The identification and classification of accident black spots on urban roads is a key element of road safety research. To solve the problems caused by the randomness of accident occurrences and the ...unclear classification of accident black spots by the traditional model, we propose a method that can quickly identify and classify accident black spots on urban roads: a combined grey Verhuls–Empirical Bayesian method. The grey Verhuls model is used to obtain the predicted/expected numbers of accidents at accident hazard locations, and the empirical Bayesian approach is used to derive two accident black spot discriminators, a safety improvement space and a safety index (SI), and to classify the black spots into two, three, four and five levels according to the range of the SI. Finally, we validate this combined method on examples. High-quality and high-accuracy data are obtained from the accident collection records of the Ningbo Jiangbei District from March to December 2020, accounting for 90.55% of the actual police incidents during this period. The results show that the combined grey Verhuls–Empirical Bayesian method can identify accident black spots quickly and accurately due to the consideration of accident information from the same types of accident locations. The accident black point classification results show that the five-level rating of accident black points is most reasonable. Our study provides a new idea for accident black spot identification and a feasible method for accident black spot risk level classification.
Local laser ablation of the cathode of OLEDs has been applied to create a population of pinholes of the same size. This enables the direct comparison at different conditions of black spots and grey ...spots in the emission of OLEDs as a result of water ingress into the device. We confirmed earlier observations on the operational effect of black spot growth as determined in a sequential test on particle induced pinholes. Furthermore, we measured the operational effect in parallel, providing data that are test independent. With the same population of pinholes we studied the operational effect of grey spot growth. The observed larger operational effect of grey spot growth with respect to that of black spot growth is attributed to a lateral flow of protons to the centre of the black spot. In this part of the black spot a depletion region is present which is created by transport of H3O+ to the cathode under the influence of the applied electric field. This proposal is supported by the observation of black and grey spot growth in polymer LEDs on basis of PEDOT:PSS with increased pH.
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•Laser ablation can be used to create a population of pinholes of equal size.•The ratio in black spot size in stress and in shelf (operational effect) increases with the test period.•The operational effect of grey spot growth is much larger than that of black spots.•The larger operational effect of grey spot growth is attributed to lateral proton transport in the PEDOT:PSS layer.
A technique is presented on tracing the sub-micron pinholes that result in black spots in organic light-emitting diodes (OLED) when exposed to ambient atmosphere. The mystery about the type and ...nature of tiny pinholes present in the OLED cathode that allow oxygen and/or moisture ingress in minute quantities causing black spot formation, is clarified. The technique can accurately locate nanodefects or pinholes in the center of black spots of various sizes, even on a centimeter scale. Pinholes in the investigated OLEDs were shown to be caused by different particles originating from various locations in the device stack. Defects in the Ba-Al cathode of a solution processed polymer LED (PLED) and pinholes in the LiF-Al cathode of a thermally evaporated small molecule organic LED (smOLED) were investigated and compared. The technique is a powerful tool for inspection and can, thereby, accelerate the process optimization for OLED fabrication.
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•Laser marking enables sub-micron pinhole detection in the cathode of OLEDs.•FIB/SEM analysis reveals the nature of the particle that creates the pinhole.•The analysis is beneficial to improve the processing of OLEDs.
Key Clinical Message
While the initial lesions of tinea capitis are often overlooked due to their small size and numerous hairs emerging from the follicle, it is crucial not to dismiss the partial ...presence of comma or harpin hairs and black spots.
Several studies have examined a wide range of accident risk factors affecting road safety. The purpose of this study is to examine the main traffic accident factors that affect the severity of road ...segments. The practical objective of the article is to assist specialists in identifying risk patterns both from a spatial and casualty point of view. To achieve the desired goals, accidents of a road network have been analyzed through three major steps; segmentation, black spot identification, and decision analysis. A new spatial clustering methodology has been used to divide accidents into smaller groups (or clusters) based on their spatial aggregations. The spatial characteristics are argued to be an important factor, in revealing the heterogeneity between accident data. Then, the empirical Bayesian has been applied to rank the resulted segments by severity level. During this step, the technique of decision rules has been applied to identify the main contributors to accidents in certain segments. The result shows that there is a significant relationship between the accident severity level and the traffic and geometrical characteristics (i.e. speed limits, average daily traffic, path shape) of road segments. The results also revealed that the closer the road to secure and non-hazardous road environmental conditions, the lower the risk level of the road segment.
