Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnostik okklusaler Läsionen mittels Quantitativer Lichtinduzierter Fluoreszenzmessung (QLF) : eine In-vitro-Studie

Die Quantitative Lichtinduzierte Fluoreszenzmessung (QLF) ist eine neue nicht invasive Diagnostikmethode, die die unterschiedlichen Fluoreszenzeigenschaften von gesunder und karioser Zahnhartsubstanz nutzt. Ziel der vorliegenden In-vitro-Studie war es, QLF als Methode zur Detektion okklusaler Dentinlasionen zu prufen und vergleichend mit den konventionellen Verfahren der visuellen und rontgenografischen Okklusalkariesdiagnostik zu bewerten. Dabei sollte auch die Moglichkeit der Nutzung aller QLF-Parameter (Fluoreszenzverlust, Flache der Lasion, Produkt aus Fluoreszenzverlust und Lasionsflache) gepruft werden. In die Untersuchung wurden 54 Okklusalflachen extrahierter Molaren mit unterschiedlichen kariosen Progressionsstadien einbezogen. Alle Zahne wurden einer differenzierten visuellen (Ekstrand et al. 1997) und rontgenografischen Untersuchung (Weerheijm et al. 1992) unterzogen. Anschliesend wurden Fluoreszenzbilder von den Okklusalflachen angefertigt und mit der QLF-spezifischen Software ausgewertet. Zur Validierung der Diagnostikmethoden wurden histologische Schnitte angefertigt und mikroradiografisch semi-quantitativ befundet. Alle Diagnostikverfahren wurden mit den Genauigkeitsparametern Sensitivitat, Spezifitat, Akkuratheit eingeschatzt. Um Aussagen uber die klinische Brauchbarkeit der Methoden zu erhalten, wurde die positive und negative Likelihood Ratio bestimmt. Nach Kombination aller drei QLF-Parameter wurde eine Sensitivitat von 86,4 % und eine Spezifitat von 90,6 % ermittelt. Die visuelle Untersuchung nach Ekstrand et al. (1997) erzielte mit 68,2 % eine relativ hohe Sensitivitat, die sich jedoch zu Lasten der Spezifitat mit nur 87,5 % auswirkte. Die Rontgendiagnostik erreichte eine Sensitivitat von 68,2 % und eine Spezifitat von 67,7 %. Die Betrachtung der Werte fur die Likelihood Ratio fuhrte ebenfalls zur Favorisierung der der QLF-Methode. Im Ergebnis der vorliegen In-vitro-Studie kann QLF nach der visuellen Basis-Diagnostik als erganzendes Verfahren zur Detektion okklusaler Dentinlasionen empfohlen werden. Da in klinischen Untersuchungen bisher keine Kriterien fur die Differentialdiagnostik von Schmelz- und Dentinkaries fur QLF definiert wurden, stellt die rontgenografische Untersuchung in der zahnarztlichen Praxis nach wie vor das Diagnostikverfahren der Wahl dar, um versteckte Dentinlasionen erganzend zur visuellen Befundung erfassen zu konnen. Die gewonnenen Erkenntnisse zur Nutzung der QLF-Parameter - Fluoreszenzverlust, Flache der Lasion, Produkt aus Fluoreszenzverlust und Lasionsflache- und die daraus resultierenden Kriterien mussen in nachfolgenden klinischen Untersuchungen gepruft werden.
Page Segmentation and Zone Classification: The State of the Art

Abstract : Page segmentation and zone classification are key areas of research in document image processing, because they occupy an intermediate position between document preprocessing and higher-level document understanding such as logical page analysis and OCR. Such analysis of the page relies heavily on an appropriate document model and results in a representation of the physical structure of the document. The purpose of this review is to analyze progress made in page segmentation and zone classification and suggest what needs to be done to advance the field.
Adaptive algorithms for history matching and uncertainty quantification

