The Great Psychotherapy Debate: Models, Methods, and Findings comprehensively reviews the research on psychotherapy to dispute the commonly held view that the benefits of psychotherapy are derived from the specific ingredients contained in a given treatment (medical model). The author reviews the literature related to the absolute efficacy of psychotherapy, the relative efficacy of various treatments, the specificity of ingredients contained in established therapies, effects due to common factors, such as the working alliance, adherence and allegiance to the therapeutic (...) protocol, and effects that are produced by different therapists. In each case, the evidence convincingly corroborates the contextual model and disconfirms the prevailing medical model. (shrink)

This collaborative publication offers salient instructional models, methods, and modalities centered on the whole person.

The relationship between methods, statistics and models in the social sciences is discussed. New models generalizing commonly used linear models to deal with qualitative and ordinal data are introduced; their basic similarity to linear models is pointed out. Rate models and stochastic linear differential equations to model social processes in continuous time are mentioned. The implications of weak substantial theory and the correct use of statistical significance tests for any kind of model are demonstrated.

The Context Comparison Model provides a promising avenue to guide persuasive communication development by highlighting the features of the communication context that require consideration, including source, target, and task variables. The model was tested in a study of global climate change. American participants read a text outlining scientific evidence for global climate change and a policy proposal to mitigate future climate change. Prior to reading the text, participants’ completed measures of their political affiliation to render their group memberships (...) salient. They were randomly assigned to one of four source conditions: ingroup minority; ingroup majority; outgroup minority; or outgroup minority. Participants completed pre- and post-measures of attitudes and the plausibility of climate change. Pretest scores revealed that global climate change attitudes were held less strongly by Republicans than Democrats. In line with expectations, participants’ subjective attitudes were more influenced by ingroup sources, and larger persuasive effects were obtained for ingroup minorities. For the plausibility of climate change, participants were more persuaded by an outgroup source, and larger effects were evident for outgroup majorities. Results were precisely predicted by the CCM. Their implications for science communication were discussed. (shrink)

A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge (...) bioengineering scientists integrate the cognitive, social, material, and cultural dimensions of practice. Her findings and conclusions have broad implications for researchers in philosophy, science studies, cognitive science, and interdisciplinary studies, as well as scientists, educators, policy makers, and funding agencies. In studying the epistemic practices of scientists, Nersessian pushes the boundaries of the philosophy of science and cognitive science into areas not ventured before. She recounts a decades-long, wide-ranging, and richly detailed investigation of the innovative interdisciplinary modeling practices of bioengineering researchers in four university laboratories. She argues and demonstrates that the methods of cognitive ethnography and qualitative data analysis, placed in the framework of distributed cognition, provide the tools for a philosophical analysis of how scientific discoveries arise from complex systems in which the cognitive, social, material, and cultural dimensions of problem-solving are integrated into the epistemic practices of scientists. Specifically, she looks at how interdisciplinary environments shape problem-solving. Although Nersessian’s case material is drawn from the bioengineering sciences, her analytic framework and methodological approach are directly applicable to scientific research in a broader, more general sense, as well. (shrink)

This collection of essays deals with three clusters of problems in the philo sophy of science: scientific method, conceptual models, and ontological underpinnings. The disjointedness of topics is more apparent than real, since the whole book is concerned with the scientific knowledge of fact. Now, the aim of factual knowledge is the conceptual grasping of being, and this understanding is provided by theories of whatever there may be. If the theories are testable and specific, such as a theory of (...) a particular chemical reaction, then they are often called 'theoretical models' and clas sed as scientific. If the theories are extremely general, like a theory of syn thesis and dissociation without any reference to a particular kind of stuff, then they may be called 'metaphysical' - as well as 'scientific' if they are consonant with science. Between these two extremes there is a whole gamut of kinds of factual theories. Thus the entire spectrum should be dominated by the scientific method, quite irrespective of the subject matter. This is the leitmotiv of the present book. The introductory chapter, on method in the philosophy of science, tackles the question 'Why don't scientists listen to their philosophers?'. (shrink)

An important method for finding the optimal solution for linear and nonlinear models is the graphical method, which is used if the linear or nonlinear mathematical model contains one, two, or three variables. The models that contain only two variables are among the most models for which the optimal solution has been obtained graphically, whether these models are linear or non-linear in references and research that are concerned with the science of operations research, when the data of (...) the issue under study is classical data. In this research, we will present a study through, which we present the graphical method for solving Neutrosophical nonlinear models in the following case: A nonlinear programming issue, the objective function is a nonlinear function, and the constraints are linear functions. Note that we can use the same method if (i) the objective function follower is a linear follower and the constraints are nonlinear; (ii) the objective function is a non-linear follower and the constraints are non-linear. In the three cases, the nonlinear models are neutrosophic, and as we know, the mathematical model is a nonlinear model if any of the components of the objective function or the constraints are nonlinear expressions, and the nonlinear expressions may be in both. At the left end of the constraints are neutrosophic values, at least one or all of them. Then, the possible solutions to the neutrosophic nonlinear programming problem are the set of rays that fulfills all the constraints. As for the region of possible solutions, it is the region that contains all the rays that fulfill the constraints. The optimal solution is the beam that fulfills all constraints and at which the function reaches a maximum or minimum value, depending on the nature of the issue under study (noting that it is not necessary to be alone). (shrink)

We present a new method of constructing a model of \SCH+\AP.

