Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure and composition of the Aleutian island arc and implications for continental crustal growth

We present results of a seismic reflection and refraction investigation of the Aleutian island arc, designed to test the hypothesis that volcanic arcs constitute the building blocks of continental crust. The Aleutian arc has the requisite thickness (30 km) to build continental crust, but it differs strongly from continental crust in its composition and reflectivity structure. Seismic velocities and the compositions of erupted lavas suggest that the Aleutian crust has a mafic bulk composition, in contrast to the andesitic bulk composition of continents. The silicic upper crust and reflective lower crust that are characteristic of continental crust are conspicuously lacking in the Aleutian intraoceanic arc. Therefore, if island arcs form a significant source of continental crust, the bulk properties of arc crust must be substantially modified during or after accretion to a continental margin. The pervasive deformation, intracrustal melting, and delamination of mafic to ultramafic residuum necessary to transform arc crust into mature continental crust probably occur during arc-continent collision or through subsequent establishment of a continental arc. The volume of crust created along the arc exceeds that estimated by previous workers by about a factor of two.
Bayesian surplus production model with the Sampling Importance Resampling algorithm (BSP): a User’s Guide

The BSP program fits either a Schaefer model or a Fletcher / Schaefer model to CPUE data using the Sampling /Importance Resampling algorithm. Required inputs are catch for all years (missing catch data in the first years of the fishery are allowed), at least one catch rate (CPUE) index of abundance, with CV’s if available (missing data are allowed). The parameters that can be fit are carrying capacity (K), the intrinsic rate of population growth (r), the biomass in the first modeled year defined as a ratio of K (alpha.b0), the shape parameter for the surplus production function for the Fletcher/Schaefer fit (n), the average annual catch for years before catch data were recorded (cat0), , variance parameters for each CPUE series, depending on the method used to weight the CPUE series, and the catchability (q) for each CPUE series. Priors can be used for all of the fitted parameters for a Bayesian fit. The program can be used to project the biomass trajectory under any constant catch or constant F harvest policy, with confidence bounds. Program outputs include decision tables showing the probability of stock rebuilding and other indicators of policy performance at specified time horizons.
On Temporal Composability of Cyber-Physical Disruption-Tolerant Networks

Disruption-Tolerant Networks (DTNs) enable transfer of data when network nodes are only intermittently connected. With respect to the scarcity of connectivity in DTNs, a key research challenge is to guarantee schedulability of data flows which are to be fed into the network and prevent network resources from being channeled into serving data packets which cannot make deadline. Research efforts in real-time community are all concerned with traditional type of resources which are not available in time, but available in space. However, the nature of DTNs resources deviates from this model: not only are the network resources temporally unavailable, but also spatially unavailable. This distinct paradigm of resources demands for specialized schedulability analysis techniques to be developed. To this end, among a wide range of problems real-time DTNs require to be studied, in this paper we take the first step in this direction and analyze schedulability of the workload in recurrent DTNs. We extend the recently proposed delay composition framework for disruptiontolerant networks and provide a worst-case estimation of end-to-end latency of data flows and investigate how latency is composed in DTNs. We then analyze whether or not the multi-criticality spatially-distributed data flows meet their end-to-end deadline constraints. Our study through simulation based experiments show that our approach has moderate pessimism and provides appropriate schedulability guarantees prior to establishment of the distributed workload.
POST SEQUENTIAL PATTERNS MINING A New Method for Discovering Structural Patterns

In this paper we present a novel data mining technique, known as Post Sequential Patterns Mining, which can be used to discover Structural Patterns. A Structural Pattern is a new pattern, which is composed of sequential patterns, branch patterns or iterative patterns. Sequential patterns mining plays an essential role in many areas and substantial research has been conducted on their analysis and applications. In our previous work [12], we used a simple but efficient Sequential Patterns Graph (SPG) to model the sequential patterns. The task to discover hidden Structural Pattern is based on our previous work and sequential patterns mining, conveniently named Post Sequential Patterns Mining. In this paper, in addition to stating this new mining problem, we define patterns such as branch pattern, iterative pattern, structural pattern, and concentrate on finding concurrent branch pattern. Concurrent branch pattern is thus one of the main forms of structural pattern and will play an important role in event-based data modelling.
Learning to rank, a supervised approach for ranking of documents

