journal article·2022-06-07Open access

Research Directions of Applied Cognitive Sciences

Attila Kovari

Applied Sciences· Volume 12· Issue 12

Abstract

Cognitive science is an interdisciplinary field of investigation of the mind and intelligence [...]
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short

Research context

OpenAlex topics: Cognitive Science and Mapping · Cognitive Computing and Networks · Robotics and Automated Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Computer Science, GAMF Faculty of Engineering and Computer Science, John von Neumann University, 6000 Kecskemét, Hungary

References (23)

Show source-provided references
1. Automatic detection and classification of emotional states in virtual reality and standard environments (LCD): Comparing valence and arousal of induced emotions10.1007/s10055-021-00506-5 ↗
2. Dimensionality reduction methods used in Machine Learning
3. Multiple criteria decision-making method solutions based on failure mode and effect analysis
4. Katona, J. (2022). Measuring Cognition Load Using Eye-Tracking Parameters Based on Algorithm Description Tools. Sensors, 22.10.3390/s22030912 ↗
5. Clean and Dirty Code Comprehension by Eye-tracking Based Evaluation using GP3 Eye Tracker10.12700/APH.18.1.2021.1.6 ↗
6. Wijkmark, C.H., Metallinou, M.M., and Heldal, I. (2021). Remote Virtual Simulation for Incident Commanders—Cognitive Aspects. Appl. Sci., 11.10.3390/app11146434 ↗
7. Ali, Q., Heldal, I., Helgesen, C.G., Krumina, G., Costescu, C., Kovari, A., Katona, J., and Thill, S. (2021). Current Challenges Supporting School-Aged Children with Vision Problems: A Rapid Review. Appl. Sci., 11.10.3390/app11209673 ↗
8. Pinter, R., Maravić Čisar, S., Kovari, A., Major, L., Čisar, P., and Katona, J. (2020). Case Study: Students’ Code-Tracing Skills and Calibration of Questions for Computer Adaptive Tests. Appl. Sci., 10.10.3390/app10207044 ↗
9. Cognitive level of consumers’ knowledge in the case of a few food products
10. Francisti, J., Balogh, Z., Reichel, J., Magdin, M., Koprda, Š., and Molnár, G. (2020). Application Experiences Using IoT Devices in Education. Appl. Sci., 10.10.3390/app10207286 ↗
11. Costescu, C., Chelba, I., Roșan, A., Kovari, A., and Katona, J. (2021). Cognitive Patterns and Coping Mechanisms in the Context of Internet Use. Appl. Sci., 11.10.3390/app11031302 ↗
12. Shin, J.-G., Choi, G.-Y., Hwang, H.-J., and Kim, S.-H. (2021). Evaluation of Emotional Satisfaction Using Questionnaires in Voice-Based Human–AI Interaction. Appl. Sci., 11.10.3390/app11041920 ↗
13. Hikawa, H., Ichikawa, Y., Ito, H., and Maeda, Y. (2021). Dynamic Gesture Recognition System with Gesture Spotting Based on Self-Organizing Maps. Appl. Sci., 11.10.3390/app11041933 ↗
14. Sharma, R., Ribeiro, B., Pinto, A.M., and Cardoso, A. (2021). Emulating Cued Recall of Abstract Concepts via Regulated Activation Networks. Appl. Sci., 11.10.3390/app11052134 ↗
15. Sáiz-Manzanares, M.C., Pérez, I.R., Rodríguez, A.A., Arribas, S.R., Almeida, L., and Martin, C.F. (2021). Analysis of the Learning Process through Eye Tracking Technology and Feature Selection Techniques. Appl. Sci., 11.10.3390/app11136157 ↗
16. Popescu, A.B., Taca, I.A., Nita, C.I., Vizitiu, A., Demeter, R., Suciu, C., and Itu, L.M. (2021). Privacy Preserving Classification of EEG Data Using Machine Learning and Homomorphic Encryption. Appl. Sci., 11.10.3390/app11167360 ↗
17. Velichkovsky, B.M., Kotov, A., Arinkin, N., Zaidelman, L., Zinina, A., and Kivva, K. (2021). From Social Gaze to Indirect Speech Constructions: How to Induce the Impression That Your Companion Robot Is a Conscious Creature. Appl. Sci., 11.10.3390/app112110255 ↗
18. Namestovski, Ž., and Kovari, A. (2022). Framework for Preparation of Engaging Online Educational Materials—A Cognitive Approach. Appl. Sci., 12.10.3390/app12031745 ↗
19. An overview of metacognitive strategies in young learners’ vocabulary learning
20. Finseth, T., Dorneich, M.C., Keren, N., Franke, W.D., and Vardeman, S.B. (2022). Manipulating Stress Responses during Spaceflight Training with Virtual Stressors. Appl. Sci., 12.10.3390/app12052289 ↗
21. Rodriguez Aguiñaga, A., Muñoz Delgado, L., López-López, V.R., and Calvillo Téllez, A. (2022). EEG-Based Emotion Recognition Using Deep Learning and M3GP. Appl. Sci., 12.10.3390/app12052527 ↗
22. Gnjatović, M., Košanin, I., Maček, N., and Joksimović, D. (2022). Clustering of Road Traffic Accidents as a Gestalt Problem. Appl. Sci., 12.10.3390/app12094543 ↗
23. Statistical analysis of road freight transport in Catalonia10.30657/pea.2022.28.05 ↗