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Search results for: SZTUCZNA INTELIGENCJA
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Intelligent system supporting diagnosis of malignant melanoma
PublicationMalignant melanomas are the most deadly type of skin cancers. Early diagnosis is a key for successful treatment and survival. The paper presents the system for supporting the process of diagnosis of skin lesions in order to detect a malignant melanoma. The paper describes the development process of an intel-ligent system purposed for the diagnosis of malignant melanoma. Presented sys-tem can be used as a decision support system...
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Deep neural networks for data analysis
e-Learning CoursesThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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Are Pair Trading Strategies Profitable During COVID-19 Period?
PublicationPair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Adam Brzeski dr inż.
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Algorytmy przetwarzania widm Ramana w procesie detekcji substancji chemicznych
PublicationRozprawa przedstawia szczegółowo algorytmy, jakie są stosowane podczas przetwarzania widm Ramana, rejestrowanych przenośnym spektrometrem o skończonej rozdzielczości. Pracę podzielono na osiem rozdziałów. W pierwszym określono cel i tezy pracy. Rozdział drugi opisuje podstawowe pojęcia dotyczące zjawiska Ramana oraz zasady budowy urządzeń do pomiarów widm Ramana. W rozdziale trzecim scharakteryzowano błędy występujące podczas pomiarów...
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IPSJ Transactions on Computer Vision and Applications
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublicationWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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Scenarios as a tool supporting decisions in urban energy policy: The analysis using fuzzy logic, multi-criteria analysis and GIS tools
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Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data
PublicationThe Side Scan Sonar and Synthetic Aperture Sonar are well known echo signal processing technologies that produce 2D images of the seafloor. Both systems combines a number of acoustic pings to form a high resolution image of seafloor. It was shown in numerous papers that 2D images acquired by such systems can be transformed into 3D models of seafloor surface by algorithmic approach using intensity information, contained in a grayscaled...
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Feature Importance of Stabilised Rammed Earth Components Affecting the Compressive Strength Calculated with Explainable Artificial Intelligence Tools
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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublicationNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Tomasz Majchrzak dr inż.
PeopleDr inż. Tomasz Majchrzak urodził się 29.01.1992 roku w Elblągu. W młodym wieku przejawiał zainteresowania z zakresu nauk społecznych i historii, stąd wykształcenie średnie uzyskał w I LO w Elblągu w klasie o profilu społeczno-prawnym. Jednak, rzucając sobie wyzwanie, zdecydował się wybrać studia na Wydziale Chemicznym Politechniki Gdańskiej, z którym związany jest do teraz. Swoją karierę naukową rozpoczął jeszcze na studiach inżynierskich...
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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The Development of a Combined Method to Quickly Assess Ship Speed and Fuel Consumption at Different Powertrain Load and Sea Conditions
PublicationDecision support systems (DSS) recently have been increasingly in use during ships operation. They require realistic input data regarding different aspects of navigation. To address the optimal weather routing of a ship, which is one of the most promising field of DSS application, it is necessary to accurately predict an actually attainable speed of a ship and corresponding fuel consumption at given loading conditions and predicted...
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WYKORZYSTANIE TESTU MUSHRA W BADANIU KORZYŚCI UŻYTKOWANIA PROTEZ SŁUCHOWYCH
PublicationOcena jakości dopasowania aparatów słuchowych w kontekście korzyści, jakie może przy-nieść proteza jest złożonym zagadnieniem. Obiektywne parametry aparatów, które można wy-znaczyć (np. wzmocnienie czy pasmo przenoszenia) nie zawsze mają bezpośredni i decydujący wpływ w subiektywnej ocenie jakości dopasowania protezy słuchowej przez pacjenta. Pomiary efektywności aparatu słuchowego mogą dotyczyć wielu aspektów, między innymi kompensacji...
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Food analysis using artificial senses.
PublicationNowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring...
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Retention modeling of some saccharides separated on an amino column.
PublicationUsing an amino column (Supelcosil LC-NH2) and different mixtures of acetonitrile-water, quantitative structure-retention relationship models are discussed. These models are based on computed molecular descriptors representing numerically structured features of some saccharides. The obtained results are underlining the lipophilicity/hydrophilicity balance, and how this is controlling the separation of the saccharides. The resulting...
