Computer Technology Research Articles

An Investigation into the Feedback of Automated Writing Evaluation System on EFL Learners’ Writing

Computer technology has developed at a rapid pace in recent decades. The combination of artificial intelligence and writing teaching has become an important development trend. For better utilization of Automated Writing Evaluation System in teaching, the quality of its feedback on various types of errors in compositions is one of the issues worth exploring. In order to investigate this issue, this study compares the diagnosis of EFL learners' compositions by Automated Writing Evaluation System with the actual errors in the compositions, and calculates the Precision and Recall of the iWrite system's feedback. Unlike previous studies, this study synthesizes macro discourse elements such as propositional logic, across-sentence logic, and discourse structure, and categorizes the actual errors in learners' compositions into seven kinds. The results show that the iWrite system performs excellent in detecting three kinds of errors, which are lexical errors, grammatical errors, and other detail-type errors, and is moderately effective in detecting pragmatic errors, while it fails to provide feedback on propositional logic, discourse cohesion and coherence, and paragraph structure, which are the high-level error types, indicating that iWrite system is completely unable to capture errors in terms of macro-discourse elements. These findings provide a strong basis for improving Automated Writing Evaluation System, and at the same time provide English teachers with a reference for writing teaching, which helps to better serve the field of foreign language education.

RPKI Defense Capability Simulation Method Based on Container Virtualization

As the main inter-domain routing protocol in today’s internet, the Border Gateway Protocol (BGP) faces serious security risks during actual usage. Research on BGP malicious attack methods requires a realistic network environment, and evaluation methods based on physical networks often suffer from high costs and insufficient flexibility. Thus, we propose an efficient BGP simulated network deployment system based on a virtualization technology called the SOD–BGP. This system, combining cloud computing and virtualization technologies, creates a scalable, highly flexible basic network environment that allows for the automated simulation and evaluation of actual BGP prefix hijacking attack scenarios. A Resource Public Key Infrastructure (RPKI) simulation suite is introduced into the system, emulating a certificate issuance system, certificate storage, and a certificate synchronization verification mechanism, thus aligning the simulation environment with real-world usage scenarios. Finally, we propose a data collection and performance evaluation technique to evaluate BGP networks deploying RPKI under different attack scenarios and to explore the effectiveness of RPKI defense mechanisms at various deployment rates. A comparative analysis with other simulation techniques demonstrates that our approach achieves a balanced performance in terms of deployment speed, complexity, and RPKI integrity, providing a solid simulation technology foundation for large-scale BGP security defense strategies.

PROBLEMS OF MANAGING THE IMMUNE RESPONSE UNDER CONDITIONS OF COMPETITIVE ADSORPTION, DIFFUSION PERTURBATIONS AND TEMPERATURE RESPONSE OF THE ORGANISM

Analysis of the problems associated with the rapid spread of infectious diseases indicates the need for new approaches to the diagnosis and develop- ment of effective personalized treatment programs. One of the important aspects of solving this problem is the creation of a mathematical modeling toolkit for predicting the dynamics of infectious diseases, taking into account spatial effects, concentrated effects, various mechanisms of body protec- tion in the conditions of the application of various types of therapeutic methods of treatment. An important component of complex methods of treat- ment of a wide range of infectious diseases is the use of adsorption drugs, which, along with detoxification of the body, are able to provide an addi- tional mechanism of neutralization of viral elements. In the process of using such means, not only pathogenic elements and toxins will be adsorbed, but also various types of immune agents, which will affect the dynamics of the immune response. In the paper the infectious disease model is generalized to take into account the features of competitive adsorption of antigens and immune agents in the conditions of diffusion perturbations, concentrated influences and temperature reaction of the body. By synthesizing the ideas of step-by-step procedures, asymptotic and numerical methods, an effective computational technology of step-by-step approximation of the solution of the original model singularly perturbed problem was built. The results of the computer experiments presented in the paper illustrate the features of reducing the predicted concentration of viral elements during their competi- tive adsorption together with immune agents, in particular, the effect of reducing the efficiency of the use of non-specific adsorbents. It is emphasized that taking into account the features of the action of competitive adsorption is important for making decisions regarding the formation of rational treatment programs with the complex use of adsorbing substances and immunological drugs.

