Reviewerly/exHarmony huggingface dataset:
Deep Learning Classification of Face Images with varying Illumination Conditions

In face recognition system, the accuracy of recognition is greatly affected by varying degree of illumination on both the probe and testing faces. Particularly, the changes in direction and intensity of illumination are two major contributors to varying illumination. In overcoming these challenges, different approaches had been proposed. However, the study presented in this paper proposes a novel approach that uses deep learning, in a MATLAB environment, for classification of face images under varying illumination conditions. One thousand one hundred (1100) face images employed were obtained from Yale B extended database. The obtained face images were divided into ten (10) folders. Each folder was further divided into seven (7) subsets based on different azimuthal angle of illumination used. The images obtained were filtered using a combination of linear filters and anisotropic diffusion filter. The filtered images were then segmented into light and dark zones with respect to the azimuthal and elevation angles of illumination. Eighty percent (80%) of the images in each subset which forms the training set, were used to train the deep learning network while the remaining twenty percent (20%), which forms the testing set, were used to test the accuracy of classification of the deep learning network generated. With three successive iterations, the performance evaluation results showed that the classification accuracy varies from 81.82% to 100.00%.
Variational inference for neural network matrix factorization and its application to stochastic blockmodeling

We consider the probabilistic analogue to neural network matrix factorization (Dziugaite &amp; Roy, 2015), which we construct with Bayesian neural networks and fit with variational inference. We find that a linear model fit with variational inference can attain equivalent predictive performance to the regular neural network variants on the Movielens data sets. We discuss the implications of this result, which include some suggestions on the pros and cons of using the neural network construction, as well as the variational approach to inference. Such a probabilistic approach is required, however, when considering the important class of stochastic block models. We describe a variational inference algorithm for a neural network matrix factorization model with nonparametric block structure and evaluate its performance on the NIPS co-authorship data set.
Speaking With Debate Methods: Class Action Research Study

The purpose of this study is to describe the improvement in speaking skills of students using the debate method in class V of SDN 10 Sapiran Bukittinggi. The types of research are PTK, qualitative and quantitative approaches. The research subjects were teachers and 26 fifth grade students of SDN 10 Sapiran Bukittinggi. Planning cycle I obtained a percentage of 82.14%, cycle II 92.85%. The implementation of the first cycle was 81.25%, the second cycle was 95%. Speaking skills in cycle I 78.54%, cycle II 93.15%. Thus, the debate method can improve the speaking skills of fifth grade students of SDN 10 Sapiran Bukittinggi.
IMPROVING THE STUDENTS’ VOCABULARY MASTERY’ USING GAMES INVOLVING PICTURES IN ELEMENTARY SCHOOL

The objectives of the study are to describe and find out the effectiveness the teaching of English vocabulary using games involving pictures in class activities at the third grade students of Elementary School. This study is action research. The subject of study is the third grade students of Elementary School of Piri Nitikan Yogyakarta. There were 17 students in the class. The data were collected from the observation, interview and test. The data were analyzed from field notes, interview transcript, the observation sheets and test result. It is concluded that using games involving picture in the class can make some progress to the students. The students can increase their vocabulary mastery and their ability both in writing words and in speaking. The students can pronounce the English words correctly. Besides, using games involving picture make the students active and enjoy English class.
PENINGKATKAN HASIL BELAJAR SISWA DENGAN MENGGUNAKAN MODEL EXAMPLES NON EXAMPLES PADA MATA PELAJARAN IPA DI KELAS IV SD NEGERI 040455 BERASTAGI

This study was conducted to determine the improvement of fourth grade science learning outcomes using the examples non examples learning model. The subjects were all students in fourth grade 040455 Berastagi, Karo. The object of the research is the improvement of the fourth grade science learning outcomes using the examples non examples learning model. The research instrument used was the observation sheet and tests. From the analysis of the data obtained from observations the implementation of learning activities of teachers increased 19,7% from a value of 60% to 79.7%, student activity increased from a score of 68% to 86%, the completeness of individuals who expressed achieving KKM scores of 70, classical completeness increased from 70% to 86.67%, and the average value increased from 67,33 to 70,33. Keywords : learning result of sciences, examples non examples
Information search in a professional context - exploring a collection of professional search tasks

Search conducted in a work context is an everyday activity that has been around since long before the Web was invented, yet we still seem to understand little about its general characteristics. With this paper we aim to contribute to a better understanding of this large but rather multi-faceted area of `professional search'. Unlike task-based studies that aim at measuring the effectiveness of search methods, we chose to take a step back by conducting a survey among professional searchers to understand their typical search tasks. By doing so we offer complementary insights into the subject area. We asked our respondents to provide actual search tasks they have worked on, information about how these were conducted and details on how successful they eventually were. We then manually coded the collection of 56 search tasks with task characteristics and relevance criteria, and used the coded dataset for exploration purposes. Despite the relatively small scale of this study, our data provides enough evidence that professional search is indeed very different from Web search in many key respects and that this is a field that offers many avenues for future research.
Logic and heuristic in education

