Search results for: road safety rating

Authors: David Nkurunziza, Rahman Tafahomi

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The population growth rate of the city of Kigali is increasing annually. In 1960 the population was six thousand, in 1990 it became two hundred thousand and is supposed to be 4 to 5 million incoming twenty years. With the increase in the residents living in the city of Kigali, there is also a need for an increase in social and economic infrastructures connected by the road networks to serve the residents effectively. A road network is a route that connects people to their needs and has to facilitate people to reach the social and economic facilities easily. This research analyzed the social and economic aspects of three selected roads networks passing through all three districts of the city of Kigali, whose center is the city center roundabout, thorough evaluation of the proximity of the social and economic facilities to the road network. These road networks are the city center to nyabugogo to karuruma, city center to kanogo to Rwanda to kicukiro center to Nyanza taxi park, and city center to Yamaha to kinamba to gakinjiro to kagugu health center road network. This research used a methodology of identifying and quantifying the social and economic facilities within a limited distance of 300 meters along each side of the road networks. Social facilities evaluated are the health facilities, education facilities, institution facilities, and worship facilities, while the economic facilities accessed are the commercial zones, industries, banks, and hotels. These facilities were evaluated and graded based on their distance from the road and their value. The total scores of each road network per kilometer were calculated and finally, the road networks were ranked based on their percentage score per one kilometer—this research was based on field surveys and interviews to collect data with forms and questionnaires. The analysis of the data collected declared that the road network from the city center to Yamaha to kinamba to gakinjiro to the kagugu health center is the best performer, the second is the road network from the city center to nyabugogo to karuruma, while the third is the road network from the city center to kanogo to rwandex to kicukiro center to nyaza taxi park.

Keywords: social economical aspect, road network functionality, urban road network, economic and social facilities

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Authors: Rania Alshikhe, Vinita Jindal

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Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

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Authors: Jane E. Mullen, Kevin Kelloway, Ann Rhéaume-Brüning

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The purpose of this study is to examine the effects of perceived leader word-action alignment on subordinate extra-role safety behavior. Using survey data gathered from a sample of nurses employed in health care facilities located in Eastern Canada (n = 192), the effects of perceived word-action alignment (measured as the cross product of leaders speaking positively about safety and acting safely) on nurse safety participation was examined. Moderated regression analysis resulted in the significant (p < .01) prediction of nurse safety participation by the interaction term. Analysis of the simple slopes comprising the interaction term suggests that positively speaking about safety only predicted safety participation when leaders were also perceived by subordinates as acting safely. The results provide empirical support for the importance of the perceived alignment between leaders’ words, or espoused safety values and priorities, and their actions. Practical implications for safety leadership training are discussed.

Keywords: leadership, safety participation, safety performance, safety training

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Authors: Sandy J. M. Balla, Jerry J. Walker, Isaac K. Kyere

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The heat transfer coefficient at the soil–air interface is important in calculating underground cable ampacity when convection occurs. Calculating the heat transfer coefficient accurately is complex because of the temperature variations at the earth's surface. This paper presents the effect of convection heat flow across the ground surface on the rating of three single-core, 132kV, XLPE cables buried underground. The Finite element method (FEM) is a numerical analysis technique used to determine the cable rating of buried cables under installation conditions that are difficult to support when using the analytical method. This study demonstrates the use of FEM to investigate the effect of convection on the rating ofburied cables in flat formation using QuickField finite element simulation software. As a result, developing a model to simulate this type of situation necessitates important considerations such as the following boundary conditions: burial depth, soil thermal resistivity, and soil temperature, which play an important role in the simulation's accuracy and reliability. The results show that when the ground surface is taken as a convection interface, the conductor temperature rises and may exceed the maximum permissible temperature when rated current flows. This is because the ground surface acts as a convection interface between the soil and the air (fluid). This result correlates and is compared with the rating obtained using the IEC60287 analytical method, which is based on the condition that the ground surface is an isotherm.