I ACKNOWLEDGMENTS . III TABLE OF CONTENTS . IV LIST OF TABLES . IX LIST OF FIGURES . X LIST OF PUBLICATIONS . XVIII CHAPTER 1: INTRODUCTION . 1 1.1 BACKGROUND . 1 1.2 RESEARCH OBJECTIVES . 3 1.3 STRUCTURE OF THE THESIS . 4 CHAPTER 2: A LITERATURE REVIEW ON RESERVOIR HISTORY MATCHING AND UNCERTAINTY QUANTIFICATION AND ALGORITHMS USED . 6 2.
Pragmalinguistik : Grundlagen, Anwendungen, Probleme

Although there is still no general agreement on the exact functions of linguistic pragmatics and the fields of activity it covers, it can generally be understood as the relationship of language to its users and the resultant practical applications of language. Thus it is one of the main concerns of research in this field to achieve a better understanding and account of the influence of extra-linguistic factors on language. In this introduction to the field, "pragmalinguistics" is seen as a field within the more general subject of "pragmatics. " The book aims to familiarize those interested in linguistics with the problems and methods of what is still an "open" field of enquiry and to present its main topic areas - pragmalinguistics as a general semiotic theory, as speech act theory, as the linguistics of conversation, and as text linguistics.
Trust-aware information retrieval in peer-to-peer environments

Information Retrieval in P2P environments (P2PIR) has become an active ? eld of research due to the observation that P2P architectures have the potential to become as appealing as traditional centralised architectures. P2P networks are formed with voluntary peers that exchange information and accomplish various tasks. Some of them may be malicious peers spreading untrustworthy resources. However, existing P2PIR systems only focus on ? nding relevant documents, while trustworthiness of documents and document providers has been ignored. Without prior experience and knowledge about the network, users run the risk to review,download and use untrustworthy documents, even if these documents are relevant. The work presented in this dissertation provide the ? rst integrated framework for trust-aware Information Retrieval in P2P environments, which can retrieve not only relevant but also trustworthy documents. The proposed content trust models extend an existing P2P trust management system, PeerTrust, in the context of P2PIR to compute the trust values of documents and document providers for given queries. A method is proposed to estimate global term statistics which are integrated with existing relevance-based approaches for document ranking and peer selection. Di? erent approaches are explored to ? nd optimal parametersettings in the proposed trust-aware P2PIR systems. Moreover, system architectures and data management protocols are designed to implement the proposed trust-aware P2PIR systems in structured P2P networks. The experimental evaluation demonstrates that P2PIR can bene? t from trust-aware P2PIR systems signi? cantly. It can importantly reduce the possibility of untrustworthy documents in the top-ranked result list. The proposed estimated global term statistics can provide acceptable and competitive retrieval accuracy within di? erent P2PIR scenarios.
Practical Cost-Conscious Active Learning for Data Annotation in Annotator-Initiated Environments

Practical Cost-Conscious Active Learning for Data Annotation in Annotator-Initiated Environments Robbie A. Haertel Department of Computer Science, BYU Doctor of Philosophy Many projects exist whose purpose is to augment raw data with annotations that increase the usefulness of the data. The number of these projects is rapidly growing and in the age of “big data” the amount of data to be annotated is likewise growing within each project. One common use of such data is in supervised machine learning, which requires labeled data to train a predictive model. Annotation is often a very expensive proposition, particularly for structured data. The purpose of this dissertation is to explore methods of reducing the cost of creating such data sets, including annotated text corpora. We focus on active learning to address the annotation problem. Active learning employs models trained using machine learning to identify instances in the data that are most informative and least costly. We introduce novel techniques for adapting vanilla active learning to situations wherein data instances are of varying benefit and cost, annotators request work “on-demand,” and there are multiple, fallible annotators of differing levels of accuracy and cost. In order to account for data instances of varying cost, we build a model of cost from real annotation data based on a user study. We also introduce a novel cost-conscious active learning algorithm which we call return-on-investment, that selects instances for annotation that contain the most benefit per unit cost. To address the issue of annotators that request instances “on-demand,” we develop a parallel, “no-wait” framework that performs computation while the annotator is annotating. As a result, annotators need not wait for the computer to determine the best instance for them to annotate—a common problem with existing approaches. Finally, we introduce a Bayesian model designed to simultaneously infer ground truth annotations from noisy annotations, infer each individual annotators accuracy, and predict its own accuracy on unseen data, without the use of a held-out set. We extend ROI-based active learning and our annotation framework to handle multiple annotators using this model. As a whole, our work shows that the techniques introduced in this dissertation reduce the cost of annotation in scenarios that are more true-to-life than previous research.
Digital skills as a basis for TPCK

