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Wyniki wyszukiwania dla: NATURAL PIGMENTS
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Modelling of a medium-term dynamics in a shallow tidal sea, based on combined physical and neural network methods
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Biotrickling filtration of n-butanol vapors: process monitoring using electronic nose and artificial neural network
PublikacjaBiotrickling filtration is one of the techniques used to reduce odorants in the air. It is based on the aerobic degradation of pollutants by microorganisms located in the filter bed. The research presents the possibility of using the electronic nose prototype combined with artificial neural network for biofiltration process monitoring in terms of reduction in n-butanol concentration and odour intensity of treated air. The study...
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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<title>Recurrent neural network application to image filtering: 2-D Kalman filtering approach</title>
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QEEG-based neural correlates of decision making in a well-trained eight-year-old chess player
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Marzenie o szczęściu, czyli idea prawa natury w filozofi i Jana Jakuba Rousseau
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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Age-dependent sympathetic neural responses to ß1 selective beta-blockade in untreated hypertension-related tachycardia
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublikacjaIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublikacjaIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Safety assessment of ships in critical conditions using a knowledge-based system for design and neural network system
PublikacjaW pracy opisano wybrane elementy metody oceny bezpieczeństwa statków w stanie uszkodzonym, ukierunkowanej na ocenę osiągów statku i ocenę ryzyka. Metoda analizy osiągów i zachowania się statku w stanie uszkodzonym została wykorzystana do oceny charakterystyk hydromechanicznych statku uszkodzonego. Do oceny ryzyka wykorzystano elementy metodyki Formalnej Oceny Bezpieczeństwa. System ekspertowy został wykorzystany do analziy podziału...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublikacjaAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublikacjaThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublikacjaThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Extreme weather layer method for implementation of nature-based solutions for climate adaptation: Case study Słupsk
PublikacjaOne of the most severe climate risks that is expected to affect all regions is related to stormwater. Climate models, constructed based on long-term trends, show that extreme weather events such as storms, cloudbursts and a large rise in sea level will be significant in the coming decades. Moreover, even the frequency and intensity of “normal” rainfall events, such as microbursts, are expected to be remarkably higher than today...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Fiber optic interface channels for united data and power supply transmission for neutral interaction application in signal transmission networks
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Feasibility study of inductor coupling in three-level neutral-point-clamped quasi-Z-source DC/AC converter
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The optimization of enzyme immobilization at Au-Ti nanotextured platform and its impact onto the response towards glucose in neutral media
PublikacjaThe market of non-invasive glucose sensors is drastically growing due to increasing number of people suffering from diabetes. Therefore, there is a significant need for any improvement in the field of biosensors that can be used for monitoring glucose level in human body. In recent years the emphasis is put onto the modification of electrode material with enzymes possessing recognition centre specific towards particular molecules....
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Sporadic amyotrophic lateral sclerosis: is SMN-Gemins protein complex of importance for the relative resistance of oculomotor nucleus motoneurons to degeneration?
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Geometrically nonlinear FEM analysis of FGM shells based on neutral physical surface approach in 6-parameter shell theory
PublikacjaThe paper presents the formulation of the elastic constitutive law for functionally graded materials (FGM) on the grounds of nonlinear 6-parameter shell theory with the 6th parameter being the drilling degree of freedom. The material law is derived by through-the-thickness integration of the Cosserat plane stress equations. The constitutive equations are formulated with respect to the neutral physical surface. The influence of...
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Identification of novel halogenated naturally occurring compounds in marine biota by high-resolution mass spectrometry and combined screening approaches
PublikacjaMarine animals, plants or bacteria are a source of bioactive naturally-occurring halogenated compounds (NHCs) such as bromophenols (BPs), bromoanisoles (BAs) and hydroxylated or methoxylated analogues of polybrominated diphenyl ethers (HO-PBDEs, MeO-PBDEs) and bromobiphenyls (HO-BBs, MeO-BBs). This study applied a comprehensive screening approach using liquid chromatography high-resolution mass spectrometry and combining target,...
