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Conversation analysis (CA) and the cooperative principle (CP) are two approaches associated with understanding structure and order in naturally occurring speech, and in particular, how speakers communicate cooperatively. While historically they are placed within differing sub-fi elds of linguistics, with CA in sociolinguistics and the CP in pragmatics, the emergence of pragmatic stylistics as a branch of stylistics combines approaches ‘to answer questions about how (literary) language is used in context and how it contributes to the characterization of the protagonists in a literary piece of art or how power structures are created and so on.’ (Norgaard, Busse and Montoro 2010, p. 39). Studying spoken interaction in literary texts is likely to consider both the CA model and the CP together even though they are interested in different aspects of verbal communication. CA and the CP can be successfully applied as analytic tools to literary dialogue in drama and novels to gain insights into characterisation and characters’ relationships with each other, and help us understand not only how coherence in spoken communication is maintained but also how meaning is intended by one speaker and inferred by another. This chapter describes CA and the CP, and illustrates how they can be applied for the analysis of spoken interaction in literary texts beyond the mechanics of turn-taking. The chapter also outlines historical perspectives as well as current contributions to the application of CA and the CP to the stylistic analysis of texts representing speech.

The purpose of this article is to revisit the well known separation principle of classical control, for systems implemented in an event-triggered fashion. We consider an scenario consistent of two independent digital channels for communications between sensor and controller, and controller and actuator, and propose a methodology to separately design controller and observer gains as well as the event conditions. Under the proposed design, we address the problem of restoring the classical separation principle for the event-based design. We show that fast enough sampling at the sensor-to-observer (S-O) channel suffices to ensure a separation principle. On the other hand, under fast sampling at the controller-to-actuator (C-A) channel, a separation principle can be obtained provided that an additional mild assumption is imposed on the stability matrices. A numerical example is provided to support the theoretical findings.

The paper presents distributed output feedback synthesis for both leaderless consensus and leader-follower consensus of linear multi-agent systems subject to jointly connected switching networks. Luenberger type distributed observers are proposed based on the neighborhood output estimation error, and distributed output feedback controllers are developed according to the certainty equivalence principle. To show uniform global exponential stability of the switched closed-loop system, a separation principle for a class of switched linear systems with a cascaded structure is established employing weak Lyapunov function and checking weak zero-state detectability of its ‘`diagonal’' switched subsystems. It is shown that the weak zero-state detectability can be guaranteed by a generalized uniform joint-connected condition of switching networks without any dwell-time constraints.

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design - such as "minimal search" criteria from theoretical syntax - adhere to the FEP. This affords a greater degree of explanatory power to the FEP - with respect to higher language functions - and offers linguistics a grounding in first principles with respect to computability. We show how both tree-geometric depth and a Kolmogorov complexity estimate (recruiting a Lempel-Ziv compression algorithm) can be used to accurately predict legal operations on syntactic workspaces, directly in line with formulations of variational free energy minimization. This is used to motivate a general principle of language design that we term Turing-Chomsky Compression (TCC). We use TCC to align concerns of linguists with the normative account of self-organization furnished by the FEP, by marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference.

In this study, an energy‐efficient speed trajectory planner is proposed for high‐speed trains traveling on tracks with steep gradients and speed limits, especially for situations in which the speed limit has been reached, which causes adjoint variable discontinuity during calculation. New optimal switching rules at points where the speed limit is reached on steep tracks are derived by analysing the jump condition of state‐constrained Pontryagin's maximum principle. Accordingly, a novel two‐step algorithm for high‐speed trains, including an optimal‐cruise minimum‐time algorithm and search‐substitution algorithm, is designed to solve dynamic train models considering time‐energy and space‐energy conversions, respectively. Practical case studies demonstrates that the proposed method can save energy by approximately 3% and 10% in comparison to the approximate‐optimal time‐satisfied and minimum running time strategies, respectively. Moreover, the proposed method approximately consumes 0.98% and 1.62% of the computation time taken by discrete dynamic programming and reinforcement learning, respectively.

Harmonic current detection is a key algorithms for shunt active power filter controller, which generates reference currents to compensate the harmonics of grid current. This paper presents a new harmonics detection method based on the triangle orthogonal principle algorithm. Compared to the conventional harmonic current detection methods, the presented method has the advantages of simple structure, low calculation, and fast execution time. Using the phase signal detected by the phase-locked loop synchronized with the power grid signal, the method based on the triangle orthogonal principle can provide a simple method to detect the reference current. At the same time, because the method proposed in this paper has lower implementation complexity and less microcontroller resource consumption, low-cost microcontrollers can be used to implement the proposed method, which has practical engineering value. Finally, this paper analysis the proposed method in detailly and verifies its great performance through experimental results.

