Miracle-dz/UniFAR-FTUs huggingface dataset:
Resource Management for HPC on the Cloud

This chapter starts by presenting an overview on existing resource management systems and scheduling algorithms for high-performance computing for clouds. Next, we describe a prototype framework for building autonomous resource management systems. This is aimed at allowing administrators to enhance their own solutions with autonomous behavior by relying on theAPI and the communication protocol we offer. The current version only supports self-healing, but we intent to extend its capabilities to those of a fully autonomous system.
Automatic error recovery using P3 response verification for a brain-computer interface

Recent advances in signal processing have made brain-computer interfaces (BCIs) feasible for use as an alternative control option for those with severe motor impairments. It is possible to increase the accuracy of a BCI system by requiring users to make multiple choices to control a single item, but this comes at a cost of reduced system speed. We present experimental results from an evoked potential BCI used to control items in a virtual apartment and show the existence of the evoked potential P3 component in responses to successfully controlled goal items. A reduced response exists when items are accidentally controlled. The presence of the P3 component in responses to goal items means that it can be used for automatic error correction. Off-line experiments have been run and with a theoretical mean improvement in recognition from 78% to 85%, we show a statistically significant improvement (p < 0.004, Wilcoxen test, two-tailed) in accuracy of 3% using the variable averaging algorithm. Since the error correction technique depends on responses to controlled items in a particular experimental paradigm rather than the control of the items themselves, it may be possible to use this response in non-evoked potential BCI systems. Future work is discussed in this context.
Optimal Controller Design of Legless Piezo Capsubot Movement

This paper presents an optimal control method based on control effort minimization for a legless piezo capsubot. The capsubot is an underactuated nonlinear dynamics system which is driven by an internal impact force and friction. Here, the motion mechanism of the capsubot is divided into two stages. In the first stage, the aim is to design an optimal controller minimizing energy consumption. In the second stage, optimization is not an objective and instead a four-step strategy for inner mass of the capsubot is proposed. Then, based on the proposed motion strategy, a trajectory profile is given. Using this trajectory profile, the capsubot moves in the desired direction. To evaluate the performance of the proposed control scheme, a comparative study has been performed by means of simulation. Simulation results show that the proposed approach is promising as compared to the Open-Loop Control (OLC) approach and Close-Loop control (CLC) approach which are widely used in the literature for control of capsubots.
Enhanced decoding for the Galileo low-gain antenna mission

Due to a malfunctioning high-gain antenna, the Galileo spacecraft is transmitting all its data through a low-gain antenna, and the data rate will seldom exceed 100 bits per second during its two-year tour of Jupiter's satellites. To offset some of the performance loss, the spacecraft's computer will be extensively reprogrammed to include new data compression and coding algorithms. The baseline coding system for the low gain antenna mission uses a Reed-Solomon (RS) outercode of block length 255 concatenated with a (14, 1/4) convolutional inner code, and interleaves the RS symbols to depth eight. The convolutionally encoded symbols are decoded by a maximum likelihood (Viterbi) decoder, and each RS codeword is decoded algebraically. Two types of decoding enhancements were proposed as feasible due to the low data rate. The first type of redecoding is confined to the RS decoder and utilizes information from neighboring codewords within the same interleaved block to erase unreliable symbols in undecoded words. The second type involves redecoding by the Viterbi decoder, using information fed back from codewords successfully decoded by the RS decoder. <<ETX>>
Studies of Intuitive Use Employing Observation and Concurrent Protocol

This paper explores intuitive interaction with products from a methodological standpoint. Intuitive use of products involves utilising knowledge gained through other products or experiences. The nature of intuitive interaction presents certain problems with its study because it is product features that users have relevant prior experience with rather than a whole product. The challenge was to find ways of recording and coding observations so this level of detail could be extracted from user tests. This was accomplished using specialist observation software. These methods have twice proved successful in studying this complex topic and gaining reliable results. Details of the methods used and implications of the results gained are discussed.
Capteurs intégrés pour la fiabilisation des technologies d'encapsulation en microélectronique

