Miracle-dz/UniFAR-FTUs huggingface dataset:
ÖĞRETMENLERİN ROL MODELLİĞİ HAKKINDA ÖĞRETMEN GÖRÜŞLERİ

Hizla degisen sosyo-kulturel yapi, ogretmenin egitimdeki onemini azaltamamistir. Ogrencinin dunyasinda ogretmen oldukca etkili bir yere sahiptir. Bu calismanin amaci; ogretmenlerin kendilerini ogrenciler icin rol model olarak gorup gormediklerini, ogretmenlerin hangi acilardan kendilerini rol model olarak gorduklerini ayrica ogretmenlerin kendilerini rol model olarak gormeme durumunda bunun nedenlerini tespit etmek ve ogrencilerin ogretmenlerini rol model olarak gorme egilimlerinin ogretmenler tarafindan fark edilip edilmedigi bilgisine ulasmaya calismaktir. Betimsel arastirma modelini esas alan bu calismada veri toplama araci olarak acik uclu iki sorudan olusan bir uygulama anketi hazirlanmistir. Anket formunda yer alan sorulara verilen cevaplarla cesitli veriler elde edilmistir. Elde edilen verilerin analizi neticesinde, ogretmenlerin buyuk olcude kendilerini ogrenciler icin rol model olarak gordukleri fark edilmistir. Ogretmenlerin ozellikle ogrencilerin kisilik egitimine ve karakter olusumuna dikkat ettikleri gozlenmistir. Ogretmenlerin davranislariyla ogrencilere iyi birer model olmalari, ogrencilerin davranislarini da etkileyerek gelecek hayatlarinin sekillenmesinde de temel olusturacagindan, ogretmenlerin rol model olarak gorulduklerine dair farkindaliklari oldukca onem tasimaktadir.
Nonverbal predication in Amazonia

[Extract] The present volume is a collection of 13 chapters selected from 32 presentations at a special session on nonverbal predication at the international conference Amazonicas V, that took place in Belem, Brazil, in May 2014. 1 Following this introductory chapter, the papers are primarily descriptive and historical, offering abundant data generally from original and extensive periods of fieldwork, often on languages with relatively little prior description. Thus, each contribution in this volume contains a great deal of new data and analyses, presenting a far more detailed picture of nonverbal predication in individual languages than is found in published grammatical descriptions. Several contributions also offer historical reconstructions, from either comparative data or internal reconstruction. This volume embodies linguistic diversity in South America, offering chapters dealing with 14 individual languages belonging to nine linguistic families: Arawakan, Cariban, Panoan, Yanomanan, Chicham (formerly known as Jivaroan), Tupian, Tukanoan, Mataguayan and Guaykuruan, plus Movima, an isolate language. In addition, it includes a historical-comparative paper combining original field data with previously published work (Cariban). This volume also embodies the diversity of researchers in this area: contributors are affiliated with academic institutions from around the globe (South and North America, Australasia, and Europe), and the majority of them are engaged in collaboration efforts aimed at promoting local development among speech communities and local institutions.
Parallel proximity computation on heterogeneous computing systems for graphics applications = 그래픽스 응용 프로그램을 위한 이종 연산장치 기반 근접질의 병렬처리 기술

Proximity computation is one of the most fundamental geometric operations for various applications including physically-based simulations, computer graphics, robotics, Etc. Also proximity computation is one of the most time consuming parts in various applications. There have been numerous attempts to accelerate the queries like adopting an acceleration hierarchy to cull redundant computations. Even though these methods are general and improve the performance of various proximity queries by several orders of magnitude, there are ever growing demands for further improving the performance of proximity queries, since the model complexities are also ever growing. Recently, the number of cores on a single chip has continued to increase in order to achieve a higher computing power. Also, various heterogeneous computing architectures consisting of different types of parallel computing resources have been introduced. However, prior acceleration techniques such as using acceleration hierarchies gave less consideration for utilizing such parallel architectures and heterogeneous computing environments. Since we are increasingly seeing more heterogeneous computing environments, it is getting more important to utilize them for proximity queries, in an efficient and robust manner. In this thesis, we employ heterogeneous parallel computing architectures to accelerate the performance of proximity computation for various applications. To efficiently utilize heterogeneous computing resources, we propose parallel computing systems and algorithms for proximity computation. We start with a specific proximity query and design a novel efficient parallel algorithm based on knowledge of the query and computing resources. Then we extend our method to various proximity queries and propose a general proximity computing framework. Also we improve the utilization efficiency of computing resources by designing optimization-based scheduling algorithm. With the proposed methods, an order of magnitude improvement is achieved on various quires by using up to two hexa-core CPUs and four different GPUs over using a single CPU core. In addition we propose an out-of-core proximity computation algorithm to handle a massive data that requires a larger memory space than the memory size of a computing resource in a heterogeneous computing system, especially for the particle-based fluid simulation. The proximity computing system using the out-of-core algorithm robustly works for a large-scale scene and achieves up to two order of magnitude performance improvement over a previous out-of-core approach. These results demonstrate the efficiency and robustness of approaches.
Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method

