High resolution real time ultrasonography is a non - invasive, simple, and safe and has a high degree of accuracy for measurement of spinal canal diameter.Also diagnostic ultrasound can demonstrate the degree and extent of bony spinal canal steno sis. It may have value in preventive medicine, identifying the subject at risk. Measurement with this technique on segments of lumbar spinal canal revealed that the ultrasound echoes originated from boundaries between the dural sac and the surrounding tissues at the level of intervertebral disc.The width of lumbar spinal canal as reflected by the ultrasonic echoes was about one millimeter less than the normal width of the dural sac.The aim of this study was to find out the normal sagital and coronal lumbar spinal canal diameter. For this purpose research was conducted on the 400 patients, and carried out from (May 1998) through (sep. 1999) that referred for abdominopelvic ultrasonography to no I hospital of Kerman University of Medical Sciences and Health Services.A prospective cross - sectional and continuative study was done. In the research 182 female (45.8%) and 218 were male (54.2%). The mean sagital and coronal spinal canal diameter at (L4-L5) disc space level was (11.7+2 mm) and (15±2.8 mm) respectively.The mean sagital and coronal spinal canal diameter at (LS-S1) level was (11.7±2.1 mm) and (16±2.8mm) respectively. The significant difference between male and female was only at coronal diameter of (L5-S1).

Soil texture is variable through space and controls most of the soil’s Physico-chemical, biological and hydrological characteristics and governs agricultural production and yield. Therefore, determining its variability and generating accurate soil texture maps have a key role in soil management and sustainable agriculture. The purpose of this study is to introduce a numerical algorithm named Least Square Support Vector Machine for Regression (LS-SVR) as a predictive model in Digital Soil Mapping (DSM) of soil texture fractions and evaluating its performances based on modeling evaluation criteria. In this study, the soil texture data of 49 soil profiles in Tabriz plain, Iran, was used. The important covariates were selected using Genetic Algorithm (GA). The model evaluation results based on ME, MAE, RMSE, and R2 indicate the high performance of LS-SVR in predicting soil texture components. The prediction RMSE for sand, silt, and clay was 6.82, 5.08 and 6.06, respectively. Silt prediction had the highest ME and the lowest MAE and RSME values. The algorithm simulated the complex spatial patterns of soil texture fractions and provided high accuracy predictions and maps. Therefore, the LS-SVR algorithm has the capability to be used as predictive models in soil texture digital mapping. This study highlighted the potential of the LS-SVR algorithm in high precision s

Let Gk, n be the Grassmann manifold of k-planes in Rn+k. The Lusternik-Schnirelmann category and topological complexity are important invariants of topological spaces. In this note we calculate the Lusternik-Schnirelmann category and topological complexity of cer-tain products of Grassmannian manifolds by using cup and zero-cup length. Also we will , nd the lower and upper bounds of the topological complexity of some Grassmannian manifolds by the same method.

In this research, several different types of geometries have been compared to prevent the influence of an explosion wave on the glasses of the APCs. This was done using validation and then using LS-DYNA software. Pre and post-processing was done in LS-PrePost software. So, a mathematical function in this software was used to generate the pressure of the wave on the structure. In order to compare, the displacement parameter was used and the minimum total displacement of the structure as a criterion for optimal performance was considered. Also, two types of cosine curves, two types of polynomial curves (third and fourth order) and a flat blade are investigated. The results showed that for the use of a 150*100 mm2 square flat blade (which is half simulated according to the model's symmetry), the explosion of a wave coming from a distance of 75 mm on the adjacent sheet requires a sheet with a thickness of 11 mm. Using a curved blade, this thickness is reduced to 3 mm. According to the recent issue, the use of curved blades will lead to a sharp decrease in the weight of armored equipment.

In this research work, two machine learning models including Least Squares Support Vector Machines (LS-SVR) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to predict the scour depth around the bridge piers. For this purpose, 240 data series including pier geometry, flow condition, sediment characteristics, and some dimensional parameters were used. Dimensional and no dimensional parameters were considered. The performance of the models was evaluated using root mean square error (RMSE), mean absolute percentage error (MAPE), and Nash–Sutcliffe efficiency (NSE) criteria. The results showed that in both models, the use of dimensional parameters for prediction leads to high prediction accuracy. The comparison between the models also showed that the LS-SVR algorithm with the criteria RMSE=46.84, MAPE=38.03, NSE=0.62 for the test data of the first model and RMSE=28.62, MAPE=38.97, NSE=0.67 for the test data results of the second pattern are more accurate than the ANFIS algorithm. This research indicates that machine learning models are a suitable alternative to empirical models in predicting scour depth of bridge piers.

Introduction: In Vietnam, the prevalence of hypertension is increasing rapidly. Patients need to be conscious of the disease for timely prevention and treatment. The Hypertension Knowledge Level Scale (HK-LS) is commonly used to assess knowledge about hypertension. Methods: Data collection was took place in a hospital in Binh Thuan province, Vietnam in February 2020 with a total of 184 paticipants. Translation and adaptation of the HK-LS, validate the questionnaire through in-person interviews with outpatients diagnosed with hypertension. The translation process followed WHO guidelines. The appraisal process evaluates through reliability (Cronbach’s alpha coefficient) and validity (meaningful relationship between the response results of the scale and the patient’s characteristics). Results: The Vietnamese version of the HK-LS was translated and proven to be reliable (Cronbach’s alpha=0. 72) and valid (statistically significant difference between age groups (P=0. 021) and educational background (P=0. 007). Conclusion: The HK-LS was translated from English into Vietnamese,the questions are clear, intelligible, and suitable for surveying patients in Vietnam.

A method based on Electrical Capacitance Tomography (ECT) and an improved Least Squares Support Vector Machine (LS-SVM) is proposed for void fraction measurement of oil-gas two-phase flow. In the modeling stage, to solve the two problems in LS-SVM, pruning skills are employed to make LS-SVM sparse and robust; then the Real-Coded Genetic Algorithm is introduced to solve the difficult problem of parameters selection in LS-SVM then. In the measurement process, the flow pattern of oil-gas two-phase flow is identified by using fast back-projection image reconstruction and a fuzzy pattern recognition technique and the void fraction is computed using the void fraction model corresponding to the identified flow pattern. Experimental results demonstrate that both the improvement of LS-SVM and the parameter optimization are effective. The results also show that the real-time performance of the proposed void fraction measurement method is good, and the measurement precision can satisfy the application requirement.