Miracle-dz/UniFAR-FTUs huggingface dataset:
Comsol for Engineers

COMSOL Multiphysics software is one of the most valuable software modeling tools for engineers and scientists. This book is designed for engineers from the fields of mechanical, electrical, and civil disciplines, and introduces multiphysics modeling techniques and examples accompanied by practical applications using COMSOL 4.x. The book includes a companion CD-ROM with files of over 25 models, images, and code. The main objective is to introduce readers to use COMSOL as an engineering tool for modeling by solving examples that could become a guide for modeling similar or more complicated problems. The objective is to provide a collection of examples and modeling guidelines through which readers can build their own models.Readers are assumed to be familiar with the principles of numerical modeling and the finite element method (FEM). The book takes a flexible-level approach for presenting the materials along with using practical examples.The mathematical fundamentals, engineering principles, and design criteria are presented as integral parts of examples. At the end of each chapter are references that contain more in-depth physics, technical information, and data; these are referred to throughout the book and used in the examples.COMSOL for Engineers could be used to complement another text that provides background training in engineering computations and methods. Examples provided in this book should be considered as "lessons" for which background physics could be explained in more detail. FEATURESIncludes a companion CD-ROM with files of over 25 models, images,codeUses progressive approach in terms of examples and modelsBRIEF TABLE OF CONTENTS1: Introduction. 2: Finite Element Method (FEM). 3: COMSOL - A Modeling Tool For Engineers. 4:COMSOL Models for Physical Systems. Appendices. Index.ON THE CD-ROMExecutable copies of each model (over 25 models) and relatedanimationsImages from the book ( 4-color and B&W)
Design and practical usage of web biological databases for the annotation and classification of proteins

En l'anomenada societat de la informacio, les dades representen unes parts estructurals clau en la generacio del coneixement. De la mateixa manera, la Bioinformatica depen en darrer terme d'una adequada gestio i processament de les dades que s'originen de les analisis tant tradicionals com d'alt rendiment. Com a objectiu principal d'aquesta tesi, s'han compilat diferents aproximacions practiques per a la manipulacio de les dades de sequenciacio de proteines i les analisis resultants que s'hi apliquen. En tot cas, com a pas preliminar, eines i algorismes bioinformatics preexistents s'han adaptat abans al paradigma de la informacio actual, basicament centrat en el World Wide Web. Despres d'una pertinent adaptacio d'aquestes aplicacions (en aquest document: ProtLoc, TransMem, TranScout i Bypass), esdeve possible encarar el processament massiu de dades proteiques que s'han originat dels darrers projectes de sequenciacio de genomes. Els resultats d'aquestes analisis es fan disponibles per a la comunitat cientifica d'arreu del mon mitjancant bases de dades biologiques basades en el web, de ple acces i d'us amigable. Com exemples, es presenten dos casos: TrSDB, un compendi de factors de transcripcio coneguts i putatius de diferents organismes models, i ArchDB, una base de dades web estructural de llacos de proteines. Com a pas posterior, a partir del programa Bypass —una eina basada en logica difusa per a la reanotacio i avaluacio d'alineaments proteics obtinguts amb cerca per homologia— s'implementa un entorn complet d'anotacio i gestio de sequencies. Com a punt fort, el sistema tambe es suficientment flexible i modular per a permetre l'entrada de diferents tipus de dades (p. ex., Gene Ontology) o comunicar-se amb altres aplicacions ja existents i potencialment futures. De forma paral·lela, i aprofitant l'explosio de dades crues de sequenciacio i la curacio de les bases de dades, es presenta una caracteritzacio bioinformatica d'una nova familia de metal·locarboxipeptidases. Mitjancant aproximacions computacionals, va ser possible plantejar unes primeres hipotesis per a l'activitat enzimatica i la historia filogenetica d'aquest grup de proteines. Notablement, llur identificacio pot representar un enfocament esperancador per a tractar processos biologics com ara la malaria o desordres neuronals, on aquestes molecules s'hi troben implicades estretament.
Analyser la qualité de l'évaluation des risques : l'exemple des perturbateurs endocriniens

