Reviewerly/exHarmony huggingface dataset:
Teaching English For Young Learner in Private IslamicElementary School at MI Baladan Amina Academic Year 2019/2020.

This research starts from the fact that Teaching English for children has becomeimportant in recent years. In Indonesia, many primary schools, including Islamicelementary schools. Teach delightful English need more effort especially for younglearners who have characteristics that can affect the atmosphere of classroom learningand the choice of learning strategies by the teacher. so, teaching English to younglearners brings a number of challenges. improvements and proficiency levels by teacheris the challenges for teaching English to young learners This study analyzed teachingEnglish for young learners at Madrasah Ibtidaiyah Baladan Amina Banjarbaru.Therefore, the researcher wanted to find out how learning process of English foryoung learners seen from the main components of learning and what are the faced bythe teacher toward the teaching English for young learners at Madrasah IbtidaiyahBaladan Amina Banjarbaru.In order to find out how teaching English for young learners at MadrasahIbtidaiyah Baladan Amina Banjarbaru, the researcher used qualitative research as themethodology of this study. The method used is descriptive. The research subjects areEnglish subject teachers who teach in grade 1, 2, and 3. The researcher conductedobservation, interview, and field note as data collection technique. The result from sixtime observations in grade 1, 2, and 3 at Madrasah Ibtidaiyah Baladan AminaBanjarbaru. Through qualitative descriptive analysis techniques according to Miles andHuberman the analytical methods are: data reduction, data presentation and drawingconclusions / verification. the result showed that teaching proccess of English foryoung learners is started from Planning, Learning Implementation, and Evaluation.and teaching proccess of English for young learners goes well even though there arestill found some problem such as poor of teaching materials and added with the lack ofEnglish teachers so that the English teacher teaches English in six classes and at sametime serves as the school principal.
Friction for privacy: Why privacy by design needs user experience design

IRMA is an open source identity platform that is run by the not-for-profit Privacy by Design foundation in The Netherlands. It grew out of academic research at Radboud University Nijmegen - and originally at IBM Research at Zurich in the 1990s. IRMA is now clearly gaining momentum and is being integrated in various ways, especially in healthcare, (local) government, and also in commercial areas such as insurance. The techniques underlying IRMA have been developed with privacy protection as explicit goal. This article explores the impact of this privacy focus on the user experience (UX) and on the ongoing (re)design of the interface of the IRMA app. The authors are both closely involved in the development of IRMA.
Improving the efficiency of neural networks with virtual training data

At Széchenyi István University, an autonomous racing car for the Shell Eco-marathon is being developed.One of the main tasks is to create a neural network which segments the road surface, protective barriers and other components of the racing track.The difficulty with this task is that no suitable dataset for special objects, e.g.protective barriers, exists.Only a dataset limited in terms of its size is available, therefore, computer-generated virtual images from a virtual city environment are used to expand this dataset.In this work, the effect of computer-generated virtual images on the efficiency of different neural network architectures is examined.In the training process, real images and computer-generated virtual images are mixed in several ways.Subsequently, three different neural network architectures for road surfaces and the detection of protective barriers are trained.Past experiences determine how to mix datasets and how they can improve efficiency.
BISON: BM25-weighted Self-Attention Framework for Multi-Fields Document Search.

Recent breakthrough in natural language processing has advanced the information retrieval from keyword match to semantic vector search. To map query and documents into semantic vectors, self-attention models are being widely used. However, typical self-attention models, like Transformer, lack prior knowledge to distinguish the importance of different tokens, which has been proved to play a critical role in information retrieval tasks. In addition to this, when applying WordPiece tokenization, a rare word may be split into several different tokens. How to translate word-level prior knowledge into WordPiece tokens becomes a new challenge for the semantic representation generation. Moreover, web documents usually have multiple fields. Due to the heterogeneity of different fields, simple combination is not a good choice. In this paper, We propose a novel BM25-weighted Self-Attention framework (BISON) for web document search. By leveraging BM25 as prior weights, BISON learns weighted attention scores jointly with query matrix Q and key matrix K. We also present an efficient whole word weight sharing solution to mitigate prior knowledge discrepancy between words and WordPiece tokens. Furthermore, BISON effectively combines multiple fields by placing different fields into different segments. We demonstrate BISON is more efficient to capture the topical and semantic representation both in query and document. Intrinsic evaluation and experiments conducted on public data sets reveal BISON to be a general framework for document ranking task. It outperforms BERT and other modern models while retaining the same model complexity with BERT.
Entity Type Prediction in Knowledge Graphs using Embeddings

