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Search results for: artificial neural network, modelling,ship speed, engine fuel consumption
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Enhanced Eye-Tracking Data: a Dual Sensor System for Smart Glasses Applications
PublicationA technique for the acquisition of an increased number of pupil positions, using a combined sensor consisting of a low-rate camera and a high-rate optical sensor, is presented in this paper. The additional data are provided by the optical movement-detection sensor mounted in close proximity to the eyeball. This proposed solution enables a significant increase in the number of registered fixation points and saccades and can be used...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublicationThe objective of the paper is to present the issue of safety manage-ment during the construction process. Threats in the form of disturb-ances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The arti-cle presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine,...
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Scale effect in the self-propulsion prediction for Ultra Large Container Ship with contra-rotating propellers
PublicationThis article addresses the problem of the scale effect for an Ultra Large Container Ship (ULCS) with a novel twin-crp-pod propulsion system. Twin-crp-pod steering-propulsion arrangement is an innovative solution that gains from three well-known systems: twin-propeller, contra-rotating propellers and pod propulsors. It is expected that applying the twin-crp-pod system to the analysed Ultra Large Container Ship will increase propulsion...
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An ANN-Based Approach for Prediction of Sufficient Seismic Gap between Adjacent Buildings Prone to Earthquake-Induced Pounding
PublicationEarthquake-induced structural pounding may cause major damages to structures, and therefore it should be prevented. This study is focused on using an artificial neural network (ANN) method to determine the sufficient seismic gap in order to avoid collisions between two adjacent buildings during seismic excitations. Six lumped mass models of structures with a different number of stories (from one to six) have been considered in...
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Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublicationIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Ship domain applied to determining distances for collision avoidance manoeuvres in give-way situations
PublicationShip domain is often used in marine navigation and marine traffic engineering as a safety condition. The basic idea behind those applications is that an encounter of two or more ships can be considered safe if neither of ship domains is intruded by other ships. Research utilising this approach has been documented in numerous works, including publications on optimising collision avoidance manoeuvres performed to fulfil domain-based...
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Tacit Knowledge Sharing and Personal Branding. How to Derive Innovation From Project Teams?
PublicationInnovation, relationships, cooperation, and knowledge are key factors which determine a competitive advantage in the networked economy. A network serves as a contemporary form of market process coordination. Network economy, according to the idea of prosumerism, is founded on collaboration of individual creators based on a network of values instead of hierarchical dependencies. Another feature of a network is that it imposes symmetry...
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Nonlinear Model of Synchronous Generator for Autonomous Electrical Power Systems Analysis
PublicationThis paper presents the nonlinear lookup table model for synchronous generator (SG) analysis. The saturation effects of the SG magnetic circuit have been considered. The saturated characteristic of the SG magnetic circuit are based on the open circuit saturation curve for magnetizing inductances. The model has been implemented into the Synopsys/Saber software using the MAST modelling language. To implement the no-load voltage characteristic...
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Dynamic Positioning Capability Assessment for Ship Design Purposes
PublicationThe article focuses on solving a problem of optimal thrust distribution over the actuators in a ship Dynamic Positioning, according to DNV-ST-0111 standard, Level 1. The classic Quadratic Programming approach is combined with the numerical solusion used to handle the propeller with the rudder constraints in the optimization task and the influence between thrusters and skeg. It is presented as an efficient method of minimizing the...
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Analytical Traffic Model for a Multidomain IMS/NGN Network Including Service and Transport Stratum
PublicationThis paper addresses the problem of modelling call processing performance (CPP) in a multidomain Next Generation Network (NGN) architecture including the elements of the IP Multimedia Subsystem (IMS) in service stratum and based on the Multiprotocol Label Switching (MPLS) technology in transport stratum. An analytical traffic model for such an architecture is proposed by integrating the formerly implemented submodels of service...
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Using FreeFEM open software for modelling the vibrations of piezoelectric devices
PublicationModelling vibrations of piezoelectric transducers has been a topic discussed in the literature for many decades. The first models - so-called one-dimensional - describe the vibrations only near operating frequency and near its harmonics. Attempts to introduce two-dimensional models were related to the possibility of one transducer working at several frequencies, including both thickness vibrations and those resulting from the transducer...
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Decomposition of the induced magnetism degaussing problem for fast determination of currents in demagnetization coils wrapped outside an object under arbitrary external field conditions
PublicationSafe passage of ships in the presence of sea mines can be ensured by limiting or reducing the ship’s magnetic footprint. For vessels with plastic hulls, the main component that requires magnetic damping is the engine. Demagnetization of such an object can be achieved by wrapping it with coils and setting the direct current appropriately. For each specific geographic location, the currents in the coils can be determined iteratively...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublicationLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Low-Power Receivers for Wireless Capacitive Coupling Transmission in 3-D-Integrated Massively Parallel CMOS Imager
PublicationThe paper presents pixel receivers for massively parallel transmission of video signal between capacitive coupled integrated circuits (ICs). The receivers meet the key requirements for massively parallel transmission, namely low-power consumption below a single μW, small area of less than 205 μm2, high sensitivity better than 160 mV, and good immunity to crosstalk. The receivers were implemented and measured in a 3-D IC (two face-to-face...
