Reviewerly/exHarmony huggingface dataset:
10.55528/18292828-2023.3-43

Social capital is a by-product of the formation of interpersonal relationship. Growing and strengthening these connections among family, friends, and colleagues, helps people build social capital by creating diverse social networks, providing access to relationship with diverse individuals and gaining additional opportunities and valuable information and knowledge. Social capital in social partnership in informal horizontal connections will create new opportunities to increase the trust factor, which is one of the important conditions for increasing profitability in modern economic relation and business environment. With the help of modern technologies, even over long distances, people are able to form relationship, create a social partnership environment. Effective management within organizations has more to do with the nature of the relationship formed between managers and employees. The relationship between work efficiency and economic profitability is directly proportional to the amount of trust. We considered the importance of internal trust as one of the integration environment within the organization. The investment of social capital in social partnership is also highlighted as an auxiliary resource for increasing reputations in the external environment.
DEVELOPMENT OF PROFESSIONAL READINESS OF MASTER’S STUDENTS TO WORK WITH GIFTED CHILDREN

A qualitative leap in the development of new technologies has led to the need of society for people who are able both to solve new problems in an unconventional way and to bring new content to all spheres of life. Therefore, today an important direction in state policy in the field of education is connected with the development and support of children with increased educational needs and abilities, which constitutes the potential of the country. To identify such children at the earliest stage, to promote the development of their talents is the task of modern education. The primary role in this process is played by teachers working with children. It depends on them whether the child will be able to develop his/her abilities or not. In modern psychological and pedagogical research works, it is noted that only a teacher with general and special knowledge, certain personal qualities of character can work effectively with such a category of students as gifted children. All this demanded the timely and qualitative preparation of students of correspondence courses to work with gifted children in educational institutions. Readiness to work with gifted children is directly related to the readiness of teachers to implement the educational process in accordance with the requirements of modern state educational policy, taking into account the needs, capabilities, desires and abilities of students, to develop and implement program and methodological documentation, to carry out scientific and methodological work and dissemination of advanced pedagogical experience, to the development and implementation of pedagogical innovations in the educational process. The purpose of our experimental work was connected with the practical implementation of the organizational and pedagogical conditions for the development of professional readiness of students of correspondence courses (teachers of additional education) to work with gifted children.
THE SPECIFICS OF THE DEVELOPMENT OF CAREER ORIENTATIONS IN PROFESSIONAL EDUCATION

Career orientations allow a person to maximize their potential and self-actualize professionally. In the case of choosing the optimal correspondence of the interests and qualities of a person with the chosen profession, his professional self-realization will proceed successfully and bring moral satisfaction. In the event that some stages are omitted in career planning, or a professional choice is made randomly, or due to the conditions of the situation (quotas for free education, lack of vacancies in desired professions, the desire of parents, etc.), then a person in most cases, faces difficulties in realizing their qualities and potential. Career orientation is a lengthy process and includes professional self-determination, awareness of needs and goals, tasks for their implementation, assessment of one’s strengths, understanding the content of the future profession. Independence and the active role of the personality itself is the driving force in the process of its development. A person makes a choice of a profession, a place of study, and then independently builds his career, gains experience and realizes his capabilities. Accordingly, the process of professional self-determination does not end after choosing a profession. It continues to develop in the course of education, as well as at the beginning of professional activity. In order to judge the success of professional self-determination, it is necessary to take into account the completeness of the formation of a person’s idea of a future profession, as well as about himself as a future professional. At present, understanding the problem of forming a career path, professional development of a specialist in the system of higher education, determining the role of each subject of professional design acquires theoretical as well as practical significance.
METHODOLOGICAL ASPECTS OF TEACHING MATHEMATICS USING INFORMATION AND END-TO-END TECHNOLOGIES

Digital transformation affects all aspects of educational and professional activities. An urgent task of digital transformation of education is access to digital and end-to-end technologies. Modern digital and end-to-end technologies provide an innovative approach to learning, put forward new digital tools for the development of the university, promote the exchange of accumulated knowledge and experience. The use of digital technologies in modern education has become an affordable and reliable tool that contributes to improving the daily work of high-tech industries and service companies. This article is devoted to the review of new opportunities of digital transformation in education. Attention is paid to the role of information and end-to-end technologies, digital tools in teaching mathematical disciplines. The necessity of including these technologies in the educational process in connection with the demand for their application in modern professional activity is substantiated. On the basis of information and digital end-to-end technologies, the authors updated the main blocks of the work program of the discipline “Discrete Mathematics and mathematical Logic” In the fund of evaluation tools, practice-oriented tasks were developed. Taking into account: analysis and integration of scientific and methodological literature, internet resources, experience of scientific and pedagogical activity, the authors have improved and tested the methodology for the formation of digital competencies of students of the 02.03.02 Fundamental Informatics and Information Technology training direction.
THE MAIN ADVANTAGES AND DISADVANTAGES OF IMPLEMENTING A STEM EDUCATION SYSTEM