Introduction: Currently, spatial and temporal distribution of safety resources in Iran is entirely based on expert opinions, regardless of network priorities. Considering the lack of resources for ...implementing safety treatments, prioritizing unsafe points is an important and complicated issue where the effectiveness of each safety treatment option should be thoroughly investigated. The political, social, and environmental aspects should also be taken into consideration, including social and political pressures and officials talks on less important topics. Obviously, this inappropriate resource allocation poses a serious challenge to the expected goals. In this study, a methodology based on economic and social issues is proposed to optimize the annual budget allocation for eliminating or reducing the risk of accident-prone points. In this methodology, the spatial and temporal distribution of budget is determined using a mathematical model aimed to maximize the benefits of reducing the accidents after deducting the costs of implementing the safety countermeasures. The outputs of this model include the safety countermeasure alternatives and a five-year time schedule for implementing them, or the alternative of no action with regard to budget, social, and judicial constraints. In order to evaluate the proposed method, it is applied to the road network of Iran and the results are compared with those of the conventional method that is currently used for resource allocation in this country. The results show that the proposed method leads to 15% higher benefits compared to the conventional method. Moreover, this method makes 641 safe points, which is about 17% more than the safe points resulted from the existing method. Therefore, the proposed method brings about a safer network as a result of the optimal allocation of available resources.
One of the important issues related to road safety is the continuous monitoring of road conditions with the aim of preserving and maintaining the quality of roads. Considering the increasing use of ...smart phones, a practical solution based on smart phone sensors is proposed in this article to control the safety status of roads. This solution includes the implementation of a centralized traffic information system that monitors the dynamic behavior of vehicles while moving on the roads and collects trip-related information for further processing. To evaluate the system, a 42-kilometer route on a highway in Iran was monitored. A total of 7 parameters comprising speed, three-dimensional instantaneous acceleration and acceleration changes were examined. An event classification approach was adopted to detect accident-black spots based on the pattern of those parameter changes. The classified dataset was trained and modeled using two types of neural network models namely, Multilayer Perceptron (MLP) and Radial Basis Function (RBF). These two neural networks models were trained, tested and validated using MATLAB software and the collected dataset. The predicted error rate was obtained for 700 samples for each output. The mean square error index for RBF and MLP neural networks was obtained as 0.0066 and 0.1399, respectively, indicating acceptable prediction accuracy.
Road segmentation is one of the most important steps in identification of high accident-proneness segments of a road. Based on the ratio of the Potential to Safety Improvement (PSI) along the road, ...the objective of the paper is to propose a novel dynamic road segmentation model. According to the fundamental model assumption, the determined segments must have the same pattern of PSI. Experimental results obtained from implementation of the proposed method took four Performance Measures (PMs) into consideration; namely, Crash Frequency, Crash Rate, Equivalent Property Damage Only, and Expected Average Crash Frequency with Empirical Bayes adjustment into the accident data obtained from Highway 37 located between two cities in Iran. Results indicated the low sensitivity of the method to PMs. In comparison with the real high accident-proneness segments, identified High Crash Road Segments (HCRS) obtained from the model, demonstrated the potential of the method to recognize the position and length of high accident-proneness segments accurately. Based on the road repair and maintenance costs limitation index for safety improvement, in an attempt to compare the proposed method of road segmentation with conventional ones, results demonstrated the efficient performance of the proposed method. So as to identify 20 percent HCRS located on a read, the proposed method showed an improvement of 38 and 57 percent in comparison with the best and worst outcomes derived from conventional road segmentation methods.
When organic light-emitting diodes (OLEDs) are exposed to the ambient atmosphere, water penetration through pinholes in the cathode results in the formation of non-emissive areas (black spots) due to ...local oxidation of the cathode around the pinhole. This degradation effect severely limits the lifetime of OLED devices and requires high performance encapsulation in order to delay its onset. We have investigated the process of degradation of OLED devices by water penetration through cathode pinholes, and have discovered that this is not just a simple oxidation of the cathode occurring as water diffuses within the device. We have observed that other layers within the device interact with the water. In solution processed OLEDs, the hole-injection layer (PEDOT:PSS) absorbs water due to the presence of the PSS acid (formation of H3O+). This results in a slight local reduction of the luminance of the device (grey spot) around the pinhole location and actually a reduction of the cathode black spot growth rate at the pinhole during a shelf lifetime test. When the device is not operated, the PEDOT:PSS layer is acting as a local reservoir for water keeping it away from the cathode and slowing down the cathode degradation. However, when the device is operated, water that is captured by the PEDOT:PSS layer to form H3O+ can be transported to the cathode under the influence of the applied electric field. This then increases the black spot growth rate. Experimental indications for this operational effect are provided by the threshold voltage behaviour of the effect and transient behaviour of the black spot growth after switching off the OLED. Direct evidence for the role of PEDOT:PSS in the operational effect has been provided by Raman Spectroscopy.
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•Black spots in OLEDs with PEDOT:PSS hole-injection layer grow faster during operation than in shelf.•In shelf water penetrating through pinholes is partly captured by PSS to form H3O+.•During operation the applied electric field causes transport of H3O+ to the cathode.•Loss of protons from PSS results in local oxidation of PEDOT, as measured by RAMAN.
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