators will aid in the understanding of the learning mechanism of motor commands in living bodies.     

A semantic model for actions and events in ambient intelligence

Event ma nagement and response generation are two essential aspects of systems for ambient intelligence. This work proposes handling these issues through the use of a semantic model for ambient intelligence which, under the umbrella of a philosophical and common-sense optic, describes what actions and events are, how they are connected, and how computational systems should think about their meaning. This model entails an approach with which to both reason about and model context events and generate behavioral responses to those events, when necessary. The model supports this ad hoc response generation by automatically composing services when those which are available do not meet the expected functionality (without requesting user intervention). An evaluation methodology is presented and illustrated with a case scenario, in which synthetic data has been generated to emulate events and analyze the system response. The evaluation of the system response is carried out on the basis of a vector of attributes.     

VMDFS: virtual machine dynamic frequency scaling framework in cloud computing

Development of modern techniques, such as virtualization, underlies new solutions to the problem of reducing energy consumption in cloud computing. However, for the infrastructure as a service providers, it would be a difficult process to guarantee energy saving. Analysis of the workload of applications shows that the average utilization of virtual machines has many fluctuations; therefore, deciding about how to control such fluctuations in virtual machines plays a significant role in improving the energy consumption of datacenters. In this study, an adaptable model called virtual machine dynamic frequency system (VMDFS) has been developed whose its innovation is monitoring the average fluctuations of workloads to vary the CPU frequency of virtual machines at runtime, dynamically. In this model, enhanced exponential moving average method is used to predict workload fluctuations, and then after calculating a smoothing coefficient for the utilization fluctuations, the coefficient is used to control the CPU frequency (or computing power) of virtual machines. The proposed model was compared with several base line approaches such as DVFS using real datasets from CoMon project (PlanetLab). The results of experiments on VMDFS show that besides the reduced service-level agreement violation by up to 43.22%, the overall energy consumption is reduced by 40.16%. In addition, the overall runtime before a host shutdown increased by 17.44% in average, while the runtime before a virtual machine migration increased by 7.2%. This also shows an overall decrease in the number of migrations.     

High performance dynamic voltage/frequency scaling algorithm for real-time dynamic load management

Modern cyber-physical systems assume a complex and dynamic interaction between the real world and the computing system in real-time. In this context, changes in the physical environment trigger changes in the computational load to execute. On the other hand, task migration services offered by networked control systems require also management of dynamic real-time computing load in nodes. In such systems it would be difficult, if not impossible, to analyse off-line all the possible combinations of processor loads. For this reason, it is worthwhile attempting to define new flexible architectures that enable computing systems to adapt to potential changes in the environment.We assume a system composed by three main components: the first one is responsible of the management of the requests arisen when new tasks require to be executed. This management component asks to the second component about the resources available to accept the new tasks. The second component performs a feasibility analysis to determine if the new tasks can be accepted coping with its real-time constraints. A new processor speed is also computed. A third component monitors the execution of tasks applying a fixed priority scheduling policy and additionally controlling the frequency of the processor.This paper focus on the second component providing a “correct” (a task never is accepted if it is not schedulable) and “near-exact” (a task is rarely rejected if it is schedulable) algorithm that can be applicable in practice because its low/medium and predictable computational cost. The algorithm analyses task admission in terms of processor frequency scaling. The paper presents the details of a novel algorithm to analyse tasks admission and processor frequency assignment. Additionally, we perform several simulations to evaluate the comparative performance of the proposed approach. This evaluation is made in terms of energy consumption, task rejection ratios, and real computing costs. The results of simulations show that from the cost, execution predictability, and task acceptance points of view, the proposed algorithm mostly outperforms other constant voltage scaling algorithms.     

An efficient PSP-based model for optimized cross-coupled MOSFETs in voltage controlled oscillator

This paper proposes an efficient PSP-based model for cross-coupled metal-oxide-semiconductor field-effect transistors(MOSFETs) with optimized layout in the voltage controlled oscillator(VCO).The model employs a PSP charge model to characterize the bias-dependent extrinsic capacitance instead of numerical functions with strong non-linearity.The simulation convergence is greatly improved by this method.An original scheme is developed to extract the parameters of the PSP charge model based on S-parameters measurement.The interconnection parasitics of the cross-coupled MOSFETs are modeled based on vector fitting.The model is verified with an LC VCO design,and exhibits excellent convergence during simulation.The results show improvements as high as 60.5% and 61.8% in simulation efficiency and accuracy,respectively,indicating that the proposed model better characterizes optimized cross-coupled MOSFETs in advanced radio frequency(RF) circuit design.     

Topological analysis of a two coupled evolving networks model for business systems

In multi-agent systems, the underlying networks are always dynamic and network topologies are always changing over time. Performance analyses of topologies are important for understanding the robustness of the system and also the effects of topology on the system efficiency and effectiveness. In this paper, we present an example of a real-world distributed agent system, a digital business ecosystem (DBE). It is modelled as a two coupled network system. The upper layer is the business network layer where business process between different business agents happen. The lower layer is the underlying P2P communication layer to support communications between the agents. Algorithms for multi-agent tasks negotiation and execution, interaction between agents and the underlying communication network, evolutionary network topology dynamics, are provided. These algorithms consider the two network layers evolving over time, with effects on each other. Through a comprehensive set of discrete event simulation, we investigate the effects of different evolutionary principles inspired by random graph and scale-free network in complex network theory on the topological properties and performance of the underlying network. We also find several rules to design a resilient and efficient P2P network.     

A fixed-grid model for simulation of a moving body in free surface flows

A two-dimensional computer model is developed to simulate free surface flow interaction with a moving body. The model is based on the cut-cell technique in a fixed-grid system. In this model, a body is approximated by the partial cell treatment (PCT), in which an irregular body is represented by the volumetric fraction of solid in Cartesian cells. The body motion is tracked by Lagrangian method whereas the fluid motion around the body is solved by Eulerian method. The concept of “locally relative stationary (LRS)” is introduced in this study. In the LRS method, a source term is added locally to the conventional continuity equation on body surfaces to take account of body motions, which subsequently affects the computational results of fluid pressure and flow velocity around the body. The LRS method is incorporated into an earlier Reynolds averaged Navier-Stokes (RANS) equations model developed by Lin and Liu [A numerical study of breaking waves in the surf zone. J Fluid Mech 1998;359:239-64]. The new model is capable of simulating generic turbulent free surface flows and their interaction with a moving body or multiple moving bodies. A series of numerical experiments have been conducted to verify the accuracy of the model for simulation of moving body interaction with a free surface flow. These tests include the generation of a solitary wave with the prescribed wave paddle movements, water exit and water impact and entry of a horizontal circular cylinder, fluid sloshing in a horizontally excited tank, and the acceleration/deceleration of an elliptical cylinder near a water surface. Excellent agreements are obtained when numerical results are compared to available analytical, experimental, and other numerical results. The model is a simple-to-implement computational tool for simulating a moving body in turbulent free surface flows.