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Year 2024
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An intelligent cellular automaton scheme for modelling forest fires
PublicationForest fires have devastating consequences for the environment, the economy and human lives. Understanding their dynamics is therefore crucial for planning the resources allocated to combat them effectively. In a world where the incidence of such phenomena is increasing every year, the demand for efficient and accurate computational models is becoming increasingly necessary. In this study, we perform a revision of an initial proposal...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublicationThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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LSA Is not Dead: Improving Results of Domain-Specific Information Retrieval System Using Stack Overflow Questions Tags
PublicationThe paper presents the approach to using tags from Stack Overflow questions as a data source in the process of building domain-specific unsupervised term embeddings. Using a huge dataset of Stack Overflow posts, our solution employs the LSA algorithm to learn latent representations of information technology terms. The paper also presents the Teamy.ai system, currently developed by Scalac company, which serves as a platform that...
Year 2023
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A Formal Approach to Model the Expansion of Natural Events: The Case of Infectious Diseases
PublicationA formal approach to modeling the expansion of natural events is presented in this paper. Since the mathematical, statistical or computational methods used are not relevant for development, a modular framework is carried out that guides from the external observation down to the innermost level of the variables that have to appear in the future mathematical-computational formalization. As an example we analyze the expansion of Covid-19....
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A multithreaded CUDA and OpenMP based power‐aware programming framework for multi‐node GPU systems
PublicationIn the paper, we have proposed a framework that allows programming a parallel application for a multi-node system, with one or more GPUs per node, using an OpenMP+extended CUDA API. OpenMP is used for launching threads responsible for management of particular GPUs and extended CUDA calls allow to manage CUDA objects, data and launch kernels. The framework hides inter-node MPI communication from the programmer who can benefit from...
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AngioScore: An artificial intelligence tool to assess coronary artery lesions
PublicationThe functionality scope of the AngioScore tool in semi-automatic assessment of stenoses according to the SYNTAX scale was presented. An evaluation of the preliminary accuracy of AngioScore in lesion assessment was performed.
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Antipsychotic drug prescription sequence analysis in relation to death occurrence and cardiometabolic drug usage: A retrospective longitudinal study
PublicationThe potential role of antipsychotics in increasing cardiovascular risk of mortality is still debated. The aim of this study was to assess the death risk associated with sequences of first-generation antipsychotic (FGA) and second-generation antipsychotic (SGA) prescriptions, including clozapine and lithium, and drugs for cardiometabolic diseases. We conducted a retrospective longitudinal analysis involving 84,881 patients who received...
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Application of a stochastic compartmental model to approach the spread of environmental events with climatic bias
PublicationWildfires have significant impacts on both environment and economy, so understanding their behaviour is crucial for the planning and allocation of firefighting resources. Since forest fire management is of great concern, there has been an increasing demand for computationally efficient and accurate prediction models. In order to address this challenge, this work proposes applying a parameterised stochastic model to study the propagation...
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Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA
PublicationLarge-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel’s Programmable Integrated Unffied Memory Architecture (PIUMA) is designed to address these challenges for graph analytics. In this paper, a detailed characterization of GCNs is presented using the Open-Graph Benchmark...
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublicationAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublicationThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublicationGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
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Efficient parallel implementation of crowd simulation using a hybrid CPU+GPU high performance computing system
PublicationIn the paper we present a modern efficient parallel OpenMP+CUDA implementation of crowd simulation for hybrid CPU+GPU systems and demonstrate its higher performance over CPU-only and GPU-only implementations for several problem sizes including 10 000, 50 000, 100 000, 500 000 and 1 000 000 agents. We show how performance varies for various tile sizes and what CPU–GPU load balancing settings shall be preferred for various domain...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublicationHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublicationIn 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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General Provisioning Strategy for Local Specialized Cloud Computing Environments
PublicationThe well-known management strategies in cloud computing based on SLA requirements are considered. A deterministic parallel provisioning algorithm has been prepared and used to show its behavior for three different requirements: load balancing, consolidation, and fault tolerance. The impact of these strategies on the total execution time of different sets of services is analyzed for randomly chosen sets of data. This makes it possible...
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Long‐time scale simulations of virus‐like particles from three human‐norovirus strains
PublicationThe dynamics of the virus like particles (VLPs) corresponding to the GII.4 Houston, GII.2 SMV, and GI.1 Norwalk strains of human noroviruses (HuNoV) that cause gastroenteritis was investigated by means of long-time (about 30 μs in the laboratory timescale) molecular dynamics simulations with the coarse-grained UNRES force field. The main motion of VLP units turned out to be the bending at the junction between the P1 subdomain (that...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Optimization of Bread Production Using Neuro-Fuzzy Modelling
PublicationAutomation of food production is an actively researched domain. One of the areas, where automation is still not progressing significantly is bread making. The process still relies on expert knowledge regarding how to react to procedure changes depending on environmental conditions, quality of the ingredients, etc. In this paper, we propose an ANFIS-based model for changing the mixer speed during the kneading process. Although the...
