Miracle-dz/UniFAR-FTUs huggingface dataset:
VP-Fronting in Czech and Polish—A Case Study in Corpus-Oriented Grammar Research

Fronting of an infinite VP across a finite main verb—akin to German “VP-topicalization”—can be found also in Czech and Polish. The paper discusses evidence from large corpora for this process and some of its properties, both syntactic and information-structural. Based on this case, criteria for more user-friedly searching and retrieval of corpus data in syntactic research are being developed.
Data mining via distributed genetic programming agents

Genetic programming is a powerful search method which can be applied to the typical data mining task of nding hidden relations in datasets. We describe the architecture of a distributed data mining system in which genetic programming agents create a large amount of structurally di erent models which are stored in a model database. A search engine for models that is connected to this database allows interactive exploration and analysis of models, and composition of simple models to hierarchic models. The search engine is the crucial component of the system in the sense that it supports knowledge discovery and paves the way for the goal of nding interesting hidden causal relations.
Influence of mathematics curriculum implementation strategies on nature of instructional tasks, classroom discourse, and student learning

This study presents a comparative case study of curriculum implementation strategies of four teachers in two school districts, the influence of teachers’ decision making on the nature of instructional tasks, and the learning environment that emanates from the two settings. The aim of the study is to gain insight into the relationships among curriculum implementation strategy, instructional tasks, and the teacher-student interaction that characterizes the classroom discourse in these settings. The results integrate research on curriculum implementation strategies, instructional tasks, and classroom discourse. This study suggests that students have a better opportunity to learn in classroom environments where teachers use standards-based curriculum materials.
POLA ASUH ORANG TUA DALAMMENGEMBANGKAN KREATIVITAS ANAK(Studi di Desa Gondoriyo, Kec. Bergas, Kab. Semarang)

Penelitian ini dilatarbelakangi oleh setiap anak memiliki bakat kreatif, namun setiap anak tentu memiliki kreativitas yang berbeda. Pola asuh orang tua yang diterapkan dalam keluarga tentunya akan berpengaruh terhadap pengembangan kreativitas anak. Kreativitas anak dapat berkembang dengan optimal, apabila orang tua dapat memberikan dorongan dan motivasi agar anak percaya diri dan mampu mengembangkan bakat yang dimiliki. Tujuan penelitian ini adalah : (1) mendeskripsikan tentang pola asuh yang diterapkan orang tua dalam mengembangkan kreativitas anak dan (2) mendeskripsikan tentang faktor-faktor yang menghambat dan mendukung perkembangan kreativitas anak. Pendekatan dalam penelitian ini menggunakan pendekatan kualitatif. Teknik pengumpulan data yang dilakukan adalah observasi, dokumentasi, dan wawancara. Sumber data penelitian adalah sumber data primer yang diambil secara langsung dalam penelitian lapangan dimana subjek penelitian terdiri dari 3 keluarga (orang tua) dan 3 orang anak sebagai informan. Teknik keabsahan data menggunakan triangulasi sumber. Teknil analisi data dalam penelitian menggunakan : (1) pengumpulan data, (2) reduksi data, (3) penyajian data, dan (4) penarikan kesimpulan. Hasil yang diperoleh dalam penelitian ini adalah pola asuh yang diterapkan oleh 3 keluarga berbeda-beda dalam mengembangkan kreativitas anak, hal ini dipengaruhi oleh tingkat usia anak. Keluarga Bapak S yang bekerja sebagai buruh pabrik menerapkan pola asuh otoriter, sedangkan keluarga Bapak JMC yang bekerja sebagai buruh pabrik dan keluarga Bapak R yang bekerja sebagai penjual jamu menerapkan pola asuh demokratis dalam mengembangkan kreativitas anak. Faktor-faktor yang menghambat dalam mengembangkan kreativitas anak yaitu aturan yang terlalu ketat, pemberian hadiah yang berlebihan, keterpaduan waktu dan peralatan bermain yang terstruktur, sedangkan faktor-faktor yang mendukung dalam mengembangkan kreativitas anak yaitu kebebasan, nilai bukan aturan, menghargai kreativitas anak, memberikan dukungan, dan memberikan fasilitas sesuai dengan kebutuhan. Berdasarkan hasil penelitian dapat disimpulakn bahwa pola asuh yang diterapkan orang tua tidak selamanya otoriter maupun demokratis. Dalam hal mendidik anak, orang tua harus pintar memposisikan pola asuh mana yang perlu diterapkan kepada anaknya. Selain itu, orang tua juga memberikan kebebasan anak dan tidak membatasi eksplorasi maupun rasa keingintahuan anak misalnya bermain dengan teman, atau bertanya hal-hal baru agar daya kreatif anak yang terpendam dapat muncul. Oleh karena itu orang tua hendaknya berperan aktif dalam mendukung dan memotivasi kegiatan anak.
Protocol and real-time scheduling issues for multimedia applications

