Wyniki wyszukiwania dla: ARTIFICIAL LIFE
-
The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
-
Social media for e-learning of citizens in smart city
PublikacjaThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
-
Green engineered biomaterials for bone repair and regeneration: Printing technologies and fracture analysis
PublikacjaDespite the exceptional self-regeneration properties of bone, severe injuries often require additional surgical intervention such as using artificial bone constructs. These structures need to meet a number of criteria regarding their structure, performance, alongside the rate and the mechanism of erosion and fracture when implanted, for stimulating the regeneration of defected bone and, more critically providing support in the...
-
Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
-
Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublikacjaFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
-
The study on the appearance of deformation defects in the yacht lamination process using an AI algorithm and expert knowledge
PublikacjaThis article describes the application of the A-priori algorithm for defining the rule-based relationships between individual defects caused during the lamination process, affecting the deformation defect of the yacht shell. The data from 542 yachts were collected and evaluated. For the proper development of the algorithm, a technological process of the yacht lamination supported by expert decisions was described. The laminating...
-
Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
-
Predicting the peak structural displacement preventing pounding of buildings during earthquakes
PublikacjaThe aim of the present paper is to verify the effectiveness of the artificial neural network (ANN) in predicting the peak lateral displacement of multi-story building during earthquakes, based on the peak ground acceleration (PGA) and building parameters. For the purpose of the study, the lumped-mass multi-degree-of-freedom structural model and different earthquake records have been considered. Firstly, values of stories mass and...
-
Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up
PublikacjaOne of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence...
-
How Machine Learning Contributes to Solve Acoustical Problems
PublikacjaMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
-
Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublikacjaThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
-
Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
-
Light4Health eLearning Course: health research for interior lighting design. Re-thinking design approaches based on science
PublikacjaThis 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...
-
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...
-
Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublikacjaHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
-
The treatment of wastewater containing pharmaceuticals in microcosm constructed wetlands: the occurrence of integrons (int1–2) and associated resistance genes (sul1–3, qacEΔ1)
PublikacjaThe aim of this study was to analyze the occurrence of sulfonamide resistance genes (sul1–3) and other genetic elements as antiseptic resistance gene (qacEΔ1) and class 1 and class 2 integrons (int1–2) in the upper layer of substrate and in the effluent of microcosm constructed wetlands (CWs) treating artificial wastewater containing diclofenac and sulfamethoxazole (SMX), which is a sulfonamide antibiotic. The bacteria in the substrate...
-
Development of novel (BiO)2OHCl/BiOBr enriched with boron doped-carbon nanowalls for photocatalytic cytostatic drug degradation: Assessing photocatalytic process utilization in environmental condition
PublikacjaIn this work, a series of novel (BiO)2OHCl/BiOBr-x%B:DGNW (x = 0%, 1%, 1.5%, 2%) composites with different content of boron-doped diamond/graphene nanowalls (B:DGNW) were fabricated by simple solvothermal synthesis. A boron-doped diamond/graphene nanowalls (B:DGNW) were prepared by CVD method. A series of analyses: XRD, XPS, SEM, and TEM showed that the photocatalyst (BiO)2OHCl/BiOBr-x%B:DGNW with a “flower-like” morphology was...
-
KNOWING WHEN TO SAY NO / SAPERE QUANDO DIRE NO
PublikacjaEver since we began illuminating the exterior of the slender skyscrapers built during the of 20s and 30s in XX century, urban lighting has been considered a way to beautify cities, and make them more visually prominent and safe. At that time, we knew so little about the impact of lighting on humans, flora and fauna, so it never occurred to lighting designers then, that their actions would have harmful consequences. In those days,...
-
MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
-
Determination of long-chain aldehydes using a novel quartz crystal microbalance sensor based on a biomimetic peptide
PublikacjaThere is an increasingly popular trend aimed at improvement of fundamental metrological parameters of sensors via implementation of materials mimicking biological olfactory systems. This study presents investigation on usefulness of the peptide mimicking HarmOBP7 region as a receptor element of the piezoelectric sensor for selective analysis of long-chain aldehydes. Identification of odorant binding proteins creates new possibilities...