Keywords: finite element method, convection, buried cables, steady-state rating

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Authors: Elbert S. Moyon, Edsel Matt O. Morales, Jaymer M. Jayoma, Kent C. Espejon, Jayson C. Dollete, Mark Phil B. Pacot

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This research paper focuses on the potential of using Web-GIS technology in prioritizing farm-to-market road projects by the Philippines’ Department of Agriculture (DA). The study aimed to explore the benefits of Web-GIS in addressing the limitations faced by the DA in terms of Farm to Market Road profiling and project prioritization, which include a lack of access to updated data, limited spatial analysis capabilities, and difficulties in sharing information between stakeholders. The research methodology involves a comprehensive literature review and a case study of a Web-GIS application developed for the DA, which was used to profile and prioritize farm-to-market road projects in the Philippines. The results showed that the Web-GIS technology provides the DA with an effective tool for analyzing and visualizing data, which can help in profiling and prioritizing road projects based on various criteria such as economic, social, and environmental impacts. The study also showed that Web-GIS technology could help in reducing the time and effort required for road project prioritization and improve communication between stakeholders.

Keywords: GIS, web application, farm-to-market road, FMR prioritization, Django, GeoServer

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Authors: Amrutha Venugopal, Rabee Rustum

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In spite of huge investments and the vital role infrastructure plays in the economy of UAE, the country has not yet developed an assessment scheme to measure the sustainability of infrastructure projects/development. The aim of this study was to develop a sustainability rating system for infrastructure projects in UAE using weighted indicator scoring. The identification of the list of 66 indicators was done by content analysis. The sources of content analysis were from government guidelines, research literature and sustainability rating system for infrastructure projects namely BCA Greenmark for Infrastructure (Singapore), ISCA (Australia) and Envision (USA). These indicators were shortlisted based on their relevance in the UAE. A mixture of qualitative and quantitative research methods is utilized to find the weightage to be applied to the indicators and to find suggestive measures to improve infrastructure sustainability in this region. Interviews and surveys were conducted with a good mix of experts from the industry. The data collected from the interviews were collated to provide suggestive measures for improving infrastructure sustainability. The collected survey data were analyzed using statistical analysis techniques to find the indicator weighing. The indicators were shortlisted by 75% to minimize the effort and investment into the process. The weighing of the deleted indicators was distributed among the critical clusters identified by Pareto analysis. Finally a simple Microsoft Excel tool was developed as the rating tool by using the calculated weighing for the indicators.

Keywords: infrastructure, rating system, suggestive measures, sustainability, UAE

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: V. A. Dubovsky, V. V. Savchenko, A. A. Baryskevich

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The current trend in the automotive industry towards automatic vehicles is creating new challenges related to human factors. This occurs due to the fact that the driver is increasingly relieved of the need to be constantly involved in driving the vehicle, which can negatively impact his/her situation awareness when manual control is required, and decrease driving skills and abilities. These new problems need to be studied in order to provide road safety during the transition towards self-driving vehicles. For this purpose, it is important to develop an appropriate conceptual model of the interaction between the driver and the automated vehicle, which could serve as a theoretical basis for the development of mathematical and simulation models to explore different aspects of driver behaviour in different road situations. Well-known driver behaviour models describe the impact of different stages of the driver's cognitive process on driving performance but do not describe how the driver controls and adjusts his actions. A more complete description of the driver's cognitive process, including the evaluation of the results of his/her actions, will make it possible to more accurately model various aspects of the human factor in different road situations. This paper presents a conceptual model of the 'driver – highly automated vehicle' system based on the P.K. Anokhin's theory of functional systems, which is a theoretical framework for describing internal processes in purposeful living systems based on such notions as goal, desired and actual results of the purposeful activity. A central feature of the proposed model is a dynamic coupling mechanism between the decision-making of a driver to perform a particular action and changes of road conditions due to driver’s actions. This mechanism is based on the stage by stage evaluation of the deviations of the actual values of the driver’s action results parameters from the expected values. The overall functional structure of the highly automated vehicle in the proposed model includes a driver/vehicle/environment state analyzer to coordinate the interaction between driver and vehicle. The proposed conceptual model can be used as a framework to investigate different aspects of human factors in transitions between automated and manual driving for future improvements in driving safety, and for understanding how driver-vehicle interface must be designed for comfort and safety. A major finding of this study is the demonstration that the theory of functional systems is promising and has the potential to describe the interaction of the driver with the vehicle and the environment.

