Reviewerly/exHarmony huggingface dataset:
A study on the design of a practical arts laboratory for elementary level technology education in Korea

This study was conducted to confirm the specifications of the laboratory and the list of practice tools for technology education in elementary schools in Korea. For effective technology education, standardized laboratory specifications and a list of practice tools are needed. However, there were no standardized laboratory specifications and a list of practice tools for elementary school students in Korea, so there were many difficulties in practicing related to technology education at the elementary level. In particular, elementary-level technology education is combined with home economic and agricultural education within the subject of practical art subjects in Korea. Therefore, the laboratory should have a complex function so that it is not only for technology education but also to enable practice in other fields. The name of the lab is “The Practical Arts Laboratory” in elementary schools in Korea. The study design and method to achieve the study purpose are as follows. First, in the theoretical analysis stage, the concept of the laboratory and considerations for designing the laboratory were confirmed through the review of previous studies. Next, a list of practice tools was derived using the big data analysis method. Then, in the actual design stage, the practical arts laboratory was designed and an expert feasibility study was conducted. The results of the study are as follows. First, the minimum area of the practical arts laboratory is 13,600mm×12,450mm, which is twice the size of a general classroom. In addition to the practical arts laboratory, a preparation room for storing practice tools is also required. The minimum area of the preparation room is 12,450mm×3,500mm, which is 1/4 the size of practical arts laboratory. Second, the practice table in the practical arts laboratory was designed as a comprehensive practice table that allows various types of practice, and the area was designed to be 600mm×1,200mm in consideration of the Korean work area. Third, the number of practice tables was set to six considering the size of the practical arts laboratory and the number of people per class in elementary schools in Korea. As of 2018, the number of people per class at an elementary school in Korea was 23.1, so four people were set to use one practice table. Practice is a key element in technology education. Thus, it will be said that the practical arts laboratory plays a very important role in Korea’s elementary level technology education as an environmental background that makes the practice effective. For this reason, the standard specifications of the practical arts laboratory and the list of practice tools presented in this study are expected to contribute to the development of elementary-level technology education in Korea. Also, our results can be a reference for other countries in the world that have a similar situation to Korea.
Online learning in pandemic era and its socio-psychology consequences

The purpose of this study is to reveal the socio-psychological consequences of online learning during the COVID-19 pandemic.This study uses a systematic literature study related to the purpose of this study.The findings of this study are: (1) parents must provide facilities that support online learning, such as laptops, large internet quotas, and modems or hotspots, (2) parents need to provide special assistance to their children, (3) parents need to improve academic knowledge, and (4) the emergence of boredom, boredom, and stress.To overcome these challenges, optimal adaptation is needed with regard to "online learning" as a new habit caused by these technological changes.
Attention Based Neural Machine Translator for Hindi to English Language

-Neural machine translation, or NMT uses the models based on neural network to gain an understanding of the statistical model so that it can be used in machine translation. Attention based mechanism used in neural networks make the translation process more reliable by using the bidirectional approach of encoder and decoder and is used to compare BLEU from different sources Keywords— NLP, Attentional Mechanism, Encoder, Decoder, Machine Translations (MT), Recurrent Neural Network
Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder

Domain generalization aims to improve the generalization capability of machine learning systems to out-of-distribution (OOD) data. Existing domain generalization techniques embark upon stationary and discrete environments to tackle the generalization issue caused by OOD data. However, many real-world tasks in non-stationary environments (e.g. self-driven car system, sensor measures) involve more complex and continuously evolving domain drift, which raises new challenges for the problem of domain generalization. In this paper, we formulate the aforementioned setting as the problem of evolving domain generalization. Specifically, we propose to introduce a probabilistic framework called Latent Structure-aware Sequential Autoencoder (LSSAE) to tackle the problem of evolving domain generalization via exploring the underlying continuous structure in the latent space of deep neural networks, where we aim to identify two major factors namely covariate shift and concept shift accounting for distribution shift in non-stationary environments. Experimental results on both synthetic and real-world datasets show that LSSAE can lead to superior performances based on the evolving domain generalization setting.
PEDAGOGICAL CONDITIONS OF USAGE DIDACTIC GAMES FOR YOUNG CHILDREN’S SENSORY EDUCATION

The article substantiates the relevance of didactic games usage by educators of preschool institutions, which play an essential role in young children’s sensory standards formation. The essence of sensory education as a purposeful, consistent, and planned pedagogical influence is determined, which ensures the formation of children’s sensory cognition, development of sensation processes, perception, and visual representations through acquaintance with human sensory culture. It has been found that the pedagogical conditions for the successful use of didactic games in the children's sensory development are the following: consistency and systematic use of didactic games; repetition of their holding with a gradual transition from the simple to the complex ones; individual approach taking into account the age characteristics of children, developmental environment. It is proved that a child's sensory development literally formed from the first days of their lives is the key to a successful implementation of various activities. That is why it is so essential that sensory education is systematically included in all spheres of a child's life, especially in the processes of cognition of objects and their properties (shape, structure, size, proportions, color, location in space, etc.).
Evaluation of private investment performance

