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Wyniki wyszukiwania dla: neural embeddings
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Evaluating Performance and Accuracy Improvements for Attention-OCR
PublikacjaIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
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The Use of an Autoencoder in the Problem of Shepherding
PublikacjaThis paper refers to the problem of shepherding clusters of passive agents consisting of a large number of objects by a team of active agents. The problem of shepherding and the difficulties that arise with the increasing number of data describing the location of agents have been described. Several methods for reducing the dimensionality of data are presented. Selected autoencoding method using a Restricted Boltzmann Machine is...
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Dissociative multi-photon ionization of isolated uracil and uracil-adenine complexes
PublikacjaRecent multi-photon ionization (MPI) experiments on uracil revealed a fragment ion at m/z 84 that was proposed as a potential marker for ring opening in the electronically excited neutral molecule. The present MPI measurements on deuterated uracil identify the fragment as C3H4N2O+ (uracil+ less CO), a plausible dissociative ionization product from the theoretically predicted open-ring isomer. Equivalent measurements on thymine...
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THE USE OF GREEN LOGISTICS ELEMENTS DURING THE CONSTRUCTION OF OFFSHORE VESSELS
PublikacjaThe article is aimed at the presentation referring to the use of green logistics elements during the construction of the offshore vessels in the following aspects: collection, removal and utilisation of any waste that is harmful for natural environment, elimination of the negative impact that such waste can have on natural environment and the search for the optimal solutions as regards these aspects.
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Monitoring the gas turbine start-up phase on the platform using a hierarchical model based on Multi-Layer Perceptron networks
PublikacjaVery often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition...
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Vehicle classification based on soft computing algorithms
PublikacjaExperiments and results regarding vehicle type classification are presented. Three classes of vehicles are recognized: sedans, vans and trucks. The system uses a non-calibrated traffic camera, therefore no direct vehicle dimensions are used. Various vehicle descriptors are tested, including those based on vehicle mask only and those based on vehicle images. The latter ones employ Speeded Up Robust Features (SURF) and gradient images...
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The trajectories of the financial crisis of companies at risk of bankruptcy
PublikacjaThis article concerns the assessment of the trajectory of the collapse of enterprises in Central Europe. The author has developed a model of a Kohonen artificial neural network. This model was used to determine 6 different classes of risk and was allowed to graphically determine the 5- to 10-year trajectory of going bankrupt. The study used data on 140 companies listed on the Warsaw Stock Exchange. This population was divided into...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn 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
PublikacjaDue 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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The ONETEP linear-scaling density functional theory program
PublikacjaWe present an overview of the ONETEP program for linear-scaling density functional theory (DFT) calculations with large basis set (planewave) accuracy on parallel computers. The DFT energy is computed from the density matrix, which is constructed from spatially localized orbitals we call Non-orthogonal Generalized Wannier Functions (NGWFs), expressed in terms of periodic sinc (psinc) functions. During the calculation, both the...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment 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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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublikacjaTo 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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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Rozdział 3.2. W: [Praca zbiorowa] Materiały do monografii przyrodniczej re-gionu gdańskiego. Gdańsk: Marpress**2002 s. 69-70. Tom 8 Diagnoza stanu i koncepcja ochrony środowiska przyrodniczo-kulturowe- go w województwie pomorskim. Diagnosis of natural-cultural environment´scondition and the idea of its protection in Pomeranian Voivodship. Red. A.Kostarczyk, M. Przewoźniak.
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Next Generation Digital
PublikacjaThe paper outlines the major objectives of the MENAID research project, eimed at novel architectures of digital documents. Such documents will enable reduction of information overflow and strain, a major threat to the growth of a digital society. They will be forward compatible, technology neutral and lightweight, allowing workers of network organizations to use personal devices of any type.
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Charge dependence of fragmentation process induced by ion collisions with furan molecule
PublikacjaThe goal of this work is to describe the system evolution after ion-molecule interaction. We combine different quantum chemistry and statistical mechanics approaches in order to give extended description of the process. Herein we report on a recent study of the fragmentation mechanism of neutral, singly- and doubly-ionized furan molecule in the gas phase.
