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1

The Impact of FDM Process Parameters on the Compression Strength of 3D Printed PLA Filaments for Dental Applications

Hamed Mostafa Adel, Abbas Tahseen Fadhil

Advances in Science and Technology. Research Journal

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2023

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Vol. 17, no 4

121--129

EN

This study evaluated Fused Deposition Modeling (FDM) for printing objects with maximum compression strength by focusing on critical process parameters. Infill density, outer shell width, infill pattern, and layer thickness were examined. Taguchi studies tested all parameter values with the fewest possible tests. Infill density (55.488 Mpa) affected compressive resistance the most, followed by outer shell width (1.8 mm), infill pattern (75%), infill pattern type (concentric), nozzle diameter (0.6 mm), and layer thickness (0.3 mm) and the liner regression model which use to prediction experimental value shown minimum percentage error(4%). The study also demonstrated the fabrication of 3D-printed crowns using PLA and FDM printing as temporary crowns, which remained intact without any discomfort until the permanent prosthesis was ready. The average printing time for temporary crowns was approximately 7 minutes. This study indicates that 3D printing of temporary crowns with PLA using FDM printing is a convenient process for dentists the result for crowns for teeth 13 and 16 of the human case study showed good accuracy and good resistance to compression.

2

Soil Salinity Monitoring and Quantification Using Modern Techniques

Al-Khuzaie Marwah M., Abdul Maulud Khairul Nizam, Mohd Taib Aizat

Journal of Ecological Engineering

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2022

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Vol. 23, nr 11

57--67

EN

Along with sea-level rise, one of the most detrimental effects of climate change, is salinity leakage, which significantly affects agricultural activities throughout most of the world. This occurrence is becoming increasingly dangerous. The purpose of this study was to use Geographical Information Systems (GIS) to assess the current situation of agricultural lands in the province of Al-Diwaniyah, by employing GIS to document the salt-affected sites and arrive at the most important criteria affecting those lands as well as build an application model for suitability to clarify the affected sites and come up with paper and digital maps. To accomplish this, the study relied on the available data by extrapolating and analyzing remote sensing images using salt equations to analyze the Landsat 8 satellite images, after which these data were subjected to spatial statistical treatment in ArcGIS software. Moreover, 20 samples were taken from ground sampling points and subjected to laboratory analysis to compare and document the results. The research resulted in the creation of an up-to-date database for the locations of salt ratio growth or decrease in the province of Al-Diwaniyah, which can be relied on, starting from and expanding in the future. Land maps, both paper and digital, have been created and can be used and inferred. The findings demonstrated the model’s ability to steadily discriminate among all salinity groups while maintaining consistency with the ground truth data. Each of the four major salinity categories was highlighted. The best-performing indicators were used to build the MLR model, which was then used to anticipate soil salinity. The salt levels may be determined by the MLR combining NDVI and SI-5 with a high correlation value (R2 = 75.29%). Finally, it is shown that by combining spectral indicators with field measurements, it is possible to chart and forecast soil salinity on a large scale.

3

A short review on feedstock characteristics in methane production from municipal solid waste

Sendilvadivelu Arunthathi, Dhandapani Balaji, Vijayasimhan Sivapriya

Architecture Civil Engineering Environment

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2022

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Vol. 15, no. 3

75--85

EN

The increase in population and industrialization leads to an increase in the solid waste year by year. The limited availability, increasing cost and adverse effect of climate change on fossil fuel leads to encouraging the research in the field of finding alternatives for energy sources. The organic fraction of municipal solid waste (OFMSW) can be utilized as a bio-energy source, which reduces the environmental impact and the requirement of landfill areas to dispose of municipal solid waste. Anaerobic digestion is the widely used sustainable approach to treat OFMSW. In recent years, the generation of methane from municipal solid waste has received increasing attention in research. This paper reviews literature published in recent years considering various characteristics of input feedstock parameters like pH, total solids, volatile solids, and water content which affect the digestion quality of the OFMSW and increase the production of methane. A regression model is developed to identify the relationship between methane production and various feedstock parameters. When the chemical compositions of feedstock were used as independent variables, the percentage variation accounted for by the model is low (r2 = 0.63) and also the important observation from the analysis is that the pH of the feedstock influences majorly methane production.

