Discrete Implementation Research Articles

Practical PID controller implementation for the speed control of a motor generator system

Windup effect in a PID controller is the condition of cumulative error in the integral action. It saturates the system actuators, letting the system out of control with a higher controller action. Putting a saturator for the controller action, it is limited into a linear range of operating values. However, it does not eliminate the cumulative error of the integral term. This paper presents the speed control of a motor generator system using a digital PID controller with antiwindup scheme to eliminate the cumulative error of the integral term of controller action. Initially, a linear model of the motor generator system was identified. From the linear model of the system, a PID controller was designed using pole placement technique. Controller discrete implementation was perform using the backward difference discretization methodology. PID controller consider the antiwindup scheme. PID controller practical implementation employed Matlab Stateflow and a data acquisition card. Obtained results showed that discrete implementation of the PID controller has a good performance against external disturbances and random noise.

Fractional quaternion cosine transform and its application in color image copy-move forgery detection

In this paper, fractional quaternion cosine transforms (FrQCT) is proposed to generalize the conventional fractional cosine transforms (FrCT) to quaternion signal processing in a holistic manner. Firstly, the new transform FrQCT is defined and the proof of its inverse transform is presented. An efficient discrete implementation method of FrQCT is then proposed, in which the relationship between FrQCT and FrCT of four components is used for a quaternion signal. Finally, a new color image copy-move forgery detection algorithm based on FrQCT and modified PatchMatch matching algorithm is proposed to evaluate the performance of the proposed FrQCT. Experimental results on two public datasets (FAU dataset and GRIP dataset) demonstrate that: (a) the proposed efficient implementation method takes only half the computational time of the direct method; (b) the proposed FrQCT-based forgery detection algorithm can achieve a better performance than some state-of-the-art algorithms, especially in the additional operation case.

Performance and robustness of discrete and finite time average consensus algorithms

ABSTRACTIn this paper, we review some of the main discrete and finite time average consensus implementations in the literature, discussing their strengths and shortcomings from a theoretical and empirical point of view. In particular, we compare the computational characteristics of the different algorithms, their behaviour considering different underlying network topologies, their ability to withstand packet losses and their robustness to attacks where a malicious node aims to steer the result of the algorithm towards a desired value, without letting the other nodes detect the attack. Specifically, we will discuss synchronous approaches, where the nodes broadcast their messages, and asynchronous approaches, where the nodes need to be able to address their neighbours individually on a point-to-point basis (i.e. by direct communication between a specific sender and a specific receiver). With the aim to overcome some critical aspects of the considered methodologies, in this paper we present an asynchronous consensus algorithm based on a broadcast-only approach. The algorithm is characterised by a good trade-off between the robustness of synchronous approaches and to low computational demands of asynchronous methods.

PLC-based Discrete Fractional-order Control Design for an Industrial-Oriented Water Tank Volume System with Input Delay

Abstract We present PLC-based fractional-order controller design for an industrial-oriented water tank volume control application. The system comprises input delay which is a typified characteristic in such industrial process control applications. The particular contribution of this work is on discrete fractional-order PID implementation via PLC and its application to the aforementioned realistic water tank test bed. Stability and robustness properties of fractional-order discrete PID feedback-loops for different approximation methods and orders are also shown. Fractional-order controllers are obtained for a variety of stability margin choices, and benefits of the non-integer-order controllers compared to the integer-order PID control are illustrated via simulation and experimental runs on a realistic test-bed.

Discretization and OpenCL-based implementation of social field pedestrian model

Abstract A discretization is applied to the continuous field-based pedestrian model to derive a discrete version. The concept of walk period is introduced so that pedestrians’ varied walking velocities can be studied without introducing any modification to the underlying logic. This further allows the discrete model to analyze a flow of randomly mixed population. Next, starting from the discrete model, a high performance GPU model targeting at the OpenCL heterogeneous parallel framework is developed. Advanced techniques are developed to allow efficient access to stored field strength, avoid atomic operations, and so on. Numerical experiments disclose that the GPU model can bring a as high as 30.8x performance improvement, with contrast to the previously developed CPU model. Thus, when equipped with proper functional modules such as a macroscopic/mesoscopic route selection and so on, the GPU model can act as a core engine for simulation of a large/very-large population.