-
Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
-
Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms
PublikacjaThe study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of...
-
Electrophoretic Deposition and Characterization of Chitosan/Eudragit E 100 Coatings on Titanium Substrate
PublikacjaCurrently, a significant problem is the production of coatings for titanium implants, which will be characterized by mechanical properties comparable to those of a human bone, high corrosion resistance, and low degradation rate in the body fluids. This paper aims to describe the properties of novel chitosan/Eudragit E 100 (chit/EE100) coatings deposited on titanium grade 2 substrate by the electrophoretic technique (EPD). The deposition...
-
Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublikacjaAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
-
The mechanisms of degradation of titanium dental implants
PublikacjaTitanium dental implants show very good properties, unfortunately there are still issues regarding material wear due to corrosion, implant loosening, as well as biological factors—allergic reactions and inflammation leading to rejection of the implanted material. In order to avoid performing reimplantation operations, changes in the chemical composition and/or modifications of the surface layer of the materials are used. This research...
-
EVALUATION OF LIQUID-GAS FLOW IN PIPELINE USING GAMMA-RAY ABSORPTION TECHNIQUE AND ADVANCED SIGNAL PROCESSING
PublikacjaLiquid-gas flows in pipelines appear in many industrial processes, e.g. in the nuclear, mining, and oil industry. The gamma-absorption technique is one of the methods that can be successfully applied to study such flows. This paper presents the use of thegamma-absorption method to determine the water-air flow parameters in a horizontal pipeline. Three flow types were studied in this work: plug, transitional plug-bubble,...
-
Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
-
A vector-enzymatic DNA fragment amplification-expression technology for construction of artificial, concatemeric DNA, RNA and proteins for novel biomaterials, biomedical and industrial applications
PublikacjaA DNA fragment amplification/expression technology for the production of new generation biomaterials for scientific, industrial and biomedical applications is described. The technology enables the formation of artificial Open Reading Frames (ORFs) encoding concatemeric RNAs and proteins. It recruits the Type IIS SapI restriction endonuclease (REase) for an assembling of DNA fragments in an ordered head-to-tail-orientation. The...
-
ChatGPT Application vis-a-vis Open Government Data (OGD): Capabilities, Public Values, Issues and a Research Agenda
PublikacjaAs a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it...
-
Development of a new generation of unmanned surface and underwater vehicles using the advanced technologies and achievements towards the application of control systems by the artificial intelligence AI.
PublikacjaThe operation of offshore structures at sea requires implementation of the advanced systems of permanent monitoring of work of such the installations. Novel solutions concerning such the systems should be associated with application of unmanned maritime surface and underwater platforms. The unmanned maritime platforms are and will be based on application of the newest achievements of some important technologies. Between these technologies...
-
Application of unmanned USV surface and AUV underwater maritime platforms for the monitoring of offshore structures at sea
PublikacjaThe operation of offshore structures at sea requires the implementation of advanced systems for their permanent monitoring. There is a set of novel technologies that could be implemented to deliver a higher level of effective and safe operation of these systems. A possible novel solution may be the application of a new maritime unmanned (USV) surface and underwater vehicles/platforms (AUV). Application of such vehicles/platforms...
-
Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublikacjaOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
-
Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
-
Comparison of hydrophilic interaction and reversed phase liquid chromatography coupled with tandem mass spectrometry for the determination of eight artificial sweeteners and common steviol glycosides in popular beverages
PublikacjaHydrophilic interaction liquid chromatography (HILIC) coupled with tandem mass spectrometry (MS/MS) was used to separate artificial and natural sweeteners approved for use in European Union (EU). Among three tested HILIC columns (BlueOrchid PAL-HILIC, Ascentis Express Si and Acclaim™ Trinity™ P2) the last one was selected for the development of HILIC method due to the best results obtained with it. Early eluting and coeluting compounds...
-
Assessment of toxic and endocrine potential of substances migrating from selected toys and baby products
PublikacjaAnalysis of literature data shows that there is limited information about the harmful biological effects of mixture of compounds from the EDC group that are released from the surface of toys and objects intended for children and infants. One of the tools that can be used to obtain such information is appropriate bioanalytical tests. The aim of this research involved determining whether tests that use living organisms as an active...