More than once were suggested that the results of the field of logic appear to be useful at the checking of ready-made proofs but refused to serve when one has to discover evidence; although some very reputable mathematicians supported this view, we allow ourselves to disagree with it. Every time they offer arguments for this point of view (and very often it speaks without any arguments), they demonstrate a â€˜frontalâ€™, straightforward interpretation of the results of logic. However, such an interpretation of the interrelations between logic and heuristic is not the only possible one. On the contrary, other interpretations possible, in which logic and heuristics are two sides of the single process of learning. In our paper, we consider both mentioned uses of the logic.&#x0D; Keywords: Intuitive evidence, logical proof, heuristic advices.
Classifying the Imaginary: An Expansion of Library of Congress’ Subclass G9930 for Local Use

Class G provides granular classification for most cartographic materials through a well-established and expanded Cuttering system, maps of imaginary places are classified under G9930 which has no formal expansion. With the creation of a collection of imaginary maps at the Texas A&M University Libraries, the lack of expansion under G9930 created access and filing complications. This case study describes the problem that growing a collection under the unexpanded classification system posed and the solution that was found through the creation of an in-house expansion for G9930.
An underwater stereo matching method based on ORB features

Since the traditional algorithm may cause problems such as slow running speed and more mismatching points when perform stereo matching on underwater environment, the ORB characteristics detection and curve restriction has been applied in this paper. Firstly the image should be detected so as to find out the characteristics, generate the descriptor, and match the feature points. Then the underwater curve restriction can be deduced according to the law of refraction combining internal and external parameters of camera. Finally the mismatching points can be decreased by means of underwater curve restriction. The experimental results have shown that in the case of effectively controlling mismatches, the speed of this algorithm are faster than traditional SIFT algorithm combined with curve restriction. As a result, it is of practical significance to improve the speed of underwater binocular vision system.
PENGEMBANGAN BAHAN AJAR BERBASIS WEB DENGAN MENGGUNAKAN ADOBE DREAMWEAVER CS6 PADA MATA KULIAH EVALUASI PROSES DAN HASIL PEMBELAJARAN SEMESTER V PROGRAM STUDI TEKNOLOGI PENDIDIKAN UNIVERSITAS BATURAJA

This study aims to develop and produce website based teaching materials using Adobe Dreamweaver CS6 in the evaluation of learning process and achievement course at fifth semester of Educational Technology Study Program at Baturaja University. This study was conducted using Bambang Warsita’s Research and Development model design. The results showed that the design, media, and material expert evaluations were at good category (84.27%, 83.6% ,and 81.4%). Meanwhile, individual evaluation result was 82.52% (good), small group evaluation was 82.99% (good), and field trial result was 83.48% (good). In addition, students also commented that website based teaching materials are good, varied, interesting and fun. From the results of the data analysis, it can be concluded that website based teaching materials using Adobe Dreamweaver CS6 are good and can be used in the learning process. Keywords: Adobe Dreamweaver CS6, Web-based teaching materials, process evaluation and learning outcomes
Las TIC y la formación inicial del profesorado / The TIC and the Initial Teacher Training

ABSTRACTSchools have been immersed in this global advance in the use of TIC. Causing a great revolution in how teachers can assume their teaching practice. The key competences (LOMCE, 2013) propel teachers to catch up on the use of TIC. The proposal is about a real experience carried out with Students University of the education of young children. Where the use of TIC resources for educational purposes is introduced. The results obtained show the potential that different digital applications have and the success achieved in relation to the academic results of the students.RESUMENLas escuelas se han visto inmersas en el avance global en el uso de las TIC. Provocando una gran revolución en cómo el profesorado puede asumir su práctica docente. Las competencias clave (LOMCE, 2013) instan al profesorado a ponerse al día en el uso de las TIC. La propuesta versa sobre una experiencia real llevada a cabo con alumnos del Grado de Educación Infantil. En la que se introduce el uso de recursos TIC con finalidad educativa. Los resultados obtenidos muestran la potencialidad que tienen diferentes aplicaciones digitales y el éxito conseguido en relación a los resultados académicos de los alumnos.
Systemic design approach to the development of a visual communication channel DYCLE case of study