Laura Maxim , Sandrine Blanchemanche, Natalia Grabar et Jeroen Van Der Sluijs 1 Études interdisciplinaires des sciences et de la technologie, Institut des Sciences de la communication, UMS 3665, CNRS, université Paris-Sorbonne, UPMC, 75013 Paris, France 2 Sociologie, Économie publique, AgroParisTech, INRA, Université Paris-Saclay, 75231 Paris cedex 05, France 3 Traitement automatique des langues, CNRS, Université de Lille, UMR 8163 – Savoirs Textes Langage, BP 60149, 59653 Villeneuve d’Ascq cedex, France 4 Sciences de l’environnement, Centre for the Studies for the Sciences and the Humanities, University of Bergen, Bergen, Norway 5 Department of Chemistry, University of Bergen, Bergen, Norway 6 Copernicus Institute of Sustainable Development, Environmental Sciences, Utrecht University, Utrecht, The Netherlands
Modelling and simulation of activity

Introduction. - The Basal Ganglia (BG). - STN activity recorded in-vitro brain slices. - STN activity recorded in 'in-vitro' dissociated cell cultures. - STN cell models and simulation of neuronal networks. - Comparison of Part I and Part II. - Summary. - Appendix I. - Appendix II. - Appendix III. - Appendix IV. - Subject index.
The Talking Heads experiment

The Talking Heads Experiment, conducted in the years 1999-2001, was the first large-scale experiment in which open populations of situated embodied agents created for the first time ever a new shared vocabulary by playing language games about real world scenes in front of them. The agents could teleport to different physical sites in the world through the Internet. Sites, in Antwerp, Brussels, Paris, Tokyo, London, Cambridge and several other locations were linked into the network. Humans could interact with the robotic agents either on site or remotely through the Internet and thus influence the evolving ontologies and languages of the artificial agents. The present book describes in detail the motivation, the cognitive mechanisms used by the agents, the various installations of the Talking Heads, the experimental results that were obtained, and the interaction with humans. It also provides a perspective on what happened in the field after these initial groundbreaking experiments. The book is invaluable reading for anyone interested in the history of agent-based models of language evolution and the future of Artificial Intelligence.
Understanding User-Generated Content on Social Media

Nagarajan, Bala Meenakshi, Ph.D., Department of Computer Science and Engineering, Wright State University, 2010. Understanding User-generated Content on Social Media. Over the last few years, there has been a growing public and enterprise fascination with ‘social media’ and its role in modern society. At the heart of this fascination is the ability for users to participate, collaborate, consume, create and share content via a variety of platforms such as blogs, micro-blogs, email, instant messaging services, social network services, collaborative wikis, social bookmarking sites, and multimedia sharing sites. This dissertation is devoted to understanding informal user-generated textual content on social media platforms and using the results of the analysis to build Social Intelligence Applications. The body of research presented in this thesis focuses on understanding what a piece of usergenerated content is about via two sub-goals of Named Entity Recognition and Key Phrase Extraction on informal text. In light of the poor context and informal nature of content on social media platforms, we investigate the role of contextual information from documents, domain models and the social medium to supplement and improve the reliability and performance of existing text mining algorithms for Named Entity Recognition and Key Phrase Extraction. In all cases we find that using multiple contextual cues together lends to reliable inter-dependent decisions, better than using the cues in isolation and that such improvements are robust across domains and content of varying characteristics, from micro-blogs like Twitter, social networking forums such as those on MySpace and Facebook, and blogs on the Web. Finally, we showcase two deployed Social Intelligence applications that build over the results of Named Entity Recognition and Key Phrase Extraction algorithms to provide near real-time information about the pulse of an online populace. Specifically, we describe what it takes to build applications that wish to exploit the ‘wisdom of the crowds’ – highlighting challenges in data collection, processing informal English text, metadata extraction and presentation of the resulting information.
Rapporto sulla stima delle emissioni diffuse da edifici industriali mediante tecnica lidar elastica

