Search results for: MACHINE TOOLS
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The conception of energetic investigations of the multisymptom fatigue of the simple mechanical systems' constructional materials
PublicationThe article presents the basic assumptions of the research project aimed, as the main scientific purpose, an identification of the slow-changeable energy processes surrounding the high-cycle fatigue of constructional materials within the plain mechanical system, especially the marine one, for diagnostic purposes. There is foreseen an application of alternative diagnostic methods based on energetic observations of the multi-symptom,...
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EMPIRICAL ASSESMENT OF THE MAIN DRIVING SYSTEM OF THE CIRCULAR SAWING MACHINE
PublicationThe producers of panel saws tend to improve sawing accuracy and minimise a level of vibrations, to increase their competitiveness at the market. Mechanical vibrations in the main saw driving system, which level depend on a plethora independent factors, may really affect sawing accuracy and general machine tool vibrations. The objective of the research was to explore vibrations signals of the main spindle system, and to extract...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublicationThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Broken rotor bar impact on sensorless control of induction machine
PublicationThe aim of the research is analysis of the sensorless control system of induction machine with broken rotor for diagnostic purposes. Increasing popularity of sensorless controlled variable speed drives requires research in area of reliability, range of stable operation, fault symptoms and application of diagnosis methods. T transformation (Cunha et al.,2003) used for conversion of instantaneous rotor currents electrical circuit...
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Video of LEGO Bricks on Conveyor Belt Dataset Series
PublicationThe dataset series titled Video of LEGO bricks on conveyor belt is composed of 14 datasets containing video recordings of a moving white conveyor belt. The recordings were created using a smartphone camera in Full HD resolution. The dataset allows for the preparation of data for neural network training, and building of a LEGO sorting machine that can help builders to organise their collections.
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Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
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Noninvasive method for rotor fault diagnosis in inverter fed induction motor drive
PublicationThis article presents a proposal, simulation and experimental results of a noninvasive rotor fault diagnosis method for the inverter fed induction motor drive. Comparing to reported methods the proposed one does not require any load, rotor brake, slip, mechanical or electrical system physical modification e.g. machine disassembly and can be applied regardless the rotor speed measurement or estimation method.
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The methodology of design of axial clearances compensation unit in hydraulic satellite displacement machine and their experimental verification
PublicationA new methodology of calculating the dimensions of the axial clearance compensation unit in the hydraulic satellite displacement machine is described in this paper. The methods of shaping the compensation unit were also proposed and described. These methods were used to calculate the geometrical dimensions of the compensation field in an innovative prototype of a satellite hydraulic motor. This motor is characterized by the fact...
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Sensorless Fault Detection of Induction Motor with Inverter Output Filter
PublicationThe paper presents the problem of monitoring and fault detection of a sensorless voltage inverter fed squirrel cage induction motor with LC filter. The detection is based on load torque estimation of the investigated torque transmission system. The load torque is calculated besides the computation of other variables that are mandatory for sensorless drive operation such as rotor flux and speed. The implemented LC filter smooths...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Robustness of the Rotor-router Mechanism
PublicationW pracy rozważano model eksploracji grafu nieskierowanego przez pojedynczego agenta, w którym sterowanie agentem odbywa się zgodnie z zasadą ''rotor-router'' (inaczej: ''Propp machine''). Przeanalizowano czas stabilizacji agenta do trajektorii w postaci cyklu Eulera w przypadku wystąpienia zaburzeń w grafie: usunięcie krawędzi, dodanie krawędzi, lokalna zamiana portów
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The application of a photopolymer material for the manufacture of machine elements using rapid prototyping techniques
PublicationThe paper discusses the application of polymer resin for 3D printing. The first section focuses on rapid prototyping technique and properties of the photopolymer, used as input material in the manufacture of machine components. Second part of the article was devoted to exemplary 3-D-printed elements for incorporation in machines. The article also contains detailed description of problems encountered in implementation of the selected...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
PublicationDeep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was...