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Krajobraz wiejski i turystyka. Poszukiwanie równowagi pomiędzy widzeniem i wizerunkiem wsi
PublikacjaNajważniejszym składnikiem marki wsi jest krajobraz. Wizerunek wsi kreowany w turystyce i dostępny widok różnią się jednak coraz bardziej: przekaz reklamowy identyfikuje wieś z przyrodą oraz ciszą i spokojem; wieś realna stanowi, najczęściej dysharmonijną, mozaikę wiejsko-miejskiego zagospodarowania. Konfrontacja dostarczonego przez turystykę komunikatu z oglądanym krajobrazem podważa wiarygodność marki wsi, co stanowi zagrożenie...
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Syntheses, Structures and Reactivity of Terminal Phosphido Complexes of Iron(II) Supported by a β-Diketiminato Ligand
PublikacjaWe report the synthesis of the first series of terminal phosphido iron complexes supported by a β‐diketiminato ligand (Dippnacnac) and their catalytic activity in dehydrocoupling of secondary phosphines. Anionic and neutral mono‐ or diphosphido complexes were obtained from the reaction of [(Dippnacnac)FeCl2Li(dme)2] with the R2PLi (R = iPr, tBu, Cy, Ph) phosphides by tuning the stoichiometric ratio, polarity of the solvent, and...
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Mineral oil-based hydrostatic drives as the basic drive systems in the construction of offshore eqiupment projects
PublikacjaThe aim of this article is to present the components used in the production of mineral oil-based hydrostatic drives as the basic drive systems for the offshore industry. The article contains de-scriptions of the components of the said systems, with the description of their suitability for mi-neral oil operation and offshore applications.
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Screening of predicted synergistic multi-target therapies in glioblastoma identifies new treatment strategies
PublikacjaAbstract Background IDH-wildtype glioblastoma (GBM) is a highly malignant primary brain tumor with a median survival of 15 months after standard of care, which highlights the need for improved therapy. Personalized combination therapy has shown to be successful in many other tumor types and could be beneficial for GBM patients. Methods We performed the largest drug combination screen to date in GBM, using a high-throughput effort...
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JERUSALEM ARTICHOKE (HELIANTHUS TUBEROSUS L.) AS ENERGY RAW MATERIAL
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QUALITY OF SWEET POTATO AS A RAW MATERIAL FOR FOOD PROCESSING
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Glioblastoma-derived spheroid cultures as an experimental model for analysis of EGFR anomalies
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Efficiency comparison of selected endoscopic video analysis algorithms
PublikacjaIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublikacjaIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublikacjaIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Style Transfer for Detecting Vehicles with Thermal Camera
PublikacjaIn this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...
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Gelatin-Modified Polyurethanes for Soft Tissue Scaffold
PublikacjaRecently, in the field of biomaterials, which are being designed for soft tissue scaffolding, is growing the interest of their modification with natural polymers. Synthetic polymers are often hard, not easy to process and they do not possess fine biodegradable profile. From the other hand natural polymers are biocompatible, but weak when used alone. The combination of natural and synthetic polymers gives the suitable properties...
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Effective Short -term Forecasting of Wind Farms Power
PublikacjaForecasting a specific wind farm's generation capacity within a 24 hour perpective requires both a reliable forecast of wind, as well as supporting tools. This tool is a dedicated model of wind farm power. This model should include not only general rules of wind to mechanical energy conversion, but also the farm's specific features. This paper present analytical, statistical, and neuron models of wind farm power. The study is based...
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Spectroscopic studies of Nb-doped tricalcium phosphate glass-ceramics prepared by sol-gel method
PublikacjaCalcium-phosphate based glasses and glass-ceramics play a crucial role in the tissue engineering development. Apart from their high biocompatibility and excellent ability to undergo varying degrees of resorbability1, they exhibit relatively high bioactivity and due to that they are commonly used as bone and dental implants. A substantial research effort is devoted to improve calcium-phosphate materials physico-chemical properties...
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Dissociative photo-double-ionization of the isoxazole molecules
PublikacjaThe five-membered heterocyclic rings are incorporated into a wide variety of structures that play a vital role in many biochemical processes. In particular, the isoxazole molecule appears in many bioactive compounds due to its unique ring structure that consists of one oxygen atom and one nitrogen atom at adjacent positions. The unique atomic composition and bond arrangement of isoxazole imply its specific electronic properties...