L’entreprise IBM a lance en 2014 un projet de recherche pour introduire de l’intelligence, c’est-a-dire des capteurs, dans des modules micro-electroniques. Le projet vise l’amelioration, a partir des donnees des capteurs, des procedes d’assemblage de puce qui serviront dans des serveurs pour du calcul haute performance ou les telecommunications.Mon projet consiste a concevoir, caracteriser, puis integrer 109 micro-capteurs, de dimensions 1 x 100 x 100 µm3, de temperature, humidite et contrainte sur une puce electronique de 2 x 2 cm2. L’objectif est d’obtenir en temps reel la repartition de l’humidite, la temperature et la contrainte dans l’assemblage, en environnement severe.Les capteurs a base de nanotubes de carbone realises sont tres sensibles a l’humidite et la temperature, avec par exemple une variation de 50% de la grandeur de sortie du capteur pour une variation de -40 a 140 °C. J’ai propose une methode novatrice a partir des proprietes de l’impedance du capteur permettant la separation de la reponse a la temperature de celle a l’humidite.
Report on the State-of-the-Art and Requirements for Annotation Representation Models

INSEMTIVES overall goals is to increase the amount of available semantic content by looking into incentives and by bridging the gap between human and computational intelligence. Annotations are one form of semantic content which are supposed to make implicit information explicit and which typically attach additional meaning to a resource. This deliverable provides a classification scheme for annotation models and summarizes the state of the art in the areas relevant for the INSEMTIVES project. It concludes with an analysis of the requirements of the use cases partners in the project with respect to annotation models and a summary of them.
Initial trends in enrolment and completion of massive open online courses

The past two years have seen rapid development of massive open online courses (MOOCs) with the rise of a number of MOOC platforms. The scale of enrolment and participation in the earliest mainstream MOOC courses has garnered a good deal of media attention. However, data about how the enrolment and completion figures have changed since the early courses is not consistently released. This paper seeks to draw together the data that has found its way into the public domain in order to explore factors affecting enrolment and completion. The average MOOC course is found to enroll around 43,000 students, 6.5% of whom complete the course. Enrolment numbers are decreasing over time and are positively correlated with course length. Completion rates are consistent across time, university rank, and total enrolment, but negatively correlated with course length. This study provides a more detailed view of trends in enrolment and completion than was available previously, and a more accurate view of how the MOOC field is developing.
A Preview of Act 1

Abstract : The next generation of artificial intelligence programs will require the ability to organize knowledge as group of active objects. Each object should have only its own local expertise, the ability to operate in parallel with other objects, and the ability to communicate with other objects. Artificial Intelligence programs will also require a great deal of flexibility, including the ability to support multiple representations of objects, and to incrementally and transparently replace objects with new, upward-compatible versions. To realize this, we proposed a model of computation based on the notion of an actor, an active object that communicates by message passing. Actors blur the conventional distinction between data and procedures. The actor philosophy is illustrated by description of our prototype actor interpreter Act 1. (Author)
Teaching and learning English grammar : research findings and future directions

