Reviewerly/exHarmony huggingface dataset:
APPLICATION OF INTELLIGENT TECHNOLOGIES IN ADAPTIVE LEARNING CONTROL

The article is devoted to the analysis of the features of teaching as a purposeful, controlled process and the determination of the role of modern artificial intelligence tools in the development of automatization teaching control systems. The purpose of the article is to determine the possibilities of using modern intellectual technologies for the implementation of adaptive control of individualized teaching. Didactic analysis, methods of system analysis and artificial intelligence were used in the research process. The article analyzes the peculiarities of teaching as a controlled process, which is determined by weak formalization, the use of a combination of analytical and heuristic models, an advantage in conditions of random external influences, a priori incompleteness of information and uncertainty of goals, which determines the use of artificial intelligence tools for the implementation of automatization systems for control individualized teaching. The conducted research made it possible to determine the most urgent tasks in the creation of adaptive teaching control systems, to analyze the necessary components of structural-parametric control schemes that have a nested structure and corresponding intellectual transformations. The choice of control models and intelligent technologies for their implementation is substantiated. Among the main intellectual transformations that must be carried out, the following are defined: the transformation of the opinions of expert teachers into a structural-parametric model of the learning discipline based on the use of fuzzy sets and relations; transformation of teachers' expert judgments about interdisciplinary relationships into a coefficient of integration between two disciplines based on fuzzy inference; transformation of data on integration relations between learning disciplines into a system of fuzzy rules regarding their influence on the formation of competencies based on fuzzy clustering; transformation of data on the achievement of current didactic goals to the degree of formation of the competence system on the basis of fuzzy derivation according to the hierarchical knowledge base. Four types of relevant didactic tasks are formulated, which are components in ensuring adaptive control of teaching. As a result of the study, the main means of creating adaptive learning control systems were determined, examples of setting individual didactic tasks and their solutions were given.
Towards Food Recommender Systems Considering the African Context

Food recommender systems (FRS) provides suggestions of recipes to human users. These systems are more and more spreading like in EU and US. However in sub-Saharan Africa, the application of these systems is less explored. This paper aims to shed light on the challenges faced by food recommender systems when applied in Sub-Saharan Africa. By identifying these limitations, we can pave the way for more inclusive and culturally sensitive human-computer interaction designs.
THE PROBLEM OF ESTABLISHING THE PROPERTIES OF UNPROTECTED IDEAS IN THE CONTEXT OF CULTURAL DEVELOPMENT

Abstract: the article discusses the problem of establishing the properties of ideas that are not protected by copyright. This problem has not received proper coverage in the civilist doctrine. The task is to determine the properties of the unprotected idea, as well as the properties that indicate the transformation of the idea in the work. It is established that ideas that are not protected by copyright are immaterial objects that have the property of abstraction and are general concepts. From the state of a unprotected object, the idea becomes a work in the course of the author's creativity, as a result of which the idea acquires a new property-specificity. This property is considered in the context of dividing creativity into two types. Attention is drawn to the property of concreteness in connection with existing trends in culture, especially in terms of the development of art and the widespread dissemination of mass culture. It is concluded that the property of specificity is determined not only by the implementation of ideas in the work, but also in other ways. It is revealed that the current civil legislation leaves the interests of creators of ideas without protection from unfair behavior. Taking into account foreign experience, it is concluded that it is necessary to develop ways to protect ideas from unfair behavior.
Dynamic Load Balancing for Improved Resource Allocation in Cloud Environments

Cloud computing has emerged as a revolutionary paradigm in information technology, offering scalable and on-demand access to computing resources. Efficient resource allocation is a crucial aspect in ensuring optimal performance and cost-effectiveness of cloud environments. Load balancing algorithms play a vital role in distributing workloads across available resources, preventing resource overutilization and underutilization. This research focuses on optimizing resource allocation in cloud computing through the application of advanced load balancing algorithms. The primary objective is to enhance resource utilization, minimize response time, and improve overall system performance. Traditional load balancing techniques often fall short in addressing the dynamic and heterogeneous nature of cloud environments. Therefore, this study investigates novel algorithms that leverage real-time resource monitoring, predictive analytics, and adaptive decision-making to intelligently allocate workloads. The research involves the design, implementation, and evaluation of multiple load balancing algorithms. Comparative analysis is conducted to assess the efficiency of the proposed algorithms against existing methods. Performance metrics such as response time, throughput, resource utilization, and scalability are used to gauge the effectiveness of the algorithms under various workload scenarios. this research explores the impact of load balancing strategies on energy consumption and environmental sustainability. Energy-efficient load balancing algorithms are developed to align resource allocation with energy consumption patterns, contributing to the overall green computing initiative.
Bitcoin as an Investment: Advantages and Risks

