Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain-Compatible Mathematics

Foreword Preface Publisher's Acknowledgements Introduction About the Author 1. Performance-Based Learning and Assessment Traditional Versus Brain-Friendly Assessments Importance of Performance Assessment Alignment of Curriculum and Assessment Assessment as Continuous Monitoring Assessment as Tool for Learning Grades K-2 Units 2. The Six Pillars of Performance Task Development Set Up Clear Performance Goals Employ "Authentic" Project Tasks Teach and Emphasize Criteria Levels and Performance Standards Provide Models and Demonstrations of Excellence Teach Strategies Explicitly Use Ongoing Assessments for Feedback and Adjustments Brain-Compatible Framework Grades 3-5 Units 3. Multiple Intelligences and Brain-Compatible Learning Theory of Multiple Intelligences Multiple Intelligences Model Assessment for Multiple Intelligences Grades 6-8 Units 4. Performance-Based Instructional Strategies Cooperative Learning Writing and Communicating in the Classroom Classroom Practice Challenge Project Unit 5. Problem-Solving Strategies Instructional Strategies Problem Exploration Heuristics Study Skills, Thinking Skills, and Thinking Processes Mnemonic Techniques Organizational Strategies Patterning Challenge Project Unit 6. Teaching and Assessing With the Rubric Scoring Rubrics Categories for Rubrics Types of Rubrics Brain-Compatible Assessment Challenge Project Unit 7. Teaching and Assessing With the Portfolio Student Evaluations Portfolio Assessment A Portfolio System Conclusion Principles and Standards for School Mathematics Glossary Resources Bibliography Index
Design and evaluation of robust nonlinear missile autopilots from a performance perspective

In this paper a general uncertainty model for a nonlinear missile system is developed, which assumes uncertainties in all aerodynamic force and moment generating terms in the equations of motion. These uncertainties are then bounded and used as a deterministic model in the design of two robust nonlinear missile autopilots. The first approach is an input/output linearized robust controller design, and the second is a recursive robust nonlinear controller design. The general uncertainty model is then used to define limited bandwidth stochastic perturbations for the evaluation of these autopilots. The resulting performance evaluations and comparisons are obtained through computer simulation and by Monte Carlo analysis.
The VAMAI-an abstract machine for incremental global data ow analysis of Prolog

A commonly used technique for global (cid:13)ow analysis of Prolog programs is abstract interpretation. Until now nearly all abstract interpretation systems for Prolog are research prototypes and very slow. These systems are not suitable for the integration in Prolog compilers. So we developed the VAMAI, an abstract machine for the abstract interpretation of Prolog. The Vienna Abstract Machine (VAM) is an abstract machine which has been designed to eliminate some weaknesses of the Warren Abstract Machine (WAM). Di(cid:11)erent versions of the VAM are used for di(cid:11)erent purposes. The VAM2P is well suited for interpretation, the VAM1P is aimed for native code generation. The VAM2P has been modi(cid:12)ed to the VAMAI, an abstract machine suited for abstract interpretation. The VAMAI does the data (cid:13)ow analysis by a factor of two hundred faster than the previous used meta interpreters written in Prolog. Preliminary results of intermediate code size and analysis time are presented.
Mathematical Approach to Computational Networks

Abstract : This report deals with design principles for iterative computational networks. Such computational networks are used for performing repetitive computations which typically are not data-dependent. Most of the signal processing algorithms, like FFT and filtering, belong to this class. The main idea in this report is the development of mathematical notation for expressing such designs. This notation captures the important features and properties of these computational networks, and can be used for analyzing, designing, and objectively evaluating computational networks.
Noun Phrase Licensing

