{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:46:41Z","timestamp":1760244401906,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T00:00:00Z","timestamp":1671580800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education, Science and Technological Development of the Republic of Serbia","award":["III44008","TR32035","III44006","337-00-426\/2021-09","2021YFE0110500"],"award-info":[{"award-number":["III44008","TR32035","III44006","337-00-426\/2021-09","2021YFE0110500"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["III44008","TR32035","III44006","337-00-426\/2021-09","2021YFE0110500"],"award-info":[{"award-number":["III44008","TR32035","III44006","337-00-426\/2021-09","2021YFE0110500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>This paper introduces a heuristic for multiple sequence alignment aimed at improving real-time object recognition in short video streams with uncertainties. It builds upon the idea of the progressive alignment but is cognitively economical to the extent that the underlying edit distance approach is adapted to account for human working memory limitations. Thus, the proposed heuristic procedure has a reduced computational complexity compared to optimal multiple sequence alignment. On the other hand, its relevance was experimentally confirmed. An extrinsic evaluation conducted in real-life settings demonstrated a significant improvement in number recognition accuracy in short video streams under uncertainties caused by noise and incompleteness. The second line of evaluation demonstrated that the proposed heuristic outperforms humans in the post-processing of recognition hypotheses. This indicates that it may be combined with state-of-the-art machine learning approaches, which are typically not tailored to the task of object sequence recognition from a limited number of frames of incomplete data recorded in a dynamic scene situation.<\/jats:p>","DOI":"10.3390\/axioms12010003","type":"journal-article","created":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T05:42:53Z","timestamp":1671601373000},"page":"3","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cognitively Economical Heuristic for Multiple Sequence Alignment under Uncertainties"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0343-7596","authenticated-orcid":false,"given":"Milan","family":"Gnjatovi\u0107","sequence":"first","affiliation":[{"name":"Department of Information Technology, University of Criminal Investigation and Police Studies, Cara Du\u0161ana 196, 11080 Beograd, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3465-7524","authenticated-orcid":false,"given":"Nemanja","family":"Ma\u010dek","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Academy of Technical and Art Applied Studies, Vojvode Stepe 283, 11000 Beograd, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2577-7927","authenticated-orcid":false,"given":"Muzafer","family":"Sara\u010devi\u0107","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, University of Novi Pazar, Dimitrija Tucovi\u0107a bb., 36300 Novi Pazar, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2875-685X","authenticated-orcid":false,"given":"Sa\u0161a","family":"Adamovi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Informatics and Computing, Singidunum University, Danijelova 32, 11000 Beograd, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5390-4052","authenticated-orcid":false,"given":"Du\u0161an","family":"Joksimovi\u0107","sequence":"additional","affiliation":[{"name":"Department of Information Technology, University of Criminal Investigation and Police Studies, Cara Du\u0161ana 196, 11080 Beograd, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5308-2503","authenticated-orcid":false,"given":"Darjan","family":"Karaba\u0161evi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, Jevrejska 24, 11000 Belgrade, Serbia"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"191","DOI":"10.12700\/APH.17.2.2020.2.11","article-title":"Putting Humans Back in the Loop: A Study in Human-Machine Cooperative Learning","volume":"17","year":"2020","journal-title":"Acta Polytech. Hung."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Singh, P., Diwakar, M., Gupta, R., Kumar, S., Chakraborty, A., Bajal, E., Jindal, M., Shetty, D.K., Sharma, J., and Dayal, H. (2022). A Method Noise-Based Convolutional Neural Network Technique for CT Image Denoising. Electronics, 11.","DOI":"10.3390\/electronics11213535"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"100225","DOI":"10.1016\/j.rineng.2021.100225","article-title":"A noise robust convolutional neural network for image classification","volume":"10","author":"Momeny","year":"2021","journal-title":"Results Eng."},{"key":"ref_4","first-page":"025503","article-title":"Comparison of deep learning and human observer performance for detection and characterization of simulated lesions","volume":"6","author":"Gang","year":"2019","journal-title":"J. Med. Imaging"},{"key":"ref_5","first-page":"79","article-title":"Machine learning in Magnetic Resonance Imaging: Image reconstruction","volume":"83","author":"Muthurangu","year":"2021","journal-title":"Phys. Med. Eur. J. Med. Phys."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gnjatovi\u0107, M., Ma\u010dek, N., and Adamovi\u0107, S. (2019, January 23\u201325). A Non-Connectionist Two-Stage Approach to Digit Recognition in the Presence of Noise. Proceedings of the 10th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), Naples, Italy.","DOI":"10.1109\/CogInfoCom47531.2019.9089923"},{"key":"ref_7","unstructured":"Seel, N. (2012). Cognitive-Economy Assumptions for Learning. Encyclopedia of the Sciences of Learning, Springer."