The article discusses the possibilities of investing in digital currency - cryptocurrencies, in particular, their most common form - Bitcoin. The high hype and rising prices of crypto coins determine the relevance of the research topic and set the trend for many years. This scientific article is devoted to the study of the nature of Bitcoin, and the history of its creation, and highlights the main features and distinguishing features from fiat money. Blockchain technology is also discussed, which is a technological breakthrough in the field of data analysis that provides many advantages, including cryptocurrency. In addition to the basic strategies of investing in Bitcoin, the option of earning money by "mining" cryptocurrencies is considered. The purpose of this paper is to show the main advantages of virtual currency, as well as to present the main disadvantages of Bitcoin compared to traditional money as an investment object. In the research, special attention is paid to determining the place of the currency in the legal framework, specifications, and perspectives of the use of cryptocurrencies in the territory of Georgia. Based on the results of the analysis conducted in the works, it was determined that this type of investment is developing very quickly. In addition, most countries already use Bitcoin as an everyday currency and also use blockchain technology outside of financial services. Keywords: investments, cryptocurrency, bitcoin, blockchain technology, mining, digital currency, crypto investment.
A Hybrid Approach for Complex Layout Detection of Newspapers in Gurumukhi Script Using Deep Learning

Layout analysis is the crucial stage in the recognition system of newspapers. A good layout analysis results in better recognition results. In this paper, we detected the complex layout of newspapers in the Gurumukhi script. We have used a hybrid approach. In this approach, firstly, we proposed an algorithm to remove pictures from newspaper images that involves various image preprocessing tasks based on binarization, finding contours, and erosion on the image to remove the graphics from the image. This method also removes pictures from complex non-Manhattan layouts. Finally, we have trained the deep-leaning model based on a convolutional network to detect the columns of text from newspapers. We have created a dataset of 500 images labelled with five classes on which the model was trained. We have tested this method on the number of newspapers of the Gurumukhi script. The results show very good accuracy with this hybrid approach of layout detection.
Design a Hybrid Algorithm for Data Encryption to Implementation in Database

In an era where digital data is increasingly prevalent, data encryption has become essential to information security. Because databases usually contain sensitive and significant data and are a popular target for cyberattacks, robust encryption solutions are necessary. This research proposes a novel hybrid encryption method that combines symmetric and asymmetric encryption approaches to safeguard databases. The recommended approach combines the security of asymmetric encryption with the speed of symmetric encryption to provide a dependable and efficient data protection solution. This paper introduces hybrid techniques by combining the two most essential algorithms AES and RSA algorithms with XORed Operation. This hybrid encryption algorithm provides more security as compared to existing hybrid algorithms. The implementation and result are also derived in the paper.
Guidelines for Development Instructional Leadership for Secondary School Teachers in Qingdao

The objectives of this research were: 1) To study the current level of instructional leadership of secondary school teachers in Qingdao. 2) To develop the guidelines of instructional leadership of secondary school teachers in Qingdao. 3) To evaluate the adaptability and feasibility of instructional leadership of secondary school teachers in Qingdao. The sample group of this research was 291 teachers. The Interview group was 9 secondary school teachers in Qingdao and the evaluate 9 experts from secondary school in Qingdao. Research instruments include: 1) questionnaire. 2) semi-structured interview. 3) evaluation form. Data analysis by using percentage, mean, standard deviation and content analysis.&#x0D; The results were: 1) the current situation of instructional leadership of secondary school teachers in Qingdao was at high level, 2) the guidelines for developing the instructional leadership of secondary school teachers in Qingdao in four aspects, which contain 23 articles. there are 6 guidelines for optimizing professional development, 6 guidelines for enhancing teaching practice, 5 guidelines for improving school culture, and 6 guidelines for promoting learn. 3) adaptability of guidelines for developing the instructional leadership of secondary school teachers in Qingdao in four aspects were at highest level. and feasibility of guidelines for developing the instructional leadership of secondary school teachers in Qingdao in four aspects were at high level.
Evaluation of the professional development of teachers as an important process of educational management

The modern world is constantly changing. The field of education is no exception. It faces multiple challenges and has to meet contemporary requirements. One of these requirements is the quality of the teaching act, which depends to a large extent on the quality of the staff trained in this field. In this article we analyze the process of evaluating the professional development of human resources in education as an important element of educational management. The evaluation is analyzed in terms of its motivating role for continuous professional development and the possibility to contribute to increasing the performance of the education system as a whole. This is because the reform of education in the Republic of Moldova has the purpose to provide high quality education, which in turn depends on an important role of the quality of the evaluation of the human resource involved.
Get Real in the Virtual World: Branding in the Metaverse Demystified