Foreword Joanne Dresner Preface MaryAnn Christison, Donna Christian, Patricia A. Duff, and Nina Spada Acknowledgments Part I. Overview of English grammar instruction Chapter 1. An overview of teaching grammar in ELT Marianne Celce-Murcia Part II. Focus on form in second language acquisition Chapter 2. Focus on form: Addressing grammatical accuracy in an occupation-specific language program Antonella Valeo Chapter 3. Teaching English grammar in context: The timing of form-focused intervention Junko Hondo Chapter 4. Form-focused instruction and learner investment: Case study of a high school student in Japan Yasuyo Tomita Chapter 5: The influence of pretask instructions and pretask planning on focus on form during Korean EFL task-based interaction Sujung Park Part III. The use of technology in teaching grammar Chapter 6. The role of corpus research in the design of advanced level grammar instruction Michael J. McCarthy Chapter 7. Corpus-based lexicogrammatical approach to grammar instruction: Its use and effects in EFL and ESL contexts Dilin Liu and Ping Jiang Chapter 8. Creating corpus-based vocabulary lists for two verb tenses: A lexicogrammar approach Keith S. Folse Part IV. Instructional design and grammar Chapter 9. Putting (functional) grammar to work in content-based English for academic purposes instruction Patricia A. Duff, Alfredo A. Ferreira, and Sandra Zappa-Hollman Chapter 10. Integrating grammar in adult TESOL classrooms Anne Burns and Simon Borg Chapter 11. Teacher and learner preferences for integrated and isolated form-focused instruction Nina Spada and Marilia dos Santos Lima Chapter 12. Form-focused approaches to learning, teaching, and researching grammar Rod Ellis Epilogue Kathleen M. Bailey About the Contributors Index
Agile Software Development: Principles, Patterns, and Practices

This comprehensive, pragmatic tutorial on Agile Development and eXtreme programming, written by one of the founding fathers of Agile Development: Teaches software developers and project managers how to get projects done on time, and on budget using the power of Agile Development; Uses real-world case studies to show how to of plan, test, refactor, and pair program using eXtreme programming; Contains a wealth of reusable C++ and Java code; Focuses on solving customer oriented systems problems using UML and Design Patterns.
Implantation et évaluation de micro-implants vasculaires (< 2mm), à base d’alcool polyvinylique

Sur la base de precedents travaux de l’unite INSERM 1148, sur des films a base d’alcool polyvinylique, nous avons implante et evalue des protheses de moins de 2mm de diametre. L’ajout de gelatine in vitro a montre des capacites d’adherence cellulaires, compatibles avec une endothelialisation in situ, des implants garant, d’une permeabilite a long terme. Notre modele etait le remplacement de 1cm d’aorte sous renale de rat. Ces implants, ont ete utilisees comme modele d’entrainement basse fidelite a la microchirurgie, avec de meilleurs resultats sur l’acquisition de la technique d’anastomose microchirurgicale, que les tubes en silicone anterieurement utilise, lors de l’enseignement chez 71 etudiants. Un nouveau moyen d’imagerie pour l’exploration vasculaire par angiographie par resonance magnetique, en temps de vol sans injection chez l’animal, et la premiere application chez l’homme sont rapportes. Apres avoir presente notre methode de fabrication par reticulation physique (Lyophilisation Congelation) et chimique (STMP) Cdu PVA, directement sous forme de tubes, nous avons confirme l’hypothese que les micro implants a base de PVA associe a la gelatine a hauteur de 1%, a permis d’ameliorer la permeabilite par rapport au PVA seul, ou a tout autre ratio de gelatine ; et ce grâce a une endothelisation in situ constatees histologiquement. Les performances biomecaniques de l’implant ont aussi etaient evaluees. Au dela de 2 mois la permeabilite chute de 75% a 50%. Le vieillissement du materiel par son enraidissement, et le relargage de la gelatine pourrait expliquer cette diminution des performances au cours du temps.
Circular external fixator application for midshaft tibial fractures: Surgical technique

The use of fine wire circular external fixation has recently undergone a resurgence in popularity among orthopaedic trauma and reconstructive surgeons. Their modularity, biomechanical characteristics and minimally invasive application make these fixators indispensable for complex trauma and post-traumatic limb reconstruction. The application of these fixators is technically demanding and a steep learning curve exists. This article aims to provide a simplified, stepwise approach to the application of a circular external fixator to the tibia.
Extraction and selection of robust features for classification of multispectral remote-sensing images

In this paper, we present an approach to the extraction and selection of robust features for classification of multispectral remote-sensing images. In particular, several robust features are proposed that, given a specific land-cover class, aim to exhibit an invariant behavior versus variations in the acquisition conditions of the images considered. In addition, a technique is presented, which is able to adaptively select the most robust features for a given problem.
The Effect of an English Language Learner Program on Student Achievement Outcomes in Language, Reading, and Math.

