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Search results for: ISLE DATASET
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Metoda kapsułkowania z wykorzystaniem systemu współosiowego
PublicationW ciągu ostatnich kilkudziesięciu lat mikrokapsułki stały się ważnym narzędziem w dostarczaniu substancji aktywnych przy jednoczesnej ochronie substancji niestabilnych. Gałęzie przemysłu w których mikrokapsułki znalazły zastosowanie to przemysł farmaceutyczny i biomedyczny, produkcja kosmetyków, przemysł spożywczy, ochrona roślin, budownictwo i wiele innych. Dotychczasowe, powszechnie wykorzystywane do tego celu metody, takie jak...
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Metoda OptD do redukcji danych w opracowaniu wyników pomiarów linii elektroenergetycznych
PublicationSkaning laserowy to technologia dostarczająca we względnie krótkim czasie dużą ilość danych pomiarowych. Jest to zarazem pozytywna jak i negatywna cecha tej technologii. Z jednej strony w wyniku skaningu otrzymuje się dane, które szczegółowo odzwierciedlają pomierzony obiekt. Z drugiej strony trudność sprawia przetwarzanie takiej ilości danych i nie zawsze wszystkie dane ze skaningu są niezbędne do realizacji wybranego zadania....
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Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach
PublicationMonitoring contamination in river water is an expensive procedure, particularly for developing countries where pollution is a significant problem. This study was conducted to provide a pollution monitoring strategy that reduces the cost of laboratory analysis. The new monitoring strategy was designed as a result of cluster and regression analysis on field data collected from an industrially influenced river. Pollution sources in...
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How do responsible universities perceive their social engagement? In search of signs of Creating Shared Value by the University
PublicationObjectives: University social responsibility still lacks legitimisation and is perceived as a burden that hinders academics from doing research and teaching. Creating Shared Value by the University may serve as a tool to motivate universities to engage in initiatives for society, as this is beneficial for both parties. Yet, some researchers perceive the creation of economic value as inappropriate for academia. Thus, it was interesting...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast 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...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal 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...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater 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...
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Detecting Apples in the Wild: Potential for Harvest Quantity Estimation
PublicationKnowing the exact number of fruits and trees helps farmers to make better decisions in their orchard production management. The current practice of crop estimation practice often involves manual counting of fruits (before harvesting), which is an extremely time-consuming and costly process. Additionally, this is not practicable for large orchards. Thanks to the changes that have taken place in recent years in the field of image...
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Analytical tools for functional assessment of architectural layouts
PublicationFunctional layout of the building, understood as a layout or set of the facility rooms (or groups of rooms) with a system of internal communication, creates an environment and a place of mutual relations between the occupants of the object. Achieving optimal (from the occupants’ point of view) spatial arrangement is possible through activities that often go beyond the stage of architectural design. Adopted in the architectural...
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3D MODELLING OF CYLINDRICAL-SHAPED OBJECTS FROM LIDAR DATA - AN ASSESSMENT BASED ON THEORETICAL MODELLING AND EXPERIMENTAL DATA
PublicationDespite the increasing availability of measured laser scanning data and their widespread use, there is still the problem of rapid and correct numerical interpretation of results. This is due to the large number of observations that carry similar information. Therefore, it is necessary to extract from the results only the essential features of the modelled objects. Usually, it is based on a process using filtration, followed by...
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Incorporating installation effects into the probability analysis of controlled modulus columns
PublicationThis technical report presents the probabilistic analysis which integrates the Monte Carlo simulation (MCS) with random field theory to model the load–displacement behavior of Controlled Modulus Columns (CMCs) in overconsolidated Poznań clay. Presented study focuses on the practical aspects of statistical analysis of geotechnical data, numerical model development, and results evaluation. Variability and spatial distribution of...
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BASECOL2023 scientific content
PublicationContext. The global context of making numerous data produced by researchers available requires collecting and organising the data, assigning meaningful metadata, and presenting the data in a meaningful and homogeneous way. The BASECOL database, which collects inelastic rate coefficients for application to the interstellar medium and to circumstellar and cometary atmospheres, meets those requirements. Aims. We aim to present the...
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Estimation of nonstructural stiffness in instrumented steel frames
PublicationLateral stiffness of nonstructural components may significantly influence the initial stiffness of the entire structure and consequently alter its dynamic characteristics. While methods for simulating structural members are well-established, approaches for modeling nonstructural components that also participate in seismic response are notably less developed. In this paper a simplified, physically-intuitive approach for estimating...
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Rola przestrzeni publicznych w procesie rewitalizacji wielkich osiedli mieszkaniowych.
PublicationOsiedla mieszkaniowe byłego NRD od 10 lat są poddawane rewitalizacji. Zmieniająca się sytuacja polityczo-ekonomiczna wpływa na zmianę postrzegania przyszłości tych struktur. Powstanie akceptowanych społecznie przestrzeni publicznych jest warunkiem przebudowy ''sypialni-blokowisk'' w sprawnie funkcjonujące dzielnice miejskie. Możliwość realizacji tej wytycznej jest zależna nie tyle od możliwości technicznych ile od czynników...
