Cloud-based Technologies Research Articles

Implementation of ESP32-Based Web Host For Control and Monitoring of Robotic Arm

In the modern technological era, the Internet of Things (IoT) plays a significant role in developing robotic control systems, including robotic arms. This study explores the implementation of an ESP32-based webhost to control and monitor robotic arm operations in real time via a web interface connected to a Wi-Fi network. The system is designed to provide ease of access, reliable performance, and low latency, making it suitable for education, technical training, and other applications. Testing revealed that the system delivers fast response times, high stability under moderate loads, and an intuitive interface for users with varying skill levels. These findings present opportunities for further development, including integration with cloud-based technologies and data security enhancements

Progress and Applications of Fully Homomorphic Encryption

In the era of digital transformation, marked by the widespread adoption of cloud-based technologies such as cloud computing and storage, ensuring data security and protecting user privacy have emerged as critical industry concerns. Fully Homomorphic Encryption (FHE) addresses these issues by allowing various computations to be performed on ciphertexts without the need for decryption, thus safeguarding data security and privacy. This paper explores the mathematical and algorithmic foundations essential for understanding FHE. It provides a detailed analysis of the advancements in FHE schemes over the past decade, focusing on various mathematical problems, including ideal lattices and integers. The discussion extends to three practical applications: cloud computing, machine learning, and electronic voting, highlighting the progress and exploring potential future research avenues and developmental strategies in the field of FHE. This comprehensive review not only underscores the significance of FHE in enhancing data security but also charts a path for its future exploration and integration into emerging technologies.

Cloud-Enabled Personalization: Transforming Educational Paradigms through Adaptive Learning Technologies

This article examines the transformative impact of cloud computing on personalized learning in education, exploring how cloud-based technologies are reshaping educational paradigms. Through a comprehensive analysis of adaptive learning platforms, real-time feedback systems, and learning analytics, we demonstrate how cloud computing facilitates tailored educational experiences. The article addresses key challenges in education, including accessibility, resource allocation, and costeffectiveness, showcasing cloud-based solutions that enhance collaboration and inclusivity. We explore the evolution of teaching and learning tools, from virtual classrooms to interactive content delivery, and their role in improving student outcomes through early intervention systems and engagement-enhancing techniques. The global reach and scalability of cloud-based education are examined, highlighting its potential for cross-border learning and ability to meet fluctuating demands. Our findings indicate that cloud computing is not merely a technological advancement but a fundamental shift in educational methodology, offering unprecedented opportunities for personalized, efficient, and globally accessible learning experiences. This article contributes to the growing body of knowledge on educational technology and provides insights for educators, institutions, and policymakers seeking to leverage cloud computing for educational excellence.

Giant Kerr nonlinearity of terahertz waves mediated by stimulated phonon polaritons in a microcavity chip

Optical Kerr effect, in which input light intensity linearly alters the refractive index, has enabled the generation of optical solitons, supercontinuum spectra, and frequency combs, playing vital roles in the on-chip devices, fiber communications, and quantum manipulations. Especially, terahertz Kerr effect, featuring fascinating prospects in future high-rate computing, artificial intelligence, and cloud-based technologies, encounters a great challenge due to the rather low power density and feeble Kerr response. Here, we demonstrate a giant terahertz frequency Kerr nonlinearity mediated by stimulated phonon polaritons. Under the influences of the giant Kerr nonlinearity, the power-dependent refractive index change would result in a frequency shift in the microcavity, which was experimentally demonstrated via the measurement of the resonant mode of a chip-scale lithium niobate Fabry-Pérot microcavity. Attributed to the existence of stimulated phonon polaritons, the nonlinear coefficient extracted from the frequency shifts is orders of magnitude larger than that of visible and infrared light, which is also theoretically demonstrated by nonlinear Huang equations. This work opens an avenue for many rich and fruitful terahertz Kerr effect based physical, chemical, and biological systems that have terahertz fingerprints.

