A new approach for time effect analysis of settlement for single pile based on virtual soil-pile model

A new approach is proposed to analyze the settlement behavior for single pile embedded in layered soils. Firstly, soil layers surrounding pile shaft are simulated by using distributed Voigt model, and finite soil layers under the pile end are assumed to be virtual soil-pile whose cross-section area is the same as that of the pile shaft. Then, by means of Laplace transform and impedance function transfer method to solve the static equilibrium equation of pile, the analytical solution of the displacement impedance fimction at the pile head is derived. Furthermore, the analytical solution of the settlement at the head of single pile is theoretically derived by virtue of convolution theorem. Based on these solutions, the influences of parameters of soil-pile system on the settlement behavior for single pile are analyzed. Also, comparison of the load-settlement response for two well-instrumented field tests in multilayered soils is given to demonstrate the effectiveness and accuracy of the proposed approach. It can be noted that the presented solution can be used to calculate the settlement of single pile for the preliminary design of pile foundation.

Real-Time Timing Channel Detection in a Software-Defined Networking Virtual Environment

Despite extensive research, timing channels (TCs) are still known as a principal category of threats that aim to leak and transmit information by perturbing the timing or ordering of events. Existing TC detection approaches use either signature-based approaches to detect known TCs or anomaly-based approach by modeling the legitimate network traffic in order to detect unknown TCs. Un-fortunately, in a software-defined networking (SDN) environment, most existing TC detection approaches would fail due to factors such as volatile network traffic, imprecise timekeeping mechanisms, and dynamic network topology. Furthermore, stealthy TCs can be designed to mimic the legitimate traffic pattern and thus evade anomalous TC detection. In this paper, we overcome the above challenges by presenting a novel framework that harnesses the advantages of elastic re-sources in the cloud. In particular, our framework dynamically configures SDN to enable/disable differential analysis against outbound network flows of different virtual machines (VMs). Our framework is tightly coupled with a new metric that first decomposes the timing data of network flows into a number of using the discrete wavelet-based multi-resolution transform (DWMT). It then applies the Kullback-Leibler divergence (KLD) to measure the variance among flow pairs. The appealing feature of our approach is that, compared with the existing anomaly detection approaches, it can detect most existing and some new stealthy TCs without legitimate traffic for modeling, even with the presence of noise and imprecise timekeeping mechanism in an SDN virtual environment. We implement our framework as a prototype system, OBSERVER, which can be dynamically deployed in an SDN environment. Empirical evaluation shows that our approach can efficiently detect TCs with a higher detection rate, lower latency, and negligible performance overhead compared to existing approaches.

Consensus-Based Distributed Control with Communication Time Delays for Virtual Synchronous Generators in Isolate Microgrid

A consensus-based distributed control method of coordinated VSGs with communication time delays in isolate microgrid is proposed. When time delays are considered in communication, there are some effects on frequency restoration and active power output allocation. In the control structure, only local information exchange is needed, while the final frequency can be controlled to the nominal value and the VSGs can automatically share loads according to their rated values. An AC microgrid with three VSGs and some loads is implemented. The proposed control strategy is verified by MATLAB/ Simulink simulation results.

LabVIEW-based auto-timing counts virtual instrument system with ORTEC 974 Counter/Timer

In order to achieve the auto-timing counts measurement of nuclear radiation using ORTEC 974 Counter/Timer, an auto-timing counts virtual instrument system based on the LabVIEW virtual instrument development platform and GPIB instrument control and transmission bus protocol is designed in this paper. By introducing software timing technique, the minimum time base of factory setting improves from 0.1 s to 0.03 s. The timing counts performance and longtime stability are also discussed in detail. The automatic data recording and saving facilitates data analysis and processing. Its real-time display and statistic function is very convenient for monitoring the nuclear radiation.

VIRTUAL WAITING TIMES IN PRIORITY-M/G/1 QUEUES WITH VACARIONS

In this paper exhaustive-service priority-M/G/1 queueing systems with multiple vacations, single vacation and setup times are studied under the nonpreemptive and preemptive resume priority disciplines. For each of the six models analysed, the Laplace-Stieltjes transform of the virtual waiting time Wk(t) at time t of class k is derived by the method of collective marks. A sufficient condition for , where U has the standard normal distribution, is also given.

