Reviewerly/exHarmony huggingface dataset:
Covid-19 Sentiment Analysis Using Random Forest Classification

The spread of the COVID-19 pandemic has reached a significant global scale, changing the dynamics of people's lives around the world. Social media platforms such as Twitter have become important channels for individuals to share experiences, voice opinions, and participate in discussions related to this pandemic. Sentiment analysis emerged as an important approach to reveal changes in people's attitudes and emotions in facing this challenge. This research involves analyzing sentiment during the COVID-19 pandemic to understand the feelings, attitudes, and views of the community after the peak phase of the pandemic. This study refers to previous findings which show that the Random Forest Algorithm provides the highest accuracy in this analysis. Through testing with the Random Forest Algorithm method, model accuracy testing is carried out using a confusion matrix and comparing test data and training data in a ratio of 80:20. Test results show that this model achieves an accuracy rate of 91%, providing a more comprehensive view of changes in public sentiment during the COVID-19 pandemic.
Retracted: Design of Interactive Vocal Guidance and Artistic Psychological Intervention System Based on Emotion Recognition

[This retracts the article DOI: 10.1155/2022/1079097.].
Retracted: A Preliminary Study on the Dramatic Factors of Ancient Chinese Poetry under the Changing Geographical Environment

[This retracts the article DOI: 10.1155/2022/4220059.].
Retracted: Improvement of Student Weariness Emotion in English Classroom Based on Intelligent Internet of Things and Big Data Technology

[This retracts the article DOI: 10.1155/2022/9369389.].
Retracted: Rural Workplace Sustainable Development of Smart Rural Governance Workplace Platform for Efficient Enterprise Performances

[This retracts the article DOI: 10.1155/2022/1588638.].
Retracted: A Continuous Deep Learning System Study of Tennis Player Health Information and Professional Input

[This retracts the article DOI: 10.1155/2022/8599894.].
Retracted: Intelligent Correction Method of Shooting Action Based on Computer Vision

[This retracts the article DOI: 10.1155/2022/8753473.].
Retracted: Construction of Emergency Procurement System and System Improvement Based on Convolutional Neural Network

[This retracts the article DOI: 10.1155/2022/6139706.].
Retracted: Analyzing the Relationship among Social Capital, Dynamic Capability, and Farmers’ Cooperative Performance Using Lightweight Deep Learning Model: A Case Study of Liaoning Province

[This retracts the article DOI: 10.1155/2023/7064236.].
Retracted: Investigating the Impact of Bank Housing Credit Risk Control Strategy by Blockchain Technology on the Household Consumption Plan

[This retracts the article DOI: 10.1155/2022/7021384.].
Retracted: A Crop Growth Prediction Model Using Energy Data Based on Machine Learning in Smart Farms

[This retracts the article DOI: 10.1155/2022/2648695.].
Retracted: Ultrasonic Image Features under the Intelligent Algorithm in the Diagnosis of Severe Sepsis Complicated with Renal Injury

[This retracts the article DOI: 10.1155/2022/2310014.].
Retracted: Visual Identification of Mobile App GUI Elements for Automated Robotic Testing

[This retracts the article DOI: 10.1155/2022/4471455.].
Retracted: A Double-Layered Belief Rule Base Model for Driving Anger Detection Using Human, Vehicle, and Environment Characteristics: A Naturalistic Experimental Study

[This retracts the article DOI: 10.1155/2022/5698393.].
Retracted: Assessment of Physical Fitness and Health Status of Athletes Based on Intelligent Medical Treatment under Machine Learning

[This retracts the article DOI: 10.1155/2022/9687496.].
Retracted: Construction and Evaluation of Neural Network Correlation Model between Syndrome Elements and Physical and Chemical Indexes of Unstable Angina Pectoris Complicated with Anxiety

[This retracts the article DOI: 10.1155/2022/6217186.].
Retracted: Evaluation of Incision Margin and Radiotherapy Adjustment in Breast Cancer-Conserving Surgery Based on VR Pathology 3D Reconstruction

[This retracts the article DOI: 10.1155/2021/2709461.].
Retracted: Local Privacy Protection for Sensitive Areas in Multiface Images

[This retracts the article DOI: 10.1155/2022/5919522.].
Retracted: The Relationship between Insomnia and Internal Carotid Artery Stenosis and Cognitive Dysfunction by Magnetic Sensitivity Weighted Imaging Based on Wireless Network Communication

[This retracts the article DOI: 10.1155/2022/6056502.].
Retracted: Cloud-Based English Multimedia for Universities Test Questions Modeling and Applications

[This retracts the article DOI: 10.1155/2022/4563491.].
Retracted: Emotion Analysis Based on Neural Network under the Big Data Environment

[This retracts the article DOI: 10.1155/2022/7123079.].
Retracted: Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor

[This retracts the article DOI: 10.1155/2021/5683433.].
Retracted: Nutritional Management Mode of Early Cardiac Rehabilitation in Patients with Stanford Type A Aortic Dissection

[This retracts the article DOI: 10.1155/2022/2124636.].
Retracted: An Optimized Decision Method for Smart Teaching Effect Based on Cloud Computing and Deep Learning

[This retracts the article DOI: 10.1155/2022/6907172.].
Retracted: Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection

[This retracts the article DOI: 10.1155/2022/8501738.].
Optimization of Performance in Cloud Data Streaming: Comprehensive Review

With the proliferation of cloud computing, the landscape of data processing has undergone a transformative shift. Cloud data streaming, a linchpin of real-time data processing, has emerged as a critical enabler for organizations seeking timely insights and informed decision-making. However, optimizing the performance of cloud data streaming systems poses intricate challenges that necessitate exploration. This comprehensive review article navigates the multifaceted terrain of enhancing performance in cloud data streaming. It encompasses foundational concepts, performance evaluation metrics, prevalent challenges, advanced optimization strategies, illustrative case studies, comparative analysis of platforms, anticipatory trends, and directions for further research.
Retracted: Examining the Effectiveness of Using Adaptive AI-Enabled e-Learning during the Pandemic of COVID-19

[This retracts the article DOI: 10.1155/2021/3928326.].
Retracted: Diffusion Tensor Imaging Observation of Frontal Lobe Multidirectional Transcranial Direct Current Stimulation in Stroke Patients with Memory Impairment

[This retracts the article DOI: 10.1155/2022/2545762.].
Retracted: A Real-Time Crowd Monitoring and Management System for Social Distance Classification and Healthcare Using Deep Learning

[This retracts the article DOI: 10.1155/2022/2130172.].
Retracted: Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network

[This retracts the article DOI: 10.1155/2023/9450816.].
Retracted: Emotional Intervention and Education System Construction for Rural Children Based on Semantic Analysis

[This retracts the article DOI: 10.1155/2022/1073717.].
Retracted: Research on the Mining of Intangible Cultural Heritage Digital Resources in the Manual Online Teaching System of Preschool Education

[This retracts the article DOI: 10.1155/2022/2136597.].
Retracted: Analysing Hate Speech against Migrants and Women through Tweets Using Ensembled Deep Learning Model

[This retracts the article DOI: 10.1155/2022/8153791.].
Retracted: The Innovative Trend of Piano Teaching in Music Education in Multicultural Education under Ecological Environment

[This retracts the article DOI: 10.1155/2022/7044904.].
Retracted: Inspecting Decorative Ceramic Defects by Fusing Convolutional Neural Network and Image Recognition

[This retracts the article DOI: 10.1155/2022/3983919.].
Retracted: The Application Value of SMI Technology and Contrast-Enhanced Ultrasound in the Differential Diagnosis of Benign and Malignant Thyroid Nodules

[This retracts the article DOI: 10.1155/2022/6157026.].
Retracted: Application of Visual Sensing Techniques in Computational Intelligence for Risk Assessment of Sports Injuries in Colleges

[This retracts the article DOI: 10.1155/2022/9080661.].
Retracted: Application of LSTM Neural Network Technology Embedded in English Intelligent Translation

[This retracts the article DOI: 10.1155/2022/1085577.].
Character Segmentation in the Development of Palmyrene Aramaic OCR

In this study, we present the research plan and the segmentation solution in progress for our Palmyrene OCR web and mobile application from sandstone tablet photographs, which will be publicly available on the ml-research.pef.czu.cz web portal in the next steps of the research. In this paper, we compare mathematical segmentation methods with artificial intelligence methods, highlighting the advantages and disadvantages of each solution, and propose a fully automated OCR procedure from photographs using convolutional neural networks exclusively and present a development model of our solution. We also present a partially completed segmentation dataset of the Palmyrene letters to demonstrate the functionality of the proposed procedure. We hope to complete the Palmyrene OCR soon, thus making the writings of ancient Palmyra accessible to the scientific community and the public, signifying progress in the area of Digital Humanities. Since the algorithm is not completely ready yet, we also present its development model here.
UIEL: An Underwater Image Enhancement Method based on Optical Geometric Properties

