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Search results for: machine%20learning
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Marine Ecology-An Evolutionary Perspective
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MARINE TECHNOLOGY SOCIETY JOURNAL
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublicationAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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Resolving Conflicts in Object Tracking in Video Stream Employing Key Point Matching
PublicationA novel approach to resolving ambiguous situations in object tracking in video streams is presented. The proposed method combines standard tracking technique employing Kalman filters with global feature matching method. Object detection is performed using a background subtraction algorithm, then Kalman filters are used for object tracking. At the same time, SURF key points are detected only in image sections identified as moving...
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Electro-optical system for the automated selection of dental implants according to their colour matching
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Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method
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Towards increasing F-measure of approximate string matching in O(1) complexity
PublicationThe paper analyzes existing approaches for approximate string matching based on linear search with Levenshtein distance, AllScan and CPMerge algorithms using cosine, Jaccard and Dice distance measures. The methods are presented and compared to our approach that improves indexing time using Locally Sensitive Hashing. Advantages and drawbacks of the methods are identified based on theoretical considerations as well as empirical evaluations...
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Response features for fast EM-driven design of miniaturized impedance matching transformers
PublicationA framework for low-cost EM-driven design optimization of compact impedance matching transformers is presented. Our technique is based on a bottom-up design where design requirements for the transformer circuit are translated into specifications for its building blocks. These elementary cells are optimized using response features. Subsequently, the entire circuit is fine-tuned using local response surface approximation models and...
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SYNTHESIS OF PHOSPHORUS TACRINE ANALOGUES AS A NEW POTENTIAL ANTI-ALZHEIMER’S DISEASE AGENTS
PublicationA series of novel phosphorus tacrine derivatives was obtained in three steps, including synthesis of 9-chlorotacrine, connection of 9-chlorotacrine with hexamethylenediamine, 1,8-diaminooctane and 1,12-diaminododecane linkers and reaction of obtained tacrine diamine analogues with corresponding acid ester to give nine tacrine organophosphorus compounds. All of the obtained final structures were characterized by 1H NMR, 13C NMR,...
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Comparing Arbitrary Unrooted Phylogenetic Trees Using Generalized Matching Split Distance
PublicationIn the paper, we describe a method for comparing arbitrary, not necessary fully resolved, unrooted phylogenetic trees. Proposed method is based on finding a minimum weight matching in bipartite graphs and can be regarded as a generalization of well-known Robinson-Foulds distance. We present some properties and advantages of the new distance. We also investigate some properties of presented distance in a common biological problem...
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The experimental investigations and modelling of trak work with the use of tamping machine's diagnostic informations
PublicationW pracy przedstawiono realizowany w Katedrze Inżynierii Kolejowej Politechniki Gdańskiej program badawczy, którego idea zasadza się na wykorzystaniu podbijarki torowej w zakresie diagnostyki toru kolejowego. Skupiono się głównie na dwóch aspektach związanych z torem bezstykowym, tj. na siłach podłużnych występujących w tokach szynowych oraz na oporach poprzecznych rusztu torowego związanych głównie ze stopniem ustabilizowania podsypki...
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Static and dynamic approach of social roles identification using PISNA and subgraphs matching
PublicationIdentyfikacja ról w sieci społecznej jest jednym z podstawowych zagadnień analiza takich sieci. W artykule przedstawiamy nowe podejście do tego zagadnienia. Pokazujemy w jaki sposób można dokonać identyfikacji ról poprzez tworzenie specjalnych struktur grafowych tzw. grafów wzorcowych. Przy definiowaniu tychże grafów wspieramy się metodą PISNA. Proponujemy statyczne i dynamiczne podejście do identyfikacji ról. Pokazujemy, w jaki...
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Selected problems of planning machinery and devices location in a ship´s engine room.
PublicationPrzedstawiono podstawowe zasady rozplanowania maszyn i urządzeń w przedziale maszynowym na statku. Podano warunki i kryteria wpływające na proces projektowania rozmieszczenia maszyn i urządzeń w siłowni. Przedstawiono główne warunki i zasady dotyczące rozplanowania głównego układu napędowego, elektrowni, kotłowni pomocniczych oraz innych instalacji siłownianych.