4

Predicting the peak particle velocity from rock blasting operations using Bayesian approach

Aladejare Adeyemi Emman, Lawal Abiodun Ismail, Onifade Moshood

Acta Geophysica

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2022

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Vol. 70, no 2

581--591

EN

Measuring the blast-induced ground vibration at blasting sites is very important, to plan and avoid adverse effects of blasting in terms of the peak particle velocity (PPV). However, the measurement of PPV often requires time, cost, and logistic commitment, which may not be economical for small-scale mining operations. This has prompted the development of numerous regression equations in the literature to estimate PPV from a relatively easier to estimate scaled distance (SD) measurement. With numerous regression equations available in the literature, there is a challenge of how to select the appropriate model for a specific blasting site, more so that rocks behave differently from site to site because of different geological processes that rocks are subjected to. This study develops a method that selects appropriate models for specific blasting sites by comparing the evidence and occurrence probability of different regression models. The appropriate model is the model with the highest evidence and occurrence probability given the available blasting site SD data. The selected model is then integrated with prior knowledge and available blasting SD data in Bayesian framework for probabilistic characterization of PPV. The SD and PPV data at the opencast coal mine, Jharia coalfield in the Dhanbad district of Jharkhand, India, is used to illustrate and validate the approach. The mean and standard deviation of simulated PPV samples from the proposed approach are 12.38 mm/s and 7.36 mm/s, respectively, which are close to the mean of 12.03 mm/s and standard deviation of 9.24 mm/s estimated from the measured PPV at the site. In addition, the probability distribution of the simulated PPV samples is consistent with the probability distribution of the measured PPV at the blasting site.

5

Estimation of standard duration maximum rainfall by using regression models

Yerdelen Cahit, Asikoglu Ömer Levend, Abdelkader Mohamed, Eris Ebru

Journal of Water and Land Development

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2021

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no. 50

281--288

EN

Gauging stations of meteorological networks generally record rainfall on a daily basis. However, sub-daily rainfall observations are required for modelling flood control structures, or urban drainage systems. In this respect, determination of temporal distribution of daily rainfall, and estimation of standard duration of rainfall are significant in hydrological studies. Although sub-daily rainfall gauges are present at meteorological networks, especially in the developing countries, their number is very low compared to the gauges that record daily rainfall. This study aims at developing a method for estimating temporal distribution of maximum daily rainfall, and hence for generating maximum rainfall envelope curves. For this purpose, the standard duration of rainfall was examined. Among various regression methods, it was determined that the temporal distribution of 24-hour rainfall successfully fits the logarithmic model. The logarithmic model’s regression coefficients (named a and b) were then linked to the geographic and meteorological characteristics of the gauging stations. The developed model was applied to 47 stations located at two distinct geographical regions: the Marmara Sea Region and Eastern Black Sea Region, Turkey. Various statistical criteria were used to test the method's accuracy, and the proposed model provided successful results. For instance, the RMSE values of the regression coefficients a and b in Marmara Regions are 0.004 and 0.027. On the other hand, RMSE values are 0.007 and 0.02 for Eastern Black Sea Region.

6

Creep Behaviors at 275°C for Aluminum-Matrix Nano-composite under Different Stress Levels

Azadi M., Behmanesh A., Aroo H.

