Emerging infectious diseases are major threats to amphibian biodiversity. Ranaviruses (Family Iridoviridae) are a group of globally emerging infections that infect poikilothermic vertebrates. In the United Kingdom, the emergence of this group of viru...
This study provides simulation and experimental results on techniques for avoiding static and dynamic obstacles using a deep Q-learning (DQL) reinforcement learning algorithm for a two-wheel mobile robot with independent control. This method integrat...
Object retrieval systems measure the degree of similarity of the shape of 3D models. They search for the elements of the 3D model databases that resemble the query model. In structural bioinformatics, the query model is a protein tertiary/quaternary...
With the global rise in consumer electronics, electric vehicles, and renewable energy, the demand for lithium-ion batteries (LIBs) is expected to grow. LIBs present a significant challenge for state estimations due to their complex non-linear electro...
Advancements in large language models have significantly transformed higher education by integrating AI chatbots into course design, teaching, administration, and student support. This study evaluates the use, effectiveness, and perceptions of chatbo...
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Persistent organic pollutants (POPs) cause a significant public and environmental health concern due to their toxicity, long-range transportability, persistence, and bioaccumulation. The US Food and Drug Administration (FDA) has a program to monitor...
Crystal habit in igneous rocks provides a window to understand magmatic processes or reveal crystallization environments. Generally, we can obtain the two-dimensional (2D) crystal habits directly from the thin section, which is easy to access. Howeve...
Computer programmers require various instructive information during coding and development. Such information is dispersed in different sources like language documentation, wikis, and forums. As an information exchange platform, programmers broadly ut...
With archaic coding techniques, there will be a time when it will be necessary to modernize vulnerable software. However, redeveloping out-of-date code can be a time-consuming task when dealing with a multitude of files. To reduce the amount of reass...
The goal of the research was to study the possibility of using the planned language Esperanto for text compression, and to compare the results of the text compression in Esperanto with the compression in natural languages, represented by Polish and E...
The spread of infectious diseases, such as COVID-19, presents a significant problem for public health and healthcare systems. Digital technology plays an important role in achieving access to healthcare by enhancing device connectivity and informatio...
Portfolio optimization is fundamental to modern finance, enabling investors to construct allocations that balance risk and return while satisfying practical constraints. When transaction costs and cardinality limits are incorporated, the problem beco...
Our paper compares the correctness, efficiency, and maintainability of human-generated and AI-generated program code. For that, we analyzed the computational resources of AI- and human-generated program code using metrics such as time and space compl...
This paper deals not only with pointwise and uniform convergence but also Y-valued fractional approximation results by univariate symmetrized neural network (SNN) operators on Banach space
The article describes the autonomous open data prediction framework, which is in its infancy and is designed to automate predictions with a variety of data sources that are mostly external. The framework has been implemented with the Kalman filter ap...
We present here Nested_fit, a Bayesian data analysis code developed for investigations of atomic spectra and other physical data. It is based on the nested sampling algorithm with the implementation of an upgraded lawn mower robot method for finding...
This paper presents the alternative training strategies we tested for an Artificial Neural Network (ANN) designed to detect JWH synthetic cannabinoids. In order to increase the model performance in terms of output sensitivity, we used the Neural Desi...
There is a growing need for remote identification of crop types, which is a serious issue for policymakers and statistical accountants (i.e., agricultural inspectors and government agencies), for verifying the degree of validity of the information co...
Single- and small-batch production requires flexible production control to maximise machine reliability and minimise delivery delays. Existing planning approaches often do not take into account the dynamic production conditions of these environments,...
The quality of machine learning models can suffer when inappropriate data is used, which is especially prevalent in high-dimensional and imbalanced data sets. Data preparation and preprocessing can mitigate some problems and can thus result in better...
This study conducts a comprehensive comparative analysis of six contemporary artificial intelligence models for Python code generation using the HumanEval benchmark. The evaluated models include GPT-3.5 Turbo, GPT-4 Omni, Claude 3.5 Sonnet, Claude 3....
Effective use of energy storage systems (ESS) is important to reduce unnecessary power consumption. In this paper, a day-ahead two-stage ESS-scheduling model based on the use of a machine learning technique for load prediction has been proposed for m...
This paper investigates the characterization of an electric double-layer capacitor (EDLC). In this study, the 300 F and 400 F EDLC supercapacitors are connected in a circuit in a laboratory experiment to produce their charge/discharge profiles at a c...
We present an automatic approach for generating learning problems for teaching introductory programming in different programming languages. The current implementation allows input and output in the three most popular programming languages for teachin...
