Journal of Technical Science and Technologies

Development of a Decision Support System for University Administration: Integrating Business Process Management and Multidimensional Data Analysis

2024-12-17T16:50:06+04:00

The paper provides an overview of decision support systems to demonstrate their role in supporting decision-making in university administration. Enhancing university performance and modernizing university administration must be top priorities for university leaders and decision-makers since quality is the foundation that supports innovation. Good decision-making is the first step towards efficiency and quality in the academic setting. The article’s main topic is developing IT solutions to support decision-making business processes of student admission. By utilizing models of university business processes and applying business intelligence principles, with the support of multidimensional data analysis, it can be effectively introduced and integrated. The study attempts to provide selection criteria for selecting a development environment for creating a support system focused on university management based on data from the student information system database and the author’s personal experience. The contributions include creating OLAP analytical models and a data warehouse model to support university managerial decisions.

Pressure Difference Measuring System for Clean Rooms

2024-12-17T17:15:12+04:00

This article presents the development and implementation of a pressure difference measuring system tailored for clean rooms, essential in medical facilities to control airflow and reduce nosocomial infections. The study evaluates various pressure sensors, leading to the selection of intelligent sensors that meet specific performance criteria. Key features and operating principles of the system are outlined, including sensor types, measurement techniques, and system architecture. A detailed comparison of sensors such as BMP180 and BMP280 highlights their suitability based on parameters like resolution, power consumption, and communication interfaces. The system’s structure includes dual pressure sensor units connected to a main control unit, enabling real- time pressure monitoring across different room zones. The sensors, equipped with a microcontroller for initial data processing, relay information to the control unit for further analysis and display. Designed with a calibration feature, the system ensures measurement accuracy by allowing recalibration under identical atmospheric conditions. Operating on low voltage, the system provides safe and reliable performance with applications extending to isolation rooms and environments requiring precise pressure regulation. Integrating the measuring system with ventilation systems significantly mitigates the risk of airborne disease transmission, contributing to the maintenance of sterile environments. The article concludes that this cost-effective, intelligent pressure monitoring solution not only enhances safety in healthcare settings but also supports regulatory compliance and improves overall infection control measures in high-risk areas.

Call Center Monitoring for Emergency Services

2024-12-17T17:27:46+04:00

Speech recognition applications can increase the efficiency of simple tasks and greatly expand the range of tasks that call center operators perform. To increase the productivity of the public security management center, a software module was created which analyzes incoming calls, converts them into text form and places this text in the database. Operators are given the opportunity to read the call text after the end of the call to better understand its content and to improve the quality of the corresponding response. The article discusses the module, which was created to convert the incoming calls into text form. The service is a .NET Core Web API application created using the C# programming language. It uses a NuGet package to communicate with Google’s Speech service. The components of the system are described, the JSON format of the message is given, the structure of the database is discussed, the corresponding software codes of the module are given. The article also shows the customer irritating factors, analyzes the situations that create a series of calls, presents the results of customer surveys, which relate to the needs of customers in terms of waiting time. The paper discusses the mechanism for prioritizing calls, the algorithm for its implementation, as well as ways to manage non-targeted calls. The article shows the pros and cons of a system for queuing priorities.

Data lakes: Opportunities, Challenges, Threats and Ways to Mitigate Them

2024-12-17T17:33:51+04:00

Data lakes, which collect and store huge amounts of structured and unstructured data, are currently one of the most important technological tools. Their structure differs from traditional databases, as they are more flexible and allow organizations to store diverse data in a single repository for further processing and analysis. Their use is advisable in many fields, ranging from business and science to public administration. However, the rapid development of data lakes presents new challenges. The paper presents the key characteristics of data lakes and data warehouses, along with a comparative analysis. It discusses the opportunities for using data lakes, which are related to the diversity of the data stored within them. The main stages of data mining from lakes are presented. The strengths of using data lakes are also described. The paper places great emphasis on analyzing the risks associated with data lakes and proposes ways to mitigate them and the future prospects of data lakes are presented. The paper places significant emphasis on analyzing the risks associated with data lakes and proposes ways to mitigate them. Future perspectives for data lakes are also presented. Working with data lakes is a complex but important process. With the right approach and consideration of the challenges outlined in this paper, organizations will be able to maximize the potential of data lakes and gain competitive advantages.