Archives of Foundry Engineering

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2021

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Vol. 21, iss. 3

81--89

EN

Aluminum alloys, due to appropriate strength to weight ratio, are widely used in various industries, including automotive engines. This type of structures, due to high-temperature operations, are affected by the creep phenomenon; thus, the limited lifetime is expected for them. Therefore, in designing these types of parts, it is necessary to have sufficient information about the creep behavior and the material strength. One way to improve the properties is to add nanoparticles and fabricate a metal-based nano-composite. In the present research, failure mechanisms and creep properties of piston aluminum alloys were experimentally studied. In experiments, working conditions of combustion engine pistons were simulated. The material was composed of the aluminum matrix, which was reinforced by silicon oxide nanoparticles. The stir-casting method was used to produce the nano-composite by aluminum alloys and 1 wt.% of nanoparticles. The extraordinary model included the relationships between the stress and the temperature on the strain rate and the creep lifetime, as well as various theories such as the regression model. For this purpose, the creep test was performed on the standard sample at different stress levels and a specific temperature of 275 oC. By plotting strain-time and strain rate-time curves, it was found that the creep lifetime decreased by increasing stress levels from 75 MPa to 125 MPa. Moreover, by comparing the creep test results of nanoparticle-reinforced alloys and nanoparticle-free alloys, 40% fall was observed in the reinforced material lifetime under 75 MPa. An increase in the strain rate was also seen under the mentioned stress. It is noteworthy that under 125 MPa, the creep lifetime and the strain rate of the reinforced alloy increased and decreased, respectively, compared to the piston alloy. Finally, by analyzing output data by the Minitab software, the sensitivity of the results to input parameters was investigated.

7

Application of projection pursuit regression model for blasting vibration velocity peak prediction

Shi Jianjun, An Huaming, Wei Xin

Archives of Civil Engineering

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2021

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Vol. 67, nr 2

653--673

EN

Based on Projection Pursuit Regression Theory (PPRT), a projection pursuit regression model has been established for forecasting the peak value of blasting vibration velocity. The model is then used to predict the peak value of blasting vibration velocity in a tunnel excavation blasting in Beijing. In order to train and test the model, 15 sets of measured samples from the tunnel project are used as the input data. It is found that predicting results by projection pursuit regression model on the basis of the input data is much more reasonable than that predicted by the traditional Sodaovsk algorithm and modified Sodaovsk formula. The results show that the average predicting error of the projection pursuit regression model is 6.36%, which is closer to the measured values. Thus, the projection pursuit prediction model is a practical and reasonable tool for forecasting the peak value of blasting vibration velocity.

8

Bank indicators management models for ensure of financial stability necessary leve

Chemchykalenko Ruslan, Dubrovina Vira, Hrebenyuk Nadiia

Zeszyty Naukowe Wyższej Szkoły Technicznej w Katowicach

|

2020

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nr 12

219--228

EN

This article constructs linear trend models for the main indicators of the balance sheet and net profit of a state bank and determines their forecast values. The structural management model for the basic indicators of the state of bank is constructed and regression equations are used. For structural regression models, growth rates and their lag values were chosen, and lag in the 1st and 2nd time periods was used for modelling. Based on the graphical analysis, it is shown that there are dependences between the indicators of financial autonomy and indicators of return on assets and equity and two clusters are distinguished: the cluster of financial stability and the cluster of unstable financial positions of the bank. Based on the structural model and its parameters, according to the state of bank, the development of a sustainable development strategy is proposed, in which special attention should be paid to planning and forecasting key indicators, their complex functional relationships taking into account the time factor, random factors and their impact on state of bank and its financial stability.

PL

W artykule autorzy budują liniowy model trendu dla głównych wskaźników bilansu i zysku netto banku państwowego oraz określają ich prognozowane wartości. Skonstruowano strukturalny model zarządzania podstawowymi wskaźnikami banku państwa, w którym wykorzystuje się równania regresji. W przypadku modeli regresji strukturalnej wybrano stopy wzrostu i ich wartości opóźnienia, a do modelowania wykorzystano opóźnienie w pierwszym i drugim okresie. Na podstawie analizy graficznej wykazano, że istnieją złożone formy zależności między wskaźnikami autonomii finansowej a wskaźnikami zwrotu z majątku i kapitału oraz wyróżnia się dwa klastry: klaster stabilności finansowej oraz klaster niestabilnych pozycji finansowych banku. Zdaniem Banku Państwowego, w oparciu o model strukturalny i jego parametry, proponuje się opracowanie strategii zrównoważonego rozwoju. W której szczególną uwagę należy zwrócić na planowanie i prognozowanie kluczowych wskaźników. Ich złożonych zależności funkcjonalnych z uwzględnieniem czynnika czasu, czynników losowych oraz ich wpływu na wynik finansowy banku oraz na jego stabilność.

