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Search results for: big data deep learning remote medical diagnostic
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublicationDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Predicting sulfanilamide solubility in the binary mixtures using a reference solvent approach
PublicationBackground. Solubility is a fundamental physicochemical property of active pharmaceutical ingredients. The optimization of a dissolution medium aims not only to increase solubility and other aspects are to be included such as environmental impact, toxicity degree, availability, and costs. Obtaining comprehensive...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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3-MCPD: A worldwide problem of food chemistry
Publication3-MCPD is a heat-induced food contaminant which has been widely investigated for decades. This paper presents an overview of current knowledge about 3-MCPD including its formation routes, occurrence in various foodstuffs, analytical approach, toxicological aspects and future research perspectives. So far 3-MCPD was determined in its free and bound form in thermally-treated foods, edible oils and fats, and infant foods including...
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PAYMENT TRANSACTIONS’ ENERGY EFFICIENCY
PublicationThe payment system and infrastructure is a sector that is not given enough attention today in the context of energy efficiency. This sector plays a big role in organizing and ensuring money circulation and funds. It has its value consisting on the one hand of the cost of payment equipment, infrastructure, payment instruments. On other hand, its value consists of the cost of energy for their manufacture and maintenance. The European...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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A Perspective on Missing Aspects in Ongoing Purification Research towards Melissa officinalis
PublicationMelissa officinalis L. is a medicinal plant used worldwide for ethno-medical purposes. Today, it is grown everywhere; while it is known to originate from Southern Europe, it is now found around the world, from North America to New Zealand. The biological properties of this medicinal plant are mainly related to its high content of phytochemical (bioactive) compounds, such as flavonoids, polyphenolic compounds, aldehydes, glycosides...
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Surgical Site Infection after Breast Surgery: A Retrospective Analysis of 5-Year Postoperative Data from a Single Center in Poland
PublicationBackground and Objectives: Surgical site infection (SSI) is a significant complication of non-reconstructive and reconstructive breast surgery. This study aimed to assess SSI after breast surgery over five years in a single center in Poland. The microorganisms responsible for SSI and their antibiotic susceptibilities were determined. Materials and Methods: Data from 2129 patients acquired over five years postoperatively by the...
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An improvement of body surface area formulas using the 3D scanning technique
PublicationObjectives: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. Material and Methods: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the...
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Development of the System Assurance Reference Model for Generating Modular Assurance Cases
PublicationAssurance cases are structured arguments used to demonstrate specific system properties such as safety or security. They are used in many industrial sectors including automotive, aviation and medical devices. Larger assurance cases are usually divided into modules to manage the complexity and distribute the work. Each of the modules is developed to address specific goals allocated to the specific objects i.e. components of the...
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Preparation and characterization of TiO2 nanostructures for catalytic CO2 photoconversion
PublicationThe titanium dioxide target (99.7%) of 1 cm in dia was ablated in vacuum by laser pulses(6 ns) at 266 nm and at repetition rate of 10 Hz. During deposition the laser fluence between 1 and 3.5 J/cm2 and the O2 pressure from the range of 10-2 - 1 Pa were applied. The thin TiO2 films were deposited on glass substrate (1 × 1 cm2) heated up to 500 °C. The chemical composition of the film and samples produced by annealing were investigated...
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Text Mining Algorithms for Extracting Brand Knowledge; The fashion Industry Case
PublicationBrand knowledge is determined by customer knowledge. The opportunity to develop brands based on customer knowledge management has never been greater. Social media as a set of leading communication platforms enable peer to peer interplays between customers and brands. A large stream of such interactions is a great source of information which, when thoroughly analyzed, can become a source of innovation and lead to competitive advantage....
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Enhancing environmental literacy through urban technology-based learning. The PULA app case
PublicationThis study addresses the need to enhance environmental literacy, focusing on urban adults through mobile applications, based on the example of PULA app that engages early adopters in gamified pro- environmental activities, offering insights into informal learning. Grounded in 'urban pedagogy,' the study combines semi-structured interviews with 17 application testers and quantitative data analysis, unveiling motivations, user feedback,...
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Tacit Knowledge Sharing and Project Performance. Does the Knowledge Workers' Personal Branding Matter?
PublicationTacit knowledge sharing is the real challenge for knowledge management today. Network economy has completely changed the role of knowledge workers who now become independent tacit knowledge producers. Bearing this fact in mind, the author studied how tacit knowledge sharing affects the process of building a personal brand and project performance. For this purpose, the authors conducted a study among Polish professionals with different...
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METHODS OF TEACHING SPATIAL AND URBAN PLANNING AT GEODESY AND CARTOGRAPHY
PublicationSpatial and town planning is a complex process caused by the interaction between natural and social systems at different temporal and spatial scales. That is the reason, why it is difficult to introduce this subject to students studying disciplines other than spatial or urban planning. The main problem is to define goals, the scope and expected educational effects. The second step is to choose the appropriate teaching and assessment...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublicationDapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...
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MOST Wiedzy jako narzędzie promocji otwartych zasobów nauki
PublicationRośnie znaczenie wiedzy zgromadzonej w różnego rodzaju systemach, w tym w kursach on-line. Połączenie systemów je przetwarzających z Internetem w znaczącym stopniu usprawniło rozprzestrzenianie informacji i zwiększyło jej dostępność. Coraz szersze uznanie zyskują ruchy Otwartego Dostępu (ang. Open Access). Politechnika Gdańska w ramach projektu Multidyscyplinarny Otwarty System Transferu Wiedzy – MOST Wiedzy buduje platformę o...
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Damage Detection in the Wind Turbine Blade Using Root Mean Square and Experimental Modal Parameters
PublicationThe paper presents results of an experimental study related to a non-destructive diagnostic technique used for preliminary determination the location and size of delamination in composite coatings of wind turbine blades. The proposed method of damage detection is based on the analysis of the ten first mode shapes of bending vibrations, which correspond to displacements of rotor blades perpendicular to the rotor plane. Modal parameters...
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The Application of Satellite Image Analysis in Oil Spill Detection
PublicationIn recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to...
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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
PublicationThe 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
PublicationThe 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
PublicationThe 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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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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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe 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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METHODS OF TEACHING NOISE PROTECTION AT ENVIRONMENTAL ENGINEERING
PublicationNoise 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
PublicationOpen 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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Algorithmic Human Resources Management
PublicationThe 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
PublicationThis 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
PublicationThis 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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Influence of algorithmic management practices on workplace well-being – evidence from European organisations
PublicationPurpose 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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Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility
PublicationSolubility 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
PublicationAn 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
PublicationComplexity 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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Visual Attention Distribution Based Assessment of User's Skill in Electronic Medical Record Navigation
PublicationCurrently, 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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Integrating Digital Twin Technology Into Large Panel System Estates Retrofit Projects
PublicationAs 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
PublicationDetermination 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
PublicationWithin 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
Publicationhe 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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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublicationLeading 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
PublicationWithin 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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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...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass 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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Storm petrels as indicators of pelagic seabird exposure to chemical elements in the Antarctic marine ecosystem
PublicationData 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
PublicationHydrographic 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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Transcriptomic Effects of Estrogen Starvation and Induction in the MCF7 Cells. The Meta-analysis of Microarray Results
PublicationEstrogen 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
PublicationThe 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
PublicationRadioactive 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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Koncepcja zdalnego sterowania i monitoringu urządzeń trakcyjnych z wykorzystaniem technologii teleinformatycznych
PublicationAdvancement 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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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, 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....