Filters
total: 613
filtered: 558
Search results for: approximation methods, fractional calculus, modeling, neural networks, recurrent neural networks
-
Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
-
Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
-
Problems of varistor quality assessment during exploitation
PublicationVaristors are commonly used elements which protect power supply networks against high-voltage surges or lightning. Therefore, quality and endurance of these elements is important to avoid losses when an expensive laboratory equipment would not be protected from random overvoltages. Additionally, excessive leakage currents generate serious costs due to high energy consumption. The paper presents shortly properties of varistors that...
-
Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach
PublicationExperimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration,...
-
Machine Learning Techniques in Concrete Mix Design
PublicationConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
-
Switched-capacitor DC-DC converters in arbitrary switching mode - topologically derived resistive models based on incremental graph approach.
PublicationIn the preceding paper we reviewed some of modeling approaches aimed at systematic formulation and solution of switched capacitor DC-DC converters. In our review, special attention was paid to computationally efficient and mathematically elegant methods. In so doing we had tried to demonstrate the virtues of unified Incremental Graph (IG) approach. Incremental Graph is, in concept, a tool originally created for analysis and synthesis...
-
Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
-
Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
-
MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
-
A METHOD OF TRUST MANAGEMENT IN WIRELESS SENSOR NETWORKS
PublicationThe research problem considered in this paper is how to protect wireless sensor networks (WSN) against cyber-threats by applying trust management and how to strengthen network resilience to attacks targeting the trust management mechanism itself. A new method, called WSN Cooperative Trust Management Method (WCT2M), of distributed trust management in multi-layer wireless sensor networks is proposed and its performance is evaluated....
-
Customizing nano-chitosan for sustainable drug delivery
PublicationChitosan is a natural polymer with acceptable biocompatibility, biodegradability, and mechanical stability; hence, it has been widely appraised for drug and gene delivery applications. However, there has been no comprehensive assessment to tailor-make chitosan cross-linkers of various types and functionalities as well as complex chitosan-based semi- and full-interpenetrating networks for drug delivery systems (DDSs). Herein, various...
-
Improving voltage levels in low-voltage networks with distributed generation – case study
PublicationThe use of distributed generation in low-voltage networks may cause the voltage variation in them, within the wide range. In unfavourable circumstances, the voltage may reach unacceptable values. The paper presents the effect of distributed generation on voltage levels in a selected low-voltage rural distribution network in Poland. An analysis of possible methods for improving voltage levels in this network is conducted. The most...
-
Verification of the Parameterization Methods in the Context of Automatic Recognition of Sounds Related to Danger
PublicationW artykule opisano aplikację, która automatycznie wykrywa zdarzenia dźwiękowe takie jak: rozbita szyba, wystrzał, wybuch i krzyk. Opisany system składa się z bloku parametryzacji i klasyfikatora. W artykule dokonano porównania parametrów dedykowanych dla tego zastosowania oraz standardowych deskryptorów MPEG-7. Porównano też dwa klasyfikatory: Jeden oparty o Percetron (sieci neuronowe) i drugi oparty o Maszynę wektorów wspierających....
-
Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublicationResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
-
Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
-
Social media for e-learning of citizens in smart city
PublicationThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
-
Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublicationIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...
-
Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
-
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...
-
Comparative study on the effectiveness of various types of road traffic intensity detectors
PublicationVehicle detection and speed measurements are crucial tasks in traffic monitoring systems. In this work, we focus on several types of electronic sensors, operating on different physical principles in order to compare their effectiveness in real traffic conditions. Commercial solutions are based on road tubes, microwave sensors, LiDARs, and video cameras. Distributed traffic monitoring systems require a high number of monitoring...
-
The Use of an Autoencoder in the Problem of Shepherding
PublicationThis paper refers to the problem of shepherding clusters of passive agents consisting of a large number of objects by a team of active agents. The problem of shepherding and the difficulties that arise with the increasing number of data describing the location of agents have been described. Several methods for reducing the dimensionality of data are presented. Selected autoencoding method using a Restricted Boltzmann Machine is...
-
Dekodowanie kodów iterowanych z użyciem sieci neuronowej
PublicationNadmiarowe kody iterowane są jedną z prostych metod pozyskiwania długich kodów korekcyjnych zapewniających dużą ochronę przed błędami. Jednocześnie, chociaż ich podstawowy iteracyjny dekoder jest prosty koncepcyjnie oraz łatwy w implementacji, to nie jest on rozwiązaniem optymalnym. Poszukując alternatywnych rozwiązań zaproponowano, przedstawioną w pracy, strukturę dekodera tego typu kodów wspomaganą przez sieci neuronowe. Zaproponowane...
-
The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings
PublicationTraffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to...
-
RNDM 2016 Workshop and 2nd Meeting of COST CA15127-RECODIS: Highlights from the Resilience Week in Halmstad, Sweden
PublicationLeading network resilience researchers took part in the Resilience Week on Sept. 12-15, 2016 at Halmstad University, SE by Prof. Magnus Jonsson from the Centre for Research on Embedded Systems (CERES), Halmstad University, SE, and Prof. Jacek Rak from Gdansk University of Technology, PL. It included two major events: - The 2nd Meeting of COST CA15127–RECODIS Action (Resilient Communication Services Protecting End-user Applications...
