Miracle-dz/UniFAR-FTUs huggingface dataset:
Virtuelle und reale Objekte als natürliche Bewegungsgrenzen in der Virtual Reality Exposure Therapy

Zur Behandlung von Angststorungen – welche mit zu den haufigsten psychischen Erkrankungen in Deutschland gehoren – bietet die klassische Expositionstherapie gute Erfolgsaussichten [1]. In den letzten Jahren entwickelte sich die Virtual Reality Exposure Therapy (VRET), welche eine interessante Alternative darstellt. Eine Studie zeigte 2013 die Effektivitat einer VRET [2]. Problematisch ist allerdings die Lokomotion in psychotherapeutischen Praxen mit geringem Raumangebot. Gangige Sicherheitssysteme zur Kollisionsvermeidung wie Lighthouse‘s Chaperone [3] [4] oder Occulus Guardian [5] zeigen bei Annaherung an die Grenzen des sicheren Bereiches eine auffallige optische Warnung an. Dies kann jedoch bei den Benutzern zu unerwunschten Prasenzeinbruchen (breaks in presence) fuhren. Simeone et al. [6] konnten nachweisen, dass in einer virtuellen Umgebung rein virtuelle Gegenstande oder Wande von den Benutzern als real wahrgenommen und umgangen werden. Dieser Effekt liess sich durch zusatzliche reale Gegenstande im Raum noch verstarken. In dieser Masterarbeit wurde untersucht, ob sich die Ergebnisse von Simeone et al. [6] auch auf die Anwendung der VRET ubertragen lassen. Dazu wurde eine Studie mit 2 Gruppen zu je 12 Probanden durchgefuhrt. Alle hielten 2 Vortrage in einer virtuellen Umgebung, je einen Vortrag mit Avatar und einen ohne. Wahrend eine Gruppe sich in einer virtuellen Umgebung mit ausschliesslich virtuellen Objekten bewegte, waren in der anderen Gruppe zusatzlich reale Gegenstande vorhanden. In der vorliegenden Masterarbeit konnte gezeigt werden, dass die Ergebnisse von Simeone et al. [6] auch fur VRET Anwendungen gultig sind. Virtuelle Objekte werden auch von Patienten eines VRET Systems als Begrenzungen akzeptiert. Zudem lassen sich physische Objekte in die virtuelle Umgebung integrieren, ohne dass es zu Kollisionen mit den Benutzern kommt oder die Benutzer eine erhohte Angst vor Kollisionen haben. Obwohl das Vorhandensein eines Avatars in der durchgefuhrten Studie keinen Einfluss auf die Ergebnisse hatte, wunschen sich die Benutzer einen Avatar in der VR. Der sichere Aufenthaltsbereich kann also bereits in der virtuellen Umgebung durch virtuelle Objekte abgegrenzt werden, wodurch - zugunsten der Vermeidung von Prasenzeinbruchen - auf ein System wie Lighthouse`s Chaperone [3] [4] verzichtet werden kann. Ausserdem mussen reale Gegenstande nicht aus dem Bewegungsbereich der Benutzer ausgeschlossen werden, sondern lassen sich in die virtuelle Umgebung integrieren. Dies stellt eine praktikable Moglichkeit dar, den fur VRET nutzbaren Raum in psychotherapeutischen Einrichtungen zu optimieren. Somit stellt die VRET eine echte Alternative zur klassischen Expositionstherapie dar.
Random walk gossip-based manycast with partition detection

Communication is vital for successful cooperation in the event of a disaster. Such a situation calls for dissemination methods that provide partition-tolerant, energyefficient, timely, and reliable delivery. We present a protocol that meets these requirements by combining a novel random walk gossip with a partition detection mechanism. The protocol is able to guarantee that at least M nodes will be reached by the message without having to know which nodes are in the system.
Analytical model of the basis of consumer decision on purchase of goods