PROTOCOL AND REAL-TIME SCHEDULING ISSUES FOR MULTIMEDIA APPLICATIONS September 1994 Sridhar Pingali, B.Tech., Indian Institute of Technology M.S., Clemson University Ph.D., University of Massachusetts Amherst Directed by: Professor James F. Kurose The growth of higher bandwidth networks and powerful new workstations has enabled the development of many new multimedia applications. These applications involve the combined use of di erent media such as voice, video and text. Supporting these applications requires the resolution of a number of issues both within the network and at the end-hosts that originate the applications. In this dissertation we consider real-time scheduling and protocol problems that arise in this arena. In the realm of applications operating under hard time-constraints, we address both network-node and workstation scheduling. In applications involving the use of video or a combination of voice and video, there can be the need to schedule classes of tra c with di ering importance but identical deadlines at a network-node. We examine scheduling algorithms that can be used in the situation of two classes of tra c. We demonstrate using probabilistic arguments that a new \balancing" discipline can provide better loss performance for both classes than more traditional schemes in some operating regions. When delay loss probabilities are low, strict priority scheduling is shown to be a reasonable option. Turning our attention to the end-hosts, we consider the need to process multimedia objects such as voice packets in a periodic fashion within a workstation, and study vi two common scheduling algorithms earliest deadline rst (ED) and rate monotonic (RM). Recent studies have revealed the importance of the preemption behavior of the scheduler in determining overall processor performance. We prove that there are always fewer preemptions under ED than under RM and show through simulations of well-known task-sets that, on occasion, there can be over 20% more preemptions under RM than under ED. Apart from these scheduling problems, we also look at protocol issues that combine network and host considerations. For applications such as world-wide multimedia lectures, it becomes important to have error-recovery protocols that will scale well to hundreds of receivers. We perform throughput analyses and demonstrate why receiver-initiated protocols based on negative acknowledgements are to be preferred over sender-initiated protocols based on positive acknowledgments. We focus on host processing costs to illustrate this result. vii TABLE OF CONTENTS Page Acknowledgements : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : v Abstract : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : vi List Of Tables : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : x List Of Figures : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : xi CHAPTER
Efficient transactional memory runtimes for unmanaged environments

The adoption of multi-core processors requires programmers to use concurrent programming to fully benefit from the available processing power. Efficient concurrent programming using locks is notoriously difficult to master. This makes the case for alternative concurrent programming paradigms. One of the most promising of these paradigms is Transactional Memory, which uses optimistic execution of code via the concept of transactions. In this thesis, we propose to improve the support and performance of transactional memory for unmanaged environment, at all levels of the system software and hardware stack. First, we improve the performance of software transactional memory by developing LSA, an algorithm based on a virtual clock to ensure transaction consistency. In this context, we propose several optimizations for efficiency and develop features that will favor the uptake and usability of transactional memory for application developers. Next, we extend our Transactional Memory library to leverage the availability of hardware mechanisms that can support the execution of transactions. We show that Hardware Transactional Memory can deliver a high performance compared to software-only approaches but suffers from several limitations. Our Hybrid Transactional Memory, extending on our LSA algorithm, combines the advantages of hardware and software transactional memory to achieve a performance close to pure hardware transactional memory while overcoming its limitations. Finally, we describe the integration of transactional memory in a complete system stack. We describe the standardization of the C/C++ language transactional constructs and the binary interface for transactional memory runtimes. We extend our Transactional Memory library to follow these specifications and make it compliant with two transactional compilers, including GCC. The resulting framework provides developers with an easy and efficient way to create applications that can take advantage of multi-core processors.
Applications of Machine Learning

This paper introduces the Zillow's Home Value Prediction Challenge and YouTube-8M Video Understanding Challenge hosted as Kaggle competitions and also describes my approach to experimenting with various models. For each of my experiments, I provide the score result as well as possible improvements to be made. Towards the end of the paper, I discuss the various ensemble learning techniques that I applied on the dataset which significantly boosted my overall competition score. Finally, I discuss the exciting future of video understanding research and also the many applications that such research could significantly improve.
A PARTITIONING SCHEME FOR HIERARCHICAL PATH FINDING ROBUST TO LINK COST UPDATE

