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Descriptive Markers for the Cognitive Profiling of Desktop 3D Spaces

Adam Csapo Anna Sudar

Publication Name: Electronics Switzerland

Publication Date: 2023-01-01

Volume: 12

Issue: 2

Page Range: Unknown

Description:

3D virtual reality spaces, whether running on desktop environments or on immersive displays, have been noted to support a radically new and highly stimulating way of working with digital content in a variety of application domains. At the same time, research in recent decades has produced a number of experimental results showing that the use of 3D, as opposed to 2D interfaces, can lead to performance improvements from a wide range of aspects, including the ability to comprehend and retain knowledge, ability to work collaboratively in more creative and effective ways, and ability to carry out workflows integrating numerous sources of information in less time. In this paper, we first review the relevant literature; then, we describe an exploratory study that we carried out with test subjects, both in a 3D desktop virtual environment and in a 2D web-based environment, while collecting eye tracking data. In the study, subjects were presented with a set of multimedia content on a range of topics within the field of astronomy, based on which they were subsequently asked to fill out a set of questionnaires. By comparing the 2D and 3D cases in terms of correctness of answers, time taken to perform the task, pupil dilation measurements, subjects’ self-reported difficulty assessments, as well as various kinds of high-level interaction patterns employed during the task (in 3D), we were able to identify a set of descriptive markers which may be relevant to the prediction of users’ effectiveness in virtual reality workspaces. In a weaker sense, the results also seem to support previous research works claiming improved effectiveness in 3D spaces compared to 2D web-based interfaces, although further work is needed to more clearly identify the constraints within which such benefits can be guaranteed.

Open Access: Yes

DOI: 10.3390/electronics12020448

Bi-directional Evolutionary, Reliability-based, Geometrically Nonlinear, Elasto-Plastic Topology Optimization, of 3D Structures

Szabolcs Fischer Majid Movahedi Rad Muayad Habashneh

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2023-01-01

Volume: 20

Issue: 1

Page Range: 169-186

Description:

An extension of bi-directional evolutionary structural optimization, by considering three-dimensional geometrically nonlinear reliability-based elasto-plastic topology optimization, is presented in this study. Due to the important role of the existence of uncertainties to make structural design more practical, this study considers the reliability-based design. Thus, for probabilistic purposes, volume fraction is considered random. The reason of considering the volume fraction as random variable that the application of reliability-based topology optimization shows different topological results comparing to those which are obtained through deterministic designs. By adopting Monte-Carlo technique, the reliability indices are calculated based on the failure probabilities. Different values of volume fractions are considered to explore the effect of changing it on the resultant topologies in case of deterministic design. Furthermore, study the influence of considering different values of reliability indices on the results of probabilistic designs. The plastic-limit analysis is considered in this study in case of elasto-plastic models. A 3D elasto-plastic L-shape beam is considered as a benchmark problem to demonstrate the proficiency of the proposed method. In addition, 3D cantilever beam is considered for deterministic and probabilistic topology optimization designs in cases of elastic and elasto-plastic materials.

Open Access: Yes

DOI: 10.12700/APH.20.1.2023.20.12

COMPARISON OF TRANSFER FUNCTIONS OF OPEN EAR CANAL HEADSETS MEASURED ON A DUMMY-HEAD AND A HUMAN HEAD

Gyorgy Wersenyi

Publication Name: Proceedings of Forum Acusticum

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Headsets that leave the ear canal open are used where environmental noise and acoustical information have to be maintained, while additional sound transmission is also required. Besides classical supra aural and in-ear phones having “hear through” functions, bone conduction and “tube-like” headsets inserted in the ear canal can be used. Usually, the transfer parameters of these devices are inferior to traditional headphones, providing decreased sound quality, sensitivity and speech intelligibility. Two different commercially available bone conduction headphones, an in-ear tube type earphone and supra aural models were tested using a dummy-head and a real human head for comparison. Measured transfer functions show the limited frequency range of open ear canal models that restricts the accessibility of such devices. Variability in repeated measurements is relatively large. Standardization of the measurement procedure for bone conduction headsets is needed, where the inclusion of human subjects can be considered.

Open Access: Yes

DOI: DOI not available

On the aggregation functions used in fuzzy signatures based medical image analysis

Ferenc Lilik Melinda Kovacs Ĺaszĺo T. Ḱoczy Szilvia Nagy

Publication Name: IEEE 23rd International Symposium on Computational Intelligence and Informatics Cinti 2023 Proceedings

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 409-414

Description:

The paper proposes the use of fuzzy signatures for modeling and analysis of pre-processed medical images, as an example, CT images of the liver are analyzed. Fuzzy signatures are used for the case of distinguishing larger and smaller malignant lesions from each other and from other (benign) nodular diseases in liver computed tomography images. As computed tomography phases are sometimes missing, the treatment of missing data is also briefly addressed. As the size of the malignant lesion influences its manifestation on the images, separate sub-signatures are developed for large and small lesions with the size being a separate layer of the signature. From the medical experts' point of view besides the tree structure of the signature it is crutial to determine the aggregations themselves, which model the ways experts fuse and combine the available information. For the subtrees for small and large lesions in the sub-roots algebraic multiplication seems to be the best fitting t-norm, while in the subtree weighted means.

