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Applied Computer Science
Scopus
ISSN 1895-3735 · Polish Association for Knowledge Promotion · 479 articles in the index
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Journal Article
A comprehensive review of metaheuristic algorithms for mobile robot path planning
Path planning and optimization are essential topics in robotics because they directly affect the effectiveness and safety of robot navigation. The application of metaheuristic methods and algorithms in the field of robot motion planning has attracted the attention of researchers in the field of…
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Journal Article
Development of non-destructive vibration method for classification of bone fracture severity
Accurate classification of bone fracture severity is critical in orthopedic evaluation. Radiation-based methods such as X-ray, CT, and MRI provide anatomical detail but lack the ability to classify fracture severity. This study presents a non-invasive, vibration-based approach to assessing fracture…
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Journal Article
A text-guided vision model for enhanced recognition of small instances
As drone-based object detection technology continues to evolve, the demand is shifting from simply detecting objects to enabling users to accurately identify specific targets. For example, users can enter specific targets as prompts to accurately detect the desired objects. To address this need, an…
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Journal Article
Smart Autolube: Optimized machine learning-based pressure prediction for AIoT lubrication systems
Autolube systems have been widely adopted in the mining industry to improve equipment reliability, but most still operate at fixed time intervals without adapting to real conditions in the field, and monitoring systems use LED lights, making it difficult to diagnose failures due to the minimal…
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Journal Article
Efficient multi-robot exploration of unknown environments using inverted ant colony optimization and reinforcement learning
Collaborative environmental exploration by a fleet of mobile robots is of growing interest, especially in the context of unknown environments. Exploration algorithms find diverse and critical applications, such as search and rescue, underwater surveillance, and space observation. However, despite…
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Journal Article
Application of artificial intelligence methods to determine the optimal process parameters in resistance projection welding of steel nuts
The study employed applied computer modelling to identify the optimal process parameters for resistance projection welding using the original procedure. The influence of technological parameters (welding power, welding time, electrode pressure) on the quality of 184 welded joints produced by…
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Journal Article
Reinforcement learning for solving optimization problems: Opportunities and limitations on the example of the assignment problem
The application of reinforcement learning techniques to optimization problems has gained increasing attention due to their adaptability, generalization potential, and capacity to handle complex decision-making processes. This study explores the opportunities and limitations of Q-learning, in the…
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Journal Article
Enhanced ELECTRE III method with interval-valued hesitant fuzzy linguistic sets for multi-criteria group decision-making in smart supply networks
This study presents a robust decision-making framework for evaluating strategic artificial intelligence (AI) initiatives within DHL's smart supply network. The objective is to prioritize four AI alternatives-autonomous warehouse routing, predictive delivery optimization, AI-driven demand…
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Journal Article
SCADA-Driven big data framework for fault prediction in spiral steel pipe manufacturing using fuzzy and neural network models
The increasing complexity of spiral steel pipe production necessitates the implementation of intelligent forecasting methods to predict potential failures. This, in turn, enables the development of reliable evaluation techniques aimed at minimizing unanticipated breakdowns and enhancing the…
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Journal Article
Addressing non-stationarity with stochastic trend in the context of limited time series data: An experimental survey in healthcare analytics
Stationarity is a fundamental assumption in time series modeling that underlies reliable statistical inference and forecasting. Time series data can be found in many domains, including industry, engineering, finance, economics, epidemiology, and health care analysis. This study addresses stochastic…
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Journal Article
A real-time adaptive traffic light control algorithm at urban intersections for smart cities
This paper investigates the challenges of intelligent traffic light control at urban intersections in the context of the Internet of Things. Increasing vehicle density and mobility have exacerbated traffic congestion and resulted in inefficient use of road infrastructure, particularly at…
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Journal Article
Development of dead-reckoning sensor system for indoor environments
This paper presents a method for constructing a dead-reckoning sensor system for indoor environments that enables autonomous control of a mobile robot. The proposed technique includes a method for achieving accurate autonomous control of robots. Using existing electronic equipment, we propose a…
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Journal Article
Quantifying pain: An AI-driven approach to detecting pain levels via facial expressions
Accurate pain assessment remains a cornerstone of effective clinical care as it significantly influences diagnosis, treatment planning, and evaluation of therapeutic outcomes. Traditional pain assessment tools such as the Visual Analog Scale (VAS), Numerical Rating Scale (NRS), and Verbal Rating…
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Journal Article
A scalable and cost-effective forest fire detection approach using deep transfer learning on a Raspberry Pi cluster
Due to the increasing frequency of forest fires and their rapid spread, early detection is critical for effective containment and mitigation. This paper proposes a cost-effective edge-based forest fire detection system that receives images from multiple sources (terrestrial cameras and UAVs) to…
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Journal Article
Models for calculating the integral quality indicator of the offset printing process for the IIOT-system
The paper is devoted to the problem of comprehensive quality assessment in offset printing. On the basis of the research conducted, the quality indicators of sheet-fed offset printing with dampening are determined, namely, the print color difference, the fine line width, the color combination…
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Journal Article
Measuring comparative eco-efficiency in the Eurasian Economic Union using MaxDEA X 12.2 software
In recent years, Data Envelopment Analysis (DEA) has gained popularity as a robust approach for assessing the eco-efficiency of economic units of different scales. This paper demonstrates the capabilities of the latest standalone version of the open-access MaxDEA X 12.2 software to measure…
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Journal Article
SSAtt-SolNet: An efficient model for dusty solar panel classification with Sparse Shuffle and Attention mechanisms
This study introduces SSAtt-SolNet, a novel deep learning approach designed to detect dusty solar panels, thereby improving the efficiency and reliability of solar photovoltaic systems. The proposed model uses MobileNetV3 as its backbone to balance accuracy and computational efficiency. We…
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Journal Article
Transforming ERP interfaces in production environments: An empirical evaluation using the User Experience Questionnaire
This study aims to evaluate the user experience (UX) of Enterprise Resource Planning (ERP) system modules in Polish enterprises' information and communication technology-based production environments. The research plan includes quantitative research as part of a doctoral thesis, which will be…
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Journal Article
Machine learning evidence towards eradication of malaria burden: A scoping review
Recent advancements have shown that shallow and deep learning models achieve impressive performance accuracies of over 97% and 98%, respectively, in providing precise evidence for malaria control and diagnosis. This effectiveness highlights the importance of these models in enhancing our…
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Journal Article
Kidney disease diagnosis based on artificial intelligence/deep learning techniques
Chronic Kidney Disease is a progressive medical ailment of growing global health importance because, in most cases, this ailment shows no symptoms during its early stages. Improving patients’ outcomes and early detection are significant aspects of managing diseases. In this paper, deep learning…