As available information gets more accessible everywhere and as the rate of new information grows very fast, the systems and models which retrieve this information deserves more attention. The purpose of this thesis is to investigate state-of-the-art machine learning methods for ranking known as learning to rank. The goal is to explore if learning to rank can be used in enterprise search, which means less data and less document features than web based search. Comparisons between several state-of-the-art algorithms from RankLib (Dang, 2011) was carried out on benchmark datasets. Further, Fidelity Loss Ranking (Tsai et al., 2007) was implemented and added to RankLib. The performance of the tests showed that the machine learning algorithms in RankLib had similar performance and that the size of the training sets and the number of features were crucial. Learning to rank is a possible alternative to the standard ranking models in enterprise search only if there are enough features and enough training data. Advise for an implementation of learning to rank in Apache Solr is given, which can be useful for future development. Such an implementation requires a lot of understanding about how the Lucene core works on a low level.
The intangible aspects of architectural spaces that influence human well-being

This research uses qualitative and quantitative approaches in order to demonstrate how intangible aspects of architectural spaces influence human well-being. The goal is to increase awareness that interior spaces do impact human well-being and that architecture can be regarded as a solution to satisfy space users’ needs. In the first study a qualitative approach is explored through narrative inquiry in order to identify intangible aspects of residential and office spaces that affect human well-being. A discussion is built around the Model of Human Experiential Responses to Space and its purpose as a tool to unearth environmental characteristics that enhance well-being and can be of value to design professionals. Results show that 43 categories are interpreted as being intangible aspects of architectural spaces that influence human well-being. These categories are then used for three other studies to find out if there are any underlying regularities in environmental characteristics that affect user moods and feelings. Results show that similar environmental characteristics heighten sense of satisfaction and well-being for both residential and office space users. In the second study, a quantitative approach is applied to neurosciences and architecture in order to measure how architectural spaces influence human well-being. Neuroscience and environment / behaviour concepts are used where eight brain-based neuroscientific correlates (Zeisel 2006) are investigated in order to measure brain effects on architectural spaces. Neuroscientific outcomes reveal that the environment can affect human moods, ability to focus attention and stress levels and may also heighten task performance. Both studies contribute to knowing how space users feel environmental characteristics affect their mood and satisfaction. They reveal that people’s moods may be affected similarly in residential or office space settings and that a good environment that energizes employees will affect their work performance in a positive way (Vischer 2005).
Cosmology in Weyl Transverse Gravity

We study the Friedmann-Lemaitre-Robertson-Walker (FLRW) cosmology in the Weyl-transverse (WTDiff) gravity in a general space-time dimension. The WTDiff gravity is invariant under both the local Weyl (conformal) transformation and the volume preserving diffeormorphisms (transverse diffeomorphisms) and is believed to be equivalent to general relativity at least at the classical level (perhaps, even in the quantum regime). It is explicitly shown by solving the equations of motion that the FLRW metric is a classical solution in the WTDiff gravity only when the spatial metric is flat, that is, the Euclidean space, and the lapse function is a nontrivial function of the scale factor.
Digital Games in Language Learning and Teaching

Foreword J.P.Gee Introduction H.Reinders PART I: FROM THEORY TO PRACTICE Contextualising Digital Game-based Language Learning: Transformational Paradigm Shift or Business as Usual? M.Thomas Conceptualizing Digital game-mediated L2 Learning and Pedagogy: Game-enhanced and Game-based Research and Practice J.Reinhardt & J.Sykes Behaviorism, Constructivism, and Communities of Practice: How Pedagogic Theories help us Understand Game-based Language Learning M.Filsecker Language Learner Interaction in a Massively Multiplayer Online Role-playing Game (MMORPG) M.Peterson PART II: FROM PRACTICE TO THEORY Digital Gameplay for Autonomous Foreign Language Learning: Gamers and Language Teachers' Perspectives A.Chik Game-based Practice in a Reading Strategy Tutoring System: Showdown in iSTART-ME T.Jackson , K.Dempsey & D.McNamara Sprites and Rules: What ERPs and Procedural Memory can tell us about Video Games and Language Learning R.Reichle Talk to me! Games and Students' Willingness to Communicate H.Reinders & S.Wattana World of VocCraft: Computer Games and Swedish learners' L2 English Vocabulary P.Sundqvist & K.Sylven Collocation Games from a Language Corpus S.Wu , M.Franken & H.Witten
Security System for Mobile Messaging Applications

Instant messaging (IM) applications are one of the most popular applications for smartphones. The IMs have the capability of sending messages or initiating voice calls via Internet which makes it almost cost free for the users to communicate with each other. Unfortunately, like any other type of applications, majority of these applications are vulnerable to malicious attacks and have privacy issues.The motivation for this thesis is the need to identifying security services of an IM application and to design a secure system for any mobile messaging application. This research proposes an E2EE (End-to-End Encryption) approach which provides a secure IM application design which protects its users with better integrity, confidentiality and privacy.To achieve this goal a research is conducted to investigate current security features of popular messaging applications in the mobile market. A list of requirements for good security is generated and based on those requirements an architecture is designed. A demo is also implemented and evaluated.
Towards deep content extraction from specialized discourse : the case of verbal relations in patent claims

