Improving Traffic Safety And Drivers\u27 Behavior In Reduced Visibility Conditions

This study is concerned with the safety risk of reduced visibility on roadways. Inclement weather events such as fog/smoke (FS), heavy rain (HR), high winds, etc, do affect every road by impacting pavement conditions, vehicle performance, visibility distance, and drivers’ behavior. Moreover, they affect travel demand, traffic safety, and traffic flow characteristics. Visibility in particular is critical to the task of driving and reduction in visibility due FS or other weather events such as HR is a major factor that affects safety and proper traffic operation. A real-time measurement of visibility and understanding drivers’ responses, when the visibility falls below certain acceptable level, may be helpful in reducing the chances of visibility-related crashes. In this regard, one way to improve safety under reduced visibility conditions (i.e., reduce the risk of visibility related crashes) is to improve drivers’ behavior under such adverse weather conditions. Therefore, one of objectives of this research was to investigate the factors affecting drivers’ stated behavior in adverse visibility conditions, and examine whether drivers rely on and follow advisory or warning messages displayed on portable changeable message signs (CMS) and/or variable speed limit (VSL) signs in different visibility, traffic conditions, and on two types of roadways; freeways and two-lane roads. The data used for the analyses were obtained from a self-reported questionnaire survey carried out among 566 drivers in Central Florida, USA. Several categorical data analysis techniques such as conditional distribution, odds’ ratio, and Chi-Square tests were applied. In addition, two modeling approaches; bivariate and multivariate probit models were estimated. The results revealed that gender, age, road type, visibility condition, and familiarity with VSL signs were the significant factors affecting the likelihood of reducing speed following CMS/VSL instructions in reduced visibility conditions. Other objectives of this survey study were to determine the content of messages that iv would achieve the best perceived safety and drivers’ compliance and to examine the best way to improve safety during these adverse visibility conditions. The results indicated that Caution-fog ahead-reduce speed was the best message and using CMS and VSL signs together was the best way to improve safety during such inclement weather situations. In addition, this research aimed to thoroughly examine drivers’ responses under low visibility conditions and quantify the impacts and values of various factors found to be related to drivers’ compliance and drivers’ satisfaction with VSL and CMS instructions in different visibility and traffic conditions. To achieve these goals, Explanatory Factor Analysis (EFA) and Structural Equation Modeling (SEM) approaches were adopted. The results revealed that drivers’ satisfaction with VSL/CMS was the most significant factor that positively affected drivers’ compliance with advice or warning messages displayed on VSL/CMS signs under different fog conditions followed by driver factors. Moreover, it was found that roadway type affected drivers’ compliance to VSL instructions under medium and heavy fog conditions. Furthermore, drivers’ familiarity with VSL signs and driver factors were the significant factors affecting drivers’ satisfaction with VSL/CMS advice under reduced visibility conditions. Based on the findings of the survey-based study, several recommendations are suggested as guidelines to improve drivers’ behavior in such reduced visibility conditions by enhancing drivers’ compliance with VSL/CMS instructions. Underground loop detectors (LDs) are the most common freeway traffic surveillance technologies used for various intelligent transportation system (ITS) applications such as travel time estimation and crash detection. Recently, the emphasis in freeway management has been shifting towards using LDs data to develop real-time crash-risk assessment models. Numerous v studies have established statistical links between freeway crash risk and traffic flow characteristics. However, there is a lack of good understanding of the relationship between traffic flow variables (i.e. speed, volume and occupancy) and crashes that occur under reduced visibility (VR crashes). Thus, another objective of this research was to explore the occurrence of reduced visibility related (VR) crashes on freeways using real-time traffic surveillance data collected from loop detectors (LDs) and radar sensors. In addition, it examines the difference between VR crashes to those occurring at clear visibility conditions (CV crashes). To achieve these objectives, Random Forests (RF) and matched case-control logistic regression model were estimated. The results indicated that traffic flow variables leading to VR crashes are slightly different from those variables leading to CV crashes. It was found that, higher occupancy observed about half a mile between the nearest upstream and downstream stations increases the risk for both VR and CV crashes. Moreover, an increase of the average speed observed on the same half a mile increases the probability of VR crash. On the other hand, high speed variation coupled with lower average speed observed on the same half a mile increase the likelihood of CV crashes. Moreover, two issues that have not explicitly been addressed in prior studies are; (1) the possibility of predicting VR crashes using traffic data collected from the Automatic Vehicle Identification (AVI) sensors installed on Expressways and (2) which traffic data is advantageous for predicting VR crashes; LDs or AVIs. Thus, this research attempts to examine the relationships between VR crash risk and real-time traffic data collected from LDs installed on two Freeways in Central Florida (I-4 and I-95) and from AVI sensors installed on two vi Expressways (SR 408 and SR 417). Also, it investigates which data is better for predicting VR crashes. The approach adopted here involves developing Bayesian matched case-control logistic regression using the historical VR crashes, LDs and AVI data. Regarding models estimated based on LDs data, the average speed observed at the nearest downstream station along with the coefficient of variation in speed observed at the nearest upstream station, all at 5-10 minute prior to the crash time, were found to have significant effect on VR crash risk. However, for the model developed based on AVI data, the coefficient of variation in speed observed at the crash segment, at 5-10 minute prior to the crash time, affected the likelihood of VR crash occurrence. Argument concerning which traffic data (LDs or AVI) is better for predicting VR crashes is also provided and discussed

