A selection of engineering papers using modern statistical and machine learning techniques

A selection of engineering papers using modern statistical and machine learning techniques
2021
1. Aguilar-Gomez, S., Arceo-Gomez, E.O., De la Cruz Toledo, E. and López, P.J.T., 2021.
LACEA WORKING PAPER SERES. No. 0054.
http://vox.lacea.org/files/Working_Papers/lacea_wps_0054_aguilar_arceo_cruz_torres.p
df
2. Casian, A. and Zannato, M., 2020. Predicting Teamfight Tactics Results with Machine
Learning Techniques. https://www.diva-
portal.org/smash/get/diva2:1463305/ATTACHMENT01.pdf
3. Cebrián Martínez, I., 2021. Estudio de la aplicación de algoritmos de enrutado al balanceo
de vehículos en sistemas de compartición de bicicletas (Doctoral dissertation, Universitat
Politècnica de València).
https://riunet.upv.es/bitstream/handle/10251/171476/Cebrian%20-
%20Estudio%20de%20la%20aplicacion%20de%20algoritmos%20de%20enrutado%20a
l%20balanceo%20de%20vehiculos%20en%20sistemas....pdf?sequence=1
4. Chen, H.C., 2021. Decompositions of Some Special Block Tridiagonal Matrices. Advances in
Linear Algebra & Matrix Theory, 11(2), pp.54-65.
https://www.scirp.org/pdf/alamt_2021060915233249.pdf
5. Cooler, Z., 2020. Personal Foul: How Head Trauma and the Insurance Industry Are
Threatening Sports.
https://digitalcommons.liberty.edu/cgi/viewcontent.cgi?article=2034&context=honors
https://core.ac.uk/download/pdf/322850874.pdf
6. Dziendzikowski, M., Heesch, M., Gorski, J., Dragan, K. and Dworakowski, Z., 2021.
Application of PZT Ceramic Sensors for Composite Structure Monitoring Using Harmonic
Excitation Signals and Bayesian Classification Approach. Materials, 14(19), p.5468.
https://www.mdpi.com/1996-1944/14/19/5468/htm
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8509222/
7. Grabovskaia, S., 2020. Pricing strategies of airline companies. Discovering the reasons
behind ticket price variation on Norwegian airline market (Master's thesis, UiT Norges arktiske
universitet).
https://munin.uit.no/bitstream/handle/10037/20636/thesis.pdf?sequence=2&isAllowed=y
8. Guo, J., Wang, H., Liu, W., Huang, G., Gui, J. and Zhang, S., 2021. A lightweight verifiable
trust based data collection approach for sensor–cloud systems. Journal of Systems Architecture,
119, p.102219.
https://www.sciencedirect.com/science/article/abs/pii/S1383762121001545
9. Kamberaj, V., 2021. Categorical Data Analysis Using Logistic Regression. Available at
SSRN 3921693. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3921693
10. Káčereková, Z., 2020. Rekonstrukce 3D povrchu z hloubkových dat se zohledněním
prázdného prostoru.
https://otik.uk.zcu.cz/bitstream/11025/41797/1/3D_surface_reconstruction_from_depth_
data_reflecting_empty_space.pdf
11. Lahiri, S., 2021. Subjective Probability, Risk Aversion, Expected Value and Utility Of Money.
https://www.academia.edu/download/67281512/Subjective_probability.pdf
12. Reinhard, D., Fauß, M. and Zoubir, A.M., 2021. Asymptotically Optimal Procedures for
Sequential Joint Detection and Estimation. arXiv preprint arXiv:2105.04828.
https://arxiv.org/pdf/2105.04828.pdf
13. Strandberg, A., 2021. Modeling telemedicine customer arrivals. https://www.diva-
portal.org/smash/get/diva2:1558755/FULLTEXT01.pdf
14. Vieth, M.E., 2021. The triple jeopardy of single mothers with a migration background: An
empirical study on intersectional discrimination and the risk of poverty in the Netherlands
(Doctoral dissertation).
