Miracle-dz/UniFAR-FTUs huggingface dataset:
Communication Based Flexible Process Management for Collaborative Work

In recent years, engineering areas and business application areas are incorporating computer support for process management for improving efficiency and cooperation. A process is a sequence of collaborative human activities for a certain goal. A process management system is effective for clarifying process structure, for managing current status of the process, and also for managing roles of participants and required resources. However, the problem is that the human activity is naturally hard to be predefined completely, and a framework for flexible process management is necessary. This thesis addresses a method for flexible process management based on asynchronous communication, which is communication in which the creation and the reference of a message is done in different time, and addresses the method for adapting dynamic design or modification of process specifications. A specification is a partial or entire description of a process, or that of a common part of several processes, and is a major factor for the effectiveness of process management. First, the message transaction model, which is a model for representing processes and various advanced transactions based on asynchronous communication, is proposed. By the model, a process which is created and executed in an ad-hoc manner can be easily captured by the system, since users’ messages are the unit of management. For example, the messages for applying the room reservation and its reply can organize a process. Moreover, the process or an aggregation of messages in the model are given transactional behaviors such as abort and commit, and various dependencies employed in advanced transaction models are given between them. These approaches provide user-friendly operations for constructing transactions flexibly adapting the situation. Our approach provides dynamic (runtime), user-specified construction of advanced transactions such as nested transactions, by processing communication. Moreover, dynamic construction of transactions requires runtime checking of required properties, such as deadlock-free. Therefore, we show several theoretical conditions and complexity issues for checking such consistencies.
Discriminative learning and spanning tree algorithms for dependency parsing

In this thesis we develop a discriminative learning method for dependency parsing using online large-margin training combined with spanning tree inference algorithms. We will show that this method provides state-of-the-art accuracy, is extensible through the feature set and can be implemented efficiently. Furthermore, we display the language independent nature of the method by evaluating it on over a dozen diverse languages as well as show its practical applicability through integration into a sentence compression system. We start by presenting an online large-margin learning framework that is a generalization of the work of Crammer and Singer [34, 37] to structured outputs, such as sequences and parse trees. This will lead to the heart of this thesis---discriminative dependency parsing. Here we will formulate dependency parsing in a spanning tree framework, yielding efficient parsing algorithms for both projective and non-projective tree structures. We will then extend the parsing algorithm to incorporate features over larger substructures without an increase in computational complexity for the projective case. Unfortunately, the non-projective problem then becomes NP-hard so we provide structurally motivated approximate algorithms. Having defined a set of parsing algorithms, we will also define a rich feature set and train various parsers using the online large-margin learning framework. We then compare our trained dependency parsers to other state-of-the-art parsers on 14 diverse languages: Arabic, Bulgarian, Chinese, Czech, Danish, Dutch, English, German, Japanese, Portuguese, Slovene, Spanish, Swedish and Turkish. Having built an efficient and accurate discriminative dependency parser, this thesis will then turn to improving and applying the parser. First we will show how additional resources can provide useful features to increase parsing accuracy and to adapt parsers to new domains. We will also argue that the robustness of discriminative inference-based learning algorithms lend themselves well to dependency parsing when feature representations or structural constraints do not allow for tractable parsing algorithms. Finally, we integrate our parsing models into a state-of-the-art sentence compression system to show its applicability to a real world problem.
Exploring the collocational competence of non-native users of medical English

Previous research on collocations has emphasised the significance of collocations as co-occurrence and recurrence. Applied linguists exploring the acquisition of collocations made a significant contribution to the understanding of the notion of collocation. However, only few studies have dealt with the difference between collocations in general English and collocations in scientific English. The present study deals with verb collocations in medical English. Collocations are observed in the interaction of syntagmatic and paradigmatic relations. The emphasis is on upward collocations (collocate and node). The study aims at analysing the level of collocational competence of non-native users of medical English in order to identify the aspects of verb collocations that require a special approach in teaching medical language.
OVERCOMING THE LIMITED INTERACTIVITY IN TELEMATIC SESSIONS FOR IN-SERVICE SECONDARY MATHEMATICS AND SCIENCE TEACHERS

