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Wyniki wyszukiwania dla: HIGH-VALUE DATASETS
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A review of explainable fashion compatibility modeling methods
PublikacjaThe paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general characteristics of publicly available datasets that are related to the fashion compatibility recommendation task. Finally, we analyzed the representation bias of datasets, fashion-based algorithms’...
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Parallel Computations of Text Similarities for Categorization Task
PublikacjaIn this chapter we describe the approach to parallel implementation of similarities in high dimensional spaces. The similarities computation have been used for textual data categorization. A test datasets we create from Wikipedia articles that with their hyper references formed a graph used in our experiments. The similarities based on Euclidean distance and Cosine measure have been used to process the data using k-means algorithm....
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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A study of nighttime vehicle detection algorithms
Dane BadawczeThis dataset is from my master's thesis "A study of nighttime vehicle detection algorithms". It contains both raw data and preprocessed dataset ready to use. In the pictures below you can see how images were annotated.
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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation
PublikacjaModern data acquisition technologies provide large datasets that are not always necessary in its entirety to properly accomplish the goal of the study. In addition, such datasets are often cumbersome for rational processing, and their processing is time and labour consuming. Therefore, methods that enable to reduce the size of the measurement dataset, such as the generalization of the Digital Terrain Model (DTM) or the reduction...
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Application of the Optimum Dataset Method in Archeological Studies on Barrows
PublikacjaLight Detection and Ranging (LiDAR) became one of the technologies used in archaeological research. It allows for relatively easy detection of archaeological sites that have their own field form, e.g.: barrows, fortresses, tracts, ancient fields [1]. As a result of the scanning, the so-called point cloud is obtained, often consisting of millions of points. Such large measurement datasets are very time-consuming and labor-intensive...
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Towards Effective Processing of Large Text Collections
PublikacjaIn the article we describe the approach to parallelimplementation of elementary operations for textual data categorization.In the experiments we evaluate parallel computations ofsimilarity matrices and k-means algorithm. The test datasets havebeen prepared as graphs created from Wikipedia articles relatedwith links. When we create the clustering data packages, wecompute pairs of eigenvectors and eigenvalues for visualizationsof...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublikacjaSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublikacjaIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection
PublikacjaAs a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...
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AffecTube — Chrome extension for YouTube video affective annotations
PublikacjaThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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MULTI-OBJECTIVE OPTIMIZATION PROBLEM IN THE OptD-MULTI METHOD
PublikacjaNew measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called...
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Expectation-Maximization Model for Substitution of Missing Values Characterizing Greenness of Organic Solvents
PublikacjaOrganic solvents are ubiquitous in chemical laboratories and the Green Chemistry trend forces their detailed assessments in terms of greenness. Unfortunately, some of them are not fully characterized, especially in terms of toxicological endpoints that are time consuming and expensive to be determined. Missing values in the datasets are serious obstacles, as they prevent the full greenness characterization of chemicals. A featured...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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A framework estimating the minimum sample size and margin of error for maritime quantitative risk analysis
PublikacjaThe average accident frequency is essential for quantitative risk analysis and is conventionally estimated from accident statistics. This paper has systematically synthesised the knowledge on statistical errors and offered the missing instructions, a framework, for determining the minimum sample size and the margin of error (MOE) when calculating the average accident frequency from an accident database at hand. We have applied...
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Plasma models, contribution matrix for detector setup and generated projections for plasma emissivity reconstruction in fusion devices
Dane BadawczeThe original plasma models for fusion devices, together with the complementary detector setup in the form of a contribution matrix and generated projections. Samples are packed inside a Plasma Tomography Format (PTF) files which is a part of the Plasma Tomography in Fusion Devices Python package, and inside the general JSON format. The constructed dataset...