Keywords: automated vehicle, driver behavior, human factors, human-machine system

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: Wen-Chen Hwang, Yu-Hsi Yuan

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According to the estimation made by researchers of safety and hygiene, 80% to 90% of workplace accidents in enterprises could be attributed to human factors. Nevertheless, human factors are not the only cause for accidents; instead, happening of accidents is also closely associated with the safety culture of the organization. Therefore, the most effective way of reducing accident rate would be to improve the social and the organizational factors that influence organization’s safety performance. Overview the present study is to understand the current level of safety culture in manufacturing enterprises. A tool for evaluating safety culture matching the needs and characteristics of manufacturing enterprises was developed by reviewing literature of safety culture, and taking the special backgrounds of the case enterprises into consideration. Expert validity was also implied for developing the questionnaire. Moreover, safety culture assessment was conducted through the practical investigation of the case enterprises. Total 505 samples were involved, 53 were executives and 452 were operators. The result of this study in comparison of the safety culture level between the executives and the operators was reached the significant level in 8 dimensions: Safety Commitment, Safety System, Safety Training, Safety Involvement, Reward and Motivation, Communication and Reporting, Leadership and Supervision, Learning and Changing. In general, the overall safety culture were executive level higher than operators level (M: 74.98 > 69.08; t=2.87; p < 0.01).

Keywords: questionnaire survey, safety culture, t-test, media studies

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Authors: Pedro Pablo Ramírez Sánchez, Alassane Ballé Ndiaye, Roberto Rendeiro Martín-Cejas

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The aim of this paper is to analyse the different environmental policies adopted in Europe for car emissions, to comment on some of the possible perverse effects generated and point out these policies which are considered more efficient under the environmental perspective. This paper is focused on passenger cars as this category is the most significant in road transport. The utility of this research lies in this being the first step or basis to improve and optimise actual policies. The methodology applied in this paper refers to a comparative analysis from a practical and theoretical point of view of European environmental policies in road transport. This work describes an overview of the road transport industry in Europe pointing out some relevant aspects such as the contribution of road transport to total emissions and the vehicle fleet in Europe. Additionally, we propose a brief practice guide with the combined policies in order to optimise their aim.

Keywords: air quality, climate change, emission, environment, perverse effect, road transport, tax policy

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Authors: Jisun Mo, Paola Boarin

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The impact of common buildings on climate and environment has prompted people to get involved in the green building standards aimed at implementing rating tools or certifications. Thus, green building rating systems were introduced to the construction industry, and the demand for certified green buildings has increased gradually and succeeded considerably in enhancing people’s environmental awareness. However, the existing certification process has been unsatisfactory in attracting stakeholders and/or professionals who are actively engaged in adopting a rating system. It is because they have faced recurring barriers regarding limited information in understanding the rating process, time-consuming procedures and higher costs, which have a direct influence on pursuing green building rating systems. To promote the achievement of green building certifications within the building industry more successfully, this paper aims at designing a Pre-Assessment Tool (PAT) framework that can help stakeholders and/or professionals engaged in the construction industry to clarify their basic knowledge, timeframe and extra costs needed to activate a green building certification. First, taking the first steps towards the rating tool seems to be complicated because of upfront commitment to understanding the overall rating procedure is required. This conceptual PAT framework can increase basic knowledge of the rating tool and the certification process, mainly in terms of all resources or information of each credit requirements. Second, the assessment process of rating tools is generally known as a “lengthy and time-consuming system”, contributing to unenthusiastic reactions concerning green building projects. The proposed framework can predict the timeframe needed to identify how long it will take for a green project to process each credit requirement and the documentation required from the beginning of the certification process to final approval. Finally, most people often have the initial perception that pursuing green building certification costs more than constructing a non-green building, which makes it more difficult to execute rating tools. To overcome this issue, this PAT will help users to estimate the extra expenses such as certification fees and third-party contributions based on the track of the amount of time it takes to implement the rating tool throughout all the related stages. Also, it can prevent unexpected or hidden costs occurring in the process of assessment. Therefore, this proposed PAT framework can be recommended as an effective method to support the decision-making of inexperienced users and play an important role in promoting green building certification.

