Miracle-dz/UniFAR-FTUs huggingface dataset:
Age of onset, socio-affect and cross-linguistic influence: a long-term classroom study

EnglishIn this longitudinal study, undertaken in Switzerland between 2008 and 2015, we home in on the interaction of starting age for English with the role of knowledge of other languages (German and French) in an array of oral and written tasks. Using longitudinal data from the same student cohort (200 learners) over a period of five years has made it possible to examine in real time and in a thorough and detailed manner (1) the impact of onset variables on the amount of cross-linguistic influence over the course of secondary school as well as on the type of transfer material, (2) transfer effects in areas of language knowledge and acquisition where transfer has previously been claimed not to occur, or to be relatively rare (e.g. inflectional morpheme transfer from the native and the additional foreign language), and (3) the sources of crosslinguistic influences, such as socio-affective factors. The results highlight the effects of target language proficiency, metalinguistic awareness and contextual factors (e.g. class effects, teaching practices and class size). DeutschIn dieser Langzeitstudie, die zwischen 2008 und 2015 in der Schweiz durchgefuhrt wurde, konzentrieren wir uns auf die Interaktion von Alter zu Lernbeginn der Fremdsprache Englisch und anderen Sprachkenntnissen (Deutsch und Franzosisch) in einer Reihe von mundlichen und schriftlichen Tests. Anhand von erhobenen Langzeitergebnissen mit einer Gruppe von 200 Lernenden in einem Zeitraum von funf Jahren konnten einerseits die Auswirkungen eines fruhen Lernbeginns auf die Quantitat und Qualitat von Spracheneinflussen und Transfer (inklusive Transferwirkungen in Bereichen von Sprachgebrauch und -erwerb, in denen bisher wenig bis gar kein Transfer dokumentiert wurde) und andererseits der Ursprung von Spracheinflussen (z.B. sozio-emotionale Faktoren) detailliert beobachtet und analysiert werden. Die Resultate beleuchten die Einflussfunktion des Leistungsstandes in der Zielsprache, der metalinguistischen Bewusstheit und von kontextuellen Aspekten, wie z.B. Klassengrosse und padagogische Praxis).
PROGRAMA DE PÓS-GRADUAÇÃO EM SISTEMAS E PROCESSOS INDUSTRIAIS - MESTRADO ÁREA DE CONCENTRAÇÃO EM CONTROLE E OTIMIZAÇÃO DE PROCESSOS INDUSTRIAIS

This dissertation presents a recognition method of pedestrian crossing, coupled with the necessary theoretical bases and concepts required to develop a computer vision system to recognize patterns and identify real-word objects. Functions of the OpenCV (Intel Open Source Computer Vision Library) image-processing library are used to develop this system, which was designed to run on a DARwIn-OP (Dynamic Anthropomorphic Robot with Intelligence Open Platform) humanoid robot. Tests were performed in a real traffic environment, in different conditions of visibility and brightness, for system evaluation and validation. Results show how efficient OpenCV functions are in this kind of system, which requires a fast response time on hardware with reduced capabilities, especially memory and processing power.
Software manual for PAUPRat: A tool to implement Parsimony Ratchet searches using PAUP*

PAUPRat is a program to generate a text file that contains commands which, when read by PAUP* (with an open and executed data file), will implement the Parsimony Ratchet of Kevin Nixon (1999b). The Parsimony Ratchet is a search strategy that is surprisingly efficient at finding shortest trees for data sets too large for traditional heuristic search methods. This manual provides a basic introduction to the Parsimony Ratchet and information on how to use PAUPRat. PAUPRat comes in three flavors: Mac, PC and Linux (Intel executable)
Locomotion control of seven-link robot with CPG-ZMP

For the Central Pattern Generation (CPG) method, it is difficult to coordinate each Degree of Freedom (DoF) of a robot by modulating the parameters of neutral network to realize stable walking. The Zero Moment Point (ZMP) method is popular in the stability control of biped robot walking. However, the reference trajectories have low energy efficiency, lack naturalness and require significant offline calculation. This paper designs a method for biped walking using a hybrid CPG-ZMP control algorithm, which can realize a stable walking pattern by combing the ZMP information with rhythmic motion control. Also, the hybrid CPG-ZMP control algorithm is elaborated systematically from the aspects of CPG model, CPG network construction and feedback for a planar seven-link robot. The simulation results show that the hybrid CPG-ZMP algorithm enhances the stability of biped robot, and the control system can generate adaptive walking patterns through the interaction among the robot, CPG and environment.
L'étiquetage grammatical de l'amazighe en utilisant les propriétés n-grammes et un prétraitement de segmentation