In daily life, an average consumer has many different alternatives when choosing a product at the customer buying process. Whether it is a choice of a product line from the shelves of supermarkets, a selection of an automobile from a car dealer or buying of an apartment of the desired plan in the required area. In turn, the companies selling goods have to more and more “attack” consumers to the end that the choice of a buyer turns precisely to their goods. Various advertising and PR campaigns are in progress, marketing approaches are put to use. However, it does not have the result the companies want to achieve. In the modern world, the consumer is already taught how to resist the many tricks of marketers. In this regard, other factors of influence on the choice of the consumer start to come to the fore. One of these factors is the study of a deeper analytical understanding of the basis on which and how the buyer decides on the product / brand choice. The article concerns a modern analytical model that makes it possible to understand what systems inside the human consciousness are responsible for making a purchasing decision, and with the help of which one can influence this choice when conducting marketing talks.
Learning and inference in weighted logic with application to natural language processing

Over the past two decades, statistical machine learning approaches to natural language processing have largely replaced earlier logic-based systems. These probabilistic methods have proven to be well-suited to the ambiguity inherent in human communication. However, the shift to statistical modeling has mostly abandoned the representational advantages of logic-based approaches. For example, many language processing problems can be more meaningfully expressed in first-order logic rather than propositional logic. Unfortunately, most machine learning algorithms have been developed for propositional knowledge representations. In recent years, there have been a number of attempts to combine logical and probabilistic approaches to artificial intelligence. However, their impact on real-world applications has been limited because of serious scalability issues that arise when algorithms designed for propositional representations are applied to first-order logic representations. In this thesis, we explore approximate learning and inference algorithms that are tailored for higher-order representations, and demonstrate that this synthesis of probability and logic can significantly improve the accuracy of several language processing systems.
Design and Implementation of Scalable and Efficient Programming Models for Fast Computation and Data Processing

Despite the tremendous growth of computational power, scientific applications and business data analytics continue to face many challenges such as programming productivity, application scalability, and efficiency. Recently, Global Address Space (GAS) or Partitioned Global Address Space (PGAS) programming models are emerging as scalable alternatives for fast computation because of their ability to alleviate programming burden by supporting data access to both local and remote memory through a simple shared-memory addressing model. Meanwhile, with the exponential growth of the digital universe, the MapReduce programming model becomes popular for data analytics because of its ease of use, low cost on commodity hardware, fault tolerance, and programming flexibility. Furthermore, with social media data gets bigger, relationships inside social media data get complex and have normally been modeled as massive graphs, which require scalable algorithms to analyze the real-world graphs for data processing. This dissertation investigates the research challenges in those directions and contributes efficient and scalable programming models for fast computation and data processing. It first focuses on addressing the critical challenges faced by the underlying runtime systems of GAS model on petascale systems. In particular, I have proposed and designed a Hierarchical Cooperation (HiCOO) supporting scalable communication for GAS programming models, which is able to realize scalable resource management and achieve resilience to network contention while at the same time maintaining or enhancing the performance of scientific applications. The second study is to address the performance challenge in the existing MapReduce programming model. I have revealed a number of issues faced by the current MapReduce Programming model and proposed a novel virtual shuffling strategy to enable efficient data movement for MapReduce data shuffling, which is able to significantly reduce
Implementation and evaluation of Norwegian Analyzer for use with DotLucene

This work has focused on improving retrieval performance of search in Norwegian document collections. The initiator of the thesis, InfoFinder Norge, desired an Norwegian analyzer for DotLucene. The standard analyzer used before did not support stopword elimination and stemming for Norwegian language. Norwegian Analyzer and standard analyzer were used in turns on the same document collection before indexing and querying, then the respective results were compared to discover efficiency improvements. An evaluation method based on Term Relevance Sets were investigated and used on DotLucene with use of the two analyzer approaches. Term Relevance Sets methodology were also compared with common measurements for relevance judging, and found useful for evaluation of IR systems. The evaluation results of Norwegian analyzer and standard analyzer gave clear indications that use of stopword elimination and stemming for Norwegian documents improves retrieval efficiency. Term Relevance Set-based evaluation was found reliable by comparing the results with precision measurements. Precision was increased with 16% with use of Norwegian Analyzer compared to use an standard analyzer with no content preprocessing support for Norwegian. Term Relevance Set evaluation with use of 10 ontopic terms and 10 offtopic terms gave an increased $tScore$ of 44%. The results show that counting term occurrences in the content of retrieved documents can be used to gain confidence that documents are either relevant or not relevant.
Diez contradicciones del enfoque comunicativo

