Miracle-dz/UniFAR-FTUs huggingface dataset:
Infant‐directed speech and language evolution

Infant-directed speech is here defined as a set of speech registers that caretakers use to address infants. There are at least three different kinds of infant-directed speech: one that is used to get the infant's attention, one that is used to soothe the infant, and one that is used to address the infant with linguistically meaningful utterances. All have different characteristics, but there are also similarities, and they could be considered as points on a continuum. Nevertheless, it is unfortunate that in general no difference is made between the different kinds of infant-directed speech in the literature. The different kinds are used in different circumstances, and from an evolutionary point of view, they would make different contributions to the infant's fitness. All kinds of infant-directed speech are characterized by slower speech rate and larger intonation contours infant-directed speech is characterized by higher volume and extreme intonation excursions, but it does not necessarily consist of meaningful utterances. Basically, caretakers use any speech-like means to get the infant's attention. Soothing infant-directed speech is characterized by lower volume, sometimes even whispered speech, and very flowing intonation contours. Lullabies could be considered part of this kind of infant-directed speech. Although it can be argued that all kinds of infant-directed speech can serve adaptive purposes, for this article, the meaningful kind of infant-directed speech is most interesting. It is characterized by short, syntactically simple utterances that are generally about the direct context, exaggerated intonation contours, lower tempo and clearer articulation. Caretakers use infant-directed speech automatically when addressing infants, even without being aware of doing so. They also automatically adapt the complexity of their speech to the level of linguistic competence of the infant. In addition, infants prefer to listen to infant-directed speech over adult-directed speech (Fernald, 1985). Infant-directed speech also appears to be nearly universal cross-culturally (Ferguson, 1964; Fernald et al., 1989) and a similar register is attested in signed languages (Masataka, 1992). Whether it really is universal cross-culturally is still an open question. It has been de Boer, Bart (2011) Infant-directed speech and language evolution,
Information Retrieval and the Statistics of Large Data Sets

Providing content-based access to large quantities of text is a diicult task, given our poor understanding of the formal semantics of human language. The most successful approaches to retrieval, routing, and categorization of documents have relied heavily on statistical techniques. We brieey review some of those techniques and point out where better statistical insight could lead to further advances. 1 IR and Statistics Today Information retrieval (IR) is concerned with providing access to data for which we do not have strong semantic models. Text is the most notable example, though voice, images, and video are of interest as well. Examples of IR tasks include retrieving documents from a large database in response to immediate user needs, routing or ltering documents of interest from an ongoing stream over a period of time, and categorizing documents according to their content (e.g. assigning Dewey Decimal numbers to abstracts of articles). Statistical approaches have been widely applied to these systems because of the poor t of text to data models based on formal logics (e.g. relational databases) 8]. Rather than requiring that users anticipate exactly the words and combinations of words that will appear in documents of interest, statistical IR approaches let users simply list words that are likely to appear in relevant documents. The system then takes into account the frequency of these words in a collection of text, and in individual documents, to determine which words are likely to be the best clues of relevance. A score is computed for each document based on the words it contains, and the highest scoring documents are retrieved, routed, categorized, etc. There are several variations on this approach 5, 17, 18, 19]. Vector space models treat the words suggested by the user as specifying an ideal relevant document in a high dimensional space. The distance of actual documents to this point is used as a measure of relevance. Probabilistic models attempt to estimate, for instance, the conditional probability of seeing particular words in relevant and nonrelevant documents. These estimates are combined under independence assumptions and documents are scored for probability of membership in the class of relevant documents. Inference
NEURODIDACTICS – A NEW STIMULUS IN ICT AND COMPUTER SCIENCE EDUCATION

Neurodidactics, a relatively young discipline, represents an interface between neuroscience and didactics. Based on the findings of brain research neurodidactics provides principles and proposals for effective (brain-based) teaching and learning. This paper shall present the most important principles and give an impetus for using them in ICT and computer science education.
The FAME approach: an assessing methodology

