Reviewerly/exHarmony huggingface dataset:
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Development of cognitive activity in future teachers

This article provides a pedagogical basis for the professional training of future teachers and their learning activities, and describes the methods and techniques for the development of learning activities. The main criteria for professional training are the practical training of the future specialist and the acquisition of knowledge, skills and abilities in the field of specialization, the level of adaptation to the requirements of professional activity. The works of medieval thinkers who lived and worked in the Near and Middle East emphasize the importance of the type, principle, structure, and criteria of scientific knowledge in relation to human mental development and perfection.
Machine Learning Based Model Development with Annotated Database for Indian Specific Object Detection

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Now-a-days, Advanced driver-assistance systems (ADAS) is equipping cars and drivers with advance information and technology to make them become aware of the environment and handle potential situations in better way semi-autonomously. High-quality training and test data is essential in the development and validation of ADAS systems which lay the foundation for autonomous driving technology.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;ADAS uses the technology like radar, vision and combinations of various sensors including LIDAR to automatize dynamic driving tasks like steering, braking, and acceleration of vehicle for controlled and safe driving. And to integrate these advance technologies, the ADAS needs labeled data to train the algorithm to detect the various objects and moments of driver. Image annotation is one the well-known service to create such training data for computer vision.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;There are number of open source annotated datasets available viz. COCO, KITTI etc. But these datasets are limited to either US or European road environment scenarios. There is hardly any dataset available for Indian Specific road conditions. In order to capture all the India Specific objects on road, we are capturing data through various environmental conditions, road conditions and annotating objects on the collected camera images. 2-D bounding boxes are being used to annotate objects in an image.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;These annotated images will then be used to train a machine learning model. Finally this trained model will be then used to detect Indian specific objects with real time data acquired through camera sensors mounted on the vehicle. Object detection is one of the prime aspects for ADAS functionality. The complete process will demonstrate end to end solution for object detection techniques from data generation to real-time object identification and recognition.&lt;/div&gt;&lt;/div&gt;
Generalization Guarantees for Neural Architecture Search with Train-Validation Split

Neural Architecture Search (NAS) is a popular method for automatically designing optimized architectures for high-performance deep learning. In this approach, it is common to use bilevel optimization where one optimizes the model weights over the training data (lower-level problem) and various hyperparameters such as the configuration of the architecture over the validation data (upper-level problem). This paper explores the statistical aspects of such problems with train-validation splits. In practice, the lower-level problem is often overparameterized and can easily achieve zero loss. Thus, a-priori it seems impossible to distinguish the right hyperparameters based on training loss alone which motivates a better understanding of the role of train-validation split. To this aim this work establishes the following results. (1) We show that refined properties of the validation loss such as risk and hyper-gradients are indicative of those of the true test loss. This reveals that the upper-level problem helps select the most generalizable model and prevent overfitting with a near-minimal validation sample size. Importantly, this is established for continuous search spaces which are highly relevant for popular differentiable search schemes. (2) We establish generalization bounds for NAS problems with an emphasis on an activation search problem. When optimized with gradient-descent, we show that the train-validation procedure returns the best (model, architecture) pair even if all architectures can perfectly fit the training data to achieve zero error. (3) Finally, we highlight rigorous connections between NAS, multiple kernel learning, and low-rank matrix learning. The latter leads to novel algorithmic insights where the solution of the upper problem can be accurately learned via efficient spectral methods to achieve near-minimal risk.
Innovative methods in improving the pedagogical skills of teachers

The purpose of the study of this article was to quantitatively analyze the relationship between the introductions of innovative teaching methods and improve the pedagogical skills of teachers. The research methodology is based on a comparative analysis of scientific research to determine changes in the globalization index in education and identify innovation links in terms of ten European countries during 2015-2019 based on data from The Global Innovation Index (2020) and Eurostat (2020). As a result, the relationship between education and innovation and its integration into the educational process on the example of ten European countries during 2015-2019. The factors determining the innovative activity of the country are established: availability and access to information and communication technologies, global research and development companies, knowledge creation, financial investments in education, innovative relationships, creation of mobile applications, etc. The practical value is in the possibility of implementing the results in national strategies for the introduction of innovative methods in improving the pedagogical skills of teachers.
명시적 계사문 연구: 프랑스어와 한국어를 중심으로

