Filters
total: 11488
filtered: 9010
-
Catalog
- Publications 9010 available results
- Journals 344 available results
- Conferences 129 available results
- Publishing Houses 1 available results
- People 263 available results
- Projects 21 available results
- Laboratories 1 available results
- Research Teams 1 available results
- Research Equipment 2 available results
- e-Learning Courses 296 available results
- Events 16 available results
- Open Research Data 1404 available results
Chosen catalog filters
displaying 1000 best results Help
Search results for: FACIAL RECOGNITION, DROWSINESS, REAL-TIME MONITORING, MACHINE LEARNING, NEURAL NETWORKS, DRIVER, FATIGUE
-
A new optimal algorithm for a time-dependent scheduling problem
PublicationIn this article a single machine time-dependent scheduling problem with total completion time criterion is considered. There are n given jobs j_1, ..., j_n and the processing time pi of the i-th job is given by p_i = 1 + b_is_i, where si is the starting time of the i-th job, i = 1, ..., n. If all jobs have different and non-zero deterioration rates and bi > bj => bi >= (b_min+1)/(b_min) b_j + 1/b_min, where b_min = min{b_i}, then...
-
Model of distributed learning objects repository for a heterogenic internet environment
PublicationW artykule wprowadzono pojęcie komponentu edukacyjnego jako rozszerzenie obiektu edukacyjnego o elementy zachowania (metody). Zaproponowane podejście jest zgodne z paradygmatem obiektowym. W oparciu o komponent edukacyjny zaprojektowano model budowy repozytorium materiałów edukacyjnych. Model ten jest oparty o usługi sieciowe i rejestry UDDI. Komponent edukacyjny oraz model repozytorium mogą znaleźć zastosowanie w konstrukcji zbiorów...
-
Fatigue fracture surface metrology of thin-walled tubular austenitic steel specimens after asynchronous loadings
PublicationThis paper aims to study the effect of asynchronous axial-torsional strain-controlled loading histories on fracture surface behavior of thin-walled tubular X5CrNi18-10 (304/304L) austenitic steel specimens. Tests under pure axial loading and pure torsional loading are also conducted to better segregate the effect of multiaxiality. The fractures surface topographies were examined through the profiles over the entire surface with...
-
On the use of uniaxial one-parameter damage laws for estimating fatigue life under multiaxial loading
PublicationThe goal of this paper is to evaluate the capabilities of different one-parameter fatigue laws to estimate crack initiation in notched components under multiaxial loading. Fatigue damage is accounted for through stress-based, strain-based, and energy-based approaches while the cyclic plasticity at the notch-controlled process zone is estimated using linear-elastic simulations. The results show that energy-based formulations established...
-
The searchlight problem for road networks
PublicationWe consider the problem of searching for a mobile intruder hiding in a road network given as the union of two or more lines, or two or more line segments, in the plane. Some of the intersections of the road network are occupied by stationary guards equipped with a number of searchlights, each of which can emit a single ray of light in any direction along the lines (or line segments) it is on. The goal is to detect the intruder,...
-
AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
-
MODEL FOR MEASUREMENT OF FLOW INSTALLATION TIME IN SDN SWITCH
PublicationSDN is the approach in telecommunication networks that separates control plane from data forwarding plane by specifying a single network entity as a controller that defines rules (called flows) of traffic forwarding for the switches connected to it. The time that is required for installation of these rules might be a hindrance for the overall performance of SDN network. In the paper, a model for testing and evaluating the influence...
-
A Survey of Fast-Recovery Mechanisms in Packet-Switched Networks
PublicationIn order to meet their stringent dependability requirements, most modern packet-switched communication networks support fast-recovery mechanisms in the data plane. While reactions to failures in the data plane can be significantly faster compared to control plane mechanisms, implementing fast recovery in the data plane is challenging, and has recently received much attention in the literature. This survey presents a systematic,...
-
Fatigue of the ship structure.
PublicationZaprezentowano wyniki prac badawczych zachowania paneli SANDWICH pod obciążeniem zginającym. Prace prowadzone były w Kat. Technol. Okrętów i Obiektów Oceanotechn. Wydz. OiO i obejmowały między innymi badania konstrukcji w skali rzeczywistej. Dokonano porównania uzyskanych rezultatów z wynikami prezentowanymi w literaturze.