This thesis addresses the problem of the development of Natural LanguageProcessing techniques for the extraction and generalization of compositionaland functional relations from specialized written texts and, in particular, frompatent claims. One of the most demanding tasks tackled in the thesis is,according to the state of the art, the semantic generalization of linguisticdenominations of relations between object components and processesdescribed in the texts. These denominations are usually verbal expressions ornominalizations that are too concrete to be used as standard labels inknowledge representation forms -as, for example, “A leads to B”, and “Cprovokes D”, where “leads to” and “provokes” both express, in abstractterms, a cause, such that in both cases “A CAUSE B” and “C CAUSE D”would be more appropriate. A semantic generalization of the relations allowsus to achieve a higher degree of abstraction of the relationships betweenobjects and processes described in the claims and reduces their number to alimited set that is oriented towards relations as commonly used in the genericfield of knowledge representation.
Neutron star observations with WFXT

The Wide-Field X-ray Telescope (WFXT) is a proposed NASA mission dedicated to performing surveys of the sky in the soft X-ray band (0.3-6 keV). The key characteristics of this missions are a constant point spread function with Half Energy Width of ~5 arcsec over a ~1 degree field of view as well as an effective area ~10 times larger than the one of Chandra. Despite the fact that the mission is tailored for extragalactic purposes, we show here that extremely interesting results can also be obtained on the study of neutron stars.
Etude du traitement visuel rétinotopique des fréquences spatiales de scènes et plasticité cérébrale au cours du vieillissement normal et pathologique

L'analyse visuelle de scenes debute par l'extraction en parallele de differentes caracteristiques visuelles elementaires a differentes frequences spatiales. L'objectif de cette these a ete de preciser les mecanismes et les bases cerebrales du traitement des frequences spatiales lors de la categorisation de scenes et leur evolution au cours du vieillissement normal et pathologique. Nous avons tout d'abord mene deux etudes en Imagerie par Resonance Magnetique fonctionnelle (IRMf) sur des adultes jeunes avec une vision normale afin de proposer un outil de cartographie retinotopique des aires visuelles permettant une localisation fine des activations cerebrales qui soit a la fois rapide et precis (Experiences 1 et 2). Dans un second temps, nous avons etudie via IRMf les bases cerebrales du traitement des frequences spatiales lors de la categorisation de scenes chez de jeunes adultes avec vision normale(Experience 3). Nous avons egalement etudie l'influence de la normalisation RMS (« root mean square ») du contraste de luminance des scenes filtrees. Au sein du cortex occipital, nous avons montre une organisation retinotopique du traitement des frequences spatiales contenues dans de larges scenes visuelles. Au sein du cortex occipito-temporal, nous avons montre que les regions selectives aux scenes (la « parahippocampal place area », le cortex retrosplenial et l'« occipital place area ») participent de facon distincte au traitement des frequences spatiales. Enfin, nous avons montre que la normalisation du contraste de luminance modifiait l'intensite et l'etendue des activations cerebrales. Dans un dernier temps, nous avons ensuite etudie le traitement des frequences spatiales au cours du vieillissement normal et pathologique. Nous avons tout d'abord montre, dans le cas du vieillissement normal (Experience 4), un deficit specifique de la categorisation de scenes en hautes frequences spatiales (HFS), associe a une hypo activation du cortex occipital et des regions selectives aux scenes. Dans le cas de la perte de la vision centrale consecutive a une degenerescence maculaire liee a l'âge (patients DMLA, Experiences 5 et 6), nous avons mis en evidence un deficit du traitement des HFS encore plus marque que celui observe au cours du vieillissement normal. De facon interessante pour l'aide aux patients DMLA, l'augmentation du contraste de luminance des scenes en HFS ameliorait significativement leur categorisation des scenes en HFS. Les resultats de ces travaux nous permettent de mieux comprendre les mecanismes neuro-fonctionnels impliques dans la perception visuelle de scenes et de differencier les changements au niveau cortical lies au vieillissement normal de ceux resultant d'une pathologie visuelle.Mots cles : Scenes visuelles, Frequences spatiales, IRMf, Cortex visuel, Retinotopie, Regions selectives aux scenes, Vieillissement normal, DMLA.
The Universal B-Tree for multidimensional Indexing

