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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublicationMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Pedestrian detection in low-resolution thermal images
PublicationOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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The role of EMG module in hybrid interface of prosthetic arm
PublicationNearly 10% of all upper limb amputations concern the whole arm. It affects the mobility and reduces the productivity of such a person. These two factors can be restored by using prosthetics. However, the complexity of human arm makes restoring its basic functions quite difficult. When the osseointegration and/or targeted muscle reinnervation (TMR) are not possible, different modalities can be used to control the prosthesis. In...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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The effect of preliminary creep-strain on material behavior under LCF tension/compression and pure torsion regimes
PublicationThis paper presents the results of experimental tests of monotonic tension and torsion, creep-rupture and preliminary creep at 200C and 300C, as well as low-cycle fatigue of 2024 T3511 aluminum alloy. The fatigue process was conducted at room temperature for uniaxial tension/compression and torsion. The as-received material and pre-deformed material were also investigated during creep at elevated temperature. Basic monotonic,...
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Seaweed utilization issues in biogas production
PublicationMacroalgae can be seen as a renewable feedstock for the production of biofuels in many coastal areas around the World and especially in Baltic Sea region where the eutrophication is particularly troublesome. The investigation of anaerobic digestion technologies for extracting inexhaustible bioenergy from seaweed was conducted in many research institutions mainly in laboratory scale. Although seaweeds seem to have a great potential...
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Small rov to detection and identification of dangerous underwater objects
PublicationA small unmanned underwater vehicle (UUV) to inspection of an undersea space is presented in the paper. Its behavior is controlled by a trained pilot. Correct detection and identification of targets depends on vehicle'sprecise displacement along a predefined route. Nowadays, the UUVs are equipped with an automatic control system to execute some basic maneuvers without constant human interventions. Hence, in the paper, an autopilot...
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Ultrasound-assisted deep eutectic solvent-based liquid–liquid microextraction for simultaneous determination of Ni (II) and Zn (II) in food samples
PublicationA new approach was developed for the simultaneous pre-concentration and determination of Ni (II) and Zn (II) in food samples. This method is based on ultrasound-assisted liquid–liquid micro extraction using hydrophobic deep eutectic solvent (DES) and 1,10-phenanthroline as chelating agent. The effect of several parameters, such as pH, selection and volume of DES, amount of chelating agent, time of sonication and centrifugation,...
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Variable Order Differential Models of Bone Remodelling * *This work was supported by FCT, through IDMEC, under LAETA, projects UID/EMS/50022/2013, BoneSys, joint Polish-Portuguese project Modelling and controlling cancer evolution using fractional calculus, PERSEIDS (PTDC/EMS-SIS/0642/2014) and IF/00653/2012
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublicationFast data-driven surrogate models can be employed as replacements of computationally demanding full-wave electromagnetic simulations to facilitate the microwave design procedures. Unfortunately, practical application of surrogate modelling is often hindered by the curse of dimensionality and/or considerable nonlinearity of the component characteristics. This paper proposes a simple yet reliable approach to cost-efficient modelling...
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What Is Troubling IT Analysts? A Survey Report from Poland on Requirements-Related Problems
PublicationRequirements engineering and business analysis are activities considered to be important to software project success but also difficult and challenging. This paper reports on a survey conducted in Polish IT industry, aimed at identifying most widespread problems/challenges related to requirements. The survey was targeted at people performing role of analyst in commercial IT projects. The questionnaire included 64 pre-defined problems...
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Using Synchronously Registered Biosignals Dataset for Teaching Basics of Medical Data Analysis – Case Study
PublicationMedical data analysis and processing strongly relies on the data quality itself. The correct data registration allows many unnecessary steps in data processing to be avoided. Moreover, it takes a certain amount of experience to acquire data that can produce replicable results. Because consistency is crucial in the teaching process, students have access to pre-recorded real data without the necessity of using additional equipment...
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The Impact of Covid-19 on the Performance of Exchange Traded Funds on Developed and Emerging Markets
PublicationIn this paper an endeavour was made to evaluate the impact of Covid-19 on the achievement of the investment objectives by selected ETFs in developed and emerging markets. For this purpose, the tracking errors calculated for 18 different ETFs operating on the basis of American, Asian and European stock indexes were analyzed. The time range of the research was selected in such a way as to compare the period before the pandemic(pre-Covid)...
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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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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Optimal detection observers based on eigenstructure assignment. W: FaultDiagnosis. Models, artificial intelligence, applications. Ed. J. Korbicz, J.M. Kościelny, Z. Kowalczuk, W. Cholewa. Berlin: Springer Verlag**2004 s. 219-259, 7 rys. bibliogr. 41 poz. Optymalne obseratory detekcyjne oparte na strukturze własnej.
