Miracle-dz/UniFAR-FTUs huggingface dataset:
Coefficients - delay simultaneous adaptation for linear transversal equalizers on nonminimum phase channels

An efficient adaptation technique of the delay is introduced for accomplishing more accurate adaptive equalization. It is focused on the adaptive Butler-Cantoni (ABC) equalizer, which can deal easily with a variable delay for each iteration and the adaptation is conducted with channel estimation. The delay is adapted by checking the first and last elements of the coefficient vector for the ABC equalizer and it results in a linear transversal equalizer (LTE) providing a lower mean square error (MSE) than the other LTEs with the same order. The performance of the ABC equalizer with the delay adaptation is confirmed by computer simulations.
Vector Quantization of Speech Spectral Parameters Using Statistics of Static and Dynamic Features

SUMMARY This paper proposes a vector quantization scheme which makes it possible to consider the dynamics of input vectors. In the proposed scheme, a linear transformation is applied to the consecutive input vectors and the resulting vector is quantized with a distortion measure deﬁned by the statistics. At the decoder side, the output vector sequence is determined using the statistics associated with the transmitted indices in such a way that a likelihood is maximized. To solve the maximization problem, a computationally eﬃcient algorithm is derived. The performance of the proposed method is evaluated in LSP parameter quantization. It is found that the LSP trajectories and the corresponding spectra change quite smoothly in the proposed method. It is also shown that the use of the proposed method results in a signiﬁcant improvement of subjective quality.
Semi-Supervised Learning for Classification with Uncertainty

Support vector machine (SVM) is a general and powerful learning machine, which adopts supervised manner. However, for many practical machine learning and data mining applications, unlabeled training examples are readily available but labeled ones are very expensive to be obtained. Therefore, semi-supervised learning emerges as the times require. At present, the combination of SVM and semi-supervised learning (S3VM) has attracted more and more attentions. In general, S3VM deals with problems with small training sets and large working sets. When the training set is large relative to the working set, We propose a new SVM model to solve the above classification problem by introducing the fuzzy memberships to each unlabeled point. Simulation results demonstrate that the proposed method can exploit unlabeled data to yield good performance effectively.
A cellular computer to implement the kalman filter algorithm

The subject of this thesis is the development of the design for a specially-organized, general-purpose computer which performs matrix operations efficiently. The content of the thesis is summarized as follows: First, a review of the relevant work which has been done with microcellular and macrocellular techniques is made, Second, the discrete Kalman filter is described as an example of the type of problem for which this computer is efficient. Third, a detailed design for a cellular, array-structured computer is presented. Fourth, a computer program which simulates the cellular computer is described. Fifth, the recommendation is made that one cell and the associated control circuits be constructed to determine the feasibility of producing a hardware realization of the entire computer. A CELLL1TAR COMPUTER TO IMPLEMENT THE JLimAN FILTER ALGORITHM
MODERN LANGUAGES ACROSS THE CURRICULUM

MODERN LANGUAGES ACROSS THE CURRICULUM. Michael Grenfell (Ed.). New York: RoutledgeFalmer, 2002. Pp. 222. $39.95 paper. The European Union has succeeded in breaking down monetary and legal barriers among its members. This volume presents a program for breaking down linguistic barriers by teaching European languages in primary and secondary schools using the approach of Modern Languages Across the Curriculum (MLAC), what is essentially called content-based instruction in the United States.
Building Blocks for Mobile Games : A multiplayer framework for App Inventor for Android

Building Blocks for Mobile Games is a client-server multiplayer game-buildingframework for the App Inventor for Android platform. The Building Blocks for Mobile Games multiplayer framework includes an App Inventor component and a Game Server running on Google App Engine. The client-side-component packages the complexity of web service calls, data transfer and game state management into a set of graphical code blocks that allow users without programming experience to create Android applications that can access the Game Server API. The Game Server provides basic functionality that can be used to create simple multiplayer games and message-passing applications, such as a multiuser bulletin board. The Game Server is also extensible and can be enhanced with custom modules which provide server commands that implement game logic, perform database operations, access third-party web services, and read RSS feeds. Custom modules were used with Building Blocks to develop a multiplayer card game, a variant of Bulls and Cows with a shared scoreboard, an application that accesses Amazon's book search API and a pair of applications for creating, managing and voting in polls. The clients for these applications are built entirely with the App Inventor graphical blocks language, which can be assembled into Android Applications. The custom modules that support the client programs average less than 50 lines of Python code. Thesis Supervisor: Hal Abelson Title: Class of 1922 Professor of Computer Science and Engineering
Mathematical morphology in image processing , edited by E R Dougherty. Pp530 $160. 1993. ISBN 0-8247-8724-2 (Marcel-Dekker)