This paper analyzes two similar types of copular sentences in Korean. Usually, the copular sentences can be divided into predicational (PCS) and specificational (SCS). The characteristics of SCS are (i) the connectivity effect, (ii) the fact that the sentence-initial noun phrase has a predicate-like property and (iii) that it tends to be interpreted as the topic of the sentence. In this study, it is shown that in Korean, there, in fact, do exist SCSs that present all the above-mentionned characteristics of SCS. Such Korean SCSs have a sentence-initial DP marked with -nun. However, copular sentences with a -ka-marked DP as the sentence-initlial element, also show the characteristics of SCS, except (iii). Such -ka-marked DPs are usually neutral subject of the sentence. The difference between those two types of copular sentences may seem minimal, but by analyzing some novels in Korean and their French versions, I conclude that the difference is real.
The Relationship Between Emotional Intelligence (EQ) and Student Learning Outcomes

Abstract : The problems examined by the research were 1) How to describe the emotional intelligence of fifth grade students of SD Group I, Tanete Riattang Barat District, Bone Regency; 2) What is the description of the learning outcomes of students in SD Group I, Tanete Riattang Barat District, Bone Regency;  3) Is there a relationship? which is significant between emotional intelligence and the learning outcomes of grade V SD Gugus I, Tanete Riattang Barat District, Bone Regency. The research objectives were 1) Knowing the description of the emotional intelligence of the fifth grade students of SD Gugus I, Tanete Riattang Barat District, Bone Regency. 2) Knowing a description of the student learning outcomes of SD Group I, Tanete Riattang Barat District, Bone Regency. 3) Determine whether there is a significant relationship between emotional intelligence and the learning outcomes of grade V SD Gugus I, Tanete Riattang Barat District, Bone Regency. The research approach is a quantitative approach. This type of research is a descriptive quantitative research with a correlational model. The research data were obtained through questionnaires and documentation. The population in the study were all fifth grade students of SD Gugus I, Tanete Riattang Barat District, Bone Regency, the school year 2019/2020 totaling 200 students. The sample in the study amounted to 50. The data analysis techniques were descriptive statistical analysis and inferential statistical analysis. The results showed that there was a significant relationship between emotional intelligence (EQ) and student learning outcomes of SD Gugus I, Tanete Riattang Barat District, Bone Regency because because tcount ≥ ttable, namely tcount of 3.02 and ttable of 1.67722 and belonged to the moderate category. Keywords : Emotional intelligence , learning outcomes
Probing Multilingual Language Models for Discourse

Pre-trained multilingual language models have become an important building block in multilingual natural language processing. In the present paper, we investigate a range of such models to find out how well they transfer discourse-level knowledge across languages. This is done with a systematic evaluation on a broader set of discourse-level tasks than has been previously been assembled. We find that the XLM-RoBERTa family of models consistently show the best performance, by simultaneously being good monolingual models and degrading relatively little in a zero-shot setting. Our results also indicate that model distillation may hurt the ability of cross-lingual transfer of sentence representations, while language dissimilarity at most has a modest effect. We hope that our test suite, covering 5 tasks with a total of 22 languages in 10 distinct families, will serve as a useful evaluation platform for multilingual performance at and beyond the sentence level.
Hurdles faced by researchers while writing and publishing academic papers in English

This paper is a systematic literature review that gives the significance of having English writing skill in academic research writing for research scholars, students and teachers. In this regard, writing in English is very challenging for students, teachers, and research scholars, people whose first language was not English. Sermsook, K., &amp; et al. (2017).
Competency-based Cultivation Pathway of New Professional Farmers

The key to the implementation of the rural revitalization strategy rests with the revitalization of rural talents, and the new type of professional farmers is an integral component of rural talents. The revitalization of rural talents hinges on how to more effectively foster new professional farmers. On the basis of literature review concerning competency, this paper preliminarily constructs a cultivation path of new professional farmers, and gives the cultivation path combined with different competencies, thereby providing some reference on the cultivation of new professional farmers.
Echo-State Networks for Predicting ENSO Beyond One Year

