Reviewerly/exHarmony huggingface dataset:
IoT Integration in Telemedicine: Investigating the Role of Internet of Things Devices in Facilitating Remote Patient Monitoring and Data Transmission

Introduction: The integration of Internet of Things (IoT) technology with telemedicine has ushered in a groundbreaking era for healthcare, allowing for remote monitoring and data transmission of patients. This research paper aims to explore the complex relationship between IoT devices and telemedicine, examining their combined potential to improve patient care and transform healthcare workflows. Method: To gain a deeper understanding of the impact of IoT-powered telemedicine, a qualitative study was conducted to explore the experiences and perspectives of both healthcare practitioners and patients. Using in-depth interviews and content analysis, we examined the integration of IoT devices, such as wearables and remote sensors, into telemedicine platforms. This allowed us to uncover real-time health data collection and transmission from patients' homes to medical professionals. Result: This study's analysis of the benefits, challenges, and user satisfaction indicates that IoT-powered remote patient monitoring significantly enhances patient care by facilitating timely interventions and reducing hospital admissions, ultimately leading to improved healthcare outcomes and highlighting the effectiveness of IoT-powered remote patient monitoring in relation to healthcare outcomes. Furthermore, we analyze the complex technical factors that influence the effective deployment of IoT devices in telehealth settings. The integration of telemedicine with IoT technology is a complex process that requires careful consideration of several factors, including data security, interoperability, and data analytics. These factors play a crucial role in ensuring the effective and secure exchange of health information between different systems. The insights gained from this research can help to inform the development of best practices for telemedicine, ultimately improving patient care and outcomes. The findings also have implications for healthcare providers, technology developers, and policymakers who seek to leverage IoTintegrated telehealth solutions in their work.
A Detailed Study on Mobile System

A thorough examination of the latest advancements in mobile systems is given in this review article, emphasizing on three key areas: security, performance, and future technologies. It integrates existing studies and literature to provide a summary of the changing terrain in the design and execution of mobile systems. In addition to exploring modern options like biometric authorization, secured enclave tech highlights the obstacles presented by cyber security threats. The study also discusses how new developments in artificial intelligence, Internet of Things (IOT) unity, and 5G networks are influencing the development of mobile systems.The review emphasizes the challenges posed by cyber security threats and explores contemporary solutions, such as biometric authentication, secure enclave technologies. and block chain integration.
Application of AI in Everyday Life

This day and age, artificial intelligence is growing quickly because of new, cutting-edge discoveries made every day. These days, computers are made to do easy things like driving a car, recognising faces, and other small jobs. The main goal of artificial intelligence, on the other hand, is to make smarter systems that can do everything better than people. This also includes getting things done, like playing chess and handling math problems, which are harder jobs. So, the end goal is to make everything better using AI. People working together can solve problems better than people working alone. Longterm, a computerised technology that does all human tasks, like moving cars and running businesses electronically, will present many problems.
Importance of Cyber Security in the Internet of Things Era

The rapid proliferation of Internet of Things (IoT) devices has ushered in a new era of interconnected technologies, promising unprecedented convenience and efficiency in our daily lives. However, the exponential growth of IoT also presents an alarming challenge in terms of cyber security. This review paper delves into the intricate landscape of cyber security in the IoT era, providing a comprehensive analysis of existing research, key challenges, and innovative solutions. The paper explores the vulnerabilities inherent in IoT ecosystems, the evolving threat landscape, and the implications for privacy, data integrity, and critical infrastructure. By examining the state-of-the-art security mechanisms, including encryption, authentication, and intrusion detection, this review sheds light on the ongoing efforts to safeguard IoT systems. Furthermore, it delves into the policy and regulatory frameworks that govern IoT security and the ethical considerations surrounding data privacy. Through an in-depth evaluation of research articles, case studies, and industry best practices, this review offers valuable insights for researchers, policymakers, and practitioners working to fortify the security of IoT ecosystems and ensure a safer and more resilient future for the Internet of Things. So, this paper talks about how to make sure these gadgets are safe and that the bad people can't do anything bad with them. It's like putting locks on your doors to keep your toys safe. They talk about how to make strong locks and rules for these gadgets so that they stay safe and you can keep using them without any worries. It's all about keeping the Internet of Things safe!
IMPROVING STUDENTS' READING COMPREHENSION THROUGH THE DRTA STRATEGY

