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Department of Informatics and Computer Engineering, University of West Attica, Agiou Spiridonos 28, 12243 Egaleo, Greece

Prof. Dr. Cleo Sgouropoulou

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Department of Informatics and Computer Engineering, University of West Attica, 12244 Egaleo, Greece

Dr. Akrivi Krouska

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Department of Informatics and Computer Engineering, University of West Attica, Agiou Spiridonos 28, 12243 Egaleo, Greece

Prof. Dr. Ioannis Voyiatzis

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Department of Informatics and Computer Engineering, University of West Attica, 12244 Egaleo, Greece

Dr. Athanasios Voulodimos

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School of Electrical and Computer Engineering, National Technical University of Athens, 9, Iroon Polytechniou st., 157 80 Athens, Greece

Interactive Artificial Intelligence and Man-Machine Communication

Abstract submission deadline

closed (11 October 2022)

Manuscript submission deadline

closed (11 December 2022)

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7364

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Dear Colleagues,

Interactive artificial intelligence is based on the perception that human intelligence is characterized by interactivity. Many of the fascinating and core research issues in artificial intelligence involve topics for which the aim of smart and adaptive systems is to interact with people on their own terms. Indeed, in this digital era, digital systems are growing at an unprecedented rate. The wishes of users to interact with tailored content are ever increasing. This means that users are seeking intelligent software with greatly individualized user experiences (UXs), not only adaptive user interfaces (UIs). Therefore, the need for redefining traditional system development is of utmost importance. As such, incorporating sophisticated mechanisms into the development of robust systems, demonstrating the usefulness of this way of thinking, and into the development of fundamental algorithms, for disruptive technological features adjusted to human needs, is relevant. Such systems can exhibit a high degree of intelligent man–machine communication and UXs, user-centric features, and intelligence in their reasoning and diagnostic mechanisms. In recent decades, research efforts have focused on promoting man–machine communication and interactive artificial intelligence. In spite of the increased research interest, there is still room for further research on the directions of man–machine communication, interactivity, and artificial intelligence.

The present call-for-papers is requesting original research papers as well as review articles and short communications in the aforementioned areas. The topics of interest include, but are not limited to, the following:

Human–computer interaction;
Personalization and adaptivity in systems and services;
Machine/deep/reinforcement learning;
Collaborative and group work, communities of practice, and social networks;
Immersive and virtual reality environments;
Ubiquitous, mobile, and cloud environments;
Adaptive support for navigation, models of users, diagnosis, reasoning, and feedback;
The aspect of the modeling of motivation, metacognition, and affect;
Affective computing; Applications of machine learning to address real-world problems.

Prof. Dr. Christos Troussas
Prof. Dr. Cleo Sgouropoulou
Dr. Akrivi Krouska
Prof. Dr. Ioannis Voyiatzis
Dr. Athanasios Voulodimos
Topic Editors

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Entropy entropy	2.738	4.4	1999	19.9 Days	2000 CHF
Future Internet futureinternet	-	5.4	2009	15.2 Days	1600 CHF
Algorithms algorithms	-	3.3	2008	17.6 Days	1600 CHF
Computation computation	-	3.3	2013	16.2 Days	1600 CHF
Machine Learning and Knowledge Extraction make	-	-	2019	16.7 Days	1400 CHF
Multimodal Technologies and Interaction mti	-	4.5	2017	20.5 Days	1600 CHF

Preprints is a platform dedicated to making early versions of research outputs permanently available and citable. MDPI journals allow posting on preprint servers such as Preprints.org prior to publication. For more details about reprints, please visit https://www.preprints.org.