-
Assessment of ecotoxicity and total volatile organic compound (TVOC) emissions from food and children's toy products
PublikacjaThe development of new methods for identifying a broad spectrum of analytes, as well as highly selective tools to provide the most accurate information regarding the processes and relationships in the world, has been an area of interest for researchers for many years. The information obtained with these tools provides valuable data to complement existing knowledge but, above all, to identify and determine previously unknown hazards. Recently,...
-
The effect of groyne field on trapping macroplastic. Preliminary results from laboratory experiments
PublikacjaMacroplastic, a precursor of microplastic pollution, has become a new scope of research interest. However, the physical processes of macroplastic transport and deposition in rivers are poorly understood, which makes the decisions of where to locate macroplastic trapping infrastructure difficult. In this research, we conducted a series of experiments in a laboratory channel, exploring the impact of groynes and flexible artificial...
-
Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale
PublikacjaDespite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by means of model hyetographs. This creates the need for the availability of credible statistical methods for the development and verification of already locally applied model hyetographs....
-
Chitosan-based inks for 3D printing and bioprinting
PublikacjaThe advent of 3D-printing/additive manufacturing in biomedical engineering field has introduced great potential for the preparation of 3D structures that can mimic native tissues. This technology has accelerated the progress in numerous areas of regenerative medicine, especially led to a big wave of biomimetic functional scaffold developments for tissue engineering demands. In recent years, the introduction of smart bio-inks has...
-
Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublikacjaRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
-
Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
-
RMS-based damage identification in adhesive joint between concrete beam and steel plate using ultrasonic guided waves
PublikacjaAdhesive joints have numerous applications in many branches of industry, such as civil engineering, automotive, aerospace and shipbuilding. As with most structural elements, adhesive joints can experience any damage mechanism, which induces the need for diagnostic testing. Ultrasonic waves are widely used for non-destructive inspection of many structures and their elements, including adhesive joints. Guided wave propagation method...
-
Healthier and Environmentally Responsible Sustainable Cities and Communities. A New Design Framework and Planning Approach for Urban Illumination
PublikacjaAlthough sustainability and sustainable development are both considered necessary practices in various fields today, a recent analysis showed that the Sustainable Development Goal SDG11: Sustainable Cities and Communities established by the United Nations does not address urban illumination and its impact. This oversight is of concern because research carried out in the last 20+ years indicates artificial light at night (ALAN)...
-
Olfactory receptor-based biosensors as potential future tools in medical diagnosis
PublikacjaThe detection of biomarkers is the future of non-invasive medical diagnosis and screening. Discovery and identification of reliable disease specific volatile organic compounds is dependent on repeatable, accurate analysis of trace level gaseous analytes mainly in breath samples. Natural variety of the olfactory systems and the compounds capable of gas molecules binding creates wide possibilities of acquisition and implementation...
-
Numerical Modelling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia
PublikacjaIn this study, correlations are developed to predict compression index (Cc) from index parameters so that one can be able to model Jimma soils with compression index using simple laboratory tests. Undisturbed and disturbed soil samples from twelve different locations in Jimma town were collected. Laboratory tests like specific gravity, grain size analysis, Atterberg limit, and one-dimensional consolidation test for a total of twenty-four...
-
Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease
PublikacjaIn this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...
-
Rethinking Sustainable Cities at Night: Paradigm Shifts in Urban Design and City Lighting
PublikacjaSince the establishment of the 17 Sustainable Development Goals (SDGs) by the United Nations General Assembly in 2015, various perspectives on sustainable cities have been developed and adopted in order to achieve a better and more sustainable future. However, background research has revealed that these goals and targets are limited because they do not take into account the growing body of lighting-related research in diverse fields...
-
Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
-
Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
-
Forecasting risks and challenges of digital innovations
PublikacjaForecasting and assessment of societal risks related to digital innovation systems and services is an urgent problem, because these solutions usually contain artificial intelligence algorithms which learn using data from the environment and modify their behaviour much beyond human control. Digital innovation solutions are increasingly deployed in transport, business and administrative domains, and therefore, if abused by a malicious...