Reviewerly/exHarmony huggingface dataset:
The Role of Image Encryption and Decryption in Secure Communication: A Survey

Information security is a vital tool for protecting the confidentiality and integrity of digital information. In this paper, we consider different image encryption techniques based on advanced encryption standard (AES), chaotic system, RSA, elliptic curve cryptography (ECC), data encryption standard (DES), and hybrid encryption schemes. Further, the discriminative capability of each encryption scheme is then examined. Various security analyzes were also considered to show the effectiveness of the respective models proposed by different researchers.
Role of Natural Language Processing for Text Mining of Education Policy in Rajasthan

The knowledge of education policy will bring an array of new growth, but it has necessitated an improved type of human–machine intercommunication, in which the machine enhances a thoughtful and interactive intelligence. Natural language processing (NLP), a part of artificial intelligence (AI), is the competence of a computer program to comprehend spoken and written human language ( https://www.linguamatics.com/what-text-mining-text-analytics-and-natural-language-processing ; Zhang and Segall in IJITDM 7(4):683–720, (2008)) [1, 2]. After being thoughtful about it, in mining, one should have sagacity for the predetermination of policy (Bhardwaj in Int J Eng Res Technol (IJERT) 1(3), 2012; Maes in Commun ACM 7:30–40, 1994) [3, 4]. Using NLP, this provides a quick way of extracting information about education policy. This paper focuses on manipulating NLP commands after data collection using unstructured interviews about the attitude of NLP and then filling out a website questionnaire form to collect the satisfaction result. Coding is executed to get the required data using Python and NLP. During the analysis of feedback at colleges in Jaipur, Rajasthan, it is divulged about the satisfaction of using NLP commands, so it is observed that NLP creates a convenient way of mining. The goal behind this text mining is to identify the importance of NLPs in getting data into an integrated form. Lastly, in the execution phase, it narrates the process to obtain cognition for extricating data about policies for gratification.
Fuzzy Physics: A New Paradigm for Modelling Physical Systems

This study investigates the application of fuzzy logic in modelling physical systems, with a specific focus on a pendulum system as a representative case. We employ a comprehensive methodology that includes the development of fuzzy models, integration with existing physical models, and a combination of simulation and experimental studies. Our findings reveal that fuzzy logic-based models outperform classical deterministic models, particularly when handling uncertainties in initial conditions, damping, and external forces. The adaptability of fuzzy models to uncertainties is a key advantage, making them well-suited for complex and unpredictable physical systems. The integration of fuzzy logic components into existing models enhances modelling accuracy without necessitating major modifications. This research highlights the potential of fuzzy physics in advancing our understanding of complex physical phenomena and calls for further interdisciplinary exploration, robust mathematical formalism development, and philosophical inquiries into its implications.
Classification of Sciences in the Context of Postnonclassical Rationality

The present article addresses the science classification problem in the context of modern postnonclassical in-tellectual culture. The aim of the article is a brief philosophical analysis of approaches to the classification of sciences and characterization of their application for solving applied problems of systematization of modern science. In the first part of the article using the material of classical systems of scientific knowledge proposed by Aristotle, F. Bacon, G.W. Leibniz, the fundamental principles of categorization of sciences are considered, assuming the reflection of the ontological structure of the surrounding world. Since postnonclassical science is a dynamic system, a combination of analytical (a priori, theoretical) and synthetic (posteriori, empirical) ap-proaches is proposed to solve modern applied problems of science systematization. The second part of the article discusses some shortcomings and practical recommendations for the compilation of scientific classifica-tions. The main emphasis is stressed on the need to reflect interdisciplinary research. To sum up, conclusions dwells upon the fact that in the context of postnonclassical rationality universal classification of sciences is un-attainable, but there is a need for philosophical search of techniques for realization of applied tasks of modern sciences classification.
SUMMER SCHOOL "NATIONAL SCIENTIFIC PSYCHOLOGICAL SCHOOLS: HISTORY AND PRESENT" AS A TOOL FOR EDUCATIONAL SOCIALIZATION OF SCIENTISTS AND TEACHERS OF PSYCHOLOGY AT UKRAINIAN HIGH SCHOOLS

