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Wyniki wyszukiwania dla: ELEARNING
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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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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublikacjaThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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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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Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology
PublikacjaLignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization...
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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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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublikacjaImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublikacjaThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Asking Data in a Controlled Way with Ask Data Anything NQL
PublikacjaWhile to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublikacjaIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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MSRL and the Real-Life Processes of Capturing and Implementing the "Urban Innovation"
PublikacjaResult of the MSRL workshop, five research projects, reflect on a broader process of exchange of the ideas between the cities, that is occurring in the real life and became one of the driving factors of the urban development nowadays. The objective of the MSRL research - concepts, which help to advance the development of the cities, support the improvement of the quality of urban environment or meet the future challenges, can be...
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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublikacjaNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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The Knowledge Transfer From Headquarter to Local Subsidiaries Through Expatriates - Local Employees’ Perspective
PublikacjaBackground. Knowledge transfer between the HQ and subsidiary has recently been targets of increasing research interest. However, the role of expatriate managers and local staff perspective on this process has not been examined enough. Research aims. This paper has two main objectives: first to develop a conceptual framework (model) of knowledge transfer between the headquarters and local subsidiary, and second to empirically evaluate...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Analysis-by-synthesis paradigm evolved into a new concept
PublikacjaThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublikacjaElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Smartphones as tools for equitable food quality assessment
PublikacjaBackground: The ubiquity of smartphones equipped with an array of sophisticated sensors, ample processing power, network connectivity and a convenient interface makes them a promising tool for non-invasive, portable food quality assessment. Combined with the recent developments in the areas of IoT, deep learning algorithms and cloud computing, they present an opportunity for advancing wide-spread, equitable and sustainable food...
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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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Effective Collaboration of Entrepreneurial Teams—Implications for Entrepreneurial Education
PublikacjaIn the situation of a permanent change and increased competition, business ventures are more and more often undertaken not by individuals but by entrepreneurial teams. The main aim of this paper is to examine the team principles implemented by eective entrepreneurial teams and how they dier in nascent and established teams. We also focused on the relationship between the implementation of these rules by entrepreneurial team members...
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Adaptacyjny system sterowania ruchem drogowym
PublikacjaAdaptacyjny system sterowania ruchem drogowym to rodzaj systemu sterowania, który dynamicznie, w czasie rzeczywistym, dostosowuje swoje parametry w oparciu o bieżące warunki ruchu drogowego. Celem niniejszej rozprawy jest sprawdzenie wpływu wybranych cech systemu, zbudowanego w oparciu o zaprojektowane i zbudowane z udziałem autora inteligentne znaki drogowe, na wybrane parametry mające wpływ na bezpieczeństwo i płynność ruchu....
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Wyzwania bezpieczeństwa nowoczesnych platform nauczania zdalnego
PublikacjaW artykule zaprezentowano aspekty bezpieczeństwa nowoczesnych platform nauczania zdalnego. Przedstawiono ich charakterystykę i wyzwania technologiczne. Zdefiniowano bezpieczeństwo i istniejące w tym obszarze zagrożenia. Przybliżono metody oceny poziomu bezpieczeństwa. Na bazie wdrożonej na Politechnice Gdańskiej platformy eNauczanie PG omówiono sposoby zapewniania zakładanego poziomu bezpieczeństwa takich systemów.
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Application of Spinel and Hexagonal Ferrites in Heterogeneous Photocatalysis
PublikacjaSemiconducting materials display unique features that enable their use in a variety of applications, including self-cleaning surfaces, water purification systems, hydrogen generation, solar energy conversion, etc. However, one of the major issues is separation of the used materials from the process suspension. Therefore, chemical compounds with magnetic properties have been proposed as crucial components of photocatalytic composites,...
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Prototype design and development of low-load-roof photovoltaic modules for applications in on-grid systems
PublikacjaFour prototypes of lightweight photovoltaic modules for applications in on-grid systems have been designed, developed, manufactured and tested for compliance with relevant IEC standards. Selected, commercially available materials characterized by thermogravimetry, differential scanning calorimetry, dilatometry, scanning electron microscopy and nanoindentation technique were used in frameless, adhesively-bonded sandwich-structures...
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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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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublikacjaHoneybees 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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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublikacjaThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublikacjaThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublikacjaWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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CNN-CLFFA: Support Mobile Edge Computing in Transportation Cyber Physical System
PublikacjaIn the present scenario, the transportation Cyber Physical System (CPS) improves the reliability and efficiency of the transportation systems by enhancing the interactions between the physical and cyber systems. With the provision of better storage ability and enhanced computing, cloud computing extends transportation CPS in Mobile Edge Computing (MEC). By inspecting the existing literatures, the cloud computing cannot fulfill...
