Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature selection by iterative reweighting: an exploration of algorithms for linear models and random forests

In many areas of machine learning and data science, the available data are represented as vectors of feature values. Some of these features are useful for prediction, but others are spurious or redundant. Feature selection is commonly used to determine the utility of a feature. Typically, features are selected in an all-or-none fashion for inclusion in a model. We describe an alternative approach that has received little attention in the literature: determining the relative importance of features via continuous weights, and performing multiple iterations of model training to iteratively reweight features such that the least useful features eventually obtain a weight of zero. We explore feature selection by employing iterative reweighting for two classes of popular machine learning models: L1 penalized linear models and Random Forests. Recent studies have shown that incorporating importance weights into L1 models leads to improvement in predictive performance in a single iteration of training. In Chapter 3, we advance the state-of-the-art by developing an alternative method for estimating feature importance based on subsampling. Extending the approach to multiple iterations of training, employing the importance weights from iteration n to bias the training on iteration n + 1 seems promising, but past studies yielded no benefit to iterative reweighting. In Chapter 4, we obtain a significant reduction of 7.48% in the error rate over standard L1 penalized algorithms, and nearly as large an improvement over alternative feature selection algorithms such as Adaptive Lasso, Bootstrap Lasso, and MSA-LASSO using our improved estimates of feature importance. In Chapter 5, we consider iterative reweighting in the context of Random Forests and contrast this with a more standard backward-elimination technique that involves training models with the full complement of features and iteratively removing the least important feature. In parallel with this contrast, we also compare several measures of importance, including our own proposal based on evaluating models constructed with and without each candidate feature. We show that our importance measure yields both higher accuracy and greater sparsity than importance measures obtained without retraining models (including measures proposed by Breiman and Strobl), though at a greater computational cost.
Thermotherapy sanitation of two grapevine cultivars.

E-mail: kominek@vurv.cz; fax: +420-233311592. Abbreviations: GLRaV-1 = grapevine leafroll-associated virus 1; ArMV = arabis mosaic virus; GFLV = grapevine fanleaf virus; GFkV = grapevine fleck virus; RSPaV = rupestris stem pittingassociated virus Two grapevine cultivars Müller-Thurgau and Portugieser Blau were selected for a thermotherapy at the onset of sanitation program in Czech Republic. These cultivars represent tradition and a good quality in wine making. Currently, the area in Czech Republic planted with Müller-Thurgau and Portugieser Blau is 1975.7 and 676 ha, respectively. From these cultivars we selected 5 promising clones that produced stable yields and a good quality wine. Examination of the 5 clones for the presence of viral infections revealed the presence of grapevine leafroll-associated virus 1 (GLRaV-1), arabis mosaic virus (ArMV), grapevine fanleaf virus (GFLV), grapevine fleck virus (GFkV), and rupestris stem pittingassociated virus (RSPaV). All tests were done using RT-PCR. The primers for ArMV and GFLV were used according to our previous work (3), and primers for GLRaV-1, GFkV, and RSPaV were used according to our study on multiple virus infection (4). Cuttings taken from the mother plants were used for growing of new plantlets. After proper rooting and growing of the new shoots in pods, the new plants were placed in a climate chamber for thermotherapy that was conducted for 45 days at 37°C. The light conditions were 16/8 hours day/ night. This procedure resulted in the onset of a new growth from the axillar buds. This effect usually called rejuvenation created a good chance for the initiation of propagation in vitro. Topical and axillar meristematic tissues were taken from the new shoots and cultivated in vitro. The optimal composition of cultivation medium differed for the cultivars tested. Müller-Thurgau grew best on C2D medium (1), while Portugieser Blau preferred modified WPM medium (6). Both media contained 20 g/l sucrose. Agar (Duchefa) concentration was 6 g/l (pH = 5.6). After cultivation of the explants, the new plantlets were separated, rooted, and cultivated in a greenhouse at non-sterile conditions. The surviving plants were tested by RT-PCR for the presence of viruses detected before sanitation. After thermotherapy, the examination of plants was repeated annually for 3 years (Table 1). Only one plant of each cultivar was found to be free of all viruses after the thermotherapy: one Müller-Thurgau cultivar, clone MT 26/19, and one Portugieser Blau cultivar, clone PM 11/48. As indicated in Table 1, the effectiveness of virus removal by thermotherapy was low. RSPaV was especially resistant to the thermotherapy procedure. Problems with the removal of RSPaV during the sanitation procedure were reported earlier (2, 5). RSPaV is a phloem-associated virus and such viruses are often resistant to the thermotherapy procedure (7). On the other hand, nepoviruses such as the GFLV and ArMV were relatively successfully removed. In summary, our study documented the relatively low efficiency of thermotherapy in the sanitation of grapevine infected with several viruses.
An Improved Outer Bound for Multisource Multisink Network Coding

