Search results for: ARTIFICIAL LIFE
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublicationOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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A mechanistically approached review upon assorted cell lines stimulated by athermal electromagnetic irradiation
PublicationThe probable influence of electromagnetic irradiation on cancer treatment has been deduced from the interaction of artificial electromagnetic emissions with biological organisms. Nonetheless, the suspected health effects induced by electromagnetic-based technology imply that such a treatment may contaminate the adjacent healthy cells. Thus, gaining mechanistic insights into the problem is required to avoid athermal health hazards....
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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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Experiments with the Universal Constructor in the DigiHive Environment
PublicationThe paper discusses the performance and limitations of the universal constructor embedded in the DigiHive environment and presents the result of two simulation experiments showing the possibility of workaround the limitations.
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublicationThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Fracture in Asymmetric Bonded Joints
PublicationAdhesion was studied in asymmetric bonded joints using fracture mechanics tests. The asymmetric bonded joints consist of two different type and/or thickness materials bonded by an adhesive. Mentions of asymmetric bonded joint tests employed so far are rare in the literature. They are imperfect and therefore are not standardized. Accordingly three new tests were introduced in this work to study bonded joints. The new metrological...
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Dendron to Central Core S1–S1 and S2–Sn (n>1) Energy Transfers in Artificial Special Pairs Containing Dendrimers with Limited Numbers of Conformations
PublicationTwo dendrimers consisting of a cofacial free-base bisporphyrin held by a biphenylene spacer and functionalized with 4-benzeneoxomethane (5-(4-benzene)tri-10,15,20-(4-n-octylbenzene)zinc(II)porphyrin) using either five or six of the six available meso-positions, have been synthesized and characterized as models for the antenna effect in Photosystems I and II. The presence of the short linkers, -CH2O-, and long C8H17 soluble side...
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Fabrication of polyurethane and polyurethane based composite fibers by the electrospinning technique for soft tissue engineering of cardiovascular system
PublicationElectrospinning is the unique technique, which provides forming of polymeric scaffolds for soft tissue engineering, which include tissue scaffolds for soft tissues of cardiovascular system. Such artificial soft tissues of cardiovascular system may possess mechanical properties comparable to native vascular tissues. Electrospinning technique gives the opportu nity to form fibres with nm- to μm-scale in diameter. The arrangement...
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Daytime Acute Non-Visual Alerting Response in Brain Activity Occurs as a Result of Short- and Long-Wavelengths of Light
PublicationVery recent preliminary findings concerning the alerting capacities of light stimulus with long-wavelengths suggest the existence of neural pathways other than melatonin suppression that trigger the nonvisual response. Though the nonvisual effects of light during the daytime have not been investigated thoroughly, they are definitely worth investigating. The purpose of the present study is to enrich existing evidence by describing...
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Assessment of Citizens’ Actions against Light Pollution with Guidelines for Future Initiatives
PublicationDue to the wide reach of media reports about scientific research and technological tools such as the world wide web (WWW), the Internet, and web browsers, citizens today have access to factual information about the negative impact of artificial light at night (ALAN) on their dark skies, and their health and well-being. This means they can now make educated decisions and take the necessary steps to help protect themselves and their...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Highly efficient maximum power point tracking control technique for PV system under dynamic operating conditions
PublicationThe application of small-scale electrical systems is widespread and the integration of Maximum Power Point Tracking (MPPT) control for Photovoltaic systems with battery applications further enhances the techno-economic feasibility of renewable systems. For this purpose, a novel MPPT control system using Dynamic Group based cooperation optimization (DGBCO) algorithm is utilized for PV systems. The population in the DGBCO is divided...
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Assessing and Mitigating Ice-Jam Flood Hazards and Risks: A European Perspective
PublicationThe assessment and mapping of riverine flood hazards and risks is recognized by many countries as an important tool for characterizing floods and developing flood management plans. Often, however, these management plans give attention primarily to open-water floods, with ice-jam floods being mostly an afterthought once these plans have been drafted. In some Nordic regions, ice-jam floods can be more severe than open-water floods,...
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Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations
PublicationThe fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction...
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SEDIMENT DEPOSITION IN RESERVOIRS IN URBAN BASIN
PublicationIn recent years Gdańsk had sustained economic and social losses due to severe flash floods coming down from moraine hills. The first flood occurred in July 2001 and the second in July 2016. Both events were caused by intense and long rainfall characterized by different from each other rain intensity in time. Among other Gdansk’s streams the Oliwski Stream has the most extended flood protection system consist of 15 small retention...
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ARTIFICIAL MODEL IN THE ASSESSMENT OF THE ALGORITHM OF OBJECTS RECORDED BY LASER SCANNING SHAPE DETECTION (ALS/TLS)
PublicationBrief description of the study and used methods. Brief description of the study and used As part of the preparatory work aimed to create the application solution allowing for the automation of searching objects in data, obtained in the scanning process using ALS (Airborne Laser Scanning) or TLS (Terrestrial Laser Scanning), the authors prepared a artificial (synthetic, theoretical) model of space, used for the verification of operation...
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Enhancing Customer Engagement in Social Media with AI – a Higher Education case study
PublicationPurpose. The study aims to demonstrate the importance of artificial intelligence (AI) and examples of tools based on it in the process of enhancing (building, measuring, and managing) customer engagement (CE) in social media in the higher education industry. CE is one of the current essential non-financial indicators of company performance in Digital Marketing strategy. The article presents a decision support system (DSS) based...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Macro-nutrients recovery from liquid waste as a sustainable resource for production of recovered mineral fertilizer: Uncovering alternative options to sustain global food security cost-effectively
PublicationGlobal food security, which has emerged as one of the sustainability challenges, impacts every country. As food cannot be generated without involving nutrients, research has intensified recently to recover unused nutrients from waste streams. As a finite resource, phosphorus (P) is largely wasted. This work critically reviews the technical applicability of various water technologies to recover macro-nutrients such as P, N, and...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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The power of personal brand authenticity and identification: top celebrity players’ contribution to loyalty toward football
PublicationPurpose: In the current era of fake news, illusions, manipulations, and other artificial attributes of virtuality and reality, authenticity is a virtue that people highly appreciate. This study examines the influence of the personal brand authenticity of top football players on loyalty to the football discipline in general, via the mediation of personal brand identification. Design: Based on data collected from a convenience sample...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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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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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublicationPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Smart Embedded Systems with Decisional DNA Knowledge Representation
PublicationEmbedded systems have been in use since the 1970s. For most of their history embedded systems were seen simply as small computers designed to accomplish one or a few dedicated functions; and they were usually working under limited resources i.e. limited computing power, limited memories, and limited energy sources. As such, embedded systems have not drawn much attention from researchers, especially from those in the artificial...