Digital methods for diagnosing dental occlusion disorders

Relevance. Occlusal disorders are not only predictors of oral diseases but are also associated with systemic conditions such as endocrine, cardiovascular, and cognitive disorders, highlighting their broader significance in medicine. The digitization of diagnostic processes and the integration of computer technologies into traditional methods offer promising advancements in assessing occlusal status. This makes the analysis of digital methods for diagnosing occlusal relationship disorders particularly relevant.Purpose. To evaluate digital methods and devices used for diagnosing occlusal relationship disorders.Material and methods. A systematic review was conducted, analyzing 40 scientific publications from 2016 to 2024 that focus on digital methods for diagnosing occlusal imbalance. The study assessed electronic devices that measure occlusal force by converting mechanical force into electrical signals using various sensors. These digital methods are employed to evaluate the functional state of the masticatory system, including the detection of temporomandibular joint disorders, mandibular fractures, and occlusal deformities, as well as to monitor occlusal force dynamics during treatment. Recent advancements in portable electronic sensors suggest potential applications for their integration with control chips into dental prostheses or occlusal stabilization splints, allowing real-time monitoring of tooth compression forces, potentially enhanced by artificial intelligence.Results. The development of new diagnostic methods and devices equipped with highly sensitive sensors for measuring masticatory pressure opens new avenues for identifying clinical parameters that were previously difficult to analyze. Recent advances in hardware technology, particularly those utilizing neural network analysis, have the potential to expedite accurate diagnosis and predict the risk of complications.Conclusion. Both in Russia and internationally, significant progress is being made in the development of digital methods for diagnosing occlusal imbalance. These methods are poised to become a priority in the future of dental practice. However, the adoption of digital occlusal methods into routine dental practice is currently hindered by challenges related to the availability of digital equipment in clinics and the insufficient digital skills of many dentists. Addressing these challenges is crucial for improving the quality of dental care for patients with occlusal disorders.

Сегнетоэлектрические материалы в современных вычислениях

Background: Ferroelectric materials, known for their spontaneous electric polarization, are reshaping the landscape of modern computing. These materials have unique qualities, such as non-volatility, high-speed operation, and energy efficiency, which are critical for advancing modern computer technology. Objective: This study intends to investigate integrating ferroelectric materials into current computer systems, emphasizing to improve memory devices and processors and solve the accompanying technological obstacles and possibilities. Methods: A thorough analysis of existing literature and experimental data was carried out to determine the capabilities and limitations of ferroelectric materials in computing applications. Key performance indicators examined include polarization retention, energy consumption, scalability, and integration with existing semiconductor technology. Results: The results show that ferroelectric materials considerably increase memory device performance and efficiency by allowing quicker write/read operations and lowering power use. However, concerns such as material deterioration, data retention, and integration complexity with silicon-based technology remain. Conclusion: Ferroelectric materials provide exciting prospects for the next generation of computer technology. While they provide significant gains in memory and processing power, addressing the technological obstacles is critical to their effective adoption into mainstream computer applications. Further research and development are needed to solve these issues and fully realize the promise of ferroelectric materials in improving computer performance.

Posthuman Practices of Care beyond the Entropocene: How the FARN. collective Designs Ways of Thinking-With in «The Shape of Trouble to Come»

In The Shape of Trouble to Come: A Posthuman Ritual (2021) the FARN. collective responds to the actual condition marked by indeterminacy and environmental destruction. In the ruins of capitalism (Anna Tsing), represented on stage with electronic waste of computer technology, the German theatre collective presents in an experimental trial various speculative stories that allow the spectators to see themselves as part of a larger ecological context and attune the perspective to polyphonic assemblages with multispecies worlds. These world-conceptions presented in various scenes are based on texts and ideas of Donna Haraway, Ursula K. Le Guin, and Paul B. Preciado. In reference to Anna Tsings attempt to focus on the “arts of noticing,” author focuses in this article on practices of care which lead to a thinking in relationalities, especially to a thinking-with (Haraway). This thinking-with is a way of living-with, being aware of troubling relations and significant otherness that transforms those involved in the relation and the worlds we live in. Analyzing different polyphonic assemblages which the FARN. collective created author shows how posthuman practices of care create trouble in established epistemologies and leads to an experience of becoming and of being vulnerable to others.

