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In: Forests, MDPI AG, Vol. 14, No. 2 ( 2023-01-21), p. 205-

Abstract: In this article, an approach to drill wear evaluation is presented. Tool condition monitoring is an important problem in furniture manufacturing and similar industries. At the same time, approaches that rely on sets of sensors, often tend to be to robust or complex for the production environment. Instead of signals acquired from dedicated sensors, presented approach uses images of drilled holes as input data. Initial pictures are processed and enhanced in order to highlight the crucial properties. A set of selected features is then calculated on the resulting images, and later used during the training of 5 state-of-the-art classifiers. Presented research also evaluates number of images for consecutive drillings that needs to be taken into account in order to produce accurate results. From the selected set, the best performing classifier was Random Forest and it achieved close to 100% accuracy.

Type of Medium: Online Resource

ISSN: 1999-4907

URL: Article

DOI: 10.3390/f14020205

Language: English

Publisher: MDPI AG

Publication Date: 2023

detail.hit.zdb_id: 2527081-3

In: eLife, eLife Sciences Publications, Ltd, Vol. 12 ( 2023-04-21)

Abstract: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 ( https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

Type of Medium: Online Resource

ISSN: 2050-084X

URL: Article

DOI: 10.7554/eLife.81916

Language: English

Publisher: eLife Sciences Publications, Ltd

Publication Date: 2023

detail.hit.zdb_id: 2687154-3

In: SSRN Electronic Journal, Elsevier BV

Type of Medium: Online Resource

ISSN: 1556-5068

URL: Article

DOI: 10.2139/ssrn.4039054

Language: English

Publisher: Elsevier BV

Publication Date: 2022

In: Informatics, Control, Measurement in Economy and Environment Protection, Politechnika Lubelska, Vol. 5, No. 4 ( 2015-10-28), p. 45-47

Type of Medium: Online Resource

ISSN: 2083-0157 , 2391-6761

URL: Article

DOI: 10.5604/20830157.1176574

Language: Unknown

Publisher: Politechnika Lubelska

Publication Date: 2015

detail.hit.zdb_id: 2784967-3

In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 19, No. 16 ( 2022-08-09), p. 9802-

Abstract: Introduction: Nursing staff working in a shift or night system are exposed to sleep disorders, which has a direct impact on the emergence of dangerous health consequences for them. Melatonin secretion is abnormal at night and the circadian rhythm is disturbed. The aim of the study was to assess the occurrence of sleep disorders and their consequences for the body in a group of representative nursing staff working in a shift and night system. Participants: The study was conducted among 126 nurses who are generally healthy, employed in health care facilities in the Małopolskie voivodship. Methods: The Athens Insomnia Scale consisting of 8 test items was used to obtain research material: falling asleep, waking up at night, waking up in the morning, total sleep time, sleep quality, well-being the next day, mental and physical fitness the next day, and sleepiness during the next day. As well as an original questionnaire. Results: The research showed significant negative consequences of shift work on the health of health-care workers. The subjects noticed symptoms related to the nervous system, such as increased nervous tension 53%, lack of patience in 62% of all respondents. As many as 85% pointed to the negative impact of shift work on their family life, 82% of all respondents on social life and 56% of all respondents on sex life. The other variables were not confirmed. Conclusions: Symptoms of insomnia are common among night-work nurses.

Type of Medium: Online Resource

ISSN: 1660-4601

URL: Article

DOI: 10.3390/ijerph19169802

Language: English

Publisher: MDPI AG

Publication Date: 2022

detail.hit.zdb_id: 2175195-X

In: Sustainability, MDPI AG, Vol. 14, No. 15 ( 2022-08-03), p. 9531-

Abstract: The COVID-19 pandemic that began in 2020 has significantly impacted businesses, regardless of size or industry. The hybrid and remote working models have moved all meetings with potential and existing suppliers to an online environment. This also applies to small- and medium-sized enterprises (SMEs), which have had to adapt themselves to the new situation and implement the solutions necessary to survive on the market. On the other hand, clients have become more aware of the environment and its changes. Customers are trying to be more eco-friendly, by choosing and moving towards Green IT. Thus, this needs to be considered. The acquisition of management information systems (MIS) in the pandemic era is based only on virtual meetings. The main goals of this paper were the identification of the changes in the negotiations caused by the COVID-19 pandemic, the transformation of this process into virtual environment, discussion of the possibility of using Green IT in addition to Management Information Systems, and the changes caused by the pandemic. The article was prepared based on the results of qualitative research using the case study method. The comparative analysis includes purposely selected cloud-based Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems’ acquisition processes, presented from the clients’ perspective. The research was conducted in 2021, based on the authors’ practical experience, and presents four cases. This research illustrates the negotiations concerning an acquisition transaction pre-pandemic and during the pandemic. Finally, the conclusions and main differences caused by the pandemic in the acquisition transaction process of management information systems (MIS) are presented.

