Miracle-dz/UniFAR-FTUs huggingface dataset:
Bring Me Men: Military Masculinity and the Benign Facade of American Empire, 1898-2001

The masculinity of those who serve in the American military would seem to beindisputable, yet it is full of contradictions. To become a warrior, one must renouncethose things in life that are perceived to be unmasculine. Yet at the same time, themilitary has encouraged and even mandated warriors to do exactly the opposite. Bring Me Men explores these contradictions in great detail and shows that theirinvisibility has been central to the concealment of American empire's darkest secrets.By examining case studies that expose these contradictions -- the phenomenon of maleon-male rape at the U.S. Naval Academy, for example, as well as historical and contemporaryattitudes toward cleanliness and filth -- Belkin utterly upends our understanding of the relationship between warrior masculinity, American empire and the fragile processes sustaining it.
Part-of-speech tagging and partial parsing for Irishusing finite-state transducers and constraint grammar

In this thesis, we present the development and evaluation of a suite of annotation tools for unrestricted Irish text, which go from tokenization, morphological analysis, part-of-speech tagging, right through to partial parsing. In order to develop such tools, a large body of texts is required for testing purposes. We, therefore, begin by describing our involvement in the creation of a 30 million word corpus of Irish texts (New Corpus for Ireland). From this corpus, we randomly extracted 3,000 sentences which we annotated and manually corrected in order to create a Gold Standard Corpus for evaluation purposes. We then present the annotation tools. Firstly, we describe scaling a proof-of-concept implementation of finite-state tokenization and morphological analysis based on Xerox Finite State Tools (Ui Dhonnchadha, 2002, p146), to unrestricted text. After semi-automatic population of the finite-state morphology (FSM) lexical resources, the morphological analyser contains a lexicon of 30K lemmas, which together with a set of morphological guessers assign at least one morphological analysis to all tokens in unrestricted texts. Following this, we describe our POS tagger for Irish, implemented using Constraint Grammar Disambiguation Rules, and vislcg2 software. The POS tagger currently achieves an f-score of 95% on development data and 94.35% on unseen test data. This tagger has been used to tag the 30 million word corpus of Irish. Finally, we present our implementation of partial parsing, which is a combination of dependency analysis overlaid with finite-state chunking. As this is the first attempt at implementing a partial parser for Irish, (to our knowledge), there were no guidelines or precedents available. The dependency analysis uses Constraint Grammar Dependency Mapping Rules, and the chunker is implemented using regular expressions and Xerox Finite-State Tools. The dependency analysis currently achieves an f-score of 93.60% on development data and 94.28% on unseen test data. The chunker achieves an f-score of 97.20% on development data and 93.50% on unseen test data.
Principles, Systems and Applications of IP Telecommunications

These are the proceedings of IPTComm 2010, the fourth of a successful series of conferences on Principles, Systems and Applications of IP Telecommunications. This year's edition of the conference is held in Garching b. Munchen, Germany, on August 2 and 3, 2010. The scope of the conference covers new services and service models, management and resilience, mobility, and a special focus on security. The call for papers asked for submission of full papers, short papers. It attracted 50 paper submissions. The technical program committee chairs ensured a rigid review process. For each paper, at least three reviews were received. The technical program committee decided to accept 12 papers as regular papers for the conference, resulting in an acceptance ratio of 24 %. Additionally, 4 papers were selected to be presented as "Work-in-Progress" papers for presentation at the conference.
Space-Based versus Message-Passing Communication A Comparison

A lot of enterprise applications are powerful and demanding distributed applications. Message passing is a widely used communication paradigm, but it has some considerable limitations. These limitations have a great influence on the design and costs of a distributed application. A quite different communication paradigm is called Space-based Computing and it relaxes these limitations to some extent. Therefore it could be better to use Space-based Computing for the constuction of distributed applications in order to save time and costs and to build more reliable distributed applications.
Experimental characterization of the MIMO wireless channel: Data acquisition, analysis, and modeling

Detailed performance assessment of space–time coding algorithms in realistic channels is critically dependent upon accurate knowledge of the wireless channel spatial characteristics. This paper presents an experimental measurement platform capable of providing the narrowband channel transfer matrix for wireless communications scenarios. The system is used to directly measure key multiple-input–multiple-output parameters in an indoor environment at 2.45 GHz. Linear antenna arrays of different sizes and construction with up to ten elements at transmit and receive are utilized in the measurement campaign. This data is analyzed to reveal channel properties such as transfer matrix element statistical distributions and temporal and spatial correlation. Additionally, the impact of parameters such as antenna element polarization, directivity, and array size on channel capacity are highlighted. The paper concludes with a discussion of the relationship between multipath richness and path loss, as well as their joint role in determining channel capacity.
Emotions, conversational systems and heterogeneous data sources