To effectively prevent river water pollution, water quality monitoring is necessary. However, existing methods for water quality assessment are limited in terms of the characterization of water quality conditions, and few researchers have been able to focus on feature extraction methods relative to water pollution identification, or to obtain accurate water pollution source information. Thus, this study proposed a feature extraction method based on the entropy-minimal description length principle and gradient boosting decision tree (GBDT) algorithm for identifying the type of surface water pollution in consideration of the distribution characteristics and intrinsic association of conventional water quality indicators. To improve the robustness to noise, we constructed the coarse-grained discretization features of each water quality index based on information entropy. The nonlinear correlation between water quality indexes and pollution classes was excavated by the GBDT algorithm, which was utilized to acquire tree transformed features. Water samples collected by a southern city Environmental Monitoring Center were used to test the performance of the proposed algorithm. Experimental results demonstrate that features extracted by the proposed method are more effective than the water quality indicators without feature engineering and features extracted by the principal component analysis algorithm. HIGHLIGHTS Different water pollutions have unique attributes for risk characterization.; Based on our study of the characteristics of water quality data, we proposed an innovative feature extraction method based on the entropy-minimal description length principle and gradient boosting decision tree algorithm.; We focus on the research into the feature extraction method in water pollution identification.

The hydraulic hybrid powertrain has great potential for reducing fuel consumption and emission of off-road vehicles. The energy management strategy is the key to hybrid powertrain and currently there are many well-developed strategies. Of which the Pontryagin’s minimum principle is of research interest since it is a global optimization method while less computational burden than dynamic programming. However, it requires full cycle information to calculate co-state value in the principle, making it not implementable. Therefore in this study an implementable Pontryagin’s minimum principle is proposed for a series hybrid wheel loader, where the optimal co-state value in the principle is trained through repetitive wheel loader duty cycle. The Pontryagin’s minimum principle formulations of hybrid wheel loader are developed. The online co-state training algorithm is presented. A dynamic simulation model of hybrid wheel loader is developed. The fuel consumption of hybrid wheel loader with proposed strategy is compared with dynamic programming strategy and rule-based strategy in wheel loader long and short loading cycles. Results show the fuel consumption with proposed strategy is close to dynamic programming result and is lower than rule-based strategy. Finally, the influence of pressure level of hybrid powertrain on vehicle fuel consumption is studied.

A measurement system based on the Scheimpflug principle is designed in this paper to solve the problem of difficulty in clear imaging due to excessively small depth of field in line-structured light close-range photogrammetry. A conversion model from the image coordinate system to the measured object coordinate system is established through the spatial projection relationship. The calibration method of the measurement system under Scheimpflug conditions is investigated and the calibration of the measurement system is completed through nonlinear iterative optimization, and the calibration re-projection error is less than 0.3 pixels. GPU (graphic processing unit) acceleration processing is performed on the center extraction of line-structured light stripe to achieve real-time output at a high frame rate. The processing time for a single 1024 × 1280 image is only 2.14 ms after acceleration. Experimental results showed that the measurement system can realize the three-dimensional measurement of complex shapes and high-reflectivity surfaces with high detection accuracy and output frame rate.

A brain network comprises a substantial amount of short-range connections with an admixture of long-range connections. The portion of long-range connections in brain networks is observed to be quantitatively dissimilar across species. It is hypothesized that the length of connections is constrained by the spatial embedding of brain networks, yet fundamental principles that underlie the wiring length distribution remain unclear. By quantifying the structural diversity of a brain network using Shannon’s entropy, here we show that the wiring length distribution across multiple species—including Drosophila, mouse, macaque, human, and C. elegans—follows the maximum entropy principle (MAP) under the constraints of limited wiring material and the spatial locations of brain areas or neurons. In addition, by considering stochastic axonal growth, we propose a network formation process capable of reproducing wiring length distributions of the 5 species, thereby implementing MAP in a biologically plausible manner. We further develop a generative model incorporating MAP, and show that, for the 5 species, the generated network exhibits high similarity to the real network. Our work indicates that the brain connectivity evolves to be structurally diversified by maximizing entropy to support efficient interareal communication, providing a potential organizational principle of brain networks.

