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PURPOSE: System-specific scanning strategies have been shown to influence the accuracy of full-arch digital impressions. Special guided scanning procedures have been implemented for specific intraoral scanning systems with special regard to the digital orthodontic workflow. The aim of this study was to evaluate the precision of guided scanning procedures compared to conventional impression techniques in vivo. METHOD: Two intraoral scanning systems with implemented full-arch guided scanning procedures (Cerec Omnicam Ortho; Ormco Lythos) were included along with one conventional impression technique with irreversible hydrocolloid material (alginate). Full-arch impressions were taken three times each from 5 participants (n = 15). Impressions were then compared within the test groups using a point-to-surface distance method after best-fit model matching (OraCheck). Precision was calculated using the (90-10%)/2 quantile and statistical analysis with one-way repeated measures ANOVA and post hoc Bonferroni test was performed. RESULTS: The conventional impression technique with alginate showed the lowest precision for full-arch impressions with 162.2 ± 71.3 µm. Both guided scanning procedures performed statistically significantly better than the conventional impression technique (p < 0.05). Mean values for group Cerec Omnicam Ortho were 74.5 ± 39.2 µm and for group Ormco Lythos 91.4 ± 48.8 µm. CONCLUSIONS: The in vivo precision of guided scanning procedures exceeds conventional impression techniques with the irreversible hydrocolloid material alginate. Guided scanning procedures may be highly promising for clinical applications, especially for digital orthodontic workflows.

Model matching is a prototype design problem that is useful in solving many problems of interest in systems and control theory. A solution is usually in the form of a dynamic compensator. It is often convenient to realize the compensator via state feedback applied to the given system. While realizability conditions are well known, least order solutions, which require as few integrators as possible, pose a difficult problem. A direct solution is proposed that avoids any restrictive hypotheses concerning system and compensator. The synthesis procedure is built on static state feedback solution applied to an extended system.

Background. Although the effectiveness of game-based learning (GBL) is well-supported, much less is known about the process underlying it. Nevertheless, developing a mental model that matches the game system, which in turn models a real-world system, is a promising proposed process. Aim. This article explores the first steps in model matching: identifying the entities and (complex) relations in a game system. Method. Participants ( N = 30) played the analog game DOMINION and completed a multi-step mental model mapping exercise. Categories of entities in mental model maps were inductively identified with grounded theory coding, while complex relations in mental model maps were identified via content analysis. Results. Participants described formal game entities, player actions, sociality, learning processes, and subjective experience in their mental model maps. Participants identified very few complex relations—and no feedback loops—in their mental model maps. Conclusions. Games—and analog games specifically—provide a breadth of resources for model matching and GBL. Through gameplay, learners come to affix conceptual meanings to material objects, a process dubbed lamination.

Controlling the looper height and strip tension is important in hot strip mills because these variables affect both the strip quality and strip threading. Many researchers have proposed and applied a variety of control schemes for this problem, but the increasingly strict market demand for strip quality requires further improvements. This work describes a dynamic matrix predictive control (DMC) strategy that realizes the optimal control of a hydraulic looper multivariable system. Simulation experiments for a traditional controller and the proposed DMC controller were conducted using MATLAB/Simulink software. The simulation results show that both controllers acquire good control effects with model matching. However, when the model is mismatched, the traditional controller produces an overshoot of 32.4% and a rising time of up to 2120.2 ms, which is unacceptable in a hydraulic looper system. The DMC controller restricts the overshoot to less than 0.08%, and the rising time is less than 48.6 ms in all cases.

In this paper we study linear systems with positivity type of constraints. First, we consider the case where the input to a system is restricted to be in the positive cone of l ∞ , denoted by l ∞ + , and seek to characterize the system’s induced norm from l ∞ + to l ∞ . We obtain an exact characterization of this norm which is particularly easy to calculate in the case of LTI systems. Furthermore, we consider and solve the model matching problem, and show that time-varying linear or nonlinear control/filtering does not improve the performance with respect to this norm for LTI systems. In the second part of the paper, we consider the case when the output is forced to be in the positive l ∞ cone when the input is in this cone. We show if internal positivity is sought, a dynamic optimal controller offers no advantage over a static one. Also, if the measurement matrix satisfies certain conditions, synthesizing an optimal static output feedback controller reduces to a linear program.

In addition to individual risk factors, recent findings surrounding the effects of violent video game play have provided compelling evidence that the contextual features of games also contribute to...

