Miracle-dz/UniFAR-FTUs huggingface dataset:
Shape Reconstruction in a Planar Dynamic Environment

We present a new method to reconstruct the shape of an unknown object using tactile sensors, without requiring object immobilization. Instead, sensing and nonprehensile manipulation occur simultaneously. The robot infers the shape, motion and center of mass of the object based on the motion of the contact points as measured by the tactile sensors. We present analytic results and simulation results assuming quasistatic dynamics. We prove that the shape and motion are observable in both the quasistatic and the fully dynamic case.
Studies in Interactional Linguistics

1. Foreword (by Thompson, Sandra A.) 2. Introducing Interactional Linguistics (by Couper-Kuhlen, Elizabeth) 3. Part I. Language structure in interaction 4. Emerging syntax for interaction: Noun phrases and clauses as a syntactic resource for interaction (by Helasvuo, Marja-Liisa) 5. At the intersection of turn and sequence: Negation and what comes next (by Ford, Cecilia E.) 6. The implementation of possible cognitive shifts in Japanese conversation: Complementizers as pivotal devices (by Tanaka, Hiroko) 7. On causal clause combining: The case of 'weil' in spoken German (by Scheutz, Hannes) 8. Dutch 'but' as a sequential conjunction: Its use as a resumption marker (by Mazeland, Harrie) 9. On some uses of the discourse particle 'kyl(la)' in Finnish conversation (by Hakulinen, Auli) 10. Interactional Linguistics and language development: A conversation analytic perspective on emergent syntax (by Corrin, Juliette) 11. Part II. Interactional order and linguistic practice 12. Fragments of units as deviant cases of unit production in conversational talk (by Selting, Margret) 13. Notes on turn-construction methods in Danish and Turkish conversation (by Steensig, Jakob) 14. An exploration of prosody and turn projection in English conversation (by Fox, Barbara A.) 15. Postposition-initiated utterances in Japanese conversation: An interactional account of a grammatical practice (by Hayashi, Makoto) 16. Confirming intersubjectivity through retroactive elaboration: Organization of phrasal units in other-initiated repair sequences in Korean conversation (by Kim, Kyu-hyun) 17. Some arguments for the relevance of syntax to same-sentence self-repair in everyday German conversation (by Uhmann, Susanne) 18. Simple answers to polar questions: The case of Finnish (by Sorjonen, Marja-Leena) 19. List of contributors 20. Index
Cloud Removal of Optical Image Using SAR Data for ALOS Applications. Experimenting on Simulated ALOS Data

Cloud is always problem of optical remote sensing data. ALOS-AVNIR2 images also will be affected. Microwave images are not affected by cloud. ALOS satellite has both optical and microwave sensor, similar resolution (~10m). Therefore, main purpose of this study is to develop a method for removing cloud in ALOS-AVNIR2 images based on ALOS-PALSAR data. This method is developed based on interpolating under cloud pixel values for ALOS-AVNIR2 images. To remove cloud, it needs to be defined. A combination method of Total Reflectance Radiance Index (TRRI) and Cloud-Soil Index (CSI) is used to define cloud. Around cloud pixels are mixture of cloud and other objects. So, that is very difficult to define. Therefore, the around cloud pixels are extended from cloud. Cloud shadow problem also is discussed in this study. Condition to apply this method is that objects in optical image and radar image change not very much. This method is experimented on simulated ALOS data from Landsat TM and JERS1-SAR images. Interpolated image is a free cloud and shadow image. Visual logic of objects is good. Original image and interpolated image is almost similar together. This method also can be applied for combination of two optical images to remove cloud if change of objects covered by cloud is not so much. Result of this study is a program with many functions like: define cloud, extend cloud, get shadow, remove cloud and so on. This is free software for every user.
Phonology and Phonetics

We investigated whether compensation for phonological assimilation in the first language depends on language specific knowledge of phonological processes. To this end, we tested two different assimilation rules, one that exists in English and involves place of articulation, and another that exists in French and involves voicing. Both contrasts were tested on speakers of French and American English. In two experiments using a word detection task, we observed that participants showed a significantly higher degree of compensation for phonological changes that correspond to rules existing in their language than to rules that do not exist in their language (even though they are phonologically possible since they exist in another language). Thus, French participants compensated more for voicing than place assimilation, while American English participants compensated more for place than voicing assimilation. In both experiments, we also found that the non-native rule induced a very small but significant compensation effect, suggesting that both a languagespecific and a language-independent mechanism are at play. Control experiments ensured that changes in stimuli were clearly perceived in isolation, compensation then being due to the phonological context of change, rather than to specific phonetic cues. The results are discussed in light of current models of lexical access and phonological processing.
But who's the man? Representations of sexuality and the feminist potential of orange is the new black