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The Matter of Decision-Making Control Over Operation Processes of Marine Power Plant Systems with the Use of their Models in the form of Semi-Markov Decision-Making Processes
PublicationThe article presents the possibility to control the real operation process of an arbitrary device installed in the marine power plant based on the four-state semi-Markov process, being the model of the process, which describes the transition process of operational states of the device and the transition process of its technical states. All these states are precisely defined for the ship main engine (SG). A hypothesis is proposed...
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Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Multi-Camera Vehicle Tracking Using Local Image Features and Neural Networks
PublicationA method for tracking moving objects crossing fields of view of multiple cameras is presented. The algorithm utilizes Artificial Neural Networks (ANNs). Each ANN is trained to recognize images of one moving object acquired by a single camera. Local image features calculated in the vicinity of automatically detected interest points are used as object image parameters. Next, ANNs are employed to identify the same objects captured...
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Performance Analysis of the OpenCL Environment on Mobile Platforms
PublicationToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
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Integrated Control in High-Speed Networks Using Constrained Model Predictive Control
PublicationThis paper studies congestion control in high-speed communication networks using Model Predictive Control (MPC). Network traffic is assumed to consist of best-effort and priority traffic sources. An integrated controller consisting of two control parts is designed. The controller calculates the capacity for priority sources and the input rate of best-effort sources. MPC is desirable as it can take into account the constraints on...
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An Impact Analysis of Artificial Light at Night (ALAN) on Bats. A Case Study of the Historic Monument and Natura 2000 Wisłoujście Fortress in Gdansk, Poland
PublicationThe artificial light at night (ALAN) present in many cities and towns has a negative impact on numerous organisms that live alongside humans, including bats. Therefore, we investigated if the artificial illumination of the historic Wisłoujście Fortress in Gdańsk, Poland (part of the Natura 2000 network), during nighttime events, which included an outdoor electronic dance music (EDM) festival, might be responsible for increased...
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Adaptacyjny algorytm filtracji sygnału fonokardiograficznego wykorzystujący sztuczną sieć neuronową
PublicationPodstawowym problemem podczas projektowania systemu autodiagnostyki chorób serca, bazującego na analizie sygnału fonokardiograficznego (PCG), jest konieczność zapewnienia, niezależnie od warunków zewnętrznych, sygnału o wysokiej jakości. W artykule, bazując na zdolności Sztucznej Sieci Neuronowej (SSN) do predykcji sygnałów periodycznych oraz quasi-periodycznych, został opracowany adaptacyjny algorytm filtracji dźwięków serca....
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Comparison of strain results at a laser weld notch obtained by numerical calculations and experimental measurements
PublicationIn the development of ship structures applying new materials and it’s purposeful placement play an important role. During the last years, especially in a construction of ro-ro type vessels, the usage of novel sandwich structures in cargo decks is profitable. Steel sandwich panel is an innovative solution which at a todays state of development can be used for the construction of any members not taking part in a global bending of...
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Wybrane metody diagnostyki łożysk silników indukcyjnych oparte o pomiar prądu
PublicationW artykule zawarto przegląd wybranych metod diagnostyki łożysk silnika indukcyjnego, bazujących na pomiarach prądu zasilającego. Jedno z nowych rozwiązań przetwarzania sygnałów zostało zaadaptowane przez autorów do stosowanego przez nich systemu diagnostycznego. Wyniki wstępnych badań symulacyjnych zweryfikowanych badaniami na rzeczywistym obiekcie wskazują, że rozwiązanie to ułatwia diagnozowanie. Autorzy zamierzają prowadzić...
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Clothes Detection and Classification Using Convolutional Neural Networks
PublicationIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
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Artificial Intelligence Aided Architectural Design
PublicationTools and methods used by architects always had an impact on the way building were designed. With the change in design methods and new approaches towards creation process, they became more than ever before crucial elements of the creation process. The automation of architects work has started with computational functions that were introduced to traditional computer-aided design tools. Nowadays architects tend to use specified tools...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublicationDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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DO WE NEED NAVIER NUMBER? – FURTHER REMARKS AND COMPARISON WITH ANOTHER DIMENSIONLESS NUMBERS
PublicationThis paper presents a role of the Navier number (Na-dimensionless slip-length) in universal modelling of flow reported in micro- and nano-channels like: capillary biological flows, fuel cell systems, micro-electro-mechanical systems and nano-electro-mechanical systems. Similar to another bulk-like and surface-like dimensionless numbers, the Na number should be treated as a ratio of internal viscous to external viscous momentum...