This research is aim at finding out direct effect of Three Teachers (Tri Guru) on environmentally soundbehavior and to identify indirect effect of Tri Guru on environmentally sound behavior through perception aboutThree Balance Concept (Tri Hita Karana), cultural value, and motivation of villagers in Sukawati Village,District Sukawati, Gianyar Regency, Bali in 2009.Data was collected by questionnaire. The item validity of instruments was tested by Product MomentCorrelation; and the reliability was tested by Alpha Cronbach. The total sample of 251 was recruited during thestudy. Data analyses applied to test the model matching was Structural Equation Modeling.The result of analysis finds out that Tri Guru affects environmentally sound behavior significantly throughperception about Tri Hita Karana, cultural value, and motivation in greater value than direct effect of Tri Guruon environmentally sound behavior. The Model match test shows that the modified path model have achievedthe criteria of model matching, because matching test indicators achieve minimum cut-off value.Based on these findings, it could be concluded that any changing or variation on environmentally soundbehavior have been directly affected by villagers evaluation on Tri Guru, indirectly affected by perception aboutTri Hita Karana, cultural value of environmental care, and motivation to preserve the function of environment.Therefore, when we want to increase environmentally sound behavior of villagers, these factors such as TriGuru, perception, cultural value and motivation are necessary to be taken into account.

Innovations in technology have led to the introduction of exercise devices that feature interactive virtual worlds, often referred to as exergames. Using the theory of model matching, this study se...

In this work, we report about research results initially published in ACM Transactions on Software Engineering and Methodology (TOSEM), volume 28 Issue 3, 2019. Nowadays software comes in many different, yet similar variants, often derived from common code via clone-and-own. Family-based-analysis strategies show promising potentials for improving efficiency of quality assurance for variant-rich programs, as compared to variant-by-variant approaches. Unfortunately, these strategies require one superimposed program representation containing all program variants in a syntactically well-formed, semantically sound, and variant-preserving manner, which is hard to obtain manually in practice. In this talk, we present our methodology SiMPOSE for generating superimpositions of program variants to facilitate family-based analyses of variant-rich software. We utilize a novel N-way model-merging methodology for control-flow automaton (CFA) representations of C programs, an abstraction used by many recent software-analysis tools. To cope with the complexity of N-way merging, we use similarity-propagation to reduce the number of N-way matches and enable incremental merging of arbitrary subsets of variants. We apply our SiMPOSE tool to realistic C programs and investigate applicability and efficiency/effectiveness trade-offs of family-based program analyses. Our results reveal efficiency improvements by a factor of up to 2.6 for unit-test generation and 2.4 for model-checking under stable effectiveness, as compared to variant-by-variant.

Many of today’s data models for 3D applications, such as City Geography Markup Language (CityGML) or Industry Foundation Classes (IFC) encode rich semantic information in addition to the traditional geometry and materials representation. However, 3D editing techniques fall short of maintaining the semantic information across edit operations if they are not tailored to a specific data model. While semantic information is often lost during edit operations, geometry, UV mappings, and materials are usually maintained. This article presents a data model synchronization method that preserves semantic information across editing operation relying only on geometry, UV mappings, and materials. This enables easy integration of existing and future 3D editing techniques with rich data models. The method links the original data model to the edited geometry using point set registration, recovering the existing information based on spatial and UV search methods, and automatically labels the newly created geometry. An implementation of a Level of Detail 3 (LoD3) building editor for the Virtual Singapore project, based on interactive push-pull and procedural generation of façades, verified the method with 30 common editing tasks. The implementation synchronized changes in the 3D geometry with a CityGML data model and was applied to more than 100 test buildings., Remote Sensing, 12 (2), ISSN:2072-4292

A model matching and passivating control architecture for multi-input/multi-output linear systems, comprising dynamic feedback and feedforward, is proposed. The approach—essentially without any restriction on the relative degree and the zeros of the underlying system and by relying only on input/output measurements—provides a closed-loop system, the transfer matrix of which matches any desired matrix of rational functions. An alternative implementation of the above design allows to achieve an arbitrary approximation accuracy of a desired transfer matrix while also preserving structural properties—in particular observability —of the overall interconnected system. Such a construction can be then specialized to provide input/output decoupling or a system that is passive from a novel control input to a modified output. The result is achieved by arbitrarily assigning the relative degree and location of the poles and zeros on the complex plane of the interconnected system in a systematic way. It is also shown that similar ideas can be employed to enforce a desired, arbitrarily small, $\mathcal {L}_2$ -gain from an unknown disturbance input to a modified output, while preserving the corresponding gain from the control input to the same output. The article is concluded with applications and further discussions on the results.