-
Marine and Cosmic Inspirations for AI Algorithms
PublicationArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
-
Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublicationW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
-
Performance Evaluation of Preemption Algorithms in MPLS Networks
PublicationPreemption is a traffic engineering technique in Multiprotocol Switching Networks that enables creation of high priority paths when there is not enough free bandwidth left on the route. Challenging part of any preemption method is to select the best set of paths for removal. Several heuristic methods are available but no wider comparison had been published before. In this paper, we discuss the dilemmas in implementing preemption...
-
Projektowanie i eksploatacja dróg szynowych z wykorzystaniem mobilnych pomiarów satelitarnych
PublicationNiniejsza monografia zawiera szczegółowy opis aktywnych sieci geodezyjnych GNSS oraz modelowania dokładności określania pozycji w pomiarach satelitarnych. Omówiono również opracowaną technikę mobilnych pomiarów satelitarnych toru kolejowego oraz aplikacje związane z jej zastosowaniem w projektowaniu i eksploatacji dróg szynowych. Autorzy zawarli w pracy wyniki swoich badań, wykonywanych na przestrzeni lat 2009–2015. Badania przeprowadzono...
-
Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
-
Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
-
Comparison of centralized and decentralized preemption in MPLS networks
PublicationPreemption is one of the crucial parts of the traffic engineering in MPLS networks. It enables allocation of high-priority paths even if the bandwidth on the preferred route is exhausted. This is achieved by removing previously allocated low-priority traffic, so as enough free bandwidth becomes available. The preemption can be performed either as a centralized or a decentralized process. In this article we discuss the differences...
-
Transport of dangerous goods by rail, and threats to the subsoil of the railway surface in the event of a disaster
PublicationIn Poland, in 2020, the mass of dangerous goods (loads) transported by rail was 26 151.06 thousand tone. This translated into the performance of 8 899 691.89 thousand tone - km of transport performance. In 2020, these figures accounted for 11.72% of the weight of goods transported by rail. The situation is similar in other countries around the world. With such a large volume of transport of dangerous...
-
Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
-
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....
-
Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
-
Dynamic coloring of graphs
PublicationDynamics is an inherent feature of many real life systems so it is natural to define and investigate the properties of models that reflect their dynamic nature. Dynamic graph colorings can be naturally applied in system modeling, e.g. for scheduling threads of parallel programs, time sharing in wireless networks, session scheduling in high-speed LAN's, channel assignment in WDM optical networks as well as traffic scheduling. In...
-
Cross-layer mDNS/ARP integration for IEEE 802.11s Wireless mesh Network
PublicationPopularization of mobile computing devices created a need for robust, efficient and ubiquitous methods of communication and network access. At the same time, evolution and standardization of Wireless Local Area Network (WLAN) technologies made them an attractive solution for building of complex network systems. Moreover, growing maturity of WLAN standards such as IEEE 802.11 allows for introduction of WLAN architectures other than...
-
The analysis of tram tracks geometrical layout based on Mobile Satellite Measurements
PublicationIn this article, the results of the research in a field of which uses active global navigation satellite system (GNSS) geodetic networks for the inventory of geodetic geometric tram tracks are presented. The applied measurement technique has been adapted for the designing of the geometric layout of tram tracks. Several configurations of receivers and settings of an active GNSS networks with the objective to increase the accuracy...
-
Novel luminescent calixarene-based lanthanide materials: From synthesis and characterization to the selective detection of Fe3+
PublicationCalix[n]arene-based coordination networks are an emerging class of materials with intriguing properties resulted from the presence of the cavity-like structure of the macrocycle and metallic nodes. In this work, four novel luminescent materials based on calix[4]arene-carboxylate and lanthanides (Eu3þ and Tb3þ) were prepared by two synthetic approaches, solvothermal (CDA-Eu-ST) and slow diffusion (CDA-Eu-RT, CDA-Tb-RT, CTA-Tb-complex)...
-
Vehicle detector training with minimal supervision
PublicationRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...
-
Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublicationThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
-
Systematic Literature Review on Click Through Rate Prediction
PublicationThe ability to anticipate whether a user will click on an item is one of the most crucial aspects of operating an e-commerce business, and clickthrough rate prediction is an attempt to provide an answer to this question. Beginning with the simplest multilayer perceptrons and progressing to the most sophisticated attention networks, researchers employ a variety of methods to solve this issue. In this paper, we present the findings...
-
Mobility management solutions for current IP and future networks
PublicationEnormous progress in the design of portable electronic devices allowed them to reach a utility level comparable to desktop computers, while still retaining their mobility advantage. At the same time new multimedia services and applications are available for IP users. Unfortunately, the performance of base IP protocol is not satisfactory in mobile environments, due to lack of handover support and higher layer mobility management...
-
Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
-
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...
-
Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublicationDevelopment of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based...
-
Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates
PublicationOver the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures. Among the various techniques, approximation surrogates are the most popular ones due to their flexibility and easy access. Notwithstanding, data-driven modeling of antenna characteristics is associated with serious...
-
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...
-
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....
-
Reactivation of seizure‐related changes to interictal spike shape and synchrony during postseizure sleep in patients
PublicationOBJECTIVE: Local field potentials (LFPs) arise from synchronous activation of millions of neurons, producing seemingly consistent waveform shapes and relative synchrony across electrodes. Interictal spikes (IISs) are LFPs associated with epilepsy that are commonly used to guide surgical resection. Recently, changes in neuronal firing patterns observed in the minutes preceding seizure onset were found to be reactivated during postseizure...