Miracle-dz/UniFAR-FTUs huggingface dataset:
Special Issue on Technology of Networked Control Systems

This special issue provides information on current and future research directions in the emerging field of networked control systems. The first paper provides a comprehensive overview of the field. The remaining 11 papers are organized in three sections: a section on the "current state of the technology of networked control systems"; a section on foundations of networked real-time systems"; and a section on "wireless networks - the backbone of networked control systems. " Each of the papers is briefly discussed.
Effective compile-time analysis for data prefetching in java

The memory hierarchy in modern architectures continues to be a major performance bottleneck. Many existing techniques for improving memory performance focus on Fortran and C programs, but memory latency is also a barrier to achieving high performance in object-oriented languages. Existing software techniques are inadequate for exposing optimization opportunities in object-oriented programs. One key problem is the use of high-level programming abstractions which make analysis difficult. Another challenge is that programmers use a variety of data structures, including arrays and linked structures, so optimizations must work on a broad range of programs. We develop a new unified data-flow analysis for identifying accesses to arrays and linked structures, called recurrence analysis. Prior approaches that identify these access patterns are ad hoc, or treat arrays and linked structures independently. The data-flow analysis is intra- and inter-procedural, which is important in Java programs that use encapsulation to hide implementation details. We show Java programs that traverse arrays and linked structure have poor memory performance. We use compiler-inserted data prefetching to improve memory performance in these types of programs. The goal of prefetching is to hide latency by bringing data into the cache prior to a program's use of the data. We use our recurrence analysis to identify prefetching opportunities in Java programs. We develop a new algorithm for prefetching arrays, and we evaluate several methods for prefetching objects in linked structures. Since garbage collection is an integral part of Java, we evaluate the impact of a copying garbage collector on prefetching. We demonstrate how to improve the memory performance of the collector itself by using prefetching. This dissertation shows that a unified whole-program compiler analysis is effective in discovering prefetching opportunities in Java programs that traverse arrays and linked structures. Compiler-inserted data prefetching improves the memory performance even in the presence of object-oriented features that complicate analysis.
Teaching Academic Content and Literacy to English Learners in Elementary and Middle School. IES Practice Guide. NCEE 2014-4012.

The Institute of Education Sciences (IES) publishes practice guides in education to bring the best available evidence and expertise to bear on current challenges in education. Authors of practice guides combine their expertise with the available findings of rigorous research to develop specific recommendations for addressing these challenges. The authors rate the strength of the research evidence supporting each of their recommendations. See Appendix A for a full description of practice guides. The goal of this practice guide is to offer educators specific, evidence-based recommendations that address the challenge of teaching English learners in the elementary and middle grades: building their English language proficiency while simultaneously building literacy, numeracy skills, and content knowledge of social studies and science. The guide provides practical and coherent information on critical topics related to literacy instruction for English learners, and is based on the best available evidence as judged by the authors.
Adaptive predictive coding of speech by means of volterra predictors

In this paper a waveform coder configuration based on non linear adaptive prediction will be described. The coder is based on the characteristic of Volterra predictors to model non linear phenomena and to gather informations about the periodicity of the signal via high order statistical moments. The main result is that, by using this type of predictor, lower variance error signals can be obtained, as compared to the classical, linear, case.
Cirurgia virtual da laringe

The present study presents a computational method designed to assist phonologists to anticipate the effects produced in the voice, as a result of physical and mechanical alterations of the larynx model, due to a surgery to correct dysphonia. The main objective of the study was to use the active contours method to develop a larynx model based on vocal fold and glottis movements. The technique is based on images obtained from endoscopic exams of the larynx. Starting with the recorded voice signal of subject, we filter the characteristics of the glottal pulse obtained from the image exam, assuming that the dysphonia is caused by irregularities of the larynx. The modifications made in the glottis model are used to estimate a new glottal filter, which is then added to the filtered signal. Using this method, one can obtain a new voice that maintains the individual’s personal characteristics after virtual surgery modifications.
CMOS Data Converters for Communications

