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Search results for: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES
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Features of a radial user interface to search engines
PublicationThe paper is concerned with a new type of user interface to search engines. Instead of presenting search results in a form of a ranked list, the results are presented in radial arrangement. In the center of the interface the most relevant web page is presented. Other web pages are located around the central one. The location of a web page depends on two factors: its relevance to the query and its content. The relevance has influence...
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublicationIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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Performance Analysis of Multicast Video Streaming in IEEE 802.11 b/g/n Testbed Environment
PublicationThe aim of the work is to analyse capabilities and limitations of different IEEE 802.11 technologies (IEEE 802.11 b/g/n), utilized for both multicast and unicast video streaming transmissions directed to mobile devices. Our preliminary research showed that results obtained with currently popular simulation tools can be drastically different than these possible in real-world environment, so, in order to correctly evaluate performance...
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EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublicationFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
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Approximation task decomposition for artificial neural network.
PublicationW pracy przedstawiono wpływ dekompozycji zadania na czasochłonność projektowania oraz dokładność i szybkość obliczeń sztucznej sieci neuronowej wykorzystanej do rozwiązania rzeczywistego problemu technicznego, którego matematyczny model był znany. Celem obliczeń prowadzonych przez sieć neuronową było określenie wartości współczynnika przepływu m na podstawie znajomości wartości: przewodności dźwiękowej C i średnicy przewodu d (a...
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Data Partitioning and Task Management in the Clustered Server Layer of the Volunteer-based Computation System
PublicationWhile the typical volunteer-based distributed computing system focus on the computing performance, the Comcute system was designed especially to keep alive in the emergency situations. This means that designers had to take into account not only performance, but the safety of calculations as well. Quadruple-layered architecture was proposed to separate the untrusted components from the core of the system. The main layer (W) consists...
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Generic emergence of classical features in quantum Darwinism
PublicationQuantum Darwinism posits that only specific information about a quantum system that is redundantly proliferated to many parts of its environment becomes accessible and objective, leading to the emergence of classical reality. However, it is not clear under what conditions this mechanism holds true. Here we prove that the emergence of classical features along the lines of quantum Darwinism is a general feature of any quantum dynamics:...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Temporal pattern of wildlife-train collisions in Poland
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Multi agent grid systems
PublicationThis chapter presents an idea of merging grid and volunteer systemswith multi agent systems. It gives some basics concerning multi agentsystem and the most followed standard. Some deliberations concerningsuch an existing systems were made in order to finally present possibilities of introducing agents into the Comcute system.
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Bimodal Emotion Recognition Based on Vocal and Facial Features
PublicationEmotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...
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Modelling of some stealth features for a small navy ship at the concept design stage - part II
PublicationIn the paper a few problems associated with modelling the basic stealth features for a small ship at the concept design stage are introduced. One problem concerns the modification of the immersed ship hull using the rapid change of the ship loading condition. The second is associated with the modification of the ship boundary layer by the hull skin cover. The other stealth features of the ship are not presented in this paper. The...
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Edge-Computing based Secure E-learning Platforms
PublicationImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...
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Assessing Industry 4.0 Features Using SWOT Analysis
PublicationThis paper assesses some features of industry 4.0 by using SWOT analysis that affects the adoption and implementation of industry 4.0. The paper identifies the strengths, weaknesses, opportunities, and threats related to industry 4.0. By the consideration of these four groups of factors, the industrial practitioners can understand how to implement industry 4.0. Moreover, industrial practitioners can use the strengths/opportunities...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublicationA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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Federated Learning in Healthcare Industry: Mammography Case Study
PublicationThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublicationA concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...
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Real-Time Gastrointestinal Tract Video Analysis on a Cluster Supercomputer
PublicationThe article presents a novel approach to medical video data analysis and recognition. Emphasis has been put on adapting existing algorithms detecting le- sions and bleedings for real time usage in a medical doctor's office during an en- doscopic examination. A system for diagnosis recommendation and disease detec- tion has been designed taking into account the limited mobility of the endoscope and the doctor's requirements. The...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Software Factory project for enhancement of student experiential learning
PublicationProviding opportunities for students to work on real-world software development projects for real customers is critical to prepare students for the IT industry. Such projects help students to understand what they will face in the industry and experience real customer interaction and challenges in collaborative work. To provide this opportunity in an academic environment and enhance the learning and multicultural teamwork experience,...
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Implementation and Validation of Multisinusoidal, Fast Impedance Measurements in Atomic Force Microscope Contact Mode.
PublicationThis study presents a novel approach to impedance measurements. The methodology discussed is limited to contact in the sample-probe system under ambient conditions without the presence of electrolyte. Comparison with results of direct and alternating current measurements for well-defined metallic surfaces are made. In spite of idealization related to the type of contact examined, the proposed technique provides an improvement of...
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Implementation and Validation of Multisinusoidal, Fast Impedance Measurements in Atomic Force Microscope Contact Mode
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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MSIS sonar image segmentation method based on underwater viewshed analysis and high-density seabed model
PublicationHigh resolution images of Mechanically Scanned Imaging Sonars can bring detailed representation of underwater area if favorable conditions for acoustic signal to propagate are provided. However to properly asses underwater situation based solely on such data can be challenging for less than proficient interpreter. In this paper we propose a method to enhance interpretative potential of MSIS image by dividing it in to subareas depending...
