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Search results for: DATA ANALYSIS, ARTIFICIAL INTELLIGENCE, EDGE DEVICES

Search results for: DATA ANALYSIS, ARTIFICIAL INTELLIGENCE, EDGE DEVICES

  • Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics

    Publication

    - Year 2020

    Remote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...

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  • ChatGPT Application vis-a-vis Open Government Data (OGD): Capabilities, Public Values, Issues and a Research Agenda

    Publication
    • E. Loukis
    • S. Saxena
    • N. Rizun
    • M. I. Maratsi
    • M. Ali
    • C. H. Alexopoulos

    - Year 2023

    As a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it...

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  • Emotion Recognition Based on Facial Expressions of Gamers

    This article presents an approach to emotion recognition based on facial expressions of gamers. With application of certain methods crucial features of an analyzed face like eyebrows' shape, eyes and mouth width, height were extracted. Afterwards a group of artificial intelligence methods was applied to classify a given feature set as one of the following emotions: happiness, sadness, anger and fear. The approach presented in this...

  • Emotion Recognition Based on Facial Expressions of Gamers

    Publication

    This article presents an approach to emotion recognition based on facial expressions of gamers. With application of certain methods crucial features of an analysed face like eyebrows' shape, eyes and mouth width, height were extracted. Afterwards a group of artificial intelligence methods was applied to classify a given feature set as one of the following emotions: happiness, sadness, anger and fear.The approach presented in this...

  • Signature Partitioning Using Selected Population-Based Algorithms

    Publication

    - Year 2020

    Dynamic signature is a biometric attribute which is commonly used for identity verification. Artificial intelligence methods, especially population-based algorithms (PBAs), can be very useful in the dynamic signature verification process. They are able to, among others, support selection of the most characteristic descriptors of the signature or perform signature partitioning. In this paper, we focus on creating the most characteristic...

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  • Cognitive motivations and foundations for building intelligent decision-making systems

    Concepts based on psychology fit well with current research trends related to robotics and artificial intelligence. Biology-inspired cognitive architectures are extremely useful in building agents and robots, and this is one of the most important challenges of modern science. Therefore, the widely viewed and far-reaching goal of systems research and engineering is virtual agents and autonomous robots that mimic human behavior in...

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  • Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?

    Publication

    - Year 2023

    Open Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...

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  • Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing

    Circulating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...

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  • Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling

    Publication

    - Scientific Reports - Year 2023

    Over the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...

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  • Adaptacyjny system oświetlania dróg oraz inteligentnych miast

    Publication

    - Year 2024

    Przedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...

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  • Influence of algorithmic management practices on workplace well-being – evidence from European organisations

    Publication

    Purpose Existing literature on algorithmic management practices –defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice...

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  • Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance

    Publication

    - Procedia Computer Science - Year 2021

    Machine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...

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  • A New, Reconfigurable Circuit Offering Functionality of AND and OR Logic Gates for Use in Algorithms Implemented in Hardware

    Publication
    • T. Talaśka
    • R. Długosz
    • T. Nikolić
    • G. Nikolić
    • T. Stefański
    • M. Długosz
    • M. Talaśka

    - Year 2023

    The paper presents a programmable (using a 1-bit signal) digital gate that can operate in one of two OR or AND modes. A circuit of this type can also be implemented using conventional logic gates. However, in the case of the proposed circuit, compared to conventional solutions, the advantage is a much smaller number of transistors necessary for its implementation. Circuit is also much faster than its conventional counterpart. The...

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  • The Impact of Generative AI and ChatGPT on Creating Digital Advertising Campaigns

    Publication

    The use of AI-based solutions is currently discussed in relation to various industries. The proliferation of tools based on generative artificial intelligence (GAI), including the emergence of ChatGPT, has resulted in testing as a first step and implementations in further areas of business life, including marketing, as a second step. Still only a few studies have analysed and evaluated specific solutions for different areas of...

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  • Insights in microbiotechnology: 2022.Editorial

    Publication

    This Research Topic serves as an invaluable resource for readers interested in staying updated with the latest progress and developments in the field of microbiotechnology. It spotlights the innovative research conducted by up-and-coming experts in the field, specifically emphasizing the transforming abilities of microorganisms that greatly influence the scientific community. The advent of multi-omic technologies has revolutionized microbiotechnology,...

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  • Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents

    Publication
    • S. Donghui
    • L. Zhigang
    • J. Zurada
    • A. Manikas
    • J. Guan
    • P. Weichbroth

    - KNOWLEDGE AND INFORMATION SYSTEMS - Year 2024

    The construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...

