Recognizing vehicle plate numbers is a key step towards implementing the legislation on traffic and reducing the number of daily traffic accidents. Although machine learning has advanced considerably, the recognition of license plates remains an obstacle, particularly in countries whose plate numbers are written in different languages or blended with Latin alphabets. This paper introduces a recognition system for Arabic and Latin alphabet license plates using a deep-learning-based approach in conjugation with data collected from two specific countries: Iraq and Malaysia. The system under study is proposed to detect, segment, and recognize vehicle plate numbers. Moreover, Iraqi and Malaysian plates were used to compare these processes. A total of 404 Iraqi images and 681 Malaysian images were tested and used for the proposed techniques. The evaluation took place under various atmospheric environments, including fog, different contrasts, dirt, different colours, and distortion problems. The proposed approach showed an average recognition rate of 85.56% and 88.86% on Iraqi and Malaysian datasets, respectively. Thus, this evidences that the deep-learning-based method outperforms other state-of-the-art methods as it can successfully detect plate numbers regardless of the deterioration level of image quality.
A case of non-fatal strangulation of the neck by rigging lines of a parachute during military training is presented. It is an unusual but potentially life-threatening injury. Probable factors leading to such injury are discussed.
The Publisher regrets that this article is an accidental duplication of an article that has already been published, doi:10.1016/j.micpath.2012.05.010;. The duplicate article has therefore been withdrawn.
Safety Intervention Need Analysis System (SINAS) is a web-based safety management program that aspires the identification for the need of construction safety intervention. It can be accessed through the website www.sinas.org. This first phase of SINAS project development only focus on safe design intervention. SINAS was created to provide assistance for safety practitioners in identifying the need of safe design intervention. This was put forward through the investigations of construction accidents that relate to design. The SINAS process of need analysis are carved up to six steps i.e. user information, accident details, accident evaluation, result of the need analysis, construction design intervention and safety intervention need analysis report. At the end of the process, Safety Intervention Need Analysis Report will be generated. This report is an essential document to proof the need of safe design intervention. Additionally, SINAS also offers recommendations for construction designers and professionals on suitable safe design intervention to prevent construction accidents and minimises construction risks.
frequency of motorcycle accidents increases every year. In Syarikat Bekalan Air Selangor (SYABAS), a substantial number of motorcycle accidents occurred between the year 2009 and 2013. The increased number of accidents serves as a wake-up call to the company to come up with a behavioural-based safety system for commuting accident. The objective of this paper is to look into the effectiveness of behavioural-based system in a company. A total of one hundred and thirty (130) respondents participated in the data-collection session for this study. From this data-collection, along with accident data from the company, a number of criteria that contributes to commuting accidents in the company is obtained. At the end of this study, the behavioural-based safety system is applied, thus showing how its implementation assists in curbing the issue of commuting accidents in the company.
Internet of Things (IoT) and 5G are enabling intelligent transportation systems (ITSs). ITSs promise to improve road safety in smart cities. Therefore, ITSs are gaining earnest devotion in the industry as well as in academics. Due to the rapid increase in population, vehicle numbers are increasing, resulting in a large number of road accidents. The majority of the time, casualties are not appropriately discovered and reported to hospitals and relatives. This lack of rapid care and first aid might result in life loss in a matter of minutes. To address all of these challenges, an intelligent system is necessary. Although several information communication technologies (ICT)-based solutions for accident detection and rescue operations have been proposed, these solutions are not compatible with all vehicles and are also costly. Therefore, we proposed a reporting and accident detection system (RAD) for a smart city that is compatible with any vehicle and less expensive. Our strategy aims to improve the transportation system at a low cost. In this context, we developed an android application that collects data related to sound, gravitational force, pressure, speed, and location of the accident from the smartphone. The value of speed helps to improve the accident detection accuracy. The collected information is further processed for accident identification. Additionally, a navigation system is designed to inform the relatives, police station, and the nearest hospital. The hospital dispatches UAV (i.e., drone with first aid box) and ambulance to the accident spot. The actual dataset from the Road Safety Open Repository is used for results generation through simulation. The proposed scheme shows promising results in terms of accuracy and response time as compared to existing techniques.
Oil spills are environmental pollution events that occur due to natural disasters or human activities, resulting in a liquid petroleum hydrocarbon release in the environment, especially into the marine ecosystem. Once oil spills happen, they cause detrimental consequences to the environment, living organisms, and humans. Although there are increasing oil and gas activities in the Arctic region, which is abundant with undiscovered oil and gas resources, the harsh environmental conditions of the region, such as the ice coverage, cold temperatures, long periods of darkness, and its remoteness, pose significant challenges to managing the risk of accidental oil spills in ice-infested waters. In this paper, a bibliometric analysis has been applied to study the global work on oil spill research in ice-infested waters. The paper aims to present an overview of the available oil spill response methods in ice-infested waters, identify the current trends of the research on oil spills in ice-infested waters, and determine the challenges with the future research directions based on the bibliometric analysis. The analysis includes a total number of 77 articles that have been published in this research field which were available in the Scopus database, involving 193 authors from 17 countries dating from 1960 to September 2022. During the bibliometric analysis, the top five most productive authors and countries as well as the most cited publications on oil spills in ice-infested waters have been identified; the authors' cooperation network and the cooperation network between the countries in oil spills research in ice-infested waters have been created; a co-citation analysis and a terms analysis have been performed to identify the popular terms and topics. For future directions, it is recommended for researchers (1) to study real oil spills as much as possible to obtain a good overview through replication under different situations; (2) to develop a new technique for the careful examination and management of the potential risks; (3) to study oil separation from the recovered oil-ice mixture.