This article is devoted to the study and disclosure of the essence of an innovative approach covering the educational environment, known as STEM technology. In addition, during the writing of the article, both the main advantages and disadvantages of introducing this category during the educational cycle were considered. The essence of STEM education lies in the integration of various disciplines into one whole to solve certain problems with the help of creative thinking, which, in turn, is accompanied by the disclosure of the creative potential of the teacher. Undoubtedly, the topic of our study is quite relevant for the modern socio-economic system, since STEM technologies open up new opportunities in the educational system, focusing on improving such personal qualities as logical thinking, analysis, making informed decisions, etc.
Soc-T-ABSO submodules and related concepts

In this paper, we present the idea of Soc-T-ABSO submodule observations and examine how-T-ABSO submodule and Socle relate to one another in terms of qualities and characteristics. Submodules of several kinds are have now been introduced. It is possible to develop new concepts based on Soc-T-ABSO submodules using the implications of this work.
TRANSFORMATION OF A RECRUITER’S PROFESSIONALISM IN THE CONTEXT OF DIGITAL TECHNOLOGIES INTRODUCTION

The purpose of this study is to consider the transformation of the parameters of a recruiter’s professionalism in the context of the increasing digitalization of the profession from the perspective of institutional interaction and ethical choice. The most common point of view on professionalism in the scientific literature is an analysis through the prism of competencies. The author focuses his attention on the parameters of knowledge, skills, and special abilities. At the same time, professionalism is a complex social phenomenon that includes, for example, issues of motivation and self-realization in a specific professional field, the power and authority of a professional depending on his expert status, problems of professional ethics, norms, stereotypes and standards of professional behavior. During a period of global changes against the backdrop of a massive transition to modern digital technologies, profound transformations are taking place in the parameters of professionalism. These changes are most noticeable in such a professional area as personnel search and selection. Live communication in the format person (candidate) –person (recruiter) is replaced by interaction between person (candidate) –machine (artificial intelligence). These changes not only affect the composition of the required competencies of personnel selection specialists, but also rebuild a significant part of social relations, primarily in the labor market. As a result, the features of sociological approaches to the problematic analysis of a recruiter’s professionalism are identified. Components of professional ethics of recruiters are subjected to experimental testing. The priority moral qualities that a recruiter should have in the new realities are identified.
Fuzzy partial T-transforms applied to a system of PDE

Fuzzy partial integro-differential equations have widespread applications in the natural and applied sciences and engineering. The fuzzy T-transform transform is proposed as a new method for solving fuzzy partial differential equations in this research. Using very broad H-differentiability ideas, a formula for the first and second order fuzzy partial derivative has been derived. After an introduction to fuzzy partial T-transforms, fuzzy partial differential equations are developed. Finally, a working example has been presented to showcase the efficacy of the suggested approach.
DEVELOPMENT OF FUN THINKERS BOOK LEARNING MEDIA IN SOCIAL STUDIES CLASS VII MTS ASHRI SUBJECTS

The limited use of learning media that is less effective causes the learning process to become a problem for students. this makes teaching and learning activities boring. Development of media fun thinkers book to assist the availability of learning media and motivation to participate in teaching and learning activities for social studies subjects. This research purpose: 1) Produce products for the development of social science learning media fun thinkers book for class VII at MTs ASHRI for 2020/2021. 2) Knowing the validity of the product development of social science learning media fun thinkers book class VII at MTs ASHRI for 2020/2021. The method used is R&amp;D, the ASSURE development model. Collecting data using questionnaires and interviews. The research subjects were social studies teachers and 35 seventh-grade students. Data analysis using qualitative and quantitative techniques. The results showed that: (1) material expert validation I with a score of 80.76% "quite valid", (2) material expert validation II with a score of 71.15% "quite valid", (3) media expert validation with a score of 68 .18% “fairly valid”. The results of the field trials showed: (1) small group trials with a score of 87.5% "very effective" category, (2) cognitive competency test results in large group trials with a score of 83% "very effective" (3) results in a large group trial response questionnaire with a score of 93.07% in the "very valid" category. The conclusions of the research are: (1) the fun thinkers book learning media was developed with the ASSURE model so that it is appropriate to use social studies learning media in class VII for the 2020/2021 school year; (2) the fun thinker's book media is validated by experts, social studies teachers and has been tested in small and large groups so that they are feasible and effective as learning media in social studies subjects for class VII for 2020/2021.
Predicting Solar Potential: A Comprehensive Analysis of On-Grid Rooftop Solar PV System through HelioScope Design