Questo documento riporta la descrizione delle modalita di progettazione, acquisizione ed analisi dei dati da campagne di misura per la stima di emissioni diffuse effettuabili presso stabilimenti industriali con il sistema lidar (radar laser) sviluppato e testato da ENEA FSN-TECFIS-DIM. Le campagne devono essere progettate previo sopralluogo per individuare le postazioni piu opportune per le misurazioni, tenuto conto delle caratteristiche sia dello strumento che degli impianti da osservare. Verranno descritti la tecnica impiegata e gli algoritmi di inversione dei dati, assieme alla procedura di individuazione delle postazioni di misura. Occorre premettere che le misure lidar di particolato rappresentano stime che sono generalmente riconosciute attendibili entro un 50% di errore relativo. Possibili sorgenti di incertezza e metodi di mitigazione degli errori saranno discussi nel testo.
Reordering in statistical machine translation

Machine translation is a challenging task that its difficulties arise from several characteristics of natural language. The main focus of this work is on reordering as one of the major problems in MT and statistical MT, which is the method investigated in this research. The reordering problem in SMT originates from the fact that not all the words in a sentence can be consecutively translated. This means words must be skipped and be translated out of their order in the source sentence to produce a fluent and grammatically correct sentence in the target language. The main reason that reordering is needed is the fundamental word order differences between languages. Therefore, reordering becomes a more dominant issue, the more source and target languages are structurally different. The aim of this thesis is to study the reordering phenomenon by proposing new methods of dealing with reordering in SMT decoders and evaluating the effectiveness of the methods and the importance of reordering in the context of natural language processing tasks. In other words, we propose novel ways of performing the decoding to improve the reordering capabilities of the SMT decoder and in addition we explore the effect of improving the reordering on the quality of specific NLP tasks, namely named entity recognition and cross-lingual text association. Meanwhile, we go beyond reordering in text association and present a method to perform cross-lingual text fragment alignment, based on models of divergence from randomness. The main contribution of this thesis is a novel method named dynamic distortion, which is designed to improve the ability of the phrase-based decoder in performing reordering by adjusting the distortion parameter based on the translation context. The model employs a discriminative reordering model, which is combining several fea-
Atmospheric optical communication system using subcarrier PSK modulation

An atmospheric optical communication (AOC) system using subcarrier phase shift keying (PSK) is proposed, and its superiority to OOK in the presence of scintillation is discussed theoretically. An experimental AOC setup using a subcarrier modulated by 155.52 Mb/s phase differential shift keying (DPSK) at light wavelength /spl lambda/ = 0.83 /spl mu/m over an 1.8 km outdoor path is employed to show the performance. Theoretical and experimental results are compared under scintillation in clear weather. Good agreement is observed. BER in various kinds of weather is given. AOC using subcarrier M-ary PSK and multiple subcarriers is discussed. <<ETX>>
Privacy preserving data mining for numerical matrices, social networks, and big data