E-SDAPONIKS: A Cloud-Based Aquaponics Management System with Data Analytics

This study endeavors to create an advanced aquaponics management system, elevating monitoring capabilities through the integration of environmental sensors. By harnessing the power of the Internet of Things (IoT) and cloud-based technology, users gain unprecedented control over devices while seamlessly recording and analyzing system data. Complementing this, a user-friendly mobile application provides realtime insights into feed consumption, water parameters, and harvest schedules, enhancing operational efficiency. The Agile Methodology serves as the framework for this project, enabling a flexible and iterative approach to hardware and software development. Key hardware components include temperature and humidity sensors, electrical conductivity sensors, and pH sensors, essential for comprehensive monitoring. Facilitating seamless integration, an ESP32 microcontroller manages these sensors, boasting built-in Bluetooth and Wi-Fi modules to facilitate connectivity with the mobile application. In assessing project performance, adherence to ISO 25010 requirements and IEEE standards validates the system’s robustness and reliability.

Pre-Service Teachers’ Inclination Towards the Utilization of Cloud-Based Technologies

By harnessing the power of 21st-century, the use of cloud computing resources in higher education has emerged as a hot area for deploying innovative technologies in teaching and learning. Accordingly, the core objective of the present study is to analyze the inclination towards the utilization of cloud-based technologies among pre-service teachers in the present digital environment. Based on studies reviewed, a research model was developed with five usability factors - perceived usefulness, perceived ease of use, perceived security, frequency of usage, and behavior intention. Quantitative survey method was used to collect data among 252 pre-service teachers in Karaikudi locality. Factor Analysis, Percentage Analysis, Pearson Correlation Analysis, Multiple Linear Regression Analysis were employed for data analysis Statistical analysis of the data indicates that pre-service teachers exhibit a favorable inclination towards using cloud-based technologies with a moderate extent, which is predominantly influenced by perceived ease of use. It is evident from the present study that pedagogical approaches need to change for successful integration of technology in future classrooms and for the development of sustainable educational practices.

Nephrological care in Ukraine during wartime: challenges and innovations

The war in Ukraine has profoundly impacted the provision of nephrological care, presenting numerous challenges while also driving significant innovations. This study aims to analyze the availability and quality of nephrological care in Ukraine during wartime, focusing on chronic kidney disease stages 1–5D/T. The conflict has caused population displacement, restricted access to treatment, and disrupted healthcare logistics, adversely affecting nephrological care. Despite these challenges, the healthcare community has adapted through the implementation of virtual nephrology, incremental and extended dialysis regimens, and increased use of new therapy approaches. The war led to a decrease in the population and migration of medical personnel, particularly from southeastern to western Ukraine, causing staffing imbalances that were gradually addressed. Technological innovations, such as digital nephrobiopsy with immunohistochemical analysis and the use of cloud-based technology, allowed for rapid and remote diagnosis. Virtual healthcare and remote consultations ensured continuity of care, while kidney transplantation activities saw a notable increase, facilitated by advanced techniques and international aid. Despite initial logistical challenges and resource shortages, the resilience and adaptability of the Ukrainian nephrological care system have been evident. This study underscores the importance of robust contingency planning, international collaboration, and the adoption of innovative solutions to maintain healthcare delivery in conflict zones. The findings offer valuable insights into managing nephrological care under extreme conditions and highlight the potential for these innovations to improve care delivery globally.

The State of The Knowledge of Cloud Computing Technology for Manufacturing Automation Systems

