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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Synthesis Attempt and Structural Studies of Novel A2CeWO6 Double Perovskites (A2+ = Ba, Ca) in and outside of Ambient Conditions
PublicationSynthesis Attempt and Structural Studies of Novel A 2 CeWO 6 Double Perovskites (A 2+ = Ba, Ca) in and outside of Ambient Conditions Damian Wlodarczyk,* Mikolaj Amilusik, Katarzyna M. Kosyl, Maciej Chrunik, Krystyna Lawniczak-Jablonska, Michal Strankowski, Marcin Zajac, Volodymyr Tsiumra, Aneta Grochot, Anna Reszka, Andrzej Suchocki, Tomasz Giela, Przemyslaw Iwanowski, Michal Bockowski, and Hanka Przybylinska Cite This: ACS Omega...
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A framework for onboard assessment and monitoring of flooding risk due to open watertight doors for passenger ships
PublicationPost-accident safety of ships is governed by damage stability, affected by watertight subdivisions which limit accidental flooding. This is important for passenger ships with watertight doors (WTDs) often fitted in the bulkheads. Awareness of the ship flooding risk due to open WTDs and the conditions under which the associated risk level changes are prerequisites for proactive risk mitigation. Accident risk is often expressed as...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Enabling Deeper Linguistic-based Text Analytics – Construct Development for the Criticality of Negative Service Experience
PublicationSignificant progress has been made in linguistic-based text analytics particularly with the increasing availability of data and deep learning computational models for more accurate opinion analysis and domain-specific entity recognition. In understanding customer service experience from texts, analysis of sentiments associated with different stages of the service lifecycle is a useful starting point. However, when richer insights...
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublicationModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Effect of rPET Content and Preform Heating/Cooling Conditions in the Stretch Blow Molding Process on Microcavitation and Solid-State Post-Condensation of vPET-rPET Blend: Part II—Statistical Analysis and Interpretation of Tests
PublicationThis research explores how varying proportions of virgin polyethylene terephthalate (vPET) and recycled polyethylene terephthalate (rPET) in vPET-rPET blends, combined with preform thermal conditions during the stretch blow molding (SBM) process, influence PET bottles’ microscopic characteristics. Key metrics such as viscosity, density, crystallinity, amorphous phase relaxation, and microcavitation were assessed using response...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublicationHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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NEW SOLUTIONS FOR THE SOLAR CHARGE CONTROLLERS DESIGN FOR OBTAINING TRUE MPP IN PARTLY SHADED PV MODULES
PublicationSoft shading sources such as tree limbs, structural elements of buildings and chimneys, scatter and refract sunlight, significantly reducing the amount of radiation reaching the surface of the module. The hard shadings located directly on the surface (i.e. bird droppings, leaves, snow) tend to stop sunlight completely. These phenomena significantly affects the output characteristics of photovoltaic modules and often contribute...
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Non-isolating bondage in graphs
PublicationA dominating set of a graph $G = (V,E)$ is a set $D$ of vertices of $G$ such that every vertex of $V(G) \setminus D$ has a neighbor in $D$. The domination number of a graph $G$, denoted by $\gamma(G)$, is the minimum cardinality of a dominating set of $G$. The non-isolating bondage number of $G$, denoted by $b'(G)$, is the minimum cardinality among all sets of edges $E' \subseteq E$ such that $\delta(G-E') \ge 1$ and $\gamma(G-E')...
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Non-isolating 2-bondage in graphs
PublicationA 2-dominating set of a graph G=(V,E) is a set D of vertices of G such that every vertex of V(G)D has at least two neighbors in D. The 2-domination number of a graph G, denoted by gamma_2(G), is the minimum cardinality of a 2-dominating set of G. The non-isolating 2-bondage number of G, denoted by b_2'(G), is the minimum cardinality among all sets of edges E' subseteq E such that delta(G-E') >= 1 and gamma_2(G-E') > gamma_2(G)....
