Search results for: EVALUATION OF E-LEARNING METHODS
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Automatic Analysis System of TV Commercial Emission Level
PublicationThe purpose of the study was to determine whether the commercial emission level is higher than the emission level of a regular program and to check if the commercials broadcasters follow the recommended levels of loudness. The paper shortly reviews some chosen methods of volume measurements specified in the ITU and EBU recommendations. Then, it describes a prototype of a system implemented in Embarcadero C++ Builder 2010 which...
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Web Questionnaire as Construction Method of Affect-annotated Lexicon - Risks Reduction Strategy
PublicationThe paper concerns credibility of construction methods for affect-annotated lexicons, specifically a web questionnaire is explored and evaluated. Web-based surveys are susceptible to some risks, which might influence credibility of the results, as some participants might perform random clicks or intentionally falsify the responses. The paper explores the risks and proposes some strategies to reduce them. The strategies are supported...
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DOROTKA, czyli Doskonalenie Organizacji, ROzwoju oraz Tworzenia Kursów Akademickich przez Internet.
PublicationW artykule zaprezentowano dedykowaną platformę wspierającą kształcenie na odległość opracowaną i uruchomioną w ramach projektu Leonardo da Vinci TeleCAD (Teleworkers Training for CAD System Users, 1998-2001), wykorzystywaną w latach 2000-2003 do wspomagania przedmiotu Podstawy Informatyki na Wydziale Inżynierii Lądowej Politechniki Gdańskiej. Przedstawiono również, bazujący na wieloletnich doświadczeniach, model DOROTKA (Doskonalenie...
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What is the future of digital education in the higher education sector? An overview of trends with example applications at Gdańsk Tech, Poland
PublicationUniversities worldwide recognise the need to adapt to changes in society, the economy and the way young people prefer to learn. Additionally, the impetus to improve the digital approach in higher education intensifies as educational institutions have to remain competitive with commercial providers of education. Following the latest technological trends and implementing strategies to develop new digital solutions helps to improve...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublicationAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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A Method of Object Re-identiciation Applicable to Multicamera Surveillance Systems
PublicationThe paper addresses some challenges pertaining to the methods for tracking of objects in multi-camera systems. The tracking methods related to a single Field of Vision (FOV) are quite different from inter-camera tracking, especially in case of non-overlapping FOVs. In this case, the processing is directed to determine the probability of a particular object’s identity seen in a pair of cameras in the presence of places non-observed...
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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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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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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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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Systematic Literature Review on Click Through Rate Prediction
PublicationThe ability to anticipate whether a user will click on an item is one of the most crucial aspects of operating an e-commerce business, and clickthrough rate prediction is an attempt to provide an answer to this question. Beginning with the simplest multilayer perceptrons and progressing to the most sophisticated attention networks, researchers employ a variety of methods to solve this issue. In this paper, we present the findings...
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CAD Integrated Architectural Design, MSc Arch (2023-24)
e-Learning CoursesDetailed understanding of optimizing the design process using parametric BIM (Building Information Modeling) in the Autodesk Revit Architecture program. Practical design exercises included familiarize students with methods of integrating parametric design and exchanging data with other CAD/BIM programs, modifying parametric objects and generating automatic 2D/3D architectural documentation. The lesson plan introduces students to...
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A METHOD OF TRUST MANAGEMENT IN WIRELESS SENSOR NETWORKS
PublicationThe research problem considered in this paper is how to protect wireless sensor networks (WSN) against cyber-threats by applying trust management and how to strengthen network resilience to attacks targeting the trust management mechanism itself. A new method, called WSN Cooperative Trust Management Method (WCT2M), of distributed trust management in multi-layer wireless sensor networks is proposed and its performance is evaluated....
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Smartphones as tools for equitable food quality assessment
PublicationBackground: The ubiquity of smartphones equipped with an array of sophisticated sensors, ample processing power, network connectivity and a convenient interface makes them a promising tool for non-invasive, portable food quality assessment. Combined with the recent developments in the areas of IoT, deep learning algorithms and cloud computing, they present an opportunity for advancing wide-spread, equitable and sustainable food...
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Analysis of IMS/NGN call processing performance using phase-type distributions
PublicationThis work is a continuation of our research on the traffic model dedicated for design and analysis of the Next Generation Network (NGN), which is standardized for distribution of current and future multimedia services based on the IP Multimedia Subsystem (IMS). Our analytical and simulation models allow evaluation of mean Call Set-up Delay E(CSD) as well as mean Call Disengagement Delay E(CDD) in a single domain of IMS/NGN. Ensuring...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions
PublicationIncreased interest in non-contact evaluation of the health state has led to higher expectations for delivering automated and reliable solutions that can be conveniently used during daily activities. Although some solutions for cough detection exist, they suffer from a series of limitations. Some of them rely on gesture or body pose recognition, which might not be possible in cases of occlusions, closer camera distances or impediments...