Communication plays an important role in the generation of meanings, knowledge and relationships in societies; the characteristics of these dynamics are related with the systemic design discipline through some guidelines that were suggested by Lidia Signori as requirements in order to develop a systemic communication. Among all the communication elements, this thesis is focused on information visualization, a channel of visual communication, in which the transmission of information is achieved through graphic elements in a proper way. DYCLE (Diaper Cycle project) is a systemic project that has revolutionize the diaper industry by creating 100% biodegradable diapers. It is an entrepreneurial initiative full of values and relations that should be spread; that is why this project was taken as a case study in which besides the guidelines, the methodology of visual thinking was considered as an adequate way to organize complex ideas, that helped represent and transmit key information adapted to the specific users of the project. The result of the investigation shows different graphic representations that vary depending on the type of information and the intention of the message. These graphic representations are presented as diagrams, schemes, infographics or illustrations. In addition, in order to achieve a complete systemic project, a diagnosis of the problems that still have the system was made. These critic factors should be considered during the implementation, regardless of the context. After describing these problems, several solutions for each one, were pointed out; in this case, specifically for DYCLE Berlin.
The Affine Geometric Heat Flow and Motion Planning for Dynamic Systems

We present a new method for motion planning for control systems. The method aims to provide a natural computational framework in which a broad class of motion planning problems can be cast; including problems with holonomic and non-holonomic constraints, drift dynamics, obstacle constraints and constraints on the magnitudes of the applied controls. The method, which finds its inspiration in recent work on the so-called geometric heat flows and curve shortening flows, relies on a hereby introduced partial differential equation, which we call the affine geometric heat flow, which evolves an arbitrary differentiable path joining initial to final state in configuration space to a path that meets the constraints imposed on the problem. From this path, controls to be applied on the system can be extracted. We provide conditions guaranteeing that the controls extracted will drive the system arbitrarily close to the desired final state, while meeting the imposed constraints and illustrate the method on three canonical examples.
Parallel algorithms through approximation

We describe a paradigm for designing parallel algorithms on massive graphs by employing approximation techniques. Instead of solving a problem exactly, for which efficient parallel algorithms do not exist, we seek a solution with provable approximation guarantees via approximation algorithms. Furthermore, we design approximation algorithms with high degrees of concurrency. We show the computation of degree-constrained subgraphs as an example of this paradigm.
A Novel Paging Query Optimization Technique for Large Datasets

Data is considered as amore valuable asset than the hardware and software. For the efficient retrieval and processing of this data, various database systems have been developed to store it in structured form. Most of the time, we need SQL which returns the retrieved results in the form of pages each consisting of multiple records. Paging Query efficiency of large datasets has a direct impact on application systemsperformance. The major bottleneck of most of the large databases which affect paging query is the volume of data returned to the database server from storage. When there is a full table scan involved,the transfer time of large data between the storage media and the database servers may affect the efficiency. In this paper, an optimized solution for paging query is presented including the key technologies of paging query efficiency using Oracle 11g platform. Oracle 11g is considered as the most elegant, innovative and high concurrent database system which delivers high quality of services and has raised the pinnacle of the IT world on the other virtues. The proposed model is based on the database optimization, SQL optimization and offloading concept. Apart from the classic database systems, only the data required by the client will be returned to the database instance from storage instead of unnecessary huge volume of data. Moving SQL processing off the database server frees server CPU cycles and eliminates a massive amount of unproductive I/O transfer. All these resources become free to provide better services to the other user requests. In this way, the queries run much faster and more of them can be processed in a shorter span of time. The validation of the proposed solution proves effectiveness and efficiency of the model. The experimental results are also reported in this paper.
INVESTIGATION STUDENTS’ INTENSIVE LISTENING THROUGH CALL (COMPUTER ASSISTED LANGUAGE LEARNING) IN EFL CLASSROOM

Listening is known as the process of identifying the sound sequences and also the process of identifying the component of sounds, whereby the words is known (Asemota, 2015). It can be seen as the process which is not only involving the process of hearing the sounds and noises, it also include identifying, understanding and interpreting spoken languages (Harrowoth, 1966, as cited in Asemota, 2015). In teaching and learning listening as foreign language using Intensive Listening usually relate to media. Media which have been used in teaching and learning foreign laguage is facilitated by technology, such as CALL (Computer Assisted Language Learning). This research of this situation is essential to conduct by researcher because Intensive Listening is listening practice that most teacher use in the classroom as a basic learning skill by investigating the process of learning and practising in the classroom or Language Laboratory. The researcher used qualitative research approach because the data in qualitative approach indicated the phenomenon in the school. The result of this research found that listening activities is needed to be applied intensively because most of respondent argued that listening activities through CALL as media brought the atmosphere of the class being enjoy, fun, and interesting.&nbsp
Formation of entrepreneurial skills as a component of professional training of future teachers