The purpose of the article: to reveal the socializing and scientific didactic potential of the Summer School (2021) "National scientific psychological schools: history and modernity" as a tool for informal educational socialization of scientists and teachers of psychology of Ukrainian higher education institutions and their students. Sample. 100 participants of teachers, doctoral students and students from various institutions of higher education at scientific institutions of Ukraine, who took part in the jubilee Summer School 2021, mastered its professional development program (180 hours) and received the corresponding certificate. Methods. Presentations and workshops by leading psychology researchers in Ukraine about achievements of representatives of Ukrainian scientific psychological schools of the past and present, scientific reports, discussions and debates, final control of participants' knowledge in the form of an achievement test. The results. The tested program of the summer psychological school (2021) National scientific psychological schools: history and modernity has proven itself as a productive means of informal educational and professional socialization of Ukrainian psychology teachers, doctoral students and students. The developmental effect of participation in such an event was demonstrated by all categories of its participants who, thanks to the introductory lecture of the organizers, independent work, presentations by speakers and fruitful discussions, significantly expanded their ideas about the history, methodology and modern features of domestic scientific and psychological research, technologies of psychological practice and interdisciplinary links of psychology.
3D Scene Graph Generation Using Prior Knowledge from Large Language Model (LLM)

In this paper, we propose a novel 3D scene graph generation model, L3DSG, which can make use of rich prior knowledge obtained from large language model (LLM) by prompt engineering. The proposed model is built upon our previous 3D scene graph generation model, C3DSG, that adopts Point Transformer as 3D geometric feature extractor and uses the NE-GAT graph neural network as context reasoner. The new proposed model addresses the inability of C3DSG to utilize prior knowledge on indoor physical environments. It focuses on issues of how to obtain prior knowledge from LLM and how to make use of it for predicting objects and their relations effectively. The proposed model is extended from C3DSG by adding several elaborate modules to prompt, encode, and fuse prior knowledge from LLM. Through various experiments using the benchmark dataset 3DSSG, we show the superiority of the proposed model.
DEVELOPMENT OF CREATIVE THINKING OF PRIMARY GRADES STUDENTS IN THE PROCESS OF EXTRACURRICULAR WORK

This work highlights certain aspects of the development of creative thinking of elementary school students in the process of extracurricular work and outlines the conditions for its development
Beyond the Virus

This collection examines social inequalities brought to stark attention by the COVID-19 pandemic under three thematic strands: power and governance, gender, and marginalized communities. This project brings together a range of international scholars from multiple disciplines (law, sociology and politics) to showcase a diversity of perspectives on these themes. The unknowns around this virus and the scale of the epidemic make COVID-19 and its inequalities a timely subject. Understanding each of these issues from the perspective of multiple disciplines, with law at its centre, is the first step towards tackling them concretely and achieving social justice. The thematic coherence on social inequalities affecting vulnerable groups from international and multidisciplinary lenses is the book’s central feature.
Deep Video Compression Based on 3D Convolution Artifacts Removal and Attention Compression Module

Most research of video compression focuses on how to effectively extract the information between frames and use this information for the subsequent reconstruction. Previous algorithms used 2D convolution to extract information between adjacent frames, but 2D convolution is insufficient in spatio-temporal extraction ability, so we consider using a 3D convolution network to remove artifacts caused by motion compensation. In order to further improve the compression performance, we put the 3D convolution network and the residual compression network into the feature space to reduce the errors caused by inaccurate pixel-level operations. In addition, we also propose a motion compression network based on attention module, so that the network can pay more attention to the complex area of the image. Experimental results show that our model achieves the same or even better performance than other end-to-end video compression models in PSNR and MS-SSIM, even though our method has a much smaller number of parameters.
Adaptive Reservoir Neural Gas: An Effective Clustering Algorithm for Addressing Concept Drift in Real-Time Data Streams

The concept drift phenomenon describes how the statistical properties of a data distribution change over time. In cybersecurity domain, where data arrives continuously and rapidly in a sequential manner, concept drift can be a significant challenge. Identifying concept drift, it enables security analysts to detect emerging attacks, respond promptly, and make informed decisions based on the changing nature of the data being analyzed. The Adaptive Reservoir Neural Gas (AR-NG) clustering algorithm is proposed in this paper to handle concept drift in real-time data streams. It is a novel approach that combines reservoir computing power with the neural gas algorithm, allowing the algorithm to automatically update its clustering structure as new data arrives. Furthermore, in order to effectively handle evolving data streams that significantly change over time in unexpected ways, the proposed method incorporates a density-based clustering mechanism (DBCM) to concept drift detection. Experiments on real-time data streams show that the proposed algorithm is effective at mitigating the impact of concept drift, making it a useful tool for real-time data analysis and decision-making in dynamic environments.
The Intersection of Ethics and Biometric Data in Eye-Tracking Systems