The aim of this thesis is to provide solutions to three real problems demanded by information society, within the field of conversational agents and the world of natural language processing, which we have faced in different projects. First of all, the improvement of the naturalness of this kind of systems. This shortcoming reduces their credibility and it can pose a big problem in certain applications. In second place, the problem of information overload. We are in a time when more and more information is stored online. However, many times this is not completely well organized or its volume makes impossible that it can be accessed efficiently. In third place, the access to heterogeneous data sources. Nowadays, information is not usually stored in just one location, but it is scattered across various sources that need to be integrated, and each could have a different format and structure. Along this thesis, we will study each one of these problems in depth. We will analyze the different alternatives available in literature and we will provide solutions in the form of methodologies, frameworks and concrete systems. The contributions made have been published on several journals and congresses both national and international, and the developed systems are commercially available.
Distributed Algorithms for Computing Closed Itemsets Based onan Iterative MapReduce Framework

Closed Itemset mining is a major task both in Data Mining and Formal Concept Analysis. It is an efficient way to determine patterns which are hidden in raw data. These patterns may be expressed as association rules which capture relations between variables in databases. In the case of Formal Concept Analysis, Closed Itemsets form the basis of formal concepts. A concept consists of an extent and intent. It turns out that the intent is exactly a closed itemset whose support is the cardinality of extent. With the increasing application of Data Mining and Formal Concept Analysis in knowledge discovery, Closed Itemset mining is fast becoming an attractive research area. While many prominent algorithms have been developed to mine closed itemsets in both Formal Concept Analysis and Frequent Closed Itemset mining area, they are typically unsuitable for distributed implementation. The root cause is that the theoretical foundation of closed itemset mining is based on a centralized data representation. By examining the features of closed itemset, we propose distributed closed itemset computing theories for Formal Concept Analysis and Frequent Closed Itemset mining in a distributed environment. Additionally, taking the MapReduce framework as our inspiration we propose a general distributed approach for performing closed itemset mining. We then provide representative exemplars of how the classic centralized algorithms in Formal Concept Analysis and Frequent Closed Itemset mining can be implemented in a distributed fashion using our methodology and present a family of MR* algorithms, where the abbreviation stands for MapReduce and * stands for the underlying algorithm that has been adapted. To analyse the factors which impact a distributed algorithm's performance, we compare our MR* algorithms with the state-of-the-art. Experiments conducted on real datasets demonstrate that the MR* algorithms for Formal Concept Analysis are efficient and scalable. The MR* algorithm and theory for Frequent Closed Itemset mining of this work set the scene for future developments. We analyze our experimental results and discuss the bottlenecks which we will focus on in future work.
CSG TO B-REP TRANSLATOR USING A NEW MARCHING CUBES ALGORITHM

The purpose of this work is to define a new algorithm for converting a CSG representation into a B-Rep representation. Usually this conversion is done by walking through the CSG tree and using implemented Boolean Operators in the B-Rep solid modeler. In this work, the CSG tree is converted to a volumetric representation, where the volume occupied by the CSG solid is represented. Then, using the volumetric representation a B-Rep Solid Model is created. Also we use the topological information present on the intermediate volumetric representation to create a more efficient algorithm, minimizing memory and time consumption and certifying that the generated solid is valid by construction. Such an algorithm can be used in the future for creating B-Rep Solid Models from Three Dimensional Medical Images. Generating a full Solid Model instead of the traditional approach of only B-Rep representations has the advantage that mass properties are easily extracted from a Solid Model, such as: volume, moment of inertia and mass centre. Furthermore the techniques used to generate surface representations do not guarantee that a closed volume is created. It is enough for visualization. However, for engineering purposes as analysis or prototyping manufacturing, a closed volume is necessary. A B-Rep Solid Model is a complete representation for engineering purposes. The construction of a Solid Model is different from the traditional construction of a surface model; thus we modified the marching cubes algorithm to reach this objective.
Chapter 21: The Open Research Web

Most of this book has been about the past and the present of Open Access (OA). Let’s now take a brief glimpse at its future, for it is already within reach and almost within sight. Imagine a world in which the optimal outcome for the research literature has become actual: With all 2.5 million of the annual articles in the planet’s 24,000 peer-reviewed research journals freely accessible online to all would-be users (Odlyzko 1995; Okerson & O’Donnell 1995; Berners-Lee et al. 2005; DeRoure et al. 2005): (1) All their OAI metadata and full-texts will be harvested, inverted and indexed by services such as
And the Ass Saw the Angel