Complex multiple risk intervention to promote healthy behaviours in people between 45 to 75\xa0years attended in primary health care (EIRA study): study protocol for a hybrid trial

BackgroundHealth promotion is a key process of current health systems. Primary Health Care (PHC) is the ideal setting for health promotion but multifaceted barriers make its integration difficult in the usual care. The majority of the adult population engages two or more risk behaviours, that is why a multiple intervention might be more effective and efficient. The primary objectives are to evaluate the effectiveness, the cost-effectiveness and an implementation strategy of a complex multiple risk intervention to promote healthy behaviours in people between 45 to 75 years attended in PHC.MethodsThis study is a cluster randomised controlled hybrid type 2 trial with two parallel groups comparing a complex multiple risk behaviour intervention with usual care. It will be carried out in 26 PHC centres in Spain. The study focuses on people between 45 and 75 years who carry out two or more of the following unhealthy behaviours: tobacco use, low adherence to the Mediterranean dietary pattern or insufficient physical activity level. The intervention is based on the Transtheoretical Model and it will be made by physicians and nurses in the routine care of PHC practices according to the conceptual framework of the “5A’s”. It will have a maximum duration of 12 months and it will be carried out to three different levels (individual, group and community). Incremental cost per quality-adjusted life year gained measured by the tariffs of the EuroQol-5D questionnaire will be estimated. The implementation strategy is based on the “Consolidated Framework for Implementation Research”, a set of discrete implementation strategies and an evaluation framework.DiscussionEIRA study will determine the effectiveness and cost-effectiveness of a complex multiple risk intervention and will provide a better understanding of implementation processes of health promotion interventions in PHC setting. It may contribute to increase knowledge about the individual and structural barriers that affect implementation of these interventions and to quantify the contextual factors that moderate the effectiveness of implementation.Trial registrationClinicalTrials.gov, NCT03136211.Retrospectively registered on May 2, 2017.

An optimized two-level discrete wavelet implementation using residue number system

Using discrete wavelet transform (DWT) in high-speed signal processing applications imposes a high degree of caution to hardware resource availability, latency and power consumption. In this paper, we investigated the design and implementation aspects of a multiplier-free two-level DWT by using residue number system (RNS). The proposed two-level takes the advantage of performing the multiplication operations using only the memory without involving special multiplier units, which preserves valuable resources for other critical tasks within the FPGA. The design was implemented and synthesized in ZYNQ ZC706 development kit, taking advantage of embedded block RAMs (BRAMs). The results of the overall experimentations showed that there is a considerable improve in the proposed two-level DWT design with regard to latency and peak signal-to-noise ratio (PSNR) precision value in the final output.

Glauber dynamics of 2D Kac–Blume–Capel model and their stochastic PDE limits

We study the Glauber dynamics of a two dimensional Blume–Capel model (or dilute Ising model) with Kac potential parametrized by (β,θ) – the “inverse temperature” and the “chemical potential”. We prove that the locally averaged spin field rescales to the solution of the dynamical Φ4 equation near a curve in the (β,θ) plane and to the solution of the dynamical Φ6 equation near one point on this curve. Our proof relies on a discrete implementation of Da Prato–Debussche method [13] as in [33] but an additional coupling argument is needed to show convergence of the linearized dynamics.

Discrete Linear Canonical Transform Based on Hyperdifferential Operators

Linear canonical transforms (LCTs) are of importance in many areas of science and engineering with many applications. Therefore a satisfactory discrete implementation is of considerable interest. Although there are methods that link the samples of the input signal to the samples of the linear canonical transformed output signal, no widely-accepted definition of the discrete LCT has been established. We introduce a new approach to defining the discrete linear canonical transform (DLCT) by employing operator theory. Operators are abstract entities that can have both continuous and discrete concrete manifestations. Generating the continuous and discrete manifestations of LCTs from the same abstract operator framework allows us to define the continuous and discrete transforms in a structurally analogous manner. By utilizing hyperdifferential operators, we obtain a DLCT matrix which is totally compatible with the theory of the discrete Fourier transform (DFT) and its dual and circulant structure, which makes further analytical manipulations and progress possible. The proposed DLCT is to the continuous LCT, what the DFT is to the continuous Fourier transform (FT). The DLCT of the signal is obtained simply by multiplying the vector holding the samples of the input signal by the DLCT matrix.