COLLECTIVE INTELLIGENCE PHENOMENON STUDY AS A PRIORITY FOR ENSURING INNOVATIVE DEVELOPMENT OF ENTERPRISES

Objective. The purpose of the article is a critical analysis of the main approaches to collective intelligence as a priority for ensuring the innovative development of enterprises and the proposals development in the context of its effective use. Methodology. The development of a theoretical and methodological approach to the study of collective intelligence should be based on the business structures practical activity, the theory of collective intelligence phenomenon of individuals and their development in innovative activities; theories of organizational and competitive advantages; motivation, creativity and innovation. General and special methods are used: dialectical cognition; deductions and inductions; generalization and scientific abstraction; synergies; morphological analysis; competence, dialectical and synergistic approaches. Results. A scientific position has been created regarding the collective intelligence effective use as a priority for ensuring the innovative development of enterprises. An analysis of collective intelligence status essence and subject, the causes, mechanisms and consequences of its formation was carried out. It is shown that in contrast to the technocratic approach, which mixes collective intelligence with concepts of artificial intelligence, neural networks, big data, etc., it can be understood from a humanistic perspective as an integral set of human consciousnesses. A new understanding of the essence of the category “collective intelligence” is proposed. The issue of collective intelligence integration with computer systems and technologies framing is considered. The author emphasizes people-centeredness, which plays an important role in the intellectual and innovative activity of economic entities. The scientific novelty. The methodological foundation of collective intelligence nature is developed. The conceptual approach to the application of collective intelligence in order to ensure the innovative development of enterprises is substantiated. Measures for the development of collective intelligence are proposed, which gives the research practical value. Practical significance of the obtained results. The results of theoretical developments and practical recommendations of the author can be used to ensure the innovative development of enterprises due to the development of enterprises collective intelligence and their network associations.

COMPUTER TECHNOLOGIES AND MEDIA LITERACY IN THE EDUCATIONAL SPACE OF GEORGIA

In the twenty-first century, digital technologies are an integral part of daily life. The technology used has added a whole new dimension to society regarding communication and relationships, learning and cognition, development, and self-realization. Virtual reality has often replaced the real one, making humanity even more dependent on technology. The merits of digital technologies are unlimited access to information, inclusiveness, and availability from anywhere in the world, breaking down cultural, social, and gender barriers, self-realization and development of creative skills, social communication through various multimedia means, promotion of education and science development, and others. At the same time, the technological age has added a whole new dimension to safety in the form of suicidal online challenges, cyberbullying, and other threats that the younger generation may face as they enter adulthood. The older generation has the responsibility to protect them in the digital environment and ensure a safe digital life. Therefore, it is a priority for the education system to develop the digital awareness of young people and prepare the young generation to deal with the challenges in the digital world. This preparation is necessary for living in both the real and virtual worlds. The paper examines the current situation and peculiarities of using modern computer technologies, digital citizenship, and media literacy in Georgia's general education space and determines the possibilities for improving it.

Atomic-level quantitative analysis of electronic functional materials by aberration-corrected STEM

Abstract The stable sub-angstrom resolution of the aberration-corrected scanning transmission electron microscope (AC-STEM) makes it an advanced and practical characterization technique for all materials. Owing to the prosperous advancement in computational technology, specialized software and programs have emerged as potent facilitators across the entirety of electron microscopy characterization process. Utilizing advanced image processing algorithms promotes the rectification of image distortions, concurrently elevating the overall image quality to superior standards. Extracting high-resolution, pixel-level discrete information and converting it into atomic-scale, followed by performing statistical calculations on the physical matters of interest through quantitative analysis, represent an effective strategy to maximize the value of electron microscope images. The efficacious utilization of quantitative analysis of electron microscope images has become a progressively prominent consideration for materials scientists and electron microscopy researchers. This article offers a concise overview of the pivotal procedures in quantitative analysis and summarizes the computational methodologies involved from three perspectives: contrast, lattice and strain, as well as atomic displacements and polarization. It further elaborates on practical applications of these methods in electronic functional materials, notably in piezoelectrics/ferroelectrics and thermoelectrics. It emphasizes the indispensable role of quantitative analysis in fundamental theoretical research, elucidating the structure–property correlations in high-performance systems, and guiding synthesis strategies.