9

Modeling sound distribution in the bus passenger area while driving

Orczyk Małgorzata, Tomaszewski Franciszek

Prace Naukowe Politechniki Warszawskiej. Transport

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2020

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z. 128

29--36

EN

The article presents the results of noise tests in 18 m Solaris Urbino public transport buses. In the passenger compartment of the tested vehicles, there were ten measuring microphones and a GPS device for measuring vehicle speed. These devices recorded speed and sound levels in the tested buses. The results of the measurements were used to assess the noise in the passenger space of buses and develop regression models for each microphone location. In their algorithms, these models considered vehicle speed and sound levels. The purpose of the tests was to check whether the noise in individual microphone locations depends on the cruising speed of the bus and to assess the sound distribution along with the inside space of the vehicle in motion.

PL

W artykule przedstawiono wyniki badań hałasu w autobusach komunikacji miejskiej typu Solaris Urbino 18 m. W przestrzeni pasażerskiej badanych pojazdów umieszczono 10 mikrofonów pomiarowych oraz urządzenie do pomiaru prędkości GPS. Urządzenia te rejestrowały prędkość jazdy i poziomy dźwięku w badanych autobusach. Na podstawie wykonanych badań oceniono hałas w przestrzeni pasażerskiej autobusów oraz opracowano dla każdej lokalizacji mikrofonu modele regresyjne. Modele te w swoich algorytmach uwzględniały prędkość jazdy i poziomy dźwięku. Celem wykonanych badań było sprawdzenie czy hałas w poszczególnych lokalizacjach mikrofonów zależy od prędkości, z jaką jest realizowana jazda oraz zbadanie rozkładu dźwięku wzdłuż pojazdu podczas jazdy.

10

Investigation of the factors that influence the evolution of bank employees

Iuga Iulia, Budeci Mihaela

Polish Journal of Management Studies

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2020

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Vol. 21, No. 2

162--178

EN

The present paper analyses the factors that influence the number of employees in the banking system. The aim of our research was to determine the influence of bank profitability (ROA), the number of branches and the number of ATM machines per 100.000 adults on evolution of the number of employees in the Central and Est European banking system (11 countries) and compare with Romanian banking system. It was used a model that refers to a multidimensional data collected for a period (Panel Data Regression) for eleven countries analyzed. For the analysis of the Romanian indicators, the multiple linear regression model was used. The analysis shows that both the Romanian model and the model performed on the 11 countries (panel data) registered a positive and direct relationship between number of banking units (BRANCHES) and number of bank employees, and an inverse correlation between number of ATM machines per 100,000 adults and number of bank employees

PL

Niniejszy artykuł analizuje czynniki wpływające na liczbę pracowników w systemie bankowym. Celem naszych badań było określenie wpływu rentowności banków (ROA), liczby oddziałów i liczby bankomatów na 100 000 osób dorosłych na ewolucję liczby pracowników w centralnym i estońskim systemie bankowym (11 krajów) oraz porównanie z rumuńskim systemem bankowym. Zastosowano model odnoszący się do danych wielowymiarowych zebranych dla okresu (regresja danych panelowych) dla jedenastu analizowanych krajów. Do analizy wskaźników rumuńskich zastosowano model regresji wielokrotnej liniowej. Analiza pokazuje, że zarówno model rumuński, jak i model wykonany w 11 krajach (dane panelowe), zarejestrowały dodatni i bezpośredni związek między liczbą jednostek bankowych (ODDZIAŁY) a liczbą pracowników banków, a także odwrotną korelację między liczbą bankomatów na 100 000 osób dorosłych i liczba pracowników banków.

11

Regression modeling and neural computing for predicting the ultimate tensile strength of friction stir welded aerospace aluminium alloy

Mishra Akshansh, Vance Jonathan Ve

Journal of Mechanical and Energy Engineering

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2019

|

Vol. 3, No 3

221--226

EN

AA7075 is an aluminum alloy which is almost as strong as steel, yet it weighs just one third as much. Unfortunately its use has been limited, due to the fact that pieces of it could not be securely welded together by the traditional welding process. Friction Stir Welding (FSW) process overcomes the limitations of conventional welding process. In our present work we have used Artificial Neural Network which is Artificial Intelligence based technique used for prediction purpose. The main objective of our present work is to compare the predicted results of the Ultimate Tensile Strength (UTS) of Friction Stir welded similar joints through Regression modeling and Artificial Neural Network (ANN) modeling. It was observed that the linear regression algorithm is able to make more accurate predictions compared to neural network algorithm for small dataset.