This book examines the syntax of direct object noun phrases in English within the Principles and Parameters, specifically Chomsky's Minimalist Program, approach to generative grammar. The main focus is on the phrase structural positions of object noun phrases at the various levels of representation, and secondarily on the relationship between structural position and semantic interpretation. Supported by a variety of empirical and conceptual arguments, the central claim of the book is that direct object noun phrases in English surface in a VP-external position; a secondary claim is that while in the overt syntax direct objects appear VP-externally, their position at the level of logical form varies depending on interpretation. Four basic constructions are studied: simple transitive clauses, transitive clauses with prepositional objects, the "raising to object" construction, and the "double object" construction. This book will be of interest to scholars in the areas of phrase structure syntax, English and Germanic syntax, the syntax-semantics interface, and all areas of generative approaches to syntax.
Decision Theory: An Introduction to Dynamic Programming and Sequential Decisions

From the Publisher: Opening with a brief discussion of the historical background, the book describes deterministic models, in which the choice between decision is unaffected by chance. Then considering decision in the face of uncertainty, the material then closes with a discussion of more complex models, introduction the reader to a wide range of applications of the method.
An Introduction to Systemic Functional Linguistics

This new edition of the best-selling An Introduction to Systemic Functional Linguistics explores the social semiotic approach to language most closely associated with the work of Michael Halliday and his colleagues. An approach which views language as a strategic, meaning-making resource, systemic linguistics focuses on the analysis of authentic, everyday texts, and asks both how people use language to make meanings, and how language itself is organized to enable those meanings to be made. The book offers both an overview of systemic theory and illustrations of how systemic techniques can be applied in the analysis of everyday texts. Written for students who may have little or no formal knowledge of linguistics, it covers most of the major concepts in systemic linguistics. In addition, it introduces readers to Halliday's functional grammatical analysis of English clauses, and presents the essentials of the systemic analysis of cohesive patterns in text.
On the bias correction of general circulation model output for Indian summer monsoon

A general circulation model (GCM) is an alternative way for predicting Indian summer monsoon rainfall (ISMR) over the existing empirical/statistical models in recent time. However, the inherent biases present in the GCM affect its performance. Therefore, there is a high requirement for bias correction of the GCM. Few studies on bias correction of GCMs are available in the context of ISMR. A comparative study is reported in this paper on the six different bias correction methods by applying on the hindcast (May start, June–July–August–September) of the climate forecast system (CFS) model from the National Centers for Environmental Prediction (NCEP) for 27 years (1982–2008). Among the six methods discussed in this paper, three methods did not use any statistical transformation (Mean Bias‐remove technique (U), Multiplicative shift technique (M) and Standardized‐reconstruction technique (Z)) and the remaining three methods used statistical transformation (Regression technique (R), Quantile Mapping Method (Q), Principal Component Regression (PCR)). Finally, it was found that the Standardized‐reconstruction technique (Z) and Quantile Mapping Method (Q) are more skilful than the others and both are equally skilful in simulating ISMR. Bias‐corrected rainfall in four extreme years, out of which 1988 and 1994 are characterized by excess rainfall and 1987 and 2002 are characterized by deficit, are also examined here. Results indicate that both methods efficiently capture the extreme rainfall cases.
Modeling, identification, and compensation of friction in harmonic drives

Harmonic drives are increasingly used in precision positioning applications such as military radars, wafer handling machines, and satellite cameras. Precision tracking performance of these drives is deteriorated by nonlinear transmission attributes including kinematic error, flexibility, hysteresis and friction. Hence characterization and compensation of these nonlinear attributes is crucial to improve the precision in tracking and regulation. This paper focuses on modeling, identification, and compensation of nonlinear friction in harmonic drives. Harmonic drive friction models presented in the literature are found to be a combination of Coulomb and viscous friction. However, a dynamic friction phenomenon exhibits, in addition to Coulomb and viscous frictions, other nonlinear phenomena including the Dahl effect, and the Stribeck effect which must be considered in an accurate friction model. In addition, in this research, harmonic drive friction is discovered to be dependent on the motor position. Complete characterization of friction in harmonic drives is carried out in this paper by using a recently developed LuGre (Lund-Grenobel) friction model superimposed with a new position-dependent part. Parameters of the proposed model are identified using linear and nonlinear identification tools. Experimental implementation of a friction compensation scheme based on the proposed model demonstrates the effectiveness of the model.
Characterizing the program design activity : neither strictly top-down nor globally opportunistic