In Ethiopia, there has been various economic and political reforms for the last ten years which can motivate private investors. Even though, some improvements have been registered as a result of such reforms, the performance of private sectors became low. This study conducted to evaluate the performances of private investment in regional distribution, sector contribution, and ownership structure and employment creation. The result shows that Most of private investment projects are concentrated around Addis Ababa, with manufacturing and service sectors. In Ethiopia, foreign private projects are capital incentive while Domestic private projects have higher share in employment creation. Emerging regions in the country exhibited small number of private projects as compared to other regions. Identified variables for the study includes private investment, inflation rate, abroad money supply, GDP per capital, interest rate, exchange rate, public investment, and external debt. To enhance the analysis, Econometrics model with OLS using multiple regression was applied. The result shows that GDP per-capital, and external debt have significant positive long run effect on private investment, while broad money supply and average exchange rate have negative long run effect. Broad money supply, GDP per-capital, and external debt have significant short run effect.
A Strengthened Branch and Bound Algorithm for the Maximum Common (Connected) Subgraph Problem

We propose a new and strengthened Branch-and-Bound (BnB) algorithm for the maximum common (connected) induced subgraph problem based on two new operators, Long-Short Memory (LSM) and Leaf vertex Union Match (LUM). Given two graphs for which we search for the maximum common (connected) induced subgraph, the first operator of LSM maintains a score for the branching node using the short-term reward of each vertex of the first graph and the long-term reward of each vertex pair of the two graphs. In this way, the BnB process learns to reduce the search tree size significantly and boost the algorithm performance. The second operator of LUM further improves the performance by simultaneously matching the leaf vertices connected to the current matched vertices, and allows the algorithm to match multiple vertex pairs without affecting the optimality of solution. We incorporate the two operators into the state-of-the-art BnB algorithm McSplit, and denote the resulting algorithm as McSplit+LL. Experiments show that McSplit+LL outperforms McSplit+RL, a more recent variant of McSplit using reinforcement learning that is superior than McSplit.
COOPERATION BETWEEN TEACHERS AND STUDENTS AS BASIS OF PERSONALITY-ORIENTED TEACHING

The article examines the problem of cooperation o f a teacher and pupils as a basis of personally oriented teaching. The reasons o f a low-level of pupils' cognitive, creative activity in the educational process are studied. Special attention is paid to dialogic teaching, which lies in the basis of cooperation of a teacher and pupils, and to the requirements of the organization of educational dialogue.
Gaussian mixture modeling of nodes in Bayesian network according to maximal parental cliques

This paper uses Gaussian mixture model instead of linear Gaussian model to fit the distribution of every node in Bayesian network. We will explain why and how we use Gaussian mixture models in Bayesian network. Meanwhile we propose a new method, called double iteration algorithm, to optimize the mixture model, the double iteration algorithm combines the expectation maximization algorithm and gradient descent algorithm, and it performs perfectly on the Bayesian network with mixture models. In experiments we test the Gaussian mixture model and the optimization algorithm on different graphs which is generated by different structure learning algorithm on real data sets, and give the details of every experiment.
An Effectual Secured Approach Against Sybil Attacks in Wireless Networks

In both wireless and mobile ad hoc networks, assaults can come from a variety of different sources. The terms "active attack" and "passive attack" describe these two types of attacks. In the network community, the Sybil attack is one of the most often used and deployed techniques for sniffing identities and repurposing them. Multiple identities or Sybil attacks have recently sparked a lot of interest in the research community. The algorithms and networks on which they are tested are vastly different among the many methods that have been offered. Since researchers can't evaluate these systems side by side or test their efficacy on real-world social networks with a variety of structural features, it's difficult to say whether there are any other (perhaps more efficient) methods of Sybil protection. In the event of a Sybil attack, the gatecrasher subverts the system framework's notoriety arrangement by creating a large number of pseudonymous individuals and then using them to add an enormously imbalanced influence. Three factors determine a notoriety framework's susceptibility to a Sybil attack: how quickly personalities can be generated, how much the notoriety framework accepts inputs from substances that lack a chain of trust, and if the notoriety framework handles all components equally. A large-scale Sybil ambush in Bittorrent Mainline may be accomplished in a cheap and effective manner, according to confirmation. A substance on a distributed system is a piece of software that has access to the resources of the local community. By displaying a character, a distributed system element reveals itself to the world. A single chemical can have an impact on more than one character. Numerous characters can be assigned to a single element. The personalities of substances in shared systems are used for the objectives of repetition, asset transfer, reliability, and trustworthiness, among other reasons. For remote elements to be aware of characters without necessarily being aware of the personality-to-neighborhood correlation, distributed systems make use of the character as a decision. Each different identification is normally considered to be associated with a separate local entity by convention. A single local entity may have several identities in actuality. In order to avoid and identify Sybil assaults, an empirical technique is used in this study. According to the base paper, any nodes with RSS greater than the provided threshold are regarded to be attackers under the present approach. A centralized way to monitor the mobile nodes is required to prevent this assault. As the server agent assumes full control of the ad-hoc network, malevolent nodes or selfish nodes are fully eliminated from the system.
Students evaluation of the impact of distance learning technologies on the organization of practice as a factor for improving the quality of professional training