The theory of image processing is a fertile area for the development of new mathematics and the adaptation and application of classical techniques. The first elements of Mathematical Morphology date to about 1967 with the work of G Matheron with another key date being the publication in 1982 of Serra's Image analysis and mathematical morphology. The basic idea is simple. Given a binary image (a collection of black and white dots/pixcels) choose a "structuring element" such as a small square or circular blob and use it to "probe" the image. The "probing" might be done by seeing at which points of the image is it possible to fit the blob completely within the black part of the shape. Analysing the resulting transformed shape allows the construction of certain invariants and a reconstruction of the image. The reconstructed image will typically have less haphazard noise in the form of scatters of black or white pixcels randomly distributed over the image. Eliminating the noise then allows identification of important features by purely algorithmic means. mathematical
Collaborative yet Independent. Information Practices in the Physical Sciences.

In many ways, the physical sciences are at the forefront of using digital tools and methods to work with information and data. However, the fields and disciplines that make up the physical sciences are by no means uniform, and physical scientists find, use, and disseminate information in a variety of ways. This report examines information practices in the physical sciences across seven cases, and demonstrates the richly varied ways in which physical scientists work, collaborate, and share information and data. This report details seven case studies in the physical sciences. For each case, qualitative interviews and focus groups were used to understand the domain. Quantitative data gathered from a survey of participants highlights different information strategies employed across the cases, and identifies important software used for research. Finally, conclusions from across the cases are drawn, and recommendations are made. This report is the third in a series commissioned by the Research Information Network (RIN), each looking at information practices in a specific domain (life sciences, humanities, and physical sciences). The aim is to understand how researchers within a range of disciplines find and use information, and in particular how that has changed with the introduction of new technologies.
INFORMATION FILTERING BASED ON USERS' NEGATIVE OPINIONS

The process of heat conduction (HC) has recently found application in the information filtering [Zhang et al., Phys. Rev. Lett.99, 154301 (2007)], which is of high diversity but low accuracy. The classical HC model predicts users' potential interested objects based on their interesting objects regardless to the negative opinions. In terms of the users' rating scores, we present an improved user-based HC (UHC) information model by taking into account users' positive and negative opinions. Firstly, the objects rated by users are divided into positive and negative categories, then the predicted interesting and dislike object lists are generated by the UHC model. Finally, the recommendation lists are constructed by filtering out the dislike objects from the interesting lists. By implementing the new model based on nine similarity measures, the experimental results for MovieLens and Netflix datasets show that the new model considering negative opinions could greatly enhance the accuracy, measured by the averag.
Emotion and Sentiment

Experiences may be divided into those which do not and those which do have an 'epistemological object. ' The former may be called Pure Feelings. The natural question to ask with regard to a feeling is: 'How are you feeling? ' And the natural answer is to utter some adjective (or, more properly, adverb), such as 'Hot,' or 'Tired,' or 'Cross. ' To feel tired is to be feeling in a certain way; it is not to be aware of a certain object, real or fictitious. On the other hand, there are many experiences about which it is natural to ask: 'What is the object of your experience? ' or 'What is it about? ' If a person says that he is seeing or hearing or thinking, it is natural to ask: What are you seeing? ' or 'What are you hearing? ' or 'What are you thinking about? ' And the answer that one expects is the utterance of some substantive or phrase equivalent to a substantive, e.g., 'A red flash,' 'A squeaky noise,' 'The square-root of minus 1. ' I shall say that experiences of the latter kind 'have an epistemological object' or are 'epistemologically intentional. ' All such experiences may be called Cognitions. It is important to notice that an experience may be epistemologically intentional, even if it be a delusive quasi-perception or a thought of something which does not and perhaps could not exist. A person who in a dream ostensibly sees a man pointing a revolver at him is having an epistemologically intentional experience, although there is no ontological object (i.e., no actual man, pointing an actual revolver at him at the time) corresponding to it. Similarly, a person who is thinking of a phoenix is having an epistemologically intentional experience. He is certainly thinking of something and he could describe what he is thinking of. If he were thinking of a dragon, instead of a phoenix, he would be thinking of something different and would give a different description. And that, in spite of the fact that there never have been, and perhaps could not be, in nature either phoenixes or dragons. So we begin by dividing experiences into Pure Feelings and Cognitions. The former are those which have only psychical qualities and do not have epistemological objects. The latter are those which have epistemological objects. Cognitions may have psychical qualities as well as epistemological objects; some of them certainly do, and perhaps all of them do. A pure feeling cannot significantly be described either as veridical or as delusive. These alternatives can be significantly predicated only of cognitions. A cognition is veridical if there is an ontological object answering to the description which the experient would naturally give of its epistemological object, i.e., the description which he would offer in answer to the question: 'What are you cognising? ' It is totally delusive, if there is no
Who benefits from learning how to use corpora

