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Wyniki wyszukiwania dla: BIG DATA DEEP LEARNING REMOTE MEDICAL DIAGNOSTIC
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Phylogenetic relationship and antimicrobial resistance in Escherichia coli isolated from the Reda River and the Oliwski Stream, Northern Poland = Lekooporność i przynależność filogenetyczna szczepów Escherichia Coli izolowanych z rzeki Redy i Potoku Oliwskiego
PublikacjaThe high abundance of fecal bacteria in surface water is usually related to poor agricultural practice, pollution caused by domesticated and wild animals as well as with septic tank failures. Identification of fecal contamination sources seems to be crucial in order to effectively estimate the inherent risk. In this study, the phylogenetic relationship of 30 isolates of E. coli, originated from surface water, was estimated by employing...
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Embedded system using Bluetooth Low Energy sensors for smart farming applications
PublikacjaThe main goal of this Bachelor of Engineering project titled Embedded system using Bluetooth Low Energy sensors for smart farming applications is to create a prototype of a system consistent with Agriculture 4.0 concept using Bluetooth Low Energy (BLE) technology. Developed solution shall be easy in implementation and its main functionality shall be periodic gathering of data from environmental sensors...
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Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit
PublikacjaThe general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublikacjaModern 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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METHODS OF TEACHING NOISE PROTECTION AT ENVIRONMENTAL ENGINEERING
PublikacjaNoise strongly influences both our health and behavior in everyday life and as employees or employers. The lost of hearing and other effects of noise on humans result not only in a significant decrease in the quality of life or work efficiency but have also have economic consequences. As noise can be preventable in part by the Environmental Engineers, but it is necessary to introduce them noise issues during their education process....
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Why do Open Government Data initiatives fail in developing countries? A root cause analysis of the most prevalent barriers and problems
PublikacjaOpen government data (OGD) include the provision of government data, which have so far been reserved for the provision of public utilities and services, wherein different stakeholders may create value out of the same source. Recently, OGD initiatives around the world have dampened or were found to be inadequate for one or other reasons. The present study seeks to underline the root causes behind these inadequate or stalled initiatives...
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Visual Attention Distribution Based Assessment of User's Skill in Electronic Medical Record Navigation
PublikacjaCurrently, the most precise way of reflecting the skills level is an expert’s subjective assessment. In this paper we investigate the possibility of the use of eye tracking data for scalar quantitative and objective assessment of medical staff competency in EMR system navigation. According to the experiment conducted by Yarbus the observation process of particular features is associated with thinking. Moreover, eye tracking is...
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Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility
PublikacjaSolubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived...
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An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
PublikacjaAn innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Influence of algorithmic management practices on workplace well-being – evidence from European organisations
PublikacjaPurpose Existing literature on algorithmic management practices –defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice...
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Algorithmic Human Resources Management
PublikacjaThe rapid evolution of Digital Human Resources Management has introduced a transformative era where algorithms play a pivotal role in reshaping the landscape of workforce management. This transformation is encapsulated in the concepts of algorithmic management and algorithmic Human Resource Management (HRM). The integration of advanced analytics, predictive and prescriptive analytics and the power of Artificial Intelligence (AI)...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Integrating Digital Twin Technology Into Large Panel System Estates Retrofit Projects
PublikacjaAs sustainability is now a standard for the proposed developments, the focus ought to be shifted towards the existing buildings and, among them, the worldwide stock of large panel system (LPS) buildings. Major upgrades and retrofits were done to some of the LPS estates in Germany and France, but a leading sustainable way must still be developed for LPS buildings in Eastern European countries, where apartments in those half‐a‐century‐old...