-
Application of the Flipped Learning Methodology at a Business Process Modelling Course – A Case Study
PublicationFlipped learning has been known for a long time, but its modern use dates back to 2012, with the publication of Bergmann and Saams. In the last decade, it has become an increasingly popular learning method. Every year, the number of publications on implementing flipped learning experiments is growing, just as the amount of research on the effectiveness of this educational method. The aim of the article is to analyze the possibilities...
-
Rearrangeability in multicast Clos networks is NP-complete
PublicationPrzestrajalność w polach Closa z połączeniami jeden do jeden jest problemem wielomianowym. W pracy pokazano, że w polach z połączeniami jeden do wiele problem ten jest NP zupełny.Three-stage elos networks are commutation networks with circuit switching. So far, graph theory has been very useful tool for solving issues related to these networks with unicast connections. This is so because if elos network is represented as a bipartite...
-
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...
-
The impact of surface slope and calculation resolution on the fractal dimension for fractures of steels after bending-torsion fatigue
PublicationThe article presents the results of the fractal dimension measurements on the fatigue fracture surfaces of 10HNAP and S355J2 steels specimens after combined bending-torsion fatigue. For smooth and ring-notched specimens, three loading conditions were analyzed: (1) bending; (2) bending-torsion; and (3) torsion fatigue. Post-failure surface topography measurements were carried out on the entire fracture surfaces using an optical...
-
Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublicationThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
-
On practical application of Shannon theory to character recognition and more
PublicationLet us consider an optical character recognition system, which in particular can be used for identifying objects that were assigned strings of some length. The system is not perfect, for example, it sometimes recognizes wrongly the characters "Y" and "V". What is the largest set of strings of given length for the system under consideration, which can be mutually correctly recognized, and the corresponding objects correctly identified?...
-
Machine-aided detection of SARS-CoV-2 from complete blood count
PublicationThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
-
Molecular Recognition in Complexes of TRF Proteins with Telomeric DNA
PublicationTelomeres are specialized nucleoprotein assemblies that protect the ends of linear chromosomes. In humans and many other species, telomeres consist of tandem TTAGGG repeats bound by a protein complex known as shelterin that remodels telomeric DNA into a protective loop structure and regulates telomere homeostasis. Shelterin recognizes telomeric repeats through its two major components known as Telomere Repeat-Binding Factors, TRF1...
-
Cooperative Data Transmission in Wireless Vehicular Networks
PublicationThe paper presents issues related to the cooperative transmission in wireless vehicular networks. Cooperative transmission involves the use of mobile terminals as relay stations to improve the transmission quality, improve network performance and reduce energy consumption. The paper presents the methods used to implement cooperative transmission and the types of cooperative networks.
-
Blended-learning w nauczaniu przedmiotów nieinformatycznych
PublicationBlended-learning jest coraz powszechniej wykorzystywany w nauczaniu przedmiotów informatycznych lub innych przedmiotów, w których ćwiczenia realizowane są w laboratoriach komputerowych. W przypadku przedmiotów bez dostępu do sal komputerowych, blended-learning wspomaga prowadzenie wykładów i ćwiczeń poprzez np. lekcje interaktywne. Artykuł opisuje zastosowanie form blended-learning w realizacji laboratoriów z przedmiotu Bezpieczeństwo...
-
Fractographic-fractal dimension correlation with crack initiation and fatigue life for notched aluminium alloys under bending load
PublicationIn this study, fatigue fracture surfaces of aluminium alloy 2017-T4 notched specimens were investigated under cyclic bending to find an alternative failure loading index.. The surface topographies were measured on the entire fracture area with an optical profilometer for different loading conditions. Fatigue crack initiation life Ni and total fatigue life Nf were examined using standard surface topography parameters (such as, root...
-
Swapping Space for Time: An Alternative to Time-Domain Interferometry
PublicationYoung's double-slit experiment [1] requires two waves produced simultaneously at two different points in space. In quantum mechanics the waves correspond to a single quantum object, even as complex as a big molecule. An interference is present as long as one cannot tell for sure which slit is chosen by the object. The more we know about the path, the worse the interference. In the paper we show that quantum mechanics allows for...