Whereas researchers have long seen the benefits of using corpora to enhance the description of language, the regular use of corpora in the EFL classroom is still a rare occurrence. One reason is likely to be that learning how to use corpora is seldom part of teacher training courses. As a result, teachers themselves – both at university level and at lower levels – lack the skills needed to use this “native-speaker consultant”. If training in how to use corpora were integrated into university level courses such as syntax, written proficiency and translation, in time it could become just as natural to consult a corpus as to look up an item in a dictionary or a grammar book.The present paper, which is based on almost a decade’s experience of using corpora in the teaching of EFL syntax at the university level, outlines how teachers can utilize this resource both to design exercises and to make grammar “come alive” in the classroom. Furthermore, it summarizes students’ attitudes regarding hands-on exercises using corpora, and discusses the problems as well as the benefits of involving students directly in interpreting edited and unedited corpus data.
Postlexical rules and the status of privative features

Recent work in distinctive features and feature geometry has presented strong evidence that certain features are privative: they have no negative values, so a sound is either marked [F] or else it is not. Evidence comes from possible types of sounds (for example, multiply articulated segments, in Sagey 1986) and from the fact that the negative values of these features are not referred to in phonological rules. Currently there is a nearly universal consensus that Place features are privative, and converging evidence from several authors (Mester & Itô 1989; Cho 1990; Lombardi 1991, 1995a) that [voice] is privative also.
Mining lidar data with spatial clustering algorithms

Clustering algorithms have been an important area of research in the domain of computer science for data mining of patterns in various kinds of data. This process can identify major patterns or trends without any supervisory information such as data labels. Broadly specified, it divides a set of objects into clusters each of which is a representative of a meaningful sub-population. In this article, we first carry out an assessment of available categories of clustering techniques and find that hierarchical- and density-based algorithms are apt for clustering light detection and ranging (lidar) data. Then, we adapt and examine the effect of two algorithms, namely density-based spatial clustering of applications with noise (DBSCAN) and ordering of points to identify the clustering structure (based on perimeter of triangles) (OPTICS (BOPT)) found in the literature in the area of knowledge discovery in databases, on lidar data. The performances of the algorithms are evaluated with respect to execution time and comparison of clustering outputs with respect to a manually classified data set of . DBSCAN performs better in both respects. The efficacy of DBSCAN is also demonstrated for detecting clusters of complex shapes for two different data sets, each of areal dimension of .
Revisiting Significant Action and Gesture Categorization

As the field of gesture studies has developed researchers have created ways of analysing and categorizing bodily movement phenomena. In this paper we look at whether gesture categorizations have any resonance with the ways that people other than gesture researchers approach bodily movement. Building on Kendon's observations that people generally have a consistent attitude towards what constitutes ‘significant action’, we asked 12 participants to conceptualize their own categories of gesture and then analyse a short video that contained a predetermined variety of bodily movements. We found that non-analysts had a wider conception of what constituted gesture than analysts. In regards to the categorizations of gesture that non-analysts made, there were a range of schemas, which we broadly categorized as being ‘form-based’ and ‘function-based’.
Testing Consumer Theory in the Field: Private Consumption Versus Charitable Goods

We present evidence from a natural field experiment designed to shed light on whether individual behavior is consistent with standard consumer theory. In conjunction with the Bavarian State Opera House, we mailed 22,000 regular opera attendees a letter describing a charitable fundraising project organized by the opera house. Recipients were randomly assigned into one of six treatments designed to test revealed preference theory and explore behavioral responses to price changes, income changes, and signals of the project quality as captured by the presence of a lead donor. We find that consumer behavior, on both the extensive and intensive margins, can be rationalized within a standard model of consumer choice in which individuals have preferences defined over own consumption and charitable donations received by the project, that satisfy GARP. We find no evidence that choices are motivated purely by warm glow, or that consumers target a certain amount of donations to give irrespective of the budget set faced. The analysis highlights that in a real world setting where consumers make simple decisions they are familiar with, standard microeconomic theory works well in explaining observed individual choices.
Wiki-Philosophizing in a Marketplace of Ideas: Evaluating Wikipedia's Entries on Seven Great Minds