Open Knowledge Graphs (such as DBpedia, Wikidata, YAGO) have been recognized as the backbone of diverse applications in the field of data mining and information retrieval. Hence, the completeness and correctness of the Knowledge Graphs (KGs) are vital. Most of these KGs are mostly created either via an automated information extraction from Wikipedia snapshots or information accumulation provided by the users or using heuristics. However, it has been observed that the type information of these KGs is often noisy, incomplete, and incorrect. To deal with this problem a multi-label classification approach is proposed in this work for entity typing using KG embeddings. We compare our approach with the current state-of-the-art type prediction method and report on experiments with the KGs.
Identification of patterns associated with areas of epithermal alteration, through responses spectral using ASTER images

Knowing the potential of natural resources associated with mining activity is critical to decision-making especially at the exploration stage, this allows organizations to assess whether the area of interest is viable, to continue with post-exploration processes of mining deposits. So, it is important to get new exploration processes that cover very wide surfaces, be low-cost and reveal high reliability, one of these alternatives is the use of satellite imagery based on the principles of spectral responses. Therefore, The objective of the research was to search for a technique that considers the quantitative criteria to relate and identify the objects by using the spectral response values whose spectral response patterns are different, in an area whose cutting law for exploitation is feasible (zones of epithermal alteration), with the spectral response values of compounds associated with alteration zones of the United States Geological Survey (USGS), using two statistical criteria, correlation analysis and quadratic mean error, which have revealed good performance in identifying objects from the comparison of spectral responses.
PENERAPAN ALGORITMA K-MEANS CLUSTERING SEBAGAI STRATEGI PROMOSI PENERIMAAN MAHASISWA BARU PADA UNIVERSITAS HASYIM ASY’ARI JOMBANG

Admission of new students at the Hasyim Asy'ari University in Jombang is held every year. To more of the newstudents, admissions Committee conducted several promotions as very important early activities such as: online,banners, brochures, school events, and orally with student roles and Alumni. The number of competition infinding new student applicants, requiring the University of Hasyim Asy'ari to conduct analysis of several waysof promotion that have been done so that the promotion strategy can be seen which is more precise and effective.This research will conduct grouping/clustering of districts or cities based on certain attributes in a Web-basedapplication. The method used in this study is a K-means clustering algorithm that can group student data intomultiple clusters based on similar attribute agreements. The attributes used are hometown, online, oral,banners/billboards, brochures and events. At this Peletitian generate a total of 5 clusters (k = 5) with the firstcluster 20 hometown with the most effective promotional media online and oral, the second cluster of 31 Origincities with the most effective promotional media oral and online, the third cluster of 4 cities originating withmedia The most effective promotion of events and banners, the fourth cluster of 15 hometown with the mosteffective promotional media brochures and oral, the fifth cluster 2 hometown with the most effective promotionalmedia oral and event. The results of this study were used as a recommendation to determine a promotionalstrategy based on the promotional media of each cluster formed.Keywords: Promotion strategy, Admission of New Students, K-means Algorithm, Clustering
DEEP LEARNING APPROACH FOR FACIAL EXPRESSION RECOGNITION

Facial expression refers to variations of faces in response to variations in humans internal emotions. Face expres- sion classification and feature extraction are the two most impor- tant task performed in facial expression recognition. Converting facial expressions into numerical values using feature extraction techniques. There are various feature extraction algorithms avail- able. Principal component analysis, Linear Discriminant analysis are some of the facial feature extractors. Classifications are used for generating facial categories. Deep Learning based facial expression recognition algorithm becomes popular nowadays. Artificial Intelligence approach provides more accuracy and efficiency than old recognition methodologies. Social networking applications like Facebook, instagram uses newly developed deep learning algorithms for improved user experience. Proposed work consists of deep learning based facial expression recognition. Deep learning uses advanced machine level models that are backed with newest algorithms. A convolutional neural network is newer technique for classification and feature extraction. A deep learning open source python libraries called keras and tensorflow are used for implementing the facial expression recognition. The performance of the deep learning technique is measured using confusion matrix. Jaffe database, a Japanese person face images with various face emotions is used to test and train the deep learning model. The performance of the proposed technique is efficient and less computational.
The Ideology and Contextual Analysis of the State of the University Address of Dr. Jose L. Bacusmo of the Visayas State University

