Reviewerly/exHarmony huggingface dataset:
Analysis of Emotional Intelligence, Environment and Discipline on Student Learning Achievement

Education is very important for improving the quality of human resources. Associated with the world of education, to create high quality and high achievers. Factors that can influence learning include emotional intelligence, the environment and the discipline in which individuals carry out certain activities so that they can achieve maximum performance. The purpose of the study was to analyze the effect of emotional intelligence , environment and discipline on student achievement in Health Vocational School Visi Global in Banyuwangi Regency . In this study, the research design used was cross sectional . The study population was all students of Banyuwangi Health Vocational School Visi Global 117 students and a sample of 91 people using stratified random sampling . Collecting data using a questionnaire sheet and then analyzed using multiple linear regression test. The results showed that a significant probability of F value of 0.000 &lt;0.05 means that there is an influence of emotional intelligence (X1), learning environment (X2) and learning discipline (X3) simultaneously or partially have a significant effect on learning achievement (Y) in Vocational School in Visi Global Banyuwangi Regency. Based on the results of this study, it needs to be at the level of things that affect learning achievement by providing facilities and infrastructure that support learning that is not yet available and create a more comfortable learning environment.
Effect of Government Youth Development Training on Knowledge, Skill, and Attitude of the Incumbents in Barisal Division of Bangladesh

With the aim of evaluating the effect of Government Youth Development Training on the KSA of the incumbents, this research used structured interview schedule and accomplished face-to-face interview of 142 randomly selected trainees from four purposefully selected Youth Training Centers. A strong positive significant change of KSA occurred due to the training and major change happened in knowledge followed by skill and attitude. The regression analysis shows that the traits of the trainers, location of the training center, and regularity in class attendance had significant relationship with knowledge change of the incumbents, while the traits of the trainers, experience of other trainings, and location of the training centers were significant determinants of skill change. Continuous improvement of trainer’s traits as well as inclusion of more practical field works in training sessions, and frequent evaluation of each training program based on KSA( Knowledge Skill &amp; Attitude) is crucial to improve the effect of government youth development training in the study area.
DESAIN NON-PLAYER CHARACTER PERMAINAN TIC-TAC-TOE DENGAN ALGORITMA MINIMAX

Abstract : Tic-Tac-Toe is one of the board games. It is played by filling the columns on the board with X or O in such a way as to form parallel lines vertically, horizontally and diagonally. This study aims to design Non-Player Characters (NPC) in the tic-tac-toe game with the minimax algorithm. The Tic-tac-toe game will be designed with two game modes: easy and minimum random modes. While in minimax NPC mode will determine the best step. The game development process of the tic-tac-toe application is based on a linear sequence process model. In the analysis phase, the NPC will be designed based on the concept of minimax. Software modeling was designed using Unified Modeling Language (UML), and coded with Visual Basic programming. Our tests show that NPCs with the Minimax algorithm can work well.
A Classification Algorithm of Unbalanced Data Samples Based on ResNet

In view of the present unbalanced data sets classification to solve the problem of low accuracy, taking Mixed National Institute of Standards and Technology database for example, considering such factors as the number of data samples, the network depth, this paper proposes a Deep Residual Network algorithm to classify unbalance sample samples. The first is to use an oversampling method for unbalanced data preprocessing, and then after a 3 * 3 of convolution layer for feature extraction, and then use two residual block on the depth of the neural network training to complete the classification of imbalanced data sets. The experimental results show that the algorithm can achieve almost 100% recognition rate for small sample unbalanced data sets, and the result is good.
Reduction of Data Risk in Cloud Computing Through the Front Layer Security Mechanism

Background/objectives: The centralised computing defines cloud computation as centralised model which is responsible to provide the network access on-request basis to a shared pool of interconnected computation resources linked together. The same is done to provision in a quick manner and to be released with the minimal management effort or cloud provider interaction. It is a platform that is built to customer convenient interface with IT framework. The promise made by the cloud computing, especially shared cloud can be decked by security infraction which are indefeasible. Methods/statistical analysis: An encryption and decryption algorithms have been proposed so as to maintain the security of the private data that is being transmitted in the cloud scenario. Findings: The increasing necessity for the secure cloud storage being handled in a centralised fashion and thereby the enticing effects of the cryptography at client side help us in prioritising and combine them together, thereby naming an innovative mechanism for the private data as third-party security and regulation issues. Improvements/applications: The proposed work provides a more secure framework layer as security to the data, but still there are various aspects which need to be addressed in future. Proposed work is suitable only for selected private data rather than a huge data input by user on cloud, we can extend this work for different types of modules with timestamp encryption converted time and efficiency in future. In future, the technique of Each Word Secure Authentication would be added to improve cloud security on behalf of private. Based on the security solutions, we will demonstrate a secure new client-side framework with advanced algorithm implementations in this article.Keywords: Cloud Enhancement, EWSA, Cloud Server, Secure Cloud Platform
A definition-by-example approach and visual language for activity patterns in engineering disciplines