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Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms
PublicationThe study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublicationConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Introduction to the ONDM 2022 special issue
PublicationThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
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Międzynarodowa Szkoła Letnia na temat algorytmów
EventsKatedra Algorytmów i Modelowania Systemów WETI PG organizuje 4. edycję Międzynarodowej Szkoły Letniej na temat algorytmów dla problemów optymalizacji dyskretnej i głębokiego uczenia
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JamesBot - an intelligent agent playing StarCraft II
PublicationThe most popular method for optimizing a certain strategy based on a reward is Reinforcement Learning (RL). Lately, a big challenge for this technique are computer games such as StarCraft II which is a real-time strategy game, created by Blizzard. The main idea of this game is to fight between agents and control objects on the battlefield in order to defeat the enemy. This work concerns creating an autonomous bot using reinforced...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublicationLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Comprehensive Comparison of a Few Variants of Cluster Analysis as Data Mining Tool in Supporting Environmental Management
PublicationA few variants of hierarchical cluster analysis (CA) as tool of assessment of multidimensional similarity in environmental dataset are compared. The dataset consisted of analytical results of determination of metals (Na, K, Ca, Sc, Fe, Co, Zn, As, Br, Rb, Mo, Sb, Cs, Ba, La, Ce, Sm, Hf and Th) in ambient air dried and kept alive, by the means of hydroponics, moss baskets collected in 12 locations on the area of Tricity (Poland)....
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Materials Design for the Titanium Scaffold Based Implant
PublicationThe main objective of here presented research is a design the scaffold/porous titanium(Ti) alloy based composite material demonstrating better biocompatibility, longer lifetime andbioactivity behaviour for load-bearing implants. The development of such material is proposed bymaking a number of consecutive tasks. Modelling the mechanical, biomechanical and biologicalbehavior of porous titanium structure and an elaboration of results...
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Materials Design for the Titanium Scaffold Based Implant
PublicationThe main objective of here presented research is a design the scaffold/porous titanium(Ti) alloy based composite material demonstrating better biocompatibility, longer lifetime andbioactivity behaviour for load-bearing implants. The development of such material is proposed bymaking a number of consecutive tasks. Modelling the mechanical, biomechanical and biologicalbehavior of porous titanium structure and an elaboration of results...
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublicationIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublicationIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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PROPRIETARY SOFTWARE IN TECHNICAL HIGHER EDUCATION
PublicationThe authors present a relatively easy way to extend the quality of education in professional studies (engineering) on major “Geodesy and Cartography”. They indicate the possibility to deepen students’ knowledge by using in the educational process proprietary software enriching education. The authors use their own experiences, results of the cooperation with employers, as well as the effects of scientific research to introduce into...
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PROPRIETARY SOFTWARE IN TECHNICAL HIGHER EDUCATION
PublicationThe authors present a relatively easy way to extend the quality of education in professional studies (engineering) on major “Geodesy and Cartography”. They indicate the possibility to deepen students’ knowledge by using in the educational process proprietary software enriching education. The authors use their own experiences, results of the cooperation with employers, as well as the effects of scientific research to introduce...
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Texture Features for the Detection of Playback Attacks: Towards a Robust Solution
PublicationThis paper describes the new version of a method that is capable of protecting automatic speaker verification (ASV) systems from playback attacks. The presented approach uses computer vision techniques, such as the texture feature extraction based on Local Ternary Patterns (LTP), to identify spoofed recordings. Our goal is to make the algorithm independent from the contents of the training set as much as possible; we look for the...
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Smart metering - social risk perception and risk governance (10h, 2 ECTS credits)
e-Learning CoursesThe goal of the course is to broaden the understanding of technology-related risks and to present the concepts of social risk perception and risk governance in the context of smart metering technology. In current phase of technological development – known as the fourth industrial revolution – rapid and profound changes are setting up new and particularly destabilizing risks. In more and more complex technological systems that constitute...
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International Conference on Genetic Algorithms
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Selected Artificial Intelligence Methods in the Risk Analysis of Damage to Masonry Buildings Subject to Long-Term Underground Mining Exploitation
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Artificial Intelligence-Based Weighting Factor Autotuning for Model Predictive Control of Grid-Tied Packed U-Cell Inverter
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Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Garnizon district in Gdansk, Poland
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Seestadt Aspern, Vienna, Austria
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Västra Hamnen, Malmö, Sweden.
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Hammarby-Sjöstad, Stockholm, Sweden.
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Pilestredet Park, Oslo, Norway.
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / King’s Cross, London, UK.
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Oceanhamnen, Helsingborg, Sweden
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / La Courrouze district in Rennes, France
Open Research DataThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Customized crossover in evolutionary sets of safe ship trajectories
PublicationThe paper presents selected aspects of evolutionary sets of safe ship trajectories-a method which applies evolutionary algorithms and some of the assumptions of game theory to solving ship encounter situations. For given positions and motion parameters of the ships, the method finds a near optimal set of safe trajectories of all ships involved in an encounter. The method works in real time and the solutions must be returned within...
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AITP - AI Thermal Pedestrians Dataset
PublicationEfficient pedestrian detection is a very important task in ensuring safety within road conditions, especially after sunset. One way to achieve this goal is to use thermal imaging in conjunction with deep learning methods and an annotated dataset for models training. In this work, such a dataset has been created by capturing thermal images of pedestrians in different weather and traffic conditions. All images were manually annotated...