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Multi-state multi-reference Møller-Plesset second-order perturbation theory for molecular calculations
PublicationThis work presents multi‐state multi‐reference Møller–Plesset second‐order perturbation theory as a variant of multi‐reference perturbation theory to treat electron correlation in molecules. An effective Hamiltonian is constructed from the first‐order wave operator to treat several strongly interacting electronic states simultaneously. The wave operator is obtained by solving the generalized Bloch equation within the first‐order...
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Segmentation of Passenger Electric Cars Market in Poland
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City as a product. Architecture as an Economic Instrument. Are Global Cities People-Friendly Places?
PublicationWhile spending time in our everyday urban environment do we ever think how particular architecture influences the economic value of that space? Space has its measurable financial value. From the economic point of view a place can be treated as a product that fights for appearing in tourists’ and investors’ consciousnesses. Space - treated as an object of demand and supply - becomes an element in a marketing game. To reach its...
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Implementation of multi-operand addition in FPGA using high-level synthesis
PublicationThe paper presents the results of high-level synthesis (HLS) of multi-operand adders in FPGA using the Vivado Xilinx environment. The aim was to estimate the hardware amount and latency of adders described in C-code. The main task of the presented experiments was to compare the implementations of the carry-save adder (CSA) type multi-operand adders obtained as the effect of the HLS synthesis and those based on the basic component...
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Employing flowgraphs for forward route reconstruction in video surveillance system
PublicationPawlak’s flowgraphs were utilized as a base idea and knowledge container for prediction and decision making algorithms applied to experimental video surveillance system. The system is used for tracking people inside buildings in order to obtain information about their appearance and movement. The fields of view of the cameras did not overlap. Therefore, when an object was moving through unsupervised areas, prediction was needed...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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The use and development of e-learning systems in educational projects
PublicationThe article introduces the problem of usage and development of e-learning systems among Polish universities. Easily accessible internet and IT development led to changes in education. Through the use of IT tools, e-learning has become an increasingly popular form of education. Presently, majority of Polish universities use an e-learning system of their own choosing designed to support the didactic processes. The goal of the article...
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MULTI-OBJECTIVE OPTIMIZATION PROBLEM IN THE OptD-MULTI METHOD
PublicationNew 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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Affective computing and affective learning – methods, tools and prospects
PublicationEvery teacher knows that interest, active participation and motivation are important factors in the learning process. At the same time e-learning environments almost always address only the cognitive aspects of education. This paper provides a brief review of methods used for affect recognition, representation and processing as well as investigates how these methods may be used to address affective aspect of e-education. The paper...
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Model of distributed learning objects repository for a heterogenic internet environment
PublicationW artykule wprowadzono pojęcie komponentu edukacyjnego jako rozszerzenie obiektu edukacyjnego o elementy zachowania (metody). Zaproponowane podejście jest zgodne z paradygmatem obiektowym. W oparciu o komponent edukacyjny zaprojektowano model budowy repozytorium materiałów edukacyjnych. Model ten jest oparty o usługi sieciowe i rejestry UDDI. Komponent edukacyjny oraz model repozytorium mogą znaleźć zastosowanie w konstrukcji zbiorów...
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Deep learning in the fog
PublicationIn 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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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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Blended-learning w nauczaniu przedmiotów nieinformatycznych
PublicationBlended-learning jest coraz powszechniej wykorzystywany w nauczaniu przedmiotów informatycznych lub innych przedmiotów, w których ćwiczenia realizowane są w laboratoriach komputerowych. W przypadku przedmiotów bez dostępu do sal komputerowych, blended-learning wspomaga prowadzenie wykładów i ćwiczeń poprzez np. lekcje interaktywne. Artykuł opisuje zastosowanie form blended-learning w realizacji laboratoriów z przedmiotu Bezpieczeństwo...
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Affective Learning Manifesto – 10 Years Later
PublicationIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Learning design of a blended course in technical writing
PublicationBlending face-to-face classes with e-learning components can lead to a very successful outcome if the blend of approaches, methods, content, space, time, media and activities is carefully structured and approached from both the student’s and the tutor’s perspective. In order to blend synchronous and asynchronous e-learning activities with traditional ones, educators should make them inter-dependent and develop them according to...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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Remote task submission and publishing in BeesyCluster: security and efficiency of Web Service interface
PublicationPrezentujemy nowy system BeesyCluster, który stanowi łatwy w użyciu portal dostępowy do rozszerzalnej sieci usług wdrożonych i opublikowanych na klastrach/komputerach PC z wirtualnymi płatnościami za wykorzystanie usług. Administratorzy/użytkownicy mogą dołączać klastry/komputery PC dostępne poprzez SSH kliknięciem myszy bez konieczności dalszej konfiguracji na klastrze/komputerze PC udostępniającego. Ponadto, użytkownicy mogą...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Multi-Decision Analysis for selection of the best procedure for PAHs determination in smoked food.
PublicationMaking a proper decision in multifacitated situation is very challenging task. Especially, if there are many alternatives and criteria, even contradictory ones. The support tools may be application of MultiCriteria Decision Analysis methods. In this study the application of PROMETHEE...
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Dental Condition as A Factor Modifying the Transmission of the Sound Vibration in the Skull Bones
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Global Prevalence and Drivers of Dental Students’ COVID-19 Vaccine Hesitancy
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Detection of vehicles stopping in restricted zones in video from surveillance cameras
PublicationAn algorithm for detection of vehicles that stop in restricted areas, e.g. excluded by traffic rules, is proposed. Classic approaches based on object tracking are inefficient in high traffic scenes because of tracking errors caused by frequent object merging and splitting. The proposed algorithm uses the background subtraction results for detection of moving objects, then pixels belonging to moving objects are tested for stability....