Keywords: green building rating tools, Pre-Occupancy Evaluation (PrOE), client’s decision-making, certification

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Yasmeen Jamal Alabdallat, Almutazballlah Bassam Qablan, Obada Ahmad Al Jayyousi, Ihdaa Mahmoud Bani Khalaf, Eman E. Alshial

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Background: Bipolar disorder, formerly known as manic depression, is a mental health status that leads to extreme mood swings that include emotional lows (depression) and highs (mania or hypomania). This systematic review and meta-analysis aimed to assess the safety and efficacy of lithium versus valproate among bipolar patients. Methods: A computer literature search of PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials was conducted from inception until June 2022. Studies comparing lithium versus valproate among bipolar patients were selected for the analysis, and all relevant outcomes were pooled in the meta-analysis using Review Manager Software. Results: 11 Randomized Clinical Trials were included in this meta-analysis with a total of 4159 patients. Our meta showed that lithium was superior to valproate in terms of Young Mania Rating Scale (YMRS) (MD = 0.00 with 95% CI, (-0.55 – 0.55; I2 = 0%), P = 1.00). The results of the Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored the valproate treated group (MD = 1.41 with 95% CI, (-0.15 – 2.67; I2 = 0%), P = 0.03). Concerning the results of the Montgomery-Asberg Depression Rating Scale (MADRS), the results showed that the lithium was superior to valproate (MD = 0.03 with 95% CI, (-0.80 to 0.87; I2 = 40%), P = 0.94). In terms of the sexual side effect, we found that the valproate was superior to lithium (RR 1.19 with 95% CI, (0.74 to 1.91; I2 = 0%), P = 0.47). The lithium-treated group was superior in comparison to valproate treated group in terms of Abnormal Involuntary Movement Scale (AIMS) (MD = -0.03 with 95% CI (-0.38 to 0.32; I2 = 0%), P = 0.87). The lithium was more favorable in terms of Simpson-Agnes scale (MD = -0.40 with 95% CI, (-0.86 to 0.06; I2 = 0%), P = 0.09). The results of the Barnes akathisia scale showed that the overall effect of the valproate was more favorable in comparison to lithium (MD = 0.05 with 95% CI, (-0.12 to 0.22; I2 = 0%), P = 0.57). Conclusion: Our study revealed that on the scales of efficacy Lithium treated group surpassed Valproate treated group in terms of Young Mania Rating Scale (YMRS), Abnormal Involuntary Movement Scale (AIMS) and Simpson-Agnes scale, but valproate surpassed it in Barnes Akathisia scale. Furthermore, on the scales of depression Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored Valproate treated group, but Lithium surpassed valproate in terms of Montgomery-Asberg Depression Rating Scale (MADRS). Valproate surpassed Lithium in terms of sexual side effects.

Keywords: bipolar, mania, bipolar-depression, sexual dysfunction, sexual side effects, treatment

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Authors: Stanislovas Buteliauskas, Aušrius Juozapavičius

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City road transport contributes significantly to climate change, and the ongoing world urbanization is only increasing the problem. The paper describes a city planning concept minimizing the number of vehicles on the roads while increasing overall mobility. This becomes possible by utilizing a recently invented two-level road junction with a unique property of serving both as an intersection of uninterrupted traffic and an easily accessible transport hub capable of accumulating private vehicles, and therefore becoming an especially effective park-and-ride solution, and a logistics or business center. Optimized layouts of city road infrastructure, living and work areas, and major roads are presented. The layouts are suitable both for the development of new cities as well as for the expansion of existing ones. Costs of the infrastructure and a positive impact on climate are evaluated in comparison to current city growth patterns.

Keywords: congestion, city infrastructure, park-and-ride, road junctions

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Authors: Khalid A. Alsaif, Mosaad A. Foda

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The primary objective of this study is to develop the first round of road traffic noise maps for Riyadh City using Geographical Information Systems (GIS) and software LimA 7810 predictor. The road traffic data were measured or estimated as accurate as possible in order to obtain reliable noise maps. Meanwhile, the attributes of the roads and buildings are automatically exported from GIS. The simulation results at some chosen locations are validated by actual field measurements, which are obtained by a system that consists of a sound level meter, a GPS receiver and a database to manage the measured data. The results show that the average error between the predicted and measured noise levels is below 3.0 dB.

