Reviewerly/exHarmony huggingface dataset:
Application of an Improved Grey Wolf Optimization Algorithm in the Process of Aluminum Electrolysis

In the process of aluminum electrolysis, in order to reduce energy consumption, it is necessary to reasonably configure related operating parameters. In this paper, an improved grey wolf optimization algorithm based on Fuch mapping (FGWO) is proposed to optimize the parameters of aluminum electrolysis. First, chaos initialization, establishment of a new individual position update equation and introduction of Gaussian variation are adopted to reduce the premature convergence probability of the algorithm and improve the ability to jump out of the local optimal solution, and further enhancements to the optimization performance of the algorithm. Second, to compare the effects of different improvement strategies on the performance of the GWO algorithm, the effectiveness of the strategy proposed in this paper is demonstrated. The comparison experiment between the FGWO algorithm and other algorithms proves its advancement. Finally, the Grey Wolf optimization algorithm is applied to a practical optimization problem in the aluminum electrolysis process. The results show that this algorithm not only has good optimization performance and fast convergence speed, but also can effectively solve the actual optimization problem of aluminum electrolysis. Therefore, FGWO algorithm has high practical value.
Disruptive regulation

Disruptive economies have captured the idea of disruption and used it to attack conventional rights and responsibilities in data arrangements. Disruptive regulation, alternatively, offers pathways for AI and big data to contribute to regulatory solutions, ensuring the equitable governance of digital transformation. The chapter takes platform hire frames to show how information generated through AI and big data can empower vulnerable stakeholders and realize integrated and representative self-regulation.
Introduction to Cryptocurrency Regulation

This Primer relates how the market for cryptocurrencies exploded after the creation of Bitcoins in 2009. That market grew to a market capitalization of $3 trillion in just a few years before its meltdown in 2022. In the meantime, widespread fraud occurred in the marketing and trading of cryptocurrencies. Federal and state financial services regulators stepped in to try and tame those excesses, but their jurisdictional boundaries were such that they were not successful in that effort. Those regulators include state banking departments, the Financial Crimes Enforcement Network (FinCEN), the Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC). This Primer explores the challenges faced by those regulators in applying their existing regulations to cryptocurrency trading. It describes the jurisdictional gaps that are hampering those efforts and describes the need for new legislation to regulate cryptocurrencies in a way that will not stifle blockchain innovation.
Real-Time Related-Key Attack on Full-round Shadow Designed for IoT Nodes

With the rapid development of the Internet of Things (IoT), many new lightweight block ciphers are designed in recent years to meet the security demand in IoT devices. Shadow is a lightweight block cipher designed for IoT Nodes (IEEE Internet of Things Journal, 2021). In this paper, an efficient attack on full-round Shadow is proposed based on the idea of a related-key differential attack. First, a differential transfer property for AND operation is illustrated. This property demonstrates a link between the difference and the input value. If the difference of the input is not zero, to lead to a zero difference, there are some constraints on the input value. Furthermore, two properties for Shadow family ciphers are identified. According to these properties, some related keys on Shadow will lead to an internal collision for the subkey generator, which will eventually lead to a full-round distinguisher. Finally, with the idea of related-key differential attack, an efficient attack is applied to Shadow. For Shadow-32, with 4 related keys, 8 master key bits can be derived in about 0.044 seconds on average. For Shadow-64, with 4 related keys, 24 master key bits can be derived in about 3.9 hours on average. All our theoretical results are verified by experiments.
Building a Recommender System to Predict the Shape of Bacteria in Urine Cytobacteriological Examination Using Machine Learning

This study aimed to build a recommender system that predicts the shape of bacteria for biological requests of urine cytobacteriological examination (UCBE) using machine learning techniques, to reduce the time taken to identify the shape of bacteria (Cocci or Bacilli). We used different methods and techniques in the process: Unified Modelling Language (UML) was used for digital design architecture, Rstudio tool with R programming language for system development, and Random Forest (RF) algorithm for the prediction. Experimental results showed that the time needed to identify the shape of bacteria is decreased, and bacilli bacteria are better recognized by the algorithm with an error rate of 3%. In addition to that, the proposed recommender system allows biologists to validate and correct the prediction and improve the accuracy of the classification algorithm used in the future.
Integrating digital knowledge in teaching systems as grounds for developing knowledge economy