In this paper, we propose a new face hallucination technique, face images reconstruction in HSV color space with a semi-orthogonal multilinear principal component analysis method. This novel hallucination technique can perform directly from tensors via tensor-to-vector projection by imposing the orthogonality constraint in only one mode. In our experiments, we use facial images from FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color faces. The experimental results assure clearly demonstrated that we can generate photorealistic color face images by using the SO-MPCA subspace with a linear regression model.
Kahoot! or Quizizz: the Students’ Perspectives

Kahoot! and Quizizz are e-learning web-apps commonly used in conducting online quizzes. This research was aimed at: (1) knowing the students' perceptions of Kahoot! and Quizizz's efficacy in a daily online quiz, (2) figuring out the students' choices and (3) finding out their reasons. The research design was qualitative research concerning phenomenological studies with a sample of 250 students of English Education Department of STKIP PGRI Trenggalek. It used a close-ended questionnaire to collect the data of the students' perceptions. Data analysis of the questionnaires was analyzed quantitatively by implementing the Likert scale. Research findings of the first questionnaire toward Kahoot! and Quizizz's efficacy gained supportive responses with a total score of 15.484. The second questionnaire toward the students' choices and their reasons resulted in the total score 15.002 (Quizizz) and 12.248 (Kahoot! ). In conclusion, Quizziz was more effective to foster students' enthusiasm for learning and better than Kahoot! for some reasons.
Covariant energy density functionals with and without tensor couplings at the Hartree-Bogoliubov level

Background: The study of additional terms in functionals is relevant to better describe nuclear structure phenomenology. Among these terms, the tensor one is known to impact nuclear structure properties, especially in neutron-rich nuclei. However, its effect has not been studied on the whole nuclear chart yet. Purpose: The impact of terms corresponding to the tensor at the Hartree level, is studied for infinite nuclear matter as well as deformed nuclei, by developing new density-dependent functionals including these terms. In particular, we study in details the improvement such a term can bring to the description of specific nuclear observables. Methods: The framework of covariant energy density functional is used at the Hartree-Bogoliubov level. The free parameters of covariant functionals are optimized by combining Markov-Chain-Monte-Carlo and simplex algorithms. Results: An improvement of the RMS binding energies, spin-orbit splittings and gaps is obtained over the nuclear chart, including axially deformed ones, when including tensors terms. Small modifications of the potential energy surface and densities are also found. In infinite matter, the Dirac mass is shifted to a larger value, in better agreement with experiments. Conclusions: Taking into account additional terms corresponding to the tensor terms in the vector-isoscalar channel at the Hartree level, improves the description of nuclear properties, both in nuclei and in nuclear matter.
Social eye gaze in human-robot interaction

This article reviews the state of the art in social eye gaze for human-robot interaction (HRI). It establishes three categories of gaze research in HRI, defined by differences in goals and methods: a human-centered approach, which focuses on people's responses to gaze; a design-centered approach, which addresses the features of robot gaze behavior and appearance that improve interaction; and a technology-centered approach, which is concentrated on the computational tools for implementing social eye gaze in robots. This paper begins with background information about gaze research in HRI and ends with a set of open questions.
Multi-modal image registration via depth information based on point set matching

Image registration is an important pre-processing operation to perform multi-modal joint analysis correctly. However, registration of images captured by different sensors is a very challenging problem due to the apparent differences of scenes. Traditional Coherent Point Drift method (CPD) is a global registration approach, which strongly relies on the extracted features. In the case of infrared and visible images, registration methods based on edges or points are inappropriate since those features might be significantly different. Fortunately, depth information is more robust feature for multi-modal image pairs. In this paper, we propose an algorithm based on Canny to extract edge of objects. And the regions of interest (ROI) is obtained by depth maps of image pairs in which common features usually successfully implemented by point set registration. Experimental results on real world data demonstrate the effectiveness of the proposed approach, which is superior to the traditional CPD algorithm for multi-modal image registration.
Comparison of Vocal Characteristics of Future Professionals in Three Different University Majors