Real-Time Crash Risk Estimation: Are All Freeways Created Equal?

Underground loop detectors have been recently used by many researchers to investigate the links with real-time crash risk and the traffic data. An issue that has been raised but not explicitly addressed in these studies is how the results from one freeway might transfer to another. This study attempts to look at the relationship between crash risk and real-time traffic variables from a freeway corridor (I4 eastbound in Orlando, FL) and attempts to apply the models to three other freeway corridors (I-4 westbound, and I-95 north and southbound). Traffic data used in the study were collected using loop as well as radar detectors already installed on these freeways. The traffic information was collected for crash as well as random non-crash cases so that a binary classification approach may be adopted. The Random Forest based models provide a list of significant variables based on the mean average reduction in the Gini indices to the overall forest classification. The period between 5-10 minutes before and 10-15 minutes before the crash were taken into consideration to allow for the model to be developed so as to facilitate the issuance of warning in advance. Average occupancy of upstream station and average speed and coefficient of variation of volume for downstream stations were observed to better the classification trees. Application of multilayer perceptron neural network models showed that while the model developed for I-4 corridor works reasonably well for the I-4 westbound data the performance is not as good for the I-95 sections. It indicates that the same model for crash risk identification may only work for corridors with very similar travel patterns. Keywords: Real-time crash risk, transferability, freeway safety, random forest, neural network

Aligning cloud computing security with business strategy

These days, the technological growth in the IT sector is rapid. Cloud computing is also one of the new technologies that have both benefits and limitations. This paper gives an overview of how cloud computing can be helpful for an enterprise. It emphasizes on how cloud computing can be adopted in the IT sector. The paper also discusses the security issues of cloud computing. This article also highlights the issue of data leakage in this technology which faces cloud computing clients. The authors have designed a model to solve this issue through data isolation. A business value will be achieved through the proposed model by aligning the cloud computing security with the business strategy and increase the security procedures to verify the authenticated users through the virtual system

Heteroaromatization with 4-phenyldiazenyl-1-naphthol. Part III: One-pot synthesis and DFT study of 4H-naphthopyran derivatives

A one pot three component reaction of 4-phenyldiazenyl-1-naphthol (1), p-chloro benzaldehyde (2) and malononitrile or ethyl cyanoacetate (3) in ethanol/piperidine under reflux afforded 2-amino-4-(p-chlorophenyl)-6-phenyldiazenyl-4H-naphtho[1,2-b]pyrano-3-carbonitrile (4a) and ethyl 2-amino-4-(p-chlorophenyl)-6-phenyldiazenyl-4H-naphtho[1,2-b]pyrano -3-carboxylate (4b). Structure of these compounds was established on the basis of IR, 1H NMR, 13C NMR, Mass and UV-Vis spectra. Molecular geometry of compounds 4a and b was obtained at B3LYP/6-31+G(d) level. Two tautomers and two conformers were geometrically optimized. The tautomers are separated by about 7.942 kcal/mol while rotational conformers are only separated by 0.511 kcal/mol. Molecular reactivity descriptors including global electrophilicity, hardness, softness and local condensed Fukui functions were computed and discussed. Frontier molecular orbitals (HOMO and LUMO) were also computed