-
Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublicationThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
-
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...
-
Damage Detection Strategies in Structural Health Monitoring of Overhead Power Transmission System
PublicationOverhead power transmission lines, their supporting towers, insulators and other elements create a highly distributed system that is vulnerable to damage. Typical damage scenarios cover cracking of foundation, breakage of insulators, loosening of rivets, as well as cracking and breakage of lines. Such scenarios may result from various factors: groundings, lightning strikes, floods, earthquakes, aeolian vibrations, conductors galloping,...
-
Deep convolutional neural network for predicting kidney tumour malignancy
PublicationPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
-
Transfer learning in imagined speech EEG-based BCIs
PublicationThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
-
Total Completion Time Minimization for Scheduling with Incompatibility Cliques
PublicationThis paper considers parallel machine scheduling with incompatibilities between jobs. The jobs form a graph equivalent to a collection of disjoint cliques. No two jobs in a clique are allowed to be assigned to the same machine. Scheduling with incompatibilities between jobs represents a well-established line of research in scheduling theory and the case of disjoint cliques has received increasing attention in recent...
-
Discrete-time estimation of nonlinear continuous-time stochastic systems
PublicationIn this paper we consider the problem of state estimation of a dynamic system whose evolution is described by a nonlinear continuous-time stochastic model. We also assume that the system is observed by a sensor in discrete-time moments. To perform state estimation using uncertain discrete-time data, the system model needs to be discretized. We compare two methods of discretization. The first method uses the classical forward Euler...
-
Discrete-time estimation of nonlinear continuous-time stochastic systems
PublicationIn this paper we consider the problem of state estimation of a dynamic system whose evolution is described by a nonlinear continuous-time stochastic model. We also assume that the system is observed by a sensor in discrete-time moments. To perform state estimation using uncertain discrete-time data, the system model needs to be discretized. We compare two methods of discretization. The first method uses the classical forward Euler...
-
Theoretical modelling of efficient fire safety water networks by certified domination
PublicationThis paper explores a new way of designing water supply networks for fire safety using ideas from graph theory, focusing on a method called certified domination. Ensuring a good water supply is crucial for fire safety in communities, this study looks at the rules and problems in Poland for how much water is needed to fight fires in different areas and how this can be achieved at a lowest possible cost. We present a way to plan...
-
Optimization of Wireless Networks for Resilience to Adverse Weather Conditions
PublicationIn this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical...
-
Bimodal deep learning model for subjectively enhanced emotion classification in films
PublicationThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
-
Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublicationGlobal sensitivity analysis (GSA) is a method to quantify the effect of the input parameters on outputs of physics-based systems. Performing GSA can be challenging due to the combined effect of the high computational cost of each individual physics-based model, a large number of input parameters, and the need to perform repetitive model evaluations. To reduce this cost, neural networks (NNs) are used to replace the expensive physics-based...
-
The real alternative? A comparison of German real estate returns with bonds and stocks
Publication -
Developing a Low SNR Resistant, Text Independent Speaker Recognition System for Intercom Solutions - A Case Study
PublicationThis article presents a case study on the development of a biometric voice verification system for an intercom solution, utilizing the DeepSpeaker neural network architecture. Despite the variety of solutions available in the literature, there is a noted lack of evaluations for "text-independent" systems under real conditions and with varying distances between the speaker and the microphone. This article aims to bridge this gap....
-
Selecting wells for an optimal design of groundwater monitoring network based on monitoring priority map: A Kish Island case study
PublicationThis paper presents a novel approach, i.e. a combination of gamma test and monitoring priority map, for optimal design of groundwater monitoring network (GMN) by considering the cumulative effects of industries, human activities, and natural factors on the groundwater quality. The proposed method was successfully applied to design an optimal network for groundwater salinity monitoring on Kish Island, Persian Gulf. The priority...