CMOS Data Converters for Communications distinguishes itself from other data converter books by emphasizing system-related aspects of the design and frequency-domain measures. It explains in detail how to derive data converter requirements for a given communication system (baseband, passband, and multi-carrier systems). The authors also review CMOS data converter architectures and discuss their suitability for communications. The rest of the book is dedicated to high-performance CMOS data converter architecture and circuit design. Pipelined ADCs, parallel ADCs with an improved passive sampling technique, and oversampling ADCs are the focus for ADC architectures, while current-steering DAC modeling and implementation are the focus for DAC architectures. The principles of the switched-current and the switched-capacitor techniques are reviewed and their applications to crucial functional blocks such as multiplying DACs and integrators are detailed. The book outlines the design of the basic building blocks such as operational amplifiers, comparators, and reference generators with emphasis on the practical aspects. To operate analog circuits at a reduced supply voltage, special circuit techniques are needed. Low-voltage techniques are also discussed in this book. CMOS Data Converters for Communications can be used as a reference book by analog circuit designers to understand the data converter requirements for communication applications. It can also be used by telecommunication system designers to understand the difficulties of certain performance requirements on data converters. It is also an excellent resource to prepare analog students for the new challenges ahead.
Sosyal Bilgiler Öğretmen Adaylarının Sözlü Tarih Çalışmalarına Yönelik Tutumları

Bu calismanin amaci, Sosyal Bilgiler ogretmen adaylarinin sozlu tarih calismalarina yonelik tutumlarini cesitli degiskenlere gore belirlemektir. Arastirmanin orneklemini Kastamonu Universitesi, Bulent Ecevit Universitesi ve Gazi Universitesi Sosyal Bilgiler Ogretmenligi ana bilim dallarinda ogrenim goren 585 ogretmen adayi olusturmaktadir. Arastirmanin sonuclarina gore katilimcilarin sozlu tarih calismalarina yonelik tutumlari; cinsiyet, sinif duzeyi, lisans egitimleri boyunca derslerinde sozlu tarih calismasi yapma durumu, lisans egitimine baslamadan once yasanilan yer, tarihi roman, hikâye, hatirat okuma sayisi ve sozlu tarih calismasi icin medya araclarina (TV, Internet, radyo, gazete) gunluk ayrilan zaman degiskenlerine gore anlamli farklilik gostermezken, aile fertlerinden sozlu tarih yoluyla gecmise dair tarih bilgisi edinme durumu, lisans egitimleri suresince derslerinde sozlu tarih calismasi yapilma durumu ve sozlu tarih calismalarina merak duzeyi degiskenlerine gore anlamli farklilik gostermistir. Anahtar Sozcukler: Sosyal bilgiler, ogretmen adayi, sozlu tarih, tutum
Why Is Discourse Coherent

Abstract : When people produce a discourse, what needs are they responding to when they make it coherent, and what form does this coherence take? In this paper, it is argued that coherence can be characterized in terms of a set of `? coherence relations% between segments of a discourse. It is shown, from an abstract description of the discourse situation, that these relations correspond to the kinds of communicative work that needs to get done in discourse. In particular, four requirements for successful communication are isolated: the message itself must be conveyed; the message must be related to the goals of the discourse; what is new and unpredictable in the message must be related to what the listener already knows; and the speaker must guide the listener's inference processes toward the full intended meaning of the message. Corresponding to each requirement is a class of coherence relations that help the speaker satisfy the requirements. The coherence relations in each class are discussed and defined formally. Finally, a fragment of a conversation is analyzed in detail to illustrate the problems that face a speaker in trying to satisfy these requirements, and to demonstrate the role that the coherence relations play in the solution.
Activity, Context, Interaction, and Authority

Situated learning theories offer useful insights into how learning to write can be supported and transacted through interactions between newcomers and experienced practitioners in academic and professional domains. Reporting the findings from a study of a mentoring relationship in physics, this article addresses how such processes work to teach composing in advanced academic contexts and what can make them more or less effective. The author identifies and discusses three factors that may constrain situated learning in such contexts and the transmission of authority that purportedly occurs through such learning. These factors include newcomers' existing skills for, and approaches to, composing, which may limit their acquisition and use of new skills; the implicitness of situated learning, which may pose difficulties for newcomers as they struggle to grasp the conceptual complexity entailed in composing disciplinary texts; and the location and distribution of authority in practitioner/newcomer relationships, which may inhibit newcomers as they struggle to acquire and establish their own authority by making original contributions to their fields.
Statistical inference of causal and ordinary differential equation models

Netwerken komen voort uit het modelleren van complexe systemen in verschillende gebieden van de wetenschap. Analyseren van de structuur van een netwerk helpt ons om deze complexe systemen beter te begrijpen en er bruikbare informatie uit te halen. Een belangrijk probleem in netwerk-analyse is het modelleren van het onderliggende genererende mechanisme van een netwerk gebaseerd op datastructuren en het vervolgens vaststellen van het karakter van afhankelijkheid. Het is een uitdaging om oorzakelijke verbanden af te leiden tussen knopen van waargenomen data of een mix van waargenomen data en experimentele data, met name op het gebied van grafisch causaal modelleren. Bijvoorbeeld het begrijpen van de structuur van biologische netwerken en het ontrafelen van netwerken van gen-interacties van onderliggende complexe menselijke fenotypes is een grote uitdaging in de systeembiologie. Een van de interessante onderwerpen na het construeren van een netwerk is het ontdekken van de dynamica van zo’n netwerk. Een veel gebruikte klasse van modellen voor de dynamica van netwerken wordt gevormd door de gewone differentiaalvergeli- jkingen. In dit proefschrift dragen we bij aan de methodologie om de schatting van oorzakelijk netwerken en dynamische systemen te verbeteren.
Implementation and simulation of a fractal modulation communication system