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VUV photofragmentation of the six-membered heterocyclic molecules containing oxygen
PublikacjaCancer is a significant public health concern worldwide, which results in millions of deaths each year. The standard cure routine for cancer is surgery, and nowadays, radiotherapy or a hadrontherapy. Depending on the type of cancer, patients may undergo additional treatment, including targeted therapy. A combination of radio- or hadron-therapy with proper drug treatment can inhibit the proliferation of cancer cells and thus can...
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The use of modified vegetable oil from Crambe abyssinica as a lubricant base for the food industry
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Nano-structured Pt embedded in the acidic salts of heteropolymolybdate matrices: MS XAFS study
PublikacjaMultiple-scattering extended X-ray absorption fine structure (MS EXAFS) study combined with TEM and XRD analysis of a novel Pt-based catalyst operating at low temperature fuel cells (FCs) is presented. Innovation in the case of the considered catalyst resides in the use of a porous inorganic matrix of acidic heteropolymolybdate salts as a catalyst support. Obtained results show the relation between the matrix composition and the...
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Hydrogen migration in formation of NH(A3Π) radicals in photodissociations of isoxazole and pyridine molecules
PublikacjaIn the present study, the H atom migration was observed in the photodissociation processes of the isoxazole and pyridine molecules in the gas-phase, applying the photon-induced fluorescence spectroscopy (PIFS).
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Fragmentomic analysis of biopeptides in silico released from milk proteins
PublikacjaThe fragmentomic-assisted method was employed to predict the biological potential of peptides derived from milk proteins hydrolyzed by papain and bromelain. Firstly, protein sequences were acquired from the BIOPEP-UWM database and then hydrolyzed by the above enzymes using a BIOPEP-UWM tool called “Enzyme(s) action”. The released peptides were defined as parent peptides and further analyzed for the presence of shorter peptidic...
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Invariant measures for interval translations and some other piecewise continuous maps
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Cooperation of mono- and bi-articular muscles: human lower limb
PublikacjaObjectives: The aim of this study was to create and analyze a Pareto-optimal problem that would describe cooperation between mono- and bi-articulate lower limb muscles in sagittal plane. Methods: Equations describing the problem were derived and analyzed, additional constrains were introduced and experimental verification based on gait video analysis was performed. Results: Uncertainty of Pareto-optimal solution is shown for the...
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Valence and ionic lowest-lying electronic states of small esters studied by high resolution vacuum ultraviolet photoabsorption, photoelectron spectroscopy and ab initio calculations
PublikacjaEsters are an important class of oxygenated volatile organic compounds used in food flavorings, perfumes and other cosmetic products. They are present in fruits and pheromones and are emitted to the atmosphere naturally. Esters are also formed in the atmosphere as a product of the oxidation of ethers. Some of them form poly-molecule chains and are used in plastics. Phosphoesters form DNA backbone, while nitroesters are known for...
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The Effect of Openings’ Size and Location on Selected Dynamical Properties of Typical Wood Frame Walls
PublikacjaThe wooden frame constructions are now popular in many developed countries of the world. Many of these locations where such buildings are constructed are exposed to seismic and other shocks which are generated by human activities. This paper discusses the effect of the size and location of openings in the wooden frame walls under dynamic loadings. Natural frequencies of such frames with and without openings have been determined....
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Wulkanizaty kauczuku naturalnego otrzymane z użyciem plastyfikatorów pochodzenia roślinnego
PublikacjaCelem niniejszej pracy było zbadanie wpływu epoksydowanych olejów roślinnych na wybrane właściwości wul-kanizatów kauczuku naturalnego. Jako plastyfikatorów użyto epoksydowanego oleju sojowego oraz epoksydo-wanego oleju palmowego. Wpływ olejów naturalnych porównano także z wulkanizatami przygotowanymi bez użycia zmiękczaczy, jak i zawierającymi olej maszynowy, pochodzący z przerobu ropy naftowej. Zbadano wpływ rodzaju...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublikacjaThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublikacjaIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublikacjaThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Deep learning approach on surface EEG based Brain Computer Interface
PublikacjaIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublikacjaThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...