Keywords: noise pollution, road traffic noise, LimA predictor, GIS

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Authors: Julie Berame

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The study probed that out of eight (8) lessons in Science Six have been validated, lessons 1-3 got the descriptive rating of very satisfactory and lessons 4-8 got the descriptive rating of outstanding based on the content analysis of the prepared CBL lesson plans. The evaluation of the lesson plans focused on the three main features such as statements of the lesson objectives, lesson content, and organization and effectiveness. The study used developmental research procedure that contained three phases, namely: Development phase consists of determining the learning unit, lesson plans, creation of the table of specifications, exercises/quizzes, and revision of the materials; Evaluation phase consists of the development of experts’ assessment checklist, presentation of checklist to the adviser, comments and suggestions, and final validation of the materials; and try-out phase consists of identification of the subject, try-out of the materials using CBL strategy, administering science attitude questionnaire, and statistical analysis to obtain the data. The findings of the study revealed that the relevance and usability of CBL lessons 1 and 2 in terms of lesson objective, lesson content, and organization and effectiveness got the rating of very satisfactory (4.4) and lessons 3-8 got the rating of outstanding (4.7). The lessons 1-8 got the grand rating of outstanding (4.6). Additionally, results showed that CBL strategy helped foster positive attitude among students and achieved effectiveness in psychomotor learning objectives.

Keywords: development, validation, center-based learning, science

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Nacer Eddine Chelbi, Ayet Bagane, Annie Saleh, Claude Sauvageau, Denis Gingras

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As recently stated by National Highway Traffic Safety Administration (NHTSA), to demonstrate the expected performance of a highly automated vehicles system, test approaches should include a combination of simulation, test track, and on-road testing. In this paper, we propose a new validation method for autonomous vehicles involving on-road tests (Field Operational Tests), test track (Test Matrix) and simulation (Worst Case Scenarios). We concentrate our discussion on the simulation aspects, in particular, we extend recent work based on Importance Sampling by using a Metropolis-Hasting algorithm (MHS) to sample collected data from the Safety Pilot Model Deployment (SPMD) in lane-change scenarios. Our proposed MH sampling method will be compared to the Importance Sampling method, which does not perform well in high-dimensional problems. The importance of this study is to obtain a sampler that could be applied to high dimensional simulation problems in order to reduce and optimize the number of test scenarios that are necessary for validation and certification of autonomous vehicles.

Keywords: automated driving, autonomous emergency braking (AEB), autonomous vehicles, certification, evaluation, importance sampling, metropolis-hastings sampling, tests

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Authors: James Boylan, Denny Meyer, Won Sun Chen

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Background: Globally, there is an increasing trend of road traffic deaths, reaching 1.35 million in 2016 in comparison to 1.3 million a decade ago, and overall, road traffic injuries are ranked as the eighth leading cause of death for all age groups. The reported death rate for younger drivers aged 16-19 years is almost twice the rate reported for older drivers aged 25 and above, with a rate of 3.5 road traffic fatalities per annum for every 10,000 licenses held. Telematics refers to a system with the ability to capture real-time data about vehicle usage. The data collected from telematics can be used to better assess a driver's risk. It is typically used to measure acceleration, turn, braking, and speed, as well as to provide locational information. With the Australian government creating the National Telematics Framework, there has been an increase in the government's focus on using telematics data to improve road safety outcomes. The purpose of this study is to test the hypothesis that improvements in telematics measured driving behaviour to relate to improvements in road safety attitudes measured by the Driving Behaviour Questionnaire (DBQ). Methodology: 28 participants were recruited and given a telematics device to insert into their vehicles for the duration of the study. The participant's driving behaviour over the course of the first month will be compared to their driving behaviour in the second month to determine whether feedback from telematics devices improves driving behaviour. Participants completed the DBQ, evaluated using a 6-point Likert scale (0 = never, 5 = nearly all the time) at the beginning, after the first month, and after the second month of the study. This is a well-established instrument used worldwide. Trends in the telematics data will be captured and correlated with the changes in the DBQ using regression models in SAS. Results: The DBQ has provided a reliable measure (alpha = .823) of driving behaviour based on a sample of 23 participants, with an average of 50.5 and a standard deviation of 11.36, and a range of 29 to 76, with higher scores, indicating worse driving behaviours. This initial sample is well stratified in terms of gender and age (range 19-27). It is expected that in the next six weeks, a larger sample of around 40 will have completed the DBQ after experiencing in-vehicle telematics for 30 days, allowing a comparison with baseline levels. The trends in the telematics data over the first 30 days will be compared with the changes observed in the DBQ. Conclusions: It is expected that there will be a significant relationship between the improvements in the DBQ and the trends in reduced telematics measured aggressive driving behaviours supporting the hypothesis.