https://frw.studenttheses.ub.rug.nl/3567/1/Master%20Thesis_Miriam%20Vieth_S448590
4.pdf
15. Yambe, K., Hoshimi, Y. and Kuramoto, N., 2021. The Effect of the Side Edge on the Plasma
Current during Interactions between a Cold Plasma and a Metal Object. Journal of the Physical
Society of Japan, 90(8), p.084501. https://journals.jps.jp/doi/abs/10.7566/JPSJ.90.084501

2020
16. Decolli, C., 2020. Economic and financial aspects of commodity markets during Covid
pandemic crisis: focus and forecasts on Crude Oil prices and Renewables evolution (Bachelor's
thesis, Università Ca'Foscari Venezia).
http://dspace.unive.it/bitstream/handle/10579/18136/877607-1243565.pdf?sequence=2
17. Getino, A.M. and Care, A.M.H., 2020. Bivariate confidence probability plots as a method to
test the accuracy and variability of microbiological measures. bioRxiv.
https://www.biorxiv.org/content/biorxiv/early/2020/11/18/2020.11.18.388603.full.pdf
18. Kharkovskii, D., Ling, C.K. and Low, B.K.H., 2020, June. Nonmyopic Gaussian process
optimization with macro-actions. In International Conference on Artificial Intelligence and
Statistics (pp. 4593-4604). PMLR.
http://proceedings.mlr.press/v108/kharkovskii20a/kharkovskii20a.pdf
https://www.comp.nus.edu.sg/~lowkh/pubs/aistats2020.pdf
https://arxiv.org/pdf/2002.09670.pdf
19. Kopić, K., 2020. Slučajni vektor (Doctoral dissertation, Josip Juraj Strossmayer University of
Osijek. Department of Mathematics. Chair of Pure Mathematics. Probability and Mathematical
Statistics Research Group).
https://zir.nsk.hr/islandora/object/mathos:435/datastream/PDF/view
https://repozitorij.unios.hr/islandora/object/mathos%3A435/datastream/PDF/view
20. Morgan, T.J. and Thompson, B., 2020. Biased transformation erases traditions sustained by
conformist transmission. Biology letters, 16(11), p.20200660.
https://royalsocietypublishing.org/doi/pdf/10.1098/rsbl.2020.0660
https://europepmc.org/article/med/33232652
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728688/
21. Nåbo, A. and Wahlgren, O., 2021. The Impact of Fiscal Policy on Inflation: A panel data
analysis on government spending and the price level. https://www.diva-
22. Nedić, M., 2020. Konvergencija nizova slučajnih varijabli (Doctoral dissertation, Josip Juraj
Strossmayer University of Osijek. Department of Mathematics. Chair of Pure Mathematics.
Probability and Mathematical Statistics Research Group).
https://repozitorij.mathos.hr/en/islandora/object/mathos%3A436/datastream/PDF/view
http://www.mathos.unios.hr/~mdjumic/uploads/diplomski/NED05.pdf
23. Oziel, M., Korenstein, R. and Rubinsky, B., 2020. A brain phantom study of a noncontact
single inductive coil device and the attendant algorithm for first stage diagnosis of internal
bleeding in the head. Journal of Medical Devices, 14(1).
https://asmedigitalcollection.asme.org/medicaldevices/article-
abstract/14/1/011102/1069499/A-Brain-Phantom-Study-of-a-Noncontact-Single
24. Káčereková, Z., 2020. Rekonstrukce 3D povrchu z hloubkových dat se zohledněním
prázdného prostoru.
https://otik.uk.zcu.cz/bitstream/11025/41797/1/3D_surface_reconstruction_from_depth_
data_reflecting_empty_space.pdf
25. Saratlija, J., 2020. Izgradnja sustava za neuralno strojno prevođenje (Doctoral dissertation,
University of Zagreb. University of Zagreb, Faculty of Humanities and Social Sciences.
