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Search results for: SOFTWARE METRICS
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Psychological and physical components in forming preferences on urban greenery management – The case of trees
PublicationPublic opinion is increasingly important in managing urban greenery. In this regard, this study demonstrates the importance of sociological (environmental worldviews), psychological (place attachment, perceived benefits of trees), and physical factors (type of building people live in, and urban greenery) in forming residents’ opinions on whether the municipality or landowners should decide about tree removal on private land. Logistic...
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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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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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Analyzing Wind Energy Potential Using Efficient Global Optimization: A Case Study for the City Gdańsk in Poland
PublicationWind energy (WE), which is one of the renewable energy (RE) sources for generating electricity, has been making a significant contribution to obtaining clean and green energy in recent years. Fitting an appropriate statistical distribution to the wind speed (WS) data is crucial in analyzing and estimating WE potential. Once the best suitable statistical distribution for WS data is determined, WE potential and potential yield could...
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Mathematical approach to design 3D scaffolds for the 3D printable bone implant
PublicationThis work demonstrates that an artificial scaffold structure can be designed to exhibit mechanical properties close to the ones of real bone tissue, thus highly reducing the stress-shielding phenomenon. In this study the scan of lumbar vertebra fragment was reproduced to create a numerical 3D model (this model was called the reference bone sample). New nine 3D scaffold samples were designed and their numerical models were created....
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Dual-band Millimetre Wave MIMO Antenna with Reduced Mutual Coupling Based on Optimized Parasitic Structure and Ground Modification
PublicationIn this study, a high-isolation dual-band (28/38 GHz) multiple-input–multiple-output (MIMO) antenna for 5G millimeter-wave applications is presented. The antenna consists of two interconnected patches. The primary patch is connected to the inset feed, while the secondary patch is arc-shaped and positioned over the main patch, opposite to the feed. Both patches function in the lower 28 GHz band, while the primary patch is accountable...
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Customer Assessment of Brand Valuation and Social Media
PublicationThe research problem engaged in this article is to determine whether contemporary consumers are able to assess brand equity in the overabundance of brands and products with similar features and qualities. The author argues that in the existing circumstances when differences between brands become insignificant the consumer is not capable of assessing their equity adequately. In order to verify the thesis the author has accepted...
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Combining MUSHRA Test and Fuzzy Logic in the Evaluation of Benefits of Using Hearing Prostheses
PublicationAssessing the effectiveness of hearing aid fittings based on the benefits they provide is crucial but intricate. While objective metrics of hearing aids like gain, frequency response, and distortion are measurable, they do not directly indicate user benefits. Hearing aid performance assessment encompasses various aspects, such as compensating for hearing loss and user satisfaction. The authors suggest enhancing the widely used...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublicationThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Design and Optimization of a Compact Super-Wideband MIMO Antenna with High Isolation and Gain for 5G Applications
PublicationThis paper presents a super-wideband multiple-input multiple-output (SWB MIMO) antenna with low profile, low mutual coupling, high gain and compact size for microwave and millimeter wave (mm-wave) fifth-generation (5G) applications. A single antenna is a simple elliptical-square shape with a small physical size of 20 × 20 × 0.787 mm3. The combination of both square and elliptical shapes results in an exceptionally broad impedance...
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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...
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Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms
Publication3D printing technology is growing swiftly in the construction sector due to its numerous benefits, such as intricate designs, quicker construction, waste reduction, environmental friendliness, cost savings, and enhanced safety. Nevertheless, optimizing the concrete mix for 3D printing is a challenging task due to the numerous factors involved, requiring extensive experimentation. Therefore, this study used three machine learning...
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Screening of predicted synergistic multi-target therapies in glioblastoma identifies new treatment strategies
PublicationAbstract Background IDH-wildtype glioblastoma (GBM) is a highly malignant primary brain tumor with a median survival of 15 months after standard of care, which highlights the need for improved therapy. Personalized combination therapy has shown to be successful in many other tumor types and could be beneficial for GBM patients. Methods We performed the largest drug combination screen to date in GBM, using a high-throughput effort...
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Knowledge-based performance-driven modeling of antenna structures
PublicationThe importance of surrogate modeling techniques in the design of modern antenna systems has been continuously growing over the recent years. This phenomenon is a matter of practical necessity rather than simply a fashion. On the one hand, antenna design procedures rely on full-wave electromagnetic (EM) simulation tools. On the other hand, the computational costs incurred by repetitive EM analyses involved in solving common tasks...
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Designing acoustic scattering elements using machine learning methods
PublicationIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....