In rapidly expanding possibilities for harnessing digital technologies for blended learning purposes worldwide, this paper explores the challenges of overcoming the limited interactivity of telematic sessions, face-to-face contact sessions and distance from campus for in-service teachers in remotely located schools. The Centre for Pedagogy at Stellenbosch University in South Africa entered was contracted by the Department of Education to deliver in-service programmes through contact sessions and telematic sessions in an attempt to up skill their mathematics and science pedagogical content knowledge (PCK) and subject matter knowledge (SMK) according to their needs. A major limitation of the telematic sessions is their lack of interactivity. What are the instructional design imperatives that should accompany such blended learning delivery modes to make them more effective? More importantly, how can the one-way lectures be made more interactive so that the needs and understandings of the audience are catered for? Can the advent of social media such as the WhatsApp instant messaging service applications be of any value? Using a case study design coupled with discourse and content analyses of WhatsApp conversations, feedback from 73 teachers has been positive.
Computers in physics instruction : students' interactions in a constructivist microcomputer-based laboratory

This study aimed to increase understanding of students' interactions in a physics microcomputer-based laboratory (MBL) specifically designed to be consistent with a constructivist theory of learning. The study was motivated by a perceived need to understand better how the materials and strategies support or constrain students construction of understanding. The teacher-researcher conducted the study with two of his Year 11 physics classes, comprising 15 students studying thermal physics and 29 students studying kinematics. Dyads of students worked at tasks using a predict-observe-explain (POE) format as part of the normal class program. Data included video and audio recordings during four 70-minute sessions for each class, students' written notes, semi-structured student interviews, and the teacher's reflections on each session. The study describes the actors and network relationships during task activities. An analysis of students' discourse identified features common to both domains of physics, while the findings about studentdisplay- teacher interactions are presented as a series of eight assertions. Finally, the researcher's interpretation of learning in an MBL leads to recommendations for teaching practice.
Query Optimization and Execution for Multi-Dimensional OLAP

Online Analytical Processing (OLAP) is a database paradigm that supports the rich analysis of multi-dimensional data. While current OLAP tools are primarily constructed as extensions to conventional relational databases, the unique modeling and processing requirements of OLAP systems often make for a relatively awkward fit with RDBM systems in general, and their embedded string-based query languages in particular. In this thesis, we discuss the design, implementation, and evaluation of a robust multi-dimensional OLAP server. In fact, we focus on several distinct but related themes. To begin, we investigate the integration of an open source embedded storage engine with our own OLAP-specific indexing and access methods. We then present a comprehensive OLAP query algebra that ultimately allows developers to create expressive OLAP queries in native client languages such as Java. By utilizing a formal algebraic model, we are able to support an intuitive Object Oriented query API, as well as a powerful query optimization and execution engine. The thesis describes both the optimization methodology and the related algorithms for the efficient execution of the associated query plans. The end result of our research is a comprehensive OLAP DBMS prototype that clearly demonstrates new opportunities for improving the accessibility, functionality, and performance of current OLAP database management systems.
Book Review: Can Co-Teachers Provide Quality Education? Let the Data Tell Us!

Nagiera and Simmons are teacher educators who collaborated with middle school personnel over a period of 3 years to develop, implement, field-test, and redesign the Quality Indicator Model of Co-Teaching. Results of the implementation of this model have been published (Magiera, Simmons, Marotta, & Battaglia, 2005) and presented at national conferences (Magiera & Simmons, 2005). Magiera and Simmons identify five categories of quality indicators. For each category, they provide a definition and examples of the sequential skills that can be observed when coteachers are effective. The categories include (a) professionalism (demeanor toward each other and the students); (b) classroom management (rules, behavioral accommodations, shared responsibility); (c) instructional process (group and individual instruction, sharing both content and strategy teaching, etc.); (d) learning groups (variety, heterogeneity emphasized, multiple approaches to coteaching); and (e) student progress (elicits/reinforces active responses, both teachers accessed by all students, shared evaluation and grading of student work). The quality indicators can be rated as present or absent when directly observing coteacher lessons. Observers are cautioned to be aware that not all of the indicators are explicitly observable during a lesson. Some indicators may be embedded in overall routines and procedures that had been established prior to the observation. Thus, it is important to ask coteachers to describe their perceptions of their implementation of the quality indicators through an open-ended survey. Finally, Magiera and Simmons provide a protocol to guide participants when they debrief and reflect on the information gathered through observations.
Handwriting fluency in kindergarten: exploring the issue of time