Real-time virtual sonography visualization and its clinical application in biliopancreatic disease

AIM:To evaluate the usefulness of real-time virtual sonography(RVS)in biliary and pancreatic diseases.METHODS:This study included 15 patients with biliary and pancreatic diseases.RVS can be used to observe an ultrasound image in real time by merging the ultrasound image with a multiplanar reconstruction computed tomography(CT)image,using pre-scanned CT volume data.The ultrasound used was EUB-8500with a convex probe EUP-C514.The RVS images were evaluated based on 3 levels,namely,excellent,good and poor,by the displacement in position.RESULTS:By combining the objectivity of CT with free scanning using RVS,it was possible to easily interpret the relationship between lesions and the surrounding organs as well as the position of vascular structures.The resulting evaluation levels of the RVS images were12 excellent(pancreatic cancer,bile duct cancer,cholecystolithiasis and cholangiocellular carcinoma)and 3 good(pancreatic cancer and gallbladder cancer).Compared with conventional B-mode ultrasonography and CT,RVS images achieved a rate of 80%superior visualization and 20%better visualization.CONCLUSION:RVS has potential usefulness in objective visualization and diagnosis in the field of biliary and pancreatic diseases.

A State-of-the-Art Survey on Real-Time Issues in Embedded Systems Virtualization

Virtualization has gained great acceptance in the server and cloud computing arena. In recent years, it has also been widely applied to real-time embedded systems with stringent timing constraints. We present a comprehensive survey on real-time issues in virtualization for embedded systems, covering popular virtualization systems including KVM, Xen, L4 and others.

Optimizing Real-Time Performance of 3D Virtual Mining Environment with MultiGen Creator

System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a virtual mining system were discussed: optimizing 3D models to keep the polygon number in VR system within target hardware's processing ability; optimizing texture database to save texture memory with perfect visual effect; optimizing database hierarchy structure to accelerate model retrieval; and optimizing LOD hierarchy structure to speed up rendering.

Pilot Placement for Time-Varying MIMO OFDM Channels with Virtual Subcarriers

The rapid time-variation of a fading multipath environment can impair the performance of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO OFDM). This paper proposes a pilot placement method for MIMO OFDM systems under time-varying channels with the guard band. The time-varying channel is described by complex exponential basis expansion model (BEM). We discuss the least square (LS) channel estimation to obtain the minimum mean square error (MSE) and derive the pilot allocation that can satisfy the minimum MSE with regard to guard band in time-varying channels. It is shown that optimal pilot clusters can distribute non-uniformly in frequency domain and minimize the MSE. We generalize our scheme over G OFDM symbols and compare it with comb pilots. It is demonstrated that the proposed approach is more effective than previous work. Simulation results validate our theoretical analysis.

Joint decision-making of virtual module formation and scheduling considering queuing time

Formation and scheduling are the most important decisions in the virtual modular manufacturing system;however,the global performance optimization of the system may be sacrificed via the superposition of two independent decision-making results.The joint decision of formation and scheduling is very important for system design.Complex and discrete manufacturing enterprises such as shipbuilding and aerospace often comprise multiple tasks,processes,and parallel machines,resulting in complex routes.The queuing time of parts in front of machines may account for 90%of the production cycle time.This study established a weighted allocation model of a formation-scheduling joint decision problem considering queuing time in system.To solve this nondeterministic polynomial(NP)problem,an adaptive differential evolution-simulated annealing(ADE-SA)algorithm is proposed.Compared with the standard differential evolution(DE)algorithm,the adaptive mutation factor overcomes the disadvantage that the scale of DE’s differential vector is difficult to control.The selection strategy of the SA algorithm compensates for the deficiency that DE’s greedy strategy may fall into a local optimal solution.The comparison results of four algorithms of a series of random examples demonstrate that the overall performance of ADE-SA is superior to the genetic algorithm,and average iteration,maximum completion time,and move time are 24%,11%,and 7%lower than the average of other three algorithms,respectively.The method can generate the joint decision-making scheme with better overall performance,and effectively identify production bottlenecks through quantitative analysis of queuing time.

