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Search results for: neural embeddings
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The Reactivity of Phosphanylphosphinidene Complexes of Transition Metals Toward Terminal Dihaloalkanes
PublicationThe reactivities of phosphanylphosphinidene complexes [(DippN)2W(Cl)(η2-P−PtBu2)]− (1), [(pTol3P)2Pt(η2- P=PtBu2)] (2), and [(dppe)Pt(η2-P=PtBu2)] (3) toward dihaloalkanes and methyl iodide were investigated. The reactions of the anionic tungsten complex (1) with stochiometric Br(CH2)nBr (n = 3, 4, 6) led to the formation of neutral complexes with a tBu2PP(CH2)3Br ligand or neutral dinuclear complexes with unusual tetradentate...
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Selected biotrends in development of epoxy resins and their composites
PublicationEpoxy resins and their fibre or particulate composites are widely used in various industries, including building, naval, aircraft, automotive and aerospace. Modern polymer science and technology focus on the development of green polymers and composites. There are two major areas of interest in the case of epoxy resins: the development of bio-based resins and the production of composites with natural fibers. One of the most interesting...
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Novel approach to interference analysis of glucose sensing materials coated with Nafion
PublicationA gold-based sensing platform, TiND | AuNP | Nafion, was prepared as an exemplary electrode material exhibiting a response to glucose in a neutral solution. The change of electrochemical properties after exposure to glucose and interference compounds such as vitamin C, glycine, urea, paracetamol and acetylsalicylic acid was tested.
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The Use of an Autoencoder in the Problem of Shepherding
PublicationThis paper refers to the problem of shepherding clusters of passive agents consisting of a large number of objects by a team of active agents. The problem of shepherding and the difficulties that arise with the increasing number of data describing the location of agents have been described. Several methods for reducing the dimensionality of data are presented. Selected autoencoding method using a Restricted Boltzmann Machine is...
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Signal Processing in the Investigation of Two-phase Liquid-gas Flow by Gamma-ray Absorption
Publicationn this paper, the use of the gamma-absorption method applied in the investigation of the two-phase liquid-gas flow in the pipeline is described. An example of its application to the air transported by water in a horizontal pipeline is evaluated. In the measurements, Am-241 radioactive sources and probes with Nal (Tl) scintillation crystals have been used. The signals from the radiometric set were used to determine the velocity...
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Evaluating Performance and Accuracy Improvements for Attention-OCR
PublicationIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
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KEMR-Net: A Knowledge-Enhanced Mask Refinement Network for Chromosome Instance Segmentation
PublicationThis article proposes a mask refinement method for chromosome instance segmentation. The proposed method exploits the knowledge representation capability of Neural Knowledge DNA (NK-DNA) to capture the semantics of the chromosome’s shape, texture, and key points, and then it uses the captured knowledge to improve the accuracy and smoothness of the masks. We validate the method’s effectiveness on our latest high-resolution chromosome...
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Collaborative Data Acquisition and Learning Support
PublicationWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Dissociative multi-photon ionization of isolated uracil and uracil-adenine complexes
PublicationRecent multi-photon ionization (MPI) experiments on uracil revealed a fragment ion at m/z 84 that was proposed as a potential marker for ring opening in the electronically excited neutral molecule. The present MPI measurements on deuterated uracil identify the fragment as C3H4N2O+ (uracil+ less CO), a plausible dissociative ionization product from the theoretically predicted open-ring isomer. Equivalent measurements on thymine...
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THE USE OF GREEN LOGISTICS ELEMENTS DURING THE CONSTRUCTION OF OFFSHORE VESSELS
PublicationThe article is aimed at the presentation referring to the use of green logistics elements during the construction of the offshore vessels in the following aspects: collection, removal and utilisation of any waste that is harmful for natural environment, elimination of the negative impact that such waste can have on natural environment and the search for the optimal solutions as regards these aspects.
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The ONETEP linear-scaling density functional theory program
PublicationWe present an overview of the ONETEP program for linear-scaling density functional theory (DFT) calculations with large basis set (planewave) accuracy on parallel computers. The DFT energy is computed from the density matrix, which is constructed from spatially localized orbitals we call Non-orthogonal Generalized Wannier Functions (NGWFs), expressed in terms of periodic sinc (psinc) functions. During the calculation, both the...
