Performance evaluation of GRNN and ANFIS controlled DVR using machine learning in distribution network

A machine learning based generalized neural network estimator (GRNNE) and Takagi-Sugeno (T-S) fuzzy control system is implemented to accelerate the functional performance indices of dynamic voltage restorer (DVR). The GRNNE predictive model is recommended for the fast estimation of the reference load voltage under the distorted power supply. The fruit fly optimization learning strategy is employed to optimize the weights and smoothing parameters for the extraction of the reference voltage signals as well as unit vectors, resulting in the required sinusoidal load component. The dynamics in the DC-link voltage are optimized by the metaheuristic-based gray wolf optimization algorithm. The coefficients of the adaptive controller are updated automatically to achieve the best fitted adaptive neuro-fuzzy inference system predictive model with the least tracking voltage deviation error even in the presence of voltage disturbances. In comparison to classical techniques, the recommended neural-based approach offers a faster convergence speed with fewer parameters to tune, shorter training time, and lower risks of local entrapment. The performance metrics such as mean square error, root mean square error, mean absolute error, mean absolute percent error, coefficients of correlational and determination (R and R²) are used to evaluate the efficacy of the proposed controller and hence enhance the DVR performance. Finally, the simulation results of the hybrid approach confirm that the NN-based DVR estimator has proven its ability to alleviate voltage sensible issues at critical loads and outperform others in reducing power quality issues.     

Controller design for optimal tracking response in discrete‐time systems

The problem of designing a controller, which results in a closed‐loop system response with optimal time‐domain characteristics, is considered. In the approach presented in this paper, the controller order is fixed (higher than pole‐placement order) and we seek a controller that results in closed‐loop poles at certain desired and pre‐specified locations; while at the same time the output tracks the reference input in an optimal way. The optimality is measured by requiring certain norms on the error sequence—between the reference and output signals—to be minimum. Several norms are used. First, l₂‐norm is used and the optimal solution is computed in one step of calculations. Second, l_∞‐norm (i.e. minimal overshot) is considered and the solution is obtained by solving a constrained affine minimax optimization problem. Third, the l₁‐norm (which corresponds to the integral absolute error‐(IAE)‐criterion) is used and linear programming techniques are utilized to solve the problem. The important case of finite settling time (i.e. deadbeat response) is studied as a special case. Examples that illustrate the different design algorithms and demonstrate their feasibility are presented. Copyright © 2007 John Wiley & Sons, Ltd.     

Surgonomics: the identifier concept. Hospital charges in general surgery and surgical specialties under prospective payment systems.

Surgical care is entering a new payment era for inhospital care using the diagnostic related group (DRG) mechanism for Medicare. A study at The Long Island Jewish-Hillside Medical Center showed that a majority of its surgical DRGs would be unprofitable under the proposed reimbursement scheme. This study was undertaken to develop a method of allowing the hospital to group patients with each DRG that would show a difference in hospital charges and be clinically meaningful to surgeons. The study implementors tested the hypothesis that entities called identifiers, arbitrarily chosen as mode of admission [emergency (+ER vs. nonemergency (-ER)] and presence (+T) or absence (-T) of blood transfusion, would show a difference in charges (mean hospital charge exclusive of physician fees) within a DRG. Nine hundred five patients in nine DRGs encompassing general surgery, thoracic surgery, cardiac surgery, neurosurgery, orthopedics, urology, and head and neck surgery were studied. For ER identifier, eight of nine DRGs were found to be positive (greater than 20% difference in charges between positive and negative identifier); for T identifier, all DRGs (9) were positive. These findings demonstrate that these identifiers may enable teaching institutions to disaggregate each DRG and, in this way, propose more equitable reimbursement rates.     

