Reviewerly/exHarmony huggingface dataset:
Models of modern school science education: the curriculum of the discipline for higher education applicants of the degree of Doctor of Philosophy in the specialty "014 Secondary education"

The content of the course reveals the specifics of models of natural school education of domestic STEM-education and models of education for sustainable development "Environment" - the domestic analogue of STEM-education; gives an idea of the basic natural science concepts as the basis of modern PNKS; reveals the role of man in the biosphere, the possibility of forming in students high levels of intelligence, levels of social maturity and recovery of students.
Addressing the security challenges of IoT-enabled networks using artificial intelligence, machine learning, and blockchain technology

The Internet of Things (IoT) usage in 6G networks is one of the most trending and rapidly growing domains, amalgamating with many new technologies like machine learning (ML), deep learning, and blockchain. Due to this, smart devices are improving in terms of various parameters like efficiency, complexity, reliability, and so on. IoT helps track and monitor the 6G networks in communication and processing and tackles various security challenges. The implementation system of these technologies comes with many heterogeneous challenges that require specific protocols to overcome these issues. Furthermore, the advent of such a huge amount of data being generated with these systems has resulted in different types of security issues in such 6G frameworks. Therefore, this survey addresses the major challenges in implementing and deploying these IoT-enabled 6G frameworks. In this survey, an exhaustive literature review has been done. Various attacks that can take place in any IoT-enabled 6G platform have also been covered in detail. Also, the challenges related to the security aspects of 6G networks have been discussed, and their corresponding solutions have been proposed. Further, critical analysis of these issues being addressed with the trending technologies has also been discussed.
Cyberpsychology Based insider Threat Prediction Model Approach for Cybersecurity

This paper focuses on demonstrating a fundamental prediction model based on ordinal logistic regression technique for creating an awareness and the importance a holistic cybersecurity product and services based on Cyberpsychology. This is helpful for the universities and also the industries to integrate cyberpsychology into an AI-based cybersecurity product or services and that will be a powerful combination and may effectively prevent malicious internal attacks.
The deep structure of the Kuznetsk deflection and Kamzhelinsky block junction zone of the Kuznetsk Alatau according to magnetotelluric sounding data

The Kelbes-Zolotokitat region is one of the oldest gold-placer nodes in the Kuznetsk Alatau (Western Siberia, Russia). The production target in this area nowadays is mainly shallow valley alluvial placers. However, it is assumed that placer deposits accumulate a minor part of the region's gold resources, while large primary gold sources still remain undetected. Neither deep structure of gold ore regions, nodes and fields in the junction zone between the Kuznetsk deflection and the Kamzhelinsky block nor the regional distribution patterns of gold mineralization reflected in physical fields have been given proper investigation and analysis. The paper deals with the results of magnetotelluric studies together with the analysis results of potential geophysical fields in order to search for an ore-controlling structure hosting primary gold sources. The selected complex of methods is efficient for studying crustal heterogeneities spatially associated with orebearing structures in the Kuznetsk Alatau. A conductive heterogeneity with the vertical thickness up to 7 km caused by the endogenous channels of basement rocks fluid-magmatic processing and limited by deep-penetrating fault zones has been distinguished on the geoelectric section. The identified signs of intrusive magmatism in the area of the Kuznetsk deflection is also a significant result. The depth of the top of the granitoid body is 5 km. The watershed zone of the Konyukhta and Sukhaya rivers is marked as promising for further research using a detailed observation network.
Improvement of Bounding Box and Instance Segmentation Accuracy Using ResNet-152 FPN with Modulated Deformable ConvNets v2 Backbone-based Mask Scoring R-CNN

A challenging task is to make sure that the deep learning network learns prediction accuracy by itself. Intersection-over-Union (IoU) amidst ground truth and instance mask determines mask quality. There is no relationship between classification score and mask quality. The mission is to investigate this problem and learn the predicted instance mask’s accuracy. The proposed network regresses the MaskIoU by comparing the predicted mask and the respective instance feature. The mask scoring strategy determines the disorder among mask score and mask quality, then adjusts the parameters accordingly. Adaptation ability to the object’s geometric variations decides deformable convolutional network’s performance. Using increased modeling power and stronger training, focusing ability on pertinent image regions is improved by a reformulated Deformable ConvNets. The introduction of modulation technique, which broadens the deformation modeling scope, and the integration of deformable convolution comprehensively within the network enhance the modeling power. The features which resemble region-based convolutional neural network (R-CNN) feature’s classification capability and its object focus are learned by the network with the help of feature mimicking scheme of DCNv2. Feature mimicking scheme of DCNv2 guides the network training to efficiently control this enhanced modeling capability. The backbone of the proposed Mask Scoring R-CNN network is designed with ResNet-152 FPN and DCNv2 network. The proposed Mask Scoring R-CNN network with DCNv2 network is also tested with other backbones ResNet-50 and ResNet-101. Instance segmentation and object detection on COCO benchmark and Cityscapes dataset are achieved with top accuracy and improved performance using the proposed network.
Security In Wireless Body Area Network (WBAN) Using Blockchain