THE EFFECT OF AN ENGLISH LANGUAGE LEARNER PROGRAM ON STUDENT ACHIEVEMENT OUTCOMES IN LANGUAGE, READING, AND MATH Jennifer L. Reid University of Nebraska, 2011 Advisor: Dr. Peter Smith The purpose of the study was to determine the reading, math, and language proficiency outcomes of 4th-grade through 7th-grade students with limited English proficiency following nearly two years or more of instruction in the English Language Learner Program (ELL) and concurrent general education studies. The maximum accrual for this study was students (N = 31) participating in the research school districts English Language Learner Program. The independent variables for this study were three student groups representing students who were identified as limited English proficient and who had participated in the ELL Program and general education program. Study participants in the first arm (n = 4) were limited English proficient students whose language proficiency at the time of entrance to the ELL Program was at the beginning level (Levels 1 and 2). Study participants in the second arm (n = 10) were limited English proficient students whose language proficiency at the time of entrance to the ELL Program was at the intermediate level (Level 3). Study participants in the third arm (n = 17) were limited English proficient students whose language proficiency at the time of entrance to the English Language Learner Program was at the advanced level (Levels 4 and 5). The results of the study supported the effectiveness of the ELL Program and concurrent general education studies in
Automatic recognition of handwritten dates on brazilian bank cheques

In this thesis, an HMM-MLP hybrid system for segmenting and recognizing unconstrained handwritten dates written on Brazilian bank cheques is presented. The system evolves by dealing with many sources of variability, such as heterogeneous data types and styles, variations present in the date field, and difficult cases of segmentation that make the recognizer task particularly hard to do. The system takes an HMM-based strategy for identifying and separating the date into sub-fields. It makes use of the concept of meta-classes of digits in order to reduce the lexicon size of the day and year and produce a more precise segmentation. After that, the three obligatory sub-fields (day, month, and year) are recognized using specialized classifiers according to their respective data types which are known. In such cases, we propose an HMM word recognition and verification scheme to process month words and an MLP approach to decipher strings of digits (day and year). The digit string recognition strategy also makes use of the meta-classes of digits in order to reduce the lexicon size on digit string recognition and improve the recognition results. In addition to the date database, we have used other databases in order to validate the strategies employed in digit string recognition and word verification. Experiments show encouraging results on date, word, and digit string recognition. The system also contains a final decision module which makes an accept/rejection decision. Finally, a methodology for feature selection in unsupervised learning is proposed. It makes use of an efficient multi-objective genetic algorithm to generate a set of solutions, which contain the more discriminant features and the more pertinent number of clusters. The proposed strategy is assessed using two synthetic data sets where the significant features and the appropriate clusters in any given feature subspace are known. Afterwards, it is applied to optimize classifiers in a supervised learning context, i.e., handwritten word recognition. In this scenario, our approach is evaluated by conducting some experiments on isolated month word recognition. In this thesis, it is also used to optimize the word verifier of the date recognition system. Comprehensive experiments demonstrate the feasibility and efficiency of the proposed methodology.
Placement techniques for the physical synthesis of nanometer-scale integrated circuits

Placement is a critical component in the physical synthesis of nanometer-scale integrated circuits. Placement of circuit modules determines to a large extent interconnect length and routing resource demand. Interconnect length has a direct impact on the interconnect delay, which has become the determining factor of circuit performance in nanometer-scale process technology. In addition, interconnect length has a direct impact on the circuit power. Hence, the quality of the placement significantly affects the ability of a physical synthesis tool or designer to achieve design closure. In this work, efficient and high quality placement techniques have been developed for the physical synthesis of multi-million gate integrated circuits in the nanometer regime. The focus of these techniques are: (a) global placement and legalization of mixed-size circuits to minimize interconnect length, circuit power and routing resource demand, and (b) incremental physical synthesis via integrated timing optimization and placement to achieve timing closure. The effectiveness of the techniques is demonstrated by: (a) comparing them with existing approaches that perform integrated circuit placement, and (b) embedding them within a stateof-the-art industrial physical synthesis tool that is used in the design of high performance integrated circuits in the 65nm and 45nm process technology nodes.
Dynamic neural networks for input-output linearisation