Today almost all database systems use B-trees as their main access method. One of the main drawbacks of the classical B-tree is, however, that it works well only for one-dimensional data. In this paper we present a new access structure, called UB-tree (for universal B-tree) for multidimensional data. The UB-tree is balanced and has all the guaranteed performance characteristics of B-trees, i.e. it requires linear space for storage and logarithmic time for the basic operations of INSERT FIND DELETE. In addition the UB-tree has the fundamental property, that it preserves clustering of objects w.r. to Cartesian distance. Therefore, the UB-tree shows its main strengths for multidimensional data. It has very high potential for parallel processing. With the new method, a single UB-tree can replace an arbitrary number of secondary indexes. For updates this means that only one UB-tree must be managed instead of several secondary indexes. This reduces runtime and storage requirements substantially. For queries and in particular range queries the UB-tree has multiplicative complexity instead of the additive complexity of multiple secondary indexes. This results in dramatic performance improvements over secondary indexes. The UB-tree is obviously useful for geometric databases, datawarehousing and datamining applications, but even more for databases in general, where multiple secondary indexes are widespread, which can all be replaced by a single UB-tree index.
Fast Face Finding

Face detection is a classical application of object detection. There are many practical applications in which face detection is the first step; face recognition, video surveillance, image database management, video coding. This report presents the results of an implementation of the AdaBoost algorithm to train a Strong Classifier to be used for face detection. The AdaBoost algorithm is fast and shows a low false detection rate, two characteristics which are important for face detection algorithms. The application is an implementation of the AdaBoost algorithm with several command-line executables that support testing of the algorithm. The training and detection algorithms are separated from the rest of the application by a well defined interface to allow reuse as a software library. The source code is documented using the JavaDoc-standard, and CppDoc is then used to produce detailed information on classes and relationships in html format. The implemented algorithm is found to produce relatively high detection rate and low false alarm rate, considering the badly suited training data used.
A stochastic optimal control perspective on affect- sensitive teaching

For over half a century, computer scientists and psychologists have strived to build machines that teach humans automatically, sometimes dubbed intelligent tutoring systems (ITS). The earliest such systems focused on "flashcard"-style vocabulary learning, while more modern ITS can tutor students in diverse subjects such as high school geometry, physics, algebra, and computer programming. Compared to human tutors, however, most contemporary ITS still use a rather impoverished set of low-bandwidth sensors consisting of mouse clicks, keyboard strokes, and touch events. In contrast, human teachers utilize not only students' explicit responses to practice problems and test questions, but also auditory and visual information about the students' affective, or emotional, states, to make decisions. It is possible that, if automated teaching systems were affect-sensitive and could reliably detect and respond to their students' emotions, then they could teach even more effectively. In this dissertation we examine the affect-sensitive teaching problem from a stochastic optimal control (SOC) perspective. Stochastic optimal control theory provides a rigorous computational framework for describing the challenges and possible benefits of affect-sensitive teaching systems, and also provides computational tools that may help in building them. After framing the problem of affect-sensitive teaching using the language of SOC, we (1) present an experimental technique for measuring the importance to teaching of affect-sensitivity within a given learning domain. Next, we develop machine learning and computer vision tools to recognize automatically certain aspects of the student's affective state in real-time, including (2) student "engagement" and (3) the student's perception of curriculum difficulty. Finally, (4) we propose and evaluate an automated procedure, based on SOC, for creating an automated teacher that teaches foreign language by image association (a la Rosetta Stone). In a language learning experiment on 90 human subjects, the controller developed using SOC showed higher learning gains compared to two heuristic controllers, and also allows for affective observations to be easily integrated into the decision-making process.
Underwater thrust and power generation using flexible piezoelectric composites: an experimental investigation toward self-powered swimmer-sensor platforms

Fiber-based flexible piezoelectric composites offer several advantages to use in energy harvesting and biomimetic locomotion. These advantages include ease of application, high power density, effective bending actuation, silent operation over a range of frequencies, and light weight. Piezoelectric materials exhibit the well-known direct and converse piezoelectric effects. The direct piezoelectric effect has received growing attention for low-power generation to use in wireless electronic applications while the converse piezoelectric effect constitutes an alternative to replace the conventional actuators used in biomimetic locomotion. In this paper, underwater thrust and electricity generation are investigated experimentally by focusing on biomimetic structures with macro-fiber composite piezoelectrics. Fish-like bimorph configurations with and without a passive caudal fin (tail) are fabricated and compared. The favorable effect of having a passive caudal fin on the frequency bandwidth is reported. The presence of a passive caudal fin is observed to bring the second bending mode close to the first one, yielding a wideband behavior in thrust generation. The same smart fish configuration is tested for underwater piezoelectric power generation in response to harmonic excitation from its head. Resonant piezohydroelastic actuation is reported to generate milli-newton level hydrodynamic thrust using milli-watt level actuation power input. The average actuation power requirement for generating a mean thrust of 19 mN at 6 Hz using a 10 g piezoelastic fish with a caudal fin is measured as 120 mW. This work also discusses the feasibility of thrust generation using the harvested energy toward enabling self-powered swimmer-sensor platforms with comparisons based on the capacity levels of structural thin-film battery layers as well as harvested solar and vibrational energy.