12

Agro-Environmental Evaluation of Irrigation Water from Different Sources, Together with Drainage and Escape Water of Rice Irrigation Systems, According to its Impact on Maize (Zea mays L.)

Lykhovyd Pavlo, Dementiieva Olha, Lavrenko Sergiy, Lavrenko Nataliia

Journal of Ecological Engineering

|

2019

|

Vol. 20, nr 2

1--7

EN

The water supply deficit requires agro-environmental rationale for the use of alternative water sources to feed agricultural crops, viz.: industrial wastes, municipal drains, farm animal waste, drainage and escape water of rice irrigation systems. We analyzed the quality of irrigation water from different sources, with regard to the content of cations, anions, water-soluble salts, power of hydrogen (рН), sodium adsorption ratio (SAR), etc. in it. In the course of the greenhouse trial, we diagnosed its impact on the indicator crop (maize) (Zea mays L.) with its herbage crop stage of 10 leaves, supplied with water of varying quality. We proved the viability of improved drainage and escape water from rice irrigation systems in irrigated agriculture, owing to which maize herbage was diminished, on average, by 5.82%. We verified the negative impact of irrigation water, which contains the effluent disposals of metallurgical production, on croppers – it had contributed to diminishing the watered maize herb, on average, by 39.27%. A correlation analysis of the test data proved the closely interrelated feedback between the maize herbage amount and the content of cations, anions and water-soluble salts in irrigation water (coefficient of correlation r varied between 0.88 and 0.98). The worked-out linear regressive model for maize herbage, based on the content of water-soluble salts in irrigation water, together with SAR index (Y=2342.71–1.82×x1+366.78×x2), affirmed the validity of the pattern, discovered by means of the correlation analysis.

13

Application of Partial Regression Methods to Long Range Forecasts

Konca-Kędzierska K.

Przegląd Geofizyczny

|

2018

|

Z. 4

353--362

EN

The article presents the construction of a regression model for the long-range forecast of tercile categories of the monthly mean temperature. Two methods from the group of the partial least squares (PLS) and sparse partial least squares (SPLS) methods were used. The selected methods combine the properties of principal component analysis (PCA) with features of multiple regression methods, and apply the creation of latent layers. These methods also have no restrictions related to the independence of predictors and no constraints on the model dimension. The predictors are percentiles (10%, 50% and 90%) for selected fields of the NCEP/NCAR Reanalysis dataset. The model uses a time series of predictors for periods from 5 to 30 years. The obtained set of forecasts is subjected to the evaluation process based on indicators for the dependent period. This allows for the selection of a reliable ensemble of forecasts. The presented model was tested between January 2014 and December 2016.

14

Próba opracowania modelu regresyjnego do szacowania wartości BZT5 ścieków komunalnych

Kowalewski Z., Neverova-Dziopak E., Preisner M.

Ochrona Środowiska

|

2018

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Vol. 40, nr 1

21--27

PL

Jednym z podstawowych składników ścieków komunalnych są zanieczyszczenia organiczne, których zawartość jest określana najczęściej na postawie ich biochemicznego zapotrzebowania na tlen (BZT5). W artykule opracowano prosty model regresyjny do szacowania wartości BZT5 ścieków komunalnych w celu zapewnienia bieżącej kontroli sprawności procesu biologicznego oczyszczania oraz możliwości optymalizacji warunków eksploatacji reaktorów biologicznych. Model opracowano na podstawie danych pochodzących z wieloletniego (1990–2000) monitoringu jakości ścieków w oczyszczalni Terrence J. O’Brien Water Reclamation Plant w Chicago (USA). Analizie statystycznej poddano wartości następujących wskaźników jakości ścieków dopływających do oczyszczalni: pH, BZT5, zawiesiny ogólne, azot amonowy, azot Kjeldahla oraz azotany. Wszystkie obliczenia wykonano w programie statystycznym R z nakładką R Studio w wersji 1.0.143. Do wyboru parametrów istotnych do budowy modelu zastosowano kryterium informacyjne Akaikego (AIC) oraz algorytm Leaps. Na podstawie wyników testowania sformułowano model regresyjny do szacowania wartości BZT5 ścieków komunalnych wykorzystujący zawartości zawiesin ogólnych oraz azotu Kjeldahla i azotanów w ściekach. Algorytm formułowania modelu regresyjnego, przydatnego do szybkiego uzyskiwania przybliżonych wartości BZT5 ścieków, może posłużyć do budowy podobnych modeli na potrzeby innych oczyszczalni ścieków, bez konieczności częstego wykonywania oznaczeń laboratoryjnych i długiego oczekiwania na ich wyniki.