This research is aimed at improving the reading comprehension ability of Serambi Mekkah English students on narrative texts through DRTA (directed reading thinking activity). The strategy was conducted beyond the consideration of finding that the researcher found during the preliminary study. Many of the students at the university, especially the students of English department encountered problems in comprehending the texts or passages. It was found that students hardly understood the narrative text especially about factual detail, main idea, and word meaning. Therefore, researchers implemented the DRTA strategy. The researcher used collaborative classroom action research design. It was conducted in two cycles by following the procedures of action research, i.e., planning, implementing, observing, and reflecting. Each cycle was carried out two meetings of strategy implementation and one meeting for the test. The data of the study was gathered through observation sheet, students' observation sheet, reading comprehension test and questionnaire. The result of the research showed that the DRTA strategy has improved students’ reading comprehension. The improvement could be seen from the increase of the students' score in reading comprehension which reached the target score (70 in the range of 0 to 100), i.e., in preliminary the mean score was 6,42. Then the mean score increased to 6,96 in post-test cycle I. The mean score of the student’s proficiency improved to 8,33 in post-test cycle II. This evidence suggested that the students had already reached the intended target score, namely 7,00. It means that many students responded that the application of DRTA strategy was helpful to improve their reading skill, and the strategy was very good to improve the student's comprehension of main idea, factual detail and word meaning.
Data Visualization Analysis in the Management Information System for Submitting Credit Scores for Education Personnel

Education staff have an important role in facilitating the implementation of the tridharma of higher education and are an indicator of educational administration success. This study looks at how data visualization was implemented in the Management Information System for Submitting Credit Scores for Education Personnel. The research is primarily concerned with the Functional Position of Intermediate Expert Computer Staff. The study's goal is to create web-based data visualization tools to enable submitting and assessing credit scores for Intermediate Computer Experts easier, thereby meeting the requirement for efficiency and accuracy in the promotion and position process. This study employs a research and development (R&amp;D) methodology with an iterative prototype approach. The initial step involves a needs analysis, including an in-depth understanding of the Associate Computer Expert promotion process and the associated administrative requirements. Next, a web-based data visualization prototype was designed, which included an intuitive user interface, database integration, and a credit number calculation algorithm. The prototype was then implemented and tested on a limited basis in the IPDN environment. The proposed system is designed to provide easy access, facilitate data verification, and enable computerized sorting and calculation of credit numbers. The main contribution of this research lies in developing information technology solutions that can increase the transparency and effectiveness of administrative processes in the IPDN environment. It is hoped that the output of this research can provide conceptual and practical contributions to managing the credit figures for educational staff and provide a basis for developing similar systems in other educational institutions.
Guided tours of the educational subject "The world around us" in the first and second grades

The publication highlights one of the active forms of organizing training – an excursion. The types of excursions conducted with first and second grade schoolchildren in accordance with the requirements of the Federal educational program in the subject “The World Around Us” are considered. The types of excursions are characterized: local history (social and natural history) and complex. In connection with the integrative content of the educational subject “The World Around Us,” preference is given to comprehensive excursions, since they allow children to be introduced to different objects, bring knowledge from different fields, that is, to form a well-rounded, informed personality. Particular attention is paid to the preparation of the teacher for the excursion, taking into account the age characteristics of the children, as well as the productive use of the observation method during its implementation.
The Demonstration of Mathematical Logic Ability and Control Consciousness of Higher Vocational Students

Math is upmost basic for working and learning. It exists for solving some problems. The authors focus on that only by combining the students’ problem-solving control consciousness in vocational education we can enhance the mathematical logic ability. This paper discusses the best way to solve the paper’s key point, that is connotative relationship between various factors of learners, how to sort out the control consciousness, improve the mathematical logic ability, and then build a practical logic thinking way, to form a system of students’ mathematical self-added value, and put forward new possibilities for the scientific cultivation of the quality of mathematical education talents. This paper emphasizes the effective role of mathematical logic ability and regulation awareness in the application of information technology in higher vocational education learning. Given many examples to demonstrate how to get the useful abilities to solve the problems facing in the future.
Design and Application of Personalized Teaching Model Based on Learning Styles and BOPPPS