The manufacturing sector is grappling with the need to adapt to rapid technological changes, and leveraging cloud computing is becoming crucial for staying competitive and resilient. The presentation of knowledge in this work focuses on highlighting the specific challenges and opportunities in integrating cloud technologies into manufacturing systems. It aims to answer critical questions such as how cloud computing can enhance manufacturing automation, solve problems, and benefit to the industry. The methodology employed in this research takes a comprehensive and top-down approach, aligning and exploring the practical aspects of implementing these X-as-a-Service (XaaS) model in manufacturing setups. The research also acknowledges the shift from legacy Distributed Numerical Control (DNC) systems to modern solutions like MTConnect and Open Platform Communication (OPC) for data exchange in automated manufacturing systems. Emphasizing the important of data collection and real-time monitoring, the study highlights the role of Industrial Internet of Things (IoT) sensors deployed at various points of manufacturing system components (machine tools, spindles, cutting tools, production units, etc.). These sensors capture real-time production and condition data, enabling informed decision-making in manufacturing systems. This research not only presents the latest knowledge but also offers insights into the challenges, strategies, and methodologies involved in the successful integration of cloud-based technology into manufacturing automation systems. It also aims to serve as a valuable resource for manufacturers, researchers, and industry professionals navigating the transformative journey toward cloud-powered manufacturing.

IOT Based Smart Baby Cradle

Abstract: An infant/toddler care monitoring system utilizing IOT is a system that uses the Internet of Things (IoT) to monitor and care for a baby while they are in their cradle is known as an infant/toddler care monitoring system. A microcontroller, a cloud-based platform, and a cradle with sensors and actuators typically make up the system. The sensors can track the temperature, respiration rate, and heart rate of the infant. They can be used to track the baby's movements and cries. The cradle's swinging motion as well as other elements like a nightlight and lullaby music player can be controlled by the actuators. The microcontroller, which also controls the actuators, processes the sensor data. Additionally, it is in charge of interacting with the cloud-based platform. The cloud-based technology retains the sensor data and makes it accessible to parents via a web or mobile app. Parents can watch their child's vital signs, get warnings if something is wrong, and manage the cradle's capabilities using the web or a mobile app. For instance, if the infant starts to cry, the parent can start the cradle swaying or play lullaby music from a distance to assist in soothing the child.

Cloud Computing And Security Issues In The Cloud

For future of computing, cloud computing serves as conceptual and infrastructure foundations. There is significant shift in worldwide computer infrastructure toward cloud-based architectures. To take benefit of Cloud Computing, it is vital to deploy it across wide range of industries. However, Security remains primary concern in Cloud Computing environment. There is fresh business paradigm cloud-based technologies because of evolution of cloud services and providers. Because of the widespread use of the internet in many businesses as well as geographically dispersed cloud servers, confidential material of various organizations is typically stored on remote servers and in locations that could potentially be exposed by unwanted parties in cases where those servers are compromised. In the absence of reliable security, cloud computing's flexibility and benefits would be deemed unreliable. Our paper offers a overview of cloud computing ideas and also safety challenges that arise into regards of cloud technology including cloud architecture.

DengueFog: A Fog Computing-Enabled Weighted Random Forest-Based Smart Health Monitoring System for Automatic Dengue Prediction.

Dengue is a distinctive and fatal infectious disease that spreads through female mosquitoes called Aedes aegypti. It is a notable concern for developing countries due to its low diagnosis rate. Dengue has the most astounding mortality level as compared to other diseases due to tremendous platelet depletion. Hence, it can be categorized as a life-threatening fever as compared to the same class of fevers. Additionally, it has been shown that dengue fever shares many of the same symptoms as other flu-based fevers. On the other hand, the research community is closely monitoring the popular research fields related to IoT, fog, and cloud computing for the diagnosis and prediction of diseases. IoT, fog, and cloud-based technologies are used for constructing a number of health care systems. Accordingly, in this study, a DengueFog monitoring system was created based on fog computing for prediction and detection of dengue sickness. Additionally, the proposed DengueFog system includes a weighted random forest (WRF) classifier to monitor and predict the dengue infection. The proposed system's efficacy was evaluated using data on dengue infection. This dataset was gathered between 2016 and 2018 from several hospitals in the Delhi-NCR region. The accuracy, F-value, recall, precision, error rate, and specificity metrics were used to assess the simulation results of the suggested monitoring system. It was demonstrated that the proposed DengueFog monitoring system with WRF outperforms the traditional classifiers.