Confronted with the possibility of severe environmental harms, such as catastrophic climate change, some researchers have suggested that we should abandon the principle at the heart of standard decision theory—the injunction to maximize expected utility—and embrace a different one: the Precautionary Principle. Arguably, the most sophisticated philosophical treatment of the Precautionary Principle (PP) is due to Steel (2015). Steel interprets PP as a qualitative decision rule and appears to conclude that a quantitative decision-theoretic statement of PP is both impossible and unnecessary. In this article, we propose a decision-theoretic formulation of PP in terms of lexical (or lexicographic) utilities. We show that this lexical model is largely faithful to Steel’s approach, but also that it corrects three problems with Steel’s account and clarifies the relationship between PP and standard decision theory. Using a range of examples, we illustrate how the lexical model can be used to explore a variety of issues related to precautionary reasoning.

A functional method of localization has proved to be good in solving the qualitative analysis problems of dynamic systems. Proposed in the 90s, it was intensively used when studying a number of well-known systems of differential equations, both of autonomous and of non-autonomous discrete systems, including systems that involve control and / or disturbances.The method essence is to construct a set containing all invariant compact sets in the phase space of a dynamical system. A concept of the invariant compact set includes equilibrium positions, limit cycles, attractors, repellers, and other structures in the phase space of a system that play an important role in describing the behavior of a dynamical system. The constructed set is called localizing and represents an external assessment of the appropriate structures in the phase space.Relatively recently, it was found that the functional localization method allows one to analyze a behavior of the dynamical system trajectories. In particular, the localization method can be used to check the stability of the equilibrium positions.Here naturally emerges an issue of the relationship between the functional localization method and the well-known La Salle invariance principle, which can be regarded as a further development of the method of Lyapunov functions for establishing stability. The article discusses this issue.

In many ways, entropy and probability are two concepts that complement each other. But it has been argued that there is no ‘straightforward connection’ between them with a no-go thesis from Kevin Davey. However, this skeptical conclusion rests on counterexamples that fail to do justice to the entropy principle and the equivocality of the notion of probability. Proceeding from the disambiguation of probability, and acknowledging the explanatory goal of the entropy principle, it is argued that the Boltzmannian statistical mechanics account can be vindicated with a justification of the explanandum, the reference class, and the standard uniform probability measure.

Kişilerin düşünsel çabalarının ürünü olan gayri maddi varlıklar günümüzde transfer fiyatlandırması işlemlerinin büyük bir kısmının teşkil etmektedir. Gerek dijital ekonominin giderek artan kullanımı, gerekse 19. yüzyılın ortasından beri artan bilimsel gelişmelerin ekonomik sonuçları, başta çok uluslu şirketler olmak üzere, vergi yükünü azaltmak isteyen mükelleflerin vergi yasasının dolanılması niteliğindeki hukuka aykırı davranış biçimlerini gerçekleştirmelerine sebep olmaktadır. Bu davranış biçimlerine bir yanıt olarak vergi idarelerinin de kapsamlı bir biçimde ekonomik gerçekliğe ulaşma çabası söz konusu olmaktadır. Bu durum ise, vergilendirme sürecini hem mükellefler hem de idare açısından uygulanması zor bir süreç haline getirmektedir. Gayri maddi varlıkların konu olduğu transfer fiyatlandırması işlemlerinde, emsallere uygunluk ilkesinin uygulanması günümüzde hem vergi idareleri hem de mükellefler için zor bir yapıya bürünmüştür. Ayrıca Avrupa Ekonomik İşbirliği Teşkilatı’nın (OECD) Matrah Aşındırma ve Kâr Aktarımı (BEPS) projesiyle ile birlikte yapılan ve gayri maddi hak ödemelerinin konusunu oluşturan gayri maddi varlıkların tanımlanmasına ilişkin olan değişiklikler, konunun güncel gelişmeler ışığında ele alınmasını gerektirmiştir.

The revelation principle is a key tool in mechanism design. It allows the designer to restrict attention to truthful mechanisms, greatly facilitating analysis. This is also borne out algorithmically, allowing certain computational problems in mechanism design to be solved in polynomial time. Unfortunately, when not every type can misreport every other type (the partial verification model) or—more generally—misreporting can be costly, the revelation principle can fail to hold. This also leads to NP-hardness results. The primary contribution of this article consists of characterizations of conditions under which the revelation principle still holds when reporting can be costly. (These are generalizations of conditions given earlier for the partial verification case [11, 21].) Furthermore, our results extend to cases where, instead of reporting types directly, agents send signals that do not directly correspond to types. In this case, we obtain conditions for when the mechanism designer can restrict attention to a given (but arbitrary) mapping from types to signals without loss of generality.