Esta version de "Diez contradicciones del enfoque comunicativo" es en su mayor parte igual a la que lei en el V encuentro nacional de profesores de lenguas; los cambios que he efectuado son pocos, y la mayoria de ellos menores. Por ejemplo, en algunos parrafos he reducido la puntuacion, que me sirvio de apoyo en la presentacion oral y que pudiera ser excesiva para una lectura en silencio fluida. Por razones similares, he eliminado ciertas repeticiones. Tambien he sustituido dos o tres palabras que resultaban demasiado informales en un texto escrito.
Collins COBUILD idioms dictionary

This reissue of the second edition of the Collins COBUILD Dictionary of Idioms offers in-depth treatment of the most important idioms in current British and American English. The Dictionary of Idioms offers in-depth coverage of the most important idioms in English, and provides additional information about their frequency, contexts, meanings, and usage. Thousands of examples from the Bank of English have been used to illustrate clearly how the idioms are used in the language today. New to this edition is fascinating information about the origins of hundreds of idioms, essential for learners wishing to gain a fuller understanding of the language. Clearly laid-out and easy-to-use, the Collins COBUILD Dictionary of Idioms will prove to be fascinating and invaluable to teachers and learners of English at all levels.
A Grounded Theory Study of Working Adults Navigating Advanced Degrees

A Grounded Theory Study of Working Adults Navigating Advanced Degrees by Charles V. Slider, Jr. MEd, Drury University, 2008 MA, Wayne State University, 1994 BS, University of Maryland, 1989 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of
Android Recipes: A Problem-Solution Approach

Android continues to be one of the leading mobile OS and development platforms driving today's mobile innovations and the apps ecosystem. Androidappears complex, but offers a variety of organized development kits to those coming into Android with differing programming language skill sets. Android Recipes: A Problem-Solution Approach, Second Editionguides you step-by-step through a wide range of useful topics using complete and real-world working code examples. It's updated to include latest Jelly Bean Android SDK as well as earlier releases. In this expanded edition, You'll start off with a recap of Android architecture and app fundamentals, and then get down to business and build an app with Android SDK 4.1 version or earlier releaseat the command line and Eclipse. Next, you'll learn how to accomplish practical tasks pertaining to the user interface, communications with the cloud, device hardware, data persistence, communications between applications, and interacting with Android itself. Finally, you'll learn how to leverage various libraries and Scripting Layer for Android (SL4A)to help you perform tasks more quickly, how to use the Android NDK to boost app performance, and how to design apps for performance, responsiveness, seamlessness, and more. Instead of abstract descriptions of complex concepts, in Android Recipes, you'll find live code examples. When you start a new project, you can consider copying and pasting the code and configuration files from this book, then modifying them for your own customization needs. This can save you a great deal of work over creating a project from scratch! What youll learn Discover Android architecture and various Android-specific APIs How to develop a unit conversion app in the context of command-line/Android SDK and Eclipse/Android SDK environments How to accomplish various tasks related to the user interface and more How to use external libraries to save time and effort How to quickly develop an app using the Scripting Layerfor Android (SL4A) tool How to boost app performance by using the Android NDK Guidelines for designing filtered apps, performant apps, responsive apps, and seamless apps Who this book is for This book is a handy reference for all Android app developers. Newcomers may also find this of interest, too. Table of Contents1. Getting Started with Android 2. User Interface Recipes 3. Communications and Networking 4. Interacting with Device Hardware and Media 5. Persisting Data 6. Interacting with the System 7. Working with Libraries 8. Working with Android NDK and Renderscript 9. Appendix A: Scripting Layer for Android 10. Appendix B: Android Tools Overview 11. Appendix C: App Design Guidelines 12. Appendix D: Univerter Architecture
İlköğretim 6. Ve 7. Sınıf sosyal bilgiler programlarında türk halk kültürü oğelerinin yeri ve önemi