This book publishes 31 of the author's selected papers which have appeared, with one exception, since 1970. The papers cover a wide range of topics in the philosophy of science. Part I is concerned with general methodology, including formal and axiomatic methods in science. Part II is concerned with causality and explanation. The papers extend the author's earlier work on a probabilistic theory of causality. The papers in Part III are concerned with probability and measurement, especially foundational questions about probability. (...) Part IV consists of several papers, including two historical ones, on the foundations of physics, with the main emphasis being on quantum mechanics. Part V, the longest part, is on the foundations of psychology and includes papers mainly on learning and perception. The book is aimed at philosophers of science, scientists concerned with the methodology of the social sciences, and mathematical psychologists interested in theories of learning, perception and measurement. (shrink)

We show how to build various models of first-order theories, which also have properties like: tree with only definable branches, atomic Boolean algebras or ordered fields with only definable automorphisms. For this we use a set-theoretic assertion, which may be interesting by itself on the existence of quite generic subsets of suitable partial orders of power λ + , which follows from ♦ λ and even weaker hypotheses . For a related assertion, which is equivalent to the morass see Shelah (...) and Stanley [16]. The various specific constructions serve also as examples of how to use this set-theoretic lemma. We apply the method to construct rigid ordered fields, rigid atomic Boolean algebras, trees with only definable branches; all in successors of regular cardinals under appropriate set- theoretic assumptions. So we are able to answer the following algebraic question. Saltzman's Question . Is there a rigid real closed field, which is not a subfield of the reals? (shrink)

In this paper we describe a method for the specification of computationalmodels of argument using dialogue games. The method, which consists ofsupplying a set of semantic definitions for the performatives making upthe game, together with a state transition diagram, is described in full.Its use is illustrated by some examples of varying complexity, includingtwo complete specifications of particular dialogue games, Mackenzie's DC,and the authors' own TDG. The latter is also illustrated by a fully workedexample illustrating all the features of (...) the game. (shrink)

The self-disorder model provides a phenomenological framework for understanding how the core symptoms of Schizophrenia Spectrum Disorders (SSDs) are rooted in an instability of minimal selfhood. This instability involves a range of “anomalous experiences”: transformations in an individual’s perceptual field and sense of being an agent of action. The explanatory value of this theoretical model can be summarized in two claims about the role of anomalous experiences in self-disorders: (1) anomalous experiences express a common trait-like disturbance that is (...) characteristic of SSDs, and (2) anomalous experiences contribute to explanations regarding how self-disorders progress into SSDs. While hypotheses consistent with the first claim have been substantiated in several studies, hypotheses consistent with the second claim remain underexamined. We argue that attending to this gap in the literature requires considering which methodological strategies are best suited for investigating if and how anomalous experiences contribute to the development of self-disorders into SSDs and psychotic states. Network modeling is discussed as one such strategy suitable for examining the role of anomalies of lived-world in the maintenance of paranoid delusions in SSDs. (shrink)

ABSTRACTJohn Pocock gave “A method, a model and Machiavelli” as a talk at Princeton University in 1968. What happened to the text afterwards is uncertain, but it remained in the papers of Professor Donald Weinstein until his death in 2015, when it was identified by his widow Beverly Parker as being of importance. The text is especially revealing about Pocock’s attitudes to the history of ideas/intellectual history in the late 1960s and more especially the state of the grand (...) project that became The Machiavellian Moment some years later. (shrink)

This paper employs the methodological framework of linguistic analytic philosophy to explore the conceptual issues arising from a study of the different models of disorder implicit in five groups of stakeholders concerned in the community care of people with a diagnosis of long-term schizophrenia. Linguistic analysis, gives a precise fix on the nature of the practical difficulties presented by such models, suggests a powerful heuristic for displaying and comparing models, is the basis of a methodology which is neutral as between (...) users and providers of services, provides an intuitively powerful way of understanding the results of work of this kind, and facilitates the translation of research into practice. (shrink)