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Jaroslaw Spychala dr
OsobyOprócz bardzo dobrego wykształcenia osoba posiada również wieloletnie doświadczenie zawodowe, które jest poświadczeniem tego, że potrafi wykorzystać swoją wiedzę teoretyczną w praktycznych działaniach. Doświadczenie zawodowe jest bardzo bogate i rozbudowane. Ze względu na nabyte całkiem nowe umiejętności zwiększa się atrakcyjność doświadczonego pracownika. Są to między innymi kreatywne myślenie, zorientowanie na cel, odporność...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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Client-side versus server-side geographic data processing performance comparison: Data and code
PublikacjaThe data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-point and multi-polygon data of different scales and volumes, representing real-world geographic features. The datasets cover the area...
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Towards New Mappings between Emotion Representation Models
PublikacjaThere are several models for representing emotions in affect-aware applications, and available emotion recognition solutions provide results using diverse emotion models. As multimodal fusion is beneficial in terms of both accuracy and reliability of emotion recognition, one of the challenges is mapping between the models of affect representation. This paper addresses this issue by: proposing a procedure to elaborate new mappings,...
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Parameters of land reference points in the Gdynia region and the Free-air anomaly grid of the South Baltic
Dane BadawczeThe data was registered during the campaign to verify the catalog value of the absolute point coordinates [point 5403 (POLREF-GORA DONAS)] of the national gravimetric control network. The data was recorded in two three-hour stationary measurement campaigns at the following points: Rozewie of the EUREF-POL network, Góra Donas POLREF, and mareograph points...
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The analysis of the expression of hTERT in anthraquinone-treated NSCLC cells
Dane BadawczeThe datasets showcase an analysis of hTERT relative gene expression in NSCLC cells treated with anthraquinone, quantified as fold change compared to DMSO-treated control cells, using the comparative CT method.
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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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Wind speed, wind direction and solar radiation datasets; wind and solar energy resources analysis
Dane BadawczeDataset contain the results of wind speed, wind direction and solar radiation for wind and solar energy resources analysis performed in years 2008 and 2009. Application for efficiency and profitability of solar and wind power plants anaylsis and for energy generation forecasting algorithms design and anaysis. Datasets used in doctoral dissertations,...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Analysis of cellular senescence following anthraquinone treatment in A549, H226, and H460 cells
Dane BadawczeThe datasets comprise microscopic images of A549, H226, and H460 cells following treatment with anthraquinones and staining with senescence-associated β-galactosidase. The images were captured using an Olympus BX60 microscope (Tokyo, Japan).
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A CNN based coronavirus disease prediction system for chest X-rays
PublikacjaCoronavirus 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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RDF dataset profiling - a survey of features, methods, vocabularies and applications
PublikacjaThe Web of Data, and in particular Linked Data, has seen tremendous growth over the past years. However, reuse and take-up of these rich data sources is often limited and focused on a few well-known and established RDF datasets. This can be partially attributed to the lack of reliable and up-to-date information about the characteristics of available datasets. While RDF datasets vary heavily with respect to the features related...
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thestats: An Open-Data R Package for Exploring Turkish Higher Education Statistics
PublikacjaThere are open datasets available for official statistics, finance, education, and a variety of other domains. The open datasets are published by third-party vendors as well as official authorities. For example, The Turkish Higher Education Council maintains a web portal dedicated to higher education in Türkiye. Detailed datasets about universities, faculties, and departments can be obtained from the portal. Using the data provided...
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Effect of C-1748 derivatives on the biofilm formation of C. albicans ATCC 10231 cells
Dane BadawczeThe datasets contain the results of the impact of five C-1748 derivatives (IKE28 - IKE32) on the biofilm formation of Candida albicans strain ATCC 10231 cells. Photographic documentation prepared with the TECAN Spark 10M titration plate reader.
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Effect of C-1748 derivatives on the morphological transformation of C. albicans ATCC 10231 cells
Dane BadawczeThe datasets contain the results of the impact of five C-1748 derivatives (IKE28 - IKE32) on morphological transformation of Candida albicans strain ATCC 10231 cells. Photographic documentation prepared with the TECAN Spark 10M titration plate reader.