Increasing Accessibility and Scalability of Student Services Using Microservice Architecture: A Case Study on Developing a Timetable Service

2024-12-17T17:43:25+04:00

This paper describes the development of a service for tracking the university schedule, implemented using a microservice architecture with a chat-bot as the client interface. During the development process, the needs of students and professors, as well as publicly available university data, were considered, allowing for the selection of an optimal platform and the creation of an interactive chat-bot interface. All stages of the project’s development are listed, starting from defining the main service objectives and ending with configuration and testing. Information is also provided about the chosen technologies and tools used during the development process, such as the Python and Java programming languages, the BeautifulSoup and Requests libraries, the Cloud Native and Domain-Driven Design architectural approaches, as well as containerization with Docker and orchestration with Kubernetes. The service is designed to help students stay informed about upcoming classes and events by providing information in an accessible and intuitive format. It serves as a convenient addition to traditional methods of information delivery

Development of Internet of Things (IoT) and its Impact on the Healthcare Industry

2024-12-17T17:48:25+04:00

The Internet of Things (IoT) has the potential to modernize healthcare through remote patient monitoring, disease management, and improved health outcomes. IoT devices, such as wearables and sensors, can collect and transmit data in real time, enabling healthcare providers to make informed and timely decisions. This paper examines the current state of the Internet of Things in healthcare, the opportunities presented by the Internet of Things, and the challenges faced during implementation. This paper first describes the benefits of IoT in healthcare, including improving patient outcomes, reducing healthcare costs, and increasing access to care. We look at a variety of IoT devices used in healthcare, including wearables, smart implants, and medical sensors. This paper also outlines the challenges facing the use of IoT in healthcare, including data security, privacy issues, and regulatory issues. The paper concludes with a discussion of the future of IoT in healthcare and its potential impact on the healthcare industry.

Web Technology Innovations and Their Impact on Georgia’s Labor Market

2024-12-17T17:51:32+04:00

The development of modern web technologies is associated with unprecedented changes in the digital world around us. This fact determines the existence of diverse software support and technologies for creating websites. The web technology ecosystem is developing fast, driven by emerging technologies, changing user expectations, and the ongoing digital transformation across industries. This article explores the most significant trends reshaped web development in the latest period of time, highlighting the technological innovations that are redefining how developers create, deploy, and optimize digital experiences. From advances in frontend frameworks to the integration of artificial intelligence, serverless architectures, and enhanced performance optimization techniques, the current web technology landscape represents a dynamic intersection of innovation, efficiency, and user-centric design. The paper also discusses the latest trends in web technologies in relation to the Georgian labor market.

Prospects of Using AI Technologies in Open Journal Systems (OJS)

2024-12-17T17:55:31+04:00

Open Journal Systems (OJS) is a widely used open-source platform for managing and publishing academic journals (Ndungu, 2020), (Hunter, 2010), (Tabatadze B. , 2024). Its modular design and open framework provide opportunities for integrating artificial intelligence (AI) technologies, which hold transformative potential for academic publishing. AI can enhance OJS by automating editorial workflows, improving user experience, and fostering global accessibility. Key areas for AI integration include automated peer review, where natural language processing (NLP) can identify relevant reviewers, detect plagiarism, and ensure structural compliance. AI-powered recommendation systems can personalize content delivery, offering tailored article suggestions based on user preferences and behaviors. Additionally, linguistic diversity can be bolstered through real-time translation tools and speech-to-text features, facilitating broader engagement with a global audience. AI also enables automation in editorial processes such as grammar checks, citation management, and abstract generation. Advanced analytics powered by AI can provide actionable insights into readership trends, engagement metrics, and impact factor predictions, supporting strategic decision-making for journal administrators. Despite its potential, AI integration poses challenges, including technical expertise requirements, financial constraints, and ethical concerns such as data privacy and bias. Overcoming these barriers will require careful planning and community collaboration. The future of AI in OJS looks promising, with opportunities to incorporate blockchain, adaptive learning systems, and AI-driven collaboration tools. By addressing these challenges, OJS can lead the evolution of open-access publishing, enhancing efficiency, accessibility, and inclusivity in scholarly communication.