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The Impact of Building Performance Analysis on intuition Development and Decision Making Rationality
PublicationContemporary architectural workshop is characterized by the ability to efficiently collect and process huge amounts of geometric and non-geometric information. Virtual substitutes for buildings and structures allow to analyze various aspects of real life activity at various stages of the design process. The possibility of increased prognostic quantitative data acquisition, such as cost of energy consumption, shifts architectural...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Direct electrical stimulation of the human brain has inverse effects on the theta and gamma neural activities
PublicationObjective: Our goal was to analyze the electrophysiological response to direct electrical stimulation (DES) systematically applied at a wide range of parameters and anatomical sites, with particular focus on neural activities associated with memory and cognition. Methods: We used a large set of intracranial EEG (iEEG) recordings with DES from 45 subjects with electrodes...
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Optimized Computational Intelligence Model for Estimating the Flexural Behavior of Composite Shear Walls
PublicationThis article presents a novel approach to estimate the flexural capacity of reinforced concrete-filled composite plate shear walls using an optimized computational intelligence model. The proposed model was developed and validated based on 47 laboratory data points and the Transit Search (TS) optimization algorithm. Using 80% of the experimental dataset, the optimized model was selected by determining the unknown coefficients of...
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An Improved Method of Minimizing Tool Vibration during Boring Holes in Large-Size Structures
PublicationThe paper presents a thoroughly modified method of solving the problem of vibration suppression when boring large-diameter holes in large-size workpieces. A new approach of adjusting the rotational speed of a boring tool is proposed which concerns the selection of the spindle speed in accordance with the results of the simulation of the cutting process. This streamlined method focuses on phenomenological aspects and involves the...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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A 0.5 V Nanowatt Biquadratic Low-Pass Filter with Tunable Quality Factor for Electronic Cochlea Applications
PublicationA novel implementation of an analogue low-power, second-order, low-pass filter with tunable quality factor (Q) is presented and discussed. The filter feature is a relatively simple, buffer-based, circuit network consisting of eleven transistors operating in a subthreshold region. Q tuning is accomplished by injecting direct current into a network node, which changes the output resistance of the transistors and, as a result, modifies...
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Digitalization of High Speed Craft Design and Operation Challenges and Opportunities
PublicationIn recent years, global demands for safe and sustainable ships led to dramatic changes in the maritime industry. Digitalization is expected to play an important part in the future. This is supported by analysis of the autonomous ships market which shows that digitalization of large ship types such as tankers and container ships is well on track. Although to date designs of autonomous High-Speed Craft (HSC) have been developed,...
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"Shadow" method application within endoscopic examinations of marine engines
PublicationThe paper deals with diagnostic issues concerning endoscopic examinations of the working spaces within marine diesel and gas turbine engines. In the beginning, the endoscopy apparatus being on the laboratory equipment of the Department of Ship Power Plants of Gdansk University of Technology in Poland has been characterized. The endoscopy considerations have been focused on theoretical bases of a digital image processing and especially...
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"Shadow" method application within endoscopic examinations of marine engines
PublicationThe paper deals with diagnostic issues concerning endoscopic examinations of the working spaces within marine diesel and gas turbine engines. In the beginning, the endoscopy apparatus being on the laboratory equipment of the Department of Ship Power Plants of Gdansk University of Technology in Poland has been characterized. The endoscopy considerations have been focused on theoretical bases of a digital image processing and especially...
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AN ENERGY APPROACH TO THE FATIGUE LIFE OF SHIP PROPULSION SYSTEMS
PublicationThe conducted research investigations aimed to carry out an identification of the constructional materials fatigue state of the ship propulsions’ rotational mechanical units for diagnostic purposes. The fatigue cracks of the elements transmitting mechanical energy streams from the propulsion engines to the ship propellers or to the generators of the ship’s electric power station stand for a primary reason for the secondary, usually...
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Cellular network quality evaluation at a university campus on the eve of 5G
PublicationThanks to the availability of mobile devices and the spread of broadband access around the world, the number of network users continues to grow. This has raised user awareness when it comes to the quality of content they consume. Many service providers and operators focus on monitoring QoN (Quality of Network) and QoS (Quality of Service) parameters, particularly those influenced by bandwidth and latency. However, for most end-users,...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Leader election for anonymous asynchronous agents in arbitrary networks
PublicationWe consider the problem of leader election among mobile agents operating in an arbitrary network modeled as an undirected graph. Nodes of the network are unlabeled and all agents are identical. Hence the only way to elect a leader among agents is by exploiting asymmetries in their initial positions in the graph. Agents do not know the graph or their positions in it, hence they must gain this knowledge by navigating in the graph...