Department of information and Communication sciences).
https://repozitorij.ffzg.unizg.hr/islandora/object/ffzg:2602/datastream/PDF/download
https://zir.nsk.hr/islandora/object/ffzg:2602/datastream/PDF/download
26. Reese, M., 2020. The Self versus Others: Spatial Localization and Timing of Trait Judgments
in the mPFC and PCC/Precuneus.
https://shareok.org/bitstream/handle/11244/326595/2020_Reese_Melody_Dissertation.p
df?sequence=3
27. Sarker, A., Sarker, M. and Amin, R., 2020. The Effects of ESG Score on Goodwill: A
Quantitative Study on Swedish Listed Companies. https://www.diva-
2019
28. Alfaisal, F.M., 2019. Development of Optimization Models for Regional Wastewater and
Storm Water Systems with Application in the Jizan Region, Saudi Arabia. Arizona State
University.

https://www.proquest.com/openview/7eee47a66fb6a9afa687e9f5634907cd/1?pq-
origsite=gscholar&cbl=18750&diss=y
29. Arribas Zapater, L.E., 2019. Clasificación automática de objetos astronómicos por fotometría
en series históricas recogidas por el Large Synoptic Survey Telescope (LSST).
http://openaccess.uoc.edu/webapps/o2/bitstream/10609/99207/4/larribas24TFG0719me
moria.pdf
30. Alnahwi, A. and Loucks, R.G., 2019. Mineralogical composition and total organic carbon
quantification using x-ray fluorescence data from the Upper Cretaceous Eagle Ford Group in
southern Texas. AAPG Bulletin, 103(12), pp.2891-2907.
https://pubs.geoscienceworld.org/aapgbull/article-
abstract/103/12/2891/575939/Mineralogical-composition-and-total-organic-
carbon?redirectedFrom=fulltext
31. Baer, M.A., 2019. Adolescent Perceptions on the Importance of Contributing to Society: A
Longitudinal Analysis Derived from the 4-H Study of Positive Youth Development (Doctoral
dissertation, Utica College).
https://www.proquest.com/openview/d0c62492af6699840ca24b0502fedd51/1?pq-
origsite=gscholar&cbl=18750&diss=y
32. Chirkis, K.R. and Cantone, A.S., 2019. Safety Considerations With Kalman Filters. Naval Air
Warfare Center Weapons Division China Lake United States.
https://apps.dtic.mil/sti/pdfs/AD1078469.pdf
33. Gates, G., 2019. Microarray Data Analysis and Classification of Cancers. Computer Science,
11, pp.20-2019.
https://ideaexchange.uakron.edu/cgi/viewcontent.cgi?article=2027&context=honors_res
earch_projects https://core.ac.uk/download/pdf/323028389.pdf
34. Ekelund, S. and Iskoujina, Z., 2019. Cybersecurity economics–balancing operational security
spending. Information Technology & People. https://doi.org/10.1108/ITP-05-2018-0252
35. Enoksson, J. and Lindqvist, V., 2019. Can changes in commodity prices help to predict
inflation?: A Bayesian Approach. https://www.diva-
36. Lukuyu, J.M., Blanchard, R.E. and Rowley, P.N., 2019. A risk-adjusted techno-economic
analysis for renewable-based milk cooling in remote dairy farming communities in East Africa.
Renewable energy, 130, pp.700-713.
37. Martinjak, P., 2019. Probabilistički (vjerojatnosni) model posjeta kategorijama prostornih
objekata u polazišno-odredišnoj matrici (Doctoral dissertation, University of Zagreb. Faculty of
Science. Department of Mathematics.).