A discrete element implementation for concrete: particle generation, contact calculations, packing under gravity and modeling material response

A three-dimensional discrete element modelling capability for concrete based on rigid particles of arbitrary shape and size has been developed. The novel particle generation algorithm allows control of particle size, angularity and flakiness. General rigid body kinematics including finite rotations is accounted for, and an explicit time integration algorithm that conserves energy and momentum is implemented. An efficient contact algorithm with several features to increase the efficiency of the contact computations has been developed. This enables the gravity packing problem for arbitrary shaped particles to be solved in reasonable run time. The proposed procedure is used to generate assemblies of concrete specimens of various sizes that are homogeneous and isotropic in the bulk, and can capture the wall effect due to the formwork. The calibrated specimens are seen to be capable of accurately capturing experimentally observed macro stress strain response and failure patterns. The influence of aggregate shape on texture formation in the packed specimen, and on macro strength and failure patterns in hardened concrete, is demonstrated and is seen to be consistent with experimental results.

An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM

Advances in computing power have enabled computational fluid dynamics (CFD) to become a crucial tool in aerodynamic design. To facilitate CFD-based design, the combination of gradient-based optimization and the adjoint method for computing derivatives can be used to optimize designs with respect to a large number of design variables. Open field operation and manipulation (OpenFOAM) is an open source CFD package that is becoming increasingly popular, but it currently lacks an efficient infrastructure for constrained design optimization. To address this problem, we develop an optimization framework that consists of an efficient discrete adjoint implementation for computing derivatives and a Python interface to multiple numerical optimization packages. Our adjoint optimization framework has the following salient features: (1) The adjoint computation is efficient, with a computational cost that is similar to that of the primal flow solver and scales up to 10 million cells and 1024 CPU cores. (2) The adjoint derivatives are fully consistent with those generated by the flow solver with an average error of less than 0.1%. (3) The adjoint framework can handle optimization problems with more than 100 design variables and various geometric and physical constraints such as volume, thickness, curvature, and lift constraints. (4) The framework includes additional modules that are essential for successful design optimization: a geometry-parametrization module, a mesh-deformation algorithm, and an interface to numerical optimizations. To demonstrate our design-optimization framework, we optimize the ramp shape of a simple bluff geometry and analyze the flow in detail. We achieve 9.4% drag reduction, which is validated by wind tunnel experiments. Furthermore, we apply the framework to solve two more complex aerodynamic-shape-optimization applications: an unmanned aerial vehicle, and a car. For these two cases, the drag is reduced by 5.6% and 12.1%, respectively, which demonstrates that the proposed optimization framework functions as desired. Given these validated improvements, the developed techniques have the potential to be a useful tool in a wide range of engineering design applications, such as aircraft, cars, ships, and turbomachinery.

WavePacket: A Matlab package for numerical quantum dynamics.II: Open quantum systems, optimal control, and model reduction