The aim of this paper is to present the first amazigh POS tagger. Very few linguistic resources have been developed so far for amazigh and we believe that the development of a POS tagger tool is the first step needed for automatic text processing. In order to achieve this endeavor, we have trained two sequence classification models using Support Vector Machines (SVMs) and Conditional Random Fields (CRFs) after using a tokenization step. We have used the 10fold technique to evaluate our approach. Results show that the performance of SVMs and CRFs are very comparable. Across the board, SVMs outperformed CRFs on the fold level (92.58% vs. 92.14%) and CRFs outperformed SVMs on the 10 folds average level (89.48% vs. 89.29%). These results are very promising considering that we have used a corpus of only ~20k tokens. Mots-cles etiquetage grammatical automatique, langue amazighe, TAL, apprentissage supervise, segmentation
Moriarty: Improving ‘Time To Market’ in big data and Artificial intelligence applications

The objective of this paper is to present the Moriarty framework and show one use case of the recommendation of entertainment events. Moriarty is a tool that can generate Big Data near real-time analytics solutions (Streaming Analytics). This new tool makes possible the collaboration among the data scientist and the software engineer. Through Moriarty, they join forces for the rapid generation of new software solutions. The data scientist works with algorithms and data transformations using a visual interface, while the software engineer works with the idea of services to be invoked. The underlying idea is that a user can build projects of Artificial Intelligence and Data Analytics without having to make any line of code. The main power of the tool is to reduce the ‘time to market’ in an application which embeds complex algorithms of Artificial Intelligence. It is based on different Artificial Intelligence algorithms (like Deep Learning, Natural Language Processing and Semantic Web) and Big Datamodules (Spark as a distributed data engine and access to NoSQL databases). Moriarty is divided into several layers; its core is a BPMN engine, which executes the processing and defines data analytics process, called workflows. Each workflow is defined by the standard BPMN model and is linked to a set of reusable functions or Artificial Intelligence algorithms written following a service-oriented architecture. An example of service presented is a recommendation application of restaurants, concerts, entertainment and events in general, where information is collected from social networks and websites, is processed by Natural Language Processingalgorithms and finally introduced into a graph database.
A Shared Future of Mankind: a New Concept and its Paramount Pedagogical Importance

The recent Congress of the Chinese Communist Party, held in Beijing, marked a very important evolution in the political international thinking, enucleating the concept of the “shared future of mankind”. This concept presents a series of very important implications concerning various issues and themes confronting nowadays the international community. Topics such as the preservation of international peace and security, the solution of urgent environmental problems, like climate change, the need for a sustainable growth of world economy, and others. The attitude of the Popular Republic of China is very constructive and reflects the aforesaid new concept, paving the way to unprecedented developments of international cooperation in different areas. The present essay illustrates the main features of this concept and highlights its paramount importance in the framework of the current international situation. It also evidences the pedagogical implications of the concept, given the growing interconnectedness among different national society and the need to create a common conscience of humankind especially of the younger generations. Keywords—gobalization, humankind, peace, China
Integrating performance analysis in model driven software product line engineering

A Software Product Line (SPL) is a set of similar software systems that share a common set of features satisfying a particular domain, and are built from a shared set of software assets using a common means of production. This research proposes to integrate performance analysis in the early phases of the model-driven development process of SPL. We start by adding generic performance annotations to the UML model representing the set of core reusable SPL assets using the MARTE Profile adopted by OMG. A model transformation realized in Atlas Transformation Language (ATL), derives the UML model of a specific product with concrete performance annotations from the SPL model, which is further transformed into a performance model by using a previously developed transformation called PUMA. The automatic derivation of a specific product model based on a given feature configuration is enabled through the mapping between features from the feature model and their realizations in the design model. An efficient mapping technique is proposed that aims to minimize the amount of explicit feature annotations in the UML model of SPL. Implicit feature mapping is inferred during product derivation from the relationships between annotated and non-annotated model elements as defined in the UML metamodel. The mapping technique is used to derive automatically a given product model. Performance is a run-time property of the deployed system and depends on other factors that are external to the design model, characterizing the underlying platforms and run-time environment. Performance completions provide a means to extend the modeling constructs of a system by including the influence of these factors. The variability space of the performance completions is covered and represented through Performance Completion-feature model (PC-feature model). Dealing manually with a large number of performance parameters annotating a UML+MARTE product model is an error-prone process. A model-driven user-friendly technique is proposed to automatically collect all generic performance parameters that need binding from the generated product model and present them to developers in a spreadsheet format, together with context and guiding information where each PC-feature is mapped to certain MARTE annotations corresponding to UML model elements in the product model.
Real-time running event detection via a community patrol robot

