Reviewerly/exHarmony huggingface dataset:
The Effect of Handling Imbalanced Datasets Methods on Prediction of Entrepreneurial Competency in University Students

As of today, entrepreneurs and entrepreneurship are considered to be the integral parts of the economic and technological advancements. Entrepreneurs are promoted in many countries because of their high return on investment opportunities both in terms of income and new inventions. Numerous studies prove that entrepreneurs have many traits in common and these common traits can correlate with each other. Based on these common traits, potential entrepreneurs can be predicted, current entrepreneurs can be improved by realising their weak sides and the ones who wish to be entrepreneurs can be provided with insights. A machine learning approach can light the way for a better rewarding future for entrepreneurship, helping these goals significantly. There exist several studies for the prediction of entrepreneurial competency with the use of machine learning algorithms. Most machine learning methods perform better accuracy and F1-score imbalanced data instead in imbalanced data. This study focuses on utilizing imbalanced class handling methods to increase prediction performance. Random Oversampling, Random Undersampling, SMOTE, and NearMiss methods are used to handling imbalanced data for this purpose in this study. The performance of the machine learning algorithms with Imbalanced Data Handling methods is compared with the machine learning algorithms without these methods. The comparison shows that with the handling imbalanced data methods machine learning algorithms perform better.
Real-Time Video Synopsis via Dynamic and Adaptive Online Tube Resizing

Nowadays, with the increased numbers of video cameras, the amount of recorded video is growing. Efficient video browsing and retrieval are critical issues when considering the amount of raw video data to be condensed. Activity-based video synopsis is a popular approach to solving the video condensation problem. However, conventional synopsis methods always consists of complicated and pairwise energy terms that involve a time-consuming optimization problem. In this paper, we propose a simple online video synopsis framework in which the number of collisions of objects is classified first. Different optimization strategies are applied according to different collision situations to maintain a balance among the computational cost, condensation ratio, and collision cost. Secondly, tube-resizing coefficients that are dynamic in different frames are adaptively assigned to a newly generated tube. Therefore, a suitable mapping result can be obtained in order to represent the proper size of the activity in each frame of the synopsis video. The maximum number of activities can be displayed in one frame with minimal collisions. Finally, in order to remove motion anti-facts and improve the visual quality of the condensed video, a smooth term is introduced to constrain the resizing coefficients. Experimental results on extensive videos validate the efficiency of the proposed method.
Survey on Cryptocurrency Wallet

Normal cash has developed and appears numerous downsides such as inaccessibility. It is inclined to burglary and is intensely directed by government offices. Cryptocurrencies have risen as a egotistic money related framework. They depend upon secure disseminated ledger data structure. Mining plays a critical portion in this framework [1]. Basically, our cryptocurrency could be a conveyed database that keeps up tamper-proof information structure pieces containing his bunches of person exchanges. Blockchain innovation can be a widely emerging approach to data innovations. Bitcoin as a cryptocurrency has made several considerations since it was one of its earliest implementations. They discuss the key elements driving the development of sophisticated cryptocurrencies alongside Ethereum, a blockchain implementation with a focus on informed contracts [1]. In its most basic form, our cryptocurrency may be thought of as a distributed database that keeps track of tamper-proof data structure blocks comprising batchesof individual transactions [1].
3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving Object

This paper aims to develop a multi-rotor-based visual tracker for a specified moving object. Visual object-tracking algorithms for multi-rotors are challenging due to multiple issues such as occlusion, quick camera motion, and out-of-view scenarios. Hence, algorithmic changes are required for dealing with images or video sequences obtained by multi-rotors. Therefore, we propose two approaches: a generic object tracker and a class-specific tracker. Both tracking settings require the object bounding box to be selected in the first frame. As part of the later steps, the object tracker uses the updated template set and the calibrated RGBD sensor data as inputs to track the target object using a Siamese network and a machine-learning model for depth estimation. The class-specific tracker is quite similar to the generic object tracker but has an additional auxiliary object classifier. The experimental study and validation were carried out in a robot simulation environment. The simulation environment was designed to serve multiple case scenarios using Gazebo. According to the experiment results, the class-specific object tracker performed better than the generic object tracker in terms of stability and accuracy. Experiments show that the proposed generic tracker achieves promising results on three challenging datasets. Our tracker runs at approximately 36 fps on GPU.
WhatsApp as a technological tool in the learning of higher education [WhatsApp como herramienta tecnológica en el aprendizaje de la educación superior]