Curriculum-based measures (CBM) are necessary for educators to quickly assess student skill levels and monitor progress. This study examined the use of the alphabet fluency task, a CBM of writing which assesses how well children access, retrieve, and write letter forms automatically. The alphabet fluency task was administered at both the beginning and end of the kindergarten school year. Scores were collected at two time points, 15 seconds and 60 seconds. Alphabet fluency scores at both points were compared to criterion measures of writing—standardized writing assessments and compositional CBM of writing. Results indicate that although measures at both 15 and 60 seconds are valid, measures at 60 seconds are more valid in assessing handwriting fluency of kindergarten students at both the beginning and end of kindergarten. Future applications of this task and further areas of study are discussed.
Automated analysis of discrete event simulations using event pattern mappings

Event patterns are a language construct for expressing relationships between specifications made at different levels of a hierarchical design of a concurrent system. This presentation (1) explains the use of event patterns in defining mappings between different levels of a design hierarchy, (2) defines a language for specifying event pattern mappings, and (3) shows how mappings can be used in debugging discrete event simulations. The concurrent system specification language used in this research is VHDL. VAL+ is an annotation language for VHDL, geared toward the specification of event pattern mappings. VAL+ features are its simplicity, its ability to define mappings as well as design constraints, its ability to report both pattern occurrences and incorrect ordering relationships in a simulation, and a semantics suitable for efficient implementation. The VAL+ mapping construct defines the relationship between one event at a (high) level of abstraction and a pattern of events at a (lower) level. To investigate the application of event pattern mappings, a debugger has been implemented and used in analyzing gate level simulations. Using mappings specified in VAL+, the debugger extracts, from a VHDL gate level simulation, simulations at the register transfer level and the instruction level. The higher the simulation level, the smaller the number of events. The mapping definitions help the designer trace a missing event at the instruction level down to one or more missing events at the register transfer level, and similarly from the register transfer level to the gate level. This method allows for fast bug detection and pinpointing.
Complex Networks and Extractive Summarization

Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization strategies. In this work we employ concepts and metrics of complex networks to select sentences for an extractive summary. The graph or network representing one piece of text consists of nodes corresponding to sentences, while edges connect sentences that share common meaningful nouns. Because various metrics could be used, we developed a set of 14 summarizers, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores. An additional summarizer was created which selects the highest ranked sentences in the 14 systems, as in a voting system. When applied to a corpus of Brazilian Portuguese texts, some CN-Summ versions performed better than summarizers that do not employ deep linguistic knowledge, with results comparable to state-of-the-art summarizers based on expensive linguistic resources. The use of complex networks to represent texts appears therefore as suitable for automatic summarization, consistent with the belief that the metrics of such networks may capture important text features.
Focus on Form in Classroom Second Language Acquisition. The Cambridge Applied Linguistics Series.

1 Introduction I THEORETICAL FOUNDATIONS OF FOCUS ON FORM 2 Focus on form: Theory research and practice 3 Focus on form through conscious reflection 4 Beyond focus on form II FOCUS ON FORM IN THE CLASSROOM 5 Getting the learners' attention 6 Communicative focus on form 7 FonF: What kind of focus and on which forms? 8 The role of form-focused tasks in promoting the second language acquisition of children in grade 2 9 The importance of timing in focus on form 10 Pedagogical choices in focus on form
Gender and small business growth in Tanzania: the role of habitus

In de gehele wereld stijgt het aantal bedrijven dat gerund wordt door vrouwelijke ondernemers. Toch blijven dat vaak (erg) kleine bedrijven. In haar geboorteland Tanzania onderzocht promovendus Hawa Tundui welke rol ‘habitus’ speelt om genderverschillen in de groei van kleine ondernemingen te verklaren: de wijze waarop men de wereld percipieert en de wijze waarop men aspiraties en ambities ontwikkelt. Habitus is gebaseerd op de kennis en vaardigheden die mensen hebben verworven toen ze jong waren. De sociale omgeving en rolmodellen hebben grote invloed bij de vormgeving van de groei-aspiraties van ondernemers. Dit gegeven is belangrijk voor het ontwikkelen van beleid door overheid en organisaties van het bedrijfsleven. Trainingen, workshops, (in)formele scholing en het lidmaatschap van netwerkorganisaties kunnen de succesvolle, niet-succesvolle of startende ondernemer helpen haar of zijn vaardigheden te verbeteren. Het onderzoek laat zien dat onderwijs van belang is voor groei-aspiraties van de onderneming. Hoe hoger het niveau van het genoten onderwijs, des te hoger deze aspiraties.
Enhancing the Writing Skills of Students with Learning Disabilities through Technology: An Investigation of the Effects of Text Entry Tools, Editing Tools, and Speech Synthesis. Final Report.