Abstract Early studies of programming and of other more general planning and problem-solving activities emphasized the hierarchical nature of such tasks. For instance, the dominant approach to problem-solving and planning views such processes as top-down focused activities which start from high level goals that are in turn decomposed into achievable actions via a successive refinement process. Similarly, empirical studies of the programming activity have highlighted such top-down and breadth-first decomposition strategies. These processes are also clearly mirrored in prescriptive accounts of the programming task. More recent characterizations of the programming activity present an alternative view—one which emphasizes the broadly opportunistic nature of the programming process. From this perspective, program design is seen to deviate from the top-down, breadth-first model proposed by previous studies. Here, program design is viewed as opportunistic in the sense that elements of the design can be created a.
English learners’ dictionaries on CD-ROM as reference and language learning tools

This paper discusses the findings of two empirical studies which investigated how students of English used two English learners’ dictionaries on CD-ROM. The outcome of these studies will indicate in what way such dictionaries can serve as reference and language learning tools. It is argued that an English learner’s dictionary on CD-ROM could be much more than an ‘ordinary’ reference work because it includes facilities that are not available in book form, such as audio and visual elements, exercises and games. The studies suggest, however, that a number of changes in content and design will have to be made in order to make such dictionaries more effective and beneficial to their users. Learners, on the other hand, may need to acquire special skills in order to benefit from all the information an English learner’s dictionary on CD-ROM contains.
Computational learning theory: an introduction

Computational learning theory is a subject which has been advancing rapidly in the last few years. The authors concentrate on the probably approximately correct model of learning, and gradually develop the ideas of efficiency considerations. Finally, applications of the theory to artificial neural networks are considered. Many exercises are included throughout, and the list of references is extensive. This volume is relatively self contained as the necessary background material from logic, probability and complexity theory is included. It will therefore form an introduction to the theory of computational learning, suitable for a broad spectrum of graduate students from theoretical computer science and mathematics.
Book Reviews: The Logic of Typed Feature Structures

For those of us who belonged to the "Bay Area (Computational) Linguistics Community," the early eighties were a heady time. Local researchers working on linguistics, computational linguistics, and logic programming were investigating notions of category, type, feature, term, and partial specification that appeared to converge to a powerful new approach for describing (linguistic) objects and their relationships by monotonic accumulation of constraints between their features. The seed notions had almost independently arisen in generalized phrase structure grammar (GPSG) (Gazdar et al. 1985), lexical-functional grammar (LFG) (Bresnan and Kaplan 1982), functionalunification grammar (FUG) (Kay 1985), logic programming (Colmerauer 1978, Pereira and Warren 1980), and terminological reasoning systems (Ait-Kaci 1984). It took, however, a lot of experimental and theoretical work to identify precisely what the core notions were, how particular systems related to the core notions, and what were the most illuminating mathematical accounts of that core. The development of the unificationbased formalism PATR-II (Shieber 1984) was an early step toward the definition of the core, but its mathematical analysis, and the clarification of the connections between the various systems, are only now coming to a reasonable closure. The Logic of Typed Feature Structures is the first monograph that brings all the main theoretical ideas into one place where they can be related and compared in a unified setting. Carpenter's book touches most of the crucial questions of the developments during the decade, provides proofs for central results, and reaches right up to the edge of current research in the field. These contributions alone make it an indispensable compendium for the researcher or graduate student working on constraint-based grammatical formalisms, and they also make it a very useful reference work for researchers in object-oriented databases and logic programming. Having discharged the main obligation of the reviewer of saying who should read the book under review and why, I will now survey each of the book's four parts while raising some more general questions impinging on the whole book as they arise from the discussion of each part.
A Literature Survey of the Internet Topology Generation Models