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Multimodal human-computer interfaces based on advanced video and audio analysis
PublikacjaMultimodal interfaces development history is reviewed briefly in the introduction. Some applications of multimodal interfaces to education software for disabled people are presented. One of them, the LipMouse is a novel, vision-based human-computer interface that tracks user’s lip movements and detect lips gestures. A new approach to diagnosing Parkinson’s disease is also shown. The progression of the disease can be measured employing...
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Multimodal human-computer interfaces based on advanced video and audio analysis
PublikacjaMultimodal interfaces development history is reviewed briefly in the introduction. Examples of applications of multimodal interfaces to education software and for the disabled people are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with mouth gestures and the audio interface for speech stretching for hearing impaired and stuttering people. The Smart...
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Online sound restoration system for digital library applications.
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublikacjaEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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A note on the applications of artificial intelligence in the hospitality industry: preliminary results of a survey
PublikacjaIntelligent technologies are widely implemented in different areas of modern society but specific approaches should be applied in services. Basic relationships refer to supporting customers and people responsible for services offering for these customers. The aim of the paper is to analyze and evaluate the state-of-the art of artificial intelligence (AI) applications in the hospitality industry. Our findings show that the major...
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Buzz-based honeybee colony fingerprint
PublikacjaNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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An automated, low-latency environment for studying the neural basis of behavior in freely moving rats
PublikacjaBackground Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes). Results To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding...
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Review of Segmentation Methods for Coastline Detection in SAR Images
PublikacjaSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
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Platforma edX - nowe podejście do kursów online
PublikacjaWspółczesne metody nauczania na odległość zmieniają się dynamicznie. Powstają światowe konsorcja podejmujące starania zapewnienia dostępu do edukacji na najwyższym poziomie z wykorzystaniem Internetu. Jedną z takich prób jest platforma edX. Jej rozwój zapoczątkowały niemal 2 lata temu MIT i Harvard. Obecnie zespół liczy już 30 uczelni z całego świata. Renoma ośrodków naukowych biorących udział w projekcie przyciągnęła już ponad...
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The use of Kamienna głowa cabbage species for phytoextraction of zinc and cadmium from the soil
PublikacjaAlthough traditional technologies for cleaning contaminated soils have proven to be efficient, they are usually expensive, labor intensive, and in the case of soil, they produce severe disturbance. Most recently, the use of plants in metal extraction (phytoremediation) has appeared as a promising alternative in the removal of heavy metal excess from soil. Phytoremediation uses of plant for pollutant stabilization, extraction, degradation,...
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Analysis of Airport Runoff Waters
PublikacjaA particularly important facet of airport operation is the impact of the pollution caused byrunoff waters. Runoff waters at an airport may contain relatively high concentrations of differentcontaminants resulting from the various aspects of its operation: de/anti-icing operations,washing and cleaning operations, spills of fuel and lubricants, exhaust fumes, and weed removal.The pollution caused by airport operations affects soil,...
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Phytoremediation of heavy metals by white cabbage
PublikacjaPhytoremediation is regarded as the cheapest and environmentally most friendly technology for cleaning up soil. The most widespread and most profitable technique is phytoextraction, used mainly for removing heavy metals and radioactive elements from thesoil. Over 400 plant species have been identified as natural metal hyperaccumulators representing about 0.2 % of all angiosperms. Unfortunately, most of these plants are characterised...
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Research on the separation properties of empty-column gas chromatography (EC-GC) and conditions for simulated distillation (SIMDIS)
PublikacjaThe paper presents the results of investigations on new procedures of determination of selected cleaning additives in diesel fuel. Two procedures: one-step analysis using gas chromatography with flame ionization detection (GC-FID) or mass spectrometry (GC-MS) and a two-step procedure in which normal-phase high-performance liquid chromatography (NP-HPLC) was used for preliminary separation of the additives, were compared. The additive...
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Application of normal-phase high-performance liquid chromatography followed by gas chromatography for analytics of diesel fuel additives
PublikacjaThe paper presents the results of investigations on new procedures of determination of selected cleaning additives in diesel fuel. Two procedures: one-step analysis using gas chromatography with flame ionization detection (GC-FID) or mass spectrometry (GC-MS) and a two-step procedure in which normal-phase high-performance liquid chromatography (NP-HPLC) was used for preliminary separation of the additives, were compared. The additive...
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Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.
PublikacjaCoordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During...
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Smart skills and education in a future economy
PublikacjaWhether the role of education is to prepare people for employment or to have meaningful lives in general, it will identify and develop skills and competencies, as well as vocational and personal attributes. Skills, such as critical thinking, novel ideation, and complex cognitive and social skills, are areas where humans continue to outperform smart machines. The purpose of this article is to review the skills and competencies that...
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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 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...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublikacjaAs 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...