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Search results for: ORGANIZATIONAL%20LEARNING
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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AMO model for neuro-inclusive remote workplace
PublicationPurpose The aim of this article is to extend current debates on organizational equality, diversity and inclusion to a consideration of neurodivergence in the remote workplace context. Design/methodology/approach Drawing on the ability, motivation, and opportunity (AMO) model and an emerging strength-based approach to neurodiversity, this conceptual paper integrates research on neurodiversity at work and remote working to provide...
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New Challenges in Management and Economics in 21st century. Selected studies and examples
PublicationIn Chapter 1 authors describe the method used to assess the level of readiness of an organization to introduce the Lean Six Sigma concept supporting the Quality 4.0 assumptions, which is gaining more and more interest not only in large organizations, but also in the SME sector. Its use will be illustrated by the example of a small service company. Chapter 2 presents the characteristics of blockchain technology applications in the...
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Validating the Rules of Government Automation
PublicationThere is growing evidence on the benefits and risks of government automation, and how should government organizations proceed with automation when the benefits outweigh the risks. This evidence was recently consolidated into the "rules of government automation", part of the project funded by the Inter-American Development Bank. The project uncovered that the combined nature of government work and its transformation into digital...
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Factors Affecting the Effectiveness of Military Training in Virtual Reality Environment
PublicationIn this paper, we explored the factors influencing the effectiveness of military trainings performed in a virtual reality environment. The rationale for taking up the topic is the fact that such trainings are often conducted under specific operational procedures. These procedures may create rigorous frameworks for all elements of the learning environment, including the teacher’s performance. Therefore, to ensure the most conducive...
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Antecedents to Achieve Kanban Optimum Benefits in Software Companies
PublicationIn 2004, Kanban successfully entered into the Agile and Lean realm. Since then software companies have been increasingly using it in software development teams. The goal of this study is to perform an empirical investigation on antecedents considered as important for achieving optimum benefits of Kanban use and to discuss the practical implications of the findings. We conducted an online survey with software professionals from...
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INTERNAL DETERMINANTS OF FIRMS’ INNOVATIVENESS
PublicationThis article presents an analysis of the determinants of a firm’s innovativeness deriving from its internal potential and characteristics. The analysis is based on research carried out on 1355 firms that applied for public subsidies from the Innovative Economy Operational Program in 2014. The methods applied are logit regression, comparative analysis and literature review. The analysis is structured ac- cording to Bielski’s model...
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Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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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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Challenges for universities in the face of the knowledge-based economy - Directions for higher education institutions in the Baltic Sea Region
PublicationThe aim of this paper is to present new challenges that are faced by universities in the knowledge-based economy. There are several phenomena that can presently be observed like the need for life-long learning or interdisciplinary approach, and universities should prepare their graduates for those challenges. One of the crucial questions that universities need to ask is how to teach and what to teach. Knowledge becomes obsolete...
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Challenges for universities in the face of knowledge-based economy - directions for higher education institutions in the Baltic Sea Region
PublicationThe aim of this paper is to present new challenges that are faced by universities in the knowledge-based economy. There are several phenomena that can presently be observed like the need for life-long learning or interdisciplinary approach, and universities should prepare their graduates for those challenges. One of the crucial questions that universities need to ask is how to teach and what to teach. Knowledge becomes obsolete...
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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E-learning przez Internet w szkolnictwie wyższym. Doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej.
PublicationOpisano cztery podstawowe rodzaje e-learningu, przedstawiono strukturę funkcjonalną systemów zarządzania nauczaniem na odległość i zarządzania treścią nauczania (ang. LMS, LCMS) oraz zaprezentowano doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej w nauczaniu na odległość.
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Construction of a simulation model of goods delivery in international road transportation taking into account the functioning efficiency of logistics supply chain
PublicationThe object of this study is the process of goods delivery in international road transport using various types of logistics chains. The problem being solved is due to the need to develop recommendations for exporters of goods to reformat or design new supply chains during wartime. The expediency of organizing foreign trade operations by the cargo owners' own forces or with the involvement of enterprises providing logistics consulting...
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Where Did Knowledge Management Go?: A Comprehensive Survey
PublicationKnowledge Management (KM) research outputs have been expanding exponentially in the past years, generating diversified topics, which lack integration and classification. It has been challenging for experts to classify KM because of its versatile open fields, and in our view, it contributes to the technocratic approach remaining behind the organizational approach. This paper highlights a way to classify KM publications through a...
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Social Capital, Human Capital, Tacit Knowledge, and Innovations: A Polish-US Cross-Country Study
PublicationThis study measures the relationship between human and social capital (internal and external) and tacit knowledge sharing's influence on innovativeness among knowledge workers employed in Polish (n=1050) and US (n=1118) organizations. The structural equation modeling method revealed that internal social capital matters more for organizational innovativeness in the US. In Poland, both external and internal were important. Specifically,...