https://zir.nsk.hr/islandora/object/pmf:6180/datastream/PDF/download
38. Merrick, L., 2019. Randomized Ablation Feature Importance. arXiv preprint
arXiv:1910.00174. https://arxiv.org/pdf/1910.00174.pdf
39. Ranzato, G., 2019. Distribuzioni mistura per l'analisi della sopravvivenza in disegni clinici
randomizzati a due stadi. http://tesi.cab.unipd.it/62529/1/RanzatoGiovanna.pdf
40. Rylander, A. and Persson, L., 2019. Modelling the Impact of Drug Resistance on Treatment
as Prevention as an HIV Control Strategy. https://www.diva-
2018
41. Alnahwi, A.W., 2018. Stratigraphic architecture and associated sedimentological and
geochemical variability in the Upper Cretaceous Eagle Ford Group, south Texas (Doctoral
dissertation). https://repositories.lib.utexas.edu/bitstream/handle/2152/83007/ALNAHWI-
DISSERTATION-2018.pdf?sequence=1
42. Chiputa, M. and Xiangyang, L., 2018. Real time Wi-Fi indoor positioning system based on
RSSI measurements: A distributed load approach with the fusion of three positioning algorithms.
Wireless Personal Communications, 99(1), pp.67-83.
http://pdf.xuebalib.com:1262/57vl2auLMRft.pdf
https://link.springer.com/article/10.1007/s11277-017-5037-y

43. Cumani, S. and Laface, P., 2018. Speaker recognition using e–vectors. IEEE/ACM
Transactions on Audio, Speech, and Language Processing, 26(4), pp.736-748.
https://dl.acm.org/doi/abs/10.1109/TASLP.2018.2791806
44. Hensen, E.J., Kouris, P.D., Brini, A. and Filot, I.A., 2018. Towards the optimization of the
lignin ethanolysis process using Design of Experiments and kinetic modeling.
https://pure.tue.nl/ws/portalfiles/portal/137273514/Afstudeerverslag_Eline_Schepers_09
50887_.pdf
45. Karong'oi, A.N., 2018. Comparing different approaches of epidemiological modeling.
https://lutpub.lut.fi/bitstream/handle/10024/157337/Njambi_MasterThesis.pdf?sequence
=1
46. Liang, X., Wang, G. and Han, Z., 2018, July. A low-cost collaborative indoor localization
system based on smartphone platform. In 2018 IEEE International Conference on Internet of
Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber,
Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) (pp. 404-411).
IEEE. https://ieeexplore.ieee.org/abstract/document/8726476
47. Olsson, J. and Asante, J., 2018. 5G Simulation Framework. https://www.diva-
48. Rupnik, T., 2018. Določitev velikosti vzorca: delo diplomskega seminarja (Doctoral
dissertation, Univerza v Ljubljani, Fakulteta za matematiko in fiziko). https://repozitorij.uni-
lj.si/Dokument.php?id=114023&lang=slv
49. Trotskii, I., 2018. Heating energy consumption forecasting based on machine learning.
https://www.theseus.fi/bitstream/handle/10024/150183/Trotskii_Igor.pdf?sequence=1
https://core.ac.uk/download/pdf/161431448.pdf
50. Zodenkamp, J., 2018. The Impact of Customer Empowerment on Observer-Based Brand
Equity.
https://dk.upce.cz/bitstream/handle/10195/75519/MinarikT_KalmanovaFiltrace_PB_202
0.pdf?sequence=1
2017
51. Alam, F., Mehmood, R., Katib, I., Albogami, N.N. and Albeshri, A., 2017. Data fusion and IoT
for smart ubiquitous environments: A survey. IEEE Access, 5, pp.9533-9554.