Public speaking is one of the common ways in which the majority of institutional leaders have opted to use their ideologies in a specific context. The world of speech in narratives can be a material for critical discourse analysis, as this, in turn, provides the researcher with an opportunity to study the context of the spoken narrative delivered before the crowd. In this academic paper samples employed three State of the University Addresses delivered by former Visayas State University President Dr. Jose L. Bacusmo during the period July 2012 to July 2014. These samples were used for data analysis using MAXQDA 11, and the tools used for data analysis helped to determine the number of terms used, context analysis, and ideologies in the three speeches delivered by Dr. Jose L. Bacusmo, President of Visayas State University.
Sustaining Practices for On Demand &amp; Deterministic Data Publishing using Privacy Preservation

The time has changed on behalf of modular intervention of data and users.The data categories can be significantly determined.Once the category of published data can be interrogated the contextual determination becomes vital.In today"s age of hand held devices, smart phones, the data is just seat back in cloud and as per the use called on demand.Thus deterministic & collaborative data publishing must be addressed to promote the sustainable privacy metrics at peers.The healthcare data is the constraint collaborative data on which privacy of patient, hospital resources and vivid data analytical intervention can be applicable.If this leaks or untrue its privacy metrics before or after publishing, the trust among communicating parties can be challenged.So by enabling this privacy preserving methodologies for the critical data suite, the scope of this work become sensible.
Do We Need a New Conception of Authorship

Here’s the core idea that I want to suggest: that one of the concerns that we have with conceptual art going forward, and with the question of copyrightability, is that copyright law, for a really long time now, has had a nascent and unstated theory of authorship that connects to the way in which we conceptualize the connection between inputs and outputs, agency in the real world, and the nature of the human connection to the work—and that these works of conceptual art are calling that theory into question. And part of the concern is that this test and this conception, being unstated—when we take a step back to try and understand how we might update it or liberate it from these conceptions, we have a hard time wrestling with it, to nail it down. And so, what I want to leave you with is the question of whether it’s time to update our traditional conception of authorship.
역사교과서 서술 변화의 요인과 교재화

This study analyzed factors of changed descriptions in history textbooks and explored materializing strategies for history teaching. There are three factors that change the description in history textbooks.The first factor is the historians’ researching achievements. However, even though new research results emerge, it is generally late for the textbook authors to describe them in the textbooks. This is because they tend to postpone to describe changed contents in the textbook until researched findings are acknowledged by academic discipline.The second factor is the difference in historical interpretation. If the national curriculum or standards for history textbook adopts any of interpretations, the descriptions will be changing. However, the textbook author’s own historical interpretation sometimes alters the narrative, and sometimes individual scholar’s opinions are included in the writing textbook criteria or during authorizing the textbook.The third factor is derived from political and social problem. When a social conflict over the contents of history textbook happens or a controversy arises, the textbook authors describe its contents to avoid in a direction being swept away rather than based on their own views or interpretations.Depending on what factor causes the change in the history textbook contents, the strategy for materializing them are different. Changes in the textbook description can be used to help students acquire historical knowledge if they reveal new historical facts or correct misleading facts. Changes in the textbook contents by historical interpretation can be used as the teaching material for students to interpret and evaluate historical facts. This kind of history teaching gives students the experience of ‘doing history’. Changes in the textbook descriptions by the political and social problem can be used as the teaching material for critical reading. In this lesson, the object of critical reading is mainly the national view. However, the author''s personal point of view may be included in the change of textbook description. Such change in the textbook descriptions can be read critically. These three factors are not clearly distinguishable, and two or more of them often work at the same time.
SELF-MANAGEMENT AS A MECHANISM OF SELF-IMPROVEMENT OF PRIMARY SCHOOL TEACHERS