EN

One of the primary components of municipal sewage is organic pollution, the content of which is determined most often on the basis of its biochemical oxygen demand (BOD5). In the paper, a simple regression model was developed to estimate BOD5 values of municipal sewage in order to ensure ongoing effi ciency control of the biological treatment process and possibilities for optimizing the operating conditions of biological reactors. The model was developed from the long-term monitoring data (1990–2000) on wastewater quality in the Terrence J. O’Brien Water Reclamation Plant in Chicago (USA). Statistical analysis covered the following quality indicators for the sewage material fl owing into the treatment plant: pH, BOD5, total suspended solids, ammonium nitrogen, Kjeldahl nitrogen and nitrates. All calculations were made using a statistical program R with R Studio patch, version 1.0.143. Akaiki Information Criterion (AIC) and the Leaps algorithm were employed to select parameters relevant to constructing the model. Based on the results of model testing, the regression model for BOD5 values estimation in municipal wastewaters was formulated. The model employed parameters such as total suspended solids, Kjeldahl nitrogen and nitrates wastewater content. The algorithm of formulating the regression model that allows for quick generation of approximate BOD5 values in wastewater can be applied to development of similar models for other treatment plants, with no need for frequent laboratory testing and long wait for the results.

15

Prediction of Solar Radiation for the Major Climates of Jordan: A Regression Model

Badran A. A., Dwaykat B. F.

Journal of Ecological Engineering

|

2018

|

Vol. 19, nr 2

24--38

EN

Multiple regression models were developed for calculating the regression coefficients a and b of the Angström-type equation for estimating the monthly average daily global radiation on a horizontal surface for six major climates in Jordan. The equations for a and b were developed from the available values of these constants reported in the literature for locations across the country, along with the sunshine duration and the values of ground albedo (ρ_g). The developed correlations were tested for their applicability by estimating the regression constants and the solar radiation for six locations spread over the country, which were Irbid, Amman, Azraq, Al-Shawbak, Ma’an and Aqaba. The remarkable agreement between the estimated and experimental data of solar radiation in those locations suggests a wide applicability of the method for the locations with sunshine duration ranging from 0.7 to 0.8. The maximum and minimum percentages of error for those locations were found to be 6.3, 0.05%, respectively.

16

Ensembling a linear regression model with an error mitigation component

Nowosielski A., Kowalski P. A., Kulczycki P.

Journal of Automation Mobile Robotics and Intelligent Systems

|

2018

|

Vol. 12, No. 1

40--43

EN

This paper presents a proposal of a model error mitigation technique based on the error distribution analysis of the original model and creatng the additional model that tempers the error impact in particular domain areas identified as the most sensitive. both models are then combined into single ensemble model. The idea is demonstrated on the trivial two-dimensional linear regression model.

17

Model of hierarchical regression in decision problems of transportation systems

Topolska K.

Archives of Transport System Telematics

|

2017

|

Vol. 10, iss. 2

27--32

EN

This article presents a method of multilevel hierarchical analysis for managing transportation systems – Intelligent Transport Systems (ITS). The task of multilevel planning it is essential to connect various links of the system. To make decisions a model of hierarchical structure has been applied as quite frequently actions in one point of the system affect results and actions taken in its other constituent. The article presents a method of estimation of the system parameters for the task of prediction. In the article the author is trying to prove that to select appropriate parameters to the model a weak correlation of independent features at simultaneous high correlation of these features with a dependent variable is necessary. All parameters necessary to solve decision problems must be random. A proposed model represents a compromise between estimation of the model in each group of routes separately and for all units of observations without taking into consideration grouping of routes.