Abstract: This work focuses on designing an MWh generating On-grid Solar PV system installed in Mangalpally, Hyderabad. Regionally, this location receives 5.5 kWh/sq.mts/day of Solar Energy on an average. The main objective of this paper is to designing and simulation of a Solar PV system using a methodology that is capable of analysing the performance in an optimizable way irrespective of the capacity of the PV plant. Such software is HelioScope- a web-based software developed by Folsom Labs. This paper uses HelioScope methodology for simulation for assess and estimate of the Solar Energy Production. The results verify the Solar PV generation of the considered installation area.
Diffractive optical networks &amp; computational imaging without a computer

I will discuss diffractive optical networks designed by deep learning to all-optically implement various complex functions as the input light diffracts through spatially-engineered surfaces. These diffractive processors designed by deep learning have various applications, e.g., all-optical image analysis, feature detection, object classification, computational imaging and seeing through diffusers, also enabling task-specific camera designs and new optical components for spatial, spectral and temporal beam shaping and spatially-controlled wavelength division multiplexing. These deep learning-designed diffractive systems can broadly impact (1) all-optical statistical inference engines, (2) computational camera and microscope designs and (3) inverse design of optical systems that are task-specific. In this talk, I will give examples of each group, enabling transformative capabilities for various applications of interest in e.g., autonomous systems, defense/security, telecommunications as well as biomedical imaging and sensing.
Intelligent Blockchain: Use of Blockchain and Machine Learning Algorithm for Smart Contract and Smart Bidding

With the growth of population, there is an increase in demand in food, as well as growth in agribusiness and hence, an increase in contract farming. Contract farming provides the farmers with the benefits such as enhanced agricultural production and a rise in incomes of contract farmers, giving them an exposure to services and resources inculcated with opportunities to participate in markets. However, time and again contract farming is criticised for the uneven bargaining power that may lead to the exploitation of farmers by contractors or large agribusiness firms. The presence of middlemen or brokers in the supply chain further coerces the farmers to rely on them to sell their products. Again, there is another issue of differentiating among bids. So, the solution for all these problems lies in “BidBlock”, a bidding integrated e-commerce platform, having built over blockchain and machine learning. Blockchain, with smart contracts, helps in restoring the trust of the farmers with its decentralization and machine learning, by interpreting and simplifying bids, helps them gaining maximum profit. Results show that most buyers prefer to have deals directly with the farmers and with a ease of doing business (like easy contract and payment). The addition of delivery services will be better too, but in this paper, it provides emphasis on how to simplify bidding with smart contracts, both for farmers and farms. Hence, introduction to BidBlock.
What Makes Content Personalization Work?

The Membership Management ReportVolume 19, Issue 11 p. 8-8 Communications and Marketing What Makes Content Personalization Work? First published: 04 October 2023 https://doi.org/10.1002/mmr.32232Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume19, Issue11November 2023Pages 8-8 RelatedInformation
Feature selection using differential evolution for microarray data classification

Abstract The dimensions of microarray datasets are very large, containing noise and redundancy. The problem with microarray datasets is the presence of more features compared to the number of samples, which adversely affects algorithm performance. In other words, the number of columns exceeds the number of rows. Therefore, to extract precise information from microarray datasets, a robust technique is required. Microarray datasets play a critical role in detecting various diseases, including cancer and tumors. This is where feature selection techniques come into play. In recent times, feature selection (FS) has gained significant importance as a data preparation method, particularly for high-dimensional data. It is preferable to address classification problems with fewer features while maintaining high accuracy, as not all features are necessary to achieve this goal. The primary objective of feature selection is to identify the optimal subset of features. In this context, we will employ the Differential Evolution (DE) algorithm. DE is a population-based stochastic search approach that has found widespread use in various scientific and technical domains to solve optimization problems in continuous spaces. In our approach, we will combine DE with three different classification algorithms: Random Forest (RF), Decision Tree (DT), and Logistic Regression (LR). Our analysis will include a comparison of the accuracy achieved by each algorithmic model on each dataset, as well as the fitness error for each model. The results indicate that when feature selection was used the results were better compared to the results where the feature selection was not used.
A Systematic Review on Blockchain Scalability

