Miracle-dz/UniFAR-FTUs huggingface dataset:
TEACHING LISTENING COMPREHENSION ON DIALOGUE USING INFORMATION TRANSFER TECHNIQUE

Abstract: The aim of this research was to investigate the effectiveness of teaching technique called information transfer technique in teaching listening comprehension on dialogue to Year-7 students of SMP Negeri 2 Mempawah Hilir in Academic Year 2012/2013. It was a pre-experimental study in one group pretest posttest design . The data were collected by using audio file with the written test in form of table, total of the test items were 8 and then analyzed by using ES (Effect Size) formula. The sample was VIIA class that consisted of 36 students. The finding showed that the effect size of treatment was 0.89 (ES > 0.80) and categorized as high with the mean score of the students’ 74.65. This mean score after the teaching (post-test) increased if compared with the mean score before the teaching (pre-test) 61.45. The difference score between pre-test and post-test was 13.20. Key words: Information Transfer, Listening Comprehension. Abstrak: Penelitian ini bertujuan untuk menyelidiki keefektifan dari penggunaan teknik pengajaran yang disebut Information Transfer, dalam pemahaman menyimak dialog terhadap siswa-siswi kelas VII SMP Negeri 2 Mempawah Hilir tahun ajaran 2012/2013. Penelitian ini menggunakan pre-eksperimen studi dengan disain satu grup pre-test post-test. Data penelitian didapatkan dengan menggunakan audio file besertakan tes tertulis dalam bentuk tabel, dengan jumlah soal 8 dan kemudian dianalisa dengan menggunakan rumus ES (tingkat efektifitas). Sampel penelitian diambil dari 1 kelas (VIIA) yang terdiri dari 36 siswa. Hasil penelitian menunjukan bahwa ukuran keefektifan dari perlakuan adalah 0.89 (ES>0.80) dan dikategorikan tinggi dengan nilai rata-rata siswa 74.65. Nilai rata-rata setelah pengajaran (post-test) tersebut menunjukkan perubahan yang meningkat jika dibandingkan dengan nilai rata-rata siswa sebelum pengajaran (pre-test) 61.45. Perbedaan nilai yang ditunjukkan antara nilai pre-test dan post-test adalah 13.20. Kata kunci: Transfer Informasi, Pemahaman Menyimak .
SAM: SEQUENCE ALIGNMENT AND MODELING SOFTWARE SYSTEM

The Sequence Alignment and Modeling system (SAM) is a collection of flexible software tools for creating, refining, and using linear hidden Markov models for biological sequence analysis. The model states can be viewed as representing the sequence of columns in a multiple sequence alignment, with provisions for arbitrary position-dependent insertions and deletions in each sequence. The models are trained on a family of protein or nucleic acid sequences using an expectation-maximization algorithm and a variety of algorithmic heuristics. A trained model can then be used to both generate multiple alignments and search databases for new members of the family. SAM is written in the C programming language for Unix machines and MasPar parallel computers, and includes extensive documentation. The algorithms and methods used by SAM have been described in several pioneering papers from the University of California, Santa Cruz. These papers, as well as the SAM software suite, are available via anonymous ftp to ftp.cse. ucsc.edu in the pub/protein directory, or via the World-Wide Web to http://www.cse. ucsc.edu/research/compbio/.
Algorithms for Sequential Decision Making

Sequential decision making is a fundamental task faced by any intelligent agent in an extended interaction with its environment; it is the act of answering the question ``What should I do now? '''' In this thesis, I show how to answer this question when ``now'''' is one of a finite set of states, ``do'''' is one of a finite set of actions, ``should'''' is maximize a long-run measure of reward, and ``I'''' is an automated planning or learning system (agent). In particular, I collect basic results concerning methods for finding optimal (or near-optimal) behavior in several different kinds of model environments: Markov decision processes, in which the agent always knows its state; partially observable Markov decision processes (POMDPs), in which the agent must piece together its state on the basis of observations it makes; and Markov games, in which the agent is in direct competition with an opponent. The thesis is written from a computer-science perspective, meaning that many mathematical details are not discussed, and descriptions of algorithms and the complexity of problems are emphasized. New results include an improved algorithm for solving POMDPs exactly over finite horizons, a method for learning minimax-optimal policies for Markov games, a pseudopolynomial bound for policy iteration, and a complete complexity theory for finding zero-reward POMDP policies.
The soar papers : research on integrated intelligence

