Background: Estimating intraoperative blood loss can be a difficult task, especially when blood is mostly absorbed by gauze. In this study, we have provided an improved method for estimating blood absorbed by gauze.Objectives: To develop a guide to estimate blood absorbed by surgical gauze.Materials and Methods: A clinical experiment was conducted using aspirated blood and common surgical gauze to create a realistic amount of absorbed blood in the gauze. Different percentages of staining were photographed to create an analogue for the amount of blood absorbed by the gauze.Results: A visual analogue scale was created to aid the estimation of blood absorbed by the gauze. The absorptive capacity of different gauze sizes was determined when the gauze was dripping with blood. The amount of reduction in absorption was also determined when the gauze was wetted with normal saline before use.Conclusions: The use of a visual analoguemayincrease the accuracy of blood loss estimationanddecrease the consequences related to over or underestimation of blood loss.

It is well known that stripping (separation of aggregates and bitumen) is one of the reasons for asphalt-mixture failure in humid conditions. This could be due to moisture diffusion into the asphalt mixtures that is related to bond weakness between aggregate and bitumen in the asphalt mixtures, and consequently, damages the pavement surface. There are several standard laboratory methods for the evaluation of stripping resistance of asphalt mixtures. The modified Lottman indirect tensile test and determination of the TSR parameter is a common method for evaluating stripping resistance of asphalt mixtures. In this study, a method based on image processing is presented to determine the stripping resistance of asphalt mixtures, and a stripping parameter is developed as an indicator for assessing the moisture susceptibility of asphalt mixtures. The specimens in this research were prepared by mixing limestone materials, slag and hydrated lime filler. Comparison between stripping parameter and TSR values showed that the proposed method has sufficient reliability and is suitable for determining the stripping resistance of asphalt mixtures.

Background: Postpartum hemorrhage is a leading cause of maternal morbidity and mortality that is preventive by appropriate estimation of blood loss and its treatment.This study was undertaken to evaluate the accuracy of visual estimation of postpartum hemorrhage by clinicians and co worker who work in the obstetrics department.Methods: In this descriptive observational study, 199 educational/clinical personnel participated who worked in the obstetrics department of 3 training hospital in Mashhad in 2010. First characteristic of their occupation, educational and period of work experience recorded. Then scenes similar of postpartum hemorrhage were rebuilt by using of expired whole blood in five different volume (500, 1000, 1500, 2000, 2500, 3000 cc). Participants looked each scenes and estimated volume and necessary treatment and record in forms. Data were analyzed by SPSS software version 12 and fisher and student tests and relation between accurate volume of hemorrhage and estimated volume and treatment, occupation and experience of participants were determined.Results: Accuracy visual estimation of blood loss in different volume of postpartum hemorrhage was between 14.3% to 52%. There was no significant association between the position of the participants and accuracy of their estimation and proposed treatments. There was no association between the staffs’ work experience and accuracy of their estimation.Conclusion: Visual estimation of blood loss was not accurate in the majority of participants. For prevention of maternal morbidity and mortality education is necessary that to be skilled for accurate estimation of blood loss.

Due to some physiological and physical limitations in the brain and the eye, the human visual system (HVS) is unable to perceive some changes in the visual signal whose range is lower than a certain threshold so-called just-noticeable distortion (JND) threshold. Visual attention (VA) provides a mechanism for selection of particular aspects of a visual scene so as to reduce the computational load on the brain. According to the current knowledge, it is believed that VA is driven by “ visual saliency” . In a visual scene, a region is said to be visually salient if it possess certain characteristics, which make it stand out from its surrounding regions and draw our attention to it. In most existing researches for estimating the JND threshold, the sensitivity of the HVS has been consider the same throughout the scene and the effects of visual attention (caused by visual saliency) which have been ignored. Several studies have shown that in salient areas that attract more visual attention, visual sensitivity is higher, and therefore the JND thresholds are lower in those points and vice versa. In other words, visual saliency modulates JND thresholds. Therefore, considering the effects of visual saliency on the JND threshold seems not only logical but also necessary. In this paper, we present an improved non-uniform model for estimating the JND threshold of images by considering the mechanism of visual attention and taking advantage of visual saliency that leads to non-uniformity of importance of different parts of an image. The proposed model, which has the ability to use any existing uniform JND model, improves the JND threshold of different pixels in an image according to the visual saliency and by using a non-linear modulation function. Obtaining the parameters of the nonlinear function through an optimization procedure leads to an improved JND model. What make the proposed model efficient, both in terms of computational simplicity, accuracy, and applicability, are: choosing nonlinear modulation function with minimum computational complexity, choosing appropriate JND base model based on simplicity and accuracy and also Computational model for estimating visual saliency that accurately determines salient areas, Finally, determine the Efficient cost function and solve it by determining the appropriate objective Image Quality Assessment. To evaluate the proposed model, a set of objective and subjective experiments were performed on 10 selected images from the MIT database. For subjective experiment, A Two Alternative Forced Choice (2AFC) method was used to compare subjective image quality and for objective experiment SSIM and IWSSIM was used. The obtained experimental results demonstrated that in subjective experiment the proposed model achieves significant superiority than other existing models and in objective experiment, on average, outperforms the compared models. The computational complexity of proposed model is also analyzed and shows that it has faster speed than compared models.