-
MagMax: Leveraging Model Merging for Seamless Continual Learning
PublicationThis paper introduces a continual learning approach named MagMax, which utilizes model merging to enable large pre-trained models to continuously learn from new data without forgetting previously acquired knowledge. Distinct from traditional continual learning methods that aim to reduce forgetting during task training, MagMax combines sequential fine-tuning with a maximum magnitude weight selection for effective knowledge integration...
-
THE METHODS OF TEACHING / LEARNING STRUCTURAL MECHANICS
PublicationStructural mechanics is a key issue to study for engineers. A high rank and high social responsibility profession requires both a high graded and intuitive approach. The evolution of learning / teaching methodology follows the novel technical achievements of every decade. The aim remains the same: to produce a professional to perform advanced relevant analysis and safe, optimal structural design
-
Survival time prognosis under a Markov model of cancer development
PublicationIn this study we look at a breast cancer data set of women from Pomerania region collected in year 1987-1992 in the Medical University of Gdańsk. We analyze the clinical risk factors in conjunction with Markov model of cancer development. We evaluate Artificial Neural Network (ANN) survival time prediction via a simulation study.
-
Advanced fatigue and rutting characterisation of Polish asphalt mixtures based on the VECD model and viscoplastic shift model
PublicationThe advanced asphalt mixture performance-related specifications (AM-PRS) recently developed in USA can allow an optimisation of the design process of asphalt pavements thanks to the possibility to fully take into account the intrinsic material properties. In this study, four typical Polish mixtures, i.e. a Stone Mastic Asphalt (SMA) for wearing course, two mixtures for binder course with neat bitumen or Polymer modified Bitumen...
-
Automatic recognition of therapy progress among children with autism
PublicationThe article presents a research study on recognizing therapy progress among children with autism spectrum disorder. The progress is recognized on the basis of behavioural data gathered via five specially designed tablet games. Over 180 distinct parameters are calculated on the basis of raw data delivered via the game flow and tablet sensors - i.e. touch screen, accelerometer and gyroscope. The results obtained confirm the possibility...
-
A comparative study of English viseme recognition methods and algorithms
PublicationAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector construction...
-
A comparative study of English viseme recognition methods and algorithm
PublicationAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector...
-
Computation of cubical homology, cohomology, and (co)homological operations via chain contraction
Publication -
Fracture evolution in concrete compressive fatigue experiments based on X-ray micro-CT images
PublicationArtykuł omawia ewolucje pękania w betonie podczas cyklicznego ściskania betonu. Przestrzenną ewolucję pękania zobrazowano stosując mikro-tomograf rentgenowski. Zdjęcia wykonano dla różnych cykli zmęczeniowych. Wyniki porównano z testami monotonicznymi. Jakościowa ewolucja objętości pękania ze wzrostem zmęczeniowego zniszczenia pokazała silnie nieliniowy kształt.
-
Modeling the economic dependence between town development policy and increasing energy effectiveness with neural networks. Case study: The town of Zielona Góra
Publication -
Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using pressure distribution in blade tip clearance.
PublicationW pracy sprawdzono, czy zastosowanie sieci neuronowych umożliwia identyfikację wymuszeń powstających w wyniku funkcjonowania maszyny jak i zależnych od jej stanu mechanicznego przy zastosowaniu rozkładu ciśnienia w uszczelnieniu nadbandażowym. Przeprowadzono pomiary rozkładu ciśnienia dla różnych warunków pracy, uwzględniając zmianę mimośrodu oraz zmianę skośnego ustawienia osi wirnika względem osi korpusu. Dokonano analiz przy...
-
Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task
PublicationGOAL: Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures...
-
Statistical significance of displacements in heterogeneous control networks
PublicationThis paper proposes a modification of the classical process for evaluating the statistical significance of displacements in the case of heterogeneous (e.g. linear-angular) control networks established to deformation measurements and analysis. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal control...
-
Efficient Use of Capital: Paradox of Real Estate and Industry in Turkey
PublicationIn recent years, one of the hottest debates on Turkish economy is the conflict on resource allocation between real estate and industry sectors. The debate was so intense that ex-minister of Economy Mr. Ali Babacan declared his opinions. Mr. Babacan’s statements about the creation of fixed capital by the private sector is not promising, and private sector fixed capital expenditures are not in the desired level. This situation is...