We currently live in a digital world, surrounded by and immersed in technology. The pace of technological change and innovation is increasing and leading to massive changes in all aspects of our lives, including the way we teach and learn. Nevertheless, the design of teaching and learning in academic institutions in Israel hardly serves the needs of the digital revolution generation. In some cases, and in a number of educational institutions, the digital space is small and limited, and many student audiences are not exposed to it. Integrating digital knowledge is a key tool in the development of knowledge-intensive professions associated with the employment world of knowledge economy. is article attempts to examine how it is possible, and even required to integrate the acquisition of digital tools into the world of teaching, students, and teachers, in order to prepare the grounds for knowledge economy professions among learners.
IoT Based Flood Monitoring and Alerting System

Flood is one of the most dangerous natural disasters in the world and that cannot be avoided. It has the capability to destroy and kills the people. It happens too fast and affected so numerous lives and parcels. When the flood tide occurs in the people living area it come veritably dangerous and beget damage to the people. Other than that, maturity of the public can not cover and have no idea when the flood tide going to be happed since they don't have any information and data about the rainfall conditions. This system is suitable for metropolises and vill areas. Likewise, if the public has an internet access, they can cover what's passing and prognosticate if there is any forthcoming flood tide at the web garcon. This design will modernize the water position at the web garcon and the system will issue an alert signal to the citizens for evacuation so that presto necessary conduct can be taken. For this reason we develop a waking system named “IOT Based Flood Monitoring and Alerting System”.
An Advanced Facial Emotional Recognition Using HAAR Cascade Algorithm in Machine Learning

Interpersonal relationships rely heavily on facial expression-based nonverbal cues. A typical part of human-machine points of interaction is the programmed acknowledgment of looks; It could also be used in behavioral science and clinical practice. Despite the fact that people see facial expressions almost immediately, machine expression recognition still faces challenges. From the point of view of automatic recognition, a facial expression can be thought of as changes in the pigmentation of the face or disfigurements of the facial parts and their spatial relationships. Automatic facial expression recognition research focuses on the issues surrounding the representation and arrangement of static or dynamic qualities of these distortions or face pigmentation.
Detecting Spammers on Social Networks

Social media is an online platform, one person can make social relations with the other persons easily via social platform (Facebook, twitter, LinkedIn).Nowadays in social media platform peoples are sharing their personal information’s, habits, carrier interest, activities to their friends. Various information is propagating through online social networks including both the positive and negative. Online information sharing is becoming ubiquitous every day. In this paper, naïve Bayes algorithm is used to detect the wrong information for example the online rumors, and it is also used to work out the distinguish and predictive problems. And Naïve Bayes algorithm is also used for text classification, spam filtering, hybrid recommender system and collaborative filtering.
MOTIVATION OF EMPLOYEES IN THE PUBLIC SECTOR THROUGH ORGANIZATIONAL COMMUNICATION CASE STUDY: VALA MOBILE COMPANY, KOSOVO

The aim of this study is to reveal the role of internal organizational communication in motivating employees in public service organizations. Data were collected from 249 surveyed employees, in the mobile telecommunications sector in Kosovo, specifically in the Vala mobile company. The collected data was analyzed by using the SPSS system. The study found that information sharing had the greatest effect on employee motivation, followed by employee involvement in decision-making. This paper can be useful for managers and heads to create an organizational culture that promotes both motivation and performance. This paper is unique as it examines the links between organizational communication, motivation, and performance.
AI Based Spam Detection Using Logistic Regression Algorithm

