Reviewerly/exHarmony huggingface dataset:
Development of an Educational Software as Support for Learning English and Mayan Languages through the use of the Kinect Sensor

In the educational environment, the student and the teacher have a very important role in the teaching-learning process for the development of their skills, leading to the development of significant approaches that involve new forms of learning allowing a playful interaction with students, where they learn about new technologies.The aim of this paper is to show a basic tool as a teaching-learning strategy that will allow students to interact with the computer and Kinect, allowing the development of skills and gaining knowledge of English and Mayan language.The interface presented to the student is friendly and intuitive, so the student can learn and have fun at the same time.It's intended that this software improve the teaching-learning strategies and teachers can implement it in the classroom.
Subexponential-Time Algorithms for Finding Large Induced Sparse Subgraphs

Let C and D be hereditary graph classes. Consider the following problem: given a graph G in D, find a largest, in terms of the number of vertices, induced subgraph of G that belongs to C. We prove that it can be solved in 2^{o(n)} time, where n is the number of vertices of G, if the following conditions are satisfied: - the graphs in C are sparse, i.e., they have linearly many edges in terms of the number of vertices; - the graphs in D admit balanced separators of size governed by their density, e.g., O(Delta) or O(sqrt{m}), where Delta and m denote the maximum degree and the number of edges, respectively; and - the considered problem admits a single-exponential fixed-parameter algorithm when parameterized by the treewidth of the input graph. This leads, for example, to the following corollaries for specific classes C and D: - a largest induced forest in a P_t-free graph can be found in 2^{O~(n^{2/3})} time, for every fixed t; and - a largest induced planar graph in a string graph can be found in 2^{O~(n^{3/4})} time.
Development of the Criteria of Information Culture in Students’ Youth in the Context of Information-Hybrid Warfare

The article is devoted to topical problems of development of the criteria of information culture in students’ youth in the context of information-hybrid warfare; determination of the degree of this problem elaboration in theory and its practical accomplishment in pedagogy of higher professional education; revealing of educational process features under the conditions of information-hybrid warfare which make it possible to conduct scientific-and-pedagogical diagnostics of the current level of development of information culture in prospective teachers under the specified conditions. The fundamental nature of the concepts “diagnostic activity” and “diagnostics” are defined in the course of the given article. Key functions and the main purpose of pedagogical diagnostics (information support of the educational process management system in the context of determining the contents and the most advantageous methods of learning at a particular moment of the educational process) are characterized. The terms “criterion” and “indicator” are considered. In the structure of information culture of students’ youth such components as value-based, cognitive-communicative, interactive-technological and critical-reflexive are distinguished. On the background of the identified components of the information culture, the following criteria are distinguished: motivational-axiological, contensive-procedural, prognostic activity-based and analytical-resultative. The activity-based component reflects the ability of students’ youth to introduce into current practice modern educational technologies which contribute to the development of information culture. A detailed description of each of the criteria of information culture of students’ youth in the context of information-hybrid warfare is presented. According to the defined criteria, relevant indicators in terms of their content which reveal the fundamental nature of both the criteria and the components of the information culture are suggested. The prospects for further researches include the development of diagnostic tools to define the level of information culture in students’ youth.
Assessment of Optical Character Recognition Techniques for Hindi Language

Optical Character Recognition(OCR) is one of the actively researched areas in both industry and academia because of its potential applications.OCR is a widely used technology to recognize text inside images, such as scanned documents and photos.OCR technology is used to convert virtually any kind of images containing written text (typed, handwritten or printed) into machine-readable encoded text data.It is a common method of digitizing printed texts so that they can be electronically edited, searched, stored more compactly, displayed on-line, and used in machine processes such as cognitive computing, machine translation, text-to-speech and text mining.OCR engines are used to read typed (machine printed) characters.At present, there are several OCR engines available for usage.One such OCR engine is Tesseract.Tesseract is an optical character recognition engine that can be used with various operating systems.It can recognize over 100 different languages.It does various image processing operations internally before carrying out the actual OCR.Tessaract performs a reasonably good OCR, but there are certain cases where it is not good enough, which can result in a significant reduction in accuracy.The present work involves using different predefined functions and features of MATLAB and various techniques available in MATLAB for improving the efficiency and performance of Optical Character Recognition (OCR) for the Hindi language.The results of this work are subjected to comparison with an existing OCR engine.
To Avoid the Pitfall of Missing Labels in Feature Selection: A Generative Model Gives the Answer