A model predictive control method based on recursive backpropagation neural network and genetic algorithm is proposed for a class of nonlinear systems with time delays and uncertainties. In the offline modeling stage, a multistep-ahead predictor with GA-RBP neural network is designed, where GA-BP neural network is used as a one-step prediction model and GA is employed to train the initial weights and bias of the BP neural network. The incorporation of GA into RBP can reduce the possibility (...) of the BP neural network falling into a local optimum instead of reaching global optimization. In the online optimizing stage, a multistep-ahead GA-RBP neural network predictor and an improved gradient descent method are proposed to efficiently solve the online optimization problem of nonlinear MPC by minimizing a modified quadratic criterion. The designed MPC strategy can avoid information loss while linearizing the controlled system and computing the Hessian matrix and its inverse matrix. Experimental results show that the proposed approach can reduce the computational burden and improve the performance of MPC for the solution of nonlinear controlled systems. (shrink)

The case of the Arabian babblers is a controversial and significant one in ethology that troubles standard sociobiological theories of the evolution of behaviour. In this chapter from her book Naissance d'une théorie éthologique, Vinciane Despret examines the divergent models and methods of the scientists studying the babblers, their different epistemologies and ontologies that are only truly visible and understandable if one takes into account their particular ways of comporting themselves with the birds, and the babblers’ active role in writing (...) their own scripts. In so far as it resembles the immersive participation and individual biographing of anthropological and primatological methods, and pays skilful attention to the reasons for their actions, Zahavi's way of relating to and questioning the babblers gives them the opportunity to respond. (shrink)

This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues that, although often useful in specific settings, most of these approaches are limited in their ability to give a general assessment of models. This article argues that hierarchical methods, generally, and hierarchical Bayesian methods, specifically, can provide (...) a more thorough evaluation of models in the cognitive sciences. This article presents two worked examples of hierarchical Bayesian analyses to demonstrate how the approach addresses key questions of descriptive adequacy, parameter interference, prediction, and generalization in principled and coherent ways. (shrink)

In order to obtain a new structure of beam flexure hinge with good performance, the flexure hinge based on the X-lattice structure is researched in this paper. The truss model in the finite element method is used to model the 6-DOF compliance of the flexure hinge based on the X-lattice structure. The influence of structural parameters on the compliance and compliance ratio of flexure hinges is analyzed based on this model, and the performance is compared with (...) the traditional beam flexure hinge of the same size. In order to design a flexure hinge based on the X-lattice structure with good comprehensive performance, this paper proposes an intelligent structure optimization method based on a genetic algorithm. The feasibility of the optimization algorithm is verified by an example. (shrink)

Water quality control helps in the estimation of water bodies and detects the span of pollutants and their effect on the neighboring environment. This is why the water quality of the northern part of Lake Manzala has been studied here from January to March, 2016. This study aims to model and create a program for linear and nonlinear regression of the water elements in Lake Manzala to assess and predict the water quality. Water samples have been extracted from various (...) depths, and physio-chemical properties and heavy metal concentrations have been evaluated. This study has proposed a new algorithm for predicting water quality called “Algorithm of Estimation Regression Model”. On the contrary, in renewable energy applications, statistical modeling and forecasting the solar radiation remains a significant issue with detect to reinforce power management. A new proposed method for forecasting the average Monthly Global Solar Energy in Queensland, Australia, is called, Converting Data Set into Markov Model. It was used to obtain Markov transition probability matrices for three and six states of the solar energy. The proposed forecasting method yielded accurate results with minimal error. (shrink)

The semantic method of extension and intension presented by Rudolf Carnap may have some problems from the current perspective in cognitive science. For example, that method is strongly linked to logic, and it is hard to determine where its state-descriptions come from, how many they are, and what the relation of accessibility between them is. This paper tries to solve difficulties such as those by updating the method resorting to the theses and results of a contemporary reasoning (...) theory: the theory of mental models. Basically, the update consists of replacing the state-descriptions of the original method with the possibilities of the theory of mental models. That allows reformulating several relevant concepts in Carnap’s method in order to better adjust them to the real characteristics of human language. (shrink)

As is well known, some paradoxes arise through inadequate analysis of the meanings of terms in a language, an adequate analysis showing that the paradoxes arise through a lack of separation of an object theory and a metatheory. Under such an adequate analysis in which parts of the metatheory are modelled in the object theory, the paradoxes give way to remarkable theorems establishing limitations of the object theory.Such a modelling is often accomplished by a Gödel numbering. Here we shall use (...) a somewhat different technique in axiomatic set theory, from which we shall reap a few results having the effect of comparing the strength of various axiom schema of comprehension for sets and classes. Similar results were obtained by A. Mostowski [7] using Gödel numbering. (shrink)

It is a hallmark of a good model to make accurate a priori predictions to new conditions (Busemeyer & Wang, 2000). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the parameters for each participant from 1 task and using those same parameters to predict on the other task. Three methods were used to (...) evaluate the models at the individual level of analysis. The first method used a post hoc fit criterion, the second method used a generalization criterion for short‐term predictions, and the third method again used a generalization criterion for long‐term predictions. The results suggest that the models with the prospect utility function can make generalizable predictions to new conditions, and different learning models are needed for making short‐versus long‐term predictions on simple gambling tasks. (shrink)

Changemaker Education is a collection of practitioner-based case studies that highlight the why, what, and how of empowering educational experiences.

