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Wyniki wyszukiwania dla: ARTIFICIAL NEURAL NETWORK, MODELLING,SHIP SPEED, ENGINE FUEL CONSUMPTION
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublikacjaThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublikacjaPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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A method for determination of fuel oil consumption saving by stepvise differetiating loads on ship diesel engines running in paralel.
Publikacjaprzedstawiono metodykę wyznaczania oszczędniości w zużyciu paliwa dla silników pracujących na wspólną sieć w wyniku różnicowania ich obciążeń oraz stosowania metody krokowych zmian obciążenia. znajomość charakterystyk zużycia paliwa poszczególnych silników oraz histogramu rozkładu obciążeńeksploatacyjnych pozwala po zastosowaniu proponowanej metody na wyznaczanie oszczędności w zuzyciu paliwa.
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublikacjaThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Digits Recognition with Quadrant Photodiode and Convolutional Neural Network
PublikacjaIn this paper we have investigated the capabilities of a quadrant photodiode based gesture sensor in the recognition of digits drawn in the air. The sensor consisting of 4 active elements, 4 LEDs and a pinhole was considered as input interface for both discrete and continuous gestures. Index finger and a round pointer were used as navigating mediums for the sensor. Experiments performed with 5 volunteers...
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Problems of modelling toxic compounds emitted by a marine internal combustion engine in unsteady states
PublikacjaContemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous...
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Impacts of Using Exhaust Gas Recirculation and Various Amount of Dimethyl Ether Premixed Ratios on Combustion and Emissions on a Dual-Fuel Compression Ignition Engine
PublikacjaIn the presented research, the authors dealt with the specific properties of the combustion process of dimethyl ether (DME) in a combustion car (Volkswagen Golf IV) engine AJM 1.9 TDI PDE made by Volkswagen factory. Dimethyl ether is an alternative fuel produced most often from natural gas, which can be used in compression ignition engines as a single fuel or co-burned with diesel oil. This work describes the impacts of using exhaust...
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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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Emission of CO2 and Fuel Consumption for Automotive Vehicles
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Influence of traffic conditions on the operating fuel consumption
PublikacjaPrzedstawiona w pracy metoda umożliwia ocenę warunków eksploatacji pojazdu. Warunki te mogą wynikać zarówno z lokalnej specyfiki ruchu pojazdów jak również ze sposobu prowadzenia auta przez kierowcę. W pracy zamieszczono przykłady oceny zarejestrowanych w normalnej eksploatacji warunków ruchu pojazdu i ich wpływu na przebiegowe zużycie paliwa.
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Modelling of some stealth features for a small navy ship at the concept design stage.
PublikacjaIn this paper the basic research problems associated with modelling the basic stealth features for a small navy ship at the concept design stage are introduced. Amongst the major stealth features considered are: the modification of the immersed ship hull form by a rapid change of the ship loading condition, and modification of the ship boundary layer by the hull skin cover. The other stealth features of the ship are not presented...
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublikacjaIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublikacjaThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Application of road map of operating condition for estimation of fuel and electric energy consumption from city transport
PublikacjaThe paper presents procedure of data collecting and generation of road map of operating condition in the selected urban area. This map allows forecasting the selected vehicle operating parameters for the assumed road. The main parameters calculated using the road maps of operating conditions are: total energy spent to drive the selected vehicle, consumed fuel, travel time, average speed of travel, CO2 emissions. Presented example...
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Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Artificial Neural Networks for Comparative Navigation
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Combined Close Range Photogrammetry and Terrestrial Laser Scanning for Ship Hull Modelling
PublikacjaThe paper addresses the fields of combined close-range photogrammetry and terrestrial laser scanning in the light of ship modelling. The authors pointed out precision and measurement accuracy due to their possible complex application for ship hulls inventories. Due to prescribed vitality of every ship structure, it is crucial to prepare documentation to support the vessel processes. The presented methods are directed, combined...
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublikacjaIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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EPILEPTIC BEHAVIOR WITH A DISTINGUISHED PREICTAL PERIOD IN A LARGE-SCALE NEURAL NETWORK MODEL
PublikacjaWe present a neural network model capable of reproducing focal epileptic behavior. An important property of our model is the distinguished preictal state. This novel feature may shed light on the pathologi-cal mechanisms of seizure generation and, in perspective, help develop new therapeutic strategies to manage refractory partial epilepsy.
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Investigations of the Working Process in a Dual-Fuel Low-Emission Combustion Chamber for an FPSO Gas Turbine Engine
PublikacjaThis investigation is devoted to an analysis of the working process in a dual-fuel low-emission combustion chamber for a floating vessel’s gas turbine. The low-emission gas turbine combustion chamber with partial pre-mixing of fuel and air inside the outer and inner radial-axial swirlers was chosen as the object of research. When modelling processes in a dual-flow low-emission gas turbine combustion chamber, a generalized method...
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Evolutionary sets of safe ship trajectories with speed reduction manoeuvres within traffic separation schemes
PublikacjaIn the previous paper the author presented the evolutionary ship trajectory planning method designed to support Traffic Separation Schemes (TSS). This time the extensions of this method are described which allow to combine evolutionary trajectory planning with speed reduction manoeuvres. On TSS regions with higher than usual density of traffic and smaller distances between ships, the course alterations alone are not always sufficient...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublikacjaRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublikacjaIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Wind-wave variability in a shallow tidal sea—Spectral modelling combined with neural network methods
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Assesment of operation of ship main diesel engine using the theory of semi-markovian and markov processes.