The problem and the aim. One of the problems of a modern university in the new sanitary and epidemiological conditions is the organization of students' practice. Changes are taking place when working with databases of practices, coordination of information interaction, network communication at enterprises. The purpose of the article – is an analysis of students' assessments of the organization of practice to gain professional experience before the pandemic and in the transition to distance learning technologies. Research methods. Students' assessment of the impact of distance technologies on the organization of practice was carried out during a questionnaire through forms of Microsoft Teams. 124 students of the Orel State Institute of Culture from the faculties of documentary Communications and socio-cultural activities were involved in the following areas of training: 46.03.02 Documentation and Archival Studies; 43.03.02 Tourism; 51.03.03 Socio-cultural Activities; 51.03.04 Museology and Protection of Cultural and Natural Heritage Objects; 51.03.06 Library and Information Activities. The average age of respondents was 22 years (48% of girls and 52% of young people). Pearson’s criterion χ2 (chi-squared) was used for statistical data processing. Results. The questionnaire in Microsoft Teams has been developed. It contains the following blocks: "Distance technologies at the stages of the organization of practice (assessment of the spectrum, validity of the choice and problems of the means used by the university and the practice base)"; "Satisfaction with the quality of the organization of practice without the use (with use) distance technologies"; "Directions for improvement in the university / practice base". The Moodle course implements an appropriate algorithm of organizing practice based on distance technologies. Statistically significant differences in the qualitative changes in the pedagogical system were revealed, χ2observ. 2 &gt; χ2critic0.05 (8,27 &gt; 5,99). In conclusion, the directions of modernization of the electronic information and educational environment of the university on the organization of practice in accordance with the identified problems are described.
MANAGEMENT OF INDEPENDENT WORK OF STUDENTS IN EDUCATIONAL PROCESS

The article deals with different forms of pupils’ individual activities while working with the textbook. Some recommendations are given on the problem of pedagogical leadership intended for pupils ’ educational individual work.
Abnormal Event Detection in Videos using Spatiotemporal AutoEncoder

The detection of abnormal events from surveillance video input is more difficult due to the small number of such occurrences that may occur over time. Through learning a supervised model, this can be achieved to detect such events from video sequences. The proposed system used Deep learning based Convolutional Long Short- Term Memory (Conv-LSTM) networks to learn video sequences as supervised models and to compute the regularity score from the learned frames. Any divergences on the computed scores represents the detection of events as the learning model has represented it through reconstruction of errors. The learned model can be chosen as the best model based on the detection performed through regularity scores. The learning videos of abnormal sequences are very less in real time video and which has to be determined through the model accurately. Thus, the proposed work is more challenging to get the event detection identification at a particular frame accurately. Auto encoder and decoders used in the proposed model. The model is also experimented on Avenue Dataset for detection of abnormal events. The Detection of Anomalous Occurrences from video sequences is accurately detected in experimental results. Key Words: Deep learning, Convolutional Neural Networks - Long Short-Term Memory (CNN-LSTM), Supervised learning, Regulatory scores
SPOTIFY PODCAST BECOME A NEW LEARNING MEAN FOR YOUTH

The development of technology, especially in the field of communication, has experienced a significant change in the practice of consuming information or content, teenagers who are not included in the adult/older group or children, are vulnerable to being affected by the new media they consume, one form of digital technology that is developing are podcasts. Spotify podcast is a new medium in the consumption of information or content. The nature of podcasts that can be used freely by teenagers will affect them in social and even educational aspects. The widespread use of podcasts among teenagers makes it a new means of learning. The main problem in this research is how the Spotify podcast becomes a new learning tool for teenagers. The purpose of the study was to find out how Spotify's podcast became a new learning tool for teenagers. Using qualitative research methods, primary data in the form of questionnaires distributed via google form to the youth of Bogor City, and secondary data is the result of previous research. Using descriptive analysis, observations were made with direct observation of the results of the questionnaires that had been collected. The results obtained in this study show that Spotify podcasts are a new educational tool for teenagers that contain elements of education in it, formal or non-formal, packaged in a concise and entertaining way. This research can be a recommendation for lecturers, especially lecturers at the University of Djuanda, to apply the new Spotify podcast media in teaching and learning activities
Triplicate functions