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Optimization of parallel implementation of UNRES package for coarse‐grained simulations to treat large proteins
PublicationWe report major algorithmic improvements of the UNRES package for physics-based coarse-grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time-consuming energy/force terms...
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Parallel implementation of a Sailing Assistance Application in a Cloud Environment
PublicationSailboat weather routing is a highly complex problem in terms of both the computational time and memory. The reason for this is a large search resulting in a multitude of possible routes and a variety of user preferences. Analysing all possible routes is only feasible for small sailing regions, low-resolution maps, or sailboat movements on a grid. Therefore, various heuristic approaches are often applied, which can find solutions...
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Performance assessment of OpenMP constructs and benchmarks using modern compilers and multi-core CPUs
PublicationConsidering ongoing developments of both modern CPUs, especially in the context of increasing numbers of cores, cache memory and architectures as well as compilers there is a constant need for benchmarking representative and frequently run workloads. The key metric is speed-up as the computational power of modern CPUs stems mainly from using multiple cores. In this paper, we show and discuss results from running codes such as:...
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Photos and rendered images of LEGO bricks
PublicationThe paper describes a collection of datasets containing both LEGO brick renders and real photos. The datasets contain around 155,000 photos and nearly 1,500,000 renders. The renders aim to simulate real-life photos of LEGO bricks allowing faster creation of extensive datasets. The datasets are publicly available via the Gdansk University of Technology “Most Wiedzy” institutional repository. The source files of all tools used during...
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Previous Opinions is All You Need - Legal Information Retrieval System
PublicationWe present a system for retrieving the most relevant legal opinions to a given legal case or question. To this end, we checked several state-of-the-art neural language models. As a training and testing data, we use tens of thousands of legal cases as question-opinion pairs. Text data has been subjected to advanced pre-processing adapted to the specifics of the legal domain. We empirically chose the BERT-based HerBERT model to perform...
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Simulation Environment in Python for Ship Encounter Situations
PublicationTo assess the risk of collision in radar navigation distance-based safety measures such as Distance at the Closest Point of Approach and Time to the Closest Point of Approach are most commonly used. Also Bow Crossing Range and Bow Crossing Time measures are good complement to the picture of the meeting situation. When ship safety domain is considered then Degree of Domain Violation and Time to Domain Violation can be applied. This...
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The Idea of a Student Research Project as a Method of Preparing a Student for Professional and Scientific Work
PublicationIn the paper we present the idea and implementation of a student research project course within the master’s program at the Faculty of Electronics, Telecommunications and Informatics, Gdansk Tech. It aims at preparing students for performing research and scientific tasks in future professional work. We outline the evolution from group projects into research project and the current deployment of both at bachelor’s and master’s levels...
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UNRES-GPU for Physics-Based Coarse-Grained Simulations of Protein Systems at Biological Time- and Size-Scales
PublicationThe dynamics of the virus like particles (VLPs) corresponding to the GII.4 Houston, GII.2 SMV, and GI.1 Norwalk strains of human noroviruses (HuNoV) that cause gastroenteritis was investigated by means of long-time (about 30 μs in the laboratory timescale) molecular dynamics simulations with the coarse-grained UNRES force field. The main motion of VLP units turned out to be the bending at the junction between the P1 subdomain (that...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublicationThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
Year 2022
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Active Learning Based on Crowdsourced Data
PublicationThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...
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Algorytm mrówkowy do zarządzania zasobami sprzętowymi chmury obliczeniowej w przypadku różnych kategorii usług
PublicationZarządzanie chmurą obliczeniową odbywa się na dwóch poziomach: zarządzanie żądaniami klientów chmury oraz zarządzanie jej infrastrukturą, na której te usługi są realizowane. Analizując standardy dotyczące zarządzania usługami, w niniejszym rozdziale skoncentrowano się na drugim poziomie zarządzania, którego głównym celem jest efektywne wykonanie wskazanej usługi (lub usług) na dostępnych zasobach sprzętowych, tak by spełnione zostały...
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Architecture Design of a Networked Music Performance Platform for a Chamber Choir
PublicationThis paper describes an architecture design process for Networked Music Performance (NMP) platform for medium-sized conducted music ensembles, based on remote rehearsals of Academic Choir of Gdańsk University of Technology. The issues of real-time remote communication, in-person music performance, and NMP are described. Three iterative steps defining and extending the architecture of the NMP platform with additional features to...
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Architektury klasyfikatorów obrazów
PublicationKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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Badanie wpływu przydziału rdzeni procesora na wydajność w środowisku skonteneryzowanym oparte na wybranym serwerze warstawy pośredniej w IoT - obserwacje i rekomendacje
PublicationInternet Rzeczy cieszy się coraz większym zainteresowaniem. Za- gadnienie to jest szeroko omawiane zarówno w środowisku nauko- wym, jak i w przemyśle. Ze względu na jego wielowymiarowość jest wiele aspektów, które wymagają zbadania i obserwacji. Jednym z nich jest efektywne wdrożenie i uruchomienie aplikacji w kontekście wykorzystania zasobów sprzętowych. Innym, równie istotnym, za- gadnieniem jest konteneryzacja platform IoT....