Personalized teaching is the future development trend, and learners have their own characteristics and talents, so teaching that meets the characteristics of learners can give full play to the “learner-centered” teaching concept. Although the research on learning styles has confirmed that it is not correlated with teaching interaction, the value of learning styles has not been fully explored, and there are still few studies on effectiveness. According to Kolb’s experience and learning theory, this paper analyzes the personality characteristics of learners with each learning style. Based on the characteristics of learners with various learning styles, the teaching model of four different learning styles was designed in combination with the BOPPPS teaching model to realize personalized teaching. According to the designed teaching mode, the corresponding teaching mode is applied to the high school IT course “Processing and Handling of Picture Information” as an example, which fully reflects the application of personalized teaching in the secondary school classroom.
QUANTUM CRYPTOGRAPHY METHODS AND INSTRUMENTS

Secure data exchange over the network is ensured by the requirements of confidentiality, integrity and availability of information. To meet these requirements, sent data is encrypted on the sending side, and the received information is decrypted on the receiving side. Transmitted message is encrypted according to rules determined by the algorithm and key. Crypto security of encrypted information depends on the key length. Among the encryption algorithms, there are algorithms with a symmetric (private) key and with an asymmetric (public) key. Despite all the advantages of a private key, asymmetric keys are used to deliver it from one user to another (key distribution). However, high-performance quantum computers are capable to decrypt intercepted data. Therefore, modern cryptographic systems use quantum key distribution method. The idea of using quantum bits was proposed in 1970 by S. Wiesner. In 1984, Ch. Bennett and G. Brassard proposed the BB84 protocol. The use of «entangled » quanta for systems with quantum key distribution was offerred in 1991 by A. Eckert. All modern quantum cryptography systems are based on these above-mentioned protocols.
Identifying Promising and Talented Students Based on Intellectual System KOMPOS+

The article studies relevant issues of identifying promising and talented students in secondary and higher educational institutions. These issues are as follows: assessing how successfully the curriculum was mastered by a group of students as a whole; finding out who of the students in the group showed the best and the worst results; assessing how well a particular academic discipline is mastered by each student; testing whether a particular student has vocational and personal qualities necessary for future profession; identifying strengths and weaknesses of the future specialist; revealing disadvantages and advantages hidden in the group of students. To solve these problems, it is proposed to use the intellectual system "KOMPOS +" ("Comprehensive assessment of students"). The system allows assessing vocational and personal qualities of senior students and their vocation potential, as well as creating vocational portraits of graduates of educational institutions. The system gives recommendations to ensure graduates’ optimal performance in the market economy. It is proposed to create a bank of promising and talented students and a bank of employers and make them available at offices and departments of educational institutions. This enables to optimally combine graduates’ interest in obtaining jobs and that of employers in attracting promising and talented specialists, which guarantees effective operation of enterprises in the competitive environment.
The Implementation of Quizizz in Learning at SDN 08 Sui Ruk Bengkayang

The development of Information and Computer Technology (ICT) has had a broad impact on various sectors of life, including the education sector and ICT mastery. Through formal education, students are equipped with insight from an early age which becomes the basis for continuous learning and developing problem-solving skills. However, in Bengkayang District, West Kalimantan, the ICT education program has not yet reached students in several rural schools, including SDN 08 Sungai Ruk, where students are not familiar with computers both in terms of hardware and software. In addition, the COVID-19 pandemic has had a significant impact on education. Since March 16 2020 in Indonesia, students have been studying from home through an online system to prevent the spread of the virus.&#x0D; Nonetheless, the government continues to encourage teaching and learning activities even though remotely. Based on these problems, Quizizz is implemented for students of SDN 08 Sungai Ruk so that elementary school students have knowledge and skills in operating computers both in terms of hardware and software, and increase learning motivation. This implementation provides an introduction to computer introduction material regarding computer basics such as computer components and their functions. Followed by a Fun Game that aims to break the ice. And finally an interactive quiz was held using the Quizizz platform which was based on the material previously presented.
A Novel Radon Transform for Image Registration

Objective: Registration is a critical step in any image analysis. In the Radon Transform, rotation can be expressed as translation, and the Fourier Transform is invariant to translation. In this paper we present an efficient combination of Radon Transform and Fourier Transform for obtaining transformation to correct scale, translation and rotation. This concept is used for image matching. Method : This study presents an innovative Radon Transform to register two images. The method involves calculating a Radon Transform first, followed by a Fourier description for each image that needs to be matched. Mono-modal visuals are used in experiments. The Lena dataset is used for correcting scale, translation, and rotation. The same algorithm is used on around 36 images to correct scale, translation, rotation, scale and rotation, rotation and translation, scale and translation etc. Findings : This algorithm is tested successfully with different datasets, which differ by translation and/or rotation. Lena image dataset is used that was scaled, rotated and translated with the objective of template matching. Around 36 datasets are used for experimentation. Novelty : Innovative method of combination of Fourier and Radon Transform for image registration is attempted with 98 % accuracy. Keywords: Image registration, image fusion, Radon Transform, Fourier transforms, affine transform
Research Review on Measuring Information Security Awareness