The Max-flow Min-cut bound is a fundamental result in the theory of communication networks, which characterizes the optimal throughput for a point-to-point communication network. The recent work of Ahlswede et al [1] extended it to the single-source multisink multicast networks and Li et al [2] proved that it can be achieved by linear codes. Following this line, Erez, Feder [3] and Ngai, Yeung [4] both proved that the Max-flow Min-cut bound remains tight in the single-source twosink non-multicast networks. But the Max-flow Min-cut bound is in general quite loose [5]. In this work we prove an improved outer bound, named network sharing bound, for a special class of networks, the three-layer networks. We further show that the network sharing bound implies that the coding among messages from different sources has no benefit if the goal is to minimize the total needed bandwidth.
Determining the significance of associations between two series of discrete events : bootstrap methods /

We review and develop techniques to determine associations between series of discrete events. The bootstrap, a nonparametric statistical method, allows the determination of the significance of associations with minimal assumptions about the underlying processes. We find the key requirement for this method: one of the series must be widely spaced in time to guarantee the theoretical applicability of the bootstrap. If this condition is met, the calculated significance passes a reasonableness test. We conclude with some potential future extensions and caveats on the applicability of these methods. The techniques presented have been implemented in a Python-based software toolkit.
Teaching Vocabulary Through Data-Driven Learning

Teaching Vocabulary Through Data-driven Learning Erin M. Shaw Department of Linguistics and English Language, BYU Master of Arts The purpose of this master's project was to write a resource book that demonstrates how teachers can use data-driven learning methods to teach vocabulary. First, a brief overview of corpus linguistics, data-driven learning, and the corpus used in this book (COCA) is given. Then, the book presents different aspects of vocabulary learning in the context of a corpus. Topics included are frequency knowledge, part of speech knowledge, morphological knowledge, synonym knowledge, collocational knowledge, and register knowledge with a chapter on each topic. For each aspect of vocabulary learning there is a section that introduces the topic to the teacher, followed by instructions on performing topic related searches in the corpus. Each chapter also includes examples and ideas for application to the vocabulary classroom. Additional chapters provide information on individual language learning, and an evaluation of the project. The goal of this project was to provide teachers with specific knowledge of vocabulary and corpus-linguistics to be able to teach less-frequently addressed aspects of vocabulary instruction and to encourage more use of corpora in the language classroom. It is hoped that after reading this book, teachers will be able to improve their vocabulary teaching and ability to use the Corpus of Contemporary American English and DDL methods in the ESL/EFL classroom. The evaluation of this project will consist of teacher reviews of the book after reading. Specifically, the questionnaire addresses readers' feelings of increased knowledge and understanding of these areas and desire to use them in the classroom.
Can regadenoson pharmacologic SPECT be performed effectively in patients with left bundle branch block or paced rhythm patients? A retrospective comparison to adenosine SPECT

Purpose: Regadenoson (REG) is currently becoming the stress agent of choice in patients undergoing pharmacologic single photon emission computed tomography (SPECT). However, in patients with left bundle branch block (LBBB) and ventricular paced rhythm (VPR), hesitation exists amongst clinicians to use REG-SPECT due to the concern that the increased heart rate could cause false positive SPECT results. We sought to evaluate the comparability of A-SPECT and REG-SPECT in patients with LBBB and VPR. Methods: Retrospective study of 30 patients who served as their own controls. All 30 patients who underwent REG-SPECT (Grp 1) were compared to their prior A-SPECT (Grp 2) done within two years prior to REG-SPECT. Heart rate (HR) and blood pressure (BP) parameters, ECG, stress perfusion and gated variables, SPECT ischemia, and side-effects were evaluated. Statistical significance was set at P could be found between the two groups among SPECT parameters. Muscle pain was significantly higher in REG (10.0% vs. 0.0%, P = 0.083) and so was the use of aminophylline (16.7% vs. 0.0%, P = 0.025) to relieve the side-effect. Conclusion: REG-SPECT can be administered in patients with LBBB and VPR patients based on favorable and comparable hemodynamic responses and arrhythmia occurrences to A-SPECT. REG-SPECT can also be used for adequate interpretation of presence or absence of SPECT ischemia particularly in the LAD territory without any concern for false positive perfusion defects.
Communication by Engineers: A Literature Review of Engineers' Information Needs, Seeking Processes, and Use.