WavePacket is an open-source program package for numeric simulations in quantum dynamics. It can solve time-independent or time-dependent linear Schrödinger and Liouville–von Neumann-equations in one or more dimensions. Also coupled equations can be treated, which allows, e.g., to simulate molecular quantum dynamics beyond the Born–Oppenheimer approximation. Optionally accounting for the interaction with external electric fields within the semi-classical dipole approximation, WavePacket can be used to simulate experiments involving tailored light pulses in photo-induced physics or chemistry. Being highly versatile and offering visualization of quantum dynamics ‘on the fly’, WavePacket is well suited for teaching or research projects in atomic, molecular and optical physics as well as in physical or theoretical chemistry. Building on the previous Part I [Comp. Phys. Comm. 213, 223–234 (2017)] which dealt with closed quantum systems and discrete variable representations, the present Part II focuses on the dynamics of open quantum systems, with Lindblad operators modeling dissipation and dephasing. This part also describes the WavePacket function for optimal control of quantum dynamics, building on rapid monotonically convergent iteration methods. Furthermore, two different approaches to dimension reduction implemented in WavePacket are documented here. In the first one, a balancing transformation based on the concepts of controllability and observability Gramians is used to identify states that are neither well controllable nor well observable. Those states are either truncated or averaged out. In the other approach, the H2-error for a given reduced dimensionality is minimized by H2 optimal model reduction techniques, utilizing a bilinear iterative rational Krylov algorithm.The present work describes the MATLAB version of WavePacket 5.3.0 which is hosted and further developed at the Sourceforge platform, where also extensive Wiki-documentation as well as numerous worked-out demonstration examples with animated graphics can be found. Program summaryProgram Title:WavePacketProgram Files doi:http://dx.doi.org/10.17632/9g8b7jychy.1Licensing provisions: GPLv3Programming language:MatlabJournal reference of previous version: Comput. Phys. Comm. 213 (2017), 223.Does the new version supersede the previous version?: The previous article focused on the treatment of closed quantum systems by discrete variable representations and implementation of various numerical algorithms for solving Schrödinger’s equations. Complementary to that, the present second part is concerned with open quantum systems and optimal control by external fields. In addition, two approaches to dimension reduction useful in modeling of quantum control are described.Reasons for the new version: The reason for having a second article on the WavePacket software package lies in the fact that a complete description of the package would have exceeded the scope of a regular article. Several significant features of the WavePacket package are introduced here which could not be mentioned in the first article, due to length constraints.Summary of revisions: Here we describe the numerical treatment of open quantum systems dynamics modeled by Lindblad master equations. Moreover, we explain the WavePacket functions for optimal control simulations, both for closed and open quantum systems. To address the problem of computational effort, two strategies for model reduction have been included.Nature of problem: Dynamics of closed and open systems are described by Schrödinger or Liouville–von Neumann equations, respectively, where the latter ones will be restricted to the Lindblad master equation. Emphasis is on the interaction of quantum system with external electric fields, treated within the semi-classical dipole approximation. Quantum optimal control simulations are used for the design of tailored fields achieving specified targets in quantum dynamics. With these features, WavePacket can be instrumental for the simulation, understanding, and prediction of modern experiments in atomic, molecular and optical physics involving temporally shaped fields.Solution method: Representing state vectors or reduced density matrices in a discrete basis, Schrödinger or Liouville–von Neumann equations are cast into systems of ordinary differential equations. Those are treated by self-written or Matlab’s built-in solvers, the latter ones offering adaptive time-stepping. The optimal control equations are solved by the rapid monotonically convergent iteration methods developed by Zhu, Rabitz, Ohtsuki and others. In order to reduce the dimensionality of large scale control problems, the balanced truncation method as well as H2-optimal model reduction approaches are available in WavePacket.Additional comments including restrictions and unusual features: The WavePacket program package is rather easy and intuitive to use, providing visualization of quantum dynamics ‘on the fly’. It is mainly intended for low-dimensional systems, typically not exceeding three to five degrees of freedom. Detailed user guides and reference manuals are available through numerous Wiki pages hosted at the SourceForge platform where also a large number of well documented demonstration examples can be found.

A randomized matched-pairs study of feasibility, acceptability, and effectiveness of systems consultation: a novel implementation strategy for adopting clinical guidelines for Opioid prescribing in primary care

BackgroundThis paper reports on the feasibility, acceptability, and effectiveness of an innovative implementation strategy named “systems consultation” aimed at improving adherence to clinical guidelines for opioid prescribing in primary care. While clinical guidelines for opioid prescribing have been developed, they have not been widely implemented, even as opioid abuse reaches epidemic levels.MethodsWe tested a blended implementation strategy consisting of several discrete implementation strategies, including audit and feedback, academic detailing, and external facilitation. The study compares four intervention clinics to four control clinics in a randomized matched-pairs design. Each systems consultant aided clinics on implementing the guidelines during a 6-month intervention consisting of monthly site visits and teleconferences/videoconferences. The mixed-methods evaluation employs the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Quantitative outcomes are compared using time series analysis. Qualitative methods included focus groups, structured interviews, and ethnographic field techniques.ResultsSeven clinics were randomly approached to recruit four intervention clinics. Each clinic designated a project team consisting of six to eight staff members, each with at least one prescriber. Attendance at intervention meetings was 83%. More than 80% of staff respondents agreed or strongly agreed with the statements: “I am more familiar with guidelines for safe opioid prescribing” and “My clinic’s workflow for opioid prescribing is easier.” At 6 months, statistically significant improvements were noted in intervention clinics in the percentage of patients with mental health screens, treatment agreements, urine drug tests, and opioid-benzodiazepine co-prescribing. At 12 months, morphine-equivalent daily dose was significantly reduced in intervention clinics compared to controls. The cost to deliver the strategy was $7345 per clinic. Adaptations were required to make the strategy more acceptable for primary care. Qualitatively, intervention clinics reported that chronic pain was now treated using approaches similar to those employed for other chronic conditions, such as hypertension and diabetes.ConclusionsThe systems consultation implementation strategy demonstrated feasibility, acceptability, and effectiveness in a study involving eight primary care clinics. This multi-disciplinary strategy holds potential to mitigate the prevalence of opioid addiction and ultimately may help to improve implementation of clinical guidelines across healthcare.Trial registrationClinicalTrials.gov (NCT02433496). https://clinicaltrials.gov/ct2/show/NCT02433496Registered May 5, 2015

