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On Inadequacy of Sequential Design of Experiments for Performance-Driven Surrogate Modeling of Antenna Input Characteristics
PublicationDesign of contemporary antennas necessarily involves electromagnetic (EM) simulation tools. Their employment is imperative to ensure evaluation reliability but also to carry out the design process itself, especially, the adjustment of antenna dimensions. For the latter, traditionally used parameter sweeping is more and more often replaced by rigorous numerical optimization, which entails considerable computational expenses, sometimes...
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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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Three-dimensional modeling and automatic analysis of the human nasal cavity and paranasal sinuses using the computational fluid dynamics method
PublicationPurpose The goal of this study was to develop a complete workflow allowing for conducting computational fluid dynam- ics (CFD) simulation of airflow through the upper airways based on computed tomography (CT) and cone-beam computed tomography (CBCT) studies of individual adult patients. Methods This study is based on CT images of 16 patients. Image processing and model generation of the human nasal cavity and paranasal sinuses...
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Marking the Allophones Boundaries Based on the DTW Algorithm
PublicationThe paper presents an approach to marking the boundaries of allophones in the speech signal based on the Dynamic Time Warping (DTW) algorithm. Setting and marking of allophones boundaries in continuous speech is a difficult issue due to the mutual influence of adjacent phonemes on each other. It is this neighborhood on the one hand that creates variants of phonemes that is allophones, and on the other hand it affects that the border...
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A Mammography Data Management Application for Federated Learning
PublicationThis study aimed to develop and assess an application designed to enhance the management of a local client database consisting of mammographic images with a focus on ensuring that images are suitably and uniformly prepared for federated learning applications. The application supports a comprehensive approach, starting with a versatile image-loading function that supports DICOM files from various medical imaging devices and settings....
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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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Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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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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Global Design Optimization of Microwave Circuits Using Response Feature Inverse Surrogates
PublicationModern microwave design has become heavily reliant on full-wave electromagnetic (EM) simulation tools, which are necessary for accurate evaluation of microwave components. Consequently, it is also indispensable for their development, especially the adjustment of geometry parameters, oriented towards performance improvement. However, EM-driven optimization procedures incur considerable computational expenses, which may become impractical...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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A Parallel Corpus-Based Approach to the Crime Event Extraction for Low-Resource Languages
PublicationThese days, a lot of crime-related events take place all over the world. Most of them are reported in news portals and social media. Crime-related event extraction from the published texts can allow monitoring, analysis, and comparison of police or criminal activities in different countries or regions. Existing approaches to event extraction mainly suggest processing texts in English, French, Chinese, and some other resource-rich...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
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[soft skills] Scientific databases and information skills
e-Learning Courses{mlang pl} Dyscyplina: wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: Liczba godzin: 5 Forma zajęć: wykład {mlang} {mlang en} Discipline: all disciplines Obligatory course for 1st-year PhD students Academic teacher: Total hours of training: 5 teaching hours Course type: lecture {mlang} Soft skills Area II - researcher's workshop "Scientific databases and information skills" The training...
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Agata Pierścieniak dr hab. inż.
PeopleAgata Pierscieniak is a graduate of the Wrocław University of Technology, Faculty of Computer Science and Management (1992). She obtained her Ph.D. degree in the field of Economic Sciences in 2004 from the Warsaw University of Life Sciences, while her post-doc (habilitated doctor) degree in the discipline of Management Sciences, in 2016, was from the Warsaw School of Economics.During the years 1998-2018, she worked at the University...
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[Soft Skills] Workshop in research ethics gr.2 AEEITK, ITIT, IMe
e-Learning Courses{mlang pl} Dyscyplina: Wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów III roku Prowadzący: A. Karalus Liczba godzin: 5 {mlang} {mlang en} Discipline: All disciplines Obligatory course for 3rd year PhD students Academic teacher: A. Karalus Total hours of training: 5 teaching hours {mlang}
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[Soft Skills] Workshop in research ethics gr.3 NCh, IMa, NF
e-Learning Courses{mlang pl} Dyscyplina: Wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów III roku Prowadzący: A. Karalus Liczba godzin: 5 {mlang} {mlang en} Discipline: All disciplines Obligatory course for 3rd year PhD students Academic teacher: A. Karalus Total hours of training: 5 teaching hours {mlang}
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[Soft Skills] Workshop in research ethics gr.1 AIU_ILGIT_IŚGIE_EIF
e-Learning Courses{mlang pl} Dyscyplina: Wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów III roku Prowadzący: A. Karalus Liczba godzin: 5 {mlang} {mlang en} Discipline: All disciplines Obligatory course for 3rd year PhD students Academic teacher: A. Karalus Total hours of training: 5 teaching hours {mlang}
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Wykorzystanie metafor w identyfikacji i kształtowaniu postaw przedsiębiorczych
PublicationEdukacja przedsiębiorcza odgrywa coraz większą rolę w promowaniu i kształtowaniu zachowań oraz kompetencji przedsiębiorczych młodego pokolenia. W tym kontekście szczególnie podkreśla się znaczenie wykorzystywania nowych, interaktywnych metod i form kształcenia, niezwykle istotnych dla jednego z aspektów edukacji przedsiębiorczej, jakim jest kształcenie kreatywności i proaktywności. Zastosowanie metafor spełnia wymagania stawiane...
