Miracle-dz/UniFAR-FTUs huggingface dataset:
Coğrafya Öğretmen Adaylarının Öğretmenlik Uygulaması Deneyimleri Üzerine Bir Araştırma: Teori ve Pratik

Bu calismanin amaci, cografya ogretmen adaylarinin lisans egitimlerinin son senesinde Fakulte Uygulama Okulu-MEB isbirligi icerisinde gerceklestirilen ogretmenlik uygulamalarinda mesleki yeterliklerini ve ogretmenlige hazir bulunusluk durumlarini ve eksikliklerini belirlemektir. Ayrica bu calisma ile cografya ogretmen adaylarinin uygulama okulunda karsilastiklari problemleri ve cozum icin uyguladiklari yollari, bu uygulamanin kendilerine sundugu katki ve kazanimlar ile ilgili dusuncelerini ortaya cikarmaktir. Amacsal orneklem yontemine gore belirlenen calismanin grubunu 2012-2013 ogretim yilinda, Marmara Universitesi Ataturk Egitim Fakultesi Cografya Ogretmenligi Anabilim Dali 5. Sinifta ogrenim goren toplam 38 ogretmen adayi olusturmaktadir. Bir yil devam eden ogretmenlik uygulamasi sonucunda katilimcilara yari yapilandirilmis bir anket formu uygulanmis ve elde edilen verilerin cozumlenmesinde siklik analizleri ve karsilastirmali tablolar kullanilmistir. Bulgular incelendiginde cografya lisans ogrencilerinin genellikle kendilerini meslege hazir bulmadiklari, ogretmenlige hazir bulunusluk durumlarina gore bazi alanlarda ve mesleki yeterliklerinde eksikliklerinin oldugu gozlenmistir. Ogretmen adaylarinin daha iyi yetistirilmeleri ve okullarda gerceklestirilen ogretmenlik uygulamalarindan daha verimli yararlanmalari adina cesitli onerilerde bulunulmustur. Anahtar Kelimeler: Cografya ogretmen adayi, Mesleki yeterlikler, Ogretmenlik uygulamasi
"Ser" and "estar" in Tortosí Catalan: Language Contact, Language Variation, and Language Change

Diversos estudis sobre l'evolucio de les copules verbals (com els de Silva-Corvalan (1990) sobre ser i estar a l'espanyol de Los Angeles i els de Sankoff i Thibaut (1977) sobre etre i avoir al frances del Canada) assenyalen que alguns canvis linguistics motivats internament en la llengua es desenvolupen mes rapidament en situacions de llengues en contacte. En els estudis abans esmentats el canvi linguistic consisteix en la substitucio de ser per estar i de etre per avoir, respectivament. La direccio d'aquest canvi, que ja era present en el llati tarda, es troba en un estadi mes avancat en les varietats bilingues de l'espanyol i el frances. L'estudi que presentem se centra en l'us de ser i estar que es fa en la varietat bilingue del catala parlat a Villafranco del Delta (Catalunya), un poble fundat durant la dictadura del General Franco. Els participants, tots ells bilingues consecutius, amb el catala com a primera llengua i l'espanyol com a segona, van realitzar tres tasques diferents, les quals variaven en modalitat (percepcio vs. produccio) i grau d'atencio (entrevista controlada vs. conversa informal). L'analisi qualitativa de les dades bilingues aporta evidencia addicional per al canvi linguistic que afavoreix l'us d'estar. Especificament, la generalitzacio d'estar sembla ser afavorida per factors linguistics com ara la qualitat d'animat del tema discursiu i del subjecte sintactic, i per l'us d'adjectius emprats per a realitzar descripcions fisiques.
An analysis of value predictability and its application to a superscalar processor