The amount of sexual content on television has grown exponentially over the last two decades. Much of this content works to enforce heteronormative ideals and demonstrate a male/active, female/passive dichotomy when performing sexuality. This mixed-methods study explored the representations of sexuality on the first season of the female-centric show Orange is the New Black from a critical feminist perspective. Interactions between three couples on the show were analyzed for the presence of the heterosexual script through a quantitative content analysis. Each of the couples, which included two queer relationships, enacted this script in their performance of sexuality. Five adult women who self-identify as feminist were interviewed to explore their opinions on the representations of sexuality on the show, analyzed through thematic analysis. Important barriers that participants noted the show had broken included having a diverse cast, a prominent transgender character, and presenting sexuality as part of larger narratives. Yet, participants questioned numerous aspects of the show, underlining a consensus that the show was not working to combat the dominant discourse of patriarchy through any meaningful ways.
Bayesian Nets and Causality: Philosophical and Computational Foundations

Bayesian nets are widely used in artificial intelligence as a calculus for casual reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover casual relationships. This book, aimed at researchers and graduate students in computer science, mathematics and philosophy, brings together two important research topics: how to automate reasoning in artificial intelligence, and the nature of causality and probability in philosophy.
Essentials of Skilled Helping: Managing Problems, Developing Opportunities

This booklet, written by Gerry Egan, with assistance from Rich McGourty and Hany Shamshoum (cultural insights and edits), demonstrates how the skills described in the Egan book apply to situations with people from different cultures. Egan relates anecdotes about his experiences abroad and in the U.S. with people from different cultures. He goes through the basic skills and describes how each should be used with diverse populations. Thirty-three personalizing exercises provide students with the opportunity to apply the skills covered in the booklet. Bundled free with every new copy of the text!
CHAPTER 5 : Maharashtra case study summary

Marx postulated that “The history of all hitherto existing society is the history of class struggles” (Marx and Engels, 1848). But many scholars engaged in dalit studies assert, “the history of hitherto existing society in India is the history of caste struggles” (Gait, 1913; Ghurye, 1961; Kancha Illaia, 1993; Omvedt, 2012). Though the debate about the root cause of such social setting in India remains inconclusive, there is little disagreement over the fact that, in Indian society, certain social groups and religious minorities such as Dalits, Adivasis and Muslims have been facing exclusion, discrimination and deprivation for generations. This phenomenon remains unabated even after the Indian constitution prohibited identity based discriminatory practices. Like other states, caste based discrimination is not uncommon in Maharashtra, as is evident from the recent violence against specific castes in the state (Khairilanji incident).
Assessing two-year-olds' knowledge of number agreement morphology

Previous research in the area of children’s knowledge of number agreement morphology has yielded mixed results. Some researchers have found evidence for sensitivity to agreement morphology at as early as 16 months, while others report that children do not comprehend number agreement morphology until as late as five or six years old. Studies of children’s production of these forms suggest that while children go through a period of optionally using agreement morphemes as part of the Optional Infinitive stage of development, they show productive use of these morphemes at age two. Therefore, some researchers have concluded that this is an area of the grammar where production precedes comprehension. This general pattern of findings has several possible explanations, three of which will be described here. The general goal of the current study was to provide new information to this area of inquiry, with a particular focus on children’s comprehension of “is” and “are” as well as plural –s marking on nouns. To address possible methodological issues with picture selection and looking-time studies, a manual search task was used to tap receptive knowledge of these forms. Forty-eight 30to 36-month-old children were tested on their receptive knowledge if “is,” “are,” and singular/plural distinctions on nous. Additionally, these children were given multiple assessments of their language production abilities and their non-verbal mental abilities. Results indicated that two-year-olds can comprehend noun morphology indicating number, but failed to show comprehension of “is” and “are. ” Additionally, when provided with both noun and verb information, the presence of the verb provided no added benefit to the children in terms strengthening their interpretation of the verbal prompts, suggesting that noun information regarding number is sufficient for sentence interpretation in two-year-olds. Analyses of
ELIMINATING BIAS DUE TO THE REPEATED MEASUREMENTS PROBLEM IN SP DATA