Turk halk kulturu, yuzyillarin deneyimlerinden suzulerek bicimlenmis, kusaktan kusaga aktarilan bir degerler butunudur. Halk kulturu urunleriyle yasadiklari yore arasinda bir bag vardir. Bu urunlerin sekillenmesinde tarihi ve kulturel mirasin onemli bir rolu vardir. Turk kultur mirasinin korunmasinda ve yasatilmasinda ders programlari ve kitaplarinin onemli islevleri bulunmaktadir
Classification automatique de documents bruités à faible contenu textuel

La classification de documents numeriques est une tâche complexe dans un flux numerique de gestion electronique de documents. Cependant, la quantite des documents issus de la retro-conversion d'OCR (Reconnaissance Optique de Caracteres) constitue une problematique qui ne facilite pas la tâche de classification. Apres l'etude et l'evaluation des descripteurs les mieux adaptes aux documents issus d'OCR, nous proposons une nouvelle approche de representation des donnees textuelles : l'approche HYBRED (HYBrid REpresentation of Documents). Elle permet de combiner l'utilisation de differents descripteurs d'un texte afin d'obtenir une representation plus pertinente de celui-ci. Les experimentations menees sur des donnees reelles ont montre l'interet de notre approche.
Segmentwise unit selection

Unit selection speech systems generate synthetic speech by concatenation of acoustic units extracted from a natural recording. Given a large speech database, the sequence of units with the best global cost is chosen by means of a Viterbi search. In this reported work, it is shown that small subcosts not related to perceptual measures can affect the sequence of units that is finally chosen, with a potential effect on the quality of synthetic speech. A segmentwise unit selection approach that minimises this effect is then proposed.
Acceleration of Sphinx 3 for implementation in embedded systems

This thesis presents a fully pipelined and parameterised parallel hardware implementation of a large vocabulary, user-independent and continuous speech recognition system for use in mobile applications. Algorithm acceleration is achieved by realising in hardware the most time-consuming components of the speech recognition system. By adopting a parallel solution, the necessary calculations can be completed in a sufficiently short elapsed time for embedded target systems. Sphinx 3 is identified as an appropriate speech recognition system for this work and is profiled to determine the most time-consuming parts of the code. As these parts of the code employ calculations based on floating point operations, which are not suitable for the high-performance and low-power execution on embedded systems, these calculations have been converted to scaled integer operations. It is verified using the AN4, RM1 and TIMIT speech databases that the scaled integer version of the speech recognition system can achieve a similar word error rate to the original floating point version, while taking less than 8% of the calculation time used by the original version. The scaled integer version of the speech recognition system is redesigned in VHDL for parallel implementation in electronic hardware. The designs of a calculation module and a data module are described, both of which can be configured according to the number of parallel units and the data module can be configured according to the total numbers of feature vectors and senones used in the speech representation. The hardware designs are synthesised to a range of FPGAs and the results showed that the larger Virtex7 devices are capable of holding several thousands of senones which are sufficient for most recognition tasks. Hardware designs with different numbers of parallel calculation units are simulated at both behavioural level and platform-based level and the resulting implementations are able to operate in real time. The results show that the hardware implementation, even with only one calculation unit, can perform the same calculations almost 80 times faster than does a modern embedded microprocessor, even when operating at only one fifth of the clock frequency. With larger numbers of parallel calculation units, the whole design can operate at even lower clock frequencies, saving power while maintaining a rapid calculation speed. The hardware designs are also implemented on a physical system having both an FPGA and a microprocessor board to demonstrate the operational capabilities of a full system.
Speech Generation in a Spoken Dialogue System