In multi-label learning, instances have a large number of noisy and irrelevant features, and each instance is associated with a set of class labels wherein label information is generally incomplete. These missing labels possess two sides like a coin; people cannot predict whether their provided information for feature selection is favorable (relevant) or not (irrelevant) during tossing. Existing approaches either superficially consider the missing labels as negative or indiscreetly impute them with some predicted values, which may either overestimate unobserved labels or introduce new noises in selecting discriminative features. To avoid the pitfall of missing labels, a novel unified framework of selecting discriminative features and modeling incomplete label matrix is proposed from a generative point of view in this paper. Concretely, we relax Smoothness Assumption to infer the label observability, which can reveal the positions of unobserved labels, and employ the spike-and-slab prior to perform feature selection by excluding unobserved labels. Using a data-augmentation strategy leads to full local conjugacy in our model, facilitating simple and efficient Expectation Maximization (EM) algorithm for inference. Quantitative and qualitative experimental results demonstrate the superiority of the proposed approach under various evaluation metrics.
PENERAPAN LOCATION BASE SERVICE UNTUK MEMPERKENALKAN HOTEL DAN WISATA KULINER DI KOTA PEKALONGAN BERBASIS AUGMENTED REALITY

Pekalongan City is one of the batik producers in the national even international level. Besides batik &#x0D; tourism, Pekalongan City also has many interesting places that need to be explored. Therefore many &#x0D; hotels and culinary tours have sprung up. The obstacle faced by tourists is the number of hotels and &#x0D; culinary locations which are quite difficult to detect because they are not on the Pantura line. &#x0D; Responding to these problems, it is necessary to make an application that can handle these problems, &#x0D; one of them is the application of location based service to introduce hotels and culinary t ours in the &#x0D; city of Pekalongan based on augmented reality. In making the application using the waterfall method &#x0D; used for software development. As for the collection of data using observation and interview methods. &#x0D; This application can find out the destination location and the information available at its destination. &#x0D; By using the application you can find out the destination location in more detail, because in the &#x0D; application can know the position of the location to be located on the right or the left, so it's easier to &#x0D; find the location. To develop the application to the next stage the developer can add location and user &#x0D; usage engine usage. In addition to the layar to find out the level of accuracy between existing engines.&#x0D; Keywords: Local base service, Hotels, Culinary tours, Augmented reality, Layar
DEDICATIONS, FOREWORDS AND AFTERWORDS TO UKRAINIAN CYRILLIC OLD-PRINTED EDITIONS: ISSUES AND PROSPECTIVES OF SCIENTIFIC BIBLIOGRAPHIC REGISTER

The research is devoted to the issue of dedications, forewords and afterwords to Ukrainian Cyrillic old-printed editions of 16-18th cc. cataloging. The aim of the article is to formulate principles of dedication, foreword and afterword presentation as informationally valuable elements of old-printed edition for the reader of particular library fund. The achievement of this aim demands revision of such texts specific features that influence to the form of their scientific bibliographic register; analysis of existed bibliographic best practices of old-printed edition apparatus elements meta description; elaboration of cataloging and systematization principles, relevant for texts, included in copies of specific library fund. The study shows that compliance of effective dedication, foreword and afterword to old-printed edition analytical bibliographic description demands unification of their author, title, source, physical shape and shelf-number presentation. The main issues that complicate these texts register are diversity of formal characteristics and informational capacity of their titles; variations of dedications and prefaces texts in different copies of the same editions; incompleteness of copies, presented in library fund. The issue of dedication and foreword long titles and absent title of afterword is proposed to resolve by elaboration of short unified formulas that include author, identification of text role in book structure and addressee (if relevant). The informational importance of certain text is proposed to mark with special subject rubrics and keywords that reflect cultural and historical value of the source and gives possibility of its multi aspect search. The issues of texts variations and copies incompleteness are to be resolved by identification of shelf-number to each copy, which includes full version of relevant text. The unified form of dedications, forewords and afterwords to Ukrainian Cyrillic old-printed editions bibliographic description and multi aspect search function would give an opportunity to enrich electronic catalogue of library fund with reader-focused information on valuable sources of national history and book culture.
Verb Class Induction with Partial Supervision

Dirichlet-multinomial (D-M) mixtures like latent Dirichlet allocation (LDA) are widely used for both topic modeling and clustering. Prior work on constructing Levin-style semantic verb clusters achieves state-of-the-art results using D-M mixtures for verb sense induction and clustering. We add a bias toward known clusters by explicitly labeling a small number of observations with their correct VerbNet class. We demonstrate that this partial supervision guides the resulting clusters effectively, improving the recovery of both labeled and unlabeled classes by 16%, for a joint 12% absolute improvement in F1 score compared to clustering without supervision. The resulting clusters are also more semantically coherent. Although the technical change is minor, it produces a large effect, with important practical consequences for supervised topic modeling in general.
Textbook Readibility Assessment of K13 English Textbook For Twelfth Grade

