7 research outputs found
Estimating investment value in railway lines reconstruction process
U radu je prikazan prognostiÄki model za procjenu investicijskih vrijednosti rekonstrukcije željezniÄkih pruga izraÄen primjenom umjetnih neuronskih mreža. Cilj izrade modela je poboljÅ”anje efikasnosti i efektivnosti donoÅ”enja odluka o ulaganju u projekte željezniÄke infrastrukture. Prikazan je proces izrade modela i dan je odgovarajuÄi primjer kojim se upuÄuje na moguÄnost primjene modela za eventualne grube i brze procjene investicijskih vrijednosti za rekonstrukciju željezniÄkih pruga s pouzdanoÅ”Äu od 80 do 85 % kada nisu poznati svi ulazni parametri.A prognostic model for estimating investment value of reconstruction of railway lines using artificial neural networks is presented in the paper. The aim of the model is to improve the efficiency and effectiveness of decision making as related to investment in rail infrastructure projects. The model development process is presented and illustrated with an appropriate example, which points to the possibility of using the model for making a rough and rapid assessment of the investment value of railway-lines reconstruction, with a reliability of 80-85% when some input parameters are unknown
Estimating investment value in railway lines reconstruction process
U radu je prikazan prognostiÄki model za procjenu investicijskih vrijednosti rekonstrukcije željezniÄkih pruga izraÄen primjenom umjetnih neuronskih mreža. Cilj izrade modela je poboljÅ”anje efikasnosti i efektivnosti donoÅ”enja odluka o ulaganju u projekte željezniÄke infrastrukture. Prikazan je proces izrade modela i dan je odgovarajuÄi primjer kojim se upuÄuje na moguÄnost primjene modela za eventualne grube i brze procjene investicijskih vrijednosti za rekonstrukciju željezniÄkih pruga s pouzdanoÅ”Äu od 80 do 85 % kada nisu poznati svi ulazni parametri.A prognostic model for estimating investment value of reconstruction of railway lines using artificial neural networks is presented in the paper. The aim of the model is to improve the efficiency and effectiveness of decision making as related to investment in rail infrastructure projects. The model development process is presented and illustrated with an appropriate example, which points to the possibility of using the model for making a rough and rapid assessment of the investment value of railway-lines reconstruction, with a reliability of 80-85% when some input parameters are unknown
The evaluation of alternative solutions for the highway route E-763 Belgrade ā South Adriatic: a case study of Serbia
Projektiranje putova predstavlja složen proces donoÅ”enja odluka Äiji osnovni cilj treba biti realizacija projekta puta i njegova eksploatacija u užem smislu, ali i omoguÄavanje mobilnosti, privrednog razvoja podruÄja i poboljÅ”anje kvaliteta života u Å”irem smislu. Sve ovo zahtjeva sagledavanje i razumijevanje mnogih problema koji su viÅ”ekriterijske prirode i donoÅ”enje odluka u vezi sa tehniÄkim komponentama, ograniÄenjima okruženja i utjecajima na druÅ”tvo. Osnovni cilj rada je da se na realnom primjeru objasni uloga i znaÄaj metoda viÅ”ekriterijskog vrednovanja. Prezentirane su teorijske postavke viÅ”ekriterijskog vrednovanja. Primjenom metode viÅ”ekriterijskog vrednovanja (metoda VIKOR) izvrÅ”eno je rangiranje ponuÄenih alternativnih reÅ”enja trase autoputa E-763 Beograd-Južni Jadran (dionica Požega-Boljare). Rangiranje je izvrÅ”eno na osnovu 12 kriterija koji Äine osnovu vrednovanja svakog alternativnog reÅ”enja. ProraÄun je izveden primjenom programskog paketa VIKOR i izvrÅ”ena je analiza dobivenih rezultata.Designing road projects involves a complex decision-making process whose objectives should be the implementation of the road design and its utilization in the narrowest sense, but also the facilitation of mobility, economic development of the area and improvement of the quality of life in a wider sense. All of this requires the consideration and understanding of many problems multi-criterial in nature, and decision making with regard to technical components, environmental constraints and the impact on society. The main goal of this paper is to use a real example to explain the role and significance of multi-criteria evaluation methods. The theoretical postulates of multi-criteria evaluation are presented (VIKOR method). Using multi-criteria evaluation methods ranking was carried out of the alternative solutions offered for the E-763 highway route Belgrade-South Adriatic (Požega-Boljare section). Ranking was carried out on the basis of 12 criteria which form the basis for evaluating each of the alternative solutions. The calculation was performed using the VIKOR program packages and an analysis of the results obtained was carried out
Decision-Support System for Estimating Resource Consumption in Bridge Construction Based on Machine Learning