Modeling tools are well established in software development. A model is the result of a series of modeling activities. The ability to recognize when a user is working on a certain modeling activity opens up a range of possibilities for context-sensitive support. One possible way to support the user is offering the auto-completion of the current task. The recognition of modeling activities is typically carried out by matching event patterns against events emitted by a user’s editing operations. A user that intends to add or customize auto-completions must be able to easily understand and create activity definitions. However, defining the currently required complex event patterns is a challenging and error-prone task even for a person with an intensive knowledge of event-processing languages. In this paper, we propose the visual definition language VisPaRec accompanied by a method that allows creating activity definitions in a semi-automated and graphical way. We evaluate our visual definition language in a comparative user study against the generic event-processing language Rapide. We found that the proposed visual representation increases comprehensibility while reducing time for constructing and modifying activity definitions significantly.
Τεχνικές επεξεργασίας ήχου στην ηχογράφηση/ ηχοληψία

This paper examines digital and analog audio processing through sound engineer and recording techniques, with methods for improving the audio signal through software and applications of a Digital Audio Workstation (DAW).
Improved K-means Algorithm Based on Threshold Value Radius

Abstract K-means algorithm is a classical clustering algorithm, which needs to specify K value artificially and chooses the initial clustering center randomly. However, it is easy to fall into local optimal solution. In order to overcome the shortcomings of K-means algorithm, an improved algorithm based on threshold value radius is proposed in this paper. The initial clustering center and threshold radius are determined automatically by the average value of Euclidean distance between data. The experimental results show that the method proposed can effectively and accurately overcome the shortcomings of the traditional K-means algorithm.
Evaluating Contemporary Digital Awareness Programs for Future Application within the Cyber Security Social Engineering Domain

Social engineering is a rising threat to individuals and organizations, causing massive losses every day.Contemporary and innovative methods to mitigate these threats are needed today more than any other time in the past.This study aimed to assess the different awareness programs and techniques being developed or utilized against cyber security social engineering.A systematic review of various studies was performed, identifying that interactive awareness programs against social engineering are far superior and more engaging than traditional training sessions.
Crisis Issues: In Life and Education

In this particular issue we have presented three important crises that the world is facing today. The crisis of Management and Education, the Crisis of the Immigrant Assimilation into a new culture and its expectations and the Crisis of the Identity of the self that displaced people like Orphans and Immigrants face. Through well planned, meticulously researched, and well documented research the writers have trod the fine line between the facts and the realities of human life because research finally depends upon the human needs that surface constantly, demanding answers in the path to progress.
Fingerprint Based Watermarking Using DWT and LSB Algorithm

Present age is the age of information and digital multimedia plays a very vital role in the representation, expression and propagation of the information. Equally important is to secure the information from being duplicated, altered and mutilated. Digital watermarking, hence has become a research topic to safeguard the copyright of the content. This work provides an innovative image watermarking scheme in two transform domains  Discrete Cosine Transform and Discrete Wavelet Transform. It is proved that DWT is more suited for authentication of fingerprints. DWT is better than DCT because the decomposition of images into three different levels. And concluded using the parameter mean square error, PSNR. From the study, it is obvious that DWT is better technique than DCT for the application of watermarking.
DEVELOPMENT OF TEACHERS' PROFESSIONAL COMPETENCE WITHIN EDUCATIONAL TRANSFORMATIONS

Socio-political and socio-economic changes that are taking place at the present stage of development of Ukraine, predetermine the strengthening of attention to the systematic development of teachers' professional competence. The change in the educational paradigm, that takes place in Ukraine, requires a revision of the approaches of professional training and retraining of teachers. The old slogan concerning the teacher as a leading figure of the educational process has disappeared from the arena, giving way to the idea of the XXI century, which proves that the teacher is "a carrier of educational and social changes". The high requirements imposed by the state to the level of professional competence of the teacher of a new formation – personality that capable of self-improvement, self-development and creativity are constantly being improved and increased. Teachers are encouraged to systematic advanced training, the search for new, alternative directions of professional training and constant development of professional competence. Key words: competence, competency, professional competence, professional competence of a young teacher, management of professional competence development, formation and development of the teacher, advanced training.
Methodological support of the teacher as a condition of his professional becoming

