Miracle-dz/UniFAR-FTUs huggingface dataset:
ARFCOM: MODELS FOR ESTIMATING LIGHT TO HEAVY VEHICLE FUEL CONSUMPTION

A model, known as arfcom, is described for estimating the fuel consumption of vehicles ranging from cars to 40 tonne articulated trucks. Arfcom contains three forms of fuel consumption model (instantaneous, four mode elemental and running speed) which use vehicle speed data ranging from second by second to average travel speeds. Arfcom is a detailed power based model which is capable of estimating the fuel consumption due to speed changes induced by curvature, grade or traffic control devices and due to the extra power required to overcome grade and cornering resistance. Expressions and/or tables are given for calculating the power components and default vehicle parameters from a small number of easily observable parameters. The model and the default parameters are validated using data from a number of sources. The limited input data requirements, accuracy at a trip and driving mode level and the three forms of fuel model make arfcom suitable for use in the areas of rural and urban traffic and transport management. Use of the model in conjunction with traffic models in rural and urban applications is discussed and examples of the use of arfcom are given. Vehicle parameters for ten vehicle classes and typical proportions of vehicles kilometres of travel in each class are given (a). The isbn of the microfiche version is 0-86910-354-7.
Cross-linguistic influence and language switches in L4 oral production

This study examines cross-linguistic influence and language switches in the oral production of English by Catalan-Spanish bilingual learners who have learned French as the first foreign language at school. The research questions consider the sources of borrowing, the choice of language for borrowings and code switched utterances, the type of transfer material (content and function words), as well as the effect of learners’ TL proficiency level on cross-linguistic influence. The results highlight the effect of proficiency level and contextual factors. It is also suggested in the discussion that the different patterns of language choice in borrowing and code switching may be explained in terms of the different stages in the speaking process.
Uses of Japanese in the English Classroom: Introducing the Functional-Translation Method.

A discussion of the use of Japanese in the English language classroom in Japan proposes that whatever justification is given for the English-only classroom is based on two flawed arguments: (1) outright rejection of the traditional grammar-translation method; and (2) the false assumption that an English-only requirement is an essential element of current "communicative" methodologies. The translation element of the grammar-translation method has been blamed for the faflure of Japanese-speakers to learn English; however, it is claimed here that the emphasis on grammar, which focuses on the referential meaning of a phrase rather than its social meaning, is instead at fault. An alternative "functional-translation" method is preferred because such an approach places emphasis first on helping the student understand and convey the meaning of ideas that are the most useful to him; only then is the appropriate grammar sought out as the framework in which to express those ideas. Materials and classroom procedures for the grammar-translation and functional translation methods are compared and contrasted, and some sample bilingual (Japanese-English) classroom activities are described. (Contains 39 references.) (MSE) ******************************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ******************************************************************************** -Uses of Japanese in the English Classroom : Introducing the Functional-Translation Method
Storytelling in den Naturwissenschaften - erste Ergebnisse einer Pilotstudie zur Untersuchung der Wirksamkeit -

Narrative Ansatze haben in den letzten Jahren speziell im angelsachsischen Bereich in den naturwissenschaftlichen Fachern an Bedeutung gewonnen. Im Rahmen des bereits vorgestellten Storytelling@TeachingModel (S@TM) Projekts wurden Materialien entwickelt und erprobt, die Lehrkrafte in die Lage versetzen sollen Geschichten fur naturwissenschaftliche Bildungsprozesse fruchtbar zu machen. Dafur konnen die auf historischen Episoden basierenden Stories, die aus den Bereichen Biologie, Chemie und Physik stammen, nicht nur im Hinblick auf inhaltliche Aspekte ausgewahlt werden, sondern auch, um jeweils definierte Nature of Science (NoS) -Aspekte zu thematisieren. Im Sommersemester 2013 wurden ausgewahlte Materialien und deren Darbietungsform im Rahmen eines universitaren Seminars mit Studierenden erprobt und evaluiert. Im September 2013 folgten dann zwei Lehrerfortbildungen, die ebenfalls evaluiert wurden. Im Rahmen des Beitrags sollen erste Erfahrungen und Ergebnisse der empirischen Pilotstudie zur Wirksamkeit des Bildungsangebotes diskutiert und hieraus resultierende mogliche Konsequenzen vorgestellt werden.
Understanding how reverse engineers make sense of programs from assembly language representations

