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Search results for: multi-task learning
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Revisiting Supervision for Continual Representation Learning
Publication"In the field of continual learning, models are designed to learn tasks one after the other. While most research has centered on supervised continual learning, there is a growing interest in unsupervised continual learning, which makes use of the vast amounts of unlabeled data. Recent studies have highlighted the strengths of unsupervised methods, particularly self-supervised learning, in providing robust representations. The improved...
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DETERMINATION OF THE CITY CENTRE. STUDY FOR THE TROJMIASTO AGGLOMERATION
PublicationDetermination of the centre of the city or agglomeration or generally the geographic area is a task which is often undertaken as part of the promotional actions realized by local authorities or directly by inhabitants. Nowadays, especially due to the development and availability of positioning technology and satellite imaging, this job is undertaken within the framework of general didactic tasks and group projects during the study...
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BeesyBees: A mobile agent-based middleware for a reliable and secure execution of service-based workflow applications in BeesyCluster
PublicationIntegrating distributed services into workflows comes with its own set of challenges, including security, coordination, fault tolerance and optimisation of execution time. This paper presents an architecture and implementation - nicknamed BeesyBees - that allows distributed execution of workflow applications in BeesyCluster using agents. BeesyCluster is a middleware that allows users to access distributed resources as well as publish...
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Modeling of flow phenomena associated with polymer injection into a mold
PublicationPodczas wtrysku tworzywa do formy w strefie tworzywo-ścianka formy występują zjawiska, które są źródłem zwiększonej chropowatości powierzchni i wad wypraski. W pracy pisano powyższe zjawiska oraz zaprezentowano model numeryczny, umożliwiający symulację tych zjawisk. Symulację komputerową wykonano w CI TASK stosując program FIDAP. Wyniki badań symulacyjnych zweryfikowano badaniami doświadczalnymi, wykonując fotografie i profilogramy...
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Parametrical Method for Determining Optimal Ship Carrying Capacity and Performance of Handling Equipment
PublicationThe paper presents a method of evaluating the optimal value of the cargo ships deadweight and the coupled optimal value of cargo handling capacity. The method may be useful at the stage of establishing the main owners requirements concerning the ship design parameters as well as for choosing a proper second hand ship for a given transportation task. The deadweight and the capacity are determined on the basis of a selected economic...
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Stereo image visualization for a VISROBOT system
PublicationThe article describes a novel approach to robotic vision in mobile robot systems. The system implements a Visrobot system which implements a generic idea of using mobile robots for exploring an indoor environment. The task of such a robot is to visualize a stereo image properly for an operator. The system uses different stereo baseline values. Variable baseline can result in increasing depth resolution for distant objects. We assume...
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Autonomous Driver Based on an Intelligent System of Decision-Making
PublicationThe paper presents and discusses a system (xDriver) which uses an Intelligent System of Decision-making (ISD) for the task of car driving. The principal subject is the implementation, simulation and testing of the ISD system described earlier in our publications for the task of autonomous driving. The design of the whole ISD system is a result of a thorough modelling of human psychology based on an extensive literature study. Concepts...
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How Specific Can We Be with k-NN Classifier?
PublicationThis paper discusses the possibility of designing a two stage classifier for large-scale hierarchical and multilabel text classification task, that will be a compromise between two common approaches to this task. First of it is called big-bang, where there is only one classifier that aims to do all the job at once. Top-down approach is the second popular option, in which at each node of categories’ hierarchy, there is a flat classifier...
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Genetic Programming for Workload Balancing in the Comcute Grid System
PublicationA genetic programming paradigm is implemented for reliability optimization in the Comcute grid system design. Chromosomes are generated as the program functions and then genetic operators are applied for finding Pareto-suboptimal task assignment and scheduling. Results are compared with outcomes obtained by an adaptive evolutionary algorithm.
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Using creative approaches for discovering biomorphic forms for appropriate human habitation in natural environments. Case study of Kashubian Lake District
PublicationThe research process consisted of studies of natural and cultural conditions of the Kashubian Lake District This is an area of exceptional natural conditions. For centuries, it has seen human habitation with respect to landscape values. Given its extensive forest cover and the lack of heterogeneity of natural conditions, the area has become an interesting inspiration for the author’s original project. The project is aimed at searching...
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Linear game non-contextuality and Bell inequalities—a graph-theoretic approach
PublicationWe study the classical and quantum values of a class of one-and two-party unique games, that generalizes the well-known XOR games to the case of non-binary outcomes. In the bipartite case the generalized XOR(XOR-d) games we study are a subclass of the well-known linear games. We introduce a 'constraint graph' associated to such a game, with the constraints defining the game represented by an edge-coloring of the graph. We use the...