Тенденции развития науки и образования -5 -РАЗДЕЛ IV.ПЕДАГОГИКА
T0 convergence-approach spaces

In previous papers, several T₀-objects in set-based topological category have been introduced and compared. In this paper, we give the characterization of general T₀ (resp. T₀, and T₀′) convergence approach spaces as well as show how these notions are linked to each other.
CHALLENGES OF DIGITAL REALITY TO HIGHER EDUCATION

Воронежский государственный технический университет», Воронеж, e-mail:
K-Nearest Neighbor for Recognize Handwritten Arabic Character

Handwritten text recognition is the ability of a system to recognize human handwritten and convert it into digital text. Handwritten text recognition is a form of classification problem, so a classification algorithm such as Nearest Neighbor (NN) is needed to solve it. NN algorithms is a simple algorithm yet provide a good result. In contrast with other algorithms that usually determined by some hypothesis class, NN Algorithm finds out a label on any test point without searching for a predictor within some predefined class of functions. Arabic is one of the most important languages in the world. Recognizing Arabic character is very interesting research, not only it is a primary language that used in Islam but also because the number of this research is still far behind the number of recognizing handwritten Latin or Chinese research. Due to that's the background, this framework built a system to recognize handwritten Arabic Character from an image dataset using the NN algorithm. The result showed that the proposed method could recognize the characters very well confirmed by its average of precision, recall and accuracy.
ERP Evidence on Processing Adverbs and Verb Inflections by the Korean EFL Learners

Our study is to investigate whether or not the Korean EFL learners rely more on adverbs than verb inflections in collateralness to the previous studies when they process English sentences with verbs and adverbs. As we checked their responses on an ERP experiment, we found some significant results that N400 appeared at the verb position either preceding the adverbs or following when both incongruent and congruent constructions are compared and P600 slightly at the verb position when the verb-adverb constructions are congruent and incongruent. It revealed that even though the Korean EFL learners seem to rely on the lexical meaning in determining the verb inflections, they try to process them syntactically and are affected by L1 of Korean. Along with a result of this aspect, we claim that there should be some universal operating properties in processing adverbs and verb inflections in languages.
A New Approach to the Ordered Classification of Critical Factors in the Degradation Processes of River Basins

The aim of this paper is to present through information collected via qualitative analysis in order to provide an alternative perspective to classify critical factors and their correlations in the processes of degradation of river basins in countries in development in an ordered way.This study was started with a bibliographical review for gathering relevant information about the main factors, which was submitted to specialists and related professionals via survey developed in a format of answers on Likert scale, with the analyses of data from the respondents as well as their contribution within sample assembly exploratory factorial analysis and the charge factor item from the questionnaire with usage of polychoric correlation matrix with which it is proposed to establish the ordering of the factors relevance as well as their correlations through parametric statistical analysis with the usage of a generalized model of partial credit which belongs to the family of the models for polyatomic gradual answers to the item response theory (IRT) and the applying of cluster analysis (ICLUST) with the usage of both alpha and omega coefficient for the estimation of the variables group, with the R tool.As a result, the present study aims to establish a comprehension of the main factors for the ordering of the actions and attention of public and private sectors towards the preservation of urban river basins.
Probabilistic regression and Bayes nets

This chapter revises regression with the inclusion of uncertainty in the data in probabilistic models. It shows how modern probabilistic machine learning can be formulated. First, a simple stochastic generalization of the linear regression example is offered to introduce the formalism. This leads to the important maximum likelihood principle on which learning will be based. This concept is then generalized to non-linear problems in higher dimensions and the chapter relates this to Bayes nets. The chapter ends with a discussion about how such a probabilistic approach is related to deep learning.
An Attention Module for Multi-Person Pose Estimation

In the top-down approaches of multi-person pose estimation, a human detector is adopted first to generate a set of human bounding boxes, then crop these human body and perform a single-person pose estimation model to get the final result. However, some body part of another person on the cropped image will interfere the single-person pose estimation model leading to an inaccuracy result. In order to model the relationship between adjacent keypoints effectively to alleviate this problem, we propose and attention module that could let the model get global receptive field at the shallow layer of the network and pay more attention to the key areas which is more important to pose estimation. Experiment results show that our method achieves 73.9% mAP with 2.4% absolute improvement compared to our baseline on the COCO test-dev dataset.
LibGuides: How to do Research as a Librarian: Tracking the Impact of Your Research