The central theme of this thesis is the predictability of data-dependence values. Value predictability is studied first at a fundamental level. The analysis shows for SPEC95 programs that: (1) Values are amenable to prediction and that predictors that capture repeated behavior are necessary for high prediction accuracy. (2) Value predictability is mainly dependent on the program internal structure and immediate values, not input data. Value prediction and speculation is then applied to a superscalar processor to (a) determine its consequences on processor and value predictor design, and (b) evaluate its performance potential. Speculative execution and timing models are defined to describe concisely the design space of a superscalar processor influenced by value prediction. It is shown that invalidation and verification of dependent chains of instructions can be performed in “parallel”, contingent on technology constraints. For predictor implementations, emphasis is given to the design of a context-based predictor capable of predicting repeated value sequences, and a hybrid predictor that combines context-based and stride prediction. The following issues are also discussed: (a) delayed updates, speculative updates, and the use of old versus current information for deterministic updates, (b) removal on branch mispredictions of the side-effects due to speculative updates, and (c) high bandwidth value prediction. Performance simulations suggest that: (1) Value prediction can reduce the instruction window size required to achieve a given level of parallelism. (2) Value prediction has potential to improve performance on the average 3%–20% depending on the predictor, timing and confidence model used. (3) Hybrid predictors are the most cost effective predictors for achieving a given prediction accuracy. (4) There is a correlation between prediction accuracy and performance for a given predictor, i.e. improved accuracy translates to better performance. (5) When comparing different predictors, accuracy is not a good indication of their performance relation. (6) The predictors with the best performance are context-based and hybrid. (7) Delayed-updating a context-based predictor does not affect significantly its correct prediction accuracy, it increases however the number of incorrect predictions with high confidence (i.e. misspeculations). (8) Fast verification latency and accurate confidence are very critical to value prediction.
Scheduling for Modern Disk Drives and Non-Random Workloads

Disk subsystem performance can be dramatically improved by dynamically ordering, or scheduling, pending requests. Modern disk drives have several features, such as complex logical-to-physicalmappings and large prefetching caches, that can in uence scheduling e ectiveness. Via strongly validated simulation, we examine the impact of these features on various scheduling algorithms. Using both synthetic workloads and traces captured from six di erent user environments, we arrive at three main conclusions: (1) Incorporating complex mapping information into the scheduler provides only a marginal (less than 2%) decrease in response times for seek-reducing algorithms. (2) Algorithms which e ectively utilize a prefetching disk cache provide signi cant performance improvements for workloads with read sequentiality. The cyclical scan algorithm (C-LOOK), which always schedules requests in ascending logical order, achieves the highest performance among seek-reducing algorithms for such workloads ( ve of the six examined). (3) Algorithms that reduce overall positioning delays produce the highest performance provided that they recognize and exploit a prefetching cache.
Effects of individualized examples and personalized contexts in computer-based adaptive teaching of algebra word problems

approved: 7idi argaret L. Niess The purpose of the present investigation was to develop an adaptive teaching model for an interactive computer-assisted instruction (CAT) program and to evaluate the effectiveness of the implementation of individualized examples or individualized examples in personalized contexts. Translating word problems into equations provided the context for the CAT investigation. Four classes from two middle schools in Oregon constituted the population from which subjects were selected. Subjects completed a biographical questionnaire and a pretest prior to treatment. During the 45-minute treatment, subjects received a CAT lesson and practice problems following each example. On the day following the treatment, a posttest and a reaction questionnaire were administered to measure the main effects of these approaches. Three parallel CAT versions were developed as treatments for algebra word problem translations: 1) abstract, 2) individualized, and 3) individualized/personalized. In the abstract version, example and practice problems were presented without the involvement of specific learner interests or experiences. In the individualized version, example and practice problems were selected and constructed based upon learner interests and experiences. In the individualized/personalized version, exampie and practice problems were selected and constructed based upon learner interests and experiences, in addition to which personal biographical information was embedded into the contexts of problems. With respect to learning outcomes, the three different examples and contexts produced equivalent performances, with no significant posttest performance differences. Effects for individualized examples and personalized contexts for interactive CAT were not significant. The treatment effects for the practice performance were significant. Individualized and individualized/personalized groups answered significantly more practice problems correctly than the abstract group. Differences between the individualized and the individualized/personalized groups were not signi-
The Mug-Shot Search Problem