Technological progress has transcended communication, immediacy, sending audiovisual and written materials, interaction and interactivity anywhere in the world. Reason, that the efficiency of WhatsApp for learning in higher education was investigated. The objective was to determine if there is a correlation between the usefulness of the application and the improvement of learning. The methodology is based on descriptive, the representative sample was 20 students; For this reason, the questionnaires were elaborated. How often do you review the messages of this application during the day? Is the reception and storage of educational materials of the application efficient? Is it effective in sending and receiving the link of the virtual platforms through WhatsApp? Does your rating improve due to the availability of educational materials for use per month? Do you consider the tool useful for evaluations in each module? and Does it improve learning by using WhatsApp as an interactive and indispensable tool per month? Once the data was obtained, it was processed using basic statistics and correlation. The results determined that the moment the application is reviewed was 35%, reviews 4 to 7 times a day, efficiency in sending and receiving materials 80%, efficiency in sending and receiving links with 75%, improves qualifications when using WhatsApp with 45% improved a rating of 15, considers it useful for evaluations with 90% considers it useful, improves learning its use with 85% and correlation between considers WhatsApp useful and improvement of learning with r = 0.973. It concludes that there is a high correlation between considering WhatsApp useful and learning improvement, which means that the use of this tool influences the improvement of learning, however it is necessary to take into account that it is used for academic purposes.
A Survey on Digitization of Handwritten Notes in Kannada

Recognition of handwritten text is still an unresolved research problem in the field of optical character recognition. This article suggests an efficient method for creating handwritten text recognition systems. This is a challenging subject that has received a lot of attention recently. A discipline known as optical character recognition makes it possible to convert many kinds of texts or photos into editable, searchable, and analyzable data. Researchers have been using artificial intelligence and machine learning methods to automatically evaluate printed and handwritten documents during the past ten years in order to digitize them. This review paper's goals are to present research directions and a summary of previous studies on character recognition in handwritten texts. Since different people have different handwriting styles, handwritten characters might be challenging to read. Our "Digitization of handwritten notes" research and effort is to categorize and identify characters in the south Indian language of Kannada. The characters are extracted from printed texts and pre-processed using NumPy and OpenCV before being fed through a CNN
Investigation and Research on the Participation of Graduate Students in Academic Activities in Local Engineering Colleges

This study takes some postgraduate students of Guangxi University of Science and Technology as the object. We adopt the field investigation method and questionnaire survey method to investigate and analyze the participation of graduate students in local engineering universities. There are several major problems: the number and quality of research achievements of postgraduate students in our university are not qualified; the academic research ability needs to be further improved; the motivation to participate in academic activities needs to be improved; academic activities in forms are relatively simple and not rich in level; the frequency of participating in academic activities is not high. Based on the above problems, the following strategies are put forward: tutors could strengthen the guidance to their graduate students and encourage them to participate in academic activities; to carry out and diversify academic activities; to expand the horizons of graduate students and focus on national and international academic conferences.
FEATURES OF A MULTIMEDIA WORK

In connection with the comparative novelty of the concept of "multimedia work" and the lack of a unified approach to its interpretation among lawyers, the issue of determining the signs that could serve as the basis for distinguishing works of this kind from other objects of copyright is relevant.&#x0D; The article analyzes and systematizes the theoretical provisions on the research topic, identifies and considers the following features of a multimedia work: interactivity; the presence in the structure of the totality of several results of intellectual activity; complexity; digital form; virtuality; the presence in the structure of a computer program; providing information using a combination of many perceived by the person; the presence of several storylines; artistic design of the interface and navigation tools; embodiment on material carriers; the need to use special technical devices for working with multimedia works. Based on the results of the study, the essential legally significant features of a multimedia work are highlighted.
Segmentation in Structural Equation Modeling Using a Combination of Partial Least Squares and Modified Fuzzy Clustering