The article analyzes modern approaches to the definition of self-management and self-improvement of the individual, reveals their frequent identification and proposes to distinguish these concepts by the basic nature of actions: management and organization of any human activity (during self-management), and the movement to perfection (in the process of self-improvement). They also point to their common features: autonomy, self-determination, and focus on the subject itself (recorded in the “self-” section). After all, self-improvement is defined as an independent, self-determined activity of a person aimed at improving oneself, and self-management is defined as an independent, self-determined activity of a person aimed at organizing and optimizing any human activity. In the case of self-organization of professional and pedagogical self-improvement, self-management is considered as a mechanism of self-improvement, which consists in the organization of all stages of self-improvement of the teacher-tutor, ensuring their effectiveness through the implementation of productive technologies of self-management. Self-management provides the effectiveness of self-improvement for primary school teachers by optimally managing this activity at its various stages: from diagnosis, goal setting and planning to implementation, control and correction. The basic functions of self-management, which traditionally determine goal setting, planning, decision-making, execution, control and correction, information and communication, fully correspond to the main stages of self-improvement of the teacher-educator, acting as mechanisms for their implementation. The correlation of the stages of self-improvement and the functions of self-management contributes to the awareness of their close interconnection and facilitates the use of basic methods and techniques of self-management due to their attachment to the corresponding stages of self-improvement. Selected specificity of pedagogical activity of primary school teachers, which is a frequent change of topics with the constancy of student and parental composition, is reflected in the peculiarities of their professional self-improvement, and needs to take into account in the process of self-management of this specific elementary school teacher. Thus, professional and pedagogical self-management (self-organization, self-management) we are considered as specific activity of the teacher, based on technologies of efficient use of time and purposeful regulation of behavior and actions, aimed at organizing their own activity in various spheres of life and development, acts as an important mechanism, which ensures the effective organization of all forms and stages of teacher’s work on themselves.
Lineamientos para construir actividades pedagógicas basada en gestores de contenidos

The impact that technology has reached worldwide in education, leads to research on a set of problems inherent in the acquisition of learning. Based on this problem, the present investigation was developed, the objective of which was to generate theoretical guidelines for the construction of pedagogical activities linked to the different types of perception intelligence dominant in higher education students, based on learning styles according to the Bandler model. and Ginder. Methodologically, a documentary study was carried out with a descriptive design. As results, there is the formulation of theoretical guidelines aimed at identifying the type of intelligence of dominant perception of university students, according to the Neurolinguistic Programming model. In conclusion, it is highlighted that the construction of pedagogical activities linked to the different types of perceptual intelligence dominant in students and content managers.
Geomatics data management system

The efficient storage and processing of raw dataset from topographic and geodetic surveys are preponderant factors. Currently, the collection of such information is performed through different types of sensors, and each sensor presents its own raw data in different formats. It is therefore important to develop a data management system that would be able to properly manage these different data, allowing the user to retrieve and apply them conveniently, at any time, simply and quickly. For this purpose, this article proposes a data management system for this type of application, based on a set of control indexes of a representative primary key common to all elements of the database. The quality of the proposed data management system was proven by a dataset of a geodetic structural monitoring project.
Experimental Research of Motivational and Reflexive Components of Students’ Reading Culture

-The authors have defined the content of the concepts of reading culture and to reveal the real state of the level of development of the structural components of students' reading culturefor the first time with the help of experimental research. The conducted content analysis of the category of reading culture substantiated its essence. Structural components of students' reading culture were revealed. The experimental work was done to determine the levels of structural components of students' reading culture. The purpose is to analyze the state of studying the problem of students' reading culture development using psychological, philological, pedagogical, sociocultural, and communicative approaches and to present the results of diagnostics of the real state of its structural components.
Il principio d’eguaglianza nell’ambito del Biodiritto

The article deals with the principle of equality in the field of biolaw. It takes into consideration some examples concerning fundamental rights and freedom, in the light of the relationship between law and science. It considers informed consent as an instrument of equality and analyses the role played by science in the field of biolaw.
Beginning with Weka and R Language

Chapter Objectives✓ To learn to install Weka and the R language✓ To demonstrate the use of Weka software✓ To experiment with Weka on the Iris dataset✓ To introduce basics of R language✓ To experiment with R on the Iris dataset
The Impact of Groundwater Salinity on the Quality of Agricultural Crops in the Ishaqi Area

The study of the effect of groundwater salinity on the quality of agricultural crops in the Ishaqi area aims to identify the percentage of salts of groundwater in the region and to identify areas of high and low percentage as well as to determine the spatial distribution of groundwater abundance to be relied upon in determining the areas of distribution of different agricultural crops from Through the adoption of modern geographic technologies (GIS) to advance the reality of groundwater in the region and benefit from it in various investments by analyzing the hydrological characteristics of the groundwater spatially and its chemical analysis, studies have reached several The most important results: