Wyniki wyszukiwania - BazTech

1

Study of AQI Monitoring System of Indoor Environment Using Machine Learning Model and IoT Device

Talati Isha, Shah Kunjan, Patel Om, Tanna Jaymin, Jain Akshat, Oza Ankit D., Yadav Amruta Arun, Alshayeb Mohammed J., Khan Mohammad Amir, Islam Saiful

Rocznik Ochrona Środowiska

|

2025

|

Tom 27

152--163

EN

Indoor air quality has a direct impact on human health. Thus, it's essential to comprehend the various aspects of indoor air quality. It supports both the implementation of preventative measures and the monitoring of indoor air pollution. Monitoring and forecasting air pollution is extremely essential, especially in developing countries like India. This study proposes a system that employs ESP8266 (NodeMCU) data sent to the cloud to monitor the levels of air pollutants such as ozone, particle matter, carbon monoxide, carbon dioxide, temperature, and total volatile organic compounds. Our sensors include the ozone sensor MQ-131, the dust sensor GP2Y1010-AU0F, the TVOC sensor AGS02MA, the carbon monoxide sensor MQ-9, the carbon dioxide sensor MQ-135, and the humidity sensor DHT11. The IoT device continuously shows the indoor air quality level (IAQL). The next step was to accurately anticipate the Internal Air Quality Level (IAQL) and pollution levels from dangerous gases for the next seven days using the LSTM, Seasonal ARIMA, and Linear Regression models. The Authors could accurately predict the observations of the following seven days after using data from the previous ninety days to create our best model. This implies that our model can accurately predict the values for each parameter with an accuracy of at least 95%. Therefore, we believe such a solution would be advantageous if a large-scale installation were implemented. If consumers can remotely verify the air quality in their homes, the pollution in the interior atmosphere will decrease. This has the potential to make civilization healthier.

2

Mechanical performance prediction of asphalt mixtures: a baseline study of linear and non-linear regression compared with neural network modeling

Baldo Nicola, Rondinella Fabio, Daneluz Fabiola, Vacková Pavla, Valentin Jan, Gajewski Marcin, Król Jan

Roads and Bridges - Drogi i Mosty

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2025

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Vol. 24, no. 1

27--35

EN

Accurate predictions of asphalt mixtures’ mechanical performance are crucial to improve the conventional mix-design procedures and to optimize both pavements’ performance and service life. This research explores this issue by means of a comparative analysis between different modeling approaches: conventional regressions, both linear and non-linear, and artificial neural networks. The former are widely used but may lack the flexibility to capture complex relationships between testing conditions and the corresponding mechanical behavior. The latter represent promising alternatives due to their capability to successfully model non-linear interactions between variables. This research compares the predictive accuracy of these different modeling approaches using experimental data resulting from 4-point bending tests carried out under several temperatures and loading frequencies. The outcomes suggest that neural networks outperform conventional regression models in capturing complex relationships, highlighting the strengths and limitations of each modeling approach and providing insights for selecting optimal models in road pavement engineering applications.

PL

Dokładne przewidywanie właściwości mechanicznych mieszanek mineralno-asfaltowych jest kluczowe w doskonaleniu konwencjonalnych procedur projektowania mieszanek oraz optymalizacji ich właściwości i trwałości nawierzchni. Niniejsze badania dotyczą pogłębionej analizy tego zagadnienia z wykorzystaniem analizy porównawczej dwóch różnych podejść do modelowania: konwencjonalnymi metodami regresji liniowej i nieliniowej oraz metodą sztucznych sieci neuronowych. Pierwsze podejście z konwencjonalnymi metodami regresyjnymi jest szeroko stosowane, ale może mieć pewne ograniczenia co do zastosowania, szczególnie tam, gdzie należy uwzględnić złożone zależności między warunkami badania, a odpowiadającymi im wyjściowymi właściwościami mechanicznymi. Drugie podejście stanowi obiecującą alternatywę, ze względu na przydatność sztucznych sieci neuronowych w modelowaniu nieliniowych interakcji między zmiennymi. Niniejsze badania porównują dokładność przewidywania różnymi metodami predykcyjnymi właściwości mechanicznych mieszanek mineralno-asfaltowych, wykorzystując dane eksperymentalne uzyskane w badaniu cztero-punktowego zginania przeprowadzonych w różnych temperaturach i częstotliwościach obciążenia. Wyniki analiz wskazują na przewagę sieci neuronowych nad konwencjonalnymi metodami modeli regresyjnych ze względu na złożoność analizowanych zależności. Dodatkowymi efektami przeprowadzonych badań jest wskazanie mocnych i słabych strony każdego podejścia do modelowania oraz praktyczne rekomendacje dotyczące wyboru optymalnych modeli do zastosowania w praktyce inżynierskiej budownictwa drogowego.

3

Zastosowanie wybranych metod korelacji do analizy zjawisk zachodzących w systemach bezpieczeństwa informacyjnego

Torbus Sławomir Andrzej, Kolano Dawid, Kuczkowski Adam, Weryho Mateusz

Przegląd Elektrotechniczny

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2025

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R. 101, nr 1

69--72

PL

W części teoretycznej pracy omówiono wybrane metody korelacyjne (współczynnik korelacji liniowej Pearsona, diagram rozrzutu, nożyce korelacji, regresja liniowa), które należy stosować podczas analizy zjawisk zachodzących w systemach bezpieczeństwa informacyjnego. W części praktycznej pracy zaprezentowano przykładową analizę korelacyjną (metodami analitycznymi i graficznymi) rzeczywistych danych (nakładów finansowych na poziom cyberbezpieczeństwa w RP oraz liczby oszustw komputerowych zgłaszanych do CERT Polska przez obywateli RP). Na podstawie uzyskanych wyników sformułowano wnioski dotyczące zależności pomiędzy rozpatrywanymi danymi za lata 2018 – 2023.

EN

The theoretical part of the work discusses the selected correlation methods (Pearson's linear correlation coefficient, scatter diagram, correlation scissors, linear regression), which should be used for analyze phenomena occurring in systems of information security. The practical part of the work presents an example of a correlation analysis (using analytical and graphical methods) of the real data (financial outlays on the level of cybersecurity in the Republic of Poland and the number of computer frauds reported to CERT Polska by citizens of the Republic of Poland). On the basis of the obtained results, conclusions were formulated regarding the relationship between the data considered for the years 2018 – 2023.

4

Empirical modeling of the impact of Industry 4.0 technologies on logistics service quality

Bilad Assia, Zaim Mounia, Zaim Faical

LogForum

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2025

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Vol. 21, no 3

443--457

EN

Background: Industry 4.0 technologies are transforming supply chains, enabling higher-quality services in the era of digitalization. However, the specific contributions of these tools to different dimensions of service quality, particularly in logistics, are not yet fully understood. This study investigates the impact of Industry 4.0 technologies on logistics service quality, focusing on four key dimensions: reliability, responsiveness, flexibility, and communication. Methods: A mixed-method approach combining a literature review, a survey of logistics professionals, conceptual framework development, and statistical modeling was employed. Eight digital tools were analyzed: The Internet of Things (IoT), big data, blockchain, artificial intelligence (AI), cloud computing, digital twins, cyber-physical systems, and ERP. Data were collected via a structured questionnaire and analyzed using multiple linear regression. Results: The analysis shows that each technology influences service quality differently: IoT and big data enhance reliability and responsiveness; cloud computing and ERP support flexibility; blockchain and AI improve communication within the supply chain. Some tools have a pronounced effect on specific dimensions, demonstrating the nuanced role of digital technologies in service enhancement. Conclusions: This study contributes to a clearer understanding of how Industry 4.0 tools functionally enhance logistics service performance. The findings offer practical guidance for decision-makers on prioritizing digital initiatives. Future research could apply this framework across industries, regions, or over time to capture evolving impacts. These insights support strategic decisions to optimize service quality and technological adoption in supply networks.

5

Assessing Two-Decade Coastal Sea-Level Rise Trends in the Mekong Delta, Vietnam Using Multi-Mission Satellite Altimetry

Pham Van Thuyen

Inżynieria Mineralna

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2025

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Vol. 1, no. 2

469--481

EN

Sea level rise due to thermal expansion of the ocean and melting Arctic ice poses a serious threat to low-lying coastal areas such as the Mekong Delta (MD), Vietnam. This study will assess sea-level rise trends in the coastal region of the Mekong Delta over two decades (2005–2024) based on various types of satellite altimetry data. The authors utilized 147,352 sea surface height (SSH) points from five types of altimetry satellites (Envisat, Saral/AltiKa, CryoSat-2, Sentinel-3A, Sentinel-3B) and applied the cross-over adjustment method to eliminate the time-varying dynamic sea surface height component (ht). This allowed for the construction of mean sea surface (MSS) models for four consecutive five-year periods (2005–2009, 2010–2014, 2015–2019, 2020–2024). Eight representative locations across the study area were selected, and a simple linear regression method was used to determine the local sea-level rise rate for the study region. The results indicate that the average sea-level rise rate for the study area is 3.92 mm/year. This finding is consistent with sea-level observations from tide gauge stations in the region (3.73 mm/year), thereby affirming the feasibility and effectiveness of applying altimetry data in assessing sea-level rise trends. The research findings will provide a solid scientific basis for climate change adaptation planning in the Mekong Delta

6

Impact of rainfall variability on cereal yield in the Fez-Meknes region (Morocco)

Belmahi Mohamed, Hanchane Mohamed, Benbaqqal Hicham, Kabach Mohammed, Zouhri Driss, Kessabi Ridouane, Elkhazzan Bouchta, Zriouli Khalid

Ecological Engineering & Environmental Technology

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2025

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Vol. 26, iss. 2

109--121

EN

The Fez-Meknes region is distinguished by its agricultural vocation and its emergence as a hub in the agro-food industry. This study aims to assess the main crop yield, production, and percentage of the agricultural area within each province of the Fez-Meknes region from 2000 to 2020, based on an analysis of descriptive statistics and cartography data. The objective is to determine the national ranking of autumn cereals within the region. Then, multiple linear regression between precipitation and cereal yield in the region’s provinces was established, and the trend in sown areas and cereal yield was analysed using the Man Kendall test. The results revealed that the area sown to autumn cereals accounted for 15% of the national cereal area. Despite that, regional cereal production is ranked second nationally after the Casablanca-Settat region, with a small difference that does not exceed 1.5%. Regarding regional provinces, Taounate and Taza account for almost half of the region’s cereal production. The correlation coefficient between monthly precipitation and cereal yield ranged from 0.51 in Boulmane province to 0.84 in Fez and Moulay Yaacoub province. The coefficient of determination ranged from 0.21 in Boulmane province to 0.70 in Fez province. On the other hand, precipitation in November, December, January, and March had the greatest impact on cereal yields. The differences between observed and estimated yields using multiple regression are acceptable in all region’s provinces, especially when only one predictor was retained. Finally, the Man-Kendall test indicates that the area sown to autumn cereals has a slight downward trend of 4965 ha/year, with a significance of α = 0.07. However, cereal yield also tends to increase by 0.34 q/year with a p- value α = 0.12.

7

Determining the optimal number of stretch film layers for ensuring palletized cargo stability: a simulation study

Matyja Tomasz

Zeszyty Naukowe. Transport / Politechnika Śląska

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2024

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z. 124

93--108

EN

Numerical simulation tests were carried out to determine the influence of the characteristic features of a load unit (such as: weight, height, number of load layers, coefficient of friction between the layers) per number of wraps with stretch film necessary to ensure unit stability. Manufacturers of stretch film sometimes provide guidelines on how many layers of film should be used depending on the weight and height of the load. But they do not explain on the basis of which studies these values were determined. Performing simulations similar to those made in this work in laboratory conditions would be very expensive. The work attempts to determine such relationships by simulation methods. A developed by the author in his earlier works dynamic model of a layered cargo unit wrapped with stretch film was used. The study plan was to check 108 cases. On the basis of the collected data, an attempt was made to develop a mathematical formula that would allow to estimate the optimal number of foil wraps when certain parameters of the load unit are known. In the author's opinion such an estimate could reduce film consumption, which would have a positive impact on the environment.

8

Predictive Analysis of Ceramic Waste Modified Concrete Properties Using ANN and Linear Regression Algorithm

Asiri Abdullah

Rocznik Ochrona Środowiska

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2024

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Tom 26

273--283

EN

In this study, concrete modified with ceramic waste was modelled. The ceramic waste percentage ranged from 2.5% to 5% to 10% to 12.5% to 15% to 17.5% to 20%. Modelling was done for the concrete's tensile strength and compressive strength. Regression modelling and artificial neural networks were used as prediction methods for concrete strength. The models developed in this study to predict the mechanical properties of concrete were evaluated using Mean absolute error, coefficient of determination and root mean square error. The R2 value for the ANN model was determined to be 0.97, compared to 0.95 for the linear regression model. For the one-week, two-week, and four-week prediction models, RMSE values were 1.1 MPa, 1.15 MPa, and 1.05 MPa for the ANN model for one-week, two-week and four-week, respectively, while the linear regression model displayed the RMSE values of 1.08 MPa, 1.22 MPa, and 1.25 MPa. The R2 values for ANN and LR models were estimated to be 0.87 and 0.7, respectively, for predicting split tensile strength. This study will conclude that the artificial neural network model has high accuracy. It can be employed in modelling the mechanical properties of ceramic-modified concrete.

9

Badanie właściwości mechanicznych papieru z zastosowaniem metod obrazowych

Pełczyński Paweł, Jabłecka Agnieszka

Przegląd Papierniczy

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2024

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R. 80, nr 12

673--677

PL

Ważnym aspektem, mającym istotny wpływ na właściwości użytkowe papieru, jest jego przezrocze, które wpływa na właściwości optyczne i mechaniczne papieru. Celem prezentowanych prac była ocena możliwości zastosowania obrazowych metod do analizy obrazu przezrocza i przewidywania właściwości mechanicznych papieru. Zakres pracy obejmował badania właściwości mechanicznych papierów opakowaniowych w próbach jednokierunkowego rozciągania z wykorzystaniem informacji obrazowej, jaką niesie przezrocze papieru. Przeprowadzono badania wybranych papierów opakowaniowych i wyciągnięto wnioski o użyteczności zastosowanej techniki w badaniu właściwości mechanicznych papieru.

EN

An important aspect significantly affecting the functional properties of paper is its formation, which influences both its optical and mechanical properties. The aim of the presented study was to evaluate the potential of image-based methods for analyzing paper formation and predicting its mechanical properties. The scope of the work included testing the mechanical properties of packaging papers in uniaxial tensile tests, utilizing the image information provided by paper formation. Selected packaging papers were examined, and conclusions were drawn about the applicability of the technique for assessing the mechanical properties of paper.

10

Comparison of lndependent aomponent analysis, linear regression and adaptive filtering for artifact removal in SSVEP registration

Jurczak Marcin, Kołodziej Marcin, Majkowski Andrzej

Przegląd Elektrotechniczny

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2024

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R. 100, nr 5

282--285

EN

Artifacts pose a significant challenge in the analysis of EEG signals. In this study, the authors investigated the impact of artifacts on the detection of steady-state visually evoked potentials (SSVEPs). The article explored various techniques for physiological artifact elimination, including linear regression, adaptive filters, and independent component analysis (ICA). The effectiveness of the algorithms was evaluated using classification accuracy as a metric. The results indicate that the most promising outcomes were achieved with independent component analysis.

PL

Artefakty odgrywają znaczącą rolę w analizie sygnałów EEG. Autorzy zbadali wpływ artefaktów na detekcję potencjałów wywołanych SSVEP. Artykuł przedstawia różne techniki eliminacji artefaktów fizjologicznych – regresję liniową, filtrację adaptacyjną oraz analizę składowych niezależnych (ICA). Efektywność algorytmów została oceniona z wykorzystaniem metryki jaką była skuteczność klasyfikacji. Wyniki wskazują, że najbardziej obiecujące wyniki osiągnięto dzięki analizie składowych niezależnych (ICA).

11

Quality Control of Body Measurement Data Using Linear Regression Methods

Bicevskis Janis, Bicevska Zane, Diebelis Edgars, Purina Liva

Annals of Computer Science and Information Systems

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2024

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Vol. 39

289–-300

EN

Determining the accuracy of measurements for different types of objects is a complex task because (1) allowable deviations depend on the intended use of the measurements, and (2) different applications use different methods to identify incorrect measurements. In the construction of clothing patterns, up to 50 different human body measurements are used, and each person is unique. Therefore, it is difficult to draw conclusions from a specific set of measurements as to whether the included measurements are correct or not. In this study, the quality of body measurement data is being verified using linear regression methods. Linear regression models are trained with 80\% of the entire dataset, while the remaining 20\% is used for testing. The obtained results have been validated on a real dataset, and they allow for predicting missing or inaccurate body measurements with sufficiently high accuracy.

12

New index for evaluating pedaling techniques using the pedaling efficiency index with gradually increasing load

Kitawaki Tomoki, Fukuda Masahiro

Acta of Bioengineering and Biomechanics

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2024

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Vol. 26, no. 4

145--153

EN

Measuring the pedal force vector during bicycle pedaling has recently become easy, and research have been conducted using mechanical efficiency (the ratio of an effective driving force to total pedaling force); however, the relationships between these forces were not considered. This study aimed to show that the relationship between these forces can be linearly regressed under gradually increasing load conditions and propose that the slope parameter can serve as a new index for evaluating pedaling skills. Methods: Twenty-eight participants performed the experiment in which the load was increased every minute until the maximum load was exerted. Using sensors installed on both bicycle cranks, the pedaling force vector was divided into tangential and radial components to determine the total pedaling and effective driving forces per minute. The maximum load force and efficiency index were calculated. Results: Our results showed a strong linear relationship (coefficient of determination: 0.982, 95% CI 0.909–0.996) between the total pedaling and effective driving force. The slope parameters from this regression exhibited significant correlations (–0.560 and –0.674) with the maximum load force and efficiency index during maximum exertion, respectively. These correlations highlight the slope parameter potential for capturing pedaling characteristics. Conclusions: The slope parameter derived from the linear regression between the total pedaling force and effective driving force reflects individual pedaling characteristics. This parameter stands out as a promising new index for evaluating pedaling motion, offering insights into participant-specific pedaling behaviors. Consequently, this novel index could be instrumental in assessing and analyzing pedaling skills.

13

Misje stratosferyczne Akademii Tarnowskiej Część 2: analiza danych

Antosz Jakub, Wielgat Robert, Plata Sylwia, Jasielski Piotr, Pękala Damian, Arabik Regina, Witek Maciej

Science, Technology and Innovation

|

2023

|

Vol. 18, no. 3-4

46--64

PL

W okresie od 29 lipca do 29 września 2023 roku wysłano z kampusu Akademii Tarnowskiej trzy misje stratosferyczne poprzez wyniesienie ładunku za pomocą balonów wypełnionych helem. W trakcie misji zarejestrowano szereg pomiarów dotyczących temperatury, ciśnienia i wilgotności powietrza; temperatury wewnątrz kapsuł ładunkowych, w szczególności na źródłach zasilania; szybkości wznoszenia, opadania i przemieszczania się; parametrów transmisji radiowej. W artykule przedstawiono analizę wybranych danych obejmujących pomiary wilgotności, ciśnienia, temperatury w troposferze i stratosferze oraz temperatury wewnątrz kapsuły. Wyznaczono zależności wielkości fizycznych od wysokości. Przedstawiono wnioski wypływające z analizy danych.

EN

In the period from July 29 to September 29, 2023, three stratospheric missions were sent from the campus of the University of Applied Sciences in Tarnow, Poland, by lifting the payload using helium-filled balloons. During the mission, a number of measurements were recorded regarding air temperature, pressure and humidity; temperature inside the payload capsules, in particular at the power sources; rate of ascent, descent and movement; radio transmission parameters. The article presents an analysis of selected data including measurements of humidity, pressure, temperature in the troposphere and stratosphere and temperature inside the capsule. The dependencies of physical quantities on altitude were determined. Conclusions resulting from the analysis of the data were presented.

14

Evaluation of the performance of data-driven approaches for filling monthly precipitation gaps in a semi-arid climate conditions

Katipoğlu Okan Mert

Acta Geophysica

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2023

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Vol. 71, no. 5

2265--2285

EN

Missing data cause problems in meteorological, hydrological, and climate analysis. The observation data should be complete and cover long periods to make the research more accurate and reliable. Artificial intelligence techniques have attracted interest for completing incomplete meteorological data in recent years. In this study the abilities of machine learning models, artificial neural networks, the nonlinear autoregressive with exogenous input (NARX) model, support vector regression, Gaussian processes regression, boosted tree, bagged tree (BAT), and linear regression to fill in missing precipitation data were investigated. In developing the machine learning model, 70% of the dataset was used for training, 15% for testing, and 15% for validation. The Bayburt, Tercan, and Zara precipitation stations, which are closest to the Erzincan station and have the highest correlation coefficients, were used to fill the data gaps. The accuracy of the constructed models was tested using various statistical criteria, such as root-mean-square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe model efficiency coefficient (NSE), and determination coefficient (R2) and graphical approaches such as scattering, box plots, violin plots, and Taylor diagrams. Based on the comparison of model results, it was concluded that the BAT model with R2: 0.79 and NSE: 0.79 and error (RMSE: 11.42, and MAE: 7.93) was the most successful in the completion of missing monthly precipitation data. The contribution of this research is assist in the choice of the best and most accurate method for estimating precipitation data in semi-arid regions like Erzincan.

15

Pattern recovery and signal denoising by SLOPE when the design matrix is orthogonal

Skalski Tomasz, Kołodziejek Bartosz, Graczyk Piotr, Wilczyński Maciej

Probability and Mathematical Statistics

|

2022

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Vol. 42, Fasc. 2

283--302

EN

Sorted ℓ1 Penalized Estimator (SLOPE) is a relatively new convex regularization method for fitting high-dimensional regression models. SLOPE allows the reduction of the model dimension by shrinking some estimates of the regression coefficients completely to zero or by equating the absolute values of some nonzero estimates of these coefficients. This allows one to identify situations where some of true regression coefficients are equal. In this article we will introduce the SLOPE pattern, i.e., the set of relations between the true regression coefficients, which can be identified by SLOPE. We will also present new results on the strong consistency of SLOPE estimators and on the strong consistency of pattern recovery by SLOPE when the design matrix is orthogonal and illustrate advantages of the SLOPE clustering in the context of high frequency signal denoising.

16

Regresja i niepewność linii prostej dla pomiarów obu zmiennych x i y ze wszystkimi korelacjam

Puchalski Jacek, Warsza Zygmunt Lech

Pomiary Automatyka Robotyka

|

2022

|

R. 26, nr 2

47--58

PL

Praca kontynuuje cykl publikacji o szacowaniu metodą regresji liniowej parametrów równania i granic pasma niepewności linii prostej y = ax + b dopasowanej do wyników pomiarów obu współrzędnych punktów badanych. Rozpatrzono przypadek ogólny, gdy współrzędne te mają różne niepewności i występują wszystkie możliwe autokorelacje i korelacje wzajemne. Zastosowano opis równaniami macierzowymi. Wyniki pomiarów współrzędnych przedstawiono jako elementy wektorów w X i Y. Propagację niepewności opisano macierzą kowariancji UZ o czterech macierzach składowych, tj. UX i UY - dla niepewności i autokorelacji zmiennych X i Y oraz UXY i jej transpozycja UTXY - dla korelacji wzajemnych. Podano równanie linii prostej i granice jej pasma niepewności. Otrzymane je dla funkcji parametrów a i b spełniającej tzw. kryterium totalne WTLS, tj. minimum sumy kwadratów odległości punktów od prostej ważonych przez odwrotności niepewności współrzędnych. Przy nieskorelowaniu współrzędnych różnych punktów stosuje się uproszczone kryterium WLS. Kierunki rzutowania punktów wnikają z minimalizacji funkcji opisującej kryterium. W przypadku ogólnym istnieje tylko rozwiązanie numeryczne. Zilustrowano to przykładem. Parametry a i b linii prostej wyznaczono numerycznie z powiększonych fragmentów wykresu funkcji kryterialnej wokół jej minimum. Podano też warunki wymagane dla niepewności i korelacji współrzędnych punktów, które umożliwiają uzyskanie rozwiązania analitycznego i jego przykład.

EN

The work continues the series of publications on the estimation of the parameters of the equation and the limits of the uncertainty band of the straight-line y = ax + b fitted to the measurement results of both coordinates of the tested points with the use of the linear regression method. A general case was considered when these coordinates have different uncertainties and there are all possible autocorrelations and cross-correlations. Description of matrix equations was used. The results of the coordinate measurements are presented as elements of the X and Y vectors. The propagation of their uncertainty was described by the UZ covariance matrix with four component matrices, i.e., UX and UY - for the uncertainties and autocorrelations of X and of Y, and UXY and its transposition UTXY - for the cross-correlations. The equation of a straight line and of the borders of its uncertainty band are given. Obtained them for the function of parameters a and b satisfying the so-called total criterion WTLS, i.e., the minimum sum of squared distances of points from the straight line weighted by the reciprocal of the coordinate uncertainty. When the coordinates of different points are not correlated, the simplified criterion WLS is used. The directions of projecting the points result from the minimization of the function describing the criterion. In the general case, there is only a numerical solution. This is illustrated by an example, in which the parameters a and b of the straight line were determined numerically from the enlarged fragments of the graph of the criterion function around its minimum. The conditions for the uncertainty and correlation of coordinates of points required to obtain an analytical solution and its example are also given.

17

An accurate model of LED luminaire using measurement results for estimation of electrical parameters based on the multivariable regression method

Sikora Roman, Markiewicz Przemysław, Rózga Paweł

Metrology and Measurement Systems

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2022

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Vol. 29, nr 2

251--269

EN

Light sources and luminaires made in the LED technology are nowadays widely used in industry and at home. The use of these devices affects the operation of the power grid and energy efficiency. To estimate this impact, it is important to know the electrical parameters of light sources and luminaires, especially with the possibility of dimming. The article presents the results of measurements of electrical parameters as well as luminous flux of dimmable LED luminaires as a function of dimming and RMS supply voltage. On the basis of the performed measurements, a model of LED luminaire was developed for prediction of electrical parameters at set dimming values and RMS values of the supply voltage. The developed model of LED luminaire has 2 inputs and 26 outputs. This model is made based on 26 single models of electrical parameters, whose input signals are supply and control voltages. The linear regression method was used to develop the models. An example of the application of the developed model for the prediction of electrical parameters simulating the operation of an LED luminaire in an environment most similar to real working conditions is also presented.