In recent times the approach to health care has been mostly influenced by the growing number of biomedical equipment used in hospitals, which needs the presence of the Clinical Engineering Service (CES). The aim of this work is to suggest a methodology to improve the performance of a CES through the application of Pareto principle to main Key Performance Indicators (KPIs). The methodology is applied by focusing on the use of KPIs that represent a quantifiable measure of achieving goals set by an organization. In this study five KPIs are considered: Uptime, MTTR (mean time to repair), PPM (percentage preventive maintenance), MTBF (mean time between failures) and the COSR (cost of service ratio). The first three indicators express the measure of CES efficiency in ensuring regular maintenance. The first step consists in retrieving data related to work orders for the years 2015-2016 on 6000 installed devices, carried out by a management software. The second step is to get the results through the use of an environment for numerical calculation and statistical analysis. In order to identify the main critical issues that may be present, three indicators (Uptime, MTTR and MTBF) are analyzed by applying the Pareto principle (i.e. 20% of the causes produce 80% of the effects). Considering the totality of work orders, therefore, it is possible to concentrate on only 20% of them in order to focus on a small group to understand the correlations between them. Identifying these characteristics means identifying the main critical issues that are present, on which action must be taken, and which affect 80% of the overall behavior. The COSR and PPM indicators, instead, suggest distribution models that allow to focus attention on the most critical devices. In conclusion, the way to analyze the results is obtained, when possible, by applying Pareto principle. Therefore, a CES will be able to focus on a few causes of poor performance. The achievement of these results could allow the standardization of the method used, enabling it to be applied to any healthcare system.

We show how a number of well-known uncertainty principles for the Fourier transform, such as the Heisenberg uncertainty principle, the Donoho--Stark uncertainty principle, and Meshulam's non-abelian uncertainty principle, have little to do with the structure of the Fourier transform itself. Rather, all of these results follow from very weak properties of the Fourier transform (shared by numerous linear operators), namely that it is bounded as an operator $L^1 \to L^\infty$, and that it is unitary. Using a single, simple proof template, and only these (or weaker) properties, we obtain some new proofs and many generalizations of these basic uncertainty principles, to new operators and to new settings, in a completely unified way. Together with our general overview, this paper can also serve as a survey of the many facets of the phenomena known as uncertainty principles., 43 pages

This paper proposes a non-weighted maximal approach of multi-attribute risk assessment for production accidents, which comes from the Chinese practice of risk management rather than the theoretical weighted multi-attribute approach. The existing literature for risk assessment of pipeline accidents, there is an absence of or lack of explicit consideration of some special dimensions, i.e., environmental pollution as the important derivative disaster. The non-weighted maximal approach is described the maximum function among multiple criteria, which include fatalities, serious injuries, direct economic loss, and environment pollutions. The approach comes from the Chinese government official achievement assessment system with the characteristics of “one ticket veto system for production safety”, and has applied to ex ante assessing likelihood of the accident, and ex post holding the responsible for accidents. At last, applying the case of the Chinese Qingdao oil pipeline accident, the maximal approach is compared with the FN curve criterion, the ALARP principle and the ELECTRE TRI method. The results show that the maximal approach of production safety accident criterion pays more attention to the risk density or risk consequences, which follows the “cask principle” and is much more useful controlling the risk when targeting the vulnerable links of engineering systems.

This article focuses on institutional discourse pragmatics, highlighting its salient features in a business to customer negotiation model, based on an authentic business correspondence (email), through a prism of H. Grice’s Theory of Cooperative Principle. The central thrust of this theory is the application of the maxims of Quantity, Quality, Relation and Manner to speech acts to secure identification of participants’ intentions and sentence meaning, excluding irrelevancies throughout the communication process. Any kind of interaction in our life is accompanied by diverse tangible and intangible components. The role, function and impact of these aggregate components on the natural flow of communication irrespective of the form (oral/written) are the concern of pragmatics.

In this paper, we address the state/fault estimation and observer-based control issues for switched systems with sensor faults. The main objective is to estimate sensor faults and compensate for their effects on the system state estimation, and then stabilize the switched system by the estimated state feedback. Applying the mode-dependent average dwell time (MDADT) concept and the Lyapunov stability theory, a new separation principle is developed, which allows formalizing the observer-based controller design in the form of linear matrix inequalities (LMI) instead of bilinear ones. Finally, a highly manoeuvrable aircraft technology (HiMAT) example, a DC–DC boost converter example, and a numerical example are investigated to show the practicability and efficiency of the obtained results.

The article provides a general description of the analytic hierarchy process and analyzes the problem of the influence of Pareto-inefficient alternatives on ranking results. It is shown that the presence of Pareto-inefficient alternatives in the original set can lead to erroneous ranking, and the lack of a mechanism within the framework of the analytic hierarchy process that confirms or disproves the existence of such alternatives decreases the level of validity of the obtained results. An approach to the integrated use of the Pareto principle and the analytic hierarchy process is proposed. The possibility of its practical application is shown on a specific example of calculations. The use of this approach will increase the validity of the ranking results of alternatives by either eliminating Pareto-inefficient ones from consideration or confirming their absence.