Path guidance has been identified as a primary requirement of ITS. The key to it is the real-time capability to find a minimum cost path over a large-scale dynamic road graph. For efficient path fending, hierarchical methods, which use a precomputed hierarchical graph to reduce search space, have been investigated recently. However, hierarchical methods consume significant processing time to propagate link cost update from the leaf of a hierarchical graph to the root of it. To avoid this propagation, this paper proposes a partitioning scheme that isolates dynamic links from static ones. This scheme is a tradeoff between update cost and path finding time. This tradeoff is viable if a large portion of a graph is static. This condition holds for typical real-world road maps, where real-time traffic information is collected only for major roads. For the covering abstract see IRRD E102946.
Robotics for archaeology: in quest of the Grotta dei Cervi

The search for an underground cave of utter historical importance is performed with the aid of an autonomous robot. This autonomy is reached through the self localisation deriving from the fusion of data incoming from the robot odometry, a GPS system and a magnetic compass. The system carries a ground penetrating radar to spot underground cavities. The found underground voids have been geo-referenced and have helped in the correct localization of the cave.
MACSIS: A Scalable Acoustic Index for Content-Based Music Retrieval

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Research questions and methodological issues

This chapter provides an overview of current learning technology research and demonstrates how it has emerged as a new field over the past decade. It will consider the cognate disciplines which feed into the area and the ways in which they inform it, as well as considering how these provide rich multiple perspectives but also give rise to inherent tensions due to differences in values and language. Current research activities are categorised, along with illustrative research questions. An outline of the research methods used to investigate these questions is given, along with an overview of the methodological issues which arise. The chapter reflects on how the area has developed over the past decade and concludes with some thoughts on future research directions. It describes the different dimensions of learning technology in terms of the both the pedagogical and technical aspects and also the impact of technologies on both individual tutors and learners and on organisational structures.
A machine learning-based approach to predicting success of questions on social question-answering

While social question-answering (SQA) services are becoming increasingly popular, there is often an issue of unsatisfactory or missing information for a question posed by an information seeker. This study creates a model to predict question failure, or a question that does not receive an answer, within the social Q&A site Yahoo! Answers. To do so, observed shared characteristics of failed questions were translated into empirical features, both textual and non-textual in nature, and measured using machine extraction methods. A classifier was then trained using these features and tested on a data set of 400 questions—half of them successful, half not—to determine the accuracy of the classifier in identifying failed questions. The results show the substantial ability of the approach to correctly identify the likelihood of success or failure of a question, resulting in a promising tool to automatically identify ill-formed questions and/or questions that are likely to fail and make suggestions on how to revise them.
A Secure Zone-Based Routing Protocol for Mobile Ad Hoc Networks

In this thesis, we proposed a secure hybrid ad hoc routing protocol, called Secure Zone Routing Protocol (SZRP), which aims at addressing the above limitations by combining the best properties of both proactive and reactive approaches. The proposed protocol is based on the concept zone routing protocol (ZRP). It employs an integrated approach of digital signature and both the symmetric and asymmetric key encryption techniques to achieve the security goals like message integrity, data confidentiality and end to end authentication at IP layer. The thesis details the design of the proposed protocol and analyses its robustness in the presence of multiple possible security attacks that involves impersonation, modification, fabrication and replay of packets caused either by an external advisory or an internal compromised node within the network. The security and performance evaluation of SZRP through simulation indicates that the proposed scheme successfully defeats all the identified threats and achieves a good security at the cost of acceptable overhead. Together with existing approaches for securing the physical and MAC layer within the network protocol stack, the Secure Zone Routing Protocol (SZRP) can provide a foundation for the secure operation of an ad hoc network.
Transparent Cryptographic File System for BSD. A primer

This document is a “quick and dirty” introduction to installation and usage of the Transparent Cryptographic File System (TCFS), for 4.4BSD systems. This guide refers to the preliminary version released for OpenBSD 2.6 and NetBSD 1.4 on April 17, 2000.
Statistical language modelling of dialogue material in the British national corpus