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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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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublicationImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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DEPO: A dynamic energy‐performance optimizer tool for automatic power capping for energy efficient high‐performance computing
PublicationIn the article we propose an automatic power capping software tool DEPO that allows one to perform runtime optimization of performance and energy related metrics. For an assumed application model with an initialization phase followed by a running phase with uniform compute and memory intensity, the tool performs automatic tuning engaging one of the two exploration algorithms—linear search (LS) and golden section search (GSS), finds...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublicationHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublicationIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Greencoin – educational information system for ecoinclusion and empowering urban adaptability.
PublicationThe SARS-CoV19 pandemic exposed a broad spectrum of challenges for modern cities, societies and the environment at large. The post-Covid transformation requires new social, ecological and educational solutions, adjusted to modern challenges, but also equipped with technological advances that allow for digital inclusion and sustainable urban development to benefit the local economy and society. Many information systems designed...
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How to Sort Them? A Network for LEGO Bricks Classification
PublicationLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Inteligentne zarządzanie usługami chmurowymi
PublicationRozwój chmur obliczeniowych stanowi wyzwanie dla nowych efektywnych metod zarządzania zasobami chmurowymi, zwłaszcza, że oprócz usług typu SaaS rozwija się nowe kategorie usług jak obliczenia brzegowe czy wielochmurowe. W pracy zaproponowano ogólny model zarządzania usługami oraz efektywne procedury alokacji zasobów. Podkreślono potrzebę oszacowania parametrów zasobów chmury by zapewnić wykonanie żądanych usług. Przedstawiono również...
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Investigation of Performance and Configuration of a Selected IoT System—Middleware Deployment Benchmarking and Recommendations
PublicationNowadays Internet of Things is gaining more and more focus all over the world. As a concept it gives many opportunities for applications for society and it is expected that the number of software services deployed in this area will still grow fast. Especially important in this context are properties connected with deployment such as portability, scalability and balance between software requirements and hardware capabilities. In...
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Metody ekstrakcji ustrukturalizowanej treści z Wikipedii
PublicationWikipedia jest od dawna przedmiotem zainteresowania badaczy. Jednym z obszarów zainteresowania jest pozyskiwanie wiedzy z treści Wikipedii a to wymaga parsowania tekstu artykułów. W tym rozdziale przedstawiono analizę porównawczą różnych możliwości parsowania treści Wikipedii, wskazując problemy, z jakimi muszą się mierzyć autorzy parserów. Dzięki temu można zrozumieć, dlaczego proces wydobywania wiedzy z Wikipedii jest trudny
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Performance Assessment of Using Docker for Selected MPI Applications in a Parallel Environment Based on Commodity Hardware
PublicationIn the paper, we perform detailed performance analysis of three parallel MPI applications run in a parallel environment based on commodity hardware, using Docker and bare-metal configurations. The testbed applications are representative of the most typical parallel processing paradigms: master–slave, geometric Single Program Multiple Data (SPMD) as well as divide-and-conquer and feature characteristic computational and communication...
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Privacy-Preserving, Scalable Blockchain-Based Solution for Monitoring Industrial Infrastructure in the Near Real-Time
PublicationThis paper proposes an improved monitoring and measuring system dedicated to industrial infrastructure. Our model achieves security of data by incorporating cryptographical methods and near real-time access by the use of virtual tree structure over records. The currently available blockchain networks are not very well adapted to tasks related to the continuous monitoring of the parameters of industrial installations. In the database...
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Segmentacja obrazów medycznych przy ograniczonej liczbie adnotacji
PublicationW dziedzinie badań klinicznych i opieki zdrowotnej tradycyjne podejście w uczeniu głębokim polegające na wykorzystaniu dużych zbiorów danych jest trudne w realizacji. Przyczyną takiego stanu rzeczy są koszty znakowania obrazów medycznych, zwłaszcza w przypadku segmentacji obrazów medycznych. Jest to żmudna operacja, która zazwyczaj wymaga intensywnego znakowania pikseli wykonanego przez ekspertów – lekarzy. W tym rozdziale zaprezentowano...
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Semantyczne wektory słów
PublicationNiniejszy rozdział stanowi wstęp do rozległego zagadnienia, jakim są semantyczne wektory słów. W szczególności skupiono się w niej na metodach automatycznego tworzenia tego typu reprezentacji na podstawie dużych zbiorów danych. Omówiono także różne możliwe interpretacje tego, czym tak naprawdę jest podobieństwo słów, oraz przedstawiono wybrane zastosowania tego typu modeli.
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Synchronizacja wiedzy w systemach agentowych
PublicationAgenty inteligentne są jednym z komponentów stosowanych w pro- jektowaniu rozproszonych inteligentnych systemów obliczeniowych. W rozdziale wskazano istotne aspekty systemów agentowych, a na- stępnie omówiono wybrane metody synchronizacji wiedzy między agentami będącymi częścią systemu agentowego. Omówiono podej- ście właściwe dla agentów zaufanych oraz jego modyfikację dla agen- tów, które mogą celowo próbować wprowadzać inne...