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  • From Individual to Collective: Intelligence Amplification with Bio-Inspired Decisional DNA and its Extensions

    Publication

    - Year 2022

    In nature, deoxyribonucleic acid (DNA) contains the genetic instructions used in the development and functioning of all known living organisms. The idea behind our vision is to develop an artificial system, an architecture that would support discovering, adding, storing, improving and sharing information and knowledge among agents and organizations through experience. We propose a novel Knowledge Representation (KR) approach in...

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  • Machine learning approach to packaging compatibility testing in the new product development process

    The paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...

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  • Spectrum-based modal parameters identification with Particle Swarm Optimization

    Publication

    - MECHATRONICS - Year 2016

    The paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....

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  • Qualitative data analysis methods

    e-Learning Courses
    • M. Starnawska

    This is the continuation of Qualitatative Data Analysis Methods course provided online

  • Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework

    Publication

    - OCEAN & COASTAL MANAGEMENT - Year 2024

    The rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...

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  • Bio-inspired Decisional DNA in Machinas and other Man-made Systems: The Way Forward

    Publication

    - Year 2014

    Artificial bio-inspired intelligent techniques and systems supporting smart, knowledge-based solutions of real world problems which are currently researched very extensively by research teams around the world, have enormous potential to enhance automation of decision making and problem solving for a number of diverse areas including design, manufacturing, Information Technology (IT), social communities of practice, and economics...

  • ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

    Journals

    ISSN: 0952-1976 , eISSN: 1873-6769

  • L23_24 Artificial Intelligence in Healthcare

    e-Learning Courses
    • J. Rumiński

  • Quantum aspects of semantic analysis and symbolic artificial intelligence.

    Publication

    - Year 2004

    Nowoczesne podejścia do analizy semantycznej, jeśli przeformułować je w język przestrzeni Hilberta, ujawniają formalne struktury znane z mechaniki kwantowej. Podobna sytuacja występuje w rozproszonych reprezentacjach struktur poznawczych rozwijanych na użytek sieci neuronowych. W pracy przyglądamy się różnicom i podobieństwom owych teorii do kwantowej teorii informacji.

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  • To Survive in a CBRN Hostile Environment: Application of CAVE Automatic Virtual Environments in First Responder Training

    Publication
    • P. Maciejewski
    • M. Gawlik-Kobylińska
    • J. Lebiedź
    • W. Ostant
    • D. Aydın

    - Year 2020

    This paper is of a conceptual nature and focuses on the use of a specific virtual reality environment in civil-military training. We analyzed the didactic potential of so-called CAVE automatic virtual environments for First Responder training, a type of training that fills the gap between First Aid training and the training received by emergency medical technicians. Since real training involves live drills based on unexpected situations,...

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  • Comparison and Analysis of Service Selection Algorithms

    Publication

    - Year 2013

    In Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...

  • Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach

    Publication
    • M. Saeb
    • B. Rezaee
    • A. Shadman
    • K. Formela
    • Z. Ahmadi
    • F. Hemmati
    • T. Kermaniyan
    • Y. Mohammadi

    - DESIGNED MONOMERS AND POLYMERS - Year 2017

    Experimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration,...

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  • I, Robot: between angel and evil

    Publication

    - Year 2020

    The boosting of most digital innovations within recent technology progress by artificial intelligence (AI) constitutes a growing topic of interest. Besides its technical aspects, increasing research activity may be observed in the domain of security challenges, and therefore of responsibility related to the controlled or hypothetically uncontrolled or autonomous emergence of AI solutions. Consequently, responsibility and ethics...

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  • Deep Learning: A Case Study for Image Recognition Using Transfer Learning

    Publication

    - Year 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Deep Learning

    Publication

    - Year 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover

    Publication

    The process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...

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  • Artificial Intelligence - Summer 2023/24

    e-Learning Courses
    • J. Dembski
    • A. Sobociński

  • Data Analysis 2023/24

    e-Learning Courses
    • K. Flisikowski

    Data Analysisdr inż. Karol Flisikowski, prof. PG - winter semester 2023/24

  • Big Data and the Internet of Things in Edge Computing for Smart City

    Publication

    - Year 2019

    Requests expressing collective human expectations and outcomes from city service tasks can be partially satisfied by processing Big Data provided to a city cloud via the Internet of Things. To improve the efficiency of the city clouds an edge computing has been introduced regarding Big Data mining. This intelligent and efficient distributed system can be developed for citizens that are supposed to be informed and educated by the...