'Bible-black humour.enough visitations, portents and religious lunacy to qualify as the second-greatest story ever told' - "Elle". 'It is as if a Faulkner novel had been crossed with "Whistle Down the Wind" and then narrated by a stoned blues musician' - "Daily Telegraph".
A Clustering Method for Information Retrieval

A classical information retrieval system retrieves and ranks documents according to distances between texts and a user query. The answer list is often so long that users cannot examine all the documents retrieved whereas some relevant ones are badly ranked and thus never examined. To solve this problem, retrieved documents are automatically clustered. We describe a classification algorithm based on hierarchical and clustering methods. It classifies the set of documents retrieved by any IR-system. Then, this method is evaluated over the TREC-7 corpora and queries. We show that it improves the results of the retrieval by providing to users at least one high precision cluster. The impact of the number of clusters and the way to browse them are examined. The best results are obtained by choosing the number of clusters according to query sizes.
Control and Design of Snake Robots

Snake robots are ideally suited to highly confined environments because their small cross-sections and highly redundant kinematics allow them to enter and move through tight spaces with a high degree of dexterity. Despite these theoretical advantages, snake robots also pose a number of practical challenges that have limited their usefulness in the field. These challenges include the need to coordinate a large number of degrees of freedom, decreased system reliability due to the serially chained nature of the robot’s design, and the complex interaction of the robot’s shape with the world. This thesis makes progress towards addressing these issues with two main areas of contribution. In the first part, we provide tools for supportive autonomy in snake robots. To provide intuitive high-level autonomous behaviors, we extend our lab’s existing gait-based control framework to develop gait-based compliant control. To reliably and accurately sense the robot’s pose and shape we present new techniques for robust state estimation that leverage the redundancies in the distributed sensing capabilities of our group’s articulated snake robots. To demonstrate these contributions in a practical application, we use them to enable a snake robot to navigate a real-world underground pipe network. One of the most limiting characteristics of our snake robots (and robots in general) is the inability to precisely sense and control the torques and forces of their actuators. As such, the second part of this thesis focuses on the design and control of a new series-elastic actuated snake robot that incorporates a high performance series-elastic actuator (SEA) and torque control. After describing the novel design of the SEA, we discuss our perspective on how to incorporate torque control and series elasticity into snake robots. Finally, we demonstrate prototypes of new low impedance motions for snake robots. These motions naturally comply to obstacles and unstructured terrain, and open a new avenue of research for snake robot locomotion.
The REXX language: a practical approach to programming (2nd ed.)

I. BACKGROUND. 1. What Kind of a Language is REXX? 2. Summary of the REXX Language. 3. Fundamental Language Concepts. 4. Design Principles. 5. History. II. REXX LANGUAGE DEFINITION. 1. Characters and Encodings. 2. Structure and General Syntax. 3. Expressions and Operators. 4. Clauses and Instructions. 5. Assignments and Variables. 6. Commands to External Environments. 7. Keyword Instructions. 8. Function Calls. 9. Built-in Functions. 10. Parsing for ARG, PARSE, and PULL. 11. Numbers and Arithmetic. 12. Input and Output Streams. 13. Conditions and Condition Traps. 14. Interactive Tracing. 15. Reserved Keywords and Language Extendibility. 16. Special Variables. 17. Error Numbers and Messages. Appendix A. Appendix B. Appendix C. Appendix D. Index.
Single Group Repeated Measures Analysis: Pairwise Multiple Comparisons under Bradley's Stringent Criterion.

A large number of pairwise multiple comparisons (P-MCPs) have been introduced recently to the educational research community. The use of these P-MCPs with single group repeated measures data was studied through an exploratory Monte Carlo study of P-MCPs that have been shown to control different types of Type 2 error and Type 1 familywise error under both no violations and violations of assumptions in other designs. A second purpose of the study was to recommend the P-MCPs based on ease of use. The stringent level of robustness developed by J. V. Bradley (1978) was used to examine the P-MCPs empirical rate of Type 1 error, and the range of sphericity was expanded to cover the values found in practice more realistically. Pairwise power among the P-MCPs was also compared. Nine P-MCPs were studied. Results indicate that all the new methods can not be recommended with single group repeated measures designs because their omnibus tests failed to control Type I error adequately. A familiar and easy-to-calculate method, the Dunn-Bonferroni procedure, successfully controlled familywise Type I error and may be recommended for use as a followup procedure with single group repeated measures designs. Further research with single group repeated measures designs through the Studentized maximum modulus statistic is recommended. (Contains 3 tables and 27 references.) (SLD) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDU TIONAL RESOURCES INFORMATION CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. I PI PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY keilooxp s E<<,627TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) Single Group Repeated Measures Analysis: Pairwise Multiple Comparisons Under Bradley's Stringent Criterion Robert S. Barcikowski Ronald S. Elliott Ohio University
Using social media intelligence to support business knowledge discovery and decision making