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Constant-Factor Approximation Algorithm for Binary Search in Trees with Monotonic Query Times
PublicationWe consider a generalization of binary search in linear orders to the domain of weighted trees. The goal is to design an adaptive search strategy whose aim is to locate an unknown target vertex of a given tree. Each query to a vertex v incurs a non-negative cost ω(v) (that can be interpreted as the duration of the query) and returns a feedback that either v is the target or the edge incident to v is given that is on the path towards...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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A risk comparison framework for autonomous ships navigation
PublicationMaritime autonomous surface ships (MASS) may operate in three predefined operational modes (OM): manual, remote, or autonomous control. Determining the appropriate OM for MASS is important for operators and competent authorities that monitor and regulate maritime traffic in given areas. However, a science-based approach to this respect is currently unavailable. To assist the selection of the proper OM, this study presents a risk-based...
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Measuring the effectiveness of digital communication - social media performance: an example of the role played by AI-assisted tools at a university
PublicationThe aim of the article is to show the role played by AI-powered tools in measuring the effectiveness of digital communication in social media using a university case study. Therefore, a research problem was formulated to identify the metrics (KPIs) used to measure the effectiveness – non-financial outcomes – of digital social media communication at the university using AI tools. The literature review on the role of AI in digital...
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Blue applicability grade index (BAGI) and software: a new tool for the evaluation of method practicality
PublicationIn this work, blue applicability grade index (BAGI) is proposed as a new metric tool for evaluating the practicality of an analytical method. BAGI can be considered complementary to the well-established green metrics, and it is mainly focused on the practical aspects of White Analytical Chemistry. This tool evaluates ten main attributes including the type of analysis, the number of analytes that are simultaneously determined, the...
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Creating new voices using normalizing flows
PublicationCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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A survey of automatic speech recognition deep models performance for Polish medical terms
PublicationAmong the numerous applications of speech-to-text technology is the support of documentation created by medical personnel. There are many available speech recognition systems for doctors. Their effectiveness in languages such as Polish should be verified. In connection with our project in this field, we decided to check how well the popular speech recognition systems work, employing models trained for the general Polish language....
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Pawlak's flow graph extensions for video surveillance systems
PublicationThe idea of the Pawlak's flow graphs is applicable to many problems in various fields related to decision algorithms or data mining. The flow graphs can be used also in the video surveillance systems. Especially in distributed multi-camera systems which are problematic to be handled by human operators because of their limited perception. In such systems automated video analysis needs to be implemented. Important part of this analysis...
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Investigation of Continuous Wave Jamming in an IEEE 802.15.4 Network
PublicationThis paper presents how continuous wave jamming affects IEEE 802.15.4 network. To this end, an office-based measurement setup has been proposed. Within the measurement area, 25 nodes have been set up in order to create a IEEE 802.15.4 tree-based test network structure. A dedicated jamming device that generates and transmits a continuous wave signal has been developed. Several tests have been conducted and presented to demonstrate...
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Enhancing Availability for Critical Services
PublicationTraditional approaches to provide classes of resilient service take the physical network availability as an input and then deploy redundancy and restoration techniques at various layers, often without full knowledge of mappings between layers. This makes it hard (and often inefficient) to ensure the high availability required by critical services which are typically a small fraction of the total traffic. Here, the innovative technique...
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Privacy-Preserving, Scalable Blockchain-Based Solution for Monitoring Industrial Infrastructure in the Near Real-Time
PublicationThis paper proposes an improved monitoring and measuring system dedicated to industrial infrastructure. Our model achieves security of data by incorporating cryptographical methods and near real-time access by the use of virtual tree structure over records. The currently available blockchain networks are not very well adapted to tasks related to the continuous monitoring of the parameters of industrial installations. In the database...
