The intelligent estimating of spinal column abnormalities by using artificial neural networks and characteristics vector extracted from image processing of reflective markers

Spinal column abnormities such as kyphosis and lordosis are the most common deformity that normally compare to the standard norms. To classify the subjects into the healthy and abnormal groups based on the angle values of the standard norms, the aim of this study was to use the artificial neural network method as a standard way for realizing the spinal column abnormalities. In this way, 40 male students (26 ± 2 years old, 72 ± 2.5 kg weight, and 169 ± 5.5 cm height) volunteered for this research. The lumbar lordosis and thoracic kyphosis angles were analyzed using an image processing of 13 reflective markers set on the spines process of the thoracic and lumbar spine. Therefore, after analyzing the position of these markers, a characteristic vector was extracted from the lateral side of every subject. The artificial neural network was trained by using the characteristic vector extracted from the labeled image of that person to diagnose abnormalities. The results indicate that the high efficiency of this method as the CCR (train) and CCR (test) was about 96 and 93%, respectively. These results show that the neural network can be considered as a standard way to diagnose the spinal abnormalities. Moreover, the most important benefit of this method is the estimation of spinal column abnormalities without considering intermediate quantities, and also the standard norms of these intermediate quantities can be considered as a non-invasive method.Keywords: Abnormality, spinal column, kyphosis, lordosis, neural network, classificationAfrican Journal of Biotechnology Vol. 12(4), pp. 419-42

Effect of Building Rotation on Thermal Energy Reduction and Total Solar Gain in Tehran Residential Buildings

Decreasing energy consumption is the one of the most important subject. Besides, in any building design, one employs simple techniques such as orientation, shading of windows, color, and vegetation among others, to create comfortable conditions. Accordingly, Total thermal and solar gain and the effective factors on them should be investigated and optimized. The objective of this research was to find out the impact of rotation on total thermal and solar gain which can lead us to achieve less energy-use in Iran. The software used for this research was Grasshopper and Lady Bug and Honey bee plugins. The typical plan without any environment effects was simulated and effect of rotation on total thermal and solar gain was analyzed. The results showed that using south radiation can be helped to decline total thermal and energy consumption. However, solar gain for east and west radiation was in maximum level. Keywords: thermal energy, rotation, energy reduction, building simulation, residential buildin

Analyzing uncertainty in the price of materials and financial risk management strategies

Significant volatility and unprecedented uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs with regards to proper cost estimating and budgeting of transportation projects. Previous studies indicate that owner organizations often overpay for projects under fixed-price contracts that transfer the material price risk to contractors due to increased risk premiums and hidden contingencies in contractors’ submitted bid prices. A common method widely used by state DOTs for handling the issue of extra risk premiums in submitted bid prices and avoiding overpayment to contractors is to offer price adjustment clauses (PACs) in contracts. A PAC is a risk sharing contractual mechanism that guarantees an adjustment in payment to contractors based on the size and direction of the material price change. Although uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs and many transportation agencies utilize PACs to control consequences of material price volatility, there is little knowledge about analyzing uncertainties in the price of asphalt cement and actual performance of PACs. This dissertation aims to analyze uncertainty in the price of asphalt cement and examine performance of PACs in highway construction projects. After a comprehensive review of the existing body of knowledge about uncertainties in the price of critical materials in transportation projects and PACs, time series analysis is conducted and four univariate time series forecasting models are created to forecast future price of asphalt cement. The results of the time series forecasting show that all four time series models can predict the future values of asphalt cement price with proper accuracy but among the four models, the ARIMA and Holt Exponential Smoothing models are the most accurate prediction models with less than 2% error. Then, ARCH/GARCH time series analysis is conducted to quantify and forecast level of uncertainties in the price of asphalt cement. The results of this step can help transportation agencies systematically measure, analyze and forecast the uncertainties in the price of asphalt cement and implement their risk management strategies at the right time. In next step, impacts of offering PACs on submitted bid prices for major asphalt line items are analyzed using multivariate regression analysis. Finally, effects of offering PACs on dispersion of submitted bid prices and number of bidders are analyzed using system monitoring processes.Ph.D

Using Internet-based marketplaces to conduct surveys: an application to airline itinerary choice models

Within the transportation community, there has been increasing interest in using online outsourcing platforms such as Amazon Mechanical Turk (AMT) to conduct surveys. To date, transportation researchers’ use of AMT has been justified based on findings from studies in other fields. That is, to the best of our knowledge, there has been no study that has evaluated how the distribution of responses associated with each question and behavioral model estimated from AMT survey data compares to survey data collected from a traditional platform for a travel behavior application. This paper fills an important gap in the literature by examining (1) whether the distributions of responses from AMT and Qualtrics (a traditional market research firm) respondents are statistically equivalent, and (2) whether itinerary choice models estimated from these two surveys are statistically equivalent? Results show that AMT and Qualtrics respondents reported similar air trip characteristics and were drawn from a similar geographic distribution, but they exhibited distinct sociodemographic characteristics. After controlling for different age distributions in the two datasets, we found that airline itinerary choice models estimated from the AMT and Qualtrics survey data produced similar results, with the key difference related to price sensitivities. Our study provides preliminary evidence on the viability of using AMT and similar online outsourcing platforms for air travel behavior studies

