Articles in "Computer Science"

Back to Categories

A NUMERICAL ANALYSIS OF A QUEUING-INVENTORY SYSTEM WITH CATASTROPHES

Publication date: 2024-12-20 08:23:00
Authors: LAMAN POLADOVA; GULNARA VALIJANOVA
Category: Computer Science
Summary: A mathematical model of a queuing-inventory system (QIS) with catastrophes is built. Incoming customers form a Poisson flow with rate λ. The customer servicing time in the considered QIS is zero. The (S,Q) replenishment policy is used to increase the inventory level in the system. Here, S is the maximum storage size of the QIS, and Q=S-s indicates the fixed size of the proposed order.
Author keywords: queuing-inventory system; catastrophes; Markov chain; calculation

PNEUMONIA DETECTION THROUGH CNN AND RESNET-50

Publication date: 2024-12-20 08:21:00
Authors: FILZA JAVED
Category: Computer Science
Summary: Pneumonia is a prevalent illness that has a global impact, primarily affecting children and older individuals. Timely identification is essential for immediate intervention, particularly in regions with restricted healthcare availability. The purpose of this paper is to compare how well two methods work for finding pneumonia on chest X-rays creating a custom Convolutional Neural Network (CNN) and using a model that has been pre-trained, such as ResNet-50. The results indicated that although the customized CNN had difficulties achieving satisfactory performance, the ResNet-50 model demonstrated encouraging outcomes following the process of fine-tuning. This paper seeks to improve the detection of pneumonia, especially in disadvantaged places with limited medical resources, by utilizing modern technologies such as deep learning and pre-trained models. Considering the results gained to enhance patient outcomes and decrease mortality rates associated with pneumonia by enabling more precise and prompt detection, this has a beneficial effect on global public health
Author keywords: Pneumonia; Convolutional Neural Network (CNN); ResNet-50; chest X-rays; deep learning.

IMPLICATIONS OF ARTIFICIAL INTELLIGENCE DRIVEN DRONE SYSTEMS FOR RECOGNITION OF ENVIRONMENTAL HAZARDS

Publication date: 2024-12-20 08:18:00
Authors: FAIG SAFIYEV
Category: Computer Science
Summary: Artificial intelligence driven drone systems offer promising solutions for early detection and response to environmental hazards like wildfires and oil leaks. However, their widespread adoption raises significant ethical and environmental implications, including privacy infringements, algorithmic bias, data security, noise pollution, and greenhouse gas emissions. This study addresses these issues through literature reviews, surveys of affected populations, and prototype testing of AI models for disaster identification, in order to mitigate ethical issues. A specific metric was developed to rate drone components and identify the most sustainable options, minimizing the environmental impact. By promoting these solutions, this research aims to ensure the sustainable and responsible integration of artificial intelligence systems in environmental monitoring, protecting ecosystems and communities effectively.
Author keywords: environmental impact; machine learning; artificial intelligence; ethical concerns; remote sense technology; drone systems; noise pollution

EVALUATING THE EFFECTIVENESS OF MICROSOFT INTUNE IN SECURING DEVICES: BALANCING SECURITY FEATURES AND USER EXPERIENCE IN ENTERPRISE ENVIRONMENTS

Publication date: 2024-12-20 07:41:00
Authors: SAMUR AHMADOV
Category: Computer Science
Summary: Nearly every organization would like to adapt their environment to the cloud to increase productivity and decrease operational costs. By moving to the cloud, organizations are still struggling with enterprise mobile management systems. Managing devices can be challenging because of the complexity of the Microsoft ecosystem. However, Microsoft Intune is a service which was created to solve issues with managing devices and increase device security. This product can help to reduce potential security incidents within the organization and even during collaboration with other organizations. The research employs a methodical approach where organizations utilize Microsoft Intune with its full capabilities and all available security configurations. This paper will examine Microsoft Intune's effectiveness in the matter of device management and security with different aspects.
Author keywords: Microsoft Intune; Mobile device management; Cloud security; Enterprise mobility and security