Blockchain is an exciting new technology that has garnered attention across multiple industries. This new technology offers several advantages, including decentralization, transparency, and immutability. However, several issues limit the effectiveness of this technology, such as scalability, interoperability, and privacy. A systematic review of blockchain scalability research was conducted using three primary databases: ACM, Science Direct, and IEEE. The review examined the state of the art in blockchain scalability, identifying the most important research trends and challenges. The solutions that have been established can be categorized into two main groups: those that pertain to block storage and those that pertain to the underlying blockchain mechanism. Numerous solutions were suggested for each main group. The most common proposed solutions for improving the scalability of blockchain networks in the literature are improving the consensus algorithm and using sharding. Most of the solutions were proof of concept and need more investigation in the future.
Cyberbullying Detection Based on Hybrid Ensemble Method using Deep Learning Technique in Bangla Dataset

Globalization is certainly a blessing for us. Still, this term also brought such things that are constantly not only creating social insecurities but also diminishing our mental health, and one of them is Cyberbullying. Cyberbullying is not only a misuse of technology but also encourages social harassment among people. Research on Cyberbullying detection has gained increasing attention nowadays in many languages, including Bengali. However, the amount of work on the Bengali language compared to others is insignificant. Here we introduce a Hybrid ensemble method using a voting classifier in Bangla Cyberbullying detection and compare this with traditional Machine Learning and Deep Learning Classifiers. Before implementation, Exploratory Data Analysis was performed on the dataset to gather better insight. There are lots of papers that have already been published in other languages where it is seen that the hybrid approach provides better outcomes compared to traditional methods. Thus, we propose a highly well-driven method for Cyberbullying detection on the Bangla dataset using the hybrid ensemble method by voting classifier. The overall deployment consists of three Machine Learning classifiers, three Deep Learning classifiers, and a Hybrid approach using the voting classifier. Finally, the Hybrid ensemble method yields the best performance with an accuracy of 85%, compared with other Machine and Deep Learning methods.
Tampering Detection and Segmentation Model for Multimedia Forensic

When an image undergoes hybrid post-processing transformation, detecting tamper region, localizing it and segmentation becomes very difficult tasks. In particular, when a copy-move attack with hybrid transformation has similar contrast and illumination parameters with an authenticated image it makes tamper detection difficult. Alongside, under small-smooth attack existing tamper identification model provides a very poor segmentation outcome and sometimes fails to identify an image as tampered. This article focused on addressing the difficulty through the adoption of the Deep Learning model. The proposed technique is efficient in detecting tampering with good segmentation outcomes. However, existing models fail to distinguish adjacent pixels' relationships affecting segmentation outcomes. In this paper, an Improved Convolution Neural Network (ICNN) assuring correlation awareness-based Tamper Detection and Segmentation (TDS) model for image forensics is presented. This model brings good correlation among adjacent pixels through the introduction of an additional layer namely the correlation layer alongside vertical and horizontal layers. The TDS-ICNN is very effective in localizing and segmenting tamper regions even under small-smooth post-processing tampering attacks by using a feature descriptor built using aggregated three-layer ICNN architecture. An experiment is done to study TDS-ICNN with other tamper identification models using various datasets such as MICC, Coverage, and CoMoFoD. The TDS-ICNN is very efficient under different post-processing hybrid attacks when compared with existing models.
Handwritten Character Recognition Using Deep Learning

Handwritten digit or character recognition in transforming the printed or handwritten text from an image. Optical character recognition plays an important role in documentation scanning ,text extractions from the image. Optical character recognition is used in different fields like postal services ,Ecommerce , Shipping ,Banking sector for character extraction from the images . However the existing character recognition system faces many challenges in extracting text from noisy and distortion images or complex layout and Extraction mostly limited to numbers and English alphabets . The introduction of Deep learning has changed Optical Character Recognition by using models like Recurrent Neural Networks,convolutional neural network .In this paper i am gonna compare the different models like CNN model and CRNN model with current State of art model Transformer based Optical Character Recognition KeyWords :Transformers ,Convolution Recurrent Neural Network, Handwritten ,Optical Character Recognition