18

Uogólniona metoda najmniejszych kwadratów

Puchalski Jacek

Metrologia i Probiernictwo : biuletyn Głównego Urzędu Miar

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2022

|

nr 1 (28)

9--16

PL

Artykuł przedstawia uogólnione podejście dla dobrze znanej metody najmniejszych kwadratów stosowanej w praktyce metrologicznej. Wyznaczone niepewności punktów pomiarowych i korelacje między mierzonymi zmiennymi tworzą symetryczną macierz kowariancji, której odwrotność mnożona jest lewostronnie i prawostronnie przez wektory błędów obu zmiennych losowych i stanowi funkcję kryterialną celu. Aby uzyskać maksymalną wartość funkcji największej wiarygodności i rozwiązać złożony problemu minimalizacji funkcji kryterialnej, zaprezentowano oryginalny sposób wyznaczenia funkcji kryterialnej do postaci jednoargumentowej zależności obliczanej numerycznie, w której jedyną zmienną jest poszukiwany współczynnik kierunkowy prostej regresji. Artykuł zawiera podstawowe informacje o tego typu regresji liniowej, dla której najlepiej dopasowana prosta minimalizuje funkcję celu. Na przykładzie obliczeniowym pokazana jest pełna procedura dopasowania numerycznego prostej do danego zestawu punktów pomiarowych o zadanych niepewnościach i współczynnikach korelacji tworzących macierz kowariancji.

EN

The paper presents a generalized approach for the well-known least squares method used in metrological practice. In order to solve the complex problem of minimizing the objective function to obtain the maximum value of the likelihood function, the original way of determining this function in the form of a unary relationship calculated numerically was presented. The article presents borderline cases with analytical solutions. The computational example shows the full procedure of numerical adjustment of a straight line to a given set of measurement points with given uncertainties and correlation coefficients forming the covariance matrix.

19

Assessment of the benefits of implementing the EMS system on the example of a container glass industry

Dec Przemysław, Skorek-Osikowska Anna

Journal of Power Technologies

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2022

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Vol. 102, nr 4

160--174

EN

The paper describes the glass manufacturing process, the process areas and their energy intensity. The implementation of an energy management system, its operation and participation in the decision-making chain as well as benefits from implementation are also described. The use of regression as a numerical technique for determining energy consumption is presented with reference to the historical experience of the glassworks and its developed trends on the example of gas consumption in the melting process in the glass furnace. The paper compared the deviation of actual energy consumption in the glass melting process to that calculated from linear regression variables for data before and after the implementation of the Energy management system. The study confirmed the sensibility of implementing the described managing system. Constant observation and response to factors affecting the running process allows for its stabilization and optimization.

20

The Interaction of Chlorophyll-a and Total Suspended Matter along the Western Semarang Bay, Indonesia, Based on Measurement and Retrieval of Sentinel 3

Maslukah Lilik, Ismunarti Dwi Haryo, Widada Sugeng, Sandi Nur Fikri, Prayitno Hanif Budi

Journal of Ecological Engineering

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2022

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Vol. 23, nr 10

191--201

EN

The Kendal Regency area is one of the areas on the northern coast of Central Java that has been experiencing rapid industrial development. The high human activity in this area will impact the quality of water in these surrounding areas and affect the fertility of the waters. The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are major water quality parameters that can be retrieved using remotely sensed data. The retrieval satellite of the 3 OLCI chosen in this study has a 300 m spatial resolution. This study aimed to see the distribution and effect of total suspended matter (TSM) on chlorophyll-a based on measurement and retrieval of Sentinel 3 imagery using the linear regression method. The results show the chlorophyll-a distribution and the value from retrieval satellite are higher and occur over larger surface area compared to chlorophyll-a measurements. The linear regression model of chlorophyll-a by retrieval satellite imagery and measurement is y = 0.65x + 4.65 with R2 = 0.54. The presence of high amounts of suspended solids in the waters causes disturbances in the reflectance values, which are recorded by the retrieval of satellite. The model regression chlorophyll-a with TSM accuracy from retrieval satellite results in the equation y = -0.0416x + 5.14 (R2 = 0.45, p = 0.05, n = 13). The determination (R2) coefficient value is 0.445, which means that suspended solids have a 44.5% effect on chlorophyll-a and 55.5% is influenced by other factors and not examined in this study. The results show that TSM has an influence on the accuracy of chlorophyll-a and retrieval satellite recording can be disrupted if waters have high turbidity.