Creation and Validation of Linkage Between Orthopedic Registry and Administrative Data Using Indirect Identifiers

BackgroundRegistries and administrative databases have unique and complementary strengths in device epidemiologic studies. We sought to develop, validate, and assess a sequential algorithm using indirect identifiers to link registry and administrative data.MethodsHip and knee arthroplasty procedures performed at 6 New York State hospitals enrolled in American Joint Replacement Registry in 2014 were included. After conducting a direct linkage using patient identifiers including name and social security numbers, we validated the methodology of indirect linkage using facility ID, patients’ year and month of birth, sex, and zip code, and procedure date and site (hip/knee). We further evaluated the influence of absent indirect identifier(s) and compromised data quality on linkage success.ResultsUsing our sequential algorithm, 3739 of the 4063 directly linked records (92.03%) were matched with indirect identifiers, with an accuracy of >99.9%. Main reasons for nonmatching included discrepancies in procedure codes and dates. When one of the indirect identifiers was not available, the linkage algorithm still achieved over 90% sensitivity and 99.8% accuracy. Analyses showed that the algorithm was robust when quality of data was moderately compromised.ConclusionThis study demonstrated high sensitivity and accuracy of an algorithm to create linkages between a registry and an administrative database using indirect identifiers. The methodology will enable long-term surveillance and outcome assessment of a wide variety of devices and procedures. Variations in the coding of procedures, availability of indirect identifiers, and their quality have limited impact on this algorithm.     

On the approximate identification of the leading coefficient of a linear elliptic equation by output error and equation error minimization

By definition, the approximate solution to the (finite-dimensional) identification problem is a minimizing element of either cost function. The output error is minimized by two methods: finite difference-discretized gradient (FD-DZG) and finite element—discrete gradient (FE-DG). The equation error is minimized by a DZG method. Two-sided constraints are applied. With reference to an example of polynomial type in a rectangular domain, some tests are carried out in which the role of several parameters, including data noise, is investigated. Most computational results pertaining to the output error are interpreted according to: (a) sensitivity analysis; (b) an error estimate, which compares FD-DZG to FD-DG; and (c) a dynamical system model of the algorithm. An optimal uniform initial value of the unknown coefficient is found which yields a computed solution very close to the reference solution, regardless of domain discretization and output error minimization method. The superior noise immunity of FE-DG over FD-DZG is demonstrated. The results obtained from equation error minimization are less satisfactory.     

Optimal spatial field control for controlled release

Most distributed parameter control problems involve manipulation within the spatial domain. Such problems arise in a variety of applications including epidemiology, tissue engineering, and cancer treatment. This paper proposes an approach to solve a state‐constrained spatial field control problem that is motivated by a biomedical application. In particular, the considered manipulation over a spatial field is described by partial differential equations (PDEs) with spatial frequency constraints. The proposed optimization algorithm for tracking a reference spatial field combines three‐dimensional Fourier series, which are truncated to satisfy the spatial frequency constraints, with exploitation of structural characteristics of the PDEs. The computational efficiency and performance of the optimization algorithm are demonstrated in a numerical example. In the example, the spatial tracking error is shown to be almost entirely due to the limitation on the spatial frequency of the manipulated field. The numerical results suggest that the proposed optimal control approach has promise for controlling the release of macromolecules in tissue engineering applications.     

基于标记点形成实时动态耳廓三维影像导板的实验研究

目的设计一种基于标记点的实时动态耳廓三维影像导板,并对其进行评价。方法以1个商品化人头模型以及2019年8月于中国医学科学院整形外科医院招募的3名志愿者为研究对象,其中男性2名,女性1名,年龄24~27岁。运用ITK-SNAP 3.6.0和MeshLab软件(V 2016.12.23) 对3名志愿者的头颅CT图像进行三维重建,获得虚拟耳廓三维模型。通过人头模型论证标记点放置的最佳数量为3个,最佳位置为眉角、鼻尖及耳垂下点,利用这3个标记点将虚拟耳廓三维模型与对应的真实耳廓进行关联注册,通过投影仪将虚拟耳廓三维影像投射至对应的真实耳廓,红外线动态捕捉仪捕捉标记点位置变化对投射图像进行实时跟踪,通过计算注册后的重合误差率、跟踪过程中的重合误差率、投射图像变形率和追踪延迟度,评价实时动态耳廓三维影像导板的注册精准度、跟踪精准度、投射图像变形度及跟踪延迟度。结果注册后平均重合误差率为2.5%(正常人双侧耳廓大小差距为2.7%);在顺时针旋转30°内跟踪平均重合误差率小于2.7%;在顺时针旋转30°与逆时针15°范围内投射图像变形率小于2.6%,一定旋转角度范围内平均重合误差率和投射图像变形率小于2.7%,说明一定旋转角度范围内跟踪精准度高,投射图像变形度小,跟踪延迟时间均小于0.1 s,满足手术需求。结论成功构建了基于标记点的实时动态耳廓三维影像导板,其注册精准度高、跟踪精准度高、投射图像变形度小、跟踪速度快,为将来其应用于临床耳廓再造术打下基础。     