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Thriving in multicultural workplace
PublicationThriving at work is defined as the psychological state that links both a sense of vitality and learning. The vitality component of thriving may be seen as positive energy, while learning enhances a sense of competence and efficacy. Thriving sheds new light on individual psychological functioning and the experience of growth in the work context. Thriving at work promotes growth through playing an active role in interaction with...
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A Comprehensive Investigation of Knowledge Management Publications
PublicationRecent trends in knowledge management (KM) have increasingly indicated a lack of agreement, integration and classification between different KM domains. As such, experts are inadequately equipped when attempting to classify KM into their specific areas that could effectively contribute to a technocratic approach behind the organizational strategy. This paper illustrates a method of classifying KM publications by using a scheme...
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Od modelu biznesu przedsiębiorstwa do modelu biznesu organizacji publicznej
PublicationZadowolenie obywateli z jakości życia jest związane z poziomem zaspokajania ich potrzeb, wśród których występuje możliwość korzystania z dóbr publicznych. Wiąże się to z dostępem do usług publicznych. Gospodarzami w zakresie świadczenia tych usług są organizacji publiczne. Zatem z rozumowania logicznego wynika, że wzrost zadowolenia mieszkańców może nastąpić wówczas, gdy podniesie się dostępność i poziom jakości usług publicznych....
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Techniczne aspekty implementacji nowoczesnej platformy e-learningowej
PublicationZaprezentowano aspekty techniczne implementacji nowoczesnej platformy nauczania zdalnego. Omówiono obszary funkcjonalne takie jak: system zarządzania nauczaniem, serwis informacyjny, dodatkowe oprogramowanie dydaktyczne oraz kolekcja zasobów multimedialnych. Przybliżono zagadnienia związane z bezpieczeństwem takiej platformy. Na końcu przedstawiono parametry techniczne wdrożonej na Politechnice Gdańskiej platformy eNauczanie.
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Tacit knowledge acquisition & sharing, and its influence on innovations: A Polish/US cross-country study
PublicationThis study measures the relationship between tacit knowledge sharing and innovation in the Polish (n=350) and US (n=379) IT industries. Conceptually, the study identifies the potential sources of tacit knowledge development by individuals. That is, the study examines how “learning by doing” and “learning by interaction” lead to a willingness to share knowledge and, as a consequence, to support process and product/service innovation....
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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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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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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Magdalena Popowska dr
PeopleMagdalena Popowska (PhD) is a researcher and lecturer of Organization Science and Entrepreneurship at the Faculty of Management and Economics of Gdansk University of Technology. For many years she has been in charge of exchange programmes, double degrees and other internationalization activities. In 2008-2016 she was a Vice-Dean for International and Public Affairs and now she is a Dean Proxy for International Cooperation. Her...
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International Journal of Continuing Engineering Education and Lifelong Learning
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International Journal of Computer-Assisted Language Learning and Teaching
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International Journal of Web-Based Learning and Teaching Technologies
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International Journal for Research on Service-Learning and Community Engagement
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Kreatywna destrukcja uniwersytetu = Creative destruction of the university
PublicationAutorzy podejmują problematykę zmian we współczesnym uniwersytecie. Wychodząc z założenia, że celem uniwersytetu jest, obok kształcenia masowego, wykształcenie elity przedsiębiorców intelektualnych przyszłych liderów społeczeństwa wiedzy, zaproponowano twórczą destrukcję organizacji uczelni, której istotą jest przeniesienie osi organizacyjnej z podstawowych jednostek uczelni, jakimi są wydziały na zespoły, a osi koordynacyjnej...
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E-Learning as a Factor Optimizing the Amount of Work Time Devoted to Preparing an Exam for Medical Program Students during the COVID-19 Epidemic Situation
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublicationThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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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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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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International Workshop on Coordination, Organizations, Institutions, Norms and Ethics for Governance of Multi-Agent Systems (Workshop on Coordination, Organizations, Institutions and Norms in agent Systems [COIN])
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Signals of the 5G Standalone Radio Interface
Open Research DataThe research work conducted within the scope of NATO-STO (North Atlantic Treaty Organization – Science and Technology Organization) IST-187 group assumed investigation of the 5G gNodeB performance. The downlink (DL) signals of the FDD (Frequency Division Duplex) 5G-Standalone station were registered in isolated and controlled laboratory conditions....
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How to achieve sustainability?-Employee's point of view on company's culture and CSR practice
PublicationThe people are the company. This study aims to examine the structure of relationships between company culture, performance, corporate social responsibility (CSR), and reputation, as seen from the employee's perspective, to determine which company culture factors most influence CSR practice and, as a result, sustain a company's development and improve its performance. To accomplish this goal, we conducted a survey among employees...