Open Access: Yes

DOI: 10.1109/CINTI59972.2023.10381986

Capsule Network based 3D Object Orientation Estimation

Claudiu Radu Pozna Áron Ballagi János Hollósi

Publication Name: International Conference on Electrical Computer Communications and Mechatronics Engineering Iceccme 2023

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Convolutional neural networks have proven to be one of the most efficient methods for processing visual data. Due to the popularity of the field, there is a growing interest in the reliability of intelligent systems. It has been shown that convolutional neural networks can be fooled by extreme inputs or noisy inputs. To overcome the current problems of convolutional neural networks, the theory of capsule networks was introduced by Geoffrey Hinton and his research team. In this work we want to investigate the theory of capsule networks for orientation recognition of 3-dimensional objects. We consider the case when the data are noise loaded by various adversarial attacking methods. We compare our results with the efficiency of convolutional neural network based solutions, highlighting the difference between the two theories. We investigate the efficiency reduction that can be observed using different adversarial attacking methods. Our results will show how much more efficient the capsule network is compared to the neural networks.

Open Access: Yes

DOI: 10.1109/ICECCME57830.2023.10252762

Adaptive ICT-based evaluation system in teaching and learning process

Eniko Nagy Karl Eva Gyorgy Molnar

Publication Name: Ines 2023 27th IEEE International Conference on Intelligent Engineering Systems 2023 Proceedings

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 89-94

Description:

Evaluation is an essential part of education. In addition to helping track student progress and learning processes, evaluations play a significant critical and important role in developing the individual's personality and forming a realistic self-image. Therefore, evaluations must be accurate, reliable, encompassing of changes, and supportive of developmental paths. Assessments can take various forms and can be carried out in-person, verbally, in writing, or through practical tasks, but they can also be conducted online, in a digital format, within a suitable framework. Regardless of these, one common element, the assessing educator is the adult who plans, integrates, and conducts the periodic control and evaluation process. Thus, there is also a generational difference inherently present and this affects the entire teaching and learning process, thereby influencing the evaluation process significantly, and reducing its efficiency. In this study, we present a self-developed system that increases the efficiency of the control and evaluation process by assisting the educator's work and reducing the communication gap due to generational differences. In addition to describing the applied technologies during the system's demonstration, we also discuss the methods and operating processes, which we conclude by evaluating the test results.

Open Access: Yes

DOI: 10.1109/INES59282.2023.10297735

A Holistic Framework to Prioritizing Building Interventions for Sustainable and Resilient Construction in Seismic-Prone Regions

Nurullah Bektaş

Publication Name: Chemical Engineering Transactions

Publication Date: 2023-01-01

Volume: 107

Issue: Unknown

Page Range: 1-6

Description:

During earthquakes, damage and collapse of structures pose physical risks but also social, economic, and environmental challenges. Even buildings that appear not significantly damaged may require demolition and reconstruction to ensure their resilience. The demolition of existing buildings not only results in the loss of property and lives but also contributes to the unsustainability of the building stock. To mitigate these challenges, development of a comprehensive framework is imperative, one that can seamlessly integrate vulnerability and sustainability parameters. This holistic approach aims to achieve a sustainable building stock that not only mitigates physical vulnerabilities but also can be used to address the social and economic aspects. This study presents an interpretable, adaptable, and transparent Rapid Visual Screening (RVS) method combining machine learning, fuzzy logic, and neural networks to assess existing buildings and prioritize them based on intervention requirements and promote building stock sustainability. Buildings with higher scores indicate lower seismic sustainability ratings, emphasizing the need for intervention and improvement to enhance their resilience. The implementation of this framework facilitates the development of a safe, resilient, and environmentally sustainable building stock. In its initial stages, the proposed RVS method achieved an accuracy rate surpassing both conventional methods and the baseline. Ultimately, its application extends beyond existing buildings, as the method can also be used during the design of new buildings in seismic-prone regions.

Open Access: Yes

DOI: 10.3303/CET23107001

A Linear Driver Model of Local Path Planning for Lane Driving

Ernö Horváth Gergo Igneczi Krisztian Nyilas

Publication Name: Sisy 2023 IEEE 21st International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 103-108

Description:

Modern lane centering assistance systems often use the mid-lane as a reference line for tracking. However, human drivers prefer to keep an offset to the mid-lane. Therefore, we have proposed in our previous work a driver model which calculates human-like offset values and enable the path planner to plan human-like paths. The driving data of 15 drivers have been analyzed. It has been revealed that drivers behave differently in left or right curves and choose to drive on either the left or the right side in straight road sections. Therefore, we extend our model to handle these traits. We have shown that the extended model outperforms the previous symmetric model.

Open Access: Yes

DOI: 10.1109/SISY60376.2023.10417953

THE END OF AN ERA

Andor Wesselényi-Garay

Publication Name: Metszet

Publication Date: 2023-01-01

Volume: 14

Issue: 6

Page Range: 34-39

Description:

Today's innovation will help to inform the future's tradition or 01vice versa. Drawing inspiration from traditional and regional Transylvanian architectural forms a new residential building has been developed to house trainee ice hockey players. The building itself although described as traditional, merely a reference to its external appearance, is seen to innovative in the use of building technology and mechanical services on closer inspection.

Open Access: Yes

DOI: 10.33268/Met.2023.6.3