Central Hemodynamic and Thermoregulatory Responses to Food Intake as Potential Biomarkers for Eating Detection: Systematic Review.

Diet-related diseases, such as type 2 diabetes, require strict dietary management to slow down disease progression and call for innovative management strategies. Conventional diet monitoring places a significant memory burden on patients, who may not accurately remember details of their meals and thus frequently falls short in preventing disease progression. Recent advances in sensor and computational technologies have sparked interest in developing eating detection platforms. This review investigates central hemodynamic and thermoregulatory responses as potential biomarkers for eating detection. We searched peer-reviewed literature indexed in PubMed, Web of Science, and Scopus on June 20, 2022, with no date limits. We also conducted manual searches in the same databases until April 21, 2024. We included English-language papers demonstrating the impact of eating on central hemodynamics and thermoregulation in healthy individuals. To evaluate the overall study quality and assess the risk of bias, we designed a customized tool inspired by the Cochrane assessment framework. This tool has 4 categories: high, medium, low, and very low. A total of 2 independent reviewers conducted title and abstract screening, full-text review, and study quality and risk of bias analysis. In instances of disagreement between the 2 reviewers, a third reviewer served as an adjudicator. Our search retrieved 11,450 studies, and 25 met our inclusion criteria. Among the 25 included studies, 32% (8/25) were classified as high quality, 52% (13/25) as medium quality, and 16% (4/25) as low quality. Furthermore, we found no evidence of publication bias in any of the included studies. A consistent postprandial increase in heart rate, cardiac output, and stroke volume was observed in at least 95% (heart rate: 19/19, cardiac output: 18/19, stroke volume: 11/11) of the studies that investigated these variables' responses to eating. Specifically, cardiac output increased by 9%-100%, stroke volume by 18%-41%, and heart rate by 6%-21% across these studies. These changes were statistically significant (P<.05). In contrast, the 8 studies that investigated postprandial thermoregulatory effects displayed grossly inconsistent results, showing wide variations in response with no clear patterns of change, indicating a high degree of variability among these studies. Our findings demonstrate that central hemodynamic responses, particularly heart rate, hold promise for wearable-based eating detection, as cardiac output and stroke volume cannot be measured by any currently available noninvasive medical or consumer-grade wearables. PROSPERO CRD42022360600; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=360600.

Role of Telemedicine and Telehealth in Public Healthcare Sector: A Narrative Review.

Clinicians, researchers in health services, and other experts have been investigating how to improve healthcare using advanced computer and telecommunication technology for more than 30 years. Adequate medical facilities are still lacking in many places of the world. In these kinds of situations, technology can be quite helpful in expanding healthcare access to rural locations and offering better care at a lower cost. The delivery of healthcare is changing dramatically because of telemedicine and telehealth, particularly in terms of improving access to care. This paper aims to provide an update on the history, background, applications, benefits, barriers, and challenges of these recent technologies. This review article also covers the healthcare conditions of rural as well as urban communities. Furthermore, the implications of technologies used and improvement in the health status of an individual are also discussed. During the COVID-19 epidemic, telehealth quickly gained popularity, bringing to light a number of issues. Effective primary medical networks are crucial, as the COVID-19 pandemichighlighted the need for improving public health responses during crises and revealed the existing fragmentation in healthcare delivery systems.

Exploration and Practice of Course Ideology and Politics Construction in Engineering Course of Application-oriented Universities

This paper analyzes the problems in the construction of course ideology and politics, uses information technology to enable the change of thinking mode, and explores the innovation research on the new carrier and new model. The concept of tree in computer science and technology is applied to the construction of course ideology and politics, based on that a standardized ideological and political case base is built and a closed-loop model is proposed. Through the integration design of the core value system and the entire process of education and teaching, the integrated development of professional construction and ideological and political education is realized.