Mechanotransduction and functional response of the skeleton to physical stress: The mechanisms and mechanics of bone adaptation

The skeleton's primary mechanical function is to provide rigid levers for muscles to act against as they hold the body upright in defiance of gravity. Many bones are exposed to thousands of repetitive loads each day. During growth and development, the skeleton optimizes its architecture by subtle adaptations to these mechanical loads. The mechanisms for adaptation involve a multistep process of cellular mechanotransduction including: mechanocoupling— conversion of mechanical forces into local mechanical signals, such as fluid shear stresses, that initiate a response by bone cells; biochemical coupling— transduction of a mechanical signal to a biochemical response involving pathways within the cell membrane and cytoskeleton; cell-to-cell signaling from the sensor cells (probably osteocytes and bone lining cells) to effector cells (osteoblasts or osteoclasts) using prostaglandins and nitric oxide as signaling molecules; and effector response— either bone formation or resorption to cause appropriate architectural changes. These architectural changes tend to adjust and improve the bone structure to its prevailing mechanical environment. Structural changes can be predicted, to some extent, by mathematical formulas derived from three fundamental rules: (1) bone adaptation is driven by dynamic, rather than static, loading; (2) extending the loading duration has a diminishing effect on further bone adaptation; (3) bone cells accommodate to a mechanical loading environment, making them less responsive to routine or customary loading signals. Received for publication on Dec. 25, 1997; accepted on Feb. 24, 1998     

Symmetric Energy-Conserved Splitting FDTD Scheme for the Maxwell's Equations

In this paper, a new symmetric energy-conserved splitting FDTD scheme (symmetric EC-S-FDTD) for Maxwell's equations is proposed. The new algorithm inherits the same properties of our previous EC-S-FDTDI and EC-S-FDTDII algorithms: energy-conservation, unconditional stability and computational efficiency. It keeps the same computational complexity as the EC-S-FDTDI scheme and is of second-order accuracy in both time and space as the EC-S-FDTDII scheme. The convergence and error estimate of the symmetric EC-S-FDTD scheme are proved rigorously by the energy method and are confirmed by numerical experiments.     

A Posteriori Error Estimate of Weak Galerkin FEM for Stokes Problem Using Auxiliary Subspace Techniques

Based on the auxiliary subspace techniques, a posteriori error estimator of nonconforming weak Galerkin finite element method (WGFEM) for Stokes problem in two and three dimensions is presented. Without saturation assumption, we prove that the WGFEM approximation error is bounded by the error estimator up to an oscillation term. The computational cost of the approximation and the error problems is considered in terms of size and sparsity of the system matrix. To reduce the computational cost of the error problem, an equivalent error problem is constructed by using diagonalization techniques, which needs to solve only two diagonal linear algebraic systems corresponding to the degree of freedom $(d.o.f)$ to get the error estimator. Numerical experiments are provided to demonstrate the effectiveness and robustness of the a posteriori error estimator.     