Type of Medium: Online Resource

ISSN: 2071-1050

URL: Article

DOI: 10.3390/su14159531

Language: English

Publisher: MDPI AG

Publication Date: 2022

detail.hit.zdb_id: 2518383-7

In: Brain Sciences, MDPI AG, Vol. 11, No. 5 ( 2021-05-07), p. 599-

Abstract: The goal of this paper is to investigate the baseline brain activity in euthymic bipolar disorder (BD) patients by comparing it to healthy controls (HC) with the use of a variety of resting state functional magnetic resonance imaging (rs-fMRI) analyses, such as amplitude of low frequency fluctuations (ALFF), fractional ALFF (f/ALFF), ALFF-based functional connectivity (FC), and r egional homogeneity (ReHo). We hypothesize that above-mentioned techniques will differentiate BD from HC indicating dissimilarities between the groups within different brain structures. Forty-two participants divided into two groups of euthymic BD patients (n = 21) and HC (n = 21) underwent rs-fMRI evaluation. Typical band ALFF, slow-4, slow-5, f/ALFF, as well as ReHo indexes were analyzed. Regions with altered ALFF were chosen as ROI for seed-to-voxel analysis of FC. As opposed to HC, BD patients revealed: increased ALFF in left insula; increased slow-5 in left middle temporal pole; increased f/ALFF in left superior frontal gyrus, left superior temporal gyrus, left middle occipital gyrus, right putamen, and bilateral thalamus. There were no significant differences between BD and HC groups in slow-4 band. Compared to HC, the BD group presented higher ReHo values in the left superior medial frontal gyrus and lower ReHo values in the right supplementary motor area. FC analysis revealed significant hyper-connectivity within the BD group between left insula and bilateral middle frontal gyrus, right superior parietal gyrus, right supramarginal gyrus, left inferior parietal gyrus, left cerebellum, and left supplementary motor area. To our best knowledge, this is the first rs-fMRI study combining ReHo, ALFF, f/ALFF, and subdivided frequency bands (slow-4 and slow-5) in euthymic BD patients. ALFF, f/ALFF, slow-5, as well as REHO analysis revealed significant differences between two studied groups. Although results obtained with the above methods enable to identify group-specific brain structures, no overlap between the brain regions was detected. This indicates that combination of foregoing rs-fMRI methods may complement each other, revealing the bigger picture of the complex resting state abnormalities in BD.

Type of Medium: Online Resource

ISSN: 2076-3425

URL: Article

DOI: 10.3390/brainsci11050599

Language: English

Publisher: MDPI AG

Publication Date: 2021

detail.hit.zdb_id: 2651993-8

In: Frontiers in Human Neuroscience, Frontiers Media SA, Vol. 14 ( 2020-11-13)

Type of Medium: Online Resource

ISSN: 1662-5161

URL: Article

DOI: 10.3389/fnhum.2020.585766

Language: Unknown

Publisher: Frontiers Media SA

Publication Date: 2020

detail.hit.zdb_id: 2425477-0

In: ITM Web of Conferences, EDP Sciences, Vol. 29 ( 2019), p. 01008-

Abstract: The paper deals with numerical modeling of objects with a natural origin. The stochastic approach based on description using random variables allows processing such challenges. The Monte-Carlo methods are known a tool for simulations containing stochastic parameters however, they require significant computational power to obtain stable results. Authors compare Monte- Carlo with more advanced Polynomial Chaos Expansion (PCE) method. Both statistical tools have been applied for simulation of the electric field used in ohmic heating of potato tuber probes. Results indicate that PCE is remarkably faster, however, it simplifies some probabilistic features of the solution.

Type of Medium: Online Resource

ISSN: 2271-2097

URL: Article

DOI: 10.1051/itmconf/20192901008

Language: English

Publisher: EDP Sciences

Publication Date: 2019

detail.hit.zdb_id: 2755683-9

In: LOGI – Scientific Journal on Transport and Logistics, Walter de Gruyter GmbH, Vol. 9, No. 2 ( 2018-11-01), p. 61-72

Abstract: The theoretical part of this article presents knowledge of selected methods used to study the quality level of basic processes. Authors paid particular attention to the Servqual method, which shows the differences that exist between the perceived and delivered quality of services provided by enterprises and the TUL method. The research part will show the Servqual and TUL analysis based on the processes of the existing transport company. The article is based on well-known methodology of Servqual and TUL analysis, which was adjusted to observation of transport processes of logistics service provider. The main scientific goal of the paper was to examine the effectiveness of the methodology used on the example of a transport company and comparison of methods utility. The improvement of the transport process will increase the level of customer satisfaction, and this is the first step to increase the number of transport orders received.

Type of Medium: Online Resource

ISSN: 2336-3037

URL: Article

DOI: 10.2478/logi-2018-0019

Language: English

Publisher: Walter de Gruyter GmbH

Publication Date: 2018

detail.hit.zdb_id: 2926396-7