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7911293
52. Alavi, O. and Hooshmand Viki, A., 2017. A particle swarm optimization-based flowchart to
select wind speed distribution function. International Journal of Energy and Statistics, 5(01),
p.1750003. https://www.worldscientific.com/doi/abs/10.1142/S233568041750003X
https://www.researchgate.net/profile/Omid-
Alavi/publication/313870645_A_particle_swarm_optimization-
based_flowchart_to_select_wind_speed_distribution_function/links/5a0dd5de45851541b7079ac5
/A-particle-swarm-optimization-based-flowchart-to-select-wind-speed-distribution-function.pdf
53. Boileau, P., Kakinami, L. and Popovic, L., 2017. Exploration of Multi-Network Data with
Heatmaps. http://www.ism.uqam.ca/~ism/pdf/Boileau-scientific%20report.pdf
54. Duru, C. and Ani, C., 2017. A statistical analysis on the leak detection performance of
underground and overground pipelines with wireless sensor networks through the maximum
likelihood ratio test. Sādhanā, 42(11), pp.1889-1899.
https://link.springer.com/article/10.1007/s12046-017-0731-8
https://www.ias.ac.in/article/fulltext/sadh/042/11/1889-1899
55. Jaya, A.I., 2017. Pemodelan Regresi Spasial Autologistik dalam Menentukan Faktor-faktor
Kemiskinan di Provinsi Sulawesi Selatan (Doctoral dissertation, FMIPA).
http://eprints.unm.ac.id/6029/1/3.%20BAB%20I-V.pdf
56. Karch, J., Brandmaier, A.M. and Voelkle, M., 2017. Gaussian process panel modeling–
Kernel-based longitudinal modeling. https://psyarxiv.com/kvw5y/download?format=pdf
https://psyarxiv.com/kvw5y/ https://osf.io/kvw5y/download
57. Lisova, E., Uhlemann, E., Åkerberg, J. and Björkman, M., 2017, March. Delay attack versus
clock synchronization—A time chase. In 2017 IEEE International Conference on Industrial
Technology (ICIT) (pp. 1136-1141). IEEE. http://www.es.mdh.se/pdf_publications/4699.pdf
https://www.diva-portal.org/smash/get/diva2:1107228/FULLTEXT01.pdf

58. Poláková, M., 2017. Číselné charakteristiky spojitých náhodných veličin (Doctoral
dissertation, Masarykova univerzita, Přírodovědecká fakulta).
https://is.muni.cz/th/vx58z/Sablona.pdf
59. Tao, L., Wu, D., Liu, S. and Lambert, J.H., 2017. Schedule risk analysis for new-product
development: The GERT method extended by a characteristic function. Reliability Engineering &
System Safety, 167, pp.464-473.
2016
60. Arroyo, S.I., Safar, F. and Oliva, D., 2016, June. Probabilidad de infracción de velocidad de
vehículos utilizando visión artificial en cámaras de campo amplio. In 2016 IEEE Biennial
Congress of Argentina (ARGENCON) (pp. 1-6). IEEE.
https://ieeexplore.ieee.org/abstract/document/7585314 http://b-dig.iie.org.mx/BibDig2/P16-
0417/papers/IEEE_ARGENCON_2016_paper_187.pdf
61. Morais, I., Stona, F. and Schuck, G., 2016. Econometria Aplicada no EViews®. Porto Alegre:
Fundação de Economia e Estatística.
https://www.fstona.com/files/Econometria%20Aplicada%20no%20EViews.pdf
https://arquivofee.rs.gov.br/wp-content/uploads/2016/10/20161031livro-econometria-aplicada-no-
eviews-isbn-978-85-7173-141-7.pdf
62. Qin, W.B., Gomez, M.M. and Orosz, G., 2016. Stability and frequency response under
stochastic communication delays with applications to connected cruise control design. IEEE
Transactions on Intelligent Transportation Systems, 18(2), pp.388-403. http://www-
personal.umich.edu/~orosz/articles/ITS_2017_Wubing_Marcella.pdf
https://ieeexplore.ieee.org/document/7514759/references#references
63. Richter, W.D., 2016. Exact inference on scaling parameters in norm and antinorm contoured
sample distributions. Journal of Statistical Distributions and Applications, 3(1), pp.1-16.
https://link.springer.com/article/10.1186/s40488-016-0046-z http://www.math.uni-
rostock.de/~richter/W-DR2016-5.pdf https://cyberleninka.org/article/n/1376273.pdf
https://d-nb.info/109538399X/34
64. Rivera, F.P. and Braga Jr, R.A., 2017. Selection of statistical indices in the biospeckle laser
analysis regarding filtering actions. Optics Communications, 394, pp.144-151.