Security surveillance is an important application for patrol robots. In this article, a real-time running event detection method is proposed for the community patrol robot. Although sliding window-based approaches have been quite successful in detecting objects in images, directly extending them to real-time object detection in video is not simple. This is due to the huge samples and diversity of object appearances with multivisual view and scale. To address these limitations, first, a simple and effective spatial–temporal filtering-based approach is proposed to obtain moving object proposals in each frame; then, two-stream convolutional networks fusion architecture is introduced to best take advantage of the spatial–temporal information from the proposal. The algorithm is applied on PatrolBot in community environments and runs at 15 fps on a consumer laptop. Two benchmark data sets (the Kungliga Tekniska Högskolan [KTH] data set and Nanyang Technological University [NTU] running data set) were also used to compare results with previous works. Experimental results show higher accuracy and lower detection error rate in the proposed method.
Task analysis as 'catalytic tool' for feedback and teacher learning : working with teachers on curriculum materials to develop mathemathecal knowledge in/for teaching.

Working with mathematics curriculum materials to create learning opportunities for pupils, and at the same time to develop mathematical knowledge for teaching is an important part of the work of teaching. In this study I investigate the role of curriculum materials, more precisely a task analysis schedule, as catalyst for teacher learning. I explore the different forms of feedback resulting from developing and working with a "tool" designed to analyse mathematical tasks/curriculum materials for instruction. The results are based on the work with two lower secondary school teachers in England, John and Paul, as they work together, over the period of 9 months, in a group of teachers and with a university academic, on the analysis, development and teaching of mathematics curriculum materials. It is argued that the task analysis "tool" develops, to become a "catalytic tool" to provide feedback for teacher learning. In the process it affords feedback loops and changes its character, from "tool" as artefact to "epistemic object" at the interface between task design and enactment. The results provide deeper insights into the processes of teacher learning with the help of analytic tools and the feedback these may afford.
The Practice of Use and Development of Boarder Situation Potential (Based on The Materials of the Amur Region)

The article is devoted to the actual problem of regional development – the existing practice and promising directions of using the potential of the border situation for the socioeconomic development of the region. The author’s position is justified basing on the theoretical analysis of existing research approaches to boarder potential. In the study the current state and transformations in the use and development of border potential in terms of development of Russian-Chinese border cooperation were estimated. It is concluded that the changes under the general foreign economy conditions of cooperation and transformation of border potential provide a significant increase in regional competitive advantages. It causes the necessity to correct strategic plans, so a special importance appears - the use of the new possibilities to create international transport corridor and increase export capacity. It is revealed that the low attractiveness of the region as a place of permanent residence remains. The outflow of population is largely determined by the negative trends in the system of settlement of the region, the increase in the number of small villages and the preservation of the border zone. The paper presents the results of calculations of costs and economic effect of the use of various options for the organization of resettlement of the population in large rural settlements of the region.
Human-computer cryptography: an attempt

Can you securely prove your identity to a host computer by using no dedicated software at your terminal and no dedicated token at your hands ? Conventional password checking schemes don't need 8uch a software and hardware but have a disadvantage that an attacker who has correctly observed an input password by peeping or wiretapping can perfectly impersonate the corresponding user. Conventional dynamic (one-time) password schemes or zero-knowledge identification schemes can be securely implemented but require special software or hardwar(~ or memorandums. This paper develops human-friendly identification schemes such that a human prover knowing a secret key in her or his brain is asked a visual question by a machine verifier, who then checks if an answer sent from the prover matches the question with respect to the key. The novelty of these schemes lies in their ways of displaying questions. This paper also examines an application of the human identification schemes to humancomputer cryptographic communication protocols. Keywordt~: authentication, human-computer interaction, passwords, information security.
The Gestural Control of Audio Processing

Gesture enabled devices have become so ubiquitous in recent years that commands such as ‘pinch to zoom-in on an image’ are part of most people’s gestural vocabulary. Despite this, gestural interfaces have been used sparingly within the audio industry. The aim of this research project is to evaluate the effectiveness of a gestural interface for the control of audio processing. In particular, the ability of a gestural system to streamline workflow and rationalise the number of control parameters, thus reducing the complexity of Human Computer Interaction (HCI). A literature review of gestural technology explores the ways in which it can improve HCI, before focussing on areas of implementation in audio systems. Case studies of previous research projects were conducted to evaluate the benefits and pitfalls of gestural control over audio. The findings from these studies concluded that the scope of this project should be limited to two-dimensional gestural control. An elicitation of gestural preferences was performed to identify expert-user’s gestural associations. This data was used to compile a taxonomy of gestures and their most widely-intuitive parameter mappings. A novel interface was then produced using a popular tablet-computer. This facilitated the control of equalisation, compression and gating. Objective testing determined the performance of the gestural interface in comparison to traditional WIMP (Windows, Icons, Menus, Pointer) techniques, thus producing a benchmark for the system under test. Further testing is carried out to observe the effects of graphic user interfaces (GUIs) in a gestural system, in particular the suitability of skeuomorphic (knobs and faders) designs in modern DAWs (Digital Audio Workstations). A novel visualisation method, deemed more suitable for gestural interaction, is proposed and tested. Semantic descriptors are explored as a means of further improving the speed and usability of gestural interfaces, through the simultaneous control of multiple parameters. This rationalisation of control moves towards the implementation of gestural shortcuts and ‘continuous pre-sets’.
The Big Data Mining Approach for Finding top rated URL