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublicationVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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International FLINS Conference on Robotics and Artificial Intelligence (International Fuzzy Logic and Intelligent technologies in Nuclear Science Conference)
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Scoreboard Architectural Pattern and Integration of Emotion Recognition Results
PublicationThis paper proposes a new design pattern, named Scoreboard , dedicated for applications solving complex, multi-stage, non-deterministic problems. The pattern provides a computational framework for the design and implementation of systems that integrate a large number of diverse specialized modules that may vary in accuracy, solution level, and modality. The Scoreboard is an extension of Blackboard design pattern and comes under...
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On evolutionary computing in multi-ship trajectory planning, Applied Intelligence
PublicationThe paper presents the updated version of Evolutionary Sets of Safe Ship Trajectories: a method which applies evolutionary algorithms and some of the assumptions of game theory to solving ship encounter situations. For given positions and motion parameters of the ships,the method finds a near optimal set of safe trajectories of all ships involved in an encounter. The method works in real time and the solutions must be returned...
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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE RESEARCH
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International Journal of Computational Intelligence and Applications
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International Journal of Computational Intelligence Techniques
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Applied Computational Intelligence and Soft Computing
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International Journal of Computational Intelligence Systems
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International Journal of Computational Intelligence in Control
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Integrated algorithm for selecting the location and control of energy storage units to improve the voltage level in distribution grids
PublicationThis paper refers to the issue that mainly appears in distribution grids, where renewable energy sources (RES) are widely installed. In such grids, one of the main problems is the coordination of energy production time with demand time, especially if photovoltaic energy sources are present. To face this problem, battery energy storage units (ESU) can be installed. In recent years, more and more attention has been paid to optimizing...
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International Journal of Interactive Multimedia and Artificial Intelligence
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BRAIN-Broad Research in Artificial Intelligence and Neuroscience
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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
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Dobór parametrów silnika indukcyjnego dużej mocy
PublicationW artykule przedstawiono trzy typy statycznych modeli matematycznych silników klatkowych oraz metodę estymacji parametrów, przy wykorzystaniu algorytmów genetycznych. Korzystając z kryteriów: suma kwadratów, suma wartości bez-względnych oraz całkowego, oceniono przydatność badanych modeli. Opracowane modele matematyczne zostały wykorzystane przy doborze algorytmów sterownia sterów strumieniowych. Po-kazano metodykę doboru parametrów...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublicationMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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Categorization of Cloud Workload Types with Clustering
PublicationThe paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional...
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Optymalizacja alokacji modułów programistycznych w rozproszonym systemie szkolenia wojskowego
PublicationW pracy przedstawiono system metodologiczny do wyznaczania i oceny przydziałów modułów programistycznych w rozproszonym systemie informatycznym, bazującym na systemie MOODLE, wspomagającym zdalne nauczanie i szkolenie wojskowe. Opracowano modele matematyczne rozproszonych systemów komputerowych, na podstawie których sformułowano zadania optymalizacji wielokryterialnej. Główny nacisk położono na zastosowanie algorytmów ewolucyjnych...
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Music genre classification applied to bass enhancement for mobile technology
PublicationThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The proposed algorithm is related to intelligent, rule-based setting of synthesis parameters according to music genre of an audio excerpt. The classification of music genres is automatically executed employing MPEG 7 parameters and the Principal Component Analysis method applied to reduce information...
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Geoscience Methods in Real Estate Market Analyses Subjectivity Decrease
PublicationReal estate management, including real estate market analysis, is part of a so-called geosystem. In recent years, the popularity of creating various types of systems and automatic solutions in real estate management, including those related to property classification and valuation, has been growing in the world, mainly to reduce the impact of human subjectivity, to increase the scope of analyses and reduce research time. A very...
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International Journal of Data Mining Modelling and Management
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International Journal of Business Intelligence and Data Mining
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Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublicationIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
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Adam Dąbrowski dr inż.
PeopleAdam Dabrowski has obtained a PhD in mechanical engineering from Gdańsk University of Technology and MSc. degree in mechatronics from Technische Universität Hamburg. He has an industry experience in Institute of Aviation Engineering Design Center (Warsaw, Poland) and SICK AG (Hamburg, Germany). Additionally, as an assistant at Gdansk University of Technology he teaught courses on mechanics, space mechanisms and dynamics of space...
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How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe
PublicationThis paper uses a sample of over 9 million workers from 22 European countries to study the intertwined relationship between digital technology, cross-border production links and working conditions. We compare the social consequences of technological change exhibited by three types of innovation: computerisation (software), automation (robots) and artificial intelligence (AI). To fully quantify work-related wellbeing, we propose...