Automatic Segmentation of Hemorrhages in the Ultra-wide Field Retina: Multi-scale Attention Subtraction Networks and An Ultra-wide Field Retinal Hemorrhage Dataset.

Ultra-wide field (UWF) retinal imaging can improve the detection rate of retinal hemorrhage as compared with conventional fundus images. However, hemorrhages in UWF retinal images can also become smaller and more widely distributed, which can be time consuming and labor intensive. With the development of computer technology, automatic segmentation techniques can assist physicians in diagnosis. However, the lack of publicly available UWF retinal hemorrhage segmentation datasets has limited the development of automatic hemorrhage segmentation techniques in UWF retinal images. We present a large-scale high-quality UWF retinal hemorrhage segmentation dataset, named UWF-RHS Dataset, for public use. To the best of our knowledge, we are the first team to make the UWF retinal hemorrhage segmentation dataset publicly available. In addition, we propose a multi-scale attention subtraction network (MASNet) for UWF retinal hemorrhage segmentation. Specifically, highly focused lesion features are extracted by using the proposed multi-scale attention subtraction (MAS) module at the progress of the skip-connection. Several comparative experiments and ablation experiments were performed at the UWF-RHS Dataset, and all experiments state that our proposed method is effective in diagnosing retinal hemorrhages with state-of-the-art results. The proposed UWF-RHS dataset and MASNet will greatly facilitate the development of automated segmentation techniques for UWF retinal hemorrhages. Links to the UWF-RHS dataset and the MASNet model code are available fromhttps://github.com/wurenkai/UWF-RHS-Dataset-and-MASNet.

GIS-technologies and algorithm for developing regional systems for handling medical waste on the example of three regions

Introduction. GIS is a modern computer technology designed for collecting, storing, analyzing and visualizing spatial data – mapping. GIS is also actively used in healthcare to solve many regional problems, including optimization and management of healthcare resources. Over last decade, many researchers have used mathematical software models for healthcare waste management. A review of the literature shows facility location, risk to the public, and economic feasibility to be among the issues that have been extensively covered in the literature. Designing a reverse logistics network using mathematical software tools is an efficient and effective way to manage healthcare waste. The objective of the study. To determine the optimal approach to creating a functional model of a system for managing medical waste of class B and C using GIS-technologies for each of the three regions, based on the characteristics of each. Materials and methods. Medical institutions in three regions (St. Petersburg, Leningrad Region and Krasnoyarsk Territory) as sources of medical waste generation were considered taking into account their capacity and specialization. The composition and volumes of waste by class were determined using a calculation method based on indicative waste generation standards. The identification of local technologies for the neutralization of medical waste existing in medical institutions was carried out. The obtained data was processed statistically and displayed on electronic maps for subsequent use in GIS technologies, as well as for the development and justification of a waste management system for medical institutions, taking into account the prospects for the development of healthcare. Results. Based on the analysis of data on medical waste of classes B and C in individual medical institutions, as well as an analysis of the power of existing technologies for neutralizing this waste using GIS technologies, proposals were developed to improve the medical waste management system in three regions. The proposals are aimed at improving the sanitary and epidemiological situation in the regions over a five-year period and take into account the features of the existing transport infrastructure and the requirements of sanitary legislation. Limitations. The model of a medical waste management system using GIS technologies was used only for managing waste of classes B and C. Conclusion. To ensure the safe and environmentally sustainable functioning of the waste management system of classes B and C in the regions, it is necessary to apply an integrated approach based on GIS technologies. This approach should take into account the regional characteristics of the management of the medical waste disposal system and its economic feasibility and take into account the regional characteristics of transport logistics and the prospects for the development of healthcare.