The application of a structural equation modeling (SEM) assumes that all data follow only one model. This assumption may be inaccurate in certain cases because individuals tend to differ in their responses, and failure to consider heterogeneity may threaten the validity of the SEM results. This study focuses on unobservable heterogeneity, where the difference between two or more data sets does not depend on observable characteristics. In this study, we propose a new method for estimating SEM parameters containing unobserved heterogeneity within the data and assume that the heterogeneity arises from the outer model and inner model. The method combines partial least squares (PLS) and modified fuzzy clustering. Initially, each observation was randomly assigned weights in each selected segment. These weights continued to be iteratively updated using a specific objective function. The sum of the weighted residual squares resulting from the outer and inner models of PLS-SEM is an objective function that must be minimized. We then conducted a simulation study to evaluate the performance of the method by considering various factors, including the number of segments, model specifications, residual variance of endogenous latent variables, residual variance of indicators, population size, and distribution of latent variables. From the simulation study and its application to the actual data, we conclude that the proposed method can classify observations into correct segments and precisely predict SEM parameters in each segment.
Prediction of Graduate Admission Using Machine Leering

The goal of this study is to create a model that may assist students in selecting the best institutions based on their scores and their profiles. We can evaluate candidates across a broad range of disciplines, such as Master of Science (international), Master of Technology (India), and Masters in Business Administration (India and international). We intend to build a machine learning model in order to produce outcomes that may benefit the students in choosing the right University. The dataset includes facts on the university and student profiles, together with a field that indicates whether or not the admission was successful. Key performance indicators have been used to compare the predictions made using a variety of algorithms, including Ensemble Machine Learning (KPI).The dependent variable, or the likelihood of admission to a university, is then evaluated using the model that is performing the best. The chances of admit variable, which has a range of 0 to 1, represents the anticipated likelihood of being accepted to a university. Additionally, we want to build a portal that sorts universities according to their acceptance range before listing them.
Development of an automated batch script for CORS massive data based on GAMIT/GLOBK

Aiming at the problem of low efficiency and automation of CORS massive data precision processing, an automated batch processing method for CORS massive data is proposed. Based on the Bash programming language, an automated batch script program for CORS massive data is designed and built. Through the examples in the paper, it is verified that the script of the proposed method is feasible and effective and has certain practical value for the application of power CORS massive data precision processing technology.
Gradual road network simplification with shape and topology preservation

In this paper, we consider the problem of gradual road network simplification, where given an embedded road network the goal is to compute a fine-grained succession of simplifications with decreasing level-of-detail. This allows to render the network on any desired zoom level or with a user-defined number of segments. Previous work has established that this can be achieved based on a Contraction Hierarchies (CH) data structure. CH was originally developed as a graph preprocessing method to speed up shortest path planning in road networks. However, since it is inherently based on a graph simplification mechanism, it can also serve as a basis for rendering. But the existing method exhibits several shortcomings, for example, topological inconsistencies arise on many simplification levels and the preservation of the shape of routes and the overall network for coarser graph representations is insufficient. This severely impairs the navigability of the map. We significantly improve upon the existing method by modifying the CH construction process as well as the rendering algorithm.
ANALISIS VISUAL ILUSTRASI ANIMASI PADA IKLAN TVC DJARUM BEASISWA BULUTANGKIS 2018

TVC Djarum badminton scholarship 2018 advertisement is the only TVC PB Djarum that applies 2D animation, since TVC Djarum badminton scholarship has existed since 2007. This TVC’s 2018 was able to get the highest number of viewers on the official account of PB Djarum's Youtube platform. Thus, it was found the effect of animation on this TVC. Visually, the 2D animation in this TVC depicts children's characters and figures. This study aims to analyze how 2D animation in the form of illustrations of children playing badminton is applied to this TVC advertisement. Analysis of the application of this animation can examine the visualization of meaning, uniqueness, colors used, and the role of the illustration itself. The purpose of this study was to determine the character and meaning of the animation applied to the 2018 TVC Djarum Badminton Scholarship ad. literature review. This study found that TVC videos targeting the children's category would be better off using a 2D animation approach, using a cartoon style, and displaying color visuals that are impressively cheerful, enthusiastic, active, and courageous.
Differential Optimization Federated Incremental Learning Algorithm Based on Blockchain

Federated learning is a hot area of concern in the field of privacy protection. There are local model parameters that are difficult to integrate, poor model timeliness, and local model training security issues. This paper proposes a blockchain-based differential optimization federated incremental learning algorithm, First, we apply differential privacy to the weighted random forest and optimize the parameters in the weighted forest to reduce the impact of adding differential privacy on the accuracy of the local model. Using different ensemble algorithms to integrate the local model parameters can improve the accuracy of the global model. At the same time, the risk of a data leakage caused by gradient update is reduced; then, incremental learning is applied to the framework of federated learning to improve the timeliness of the model; finally, the model parameters in the model training phase are uploaded to the blockchain and synchronized quickly, which reduces the cost of data storage and model parameter transmission. The experimental results show that the accuracy of the stacking ensemble model in each period is above 83.5% and the variance is lower than 10−4 for training on the public data set. The accuracy of the model has been improved, and the security and privacy of the model have been improved.
Estimation of the Randomness of Continuous and Discrete Signals Using the Disentropy of the Autocorrelation