PublicationPraca dotyczy analitycznych metod syntezy algorytmów detekcji uszkodzeń. De-finiując wektor resztowy jako ważony błąd uzyskanej oceny wyjścia danego o-biektu, poszukuje się takich obserwatorów stanu, dostarczających owych osza-cowań, dla których wektor resztowy jest w możlwie wysokim stopniu niezależnyod niemierzalnych zakłóceń oddziałujących na obiekt oraz od niemierzalnychszumów w torach pomiarowych. Rozważa się algorytmy...
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Depth Images Filtering In Distributed Streaming
PublicationIn this paper, we propose a distributed system for point cloud processing and transferring them via computer network regarding to effectiveness-related requirements. We discuss the comparison of point cloud filters focusing on their usage for streaming optimization. For the filtering step of the stream pipeline processing we evaluate four filters: Voxel Grid, Radial Outliner Remover, Statistical Outlier Removal and Pass Through....
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The Influence of Low-Temperature Disintegration on the Co-Fermentation Process of Distillation Residue and Waste-Activated Sludge
Publication: Innovative low-temperature disintegration (process temperature 55 ◦C and oxygen concentration 0.2 mg/dm3 ) can be an economically rational technology to intensifying energy production from renewable sources. The proposed process can achieve a degree of disintegration—under optimal conditions—of about 50%, which is excellent when compared with other methods of feed pre-treatment. The low-temperature disintegration of distillation...
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Block-based Representation of Application Execution on Modern Parallel Systems
PublicationThe chapter presents how to model execution of a parallel computational application that is to be executed in a large-scale parallel or distributed environment with potentially thousands to millions of execution units. The representation uses pre- viously attributes and factors representative of modern high performance systems including multicore CPUs, GPUs, dedicated accelerators such as Intel Phi.
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Identification of the customer meter assignment to phases in LV grid: Selected issues of UPGRID project realization
PublicationThe paper presents selected issues on the European UPGRID grant implemented by a consortium of companies from seven European states, including from Poland, on the monitoring and control of low voltage grid using measurement pre-registered data by smart AMI meters. The paper focuses on the issue of lack of information on the assignment of communal meters to individual phases.
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A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms
PublicationThis paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Drop-coating deposition surface-enhanced Raman spectroscopy on silver substrates for biofluid analysis
PublicationUtilization of surface-enhanced Raman spectroscopy as a measurement technique is of particular interest in biodetection due to its superb chemical specificity and high sensitivity. The use of SERS substrates further improve this method by massive enhancement of the molecule Raman spectrum, permitting very low levels of detection. Therefore it is important to seek for new ways to develop reliable substrates, which are quickly and...
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DEPTH IMAGES FILTERING IN DISTRIBUTED STREAMING
PublicationIn this paper we discuss the comparison of point cloud filters focusing on their applicability for streaming optimization. For the filtering stage within a stream pipeline processing we evaluate three filters: Voxel Grid, Pass Through and Statistical Outlier Removal. For the filters we perform series of the tests aiming at evaluation of changes of point cloud size and transmitting frequency (various fps ratio). We propose a distributed...
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Simulations of hydro-fracking in rock mass at meso-scale using fully coupled DEM/CFD approach
PublicationThe paper deals with two-dimensional (2D) numerical modelling of hydro-fracking (hydraulic fracturing) in rocks at the meso-scale. A numerical model was developed to characterize the properties of fluid-driven fractures in rocks by combining the discrete element method (DEM) with computational fluid dynamics (CFD). The mechanical behaviour of the rock matrix was simulated with DEM and the behaviour of the fracturing fluid flow...
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Low-Cost Automated Design of Compact Branch-Line Couplers
PublicationBranch-line couplers (BLCs) are important components of wireless communication systems. Conventional BLCs are often characterized by large footprints which make miniaturization an important prerequisite for their application in modern devices. State-of-the-art approaches to design of compact BLCs are largely based on the use of high-permittivity substrates and multi-layer topologies. Alternative methods involve replacement of transmission-line...
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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublicationReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...
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Inverse Modeling and Optimization of CSRR-based Microwave Sensors for Industrial Applications
PublicationDesign optimization of multivariable resonators is a challenging topic in the area of microwave sensors for industrial applications. This paper proposes a novel methodology for rapid re-design and parameter tuning of complementary split-ring resonators (CSRRs). Our approach involves inverse surrogate models established using pre-optimized resonator data as well as analytical correction techniques to enable rapid adjustment of geometry...
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In-Out Surface Modification of Halloysite Nanotubes (HNTs) for Excellent Cure of Epoxy: Chemistry and Kinetics Modeling
PublicationIn-out surface modification of halloysite nanotubes (HNTs) has been successfully performed by taking advantage of 8-hydroxyquinolines in the lumen of HNTs and precisely synthesized aniline oligomers (AO) of different lengths (tri- and pentamer) anchored on the external surface of the HNTs. Several analyses, including FTIR, H-NMR, TGA, UV-visible spectroscopy, and SEM, were used to establish the nature of the HNTs’ surface engineering....