Statistical language modelling may not only be used to uncover the patterns which underlie the composition of utterances and texts, but also to build practical language processing technology. Contemporary language applications in automatic speech recognition, sentence interpretation and even machine translation exploit statistical models of language. Spoken dialogue systems, where a human user interacts with a machine via a speech interface in order to get information, make bookings, complaints, etc., are example of such systems which are now technologically feasible. The majority of statistical language modelling studies to date have concentrated on written text material (or read versions thereof). However, it is well-known that dialogue is significantly different from written text in its lexical content and sentence structure. Furthermore, there are expected to be significant logical, thematic and lexical connections between successive turns within a dialogue, but "turns" are not generally meaningful in written text. There is therefore a need for statistical language modeling studies to be performed on dialogue, particularly with a longer-term aim to using such models in human-machine dialogue interfaces. In this thesis, I describe the studies I have carried out on statistically modelling the dialogue material within the British National Corpus (BNC) - a very large corpus of modern British English compiled during the 1990s. This thesis presents a general introductory survey of the field of automatic speech recognition. This is followed by a general introduction to some standard techniques of statistical language modelling which will be employed later in the thesis. The structure of dialogue is discussed using some perspectives from linguistic theory, and reviews some previous approaches (not necessarily statistical) to modelling dialogue. Then a qualitative description is given of the BNC and the dialogue data within it, together with some descriptive statistics relating to it and results from constructing simple trigram language models for both dialogue and text data. The main part of the thesis describes experiments on the application of statistical language models based on word caches, word "trigger" pairs, and turn clustering to the dialogue data. Several different approaches are used for each type of model. An analysis of the strengths and weaknesses of these techniques is then presented. The results of the experiments lead to a better understanding of how statistical language modelling might be applied to dialogue for the benefit of future language technologies.
Tailored tagger: A personalized, adaptive music tagging system

We present an adaptive music tagging system, the Tailored Tagger, which allows users to tag their music collections by mood and tracks the user’s tagging behavior. This allows the Tailored Tagger to alter the mood classification to classify songs in the same way that the user would, resulting in a personalized mood recommendation system. To accomplish this personalization, SVMs are retrained to correspond with the way the user tags. The result is a set of SVM classifiers that are unique to each individual.
An implementation of prolog

In what case do you like reading so much? What about the type of the implementation of prolog book? The needs to read? Well, everybody has their own reason why should read some books. Mostly, it will relate to their necessity to get knowledge from the book and want to read just to get entertainment. Novels, story book, and other entertaining books become so popular this day. Besides, the scientific books will also be the best reason to choose, especially for the students, teachers, doctors, businessman, and other professions who are fond of reading.
Algorithms for Grid Graphs in the MapReduce Model

The MapReduce programming paradigm has seen widespread use in analyzing large data sets. Often these large data sets can be formulated as graphs. Many algorithms, such as filtering based algorithms, are designed to work efficiently for dense graphs-graphs with substantially more number of edges than the number of vertices. These algorithms are not optimized for sparse graphs-graphs where the number of edges is of the same order as the number of vertices. However, sparse graphs are also common in big data sets. In this thesis we present algorithms for maximal matching, approximate edge covering, and approximate maximum weighted matching problems over grid graphs, a natural class of sparse graphs-graphs where the vertices and edges lie on a two dimensional integer grid. These algorithms take advantage of the inherent structure of grid graphs, thus making them more efficient than the known algorithms. In addition, in the case of maximum weighted matching, the algorithm presented gives a better approximation ratio than previous MapReduce algorithms.
A processing model for temporal analysis and its application to plan recognition

Temporal analysis is the process of extracting through linguistic analysis the temporal relations between the states and events mentioned in a discourse. We generally call these states and events "situations. " One main contribution in this thesis is to present a processing model for the temporal analysis of a restricted class of discourse referred to as simple narratives. Our model for temporal analysis considers the effects of tense and aspect. For tense interpretation, we present detailed rules for interpreting tense, suggest heuristics for capturing coherent tense sequences, and design a processing algorithm for determining the temporal ordering between the situations mentioned in a discourse. For aspect determination, we clearly distinguish various views of a situation, i.e., the parts of the situation described by utterances, and further present a procedure for determining the view of a situation from linguistic analysis. Tense and aspect together help decide temporal relations between situations treated as a whole. Although temporal relations have been used for plan recognition, there are no algorithms for extracting these relations from plan-based input. We apply our model for temporal analysis to plan-based input and work out a simpler and more accurate algorithm for extracting the temporal relations between the actions in a plan. We use the extracted temporal relations from temporal analysis as constraints to improve the results of plan recognition. We also use the prestored temporal constraints in the plans of the system's plan library to assist in temporal analysis. The interaction between extracted constraints and prestored constraints can be formulated as the temporal reasoning problem. We find that previous algorithms for temporal reasoning give weak results when applied to plan recognition, specifically for the case where some actions and defined in terms of their decomposed subactions. We then provide a strengthened procedure, which closes the temporal constraints between an action and its decomposed subactions. The model for temporal analysis is further defended through experiments with naturally occurring examples, and the contributions in the special case of plan-based input are made clearer by comparison to the previous work in that area.