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublicationE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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Pealizacija inicjatiw wostocznogo partnerstwa w Azerbajdżane
PublicationAzerbaijan established political relations with the EU during the implementation of TACIS Programme projects and signed the Partnership and Cooperation Agreement with the EU in 1996. It joined the European Neighbourhood Policy in 2004 and the Eastern Partnership programme in 2009. Despite the sceptical attitude taken by Azerbaijan's government towards the Eastern Partnership initiative, the EU earmarked further funds for Azerbaijan for 2011 – 2014 as part of the European Neighbourhood and Partnership Instrument. During the third Eastern Partnership summit in Vilnius in November 2013, Azerbaijan signed only an agreement concerning visa facilitations and readmission. However, it also undertook certain measures as part of the five Eastern Partnership initiatives. In the framework of the Integrated Border Management Programme, Azerbaijan implemented projects connected with improving the access of resettled people to the judicial system, creation of electronic border control systems, social protection, increasing public awareness to eliminate domestic violence, improving assimilation of asylum - seekers and immigrants, and supporting occupational health organisations. Activities aimed at supporting SMEs included training for entrepreneurs, promotional conferences and loans to the SME sector. Recommendations of the initiative promoting the creation of regional electrical and renewable energy markets were implemented by Azerbaijan in the form of 33 projects as part of the INOGATE Programme. With respect to environmental management, Azerbaijan developed a digital regional atlas of natural disasters, and with respect to natural disaster mitigation it planned population protection measures. Azerbaijan was ranked last but one in the evaluation presented in the annual report prepared by the EU. The transformation process in this country has been slow and illusory in certain aspects. Nevertheless, the EU has continued its Eastern Partnership initiative activities, allocating between EUR 252,000 and 308,000 for transformations in Azerbaijan
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The future of the logistician education in Poland and Ukraine: comparative analysis of the student’s opinion
PublicationBackground: A professional future is the next logical step after a student completes their chosen degree course. More frequently, even during their studies, young people seek opportunities to participate in various conferences, training courses, internships, work placements, and to travel abroad, etc. All of this has one main goal - to increase the student's attractiveness as a potential employee on the labour market. Thus, it...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublicationReflectarrays (RAs) have been attracting considerable interest in the recent years due to their appealing features, in particular, a possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublicationThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublicationThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...
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Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates
PublicationUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublicationCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Ensembling noisy segmentation masks of blurred sperm images
PublicationBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
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[Soft Skills] Academic writing Group 3
e-Learning Courses{mlang pl} Dyscyplina: Soft Skills Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: CJO PG Liczba godzin: 30 {mlang} {mlang en} Discipline: Soft Skills Obligatory course for 1st-year PhD students Academic teacher: CJO PG Total hours of training: 30 teaching hours {mlang}
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[Soft Skills] Academic writing Group 2024/1
e-Learning Courses{mlang pl} Dyscyplina: Soft Skills Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: CJO PG Liczba godzin: 30 {mlang} {mlang en} Discipline: Soft Skills Obligatory course for 1st-year PhD students Academic teacher: CJO PG Total hours of training: 30 teaching hours {mlang}
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[NCh, ICh] Physical Chemistry of Organic Compounds in Natural Waters
e-Learning Courses{mlang pl} Dyscyplina: Nauki chemiczne Zajęcia obieralne dla doktorantów Prowadzący: prof. dr hab. Tadeusz Górecki Liczba godzin: 15 {mlang} {mlang en} Discipline: Chemical science Elective course for PhD students Academic teacher: prof. dr hab. inż. Tadeusz Górecki Total hours of training: 15 teaching hours {mlang}
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[Soft Skills] Academic writing Group 5 (2022)
e-Learning Courses{mlang pl} Dyscyplina: Soft Skills Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: CJO PG Liczba godzin: 30 {mlang} {mlang en} Discipline: Soft Skills Obligatory course for 1st-year PhD students Academic teacher: CJO PG Total hours of training: 30 teaching hours {mlang}