Even though the first docking procedures were developed almost 40 years ago, they are still under intense development, alongside with their validation. In this article, we are proposing the use of the quantum free-orbital AlteQ method in evaluating the correctness of ligand binding poses and their ranking. The AlteQ method calculates the electron density in the interspace between the ligand and the receptor, and since their interactions follow the maximum complementarity principle, an equation can be obtained, which describes these interactions. In this way, the AlteQ method evaluates the quality of contacts between the ligand and the receptor, bypasses the drawbacks of using ligand RMSD as a measure of docking quality, and can be considered as an improvement of the “fraction of recovered ligand−receptor contacts” method. Free Windows and Linux versions of the AlteQ program for assessing complementarity between the ligand and the receptor are available for download at www.chemosophia.com.

The special affine Fourier transform (SAFT) generalizes a number of well known unitary transformations, signal processing transformations and optics related mathematical operations. For example, Fourier transform, fractional Fourier transform, linear canonical transform, etc. The short-time special affine Fourier transform (STSAFT) is a novel time-frequency analysis tool, which solve the limitation of SAFT in time-frequency signal description. In this paper, we generalize some different uncertainty principles (UPs) for the SAFT and STSAFT of complex signals. The UPs for the STSAFT of complex signals are obtained in both local and global cases. Then the uncertainty principle for two STSAFT time-frequency domains is discussed. Finally, we provide a class of signals to illustrate our results.

The second law of thermodynamics is probabilistic in nature. Its formulation requires that the state of a system be described by a probability distribution. A natural question, thereby, arises as to whether a prior knowledge about the state of the system affects the second law. This question has now been nurtured for over a century, and it was incepted by C Maxwell through his famous thought experiment wherein comes the idea of Maxwell’s demon. The next important step in this direction was provided by L Szilard, who demonstrated a theoretical model for an information engine incorporating Maxwell’s demon. The final step that led to the inter-linkage of information theory and thermodynamics was through Landauer’s principle of information erasure that established the fact that information is physical. Here, we will present an overview of these three major works that laid the foundations of information thermodynamics.

This paper presents an optimization method that deal with control techniques for electrical machines, in order to impose a displacement with a minimum of energy consumption. It’s a generic method; However, its application to electrical machines is complex for implementation. The present work provides the shape of the optimal solution. Moreover, a resolution technique related to the nature of the model is proposed, which facilitate the numerical resolution of costate problem. The method is applied to hybrid stepper motor and the obtained results are then analyzed.

The extension principle is always used to fuzzify the crisp functions to obtain the fuzzy functions in which the α-level sets of fuzzy sets are involved in the calculation. In this paper, we shall ...

Actuators in real-world systems operate under limited bandwidth and saturation constraints. Mathematically, these limitations manifest as certain types of constraints being imposed on the sequence of control action. While saturation constraints have been studied extensively, bandwidth limitations in the actuators have received very little attention in the control community. While an attempt has been made in the direction of incorporating frequency constraints at the synthesis stage, rate constraints on the control at the design stage has not been studied extensively in the regime of discrete-time. This article tries to fill in that gap by incorporating rate constraints on the control trajectories. We propose a new discrete-time Pontryagin maximum principle (PMP) with rate constraints being imposed on the control and derive a set of first order necessary conditions for optimality. As an illustration, the linear quadratic (LQ) optimal control problem under rate constraints has been considered.

In recent years, with the continuous development of online geographic information services, the multiscale online expression of geographic elements and topological information has become a hot research topic. Currently, a large amount of research focuses mainly on the compression of vector line elements. The main shortcoming of current algorithms is that vector data compression does not consider the optimality of line simplification. In the face of terabytes or even petabytes of data, problems arise such as low processing efficiency and long transmission time. Based on the shape-tree principle, the proposed method aims to reconstruct the organizational structure of a geographic element and establish a hierarchical representation model of the element based on its structure, realizing multiscale shape recognition and matching and searching geographic elements. Finally, the proposed method is compared with a model based on the wavelet transform and discrete Fourier transform. The results demonstrate the applicability and effectiveness of the proposed method in morphological expression with geospatial big data.

This paper presents the first framework (up to the authors' knowledge) to address time-varying objectives in finite-horizon Deep Reinforcement Learning (DeepRL), based on a switching control soluti...

