Sharif Digital Repository

Crash forecasting enables safety planners to take appropriate actions before casualty or loss occurs. Identifying and analyzing the attributes influencing forecasting accuracy is of great importance in road crash forecasting. This study aims to model the forecasting accuracy of 31 provinces using their macroeconomic variables and road traffic indicators. Iran's road crashes throughout 2011–2018 are calibrated and cross-validated using the Holt-Winters (HW) forecasting method. The sensitivity of crash forecast reliability is studied by a regression model. The results suggested that the root mean square error (RMSE) of crash prediction increased among the provinces with higher and more variant... 

Our transportation field has recently witnessed an arms race of neural network-based trajectory predictors. While these predictors are at the core of many applications such as autonomous navigation or pedestrian flow simulations, their adversarial robustness has not been carefully studied. In this paper, we introduce a socially-attended attack to assess the social understanding of prediction models in terms of collision avoidance. An attack is a small yet carefully-crafted perturbations to fail predictors. Technically, we define collision as a failure mode of the output, and propose hard- and soft-attention mechanisms to guide our attack. Thanks to our attack, we shed light on the... 

Ionic liquids (ILs) have been considered as a good candidate to be replaced by the conventional solvent in recent years due to their potential consumptions and unique properties. In the present study, artificial neural network was used to predict the ternary viscosity of mixtures containing ILs. A collection of 729 experimental data points were gathered from the previously public shed literatures. Different topologies of a multilayer feed forward artificial neural network (MFFANN) were examined and optimum architecture was determined. Ternary viscosity data from the literature for 5 ILs with 547 data points have been used to train the network. In addition, to differentiate dissimilar... 

This paper presents two effective methods to reduce power consumption of branch target buffer (BTB): 1) the first method is based on storing distance to next branch address in tag array instead of storing whole branch address, 2) the second method is to use a new field in data array of BTB namely Next Branch Distance (NBD) which holds distance of next branch address from current branch address. When a new hit is performed in BTB, based on NBD field, there would be no access through NBD number of instructions, so BTB can be shutdown not to consume power. The new architecture does not impose extra delay and reduction in prediction accuracy. Both methods were implemented and simulated using... 

Background. The Arthritis Impact Measurement Scales 2 (AIMS2) has not been translated and validated for Persian-speaking patients with osteoarthritis of the knee. This was to provide a validated instrument to measure functional disability and health-related quality of life in patients with osteoarthritis of the knee in Iran. The aim of this study was to culturally adapt and validate the AIMS2 for Persian-speaking patients with osteoarthritis of the knee in Iran. Methods. A consecutive sample of patients with knee osteoarthritis were asked to complete the AIMS2, the Short Form Health Survey (SF-36) and four visual analog scales for pain, joint stiffness, patient's and physician's global... 

Water-quality modeling and prediction is a complicated task because of inherent randomness and uncertainties associated with various processes and variables throughout the stream environment and the lack of appropriate data. Hence, the results of mathematical models are always approximate, lying within an uncertainty. This paper describes and demonstrates the application of the U.S. Environmental Protection Agency's water-quality model, QUAL2E-UNCAS, to the Zayandeh-Rood River in Iran. First-order reliability analysis is used to examine the variability of predicted water-quality parameters of total dissolved solids, dissolved oxygen, and biochemical oxygen demand. This analysis also... 

This paper presents two effective methods to reduce power consumption of branch target buffer (BTB): 1) the first method is based on storing distance to next branch address in tag array instead of storing whole branch address, 2) the second method is to use a new field in data array of BTB namely Next Branch Distance (NBD) which holds distance of next branch address from current branch address. When a new hit is performed in BTB, based on NBD field, there would be no access through NBD number of instructions, so BTB can be shutdown not to consume power. The new architecture does not impose extra delay and reduction in prediction accuracy. Both methods were implemented and simulated using... 

The goal of the present study is to predict the formation of solidification induced defects in castings by thermal criteria functions. In a criterion function method, the heat transfer equation is firstly solved, and then the susceptibility of defect formation at every point in the casting is predicted by computing a local function, criterion function, using results of the thermal analysis. In the first part of the paper, some famous criteria functions, in particular, the Pellini and Niyama criteria, are analyzed and their shortcomings are discussed in details. Then, a new criterion function is suggested to decrease the shape-dependency issue of the former criteria. The feasibility of the... 

In recent years, Wireless Ad-hoc networks have been considered as one of the most important technologies. The application domains of Wireless Ad-hoc Networks gain more and more importance in many areas. One of them is controlling and management the packet traffic. In this paper our goal is controlling the performance of every sections of pipeline of the factory by checking network periodically. Along the factory the traffic is modeled with a Poisson process. We present, with obtaining traffic packets at time (t) for each node in Wireless Ad-hoc Network, we can completely train a Neural Network and successfully predict the traffic at time (t+1) for each node. By this way we can recognize the... 

We present a novel corpus for automatic punctuation prediction in persian texts. punctuation prediction is an important task in automatic speech recognition (ASR). The output of ASR systems is typically a raw sequence of words with no punctuation marks; this makes the text difficult or even impossible to make sense of for humans and also for any text processing unit. In this work, we have assembled a state-of-the-art Persian corpus to train and test a punctuation prediction model. To the best of our knowledge, this is the first ever corpus specifically designed for punctuation prediction in Persian texts. The corpus is a modification of a manually part-of-speech (POS) tagged Persian one,...