Nowadays, a big part of people caused by unsolicited bulk email messages commonly referred to as Spam. Email has now become one of the best ways for advertisements due to which spam emails are generated. Spam emails are rely on available email or messages sent by the stranger. The possibility that anybody can leave an email or a message provides a golden opportunity for spammers to write spam message about our different interests. Spam fills inbox with number of ridiculous emails. Degrades our internet speed to a great extent .Steals useful information like our details on our contact list. Identifying these spammers and also the spam content can be a hot topic of research and laborious tasks. Email spam is an operation to send messages in bulk by mail .Since the expense of the spam is borne mostly by the recipient, it is effectively postage due advertising. Spam email is a kind of commercial advertising which is economically viable because email could be a very cost effective medium for sender .With this proposed model the specified message can be stated as spam or not using Bayes’ theorem and Naive Bayes’ Classifier and Also IP addresses of the sender are often detected.
The system of pedagogical assessment in higher education: from formalized to creative approach

In modern conditions, the development strategy of the domestic system of higher education involves a focus on the harmonious development of the individual and his creative abilities. However, the current system of pedagogical assessment in most universities, based on a point-rating system for assessing the knowledge, skills and abilities of students, is excessively formalized. The problem is that there is an urgent need to give the point-rating system a more creative content. The methods of research are the analysis of publications on the subject of the point-rating system and the identification of white spots in this subject field. An option is proposed to supplement the existing system of pedagogical assessment in higher education with a system of markers of students’ achievements, with their conversion at the end of the semester into bonus points. Such a system of fixing the super successes of students is designed to take into account their ability and desire to learn, diligence, interest in mastering new knowledge, breadth of horizons, involvement in the educational process. It also makes it possible to fully implement an individual approach to the assessment of the learning process and its results in relation to each specific student and take into account his various abilities in mastering certain competencies. The transition to an innovative point-bonus system of pedagogical assessment of training and its results allows you to add a creative, creative component to the formalized point-rating, as well as to any other assessment system. When introducing a point-bonus system in institutions of higher education, it is required to take into account their features based on the specifics of the areas of training, specialties and specializations, the region of the location of the university and other factors. In the context of a changing world and pedagogical paradigms, the point-bonus system of pedagogical assessment is designed to contribute to the improvement of higher education in Russia in the direction of the formation of a creative and creative personality of the teacher.
Watermarking and Encryption Technique to Avoid Data Leakage in Cloud Storage with Block Chain Technology

Multimedia data sharing is increasingly becoming an essential part of the daily life for end users to access different systems, services, and applications. Data disclosure frequently occurs in real-world cloud storage services. Authentication and copyright protection of multimedia contents has always been a concern in secure data transfer media. The problem has become more critical with the increasing use of the Internet and digital technologies. However, making the protection of copyright is more complex and difficult. In proposed approach both Watermarking and Proxy Re-encryption (PRE) approach utilized for efficient multimedia content sharing. Watermarking is used to hiding the information such as hide secret information in digital media like images. Encryption techniques used to provide security to data. In proposed work, secret key can be encrypted using encryption algorithm with the help of key. Then user’s private key combined with encrypted key information and can be embedded within the image or audio using LSB (Least Significant Bit). After embedding of secret information, image or audio can be encrypting using ECC Encryption algorithm. Finally, authorized user can extract decryption key with the help of embedded data verification process. Unauthorized or illegal access can identify, when user information does not match with embedded information. And also secure these transaction details using Block chain technology.
Synergistic Training: Harnessing Active Learning and Pseudo-Labeling for Enhanced Model Performance in Deep Learning

This research addresses the growing need for efficient data labeling methods by leveraging deep learning models. The proposed approach combines pre-training and active learning to automate the labeling process and reduce reliance on human annotators. In the pre-training phase, two deep learning models are trained using labeled data, adjusting the data ratio to ensure approximately 50% accuracy on the test set. In the active learning phase, the models generate pseudo labels for unlabeled data based on a confidence threshold, and the selected data is used to improve the models' performance through alternating epochs. The experimental results demonstrate the effectiveness of the approach, achieving significant improvements in accuracy compared to traditional methods. This research contributes to the trend of using deep learning for efficient data labeling and offers a promising solution for reducing the time and cost associated with manual annotation.
On-Screen Games as Illusions of Heroism and Immortality in the Non-Heroic Era