Spoken dialogue systems accessed over the telephone network are rapidly becoming more popular as a means to reduce call-centre costs and improve customer experience. It is now technologically feasible to delegate repetitive and relatively simple tasks conducted in most telephone calls to automatic systems. Such a system uses speech recognition to take input from users. This work focuses on the speech generation component that a specific prototype system uses to convey audible speech output back to the user. Many commercial systems contain general text-to-speech synthesisers. Text-to-speech synthesis is a very active branch of speech processing. It aims to build machines that read text aloud. In some languages this has been a reality for almost two decades. While these synthesisers are often very understandable, they almost never sound natural. The output quality of synthetic speech is considered to be a very important factor in the user’s perception of the quality and usability of spoken dialogue systems. The static nature of the spoken dialogue system is exploited to produce a custom speech synthesis component that provides very high quality output speech for the particular application. To this end the current state of the art in speech synthesis is surveyed and summarised. A unit-selection synthesiser is produced that functions in Afrikaans, English and Xhosa. The unit-selection synthesiser selects short waveforms from a recorded speech corpus, and concatenates them to produce the required utterances. Techniques are developed for designing a compact corpus and processing it to produce a unit-selection database. Speech modification methods were researched to build a framework for natural-sounding speech concatenation. This framework also provides pitch and duration modification capabilities that will enable research in languages such as Afrikaans and Xhosa where text-to-speech capabilities are relatively immature.
Constructions with verbs of dispossession in Dutch A corpus-based case study

This paper focuses on the constructional possibilities of verbs of reception and dispossession in Dutch. These verb classes have received considerably less linguistic attention than their counterparts among the verbs of transfer of possession, the verbs of giving. In this paper, we intend to show, however, that reception and dispossession verbs constitute an interesting area of investigation as well, by laying bare the constructional variation they display, both synchronically and diachronically. The first part of our paper provides a brief overview of this variation. In the second part, we present a case study of six typical verbs of dispossession: the simplex verbs stelen ‘steal’ and roven ‘rob’ and their be - and ont - prefixed variants, bestelen , beroven , ontroven and ontstelen . Their use will be examined in corpora of Middle, 19 th Century and present-day Dutch.
A microscopic model of speech recognition for listeners with normal and impaired hearing

Diese Dissertation stellt ein mikroskopisches Modell der menschlichen Spracherkennung (HSR) vor; mikroskopisch bedeutet erstens, dass die Erkennung einzelner Phoneme (und nicht die Erkennung ganzer Satze) modelliert wird. Zweitens wird die genaue spektro-temporale Struktur von Sprache mit einem auditorischen Modell verarbeitet. Gangige Modelle der HSR verwenden hingegen die spektrale Struktur allein. Das Modell ist dazu in der Lage die Phonemerkennung von Normalhorenden (NH) im Rauschen und wichtige Aspekte der Konsonanterkennung in Ruhe vorherzusagen. Weiterhin wird das Modell zur Vorhersage von Satzverstandlichkeiten erweitert. Diese Erweiterung sagt die Spracherkennung von NH und SH mit der gleichen Genauigkeit vorher wie ein Standard-Sprachverstandlichkeitsmodell. Die uberschwellige Verarbeitung von NH und SH wird mit Hilfe psychoakustischer Messmethoden (Nachverdeckungsexperiment und kategoriale Lautheitsskalierung) erfasst. Diese uberschwellige Verarbeitung wird dann im Modell berucksichtigt. Es zeigt sich, dass eine Berucksichtigung der uberschwelligen Verarbeitung die Vorhersagegenauigkeit verbessert.
Probing Student Experience and Success in an Engineering Programme through Development of a Questionnaire and Complexity Analysis

Abstract : This paper describes the development and application of an instrument to evaluate student success in an engineering programme. The motivation for this study was the planned introduction of a very different curriculum, and a desire to provide some measure of its impact. The questionnaire used was based on previous studies done in many parts of the world and feedback from a group of fourth year students. It was administered to first year students on the old curriculum towards the end of the academic year, and will be administered again to students on the new curriculum at the same time of year. Analysis will be done using a complexity thinking framework, making use of Exploratory Factor Analysis, Multidimensional scaling, Network Analysis, and Multilayer Minimum Spanning Tree Analysis. The paper will discuss the benefits that such analyses offer in terms of the insights that can be gained into the relationships between the variables affecting student success, which could point to actions to be taken to improve student success.