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Time travel without paradoxes: Ring resonator as a universal paradigm for looped quantum evolutions
PublicationA ring resonator involves a scattering process where a part of the output is fed again into the input. The same formal structure is encountered in the problem of time travel in a neighborhood of a closed timelike curve (CTC). We know how to describe quantum optics of ring resonators, and the resulting description agrees with experiment. We can apply the same formal strategy to any looped quantum evolution, in particular to the...
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A novel dual-band rectifier circuit with enhanced bandwidth for RF energy harvesting applications
PublicationIn recent years, a rapid development of low-power sensor networks, enabling machine-to-machine communication in applications such as environmental monitoring, has been observed. Contemporary sensors are normally supplied by an external power source, typically in a form of a battery, which limits their lifespan and increases the maintenance costs. This problem can be addressed by harvesting and converting ambient RF energy into...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublicationSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Are Pair Trading Strategies Profitable During COVID-19 Period?
PublicationPair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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No-Wait & No-Idle Open Shop Minimum Makespan Scheduling with Bioperational Jobs
PublicationIn the open shop scheduling with bioperational jobs each job consists of two unit operations with a delay between the end of the first operation and the beginning of the second one. No-wait requirement enforces that the delay between operations is equal to 0. No-idle means that there is no idle time on any machine. We model this problem by the interval incidentor (1, 1)-coloring (IIR(1, 1)-coloring) of a graph with the minimum...
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Modelling of cutting by means of fracture mechanics
PublicationThe suitability of modern fracture mechanic theory was proved for the estimation of the cutting force and the cutting specific resistance. This paper shows modification of Ernst-Merchant theory and its application for determination some other properties of wood sample. This theory is acceptable for evaluation of shear yield stresses and shear plane angle. Sawing by gang saw machine was used as a process similar to the orthogonal...
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MODELLING OF CUTTING BY MEANS OF FRACTURE MECHANICS
PublicationThe suitability of modern fracture mechanic theory was proved for the estimation of the cutting force and the cutting specific resistance. This paper shows modification of Ernst-Merchant theory and its application for determination some other properties of wood sample. This theory is acceptable for evaluation of shear yield stresses and shear plane angle. Sawing by gang saw machine was used as a process similar to the orthogonal...
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Dangerous sound event recognition using Support Vector Machine classifiers
PublicationA method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification....
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Mechanical Properties of Human Stomach Tissue
PublicationThe dataset entitled Determination of mechanical properties of human stomach tissues subjected to uniaxial stretching contains: the length of the sample as a function of the corresponding load (tensile force) and the initial values of the average width and average thickness of the sample. All tests were conducted in a self-developed tensile test machine: PG TissueTester. The dataset allows the coefficients of various models of...
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Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublicationThis paper presents a new approach for variability analysis of microwave devices with a high dimension of uncertain parameters. The proposed technique is based on modeling an approximation of system by its poles and residues using several modeling methods, including ordinary kriging, Adaptive Polynomial Chaos (APCE), and Support Vector Machine Regression (SVM). The computational cost is compared with the traditional Monte-Carlo...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublicationThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Scheduling with Complete Multipartite Incompatibility Graph on Parallel Machines
PublicationIn this paper we consider a problem of job scheduling on parallel machines with a presence of incompatibilities between jobs. The incompatibility relation can be modeled as a complete multipartite graph in which each edge denotes a pair of jobs that cannot be scheduled on the same machine. Our research stems from the works of Bodlaender, Jansen, and Woeginger (1994) and Bodlaender and Jansen (1993). In particular, we pursue the...
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Modelling of steady state and transient performance of the synchronous generator considering harmonic distortions caused by non-uniform saturation of the pole shoe
PublicationIn this paper a synchronous generator model is described. This model is developed on the assumption that in loaded and no load conditions the saturation effect affects the pole shoe in a different way. The developed model is based on the multiple saliency model and is formulated using winding function approach in machine variables. The influence of the non-uniform saturation of the pole shoe in load conditions on the performance...