Investment portfolio tracking using model predictive control

The composition of an investment portfolio aiming to increase the financial returns while reducing the exposure to risk is a topic of growing interest in the world. In this direction, we propose a model predictive control (MPC) strategy in order to optimize the investment portfolio selection taking into account the tracking of a reference portfolio with desired return. In addition, an analysis comparing different sizes of the prediction horizon according to VPH-MPC (Varying Predictive Horizon-MPC) and FPH-MPC (Fixed Predictive Horizon-MPC) algorithms is conducted. Finally, we propose an optimal control problem using the tracking error as a function of loss of CVaR (Conditional Value at Risk) measurement. Numerical experiments are run based on Brazilian Stock Exchange data. The experimental results are compared with the Markowitz portfolio optimization model, a conventional tracking strategy, and benchmarks from the Brazilian financial market. This comparison indicates a good tracking performance obtained by the proposed MPC in the two versions while satisfying the constraints.     

Basic measurement concepts

Sensors are transducers that convert physical phenomena into electrical signals. The relationship between input and output signals is affected by sensor characteristics (transfer function, dynamic range, sensitivity, resolution, dynamic range, signal-to-noise ratio) and dynamic response (frequency response, lag time, resonance and damping). Systematic and random errors may affect the accuracy and precision of the measurement. Systematic errors may be compensated for by the process of one-point, two-point or more calibration. The conversion of a continuous analogue signal into a digital signal will result in an approximation of the analogue signal, and quantization error may occur.     

Symptoms of Posttraumatic Stress Disorder are Associated with Exaggerated Neural Response to Surprising Errors

Posttraumatic stress disorder (PTSD) is characterized by exaggerated salience of previously innocuous cues and associated with hyperactivity of salience‐related brain regions. Recently, computational models have been deployed to operationalize salience more precisely regarding surprise‐driven learning, leading to findings that such learning is altered in anxiety‐related disorders. In the present study, a sample of 20 combat veterans completed a probabilistic learning task during fMRI scanning. We applied a computational model to generate a trial‐by‐trial surprise signal (i.e., unsigned prediction error or difference between the expected probability of an outcome and the actual observed outcome), which allowed us to examine the neural response to surprising events. We did not observe an association between PTSD symptoms and behavioral indices of learning in the task. Surprising errors were associated with increased activity in the left precuneus/inferior parietal lobule and right inferior parietal lobule, two parietal regions that are linked to salience processing. Additionally, PTSD symptom severity was positively associated with precuneus/inferior parietal lobule activation to surprising errors, r = .63, p = .004. Taken together, this pattern of results suggests that PTSD symptoms are specifically associated with an exaggerated response to surprising errors in salience‐related regions of the brain. This altered pattern of neural activity could represent a target for intervention to improve PTSD symptoms.     

Multipurpose controller design in multivariable stochastic control systems

The paper presents a computer-aided procedure for multipurpose controller design which in multivariable (linearized) stochastic systems simultaneously ensures (1) complete dynamic decoupling of control loops, (2) arbitrary closed-loop pole placement and internal stability of the control system, (3) steady state output rejection of non-zero mean values of disturbances as well as zero steady state regulation and/or tracking errors, (4) reduction of amplitude modulation of the control signals and (5) optimal steady state estimation of the plant's state and output vectors. The polynomial matrix approach in the frequency s-domain is used to solve the stochastic control problem. Numerical results and simulations for a simplified version of a ship-positioning control system design are presented to illustrate characteristics of the problem.     

Experimental investigation of Harris Hawk optimization-based maximum power point tracking algorithm for photovoltaic system under partial shading conditions