THE FUNCTION OF CLOUD COMPUTING TECHNOLOGY: AN INVALUABLE WEAPON AGAINST COVID-19

This study looks into how important cloud computing is to reducing the difficulties brought on by the COVID-19 epidemic. As the workforce becomes more reliant on digital solutions and works remotely more frequently, cloud computing becomes a vital tool for maintaining flexibility and company continuity. The study examines how cloud-based technologies, like scalable infrastructure and tools for remote collaboration, are being used to meet the extraordinary needs of distant work environments.

Random forest evaluation using multi-key homomorphic encryption and lookup tables

In recent years, machine learning (ML) has become increasingly popular in various fields of activity. Cloud platforms have also grown in popularity, as they offer services that are more secure and accessible worldwide. In this context, cloud-based technologies emerged to support ML, giving rise to the machine learning as a service (MLaaS) concept. However, the clients accessing ML services in order to obtain classification results on private data may be reluctant to upload sensitive information to cloud. The model owners may also prefer not to outsource their models in order to prevent model inversion attacks and to protect intellectual property. The privacy-preserving evaluation of ML models is possible through multi-key homomorphic encryption (MKHE), that allows both the client data and the model to be encrypted under different keys. In this paper, we propose an MKHE evaluation method for decision trees and we extend the proposed method for random forests. Each decision tree is evaluated as a single lookup table, and voting is performed at the level of groups of decision trees in the random forest. We provide both theoretical and experimental evaluations for the proposed method. The aim is to minimize the performance degradation introduced by the encrypted model compared to a plaintext model while also obtaining practical classification times. In our experiments with the proposed MKHE random forest evaluation method, we obtained minimal (less than 0.6%) impact on the main ML performance metrics considered for each scenario, while also achieving reasonable classification times (of the order of seconds).

A New Cloud-Native Tool for Pharmacogenetic Analysis.

The advancement of next-generation sequencing (NGS) technologies provides opportunities for large-scale Pharmacogenetic (PGx) studies and pre-emptive PGx testing to cover a wide range of genotypes present in diverse populations. However, NGS-based PGx testing is limited by the lack of comprehensive computational tools to support genetic data analysis and clinical decisions. Bioinformatics utilities specialized for human genomics and the latest cloud-based technologies were used to develop a bioinformatics pipeline for analyzing the genomic sequence data and reporting PGx genotypes. A database was created and integrated in the pipeline for filtering the actionable PGx variants and clinical interpretations. Strict quality verification procedures were conducted on variant calls with the whole genome sequencing (WGS) dataset of the 1000 Genomes Project (G1K). The accuracy of PGx allele identification was validated using the WGS dataset of the Pharmacogenetics Reference Materials from the Centers for Disease Control and Prevention (CDC). The newly created bioinformatics pipeline, Pgxtools, can analyze genomic sequence data, identify actionable variants in 13 PGx relevant genes, and generate reports annotated with specific interpretations and recommendations based on clinical practice guidelines. Verified with two independent methods, we have found that Pgxtools consistently identifies variants more accurately than the results in the G1K dataset on GRCh37 and GRCh38. Pgxtools provides an integrated workflow for large-scale genomic data analysis and PGx clinical decision support. Implemented with cloud-native technologies, it is highly portable in a wide variety of environments from a single laptop to High-Performance Computing (HPC) clusters and cloud platforms for different production scales and requirements.

Triadic Technology Configuration: A Relational Perspective on Technologists’ Role in Shaping Cloud-Based Technologies

Through an ethnographic study of a manufacturing monitoring technology, the author examines how the relations among workers, managers, and third-party technologists impact the ongoing configuration of cloud-based workplace technologies. Because these technologies are broadly networked, data-driven, and highly malleable, the author argues that technologists have an increasingly prominent role. By tracing issues raised by workers and managers in the focal customer firm, the study shows that the employment relation can explain only a limited set of outcomes. An analysis that accounts for technologists’ innovative and economic relations with their users fully explains which issues are resolved and how. In contrast to research that implies technologists amplify institutionalized patterns of labor–management relations through their design choices, this study shows that technologists are complex organizational actors with situated interests, values, and identities. Through the development of a triadic model of relations, the author demonstrates why technologists must be included in analyses of contemporary technologies.