The new social media sites – blogs, micro-blogs, and social networking sites, among others – are gaining considerable momentum to facilitate collaboration and social interactions in general. These sites provide a tremendous asset for understanding social phenomena by providing a wide availability of novel data sources. Recent estimates suggest that social media sites are responsible for as much as one third of new Web content, in the forms of social networks, comments, trackbacks, advertisements, tags, etc. One critical and immediate challenge facing the MIS researchers then becomes - how to effectively utilize this huge wealth of social media data, to facilitate business knowledge discovery and decision making. Among these available data sources, social networks constitute the backbone of almost all social media sites. These network structures provide a rich description of the social scenes and contexts, which is helpful for us to address the above challenge. In this dissertation, I have primarily employed the probabilistic network models, to study various social network related problems arose from the use of social media services. In Chapter 2 and Chapter 3, I studied how information overload can affect the efficiency of information diffusion in online social networks (Delicious.com and Digg.com). Novel diffusion model were proposed to model the observed information overload. The models and their extensions are thoroughly evaluated by solving the Influence Maximization problem related to information diffusion and viral marketing applications. In Chapter 4, I studied the information overload in a micro-blogging application (Twitter.com) using a design science methodology. A content recommendation framework was proposed to help micro-blogging users to efficiently identify quality emergency news feeds. Chapter 5 presents a novel burst detection algorithm concerning identifying and analyzing correlated burst patterns by considering multiple inputs (data streams) that co-evolve over time. The algorithm was later used for discovering burst keywords/tag pairs from online social communities, which are strong indicators of emerging or changing user interests. Chapter 6 concludes this dissertation by highlighting major research contributions and future directions.
FUNDAMENTALS OF NEURAL NETWORKS

2.1 INTRODUCTION For many decades, it has been a goal of science and engineering to develop intelligent machines with a large number of simple elements. References to this subject can be found in the scientific literature of the 19th century. During the 1940s, researchers desiring to duplicate the function of the human brain, have developed simple hardware (and later software) models of biological neurons and their interaction systems. McCulloch and Pitts [1] published the first systematic study of the artificial neural network. Four years later, the same authors explored network paradigms for pattern recognition using a single layer perceptron [2]. In the 1950s and 1960s, a group of researchers combined these biological and psychological insights to produce the first artificial neural network (ANN) [3,4]. Initially implemented as electronic circuits, they were later converted into a more flexible medium of computer simulation. However, researchers such as Minsky and Papert [5] later challenged these works. They strongly believed that intelligence systems are essentially symbol processing of the kind readily modeled on the Von Neumann computer. For a variety of reasons, the symbolic–processing approach became the dominant method. Moreover, the perceptron as proposed by Rosenblatt turned out to be more limited than first expected. [4]. Although further investigations in ANN continued during the 1970s by several pioneer researchers such as Grossberg, Kohonen, Widrow, and others, their works received relatively less attention. The primary factors for the recent resurgence of interest in the area of neural networks are the extension of Rosenblatt, Widrow and Hoff's works dealing with learning in a complex, multi-layer network, Hopfield mathematical foundation for understanding the dynamics of an important class of networks, as well as much faster computers than those of 50s and 60s. The interest in neural networks comes from the networks' ability to mimic human brain as well as its ability to learn and respond. As a result, neural networks have been used in a large number of applications and have proven to be effective in performing complex functions in a variety of fields. These include pattern recognition, classification, vision, control systems, and prediction [6], [7]. Adaptation or learning is a major focus of neural net research that provides a degree of robustness to the NN model. In predictive modeling, the goal is to map a set of input patterns onto a set of output patterns. NN accomplishes this task by learning from a series of input/output …
La place de l’analyse qualitative comparée en sciences de gestion

La methode QCA (Qualitative Comparative Analysis) developpee par Ragin (1987) innove quant a son positionnement vis-a-vis des methodologies traditionnelles qualitatives et quantitatives. Elle se diffuse actuellement dans differentes sciences sociales bien que son audience en gestion reste encore faible. Nous cherchons dans cet article a identifier le positionnement potentiel de cette methode en gestion. Pour ce faire, nous replacons la QCA dans une analyse plus large des methodes de recherche a partir d'une etude quantitative des publications de trois revues internationales en management. Nous concluons a l'existence d'une niche pour la QCA, tout en presentant ses conditions d'application dans notre champ.