Miracle-dz/UniFAR-FTUs huggingface dataset:
InLéctor: enhanced bilingual e-books for language learning

The InLector project aims to promote reading in original language, offering an interactive scenario which facilitates foreign language teaching and selflearning, as well as the study of literature. In order to achieve this aim, the project develops computational techniques which provide automatically generation of bilingual e-books, incorporating dictionaries, ontologies and audios. Bilingual reading offers the option of moving from the original text to the translated one with a single click. The audio support is based on the human reading of the work in its original language. Moreover, it is planned to incorporate an interactive dictionary service which will show in advance the most difficult words in the text according to the language level of the user. Augmented information will also provide links to encyclopedic entries, images and audio directly related to the fragment of the text being read. The project ensures the creation and distribution of these parallel books in different output formats (html, epub and mobi), which are compatible with the most common tablets and e-books nowadays. The literary works and their translations are published in the public domain. The developed programs are based on free software and will also be published under a free license.
Headway distribution of heterogeneous traffic on urban arterials

This paper describes an attempt made to study the time-headway distribution of urban heterogeneous traffic over a wide range offlow levels. An appropriate methodology for the collection and extraction of headway data has been suggested. The importance of a systematic procedure for grouping of headway data through appropriate choice of class interval has been discussed. The methodology for choice of best fitting statistical distribution to the observed headway data has also been described. The result of the study has shown that, the headways of urban mixed-traffic dominated by smaller vehicles like motorised two-wheelers can be modelled using negative exponential distribution over a wide range of traffic flow levels.
Mixed stock analysis in R: getting started with the mixstock package

The mixstock package is a set of routines written in the R language R 2 Development Core Team (2005) for doing mixed stock analysis using data 3 on markers gathered from source populations and from one or more mixed 4 populations. The package was developed for analyzing mitochondrial DNA 5 (mtDNA) markers from sea turtle populations, but should be applicable 6 to any case with discrete sources, discrete mixed populations, and discrete 7 markers. (However, I do refer to sources as “rookeries” and markers as 8 “haplotypes” throughout this document, and you will see other echoes of its 9 origins, e.g. the number of markers is internally stored as variable H and 10 the number of sources is stored as R.) The package is intended to be self11 contained, but some familiarity with R or S-PLUS will definitely be helpful. 12 (Some familiarity with your computer’s operating system, which is probably 13 Microsoft Windows, is also assumed.) The statistical methods implemented 14 in the package are described in Bolker et al. (2003) and Pella and Masuda 15 (2001). 16 This package is in the public domain (GNU General Public 17 License), is©2008 Ben Bolker and Toshinori Okuyama, and comes 18 with NO WARRANTY. Please suggest improvements to me (Ben 19 Bolker) at bolker@mcmaster.ca. 20 If you are feeling impatient and confident, turn to “Quick Start” (sec21 tion 6). 22
BeesyCluster as Front-End for High Performance Computing Services

The paper presents the BeesyCluster system as a middleware allowing invocation of services on high performance computing resources within the NIWA Centre of Competence project. Access is possible through both WWW and SOAP Web Service interfaces. The former allows non-experienced users to invoke both simple and complex services exposed through easyto-use servlets. The latter is meant for integration of external applications with services made available from clusters or servers. Details of services such as APIs used for development as MPI, OpenMP, OpenCL as well as queuing systems are hidden from the user. The paper describes both the WWW and Web Service interfaces extended for use with files of large sizes. Mechanisms for selection of devices for execution of services are described along with experiments including remote invocations.
Design of M68HC08 Family PDIP MCU Common Programmer

Through analyzing and comparing the difference of M68HC08 family MCU to enter monitor mode,this paper introduces the hardware and software design method of common programmer based on MC68HC908JB8.The way to add new adapter is given.This programmer is composed of the baseboard and the adapter,it is cheap,convenient,easy expansion.It has a certain practical value.
Enhancing the Accuracy of Recommender System Using Graph Databases

