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Search results for: IMAGE SEGMENTATION, DEEP LEARNING, AUTOMATED BEHAVIOR RECOGNITION, RODENT SOCIAL BEHAVIOR
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Damage of a post-tensioned concrete bridge – Unwanted cracks of the girders
PublicationThe cracking of a post-tensioned T-beam superstructure, which was built using the incremental launching method, is analyzed in the paper. The problem is studied in detail, as specific damage was observed in the form of longitudinal cracks, especially in the mid-height zone of the girder at the interface of two assembly sections. The paper is a case study. A detailed inspection is done and non-destructive testing results of the...
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Betaine and L-carnitine ester bromides: Synthesis and comparative study of their thermal behaviour and surface activity
PublicationSix esters of both betaine and L-carnitine bromides, featuring alkyl groups ranging from C8 to C18 in length, have been synthesized. The thermal behaviour of these twelve bio-based salts has been analyzed and compared by thermal gravimetric analysis and differential scanning calorimetry. The L-carnitine alkyl ester bromides melted below 100 C and can hence be considered ionic liquids (ILs) with full rights. Conversely, the betaine...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublicationData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Psychological and physical components in forming preferences on urban greenery management – The case of trees
PublicationPublic opinion is increasingly important in managing urban greenery. In this regard, this study demonstrates the importance of sociological (environmental worldviews), psychological (place attachment, perceived benefits of trees), and physical factors (type of building people live in, and urban greenery) in forming residents’ opinions on whether the municipality or landowners should decide about tree removal on private land. Logistic...
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublicationThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons
PublicationRecent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...
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Application of Aqueous Biphasic Systems Extraction in Various Biomolecules Separation and Purification: Advancements Brought by Quaternary Systems
PublicationAqueous biphasic systems (ABS) extraction is a simple, selective, efficient and easy to scale-up technology that, over the years, has attracted a considerable attention from the researcher community as an alternative methodology in downstream processing of a wide variety of biomolecules. This review summarizes and discusses the fundamental features of ABS, as well as its advantages and disadvantages, as a separation and purification...
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CONTRASTING MODERNISMS - ARCHITECTURE OF HARBOUR CITIES GDYNIA AND ALTONA
PublicationThe presentation of the exhibition “Architect Gustav Oelsner – Light, Air, Colour,”, which took place in Gdynia 1.04-29.05.2011, showed the clinker architecture of Gustav Oelsner in Altona. As a contrast to the white-plastered architecture of Gdynia, it provided an interesting background for the comparison of two different faces of modernism. The most important feature of the aesthetics of modernism was its cosmopolitan character,...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublicationReflectarrays (RAs) have been attracting considerable interest in the recent years due to their appealing features, in particular, a possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip...
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Heterogeneous oxidation of highly boron-doped diamond electrodes and its influence on the surface distribution of electrochemical activity
PublicationThe electrochemical active surface area (EASA) of polycrystalline boron-doped diamond (BDD) electrodes is heterogeneous and can be affected by numerous factors. There is a strong need for proper consideration of BDD heterogeneity in order to improve this material's range of application in electrochemistry. Localized changes in surface termination due to the influence of oxidation agent result in increased surface resistance. The...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublicationHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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Image Representation for Cognitive Systems Using SOEKS and DDNA: A Case Study for PPE Compliance
PublicationCognitive Vision Systems have gained significant interest from academia and industry during the past few decade, and one of the main reasons behind this is the potential of such technologies to revolutionize human life as they intend to work under complex visual scenes, adapting to a comprehensive range of unforeseen changes, and exhibiting prospective behavior. The combination of these properties aims to mimic the human capabilities...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Moda jako wartość konsumencka - eksplikacja zagadnienia
PublicationCel: Celem artykułu jest przedstawienie problematyki mody jako propozycji wartości dla klienta. Realizacja niniejszego celu wymagała uszczegółowionej eksplikacji zjawiska mody. W publikacji zdefiniowaniu poddano mechanizm działania mody, istotę trendu mody, jak również omówiono główne perspektywy analizy mody oraz aktualne nurty badań nad modą. Projekt badania/metodyka badawcza/koncepcja: W pracy wykorzystano metodę krytycznej...
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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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Greencoin: a Proenvironmental Action-Reward System
PublicationThe massive destruction of the natural environment is rapidly eroding the world’s capacity to provide food and water, threatening the security of billions of people. In order to facilitate green lifestyles – understood in terms of both pro-environmental behaviors and green self-image on the one hand, and to build sustainable local and global communities, on the other, we put forward an idea of a novel action-reward system based...
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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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Topological-numerical analysis of a two-dimensional discrete neuron model
PublicationWe conduct computer-assisted analysis of a two-dimensional model of a neuron introduced by Chialvo in 1995 [Chaos, Solitons Fractals 5, 461–479]. We apply the method of rigorous analysis of global dynamics based on a set-oriented topological approach, introduced by Arai et al. in 2009 [SIAM J. Appl. Dyn. Syst. 8, 757–789] and improved and expanded afterward. Additionally, we introduce a new algorithm to analyze the return times...
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Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
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Comparative study on fracture evolution in steel fibre and bar reinforced concrete beams using acoustic emission and digital image correlation techniques
PublicationIn recent decades, the demand for sustainable construction practices has increased, but raw materials such as reinforcing steel remain scarce. Therefore, steel fibres have emerged as a popular and sustainable choice in the construction industry, offering a cost-effective alternative to traditional steel bar reinforcement for both flatwork and elevated structures. The purpose of this study is therefore to compare the performance...
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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...