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  • The study on the appearance of deformation defects in the yacht lamination process using an AI algorithm and expert knowledge

    This article describes the application of the A-priori algorithm for defining the rule-based relationships between individual defects caused during the lamination process, affecting the deformation defect of the yacht shell. The data from 542 yachts were collected and evaluated. For the proper development of the algorithm, a technological process of the yacht lamination supported by expert decisions was described. The laminating...

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  • A note on the affective computing systems and machines: a classification and appraisal

    Publication

    - Procedia Computer Science - Year 2022

    Affective computing (AfC) is a continuously growing multidisciplinary field, spanning areas from artificial intelligence, throughout engineering, psychology, education, cognitive science, to sociology. Therefore, many studies have been devoted to the aim of addressing numerous issues, regarding different facets of AfC solutions. However, there is a lack of classification of the AfC systems. This study aims to fill this gap by reviewing...

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  • Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks

    Deep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...

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  • Condition-Based Monitoring of DC Motors Performed with Autoencoders

    Publication

    - Year 2022

    This paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...

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  • Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale

    Publication
    • K. Mikołajewski
    • M. Ruman
    • K. Kosek
    • M. Glixelli
    • P. Dzimińska
    • P. Ziętara
    • P. Licznar

    - SCIENCE OF THE TOTAL ENVIRONMENT - Year 2022

    Despite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by means of model hyetographs. This creates the need for the availability of credible statistical methods for the development and verification of already locally applied model hyetographs....

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  • Algorithmic Human Resources Management

    Publication

    - Year 2024

    The rapid evolution of Digital Human Resources Management has introduced a transformative era where algorithms play a pivotal role in reshaping the landscape of workforce management. This transformation is encapsulated in the concepts of algorithmic management and algorithmic Human Resource Management (HRM). The integration of advanced analytics, predictive and prescriptive analytics and the power of Artificial Intelligence (AI)...

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  • Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction

    Publication

    - Scientific Reports - Year 2023

    This work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...

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  • The potential interaction of environmental pollutants and circadian rhythm regulations that may cause leukemia

    Publication
    • F. A. Lagunas-Rangel
    • B. Kudłak
    • W. Liu
    • M. Williams
    • H. B. Schiöth

    - CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY - Year 2022

    Tumor suppressor genes are highly affected during the development of leukemia, including circadian clock genes. Circadian rhythms constitute an evolutionary molecular machinery involving many genes, such as BMAL1, CLOCK, CRY1, CRY2, PER1, PER2, REV-ERBa, and RORA, for tracking time and optimizing daily life during day-night cycles and seasonal changes. For circulating blood cells many of these genes coordinate their proliferation,...

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  • How Machine Learning Contributes to Solve Acoustical Problems

    Publication
    • M. A. Roch
    • P. Gerstoft
    • B. Kostek
    • Z. Michalopoulou

    - Journal of the Acoustical Society of America - Year 2021

    Machine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...

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  • Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review

    Publication

    - ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING - Year 2024

    Fiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...

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  • Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0

    Publication

    - Year 2023

    The importance of the economy being up to date with the latest developments, such as Industry 4.0, is more evident than ever before. Successful implementation of Industry 4.0 principles requires close cooperation of industry and state authorities with universities. A paradigm of such cooperation is described in this paper stemming from university partners with partly overlapping and partly complementary areas of expertise in manufacturing....

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  • Automatic Rhythm Retrieval from Musical Files

    Publication

    - Year 2008

    This paper presents a comparison of the effectiveness of two computational intelligence approaches applied to the task of retrieving rhythmic structure from musical files. The method proposed by the authors of this paper generates rhythmic levels first, and then uses these levels to compose rhythmic hypotheses. Three phases: creating periods, creating simplified hypotheses and creating full hypotheses are examined within this study....

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  • Mixed-use buildings as the basic unit that shapes the housing environment of smart cities of the future

    Publication

    The contemporary approach to creating the residential function is confronted with the trend of increasing the volume of buildings and expectations regarding the future urban environment focused on sustainable development. This paper presents an overview of the residential structure in the context of defined thematic scopes. Namely, it is a systemic approach to the problem of designing mixed-use buildings which create a modern residential...

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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

    Universities 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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  • Communication as a Factor Limiting University-Business Cooperation

    Objective - Despite the broad extent of the scientific activity dealing with university-business cooperation, Poland has yet to develop a satisfactory cooperation strategy that takes business needs into account. This issue is still relevant due to the need for continuous improvement and resulting benefits aimed at improving enterprise competitiveness. Methodology/Technique - Authors of this article attempt to select an overriding...

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