Background: Value of Corticosteroid Randomisation after Significant Head Injury (CRASH) prognostic model has not been assessed in children with traumatic brain injury (TBI). This study is designed to examine the value of CRASH model in prediction of 14-day mortality and 6-month unfavourable outcome of pediatric TBI. Materials and Methods: </stron...

market crash is a phenomenon which occurs in stock markets occasionally and leads to loss of the investors’ wealth and assets in a relatively short period of time. therefore, attempts for prediction of this phenomenon are of much importance for the investors, financial institutions and government. to this date, numerous and varied studies have been carried out for predicting and modeling  stock...

introduction: to date, many prognostic models have been proposed to predict the outcome of patients with traumatic brain injuries. external validation of these models in different populations is of great importance for their generalization. the present study was designed, aiming to determine the value of crash prognostic model in prediction of 14-day mortality (14-dm) and 6-month unfavorable ou...

Crash prediction models are used to estimate the number of crashes using a set of explanatory variables. The highway safety community has used modeling techniques to predict vehicle-to-vehicle crashes for decades. Specifically, generalized linear models (GLMs) are commonly used because they can model non-linear count data such as motor vehicle crashes. Regression models such as the Poisson, Zer...

The likelihood of a crash or crash potential is significantly affected by short-term turbulence of traffic flow. For this reason, crash potential must be estimated on a real-time basis by monitoring the current traffic condition. In this regard, a probabilistic real-time crash prediction model relating crash potential to various traffic flow characteristics which lead to crash occurrence, or “c...

Stock price crash risk has a significant impact on investors, creditors, managers, and shareholders, so the prediction of this phenomenon is a very important issue in investment and risk management decisions. This research investigates the effect of business strategy and stock price synchronicity on stock price crash risk. Following Bentley et al.[2], composite strategy score has been used to ...

Road traffic crash is a cause of unnatural death and occupies fifth position in the world as per WHO records. Road crashes in India are alarming in situation while road safety is professionally lacking and politically missing. Hyderabad city, the capital of newly formed Telangana State occupies sixth position in occurrence of road crashes. An attempt is made to understan...

In recent years the development and use of crash prediction models for roadway safety analyses have received substantial attention. These models, also known as Safety Performance Functions (SPFs), relate the expected crash frequency of roadway elements (intersections, road segments, on-ramps) to traffic volumes and other geometric and operational characteristics. A commonly practiced approach f...

Stock price crash risk is a phenomenon in which stock prices are subject to severe negative and sudden adjustments. So far, different approaches have been proposed to model and predict  the  stock price crash risk, which in most cases have been the main emphasis on the factors affecting it, and often traditional methods have been used for prediction. On the other hand, using  Meta Heuristic Alg...

Every year nearly 1.5 million people are dying in traffic collisions around the world, due to unexpected behavior of pedestrians while crossing road. To address this problem an augmentation function for predicting crash risk active pedestrian is proposed. The has several functions like pre-crash scenario, vehicle trajectory, and trajectory. In a Pre-Crash movement such as entering road boundary...