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Context-aware User Modelling and Generation of Recommendations in Recommender Systems
PublicationRecommender systems are software tools and techniques which aim at suggesting new items that may be of interest to a user. This dissertation is focused on four problems in recommender systems domain. The first one is context-awareness, i.e. how to obtain relevant contextual information, how to model user preferences in a context and use them to make predictions. The second one is multi-domain recommendation, which aim at suggesting...
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Dempster-shafer theory-based trust and selfishness evaluation in mobile ad hoc networks
PublicationThe paper addresses the problem of selfishness detec-tion in mobile ad hoc networks. It describes an approach based on Dempster-Shafer theory of evidence. Special attention is paid to trust evaluation and using it as a metric for coping with (weighted) recommendations from third-party nodes. Efficiency and robustness of the pre-sented solution is discussed with an emphasis on resil-iency to false recommendations.
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The moonuments of gdynia post-war construction pace
PublicationThe impresive pace of building objects realisation in the 1950s and 1960s was a continuation of the traditional gdynia building pace of the pre-war period. A particular attention and admiration must the reserved for the use at almost every construction site in Gdynia of a considerable quantify of prototypical meterial/construction solutions implemented above all in order to simplify technology and accelerate the pace of building...
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Network Approach to Increments of RR-intervals for Visualization of Dynamics of Cardiac Regulation
PublicationThe transition network for RR -increments is pre- sented in a directed and weighted graph, with vertices represent- ing RR -increments and edges corresponding to the order in a sequence of increments. The adjacency matrix and the transition matrix of this network provide a graphical tool which could be useful in the assessment of cardiac regulation. As an example, the method is applied in detecting differences between diurnal activity...
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Fatigue damage evaluation of organic coatings subjected to mechanical stress
PublicationZnaczna liczba konstrukcji ulega niszczeniu zmęczeniowemu w wyniku oddziaływania cyklicznych naprężeń mechanicznych. Jednakże w dziedzinie organicznych powłok ochronnych czynnik ten pozostaje niedoceniany. W pracy dokonano porównania wpływu cyklicznych naprężeń mechanicznych na nowe i pre-eksponowane (w podwyższonej temperaturze lub promieniowaniu UV) powłoki epoksydowe.
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublicationIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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METHOD OF TRAINING THE ENDOSCOPIC VIDEO ANALYSIS ALGORITHMS TO MAXIMIZE BOTH ACCURACY AND STABILITY
PublicationIn the article a new training and testing method of endoscopic video analysis algorithms is presented. Classical methods take into account only eciency of recognizing objects on single video frames. Proposed method additionally considers stability of classiers output for real video input. The method is simple and can be trained on data sets created for other solutions. Therefore, it is easily applicable to existing endoscopic video...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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IMPROVING STUDENT SKILLS WITH ENGAGING IN HERITAGE PROTECTION PROJECTS. CASE STUDY OF ARCHITECTURAL INVENTORY WORKS AT WISŁOUJŚCIE FORTRESS, POLAND (2017)
PublicationToday's educational offer at universities contains a lot of theoretical and general knowledge, which becomes less understandable and less suitable for students of the new generation. Student's educational needs aimed at increasing the practical experience necessary for future professional life. Heritage conservation projects are a good opportunity to implement project-based learning methods. Such projects can be scientific and...
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Between therapy effect and false-positive result in animal experimentation
PublicationDespite the animal models’ complexity, researchers tend to reduce the number of animals in experiments for expenses and ethical concerns. This tendency makes the risk of false-positive results, as statistical significance, the primary criterion to validate findings, often fails if testing small samples. This study aims to highlight such risks using an example from experimental regenerative therapy and propose a machine-learning...
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Ensembling noisy segmentation masks of blurred sperm images
PublicationBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
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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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Effects of Salvia officinalis and Thymus vulgaris on oxidant-induced DNA damage and antioxidant status in HepG2 cells
PublicationSalvia officinalis (SO) and Thymus vulgaris (TV) are medicinal plants well known for their curative powers. However, the molecular mechanisms responsible for these abilities of sage and thyme have not been fully understood yet. In this study we investigated the composition and the quantitative estimation of plant extracts, the protective effects of plant extracts against hydrogen peroxide- and 2,3-dimethoxy-1,4 naphthoquinone-induced...
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Buckling resistance of a metal column in a corrugated sheet silo - experiments and non-linear stability calculations
PublicationThe results of experimental and numerical tests of a single corrugated sheet silo column’s buckling resistance are presented in this study. The experiments were performed in a real silo with and without bulk solid (wheat). A very positive impact of the bulk solid on the column buckling resistance occurred. The experimental results were first compared to the buckling resistance calculated by Eurocode 3 formulae. The comparison revealed that...