Synthesis, characterization and degradation activity of Methyl orange Azo dye using synthesized CuO/α-Fe2O3 nanocomposite

This study investigated the photo-degradation of methyl orange (MO) as a type of azo dye using a CuO/α-Fe2O3 nanocomposite. A CuO/α-Fe2O3 powder with a crystalline size in the range of 27-49 nm was successfully prepared using simple co-precipitation along with a sonication method. The characterization of the synthesized sample was done via XRD, FE-SEM, EDS, FTIR and DRS analyses. The Tauc equation revealed that the band gap of the nano composite in the direct mood was 2.05 ev, which is in the visible light range. The effect of operating factors containing dye concentration, photocatalyst dosage and pH on dye degradation efficiency was measured. Response Surface Method (RSM) was employed to specify the parameter effects. The photocatalytic activity of the CuO/α-Fe2O3 nanocomposite was evaluated by degradation of MO under visible light irradiation. The results showed that the pH value played a very effective role in the dye degradation process efficiency. Also, the photocatalytic degradation of MO obtained was equal to 88.47% in the optimal values

Using Internet-based marketplaces to conduct surveys:an application to airline itinerary choice models

\u3cp\u3eWithin the transportation community, there has been increasing interest in using online outsourcing platforms such as Amazon Mechanical Turk (AMT) to conduct surveys. To date, transportation researchers’ use of AMT has been justified based on findings from studies in other fields. That is, to the best of our knowledge, there has been no study that has evaluated how the distribution of responses associated with each question and behavioral model estimated from AMT survey data compares to survey data collected from a traditional platform for a travel behavior application. This paper fills an important gap in the literature by examining (1) whether the distributions of responses from AMT and Qualtrics (a traditional market research firm) respondents are statistically equivalent, and (2) whether itinerary choice models estimated from these two surveys are statistically equivalent? Results show that AMT and Qualtrics respondents reported similar air trip characteristics and were drawn from a similar geographic distribution, but they exhibited distinct sociodemographic characteristics. After controlling for different age distributions in the two datasets, we found that airline itinerary choice models estimated from the AMT and Qualtrics survey data produced similar results, with the key difference related to price sensitivities. Our study provides preliminary evidence on the viability of using AMT and similar online outsourcing platforms for air travel behavior studies.\u3c/p\u3

A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk

There is growing interest in using online outsourcing platforms that are part of the “gig economy” to conduct surveys for academic research. This interest has been driven in part by the belief that compared to traditional survey data collection methods, internet-based marketplaces such as Amazon Mechanical Turk (MTurk) enable one to collect survey data cheaper and faster from a larger, more diverse participant pool. However, many have questioned whether models based on survey data from these online marketplaces are similar to models based on survey data from more traditional platforms. To investigate this research question, we used MTurk and Qualtrics (a traditional market research firm) to survey air travelers. Our results showed that MTurk and Qualtrics respondents had distinct socio-demographic characteristics, but we found no statistical evidence for different air trip characteristics. In our data, proportionately more MTurk respondents were in the younger, single, male, and lower-income categories than for Qualtrics respondents. We found that airline itinerary choice models estimated from the MTurk and Qualtrics survey data were similar, with the key difference related to price sensitivities. Although our results provide evidence that MTurk can be used for travel demand modeling applications, we offer words of caution for others planning to conduct surveys in online marketplaces, particularly for those seeking to recruit more than 1000 participants or for those targeting specific geographic areas

A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk

There is growing interest in using online outsourcing platforms that are part of the “gig economy” to conduct surveys for academic research. This interest has been driven in part by the belief that compared to traditional survey data collection methods, internet-based marketplaces such as Amazon Mechanical Turk (MTurk) enable one to collect survey data cheaper and faster from a larger, more diverse participant pool. However, many have questioned whether models based on survey data from these online marketplaces are similar to models based on survey data from more traditional platforms. To investigate this research question, we used MTurk and Qualtrics (a traditional market research firm) to survey air travelers. Our results showed that MTurk and Qualtrics respondents had distinct socio-demographic characteristics, but we found no statistical evidence for different air trip characteristics. In our data, proportionately more MTurk respondents were in the younger, single, male, and lower-income categories than for Qualtrics respondents. We found that airline itinerary choice models estimated from the MTurk and Qualtrics survey data were similar, with the key difference related to price sensitivities. Although our results provide evidence that MTurk can be used for travel demand modeling applications, we offer words of caution for others planning to conduct surveys in online marketplaces, particularly for those seeking to recruit more than 1000 participants or for those targeting specific geographic areas