&amp;lt;p&amp;gt;Most forecasting schemes in the geosciences, and in particular for predicting weather and&amp;lt;br&amp;gt;climate indices such as the El Ni&amp;amp;#241;o Southern Oscillation (ENSO), rely on process-based&amp;lt;br&amp;gt;numerical models [1]. Although statistical modelling[2] and prediction approaches also have&amp;lt;br&amp;gt;a long history, more recently, different machine learning techniques have been used to predict&amp;lt;br&amp;gt;climatic time series. One of the supervised machine learning algorithm which is suited for&amp;lt;br&amp;gt;temporal and sequential data processing and prediction is given by recurrent neural networks&amp;lt;br&amp;gt;(RNNs)[3]. In this study we develop a RNN-based method that (1) can learn the dynamics&amp;lt;br&amp;gt;of a stochastic time series without requiring access to a huge amount of data for training, and&amp;lt;br&amp;gt;(2) has comparatively simple structure and efficient training procedure. Since this algorithm&amp;lt;br&amp;gt;is suitable for investigating complex nonlinear time series such as climate time series, we&amp;lt;br&amp;gt;apply it to different ENSO indices. We demonstrate that our model can capture key features&amp;lt;br&amp;gt;of the complex system dynamics underlying ENSO variability, and that it can accurately&amp;lt;br&amp;gt;forecast ENSO for longer lead times in comparison to other recent studies[4].&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Reference:&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[1] P. Bauer, A. Thorpe, and G. Brunet, &amp;amp;#8220;The quiet revolution of numerical weather prediction,&amp;amp;#8221;&amp;lt;br&amp;gt;Nature, vol. 525, no. 7567, pp. 47&amp;amp;#8211;55, 2015.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[2] D. Kondrashov, S. Kravtsov, A. W. Robertson, and M. Ghil, &amp;amp;#8220;A hierarchy of data-based enso&amp;lt;br&amp;gt;models,&amp;amp;#8221; Journal of climate, vol. 18, no. 21, pp. 4425&amp;amp;#8211;4444, 2005.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[3] L. R. Medsker and L. Jain, &amp;amp;#8220;Recurrent neural networks,&amp;amp;#8221; Design and Applications, vol. 5, 2001.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[4] Y.-G. Ham, J.-H. Kim, and J.-J. Luo, &amp;amp;#8220;Deep learning for multi-year enso forecasts,&amp;amp;#8221; Nature,&amp;lt;br&amp;gt;vol. 573, no. 7775, pp. 568&amp;amp;#8211;572, 2019.&amp;lt;/p&amp;gt;
Effective Interest Region Estimation Model to Represent Corners for Image

One of the most important steps to describe local features is to estimate the interest region around the feature location to achieve the invariance against different image transformation. The pixels inside the interest region are used to build the descriptor, to represent a feature. Estimating the interest region around a corner location is a fundamental step to describe the corner feature. But the process is challenging under different image conditions. Most of the corner detectors derive appropriate scales to estimate the region to build descriptors. In our approach, we have proposed a new local maxima-based interest region detection method. This region estimation method can be used to build descriptors to represent corners. We have performed a comparative analysis to match the feature points using recent corner detectors and the result shows that our method achieves better precision and recall results than existing methods.
Analisis Trafik Pengguna XL Axiata Jakarta Selama Pandemi Covid-19 dengan Menggunakan Metode Regresi Linier

2020 is a very disturbing year for the whole world because in 2020 there is a deadly virus, the virus is called Covid-19. The Indonesian government has a strategy to deal with the Covid-19 virus, namely by implementing Large-Scale Social Restrictions (PSBB). Where the implementation of this PSBB requires residents to do more activities at home. To carry out activities at home, internet access is needed. Therefore, providers are the companies that benefit the most, providers are companies that provide internet services, one of which is XL Axiata. During the Covid-19 pandemic, XL Axiata company wants to conduct analysis for XL Axiata in the next year, whether the traffic of XL Axiata users has increased or decreased and how many devices need to be upgraded or safe. In conducting this analysis, it is necessary to perform fast data processing, data processing using the Data Mining method with Linear Regression techniques. The data to be processed will be obtained from the XL Axiata company, namely XL Axiata traffic data. By processing data using Linear Regression results in future predictions, the West Jakarta Municipality has increased per week by an average of 0.12%, the East Jakarta Municipality has decreased per week by an average of 0.27%, the Central Jakarta Municipality experiences the decline per week by an average of 2.31%, the South Jakarta Municipality experienced an increase per week by an average of 1.17%, and in the North Jakarta Municipality it decreased per week by an average of 0.12%.&#x0D;
The Structure Sentence Of The Reason Sentence In New Approach Japanese Intermediate Course Book : Semantics Study

In Japanese, there are many sentence structures and words that have synonymous meanings, that in Japanese is called Ruigigo, In its use because it has the same meaning, ruigigo is often misused in sentences, sometimes it is also difficult to find the right equivalent of the word in Indonesian.In New Approach Japanese Intermediate Course book, there are many ruigigo that can be used as research objects, one of which is the structure of sentences and words that have a meaning because. From the research that has been done, the author found 10 sentence stuctures related to words that have meaning of because.The purpose of author is to conduct a semantic study on sentence stuctures which states the reason in the New Approach Japanese Intermediate Course book is to help Japanese learners to understand meaning of sentence structures and words that related reasons.
Quality of Service Aware Cost Optimization for Online Gaming Services in IaaS Clouds