Data Management as a Critical Component of Protecting Corporate Devices

Publication date: 2024-08-10 06:38:00
Authors: Melikov Agassi; Gasimov Vagif; Ahmadov Samur
Category: Computer Science
Summary: The relevance of the problem under study lies in the growing threat of cyberattacks and unauthorized access to corporate data. The need for effective data management at the moment is due to the increased importance of securing corporate devices, which requires in-depth analysis and understanding of the role of data management in this context. The aim of the study is to comprehensively analyze the role of information governance in securing organizational technology. The used methods were: experiment, systematization, comparison, analysis, synthesis. The main findings of the study emphasize the importance of information management in securing enterprise technology. The study involves the development of a C++ program designed to simulate different scenarios of using data management strategies. This program is designed to demonstrate the effectiveness of different information security techniques in organizational technologies. In addition, a comparative analysis of data control techniques designed to protect organizational devices has been carried out. The results of this analysis are presented in the form of a table that discusses the various aspects of information management in this context. And the developed structural diagram of information management in organizations presents the main components and processes required to secure organizational technology. The paper also provides examples of practical applications of data control techniques in large corporations, emphasizing their importance in protecting sensitive information. This research makes a practical contribution by providing organizations not only with theoretical foundations but also with concrete data governance strategies to enhance the security of corporate devices, which is essential for today’s companies in the face of growing cyber threats. Limitations of the study include biases, simulated situations, and an inability to adequately address issues that arise in the actual world, such as organizational culture and cyber threats.
Author keywords: Information Control, Cybersecurity of Technology Assets, Information Governance, Commercial Equipment Security, Information Security Integration

Queueing-inventory: analytical and simulation modeling and classical and retrial queues and inventory

Publication date: 2024-07-11 06:52:00
Authors: Achyutha Krishnamoorthy; Srinivas R. Chakravarthy; Agassi Melikov; Viswanath C. Narayanan
Category: Computer Science
Summary: This is the PREFACE to the Special Issue “Queueing-inventory: analytical and simulation modeling and classical and retrial queues and inventory”. The year 2022 was the 30th anniversary of Queueing-inventory. It was in that connection that the guest editors requested Professor Endre Boros, the Editor-in-Chief of Annals of Operations Research, for permission to guest edit a special issue. This was granted by the Editorial Board of the journal.
Author keywords: Queueing-inventory, Classical queue, Retrial queue, Classical inventory, Retrial inventory, Analytical and simulation modeling

Queuing-Inventory System with Catastrophes in the Warehouse: Case of Rare Catastrophes

Publication date: 2024-03-19 06:56:00
Authors: Melikov Agassi; Poladova Laman; Sztrik Janos
Category: Computer Science
Summary: A model of a single-server queuing-inventory system (QIS) with a limited waiting buffer for consumer customers (c-customers) and catastrophes has been developed. When a catastrophe occurs, all items in the system’s warehouse are destroyed, but c-customers in the system are still waiting for replenishment. In addition to c-customers, negative customers (n-customers) are also taken into account, each of which displaces one c-customer (if any). The policy (s, S) is used to replenish stocks. If, when a customer enters, the system warehouse is empty, then, according to Bernoulli’s trials, this customer either leaves the system without goods or joins the buffer. The mathematical model of the investigated QIS is constructed in the form of a continuous-time Markov chain (CTMC). Both exact and approximate methods for calculating the steady-state probabilities of constructed CTMCs are proposed and closed-form expressions are obtained for calculating the performance measures. Numerical evaluations are presented, demonstrating the high accuracy of the developed approximate formulas, as well as the behavior of performance measures depending on the input parameters. In addition, an optimization problem is solved to obtain the optimal value of the reorder point to minimize the expected total cost.
Author keywords: queuing-inventory system; catastrophes; finite waiting room; steady-state probabilities; space merging method; calculation algorithm