In the article, the authors put forward the idea that the formation of entrepreneurial skills is a conscious need for which a new philosophy of professional pedagogical education is being built. Considering the socio-cultural activities as a factor in the development of university traditions, the authors propose to use it in teaching future teachers. Examples of such traditions, their types, and forms are given, and their influence on the formation of a student’s professional characteristics is also considered. Startup becomes a new socio-cultural tradition in higher education. Identified and described features of the organization. Conclusions are drawn regarding the role of the teacher in shaping the entrepreneurial thinking of future teachers.
De Jongh's Theorem for Intuitionistic Zermelo-Fraenkel Set Theory

We prove that the propositional logic of intuitionistic set theory IZF is intuitionistic propositional logic IPC. More generally, we show that IZF has the de Jongh property with respect to every intermediate logic that is complete with respect to a class of finite trees. The same results follow for CZF.
The asymptotic induced matching number of hypergraphs: balanced binary strings

We compute the asymptotic induced matching number of the $k$-partite $k$-uniform hypergraphs whose edges are the $k$-bit strings of Hamming weight $k/2$, for any large enough even number $k$. Our lower bound relies on the higher-order extension of the well-known Coppersmith-Winograd method from algebraic complexity theory, which was proven by Christandl, Vrana and Zuiddam. Our result is motivated by the study of the power of this method as well as of the power of the Strassen support functionals (which provide upper bounds on the asymptotic induced matching number), and the connections to questions in tensor theory, quantum information theory and theoretical computer science. Phrased in the language of tensors, as a direct consequence of our result, we determine the asymptotic subrank of any tensor with support given by the aforementioned hypergraphs. In the context of quantum information theory, our result amounts to an asymptotically optimal $k$-party stochastic local operations and classical communication (slocc) protocol for the problem of distilling GHZ-type entanglement from a subfamily of Dicke-type entanglement.
Minimizing minor embedding energy: an application in quantum annealing

A significant challenge in quantum annealing is to map a real-world problem onto a hardware graph of limited connectivity. If the maximum degree of the problem graph exceeds the maximum degree of the hardware graph, one employs minor embedding in which each logical qubit is mapped to a tree of physical qubits. Pairwise interactions between physical qubits in the tree are set to be ferromagnetic with some coupling strength $F<0$. Here we address the question of what value $F$ should take in order to maximise the probability that the annealer finds the correct ground-state of an Ising problem. The sum of $|F|$ for each logical qubit is defined as minor embedding energy. We confirm experimentally that the ground-state probability is maximised when the minor embedding energy is minimised, subject to the constraint that no domain walls appear in every tree of physical qubits associated with each embedded logical qubit. We further develop an analytical lower bound on $|F|$ which satisfies this constraint and show that it is a tighter bound than that previously derived by Choi (Quantum Inf. Proc. 7 193 (2008)).
A fast online cascaded regression algorithm for face alignment

Traditional face alignment based on machine learning usually tracks the localizations of facial landmarks employing a static model trained offline where all of the training data is available in advance. When new training samples arrive, the static model must be retrained from scratch, which is excessively time-consuming and memory-consuming. In many real-time applications, the training data is obtained one by one or batch by batch. It results in that the static model limits its performance on sequential images with extensive variations. Therefore, the most critical and challenging aspect in this field is dynamically updating the tracker's models to enhance predictive and generalization capabilities continuously. In order to address this question, we develop a fast and accurate online learning algorithm for face alignment. Particularly, we incorporate on-line sequential extreme learning machine into a parallel cascaded regression framework, coined incremental cascade regression(ICR). To the best of our knowledge, this is the first incremental cascaded framework with the non-linear regressor. One main advantage of ICR is that the tracker model can be fast updated in an incremental way without the entire retraining process when a new input is incoming. Experimental results demonstrate that the proposed ICR is more accurate and efficient on still or sequential images compared with the recent state-of-the-art cascade approaches. Furthermore, the incremental learning proposed in this paper can update the trained model in real time.
Solving the maximum common subgraph problem on many-cores architectures

The Maximum Common Subgraph (MCS) Problem is a well known problem in literature. It has been proved to be an NP-hard problem, then it is often considered as not worthy to search for an exact solution due to its high complexity. Luckily, the ad-vent of newest computing technologies and processors, several algorithms have been developed to efficiently solve very complex problems. Given their still high time consumption, this thesis discusses the possibility to produce a GPU implementation under the CUDA environment of one of the most efficient strategies currently known, namely the McSplit algorithm Despite we find that such implementation it is indeed possible, experimental results showed that, considering the actual state of the CUDA APIs, it may be at least questionable to use this version against a standard CPU-only multi-thread implementation.