Eigenvalue sensitivity of sampled time systems operating in closed loop

Abstract The use of feedback to create closed-loop eigenstructures with high sensitivity has received some attention in the Structural Health Monitoring field. Although practical implementation is necessarily digital, and thus in sampled time, work thus far has center on the continuous time framework, both in design and in checking performance. It is shown in this paper that the performance in discrete time, at typical sampling rates, can differ notably from that anticipated in the continuous time formulation and that discrepancies can be particularly large on the real part of the eigenvalue sensitivities; a consequence being important error on the (linear estimate) of the level of damage at which closed-loop stability is lost. As one anticipates, explicit consideration of the sampling rate poses no special difficulties in the closed-loop eigenstructure design and the relevant expressions are developed in the paper, including a formula for the efficient evaluation of the derivative of the matrix exponential based on the theory of complex perturbations. The paper presents an easily reproduced numerical example showing the level of error that can result when the discrete time implementation of the controller is not considered.

RGB LED Driver Circuit Design for an Optical Fiber Sensor System

In this paper, the design of a programmable mixed-signal electronic circuit to control the light output of a red-green-blue (RGB) light emitting diode (LED) to be used in an optical fiber sensor system is presented and discussed. The LED is to be used as a light transmitter (light source) within the sensor system. The output of each LED color is to be independently controlled using either a d.c. current or a pulse width modulation (PWM) encoded current. The idea for, and architecture of, the mixed-signal electronic circuit design is considered as both a discrete implementation using off-the-shelf components and the concept for an application specific integrated circuit (ASIC) solution using a 0.35 µm complementary metal oxide semiconductor (CMOS) fabrication process. In this paper, the design operation principles, circuit architecture, simulation results and hardware requirements for this LED driver circuit are considered.

Implementation of high-gain observer on low-cost fused IR-OS sensor embedded in UAV system

This paper presents discrete time implementation of a high gain observer (HGO) and extended term to estimate the state velocity and acceleration from the position measured by a low-cost sensor installed on-board the unmanned aerial vehicle (UAV). Owing to the low-cost sensor, the signal produced from fused IR–OS is noisy and therefore, additional filters are used to remove the noise. This study proposes an alternative to this standard and tedious procedure using HGO. The discrete time implementation of HGO and its extended term is presented and ground tests are conducted to verify the algorithm by inducing a dynamic motion on the UAV platform embedded with the fusion IR-OS onboard. A comparison study is conducted using standard numerical differentiation and ground truth measurement by OptiTrack. The results show that EHGO can produce a velocity signal with the same quality as that of differentiated signal from fused IR-OS using Kalman filter. The novelty of HGO lies in its simplicity and its minimal tuning of parameters.

Spatio-Temporal Scale Selection in Video Data

This work presents a theory and methodology for simultaneous detection of local spatial and temporal scales in video data. The underlying idea is that if we process video data by spatio-temporal receptive fields at multiple spatial and temporal scales, we would like to generate hypotheses about the spatial extent and the temporal duration of the underlying spatio-temporal image structures that gave rise to the feature responses. For two types of spatio-temporal scale-space representations, (i) a non-causal Gaussian spatio-temporal scale space for offline analysis of pre-recorded video sequences and (ii) a time-causal and time-recursive spatio-temporal scale space for online analysis of real-time video streams, we express sufficient conditions for spatio-temporal feature detectors in terms of spatio-temporal receptive fields to deliver scale-covariant and scale-invariant feature responses. We present an in-depth theoretical analysis of the scale selection properties of eight types of spatio-temporal interest point detectors in terms of either: (i)–(ii) the spatial Laplacian applied to the first- and second-order temporal derivatives, (iii)–(iv) the determinant of the spatial Hessian applied to the first- and second-order temporal derivatives, (v) the determinant of the spatio-temporal Hessian matrix, (vi) the spatio-temporal Laplacian and (vii)–(viii) the first- and second-order temporal derivatives of the determinant of the spatial Hessian matrix. It is shown that seven of these spatio-temporal feature detectors allow for provable scale covariance and scale invariance. Then, we describe a time-causal and time-recursive algorithm for detecting sparse spatio-temporal interest points from video streams and show that it leads to intuitively reasonable results. An experimental quantification of the accuracy of the spatio-temporal scale estimates and the amount of temporal delay obtained from these spatio-temporal interest point detectors is given, showing that: (i) the spatial and temporal scale selection properties predicted by the continuous theory are well preserved in the discrete implementation and (ii) the spatial Laplacian or the determinant of the spatial Hessian applied to the first- and second-order temporal derivatives leads to much shorter temporal delays in a time-causal implementation compared to the determinant of the spatio-temporal Hessian or the first- and second-order temporal derivatives of the determinant of the spatial Hessian matrix.