Recent work has suggested the possibility of using homogenous signals, which can be conveniently represented in terms of orthonormal wavelet basis sets, as the modulating waveforms in communications systems. In order to research the performance of this "fractal modulation", we have developed a simulator and a high-level implementation of a complete transceiver, comprising: transmitter, channel, receiver, and data generation and verification components. Simulation results of this implementation matches the theoretical performance for fractal modulation over a channel with additive white Gaussian noise. <<ETX>>
Historical Change in Serial Verb Constructions

This work examines both historical and comparative evidence in documenting the sweep of diachronic change in the context of serial verb constructions. Using a wide range of data from languages of West Africa, Asia and the Caribbean, it demonstrates how shifts in meaning and usage result in syntactic, morphological and lexical change.The process by which verbs lose lexical semantic content and develop case-marking functions is described; it is argued that the change is directional, from verb to preposition (or postposition) to affix, along a grammaticalization continuum. This same grammaticalization process is shown to result in the development of complementizers, adverbial subordinators, conjunctions, adverbs and auxiliaries from verbs. Strong parallels across languages are found in the meanings of the verbs that become “defective” and in the functions they come to mark. The changes are documented in detail, with examples from a number of languages illustrating the effect of the changes on typology and word order, implications for the encoding of definiteness and aspect, and the relevance of notions such as discourse topic, foreground and transitivity.With respect to theoretical assumptions and terminology, the author has taken a relatively nonpartisan approach, and the discussion is accessible to students of language as well as of interest to theoreticians.
Sepia : semantic parsing for named entities

People's names, dates, locations, organizations, and various numeric expressions, collectivelv called Named Entities, are used to convey specific meanings to humans in the same way that identifiers and constants convey meaning to a computer language interpreter. Natural Language Question Answering can benefit from understanding the meaning of these expressions because answers in a text are often phrased differently from questions and from each other. For example, "9/11" might mean the same as "September 11th" and "Mayor Rudy Giuliani" might be the same person as "Rudolph Giuliani". Sepia, the system presented here, uses a lexicon of lambda expressions and a mildly context-sensitive parser ri ireateA data structure fe ehch' named entity. The parser and grammar design are inspired by Combinatory Categorial Grammar. The data structures are designed to capture semantic dependencies using common syntactic forms. Sepia differs from other natural language parsers in that it does not use a pipeline architecture. As yet there is no statistical component in the architecture. To evaluate Sepia, I use examples tp illustrate its qualitative differences from other named entity systems, I measure component perforrmance on Automatic Content Extraction (ACE) competition held-out training data. and I assess end-to-end performance in the Infolab's TREC-12 Question Answering competition entry. Sepia will compete in the ACE Entity Detection and Tracking track at the end of September. Thesis Supervisor: Boris Katz Title: Principal Research Scientist
Investigating learners’ meta-representational competencies when constructing bar graphs

Current views in the teaching and learning of data handling suggest that learners should create graphs of data they collect themselves and not just use textbook data. It is presumed real-world data creates an ideal environment for learners to tap from their pool of stored knowledge and demonstrate their meta-representational competences. Although prior knowledge is acknowledged as a critical resource out of which expertise is constructed, empirical evidence shows that new levels of mathematical thinking do not always build logically and consistently on previous experience. This suggests that researchers should analyse this resource in more detail in order to understand where prior knowledge could be supportive and where it could be problematic in the process of learning. This article analyses Grade 11 learners’meta-representational competences when constructing bar graphs. The basic premise was that by examining the process of graph construction and how learners respond to a variety of stages thereof, it was possible to create a description of a graphical frame or a knowledge representation structure that was stored in the learner’s memory. Errors could then be described and explained in terms of the inadequacies of the frame, that is: ‘Is the learner making good use of the stored prior knowledge? ’ A total of 43 learners were observed over a week in a classroom environment whilst they attempted to draw graphs for data they had collected for a mathematics project. Four units of analysis are used to focus on how learners created a frequency table, axes, bars and the overall representativeness of the graph vis-a-vis the data. Results show that learners had an inadequate graphical frame as they drew a graph that had elements of a value bar graph, distribution bar graph and a histogram all representing the same data set. This inability to distinguish between these graphs and the types of data they represent implies that learners were likely to face difficulties with measures of centre and variability which are interpreted differently across these three graphs but are foundational in all statistical thinking.
„I am proud of my language, but I speak it less and less!“