Soar is a computational theory of the mind that has had an impact in both artificial intelligence and cognitive science. Begun by John E. Laird, Allen Newell, and Paul S. Rosenbloom at Carnegie Mellon in the early 1980s, the Soar Project is an investigation into the architecture underlying intelligent behaviour with the goal of developing and applying a unified theory of natural and artificial intelligence. "The Soar Papers" - sixty-three article in all - provide in one place the important ideas that have emerged from this project. The book is organized chronologically, with an introduction that provides multiple organizations according to major topics. Readers interested in the entire effort can read the articles in publication order, while readers interested only in a specific topic can go directly to a logical sequence of papers to read on that topic.
Tidying up Mineral Names: an IMA-CNMNC Scheme for Suffixes, Hyphens and Diacritical marks

INTRODUCTION In 2004, Peter Bayliss successfully proposed (IMA 04-C) to change the two-word mineral name cesium kupletskite to kupletskite-(Cs). In October 2005, Bayliss submitted a proposal to the Commission on New Minerals and Mineral Names (CNMMN) to eliminate the space in all similar two-word cases. This proposal was forwarded to the members for comments, but was not voted on because the CNMMN chairman and vice-chairman were of the opinion that a more generalized correction exercise was needed. Bayliss then revised his proposal into a wider discussion paper (March 2006) on suffix and prefix nomenclature, which was made available to the members on the occasion of the IMA meeting in Kobe, July 2006. It was decided in Kobe that the Chairman of the newly merged Commission on New Minerals, Nomenclature and Classification (CNMNC) would take up the issue for further discussion. The efforts of Bayliss coincided indeed with the experiences of the Chairman during the operation to clean up the GQN* minerals (Burke, 2006): on going through the list of mineral names it was evident that mineralogical nomenclature has not always been applied in a consistent way. Many names have been given to minerals before the CNMMN started to draft any rules for nomenclature, and later such rules have regularly been ignored, even by the CNMMN itself. The present paper aims to give a view on suffix nomenclature versus prefix nomenclature, to list mineral names with correct diacritical marks, and to correct mineral names consisting of two words or having superfluous hyphens and diacritical marks. The names and the name changes given in this paper have been approved by the CNMNC (proposal IMA 07-C, September 2007). Names written in bold in this paper were approved by the CNMNC to be correctly spelled names.
Introduction to research in education

Become a more competent consumer and producer of research with INTRODUCTION TO RESEARCH IN EDUCATION with InfoTrac! Known for its exceptionally clear writing style and comprehensive coverage, this education text helps you master the basic competencies necessary to understand and evaluate the research of others. The authors familiarize you with common research problems in a step-by-step manner through examples that clarify complex concepts and strong end-of-chapter exercises. This text is a must read for anyone planning to conduct their own research or interpret the research of others.
Using Clickers to Support Information Literacy Skills Development and Instruction in First-Year Business Students

Course-integrated information literacy (IL) instruction can be enhanced via the use of student response devices, or 'clickers'. The first phase of this study focused on how first-year undergraduate students perceived the use of clickers as a mechanism to encourage active learning and engagement in order to establish a baseline of information seeking behaviour and to actively engage students in the learning process. Data collected within IL classes and subsequent surveys of student perceptions are examined with discussion on the implications for future practice and research. Our findings from this first phase of this study through the quantitative data collected with clickers indicate that first year business students have shortcomings in information literacy and can improve their information literacy skills in relation to research and assignment work in their formal assessment. Furthermore the use of clickers are positively viewed by undergraduate students and postgraduate students as a technology which can facilitate active learning and engagement if used appropriately with clearly aligned learning objectives.
Redressing the Gender Imbalance in ICT Professions: Toward State-Level Strategic Approaches

This paper reports preliminary work in an ARC Linkage Project involving collaboration among James Cook Universtiy, Education Queensland, and Technology One (a Queensland based company). The project aims to identify and interpret factors associated with low female participation rates in Information and Communications Technology (ICT) professional level occupations and education pathways. Data is being collected using qualitative and quantitative methods. A survey is being administered to over 6000 year 11 and 12 female high school students in Queensland to provide a comprehensive database that will be augmented with individual and focus group interviews. An online survey will be administered to women working in ICT industries. Reference groups representing EQ and ICT industries have been established to provide consultative advice and feedback throughout the project, and to function as working groups during the data analysis and interpretation phases. Project results will inform the development of strategic response options for education systems and ICT idustries and suggest further research and industry-based initiatives designed to enhance female participation rates.
An entropy-based reliability assessment technique for intelligent machines