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Vehicle classification based on soft computing algorithms
PublicationExperiments and results regarding vehicle type classification are presented. Three classes of vehicles are recognized: sedans, vans and trucks. The system uses a non-calibrated traffic camera, therefore no direct vehicle dimensions are used. Various vehicle descriptors are tested, including those based on vehicle mask only and those based on vehicle images. The latter ones employ Speeded Up Robust Features (SURF) and gradient images...
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The trajectories of the financial crisis of companies at risk of bankruptcy
PublicationThis article concerns the assessment of the trajectory of the collapse of enterprises in Central Europe. The author has developed a model of a Kohonen artificial neural network. This model was used to determine 6 different classes of risk and was allowed to graphically determine the 5- to 10-year trajectory of going bankrupt. The study used data on 140 companies listed on the Warsaw Stock Exchange. This population was divided into...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublicationDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Monitoring the gas turbine start-up phase on the platform using a hierarchical model based on Multi-Layer Perceptron networks
PublicationVery often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition...
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Krajobraz wiejski i turystyka. Poszukiwanie równowagi pomiędzy widzeniem i wizerunkiem wsi
PublicationNajważniejszym składnikiem marki wsi jest krajobraz. Wizerunek wsi kreowany w turystyce i dostępny widok różnią się jednak coraz bardziej: przekaz reklamowy identyfikuje wieś z przyrodą oraz ciszą i spokojem; wieś realna stanowi, najczęściej dysharmonijną, mozaikę wiejsko-miejskiego zagospodarowania. Konfrontacja dostarczonego przez turystykę komunikatu z oglądanym krajobrazem podważa wiarygodność marki wsi, co stanowi zagrożenie...
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Rozdział 3.2. W: [Praca zbiorowa] Materiały do monografii przyrodniczej re-gionu gdańskiego. Gdańsk: Marpress**2002 s. 69-70. Tom 8 Diagnoza stanu i koncepcja ochrony środowiska przyrodniczo-kulturowe- go w województwie pomorskim. Diagnosis of natural-cultural environment´scondition and the idea of its protection in Pomeranian Voivodship. Red. A.Kostarczyk, M. Przewoźniak.
Publication...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublicationHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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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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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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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Next Generation Digital
PublicationThe paper outlines the major objectives of the MENAID research project, eimed at novel architectures of digital documents. Such documents will enable reduction of information overflow and strain, a major threat to the growth of a digital society. They will be forward compatible, technology neutral and lightweight, allowing workers of network organizations to use personal devices of any type.
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Charge dependence of fragmentation process induced by ion collisions with furan molecule
PublicationThe goal of this work is to describe the system evolution after ion-molecule interaction. We combine different quantum chemistry and statistical mechanics approaches in order to give extended description of the process. Herein we report on a recent study of the fragmentation mechanism of neutral, singly- and doubly-ionized furan molecule in the gas phase.
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Syntheses, Structures and Reactivity of Terminal Phosphido Complexes of Iron(II) Supported by a β-Diketiminato Ligand
PublicationWe report the synthesis of the first series of terminal phosphido iron complexes supported by a β‐diketiminato ligand (Dippnacnac) and their catalytic activity in dehydrocoupling of secondary phosphines. Anionic and neutral mono‐ or diphosphido complexes were obtained from the reaction of [(Dippnacnac)FeCl2Li(dme)2] with the R2PLi (R = iPr, tBu, Cy, Ph) phosphides by tuning the stoichiometric ratio, polarity of the solvent, and...
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Mineral oil-based hydrostatic drives as the basic drive systems in the construction of offshore eqiupment projects
PublicationThe aim of this article is to present the components used in the production of mineral oil-based hydrostatic drives as the basic drive systems for the offshore industry. The article contains de-scriptions of the components of the said systems, with the description of their suitability for mi-neral oil operation and offshore applications.
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Glioblastoma-derived spheroid cultures as an experimental model for analysis of EGFR anomalies
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JERUSALEM ARTICHOKE (HELIANTHUS TUBEROSUS L.) AS ENERGY RAW MATERIAL
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QUALITY OF SWEET POTATO AS A RAW MATERIAL FOR FOOD PROCESSING
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Screening of predicted synergistic multi-target therapies in glioblastoma identifies new treatment strategies
PublicationAbstract Background IDH-wildtype glioblastoma (GBM) is a highly malignant primary brain tumor with a median survival of 15 months after standard of care, which highlights the need for improved therapy. Personalized combination therapy has shown to be successful in many other tumor types and could be beneficial for GBM patients. Methods We performed the largest drug combination screen to date in GBM, using a high-throughput effort...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublicationIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Efficiency comparison of selected endoscopic video analysis algorithms
PublicationIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Style Transfer for Detecting Vehicles with Thermal Camera
PublicationIn this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...