CONTE PORARY ISSUES IN COMMU ICATION SCI NCE AND DISORDERS • Volume 32 • 142–150 • Fall 2005 © NSSLHA 1092-5171/05/3202-0142 ABSTRACT: Vocal characteristics of students in three preprofessional undergraduate programs (speech-language pathology and audiology, broadcast communication, and theater) were compared across the following parameters: a number of acoustic measurements, a perceptual voice evaluation by speech-language pathologists, and selfreported vocal quality ratings using a vocal use questionnaire. Results indicated some significant differences between different student groups. Specifically, students in the broadcast communication and theater programs were found to have significantly higher scores of self-identified and perceptual voice problems than students in the speech-language pathology and audiology program. Acoustic measurements appeared to confirm the results of the self-identified and perceptual data.
Kernel Density Map Based on MapReduce

Geoprocessing plays an important role in Geographical Information Systems. In this paper, we propose a spatial processing parallel algorithm based on MapReduce architecture. The method is addressed in kernel density computation, and it also can cover other commonly used raster map processing, and the statistical calculation of the raster data, such as slope, buffer, European distribution, interpolation.
Symbolic and Sub-Symbolic Robotic Intelligence Control System (SS-RICS) Users Manual

Abstract : This is a users manual for the Symbolic and SubSymbolic Robotics Intelligence Control System. The manual explains the overall use and operation of the robotics architecture, the different setups and connections, the simulator and real-world operation, and the code-development environment for creating programs for the robot. A wide variety of topics is covered, from code deployment to the theoretical issues involving symbolic and sub-symbolic knowledge representation. It is intended to be a general platform for robotics development with an emphasis on cognitive mechanisms for robotics control.
The Fāṭimid coins from Sicily in al-Andalus: the Jabonerías hoard (Murcia, Spain)

This paper has been carried out within the framework of the research project HAR2015-67111-P, El sitio de las cosas: relacion entre la cultura material y los espacios construidos a la luz de la arqueologia (siglos VI-XIV), funded by the Spanish Ministry of Economy and Competitiveness.
Associations between environmental attributes of facilities and female participation in sport: a systematic review

ABSTRACT Purpose: To examine the association between environmental attributes of facilities, female participation in sport and according to life stage. Design: Articles were identified through seven databases and included if female specific results were reported on the association between attributes of the physical environment and sports participation. Findings: The search yielded 3118 articles, 24 met the criteria. Most studies were moderate quality and in terms of life stage focused on adolescent girls. Environmental attributes of facilities including perceived safety, convenient location and suitable amenities in sport and school facilities were associated with female participation in sport. Practical implications/research contribution: Attributes of the physical environment may influence female participation in sport. Conclusions are tentative based on minimal studies in this area. More attention to identify environmental attributes of facilities associated with encouraging female participation in sport across their transitional life stage is required to enhance understanding and guide facility development.
Twenty‐year study of in‐hospital and postdischarge mortality following emergency general surgical admission

Emergency general surgery (EGS) patients have a higher mortality than those having elective surgery. Few studies have investigated changes in EGS‐associated mortality over time or explored mortality rates after discharge. The aim of this study was to conduct a comprehensive, population‐based analysis of mortality in EGS patients over a 20‐year time frame.
Education on Structural Glass Design: Redefining glass through the design of innovative, full-glass structures.

In many famous architectural works, it is the structure and materiality of the building that manifest the project’s innovation. In such works, the structural system of the building becomes the primary form of expression. Ergo, the ability to understand the principles of structural engineering and design, and the motivation to experiment with new types of structures and materials are invaluable assets for both architects and structural engineers. Towards this goal, a series of elective courses (Shell structures, Glass structures, Bridge Design) have been integrated in the curriculum of the MSc of Building Technology at the Faculty of Architecture and the Built Environment (BK) and of the MSc of Building Engineering at the Faculty of Civil Engineering and Geosciences (CiTG) at TU Delft. Aim is to bridge the gap between architects and structural engineers. Each of these courses lasts 10 weeks and focuses on the design, engineering, calculation and materialization of a different type of structure. This paper will discuss the set-up, learning objectives, methodology and output of the “Technoledge-Glass Structures”(BK) and the “Structural Glass” (CiTG) courses. Aim of these parallel courses is to effectively teach students, of both architectural and civil engineering backgrounds, how to design, engineer and evaluate the behaviour of structures made entirely out of glass elements and how to tackle problems related to the practical aspects of a construction.
New Network Models With New Graph Labellings For Information Cryptograph