In recent years the increasing of open source solutions extended the business opportunities for the IT companies but at the same time created problems for the choice and evaluation processes. For these reasons the need of approaches and tools to address this issue has become capital. We present FAME (Filter, Analyze, Measure and Evaluate), an iterative approach for open source software assessment, and an idea for a support tool for this methodology. In this paper we analyze the most interesting and important assessment methodologies and the FAME approach that derived by these, more heavyweight, proven approaches developed in a University research and consulting company environment, aims to match the needs of small organizations. The proposed approach has been used by FlossLab, the first spin-off of University of Cagliari, to select the best solutions. This tool can be useful to make easier the whole process, supporting the users in this choice by an interactive approach, particularly in the filtering and analysis phases.
Music and Sound Processing in Squeak Using Siren

Event — Object with a property list (lazily created) DurationEvent — adds duration instance variable MusicEvent — adds pitch and voice instance variables ActionEvent — has a block that it evaluates when scheduled It is seldom necessary to extend the hierarchy of events. Examples of verbose and terse Siren event creation messages are given below. Verbose Event Creation Messages— – Class messagesMessages Create a ‘generic’ event. MusicEvent duration: 1/4 pitch: ‘c3’ ampl: ‘mf’. Create one with added properties. (MusicEvent dur: 1/4 pitch: ‘c3’) color: #green; accent: #sfz. Terse Event Creation using Using concatenation Concatenation of music Music magnitudesMagnitudes 440 Hz, (1/4 beat), 44 dB. “Simple event” 490 Hz, (1/7 beat), 56 dB, (#voice -> #flute), (#embrochure -> #tight). “with an added (arbitrary) property” (#c4 pitch, 0.21 sec, 64 velocity) voice: Voice default. “Event using different syntax” EventList objects hold onto collections of events that are tagged and sorted by their start times (represented as the duration between the start time of the event list and that of the event). The event list classes are subclasses of DurationEvent themselves. This means that event lists can behave like events and can therefore be arbitrarily deeply nested, that is, one event list can contain another as one of its events. The primary messages to which event lists respond (in addition to the behavior they inherit by being events), are (anEventList add: anEvent at: aDuration)—to add an event to the list—(anEventList play)—to play the event list on its voice (or a default one)—(anEventList edit)—to open a graphical editor in the event list—and Smalltalk-80 collection iteration and enumeration messages such as (anEventList select: [someBlock])—to select the events that satisfy the given (Boolean) function block. Event lists can map their own properties onto their events in several ways. Properties can be defined as lazy or eager, to signify whether they map themselves when created (eagerly) or when the event list is performed (lazily). This makes it easy to create several event lists that have copies of the same events and map their own properties onto the events at performance time under interactive control. Voices handle mapping of event list properties via event modifiers, as described below. In a typical hierarchical Smoke score, data structure composition is used to manage the large number of events, event generators, and event modifiers necessary to describe a full performance. The score is a
New Features for the Question Classification Using Support Vector Machines

Question classification is of crucial importance for question answering. Support Vector Machines are known to work well for sparse, high dimensional problems. However, the frequently used bag-of-words approach does not take the full advantage of information contained in a question. To capture this information we propose three new feature types: Subordinate Word Category, Question Focus and Syntactic-Semantic Structure. As the results demonstrate, the inclusion of the new features provides higher accuracy of question classification, comparing to the standard bag-of-words approach and other methods that were described in the literature so far.
Glasba slovenske povojne moderne (1918–1927)

Na osnovi analize izbranih del so revidirane sodbe o slogovni usmerjenosti slovenske glasbe med obema vojnama. Glasba skladateljev, ki so bili aktivni v omenjenem casu, izkazuje karakteristicno ambivalentnost, ki se vidi v nasprotju med novimi in progresivnimi kompozicijskimi težnjami na eni strani in ohranjanjem estetskih idealov preteklega stoletja na drugi.
Face Recognition: Study and Comparison of PCA and EBGM Algorithms