Due to the inconsistent absorption and scattering effects of different wavelengths of light, underwater images often suffer from color casts, blurred details, and low visibility. To address this image degradation problem, we propose a robust and efficient underwater image enhancement method named UIEOGP. It can be divided into the following three steps. First, according to the light attenuation effect presented by Lambert Beer's law, combined with the variance change after attenuation, we estimate the depth of field in the underwater image. Then, we propose a local-based color correction algorithm to address the color cast issue in underwater images, employing the statistical distribution law. Finally, drawing inspiration from the law of light propagation, we propose detail enhancement algorithms, each based on the geometric properties of circles and ellipses, respectively. The enhanced images produced by our method feature vibrant colors, improved contrast, and sharper detail. Extensive experiments show that our method outperforms current state-of-the-art methods. In further experiments, we found that our method is beneficial for downstream tasks of underwater image processing, such as the detection of keypoints and edges in underwater images.
The concept of the development of the mechanism of reputational responsibility of the organization within the framework of a new model of scientific attestation

The subject of the study is the concept of developing a mechanism for the reputational responsibility of organizations endowed with the rights provided for in paragraph 3.1 of Article 4 of the Federal Law from August 23, 1996 No. 127-FZ "On Science and State Scientific and Technical Policy". The purpose of the article is to propose specific tools for the implementation of the mechanism of reputational responsibility of organizations with the right to independently award academic degrees. The article examines the method of self-examination of the certification model of the organization, indicators of its effectiveness, and also provides proposals for the development of indicators for monitoring the activities of dissertation councils of organizations with the right to independently award academic degrees. The use of general logical research methods, including analysis and synthesis, the formal legal and comparative legal methods, allowed the authors to come to the following conclusions: (1) for the effective conduct of self-examination in each organization, it is advisable to adopt local regulations that approve the regulation on the procedure for conducting selfexamination and the report on the conduct of self-examination; (2) the list of information and data given in the article to be assessed during self-examination is exemplary, and can be expanded taking into account the characteristics of a scientific or educational organization; (3) organizations can be recommended to distribute digests about the dissertations defended, their real contribution to the development of science to leading educational and scientific organizations, and post them in free access on the official website of the organization. They may also contain information about self-examination and monitoring of dissertation councils, scientific attestation processes, other information that contributes to the formation of a stable positive image of the organization, the scientific community's trust in its certification model. It is substantiated that, within the framework of the new model of scientific attestation, the development of the institution of reputational responsibility of organizations with the right to independently award scientific degrees is the key to ensuring the quality of reproducible scientific personnel.
Understanding The Evolution Of Machine Learning Algorithms

Initially the computers used to perform complex calculations and stored the data as well the instructions of how the data was handled. The evolution of computers was mainly focused on managing, manipulating and storing the data while following the instructions. Furthermore, algorithms were created that read large amounts of data and could apply classification and prediction rules that understood the data and extract insights from that data. This was the beginning of Machine Learning which is a subpart of Artificial Intelligence. The revolution of Artificial Intelligence and Machine Learning is the talking point of almost every conversation that takes place today. In this paper, we take you through the history of Machine Learning and AI through its algorithms. The development and advancement of algorithms and how it is changing the scenario today. We also provide a comprehensive and comparative analysis of different Machine Learning algorithms so that it is understood in its entirety.
THE ROLE OF PARENTS TOWARDS GIFTED CHILDREN

The research objective is to describe the role of parents towards gifted children. The type of research used is qualitative. The research subjects were 6 parents of gifted students. The data collection instruments used were interviews, observation and documentation study. The results showed that the role of parents includes love, nutrition and nutrition, and stimuli given from prenatal to childhood. Affection in the form of full attention, creates a comfortable atmosphere, accompanies and helps children learn. Nutrients and nutrients in the form of nuts, eggs, green vegetables, meat, fish, fruit, and exclusive breastfeeding for 2 - 3.5 years. The stimulus given is listening to music, reading, communicating verbally and non-verbally through touching or lightly stroking the mother's stomach that is done by the father and mother when the mother is pregnant, singing, inviting the fetus to talk, and inviting the fetus to pray.
THE USE OF INFORMATION TECHNOLOGY-BASED MEDIA TO IMPROVE LEARNING OUTCOMES OF SOCIAL STUDIES SUBJECTS AT AL-FURQAN JUNIOR HIGH SCHOOL IN 2019/2020

Learning media is a vehicle for channeling messages and learning information. In this globalization era, the development of instructional media is also increasingly advanced.. The purpose of this study was to determine the improvement of student learning outcomes and student responses to the use of information technology-based interactive learning media on Integrated Social Sciences subjects in class VIII students at SMP Al-Furqan Jember. This study uses the Classroom Action Research method by conducting two learning cycles with stages in each cycle including planning, action, observation, evaluation, and reflection. Student respons data was collected through questionnaires which were then analyzed descriptively. The results of this study indicate there is an increase in student learning outcomes, this is indicated by the number of students who have completed in the first cycle of 65.52%, and the second cycle there are 93.10% of students who have completed, and student responses obtained an average score of 41.72 with a positive category. The conclusion of this research with the use of information technology-based interactive learning media in class VIII at SMP Al-Furqan Jember gave a positive response with a significant increase in learning outcomes.
Synthesis of Methods for Distance Digital Learning of Portraiture (On the Example of the Theme “Portrait of a Woman on a Light Background”)