Prompted by the remarkable progress in cloud computing, more and more game service providers are starting to deploy their gaming applications on infrastructure as a service cloud. To ensure quality of service required by gamers, game service providers need to maintain a large number of cloud servers running game instances requested by players. Therefore, game service providers need not only pay attention to the costs of operating games, but also consider the quality of game services. This paper proposes a quality-of-service aware cost optimization scheme for online gaming services deployed on IaaS clouds which combines dynamic virtual machine provisioning and Long Short-Term Memory (LSTM) based gamer request dispatching to reduce the operating costs while ensuring quality of service. The effectiveness of our proposed scheme is assessed by simulation experiments based on the real-world data sets. The results show that, compared to the state-of-the-art approaches applied to similar problems, our scheme can achieve up to 35% cost savings while providing the just-good-enough quality of service to gamers under rapidly changing workloads.
Teleworking nowadays: what are the impacts on professional performance, well-being and work context?

From the pandemic imposed by the new coronavirus, teleworking proved to be a promising and desirable work arrangement alternative in times of social isolation, so that it has received increasingly priority attention in human resources management research agendas in the public sector. Federal Data Processing Service (Serpro) was one of the pioneers in adopting teleworking in Brazil and, therefore, it was the locus of this study. This study explored the positive and negative sides of teleworking in Serpro from the point of view of managers, teleworkers and colleagues and also compared teleworkers and no teleworkers with regard to the professional performance, work context and work well-being. The research method included questionnaires and textual analysis, analysis of variance and Mann-Whitney tests. About the positive sides of teleworking, the most relevant points were productivity increase and quality of life increase. About negative sides, technical difficulties and social interaction limitations can be pointed out. Results also showed that teleworkers have more positive perceptions about work context, professional performance and work well-being. This study provides a reflective look on adopting and implementing teleworking for public managers.
OCCAM-equivalent syntax with pure singleton descent structure

Minor corrections and semantically valid restrictions, and one significant but equivalent change, allow the occam 2.0 syntax to be expressed in a yacc-compatible syntax (actually flex and bison are used) with very desirable properties. A rich 13-level descent structure (descent happens when a syntactic object is part of a definition of another syntactic object) is all singletons except for two levels (one equivalent to expression and the other equivalent to process), and these are broken up themselves into singletons by extended descent (parenthesis plus square bracket enclosure count, and indentation count, respectively). This will allow formal proofs of syntactic object behavior, and hence whole language behavior, to be vastly simplified.
ACT에 기반한 집단상담이 대학생의 가치발견 및 전념행동 촉진에 미치는 효과

The purpose of this study was to restructure program and verity its effect based on Acceptance and commitment therapy to find out values of university students and execute the committed action according to the value. For this purpose, this study set research questions and used before, after, and follow up test designs for test and contr ol groups. 16 students from C University in G City volunteered and the group was formed with 8 for the test group and the rest 8 for the control group and total of 8 sessions were given to the test group for 4 weeks. The effect of program was verified according to Valued Learning Questionnaire, Value clarity, the evaluation tool for Commitment Questionnaire, session evaluation form, and the qualitative material collected during the close interview. According to the research results, ACT program had significant influence in improving the Index of valued life, Value clarity and Commitment. Lastly, the study suggested the significance of the study and for the later studies.
EDUCATION AND PANDEMIC. AN APPROACH TO A REALITY IN THE PROVINCE OF PASTAZA

After the appearance of the COVID-19 virus in China in 2019, the world took another reality, both socially and economically, by adopting very drastic measures in order to protect the world population from what later the World Health Organization WHO, on March 11, 2020 declared a Global Pandemic, and all countries would be involved in adopting measures of confinement to its population. In March 16, the National Government of Ecuador, declared a state of health emergency and issued regulations to regulate services in public and private institutions, one of those estates was education at all levels, and alternatives were sought so that they can establish the continuation of educational activity through virtual platforms, provided by the government and / or private, in such circumstances began a new paradigm of training and education in the country. In the province of Pastaza, the considerations and guidelines issued by the Ministry of Education were taken into account and online academic activities were continued, but with a reality different from the national average because the internet connectivity in homes does not reach 65%, limited to the urban area mostly, while possibly in the rural area this coverage would not reach levels of 15%, so the governmental directives to continue with studies at the basic and high school level are far from being achieved.
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition

We introduce a new scalable variational Gaussian process approximation which provides a high fidelity approximation while retaining general applicability. We propose the harmonic kernel decomposition (HKD), which uses Fourier series to decompose a kernel as a sum of orthogonal kernels. Our variational approximation exploits this orthogonality to enable a large number of inducing points at a low computational cost. We demonstrate that, on a range of regression and classification problems, our approach can exploit input space symmetries such as translations and reflections, and it significantly outperforms standard variational methods in scalability and accuracy. Notably, our approach achieves state-of-the-art results on CIFAR-10 among pure GP models.