Mug-shot search is the classic example of the general problem of searching a large facial image database when starting out with only a mental image of the sought-after face. We have implemented a prototype content-based image retrieval system that integrates composite face creation methods with a face-recognition technique (Eigenfaces) so that a user can both create faces and search for them automatically in a database. Although the Eigenface method has been studied extensively for its ability to perform face identification tasks (in which the input to the system is an on-line facial image to identify), little research has been done to determine how effective it is when applied to the mug shot search problem (in which there is no on-line input image at the outset, and in which the task is similarity retrieval rather than face-recognition). With our prototype system, we have conducted a pilot user study that examines the usefulness of Eigenfaces applied to this problem. The study shows that the Eigenface method, though helpful, is an imperfect model of human perception of similarity between faces. Using a novel evaluation methodology, we have made progress at identifying specific search strategies that, given an imperfect correlation between the system and human similarity metrics, use whatever correlation does exist to the best advantage. The study also indicates that the use of facial composites as query images is advantageous compared to restricting users to database images for their queries.
Coded Compressed Sensing with Applications to Wireless Communication

Compressed sensing is a new paradigm that exploits the sparsity of signals to reduce the number of measurements required to recover a representation. This is accomplished using the general notion of inner-products as measurements, encapsulated in “measurement matrices. ” In this work, we focus on designing both measurement matrices as well as compressed sensing recovery algorithms. We consider several measurement code designs and recovery schemes with applications to particular systems. First, we consider chirp-coded compressed sensing measurements which, with a jointly designed recovery algorithm, is designed for computationally efficient recovery. For M measurements, O(M logM) recovery is possible, a significant speed improvement over conventional random signals and recovery methods. Subsequently, we consider OFDM channel estimation in the context of compressed sensing and note that measurement matrices are restricted to the form of sub-Fourier matrices. We provide a method to manifest suitable matrices for recovering sparse channels by deterministically selecting a few pilot tones. Next, we consider how the compressed sensing paradigm can be used to build novel wireless systems. We design a muliuser detection scheme for random access on asynchronous channels. For this system, we develop new compressed sensing recovery theory and design a codebook suitable for the recovery of sparse sets of active users. Finally, we design a virtual full-duplex adhoc wireless network system using half-duplex hardware. In the system, nodes use codes containing “listening symbols” during which the devices sense the wireless channel. When active nodes in the network transmit simultaneously, each node inheirits a unique compressed sensing problem to recover the data from its neighbors. The work in this thesis shows how, with careful consideration of the application, compressed sensing with coded matrices can provide great performance improvements and novel system designs.
Measured data used in the Watusi cross-section sets

In this document we list the experimental data that were used to make up the major cross- section sets that we use in the Watusi code to calculate the amount of detector activation in device tests. In order to use experimental data to make up a cross-section set, it is often necessary to extrapolate the cross sections down to either the threshold energy or to 0.01 keV, and to extrapolate up to 20 MeV. We then fit the data to a function so that we can get a smoothed set of interpolated values at up to 321 energy points. The combined data are then processed with the Hiroshima code into flux-weighted, group-averaged cross sections for use with the output from the different physics design codes. We typically use the standard 53 or 175 energy group structures. In a recent companion memo 1 we described the make up of all of the cross-section sets in detail, giving references to both the experimental data and the theoretical calculations that were used. The following sections have the experimental data, in the form of energy-cross section pairs, for the titanium, chromium, bromine, krypton, yttrium, zirconium, iodine, europium, lutetium, and bismuth sets. The other cross-sectionmore » sets are not directly based on enough experimental data to warrant their listing here. Many of the reactions used in these sets are based on calculated cross sections. In making these calculations certain parameters are sometimes adjusted so that the calculated cross sections match experimental data. In some of these cases we have made a further normalization to give a closer agreement to selected experimental data, and such normalizations are noted in this document. In other cases no further normalization was made. In Table 1 we summarize the reactions for which we present the experimental data given in Tables 2-46. In Figs. 1-35 we show plots of the experimental data together with the actual excitation functions used in the cross-section sets. Some reactions in the current sets are based on preliminary experimental data for which final results are now available. In those cases we show both the preliminary and the final data on the same plots. We expect to find only a few percent change in the calculated activation when we switch to the final experimental data. « less
Consistency Maintenance of Plausible Belief Bases Based on Agents Credibility

In this work we address the problem of knowledge representation in a collaborative multi-agent system where agents can obtain new information from others through communication. Informant agents will be ranked by their credibility. This credibility order will be used when new incoming information is contradictory with the current agent’s belief base. We propose a method for analyzing the received information, if inconsistency arises, the credibility order will be used to decide which information prevails. The proposed operator satisfies the minimal change principle and incoming information can be rejected when the agent has more credible beliefs that contradict the new information.
PENGARUH STRUKTUR MODAL, PERTUMBUHAN PERUSAHAAN TERHADAP NILAI PERUSAHAAN DENGAN PROFITABILITAS SEBAGAI VARIABEL INTERVENING PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA

Penelitian ini dilakukan pada perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia tahun 2008-2013. Penelitian ini bertujuan untuk mengetahui pengaruh sturktur modal dan pertumbuhan perusahaan terhadap nilai perusahaan dengan profitabilitas sebagai variabel intervening. Populasi dalam penelitian ini sebanyak 476 perusahaan. Sampel berjumlah 78 perusahaan ditetapkan dengan metode purposive sampling dengan kriteria- kriteria yang ditentukan.Teknik analisis yang digunakan adalah analisis jalur (path analysis) dengan regresi dan dilakukan uji asumsi klasik terlebih dahulu.Pengujian variabel intervening digunakan strategi causal step dan tes sobel. Hasil penelitian menunjukkan bahwa 1) DER berpengaruh positif dan signifikan terhadap PBV, 2) Perubahan Total Aktiva berpengaruh negatif dan signifikan terhadap PBV, 3) DER berpengaruh positif dan signifikan terhadap PBV dengan ROA sebagai variabel intervening, dan 4) Perubahan Total Aktiva berpengaruh positif dan signifikan terhadap PBV.
LEARNING WHILE HOLDING A CONVERSATION WITH A COMPUTER

Some of the recent electronic learning environments have moved beyond the conventional delivery of text, multimedia, and objective tests. There are systems with animated conversational agents, intelligent adaptive tutoring, interactive simulations, and other features designed to engage learners and promote deeper comprehension. One system is AutoTutor, a learning environment that tutors students by holding a conversation in natural language. AutoTutor’s design was inspired by explanation-based constructivist theories of learning, intelligent tutoring systems that adaptively respond to student knowledge, and empirical research on dialogue patterns in tutorial discourse. AutoTutor presents challenging questions and then engages in mixed initiative dialogue that guides the student in building an answer. It provides feedback to the student on what the student types in (positive, neutral, negative feedback), pumps the student for more information, prompts the student to fill in missing words, gives hints, fills in missing information, identifies and CHAPTER 8 IA255-PytlikZillig.book Page 143 Tuesday, February 15, 2005 12:59 PM
Hearing each other - how can we give feedback that students really value

In 2008 RMIT University had a focus on student feedback. One project called 'Hearing each other' looked at identifying feedback that students find useful and meaningful. Students from a range of programs including engineering and year levels were questioned. Focus groups were held where students were asked a series of questions about kinds of feedback they had received and what they found useful or less useful. The results were analysed for similarities and differences between year levels and between programs. The results showed students valued the same kinds of feedback irrespective of age or discipline, especially use of marking sheets to promote consistent clear marking. Students disliked 'tut lotto', where their marks would depend more on who was marking than what was written. Highly rated staff identified more time on feedback on non-assessed work as good. More work is planned to identify tips for good feedback from the best lecturers.
Clustering by self-updating process

We introduce a simple, intuitive, yet powerful algorithm for clustering analysis. This algorithm stands from the viewpoint of elements to be clustered, and simulates the process of how they perform self-clustering. The algorithm is therefore named Self-Updating Process (SUP). We discover the algorithm's ability to simultaneously isolate noise while performing clustering, which enables the algorithm to produce good clustering results even when the level of noise in the data is high. We present simulation studies to demonstrate the performance of this algorithm. Applications to gene expression data and image segmentation are provided.
Kernel Methods for Word Sense Disambiguation and Abbreviation Expansion in the Medical Domain

Word Sense Disambiguation (WSD) is the problem of automatically deciding the correct meaning of an ambiguous word based on the surrounding context in which it appears. The automatic expansion of abbreviations having multiple possible expansions can be viewed as a special form of WSD with the multiple expansions acting as ”senses” of the ambiguous abbreviation. Both of these are significant problems, especially in domains such as medical text with abstracts of articles in scholarly medical journals and clinical notes taken by physicians. Most popular approaches to WSD involve supervised machine learning methods which require a set of manually annotated examples of disambiguated words or abbreviations to learn patterns that help in disambiguating future unseen instances. However, manual annotation imposes a limit on the amount of labeled data that can be made available to the supervised machine learning algorithms such as Support Vector Machines (SVMs), because annotation requires significant human work. Kernel methods for SVMs provide an elegant framework to incorporate knowledge from unlabeled data into the SVM learners. This thesis explores the application of kernel methods to two datasets from the medical domain, one containing ambiguous words and the other containing ambiguous abbreviations. We have developed two classes of semantic kernels Latent Semantic Analysis (LSA) Kernels and Word Association Kernels (ASSOC) for SVMs, that are learned from unlabeled text containing the ambiguous words or abbreviations using unsupervised methods. We have found that our semantic kernels improve the accuracy of SVMs on the task of WSD in the medical domain. In particular, we find that our LSA kernels with unigram features and ASSOC kernels with bigram features perform better than off-the-shelf SVM learners and they are significantly better for five out of 11 ambiguous words, which have a balanced sense distribution and for nine out of ten abbreviations. We also focus on the feature engineering aspect of the abbreviation expansion problem in the domain of clinical notes text. We propose a flexible window approach for capturing features and show that it significantly improves performance. We make use of features specific to clinical notes such as the gender code of the patient and show that this improves performance significantly in combination with Part-of-Speech features.
Improving management skills through business simulation

A survey was conducted among students of the Accounting and Administration undergraduate degree at ISCAP – IPP (School of Accounting and Administration of Polytechnic Institute of Porto) in order to understand their perception value of their course Business Simulation (BS). This course is provided in a business environment where students can learn by doing through the management of a company as they were in the real life, but risk-free. The learning tasks are provided in an action-oriented format to maximize the learning process. Students learn by doing a set of tasks every session and have also to produce reports and presentations during the course. BS is part of the undergraduate degree of Accounting and Administration at ISCAP – IPP since the beginning of 2003. The questionnaire we used captured the students’ perception about general and specific skills and competencies considered important for managers and accountants in the real life, about the methodology used in the course, which is totally different from the traditional form, and also about the adequacy of the course included as part of the undergraduate degree. The results showed that students’ perception is highly positive and almost all of them think they improve the skills needed for a job during the course. These results are consistent with [1] Adler and Milne’s research in which the authors found that students agree with the use of action-oriented learning tasks in order to provide them the needed attitudes, skills, and knowledge. The improvement of group skills is the most important issue for students, which can be understandable as BS is the only course from the degree in Accounting and Administration they really have to work in groups.