: let's dive into the buzz around the Metaverse and why it's quickly becoming the go-to spot for businesses to boost their brand image. So, what exactly is the Metaverse? Imagine a sprawling, digital universe where you can chat, play, shop, or even attend concerts—basically, all the stuff you do in the real world but in a virtual setting. Think of it as the Internet on steroids. It's a game-changer and gaining traction like crazy, thanks in part to tech advancements and, oddly enough, the pandemic. Lockdowns have pushed us to find new ways to connect and do business, and the Metaverse is stepping up to the plate. If you're running a business, you might wonder, "How do I get in on this action?" Good news—you've got options. This chapter is about breaking down the nuts and bolts of making your brand shine in this digital playground. It's not just a place for gamers and tech nerds; it's a full-blown marketplace with real economic value. Building your brand in the Metaverse is like setting up shop in a bustling, digital city. You can create a virtual storefront, host events, collaborate with influencers, and more. There's room for traditional advertising like billboards, but they're likely to be interactive and way more relaxed in this case. You can engage with your audience in ways that were once the stuff of sci-fi
Bit Coin and the Challenges for Financial Regulation

Introduction: The main aim of this study is study is to understand the challenges that are faced by Bitcoin in financial regulation. Bitcoin helps to attract investors on a public ledger, which helps them to get back a significant return. Research objectives and research questions are highlighted in this section.&#x0D; Literature Review: Based on the research objectives, thematic analysis is highlighted. Therefore, Cryptocurrencies and Bitcoin in general have imposed numerous challenges in financial matters. The challenges Bitcoin faces due to its unique characteristics and decentralized phenomenon. Regulators are allowed to balance encouraging innovation in blockchain. Therefore, financial stability has to be maintained which helps to protect customers. After that, a clear tax guideline is required for the investors which help them to ensure compliance.&#x0D; Methodology: This study is based on the primary data collection method. Therefore, researchers used quantitative methods for collecting data. In this study, researchers can create a questionnaire set based on the 10 survey questions. In which 3 questions are based on demographic questions and 7 questions are based on variable-related questions. After that, researchers were able to collect information with the aid of 58 respondents.&#x0D; Findings: In this study, researchers are allowed to analyze the collected data with the aid of SPSS software. After that, based on the demographic test, researchers are able to identify the response rate of the participants. After that, “descriptive analysis”, and “hypothesis testing” play a significant role within this study &#x0D; Discussion: Overall discussion about the research study is highlighted in this section. Therefore, challenges of Bitcoin transaction process is discussed within this section.&#x0D; Conclusion: This research study is based on the analysis of the challenges that are faced by investors during the transaction process. After that, basic knowledge about this study is gained by this study.
Reptile Search Algorithm with Deep Convolutional Neural Network for Cloud Assisted Colorectal Cancer Detection and Classification

Cloud-based automatic colorectal cancer (CC) detection involves the usage of cloud computing technology and system to help in the earlier and accurate diagnosis of CC in medical images and patient information. This cloud-based technology aims to improve the efficiency and reliability of CC screening, monitoring, and diagnoses. Automatic CC detection refers to the use of computer-based technology and systems to aid in the earlier and accurate detection of CC in patient data and medical images. This automated system aims to increase the reliability and efficiency of CC monitoring, screening, and diagnosis. Deep learning (DL) methods, especially convolutional neural networks (CNNs), exhibit promising results in automatic CC diagnosis. They can be trained on wide-ranging datasets of medical images to learn patterns and features related to precancerous and cancerous lesion. This study develops a new Reptile Search Algorithm with Deep Learning for Colorectal Cancer Detection and Classification (RSADL-CCDC) technique. The main aim of the RSADL-CCDC method focuses on the automaticclassification and recognition of the CC in the cloud environment. Once the medical images are stored in the cloud server, the detection process is carried out. In the presented RSADL-CCDC approach, the initial stage of preprocessing is performed by bilateral filtering (BF) approach. For feature extraction, the RSADL-CCDC technique applies ShuffleNetv2 model. Besides, the recognition and classification of CC take place using convolutional autoencoder (CAE) model. Finally, the hyperparameter tuning of the CAE technique takes place by utilizing RSA. The experimental validation of the RSADL-CCDC system is performed on benchmark medical database. Extensive results stated the enhanced performance of the RSADL-CCDC technique on CC recognition over other models with respect tovarious actions.
A Study On The Relationship Between Financial Innovation And Bank Sustainability- A Case Study Of State Bank Of India