This dissertation presents a theory of how reverse engineers make sense of executable programs. The theory describes the process of sensemaking in reverse engineering as a goal-directed planning-based search activity, in which the reverse engineer interacts with an executable program using reverse engineering tools in order to construct a mental model and working understanding of the functionality of the program. This theory is developed through a case study, semi-structured interviews with expert reverse engineers, and observations of reverse engineers performing a reverse engineering task. The theory of sensemaking in reverse engineering is a step toward building autonomy into analysis tools so they will be able to discovery vulnerabilities in complex software-based systems and analyze executable programs to determine whether those programs contain undocumented malicious functionality and should not be trusted.
Adaptive Semantic Annotation of Entity and Concept Mentions in Text

Mendes, Pablo N. Ph.D., Department of Computer Science and Engineering, Wright State University, 2013. Adaptive Semantic Annotation of Entity and Concept Mentions in Text. The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc or application-specific databases. These knowledge repositories figure as a central provider of unambiguous identifiers and semantic relationships between entities. As such, these shared entity descriptions serve as a common vocabulary to exchange and organize information in different formats and for different purposes. Therefore, there has been remarkable interest in systems that are able to automatically tag textual documents with identifiers from shared knowledge repositories so that the content in those documents is described in a vocabulary that is unambiguously understood across applications. Tagging textual documents according to these knowledge bases is a challenging task. It involves recognizing the entities and concepts that have been mentioned in a particular passage and attempting to resolve eventual ambiguity of language in order to choose one of many possible meanings for a phrase. There has been substantial work on recognizing and disambiguating entities for specialized applications, or constrained to limited entity types and particular types of text. In the context of shared knowledge bases, since each application has potentially very different needs, systems must have unprecedented breadth and flexibility to ensure their usefulness across applications. Documents may exhibit different language and discourse characteristics, discuss very diverse topics, or require the focus on parts of the knowledge repository that are inherently harder to disambiguate. In practice, for developers looking for a system to support their use case, is often unclear if an existing solution is applicable, leading those developers to trial-and-error and ad hoc usage of multiple systems in an attempt to achieve their objective. In this dissertation, I propose a conceptual model that unifies related techniques in
Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces (PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions
Using Remote Desktop Applications in Education

Students often need help outside the traditional classroom when face to face interaction is not possible. This applies even more to students in online courses. The opportunity to obtain help from instructors is limited to class time in face to face classes, office hours in the instructor’s office, and online to the extent that instructors are willing to be available through email or other electronic communications channels. This paper discusses the potential use of remote desktop technologies to use remote collaboration on students’ computer desktops to demonstrate skills and assist in activities when students are not able to complete work without assistance. The Unified Theory of Acceptance and Use of Technology is used to perform a preliminary study of students’ acceptance of these technologies. Using a limited sample of 25 subjects, the data suggest that only the attraction to remote sessions as a technology may influence whether students intend to use them. Based on this limited study, students do not (yet) perceive a performance benefit for their educational work. To increase acceptance of this promising technology, instructors may need to aggressively promote its use.
In the Middle: New Understandings about Writing, Reading, and Learning. Second Edition.

When first published in 1987, this seminal work was widely hailed for its honest examination of how teachers teach, how students learn, and the gap that lies in between. In depicting her own classroom struggles, Nancie Atwell shook our orthodox assumptions about skill-and-drill-based curriculums and became a pioneer of responsive teaching. Now, in the long awaited second edition, Atwell reflects on the next ten years of her experience, rethinks and clarifies old methods, and demonstrates new, more effective approaches. The second edition still urges educators to "come out from behind their own big desks" to turn classrooms into workshops where students and teachers create curriculums together. But it also advocates a more activist role for teachers. Atwell writes, "I'm no longer willing to withhold suggestions and directions from my kids when I can help them solve a problem, do something they've never done before, produce stunning writing, and ultimately become more independent of me. " More than 70 percent of the material is new, with six brand-new chapters on genres, evaluation, and the teacher as writer. There are also lists of several hundred minilessons, and scripts and examples for teaching them; new expectations and rules for writing and reading workshops; ideas for teaching conventions; new systems for record keeping; lists of essential books for students and teachers; and forms for keeping track of individual spelling, skills, proofreading, homework, writing, and reading. The second edition of "In the Middle" is written in the same engaging style as its predecessor. It reads like a story - one that readers will be pleased to learn has no end. As Atwell muses, "I know my students and I will continue to learn and be changed. I am resigned - happily - to be always beginning for the rest of my life as a teacher. "
Information Processing and Perceptual Characteristics of Display Design: The Role of Emergent Features and Objects