The amount of randomness in a signal generated by physical or non-physical process can reveal important information about that process. For example, the presence of randomness in ECG signals may indicate a cardiac disease. On the hand, the lack of randomness in a speech signal may indicate the speaker is a machine. Hence, to quantify the amount of randomness in a signal is an important task in many different areas. In this direction, the present work proposes to use the disentropy of the autocorrelation function as a measure of randomness. Examples using noisy and chaotic signals are shown.
A Graphical Password Authentication System

Abstract Graphical passwords offer a promising various to ancient alphabetic passwords. they're engaging since individuals typically bear in mind photos higher than words. during this extended abstract, we tend to propose an easy graphical parole authentication system. we tend to describe its operation with some examples, and highlight necessary aspects of the system. Also, users usually keep identical passwords for all their accounts as a result of it's tough to recollect heaps of them. various authentication ways, like bioscience, graphical passwords square measure accustomed overcome these issues related to the standard username-password authentication technique. in a very graphical parole authentication system, the user needs to choose from pictures, in a very specific order, bestowed to them in a very graphical computer program (GUI). per a study, the human brain includes a bigger capability of memory what they see (pictures) instead of alphameric characters.
Controversy About the Ideological Orientation Around the Almanac "Mnemosyne"

The article is an analysis of the controversy that took place on the pages of the almanac "Mnemosyne", published by A. S. Griboyedov, V. K. Kyukhelbeker and V. F. Odoevsky in the 19th century. The object of the study is the negative critical reviews devoted to the almanac "Mnemosyne". The aim of the study is to identify the influence of negative critical reviews on the perception of the almanac "Mnemosyne". The main part of the work is devoted to negative reviews about the almanac. The article also contains a brief description of the history of the creation of the almanac itself for a more complete and detailed understanding of the material. When considering critical reviews of the almanac "Mnemosyne", first of all it is worth mentioning the personality of F. B. Bulgarin, famous for his loud polemics with the publishers of "Mnemosyne", as well as A. F. Voeykov and Prince Shalikov, who was directly related to this almanac. The novelty of this article lies in a more detailed consideration of the negative critical reviews on the almanac "Mnemosyne", as well as the impact of this controversy on the output of the almanac. It should be noted that "Mnemosyne" for a short but rather active period of publication acquired both ideological supporters who shared the views of the publishers and opponents who actively criticized the almanac, among whom were F. B. Bulgarin, A. F. Voeykov and Prince P. I. Shalikov. The controversy of the publishers of Mnemosyne with critics did not stop until the publication of the almanac was discontinued. These critical reviews caused a heated debate on a number of issues: starting from the appearance of "Mnemosyne", and ending with individual comments on the works of the almanac. These discussions not only did not spoil the reputation of Mnemosyne, but also helped to attract public attention to it.
Impact of professional education on the development of the staff potential in a modern library

The article examines the need for professional education in the choice of the future profession, as well as the role of staff potential diagnostics in the work of a modern library, and the prospects and tasks in this sphere. The authors perform diagnostics of employees without special library education in municipal libraries of the Belgorod region, Russia. The study concludes that it is vital for library employees to get specialized education in librarianship in addition to that which they already have. In addition, libraries are advised to have a set of methods for diagnosing the potential of their staff with descriptions of these methods and options for their use.
Professional identity of teachers as a component of university corporate culture

The article addresses the problem of establishing the impact of educational organizations’ corporate culture on the development of professional identity in teachers and their professional advancement. The study focuses on resolving the issues of creating an educational environment that supports teachers’ potential, helps them recognize their own problems, and makes them conducive to their development by transforming the problems into objectives. It is found that the established corporate culture of educational organizations contributes to the understanding of mechanisms behind the development of new personal qualities in teachers in the process of mastering certain types of activities and, as a result, to the transformation of teachers’ fragmentary experience into sustainable motivation for professional improvement in the process of collaborative work.