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Search results for: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES
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Low-Cost EM-Simulation-Driven Multi-Objective Optimization of Antennas
PublicationA surrogate-based method for efficient multi-objective antenna optimization is presented. Our technique exploits response surface approximation (RSA) model constructed from sampled low-fidelity antenna model (here, obtained through coarse-discretization EM simulation). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. A low-cost RSA model construction is possible through...
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Deep Learning Approaches in Histopathology
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e-Learning in Tourism Education
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Online Learning Based on Prototypes
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Distributed Learning with Data Reduction
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Approximate Criteria for the Evaluation of Truly Multi-Dimensional Optimization Problems
PublicationIn this paper we propose new improved approximate quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO). In the performed comparative study we take into account the various EMO algorithms of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces. It is well known that useful executive criteria, such as those based on the true Pareto...
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Remote learning among students with and without reading difficulties during the initial stages of the COVID-19 pandemic
PublicationThis article presents the results of a survey on yet under-researched aspects of remote learning and learning difficulties in higher education during the initial stage (March – June 2020) of the COVID-19 pandemic. A total of 2182 students from University of Warsaw in Poland completed a two-part questionnaire regarding academic achievements in the academic year 2019/2020, living conditions and stress related to learning and pandemic,...
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Perspektywy wykorzystania technologii internetowych typu E-learning w dydaktyce szkół wyższych.
PublicationArtykuł dotyczy nauczania przez Internet na poziomie uniwersyteckim. Zaprezentowany został model wirtualnego uniwersytetu, który obejmuje materiały dydaktyczne, komunikację, egzaminy i organizację. Artykuł koncentruje się na technicznych zagadnieniach. Przeanalizowano także wpływ wykorzystania technologii E-learning na różne aspekty życia wyższej uczelni.
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Investigation of Narrow Electrostatic Precipitator with Wire Multi-Electrode
PublicationDiesel engines emit fine particles, which are harmful to human and animal health. There are several methods for decrease particulate emission from a diesel engines, but up to now, these methods are notenough effective or very expensive. An electrostatic precipitation was proposed as an alternative method for control of a diesel particulate emission. Therefore, narrow electrostatic precipitators (ESPs) have become a subject of interest...
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A Generalized SDP Multi-Objective Optimization Method for EM-Based Microwave Device Design
PublicationIn this article, a generalized sequential domain patching (GSDP) method for efficient multi-objective optimization based on electromagnetics (EM) simulation is proposed. The GSDP method allowing fast searching for Pareto fronts for two and three objectives is elaborated in detail in this paper. The GSDP method is compared with the NSGA-II method using multi-objective problems in the DTLZ series, and the results show the GSDP method...
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RESIDENTIAL FUNCTION IN MULTI-CRITERIA MULTIFUNCTIONAL BUILDING SYSTEM DESIGN PROCESS
PublicationThe paper presents the multi-criteria approach in the design process of residential structure as a part of a multifunctional building system. The purpose of work was to broaden the field of multifunctional building system design process. Background for the presented work is to define the direction of architectural growth of the modern city center area where actually are built complex and large capacity structures with a great impact...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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A computational view on nanomaterial intrinsic and extrinsic features for nanosafety and sustainability
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Real-Time Aerial Mapping by Image Features Extraction and Matching
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Electrophysiological features in patients with sinus node dysfunction and vasovagal syncope
PublicationThe aim of the study was to identify electrophysiological criteria that can be used for identification of patients with sinus node dysfunction and concurrent vasovagal syncope.
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The Effect of Varying the Light Spectrum of a Scene on the Localisation of Photogrammetric Features
PublicationIn modern digital photogrammetry, an image is usually registered via a digital matrix with an array of colour filters. From the registration of the image until feature points are detected on the image, the image is subjected to a series of calculations, i.e., demosaicing and conversion to greyscale, among others. These algorithms respond differently to the varying light spectrum of the scene, which consequently results in the feature...
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Techniques of acquiring additional features of the responses of individual gas sensors
PublicationGas sensors usually exhibit lack of selectivity, require fre quent calibration, exhibit drift of the response and a lot of factors, such as humidity or ambient temperature, influen ce their performance. Different approaches can be used to overcome this shortcomings. Building arrays of different sensors and usage of pattern recognition methods to analyze responses of elements...
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The Multiplatform Environment for Simulation and Features Estimation of Mixed-Signal Devices
PublicationThe use of simulation laboratories is gaining popularity in thedomains of engineering programs. However, the experience in teaching showsthat the simulation itself is not very effective in didactic processes. Teachingprocesses in thefield of specialist subjects, designed for students of technicaluniversities, should be based on direct operations performed by the student onreal devices. At the same time, at the later stages of didactic...
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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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Collaborative development model and strategies of multi-energy industry clusters: Multi-indicators analysis affecting the development of coastal energy clusters
PublicationThe paper explores Coastal Energy-Based Industrial Clusters (EBICs) and their role in advancing energy efficiency and sustainability through collaborative innovation. Economic growth theory and energy sustainability have been introduced into industrial clusters to illustrate indicators that have a greater impact on the development of EBICs. This paper proposes an EBICs development model based on the Cobb-Douglas function, in which...