In this thought-provoking chapter, we delve into the ethical dimensions surrounding the utilization of eye-tracking technology. as our world becomes increasingly driven by technological advancements, eye-tracking has emerged as a powerful tool for understanding cognitive processes, knowledge synthesis, and behavioral patterns. however, the profound implications of this technology raise significant ethical concerns that demand careful examination. our exploration begins by examining the intricate relationship between biometric information and cognitive identity formation. we question the ethical correctness of capturing an individual's cognitive state without their explicit consent, considering scenarios such as using eye-tracking webcams to analyze reactions to street billboards. furthermore, we contemplate the potential consequences of this technology, including its potential for identifying criminals, monitoring health conditions, and exacerbating societal disadvantages. recognizing that eyetracking data can be processed by artificial intelligence and decision support systems, we emphasize the urgent need for a comprehensive understanding of the legal dimensions surrounding digital data. to ensure responsible usage, we argue for robust discussions that encompass both ethics and informatics law, ultimately establishing a solid infrastructure that safeguards individual rights and promotes societal well-being. this chapter serves as a critical exploration of the ethical dilemmas inherent in eye-tracking technology. by shedding light on the complexities and potential implications, we aim to foster a deeper understanding of the ethical considerations that must be taken into account when navigating the evolving landscape of cognitive research and biometric data analysis. through these discussions, we can work towards ensuring the responsible and ethical implementation of eye-tracking technology in our society.
CLASSIFYING FAKE PROFILE IN FACEBOOK ACCOUNT USING SUPPORT VECTOR MACHINE

The ability to connect people around the world and share videos, photos and communications has made online social media (OSM) popular. Despite much of literature available in this field, there is still lack of study focusing on the creation of fake profile in the OSM. In fact, there has been relatively little effort aimed at solving fake profile features using classification algorithm. For these reasons, Support Vector Machine (SVM) classifier was employed to classify the novel features that had been created in the fake profile particularly among Facebook users’ account. The study begins with the data collection process, data pre-processing, evaluation, testing and lastly obtaining the result. The findings have revealed that the SVM classifier able to predict the fake profile with high Classifying Accuracy (CA) and Area Under Curve (AUC). Ultimately, this finding will provide a new endeavour for countermeasure and protection of OSM users.
Research on the Teaching Reform of Visualization in the course of Ancient Literary History under the background of "Digital Humanities"

In recent years, the "digital humanities" technology has developed vigorously, and the corresponding research results have emerged one after another. In this context, the scientific research of classical literature is developing in a more effective, accurate and comprehensive direction, both in terms of research methods and conclusions. Starting from the perspective of "visualization", this paper deeply discusses the teaching design issues related to the teaching reform of Ancient literature, mainly from the integration of the reality and academic nature of teaching content, the diversification of teaching methods with students as the main body, the integration of innovation and operability of the assessment mechanism, and tries to solve the problems of "obscure content", "time-space separation" and other problems in the course of Ancient literature, Explore a new path of teaching reform.The data comparison results showed that the new method can significantly improved the learning enthusiasm and performance of liberal arts students, and had certain application and practical value.
A study on the Teaching Design of New word practice in online Chinese listening course based on Game Teaching method -- taking the Developing Chinese (Elementary Listening Course Ⅰ) as an example

In language learning, vocabulary practice is a boring and repetitive learning content, and simple vocabulary review is difficult to stimulate interest in learning. In order to increase students' concentration, learning effect, and improve students' listening and speaking ability, the design of practice activities needs to be designed according to the specific situation. The game teaching method provides a wealth of tools and scenes for this, but the design of off-line teaching activities often does not adapt to the teaching conditions of online classes. with the continuous development of information technology, multimedia technology has become an indispensable teaching means in the teaching process. The interaction between teachers and students needs to face the problem of remote communication. In order to reduce students' learning gap and increase students' teaching participation, using PPT to do new word practice game design has become a very effective teaching tool. Through several different PPT new word practice designs, this paper increases students' interest in practice, improves students' practice effect, and enriches online Chinese new word teaching practice means.
The Teaching Reform of “College Writing” Aiming at Cultivating Ability

College Writing is an important professional basic course of Chinese subject, aiming at cultivating students' writing ability. It has always undertaken more expectations on the cultivation of writing ability. Based on the current reform of China's higher education, this paper makes a preliminary exploration of the teaching reform of this course from the aspects of teaching concept, teaching content, teaching method and teaching evaluation, with the aim of improving students' writing ability in the teaching process.
Estimating the Maximum Power of a Concentrator Photovoltaic Module through Random Forest