Intelligent task processing using mobile edge computing: processing time optimization

<p>The fast-paced development of the internet of things led to the increase of computing resource services that could provide a fast response time, which is an unsatisfied feature when using cloud infrastructures due to network latency. Therefore, mobile edge computing became an emerging model by extending computation and storage resources to the network edge, to meet the demands of delaysensitive and heavy computing applications. Computation offloading is the main feature that makes Edge computing surpass the existing cloud-based technologies to break limitations such as computing capabilities, battery resources, and storage availability, it enhances the durability and performance of mobile devices by offloading local intensive computation tasks to edge servers. However, the optimal solution is not always guaranteed by offloading computation, therefore, the offloading decision is a crucial step depending on many parameters that should be taken in consideration. In this paper, we use a simulator to compare a two tier edge orchestrator architecture with the results obtained by implementing a system model that aims to minimize a task’s processing time constrained by time delay and the limited device’s computational resource and usage based on a modified version.</p>

Glycemic outcomes and patient satisfaction and self-management improves in transition from standard to virtual multidisciplinary care

AimsWith advances in cloud-based technologies, there has been a rise in remote T1D care. We hypothesized that transitioning T1DM care to a virtual, multidisciplinary clinic could improve measures beyond HbA1c. MethodsTo assess the impact of transitioning from standard to virtual T1DM care, we evaluated glycemic measures and patient reported outcomes. ResultsSixty-one adults with T1DM were included, with mean age 40.2 ± 13.5 years and diabetes duration 16.9 ± 9.0 years. Most patients were treated with insulin pumps and CGM. The number of annual diabetes care encounters rose from 2.1 ± 4.2 to 12.8 ± 5.5. Baseline HbA1c was 7.9 ± 1.6 %(63 ± 16.9 mmol/mol), declining to 7.3 ± 1.1 %(56 ± 8.5 mmol/mol) and 7.1 ± 1.0 %(54 ± 7.7 mmol/mol) at 6 and 12 months respectively (p < 0.001 for both). In parallel, TIR improved from 63.1 ± 19.3 % to 69.2 ± 13.8 % (p < 0.001) and 67.5 ± 19.4 % (p = 0.03) at 6 and 12 months respectively, while TBR declined. Scores from validated diabetes treatment and self-management questionnaires rose significantly and these rises were associated with a reduction in HbA1c, the latter score was also associated with increased TIR. There was a trend toward a correlation between encounter frequency and improvement in HbA1c and TIR. ConclusionsTransitioning from standard to virtual, coordinated, multidisciplinary T1DM care is associated with increased visit frequency, improving glycemic control, treatment satisfaction and self-care behaviors.

User-Centered Design to Develop Automated Short Message Service Messaging for Patient Support of Rheumatic Heart Disease Secondary Antibiotic Prophylaxis.

The Active Community Case Management Platform is a cloud-based technology developed to facilitate rheumatic heart disease case management by health care providers. This study aimed to design and pilot an automated short message service (SMS) intervention to support secondary prophylaxis adherence. We developed a concise library of messages to support secondary antibiotic prophylaxis. The SMS intervention used TextIT, an interface that enables users to send out interactive SMS messages at scale. The message bank was piloted in a cohort of 50 patients with rheumatic heart disease randomized into 2 groups. Group 1 received standard support (nurse-led/Active Community Case Management Platform). Group 2 received standard support plus SMS intervention for 2 months in the Lira and Gulu districts of Northern Uganda. We collected qualitative data on participants' experiences and assessed treatment adherence. Using a sequential user-centered process consisting of 4 phases (phases 1-4), we developed a message bank (n=43) deployed during our pilot study. There were no between-group differences in treatment adherence or acceptance. Interviews of participants indicated that the intervention was viewed positively. A total of 75% of SMS recipients responded to the messages, and 25% called the study staff to acknowledge receipt of text messages. This study has successfully developed a bank of SMS messages to support secondary antibiotic prophylaxis adherence. We have demonstrated the feasibility and acceptability of SMS technology in rheumatic heart disease care management. Future work will include integrating automated SMS into the Active Community Case Management Platform and a larger study of integrated SMS to reduce health care worker burden for patient support and improve adherence to secondary antibiotic prophylaxis.