A Study of Discrete-Time Optimum Current Controller for the Virtual Synchronous Generator under Constraints

In recent years, power generation using renewable energy sources has been increasing as a solution to the global warning problem. Wind power generation can generate electricity day and night, and it is relatively more efficient among the renewable energy sources. The penetration level of variable-speed wind turbines continues to increase. The interconnected wind turbines, however, have no inertia and no synchronous power. Such devices can have a serious impact on the transient stability of the power grid system. One solution to stabilize such grid with renewable energy sources is to provide emulated inertia and synchronizing power. We have proposed an optimal design method of current control for virtual synchronous generators. This paper proposes an optimal control method that can follow the virtual generator model under constrains. As a result, it is shown that the proposed system can suppress the peak of the output of semiconductor device under instantaneous output voltage drop.

Convolutional neural networks for time series classification

Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging problem due to the nature of time series data: high dimensionality, large in data size and updating continuously. The deep learning techniques are explored to improve the performance of traditional feature-based approaches. Specifically, a novel convolutional neural network (CNN) framework is proposed for time series classification. Different from other feature-based classification approaches, CNN can discover and extract the suitable internal structure to generate deep features of the input time series automatically by using convolution and pooling operations. Two groups of experiments are conducted on simulated data sets and eight groups of experiments are conducted on real-world data sets from different application domains. The final experimental results show that the proposed method outperforms state-of-the-art methods for time series classification in terms of the classification accuracy and noise tolerance. © 1990-2011 Beijing Institute of Aerospace Information.

Study on generalized magneto-thermoelastic problems by FEM in time domain

This paper presents an investigation of temperature, displacement, stress, and induced magnetic field in a half space perfectly-conductive plate. Finite element equations regarding generalized magneto-thermoelasticity problems with two relaxation times （i.e., the G-L theory） are derived using the principle of virtual work. For avoiding numerical complication involved in inverse Laplace and Fourier transformation and low precision thereof, the equations are solved directly in time-domain. As a numerical example, the derived equation is used to investigate the generalized magneto-thermoelastic behavior of a semi-infinite plate under magnetic field and subjecting to a thermal shock loading. The results demonstrate that FEM can faithfully predict the deformation of the plate and the induced magnetic field, and most importantly can reveal the sophisticated second sound effect of heat conduction in two-dimensional generalized thermoelastic solids, which is usually difficult to model by routine transformation methods. A peak can be observed in the distribution of stress and induced front and the magnitude of magnetic field at the heat wave the peak decreases with time, which can not be obtained by transformation methods. The new method can also be used to study generalized piezo-thermoelastic problems.

Value of virtual bronchoscopic navigation and transbronchial ultrasound-guided sheath-guided exploration in diagnosis of peripheral lung cancer

BACKGROUND Peripheral lung cancer poses a substantial harm to human health,and it is easy to become exacerbated,potentially threatening the life and safety of patients AIM To assess the value of virtual bronchoscopic navigation(VBN)combined with transbronchial ultrasound-guided sheath-guided(EBUS-GS)exploration in the diagnosis of peripheral lung cancer.METHODS A total of 236 patients with peripheral lung cancer(nodule diameter range,8-30 mm;diagnosed using high-resolution computed tomography)were selected from three centers between October 2018 and December 2019.Patients who underwent EBUS-GS exploration alone were included in a control group,and those who received VBN in combination with EBUS-GS exploration were included in an observation group.The diagnostic rate and total operating time of differentsubgroups of the two groups were compared,and the time needed to determine the lesion was recorded.RESULTS There were no significant differences in diagnosis rate or total operation time between the two groups(P>0.05),and the time needed to determine the lesion in the observation group was less than that of the control group(P<0.05).CONCLUSION The combined use of VBN and EBUS-GS exploration technology has little effect on the diagnosis rate and total operation time of peripheral lung cancer,but it significantly shortens the time needed to determine the lesion and is a valuable diagnostic method.

A Remote Real-Time Monitoring System for Power Quality

An introduction is made to the composition, design method and engineering application of a remote real time monitoring system of power quality in substations based on internet. With virtual instrument and network technique adopted, this system is characterized by good real time property, high reliability, plentiful functions, and so on. It also can be used to monitor the load of a substation, such as electric locomotives.