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A Simplified SVPWM Technique for Five-leg Inverter with Dual Three-phase Output
PublicationThis article proposes a simplified space vector pulse-width modulation (SVPWM) technique five-leg inverter with dual three-phase output. An idea to fed the dual tree-phase machine by the multiphase voltage source inverters (VSIs) is not new. Dual- and multi-motor drive systems are widely used in the industry applications. The most popular fields are: electric vehicles (EVs) and traction systems. Moreover, the specific characteristic...
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Analysis of IMS/NGN call processing performance using phase-type distributions
PublicationThis work is a continuation of our research on the traffic model dedicated for design and analysis of the Next Generation Network (NGN), which is standardized for distribution of current and future multimedia services based on the IP Multimedia Subsystem (IMS). Our analytical and simulation models allow evaluation of mean Call Set-up Delay E(CSD) as well as mean Call Disengagement Delay E(CDD) in a single domain of IMS/NGN. Ensuring...
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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...
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Daylight evaluation for multi-family housing in Poland
PublicationThis PhD dissertation focuses on methods of daylight appraisal useful in the design of the contemporary multifamily housing. The theoretical part of the thesis offers a review of daylight indicators, evaluations methods and tools within the built environment. It covers a review of daylight recommendations found in building standards and other normative documents affecting the design of the residential spaces. A pilot work survey...
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Relationship between album cover design and music genres.
PublicationThe aim of the study is to find out whether there exists a relationship between typographic, compositional and coloristic elements of the music album cover design and music contained in the album. The research study involves basic statistical analysis of the manually extracted data coming from the worldwide album covers. The samples represent 34 different music genres, coming from nine countries from around the world. There are...
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Domain adaptation for inpainting-based face recognition studies
PublicationRecent inpainting methods have demonstrated im-pressive outcomes in filling missing parts of images, especially for reconstructing facial areas obscured by occlusions. However, studies show that these models are not adequately effective in real-world applications, primarily due to data bias and the distribution of faces in images. This research focuses on domain adaptation of the commonly used Labeled Faces in the Wild (LFW) dataset,...
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Quality Evaluation of Speech Transmission via Two-way BPL-PLC Voice Communication System in an Underground Mine
PublicationIn order to design a stable and reliable voice communication system, it is essential to know how many resources are necessary for conveying quality content. These parameters may include objective quality of service (QoS) metrics, such as: available bandwidth, bit error rate (BER), delay, latency as well as subjective quality of experience (QoE) related to user expectations. QoE is expressed as clarity of speech and the ability...
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublicationSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Using Continuous Integration Techniques in Open Source Projects – An Exploratory Study
PublicationFor a growing number of software projects, continuous integration (CI) techniques are becoming an essential part of the process. However, the maturity of their adoption in open source projects varies. In this paper, we present an empirical study on GitHub repositories to explore the use of continuous integration techniques in open source projects. Following the Goal-Question-Metric (GQM) approach, 3 research questions and 7 metrics...
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Adsorptive Removal of Aqueous Phase Crystal Violet Dye by Low-Cost Activated Carbon Obtained from Date Palm (L.) Dead Leaflets
PublicationUp to now, water pollution is still one of the important issues and challenges worldwide, due to its environmental, economic and human life impacts. It is also remains a challenge to environment scientists and technologists. Nowadays, the textile dyeing industry is considered one of the largest water consuming industries and produces large volumes of colored wastewater in its dyeing and finishing process. In this study, date palm...
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SORPTION OF SELECTED CHLORINATED SOLVENTS ON PLANT DEBRIS COLLECTED IN A CITY PARK
PublicationDebris from deciduous trees in the form of park green waste was investigated as a potential biosorbent for the removal of chlorinated solvents from water. The sorption properties of beech leaves and cupules, oak leaves and acorns, birch leaves and lime leaves (all tree species common for a moderate climate) in a non-modified form were investigated with regard to the removal of perchloroethylene, 1,1,2-trichloroethane and 1,1,1,2-tetrachlorothane....