This study looks at the various forms of financial innovations that have continuously taken place in the provision of financial products /services in India over a period of 5 years. Over a period of time, India has experienced continued growth in the adoption of various non-cash modes of payment hence the need for continuous studies to establish the effect of these financial innovations in the financial services sector. Previously banks were interested only in the economic impacts of the banks but banks are now conscious of the environmental and social impact of their policies as it might affect the quality of assets and also rate of return of banks in the long run. The objective of this study was to establish the effect of financial innovation on bank sustainability. The present study is descriptive as well as analytical in nature. The State Bank of India has been selected for study deliberately being the largest commercial banks in India having wide coverage spreading throughout the country. The data, for the purpose of study, were collected from the annual reports of SBI, Bank Sustainability Report of SBI, journals and other relevant published documents. The study was conducted for a period of 5 years, from 2015-16 to 2019-2020. The analysis of data leads to the conclusion that financial innovation has increased over the period of time. However financial innovation has less impact on bank sustainability in Indian banking sector.
Application of Walsh System in Data Encryption

This article explores the application of the Walsh system in modern data encryption methods. The advantages and limitations of this system are reviewed and its effectiveness is analyzed in comparison to other encryption schemes. The article describes the mathematical basis of the Walsh transform, its use for encryption and decryption, and its practical applications. In conclusion, prospects for further research in this area are considered.
Features of the organization of the staff mentoring process

International scientific conference “MININGMETALTECH 2023 – The mining and metals sector: integration of business, technology and education” : conference proceedings (November 29–30, 2023. Riga, the Republic of Latvia). Riga, Latvia : “Baltija Publishing”, 2023. Vol. 2. 348 pages.
Research Paper on Analysis Load Balancing Algorithm using Cloud Computing

Cloud load balancing is nothing but distributing the work load among many servers &amp; computing property. It can manage work load demand as well as application demand. This process is done with the help of distributing resources among numerous computers. Cloud load balancing consist of circulation of workload traffic &amp; on time demand of internet. Various techniques were represented in literature to improve performance, quality of services, cargo distribution etc. The issue of cargo balancing is same as cloud computing which is data over loading &amp; under loading. We have to apply proper cargo balancer for cloud terrain. The study represents view of problem faced by current cargo balancing ways. The researchers make more effective algorithm. Cloud computing refers to a services &amp; application that can accessible throughout the world from data center.all services are accessible through online. There are several issues in cloud computing such as scheduling, load balancing, quality of services &amp; storage resources. Here we study load balancing. When many clients send request to server, server has already n number of task. In that case server is over loaded for this condition we have to apply load balancing algorithm. Cloud computing is a internet based network technology that share rapid growth in communication technology, by providing services to customer of various requirement with the help of online computing resources. It has both hardware &amp; software application along with software development platform. Cloud computing becomes a popular word in the area of high performance distributed computing. It provide on demand access to share pool of resources over internet. Cloud computing is still much research is required for broad array of topic. One of the important research issue which need to be focus for effective performance isload balancing. Cloud computing aim is to gives computation &amp; resources over the internet via dynamic provision of services. There are many challenges and issues associated with the implementation of cloud computing. This research paper deliberates one of cloud computing main problem that is load balancing. The main aim of load balancing is equally distribute the load on cloud server such that no host is under load &amp; over load. Several load balancing algorithm have been implemented in literature to satisfied customer request for appropriate cloud node.&#x0D;
A Study on Parkinson's Disease Parameters Using Data Mining with Machine Learning Approaches

Parkinson's disease is a long-term condition that demands continuous attention and care. While it can substantially affect an individual's quality of life, with appropriate treatment and support, people diagnosed with Parkinson's can enjoy meaningful lives for numerous years. Research into Parkinson's disease remains active, with ongoing progress in comprehending the condition and discovering innovative treatment options. Data mining, also known as Knowledge Discovery in Database (KDD), is a highly valuable technique employed by entrepreneurs, researchers, and individuals for extracting valuable insights from extensive data collections. The knowledge discovery process encompasses several key steps, including data cleaning, data integration, data selection, data transformation, data mining, pattern evaluation, and knowledge presentation.This paper considers Parkinson’s disease Data Set.The machine learning approaches which is used to analysis and predict the dataset usinglinear regression, multilayer perceptron, SMOreg, random forest, random tree, and REP tree. Numerical illustrations are provided to prove the proposed results with test statistics or accuracy parameters.