A dynamic recurrent neural network is proposed to model, linearise and control a process plant. In this approach the plant is first modelled using artificial neural networks (ANNs) based on input-output data and then the dynamic neural network model acting as a plant emulator is feedback linearised. The approach outlined in this work uses a novel ANN based structure to feedback linearise the process plant. Once the plant emulator is linearised, standard linear control strategy is used to control the plant emulator. Simulation results using actual industry data reveal the accuracy of the modelling, linearisation and control achieved.
Optimizing GP Approach Using KFINDMRD Algorithm For Record Deduplication

Deduplication is the key operation in data integration from multiple data sources. To achieve higher quality information removal of replicas within the repository is required. The accuracy in genetic programming is so less KFINDMRD(KFIND using Most Represented Data samples) is proposed to improve the accuracy of the classifier. The proposed system removes the duplicate dataset samples in the system and find the optimization solution to the deduplication of records or data samples in an efficient manner. In addition, the efficiency of the GP training phase is improved by giving the selected samples from the KFINDMRD algorithm. This deduplication process is carried out by the admin before storing the data within database so that the user can access data with good quality of information without the presence of duplicates. Secured login will be given to the users for accessing the data after the completion of the deduplication process. A performance evaluation for accuracy is done for the dataset with duplicates using Genetic programming and Genetic programming with KFINDMRD algorithm. Keywordsdeduplication, genetic programming, KFINDMRD,.
Biophysical forest type characterisation in the Colombian Amazon by airborne polarimetric SAR

Fully polarimetric C-, L- and P- band data were collected by NASA's AirSAR system at the Araracuara test site, a well-surveyed forest reserve in the centre of the Colombian Amazon. The area is characterised by a high diversity of forest types, soil types and flooding conditions. A polarimetric classification technique is used to assess AirSAR's potential for forest structural type mapping and, indirectly, forest biophysical characterisation. Field observations were made at 23 0.1 ha plots to obtain additional quantitative descriptions on forest structure and ground surface conditions, but also to assess the suitability of existing map legends for SAR mapping. It could be shown that a new type of legend leads to physically better interpretable results. A method based on iterated conditional modes is introduced and is shown to yield radar-derived maps with a high level of agreement with existing maps, as well as with the ground observations. The following results may indicate the high level of accuracy obtained: 15 classes can be differentiated, the average radar map agreement ranges from 68-94% (depending on the type of map and approach) and for only a few classes the agreement is less than 70%. The relation between physical forest structure and polarimetric signal properties is studied explicitly using polarimetric decomposition. A new method is introduced based on the decomposition of polarimetric coherence, instead of power. It is based on simple physical descriptions of the wave-object interaction. The accuracy of the complex coherence estimation derived from the complex Wishart distribution. Thus several interesting physical relations between polarimetric signal and forest structure can be revealed. The physical limitations of this technique and its relation with sample size are indicated.
Monitoring and diagnostics of a class of nonlinear systems using a nonlinear unknown input observer

In this paper we study a class of nonlinear systems with unknown inputs for which nonlinear observers with linearizable error dynamics in appropriate coordinates can be designed. Various conditions for accomplishing this task are stated. The observation scheme is then utilized as a mean for model based monitoring and failure diagnosis within the system. Selection of threshold value with reliability is discussed. Finally, the paper concludes with examples, illustrating applicability of the reported results in linear and nonlinear systems.