One of the factors that contributes to unauthorized parties releasing confidential company information, including employee personal information, is a lack of awareness of employee information security. This is a critical concern that needs to be addressed immediately by strengthening the company's information security culture and raising employee awareness of security. To enhance the clarity and emphasis of the reform policy, it is crucial to evaluate employee awareness of information security. This paper discusses several approaches that have been employed, either as models or frameworks, to evaluate an organization's level of information security awareness. With the aid of inclusion and exclusion criteria, we chose 16 papers out of the 842 that were included in the systematic literature review. Three components are commonly used to assess information security awareness: knowledge (what is already known), attitude (what is thought to be appropriate to do), and habit (what is usually done). Measurements that encompass these three aspects employ the Knowledge, Attitude, and Behavior (KAB) paradigm. This study might be a reference for organizations to measure their employees’ security awareness. Several findings are also discussed in this paper.
FINANCIAL FRAUD DETECTION AND MACHINE LEARNING ALGORITHM (UNSUPERVISED LEARNING): SYSTEMATIC LITERATURE REVIEW

This research aims to assess the usage of unsupervised learning in detecting financial fraud across various financial industries by identifying cognitive constructs, benefits, economic optimization, and challenges associated with fraud detection necessitating innovative approaches for effective detection. This study conducts Systematic Literature Review following PRISMA protocol for article selection of 27 journal articles published between 2010 and 2023, sourced from Scopus database. The analysis discloses that unsupervised learning has been implemented across diverse financial sectors, including online payments, insurance, and prominently in banking, especially for identifying anomalies in credit card transactions. K-Means is the most popular method used in unsupervised learning. Nevertheless, there are ongoing challenges that require solutions to ensure the efficacy of machine learning implementation, encompassing issues like class imbalance and the complexity of fraudulent activities. In theoretical terms, this research provides an understanding of cognitive concepts, benefits and applications, challenges, and practical recommendations in the use of unsupervised learning for financial fraud detection. This is useful for practical implementation, benefiting industry practitioners in selecting appropriate models with datasets that have the potential to enhance detection system accuracy and reduce financial losses due to fraud.
Research on Improving Education Quality and Efficiency through Artificial Intelligence and Big Data Analysis

This study mainly focuses on using artificial intelligence and big data analysis technology to improve the quality and efficiency of education. Firstly, we introduced the basic concepts and development history of artificial intelligence and big data analysis, and outlined their current application status in the field of education. Then, the advantages and challenges of artificial intelligence and big data analysis in improving education quality and efficiency were discussed. Next, the integration application of artificial intelligence and big data analysis was explored, and practical cases in the field of education were provided. We discussed in detail the specific methods and applications of using artificial intelligence and big data analysis to improve education quality and efficiency, including the construction and optimization of personalized teaching models, prediction and intervention of student learning behavior, and the development and application of teacher assistance tools. Finally, the main conclusions of the study were summarized, the limitations of the study were pointed out, and suggestions were made for future research directions and development in the field of education. Through this study, it is hoped that it can provide reference and guidance for research on using artificial intelligence and big data analysis to improve education quality and efficiency.
Dawn of a New Era: History of Uzbekistan's Higher Education System Transforms with Matrix Management

This research explores the impact of the transition to matrix management within history Uzbekistan's higher education system, marking a significant shift in its administrative and operational paradigm. The study posits that the adoption of matrix management will engender a range of positive outcomes. This approach uses a mixed-methods design with descriptive methods. Firstly, the author hypothesizes that the shift will improve operational efficiency through better resource allocation and interdepartmental collaboration. This is anticipated due to matrix management's inherently flexible structure, allowing for more dynamic resource utilization and encouraging cross-functional teamwork. This research suggests that this transformation will lead to heightened job satisfaction among faculty and staff. Matrix management, with its emphasis on open communication and collaborative decision-making, is expected to create a more engaged and motivated workforce. The results of this study could potentially inform other sectors in history Uzbekistan and other nations grappling with similar educational challenges, particularly those seeking to improve efficiency, innovation, and stakeholder satisfaction within their systems. This research underscores the significance of administrative and managerial strategies in transforming the higher education landscape, paving the way for future educational excellence.