The topic of the article is related to the concept of media reality as a matrix for the construction of cultural reality and corporeality of the modern individual. A number of philosophical views on the peculiarities of the organiza-tion of virtual game space, as well as its influence on the perception and consciousness of gamers by purpose-fully forming emotions and motivation of game achievements corresponding to game behavior are compared. Particular attention is paid to the study of the basic categories of the game, such as initial conditions, rules and features of the game chronotope, followed by the analysis of the illusory nature of the basic existentials of the hero and immortality, as well as the nature of this illusory nature. Based on the results of the study, the role of the screen as the main tool for creating the emotional attractiveness of the game is assessed, within which the basic types of game action and positioning are highlighted. In conclusion, the features of the screen as a means of organizing (interface) of gamer’s interaction with the virtual space of the game are considered.
THE INVERSE LAPLACE TRANSFORM OF SOME COMPLEX EXPRESSIONS ARISING IN SOLAR ENERGY MODELS

Recently, many mathematical models are proposed to describe storage of solar energy. Most of these models are governed by boundary value problems (BVPs). The explicit solutions of such BVPs depend in determining the inverse Laplace transform of complex expressions. This paper overcomes some of these difficulties arising on account of this. The results can be invested to construct the analytic solutions of solar energy models and also models of other fields in engineering sciences. Received: May 15, 2023Accepted: July 1, 2023
Methodological and theoretical foundations of therapy with metaphorical associative cards

Metaphorical associative cards have become a popular tool in art therapy for children and adults, which is the reason and the need for their careful study. The subject of the analysis is the methodological and theoretical foundations of the use of metaphorical associative maps. The purpose of the article is to identify methodological and theoretical grounds for the use of metaphorical associative maps. The research methods used are the analysis of scientific publications and methods of categorical-system methodology (universal scheme of interaction and the method of categorical pendulum). The article substantiates the place of metaphorical associative maps in psychotherapy, searches for theoretical grounds for the implementation of psychotherapeutic procedures related to metaphorical associative maps. Based on the idea expressed by N. V. Dmitrieva, Yu. M. Perevozkina, L. V. Levina and N. V. Buravtsova, an evidence-based analysis of the characteristic features of attributing metaphorical associative maps to the section of expressive psychotherapy, a subclass of creative therapy and a class of art therapy is carried out. The methodological components of its qualitative states (object, subject and goal) in system, process and activity variations are revealed in the theoretical justification of MAC therapy based on the reliance on system and activity approaches. The study of MAC therapy as a dynamic system allowed us to conclude that the result of interaction depends on the creative potential of the client, which indicates possible limitations in the use of metaphorical associative maps. The construction of a system model of MAC therapy allowed us to identify the basic conceptual apparatus of this field of psychotherapy. The obtained results of the theoretical study will be useful in the practice of providing assistance during psychotherapeutic procedures using metaphorical associative maps.
Manipulatiоn as a phenоmenоn оf the infоrmatiоn sосiety

The article touches upon the most urgent problem of information manipulation with the aim of influencing society. In most sources manipulation is interpreted as the use of certain techniques and technologies, under the influence of which the behavior of people changes in the direction necessary for the manipulator. It is noted that the most favorable conditions for the implementation of manipulation technologies are formed in the information society, in which information, knowledge and information technologies play a special role. The analysis of existing theories allows us to consider the information society as a special type of society at the post-industrial stage of development, the production of which is based on information. Various algorithms for presenting information are used, from the elementary dissemination of information that cannot be verified to its purposeful combination, taking into account the peculiarities of perception by different audiences, including the specifics of the preferable communication channels. At different stages society development manipulation has its own characteristics. In today's information society, the biggest threat is the media. The media today is a real force in society, which, with the help of information messages, forms certain social attitudes and influences the change in a person's beliefs. The process of manipulation includes the imposition of a certain social stereotypes, thanks to which an individual reproduces the necessary behavior patterns, perception and thinking changes. The results of a number of sociological studies reveal the features of impact technologies, among which the authors note the special role of the media in imposing stereotypes through the creation of socially significant images, which also act as propaganda and agitation tools.