Based on the idea of of “graphical construction plus number theory” and magic type of various labellings for solving network transfer delay by using other type of graphical passwords, we define a new graph labelling, called generalized edge magic graceful labelling, and build some large scale of network models having the new labellings to verify effective algorithms.
Weight Initialization based Partial Training Algorithm for Fast Learning in Neural Network

The classification problem is one of most important problems in Artificial Intelligence (AI) Research. Classification is used in various fields such as speech recognition, image classification, word prediction in text. Deep Neural Network (DNN) is the most commonly used for the classification. However, DNN requires a lot of learning time because of its deep network structure and lots of data. At this time, if a new feature or a new category class (new data) is added, the existing data on which learning has been completed is also re-learned. And the same learning time (very long time) as the previous learning time is needed. Therefore, in this paper, we proposes Weight Initialization-based Partial Training (WIPT) algorithm, that decompose the existing weight matrix through Singular Value Decomposition (SVD) and generate a latent matrix with information learned by the existing model. In order to increase the learning efficiency, we use a strategy of learning new features or classes by initializing newly added weights to appropriate values. Finally we verify the efficiency of the proposed algorithm by comparing it with the existing whole learning.
Information Retrieval based on Content and Location Ontology for Search Engine (CLOSE)

This paper mainly focuses on the personalization of the search engine based on data mining technique, such that user preferences are taken into consideration. Clickthrough data is applied on the user profile to mine the user preferences in order to extract the features to know in which users are really interested. The basic idea behind the concept is to construct the content and location ontology’s, where content represent the previous search records of the user and location refer to current location of user. SpyNB is the approach used to mining the user preferences from the Clickthrough data. The ranked support vector machine (RVSM) is performed on the searched results in order to display results according to user preferences by considering Clickthrough data.
XES Software Event Extension

During the execution of software, execution data can be recorded. With the development of process mining techniques on the one hand, and the growing availability of software execution data on the other hand, a new form of software analytics comes into reach. That is, applying process mining techniques to analyze software execution data. To enable process mining for software, event logs should be capable of capturing software-specific data. A software event log is typically recorded at the method call level during software execution. Events generated at this level reference a specific point in the software source code. The Software Event extension captures this event location information, together with some basic runtime information related to this location.
ResearchArticle Maximum Power Control of Hybrid Wind-Diesel-Storage System

Optimum wind energy extraction is a very important economical target. This paper is concerned with the development of a robust controller for the wind turbines in hybrid wind-diesel storage system (HWDSS). The proposed algorithm, which is based on fuzzy linear matrix equalities (FLME), maximizes the power coefficient for a fixed pitch. Moreover, it reduces the voltage ripple and stabilizes the system over a wide range of wind speed variations. The control scheme is tested for different profiles of wind speed pattern and provides satisfactory results.
Exploring Multiple Embedded Features on Event Extraction

In recent years, the neural network method can automatically learn effectively features. Unlike traditional discrete features, neural network features are mostly continuous features and can be automatically combined to build higher-level features. The efficiency of the features has been proven in numerous tasks in natural language processing and has led to breakthroughs. In this paper, we propose a event extraction system based on combination of multiple embedded features. Our work is mainly based on the three aspects: (1) traditional pipeline systems have serious error propagation problems; (2) there are several different event descriptions in the text; (3) representation learning can provide rich semantic and syntactic representation. As a result, we achieve competitive performance, specifically, F1-measure of 60.25 in event extraction. Meanwhile, evaluation results point out some shortcomings that need to be addressed in future work.
A Sparse-grid UKF For The State Estimation of PDEs

—Unscented Kalman Filter (UKF) has been widely used in the estimation of dynamical systems deﬁned by ordinary differential equations. For partial differential equations, their discretized systems often have very high dimensions, which result in covariance matrices that are computationally intractable. In this paper, we introduce sparse-grids and an associated reduced state space, called a surplus space, in which the covariance matrices have relatively small dimensions and the number of sigma points is signiﬁcantly reduced. The covariance in the reduced space can be used to compute the correction term for the updating process of the UKF. The resulting sparse-grid UKF is illustrated using an example of shallow water equations.
Multi-channel medium access control protocols: review and comparison

Abstract Multi-Channel networks has been widely implemented and used in wired domain. The use of multi-channel provides increased network performance by efficiently utilizing the available bandwidth. The notion of multi-channels in wireless domain isn't as mature as their wired counterparts are. In past, many protocols have been invented using the concept of multi-channels in wireless domain. In this paper, all these major techniques has been presented, discussed and compared with respect to medium access control (MAC) methods of these techniques and protocols.