Library Resources, Inc., Washington, Library Resources, 1400 16th Street, N.W. , Washington, DC 20036-2217 ($25 MF01/PC09 Plus Postage. Annotated Bibliographies; Communication (Thought Transfer); *Engineers; *Information Needs; *Information Seeking; Literature Reviews; Research and Development; Research Reports; *Scientific and Technical Information; *Scientists There have been hundreds, perhaps thousands, of studies involving scientific and technical information communication performed over the last 25 years. This review attempts to provide a window to these studies for persons interested in studying the results published in technical reports and the formal literature. This review primarily deals with the information-seeking needs and behavior of engineers and, to a lesser degree, scientists or those said to be generally engaged in research and development. The principal focus in on primary communications through interpersonal means and through information found in documents such as books, journal articles, technical reports, etc. Less attention is paid here to the use of secondary services and products Bich as printed bibliographic indexes and automated bibliographic databases; numeric databases; intermediary organizations such as libraries, information clearinghouses, and information analysis centers (IACs); and technologies used by engineers for communication purpose. The review covers research reported from 1970 forward, although some exceptions are made, particularly when earlier studies begin a sustained series of studies or when they serve as precedents for other subsequent studies. Section 2 provides a brief overview and summary observations concerning: scientific and technical information (STI) communication research approaches and models; STI communication; communication through primary STI media; interpersonal STI communication; STI communication through secondary media and databases; use of libraries, IACs, and clearinghouses; and state-of-the-art literature reviews of engineers' information needs, information-seeking processes, and information use. Section 3 discusses some distinctions made in the literature between engineers' and scientists' information needs, information-seeking processes, and information use. Several extensive and continuous STI communication research efforts are discussed in section 4, including general research themes, brief descriptions of research methods used, and some significant findings. The research review, section 5, consists of a numbered list of 456 references, given in alphabetical order by author. An annotated bibliography of many of the references follows in section 6. A subject index and author index are also provided in section 7. (MAS)
Using WSD Techniques for Lexical Selection in Statistical Machine Translation

Abstract : In current state of the art statistical MT systems, word choice in the target language is governed implicitly by a combination of "phrase" selection and language modeling. In contrast, the state of the art in word sense disambiguation takes advantage of a wide array of features, both locally and at the document level. This technical report describes our initial efforts to employ the power of WSD techniques in helping to guide a state of the art statistical MT system toward better word choices. We briefly discuss the principles underlying our approach as contrasted with another recent attempt to integrate WSD with statistical MT (Carpuat and Wu, 2005) that yielded negative results. We then describe our approach, which leads to a small improvement in translation performance over a state of the art phrase-based statistical MT system. Qualitative analysis of translation output suggests there are still significant opportunities to improve performance further.
The Impact of Information Processing on the Rating of Speeches

This paper takes a look at how information competency, information processing, and receiver apprehension, affect rating behavior when rating speeches. The paper is broken down into two studies. The first study looks at information competency, which is measured by the Information Competency Assessment Instrument, and how it affects rating behavior. The second study looks at information processing, which is broken down into three scales based on the Inventory of Learning Processes then each is analyzed based on rating behavior, and receiver apprehension which is measured using the Receiver Apprehension Test and how these two concepts affect rating behavior. Students were given surveys to measure information competency, information processing, and receiver apprehension and also asked to evaluate speeches. A negative correlation between receiver apprehension and information processing was found along with support for the idea that information competency and information processing have an affect on rating behavior. Information Processing 3
Memory systems for parallel programming

Distributed Shared-Memory (DSM) computers, which partition physical memory among a collection of workstation-like computing nodes, are emerging as the way to implement parallel computers, as they promise scalability and high performance. Shared-memory DSM machines use a coherence protocol to manage the replication of data and to ensure that a parallel program sees a consistent view of memory. Applications have very different patterns of communication and no single, general-purpose protocol suits all programs. This has prompted interest in systems in which a protocol is implemented in flexible software instead of being fixed in hardware. DSM machines with software-implemented coherence protocols provide opportunities for a variety of more complex and application-specific protocols and allow for protocols that do not just ensure consistent memory, but also provide new functionality and semantics. Parallel programming has long faced a tension between the goals of high performance and ease of use. Languages and tools can make parallel computers easier to use, but concerns about their efficiency have limited their usage. This thesis demonstrates that some high-level languages and tools can be implemented more efficiently by taking advantage of the cache coherence protocols that underly software DSM machines, thereby improving both performance and ease of use. This thesis describes a family of custom protocols that efficiently implement a large-grain data-parallel language C$\sp{**}$. On programs for which static analysis is imprecise, these Loosely Coherent Memory (LCM) protocols improve performance from a few percent up to a factor of 3, and reduce memory overheads from a factor of 2 to a factor of 5 over a compiler-copying scheme. LCM also improves performance in C-code programs by up to a factor of 3. This thesis also presents custom cache-coherence protocols that perform on-the-fly detection of actual data races for programs with barrier synchronization. Overheads in execution time for the race-detection protocols were shown to range from zero to less than a factor of three--a significant improvement over comparable approaches--and race-detection protocols found actual program errors in two applications.
Supervised Learning in Dynamic Bayesian Networks