English textbook for twelfth grade of SMA which is published by Ministry of Education and Culture is a compulsory textbook which is based on national curriculum 2013 to support education in Indonesia. This study aims to investigate the readability level of the English textbook. It uses descriptive quantitative method to examine the readability of this book. The data are in the form of texts derives from transactional and interpersonal text, short functional text, reading text, instructional text inside the book. There are 180 data taken from those four texts. They are analyzed by using Miyazaki EFL readability formulae as a tool to measure the readability level whether it is suitable or not for twelfth grade students. According to Miyazaki EFL readability test, the easiest text from the book is in 5th grade and the hardest one is in post-school/university grade. But the most frequent grade appear in this book is in 8th and 9th grade which is 77 data (texts). The average of this book score is 63.2 which means it is suitable for 8th and 9th grade. This book is too easy for twelfth grade according to Miyazaki EFL readability test.
3-D Oral Shape Retrieval Using Registration Algorithm

In this paper, we present a novel 3-D oral shape retrieval using correntropy-based registration algorithm. Fast matching as the traditional registration method can achieve, its registration accuracy is disturbed by noise and outliers. Since the 3-D oral model contains a large amount of noise and outliers, it may lead to a decrease in registration accuracy, which affects the accuracy of retrieval rate. Therefore, we introduce the correntropy into the rigid registration algorithm to solve this problem. Although the noise and outliers are suppressed by the correntropy-based algorithm, these noises and outliers still participate in the registration. For better retrieval, we choose the matched point cloud data and use mean squared error results to judge the individual differences of the shape. Finally, the accurate retrieval of the oral shape is realized. Experimental results demonstrate our 3-D shape retrieval algorithm can be successfully searched under different models, which can help forensics use the characteristics of biological individuals to accurately search and identify, and improve recognition efficiency.
The Impact of Green Marketing on Green Consumer Behaviour in Jordan

These days, businesses are conscious that they cannot carry on without being aware of environmental problems. Firms generally face more limited natural resources, and must develop new or alternative ways of marketing. This is how green marketing comes into view, as it looks at how marketing activities utilize those limited resources while satisfying consumers&amp;#39; wants― both of individuals and industry― as well as achieving the organization&amp;#39;s objectives. &#x0D; &#x0D; The general purpose of this study is to discuss the impact of green marketing strategies on green consumer behaviour in Jordan. This study used the quantitative method to gather accessible data from the study sample. The variables present in this study are marketing mix (product, place, price, promotion), and green consumer behaviour. The Partial Least Squares (PLS) approach as a statistical method was used to analyse the data. The population of the study is 2000 daytime visitors of a traditional day in two Amman malls, from which a sample of 500 randomly distributed questionnaires was analysed, according to 32 items. Results indicated that three out of four variables had a statistically significant relationship to green consumer behaviour. The exception was for the green price factor, which did not show a discernible statistical impact.
InterCriteria Analysis of body composition measurements data, associated with obesity among college students

This study assessed the body composition indices associated with overweight/obesity among students at Medical College of University "Prof.Dr. Asen Zlatarov" in Burgas and also to verify the test assessment methods using the application of InterCriteria Analysis (ICA) to the data obtained from the tests.The data was analyzed in search of correlations between the results from the method of testing for some anthropometric measurements and certain findings are outlined and commented.
Korelasi Antara Fixation Eye Tracking Metric dengan Performance Measurement Usability Testing

Not all websites have fulfilled basic principles such as accessible and easy to use (usable). There are several measuring methods that already exist. In this research, the measurement is done by combining 2 measuring methods namely usability testing and eye tracking because the measurement is done with props that are eye tracking, so that at the same time we can measure the indicator usability testing and eye tracking metrics. So researchers to know the level of relationship or correlation between usability testing indicators and eye tracking metrics. The type of research conducted is a type of associative research with quantitative and qualitative approaches. Where both of these methods will result in quantitative data such as time on task, difficulty ratings, fixation duration mean and time to first fixation. Qualitative Data is obtained from playing the recorded results and conducting interviews to examine the results of eye movements when testing is the same as the opinions or perceptions of each participant. Results of a correlation test Pearson product moment acquired correlation or relationship between time on task with fixation duration mean, time on task with time to first fixation, difficulty ratings with fixation duration mean, difficulty ratings with time to First fixation. There are two possibilities of usability measurement performance indicators with eye tracking proving a significant correlation means measurement of usability using eye tracking can be used as an alternative in doing more usability measurement Accurate with significance levels &gt; 2.048 in subsequent studies.
A New Method for Error Analysis of Binocular Stereo Vision System