Assembly retrieval is a significant technology to reuse the abundant design knowledge embedded in the products. However, the existing assembly retrieval methods are still lacking and the research on this topic is needed. It is found that the motion features of the internal mechanism in the assembly model are closely related to its mechanical function, which is significant for mechanism motion design, assembly simulation, etc. So we propose an approach for assembly matching by motion and shape features. First, assembly model are decomposed into separate kinematic components according to analyzing its motion structure. Then, we take geometric information of kinematic component as a vertex, and kinematic pair between components is taken as an edge to construct graph-based assembly descriptor, which contains motion features of the assembly. Afterwards, Ullmann algorithm is introduced to match the input descriptor with the assemblies in the library, and the maximum subgraph of them is solved so as to estimate the similarity. In case study, some experiments have been carried out, and the results have shown the feasibility of the method proposed in this paper and demonstrated the practical value in engineering.

We consider the problem of estimating signal attacks injected into the actuators or sensors of control systems, assuming the attack is detectable, i.e., it can be seen at the output. We show that there exists a trade-off between attack rejection and control, and that the estimator design depends on the controller used. We use dual rate sampling to enhance detectability of the attacks and we provide different methods to design the estimator. The first method is by solving a model matching problem subject to causality constraints. The second method exploits dual rate sampling to accurately reconstruct the unknown input. The third method is using a dual rate unknown input observer. We provide conditions on the existence of these estimators, and show that dual rate unknown input observers always exist if the multirate system does not have a zero at 1.

Industry trades report the digital marketing skills gap continues to widen. In response to this need, Experiential Learning Theory (ELT) and a partnership with a leader in marketing technology was applied to create the Applied Marketing & Media Education Norm (AMEN). AMEN provides a model matching the employment needs of the digital marketing space while creating a means for academic programs to remain current with technology. AMEN also offers unique advantages when it comes to bridging theory-based and skills-based education models through applied projects and software certifications. This produces positive outcomes for the students, faculty, department, university, and industry.

A solution of the longstanding problem of model matching by non-regular static state feedback is presented. The problem formulation avoids restrictive hypotheses concerning system and target model. Necessary and sufficient conditions for the problem to have a solution are obtained which yield a construction of a matching feedback law. Several cases of special interest are subsequently discussed. Finally, the existence of stable solutions is established and a construction of static stable solutions is addressed.

This work deals with model matching by output dynamic feedback in switched linear systems. The plant and the model are assumed to be subject to different switching signals. A necessary and sufficient condition for achieving model matching with asymptotic stability of both the closed-loop compensated system and the compensator, for a sufficiently large dwell time, is proven. Such condition is obtained by specializing the structural condition with a suitable redefinition of the robust controlled invariant subspace involved, capable of capturing not only the structural aspect of the problem but also the stability aspects. The effect of the combined action of nonzero initial states and nonzero inputs is dealt with. The solution to a more demanding problem formulation, where the dwell time is assumed to be fixed and given is also discussed.

[abstFig src='/00280005/13.jpg' width='300' text='VRFT model matching problem with prefilter F(z)' ] Prefilters for Virtual Reference Feedback Tuning (VRFT) in the time domain are realized by the least-squares method with step reference response data acquired from the closed-loop system to be tuned and are used to obtain controller parameters for making closed-loop systems as close as possible to the desired reference model. The usefulness of this proposal is shown in numerical examples in which fifth-order and PID controllers for a flexible transmission system are tuned by VRFT with prefilters.

Output synchronization of heterogeneous multi-agent systems has been one of the most interesting cooperative control problems. This paper first gives a brief survey of the research on the problem from which we see that the problem can be solved in a two-step manner with the aid of a properly designed local reference for each agent: (i) a controller is designed for each agent to achieve the trajectory regulation of the agent output to its associated reference; (ii) network collaboration is added to achieve consensus among references. In the presence of system uncertainties, the robust trajectory regulation problem in (i) can be solved by an internal model design. In this paper, we formulate a novel robust asymptotic model matching problem which is less conservative than trajectory regulation and can be solved by a static controller not relying on an internal model. Moreover, network collaboration is designed in (ii) within the so-called output communication setting such that consensus among references occurs concurrently with robust asymptotic model matching. As a result, output synchronization of heterogeneous multi-agent systems is achieved with a novel approach.