OF DISSERTATION PRIVACY PRESERVING DATA MINING FOR NUMERICAL MATRICES, SOCIAL NETWORKS, AND BIG DATA Motivated by increasing public awareness of possible abuse of confidential information, which is considered as a significant hindrance to the development of e-society, medical and financial markets, a privacy preserving data mining framework is presented so that data owners can carefully process data in order to preserve confidential information and guarantee information functionality within an acceptable boundary. First, among many privacy-preserving methodologies, as a group of popular techniques for achieving a balance between data utility and information privacy, a class of data perturbation methods add a noise signal, following a statistical distribution, to an original numerical matrix. With the help of analysis in eigenspace of perturbed data, the potential privacy vulnerability of a popular data perturbation is analyzed in the presence of very little information leakage in privacy-preserving databases. The vulnerability to very little data leakage is theoretically proved and experimentally illustrated. Second, in addition to numerical matrices, social networks have played a critical role in modern e-society. Security and privacy in social networks receive a lot of attention because of recent security scandals among some popular social network service providers. So, the need to protect confidential information from being disclosed motivates us to develop multiple privacy-preserving techniques for social networks. Affinities (or weights) attached to edges are private and can lead to personal security leakage. To protect privacy of social networks, several algorithms are proposed, including Gaussian perturbation, greedy algorithm, and probability random walking algorithm. They can quickly modify original data in a large-scale situation, to satisfy different privacy requirements. Third, the era of big data is approaching on the horizon in the industrial arena and academia, as the quantity of collected data is increasing in an exponential fashion. Three issues are studied in the age of big data with privacy preservation, obtaining a high confidence about accuracy of any specific differentially private queries, speedily and accurately updating a private summary of a binary stream with I/O-awareness, and launching a mutual private information retrieval for big data. All three issues are handled by two core backbones, differential privacy and the Chernoff Bound.
COMPUTER SYSTEM FOR ROUTINE QTL DETECTION AND GENETIC EVALUATION UNDER A MIXED INHERITANCE MODEL IN DAIRY CATTLE

SYSTEM COMPONENTS Administration of marker data. A part of the system is intended to manage continuously updated molecular data used in routine genotyping. An analysis of marker data comprises: identifying marker allele transmission errors, calculation of statistics characterising quality of particular markers, and reconstructing marker haplotypes. Data analysis. Traits currently screened for QTL comprise daughter yield deviations (DYDs) for lactation specific and for overall milk, fat, and protein yields, and somatic cell scores. The computational steps involved are: the calculation of QTL probabilities, simultaneous QTL detection and evaluation of breeding values based on a series of univariate mixed inheritance animal models, evaluation of selected multivariate models chosen based on univariate results, selection of those QTL, which inheritance is to be followed in bulls. Interchange and update of information. An important function of the system is to control flow of information between the national databases for dairy cattle and between end-users. The national pedigree-database and phenotypic-database, which also include official estimates of breeding values, provide information for QTL analysis. The system provides the front-end for automated input of marker data by genotyping labs, while errors detected in transmission of marker alleles are either resolved back at the lab or influence pedigree-database. On output regularly updated appropriate pieces of information are presented to end-users.
Control design for linear systems with saturating actuators and /spl Lscr//sub 2/-bounded disturbances

This paper addresses the problem of synthesis of state feedback control laws for systems subject to /spl Lscr//sub 2/-bounded disturbances in presence of saturating actuators. Conditions that allow to guarantee both the internal and external stability of the closed-loop system are proposed. They are formulated from the use of the Finsler's lemma and a generalized sector non-linearity description. This approach allows to introduce new variables (multipliers) in the problem which increase the degrees of freedom in the synthesis problem. Based on the stability conditions, a multiobjective problem is addressed: the synthesis of a state feedback gain that simultaneously maximizes the magnitude of the admissible /spl Lscr//sub 2/-disturbance and the size of the domain of stability of the closed-loop system.
Studies in Information Systems. Procedures for Analysis of Information System Effectiveness. A Working Manual

Abstract : The manual is a working document to assist in evaluating a variety of information processing activities. A generalized procedure is outlined to assess the capability of an information system to meet functional, user-oriented requirements. A composite overview is proposed which will be the basis of a systematic approach to information system evaluation. Stress is placed upon identification of tangible benefits and measures of effectiveness. Refinement and standardization of the approach are anticipated on the basis of experience in applying its phases to systems operating under differing circumstances.
Analysis and Exploitation of Automatically Generated Scene Structure from Aerial Imagery