Abstract : In this report, the fundamental theoretical and applied principles are outlined, which have been cited to justify the relative benefits of object displays, the representation of several quantitative variables as features of single geometric objects. In particular, the proximity compatibility principle is described, which asserts that object displays will facilitate information integration tasks but will disrupt tasks that require focused attention on the individual dimensions of the object. Finally, an experiment is described contrasting three displays: a monochrome object, a multicolor object, and a separated bar graph display. Subjects were required to either integrate or focus attention on one of three sources of displayed information in an aircraft stall judgment task. Evaluation of the monochrome object revealed superior integration performance but degraded focused attention performance relative to the bar graph display, thus illustrating the proximity compatibility principle. The multicolored object, in contrast, emerged as a display concept that could potentially support accurate integration and focused attention performance, highlighting the role of emergent features and color coding, and suggesting some modifications of the proximity compatibility principle. The results are discussed in terms of their theoretical and practical application to multi- element interface design. (kr)
Loading and distribution of the 2000 high frequency words in Malaysian english language textbooks for form 1 to form 5

Textbooks are important tools used by teachers in teaching. Today, thanks to corpus-based research and the use of concordance software to analyze language, entire textbooks can be scanned to form what we call a corpus of the language of English language textbooks. Concordance software is used to perform automated and semi-automated analyses in terms of loading and distribution of words in textbooks. In this study, the researchers studied patterns of loading, distribution and repetition, and investigated cases of words missing in books, all based on the 2000 high frequency word list. Results of the study reveal that while most of the 2000 high frequency words (93.1%) are used in the secondary school textbooks, repetition and recycling are not efficient. The research also revealed that there are 139 (6.9%) words in the 2000 high frequency word list which are not used at all in Malaysian English language textbooks. The results also caution material developers that high coverage of the 2000 high frequency words does not ensure effective learning, especially when the words are poorly distributed within and across textbooks.
Mysticism, Materialism, and the Machine in Berlin Dada

The Dada Fair exhibition of 1920 brought the self-proclaimed “central attack on the culture of the bourgeois” of Berlin Dada to its spectacular culmination. The catalogue brashly announced the abolition of the art market, while a placard by George Grosz and John Heartfield proclaimed the death of art itself and the rise of the new “machine art of Tatlin” (Figs. 1 and 2). If the latter claim was based more on the critic Konstantin Umanski's description of “Tatlinismus” as a “conquering materialism” than on any knowledge of how Vladimir Tatlin's art actually appeared, it was typical of the confident, ironic social criticism of Berlin Dada. While a profound disillusionment among the Expressionists was producing somber obituaries, Raoul Hausmann appeared triumphant in his coup de grâce published in April in Der Dada 3: “Dada is the full absence of what is called Geist. Why have Geist in a world that runs on mechanically? ”
The control system of the ATLAS/TileCal