BSV (Binocular Stereo Vision) system is a simple and efficient approach for robots. However, a BSV system exists to excessive errors during applications. Under the condition of fixed baseline and focal length, two error factors affecting the binocular vision system are analyzed in this paper: (i) the inclination angle of the binocular camera, and (ii) the lateral distance from an object to camera. Then, error analysis was experimentally performed on the calibration board row (X-axis direction) and column (Y-axis direction). The error is corrected by linear fitting, and it is reduced by 2% by correction. Finally, substantial experiments are carried out to verify the correctness of the theoretical.
LANGUAGE ATTITUDE TOWARDS BLENDED LEARNING MODEL FOR WRITING SUBJECT

The aim of this research is to analyze students’ language attitude towards blended learning model for writing subject. The mix method was applied through the combination of quantitative data and qualitative data. The former was administered to the students through the four-point likert scale survey. The latter was obtained from the interview. The data was processed and computed by employing SPSS 24, then explained descriptively. The result of the study was classified into three categories namely affective, cognitive, and conative. The first was at moderate level with range 2.51--3.50. The second was at moderate level with range 2.51--3.50. The last was at moderate level with range 2.51--3.50. Overall, it is confirmed that the students positively behave on blended learning model in writing subject. In emphasizing the result, the interview illustrated that students showed good attitude on writing subject when taught by using blended learning model.
Efficient Privacy Preserving Cross-Datasets Collaborative Outlier Detection

Outlier detection is one of the most important data analytics tasks and is used in numerous applications and domains. It is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. The accuracy of the outlier detection depends on sufficient data. However, the underlying data is distributed across different organizations. If outlier detection is done locally, the results obtained are not as accurate as when outlier detection is done collaboratively over the combined data. Unfortunately, competitive advantage, privacy concerns and regulations, and issues surrounding data sovereignty and jurisdiction prevent many organizations from openly sharing their data. In this paper, we address precisely this issue. We present new and efficient protocols for privacy preserving outlier detection to find outliers from arbitrarily partitioned categorical data. Our protocols fall in the two-server model where data owners distribute their private data among two non-colluding servers who detects on the joint data using secure two-party computation (2PC). Our method is based on Local Distance-based Outlier Factor (LDOF) using the relative location of an object to its neighbours to determine the degree to which the object deviates from its neighbourhood. We provide the privacy guarantee by using secure multiparty computation techniques. We implement our system in C++ on real data. Our experiments validate that our protocols are both effective and efficient.
On the Problem of Covering a 3-D Terrain

We study the problem of covering a 3-dimensional terrain by a sweeping robot that is equipped with a camera. We model the terrain as a mesh in a way that captures the elevation levels of the terrain; this enables a graph-theoretic formulation of the problem in which the underlying graph is a weighted plane graph. We show that the associated graph problem is NP-hard, and that it admits a polynomial time approximation scheme (PTAS). Finally, we implement two heuristic algorithms based on greedy approaches and report our findings.
Implementation via Rights Structures with Minimal State Spaces

In a recent paper, Koray and Yıldız (2018) propose implementation via rights structures ( Γ -implementability), which offers a simple framework for implementation formulated in a language closer to real-life mechanisms.They show that canonical rights structures, which renders a natural interpretation, are sufficient for implementing any image monotonic rule.However, one can question the simplicity of the rights structure on the basis of its number of states.In this paper, we address this question by formulating a rights structure which implements any Γimplementable social choice rule with a minimal state space among all individual-based rights structures.
Deterministic Value-Policy Gradients

Reinforcement learning algorithms such as the deep deterministic policy gradient algorithm (DDPG) has been widely used in continuous control tasks. However, the model-free DDPG algorithm suffers from high sample complexity. In this paper we consider the deterministic value gradients to improve the sample efficiency of deep reinforcement learning algorithms. Previous works consider deterministic value gradients with the finite horizon, but it is too myopic compared with infinite horizon. We firstly give a theoretical guarantee of the existence of the value gradients in this infinite setting. Based on this theoretical guarantee, we propose a class of the deterministic value gradient algorithm (DVG) with infinite horizon, and different rollout steps of the analytical gradients by the learned model trade off between the variance of the value gradients and the model bias. Furthermore, to better combine the model-based deterministic value gradient estimators with the model-free deterministic policy gradient estimator, we propose the deterministic value-policy gradient (DVPG) algorithm. We finally conduct extensive experiments comparing DVPG with state-of-the-art methods on several standard continuous control benchmarks. Results demonstrate that DVPG substantially outperforms other baselines.