In this era of increased technological and medical advancements, remote monitoring of patients and elderly people has become more popular. Even in situations like the present Covid’19 pandemic the hospital and medical facilities are in demand. In such scenarios, elderly people who need medical care and patients who need round-the-clock medical attention can be made to stay in their homes and can be monitored remotely with the help of a remote patient monitoring system. Such a system can be built by incorporating Wireless Body Area Networks (WBAN). WBAN encompasses various biological wearable sensors which monitor the patient’s health around the clock. The accumulated sensor data is then shared with hospitals and medical professionals through wireless sensor networks. This data includes personnel details, various vital parameters, medical images, etc. which are highly confidential. So providing security and confidentiality in such networks is mandatory. Several cryptographic mechanisms and algorithms are available for ensuring security in WBANs. In recent days several works have been proposed to incorporate the emerging Blockchain technology to improve the privacy, security, and confidentiality in WBANs. In this survey, we discuss various research that proposed blockchain-based solutions for ensuring security, integrity, and data privacy in WBAN.
Higher education's role in developing primary school teachers' it competence: Information and educational environment

The study aims to explore the competency-based approach and the integration of information and digital competence in the New Ukrainian School concept. The study employed a research framework that involved an analysis of the current state of education in Ukraine, including an examination of teacher education, professional development programs, and competency-based approaches. The study confirmed the hypothesis that enhancing teacher effectiveness is achievable through continuous improvement and adaptation of the information and educational environment. The findings revealed the need to update education content to meet the requirements of the modern information society. The integration of information and digital competence was found to be crucial, considering the growing use of technology in education. The New Ukrainian School concept emerged as a significant approach to address these challenges and foster teacher competence in the digital era. The study concludes that prioritizing the improvement of teacher education, professional development, and competence is essential for Ukraine to realize its goal of joining the European educational environment. The competency-based approach, along with the integration of information and digital competence, offers a promising framework for updating education content. By continuously enhancing the information and educational environment, Ukraine can nurture a skilled and adaptable teaching workforce capable of meeting the demands of the modern era.
Methodological aspects of forming project competence in the process of professional training of music teachers

The objective of this article is to identify the methodological characteristics involved in developing project competence among music students who are preparing to become future specialists. The study employed the analytical and bibliographic method to review the scientific literature on the formation of project competence in artistic specialties. Various methods were used for data analysis and processing, including induction, deduction, information analysis and synthesis, systemic and comparative analysis,logical and linguistic analysis, abstraction, and idealization. The study identified the theoretical aspects of project competence formation that are deemed crucial. It also provided perspectives from both scientists and practicing music teachers on key aspects of this issue. The findings highlight the significance of project competence in preparing future music teachers to meet the evolving needs of diverse fields such as science, technology, business, and the arts. Developing project competence among music students can contribute to their cultural, spiritual, social, and creative engagement, enabling them to implement professional knowledge effectively in thebroader socio-cultural context. Overall, this article emphasizes the importance of enhancing the professional training of future art teachers, especially in fine arts. It suggests that integrating project competence development into the curriculum can lead to the meaningful training of art teachers, fostering their abilities to meet the demands of contemporary society and contribute effectively to various domains.
Protected and Energy-Efficient E-Healthcare System Based on Internet of Healthcare Services

The Internet of Things (IoT) is gaining a tons of attention in numerous industries due to its low-cost autonomous sensor operations. IoT devices in healthcare and medical activities establish an environment that recognizes the patients’ health status such as stress levels, oxygen supply, pulse and warmth, and responds quickly in the event of an emergency. Moreover, various systems founded on low-powered biosensor nodules have been proposed to monitor patients’ medical conditions utilizing Wireless Body Area Network (WBAN); despite the fact that controlling increasing power usage and communication expenses is time-consuming and attention-demanding. Another difficult research problem is data privacy and integrity in the presence of malicious traffic. Therefore, to overcome the above-stated limitations, this research introduces a Safe and the Energy-Efficient Framework for e-Healthcare using Internet of Medical Things (IoMT), whose main goal is to reduce transmission cost but also power usage among biomaterials while sending health records conveniently and, on the other hand, to protect patients’ medical data from unverified and malevolent base stations to increase internet confidentiality and protection.
The role and impact of information technology on the educational process