18

Predictive geometrical model of the upper extremity of human fibula

Tufegdzic M., Arsic S., Trajanovic M.

Biocybernetics and Biomedical Engineering

|

2016

|

Vol. 36, no. 1

172--181

EN

Computer assisted preoperative planning in orthopedic surgery, as well as designing and manufacturing of personalized fixators, implants and scaffolds requires a good three-dimensional model of bone(s) of the treated patients. Existing methods that convert the Computer Tomography (CT) images into the polygonal three-dimensional models are time-consuming and inefficient. Therefore, we propose a predictive model that allows quick creation of three-dimensional (3D) surface model of a particular bone by measuring the relevant parameters from an X-ray or CT image. In this paper, we present the process of creating a predictive geometrical model using the case of proximal end of fibula as an example. The predictive model is built by defining the referential geometric entities that correspond to anatomical features, based on which appropriate points, axes, planes and curves are created. Using the method of linear and nonlinear regression with four different parameters, which can be measured from X-ray images or anterior-posterior projection of fibula at CT scans, the equations for X, Y and Z coordinates of the selected 168 points are obtained and their predictive values are calculated. These values are used for creating 3D surface model with the aim of two different methods: using loft function and converting these coordinates into point cloud. These models were compared and verified through analysis of deviations and distances between initial model and predictive models. The resulting 3D model has satisfactory accuracy, and the process of its building is much shorter.

19

Określenie optymalnej pojemności parkingu na podstawie analiz symulacyjnych

Naumov V.

Zeszyty Naukowo-Techniczne Stowarzyszenia Inżynierów i Techników Komunikacji w Krakowie. Seria: Materiały Konferencyjne

|

2015

|

Nr 1(105)

61--70

PL

W artykule przedstawiono model symulacyjny funkcjonowania parkingu wykorzystujący zorientowane obiektowo podeście. W zaproponowanym modelu uwzględniono stochastyczny charakter popytu na usługi parkowania w mieście. W artykule omówiono wyniki symulacji funkcjonowania parkingu oraz przedstawiono dyskusję praktycznych rezultatów. Przedstawiono również model regresji określający optymalną pojemność parkingu otrzymany na podstawie wyników z modelu symulacyjnego.

EN

Paper presents a simulation model of city parking functioning based on object-oriented approach. The proposed model considers stochastic nature of demand on parking services in cities. The results of parking functioning simulations are shown and the appropriate practical implications are discussed. On the base of simulation results the regression model for estimation of the parking optimal capacity has been obtained.

20

Weryfikacja planu badań napięcia akumulatora kwasowego

Dyga Grzegorz, Pszczółkowski Józef

TTS Technika Transportu Szynowego

|

2015

|

R. 22, nr 12

1856--1862, CD

PL

W artykule poddano analizie dwuczynnikowy matematyczny model regresyjny. Opisano sposób badania istotności zmiennych niezależnych na wartość napięcia mierzonego na zaciskach obciążonego akumulatora. Przedstawiono sposób postępowania podczas planowania doświadczenia umożliwiającego wyznaczenie współczynników modelu regresyjnego. Podjęto próbę jego weryfikacji wykorzystując wyznaczony model regresji. Wykazano, że odpowiednio zaplanowany eksperyment pozwala na znaczne ograniczenie czasu pracy niezbędnego do przeprowadzenia badań prowadzących do wyznaczenia współczynników modelu liniowego opisującego związki między zmiennymi, głównie poprzez ograniczenie do minimum liczby niezbędnych pomiarów (doświadczeń). Wykazano także, że mimo ograniczonej liczby doświadczeń zachowana jest liniowa struktura wyznaczonego modelu.

XX

There is presented the analysis of the two-factor mathematical regression model. The method of testing the significance of the independent variables on the voltage measures at the terminals of the battery load is described. There is shown the procedure of expertise planning to appointment of the regression model coefficients. An attempt of model verification was made using the designation regression model. It is shown that an appropriately planned experiment allows a significant reduction in working time necessary to performing the research leading to determine coefficients of the linear model describing the relationships between variables, mainly by minimizing the number of necessary measurements (experience). It was also shown that despite a limited number of experiments is preserved the linear structure of the designated model.