1. Sensors and artificial intelligence methods and algorithms for human - computer intelligent interaction: a systematic mapping studyBoštjan Šumak, Saša Brdnik, Maja Pušnik, 2022, izvirni znanstveni članek Opis: To equip computers with human communication skills and to enable natural interaction
between the computer and a human, intelligent solutions are required based on artificial intelligence
(AI) methods, algorithms, and sensor technology. This study aimed at identifying and analyzing
the state-of-the-art AI methods and algorithms and sensors technology in existing human–computer
intelligent interaction (HCII) research to explore trends in HCII research, categorize existing evidence,
and identify potential directions for future research. We conduct a systematic mapping study of the
HCII body of research. Four hundred fifty-four studies published in various journals and conferences
between 2010 and 2021 were identified and analyzed. Studies in the HCII and IUI fields have
primarily been focused on intelligent recognition of emotion, gestures, and facial expressions using
sensors technology, such as the camera, EEG, Kinect, wearable sensors, eye tracker, gyroscope, and
others. Researchers most often apply deep-learning and instance-based AI methods and algorithms.
The support sector machine (SVM) is the most widely used algorithm for various kinds of recognition,
primarily an emotion, facial expression, and gesture. The convolutional neural network (CNN)
is the often-used deep-learning algorithm for emotion recognition, facial recognition, and gesture
recognition solutions.
Ključne besede: human–computer intelligent interaction, intelligent user interfaces, IUI, sensors, artificial intelligence
Objavljeno v DKUM: 31.03.2025; Ogledov: 0; Prenosov: 1
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2. Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees : testing linear and non-linear relationshipsMaja Rožman, Polona Tominc, Borut Milfelner, 2023, izvirni znanstveni članek Opis: The paper’s main aim is to analyze five constructs of organizational culture, AI-supported leadership, AI-supported appropriate training of employees, teams’ effective performance, and employee engagement, and their relationship through the prism of artificial intelligence on a sample of large and medium-sized Slovenian companies. The second aim of the paper is to test the proposed model with two different statistical techniques in the scope of structural equation modeling (SEM) that enable us to assess linear (PLS-SEM) and non-linear relationships (CB-SEM) among the constructs. The empirical research included 437 medium-sized and large Slovenian companies. From each company, a CEO or owner participated in our research. The findings of the research with both techniques show that organizational culture had no impact on AI-supported appropriate training of employees and was not significant as well as that organizational culture had an impact on AI-supported leadership. The impact of AI-supported leadership on AI-supported appropriate training of employees were supported only for the PLS-SEM model. The impact of AI-supported leadership for employees on teams was positive. Contrary to that, the impact of AI-supported leadership for business solutions on teams was non-significant. In both cases, AI-supported appropriate training of employees’ impact on teams was strong and positive. Also, employee engagement impact on teams was positive and statistically significant with PLS-SEM and CB-SEM methods. The research yields important implications for companies seeking to integrate artificial intelligence effectively in their operations. It emphasizes the critical role of AI-supported leadership in driving positive outcomes, such as improved employee training and enhanced team effectiveness. Companies should focus on developing leaders who can leverage AI tools to foster a skilled and engaged workforce. By adopting data-driven decision-making processes and incorporating insights from structural equation modeling, organizations can develop effective AI integration strategies. These provide valuable guidance for enhancing human resource management practices and achieving successful AI adoption across companies. The findings contribute to the formation of new views in the field of artificial intelligence implementation in the companies and show companies a broader picture of which aspects of human resource management need to be improved.
Ključne besede: leadership, organizational culture, employee engagement, artificial intelligent
Objavljeno v DKUM: 22.04.2024; Ogledov: 185; Prenosov: 64
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3. Artificial intelligence versus human talents in learning processJanez Bregant, Boris Aberšek, 2011, izvirni znanstveni članek Opis: To highlight the differences between conventional educational systems and CBLS - computer based learning systems. It is useful to consider CBLS, as the class of a system most closely related to artificial intelligence - AI. In such a system, the ultimate goal is to create a virtual duplicate of reality for learning, analysis, training, experimentation, or other purposes. Simulating reality is an approach that may or may not be useful at creating experience. This distinction yield several consequences. In CBLS, behaviour should be as realistic as possible, the representation of environment tends to be uniform and consistent and allowing users to act freely within that environment.
To teach users through realistic experience CBLS design techniques can make the experience much more memorable. In such an environment the context and control afforded by design techniques allow the integration of technologies and evaluation of the overall experience. Perhaps it is time to take lessons of CBLS and AI in a learning design and teaching tools seriously.
At the beginning we will point out one simple question: could the ideas, methodology and techniques of AI also be applied to a development of relatively serious mind applications and can they substitute human teachers? And the answer will be continued in our paper.
Ključne besede: education, intelligent tutors, artificial intelligence, CBLS
Objavljeno v DKUM: 12.12.2017; Ogledov: 1440; Prenosov: 156
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4. Design of row-based flexible manufacturing system with evolutionary computationMirko Ficko, Jože Balič, 2008, objavljeni znanstveni prispevek na konferenci Opis: This paper discusses design of flexible manufacturing systems (FMSs) in one or multiple rows. Evolutionary computation, particularly genetic algorithms (GAs) proved to be successful in search of optimal solution for this type of problems. The model of solution, the most suitable way of coding the solutions into the organisms and the selected evolutionary and genetic operators are presented. In this connection, the most favourable number of rows and the sequence of devices in the individual row are established by means of genetic algorithms (GAs). In the end the test results of the application made and the analysis are discussed.
Ključne besede: flexible manufacturing system design, genetic algorithms, evolutionary computation, intelligent manufacturing systems, artificial intelligence
Objavljeno v DKUM: 31.05.2012; Ogledov: 2248; Prenosov: 102
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