Data-driven modeling and computational predictions based on the maximum entropy principle (MaxEnt principle) aim to find as simple as possible — but not simpler than necessary — models that allow one to avoid the data-overfitting problem. We derive a multivariate nonparametric and nonstationary formulation of the MaxEnt principle and show that its solution can be approximated through a numerical maximization of the sparse constrained optimization problem with regularization. Application of the resulting algorithm to popular financial benchmarks reveals memoryless models allowing for simple and qualitative descriptions of data of the major stock market indices. We compare the obtained MaxEnt models to the heteroscedastic models from computational econometrics (GARCH, GARCH-GJR, MS-GARCH, and GARCH-PML4) in terms of the model fit, complexity, and prediction quality. We compare the resulting model log-likelihoods, the values of the Bayesian information criterion, posterior model probabilities, the quality of the data autocorrelation function fits, as well as the value-at-risk prediction quality. We show that all of the seven considered major financial benchmark time series (DJI, SPX, FTSE, STOXX, SMI, HSI, and N225) are better described by conditionally memoryless MaxEnt models with nonstationary regime-switching than by the common econometric models with finite memory. This analysis also reveals a sparse network of statistically significant temporal relations for the positive and negative latent variance changes among different markets. The code is provided for open access.

This paper aims to contribute to formulations of mathematical models for finite-DOF systems based on the Gauss’s principle of least constraint. A new theorem allows to extend the definition of the Gaussian deviation function, overcoming, without requiring any change of variables, algebraic limitations that arise when this principle is applied to systems for which the generalized mass matrices become singular under relaxation of constraints. As a result of this new theorem, the recursive constraint enforcement algorithm based on Udwadia–Kalaba equation, proposed within the scope of the modular modeling methodology for finite-DOF systems, is generalized. Finally, in a case study based on the classical problem of a knife-edge disc rolling in a plane, three constraint enforcement strategies that combine the application of the theorem herein proposed with conventional numerical integration methods have its results confronted, in two simulation scenarios, with those obtained from a benchmark model of this system.

The feature-economy principle is one of the key theoretical notions which have been postulated to account for the structure of phoneme inventories in the world's languages. In this paper, we test the explanatory power of this principle by conducting a study of the co-occurrence of consonant segments in phonological inventories, based on a sample of 2761 languages. We show that the feature-economy principle is able to account for many important patterns in the structure of the world's phonological inventories; however, there are particular classes of sounds, such as what we term the ‘basic consonant inventory’ (the core cluster of segments found in the majority of the world's languages), as well as several more peripheral clusters whose organisation follows different principles.

This research had aimed to analyze cooperative principle by observing the characters’ utterances in About Time movie. A descriptive qualitative method was used in analyzing the data because it would be explained by words, phrases, and sentences. The data would be based on the characters’ utterances in About Time movie. In collecting the data, the researcher used the observational method and non-participatory, note-taking techniques. Pragmatic identity method was applied in analyzing the data. The result findings showed that all four maxims in cooperative principle were found through the utterances in About Time movie. The researcher found 37 data of maxims. The result indicated that there were 14 (38%) data maxim of quantity, 14 (38%) data maxim of relation, 7 (19%) data maxim of quality and 2 (5%) data maxim of manner. In summary, the most frequently data were found in the maxim of quantity and maxim of relation. The least data were found in maxim of manner. Keywords: Cooperative Principle, Maxims, Utterances, Movie

Purpose The purpose of this study is to present the optimization of the design and measurement principle of a six-component force/thrust measurement stand. This study highlights some key problems found in previous studies and proposes improvements in design and measurement principles. Design/methodology/approach The numerical simulation approach is used to verify the proposed improvements. An improved design and measurement principle are proposed and to verify the proposed improvements, simulation experiments are conducted. The data obtained from simulations are analyzed through the proposed improved measurement principle. The proposed stand is capable of measuring the main thrust and other components as pitch, yaw and roll. The stand is capable of measuring the main thrust more than 50,000 N and orthogonal thrust components more than 1,000 N. Improved design of measurement stand is also capable of measuring moments in three-axis more than 150 Nm. Thrust stand consists of two main sections: front and rare. Stand consists of seven piezoelectric force sensors to measure all components of force. Findings The simulations experiments and basic theoretical laws of kinematics prove that the proposed design indeed improves the precision of measurement and also enhance the efficiency of design. Evaluation results show that the measurement stand designed is highly functional. Non-linearity, coupling and repeatability errors are found to be within acceptable range during numerical simulations. Originality/value This study is unique in this kind. This study identifies the key problems found in previous studies and proposes an improved design and measurement principle. This study provides evidence for the improvements to be really functional and necessary.