Usually in Stated Preference (SP) surveys a number of choice observations is taken from each individual to reduce the cost of data collection. This raises the so-called "repeated measurements" problem. Observations taken from the same individual are not independent, which means that simple analysis methods may be biased. In this paper the application of the Jackknife and the Bootstrap techniques to attack this problem are described in the case of a simple Logit model, and their relative performance compared. The Jackknife and Bootstrap are used to investigate bias due to serial correlation, the influence of the size of the Jackknife sample, the influence of the error distribution for each respondent individually and across respondents, and the variance estimate of the model coefficients obtained in the course of Maximum-likelihood estimation. The estimation of variance in Logit models is important in the assessment of the accuracy of estimated parameters based on SP data. These procedures also have applications in joint SP-RP modelling. For the covering abstract, see IRRD 889300.
Fast machine learning algorithms for large data

Traditional machine learning has been largely concerned with developing techniques for small or modestly sized datasets. These techniques fail to scale up well for large data problems, a situation becoming increasingly common in today’s world. This thesis is concerned with the problem of learning with large data. In particular, it considers solving the three basic tasks in machine learning, viz., classification, regression and density approximation. We develop fast memory- efficient algorithmics for kernel machine training and deployment. These include considering efficient preprocessing steps for speeding up existing training algorithms as well as developing a general purpose framework for machine learning using kernel methods. Emphasis is placed on the development of computationally efficient greedy schemes which leverage state-of-the-art techniques from the field of numerical linear algebra. The algorithms presented here underline a basic premise that it is possible to efficiently train a kernel machine on large data, which generalizes well and yet has a sparse expansion leading to improved runtime performance. Empirical evidence is provided in support of this premise throughout the thesis.
Statistics, Data Mining, and Machine Learning in Astronomy

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, engage with the different methods, and adapt them to their own fields of interest. An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date. Fully revised and expanded Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from astronomical surveys Uses a freely available Python codebase throughout Ideal for graduate students, advanced undergraduates, and working astronomers
Stochastic Processes: Theory and Methods

J. Neyman, one of the pioneers in laying the foundations of modern statistical theory, stressed the importance of stochastic processes in a paper written in 1960 in the following terms: Currently in the period of dynamic indeterminism in science, there is hardly a serious piece of research, if treated realistically, does not involve operations on stochastic processes. Arising from the need to solve practical problems, several major advances have taken place in the theory of stochastic processes and their applications. Books by Doob (1953; J. Wiley and Sons), Feller (1957, 1966; J. Wiley and Sons) and Loeve (1960; D. van Nostrand and Col., Inc.) among others, have created growing awareness and interest in the use of stochastic processes in scientific and technological studies.The literature on stochastic processes is very extensive and is distributed in several books and journals.
Static and dynamic methods of polyhedral compilation for an efficient execution in multicore environments

Depuis plusieurs annees, le nombre de cœurs de calcul dans les processeurs ne cesse d'augmenter a chaque nouvelle generation. Les processeurs multi-cœurs sont maintenant tres frequents mais le developpement de logiciels sequentiels reste une pratique tres courante. Pour pallier a ce probleme, des outils de parallelisation automatique ont ete proposes mais ils ne sont pas encore prets pour une utilisation a grande echelle. Nous proposons d'etendre les outils existants dans trois directions differentes. Premierement, on peut remarquer que le code source de certains programmes n'est pas disponible. Nous proposons donc un systeme de parallelisation statique de code binaire qui permet de paralleliser un application sequentielle deja compilee. Ensuite, on peut s'apercevoir que la performance d'un programme depend du contexte d'execution dans lequel il s'execute. Nous presentons donc un systeme qui permet de selectionner une version d'un programme parmi plusieurs afin d'exploiter au mieux les particularites du contexte d'execution courant. Enfin, etant donne que certains programmes sont difficiles a analyser statiquement, nous proposons un systeme de parallelisation speculative permettant d'appliquer dynamiquement des transformations de code complexes sur ces programmes. Ces trois systemes utilisent le modeles polyedrique comme une boite a outil permettant d'analyser, de transformer ou de paralleliser les programmes. En travaillant a differentes phases de la vie des programmes, ils forment une approche globale qui etend les techniques de parallelisation existantes.
Towards a compliance support framework for global software companies