PublikacjaTo precisely determine the task it is necessary to specify also its duration time, apart from conditions in which it will be realized. When considering propulsion engine, i.e. the main element of ship propulsion system, especially important becomes not only the problem which amount of energy could be at one's disposal but also within which time interval it could be delivered. Therefore apart from applying the commonly used reliability...
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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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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublikacjaIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Deep convolutional neural network for predicting kidney tumour malignancy
PublikacjaPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Tyre rolling resistance and its influence on fuel consumption
PublikacjaRolling resistance of tyres is one of the major resistive forces acting on any wheeled vehicle. Unfortunately, it is also one of the forces very difficult to measure. It is estimated that in certain traffic conditions (like for example constant speed driving with slow or moderate speed) so called Rolling Resistance Impact Factor may be as high as 0.3. This means that reduction of rolling resistance by 50% would lead to 15% of energy...
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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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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Modelling of some stealth features for a small navy ship at the concept design stage - part II
PublikacjaIn the paper a few problems associated with modelling the basic stealth features for a small ship at the concept design stage are introduced. One problem concerns the modification of the immersed ship hull using the rapid change of the ship loading condition. The second is associated with the modification of the ship boundary layer by the hull skin cover. The other stealth features of the ship are not presented in this paper. The...
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A methodology for ultimate strength assessment of ship hull girder accounting for enhanced corrosion degradation modelling
PublikacjaThe presented work shows a methodology for the ultimate strength assessment of a ship hull, considering enhanced corrosion modelling. The approach is based on the classical Smith method. However, the recent findings regarding the impact of corrosion degradation on ultimate strength are incorporated. To this end, the stress–strain relationships for particular elements composing ship hull cross-section are modified using a specially...
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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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Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublikacjaIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
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ReFlexeNN - the Wearable EMG Interface with Neural Network Based Gesture Classification
PublikacjaThe electromyographic activity of muscles was measured using a wireless biofeedback device. The aim of the study was to examine the possibility of creating an automatic muscle tension classifier. Several measurement series were conducted and the participant performed simple physical exercises - forcing the muscle to increase its activity accordingly to the selected scale. A small wireless device was attached to the electrodes placed...
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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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Laboratory station for research of the innovative dry method of exhaust gas desulfurization for an engine powered with residual fuel
PublikacjaContemporary methods of exhaust gas desulfurization in marine engines are all expensive methods (4-5 million euro). This is, among other reasons, due to the limited market audience, but primarily due to the monop-olized position of manufacturers offering fabrication and assembly of this type of marine ship installations. Proposed as part of a research project financed by the Regional Fund for Environmental Protection and Maritime...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublikacjaIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Experimental study on the selected aspects of bow thruster generated flow field at ship zero-speed conditions
PublikacjaThe paper presents the results of experimental study on the interaction between the bow thrusters understood as the flow field changes generated by bow tunnel thruster in deep water conditions operated as a single and twin units. The research was limited to zero-speed case for the ship dead in the water. The influence of the hull form and jet spread between the neighbouring thrusters for several combinations of the applied bow...
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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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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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A model of fuel combustion process in the marine reciprocating engine work space taking into account load and wear of crankshaft-piston assembly and the theory of semi-Markov processes
PublikacjaThe ar ticle analyses the operation of reciprocal internal combu stion engines, with mar ine engines u sed a s an example. The analysis takes into account types of energy conversion in the work spaces (cylinders) of these engines, loads of their crankshaft-piston assemblies, and types of fuel combustion which can take place in these spaces during engine operation. It is highlighted that the analysed time-dependent loads of marine...
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Chapter 8 : Possibilities of operating fuel consumption estimation of vehicles
PublikacjaPrzedstawiona w pracy metoda umożliwia ocenę eksploatacyjnego zużycia paliwa pojazdu samochodowego dzięki porównaniu zarejestrowanego zużycia paliwa z referencyjnym dla tych samych warunków eksploatacji. Warunki te mogą wynikać zarówno z lokalnej specyfiki ruchu pojazdów jak również ze sposobu prowadzenia auta przez kierowcę. Zgodnie z przyjętą metodą warunki te mogą zostać w bardzo prosty sposób zarejestrowane w czasie codziennej...
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Problems of modelling toxic compounds emitted by a marine internal combustion engine for the evaluation of its structure parameters
PublikacjaThe paper presents the possibility of using an analytical study of the engine exhaust ignition to evaluate the technical condition of the selected components. Software tools available for the analysis of experimental data commonly use multiple regression model that allows the study of the effects and iterations between model input quantities and one output variable. The use of multi-equation models gives a lot of freedom in the...
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Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network
PublikacjaThe contribution of this paper is to show the opportunities for using the compressive sensing (CS) technique for detecting harmonics in a frequency sparse signal. The signal in a ship’s electrical network, polluted by harmonic distortions, can be modeled as a superposition of a small number of sinusoids and the discrete Fourier transform (DFT) basis forms its sparse domain. According to the theory of CS, a signal may be reconstructed...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublikacjaThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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Artificial neural network model of hardness, porosity and cavitation erosion wear of APS deposited Al2O3 -13 wt% TiO2 coatings
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