OF THESIS Face recognition is a complex and difficult process due to various factors such as variability of illumination, occlusion, face specific characteristics like hair, glasses, beard, etc., and other similar problems affecting computer vision problems. Using a system that offers robust and consistent results for face recognition, various applications such as identification for law enforcement, secure system access, computer human interaction, etc., can be automated successfully. Different methods exist to solve the face recognition problem. Principal component analysis, Independent component analysis, and linear discriminant analysis are few other statistical techniques that are commonly used in solving the face recognition problem. Genetic algorithm, elastic bunch graph matching, artificial neural network, etc. are few of the techniques that have been proposed and implemented. The objective of this thesis paper is to provide insight into different methods available for face recognition, and explore methods that provided an efficient and feasible solution. Factors affecting the result of face recognition and the
How do tortoises know where to go

Forschungsergebnisse mit Schildkroten haben gezeigt, dass sie in der Lage sind, sich anhand distaler Markierungen raumlich zu orientieren. Des Weiteren konnte gezeigt werden, dass sie eine kognitive Representation der Umgebung sowohl zum Navigieren als auch zur Unterscheidung verschiedener Farben und Formen verwenden konnen. In der vorliegenden Studie wurde untersucht, ob es fur sie auch moglich ist, lokale Markierungspunkte in ihrer Umgebung zu unterscheiden und sie zu nutzen, um an ein distales Ziel zu gelangen. Dieser Prozess verlangt vor allem die Fahigkeit, verschiedene Zeichen, so genannte "Cues", zu unterscheiden und sie mit einer bestimmten Richtung zu assoziieren. Dazu wurden Sporn - (Geochelone sulcata) und Pantherschildkroten (Stigmochelys pardalis) darauf trainiert, sich anhand zweier Zeichen, die sich in Farbe und Form unterschieden, in einem T-formigen Labyrinth zurechtzufinden. Die zwei Zeichen wurden mittig gegenuber der Startposition angebracht. Eines der Zeichen bedeutete eine Belohnung im rechten Arm des Versuchsaufbaus, das andere Zeichen bedeutete eine Belohnung auf der linken Seite. Die Ergebnisse zeigten, dass Spornschildkroten in der Lage waren, dies zu lernen. Danach wurden die Tiere darauf getestet, ob auch Geruche eine Rolle in der Orientierung spielten. Wie erwartet stellte sich heraus, dass dies nicht der Fall war. Im Anschluss daran wurde getestet, ob Farbe oder Form der „Cues“ wichtiger in dem Lernprozess waren. Die Leistung in diesem Test gab einen Hinweis darauf, dass Farbe, Form oder beides zusammen wichtig fur die Diskrimination sein konnten. Dies bedeutet, dass Schildkroten mit ihrer visuellen Wahrnehmung verschiedene Farben und Formen zu unterscheiden vermogen, und dass sie in der Lage sind, deren Funktionen mit Richtungen zu verbinden. Der Vergleich der beiden Arten, die ahnliche Lebensraume bewohnen, sich aber in ihrer Okologie unterscheiden, zeigte auf Grund der geringen Datenmenge keine signifikanten Ergebnisse.
Aplicación de análisis de componente principal en sistemas eléctricos de potencia

El analisis de componente principal (ACP) es una tecnica estadistica de analisis multivariable ampliamente utilizada para encontrar patrones de datos de alta dimension. La ventaja fundamental de ACP es la reduccion del numero de dimensiones de los datos, sin que exista mucha perdida de informacion. En este articulo se hace una descripcion de esta transformacion matematica, y se presentan dos aplicaciones en el area de los sistemas electricos de potencia. ABSTRACT A common method from statistics for analyzing data is principal component analysis (PCA). The purpose of PCA is to identify the dependence structure behind a multivariable stochastic observation in order to obtain a compact description of it. The paper describes the mathematical fundamentals of PCA and two applications in power system area.
An analysis on the word formation of the advertisements lexicon

