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Catalog Publications

Year 2021
  • Towards Scalable Simulation of Federated Learning

    Federated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...

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  • Wzajemne wykluczanie w programowaniu współbieżnym
    Publication

    - Year 2021

    W rozdziale opisano wzajemne wykluczanie wątków w programach współbieżnych. Przedstawiono zarówno podejście proceduralne (semafory), jak i obiektowe (monitory). Omówiono sposoby działania obu mechanizmów synchronizacji oraz różnice pomiędzy nimi. Sposoby użycia omawianych mechanizmów zostały zilustrowane wzorcami: wzajemnego wykluczania oraz producent–konsument.

  • Zjawisko wyścigu w programowaniu współbieżnym
    Publication

    - Year 2021

    W rozdziale przedstawiono omówienie podstawowego problemu, z jakim, prędzej czy później, styka się każdy programista piszący oprogramowanie wykorzystujące współbieżność. W praktyce będzie to każdy programista starający się w pełni wykorzystywać moc obliczeniową współczesnych wielordzeniowych procesorów i akceleratorów

Year 2020
Year 2019
  • Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
    Publication

    - COMPLEXITY - Year 2019

    Te feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...

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  • An Analysis of Neural Word Representations for Wikipedia Articles Classification
    Publication

    - CYBERNETICS AND SYSTEMS - Year 2019

    One of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...

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  • Bees Detection on Images: Study of Different Color Models for Neural Networks
    Publication

    This paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...

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  • Big Data and the Internet of Things in Edge Computing for Smart City
    Publication

    - Year 2019

    Requests expressing collective human expectations and outcomes from city service tasks can be partially satisfied by processing Big Data provided to a city cloud via the Internet of Things. To improve the efficiency of the city clouds an edge computing has been introduced regarding Big Data mining. This intelligent and efficient distributed system can be developed for citizens that are supposed to be informed and educated by the...

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  • Crowdsourcing-Based Evaluation of Automatic References Between WordNet and Wikipedia

    The paper presents an approach to build references (also called mappings) between WordNet and Wikipedia. We propose four algorithms used for automatic construction of the references. Then, based on an aggregation algorithm, we produce an initial set of mappings that has been evaluated in a cooperative way. For that purpose, we implement a system for the distribution of evaluation tasks, that have been solved by the user community....

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  • Deep learning in the fog

    In the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...

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  • Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
    Publication

    - Year 2019

    This paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...

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  • Distributed Architectures for Intensive Urban Computing: A Case Study on Smart Lighting for Sustainable Cities
    Publication

    - IEEE Access - Year 2019

    New information and communication technologies have contributed to the development of the smart city concept. On a physical level, this paradigm is characterised by deploying a substantial number of different devices that can sense their surroundings and generate a large amount of data. The most typical case is image and video acquisition sensors. Recently, these types of sensors are found in abundance in urban spaces and are responsible...

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  • Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments

    The paper presents state of the art of energy-aware high-performance computing (HPC), in particular identification and classification of approaches by system and device types, optimization metrics, and energy/power control methods. System types include single device, clusters, grids, and clouds while considered device types include CPUs, GPUs, multiprocessor, and hybrid systems. Optimization goals include various combinations of...

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  • Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery

    Non-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...

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  • Evaluating Performance and Accuracy Improvements for Attention-OCR

    In 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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  • Exact-match Based Wikipedia-WordNet Integration

    Ability to link between WordNet synsets and Wikipedia articles allows usage of those resources by computers during natural language processing. A lot of work was done in this field, however most of the approaches focus on similarity between Wikipedia articles and WordNet synsets rather than creation of perfect matches. In this paper we proposed a set of methods for automatic perfect matching generation. The proposed methods were...

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  • Extended investigation of performance-energy trade-offs under power capping in HPC environments
    Publication

    —In the paper we present investigation of performance-energy trade-offs under power capping using modern processors. The results are presented for systems targeted at both server and client markets and were collected from Intel Xeon E5 and Intel Xeon Phi server processors as well as from desktop and mobile Intel Core i7 processors. The results, when using power capping, show that we can find various interesting combinations of...

  • Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
    Publication

    Human-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....

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  • Low-Power WSN System for Honey Bee Monitoring
    Publication

    - Year 2019

    The paper presents a universal low-power system for biosensory data acquisition in scope of bees monitoring. We describe the architecture of the system, energy-saving components as well as we discuss the selection of used sensors. The work focuses on energy optimization in a scope of wireless communication. A custom protocol was implemented, which is the basis for presented energy-efficient devices. Data exchange process during...

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  • Mądre podejmowanie decyzji w sytuacjach problematycznych poprawiajace wybór rozwiązań
    Publication

    - Year 2019

    Przedstawiono klasyfikację problemów od precyzyjnie zdefiniowanych do intuicyjnie zrozumiałych. Dla tych drugich zaproponowano nowy model wyboru rozwiązań uwzględniający ocenę ich zalet i wad. Rozpatrzono zarówno indywidualne jak i zespołowe procedury podejmowania takich decyzji. Zasygnalizowano możliwości występowania nierozstrzygalnych sytuacji, które wymagają mądrych ludzkich działań. Sprowadzają się one do wyboru właściwej...

  • Multi-agent large-scale parallel crowd simulation with NVRAM-based distributed cache

    This paper presents the architecture, main components and performance results for a parallel and modu-lar agent-based environment aimed at crowd simulation. The environment allows to simulate thousandsor more agents on maps of square kilometers or more, features a modular design and incorporates non-volatile RAM (NVRAM) with a fail-safe mode that can be activated to allow to continue computationsfrom a recently analyzed state in...

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  • Performance evaluation of Unified Memory with prefetching and oversubscription for selected parallel CUDA applications on NVIDIA Pascal and Volta GPUs
    Publication

    The paper presents assessment of Unified Memory performance with data prefetching and memory oversubscription. Several versions of code are used with: standard memory management, standard Unified Memory and optimized Unified Memory with programmer-assisted data prefetching. Evaluation of execution times is provided for four applications: Sobel and image rotation filters, stream image processing and computational fluid dynamic simulation,...

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  • Przetwarzanie wielkoskalowych danych w ochronie zdrowia - możliwości i korzyści
    Publication

    - Year 2019

    W rozdziale przedstawiona została idea, pojęcia związane z przetwarzaniem wielkoskalowych danych oraz uogólniona architektura aktualnie wykorzystywanych tego typu systemów w zastosowaniach medycznych. Opisano funkcje oferowane przez bazowe elementy architektury ze szczególnym uwzględnieniem możliwości komponentu analityki dużych zbiorów danych medycznych. Na bazie dostępnej literatury przedmiotu dokonano zestawienia kluczowych...

  • Residual MobileNets

    As modern convolutional neural networks become increasingly deeper, they also become slower and require high computational resources beyond the capabilities of many mobile and embedded platforms. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity. In this paper, we propose a novel residual depth-separable convolution block, which is an improvement of the basic...

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  • Review of the Complexity of Managing Big Data of the Internet of Things
    Publication

    - COMPLEXITY - Year 2019

    Tere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...

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  • Review on Wikification methods
    Publication

    - AI COMMUNICATIONS - Year 2019

    The paper reviews methods on automatic annotation of texts with Wikipedia entries. The process, called Wikification aims at building references between concepts identified in the text and Wikipedia articles. Wikification finds many applications, especially in text representation, where it enables one to capture the semantic similarity of the documents. Also, it can be considered as automatic tagging of the text. We describe typical...

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