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Search results for: ARTIFICIAL INTELLIGENCE.

Search results for: ARTIFICIAL INTELLIGENCE.

  • Radar and Sonar Imaging and Processing (2nd Edition)

    Publication

    - Remote Sensing - Year 2021

    The 14 papers (from 29 submitted) published in the Special Issue “Radar and Sonar Imaging Processing (2nd Edition)” highlight a variety of topics related to remote sensing with radar and sonar sensors. The sequence of articles included in the SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends, in which the latest developments in science, including artificial intelligence,...

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  • THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN

    Publication

    - Year 2021

    In the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...

  • Application of Intuitionistic Fuzzy Sets to the assessment of technical university students

    The article proposes application of artificial intelligence methods to assess students of technical universities. The level of achieved educational goals can be assessed using measurements based on the idea of Fuzzy Intuitionistic Sets (IFS). A classification algorithm was developed and an exemplary distribution of the criteria values using IFS was presented. The application of the proposed approach in online education can enrich...

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  • Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction

    Due to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...

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  • Michał Czubenko dr inż.

    Michał Czubenko is a distinguished 2009 graduate of the Faculty of Electronics, Telecommunications, and Informatics at Gdańsk University of Technology, specializing in the discipline of automatic control and robotics. Currently, he serves as an adjunct in the Department of Robotics and Decision Systems at the same institution. In 2012, he embarked on a three-month internship at Kingston University London, broadening his horizons...

  • Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2024

    This guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...

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  • Przegląd metod szybkiego prototypowania algorytmów uczenia maszynowego w FPGA

    W artykule opisano możliwe do wykorzystania otwarte narzędzia wspomagające szybkie prototypowanie algorytmów uczenia maszynowego (ML) i sztucznej inteligencji (AI) przy użyciu współczesnych platform FPGA. Przedstawiono przykład szybkiej ścieżki przy realizacji toru wideo wraz z implementacją przykładowego algorytmu prze-twarzania w trybie na żywo.

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  • Towards detecting programmers’ stress on the basis of keystroke dynamics

    The article describes the idea of detecting stress among programmers on the basis of keystroke dynamics. An experiment with a group of students of artificial intelligence classes was performed. Two samples of keystroke data were recorded for each case, the first while programming without stress, the second under time pressure. A number of timing and frequency parameters were calculated for each sample. Then statistical analysis...

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  • Representing and Managing Experiential Knowledge with Decisional DNA and its Drimos® Extension

    Publication

    - Year 2022

    The Semantic Web concept is proposing a future concept of the WorldWideWeb (WWW) where both humans and man-made systems are able to interconnect and exchange knowledge. One of the challenges of Semantic Web is smart and trusted accommodation of knowledge in artificial systems so it can be unified, enhanced, reused, shared, communicated and distributed with added aptitude. Our research represents an important component of addressing...

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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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  • AI-powered Digital Transformation: Tools, Benefits and Challenges for Marketers – Case Study of LPP

    Publication

    - Year 2023

    The article aims to show the role (benefits and challenges) of AI-powered digital marketing tools for marketers in the age of digital transformation. The considerations were related to the Polish market and a case study of LPP, a Polish clothing retailer. The starting point for this study was the analysis of the literature on the concept of artificial intelligence (AI) with reference to digital marketing. In the next steps, the...

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  • Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje

    Publication
    • J. Kreft
    • M. Boguszewicz-kreft
    • B. Cyrek

    - Roczniki Nauk Społecznych - Year 2024

    Generatywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...

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  • 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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  • Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud

    Publication

    - Year 2020

    In a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...

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  • A survey of neural networks usage for intrusion detection systems

    In recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...

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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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  • AI in the creation of the satellite maps

    Publication

    - Year 2015

    Satellite and aerial imagery acquisition is a very useful source of information for remote monitoring of the Earth’s surface. Modern satellite and aerial systems provide data about the details of the site topography, its characteristics due to different criteria (type of terrain, vegetation cover, soil type and moisture content), or even information about emergency situations or disasters. The paper proposes and discusses the process...

  • 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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  • 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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  • Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?

    Publication

    Purpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...

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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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  • General concept of reduction process for big data obtained by interferometric methods

    Publication

    - Year 2017

    Interferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...

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  • Metaheurystyki sztucznej inteligencji w wybranych grach komputerowych

    W pracy omówiono trzy metaheurystyki sztucznej inteligencji, które mogą stać się źródłem inspiracji dla projektantów gier komputerowych. Pokazano, w jaki sposób zastosowano algorytm mrówkowy, algorytm genetyczny i algorytm tabu search w grach komputerowych zaprojektowanych przez studentów Politechniki Gdańskiej. W szczególności, odniesiono się do problematyki wyznaczania trajektorii przemieszczających się obiektów...