Pupils in today's elementary and secondary schools are in need totally different skills than 40 years ago. When they finish school, they must deal with technology-dense communities that are more complex than previously and continuously changing. This places new demands on schools and their teachers. TPCK is a suitable model to describe the skills teachers need to provide adequate teaching for their students‘ future. This paper presents results from research on newly qualified teachers about their digital literacy, their use of ICT in their work practices and various factors that may affect this. The survey focused particularly on teacher education. In this paper, I argue that teachers‘ (and students‘) need for digital user skills are undervalued and under communicated with regards to pedagogical and content knowledge. The paper concludes that the emphasis on digital skills in teacher education will lead to graduated teachers having the ability to use technology intensively in their teaching and learning facilitation; in other words, they have TPCK.
BioFrameNet: A FrameNet Extension to the Domain of Molecular Biology

BioFrameNet: a FrameNet Extension to the Domain of Molecular Biology by Andrew Eric Dolbey B.A. (Towson State University) 1992 M.A. (University of California, Berkeley) 1995 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Linguistics in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Charles J. Fillmore, Chair Professor Jerry Feldman Professor Sharon Inkelas Professor Martha Palmer Fall 2009
Type-Based Verification of Assembly Language

It is a common belief that certifying compilation, which typically verifies the welltypedness of compiler output, can be an effective mechanism for compiler debugging, in addition to ensuring basic safety properties. Bytecode verification is a fairly simple example of this approach and derives its simplicity in part by compiling to carefully crafted high-level bytecodes. In this paper, we seek to push this method to native assembly code, while maintaining much of the simplicity of bytecode verification. Furthermore, we wish to provide experimental confirmation that such a tool can be accessible and effective for compiler debugging. To achieve these goals, we present a type-based data-flow analysis or abstract interpretation for assembly code compiled from a Java-like language, and evaluate its bug-finding efficacy on a large set of student compilers.
Modelling Speaker Variability and Imposing Speaker Constraints in Phonetic Classification

Abstract : This thesis deals with intraspeaker correlation analyses of speech sounds, and the possible utilization of this correlation to speech recognition. Current approaches to phonetic classification, regardless of whether they use context-dependent or -independent models, achieve classification based on locally optimum criteria. They make no fundamental assumption about the fact that the same vocal tract is used to make all the phonemes in an utterance. Thus, for example, a system may classify one sound in the beginning of an utterance as an /s/ belonging to a long vocal tract, while inappropriately, classifying another sound in the same utterance as an /Sigma/ belonging to a short vocal tract. Clearly the different phonemes of an utterance are correlated. Hence there is a set of speaker-specific constraints that can be imposed among all sounds in an utterance, and phonetic decoding should be accomplished by exploiting these constraints.
Antithesis: A Study in Clause Combining and Discourse Structure.

Abstract : Al Research in text generation needs a strong linguistically justified descriptive theory as a basis for creating methods by which programs can write multiparagraph texts. This paper sketches Rhetorical Structure Theory, which has been designed to support text generation, and then applies RST to describing a particular class of discourse constructs. There is no concensus as to the status of clause combining relations relative to larger texts. This paper demonstrates a clause combining relation that is also found as part of larger text structures, and shows how this fact can be used to explain cases in which contrastive clause combining appears between clauses that are not in fact in contrast. The appropriate generalization is that the relations of clause combining and the relations of general text structure are the same. Use of this generalization should make Al text planning and text generation significantly easier.
Quantum Communication and Security