The paper presents and analyzes the state-of-the-art machine learning techniques that can be applied as a decision-support system in the estimation of resource consumption in the construction of reinforced concrete and prestressed concrete road bridges. The formed database on the consumption of concrete in the construction of bridges, along with their project characteristics, was the basis for the formation of the assessment model. The models were built using information from 181 reinforced concrete bridges in the eastern and southern branches of Corridor X in Serbia, with a value of more than 100 million euros. The application of artificial neural network models (ANNs), models based on regression trees (RTs), models based on support vector machines (SVM), and Gaussian processes regression (GPR) were analyzed. The accuracy of each model is determined by multi-criterion evaluation against four accuracy criteria root mean square error (RMSE), mean absolute error (MAE), Pearsonās linear correlation coefficient (R), and mean absolute percentage error (MAPE). According to all established criteria, the model based on GPR demonstrated the greatest accuracy in calculating the concrete consumption of bridges. According to the study, using automatic relevance determination (ARD) covariance functions results in the most accurate and optimal models and also makes it possible to see how important each input variable is to the modelās accuracy
Bone microRNA-21 as surgical stress parameter is associated with third molar postoperative discomfort
Objective: To evaluate an association between bone levels of inflammation/oxidative stress mediators and postoperative discomfort after third molar conventional or piezosurgery. Material and methods: Twenty-six subjects with bilaterally impacted mandibular third molars, who underwent either piezo or conventional surgery, were included in a split-mouth design study. MicroRNA-21 (miR-21) expression, interleukin-1 beta (IL-1Ī²), and vascular endothelial growth factor (VEGF) proteins, as well as superoxide dismutase (SOD) activity in alveolar bone, were evaluated. Pain intensity, the first pain appearance, analgesic first use and total dose taken, trismus, and swelling were clinically recorded. Results: MiR-21 expression was higher while VEGF protein was lower in piezosurgery vs. conventional groups. The differences in IL-1Ī² protein and SOD activity were not significant between groups. The pain intensity on the first day was significantly decreased in piezosurgery group. The first pain appearance and the first analgesic taken were reported sooner in conventional vs. piezosurgical group. Significantly pronounced trismus on the third day following conventional surgery was found. In conventional group, significantly increased trismus was observed on the third compared to the first postoperative day. MiR-21 showed significant correlation with the first pain appearance. Conclusion: Delayed onset of less pronounced postoperative pain after piezosurgical vs. conventional extraction of impacted lower third molar was significantly associated with expression of bone miR-21. Clinical relevance: Alveolar bone miR-21 may reflect surgical stress and is associated with third molar postoperative pain onset
An attempt to create a standardized (reference) model for experimental investigations on implant's sample
The aim of this study was to determine, evaluate and measure strain of vertically loaded implant using the digital image correlation method. The Straumann (R) dental implant system with the SLActive (R) surface was used in this study. Implant was immersed in poly-methyl-methacrylate during his hardening process. After preparation procedure a sample of implant and poly-methyl-methacrylate was obtained. This sample was loaded using external load from 0 to 400 N. Maximum strain in the 4 mm surface layer was 0.30% whereas maximum strain in the 6 mm surface layer (opposite side) was 0.20%, detected in the marginal and apical part of implant-poly-methyl-methacrylate sample. Minimum strain measured by Aramis software was 0.01%, detected in the 4 mm surface layer. According to results obtained by Aramis data processing, the 4 mm surface layer indicated higher overall strain in apical direction with the strains of 0.18-0.21%. Increasing the load did not affect the value of maximum strain however, higher load influenced the overall strain concentration increased especially in marginal and apical part of the sample surfaces that surrounded lateral sides of implant body
An attempt to create a standardized (reference) model for experimental investigations on implant's sample
The aim of this study was to determine, evaluate and measure strain of vertically loaded implant using the digital image correlation method. The Straumann (R) dental implant system with the SLActive (R) surface was used in this study. Implant was immersed in poly-methyl-methacrylate during his hardening process. After preparation procedure a sample of implant and poly-methyl-methacrylate was obtained. This sample was loaded using external load from 0 to 400 N. Maximum strain in the 4 mm surface layer was 0.30% whereas maximum strain in the 6 mm surface layer (opposite side) was 0.20%, detected in the marginal and apical part of implant-poly-methyl-methacrylate sample. Minimum strain measured by Aramis software was 0.01%, detected in the 4 mm surface layer. According to results obtained by Aramis data processing, the 4 mm surface layer indicated higher overall strain in apical direction with the strains of 0.18-0.21%. Increasing the load did not affect the value of maximum strain however, higher load influenced the overall strain concentration increased especially in marginal and apical part of the sample surfaces that surrounded lateral sides of implant body