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Multi-factor fuzzy sets decision system forecasting consumer insolvency risk
PublicationThe objective of this study is to develop a multi-factor decision system predicting insolvency risk for natural persons with the use of fuzzy sets. Considering that the financial situation of households is affected by various endogenous and exogenous factors, the main assumption of this study is that the system for predicting financial difficulties should not be limited to the use of only a few financial variables concerning consumers,...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublicationLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Computationally Efficient Multi-Objective Optimization of and Experimental Validation of Yagi-Uda Antenna
PublicationIn this paper, computationally efficient multi-objective optimization of antenna structures is discussed. As a design case, we consider a multi-parameter planar Yagi-Uda antenna structure, featuring a driven element, three directors, and a feeding structure. Direct optimization of the high-fidelity electromagnetic (EM) antenna model is prohibitive in computational terms. Instead, our design methodology exploits response surface...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Temporal sequence of the human RBCs' vesiculation observed in nano-scale with application of AFM and complementary techniques
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Watershed characteristics and climate factors effect on the temporal variability of mercury in the southern Baltic Sea rivers
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Research on Temporal Leachability of Trace Elements from Opoka-Rocks in The Aspect of Geochemical Environmental Indicators
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SPATIAL-TEMPORAL DETECTION OF CHANGES ON THE SOUTHERN COAST OF THE BALTIC SEA BASED ON MULTITEMPORAL AERIAL PHOTOGRAPHS
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Temporal changes in the content of labile and stabile mercury forms in soil and their inflow to the southern Baltic Sea
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Temporal Satellite Images in The Process of Automatic Efficient Detection of Changes of the Baltic Sea Coastal Zone
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Rapid Yield Optimization of Miniaturized Microwave Passives by Response Features and Variable-Fidelity EM Simulations
PublicationThe operation of high-frequency devices, including microwave passive components, can be impaired by fabrication tolerances but also incomplete knowledge concerning operating conditions (temperature, input power levels) and material parameters (e.g., substrate permittivity). Although the accuracy of manufacturing processes is always limited, the effects of parameter deviations can be accounted for in advance at the design phase...
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Experimental study of the multi-disc negative brake for a hydraulic motor
PublicationThis paper describes the methodology for experimental testing of a multi-disc brake. The construction of this brake was also present. The brake is dedicated to hydraulic motors with a small working volume. Experimental tests were carried out on a brake with plates immersed in oil and, for comparison, tests were carried out on a dry brake. As a result of the tests, the permissible torque (load) that is able to transfer the brake...
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Pareto Ranking Bisection Algorithm for Expedited Multi-Objective Optimization of Antenna Structures
PublicationThe purpose of this letter is introduction of a novel methodology for expedited multi-objective design of antenna structures. The key component of the presented approach is fast identification of the initial representation of the Pareto front (i.e., a set of design representing the best possible trade-offs between conflicting objectives) using a Pareto-ranking bisection algorithm. The algorithm finds a discrete set of Pareto-optimal...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Adapting a General Tool to Monitoring Multi-Agent Systems Through Virtual Host Layer Extenstion
PublicationNagios is a free software for IT infrastructure monitoring. Out-of-the-box it is not suited for monitoring multi-agent systems, because agents may dynamically join and leave the system or change roles. But Nagios' flexible configuration makes extensions possible. This paper presents and verifies Nagios configuration and extensions for monitoring multi-agent systems.
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Surface sliding in human abdominal wall numerical models: Comparison of single-surface and multi-surface composites
PublicationDetermining mechanical properties of abdominal soft tissues requires a coupled experimental-numerical study, but first an appropriate numerical model needs to be built. Precise modeling of human abdominal wall mechanics is difficult because of its complicated multi-layer composition and large variation between specimens. There are several approaches concerning simplification of numerical models, but it is unclear how far one could...
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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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Multi-level Virtualization and Its Impact on System Performance in Cloud Computing
PublicationThe results of benchmarking tests of multi-level virtualized environments are presented. There is analysed the performance impact of hardware virtualization, container-type isolation and programming level abstraction. The comparison is made on the basis of a proposed score metric that allows you to compare different aspects of performance. There is general performance (CPU and memory), networking, disk operations and application-like...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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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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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublicationPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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Rapid multi-criterial design of microwave components with robustness analysis by means of knowledge-based surrogates
PublicationManufacturing tolerances and uncertainties concerning material parameters, e.g., operating conditions or substrate permittivity are detrimental to characteristics of microwave components. The knowledge of relations between acceptable parameter deviations (not leading to violation of design specifications) and the nominal performance (not considering uncertainties), and is therefore indispensable. This paper proposes a multi-objective...
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Multi-Taper-Based Automatic Correction of Non-Anechoic Antenna Measurements
PublicationPrototype measurements belong to the key steps in the development of antenna structures. Although accurate validation of their far-field performance can be realized in dedicated facilities, such as anechoic chambers, the high cost of their construction and maintenance might not be justified if the main goal of measurements is to support teaching or low-budget research. Instead, they can be performed in non-anechoic conditions and...
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Efficient Multi-Objective Simulation-Driven Antenna Design Using Co-Kriging
PublicationA methodology for fast multi-objective antenna optimization is presented. Our approach is based on response surface approximation (RSA) modeling and variable-fidelity electromagnetic (EM) simulations. In the design process, a computationally cheap RSA surrogate model constructed from sampled coarse-discretization EM antenna simulations is optimized using a multi-objective evolutionary algorithm. The initially determined Pareto...
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Multi-domain and Context-Aware Recommendations Using Contextual Ontological User Profile
PublicationRecommender Systems (RS) became popular tools in many Web services like Netflix, Amazon, or YouTube, because they help a~user to avoid an information overload problem. One of the types of RS are Context-Aware RS (CARS) which exploit contextual information to provide more adequate recommendations. Cross-Domain RS (CDRS) were created as a response to the data sparsity problem which occurs when only few users can provide reviews or...
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Comparison of Single and Multi-Population Evolutionary Algorithm for Path Planning in Navigation Situation
PublicationIn this paper a comparison of single and multi-population evolutionary algorithm is presented. Tested algorithms are used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. Principle of operation of single-population and multi-population evolutionary algorithm is described....