},{"key":"ref_8","first-page":"807","article-title":"The uncertainty and explainability in object recognition","volume":"33","author":"Hui","year":"2021","journal-title":"J. Exp. Theor. Artif. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.future.2020.03.005","article-title":"Known unknowns: Indeterminacy in authentication in IoT","volume":"111","author":"Heydari","year":"2020","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1089\/cmb.1994.1.337","article-title":"On the complexity of multiple sequence alignment","volume":"1","author":"Wang","year":"1944","journal-title":"J. Comput. Biol."},{"key":"ref_11","unstructured":"Jurafsky, D., and Martin, J.H. (2009). Speech and Language Processing: An Introduction to Natural Language Processing, Speech Recognition, and Computational Linguistics, Prentice-Hall. [2nd ed.]."},{"key":"ref_12","first-page":"707","article-title":"Binary codes capable of correcting deletions, insertions, and reversals, Cybernetics and Control Theory","volume":"10","author":"Levenshtein","year":"1966","journal-title":"Cybern. Control. Theory"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1145\/321796.321811","article-title":"The String-to-String Correction Problem","volume":"21","author":"Wagner","year":"1974","journal-title":"J. Assoc. Comput. Mach."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Chao, J., Tang, F., and Xu, L. (2022). Developments in Algorithms for Sequence Alignment: A Review. Biomolecules, 12.","DOI":"10.3390\/biom12040546"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Alkuhlani, A., Gad, W., Roushdy, M., Voskoglou, M.G., and Salem, A.b.M. (2022). PTG-PLM: Predicting Post-Translational Glycosylation and Glycation Sites Using Protein Language Models and Deep Learning. Axioms, 11.","DOI":"10.3390\/axioms11090469"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"615630","DOI":"10.1155\/2013\/615630","article-title":"An Overview of Multiple Sequence Alignments and Cloud Computing in Bioinformatics","volume":"2013","author":"Daugelaite","year":"2013","journal-title":"ISRN Biomath."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.future.2020.12.009","article-title":"Detecting impersonation attacks in cloud computing environments using a centric user profiling approach","volume":"117","author":"Kholidy","year":"2021","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Campbell, J., Lewis, J.P., and Seol, Y. (2018, January 13\u201314). Sequence alignment with the Hilbert-Schmidt independence criterion. Proceedings of the 15th ACM SIGGRAPH European Conference on Visual Media Production, London, UK.","DOI":"10.1145\/3278471.3278475"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/TMM.2008.2008924","article-title":"Scene Detection in Videos Using Shot Clustering and Sequence Alignment","volume":"11","author":"Chasanis","year":"2009","journal-title":"IEEE Trans. Multimed."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Dogan, P., Li, B., Sigal, L., and Gross, M. (2018, January 18\u201322). A Neural Multi-Sequence Alignment TeCHnique (NeuMATCH). Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00912"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Schimke, S., Vielhauer, C., and Dittmann, J. (2004, January 26). Using adapted Levenshtein distance for on-line signature authentication. Proceedings of the 17th International Conference on Pattern Recognition, Cambridge, UK.","DOI":"10.1109\/ICPR.2004.1334412"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1089\/106652701753307511","article-title":"Computational complexity of multiple sequence alignment with SP-score","volume":"8","author":"Just","year":"2001","journal-title":"J. Comput. Biol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Herman, J.L., Nov\u00e1k, A., Lyngs\u00f8, R., Szab\u00f3, A., Mikl\u00f3s, I., and Hein, J. (2015). Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs. BMC Bioinform., 16.","DOI":"10.1186\/s12859-015-0516-1"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.future.2017.02.007","article-title":"Analysis of classic algorithms on highly-threaded many-core architectures","volume":"82","author":"Ma","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1007\/BF02603120","article-title":"Progressive sequence alignment as a prerequisite to correct phylogenetic trees","volume":"25","author":"Feng","year":"1987","journal-title":"J. Mol. Evol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1037\/h0043158","article-title":"The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information","volume":"63","author":"Miller","year":"1956","journal-title":"Psychol. Rev."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2032","DOI":"10.1364\/JOSAA.7.002032","article-title":"Contrast in complex images","volume":"7","author":"Peli","year":"1990","journal-title":"J. Opt. Soc. Am. A"}],"container-title":["Axioms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1680\/12\/1\/3\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:45:13Z","timestamp":1760147113000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1680\/12\/1\/3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,21]]},"references-count":27,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["axioms12010003"],"URL":"https:\/\/doi.org\/10.3390\/axioms12010003","relation":{},"ISSN":["2075-1680"],"issn-type":[{"type":"electronic","value":"2075-1680"}],"subject":[],"published":{"date-parts":[[2022,12,21]]}}}