Systematic design method for PI controller with Virtual Resistor-based Active Damping of LCL filter

The Virtual Resistor based Active Damping(VR-AD) is widely employed in converters connected to the grid via LCL filters in order to mitigate the inherent resonance of the filters. Nevertheless, in digitally controlled systems, the PWM and the calculating delays modify the system characteristics in terms of frequency and phase, thus destabilizing the system and degrading the VR-AD performances, mainly in low switching frequencies. Moreover, the stability of the system is greatly affected under weak grid operation characterized by large grid impedance variation. This paper solves these problems by proposing a systematic, robust and optimized design procedure of voltage oriented PI control(VOC) with VRAD. The considered design procedure ensures robust control(sufficient stability margins) and high quality of grid current(reduced steady-state error and minimized THD value) despite the negative impact of digital time delay, grid impedance variation and filter parameters change. Simulation and experimental results are presented to show robustness and efficiency of the suggested design procedure.

Neural Network and GBSM Based Time-Varying and Stochastic Channel Modeling for 5G Millimeter Wave Communications

In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall.

DEVELOPMENT OF VIRTUAL INSTRUMENT IN CHARACTERISTIC ANALYSIS OF ROTATING MACHINERY BASED ON INSTANTANEOUS FREQUENCY ESTIMATION

Based on the recently quick-developing time-frequency analysis (TFA)technique and virtual instrument (VI) technique, a virtual instrument in characteristic analysis ofrotating machinery is researched and developed successfully. By utilizing instantaneous frequencyestimation (IFE) theoretics of TFA technique, and based on IFE of peak searching on thetime-frequency spectrum, order analysis (OA) functions is put forward and implemented, such as orderspectrum, order spectrum matrix, order tracking, order tracking filtering, and order componentextraction, etc. Unlike the home and abroad existing popular characteristic analyzers, which needkey phasing devices such as shaft encoder, phase-locked loop (PLL), phase-locked multiple frequency,tachometer, etc, to implement constant angle sampling directly or indirectly, whereas thisinstrument only uses the vibration signal of rotating machinery to carry out OA. This instrumentmakes up the shortage of these traditional instruments in analyzing the non-stationary signal ofrun-up and run-down process of rotating machinery. Therefore, it is a great breakthrough for theexisting order analyzers.

Analysis and Comparison of Time Replica and Time Linear Interpolation for Pilot Aided Channel Estimation in OFDM Systems

This paper analyzes and compares two time interpolators, i.e., time replica and time linear interpolator, for pilot aided channel estimation in orthogonal frequency division multiplexing (OFDM) systems. The mean square error (MSE) of two interpolators is theoretically derived for the general case. The equally spaced pilot arrangement is proposed as a special platform for these two time interpolators. Based on this proposed platform, the MSE of two time interpolators at the virtual pilot tones is derived analytically;moreover, the MSE of per channel estimator at the entire OFDM symbol based on per time interpolator is also derived. The effectiveness of the theoretical analysis is demonstrated by numerical simulation in both the time-invariant frequency-selective channel and the time varying frequency-selective channel.

Test re-test reliability of virtual acoustic space identification (VASI) test in young adults with normal hearing

Background:Recent developments in virtual acoustic technology has levered promising applications in the field of auditory sciences,especially in spatial perception.While conventional auditory spatial assessment using loudspeakers,interaural differences and/or questionnaires are limited by the availability and cost of instruments,the use of virtual acoustic space identification(VASI)test has widespread applications in spatial test battery as it overcomes these constraints.Purpose:The lack of test-retest reliability data of VASI test narrows its direct application in auditory spatial assessment,which is explored in the present study.Methods:Data from 75 normal-hearing young adults(mean age:25.11 y±4.65 SD)was collected in three sessions:baseline,within 15 min of baseline(intra-session),and one week after baseline session(inter-session).Test-retest reliability was assessed using the intra-class correlation coefficient(ICC),coefficient of variation(CV),and cluster plots.Results:The results showed excellent reliability for both accuracy and reaction time measures of VASI,with ICC values of 0.93 and 0.87,respectively.The CV values for overall VASI accuracy and reaction time 9.66% and 11.88%,respectively.This was also complemented by the cluster plot analyses,which showed 93.33% and 96.00% of temporal stability in the accuracy and reaction time measures,indicative of high test-retest reliability of VASI test in auditory spatial assessment.Conclusions:The high temporal stability(test-retest reliability)of VASI test validates its application in spatial hearing test battery.