High Performance Direct Torque Control of Induction Motor Drives: Problems and Improvements

This paper presents some of the main problems, as well as their root causes, of Direct Torque Control (DTC) 3-phase induction motor drive. The high torque ripple in DTC drive due to the hysteresis controller inevitably becomes worst with the discrete implementation of the drive system. The hysteresis controller also causes variable switching frequency that depends on operating conditions, especially the speed. The simplification used in stator flux expression for voltage vectors selection in flux control results in a poor flux regulation at low speed. To overcome these problems, techniques that have been implemented at UTM-PROTON Future Drive Laboratory (UPFDL) are presented and described. Some experimental results obtained from the previous works are also presented and discussed.

Numerical solution of EFIE using MLPG methods

Meshless local Petrov-Galerkin (MLPG) methods are applied to the electric-field integral equation (EFIE), including seven previously reported schemes and two new suggested. The required dyadic weightings are provided. Especially, the dyadic Green’s function for the differential part of the equation is derived for the first time. Guidelines are suggested for both meshless discretization and efficient implementation. It is shown that by proper selection of the MLPG scheme and its parameters, the stiffness matrix corresponding to the problem can be computed using closed-form expressions, without the need to perform numerical integration. It is shown that using weightings other than the Dirac delta can significantly improve the convergence trend of the meshless solution and increase the accuracy up to two orders of magnitude. It is, also, demonstrated that a meshfree IE solver can more accurately track singularities of the surface current density at conductive edges compared to the method of moments (MoM). In addition, it is shown that such solvers can potentially supersede high-order (HO) MoM as their mesh-based counterpart.

The association between implementation strategy use and the uptake of hepatitis C treatment in a national sample

BackgroundHepatitis C virus (HCV) is a common and highly morbid illness. New medications that have much higher cure rates have become the new evidence-based practice in the field. Understanding the implementation of these new medications nationally provides an opportunity to advance the understanding of the role of implementation strategies in clinical outcomes on a large scale. The Expert Recommendations for Implementing Change (ERIC) study defined discrete implementation strategies and clustered these strategies into groups. The present evaluation assessed the use of these strategies and clusters in the context of HCV treatment across the US Department of Veterans Affairs (VA), Veterans Health Administration, the largest provider of HCV care nationally.MethodsA 73-item survey was developed and sent to all VA sites treating HCV via electronic survey, to assess whether or not a site used each ERIC-defined implementation strategy related to employing the new HCV medication in 2014. VA national data regarding the number of Veterans starting on the new HCV medications at each site were collected. The associations between treatment starts and number and type of implementation strategies were assessed.ResultsA total of 80 (62%) sites responded. Respondents endorsed an average of 25 ± 14 strategies. The number of treatment starts was positively correlated with the total number of strategies endorsed (r = 0.43, p < 0.001). Quartile of treatment starts was significantly associated with the number of strategies endorsed (p < 0.01), with the top quartile endorsing a median of 33 strategies, compared to 15 strategies in the lowest quartile. There were significant differences in the types of strategies endorsed by sites in the highest and lowest quartiles of treatment starts. Four of the 10 top strategies for sites in the top quartile had significant correlations with treatment starts compared to only 1 of the 10 top strategies in the bottom quartile sites. Overall, only 3 of the top 15 most frequently used strategies were associated with treatment.ConclusionsThese results suggest that sites that used a greater number of implementation strategies were able to deliver more evidence-based treatment in HCV. The current assessment also demonstrates the feasibility of electronic self-reporting to evaluate ERIC strategies on a large scale. These results provide initial evidence for the clinical relevance of the ERIC strategies in a real-world implementation setting on a large scale. This is an initial step in identifying which strategies are associated with the uptake of evidence-based practices in nationwide healthcare systems.