The construction of models plays a vital part in scientific thought.And many questions about the characteristics demanded of a good model, and the implications of using models are often asked by philosophers of science. Although models are frequently and successfully used in scientific explanation, this does not imply that they are a necessary feature of such explanation, though it does provide some justification for their use. However, any attempt to provide a model for a scientific theory undoubtedly leads (...) to a clearer understanding of that theory. Models and theories are often considered as separate features in a scientific explanation, but a theory is not usually devised and then consciously provided with a model. (shrink)

In this paper, we propose the model averaging estimation method for multiplicative error model and construct the corresponding weight choosing criterion based on the Kullback–Leibler divergence with a hyperparameter to avoid the problem of overfitting. The resulting model average estimator is proved to be asymptotically optimal. It is shown that the Kullback–Leibler model averaging estimator asymptotically minimizes the in-sample Kullback–Leibler divergence and improves the forecast accuracy of out-of-sample even under different loss functions. In simulations, we (...) show that the KLMA estimator compares favorably with smooth-AIC estimator, smooth-BIC estimator, and Mallows model averaging estimator, especially when some nonlinear noise is added to the data generation process. The empirical applications in the daily range of S&P500 and price duration of IBM show that the out-of-sample forecasting capacity of the KLMA estimator is better than that of other methods. (shrink)

Observability is a modelling property that describes the possibility of inferring the internal state of a system from observations of its output. A related property, structural identifiability, refers to the theoretical possibility of determining the parameter values from the output. In fact, structural identifiability becomes a particular case of observability if the parameters are considered as constant state variables. It is possible to simultaneously analyse the observability and structural identifiability of a model using the conceptual tools of differential geometry. (...) Many complex biological processes can be described by systems of nonlinear ordinary differential equations and can therefore be analysed with this approach. The purpose of this review article is threefold: to serve as a tutorial on observability and structural identifiability of nonlinear systems, using the differential geometry approach for their analysis; to review recent advances in the field; and to identify open problems and suggest new avenues for research in this area. (shrink)

After a few considerations on the limited value of reasoning by analogy, the author distinguishes between analogy, homology and model, as illustrated by electro‐pneumatic, electro‐mechanical and electro‐thermic homologies. On the other hand, there exist numerous models of a same process: mathematical and symbolic models, graphic models, analogic and numeric models. The paper ends with remarks on the limits and the applications of models, namely in adaptative systems, as well as on their philosophical scope.

Scientists, Engineers, Technocrats, Academicians, and Researchers have a vital role to play in the process of emergence of new theories, models, systems, and technologies. They also have a responsibility to harness these for common good and strive to prevent their possible ill effects in the era of rapid growth in technologies. ICM2ST-10 will play a significant role in generating awareness about the potential and the limitations of new technologies, concepts, theories, and trends. The chief objective of ICM2ST-10 is to bring (...) together experts from industries, academia, R&D institutions and other user communities on a common platform to discuss and share their expertise and experiences. (shrink)

The linear programming method is one of the important methods of operations research that has been used to address many practical issues and provided optimal solutions for many institutions and companies, which helped decision makers make ideal decisions through which companies and institutions achieved maximum profit, but these solutions remain ideal and appropriate in If the conditions surrounding the work environment are stable, because any change in the data provided will affect the optimal solution and to avoid losses and (...) achieve maximum profit, we have, in previous research, reformulated the linear models using the concepts of neutrosophic science, the science that takes into account the instability of conditions and fluctuations in the work environment and leaves nothing to chance. While taking data, neutrosophic values carry some indeterminacy, giving a margin of freedom to decision makers. In another research, we reformulated one of the most important methods used to solve linear models, which is the simplex method, using the concepts of this science, and as a continuation of what we did in the previous two researches, we will reformulate in this research. The graphical method for solving linear models using the concepts of neutrosophics. We will also shed light on a case that is rarely mentioned in most operations research references, which is that when the difference between the number of unknowns and the number of constraints is equal to one, two, or three, we can also find the optimal solution graphically for some linear models. This is done by taking advantage of the conditions of non-negativity that linear models have, and we will explain this through an example in which the difference is equal to two. Also, through examples, we will explain the difference between using classical values and neutrosophic values and the extent of this’s impact on the optimal solution. (shrink)