The recent advancements made in the field of computer vision, along with the ever increasing rate of computational power has opened up opportunities in the field of automated photogrammetry. Many researchers have focused on using these powerful computer vision algorithms to extract three-dimensional point clouds of scenes from multi-view imagery, with the ultimate goal of creating a photo-realistic scene model. However, geographically accurate three-dimensional scene models have the potential to be exploited for much more than just visualization. This work looks at utilizing automatically generated scene structure from near-nadir aerial imagery to identify and classify objects within the structure, through the analysis of spatial-spectral information. The limitation to this type of imagery is imposed due to the common availability of this type of aerial imagery. Popular third-party computer-vision algorithms are used to generate the scene structure. A voxelbased approach for surface estimation is developed using Manhattan-world assumptions. A surface estimation confidence metric is also presented. This approach provides the basis for further analysis of surface materials, incorporating spectral information. Two cases of spectral analysis are examined: when additional hyperspectral imagery of the reconstructed scene is available, and when only R,G,B spectral information can be obtained. A method for registering the surface estimation to hyperspectral imagery, through orthorectification, is developed. Atmospherically corrected hyperspectral imagery is used to assign reflectance values to estimated surface facets for physical simulation with DIRSIG. A
The Conversion method from ID-based Encryption to ID-based Dynamic Threshold Encryption

Dynamic threshold public-key encryption provides dynamic setting of the group of all users, receivers and the threshold value. Over recent years, there are many studies on the construction of scheme, called ID-based dynamic threshold encryption, which combines the ID-based encryption with dynamic threshold encryption. In this paper, we analyze the ID-based dynamic threshold encryption proposed by Xing and Xu in 2011, and show that their scheme has a structural problem. We propose a conversion method from ID-based encryption which uses the bilinear map to ID-based dynamic threshold encryption. Additionally, we prove this converted scheme has CPA security under the full model.
A coherent multiple frequency estimator and its applications in synthesis-analysis audio watermarking

Summary form only given. The paper extends our previous work on single parameter watermarking to the multiple parameter case. Watermarks are embedded in multiple sinusoidal tracks via frequency quantization index modulation (F-QIM), and extracted by a coherent multiple frequency estimator using Newton's method. Experiments are conducted subject to MP3 attacks and, in an 8-track sinusoidal synthesis-analysis setup, above bits/sec of data hiding is consistently achieved with error correction. Furthermore, the frequency estimator's performance is compared against the fundamental limit of the inverse Fisher information.
Research on the growing process of short message networks

We investigate the growing process and topological features of the short message networks (SMN). Simulations show that the networks' degree distribution，average degree and the correlation between the node's degree and its time in the network are different from those of the former networks models. With due consideration of some of the characteristics of the SMN, we suggest a new type of network growing protocol,namely the local-preference connecting protocol. The numerical results show that the networks generated from our model are more representative in simulating real networks represented by SMN when compared with other network models.
Simulation and Evaluation of Computation Offloading Algorithms in Battlefield Scenarios

Abstract : Due to their small size and ever-increasing computing capability, mobile devices, such as smart phones, are ideal tools for computation in the battlefield. However, there are some mission-critical applications that cannot be completed in real-time on these devices. Some of these applications can meet their deadlines through computation offloading: sending computationally expensive operations to high-performance computers (HPCs). However, in battlefields it may not be possible to access traditional offloading targets, such as cloud computing services. In this project we examine computation offloading on mobile ad-hoc networks (MANETs) using vehicle-mounted HPCs as offload targets. We use the network simulator ns-3 to model computation offloading in the battlefield. We implemented a suite of extensible ns-3 models, which allow for a wide variety of experiments with MANETs. Using these models, we study a number of aspects of computation offloading including: HPC placement, client offloading strategies, effects of HPC mobility, and variations in network topology. In this report, we describe the overall architecture of the models and provide experimental results on the performance gained by computation offloading when a number of parameters are varied. Our initial results indicate that offloading to mobile HPCs increases the utility of mobile devices as computation platforms in the battlefield.