TileCal is the hadronic calorimeter of the ATLAS detector that is operating at CERN. The main task of the TileCal Detector Control System (DCS) is to enable the coherent and safe operation of the detector. All actions initiated by the operator and all errors, warnings, and alarms concerning the hardware of the detector are handled by DCS. The logical structure of the TileCal DCS is subdivided in functional blocks, following a functional criteria, structured in a tree-like way where all the functional blocks can run autonomously. The system comprises the following functional blocks: the low voltage power supplies (LVPS), the high voltage (HV) and the cooling of the electronics. We report the result of four years of work dedicated to the TileCal DCS design, development, installation, testes and its integration into ATLAS detector operation. Also reported is the study done for the optimization validation of the Local Hadronic Calibration using the data from the combined test-beam in the year 2004 at CERN. The combined test-beam consisted on exposing a fully instrumented slice of the ATLAS detector to particle beams from the SPS (Super Proton Synchrotron). The results of themeasurements of the response of the hadronic Tile calorimeter to pionswith energy in the range 2 to 230 GeV using the Local Hadron Calibration schema are reported. The linearity and the resolution of the calorimeter were determined and compared to previous results and to the predictions of a simulation program using the toolkit Geant4.
A cortical model for spatial navigation planning

According to experimental evidence, spatial navigation planning is likely to rely upon a distributed neural network spanning limbic and cortical brain structures. This network includes (i) the hippocampus, which mediates robust spatial representations, and (ii) neocortical structures, such as the prefrontal cortex, which participate to the elaboration of more abstract contextual descriptions (e.g., accounting for motivation-dependent memories and action cost/risk constraints). In order to investigate this working hypothesis, we model the interaction between the hippocampus [1] and the prefrontal cortex [2]. We focus on the cortical columnar organisation to study a neuromimetic architecture suitable for spatial navigation planning. We validate the system’s learning performance on a classical spatial behavioural task, the Tolman & Honzik’s detour protocol [3], which suggests that rodents can plan flexible goal-directed trajectories in the presence of blocked pathways. We also put forth a set of statistical analysis to assess the spatial coding properties of the model hippocampal place and cortical column cells. Here, we couple our hippocampal place cell [1] and columnar cortical [2] models to provide a better understanding of the dynamics of the action planning neural network. We also improve the biological plausibility of the cortical model, by explicitly identifying the subpopulations of (rate code) neurones that encode different information (e.g., current spatial state, goal-related and prospective memory signals, local actions). This approach has several advantages: (i) the response of each subpopulation being more specific, it makes it possible to perform a series of analyses of multiple neural activity correlates; (ii) the functioning of the columnar assembly can be formalised within the reinforcement learning framework, which proved to be relevant to the understanding of goalrelated neural activities [4]; (iii) the biological plausibility of the model being enhanced, the discharges of formal units can be compared against experimental data (e.g., electrophysiological recordings [5,6]), and give rise to testable predictions. The spatial planning model reproduces the experimental results by Tolman & Honzik [3]. It also unravels the possible links between the single unit level and the behavioural level relevant to the learning of the task (e.g., to the selection of the shortest path to the reward, and to the prediction of future state sequences). Finally, our neural response analysis suggests how the interplay between the model hippocampus and the prefrontal cortex can yield to the encoding of manifold information pertinent to the spatial planning function (e.g., prospective and distance-togoal correlates).
Distributed averaging and efficient file sharing on peer-to-peer networks

The work presented in this thesis is mainly divided in two parts. In the first part we study the problem of distributed averaging, which has attracted a lot of interest in the research community in recent years. Our work focuses on the issues of implementing distributed averaging algorithms on peer-to-peer networks such as the Internet. We present algorithms that eliminate the need for global coordination or synchronization, as many other algorithms require, and show mathematical analysis of their convergence. Discrete-event simulations that verify the theoretical results are presented. We show that the algorithms proposed converge rapidly in practical scenarios. Real-world experiments are also presented to further corroborate these results. We present experiments conducted on the PlanetLab research network. Finally, we present several promising applications of distributed averaging that can be implemented in a wide range of areas of interest. The second part of this thesis, also related to peer-to-peer networking, is about modelling and understanding peer-to-peer file sharing. The BitTorrent protocol has become one of the most popular peer-to-peer file sharing systems in recent years. Theoretical understanding of the global behavior of BitTorrent and similar peer-to-peer file sharing systems is however not very complete yet. We study a model that requires very simple assumptions yet exhibits a lot structure. We show that it is possible to consider a wide range of performance criteria within the framework, and that the model captures many of the important issues of peer-to-peer file sharing. We believe the results provide fundamental insights to practical peer-to-peer file sharing systems. We show that many optimization criteria can be studied within our framework. Many new directions of research are also opened up.