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Gelatin-Modified Polyurethanes for Soft Tissue Scaffold
PublicationRecently, in the field of biomaterials, which are being designed for soft tissue scaffolding, is growing the interest of their modification with natural polymers. Synthetic polymers are often hard, not easy to process and they do not possess fine biodegradable profile. From the other hand natural polymers are biocompatible, but weak when used alone. The combination of natural and synthetic polymers gives the suitable properties...
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Effective Short -term Forecasting of Wind Farms Power
PublicationForecasting a specific wind farm's generation capacity within a 24 hour perpective requires both a reliable forecast of wind, as well as supporting tools. This tool is a dedicated model of wind farm power. This model should include not only general rules of wind to mechanical energy conversion, but also the farm's specific features. This paper present analytical, statistical, and neuron models of wind farm power. The study is based...
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Invariant measures for interval translations and some other piecewise continuous maps
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The use of modified vegetable oil from Crambe abyssinica as a lubricant base for the food industry
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Hydrogen migration in formation of NH(A3Π) radicals in photodissociations of isoxazole and pyridine molecules
PublicationIn the present study, the H atom migration was observed in the photodissociation processes of the isoxazole and pyridine molecules in the gas-phase, applying the photon-induced fluorescence spectroscopy (PIFS).
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Nano-structured Pt embedded in the acidic salts of heteropolymolybdate matrices: MS XAFS study
PublicationMultiple-scattering extended X-ray absorption fine structure (MS EXAFS) study combined with TEM and XRD analysis of a novel Pt-based catalyst operating at low temperature fuel cells (FCs) is presented. Innovation in the case of the considered catalyst resides in the use of a porous inorganic matrix of acidic heteropolymolybdate salts as a catalyst support. Obtained results show the relation between the matrix composition and the...
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Valence and ionic lowest-lying electronic states of small esters studied by high resolution vacuum ultraviolet photoabsorption, photoelectron spectroscopy and ab initio calculations
PublicationEsters are an important class of oxygenated volatile organic compounds used in food flavorings, perfumes and other cosmetic products. They are present in fruits and pheromones and are emitted to the atmosphere naturally. Esters are also formed in the atmosphere as a product of the oxidation of ethers. Some of them form poly-molecule chains and are used in plastics. Phosphoesters form DNA backbone, while nitroesters are known for...
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Cooperation of mono- and bi-articular muscles: human lower limb
PublicationObjectives: The aim of this study was to create and analyze a Pareto-optimal problem that would describe cooperation between mono- and bi-articulate lower limb muscles in sagittal plane. Methods: Equations describing the problem were derived and analyzed, additional constrains were introduced and experimental verification based on gait video analysis was performed. Results: Uncertainty of Pareto-optimal solution is shown for the...
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Spectroscopic studies of Nb-doped tricalcium phosphate glass-ceramics prepared by sol-gel method
PublicationCalcium-phosphate based glasses and glass-ceramics play a crucial role in the tissue engineering development. Apart from their high biocompatibility and excellent ability to undergo varying degrees of resorbability1, they exhibit relatively high bioactivity and due to that they are commonly used as bone and dental implants. A substantial research effort is devoted to improve calcium-phosphate materials physico-chemical properties...
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Dissociative photo-double-ionization of the isoxazole molecules
PublicationThe five-membered heterocyclic rings are incorporated into a wide variety of structures that play a vital role in many biochemical processes. In particular, the isoxazole molecule appears in many bioactive compounds due to its unique ring structure that consists of one oxygen atom and one nitrogen atom at adjacent positions. The unique atomic composition and bond arrangement of isoxazole imply its specific electronic properties...
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VUV photofragmentation of the six-membered heterocyclic molecules containing oxygen
PublicationCancer is a significant public health concern worldwide, which results in millions of deaths each year. The standard cure routine for cancer is surgery, and nowadays, radiotherapy or a hadrontherapy. Depending on the type of cancer, patients may undergo additional treatment, including targeted therapy. A combination of radio- or hadron-therapy with proper drug treatment can inhibit the proliferation of cancer cells and thus can...