Regulated companies are required to comply with the laws and regulations that apply to their industries. An important aspect of these authoritative rules is directly related to the way by which software systems, used by the regulated companies, are built, tested, and maintained. As a result, many regulated companies have turned to their software vendors to request their support in the compliance efforts. For most global software vendors, this new situation represents a significant challenge. From the technological standpoint, the complexity and sheer volume of typical authoritative rules poses a serious obstacle to implementing effective compliance support strategies. From the organizational perspective, the delivery of compliance support activities requires efficient business processes, skilled and valued employees, and a strong governance model with commitment at all management levels. To address these issues, we present a compliance support framework that aims to facilitate the linkage between compliance requirements, software development practices, and business process management. We believe that, if implemented properly, this framework can significantly improve the way software companies handle the increasing customer demand for compliance support. It can turn compliance support into a revenue-generating activity, and possibly a competitive advantage.
Multi-model technique for low flow forecasting

In forecasting low flows, four models, two determinist-statistic models (the VIDRA Model and a modified Stanford Model), a statistical model based on hydrometeorological analogues and an ARIMA class of model, were used to simulate the non-stationary and seasonal nature of the monthly flows. The result obtained was a large range of forecasted values which required a procedure in order to reach a decision on the most appropriate forecast. A solution was found in the development of a packet of procedures including both forecasting models and a decision procedure. This procedure is weight-based and uses the model errors on the last time step in its computing, so that with the help of model-weighting it is possible to incorporate in the procedure those models which best match the actual data (multi-model results optimization procedure).
Massively parallel solvers for lattice quantum gauge field theories

Faculty of Engineering School of Engineering Physics Doctor of Philosophy by Dieter John David Beaven Gauge field theories have been very successful in their description of quantum manybody field interactions. For interactions with strong coupling constants a computational approach is needed since analytic techniques fail to provide convergent solutions, such as occurs in the study of the strong nuclear force between quarks and gluons of atomic nuclei and other hadrons. The key computational bottleneck in such calculations is the solution of an extremely large linear algebra problem of finding solutions to nonsymmetric Wilson-Dirac matrices with maybe a billion unknowns. With a floating point performance requirement that challenges even the fastest petaflop supercomputers, finding algorithms that scale well over massively parallel distributed architectures is an ever present necessity. Results of an investigation into the use of small cost-effective reconfigurable devices is presented here, along with the solver methods currently being used, and those currently being researched as possible improvements. A reconfigurable design is considered and a research software library is presented as a means to efficiently investigate potential new algorithms. Results collected from this research software library are presented leading up to an improved preconditioning technique that addresses the time consuming critical slowing down problem inherent in calculations for low mass spinhalf particles near the lattice physical point. This proposed preconditioner is a hybrid combination of existing algorithms factored together in a highly configurable manner that can be dynamically adapted to any specific matrix during the solve to increase performance. Applications to solid state physics problems such as the conductivity and optical properties of graphene are discussed with regards to how these solvers are also of interest due to the existence of massless spin-half quasi-particles interacting strongly with the hexagonal carbon lattice.
Experimental investigation into the mechanism of folding

*) The authors wish to thank the board of directors of the Bataafschc Petrolpum Maatschappij, in commission of whom this investigation was performed. Thanks are also duo to Professor H. A. Kramers and others who gave the authors valuable advice on mechanical problems involved. The investigation of geological structures due to folding led de Sitter to form an opinion on the mechanical problems involved (Bibl. 7).
Communication-Avoiding Parallel Recursive Algorithms for Matrix Multiplication

Abstract : Matrix multiplication is one of the most fundamental algorithmic problems in numerical linear algebra, distributed computing, scientific computing, and high-performance computing. Parallelization of matrix multiplication has been extensively studied (e.g., [21, 12, 24, 2, 51, 39, 36, 23, 45, 61]). It has been addressed using many theoretical approaches, algorithmic tools, and software engineering methods in order to optimize performance and obtain faster and more efficient parallel algorithms and implementations. To design efficient parallel algorithms, it is necessary not only to load balance the computation, but also to minimize the time spent communicating between processors. The interprocessor communication costs are in many cases significantly higher than the computational costs. Moreover, hardware trends predict that more problems will become communication-bound in the future [38, 35]. Even matrix multiplication, which is widely considered to be computation-bound, becomes communication-bound when a given problem is run on sufficiently many processors.
Auditory Processing of Temporal Fine Structure:Effects of Age and Hearing Loss

Processing of Sound in the Auditory System and Neural Representation of Temporal Fine Structure (TFS) The Role of TFS in Masking The Role of TFS in Pitch Perception The Role of TFS in Speech Perception The Influence of Hearing Loss and Age on the Binaural Processing of TFS Overview, Conclusions and Practical Implications.