In recent years size of the data available to user over online media has increased exponentially. Due to this large amount of data, people face problem in viewing all available data due to lack of time. To overcome such type of problem, the recommender system plays an important role. In recent years, the recommender systems are most popular tool and have been used in a many types of applications such as facebook, twitter, youtube.com, Amazon.com etc. Recommender systems broadly fall into two groups: Collaborative and content based recommender systems. The collaborative-filtering methods generate the recommendation to user on the basis of the nearest user which is most similar to them. User-based Collaborative-filtering (CF) which uses the matrix to store the ratings of the user is the most frequently used recommender technique, widely used because of its simplicity and efficient performance. Although it is extensively used, one of its major problems is that its performance decreases when the user-item matrix becomes sparse. One of the proposed solutions is to the usage of combination of graph data base and Locality Sensitive Hashing (LSH). Graph database provide the flexibility to developer to design database without performing any normalization and LSH provides a faster method to find the nearest neighbor for the recommendation to user. The proposed system concludes with comparison of traditional approach with the proposed approach.
Niche Theory And Application

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“I saw the light”: Former Protestant believer testimonials in the Soviet Union, 1957-1987

ResumeCet article etudie les recits d’anciens croyants publies depuis les annees Hruscev jusqu’a la periode de Gorbacev. Il s’interesse en particulier aux anciens protestants, que la propagande atheiste de l’epoque a traites de facon disproportionnee. L’article deconstruit ces narrations dans lesquelles les anciens croyants decrivent leur passage de la religion a l’atheisme et au communisme. Ces recits sont davantage consideres comme l’un des aspects d’une tradition sovietique plus large selon laquelle la construction de l’identite et la trajectoire de vie personnelle vont de pair avec l’image idealisee du nouvel homme sovietique. Ils sont egalement le reflet d’une insistance renouvelee, de la part du pouvoir poststalinien, sur la necessite de creer une societe sans dieu, liberee de tout vestige de croyance religieuse. Pour l’Etat sovietique, les rapports publies de ces anciens croyants prouvaient que la societe evoluait veritablement dans cette direction et, par la meme, constituaient une incitation, pour les autres croyants, a suivre ces exemples et a embrasser l’atheisme. Enfin, cet article evalue dans quelle mesure ces temoignages ont reussi, ou echoue, dans leur mission d’eradication de la foi.
Design of an Authentic E-Learning Environment

The increasing necessity of a lifelong learning attitude has its influence on the ageing population in Western societies. Employees nowadays cannot rely on their skills once learned in school. Most, also older, employees have to keep up by learning new insights, new skills, and new knowledge. A lot of money is invested in training and further education. New technology can play an important role here. This chapter will give an insight into the development of an authentic multimedia learning environment to support lifelong learners. More specifically, it has been developed in order to improve learning materials in terms of giving the right amount of scaffolding at the time when it is needed to increase the motivation and the performance of the (older) learner. A design that adapts cognitive load theory to minimise cognitive overload was embedded in an authentic context that, as a result, provided a fruitful basis for authentic and simulated learning environments addressing both younger and older adults.
Towards 3D object recognition with contractive autoencoders

Nowadays, object recognition in 3D scenes has become an emerging challenge with various applications. However, an object can’t be represented well by artificial features derived only from 2D images or depth images separately, and supervised learning method usually requires lots of manually labeled data. To address those limitations, we propose a cross-modality deep learning framework based on contractive autoencoders for 3D scenes object recognition. In particular, we use contractive autoencoding to learn feature representations from 2D and depth images at the same time in an unsupervised way, it is possible to capture their joint information to reinforce detector training. Experiments on 3D image dataset demonstrate the effectiveness of the proposed method for 3D scene object recognition.
Understanding electrical trees in solids: from experiment to theory

The author reviews how far we have advanced in being able to relate experimental observation to physical theories. He concentrates on the inception process and the first stage of propagation because these are the areas in which most progress has been made, although even here there are unresolved problems. It is convenient, as well as conventional, to start at the beginning with tree inception. In this way the various mechanisms whereby energy can be transferred to the solid polymer to create damaged regions, can be introduced and discussed in the light of experimental data. For the propagation of the tree structures, this prior discussion is used to provide the background to the mechanistic features involved, so that we can concentrate upon the fascinating topic as to why tree structures have the form that they do.
Advanced Analytics with Spark: Patterns for Learning from Data at Scale