There has been much effort to improve the accuracy of the Internet topology model and include its quantitative and/or qualitative effects on studies of a variety of network problems. Such improvement is the primary motivation of this paper in listing and classifying the body of literature addressing the Internet topology. The metrics, which characterize the fundamental properties of the Internet, are also divided into five categories and their importance and applications are discussed. Finally, we suggest several future research topics for the Internet topology models to be more realistic and applicable.
Linear time logic control of linear systems with disturbances

The formal analysis and design of control systems is one of recent trends in control theory. In this area, in order to reduce the complexity and scale of control systems, finite abstractions of control systems are introduced and explored. In non-disturbance case, the controller of control systems is often generated from the controller of finite abstractions. Recently, Pola and Tabuada provide approximate finite abstractions for linear control systems with disturbance inputs. However, these finite abstractions and original linear systems do not always share the identical specifications, which obstructs designing controller (of linear systems) based on their finite abstractions. This paper tries to bridge such gap between linear systems and their finite abstractions.
Multiple Self-Organizing Maps for Control of a Redundant Manipulator with Multiple Cameras

Vision guide for a manipulator has been one of the major research issues in robotics. Coordination schemes of visuo-motor systems can be classified on the basis of the knowledge about manipulator kinematics and camera parameters. Many researchers have proposed a number of systems that deal with unknown manipulator kinematics and unknown camera parameters. In the studies, visuo-motor models are either estimated analytically during the execution of tasks on-line or learned prior to the execution off-line. Artificial neural networks can be used to learn the non-linear relationships between features in images and the manipulator joint angles. Miller et al. proposed a neural network based on the learning control system, where a cerebeller model arithmetic computer memory was employed for the learning (Miller, 1989). Carusone et al. used a network to train an uncalibrated industrial robot (Carusone & Eleurterio, 1998). In their systems, neural networks provided the estimation of the poses of targets in the manipulator coordinate frames, and the poses were used to guide the manipulator to grasp the objects. However, supervisors were needed in the systems. Self-organizing map (SOM) based on the Kohonen algorithm is an important unsupervised artificial neural network model (Kohonen, 1998). It has shown great potential in application fields such as motor control, pattern recognition, optimization, and so on, and also has provided insights into how mammalian brains are organized (Wiener et al., 2000) (Behera & Kirubanandan, 1999). During the past years it has been demonstrated that the SOM can solve the inverse kinematics problem for visuo-motor control. Buessler et al. determined arm movements by tracking an image target (Buessler & Urban, 1998) (Buessler et al., 1999). The correlation between an image-defined error and the joint movement was learned on-line using self-organizing algorithm for making the error zero. Multiple neural maps were combined to simplify neural learning in their study. Martinetz et al. and Walter et al. used a three dimensional lattice to learn the nonlinear transformation that specifies the joint angles of a 3-DOF manipulator so that the angles take the tip of the manipulator to a target point given in the coordinates provided by two cameras (Marinetz et al., 1990) (Walter & Schulten, 1993). In all of these studies, however, they solved the visuo-motor coordination problems 20
Corrected center-surround retinex: application to tone reproduction for high dynamic range images

The tone reproduction is a convenient way of rendering a high dynamic range (HDR) image on the display device with a relatively low dynamic range. This paper proposes an algorithm for tone reproduction based on retinex theory. The proposed model mainly consists of a global adaptation and a local tone reproduction. The global tone mapping is applied to enhance the light variation according to the global ambience of the image. The local tone reproduction is accomplished by the corrected center–surround retinex model. Center–surround retinex theory is corrected with a proposed three-zone histogram theory, which clearly defines the meaning of the reflectance for the local tone reproduction. Next, the illumination map is constructed based on the three-zone histogram theory, while considering the local and global light scattering. Hence, the corrected center–surround retinex consults with not only the surrounding luminance of each pixel, but also the information of the overall histogram. Experimental results show that the proposed algorithm is robust for processing various HDR images and the resulting images are visually pleasing. The merit of the proposed algorithm lies in the balanced presentation of both the whole contrast and details in an image.
Action Meets Word: How Children Learn Verbs