Mursyid Kasmir Naserly, An Analysis on the Word Formation of the Advertisements Lexicon. Thesis. Jakarta: Adab and Humanity Faculty, UIN Syarif Hidayatullah Jakarta, November 2009. This research is aimed at finding out the process and type of word formation which is used in the advertisement used morphologically. Moreover, the writer uses descriptive qualitative method by collecting the selected advertisements which has unique tag – line as the provocative message to draw people attention to buy the products. After selecting the data, then the writer analyze each of advertisement using the theory of morphology. The writer found that many advertisements designed as creative as possible, even sometimes deviates from the grammatical roles, with the intention of gaining people attention upon the product offered, since this is the effective way of promoting the brand new product through un-common way such the use of word formation which actually confuse the reader but has great impact to draw attention to watch, read and finally buy the products.
DomAns - pattern based method for protein domain boundaries prediction and analysis

Abstract. Determination of the native folded structure for a particular protein is a milestone towards understanding its function, and in most cases, can be done experimentally. However, the ability to predict in silico protein structure and related features would represent a fundamental breakthough in structural biology. The ability to predict domains in proteins is amongst the most important tasks needed for efective functional classification, homology-based structure prediction, structural genomics, as it makes function prediction easier. In this paper, we present the DomAnS, protein domain prediction approach, that is based on pattern alignment. DomAnS allows rapid screening for potential domain regions with the ability to recognize the most promising regions where domains might exists. The combination of the DomAnS algorithm with specialized databases that contains all known domains, allows us to find domain regions without solving 3D structure. Our approach has been tested on CASP7 data, and for 28 targets gave the best overall score.
Data-Intensive Computing: Architectures, Algorithms, and Applications

The world is awash with digital data from social networks, blogs, business, science, and engineering. Data-intensive computing facilitates understanding of complex problems that must process massive amounts of data. Through the development of new classes of software, algorithms, and hardware, data-intensive applications can provide timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements. This emerging area brings many challenges that are different from traditional high-performance computing. This reference for computing professionals and researchers describes the dimensions of the field, the key challenges, the state of the art, and the characteristics of likely approaches that future data-intensive problems will require. Chapters cover general principles and methods for designing such systems and for managing and analyzing the big data sets of today that live in the cloud, and describe example applications in bioinformatics and cybersecurity that illustrate these principles in practice.
Over de grenzen van organisaties : Bedrijfskunde: organisatie, strategie en omgeving

textabstractInleiding. Niets is zo praktisch als een goede theorie. En dit geldt ook voor bedrijfskunde als een recente tak van wetenschap. Bedrijfskunde heeft immers als object van studie het vanuit managementsoogpunt benaderen van het functioneren van formele organisaties in relatie tot hun omgeving. Dit ogenschijnlijk praktische vraagstuk blijkt geen eenvoudige opgave te zijn. Goede theorieen zijn daarbij onontbeerlijk.
Review Essay: Rethinking the Retrenchment Narrative in U.S. Housing Policy History

KENT W. COLTON, Housing in the Twenty-first Century: Achieving Common Ground. Cambridge, Mass. : Harvard University Press, 2003, pp. xx, 506, notes, figures, appendix, bibliography, index, $39.50 cloth. MARA S. SIDLEY, Unfair Housing: How National Policy Shapes Community Action. Lawrence: University of Kansas Press, 2003, pp. xiii, 186, tables, notes, index, $35.00 cloth, $16.95 paper. LAWRENCE J. VALE, Reclaiming Public Housing: A Half Century of Struggle in Three Public Neighborhoods. Cambridge, Mass. : Harvard University Press, 2002, pp. xiii, 482, figures, tables, maps, notes, index, $39.95 cloth. PAUL BALCHIN and MAUREEN RHODEN, Housing Policy: An Introduction, 4th ed. London: Routledge, 2002, pp. xx, 492, figures, tables, boxes, references, index, $110.00 cloth.
Semantic Similarity Detection in Natural Language Documents