Abstract We define the class of triplicate functions as a generalization of 3-to-1 functions over $$\mathbb {F}_{2^{n}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>F</mml:mi> <mml:msup> <mml:mn>2</mml:mn> <mml:mi>n</mml:mi> </mml:msup> </mml:msub> </mml:math> for even values of n . We investigate the properties and behavior of triplicate functions, and of 3-to-1 among triplicate functions, with particular attention to the conditions under which such functions can be APN. We compute the exact number of distinct differential sets of power APN functions and quadratic 3-to-1 functions; we show that, in this sense, quadratic 3-to-1 functions are a generalization of quadratic power APN functions for even dimensions, in the same way that quadratic APN permutations are generalizations of quadratic power APN functions for odd dimensions. We show that quadratic 3-to-1 APN functions cannot be CCZ-equivalent to permutations in the case of doubly-even dimensions. We compute a lower bound on the Hamming distance between any two quadratic 3-to-1 APN functions, and give an upper bound on the number of such functions over $$\mathbb {F}_{2^{n}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>F</mml:mi> <mml:msup> <mml:mn>2</mml:mn> <mml:mi>n</mml:mi> </mml:msup> </mml:msub> </mml:math> for any even n . We survey all known infinite families of APN functions with respect to the presence of 3-to-1 functions among them, and conclude that for even n almost all of the known infinite families contain functions that are quadratic 3-to-1 or are EA-equivalent to quadratic 3-to-1 functions. We also give a simpler univariate representation in the case of singly-even dimensions of the family recently introduced by Göloglu than the ones currently available in the literature. We conduct a computational search for quadratic 3-to-1 functions in even dimensions n ≤ 12. We find six new APN instances for n = 10, and the first sporadic APN instance for n = 12 since 2006. We provide a list of all known 3-to-1 APN functions for n ≤ 12.
RANCANG BANGUN DAN UJI COBA ENGINE CLEANER SEBAGAI PENUNJANG PRAKTEK TEKNOLOGI MOTOR BENSIN

Overhaul is one of the activities carried out to restore engine performance so that it appears close to its previous condition both in terms of power and fuel consumption. In carrying out an overhaul, ideally, the engine components must first be cleaned of scale and dirt. Referring to these problems, the purpose of this research is to design an engine cleaner technology which is used as an alternative solution. Through the engine cleaner, the gasoline waste from the rinse will be processed so that it does not pollute the environment. This research is a design type which is carried out by considering several factors such as design, strength, ergonomics, material requirements and cost. The research data analysis technique refers to quantitative descriptive. The research data is then presented in the form of a bar chart according to predetermined indicators to measure the efficiency and quality of the engine cleaner. Based on the results of the research, the engine clear technology functions according to the design results. In addition, in terms of convenience and usefulness, both lecturers and students are greatly helped by this technology so that in the process of cleaning machine components. Thus, the process of cleaning the components of the practicum machine is cleaner than cleaning manually.
Rotor Power Optimization of Horizontal Axis Wind Turbine from Variations in Airfoil Shape, Angle of Attack, and Wind Speed

This paper presents rotor power optimization of the Horizontal Axis Wind Turbine of various parameters such as airfoil, angle of attack, and wind speed. Simulation of HAWT rotor power uses Blade Element Momentum (BEM). Furthermore, optimization using the Taguchi method with L16(43) orthogonal array. The parameters used in this study were: airfoil NACA (National Advisory Committee for Aeronautics) 4412, NACA 2412, NACA 4412-NACA 2412, NACA 4412mod-NACA 2412mod; angle of attack 3˚, 4˚, 5˚, 6˚; and wind speed of 5, 6, 7, 8 (m/s). The simulation uses the general parameter at 1 MW HAWT. Several types of NACA airfoil, angle of attack, and wind speed were simulated, then optimized to obtain optimal parameters for the HAWT output power. The results of this study found the most optimal rotor power, namely the condition of the NACA 4412mod-NACA 2412mod airfoil, 3˚ angle of attack, and 8m/s wind speed. Wind speed is the most significant influence factor based on ANOVA analysis ranked 1st based on S/N ratio analysis, 2nd rank is an airfoil, and 3rd rank is the angle of attack. The higher the wind speed, the greater the rotor power generated.