Introduction: Progress on the Verb Learning Front PART I PREREQUISITES TO VERB LEARNING: FINDING THE VERB 1. Finding the Verbs: Distributional Cues Available to Young Learners 2. Finding Verb Dorms Within the Continuous Speech Stream 3. Discovering Verbs Through Multiple-Cue Integration PART II PREREQUISITES TO VERB LEARNING: FINDING ACTIONS IN EVENTS 4. Actions Organize the Infant's World 5. Conceptual Foundations for Verb Learning: Celebrating the Event 6. Precursors to Verb Learning: Infants' Understanding of Motion Events 7. Preverbal Spatial Cognition and Language-Specific Input: Categories of Containment and Support 8. The Roots of Verbs in Prelinguistic Action Knowledge 9. When Is a Grasp a Grasp? Characterizing Some Basic Components of Human Action Processing 10. Word, Intention, and Action: A Two-Tiered Model of Action Word Learning 11. Verbs, Actions, and Intentions PART III WHEN ACTION MEETS WORD: CHILDREN LEARN THEIR FIRST VERBS 12. Are Nouns Easier to Learn Than Verbs? Three Experimental Studies 13. Verbs at the Very Beginning: Parallels Between Comprehension and Input 14. A Unified Theory of Word Learning: Putting Verb Acquisition in Context 15. Who's the Subject? Sentence Structure and Verb Meaning PART VI HOW LANGUAGE INFLUENCES VERB LEARNING: CROSS-LINGUISTIC EVIDENCE 16. Verb Learning as a Probe Into Children's Grammars 17. Revisiting the Noun-Verb Debate: A Cross-Linguistic Comparison of Novel Noun and Verb Learning in English-, Japanese- and Chinese-Speaking Children 18. But Are They Really Verbs? : Chinese Words for Action 19. Influences of Object Knowledge on the Acquisition of Verbs in English and Japanese 20. East and West: A Role for Culture in the Acquisition of Nouns and Verbs 21. Why Verbs are Hard to Learn
Bayesian molecular phylogenetics : estimation of divergence dates and hypothesis testing

With the advent of automated sequencing, sequence data are now available to help us understand the functioning of our genome, as well as its history. To date,powerful methods such as maximum likelihood have been used to estimate its mode and tempo of evolution and its branching pattern. However, these methods appear to have some limitations. The purpose of this thesis is to examine these issues in light of Bayesian modelling, taking advantage of some recent advances in Bayesian computation. Firstly, Bayesian methods to estimate divergence dates when rates of evolution vary from lineage to lineages are extended and compared. The power of the technique is demonstrated by analysing twenty-two genes sampled across the metazoans to test the Cambrian explosion hypothesis. While the molecular clock gives divergence dates at least twice as old as those indicated by the fossil records, it is shown (i) that modelling rate change gives results consistent with the fossils, (ii) that this improves dramatically the fit to the data and (iii) that these results are not dependent on the choice of a specific model of rate change.Results from this analysis support a molecular explosion of the metazoans about 600 million years (MY) ago, i.e. only some 50 MY before the morphological Cambrian explosion. Secondly, two new Bayesian tests of phylogenetic trees are developed. The first aims at selecting the correct tree, while the second constructs confidence sets of trees. Two other tests are also developed, in the frequentist framework. Based on p-values adjusted for multiple comparisons,they are built to match their Bayesian counterparts. These four new tests are compared with previous tests. Their sensitivity to model misspecification and the problem of regions is discussed. Finally, some extensions to the models examined are made to estimate divergence dates from data of multiple genes, and to detect positive selection.