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Biophilic Design: A Trend Watch
PublikacjaDuring the 20th century, many people migrated to cities for employment and economic opportunities, abandoning farming and natural landscapes so their direct connection to the countryside and nature was lost. This process continues to this day with unprecedented urban growth, in fact, it’s estimated 68% of the world population will live in urban areas by 2050. Due to the evolutionary disposition of humans, when people live in an...
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Ontology-Aided Software Engineering
PublikacjaThis thesis is located between the fields of research on Artificial Intelligence (AI), Knowledge Representation and Reasoning (KRR), Computer-Aided Software Engineering (CASE) and Model Driven Engineering (MDE). The modern offspring of KRR - Description Logic (DL) [Baad03] is considered here as a formalization of the software engineering Methods & Tools. The bridge between the world of formal specification (governed by the mathematics)...
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Ultrasound-Assisted Dispersive Liquid-Liquid Microextraction Using Deep Eutectic Solvents (DESs) for Neutral Red Dye Spectrophotometric Determination
PublikacjaDeep eutectic solvents (DES), which have low toxicity and are low cost, biodegradable, and easily synthesized, were used for the extraction of neutral red (NR) dye before its spectrophotometric analysis. DES, containing choline chloride as a hydrogen bond acceptor and phenol as a hydrogen bond donor with a molar ratio of 1:2, was used for the extraction of NR dye from aqueous media. The possible interaction of different DESs with...
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Soft X-ray Induced Production of Neutral Fragments in High-Rydberg States at the O 1s Ionization Threshold of the Water Molecule
PublikacjaDissociation of water molecules after soft X-ray absorption can yield neutral fragments in high-Rydberg (HR) states. We have studied the production of such fragments by field ionization and ion time-of-flight (TOF) spectrometry. Neutral HR fragments are created at all resonances below the O 1s ionization potential (IP) and particularly within 1 eV above the O 1s IP. The latter effect is due to the recapture of the O 1s photoelectrons...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublikacjaSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Performance analysis of an rfid-based 3d indoor positioning system combining scene analysis and neural network methods
PublikacjaThe main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and...
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublikacjaLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublikacjaThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Management of Urban Waters with Nature-Based Solutions in Circular Cities—Exemplified through Seven Urban Circularity Challenges
PublikacjaNature-Based Solutions (NBS) have been proven to effectively mitigate and solve resource depletion and climate-related challenges in urban areas. The COST (Cooperation in Science and Technology) Action CA17133 entitled “Implementing nature-based solutions (NBS) for building a resourceful circular city” has established seven urban circularity challenges (UCC) that can be addressed effectively with NBS. This paper presents the outcomes...
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Changes on the Surface of the SiO2/C Composite, Leading to the Formation of Conductive Carbon Structures with Complex Nature of DC Conductivity
PublikacjaSol–gel layers have been the subject of many studies in recent decades. However, very little information exists about layers in which carbon structures are developed in situ. Using the spin-coating method, we obtained thin iron-doped SiO2/C composite films. The results of Raman spectroscopy showed that our samples consisted of graphitic forms and polymers. The latter’s contribution decreases with rising temperature. FTIR and EDS...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublikacjaDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using rotor trajectory.
PublikacjaW pracy dokonano analizy zastosowania sieci neuronowych do wyznaczenia wartości wymuszeń wpływających na wielkość drgań wirnika używając trajektorii jako parametr określający drgania. Badania przeprowadzono na powietrznej, jednostopniowej turbinie modelowej. Przemieszczenia poziome i pionowe wirnika turbiny mierzono przy pomocy systemu pomiarowego i rejestrowano na oscyloskopie cyfrowym. Przeprowadzono pomiary trajektorii ruchu...
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Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublikacjaAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...