In this paper, we consider the $l_{\infty}$ gain characterizations of linear switched systems (LSS) and present various relevant results on their exact computation and optimization. Depending on the role of the switching sequence, we study two broad cases: first, when the switching sequence attempts to maximize, and second, when it attempts to minimize the $l_{\infty}$ gain. The first, named as worst-case throughout the paper, can be related to robustness of the system to uncontrolled switching; the second relates to situations when the switching can be part to the overall decision making. Although, in general, the exact computation of $l_{\infty}$ gains is difficult, we provide specific classes, the input-output switching systems, for which it is shown that linear programming can be used to obtain the worst-case $l_{\infty}$ gain. This is a sufficiently rich class of systems as any stable LSS can be approximated by one. Certain applications to robust control design are provided where we show that a switched compensation independently of the plant has no advantage over a linear time invariant (LTI) compensation, and further, if the plant is strictly causal, even a switched compensation which has a matched switching with the plant does not provide a better performance over an LTI compensation. Also, we present a new necessary and sufficient condition to check the stability of LSS in form of a model matching problem. On the other hand, if one is interested in minimizing the $l_{\infty}$ gain over the switching sequences, we show that, for finite impulse response (FIR) switching systems the minimizing switching sequence can be chosen to be periodic. For input-only or output-only switching an exact, readily computable, characterization of the minimal $l_{\infty}$ gain is provided, and it is shown that the minimizing switching sequence is constant, which, as also shown, is not true for input-output switching.

In this paper, an approach to design an Admissible Model Matching (AMM) Fault Tolerant Control (FTC) based on Linear Parameter Varying (LPV) fault representation is proposed. The main contribution of this approach is to consider parametric faults as a scheduling variable in the LPV fault representation of the system that allows the controller reconfiguration on-line. The proposed strategy is an active technique that requires the fault to be detected, isolated and estimated by a FDI scheme. In case the fault estimation is not available, a passive strategy based on a single AMM FTC controller could be designed. The formulation of AMM is based on the set of admissible behaviors that are characterized by means of Linear Matrix Inequalities (LMIs). The LMIs allow to locate the poles of the close-loop system inside a region of the unit circle and the fault accommodation can be formulated in terms of several LMIs. The effectiveness and performance of proposed approach have been illustrated in simulation considering a thermal hydraulic system.

In this study, the discrete-time H∞ model matching problem with integral control by using 2 DOF static output feedback is presented. First, the motivation and the problem is stated. After presenting the notation, the two lemmas toward the discrete-time H∞ model matching problem with integral control are proven. The controller synthesis theorem and the controller design algorithm is elaborated in order to minimize the H∞ norm of the closed-loop transfer function and to maximize the closed-loop performance by introducing the model transfer matrix. In following, the discrete-time H∞ MMP via LMI approach is derived as the main result. The controller construction procedure is implemented by using a well-known toolbox to improve the usability of the presented results. Finally, some conclusions are given.

International audience; Design of complex systems goes through a multiview paradigm in which separate teams, from different business viewpoints, build partial models describing the system. As they are expressed in different languages, these partial models are called heterogeneous models. To maintain the global system's consistency, we propose a collaborative approach that combines Group Decision Making (GDM) and Model-Based Engineering. This paper presents a metamodel for collaborative decision elaboration via a set of decision policies which are instances of GDM patterns. Our approach is illustrated with a hospital Emergency Department case study and is supported by a tool allowing models alignment through GDM based processes.

Plate treatment is currently the standard treatment of proximal tibia fracture. Morphological characteristics can help orthopedic surgeons understand anatomic information of tibia and choose well-matched plate for reducing difficulties in plate treatment. However, manual measurement of morphological characteristics of patient's tibia is time-consuming and labor-intensive. Therefore, this study proposes an automatic method to accurately estimate the morphological characteristics of patient's tibia for assisting plate treatment. In the off-line stage, an average shape with typical characteristics was computed from 422 tibia models, and the morphological characteristics of the average shape were measured by the orthopedic surgeon. In the on-line stage, the point's correspondence between the average shape and every tibia model was created by the proposed morphable model matching method firstly. Then, the morphological characteristics of tibia for every patient were estimated automatically based on the point's correspondence and characteristics of average shape. The effectiveness of the method was validated by comparing the manual measured and automatic-estimated characteristics. In addition, the basic experiments of virtual and real plate implantation preliminarily confirmed that the automatic-estimated morphological characteristics were helpful for plate treatment. In all, we propose an automatic and accurate estimation method of morphological characteristics for a large-scale library of Chinese tibia models, which provides orthopedic surgeons with scientific and quantitative description of tibia.