Data leak prevention (DLP) solutions monitor and control data flow. Current techniques find data that matches user defined syntactic patterns. Unfortunately, large classes of DLP relevant data are defined by information semantics, rather than data syntax. Syntax refers to data format, whereas semantics refers to data meaning. The class of social security numbers can be adequately expressed using data syntax, whereas a new industrial process can only be adequately described using information semantics. In this paper, we propose methods for extracting and identifying document semantics using training sets of limited size (tens of documents). The first method is based on singular value decomposition, which uses linear algebra to automatically extract semantic features from documents in the training set. The second method is to infer a hidden Markov model (HMM) expressing relations between the features extracted using the singular value method. This HMM can detect documents containing the intellectual property semantic information. A third method views the English language as a probabilistic context-free grammar (PCFG), and extracts semantic information from individual sentences in order to detect documents containing intellectual property. Test results on 5 document sets show the proposed methods give at least 84% true positive and below 22% false positive rates. Our methods are trained with only positive examples, and have lower false positive rates, compared to Latent Dirichlet Allocation (LDA) and Support Vector Machines (SVM).
Techniques for efficiently recording state changes of a computer environment to support reversible debugging

The notion of a truly reversible computer offers many potential applications. One such application is reversible debugging, also known as bi-directional debugging. Modern debuggers allow one to pause the execution of a program, generally for the purpose of trying to identify an error within the program. In the early stages of attempting to locate the cause of an error, the debugging process would be more intuitive if one could undo the effects of the program on the state of the environment. That is, execute the program in reverse. The potential benefit of reversible debugging is that less time is spent on debugging, which is a process that is normally overly tedious due to the inefficient manner in which it is performed. Further, some programs, such as those that are nondeterministic and operate in real time embedded environments, cannot be debugged by traditional means. The use of state change recording, or history logging, is one means by which such programs could be debugged. This thesis describes a set of techniques that, when used together, provide an efficient means of recording state changes. A case study is included that demonstrates the use of these techniques within a fully functional MIPS simulator implemented in Java. However, the techniques described are hardware and language independent. These techniques rely on both state change recording and program re-execution. State changes are recorded incrementally during each cycle of execution. Periodically, the current set of state changes is accumulated into a checkpoint structure. A stack of checkpoints is maintained, allowing the executing program to be reversed indefinitely. The primary concern of such history logging techniques is the unbounded growth of history information. A checkpoint culling algorithm is used to bound the size of the state history to a logarithmic function, as well as maintain a linear run time for undo operations. ( ,, )
Desenvolupament de la segona versió de l'aplicació web per a la gestió d’exercicis de bases de dades del sistema LearnSQL

LearnSQL (Sistema Learning Environment for Automatic Rating Notions of SQL) es un sistema que s’usa en les assignatures de bases de dades de la FIB per donar suport l’aprenentatge als estudiants, el sistema permet per una banda la correccio automatica dels exercicis que es fan a les assignatures de bases de dades, oferir feedback immediat de la seva solucio. Per altra banda permet mantenir un repositori dels exercicis que es poden consultar i re-aprofitar al llarg dels anys. El sistema esta format per diversos subsistemes. Un d’ells, es l’anomenada Authoring Tool (AT), es una eina que permet als professors gestionar els exercicis del repositori. Aquesta aplicacio la va desenvolupar Marc Fernandez l’any 2010 [1], posteriorment degut a que l’Authoring Tool tenia limitacions de disponibilitat i distribucio, per tant l’Albert Boada va desenvolupar un projecte partint de l’AT, i la va portar cap a la plataforma web, a partir de llavors la va anomenar Authoring Tool Web (ATW) [2]. S’ha desenvolupat una aplicacio amb un disseny i implementacio que pot ser facilment extensible i modificable. Per tant, en aquest projecte es desenvolupa una segona versio que parteix d’una llista de requisits proporcionats pels professors, i aprofitar al maxim la bona feina realitzada de la primera versio, la segona versio de l’ATW segueix utilitzant el mateix disseny, els mateixos patrons, i les mateixes tecnologies com PostgresSQL, Apache Struts2, AngularJS, JSON etc.