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Równoważenie rozwoju przestrzennego miast w Polsce
PublicationZagadnienie kształtowania przestrzeni miast i obszarów metropolitalnych w sposób spójny i kompleksowy, w tym w odniesieniu do ich struktury funkcjonalno-przestrzennej, jest jednym z ważniejszych problemów współczesnej urbanistyki. Kwestii tej poświęcone jest wiele opracowań zarówno o charakterze teoretycznym, jak i odnoszących się do praktyki projektowej. Jednym z ważniejszych wątków tej debaty jest kwestia równoważenia rozwoju...
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Numbers, Please: Power- and Voltage-Related Indices in Control of a Turbine-Generator Set
PublicationThis paper discusses the proper selection and interpretation of aggregated control performance indices values mirroring the quality of electrical energy generation by a turbine-generator set cooperating with a power system. Typically, a set of basic/classical and individual indices is used in energy engineering to ensure the mirroring feature and is related to voltage, frequency and active or reactive power deviations from their...
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Podstawy pól i fal elektromagnetycznych
PublicationW pracy przedstawiono w sposób systematyczny podstawowe zagadnienia elektromagnetyzmu. Materiał zawarto w dwunastu rozdziałach, w których zagadnienia teoretyczne, o ile to było możliwe, ilustrowano przykładami przybliżającymi Czytelnikowi ich sens fizyczny. Początkowe rozdziały poświęcono narzędziom matematycznym stosowanym w analizie zagadnień polowych oraz przedstawieniu koncepcji pól: elektrycznego i magnetycznego. Następnie...
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Evaluation of a PCR Melting Profile method for intra-species differentiation of Trichophyton rubrum and Trichophyton interdigitale
PublicationW celu identyfikacji źródła infekcji spowodowanych przez dermatofity, jak i drogi ich transmisji, istnieje potrzeba szukania nowych metod, które pozwolą na głębokie zróżnicowanie genetyczne szczepów w obrębie rodzaju. W pracy po raz pierwszy pokazano zastosowanie techniki PCR MP opartej o adaptory oligonukleotydowe i różnice w temperaturze topnienia fragmentów restrykcyjnych DNA w reakcji PCR do wewnątrzgatunkowego typowania dermatofitów....
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Taking advantage of symmetries: Gathering of many asynchronous oblivious robots on a ring
PublicationOne of the recently considered models of robot-based computing makes use of identical, memoryless mobile units placed in nodes of an anonymous graph. The robots operate in Look-Compute-Move cycles; in one cycle, a robot takes a snapshot of the current configuration (Look), takes a decision whether to stay idle or to move to one of the nodes adjacent to its current position (Compute), and in the latter case makes an instantaneous...
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Automated hearing loss type classification based on pure tone audiometry data
PublicationHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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Entropy Measures in the Assessment of Heart Rate Variability in Patients with Cardiodepressive Vasovagal Syncope
PublicationSample entropy (SampEn) was reported to be useful in the assessment of the complexity of heart rate dynamics. Permutation entropy (PermEn) is a new measure based on the concept of order and was previously shown to be accurate for short, non-stationary datasets. The aim of the present study is to assess if SampEn and PermEn obtained from baseline recordings might differentiate patients with various outcomes of the head-up tilt test...
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Employment and export specialization patterns versus GDP per capita performance - unifying approach
PublicationThis paper analyses the evolution of specialization patterns along the process of economic development. The scope of the paper is twofold: first of all, it aims at understanding if the evolution of employment specialization is reflected in the same manner in trade specialisation patterns. Secondly, it explores the link between the degree of specialization on one side and cross country GDP per capita performance on the other. We...
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Detecting coupling directions with transcript mutual information: A comparative study
PublicationCausal relationships are important to understand the dynamics of coupled processes and, moreover, to influence or control the effects by acting on the causes. Among the different approaches to determine cause-effect relationships and, in particular, coupling directions in interacting random or deterministic processes, we focus in this paper on information-theoretic measures. So, we study in the theoretical part the difference between...
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A CNN based coronavirus disease prediction system for chest X-rays
PublicationCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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E-dyplomy: uwarunkowania administracyjne i funkcjonalne ich wprowadzenia na polskich uczelniach
PublicationPandemia COVID-19 wymusiła na polskim systemie szkolnictwa wyższego szereg zmian, z których główne dotyczą zmian w zakresie organizacji pracy, cyfryzacji procesów obsługi toku studiów. Przepisy prawa stanowią już o e-teczce, mamy rozporządzenia dotyczące jej prowadzenia, niemniej niewiele uczelni, o ile w ogóle, prowadzi na chwilę obecną akta osobowe studentów w postaci elektronicznej. Jednym z elementów składowych e-teczki jest...
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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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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublicationPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublicationDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Modeling and Accuracy Assessment of Determining the Coastline Course Using Geodetic, Photogrammetric and Satellite Measurement Methods: Case Study in Gdynia Beach in Poland
PublicationThe coastal environment represents a resource from both a natural and economic point of view, but it is subject to continuous transformations due to climate change, human activities, and natural risks. Remote sensing techniques have enormous potential in monitoring coastal areas. However, one of the main tasks is accurately identifying the boundary between waterbodies such as oceans, seas, lakes or rivers, and the land surface....