Dynamic Bayesian networks (DBNs) are powerful tools for unsupervised discovery of structure in time series, using generative learning algorithms such as expectation maximization (EM). While in many problems, the DBN latent variables are the primary quantities of interest for estimation purposes, unsupervised learning is often a way to perform automatic feature learning for a downstream supervised task, such as time series classification and sequential labeling. We show that the DBNs model structure allow for combination of the two aforementioned objectives using backpropagation. Our proposed architecture is motivated by the problem of nonstationary multivariate time series classification and sequential labeling. We derive supervised learning algorithms for parameter estimation and inference of latent variables in two commonly used DBN models for such time series, namely the switching vector autoregressive (SVAR) model and the switching Kalman filter (SKF). The result of our procedure can be interpreted as a compactly-parameterized recurrent neural network, which can be pre-trained using EM. Using examples from three nonstationary neurophysiological time series cohorts, we show how discriminatively-discovered dynamics in time series lead to a significant improvement in classification performance over methods based on feature learning via EM, as well as other commonly used time series classifiers.
Nineveh, Babylon and the Hanging Gardens: cuneiform and classical sources reconciled

Classical sources describing the Hanging Gardens give a wealth of detail which has never matched up with information from cuneiform sources or archaeological finds. This study reconciles them. In doing so it shows how some confusions in Classical accounts may have their origin in Akkadian sources, and are not due simply to misunderstanding and error. The Hanging Gardens of Babylon, one of the Seven Wonders of the world in Classical tradition, were marvellous not merely for being raised upon vaults, but also for an innovative system for watering them. Popularly attributed to Nebuchadnezzar II, of the 6th century B.C., they are not mentioned in any of the copious and remarkably complete written sources for that king's reign, nor have they come to light in extensive excavation of his palaces in Babylon, carried out by a large German team over more than a quarter of a century.
The Productive Tension: Mechanisms vs. Templates in Modeling the Phenomena

We argue that there is a tension present in the modeling practice between the aim of capturing the specific mechanisms underlying the phenomena and the use of general cross-disciplinary computational templates to study them. To illuminate this tension we examine the Lotka-Volterra model, which has provided a powerful template for population biology and other areas of research. We will compare the respective approaches of Alfred Lotka and Vito Volterra. What makes this comparison especially interesting is that although they ended up presenting models that from the formal point of view looked identical – and were subsequently treated like that – they nevertheless followed different kinds of modeling strategies.
PEMANFAATAN KULIT BUAH NAGA MERAH (Hylocereus polyrhizus.) SEBAGAI BAHAN TAMBAHAN DALAM PEMBUATAN ES KRIM

This study was red dragon fruit peel can be used as natural dyes. The purpose of to get the best formulations of red dragon fruit peel ice cream by physical properties, fiber and organoleptic test. This research used a completely randomized design (CRD) with four treatments and four replications. The treatment in this study are E 0 (without the addition peel of red dragon fruit), E 1 (addition of 2% red dragon fruit peel), E 2 (addition of 4% red dragon fruit peel), and E 3 (addition of 6% red dragon fruit peel). Data obtained were treated by analysis of variance followed by Duncan New Multiple Range Test (DNMRT) the level of 5%. The results showed that the addition of red dragon fruit peel had significant effect on the overrun , ice cream melting time, fiber content, hedonic of texture, colour, overall acceptance and descriptive of texture, color and flavor. The addition of red dragon fruit peel had not significant effect on hedonic of taste, flavor and descriptive sensory. The best formulation this study is addition of 6% red dragon fruit peel. Keywords : R ed dragon fruit peel , natural dyes , ice cream .
Principles and procedures of statistics: a biometrical approach (2nd ed)

Observations probability sampling from a normal distribution comparisons involving two sample means principles of experimental design analysis of variance I - the one-way classification mutiple comparisons analysis of variance II - multiway classification linear regression linear correlation matrix notation linear regression in matrix notation multiple and partial regression and correlation analysis of variance III - factorial experiments analysis of variance analysis of covariance IV analysis of covariance analysis of variance V - unequal subclass numbers some uses of chi-square enumeration data I - one-way classifications enumeration data II - contingency tables categorical models some discrete distributions nonparametric statistics sampling finite populations.