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Simulator for Performance Evaluation of ASON/GMPLS Network
PublicationThe hierarchical control plane network architecture of Automatically Switched Optical Network with utilization of Generalized Multi-Protocol Label Switching protocols is compliant to next generation networks requirements and can supply connections with required quality of service, even with incomplete domain information. Considering connection control, connection management and network management, the controllers of this architecture...
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Normalized Partial Scattering Cross Section for Performance Evaluation of Low-Observability Scattering Structures
PublicationThe development of diffusion metasurfaces created new opportunities to elevate the stealthiness of combat aircraft. Despite the potential significance of metasurfaces, their rigorous design methodologies are still lacking, especially in the context of meticulous control over the scattering of electromagnetic (EM) waves through geometry parameter tuning. Another practical issue is insufficiency of the existing performance metrics,...
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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...
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Open extensive IoT research and measurement infrastructure for remote collection and automatic analysis of environmental data.
PublicationInternet of Things devices that send small amounts of data do not need high bit rates as it is the range that is more crucial for them. The use of popular, unlicensed 2.4 GHz and 5 GHz bands is fairly legally enforced (transmission power above power limits cannot be increased). In addition, waves of this length are very diffiult to propagate under field conditions (e.g. in urban areas). The market response to these needs are the...
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Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review
PublicationThe segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...
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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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Light4Health eLearning Course: health research for interior lighting design. Re-thinking design approaches based on science
PublicationThis paper presents the results of 'Light4Health' (L4H), a three-year EU Erasmus+ Strategic Partnership grant project (2019-2021), which investigated, systematized and taught health-related research on the impact of natural and artificial light on human health and well-being relevant to indoor lighting design. The objective was to re-think evidence-based lighting design approaches for residential, working/educational, and healthcare...
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Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublicationFabrication tolerances and other types of uncertainties, e.g., the lack of precise knowledge of material parameters, have detrimental effects on electrical and field performance of antenna systems. In the case of input characteristics these are particularly noticeable for narrow- and multi-band antennas where deviations of geometry parameters from their nominal values lead to frequency shifts of the operating frequency bands. Improving...
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Optimizing Control of Wastewater Treatment Plant With Reinforcement Learning: Technical Evaluation of Twin-Delayed Deep Deterministic Policy Gradient Agent
PublicationControl of the wastewater treatment processes presents significant challenges due to the fluctuating nature of inflow and wastewater composition, alongside the system’s non-linear dynamics. Traditional control methods struggle to adapt to these variations, leading to an economically suboptimal operation of the process and a violation of norms imposed on the quality of wastewater discharged to the catchment area. This study proposes...
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A Survey on the Datasets and Algorithms for Satellite Data Applications
PublicationThis survey compiles insights and describes datasets and algorithms for applications based on remote sensing. The goal of this review is twofold: datasets review for particular groups of tasks and high-level steps of data flow between satellite instruments and end applications from an implementation and development perspective. The article outlines the generalized data processing pipelines, taking into account the variations in...
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Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublicationAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
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MutS3: a MutS homologue of unknown biological function
PublicationThe homologues of MutS proteins are widespread among both Prokaryotes and Eukaryotes. MutS designated as MutS1 is a part of MMR (mismatch repair) system which is responsible for removal of mispaired bases and small insertion/deletion loops in DNA. Initially, the only MutS homologues known were those engaged in mismatch repair and these were later designated as MutS1. Subsequently, the MutS2 homologue was distinguished. MutS2 does...
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Reconstruction of 3D image of corona discharge streamer
PublicationIn this paper, the method of reconstruction of the 3D structure of streamers in DC positive corona discharge in nozzle-to-plate electrode configuration is presented. For reconstructing of 3D image of corona discharge streamer we propose a stereographical method, where streamers are observed from several directions simultaneously. The multi-directional observation enabled to obtain fine positional coordinates of streamers for a...