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Analysis of antibiotic resistance in Escherichia coli isolated from the Reda River and the Oliwski Stream using basic statistical methods = Zastosowanie metod ststystycznych do analizy antybiotykoodporności bakterii wskaźnikowych pochodzących z rzeki Redy i Potoku Oliwskiego
PublicationIn this study distribution of antimicrobial resistance patterns among fecal indicator bacteria (Escherichia coli and Enterococcus spp.) was examined in two watercourses. The susceptibility analyses were carried out against the antimicrobial agents, important in treating human E. coli and enterococcal infection. Water samples were obtained from the Oliwski Stream and from the Reda River. On each watercourse the five representative...
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Wizualizacje w nauczaniu matematyki
PublicationCały czas aktualizowana wiedza jest niezbędnym czynnikiem, który pozwala na poruszanie się we współczesnym świecie. Tylko nowoczesna edukacja jest dzisiaj w stanie zapewnić awans cywilizacyjny młodzieży. Jak widać, dostęp do mediów i właściwe stosowanie nowych technologii są niezwykle istotne nie tylko ze względu na wykorzystanie ich w procesie podnoszenia jakości i uatrakcyjniania kształcenia. Studenci nie mający możliwości...
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Modern Arrangement for Reduction of Voltage Perturbations
PublicationThe contents of this chapter encompass general problems and the most important issues of power-supply-quality improvement in AC systems. In the context of the above, consideration is given to evaluation of bilateral interactions of receivers with an electrical power-distribution system and methods of their reduction. Also are discussed the basis of operation of the most important compensation-filtration devices and their applications...
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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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Poultry meat freshness assessment based on the biogenic amines index
PublicationIn order to safeguard the well-being of the consumers, it is important to accurately determine the shelf life of poultry and poultry-based products. In this work, it was evaluated whether the measurement of the concentration of cadaverine, putrescine, histamine and tyramine can be used to assess the shelf-life of poultry meat stored in the different types of the containers. Based on the results it can be concluded that the collective...
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Development of dynamic method for evaluation of inhibition efficiency on the example of 8-hydroxyquinolin
PublicationSelection of a proper inhibitor should be based on the evaluation of its mechanism and effective concentrations. Mechanism of inhibition usually has dynamic character due to changing physicochemical conditions of the environment and corroding metal surface. Most of actually used methods are stationary or contain assumptions which highly influences obtained values. Development of new dynamic method, based on modified EIS, allows...
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Identification of ship’s hull mathematical model with numerical methods
PublicationThe modern maritime industry is moving toward the development of technology that will allow for full or partial autonomy of ship operation. This innovation places high demands on ship performance prediction techniques at the design stage. The researchwork presented in the article is related to the design stage of the ship and concerns methods for prognosis and evaluation of the specific operational condition of the ship, namely...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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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...
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublicationThe construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and finan-cial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize deci-sion-making processes in construction scheduling....
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublicationThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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Artificial intelligence for software development — the present and the challenges for the future
PublicationSince the time when first CASE (Computer-Aided Software Engineering) methods and tools were developed, little has been done in the area of automated creation of code. CASE tools support a software engineer in creation the system structure, in defining interfaces and relationships between software modules and, after the code has been written, in performing testing tasks on different levels of detail. Writing code is still the task...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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The analysis of raw spirits – a review of methodology
PublicationAgricultural distillates (raw spirits) are alc oholic l iquids obtained thro ugh dis till ation (preceded by alcoholic ferm entation)of specific agricultural products that do not have the properties of ethyl alcohol or a spirit, but still retain th e aroma andtaste of the raw ingredients used. This review is a brief overview of agricultural distillates and of some methods commonlyused (GC-MS, GC-FID, GC-O, electronic nose) for...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublicationIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Processing of acoustical data in a multimodal bank operating room surveillance system
PublicationAn automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of...
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Development of novel smartphone-based methods of wine quality assessment
PublicationThe doctoral dissertation concerns the development of novel smartphone-based analytical methods of wine quality evaluation, which would be in line with the stipulations of green and equitable analytical chemistry. This solution is based on the analysis of biogenic amines and selected bioactive compounds. The dissertation is based on four articles containing the results of research which led to the development of smartphone-based...