Keywords: telematics, driving behavior, young drivers, driving behaviour questionnaire

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Authors: C. L. Wu, W. W. Tseng

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From the National Health Insurance (NHI) system was introduced in Taiwan in 2000, there have been some problems in transformed small-scale hospitals, such as mobility of patients, shortage of nursing staff, medical pipelines breaking fire compartments and insufficient fire protection systems. Due to shrinking of the funding scale and the aging society, fire safety in small-scale hospitals has recently given cause for concern. The aim of this study is to determine fire risk index for small-scale hospital through a systematic approach The selection of fire safety mitigation methods can be regarded as a multi-attribute decision making process which must be guaranteed by expert groups. First of all, identify and select safety related factors and identify evaluation criteria through literature reviews and experts group. Secondly, application of the Fuzzy Analytic Hierarchy Process method is used to ascertain a weighted value which enables rating of the importance each of the selected factors. Overall, Sprinkler type and Compartmentation are the most crucial indices in mitigating fire, that is to say, structural approach play an important role to decrease losses in fire events.

Keywords: Fuzzy Delphi Method, fuzzy analytic hierarchy, process risk assessment, fire events

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Authors: M. Fathy, I. Maarouf, S. El-Sayary

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Our buildings are responsible for around 50% of energy consumption and most of this consumption because of spaces design, low heat isolation building material and occupant presence and behavior in buildings beside non-efficient architectural treatments. It has been shown to have large impact on heating, cooling and ventilation demand, energy consumption of lighting and appliances, and building controls. This paper aims to focus on passive treatments in Wakala Buildings in Cairo and how far it meets the LEED Criteria as the LEED – Leadership in Energy and Environmental Design – considered the widest spread rating system in the world. By studying Wakala buildings in Cairo, there are a lot of environmental potentials in it in the field of passive treatments and energy efficiency that could be found in examples by surveying and analyzing Wakala buildings. Besides the environmental treatments through the natural materials and façade architectural treatments, there is a measuring phase to declare the efficiency of the Wakala building through temperature decline between outdoor and indoor the Wakala building. Also, measuring how far the indoor conditions matched the thermal comfort for occupants. After measuring the Wakala buildings, it is the role of applying the criteria of LEED rating system to find out how fare Wakala buildings meet the LEED rating system criteria. After all, the building technologies used in Wakala buildings in the field of passive design and caused that energy efficiency would be clear and what is needed for Wakala buildings to have a LEED Certification.

Keywords: energy awareness, historical commercial buildings, LEED, Wakala buildings

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Authors: Efua Ehiaguina, Haruna Moda

Abstract:

Interest in the development of appropriate safety culture in the oil and gas industry has taken centre stage among stakeholders in the industry. Human behaviour has been identified as a major contributor to occupational accidents, where abnormal activities associated with safety management are taken as normal behaviour. Poor safety culture is one of the major factors that influence employee’s safety behaviour at work, which may consequently result in injuries and accidents and strengthening such a culture can improve workers safety performance. Nigeria oil and gas industry has contributed to the growth and development of the country in diverse ways. However, in terms of safety and health of workers, this industry is a dangerous place to work as workers are often exposed to occupational safety and health hazard. To ascertain the impact of employees’ safety and how it impacts health and safety compliance within the local industry, online safety culture survey targeting frontline workers within the industry was administered covering major subjects that include; perception of management commitment and style of leadership; safety communication method and its resultant impact on employees’ behaviour; employee safety commitment and training needs. The preliminary result revealed that 54% of the participants feel that there is a lack of motivation from the management to work safely. In addition, 55% of participants revealed that employers place more emphasis on work delivery over employee’s safety on the installation. It is expected that the study outcome will provide measures aimed at strengthening and sustaining safety culture in the Nigerian oil and gas industry.