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Pathological and physiological high-frequency oscillations in focal human epilepsy
PublicationHigh-frequency oscillations (HFO; gamma: 40-100 Hz, ripples: 100-200 Hz, and fast ripples: 250-500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency,...
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Wikipedia Articles Representation with Matrix'u
PublicationIn the article we evaluate different text representation methods used for a task of Wikipedia articles categorization. We present the Matrix’u application used for creating computational datasets ofWikipedia articles. The representations have been evaluated with SVM classifiers used for reconstruction human made categories.
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The analysis of the conditions for best practices’ transfer
PublicationOne of the tasks of the Project Partners was identifying best practices in strengthening the economic activity of women and older people in the context of developing the competitiveness and innovation of SMEs, as well as determining the possibilities and conditions of their transfer. Transfer in this case is understood as the implementation of selected and described solutions in enterprises and public organizations from all the...
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Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublicationThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
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Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublicationIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
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MAKING OF FERROMAGNETIC ELLIPTICAL SHELL IN TRANSVERSE MAGNETIC
PublicationA ferromagnetic object, located in the Earth’s magnetic field, changes its distribution. Through measuring such disturbances, one can locate the object and destroy it. To conceal the object, a special winding is placed inside its ferromagnetic shell, and its task is to eliminate the disturbances in the distribution of the Earth’s magnetic field.
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Psychophysiological strategies for enhancing performance through imagery – skin conductance level analysis in guided vs. self-produced imagery
PublicationAthletes need to achieve their optimal level of arousal for peak performance. Visualization or mental rehearsal (i.e., Imagery) often helps to obtain an appropriate level of activation, which can be detected by monitoring Skin Conductance Level (SCL). However, different types of imagery could elicit different amount of physiological arousal. Therefore, this study aims: (1) to investigate differences in SCL associated with two instructional...
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Application of principal component and hierarchical cluster analysis in classifying defects of trolleybuses
PublicationThe failure rate of vehicles is a relevant task, which is strictly connected with the reliability of transportation systems. Methods of data analysis allow us to find similarity and differences between failure rates of several parts of trolleybuses. This paper deals with the statistic of failure of trolleybuses from the municipal transport company of Gdynia (Poland).
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Multiprocessor Implementation of Parallel Multiobjective Genetic Algorithm for Optimized Allocation of Chlorination Stations in Drinking Water Distribution System a New Water Quality Model Approach
PublicationThe Critical Infrastructure Systems (CISs) have received in recent years a considerable attention due to their heavy impact on sustainable development of modern societies. Most CISs may be classied as large scale complex systems of network structure, in uenced by strong interactions form the surrounding environment, internal and external interconnections. The later is a result of inter-CIS dependencies. The control, monitoring...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Automated Diagnostics of Current Pick-Up Disturbances in Electric Traction Networks
PublicationThe present work defines the basic causes of bow disturbances of current pick-up, sets a task of establishing a system of automated control of bow disturbances at feeder zones of electric traction networks, proposes structural variants of the technical system implementation, describes the algorithm of detection of bow disturbances of current pick-up.
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Parallel implementation of background subtraction algorithms for real-time video processing on a supercomputer platform
PublicationResults of evaluation of the background subtraction algorithms implemented on a supercomputer platform in a parallel manner are presented in the paper. The aim of the work is to chose an algorithm, a number of threads and a task scheduling method, that together provide satisfactory accuracy and efficiency of a real-time processing of high resolution camera images, maintaining the cost of resources usage at a reasonable level. Two...
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Lifelong Learning Idea in Architectural Education
PublicationThe recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...
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Acceptance Testing of Software Products for Cloud-Based On-Line Delivery
PublicationSoftware products intended for on-line delivery by distributors serving an open community of subscribers are developed in a specific life-cycle model, in which roles of the major stakeholders are strongly separated, unlike in any other software development model known in software engineering. Its specificity underlines the fact that a distributor of the final product, responsible for its acceptance for publication and delivery...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Swarm-Assisted Investment Planning of a Bioethanol Plant
PublicationBioethanol is a liquid fuel for which a significant increase in the share of energy sources has been observed in the economies of many countries. The most significant factor in popularizing bioethanol is the profitability of investments in construction of facilities producing this energy source, as well as the profitability of its supply chain. With the market filled with a large amount of equipment used in the bioethanol production...