A new method for measuring the performance of intelligent robot systems is presented. The method utilizes entropy, a concept borrowed from informaton theory, to provide a unified technique for measuring the performance of various combinations of control and sensing algorithms available in an intelligent machine in response to a given task specification. It can be shown that the entropy of a system can be decomposed into two independent terms, i.e., a term associated with the system state description, and a term associated with the task specification. It can be shown that the total system entropy is directly analogous to the reliability of the system. A review of entropy methods in reliability analysis is presented, and the derivation of the proposed reliability assessment technique is shown. The method is demonstrated in a case study. <<ETX>>
Implementation and prevention of unstable optimal compensators

Optimal control design methods frequently lead to unstable compensators, even for stable plants. These compensators present possible implementation difficulties because they are conditionally stable. If unstable compensation is not inherently required for performance, then a stable compensator is preferable. The reasons why unstable compensators arise within the linear quadratic Gaussian framework are discussed. Examples and experimental results from the Middeck Active Control Experiment (MACE) are used to illustrate the implementation difficulties associated with unstable compensators. Several approaches to designing stable compensators are compared.
Successful SAP R/3 Implementation: Practical Management of ERP Projects

From the Publisher: With the rapid growth in popularity of Enterprise Resource Planning software packages, such as SAP R/3, Baan & PeopleSoft, an increasing number of companies are making the decision to transfer to such systems. The implementation of an ERP package is an enormously complex task requiring specific project management skills and knowledge, a lack of which often leads to projects failing to meet deadlines and stay within budget. Anyone involved in the implementation of an ERP project will find this book essential reading. The authors provide readers with the knowledge and tools to help them avoid the problems and pitfalls which commonly occur during the implementation management process. Using a composite example case study of a large SAP R/3 implementation, it presents a wealth of practical advice, essential factors for successful project management and many practical tools which can be readily applied to any project to ensure success.
Probabilistic dynamic security assessment of power systems-I: Basic model

A comprehensive framework for power system security assessment which incorporates probabilistic aspects of disturbances and system dynamic responses to disturbances is presented. Standard mathematical models for power system (steady-state) power flow analysis and transient stability (dynamic) analysis are used. A linear vector differential equation is derived whose solution gives the probability distribution of the time to insecurity. The coefficients of the differential equation contain the transition rates of system structural changes and a set of transition probabilities defined in terms of the steady-state and the dynamic security regions. These regions are defined in the space of power injections. Upper and lower bounds on the time to insecurity distribution are obtained.
Die Gleichnisse Jesu

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Optimal Speckle Reduction In Polarimetric Sar Imagery*

Speckle is a major cause of degradation in synthetic aperture radar (SAR) imagery. With the availability of fully polarimetric, high-resolu tion SAR data, it is possible to use the three complex elements (HH, HV, VV) of the polarimetric scattering matrix to reduce this speckle. The optimal method of combining the elements of the scattering matrix to minimize image speckle is derived; the solution is shown to be a polari- metric whitening filter (PWF). Also, a simulation of spatially correlated, K-distributed, fully polarimetric clutter is developed and is used to compare the optimal speckle reduction method with other, suboptimal methods. Finally, the target detection performance of span, single-channel|HH|/sup 2/ data, and the PWF are compared with the optimal polarimetric detector (OPD).
A study measuring the effectiveness of outreach work, as a means of increasing public library use and social inclusion in order to meet Public Service Agreement targets

In April 2002,Warrington Borough Council entered into a three year Local Public Service Agreement aimed at improving public services throughout the Borough.Warrington Library, Museum and Archives' involvement was to increase the number of issues, visitors and newly registered members to libraries in six socially deprived wards - creating the outreach post of Service Development Officer to carry forward strategic plans. At the end of the agreement, an evaluative case study was undertaken to measure the effectiveness of outreach work as a means of increasing public library use and social inclusion by using methodological triangulation. The findings confirmed the success of meeting the targets and support for the Service Development Officer post which has been permanently mainstreamed by Warrington Library, Museum and Archives Service and contributed to the development of a model to measure future projects.
Text Mining Using Data Compression Models

