Probabilistic Crash Prediction and Prevention of Vehicle Crash

Transportation brings immense benefits to society, but it also has its costs. Costs include the cost of infrastructure, personnel, and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. This research aims to predict the probabilistic crash prediction of vehicles using Machine learning due to Natural and Structural reasons by excluding spontaneous reasons, like overspeeding, etc., in the United States. These factors range from weather factors, like Weather Conditions, Precipitation, Visibility, Wind Speed, Wind Direction, Temperature, Pressure and Humidity, to human-made structures, like Road structure factors like Bumps, Roundabouts, No Exit, Turning Loops, Give Away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes in all states collected by the US government. To calculate the probability Multinomial Expected value was used and assigned a classification label as the crash probability. We applied three classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by Natural and structural reasons for the crash. The paper has provided in-depth insights through exploratory data analysis

The effects of diclofenac suppository and intravenous acetaminophen and their combination on the severity of postoperative pain in patients undergoing spinal anaesthesia during cesarean section

Introduction: The main tasks of postoperative care are postoperative pain and complications control which play an important role in accelerating the recovery of patient’s general condition. Aim: This study was performed in order to compare the effects of diclofenac suppository, intravenous acetaminophen and their combination on the severity of postoperative pain in patients undergoing spinal anaesthesia for cesarean section in Sayyad Shirazi teaching Hospital, Gorgon, Iran. Materials and Methods: This was a double-blind clinical trial on 90 patients undergoing cesarean section. The patients were randomly divided into three groups, group A: 100 mg diclofenac suppository, group B: 1000 mg intravenous acetaminophen, group C: 100 mg diclofenac suppository and 500 mg intravenous acetaminophen. The same spinal anaesthesia circumstances were applied for all the participants. At the end of surgery, pain severity was assessed according to VAS scale at different times. Data were then analysed by SPSS 18 statistical software. Results: The mean age of participants was (28.27±6.07). There was significant difference between the mean pain scores of the three groups before the intervention (p=0.018), which was considered as co-variate. This difference was more notable between the combination of acetaminophen - diclofenac group and diclofenac alone. After the intervention, significant difference was observed in mean pain severity between acetaminophen group and the combination group and also between diclofenac and the combination group. During the study, the least mean pain severity was found in the combination group and the highest was observed in the diclofenac group. Conclusion: Results of this study indicates a significant effect of concomitant use of intravenous acetaminophen and diclofenac suppository on pain severity reduction and reducing the need for repeated doses of narcotics and prolonging the postoperative analgesia. © 2016, Journal of Clinical and Diagnostic Research. All rights reserved

Weighted Round Robin Configuration for Worst-Case Delay Optimization in Network-on-Chip

We propose an approach for computing the end-to-end delay bound of individual variable bit-rate flows in a FIFO multiplexer with aggregate scheduling under Weighted Round Robin (WRR) policy. To this end, we use network calculus to derive per-flow end-to-end equivalent service curves employed for computing Least Upper Delay Bounds (LUDBs) of individual flows. Since real time applications are going to meet guaranteed services with lower delay bounds, we optimize weights in WRR policy to minimize LUDBs while satisfying performance constraints. We formulate two constrained delay optimization problems, namely, Minimize-Delay and Multiobjective optimization. Multi-objective optimization has both total delay bounds and their variance as minimization objectives. The proposed optimizations are solved using a genetic algorithm. A Video Object Plane Decoder (VOPD) case study exhibits 15.4% reduction of total worst-case delays and 40.3% reduction on the variance of delays when compared with round robin policy. The optimization algorithm has low run-time complexity, enabling quick exploration of large design spaces. We conclude that an appropriate weight allocation can be a valuable instrument for delay optimization in on-chip network designs

Direct Computation of the Simultaneous Stone-Weierstrass Approximation of a Function and Its Partial Derivatives in Banach Spaces, and Combination with Hermite Interpolation

AbstractWe present a new variant of the simultaneous Stone-Weierstrass approximation of a function and its partial derivatives, when the function takes its values in a Banach space, and provide an explicit and direct computation of this approximation. In the particular case of approximation by means of polynomials, we show that the simultaneous approximation can be required to be exact at a finite number of prescribed points

Analytic height correlation function of rough surfaces derived from light scattering

We derive an analytic expression for the height correlation function of a rough surface based on the inverse wave scattering method of Kirchhoff theory. The expression directly relates the height correlation function to diffuse scattered intensity along a linear path at fixed polar angle. We test the solution by measuring the angular distribution of light scattered from rough silicon surfaces, and comparing extracted height correlation functions to those derived from atomic force microscopy (AFM). The results agree closely with AFM over a wider range of roughness parameters than previous formulations of the inverse scattering problem, while relying less on large-angle scatter data. Our expression thus provides an accurate analytical equation for the height correlation function of a wide range of surfaces based on measurements using a simple, fast experimental procedure.Comment: 6 pages, 5 figures, 1 tabl