In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques-classification, collaborative filtering, and anomaly detection among others-to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you'll find these patterns useful for working on your own data applications.
A perceptually optimized mapping technique for display images

Liquid crystal displays (LCDs) are often viewed in the energy‐saving mode or under high ambient illumination. However, both these conditions compress the tonal dynamic range of the display device, resulting in undesirable visual perception effects. In this paper, we propose a local algorithm for improving the display image quality under either of these conditions. The proposed algorithm is based on a tone mapping technique, and it reproduces the image appearance to almost its original quality with a lower dynamic range. We also develop a more accurate definition of the image distortion, which takes into account the difference in pixel values to reduce the distortion significantly. By minimizing the differences in contrast and pixel intensity between the input and output images, the algorithm preserves the contrast while simultaneously providing brightness compensation. Simulation results show that the proposed algorithm can effectively maintain image quality while enabling power savings of 30%–50%.
Enabling suggestions in tabular data cleaning and RDF mapping validation

Linked open data provides a powerful way to publish data on the Web. However, most publishers still choose to publish their data in tabular formats. Whereas tools for transforming tabular data to linked data are useful, they are still immature and do not provide enough support to address this issue. Firstly, the process of tabular data cleaning is complex and involves using a wide variety of operations on tuples. Nevertheless, there are a number of common operations that users tend to need in certain situations, but that information is not taken advantage of. Furthermore, the process of transforming data to RDF is not trivial in itself – it involves RDF mapping, which requires a deep knowledge and prior research of relevant ontologies. However, few tools currently provide functions to facilitate RDF mapping by providing relevant information for ontologies, making it an intricate process. Even when data are successfully mapped, due to the process being largely manual, and, thus, error-prone, there are very few facilities for validating the produced mappings. This thesis aims to address the aforementioned issues by identifying relevant algorithms, tools and methodologies, and applying them in the context of linked data transformation. Firstly, we propose a methodology for providing suggestions for data cleaning operations based on measurements of their use in given contexts. Secondly, we apply an existing algorithm for analysing the content of a table for suggesting appropriate RDF annotations. Furthermore, we describe facilities to help effectively manage RDF ontologies and, based on the constraints described within the ontologies, also validate RDF mappings. As a proof-of-concept, this thesis provides a working prototype of the aforementioned functionalities, organised as a web service. The prototype has been partially integrated in the live version of the DataGraft platform.
KJ82 Integrated Supervision System Based on Industrial Ethernet in Coal Mine

The network architecture of KJ82 integrated supervision system in coal mine is built upon redundancy ring fiber industrial Ethernet andfield bus which has the ability of multi-master transport. It supports networked control and hard real-time priority by which exceptional linkagecontrol of integrated supervision system can be achieved. Traditional network protocols are improved to satisfy real-time data processing andassemble various subsystems. Anti-explosion switch of KJJ23 and safety substation of KJF36 are implemented and used in mining scene.Application and test show response speed, integrating ability, reliability and compatibility of the supervision system are enhanced effectively.
Approach Based on Wavelet Analysis for Detecting and Amending Anomalous Samples in Data Set

Appropriate data preprocessing is the precondition to perform data mining or system modeling based on data set. It is an important to eliminate or amend the anomalous samples in data set which have been polluted. When the relationship among the samples' attributes is unknown, it's difficult to detect the anomalous samples. In this paper, an approach based on wavelet analysis for detecting and amending anomalous samples is proposed, which is able to detect and amend anomalous samples accurately because it takes full advantage of wavelet analysis' character of multiple scale. To realize the rapid numeric computation of wavelet translation for a discrete sequence, a modificatory algorithm based on Newton-Cores formula is proposed. The experiments show that the approach is accurate and practical.
A lower limb non-anthropomorphic wearable robot

This paper describes a novel wearable robot intended to assist hip and knee flexion/extension through series elastic actuators. A non-anthropomorphic design was pursued in order to improve ergonomics, while optimizing dynamical properties through a smart distribution of swinging masses. Once the anthropomorphism constraint is relaxed, the number of possible architectures becomes very high, and a methodology must be defined to point out the best options. To this purpose, a design methodology is also presented, which includes a novel approach to kinematic synthesis, topology selection and morphological optimization. The advantages offered by the novel architecture are demonstrated both theoretically and experimentally. In particular, results show a low reflected inertia on the user body, a high backdrivability and an intrinsic tolerance to wearing inaccuracies. Such advantages make the proposed robot a promising platform for the development of assistive and rehabilitation systems.
Optical Characterization Of Solids