  • Oleksandr Melnychenko dr hab.

    Oleksandr Melnychenko works as a professor in a group of research and teaching staff at the Department of Finance of the Faculty of Management and Economics, the Gdańsk University of Technology; is a sworn translator of the Ukrainian language in Poland; an entrepreneur with many years of experience in running his own business and managing the companies' finances; has experience working in a commercial bank in a position dealing...

  • Data Acquisition in a Manoeuver Auto-negotiation System

    Typical approach to collision avoidance systems with artificial intelligence support is that such systems assume a central communication and management point (such as e.g. VTS station), usually located on shore. This approach is, however, not applicable in case of an open water encounter. Thus, recently a new approach towards collision avoidance has been proposed, assuming that all ships in the encounter, either restricted or open...

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  • Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models

    Publication
    • R. Yurt
    • H. Torpi
    • P. Mahouti
    • A. Kizilay
    • S. Kozieł

    - IEEE Access - Year 2023

    This work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...

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  • Zdzisław Kowalczuk prof. dr hab. inż.

    Zdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...

  • Algorithmic Human Resources Management - Perspectives and Challenges

    Theoretical background: Technology – most notably processes of digitalisation, the use of artificial intelligence, machine learning, big data and prevalence of remote work due to pandemic – changes the way organizations manage human resources. One of the increasing trends is the use of so-called “algorithmic management”. It is notably different than previous e-HRM or HRIS (human resources information systems) applications, as it...

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  • Arsalan Muhammad Soomar Doctoral Student

    People

    Hi, I'm Arsalan Muhammad Soomar, an Electrical Engineer. I received my Master's and Bachelor's Degree in the field of Electrical Engineering from Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan.  Currently enrolled as a Doctoral student at the Gdansk University of Technology, Gdansk, Poland. Also worked in Yellowlite. INC, Ohio  as a Solar Design Engineer.   HEADLINE Currently Enrolled as a Doctoral...

  • Sensors and Sensor’s Fusion in Autonomous Vehicles

    Publication

    - SENSORS - Year 2021

    Autonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...

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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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  • Krzysztof Goczyła prof. dr hab. inż.

    Krzysztof Goczyła, full professor of Gdańsk University of Technology, computer scientist, a specialist in software engineering, knowledge engineering and databases. He graduated from the Faculty of Electronics Technical University of Gdansk in 1976 with a degree in electronic engineering, specializing in automation. Since then he has been working at Gdańsk University of Technology. In 1982 he obtained a doctorate in computer science...

  • How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe

    This paper uses a sample of over 9 million workers from 22 European countries to study the intertwined relationship between digital technology, cross-border production links and working conditions. We compare the social consequences of technological change exhibited by three types of innovation: computerisation (software), automation (robots) and artificial intelligence (AI). To fully quantify work-related wellbeing, we propose...

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  • Electronic nose algorithm design using classical system identification for odour intensity detection

    The two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...

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  • Pedestrian detection in low-resolution thermal images

    Over one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...

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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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  • How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?

    Open Research Data
    open access

    The data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...

  • Spotkanie politechnicznego klubu sztucznej inteligencji

    Events

    24-10-2019 17:30 - 24-10-2019 19:15

    Pierwsze w tym roku akademickim spotkanie klubu AI Bay – Zatoka Sztucznej Inteligencji, który działa na Politechnice Gdańskiej odbędzie się w Gmachu B Wydziału Elektroniki, Telekomunikacji i Informatyki (Audytorium 1P).

  • PPAM 2022

    Events

    11-09-2022 07:00 - 14-09-2022 13:56

    The PPAM 2022 conference, will cover topics in parallel and distributed computing, including theory and applications, as well as applied mathematics.

  • Addressing Challenges in AI-based Systems Development: A Proposal of Adapted Requirements Engineering Process

    Publication

    [Context] Present-day IT systems are more and more dependent on artificial intelligence (AI) solutions. Developing AI-based systems means facing new challenges, not known for more conventional systems. Such challenges need to be identified and addressed by properly adapting the existing development and management processes. [Objective] In this paper, we focus on the requirements engineering (RE) area of IT projects and aim to propose...

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  • Roman Śmierzchalski prof. dr hab. inż.

    Roman Śmierzchalski born in 1956 in Gdynia. He received the M.Sc. degree in 1979, the Ph.D. degree in 1989, both from the Gdańsk University of Technology, and the D.Sc. (‘habilitation’) degree in 1999 from the Warsaw University of Technology. From 1980 to 2009 he was an academic teacher and researcher with the Gdynia Maritime University, and since 2009 he has been with the Gdansk University of Technology, where he is currently...

  • 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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  • 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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  • 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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  • 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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  • Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons

    Publication

    Recent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...

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