This volume aims to assess the state-of-the-art in the field of Quantum Communication and Security and to identify new research challenges. The papers in this book concentrate mainly on quantum cryptography (both technical and experimental aspects and pure theory), general problems of theoretical quantum information and its realizations (laboratories and applied physics), and finally the related topics concerning quantum theory itself - the most fundamental questions. This publication is divided into four chapters: Quantum Cryptography; Theory of Quantum Information; Production of Entangled States, Experimental Techniques; and Quantum Communication and Computation. The editors hope to disseminate a broad spectrum of advances in quantum information and communication with this book.
A Network Link Prediction Model Based on Object-Object Match Method

In this paper, we proposed and evaluated a new network link prediction method that can be used to predict missing links in a social network. In the proposed model, to improve the prediction accuracy, the network link prediction problem is transformed to a general object-object match prediction problem, in which the nodes of a network are regarded as objects and the neighbors of a node are regarded as the node's associated features. Also a machine learning framework is devised for the systematic prediction. We compare the prediction accuracy of the proposed method with existing network link prediction methods using well-known network datasets such as a scientific co-authorship network, an e-mail communication network, and a product co-purchasing network. The results showed that the proposed approach made a significant improvement in all three networks. Also it reveals that considering the neighbor's neighbors are critical to improve the prediction accuracy.
Clustering de instalações, com (re)definição de segmentos em função do comportamento energético

This report describes all the work realized throughout the Mathematical Engineering Master Degree’s internship at EDP Distribuição Energia, S.A. EDP Distribuição has installed smart meter reading (telemetry) in various companies located in the national territory. The present study’s aim was to cluster companies considering their daily energy consumption. Initially, to achieve this goal, it was necessary to understand energy consumption by setting explanatory variables of consumption, such as the opening hours of each company, holidays and climatic variables (temperature, humidity, etc). Then, a study on consumption in a time series perspective was conducted, using decomposition methods, smoothing and singular spectral analysis, and multiple linear regression. It was observed that only a few variables influence the consumption and, for this reason, backward, random forest and correlation methods were employed to find the most significant variables in energy consumption. After selecting the companies for this work, methods of clustering time series for big data were researched and u-shapelets and similarity factors methods were used. FCUP iii Clustering de instalações, com (re)definição de segmentos em função do comportamento energético
A Web Personalized Recommender System Using Clustering-based CBR

Recently, many researches on recommendation systems and collaborative filtering have been proceeding in both research and practice. However, although product items may have multi-valued attributes, previous studies did not reflect the multi-valued attributes. To overcome this limitation, this paper proposes new methodology for recommendation system. The proposed methodology uses multi-valued attributes based on clustering technique for items and applies the collaborative filtering to provide accurate recommendations. In the proposed methodology, both user clustering-based CBR and item attribute clustering-based CBR technique have been applied to the collaborative filtering to consider correlation of item to item as well as correlation of user to user. By using multi-valued attribute-based clustering technique for items, characteristics of items are identified clearly. Extensive experiments have been performed with MovieLens data to validate the proposed methodology. The results of the experiment show that the proposed methodology outperforms the benchmarked methodologies: Case Based Reasoning Collaborative Filtering (CBR_CF) and User Clustering Case Based Reasoning Collaborative Filtering (UC_CBR_CF).
Large-Signal RF Modeling with the EKV3 MOSFET Model

This paper presents a validation of the EKV3 MOSFET model under load-pull conditions with high input power at 5.8 GHz, as well as S-parameter measurements with low input power up to 20 GHz. The EKV3 model is able to represent coherently the largeand small-signal RF characteristics in advanced 90 nm CMOS technology. Multifinger devices with nominal drawn gate length of 70 nm are used. Keywords—compact model, EKV3 model, large-signal, loadpull, MOSFET model, radio frequency.
A Constrained Gaussian Mixture Model for Correlation-Based Cluster Analysis of Gene Expression Data