This guide will include the research tools available to librarians, and contact information for who can help with navigating those tools in the library and on campus.
Global Anomaly Detection Based on a Deep Prediction Neural Network

Abnormal event detection in public scenes is very important in recent society. In this paper, a method for global anomaly detection in video surveillance is proposed, which is based on a deep prediction neural network. The deep prediction neural network is built on the Convolutional Neural Network (CNN) and a variant of the Recurrent Neural Network (RNN)-Long Short-Term Memory (LSTM). Especially, the feature of a frame is the output of CNN, which is instead of the hand-crafted feature. First, the feature of a short video clip is obtained through CNN. Second, the predicted feature of the next frame can be gained by LSTM. Finally, the prediction error is introduced to detect that a frame is abnormal or not after the feature of the frame is achieved. Experimental results of global abnormal event detection show the effectiveness of our deep prediction neural network. Comparing with state-of-the-art methods, the model we proposed obtains superior detection results.
LibGuides: Open Educational Resources: Further Reading

A guide for faculty interested in incorporating open access materials into their curriculum. Articles and more with information about open access
IMPROVEMENT OF CREATIVE THINKING AT STUDENTS IN HIGHER EDUCATION INSTITUTIONS

The article provides an overview of creative types of training. There are ideas about how pedagogical methods should be used in the formation of students' creative thinking in higher education. KEY WORDS: Creativity, pedagogy, creative pedagogy. The main categories of science, research methods, creativity, thinking, critical thinking
A Study on Perception of the Tourism Values of the Demilitarized Zone(DMZ) for Unification Tourism: Focused on Social Media Big Data

This study utilizes social media data related to the Demilitarized Zone for 10 years from 2009 to 2019. The topic modeling of the text mining methods is applied to identify the core topics and to identify changes in the perception of the DMZ. Through this, a change in the perception of the tourism value of the DMZ is analyzed phenomenologically. The purpose of this study is to suggest policy implications for the value and role of the DMZ in the unification of the Korean Peninsula. As a result of analyzing the frequency and weight of the key-words, the key-words with the highest exposure frequency each year were peace, ecology, war, tourism, unification, North and South Korea and regions. Although the analysis indicated differences in weights by year and topic, and the emergence of new topics, it was analyzed that most people recognized the DMZ as key topics such as "tourism", "ecology", "history", "security", "event", "infrastructure" and "politics". Based on the results of the study, it was suggested that the policy that can lead to the perception of Korean nationals on the use value and non-use value among the tourism values of DMZ should be maintained continuously.
Využití programovatelné robotické hračky Bee-bot v mateřské škole a na prvním stupni ZŠ pro testování klíčové kompetence k řešení problémů

Programming lessons appear especially in upper classes of elementary schools or at high-schools. However, it progressively gets into the lessons at the first stage of elementary schools or even to kindergartens in the form of similar programmable toys. Such programmable toys are meant to develop not just algorithmic thinking, spatial orientation, creative thinking, but namely problem solving. The base is formed as a complex problem, pupils learn to divide it into minor parts and work with them. The obtained findings come from experience and empirical measuring which was executed in a kindergarten in Klatovy and also by two groups from elementary schools in Pilsen region. Everything was obtained based on a random selection. The robotic toys were used to find out the success rate of children while completing the given tasks and to observe the ways of heir procedure. While performing the tasks, girls showed higher success rate of accomplishing them although they required more time to do so, as they checked the program setting more and worried more about making an error. For further research, a larger sample of children is going to be ested to confirm our hypotheses – focused on differences between programming by men and women.
Automating visual privacy protection using a smart LED

The ubiquity of mobile camera devices has been triggering an outcry of privacy concerns, whereas existing privacy protection solutions still rely on the cooperation of the photographer or camera hardware, which can hardly be enforced in practice. In this paper, we introduce LiShield, which automatically protects a physical scene against photographing, by illuminating it with smart LEDs flickering in specialized waveforms. We use a model-driven approach to optimize the waveform design, so as to ensure protection against the (uncontrollable) cameras and potential image-processing-based attacks. We have also designed mechanisms to unblock authorized cameras and enable graceful degradation under strong ambient light interference. Our prototype implementation and experiments show that LiShield can effectively destroy unauthorized capturing while maintaining robustness against potential attacks.