This paper investigates the regulation problem for a class of nonholonomic systems that includes power form systems and an approximated system of the rolling sphere as special cases. The basic idea is first to introduce a virtual periodic moving trajectory that satisfies certain persistent excitation condition (PE) and has the zero value at some time instants. Based on LaSalle invariance principle, the associated tracking problem is then solved under a necessary condition for stabilization and particularly true for the power form systems and the rolling sphere. With the help of virtual trajectory, the achieved tracking result is applied to the regulation problem and used to guarantee practical stability. The proposed controllers have a simple and explicit form, and hence are easily implemented. Simultaneously, fast convergence is guaranteed, thanks to the $\boldsymbol {\mathcal {K}}$ -exponential convergence. More interestingly, the used approach is adding sufficiently exciting signals to the systems by considering virtual tracking signals so that the attractivity of the origin can be guaranteed based on LaSalle invariance principle. Thus, it is possible to extend the proposed results to more general systems. To verify the effectiveness of the proposed scheme, interesting simulation results are presented.

The free energy principle says that any self-organising system that is at nonequilibrium steady-state with its environment must minimize its (variational) free energy. It is proposed as a grand unifying principle for cognitive science and biology. The principle can appear cryptic, esoteric, too ambitious, and unfalsifiable—suggesting it would be best to suspend any belief in the principle, and instead focus on individual, more concrete and falsifiable ‘process theories’ for particular biological processes and phenomena like perception, decision and action. Here, I explain the free energy principle, and I argue that it is best understood as offering a conceptual and mathematical analysis of the concept of existence of self-organising systems. This analysis offers a new type of solution to long-standing problems in neurobiology, cognitive science, machine learning and philosophy concerning the possibility of normatively constrained, self-supervised learning and inference. The principle can therefore uniquely serve as a regulatory principle for process theories, to ensure that process theories conforming to it enable self-supervision. This is, at least for those who believe self-supervision is a foundational explanatory task, good reason to believe the free energy principle.

We discuss the role of a heuristic principle known as the Principle of Permanence of Forms in the development of mathematics, especially in abstract algebra. We try to find some analogies in the development of modern formal logic. Finally, we add a few remarks on the use of the principle in question in mathematical education.

The physics-of-failure (PoF) technique is a practical approach to evaluate the reliability of semiconductor devices. However, the PoF approaches are usually insufficient in dealing with multi-mechanism failure and fitting the Monte Carlo (MC) sampling data. In our study, we propose an improved reliability evaluation method based on PoF technique and maximum entropy (MaxEnt) principle. The PoF models are used to generate time-to-failure samples of the failure mechanisms. Cumulative damage rules and competing failure rules are adopted to deal with multi-point and multi-mechanism failure and generate lifetime samples of the device. And the lifetime samples are fitted by MaxEnt distributions through the proposed fitting algorithm. The numerical examples given in the paper indicate that the MaxEnt distributions can describe the samples well and have a competitive advantage in dealing with multi-peak samples. A case study about a semiconductor device with multi-mechanism failure is presented to explain the workflow of the proposed reliability evaluation approach. The results show that the proposed MaxEnt distributions can yield reliable reliability evaluation results compared with Weibull and Lognormal distributions in the multi-mechanism failure process.

none 6 si This study proposes an approach to the construction of granular models directly based on information granules expressed both in input and output spaces. Associating these information granules, the con- structed granular models come in the framework of three layers networks: input granules, an inference scheme and output granules. The proposed approach consists of two stages. First, an augmented principle of justifiable granularity is proposed and applied to construct information granules in an input space. This principle constructs information granules not only through establishing a sound balance between two criteria, i.e., coverage and specificity, but also by optimizing those information granules on the basis of their homogeneity assessed with respect to data localized in output space. At the second stage, we propose an inference scheme by analyzing a location of an input datum in relation with the already formed information granules in an input space. The computed relation can be quantified as membership grades, thus yielding aggregation results involving information granules in an output space. The performance of the proposed granular model is supported by the mechanisms of granular computing and the principle of justifiable granularity. Experimental studies concerning synthetic and publicly available data are performed and some comparative analysis involving rule-based models is given. none Jing, TaiLong; Wang, Cong; Pedrycz, Witold; Li, ZhiWu; Succi, Giancarlo; Zhou, MengChu Jing, TaiLong; Wang, Cong; Pedrycz, Witold; Li, ZhiWu; Succi, Giancarlo; Zhou, MengChu

Deep neural networks have achieved breakthrough improvement in various application fields. Nevertheless, they usually suffer from a time-consuming training process because of the complicated structures of neural networks with a huge number of parameters. As an alternative, a fast and efficient discriminative broad learning system (BLS) is proposed, which takes the advantages of flat structure and incremental learning. The BLS has achieved outstanding performance in classification and regression problems. However, the previous studies ignored the reason why the BLS can generalize well. In this article, we focus on the interpretation from the viewpoint of the frequency domain. We discover the existence of the frequency principle in BLS, i.e., the BLS preferentially captures low-frequency components quickly and then fits the high frequencies during the incremental process of adding feature nodes and enhancement nodes. The frequency principle may be of great inspiration for expanding the application of BLS.