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Security Overlay for RMI

This thesis presents a popular distributed object architecture, Remote Method Invocation (RMI). As RMI works on a Java framework, it provides the same features Java provides. Its portability, ability to transport objects as a whole, and power to connect to existing as well as legacy systems makes a strong choice amongst other competing technologies. Needless to say, the transport of objects across systems brings along with it the necessity for a strong security framework.
High-precision LED driving system based on LLC resonant converter

A novel high-precision LED driving system based on LLC resonant converter is presented in this paper. Dual control loops are embedded in this system. One is used as the main loop of the whole system, which can regulate the output signal, and realize analog dimming. The other loop is an assistant loop, which is used to achieve high-precision PWM dimming. Analog dimming loop achieves constant current through the error amplifier (EA) and the voltage-controlled oscillator (VCO). Intelligent duty-cycle builder (IDCB) is realized with the external PWM signal and the difference between the actual output current and the pre-set current. The actual PWM control signal in the system can be dynamically adjusted by the IDCB, which can greatly improve the accuracy of PWM dimming. Besides, the transformer-isolated driver is adopted in this system to reduce the operating voltage of the control chip. The proposed LED driving system has been validated with 0. 35μm BCD technology. The accuracy of PWM dimming can be improved by 17% with the assistant loop and reaches up to 95%. The current consumption of the LLC resonant controller IC is 5mA for a 100 kHz operation frequency using a 400V supply voltage. In addition, the power switching MOSFETs can achieve zero-voltage switching (ZVS) and the rectifier diodes can achieve zero-current switching (ZCS).
The Hundred Days

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An Information Flow Model for Conflict and Fission in Small Groups

Data from a voluntary association are used to construct a new formal model for a traditional anthropological problem, fission in small groups. The process leading to fission is viewed as an unequal flow of sentiments and information across the ties in a social network. This flow is unequal because it is uniquely constrained by the contextual range and sensitivity of each relationship in the network. The subsequent differential sharing of sentiments leads to the formation of subgroups with more internal stability than the group as a whole, and results in fission. The Ford-Fulkerson labeling algorithm allows an accurate prediction of membership in the subgroups and of the locus of the fission to be made from measurements of the potential for information flow across each edge in the network. Methods for measurement of potential information flow are discussed, and it is shown that all appropriate techniques will generate the same predictions.
Using Object Matching And Materialization To Integrate Heterogeneous Databases

This chapter addresses the problem of object matching, that is, determining when object representations (e.g., OIDs) in different databases correspond to the same object-in-the-world. Traditional approaches to data integration based on query pre-processing and query shipping typically use universal keys to perform object matching, and cannot efficiently support more intricate object matching criteria. We present a framework for data integration that is based on partial or full materialization of integrated views, that can efficiently handle very intricate object matching criteria, e.g., involving boolean conditions and user-defined heuristics. Materialized data is maintained using techniques generalized from active databases. To establish a context for our research, this chapter presents a taxonomy of the solution space for supporting and maintaining integrated views. The chapter also describes a prototype that we are implementing for data integration, that supports intricate object matching, and incremental maintenance of materialized information.
Restricted Legal Dictionary generation for Legal Domain Specific Mining

The Indian legal domain maintains largest heterogeneous multi domain based text corpora. In order to document specific search domain specific dictionaries are widely acceptable compared to whole legal dictionary. Many domain specific dictionary extractions proposed by various authors for business and scientific domains. In this paper we proposed a two stage domain specific dictionary for legal domain. The approach helps to construct Restricted Legal Dictionary which is domain specific in nature. The dictionary constructed supports text mining mechanisms over specific crime (dowry) based legal documents and improves the BoW construction with higher domain specific terminology. The Restricted Legal Dictionary constructed in this paper improves the efficiency of similarity measures during document comparison techniques