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Importance of Bile Composition for Diagnosis of Biliary Obstructions
PublikacjaDetermination of the cause of a biliary obstruction is often inconclusive from serum analysis alone without further clinical tests. To this end, serum markers as well as the composition of bile of 74 patients with biliary obstructions were determined to improve the diagnoses. The samples were collected from the patients during an endoscopic retrograde cholangiopancreatography (ERCP). The concentration of eight bile salts, specifically...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublikacjaLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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Desirability-based optimization of dual-fuel diesel engine using acetylene as an alternative fuel
Publikacjahe study examined the dual-fuel engine performance employing acetylene gas as primary fuel and diesel as pilot fuel. The engine's operational parameters were adjusted using the Box-Behnken design, and the results were recorded. The best operating settings were yielded as 81.25 % engine load, 4.48 lpm acetylene gas flow rate and the compression ratio were 18. At this optimized setting the BTE was 27.1 % and the engine emitted 360...
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Storm petrels as indicators of pelagic seabird exposure to chemical elements in the Antarctic marine ecosystem
PublikacjaData on trace element bioavailability in the south-polar marine ecosystem is still scarce, compared to that relating to temperate zones. Seabirds can be used as indicators of ecosystem health and sentinels of environmental pollution, constituting a link between marine and terrestrial environments. Here, we analysed the concentration of 17 elements (with special emphasis on mercury, Hg) in feathers of adults and chicks of two pelagic...
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Analysis of Methods for Determining Shallow Waterbody Depths Based on Images Taken by Unmanned Aerial Vehicles
PublikacjaHydrographic surveys enable the acquisition and processing of bathymetric data, which after being plotted onto nautical charts, can help to ensure safety of navigation, monitor changes in the coastal zone, and assess hydro-engineering structure conditions. This study involves the measurement of waterbody depth, identification of the seabed shape and geomorphology, the coastline course, and the location of underwater obstacles....
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Reactivation of seizure‐related changes to interictal spike shape and synchrony during postseizure sleep in patients
PublikacjaOBJECTIVE: 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...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Transcriptomic Effects of Estrogen Starvation and Induction in the MCF7 Cells. The Meta-analysis of Microarray Results
PublikacjaEstrogen is one of the most important signaling molecules which targets a number of genes. Estrogen levels regulate cell proliferation and a plethora of metabolic processes, which may interfere with a range of medical conditions and drug metabolism. The MCF7 breast cancer cell line, expressing the estrogen receptor α, is a well-studied model of cellular answer to estrogen. The aim of this study was to characterize transcriptomic...
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Advanced polarization sensitive analysis in optical coherence tomography
PublikacjaThe optical coherence tomography (OCT) is an optical imaging method, which is widely applied in variety applications. This technology is used to cross-sectional or surface imaging with high resolution in non-contact and non-destructive way. OCT is very useful in medical applications like ophthalmology, dermatology or dentistry, as well as beyond biomedical fields like stress mapping in polymers or protective coatings defects detection....
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Modeling and simulation of blood flow under the influence of radioactive materials having slip with MHD and nonlinear mixed convection
PublikacjaRadioactive materials are widely in industry, nuclear plants and medical treatments. Scientists and workers in these fields are mostly exposed to such materials, and adverse effects on blood and temperature profiles are observed. In this regard, objective of the current study is to model and simulate blood based nanofluid with three very important radioactive materials, named as Uranium dioxide (UO2), Thorium dioxide (ThO2) and...
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People’s Influence on Indoor Body Area Networks Channel Characteristics
PublikacjaThe influence of people’s presence on wideband off-body channel characteristics is presented in this paper. This research is significant for the development of Body Area Networks, as a promising solution for 5G and 6G networks, namely as an emerging technology expected to revolutionize mobile healthcare via real-time monitoring and analysis of medical data. The analysis is based on power delay profile measurements performed in...
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Koncepcja zdalnego sterowania i monitoringu urządzeń trakcyjnych z wykorzystaniem technologii teleinformatycznych
PublikacjaAdvancement in wireless communication enables engineers to apply sophisticated and relatively inexpensive technologies in new fields of industry, which were previously designated solely to wire-based solutions. One of those fields is railway transportation system. In effect of a high reliability and safety demands, this area was resistive to new technologies. Nowadays, increased security and reliability of wireless sensor networks...