Breast Cancer Diagnosis Using Virtualization and Extreme Learning Algorithm Based on Deep Feed Forward Networks

One of the leading causes of death for women worldwide is breast cancer. Early detection and prompt treatment can reduce the risk of breast cancer-related death. Cloud computing and machine learning are crucial for disease diagnosis today, but they are especially important for those who live in distant places with poor access to healthcare. While machine learning-based diagnosis tools act as primary readers and aid radiologists in correctly diagnosing diseases, cloud-based technology can also assist remote diagnostics and telemedicine services. The promise of techniques based on Artificial Neural Networks (ANN) for sickness diagnosis has attracted the attention of several re-searchers. The 4 methods for the proposed research include preprocessing, feature extraction, and classification. A Smart Window Vestige Deletion (SWVD) technique is initially suggested for preprocessing. It consists of Savitzky-Golay (S-G) smoothing, updated 2-stage filtering, and adaptive time window division. This technique separates each channel into multiple time periods by adaptively pre-analyzing its specificity. On each window, an altered 2-stage filtering process is then used to retrieve some tumor information. After applying S-G smoothing and integrating the broken time sequences, the process is complete. In order to deliver effective feature extraction, the Deep Residual based Multiclass for architecture (DRMFA) is used. In histological photos, identify characteristics at the cellular and tissue levels in both tiny and large size patches. Finally, a fresh customized strategy that combines a better crow forage-ELM. Deep learning and the Extreme Learning Machine (ELM) are concepts that have been developed (ACF-ELM). When it comes to diagnosing ailments, the cloud-based ELM performs similarly to certain cutting-edge technology. The cloud-based ELM approach beats alternative solutions, according to the DDSM and INbreast dataset results. Significant experimental results show that the accuracy for data inputs is 0.9845, the precision is 0.96, the recall is 0.94, and the F1 score is 0.95.

Research into the world of Cloud-Virtual Reality

Virtual Reality technology has not been able to penetrate the mainstream consumer market due to restrictions on hardware and content. With the advancement of cloud computing technologies, Virtual Reality hardware and technology applications may now be supported strongly. The metaverse, cloud VR gaming, and cloud VR stimulator are just a few of the real-world applications that are now employing cloud computing in Virtual Reality. We can lower the cost of Virtual Reality technology which would begin a new era of many users to apply cloud-based technologies. With the aid of technology, it will be possible to operate from anywhere without having to transport a lot of equipment. The performance, usability, and compatibility of Virtual Reality software and hardware can be improved by cloud computing on the level of hardware and content. The VR dataset is made available for public collaboration through the Internet using a VR-Cloud server. The digital asset that represents the layout of our pedestrian bridge comprises images of all the streets, buildings, trees, and other urban amenities. In the virtual environment of the metropolitan area, where they run and stroll according to predetermined behaviour scenarios, the cars and people are created and entered. By employing cloud communication software to analyse simulations of vehicles and pedestrian crowds and to debate design ideas, users share the VR reality by connecting to the VR Cloud servers from remote devices. This research demonstrates how VR-cloud may be combined with Neuralink and NFT in the virtual world for future enhancement. This paper is a research note on cloud computing and its application using the Virtual Reality (VR) platform for the modern world with futuristic innovations. Keywords: Cloud Computing, Metaverse, Neuralink, Virtual Reality, VR-Cloud.)