Digital technologies have influenced various spheres of social relations, transcending national borders and legal system peculiarities. As a result, the determinants of social relations have been transformed, impacting the educational process. This study aims to examine the current state of the educational process in Ukraine concerning the application of information and telecommunication technologies. During the research, general methods of scientific inquiry were employed, including dialectical, formal-logical, and structural-functional methods, as well as several empirical methods. The conclusion was drawn regarding the necessity of restructuring elements of the educational process, primarily to enable distance learning. Also, the authors of this research identified the absence of a single correct strategy for adapting entrepreneurial entities to digital technologies. Therefore, an approach to structuring the educational process was proposed, highlighting the measures that need to be modified when utilizingdigital technologies. The research findings are relevant and useful for the authorities to implement tools to influence the digitalization of education in Ukraine.
Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned

Abstract The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane‐of‐array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and −3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.
Foundry-ML: a Platform for FAIR Machine Learning in Materials Science

Journal Article Foundry-ML: a Platform for FAIR Machine Learning in Materials Science Get access Jingrui Wei, Jingrui Wei University of Wisconsin Madison, Department of Materials Science and Engineering, Madison, Wisconsin, United States Search for other works by this author on: Oxford Academic Google Scholar Paul M Voyles Paul M Voyles University of Wisconsin Madison, Department of Materials Science and Engineering, Madison, Wisconsin, United States Corresponding author: paul.voyles@wisc.edu Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 29, Issue Supplement_1, 1 August 2023, Page 720, https://doi.org/10.1093/micmic/ozad067.355 Published: 22 July 2023
PENGGUNAAN APLIKASI GOOGLE CLASSROOM UNTUK MOTIVASI DAN HASIL BELAJAR MATERI GEREJA SEBAGAI UMAT ALLAH PADA SISWA KELAS XI IPA SMAN 1 SIBORONGBORONG SEMESTER 1 TAHUN PELAJARAN 2021/2022

This study aims to: 1) To find out an increase in motivation to study Catholic religious education on church material as God's people in class XI IPA students at SMAN 1 Siborongborong Semester 1 Academic Year 2021/2022 through the use of an application based on google classroom. 2) To find out the learning outcomes of Catholic religious education on church material as God's people in class XI IPA students of SMAN 1 Siborongborong Semester 1 of the 2021/2022 Academic Year through the use of a google classroom-based application. This research method uses classroom action research (CAR). The research subjects were students of Class XI IPA at SMAN 1 Siborongborong. The data collection technique uses: 1) observation; 2) Test; 3) Documentation. The results of the study show that: 1) The use of a google classroom-based application for learning Catholic religious education for church materials as God's people can increase student motivation. This is evidenced by an increase in learning motivation from 6 students or 26.09% in the initial study to 15 students or 65.22% in the first cycle and 21 students or 91.30% in the last cycle. 2) The use of google classroom-based applications for learning church materials as God's people can improve student learning outcomes. This is evidenced by the increase in the average initial study learning outcomes of 54.78, in the first cycle the average value obtained by students was 66.52 and in the second cycle the average value obtained by students was 74.78 and was supported by an increase learning completeness in the initial state was 4 students (17.39%), in cycle I it increased to 12 students or 52.17% and in cycle II it increased again to 20 students or 86.96%.
PENERAPAN PENDEKATAN BERBASIS GENRE DENGAN AUDIO VISUAL AID UNTUK MENINGKATKAN KEMAMPUAN MENULIS SISWA KELAS 11 MADRASAH ALIYAH NEGERI SERDANG BEDAGAI