Conventional art education at the present stage is actively developing. Nowadays there is a purposeful search for means and mechanisms of knowledge transfer from teacher to students using digital technologies. The article reviews the existing teaching methods, the use of which can be applied in the system of remote art edu-cation to improve the level of practical skills in painting, drawing and composition. As an example, the theme “Portrait of a Woman on a Light Background in Painting” was chosen as a training course for a teacher of art disciplines at the Russian State Pedagogical University. A.I. Herzen. The main five methods of online learning are considered, which can be applied using platforms, social networks and instant messengers that can elimi-nate communication difficulties as well as helping to achieve effective solution of educational tasks.
Enabling Barrier-Free Training and Employability of People with Disabilities in the Context of Digitalization

The work describes the fundamental difference between the competencies that are necessary for conventional teaching and e-learning of people with disabilities (HIA). Methods of barrier-free employment and organization of the working process of such citizens in the context of digitalization are presented. Using a software product designed for simulation modeling, an algorithm for implementing the submission of educational material for people with disabilities is developed, the main criteria for ensuring the principles of mobility, standardization, individualization in e-learning for this group of citizens are identified. It is hypothesized that with e-learning the process of lifelong education becomes easier, and people with disabilities acquire not only comprehensive access to information and learning materials, but also the possibility of transforming them under the existing physical limitations. Conditions favorable not only for lifelong learning of citizens with disabilities, but also for their remote employment and easy adaptation in the workplace have been created.
ADAPTATION OF STAFF IN AN EDUCATIONAL INSTITUTION: PROBLEMS AND SOLUTIONS

The article discusses the problems of personnel adaptation in an educational institution (using the example of IPSM RANEPA). It is emphasized that the currently existing methodology for personnel adaptation is poorly applicable in the field of higher education and is rarely found in the practical field. Modern methods and tools for adapting employees in the organization have been studied. The place of adaptation in the personnel management system of the Federal State Educational Institution of Higher Education RANEPA is analyzed. An analysis of the personnel adaptation system was carried out, which made it possible to identify emerging problems during the adaptation of personnel of the RANEPA. It has been determined that the adaptation of young specialists should consider all the modern features of the functioning of scientific and educational organizations in a competitive market environment, as well as the socio-psychological and socio-cultural features of the youth contingent of employees of the RANEPA.
Four Questions to Guide Decision-Making for Data Sharing and Integration

IntroductionThis paper presents a Four Question Framework to guide data integration partners in building a strong governance and legal foundation to support ethical data use. ObjectivesWhile this framework was developed based on work in the United States that routinely integrates public data, it is meant to be a simple, digestible tool that can be adapted to any context. MethodsThe framework was developed through a series of public deliberation workgroups and 15 years of field experience working with a diversity of data integration efforts across the United States. ResultsThe Four Questions - Is this legal? Is this ethical? Is this a good idea? How do we know (and who decides)? - should be considered within an established data governance framework and alongside core partners to determine whether and how to move forward when building an Integrated Data System (IDS) and also at each stage of a specific data project. We discuss these questions in depth, with a particular focus on the role of governance in establishing legal and ethical data use. In addition, we provide example data governance structures from two IDS sites and hypothetical scenarios that illustrate key considerations for the Four Question Framework. ConclusionsA robust governance process is essential for determining whether data sharing and integration is legal, ethical, and a good idea within the local context. This process is iterative and as relational as it is technical, which means authentic collaboration across partners should be prioritized at each stage of a data use project. The Four Questions serve as a guide for determining whether to undertake data sharing and integration and should be regularly revisited throughout the life of a project. Highlights Strong data governance has five qualities: it is purpose-, value-, and principle-driven; strategically located; collaborative; iterative; and transparent. Through a series of public deliberation workgroups and 15 years of field experience, we developed a Four Question Framework to determine whether and how to move forward with building an IDS and at each stage of a data sharing and integration project. The Four Questions—Is this legal? Is this ethical? Is this a good idea? How do we know (and who decides)? —should be carefully considered within established data governance processes and among core partners.
E-learning and Medical Assistance for Physically Impaired People

This application is a web portal which serves deaf children to learn language basics. In fact it is an e-Learning platform that helps deaf children to equip with language basics. It helps them to learn in their own pace as it is done online. The scope of the project is limited to developing web portal application that can work in various devices to support education to deaf children in terms of acquiring language. Sign Language Recognition is a breakthrough for helping deaf-mute people and has been researched for many years. Unfortunately, every research has its own limitations and are still unable to be used commercially. Some of the researches have known to be successful for recognizing sign language, but require an expensive cost to be commercialized.