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Effect of novel bisacridines (IKE16, IKE18, IKE19, IKE21) and IE10 on the biofilm formation of C. albicans ATCC 10231 cells
Dane BadawczeThe datasets contain the results of the impact of novel bisacridines (IKE16, IKE18, IKE19, IKE21) and IE10 on the biofilm formation of Candida albicans strain ATCC 10231 cells. Photographic documentation prepared with the TECAN Spark 10M titration plate reader.
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Wikipedia Articles Representation with Matrix'u
PublikacjaIn the article we evaluate different text representation methods used for a task of Wikipedia articles categorization. We present the Matrix’u application used for creating computational datasets ofWikipedia articles. The representations have been evaluated with SVM classifiers used for reconstruction human made categories.
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Categorization of Wikipedia articles with spectral clustering
PublikacjaAbstract. The article reports application of clustering algorithms for creating hierarchical groups withinWikipedia articles.We evaluate three spectral clustering algorithms based on datasets constructed with usage ofWikipedia categories. Selected algorithm has been implemented in the system that categorize Wikipedia search results in the fly.
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The Optimum Dataset method – examples of the application
PublikacjaData reduction is a procedure to decrease the dataset in order to make their analysis more effective and easier. Reduction of the dataset is an issue that requires proper planning, so after reduction it meets all the user’s expectations. Evidently, it is better if the result is an optimal solution in terms of adopted criteria. Within reduction methods, which provide the optimal solution there is the Optimum Dataset method (OptD)...
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Determination of the minimum inhibitory concentration of C-1305 derivatives (IKE1-IKE8) against Candida strains
Dane BadawczeThe datasets contain the results of determining the minimum inhibitory concentration of acridone derivatives against C. albicans ATCC 10231, C. glabrata ATCC 90030, C. krusei ATCC 6258 and C. parapsilosis ATCC 22019 by the modified M27-A3 specified by the CLSI.
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis
PublikacjaMost of the research in the field of emotion recognition is based on datasets that contain data obtained during affective computing experiments. However, each dataset is described by different metadata, stored in various structures and formats. This research can be counted among those whose aim is to provide a structural and semantic pattern for affective computing datasets, which is an important step to solve the problem of data...
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Methods for quality improvement of multibeam and LiDAR point cloud data in the context of 3D surface reconstruction
PublikacjaPoint cloud dataset is the transitional data model used in several marine and land remote-sensing applications. During further steps of processing, the transformation of point cloud spatial data to more complex models containing higher order geometric structures like edges and facets may be possible, if an appropriate quality level of input data is provided. Point cloud datasets usually contain a considerable amount of undesirable...
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Determination of the minimum inhibitory concentration of C-1330 derivatives (IKE9-IKE14) against Candida strains
Dane BadawczeThe datasets contain the results of determining the minimum inhibitory concentration of C-1330 derivatives (IKE9-IKE14) against C. albicans ATCC 10231, C. glabrata ATCC 90030, C. krusei ATCC 6258 and C. parapsilosis ATCC 22019 by the modified M27-A3 specified by the CLSI.
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublikacjaIn 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....
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General concept of reduction process for big data obtained by interferometric methods
PublikacjaInterferometric 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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Determination of the minimum inhibitory concentration of C-1311 derivatives (C-1296, C-1410, Compound 1, Compound 1-R8) against Candida strains
Dane BadawczeThe datasets contain the results of determining the minimum inhibitory concentration of imidazoacridinone derivatives against C. albicans ATCC 10231, C. glabrata ATCC 90030, C. krusei ATCC 6258 and C. parapsilosis ATCC 22019 and C. albicans clinical strains by the modified M27-A3 specified by the CLSI.
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Determination of Changes in Viscosity of Hydrogel Depending on Shear Rates
PublikacjaThe datasets entitled Determination of changes in viscosity of hydrogel depending on shear rate contain the results of viscosity measurements using a Brookfield viscometer, with different kinds of spindles and shear rates. The data allowed the used hydrogel preparations to be characterised and their functional parameters, as substances modifying the rheology of thickeners and determining the effect of shear rate on the viscosity...