Many major accidents due to toxic release in the past have caused many fatalities such as the tragedy of MIC release in Bhopal, India (1984). One of the approaches is to use inherently safer design technique that utilizes inherent safety principle to eliminate or minimize accidents rather than to control the hazard. This technique is best implemented in preliminary design stage where the consequence of toxic release can be evaluated and necessary design improvements can be implemented to eliminate or minimize the accidents to as low as reasonably practicable (ALARP) without resorting to costly protective system. However, currently there is no commercial tool available that has such capability. This paper reports on the preliminary findings on the development of a prototype tool for consequence analysis and design improvement via inherent safety principle by utilizing an integrated process design simulator with toxic release consequence analysis model. The consequence analysis based on the worst-case scenarios during process flowsheeting stage were conducted as case studies. The preliminary finding shows that toxic release consequences analysis tool (TORCAT) has capability to eliminate or minimize the potential toxic release accidents by adopting the inherent safety principle early in preliminary design stage.
Lower limb injuries are the main cause of temporary and permanent disability among motorcyclists in Malaysia. They cause non-fatal but serious injuries requiring hospitalisation. Detailed studies on factors influencing lower limb injuries are justified in an attempt to reduce the occurrence of these injuries. This study presents a computer simulation of the crash behaviour of the basket of a small-engined motorcycle with the lower limb using finite element (FE) methods. The results suggest that the extensive deformation of the motorcycle basket may reduce the risk of injury to the lower limb. The behaviour of the basket during collision is analogous to the crumple zone of automobiles.
Most of the decisions taken to improve road safety are based on accident data, which makes it the back bone of any country's road safety system. Errors in this data will lead to misidentification of black spots and hazardous road segments, projection of false estimates pertinent to accidents and fatality rates, and detection of wrong parameters responsible for accident occurrence, thereby making the entire road safety exercise ineffective. Its extent varies from country to country depending upon various factors. Knowing the type of error in the accident data and the factors causing it enables the application of the correct method for its rectification. Therefore there is a need for a systematic literature review that addresses the topic at a global level. This paper fulfils the above research gap by providing a synthesis of literature for the different types of errors found in the accident data of 46 countries across the six regions of the world. The errors are classified and discussed with respect to each type and analysed with respect to income level; assessment with regard to the magnitude for each type is provided; followed by the different causes that result in their occurrence, and the various methods used to address each type of error. Among high-income countries the extent of error in reporting slight, severe, non-fatal and fatal injury accidents varied between 39-82%, 16-52%, 12-84%, and 0-31% respectively. For middle-income countries the error for the same categories varied between 93-98%, 32.5-96%, 34-99% and 0.5-89.5% respectively. The only four studies available for low-income countries showed that the error in reporting non-fatal and fatal accidents varied between 69-80% and 0-61% respectively. The logistic relation of error in accident data reporting, dichotomised at 50%, indicated that as the income level of a country increases the probability of having less error in accident data also increases. Average error in recording information related to the variables in the categories of location, victim's information, vehicle's information, and environment was 27%, 37%, 16% and 19% respectively. Among the causes identified for errors in accident data reporting, Policing System was found to be the most important. Overall 26 causes of errors in accident data were discussed out of which 12 were related to reporting and 14 were related to recording. "Capture-Recapture" was the most widely used method among the 11 different methods: that can be used for the rectification of under-reporting. There were 12 studies pertinent to the rectification of accident location and almost all of them utilised a Geographical Information System (GIS) platform coupled with a matching algorithm to estimate the correct location. It is recommended that the policing system should be reformed and public awareness should be created to help reduce errors in accident data.
Blood alcohol levels from 155 UKM forensic postmortem cases of various causes of death from August 1988 to mid-September 1989 were studied. 59 cases (38%) were related to fatal road traffic accidents. 13 of these 59 cases (22%) showed blood alcohol levels of more than 50 mg/dl. 11 of these 13 cases (84.6%) revealed blood alcohol levels of more than 100 mg/dl after correction. Further analysis showed 53.8% were Indian, 76.9% aged between 20 and 40 years, 84.6% of the accidents occurred between 8.00 p.m. and 4.00 a.m. and all the alcohol related fatal road traffic accident victims studied in this series were males. This study provides helpful information.
This paper focuses on the study of the change of various types of riding behaviour, such as speed, brake force, and throttle force applied, when they ride across the speed table. An instrumented motorcycle equipped with various types of sensor, on-board camera, and data logger was used in acquiring the traffic data in the research. Riders were instructed to ride across two speed tables and the riding data were then analyzed to study the behaviour change from different riders. The results from statistical analysis showed that the riding characteristics such as speed, brake force, and throttle force applied are influenced by distance from hump, riding experience, and travel mileage of riders. Riders tend to apply higher brake intensity at distance point 50 m before the speed table and release the braking at point -10 m after the hump. In short, speed table has different rates of influence towards riding behaviour on different factors, such as distance from hump and different riders' attributes.