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation 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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Evaluation of a company’s image on social media using the Net Sentiment Rate
PublicationVast amounts of new types of data are constantly being created as a result of dynamic digitization in all areas of our lives. One of the most important and valuable categories for business is data from social networks such as Facebook. Feedback resulting from the sharing of thoughts and emotions, expressed in comments on various products and services, is becoming the key factor on which modern business is based. This feedback is...
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Reliable Surrogate Modeling of Antenna Input Characteristics by Means of Domain Confinement and Principal Components
PublicationA reliable design of contemporary antenna structures necessarily involves full-wave electromagnetic (EM) analysis which is the only tool capable of accounting, for example, for element coupling or the effects of connectors. As EM simulations tend to be CPU-intensive, surrogate modeling allows for relieving the computational overhead of design tasks that require numerous analyses, for example, parametric optimization or uncertainty...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Generation of large finite-element matrices on multiple graphics processors
PublicationThis paper presents techniques for generating very large finite-element matrices on a multicore workstation equipped with several graphics processing units (GPUs). To overcome the low memory size limitation of the GPUs, and at the same time to accelerate the generation process, we propose to generate the large sparse linear systems arising in finite-element analysis in an iterative manner on several GPUs and to use the graphics...
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Analityka związków chemicznych z grupy bisfenoli w próbkach o skomplikowanym składzie matrycy, w tym pochodzenia biologicznego
PublicationBisfenol A jest substancja produkowaną globalnie na ogromną skalę. Używany jest w produkcji opakowań do żywności, papieru termalnego, wypełnień dentystycznych i całej gamy innych przedmiotów, z którymi człowiek ma na co dzień kontakt. Ze względu na stosunkowo dobrze poznane mechanizmy jego szkodliwego działania, zarówno w kontekście zdrowia ludzkiego jak i dobrostanu ekosystemów, przemysłowe zastosowanie tego związku podlega szeregowi...
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Projektowanie zagregowanych KPI jako metoda implementacji procesów decyzyjnych w zarządzaniu Smart Cities
PublicationCelem artykułu jest prezentacja koncepcji pomiaru wydajności procesów zarządzania miastem z wykorzystaniem koncepcji zagregowanych KPI. W zarządzaniu organizacjami, a w konsekwencji stosowania wspólnych ram projektowych również w zarządzaniu miastami stosuje się powszechnie silosowe KPI obrazujące stany procesów organizacji/miasta. Pojawia się więc pytanie na ile proponowane w artykule zagregowane KPI mogą być stosowane w procesach...
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Konkurencyjność : teoria i praktyka : na przykładzie polskiego eksportu artykułów przemysłowych na unijny rynek w latach 1995-2006
PublicationCzym jest konkurencyjność? Jak w gąszczu definicji konkurencyjności wybrać tę jedyną właściwą dla badanego zjawiska? Czy istnieje teoria konkurencyjności? Jak zmierzyć poziom konkurencyjności przedsiębiorstwa, branży i gospodarki? Rozpoczynając od odpowiedzi na powyższe pytania autorka w sposób niezwykle przystępny i obrazowy przeprowadza wnikliwą analizę konkurencyjności polskiego eksportu na unijne rynki w latach 1995-2006....
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Węzły grupy B
PublicationWęzły grupy B są budowane na przecięciach dróg, z których jedna - z definicji - nie może mieć punktów kolizji, na drugiej natomiast są one dopuszczalne. Węzeł taki oznacza zazwyczaj połączenie drogi ruchu szybkiego z drogami podrzędnymi. Oczywiście, nawet na przecięciu dróg ogólnodostępnych może być zastosowany węzeł grupy A - czyli węzeł całkowicie bezkolizyjny, o ile natężenia i ranga krzyżujących się dróg uzasadniają przyjecie...
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The computational methods in the development of a novel multianalyte calibration technique for potentiometric integrated sensors systems
PublicationIn recent years, integration and miniaturization of ion-selective electrodes (ISEs) have brought many benefits resulting in the possibility of simultaneous determination of the ions concentration in small volume samples. One of the key problems related to the preparation of potentiometric integrated sensors systems (PISSs) is a calibration procedure due to the necessity to calibrate each particular sensor separately. The main aim...
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CFFT columns in road through railroad crossings
PublicationThere were 12801 road through railroad one-level crossings in Poland in 2018. 215 accidents happened at them in 2018. In order to increase safety in rail and road traffic two-level crossings should be used. They are definitely safer and make the traffic more smooth. In the design and construction of two-level intersections of railway and road or path columns of circular cross-section are often used. They can be successfully replaced...
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Extraction of stable foreground image regions for unattended luggage detection
PublicationA novel approach to detection of stationary objects in the video stream is presented. Stationary objects are these separated from the static background, but remaining motionless for a prolonged time. Extraction of stationary objects from images is useful in automatic detection of unattended luggage. The proposed algorithm is based on detection of image regions containing foreground image pixels having stable values in time and...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....