The idea of using data compression algorithms for machine learning has been reinvented many times. Intuitively, compact representations of data are possible only if statistical regularities exist in the data. Compression algorithms identify such patterns and build statistical models to describe them. This ability to learn patterns from data makes compression methods instantly attractive for machine learning purposes. In this thesis, we propose several novel text mining applications of data compression algorithms. We introduce a compression-based method for instance selection, capable of extracting a diverse subset of documents that are representative of a larger document collection. The quality of the sample is measured by how well a compression model, trained from the subset, is able to predict held-out reference data. The method is useful for initializing k-means clustering, and as a pool-based active learning strategy for supervised training of text classifiers. When using compression models for classification, we propose that trained models should be sequentially adapted when evaluating the probability of the classified document. We justify this approach in terms of the minimum description length principle, and show that adaptation improves performance for online filtering of email spam. Our research contributes to the state-of-the-art of applied machine learning in two significant application domains. We propose the use of compression models for spam filtering, and show that compression-based filters are superior to traditional tokenization-based filters and competitive with the best known methods for this task. We also consider the use of compression models for lexical stress assignment, a problem in Slovenian speech synthesis, and demonstrate that compression models perform well on this task, while requiring fewer resources than competing methods. The topic of this thesis is text mining. However, most of the proposed methods are more general, and are designed for learning with arbitrary discrete sequences.
The force of the argument

In reply to Wiklund (2009), this paper addresses once again embedded V2 clauses in Scandinavian: the behaviour of certain discourse oriented elements in these clauses, the possibility of topicalising embedded V2 clauses, and the optionality of embedded V2. The conclusion is that the analysis according to which embedded V2 clauses have illocutionary force can still be maintained.
Computational principles of single neuron adaptation

Cortical neurons continuously transform sets of incoming spike trains into output spike trains. This input-output transformation is referred to as single-neuron computation and constitutes one of the most fundamental process in the brain. A deep understanding of single-neuron dynamics is therefore required to study how neural circuits support complex behaviors such as sensory perception, learning and memory. The results presented in this thesis focus on single-neuron computation. In particular, I address the question of how and why cortical neurons adapt their coding strategies to the statistical properties of their inputs. A new spiking model and a new fitting procedure are introduced that enable reliable nonparametric feature extraction from in vitro intracellular recordings. By applying this method to a new set of data from L5 pyramidal neurons, I found that cortical neurons adapt their firing rate over multiple timescales, ranging from tens of milliseconds to tens of second. This behavior results from two cellular processes, which are triggered by the emission of individual action potentials and decay according to a power-law. An analysis performed on in vivo intracellular recordings further indicates that power-law adaptation is near-optimally tuned to efficiently encode natural inputs received by single neurons in biologically relevant situations. These results shade light on the functional role of spike-frequency adaptation in the cortex. The second part of this thesis focuses on the long-standing question of whether cortical neurons act as temporal integrators or coincidence detectors. According to standard theories relying on simplified spiking models, cortical neurons are expected to feature both coding strategies, depending on the statistical properties of their inputs. A model-based analysis performed on a second set of in vitro recordings demonstrates that the spike initiation dynamics implements a complex form of adaptation to make cortical neurons act as coincidence detectors, regardless of the input statistics. This result indicates that cortical neurons are well-suited to support a temporal code in which the relevant information is carried by the precise timing of spikes. The spiking model introduced in this thesis was not designed to study a particular aspect of single-neuron computation and achieves good performances in predicting the spiking activity of different neuronal types. The proposed method for parameter estimation is efficient and only requires a limited amount of data. If applied on large datasets, the mathematical framework presented in this thesis could therefore lead to automated high-throughput single-neuron characterization.
Women in Community College: Factors Related to Intentions to Pursue Computer Science

Community colleges (CC) are obvious places to recruit more women into computer science. Enrollment at CCs has grown in response to a struggling economy, and students are more likely to be from underrepresented groups than students enrolled in 4-year universities (National Center for Education Statistics, 2008). However, we know little about why so few go on to study computing and information sciences (CIS) at 4-year universities. This study was designed to test three widely held beliefs about recruiting and retaining women in CIS majors by focusing on women who have expressed interest in computer science. Data were collected from 191 female students enrolled in an introduction to programming class at one of 15 community colleges in California. Results show that women with high intention of pursuing CIS were more avid computer users in their teens and currently play more video games. They also have a positive view of computer programming and place greater value on computing, related to an interest in solving challenging problems and financial motives, rather than an interest in using computing for the social good. Support from others, such as family, friends, and teachers, was not related to intention. The authors discuss how the results can inform strategies to increase the number of women who transfer from community colleges to 4-year universities in CIS fields.