PurposeThe purpose of this paper is to report the first practical applications of FCAUP (Framework for Conformity Assessment inspired by the Uncertainty Principle) carried out using a pilot implementation in a boat trailer manufacturer company in Maryville, Tennessee, USA and a practical application in a metrology company in São José dos Campos, São Paulo, Brazil.Design/methodology/approachField studies have been conducted in two different companies: a pilot implementation during the preparation activities of the acceptance inspection of finished products and a practical application during the internal audit related to the quality management system.Findings(1) partial double inspection is advantageous in conformity assessment; (2) a structured procedure tends to reduce the risks arising from the use of partial double inspection; (3) the recommended amount of double inspections is directly proportional to the uncertainty involved in the process and it is inversely proportional to the degree of trust in a presumed conformity status.Research limitations/implicationsThis novel framework is for practitioners in manufacturing industries and test laboratories.Practical implicationsThe results of these practical applications suggest that FCAUP is a consistent approach to be used in several categories of conformity assessment in manufacturing industries and test laboratories due to the balance between result and time (cost).Originality/valueThis new framework, named FCAUP, for planning and executing conformity assessment activities has been introduced in a theoretical study published by Moraes and Silva (2018) and it is based on an analogy with the Uncertainty Principle of Quantum Mechanics.

Environmental issues associated with the development of mineral deposits are largely caused by the need to store mining and processing waste which becomes a source of environmental pollution. Large areas of dumped ore processing wastes determine the expediency of applying satellite data to monitor the environmental condition of the disturbed lands in order to make justified decisions on restoring the integrity of natural landscapes, which is crucial for the Arctic regions. The purpose of the research is to use the satellite data as the basis to reveal the dynamics of plant formation on the surrounding natural terrain when implementing the technology developed in the Mining Institute of the Kola Scientific Center of the Russian Academy of Sciences in accordance with the self-organizing principle of natural systems in the framework of the rock-biota system evolution. This is achieved by introducing a gramineous plant community without creating a fertile layer, which creates a biologically active environment. Analysis of the vegetation index obtained from a time series of the satellite data that characterizes the introduced vegetational change of the gramineous plant community on the bund wall slopes at the Khibiny group of apatite-containing ore deposits demonstrates the determinant influence of phytocoenotic factors on the recovery dynamics of natural ecosystems. A geobotanical study of the monitoring site has shown that in transition from the introduced gramineous to the forest stage of vegetational change, we observe a tier structure and large-scale resettlement of species from the adjacent natural areas, which is consistent with an increase in the vegetation index and allows to predict the dynamics of the natural ecosystem recovery.

A method of synthesis of a filter for estimating the state of dynamic systems of Kalman type with an adaptive model built on the basis of the principle of decomposition of the system using kinematic relations from the condition of constancy of motion invariants has been developed. The structure of the model is determined from the condition of the maximum function of the generalized power up to a nonlinear synthesizing function that determines the rate of dissipation and, accordingly, the degree of structural adaptation. The resulting model has an explicit relation with the gradient of the estimation error functional, which makes it possible to adapt to the intensity of regular and random influences and can be used to construct a filter for estimating the state of the Kalman structure. On the basis of the developed method, a discrete algorithm is obtained and its comparative analysis with the classical Kalman filter is carried out.

Redundancy in the constrained mechanical systems often occurs in complex multibody mechanic systems in the existence of excessive constraints and singular positions due to system motion. In this work, Gauss principle of least constraint (GPLC) is applied to solve the dynamic motion of system with redundant constraints without changing the physics of system. Furthermore, the particle swarm optimization method is used to handle the minimization optimization problem. Eventually, the effectiveness of GPLC is validated through the dynamic modelling and simulation of two numerical examples (a planar four-bar mechanism and a spatial parallelogram mechanism). The simulation results are analyzed and compared with those obtained from Udwaia-Phohomsiri formulation and augmented Lagrangian formulation, in terms of constraint violation, computational efficiency and variation of the mechanical energy. From the viewpoint of computational efficiency and accuracy, GPLC can be regarded as a practical real-time simulation method for multibody systems with redundant constraints.