Published Papers (6 papers)

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Open AccessArticle

Automatic Generation of Literary Sentences in French

Luis-Gil Moreno-Jiménez

Juan-Manuel Torres-Moreno

and

Roseli Suzi. Wedemann

Algorithms 2023, 16(3), 142; https://doi.org/10.3390/a16030142 - 06 Mar 2023

Viewed by 427

Abstract

In this paper, we describe a model for the automatic generation of literary sentences in French. Although there has been much recent effort directed towards automatic text generation in general, the generation of creative, literary sentences that is not restricted to a specific genre, which we approached in this work, is a difficult task that is not commonly treated in the scientific literature. In particular, our present model has not been previously applied to the generation of sentences in the French language. Our model was based on algorithms that we previously used to generate sentences in Spanish and Portuguese and on a new corpus, which we constructed and present here, consisting of literary texts in French, called MegaLite^fr. Our automatic text generation algorithm combines language models, shallow parsing, the canned text method, and deep learning artificial neural networks. We also present a manual evaluation protocol that we propose and implemented to assess the quality of the artificial sentences generated by our algorithm, by testing if they fulfil four simple criteria. We obtained encouraging results from the evaluators for most of the desired features of our artificially generated sentences. Full article

(This article belongs to the Topic Interactive Artificial Intelligence and Man-Machine Communication)

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Open AccessArticle

Can AI-Oriented Requirements Enhance Human-Centered Design of Intelligent Interactive Systems? Results from a Workshop with Young HCI Designers

and

Multimodal Technol. Interact. 2023, 7(3), 24; https://doi.org/10.3390/mti7030024 - 25 Feb 2023

Viewed by 438

Abstract

In this paper, we show that the evolution of artificial intelligence (AI) and its increased presence within an interactive system pushes designers to rethink the way in which AI and its users interact and to highlight users’ feelings towards AI. For novice designers, it is crucial to acknowledge that both the user and artificial intelligence possess decision-making capabilities. Such a process may involve mediation between humans and artificial intelligence. This process should also consider the mutual learning that can occur between the two entities over time. Therefore, we explain how to adapt the Human-Centered Design (HCD) process to give centrality to AI as the user, further empowering the interactive system, and to adapt the interaction design to the actual capabilities, limitations, and potentialities of AI. This is to encourage designers to explore the interactions between AI and humans and focus on the potential user experience. We achieve such centrality by extracting and formalizing a new category of AI requirements. We have provocatively named this extension: “Intelligence-Centered”. A design workshop with MsC HCI students was carried out as a case study supporting this change of perspective in design. Full article

(This article belongs to the Topic Interactive Artificial Intelligence and Man-Machine Communication)

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Open AccessReview

Dental Age Estimation Using Deep Learning: A Comparative Survey

Essraa Gamal Mohamed

Rebeca P. Díaz Redondo

Abdelrahim Koura

Mohamed Sherif EL-Mofty

and

Mohammed Kayed

Computation 2023, 11(2), 18; https://doi.org/10.3390/computation11020018 - 29 Jan 2023

Viewed by 552

Abstract

The significance of age estimation arises from its applications in various fields, such as forensics, criminal investigation, and illegal immigration. Due to the increased importance of age estimation, this area of study requires more investigation and development. Several methods for age estimation using biometrics traits, such as the face, teeth, bones, and voice. Among then, teeth are quite convenient since they are resistant and durable and are subject to several changes from childhood to birth that can be used to derive age. In this paper, we summarize the common biometrics traits for age estimation and how this information has been used in previous research studies for age estimation. We have paid special attention to traditional machine learning methods and deep learning approaches used for dental age estimation. Thus, we summarized the advances in convolutional neural network (CNN) models to estimate dental age from radiological images, such as 3D cone-beam computed tomography (CBCT), X-ray, and orthopantomography (OPG) to estimate dental age. Finally, we also point out the main innovations that would potentially increase the performance of age estimation systems. Full article

(This article belongs to the Topic Interactive Artificial Intelligence and Man-Machine Communication)

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Open AccessArticle

The Study of Mathematical Models and Algorithms for Face Recognition in Images Using Python in Proctoring System

Shakizada Niyazbekova

Alexander Semenov

and

Leila Maisigova

Computation 2022, 10(8), 136; https://doi.org/10.3390/computation10080136 - 09 Aug 2022