Abstract Finding out the widely used URL’s from online shopping sites for any particular category is a difficult task as there are many heterogeneous and multi-dimensional data set which depends on various factors. Traditional data mining methods are limited to homogenous data source, so they fail to sufficiently consider the characteristics of heterogeneous data. This paper presents a consistent Big Data mining search which performs analytics on text data to find the top rated URL’s. Though many heuristic search methods are available, our proposed method solves the problem of searching compared with traditional methods in data mining. The sample results are obtained in optimal time and are compared with other methods which is effective and efficient.
Topology prediction in mobile ad hoc networks

In this work, I have reviewed existing prediction methods for the mobility of nodes and proposed three new schemes to predict the future set of topology of the mobile network. The proposed schemes are simple, efficient, and applicable to many existing algorithms. I evaluate the presented schemes on simulated and real data obtained from the Databases and Mobile Computing Laboratory at the University of Illinois at Chicago. The results show that the schemes successfully predict the future topology of the dynamic networks with high accuracy. They also minimize the frequency of route and location updates and any associated delays. The implementation of the proposed schemes on the upper layers makes them applicable to various routing algorithms including topology based routing algorithms and geographical routing algorithms, giving them the advantage of platform independence
An Introduction to the Palacios Virtual Machine Monitor—Release 1.0

Palacios is a virtual machine monitor (VMM) from the V3VEE Project that is available for public use as a community resource. Palacios is highly configurable and designed to be embeddable into different host operating systems, such as Linux and the Kitten lightweight kernel. Palacios is a non-paravirtualized VMM that makes extensive use of the virtualization extensions in modern Intel and AMD x86 processors. Palacios is a compact codebase, consisting of ∼ 96, 000 lines of C and assembly of which ∼ 40, 000 are in the core VMM, and the remainder are in virtual devices, extensions, an overlay network, and other optional features. Palacios is designed to be easy to understand and readily configurable for different environments. It is unique in being designed to be embeddable into other OSes instead of being implemented in the context of a specific OS. This document describes the overall structure of Palacios and how it works, with a focus on the Linux kernel module variation (other embeddings, such as for Kitten and Minix are documented separately). We also explain how to download and run Palacios, develop within it, and extend it. The author list reflects the writers of this technical report. The Palacios codebase has numerous contributors, as described briefly in Section 16 and on the V3VEE web site (v3vee.org). This project is made possible by support from the National Science Foundation (NSF) via grants CNS-0709168 (Northwestern University), CNS-0707365 (University of New Mexico), and the Department of Energy (DOE) via DE-SC0005343 (Northwestern University, University of Pittsburgh, University of New Mexico, Sandia National Labs, and Oak Ridge National Labs). Initial support for the development of Palacios was provided to Northwestern University via a subcontract from Oak Ridge National Laboratory on grant DE-AC05-00OR22725. Sandia National Laboratory provided seed funding to Northwestern University for multicore guest support. Jack Lange was partially supported by a Symantec Research Labs Fellowship.
Voxel-Based Level-of-Detail Visualization of Isogeometric Volumes

3D models created in Computer Aided Design (CAD) software are ubiquitous in the manufacturing industry. Preparing for analysis on them has typically been a very timeconsuming process, and isogeometric analysis was therefore proposed as an alternative approach. It is desirable to be able to visualize the models during isogeometric analysis, but this is not a straightforward process due to how the CAD models are defined. A recently developed approach allows interactive visualization of these models as volumes by ray-casting. This approach ensures highly accurate renderings, but at the cost of being computationally expensive. This thesis explores ways of achieving improved performance while rendering these models, by looking at combining the isogeometric models with simplified voxelized representations. A 2D prototype was developed to experiment and test different raycasting methods, before moving to a 3D implementation. To determine the visual accuracy of the different methods the CIEDE2000 algorithm for color difference was used to compare the results from rendering to a reference solution. Several methods have been proposed in this thesis that significantly improves the rendering performance with the results also having good visual accuracy. This includes hybrid methods that dynamically switch between isogeometric models and their voxelized representations while ensuring that samples are pixel accurate. The methods have been compared against each other in different examples, and the generated results show that some of the proposed methods are very good candidates for visualizing isogeometric volumes with increased performance.