This final report discusses the outcomes of a 3-year project that studied the effectiveness of word processing tools in improving the literacy skills of students with learning disabilities in grades 4-12. In Year 1 (1994-95), four text entry strategies were compared in 132 students with learning disabilities: keyboarding instruction, alternative keyboards, word prediction, and word prediction with speech synthesizers. The Year 2 study (1995-96), investigated the effects of two types of text editing tools, such as spelling and grammar aids with and without speech synthesis, in 106 students with learning disabilities. The Year 3 study (1996-97), investigated speech synthesis under three conditions in 103 students with learning disabilities: when available at all times versus when available only during the text entry or the editing/revising stages of writing. Results of the studies found: (1) that word processing had the most impact upon the accuracy of students' writing; (2) word prediction was the most promising strategy for improving the text entry speed; (3) spell checks were effective editing tools, although grammar checkers were not, and spell checks had a more positive effect on students' writing quality and accuracy than synthesized speech. (Contains 35 references.) (CR) ******************************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ********************************************************************************
Spatio-temporal models of the functional architecture of the visual cortex

In this work I tried to explore many aspects of cognitive visual science, each one based on different academic fields, proposing mathematical models capable to reproduce both neuro-physiological and phenomenological results that were described in the recent literature. The structure of my thesis is mainly composed of three chapters, corresponding to the three main areas of research on which I focused my work. The results of each work put the basis for the following, and their ensemble form an homogeneous and large-scale survey on the spatio-temporal properties of the architecture of the visual cortex of mammals.
A reasoning framework for dependability in software architectures

The degree to which a software system possesses specified levels of software quality attributes, such as performance and modifiability, often have more influence on the success and failure of those systems than the functional requirements. One method of improving the level of a software quality that a product possesses is to reason about the structure of the software architecture in terms of how well the structure supports the quality. This is accomplished by reasoning through software quality attribute scenarios while designing the software architecture of the system. As society relies more heavily on software systems, the dependability of those systems becomes critical. In this study, a framework for reasoning about the dependability of a software system is presented. Dependability is a multi-faceted software quality attribute that encompasses reliability, availability, confidentiality, integrity, maintainability and safety. This makes dependability more complex to reason about than other quality attributes. The goal of this reasoning framework is to help software architects build dependable software systems by using quantitative and qualitative techniques to reason about dependability in software architectures.
The Problem and Its Solutions

An abutment assembly for an internal shoe drum brake, particularly a vehicle wheel brake, comprising a pair of opposed abutment members for engagement with respective ends of the brake shoes and an arrangement for transmitting only part of the input force applied to one abutment member, to the other abutment member. The arrangement comprises a plurality of individual force-transmitting members each pivotally supported between and engaging the said one abutment member and an output member coupled to the other abutment member.
Combining Web Usage and Content Mining for More Effective Personalization

Three common approaches to server-directed automatic Web personalization have been collaborative filtering, content-based filtering, and manual decision rule systems. Recent proposals have suggested Web usage mining as an enabling mechanism to overcome the problems associated with these more traditional techniques. These problems include, for example, the reliance on subjective user ratings or static profiles, and the inability of techniques based on content similarity to capture a richer set of semantic relationships among objects (i.e., pages or products). Yet, usagebased personalization can be problematic when little usage data is available pertaining to some objects or when the site content changes regularly. For more effective personalization, both usage and content attributes of a site must be integrated into a Web mining framework and used by the recommendation engine in a uniform manner. In this paper we present such a framework, distinguishing between the offline tasks of data preparation and mining, and the online process of customizing Web pages based on a user's active session. We describe effective techniques based on clustering to obtain a uniform representation for both site usage and site content profiles. We then show how these profiles can be combined with an active user session to perform real-time personalization.