Clustering is a practical data analysis step in gene expression-based studies. Model-based clusterings, which are based on probabilistic generative models, have two advantages: the number of clusters can be determined based on statistical criteria, and the clusters are robust against the observation noises in data. Many existing approaches assume multi-variate Gaussian mixtures as generative models, which are analogous to the use of Euclidean or Mahalanobis type distance as the similarity measure. However, these types of similarity measures often fail to detect co-expressed gene groups. We propose a novel probabilistic model for cluster analyses based on the correlation between gene expression patterns. We also propose a “meta” cluster analysis method to eliminate the dependence of the clustering result on initial values of the clustering algorithm. In empirical studies with a time course gene expression dataset of Bacillus subtilis during sporulation, our method acquires more stable and informative results than the ordinary Gaussian mixture model-based clustering, k-means clustering and hierarchical clustering algorithms, which are widely used in this field. In addition, with the meta-cluster analysis, biologically-meaningful expression patterns are extracted from a set of clustering results. The constraints in our model worked more efficiently than those in the previous studies. In our experiment, such constraints contributed to the stability of the clustering results. Moreover, the clustering based on the Bayesian inference was found to be more stable than those by the conventional maximum likelihood estimation.
Cross-Domain, Single Resource Authorization using HCM

Grid is a heterogeneous and very dynamic environment where a scalable authorization system is needed. Existing grid authorization systems adopt mechanisms for storing resources’ security policies that suffer from huge repetitions while checking security rules. To overcome this problem, the Hierarchical Clustering Mechanism (HCM) was introduced. When HCM is used to find the SET of resources which the user is authorized to access, it tremendously reduces the redundancy in checking security rules compared to the classical methods (the Brute Force Approach and the Primitive Clustering Mechanism (PCM)). However, HCM demands a centralized authorization database where all the resources’ security policies have been kept in order to build its decision tree which is difficult to achieve in a heterogeneous environment like the grid. Moreover, HCM adds extra complexity when it is used in case of SINGLE resource authorization scenarios, which may happen very frequently in the grid. This paper tries to address these issues of HCM and comes up with an efficient solution.
Évolution au cours du temps d'un lixiviat traité par lagunage naturel et évaluation de l'efficacité de filtres en sable pour la réduction de sa charge organique et minérale. Cas de la décharge d'ordures ménagères d'Etueffont (France)

Dans la decharge d'ordures menageres d'Etueffont (Belfort, France) un traitement par lagunage naturel des lixiviats produits est effectue a l'aval de l'emissaire principal par l'intermediaire de quatre bassins places en serie. Deux filtres a sable ont ete installes dans la partie centrale et a l'amont du premier bassin, afin de reduire la charge organique et minerale de l'effluent. Un suivi analytique des parametres classiques physiques et chimiques (elements majeurs, metaux et composes organiques dont les AOX, les AGV et l'atrazine) a ete realise dans le lixiviat brut, a la sortie des filtres a sables et a la sortie de la station de traitement par lagunage. Les resultats mettent en evidence une legere variation de la composition physico-chimique du lixiviat, vraisemblablement attribuable a la maturation de la decharge et un abattement tres important des MES par les filtres a sable qui se repercute pour l'ensemble des parametres suivis. Le fonctionnement sur le plan physico-chimique du filtre a sable est detaille ainsi que l'efficacite du lagunage global sur les effluents issus de la decharge.
Algebraic Specification of Communication Protocols

Abstract : This report is concerned with specifying communication protocols and proving their behavior correct. Many different approaches have been taken for modeling communication protocols; the approach taken here is algebraic. Communication protocols are seen as complex data types and are defined using the algebraic method. The modeling techniques devised are applied to the specification and verification of a complex data transfer protocol. Properties proven include system invariants and those of an operational nature. These experiments have been carried out using the Affirm system for designing abstract data types algebraically and proving their properties.
C3I Kernel Selection Report.

Abstract : The main purpose of the benchmark suite is to provide an effective means to evaluate the use of high performance computing technologies for future C3I systems. This report summarizes the C3I kernels selected for inclusion in this benchmark set and the reasons for this inclusion. Each kernel is presented with an introduction and the associated parallelization issues.