An integrated quasi Z-source DC–DC converter (qZSC) along with Harris Hawk Optimization (HHO)-based maximum power point tracking (MPPT) algorithm is proposed in this paper to increase the efficiency of photovoltaic (PV) system. The qZSC-based PV system experiences more voltage and current stress during partial shading conditions (PSCs), which causes overheat on qZSC components hence, degrade the efficiency and reliability of the system. Conventional swarm intelligence-based MPPT algorithms track the G_MPP during PSC, but these take longer convergence time and fail to settle at G_MPP. This uncertainty of finding the G_MPP leads to fluctuations at output of qZSC, hence more stress on the converter components. HHO in tracking the G_mpp eliminates premature local MPPs, enhances convergence speed by expanding the search space for finding the G_MPP. The proposed system is developed in MATLAB/Simulink environment and verified the results by developing prototype model in the laboratory by using C2000™ Piccolo™ Launch Pad™, LAUNCHXL-F28027 controller. The tracking performance of the proposed HHO-based MPPT algorithm is tested under fast changing and PSCs in comparison with perturb & observe (P&O), particle swarm optimization (PSO), and artificial bee colony (ABC)-based MPPT algorithms. The simulation and experimental results show that the proposed HHO-based MPPT algorithm is robust, tracks maximum power point in minimum convergence time in comparison with P&O, PSO and ABC-based MPPT algorithms. Hence, voltage and current fluctuations at the output of qZSC are reduced. Therefore, voltages and current stress on qZSC components are reduced and the efficiency of the system is improved.     

Human auditory cortical dynamics during perception of long acoustic sequences: phase tracking of carrier frequency by the auditory steady-state response

We recorded human auditory cortical activity during the perception of long, changing acoustic signals and analyzed information provided by dynamic neural population measures over a large range of time intervals (approximately 24 ms-5 s). Participants listened to musical scales that were amplitude modulated at a rate of 41.5 Hz, generating an ongoing, stimulus-related oscillatory brain signal, the auditory steady-state response (aSSR). The aSSR generated energy at the amplitude modulation rate that was recorded using magnetoencephalography. As in previous work, the timing (phase) of this response varied with stimulus carrier frequency over the entire course of minute-long tone sequences ('phase tracking' of carrier frequency). The length of the time interval over which phase was calculated was systematically varied; significant phase tracking was regularly observed at analysis intervals of <50 ms in length. The right auditory cortex exhibited better phase tracking performance than the left at analysis intervals of 24-240 ms, and frequency dependent phase delays were consistently larger than those predicted by cochlear mechanics. Based on these empirical data, a model of the neural populations responsible for phase tracking suggests that it is produced by a subpopulation ( approximately 25%) of the cells generating the aSSR.     

Correlating motor performance with surgical error in laparoscopic cholecystectomy

Background Analysis of motor performance in minimally invasive surgery (MIS) is a new field with applications in surgical training, surgical simulators, and robotics. Force/torque and derivatives of tool tip position (velocity, acceleration, and jerk) are examples of measures of motor performance (MMPs). Few studies have measured MMPs or have correlated MMPs with surgical performance during MIS on humans. The objectives of this study were to determine the feasibility of a novel multimodal system to quantify MMPs in laparoscopic cholecystectomy and to attempt to correlate MMPs with the magnitude of error as a measure of surgical performance. Methods Novice and expert surgeons performed laparoscopic cholecystectomies in two groups of three patients each. MMPs were obtained using a combination of optical and electromagnetic tool tip tracking and a force/torque sensor on a modified Maryland dissector. Error scores for laparoscopic cholecystectomy were calculated using a previously validated system. Novice and expert measurements were compared, and correlations were made between error scores and MMPs. Results Error scores were similar between novices and experts. Novice surgeons had a significantly greater mean velocity (566 ± 83 vs 85 ± 32 mm/s, p = 0.006) and acceleration (2,600 ± 760 vs 440 ± 174 mm/s², p = 0.050) compared to expert surgeons. Force (16.5 ± 4.6 vs 18.3 ± 6.0 N, p = 0.829), position (121 ± 25 vs 135 ± 72 mm, p = 0.863), and jerk (19,600 ± 7,410 vs 2,430 ± 367 mm/s³, p = 0.138) were similar between groups. A positive correlation was found in novice surgeons between error score and jerk (Pearson correlation, 0.999; p = 0.035). Conclusions It is feasible to quantify MMPs in laparoscopic cholecystectomy. Novice and expert surgeons can be differentiated by MMPs; moreover, there may be a positive correlation between jerk and error score in novice surgeons.