The impact of technostress on caregivers of primary and secondary school children during distance-learning throughout the COVID-19 pandemic

ABSTRACT The shift to online learning due to the COVID-19 pandemic has led to numerous complaints from caregivers unaccustomed to new technologies, resulting in technostress, defined as “stress or psychosomatic illness caused by working with computer technology on a daily basis.” This study investigates the prevalence and impact of technostress on caregivers of primary and middle school children attending online school from home in the United Arab Emirates (UAE). A cross-sectional study was conducted among caregivers with children in primary and middle school residing in the UAE (n = 727; males = 86, females = 641). Data was collected using an online questionnaire examining technostress and its impact on caregiver-child relationships and health, including sleep, anxiety, and appetite. Data analysis was performed using SPSS (version 26). Caregivers aged 30–39 years and females had the highest technostress scores (p < 0.05), while occupation and education levels had no effect. Technostress was significantly correlated with mental health (r2 = 0.291; p < 0.001) and caregiver-child relationships (r2 = 0.429; p < 0.001). Caregivers with two or more children in primary and middle school had higher technostress scores (p < 0.05). In conclusion, female caregivers aged 30–39 experienced higher technostress, negatively impacting their mental health and relationships with their children. We recommend targeted anti-technostress courses and enhanced communication.

No Drone’s Sky: Full Spectrum Drone Surveillance and Neutralisation Concept for Enhanced Counter-UAS Framework

Unmanned Aircraft Systems (UAS), commonly known as drones, have witnessed substantial global proliferation in the past decade. Their constructive applications hold the promise of being a useful, yet critical component in creating a more efficient society with the enhancement of safety, efficiency, and facilitating advancements in various domains, ultimately contributing to our modern daily lives. However, the escalating dependence on computer and communication technologies renders, especially small, UAS susceptible to various threats, posing risks to public safety, national security, and individual privacy. Addressing these concerns necessitates the development of innovative technologies designed to detect, track, identify, and eliminate UAS in a manner that upholds safety, security, and privacy. A Counter-Unmanned Aircraft System (C-UAS) is defined as a system or apparatus capable of legally and securely incapacitating, disrupting, or assuming control over an UAS. Recent years have witnessed significant research endeavours aimed at detecting and eliminate drone threats. Detection methodologies encompass acoustic, visual, passive radio frequency, radar, and data fusion techniques, while neutralisation strategies encompass physical capture and jamming approaches. This paper, delving into the realm of small drone surveillance, is the opening segment of a three-part series aims to envision a C-UAS framework; it provides an exhaustive review of existing literature in the domain of UAS surveillance, delineating the challenges associated with countering unauthorised or unsafe drone operations, and evaluating the trajectory of detection to prepare against UAS-induced threats. Therefore, the fundamental objective of this paper is to offer a comprehensive surveillance baseline for a structured vision to a C-UAS framework, thus fostering a research community dedicated to the secure integration of drones into the airspace system.

METHODOLOGY FOR QUANTITATIVE ASSESSMENT OF THE FILAMENTOUS INDEX IN TECHNOLOGIES OF BIOLOGICAL WASTEWATER TREATMENT

For the quantitative control of the filamentous index in biological treatment facilities, a computerized methodology has been developed within the presented study. Its use enhances the reliability and techno-genic safety of operating biological treatment facilities. Problems related to filamentous microorganisms, which can hinder effective wastewater treatment, are considered. Sludge bulking occurs when the intensive growth of these microorganisms complicates the separation of activated sludge from treated wastewater, leading to various operational issues. The study emphasizes the importance of microscopic analysis in identifying and addressing problems associated with filamentous organisms. The use of microscopic analysis as a crucial tool for managing activated sludge issues is discussed. The classification system developed by D. Eikelboom, which identifies 21 types of filamentous organisms based on visual characteristics, is described in detail. The filamentous index, a key parameter for monitoring the quality of activated sludge, is examined in detail, along with methods to minimize subjective evaluation factors using computer technologies. The primary goal of the study is to develop a computerized methodology for the rapid quantitative determination of the filamentous index, and area of filamentous microorganisms in activated sludge. The ImageJ software was used for processing microphotographs of sludge, enabling precise measurements of geometric characteristics. The analysis includes processing images from Eikelboom's work to establish reference values for the filamentous index. Microsoft Excel software was used for theoretical calculations and statistical analysis of experimental data. The results of the research, which confirm the effectiveness of the proposed methodologies, are presented. Keywords: activated sludge, sludge bulking, filamentous index, quantitative analysis, treatment efficiency.