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State of the art and prospects of methods for determination of lipophilicity of chemical compounds
PublicationLipophilicity of the compounds is useful to (i) explain their distribution in biological systems, which is different in plant and in animal organisms, (ii) predict the possible pathways of pollutant transport in the environment, and (iii) support drug discovery process and select optimal composition in terms of bioactivity and bioavailability. The lipophilic properties can be determined by two main approaches, experimental, which...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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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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Aiming at methods’ wider adoption: Applicability determinants and metrics
PublicationNumerous computer science methods and techniques have been proposed by the scientific community. However, depending on the domain, only their minor fraction has met wider adoption. This paper brings attention to the concept of applicability - the notion that is well acknowledged in the scientific field but have not been analysed with respect to determinants, metrics and systematisation. The primary objective of the study was to...
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Towards Emotion Acquisition in IT Usability Evaluation Context
PublicationThe paper concerns extension of IT usability studies with automatic analysis of the emotional state of a user. Affect recognition methods and emotion representation models are reviewed and evaluated for applicability in usability testing procedures. Accuracy of emotion recognition, susceptibility to disturbances, independence on human will and interference with usability testing procedures are...
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Opportunities and shortcomings of ionic liquids in single-drop microextraction
PublicationThe synergistic combination of ionic liquids (ILs) and single-drop microextraction (SDME) involves a powerful coupling toward the development of sustainable analytical methodologies. This overview provides a survey of the literature regarding the IL-SDME, including a database on relevant physicochemical properties of ILs for their application in SDME, the strategies implemented to combine IL-based SDME methods efficiently with...
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THE ROLE OF THE STATE IN TAXATION. POLISH TAX POLICY AFTER 2015
PublicationThis article is an attempt to present and evaluate tax policy Polish of the years 2015-2020, i.e. the period which resulted in formulating the new government. These time was a period of tax reforms, the introduction of new taxes and public tributes, as well as new mechanisms to control tax collection. Moreover, the policies introduced also concern changes in the level of fiscalism and tax redistribution. The research methods adopted...
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METHODS OF TEACHING NOISE PROTECTION AT ENVIRONMENTAL ENGINEERING
PublicationNoise strongly influences both our health and behavior in everyday life and as employees or employers. The lost of hearing and other effects of noise on humans result not only in a significant decrease in the quality of life or work efficiency but have also have economic consequences. As noise can be preventable in part by the Environmental Engineers, but it is necessary to introduce them noise issues during their education process....
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Dagmara Nikulin dr
PeopleBio: Dagmara Nikulin Dagmara Nikulin has been employed at the Faculty of Management and Economics as a research and teaching assistant professor since 2014. Initially, she worked at the Department of Economic Sciences, and now at the Department of Statistics and Econometrics. She is a graduate of the Faculty of Economics at the Poznań University of Economics (2009) and the Faculty of Social Sciences of the Adam Mickiewicz University...
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Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up
PublicationOne of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence...
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Nitrofurazone Removal from Water Enhanced by Coupling Photocatalysis and Biodegradation
Publication(1) Background: Environmental contamination with antibiotics is particularly serious because the usual methods used in wastewater treatment plants turn out to be insufficient or ineffective. An interesting idea is to support natural biodegradation processes with physicochemical methods as well as with bioaugmentation with efficient microbial degraders. Hence, the aim of our study is evaluation of the effectiveness of different...
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Integracja bezprzewodowych heterogenicznych sieci IP dla poprawy efektywności transmisji danych na morzu
PublicationWraz ze wzrostem istotności środowiska morskiego w naszym codziennym życiu np. w postaci zwiększonego wolumenu transportu realizowanego drogą morską. czy zintensyfikowanych prac dotyczących obserwacji i monitoringu środowiska morskiego, wzrasta również potrzeba opracowania efektywnych systemów komunikacyjnych dedykowanych dla tego środowiska. Heterogeniczne systemy łączności bezprzewodowej integrowane na poziomie warstwy sieciowej...
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An improved scalable method of isolating asphaltenes
PublicationA new, improved and scalable procedure of asphaltene fraction isolation is presented and compared to standard test methods. The new procedure uses 1:40 feedstock to solvent (n-heptane) ratio (g/mL), filtration through a cellulosic thimble and extensive washing in a Soxhlet type extractor. The group type composition and purity of the asphaltene fractions have been examined using thin-layer chromatography with flame-ionization detection....