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Uncertainty analysis of measuring system for instantaneous power research
PublicationThe paper presents a metrological analysis of the measurement system used for diagnosis of induction motor bearings, based on the analysis of the instantaneous power. This system was implemented as a set of devices with dedicated software installed on a PC. A number of measurements for uncertainty estimation was carried out. The results of the measurements are presented in the paper. The results of the aforementioned analysis helped...
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Introduction to the ONDM 2022 special issue
PublicationThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
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Euler tour lock-in problem in the rotor-router model
PublicationW pracy rozważano model eksploracji grafu nieskierowanego przez pojedynczego agenta, w którym sterowanie agentem odbywa się zgodnie z zasadą ''rotor-router'' (inaczej: ''Propp machine''). Porównano czas stabilizacji agenta do trajektorii w postaci cyklu Eulera dla różnych klas grafów, prowadząc rozważania w kontekście teorii gier. Przydział początkowych portów i wskaźników w modelu jest traktowany jako rozgrywka pomiędzy graczem...
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Towards hardware built-in support for computer system safety
PublicationArtykuł omawia dostępne technologie wirtualizacji zasobów pamięci i systemów I/O w systemach komputerowych takie jak Execute Disable Bit (EDB) capability i Virtual Machine Architecture (VMA). Nastepnie wprowadza założenia na rozszerzenie tych technologii w celu uzyskania funkcjonalności Safe Call Execution dzieki technologii Execution Disabling Policies (EDP). Wprowadzono również założenia na funkcjonalność Memory Virtualization...
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Design. Metodology outline and practice
PublicationNa tle - uznawanego za typowy - schematu prac składających się na proces projektowania, pokazano przykładowe tworzenie inicjatywy sprawczej oraz rozwój koncepcji dotyczących sformułowania konkretnego zadania projektowego w dziedzinie budowy maszyn.Temat dotyczył obszaru projektowania turbin wodnych.The origin of project initiative, as well as concept development related to formulating a specific design goal, are presented in the...
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Knowledge representation of motor activity of patients with Parkinson’s disease
PublicationAn approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...
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Installation of CMC columns in overconsolidated clays
PublicationDuring rigid inclusions execution in the subsoil some monitoring data are registered by a drilling rig for quality control. The use of these data can improve the design procedure of soil improvement as they can provide some information about the position of bearing strata and the energy necessary to install the column in the ground. In this paper the parameters registered in a drilling machine are described, the installation...
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MACHINE VISION DETECTION OF THE CIRCULAR SAW VIBRATIONS
PublicationDynamical properties of rotating circular saw blades are crucial for both production quality and personnel safety. This paper presents a novel method for monitoring circular saw vibrations and deviations. A machine vision system uses a camera and a laser line projected on the saw’s surface to estimate vibration range. Changes of the dynamic behaviour of the saw were measured as a function of the rotational speed. The critical rotational...
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Acceleration of decision making in sound event recognition employing supercomputing cluster
PublicationParallel processing of audio data streams is introduced to shorten the decision making time in hazardous sound event recognition. A supercomputing cluster environment with a framework dedicated to processing multimedia data streams in real time is used. The sound event recognition algorithms employed are based on detecting foreground events, calculating their features in short time frames, and classifying the events with Support...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Non-conventional approach in single-sided lapping process: kinematic analysis and parameters optimization
PublicationThe lapping process is strongly affected by a number of input parameters. One of the fundamental mechanical processes in lapping is the abrasive effect of particles. In order to examine the influence of the kinematic parameters on the lapping uniformity of unconventional single-sided machine, numerical simulations of particles sliding trajectories are performed. Changing the kinematic parameters, e.g., rotational velocities or...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Buzz-based honeybee colony fingerprint
PublicationNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Mechanical and structural investigations of wings of selected insect species
PublicationThis paper presents research and measurements leading to obtaining the Young’s modulus of wing bearing structures of selected insect species. A small testing machine intended for three-point bending and equipped with instruments registering low forces was constructed for the needs of the experiment. The machine was used to perform numerous bending tests of wings of three species of insects (obtained from a breeding farm): Attacus...