2015
65. Anyika, E., 2015. Non-Diversifiable Risk in Investment Portfolios---an Aid to Investment
Decision Making. Journal of Risk Analysis and Crisis Response, 5(1). https://www.atlantis-
press.com/article/18932.pdf https://www.jracr.com/index.php/jracr/article/view/133/105
66. Bjarnle, J. and Holmström, E., 2015. Implementation and Evaluation of Historical Consistent
Neural Networks Using Parallel Computing. https://www.diva-
67. Damian, C., Crisan, A., Vasile, T., Coltuc, D. and Damian, V., 2015, July. Noise evaluation in
Hadamard spectroscopy. In 2015 International Symposium on Signals, Circuits and Systems
(ISSCS) (pp. 1-4). IEEE.
https://ieeexplore.ieee.org/abstract/document/7204006/references#references
68. Kamps, T.C., 2015. Improvement of rescheduling policies in a dynamic multi-echelon
MTO/ATO environment at VDL ETG. https://pure.tue.nl/ws/files/47018369/791927-1.pdf
69. Nemţanu, F.C., Bureţea, D.L. and Obreja, L.G., 2015. Comparative assessment of virtual
track circuit based on image processing. Urban Rail Transit, 1(2), pp.131-137.
https://link.springer.com/article/10.1007/s40864-015-0013-x
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70. Pavlovic, D., 2015. Splice isoform identification from transcript graphs.
https://www.bib.irb.hr/773756/download/773756.Dario_Pavlovic_diplomski.pdf
71. Schmit, S., 2015. CME 106: Review Probability theory.
https://web.stanford.edu/~schmit/misc/cme106_review.pdf
72. Strebeika, D., 2015. Pensijų fondų rizikos matų analizė įvairiems skirstiniams (Doctoral
dissertation, Kauno technologijos universitetas).
https://epubl.ktu.edu/object/elaba:8669558/8669558.pdf

2014
73. Jayapal, A. and Emms, M., 2014. Topic Models-Latent Dirichlet Allocation.
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74. Starrett, R. and Su, A., 2014. Exploring the Moisture Susceptibility of Multi-scale Modified
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76. Veloso, J.F.A., 2014. An empirical study on deprivation (Doctoral dissertation, Instituto
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77. Yuan, X., Kong, H.C., He, Y.J., Ma, Z.F., Yang, Y. and Li, Q., 2014. Effects of composition
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78. Atasoy, A.İ., 2013. Küçük Alanlı Tedavi Planlarının Dozimetrik Ölçümlerinin Karşılaştırılması
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83. Zhang, Y., 2013. Complex Analysis and Brownian Motion.
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2012
84. Kaisla, E., 2012. Riemann-Stieltjesin integraali.
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85. Portilla, J. and Barbero, S., 2012, December. Accuracy of geometric point spread function
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86. Gutterman, C., Agas, B. and Fridman, R., 2011. Assignment 3: TCP Tahoe with More
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“HUGE” LOSS AVERSION. http://mathematical-forum.org/wp-content/uploads/2021/07/3.-
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Other
88. Adina-Zada, M., Autonomous Vehicle Reliability and Localization.
https://robotics.ee.uwa.edu.au/theses/2018-REV-Localization-Adina-Zada.pdf
89. Breznická, A., Spojitá rozdělení v aktuárské matematice.
https://is.muni.cz/th/py93e/Bakalarska_praca_Breznicka.pdf
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%20r%C3%A9ttir%20vaxtaferlar%20og%20%C3%A1lagsferlar%20%C3%A1%20skulda
br%C3%A9fum%20%C3%8Dslandsbanka.pdf

A selection of engineering papers using modern statistical and machine learning techniques

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A selection of engineering papers using modern statistical and machine learning techniques