This paper investigates what speakers of Texas German, a critically endangered dialect spoken for more than 150 years, think about their dialect and how this influences their linguistic choices. Based on data collected by the Texas German Dialect Project (www.tgdp.org), we discuss the attitudes that Texas German speakers have towards their dialect, their identity, and the on-going changes in their speech community. We show that almost all Texas German speakers are proud of their history, culture, and dialect, but that even though they identify as Texas Germans, they are in the process of switching to English as a result of socio-political and economic developments. Our results demonstrate that the survival of heritage languages is problematic even in cases in which the overwhelming majority of speakers have a positive image of their language.
Analisis Butir Soal Matematika Pada Instrumen Uji Coba Materi Segitiga

Penelitian ini bertujuan pada upaya untuk mengetahui kualitas butir soal matematika pada materi segitiga. Metode yang digunakan dalam penelitian ini adalah deskriptif kuantitatif. Pengumpulan data dilakukan dengan metode pengumpulan data lapangan . Pembuatan aplikasi berdasarkan analisis hasil dari metode statistik yaitu analisis respon butir. e? a Hasil dari penelitian ini adalah informasi berupa validitas soal, reliabilitas soal, evaluasi daya pembeda, dan tingkat kesukaran soal. Hasil analisis menunjukkan bahwa kualitas butir soal dari tingkat validitas soal, yang valid sebesar 70% dan tidak valid sebesar 30%. Dari tingkat reliabilitas soal dengan taraf signifikansi 5% soal dinyatakan reliabel. Berdasarkan tingkat kesukaran soal? e? a 60% berada pada kategori mudah, 30% berada pada kategori sedang, dan 10% berada pada kategori sukar. Daya beda soal menunjukkan 50% soal dikategorikan baik dan50% dengan kategori cukup. Berdasarkan hasil analisis data, dapat disimpulkan? e? a bahwa kualitas soal memiliki validitas dan reliabilitas yang tinggi, sedangkan dari tingkat kesukaran tergolong mudah dan daya bedanya tergolong cukup.
Exploiting Structure for Sentiment Classification

This thesis studies the problem of sentiment classification at both the document and sentence level using statistical learning methods. In particular, we develop computational models that capture useful structure-based intuitions for solving each task, treating the intuitions as latent representations to be discovered and exploited during learning. For document-level sentiment classification, we exploit structure in the form of informative sentences—those sentences that exhibit the same sentiment as the document, thus explain or support the document’s sentiment label. We first show that incorporating automatically discovered informative sentences in the form of additional constraints for the learner improves performance on the document-level sentiment classification task. Next, we explore joint structured models for this task: our final proposed model does not need sentence-level sentiment labels, and directly optimizes document classification accuracy using inferred sentence-level information. Our empirical evaluation on two publicly available datasets shows improved performance over strong baselines. For phrase-level sentiment classification, we investigate the compositional linguistic structure of phrases. We investigate compositional matrix-space models, learning matrix-space word representations and modeling composition as matrix multiplication. Using a publicly available dataset, we show that the matrix-space model outperforms the standard bag-of-words model for the phrase-level sentiment classification task.
Comparing innovation styles profile of IS personnel to other occupations

W.C. Miller's Innovation Style Profile instrument was used to collect data from IS (information systems) personnel to compare the innovation styles of IS personnel to those in other occupations. Analysis of the results revealed significant differences. Knowledge of these differences should enable teams composed of IS personnel and user personnel not only to better tolerate their differences but also to better appreciate the value of multiple approaches to innovation. <<ETX>>
An exploration of the effect of super large n-tuples on single layer RAMnets

N-tuple recognition systems (RAMnets) are normally modeled using a small number of input lines to each RAM, because the address space grows exponentially with the number of inputs. It is impossible to implement an arbitrarily-large address space as physical memory. But given modest amounts of training data, correspondingly modest numbers of bits will be set in that memory. Hash arrays can therefore be used instead of a direct implementation of the required address space. This paper describes some exploratory experiments using the hash array technique to investigate the performance of RAMnets with very large numbers of input lines. An argument is presented which concludes that performance should peak at a relatively small n-tuple size, but the experiments carried out so far contradict this. Further experiments are needed to confirm this unexpected result.