Routine versus selective plasma exchange before thymectomy in myasthenia gravis

Background: Prethymectomy plasma exchange may improve the outcome of surgery; however, the technique is associated with an increased risk of complications. Therefore, the objective of this study was to compare selective versus routine plasma exchange before thymectomy in patients with myasthenia gravis. Method: We conducted a prospective multi-center cohort study to compare two protocols for plasma exchange before thymectomy. We compared the routine plasma exchange in all patients undergoing thymectomy for myasthenia gravis (group I; n= 30) versus selective exchange (Group II; n= 30). Endpoints were the duration of postoperative mechanical ventilation, plasma exchange, and operative complications. Results: There was no difference in age between both groups (30± 10.1 vs. 29± 9.2 years in Group I and II, respectively; p= 0.69). There were 17 females in Group I (56.67%) vs. 16 in group II (53.33%) (p= 0.8). Comorbidities are comparable between groups. All patients preoperative pyridostigmine, and 27 patients (90%) in Group I and 26 patients (87%) in Group II received glucocorticoids. There was no difference in pulmonary function tests between groups. Plasma exchange related complications were not different between groups. Immediate extubation was achieved in 29 patients (97%) in Group II, and after 6 hours in one patient (3.33%). In Group I, 28 patients (93%) extubated immediately, and two patients were ventilated for 7-12 hours. The mean ICU stay was 1.5 days in Group I and 1.4 days in group II (p= 0.615). The mean hospital stay was 8.5 days in Group I and 9.2 days in group II (p= 0.118). There was no significant difference in pathology between groups (p= 0.137). Conclusion: Selective plasma exchange is feasible before thymectomy for myasthenia gravis. Selective plasma exchange may decrease exchange related complications without affecting the operative outcomes

Impersonate affecting users' attitude toward facebook in Egypt

Social networking sites such as Facebook have mushroomed very rapidly. Anyone with an email address can make an account as long as he accepts the terms and conditions of the website regarding privacy. There are several pages of celebrities, public figures and famous personalities being tricked by hackers on the Web. The real problem arises when a subscriber follows the wrong page taking it as real. This study has been done to share the opinions from Facebook account holders. It intends to impart awareness regarding the phenomenon "Impersonation" on Facebook, which means the imposter sending a bad message from another account which made as a real account. This study has been conducted to assess the impersonation on Facebook in the Egyptian context. This study prove, impersonate has a negative impact in the Egyptian society from a sample of 210 respondents by quantitative research. The study shows people has a higher education level, is greater than awareness about the existence of impersonation

Synthesis, reactions and biological evaluation of benzyltriazolophthalazine derivatives

A series of triazolophthalazine derivatives (4-22) were synthesized and characterized. The structures of the newly synthesized compounds were confirmed by spectral data. The newly synthesized compounds were also screened for their antimicrobial activity

Knowledge Transfer Program (KTP) from International Islamic University Malaysia (IIUM): leveraging MyEntrepreneur2Cloud and Network of Mosque (NoM) to obliterate poverty in Malaysia

Poverty is both a social and an economic problem. Eradicating poverty has become the main concern in most developed countries. In this paper, the authors elaborate on how Knowledge Transfer Program (KTP) from International Islamic University Malaysia (IIUM) would support Malaysia to obliterate the poverty. The authors proposed an integrative and collaborative mechanism namely MyEntrepreneur2Cloud which leverage on Quadruple Helix Model (QHM) and Whole of Government (WoG) concepts. Network of Mosque (NoM) concept also introduced in this paper to assist the proposed mechanism in the delivering processes. By leveraging to MyEntrepreneur2Cloud and Network of Mosque (NoM), the authors expect that the poverty in Malaysia can be obliterated