The estimation of metallurgical parameters of flotation process from froth visual features is the ultimate goal of a machine vision based control system. In this study, a batch flotation system was operated under different process conditions and metallurgical parameters and froth image data were determined simultaneously. Algorithms have been developed for measuring textural and physical froth features from the captured images. The correlation between the froth features and metallurgical parameters was successfully modeled, using artificial neural networks. It has been shown that the performance parameters of flotation process can be accurately estimated from the extracted image features, which is of great importance for developing automatic control systems.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

Introduction: We designed and implemented a Programmed Learning Simulation (PLS) exercise depicting obstetric scenarios of hemorrhage to train anesthesiologists, ancillary staff, and surgeons to accurately estimate blood loss visually. We then measured the efficacy of this exercise in a clinical setting. Methods: We conducted a prospective study to assess the effect of implementing a PLS exercise on quantification of blood loss in an operative setting. The PLS exercise consisted of 13 simulation stations of varying quantities of simulated blood loss paired with standardized objects of known volume. Eighty-eight individuals participated including attending physicians, residents, medical students, and ancillary staff participated in this study. The PLS was part of regularly scheduled continuing medical education activities,thus, the sampling used was non-randomized convenience method. The percent error was calculated for each of the 13 stations. A subgroup analysis was performed to assess the effect of the years of experience, size of hemorrhage, and occupation on accuracy. Univariate analyses for continuous variables were compared using a one-way ANOVA test. For the comparison of the three groups (years of experience and size of hemorrhage), a p-value of <0. 02 was considered statistically significant and for 5-way comparison (professional grouping) a P<0. 01 was considered significant after application of the Bonferroni correction (α, =0. 05). (Part A). To determine the effect of PLS in a clinical setting, the percent error of blood loss estimation for cesarean deliveries during the two-month period after the PLS exercise was compared to the twomonth period immediately prior to using the student’, s t-test with P<0. 05 as significant (Part B). Statistical analysis was performed using International Business Machine, Statistical Package for the Social Sciences, Version 26. 0 (IBM SPSS). Results: During Part A, the baseline performance of the participants was evaluated during the PLS activity. The PLS data showed no significant difference in absolute value of mean percent error estimation (standard deviation) across professions: student 63. 61% (69. 74), ob/gyn 56. 91% (47. 72), ancillary 62. 15% (77. 90), general/trauma surgeon 66. 70% (65. 06), anesthesia 61. 51% (63. 12). (P=0. 681), or levels of experience 0-5: 62. 21% (60. 06), 6-10 years: 56. 22% (52. 66), greater than 10 years: 61. 89% (71. 89) (P=0. 831). However, mean percent error of estimation was higher when participants estimated smaller samples 77. 7% (104. 73) compared to either medium 56. 8% (49. 06) or large 57. 9% (46. 19) samples (P<0. 001). For Part B, 179 cesarean deliveries occurred during the pre-intervention period and 193 occurred during the postintervention period. Mean error in provider estimation of blood loss significantly improved from 47% (68. 51) pre-intervention to 31% (32. 70) post-intervention (P=0. 009). Conclusion: We believe our described PLS activity was effective in teaching techniques for visual blood loss estimation. This was reflected by improved competency in a clinical setting, demonstrated by more accurate visually estimated blood loss during the period immediately following simulation activity compared to a prior time frame. Further research is needed to assess the impact of simulation activities on patient outcomes, such as utilization of blood products and patient morbidity.