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Feasibility Study for Food Intake Tasks Recognition Based on Smart Glasses
PublicationIn this exploratory study 13 adult test subjects have performed different food intake tasks while wearing a three axis accelerometer mounted at a temple of glasses. Two different algorithms for task recognition have been applied and compared. The retrospective data processing leads to better task recognition results when the frequency range of 50 Hz to 100 Hz is analysed within accelerometer signal recordings. A straightforward...
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Pupil size reflects successful encoding and recall of memory in humans
PublicationPupil responses are known to indicate brain processes involved in perception, attention and decision-making. They can provide an accessible biomarker of human memory performance and cognitive states in general. Here we investigated changes in the pupil size during encoding and recall of word lists. Consistent patterns in the pupil response were found across and within distinct phases of the free recall task. The pupil was most...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublicationPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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Dedicated scheduling of tasks to minimize mean flow time
PublicationThis paper investigates the complexity of scheduling biprocessor tasks on dedicated processors to minimize mean flow time. Since the general problem is strongly NP-hard, we assume some restrictions on task lengths and the structure of associated scheduling graphs. Of particular interest are acyclic graphs. In this way we identify a borderline between NP-hard and polynomially solvable special cases.
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Simulation of the IT Service and Project Management Environment
PublicationThe authors of this paper present a simulation of the socio-technical system in which teams of students – regarded as low-maturity organizations – were given a task to utilize the (relatively) mature technologies that support IT project and service management. The experiment consisted of the following phases: teams formation, introduction to technologies used during the simulation, performing a set of reactive and proactive service...
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MANAGING LEARNING PROCESS WITH E-LEARNING TOOL
PublicationThis article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublicationMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Wear of Ultra-thin DLC or Tungsten-modified DLC Coatings under Reciprocating Sliding
PublicationIn the paper results are presented from tests in reciprocating sliding of self mated specimens of DLC and tungsten modified DLC coatings on stainless steel substrate. The contact geometry chosen for the research task was ball on flat. The contacts were lubricated either with distilled water or medical saline solution. Results are presented with regard to wear resistance as a function of material type and lubricant used.
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Blended Learning Model for Computer Techniques for Students of Architecture
PublicationAbstract: The article summarizes two-year experience of implementing hybrid formula for teaching Computer Techniques at the Faculty of Architecture at the Gdansk University of Technology. Original educational e-materials, consisting of video clips, text and graphics instructions, as well as links to online resources are embedded in the university e-learning educational platform. The author discusses technical constraints associated...
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Optimisation of turbine shaft heating process under steam turbine run-up conditions
PublicationAn important operational task for thermal turbines during run-up and run-down is to keep the stresses in the structural elements at a right level. This applies not only to their instantaneous values, but also to the impact of them on the engine lifetime. The turbine shaft is a particularly important element. The distribution of stresses depends on geometric characteristics of the shaft and its specific locations. This means a groove manufactured...
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Four-state stochastic model of changes in the reliability states of a motor vehicle
PublicationThe properties of semi-Markov processes have been generally characterized and the applicability of the theory of such processes to the determining of the reliability of motor cars and other road vehicles has been explained. A formal description of the process of changes in the motor vehicle technical states considered as reliability states and a model of this process in the form of a one-dimensional stochastic process have been...
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Microgrid Energy Management System
PublicationIn the era of rapid development of "green energy” and storage devices, microgrids implemented in line with the concept of distributed generation can be an effective form of power management. There is a need for an efficient, optimal and reliable control of the combined infrastructure. The article presents a flexible, configurable microgrid's resources control system, which executes the task of meeting the electricity demand of...
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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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Expedited Re-Design of Multi-Band Passive Microwave Circuits Using Orthogonal Scaling Directions and Gradient-Based Tuning
PublicationGeometry scaling of microwave circuits is an essential but challenging task. In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates utilization of numerical optimization methods. Nonetheless, if the intended frequencies are distant from the ones at the starting point,...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Maritime traffic situation awareness analysis via high-fidelity ship imaging trajectory
PublicationSituation awareness provides crucial yet instant information to maritime traffic participants, and significant attentions are paid to implement traffic situation awareness task via various maritime data source (e.g., automatic identification system, maritime surveillance video, radar, etc.). The study aims to analyze traffic situation with the support of ship imaging trajectory. First, we employ the dark channel prior model to...
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Selected problems of decision making modelling in power engineering
PublicationThe paper presents the selected problems of decision making modelling in power engineering specially investment risk evaluation methods. The proposed model can be used in the range programming the development and investing process in power engineering. Decision making problems in power engineering and the evaluation of investment effectiveness in particular are closely related to modelling which relatively accurately reflects...
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Clothes Detection and Classification Using Convolutional Neural Networks
PublicationIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...