A very conspicuous part of the new participatory media, Wikipedia has emerged as the Internet's leading source of all-purpose information, the volume and range of its articles far surpassing that of its traditional rival, the Encyclopedia Britannica. This has been accomplished by permitting virtually anyone to contribute, either by writing an original article or editing an existing one. With almost no entry barriers to the production of information, the result is that Wikipedia exhibits a perfectly competitive marketplace of ideas. It has often been argued that such a marketplace is the best guarantee that quality information will be generated and disseminated. We test this contention by examining Wikipedia's entries on seven top Western philosophers. These entries are evaluated against the consensus view elicited from four academic reference works in philosophy. Wikipedia's performance turns out to be decidedly mixed. Its average coverage rate of consensus topics is 52%, while the median rate is 56%. A qualitative analysis uncovered no outright errors, though there were significant omissions. The online encyclopedia's harnessing of the marketplace of ideas, though not unimpressive, fails to emerge as clearly superior to the traditional alternative of relying on individual expertise for information.
Particle swarm optimisation applied to nuclear engineering problems

Evolutionary computation (EC) techniques, and more specifically genetic algorithms (GA) and their variations, have been efficiently applied to many complex problems found in the nuclear engineering field. Such methods have been shown to be robust and efficient, but highly time consuming. Other population-based methods have been proposed as alternatives to these traditional EC techniques. The Particle Swarm Optimisation (PSO) technique has been shown to be faster and many times more efficient than GA. Motivated by that, investigations concerning applications of PSO to nuclear engineering problems have started in the Brazilian Nuclear Engineering Institute (IEN/CNEN) and Federal University of Rio de Janeiro (UFRJ). This paper describes applications of PSO to four classical nuclear engineering problems: (i) nuclear fuel reload, (ii) core design optimisation, (iii) surveillance tests planning and (iv) accident classification. Computational experiments demonstrate that PSO can be efficiently applied to the problems studied. Moreover, the results described are comparable with, or even better than, some good results (obtained by GA) found in the literature.
Conceptual flexibility: Behavioral and neural variations in semantic memory retrieval

Understanding the neural organization of semantic memory our shared general knowledge has the potential to uncover the neural mechanisms by which we give meaning to the endless array of objects that we encounter in the world. One prominent set of theories posits a distributed organization of semantic memory remembering object features activates brain regions overlapping with or adjacent to regions involved in perceiving and acting on those features (e.g., Allport, 1985). Despite accumulated evidence favoring these theories, it is important to understand both the commonalities in the mapping between perception and memory, as well as meaningful variability across sources such as contexts, people, and use. In three studies, we found evidence that while conceptual knowledge is grounded in neural substrates, several factors contribute to variations in semantic memory retrieval. In Chapter 2, we used the logic often used in neuroimaging studies of semantic memory by demonstrating overlapping chromaticity effects (e.g., greater response to colored than grayscale stimuli) in the left lingual gyrus for both color perception and color knowledge. Chapter 3 investigated whether the mapping between perception and memory varied across contexts and participants. Whereas context (here, fidelity of color information as manipulated through task demand) varied the extent to which the left fusiform gyrus was active during a color similarity judgment, individual differences in cognitive style predicted activity in the left lingual gyrus. We replicated these results in a second experiment that controlled for stimulus modality and anticipatory strategies. In Chapter 4, we used a training paradigm to investigate the role of feature diagnosticity (i.e., features that best distinguish between two otherwise similar categories) in semantic representations. Whereas subjects had knowledge of feature importance in novel object categorization, whether they used this information affected neural representations. Ventral temporal brain regions were more active during a separate retrieval task for subjects who learned and used the diagnostic feature for object categorization. Additionally, behavioral ratings of similarity predicted multivariate neural similarity. Collectively, this work suggests that semantic representations, integral to a memory system often thought of as free of contextual constraints, contain meaningful variations across contexts, people, and use. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Neuroscience First Advisor Sharon L. Thompson-Schill