Concentrator photovoltaics achieves the highest conversion efficiencies of sunlight to electricity and is a promising alternative for mass production of energy. However, these systems are complex and predicting their power generation is difficult. In this study, the maximum power of a real concentrator photovoltaic module is estimated by a new method based on random forest. The method has the advantage that only atmospheric variables relatively easy to be measured are used as inputs, i.e. no measurements on the physical module are required, enabling the energy prediction from atmospheric databases to be performed. Results of applying the method to data registered in an experimental campaign show a good behavior of the method for maximum power estimation. Therefore, the method can contribute to give certainty to the energy predictions, promoting the deployment of this technology.
Financial Report Application Design

Currently, PERUM Perhutani Tambak Ruyung Timur continues to rely on manual methods for financial reporting, resulting in incomplete financial reports. The process above has the potential to be significantly unproductive and inefficient, hence increasing the likelihood of errors in the recording procedure. Based on the backdrop above, PERUM Perhutani Tambak Ruyung Timur must implement a more pragmatic financial accounting recording system. Hence, the author interned at the organization above and produced a comprehensive Internship Report entitled "Designing a Financial Report Application: A Case Study at Perum Perhutani Tambak Ruyung Timur Pasir Jambu."The research method refers to the systematic approach researchers employ to investigate and gather data to answer research questions or test hypotheses.The research methodology employed in this study is the Descriptive Research Method. Object-Oriented Analysis and Design (OOAD) is employed in system development. The implementation of this system utilizes web programming languages, including PHP, CI, and UML. This research has yielded a financial reporting application software that is both effective and efficient.Based on the conducted research, it is inferred that the application developed by the researcher is anticipated to offer utility to PERUM Perhutani in streamlining the process of inputting financial data. Based on the acquired information, it is possible to fill incomplete financial reports by utilizing the programdeveloped by the researcher.
Using Visual Cryptography, A Safe Online Payment Method

Due to the growing usage of online shopping and online payments in recent years, the E-Payment system has experienced enormous growth. The acceptance of electronic payments for offline transfers is made easier by an electronic payment system. An electronic payment system is a technique to conduct transactions or pay for goods and services online. Systems for electronic payments are now widely employed across all industries, including banking, finance, online commerce, and many more. There were some security risks in the conventional e-payment systems, including phishing, credit card fraud, and debit card fraud. In order to solve this issue, we developed an electronic payment system that combines visual and quantum cryptography methods for safe transmission. Quantum cryptography secures the transmission of the one-time password, whereas visual cryptography conceals customer information by creating shares. We adjusted our system using the email OTP notification mechanism for OTP processing. The share is securely transmitted to the bank thanks to image steganography, which embeds a one-time password in the share. The proposed approach offers unconditional security as opposed to the conventional E-payment mechanism. Key Words: One-time passwords, online payments, image processing Quantum cryptography, visual cryptography, and image encryption.
Algoritma Apriori Dalam Identifikasi Pola Pembelian Konsumen Pada Produk Minuman

Competition between companies is getting tougher and entrepreneurs indirectly need a better product marketing strategy. Inventory management system is a very popular business in Indonesia, especially in the beverage industry. Related to inventory, there is a technique in the development of science today, one of which is data mining techniques or mining techniques. In data mining, a priori algorithms contain a type of association rules that aim to find interesting relationships between combinations of elements hidden within the dataset. The application of a priori algorithm in this study can help Pekopen tavern managers find the right consumer buying behaviour . So that it can be used as material for business decision-makers to determine marketing strategies and optimize sales of menu variants, especially for several types that are in great demand. These results are used to find new information to determine a better product marketing strategy. Data processing using apriori algorithm is carried out by conducting the highest frequency analysis based on the minimum support value followed by determining the association rules based on the confidence value and then continued with the evaluation process through determining the lift ratio. There are 2000 sales transaction data processed from the data processing process obtained from a combination of itemset {Chizu Redvelvet, Cokolateh} with a support value of 40% and a confidence value of 67%.
APPLICATION OF THE K-MEANS CLUSTERING METHOD FOR PERFORMANCE ASSESSMENT BASED ON EDUCATOR COMPETENCE

Performance appraisal is one thing to respect someone while working in an institution, one of which is a private higher education institution. To respect the performance of resources, there needs to be a value assigned to someone. Assessments carried out for one semester need to be reviewed again because during filling in the student assessments do not fill in according to their understanding so that a review needs to be carried out again. The assessment was carried out using the K-Means method by applying the concept of the centroid value. There are 4 (four) variables used, namely pedagogic competence, personal competence, social and professional competence with a value of K = 3. The maximum number of observations for cluster 3 is 368 while the value of Distances Between Cluster Centroids shows 2 suitable clusters, namely cluster 1 and cluster 2, which is 1.7020. The author gives suggestions to remove outlier data before entering the data to be trained into the algorithm to improve visualization if the dataset is large. Key Word: Performance Appraisal, Data Mining, K-Means