Enhancing rural healthcare through internet-based remote collaborative outpatient services: A comprehensive evaluation in Changzhi, Shanxi Province.

The advancement of digital technology, particularly telemedicine, has become crucial in improving healthcare access in rural areas. By integrating cloud computing and mHealth technologies, Internet-based Collaborative Outpatient Clinics offer a promising solution to overcome the limitations of traditional healthcare delivery in underserved communities. A trial was conducted in 4 counties of Changzhi City in Shanxi Province, China. The system extended to 495 rural communities and served over 5000 rural residents. Deep learning algorithms were employed to analyze medical data patterns to increase the accuracy of diagnoses and the quality of personalized treatment recommendations. After the implementation of the system, there was a significant improvement in the satisfaction levels of rural residents regarding medical services; the accuracy of medical consultations increased by 30%, and the convenience of medical access improved by 50%. There was also a notable enhancement in overall health management. Satisfaction rates among healthcare professionals and rural inhabitants were over 90% and 85%, respectively, indicating that the system has had a significant positive impact on the quality of health-care services. The study confirms the feasibility of implementing telemedicine services in rural areas and offers evidence and an operational framework for promoting innovative healthcare models on a large scale.

Mapping the Path of Digital Transformation: The Role of Leadership in Building Adaptive Organizational Culture

The development movement continues towards the digital transformation era, marked by rapid advances in information and computer technology (ICT) and the emergence of social media platforms that change the order of life to be more practical and accessible and deny the geographical distance between people. These changes require universities to adapt to the demands of rapid development. This study aims to explore the strategies carried out by university leaders in facing the challenges of the digital era and map the extent to which the transformation of university organizational culture is operated in the face of digital technology pressure. The research used a qualitative approach with a multi-site format in three private universities. Data analysis applies constant comparative analysis, which ends with a simultaneous analysis step. The results showed that university leaders are ready to implement an open strategy in facing the challenges of the digital era by utilizing these technological advances. However, there are differences in the utilization of network assets owned by institutions and the knowledge and experience of leaders. Organizational culture transformation is operated to the extent that institutions can master digital technology to optimize the performance of institutional services. Universities' engagement with digital technology does not disrupt the resilience of their organizational culture because it only leads to an adaptive surface layer.

Optimization of machine learning model training procedure on multi-gpu systems to enhance cyber security in telecommunication networks

This paper analyzes the optimization features of machine learning (ML) model training procedures using multi-GPU systems to enhance cyber security in telecommunication networks. A key aspect of the study is the use of data parallelism, which allows the distribution of the training load across multiple GPUs, significantly reducing training time and improving model accuracy-critical factors for rapid threat detection in cyberspace. A novel approach for optimizing data batch size using Mutual Information (MI) is proposed, which harmonizes the utilization of computational resources with the information content of the training data. MI helps to determine the optimal data batch size that minimizes training errors and improves model accuracy without a significant increase in training time. Experimental results demonstrate the substantial advantages of multi-GPU configurations compared to single-GPU setups, providing faster training and improved model accuracy. It was particularly emphasized that MI-guided batch size tuning significantly outperforms traditional manual tuning methods, ensuring higher validation accuracy and reducing training time. The study showed that the MI-based approach is an effective tool for addressing the problem of optimizing ML model training processes in real-world scenarios where cyber security is critical. The proposed methods allow ML models to train faster and more accurately identify potential threats, making them particularly relevant for telecommunication networks where a rapid response to new threats in real time is required. The implementation of modern computational technologies such as multi-GPU systems and MI-optimized training enhances the efficiency and accuracy of machine learning models. This, in turn, improves cyber security measures and ensures a more reliable defence of telecommunication networks against malicious attacks. It is noted that the proposed approaches can be adapted not only for cyber security but also for other areas where high model accuracy and fast training are important. Future research prospects include the development of new machine learning methods, particularly deep neural networks, the exploration of alternative computational architectures such as quantum computing or distributed systems, and their integration into real-time systems. Special attention should be paid to the ethical aspects of implementing automated cyber security systems, particularly in preventing bias in algorithms and ensuring fairness in their application.