Cited by 1 | Viewed by 1255

Abstract

The article analyzes the possibility and rationality of using proctoring technology in remote monitoring of the progress of university students as a tool for identifying a student. Proctoring technology includes face recognition technology. Face recognition belongs to the field of artificial intelligence and biometric recognition. It is a very successful application of image analysis and understanding. To implement the task of determining a person’s face in a video stream, the Python programming language was used with the OpenCV code. Mathematical models of face recognition are also described. These mathematical models are processed during data generation, face analysis and image classification. We considered methods that allow the processes of data generation, image analysis and image classification. We have presented algorithms for solving computer vision problems. We placed 400 photographs of 40 students on the base. The photographs were taken at different angles and used different lighting conditions; there were also interferences such as the presence of a beard, mustache, glasses, hats, etc. When analyzing certain cases of errors, it can be concluded that accuracy decreases primarily due to images with noise and poor lighting quality. Full article

(This article belongs to the Topic Interactive Artificial Intelligence and Man-Machine Communication)

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Open AccessArticle

Behaviour of True Artificial Peers

Norman Weißkirchen

and

Ronald Böck

Multimodal Technol. Interact. 2022, 6(8), 64; https://doi.org/10.3390/mti6080064 - 02 Aug 2022

Cited by 1 | Viewed by 925

Abstract

Typical current assistance systems often take the form of optimised user interfaces between the user interest and the capabilities of the system. In contrast, a peer-like system should be capable of independent decision-making capabilities, which in turn require an understanding and knowledge of the current situation for performing a sensible decision-making process. We present a method for a system capable of interacting with their user to optimise their information-gathering task, while at the same time ensuring the necessary satisfaction with the system, so that the user may not be discouraged from further interaction. Based on this collected information, the system may then create and employ a specifically adapted rule-set base which is much closer to an intelligent companion than a typical technical user interface. A further aspect is the perception of the system as a trustworthy and understandable partner, allowing an empathetic understanding between the user and the system, leading to a closer integrated smart environment. Full article

(This article belongs to the Topic Interactive Artificial Intelligence and Man-Machine Communication)

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Open AccessArticle

AI Technologies for Machine Supervision and Help in a Rehabilitation Scenario

Gábor Baranyi

Bruno Carlos Dos Santos Melício

and

Multimodal Technol. Interact. 2022, 6(7), 48; https://doi.org/10.3390/mti6070048 - 22 Jun 2022

Viewed by 1645

Abstract

We consider, evaluate, and develop methods for home rehabilitation scenarios. We show the required modules for this scenario. Due to the large number of modules, the framework falls into the category of Composite AI. Our work is based on collected videos with high-quality execution and samples of typical errors. They are augmented by sample dialogues about the exercise to be executed and the assumed errors. We study and discuss body pose estimation technology, dialogue systems of different kinds and the emerging constraints of verbal communication. We demonstrate that the optimization of the camera and the body pose allows high-precision recording and requires the following components: (1) optimization needs a 3D representation of the environment, (2) a navigation dialogue to guide the patient to the optimal pose, (3) semantic and instance maps are necessary for verbal instructions about the navigation. We put forth different communication methods, from video-based presentation to chit-chat-like dialogues through rule-based methods. We discuss the methods for different aspects of the challenges that can improve the performance of the individual components. Due to the emerging solutions, we claim that the range of applications will drastically grow in the very near future. Full article

(This article belongs to the Topic Interactive Artificial Intelligence and Man-Machine Communication)

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Submit your Abstract

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Entropy entropy	2.738	4.4	1999	19.9 Days	2000 CHF
Future Internet futureinternet	-	5.4	2009	15.2 Days	1600 CHF
Algorithms algorithms	-	3.3	2008	17.6 Days	1600 CHF
Computation computation	-	3.3	2013	16.2 Days	1600 CHF
Machine Learning and Knowledge Extraction make	-	-	2019	16.7 Days	1400 CHF
Multimodal Technologies and Interaction mti	-	4.5	2017	20.5 Days	1600 CHF

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Interactive Artificial Intelligence and Man-Machine Communication

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Published Papers (6 papers)

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