APPLICATION OF A GENRE-BASED APPROACH USING AUDIO VISUAL AID TO IMPROVE THE WRITING ABILITY OF CLASS 11 STUDENTS OF SERDANG BEDAGAI MADRASAH ALIYAH. The purpose of this study was to determine the effectiveness of applying GBA with Audio Visual Media in Teaching Listening to improve writing skills in grade 11 students at MANSB. The research subjects were all students of class XI MANSB. The procedure for this research includes: Preparing the GBA learning model; Determination of the treatment class/group, namely the control group and the experimental group, Conducting pre-tests, Conducting teaching and learning activities (KBM) in the experimental class and control class with the GBA learning model, Conducting Post-tests, and Analyzing data. The learning outcomes in the experimental class (Pre-Test) were 36 students,60.00.and in the control class (Pre-Test) of 35 students, most students (13 students or 37%) got scores in the range50.01 - 60.00.The learning outcomes in the experimental class (Post-Test) were 36 students, the majority (8 students or 22%) got the core in the82.51 - 88.33.and in the control class (Post-Test) of 35 students, most of the students (12 students or 34%) got scores in the62.51 - 70.00.
Evaluation of Forensic Medical Examination using the DEMATEL Method

Forensic medical examination is Searching for injuries and police to be used as evidence at trial Taking samples and A lawsuit following Sexual Assault Forensic Medicine The purpose of the test is to the victim's Health needs assessment Treatment of any injuries When consolidating and prosecuting Gather resources for potential use trial (US Department of Justice, 2004, pp. 30-2). Because the body is the scene of the crime, testimony is time sensitive and may only last until the victim has showered, washed, and/or urinated. (1) Examination by a health care provider is recommended even if no injuries are seen. As a result of the attack, (2) the victim did not want to collect evidence, or (3) the attack was not recent. In these cases, the victim may have injuries that are not obvious or serious or have associated health concerns Forensics in the criminal justice system Science is an important part. Forensic scientists at crime scenes and sources from elsewhere study commonly murder in major criminal cases including impeachment Guilt or innocence Forensic Science as a Factor in Determining was used. Forensic Medicine or Forensics Pathology is a branch of forensic science that helps in finding the results of crime evidence. Visualize by applying clinical facts to the situation. Course subjects help individuals become proficient in identifying the cause and time of death and other details about the deceased DEMATEL (Decision Making Trial and Evaluation Laboratory) They are divided into analysis using the Forensic Medical Examination Assessment of the victim, Informed consent, Medical, and gynecological history, Assault history, and Physical top-to-toe examination It is the interaction between the factors Visualized and assesses dependent relationships Through the structural model Also deals with identifying important.Assessment of the victim, Informed consent, Medical, and gynecological history, Assault history, Physical top-to-toe examination the assessment of the victim got the first rank whereas the Informed consent number is having the lowest rank.Forensic Medical Examination. Assessment of the victim is got the first rank whereas the Armed consent number is having the Lowest Rank
Human-AI Collaboration in Explainable Recommender Systems: An Exploration of User-Centric Explanations and Evaluation Frameworks

Explainable Recommender Systems (XRS) have emerged as a transformative technology that bridges the gap between recommendation accuracy and transparency, providing users with understandable explanations for the AI-driven suggestions. This research paper delves into the critical aspect of Human-AI Collaboration in XRS, aiming to enhance user understanding, trust, and satisfaction in the recommendation process. The paper begins by investigating the dynamics of collaboration between users and AI algorithms within the context of XRS. It explores the intricate interaction between users' preferences and cognitive processes and the explanations generated by the system. This exploration forms the foundation for developing user-centric explanations that cater to individual comprehension levels and preferences. Various techniques for facilitating Human-AI Collaboration are examined, including model-based explanations, post-hoc approaches, interactive interfaces, and hybrid methods. These techniques empower users to interact with the XRS, customize explanations, and gain insights into the recommendation process. Addressing challenges in the implementation of Human-AI Collaboration, the paper explores interpreting complex AI models, balancing explanation simplicity with comprehensiveness, and ensuring user trust and system adoption. Ethical considerations regarding user privacy and fairness are also discussed. To enable user-driven explanation generation, the paper proposes strategies for empowering users to personalize the explanation process, select preferred explanation styles, and provide contextual information. Such user-driven approaches foster a more transparent and collaborative relationship between users and XRS. In order to evaluate the effectiveness of Human-AI Collaborative XRS, the paper introduces a comprehensive evaluation framework. This framework includes metrics for explanation quality, user understanding, satisfaction, trust, and engagement. The results of this evaluation can guide further improvements in XRS, ensuring the delivery of transparent, user-centric, and trustworthy recommendations. The findings of this research contribute to advancing XRS technology and serve as a foundation for future investigations into the collaborative nature of recommendation systems. By fostering collaboration between humans and AI, we can design recommender systems that empower users, promote user satisfaction, and facilitate informed decision-making in various real-world scenarios.