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Cost minimization of locating construction machinery park with the use of simulation and optimization algorithms
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Antibody Response to Trivalent Influenza Vaccine in the Northern and the Southern Hemisphere in Elite Athletes
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Evaluation of the BNT162b2 Covid-19 Vaccine in Children 5 to 11 Years of Age
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Comparing Phylogenetic Trees by Matching Nodes Using the Transfer Distance Between Partitions
PublicationAbility to quantify dissimilarity of different phylogenetic trees describing the relationship between the same group of taxa is required in various types of phylogenetic studies. For example, such metrics are used to assess the quality of phylogeny construction methods, to define optimization criteria in supertree building algorithms, or to find horizontal gene transfer (HGT) events. Among the set of metrics described so far in...
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An optimized system for sensor ontology meta-matching using swarm intelligent algorithm
PublicationIt is beneficial to annotate sensor data with distinct sensor ontologies in order to facilitate interoperability among different sensor systems. However, for this interoperability to be possible, comparable sensor ontologies are required since it is essential to make meaningful links between relevant sensor data. Swarm Intelligent Algorithms (SIAs), namely the Beetle Swarm Optimisation Algorithm (BSO), present a possible answer...
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Exploring application relationships within enterprise system by matching messages in enterprise log
PublicationWith data becoming their key asset, large enterprises require data governance processes to maintain its quality. Because a large portion of business value in enterprise systems is usually delivered by legacy applications without proper documentation, there is a need for a better understanding of these applications and the data produced by them. In this paper, we present an approach to collecting insights into the data managed by...
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An Instantaneous Engine Speed Estimation Method Using Multiple Matching Synchrosqueezing Transform
PublicationInstantaneous rotational speed measurement of the engine is crucial in routine inspection and maintenance of an automobile engine. Since the contact measurement of rotational speed is not always available, the vibration measurement has been used for noncontact rotational speed estimation methods. Unfortunately, the accuracy of the noncontact estimation methods by analyzing engine vibration frequency is not satisfactory due to the...
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HCI-Based Wireless System for Measuring the Concentration of Mining Machinery and Equipment Operators
PublicationMaintaining stable and reliable working conditions is a matter of vital importance for various companies, especially those involving heavy machinery. Due to human exhaustion, as well as unpredicted hazards and dangerous situations, the personnel has to take actions and wisely plan each move. This paper presents a human–computer interaction (HCI)-based system that uses a concentration level measurement function to increase the safety...
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Mapping of the Covid-19 Vaccine Uptake Determinants From Mining Twitter Data
PublicationOpinion polls on vaccine uptake clearly show that Covid-19 vaccine hesitancy is increasing worldwide. Thus, reaching herd immunity not only depends on the efficacy of the vaccine itself, but also on overcoming this hesitancy of uptake in the population. In this study, we revealed the determinants regarding vaccination directly from people’s opinions on Twitter, based on the framework of the 6As taxonomy. Covid-19 vaccine acceptance...
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublicationIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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Farzin Kazemi Ph.D. Student at Gdansk University of Technology
PeopleHis main research areas are seismic performance assessment of structures and seismic hazard analysis in earthquake engineering. He performed a comprehensive study on the effect of pounding phenomenon and proposed modification factors to modify the seismic collapse capacity of structures or predict the seismic collapse capacity of structures which were retrofitted with linear and nonlinear Fluid Viscous Dampers (FVDs). His current...
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Basic evaluation of limb exercises based on electromyography and classification methods
PublicationSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublicationAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublicationContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublicationIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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Publicly available lecture webcasts - e-learning or promotion tool? case study
PublicationThis paper aims to show how universities interact with Internet users by webcasting selected courses. Paper has exploratory case-study character, presenting example of Berkeley Webcast initiative of University of California, Berkeley, webcasting undergraduate courses and on-campus events. On the base of short introduction to webcasting usage as an e-learning and promotional tool, the analysis of 3 purposely chosen different courses...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Effects of mutual learning in physical education to improve health indicators of Ukrainian students
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DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Innovative e-learning approach in teaching based on case studies - Innocase project
PublicationThe article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublicationThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-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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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Simulation Method for Scheduling Linear Construction Projects Using the Learning– Forgetting Effect
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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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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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...