In programming education, it is common for students to submit solutions to algorithmic problems that implement the same functionality but are not labeled, making it difficult to identify which codes employ similar strategies. Students approach proble...
Three-dimensional block models are the most widely used tool for the study and evaluation of ore deposits, the calculation and design of economical pits, mine production planning, and physical and numerical simulations of ore deposits. The way these...
The coordination of multiple unmanned aerial vehicles traditionally relies on pre-defined control strategies and complex programming implementations, making adaptation to dynamic environments and tasks challenging. The purpose of this study is to exp...
This paper deals with the application focused on motion control for a cooperating YuMi robot. The use of sensors on gloves or other controls to control robots may restrict both operation of the robot and the operator’s activities. Therefore, research...
This article describes the development and implementation of a water resource management system utilizing open technologies such as the ESP32 microcontroller and MicroPython. This system stands out for its low cost, high efficiency and adaptability t...
Nowadays, communication and web services are part of our lives, including education, and e-learning applications are used more and more. However, teaching in engineering sciences requires an important amount of practical experiments. Hence, remote la...
Can we turn AI black boxes into code? Although this mission sounds extremely challenging, we show that it is not entirely impossible by presenting a proof-of-concept method, MIPS, that can synthesize programs based on the automated mechanistic interp...
In this paper, a theoretical estimation model of TBM thrust, torque, and power in the rock–soil interface (RSI) of mixed ground is developed, including a new force model for the drag cutter that accounts for chamber pressure and soil friction....
This study harnesses EEG signals to enable the real-time control of servo motors, utilizing the OpenBCI Community Dataset to identify and assess brainwave patterns related to motor imagery tasks. Specifically, the dataset includes EEG data from 52 su...
Interaction between medical image platform and external environment is a desirable feature in several clinical, research, and educational scenarios. In this work, the integration between 3D Slicer package and Arduino board is introduced, enabling a s...
Hydrologists use a number of tools to compare model results to observed flows. These include tools to pre-process the data, data frames to store and access data, visualization and plotting routines, error metrics for single realizations, and ensemble...
Studying parallel and convergent amino acid replacements in protein evolution is frequently used to assess adaptive evolution at the molecular level. Identifying parallel and convergent replacements involves multiple steps and computational routines,...
This work presents the design and implementation of an automated, digital, and modular system to address a real-world industrial challenge: the automation and optimization of production schedules for Computer Numerical Control (CNC) machines in a fac...
This paper presents the design, development, and evaluation of an embedded hardware and digital signal processing (DSP)-based real-time gesture-controlled system. The system architecture utilizes an MPU6050 inertial measurement unit (IMU), Arduino Un...
Automated code translation plays an important role in improving software reusability and supporting system migration, particularly in scenarios where Python implementations need to be converted into efficient C++ programs. However, existing approache...
Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data...
The quality assurance of publication data in collaborative knowledge bases and in current research information systems (CRIS) becomes more and more relevant by the use of freely available spatial information in different application scenarios. When i...
Unmanned Aerial Vehicles (UAVs) are part of our daily lives with a number of applications in diverse fields. On many occasions, developing these applications can be an arduous or even impossible task for users with a limited knowledge of aerial robot...
This work presents a mathematical model of a fast-acting single-layer artificial neural network applied to the task of image reconstruction after noise. For research purposes, this algorithm was implemented in the Python and C++ programming languages...
This article presents a comparison of the results obtained using the newly proposed Simple Weighted Sum Product method and some prominent multiple criteria decision-making methods. For comparison, several analyses were performed using the Python prog...
This study investigates a complex system that describes a non-trivial epidemiological model with integrated internal conflict (interregional migration) on the example of cyclic migration using the software. JetBrains PyCharm Community Edition 2020.3....
This paper explores the idea of a quantum exchange protocol between two entities, validated by (at least) a third one. Two entities, part of a greater system, decide they want to trade quantum goods: their exchange is configurable, and allows them to...
An algorithm that presents the best possible approximation for the theoretical Bézier curve and the real path on which a mobile robot moves in a dynamic environment with mobile obstacles and boundaries is introduced in this paper. The algorith...
Programming has gained significant importance worldwide as societies increasingly rely on computer application systems. To support novices in learning various programming languages, we have developed the Programming Learning Assistant System (PLAS)....
In this paper, we formulate and solve a novel real-life large-scale automotive parts paint shop scheduling problem, which contains color arrangement restrictions, part arrangement restrictions, bracket restrictions, and multi-objectives. Based on the...
The Delphi method is one of the basic tools for forecasting values in various types of issues. It uses the knowledge of experts, which is properly aggregated (e.g., in the form of descriptive statistics measures) and returns to the previous group of...
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