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublikacjaMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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A Case Study of Electric Vehicles Load Forecasting in Residential Sector Using Machine Learning Techniques
PublikacjaElectric vehicles (EVs) have been widely adopted to prevent global warming in recent years. The higher installation of Level-1 and Level-2 chargers in residential areas soon poses challenges to the distributed network. However, such challenges can be mitigated through the adoption of smart charging or controlled charging schemes. To facilitate the implementation of smart charging, accurate forecasting of EV charging demand in residential...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Model zaangażowania w relacji usługodawca-klient
PublikacjaW niniejszej monografii przedstawiono rozwiązania pozwalające lepiej zrozumieć złożoność relacji występujących pomiędzy usługodawcami a klientami oraz metody, które pozwalają tę wiedzę wykorzystać w doskonaleniu procesów organizacji usługowych. Monografia podejmuje problem kształtowania zaangażowania na styku usługodawca–klient jako wstępnego i koniecznego warunku rozwijania relacji w usługach. Opierając się na klasycznej drabinie...
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RAGE as a Novel Biomarker for Prostate Cancer: A Systematic Review and Meta-Analysis
PublikacjaThe receptor for advanced glycation end-products (RAGE) has been implicated in driving prostate cancer (PCa) growth, aggression, and metastasis through the fueling of chronic inflammation in the tumor microenvironment. This systematic review and meta-analysis summarizes and analyzes the current clinical and preclinical data to provide insight into the relationships among RAGE levels and PCa, cancer grade, and molecular effects....
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Propagation of Ship-Generated Noise in Shallow Sea
PublikacjaContamination of sea environment by noise and any energy radiated to water constitutes today a problem to which more and more attention is paid, in view, a.o., of consequences of an impact of these factors onto marine fauna. European Union has introduced a directive by which EU countries are made responsible to undertake efforts aimed at reaching a good envirenmental status of European seas by 2020. A main source of underwater...
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First deep eutectic solvent-based (DES) stationary phase for gas chromatography and future perspectives for DES application in separation techniques
PublikacjaThe paper presents the first application of deep eutectic solvents (DES) as stationary phases for gas chromatography. DES obtained by mixing tetrabutylammonium chloride (TBAC) as a hydrogen bond acceptor (HBA) with heptadecanoic acid being a hydrogen bond donor (HBD) in a mole ratio of HBA:HBD equal to 1:2 was characterized by its ability to separate volatile organic compounds (VOCs). The Rohrschneider – McReynolds constants determined...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublikacjaTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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Encouraging pro-environmental behaviour through an educational mobile application: Preliminary insights from early adopters
PublikacjaThis article aims to explore the extent to which the educational mobile application PULA supports and promotes pro-environmental behaviours, identify the most utilised functionalities by early adopters, and explore the least engaged functionalities. The study employs a quantitative approach based on data collected from the application. The analysis provides a comprehensive understanding of users' experiences and behaviours within...
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The evaluation of eGlasses eye tracking module as an extension for Scratch
PublikacjaIn this paper we present the possibility of using eGlasses eye tracking module as an extension for Scratch programming tool which is a visual programming language supporting computer skills learning. The main concept behind this project is to setup the interface for rapid interaction design. Eye tracking is a powerful tool for hands free communication but for that requires a dedicated software. This software is rarely tailored...
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Resource productivity and environmental degradation in EU-27 countries: context of material footprint
PublikacjaThis study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation–maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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Kriging-assisted hybrid reliability design and optimization of offshore wind turbine support structure based on a portfolio allocation strategy
PublikacjaIn recent years, offshore wind power generation technology has developed rapidly around the world, making important contributions to the further development of renewable energy. When designing an Offshore Wind Turbine (OWT) system, the uncertainties in parameters and different types of constraints need to be considered to find the optimal design of these systems. Therefore, the Reliability-Based Design Optimization (RBDO) method...
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Encouraging Pro-environmental Behaviour Through an Educational Mobile Application: Preliminary Insights from Early Adopters
PublikacjaThis article aims to explore the extent to which the educational mobile application PULA supports and promotes pro-environmental behaviours, identify the most utilised functionalities by early adopters, and explore the least engaged functionalities. The study employs a quantitative approach based on data collected from the application. The analysis provides a comprehensive understanding of users' experiences and behaviours within...