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[Soft Skills] Academic writing Group 3
e-Learning Courses{mlang pl} Dyscyplina: Soft Skills Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: CJO PG Liczba godzin: 30 {mlang} {mlang en} Discipline: Soft Skills Obligatory course for 1st-year PhD students Academic teacher: CJO PG Total hours of training: 30 teaching hours {mlang}
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[Soft Skills] Workshop in research ethics
e-Learning Courses{mlang pl} Dyscyplina: Wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów III roku Prowadzący: Liczba godzin: 5 Forma zajęć: warsztaty {mlang} {mlang en} Discipline: All disciplines Obligatory course for 3rd year PhD students Academic teacher: Total hours of training: 5 teaching hours Course type: workshops {mlang}
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[Soft Skills] Academic writing Group 1
e-Learning Courses{mlang pl} Dyscyplina: Soft Skills Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: CJO PG Liczba godzin: 30 {mlang} {mlang en} Discipline: Soft Skills Obligatory course for 1st-year PhD students Academic teacher: CJO PG Total hours of training: 30 teaching hours {mlang}
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[Soft Skills] Academic writing Group 2024/2
e-Learning Courses{mlang pl} Dyscyplina: Soft Skills Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: CJO PG Liczba godzin: 30 {mlang} {mlang en} Discipline: Soft Skills Obligatory course for 1st-year PhD students Academic teacher: CJO PG Total hours of training: 30 teaching hours {mlang}
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[Soft Skills] Commercialization of scientific outcomes
e-Learning Courses{mlang pl} Soft Skills Zajęcia obowiązkowe dla doktorantów II roku Prowadzący: Agnieszka Krawczyk-Kłos, Damian Kuźniewski Liczba godzin: 5 {mlang} {mlang en} Soft Skills Obligatory course for 2nd-year PhD students Academic teacher: Agnieszka Krawczyk-Kłos, Damian Kuźniewski Total hours of training: 5 teaching hours {mlang}
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[Soft Skills] Academic writing Group 2 (2023: 10x3h)
e-Learning Courses{mlang pl} Dyscyplina: Soft Skills Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: CJO PG Liczba godzin: 30 {mlang} {mlang en} Discipline: Soft Skills Obligatory course for 1st-year PhD students Academic teacher: CJO PG Total hours of training: 30 teaching hours {mlang}
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[Soft Skills] Smart metering - social risk perception and risk governance
e-Learning Courses{mlang pl} Dyscyplina: soft skills Zajęcia obowiązkowe dla doktorantów II roku, Prowadzący: mgr Maciej Galik Liczba godzin: 10 Forma zajęć: {mlang} {mlang en} Discipline: soft skills Obligatory course for 2nd-year PhD students Academic teacher: mgr Maciej Galik Total hours of training: 10 teaching hours Course type: {mlang}
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Tomasz Korczyński mgr
PeopleFrom February 2007 I'm working as a psychologist in Prison Service. I was working in almost all types of prisons with juvenile inmates, recidivist, “dangerous” inmates, women and first time offenders. I'm responsible for carrying out psychological consultations, testing, crisis intervention, suicide prevention. Other duties include promoting a healthy institutional environment to improve staff and inmate safety, delivering direct...
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QUICK IGA QUICK: Innovative SMEs by Gender and Age - QUICK IGA
ProjectsProject realized in Faculty of Management and Economics from 2011-12-08
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Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublicationGlobal sensitivity analysis (GSA) is a method to quantify the effect of the input parameters on outputs of physics-based systems. Performing GSA can be challenging due to the combined effect of the high computational cost of each individual physics-based model, a large number of input parameters, and the need to perform repetitive model evaluations. To reduce this cost, neural networks (NNs) are used to replace the expensive physics-based...
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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublicationDevelopment of modern high-frequency components and circuits is heavily based on full-wave electromagnetic (EM) simulation tools. Some phenomena, although important from the point of view of the system performance, e.g., EM cross-coupling effects, feed radiation in antenna arrays, substrate anisotropy, cannot be adequately accounted for using simpler means such as equivalent network representations. Consequently, the involvement...
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Recent Advances in Accelerated Multi-Objective Design of High-Frequency Structures using Knowledge-Based Constrained Modeling Approach
PublicationDesign automation, including reliable optimization of engineering systems, is of paramount importance for both academia and industry. This includes the design of high-frequency structures (antennas, microwave circuits, integrated photonic components), where the appropriate adjustment of geometry and material parameters is crucial to meet stringent performance requirements dictated by practical applications. Realistic design has...