Keywords: oil and gas safety, safety behaviour, safety culture, safety compliance

Procedia PDF Downloads 114

Authors: Caihong Sun, Xizi Zhang

Abstract:

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

Procedia PDF Downloads 218

Authors: Nurten Akgun, Dilum Dissanayake, Neil Thorpe, Margaret C. Bell

Abstract:

Cycling has gained a great attention with comparable speeds, low cost, health benefits and reducing the impact on the environment. The main challenge associated with cycling is the provision of safety for the people choosing to cycle as their main means of transport. From the road safety point of view, cyclists are considered as vulnerable road users because they are at higher risk of serious casualty in the urban network but more specifically at roundabouts. This research addresses the development of an enhanced mathematical model by including a broad spectrum of casualty related variables. These variables were geometric design measures (approach number of lanes and entry path radius), speed limit, meteorological condition variables (light, weather, road surface) and socio-demographic characteristics (age and gender), as well as contributory factors. Contributory factors included driver’s behavior related variables such as failed to look properly, sudden braking, a vehicle passing too close to a cyclist, junction overshot, failed to judge other person’s path, restart moving off at the junction, poor turn or manoeuvre and disobeyed give-way. Tyne and Wear in the UK were selected as a case study area. The cyclist casualty data was obtained from UK STATS19 National dataset. The reference categories for the regression model were set to slight and serious cyclist casualties. Therefore, binary logistic regression was applied. Binary logistic regression analysis showed that approach number of lanes was statistically significant at the 95% level of confidence. A higher number of approach lanes increased the probability of severity of cyclist casualty occurrence. In addition, sudden braking statistically significantly increased the cyclist casualty severity at the 95% level of confidence. The result concluded that cyclist casualty severity was highly related to approach a number of lanes and sudden braking. Further research should be carried out an in-depth analysis to explore connectivity of sudden braking and approach number of lanes in order to investigate the driver’s behavior at approach locations. The output of this research will inform investment in measure to improve the safety of cyclists at roundabouts.

Keywords: binary logistic regression, casualty severity, cyclist safety, roundabout

Procedia PDF Downloads 160

Authors: Hyeondal Jeong, Yoonjung Baek

Abstract:

This study examines the relationship between ethical leadership and individual creativity and focused on mediating effects of psychological safety. In order to clarify the mechanism of ethical leadership, psychological safety of the members was set as a mediator. Using data gathered from a sample of 150 employees. For data analysis, exploratory factor analysis, correlation analysis, hierarchical regression analysis and Sobel-Test were performed. The results showed that ethical leadership had a positive effect on psychological safety and individual creativity, and psychological safety had a positive mediating effect. Since the mediating effect of psychological safety has been confirmed, we need to find ways to improve the psychological safety of the members in terms of organizational management. Psychological safety has a positive effect on individual creativity, which can have a positive impact on innovation throughout the organization.

Keywords: ethical leadership, creativity, psychological safety, ethics management, innovative behaviors

Procedia PDF Downloads 222

Authors: Pratham Baheti, Rohan Sanghi, Aditya Gupta

Abstract:

In the largely populated city of New Delhi, India, there are a lot of people that travel by two-wheelers. Majority of the people wear helmets while traveling and know how important it is to wear helmets for their safety. Still, the number of deaths because of road accidents involving two-wheelers is significant. We had conducted a survey by traveling within and in the outskirts of Delhi so as to see the variation in data and in the opinion of people towards helmet being a safety device rather than to escape the traffic police. We conducted a survey at traffic junctions and crossings of all the stakeholders and collected feedback on the Helmet scenario in India. According to the survey, the possible reason for these deaths is that the people, being unaware of helmet safety standards (ISI standards for helmets), buy helmets with fake ISI mark from unauthorized helmet sellers for a cheap price. Also, for the people who do not wear a helmet at all or wear a helmet just because it is a law, the reasons that they do not want to wear a helmet is heavyweight, lack of ventilation, inconvenience due to a strap, and hair problems. To address all these problems, we are designing a helmet with reduced weight and also working on the Helmet’s retention system and ventilation. We plan to provide this product at a cheap cost whilst maintaining the ISI standards so that a larger section of the population would be able to afford the helmet.

Keywords: safety, survey, ISI marks, stakeholders, helmet

Procedia PDF Downloads 256

Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

Abstract:

This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

Procedia PDF Downloads 213

Authors: Kittichai Thanasupsin, Satis Sukniam

Abstract:

Pavement marking is an essential task of road construction and maintenance. One of several benefits of pavement markings has been used to provide information about road alignment and road conditions ahead. In some cases, retro-reflectivity of road marking at night may not meet the standard. This degradation may be caused by internal factors such as the size of glass beads and the number of glass beads or external factors such as traffic volume, lane width, vehicle weight, and so on. This research aims to investigate the reflective efficiency of thermoplastic road marking with the glass beads. Ratios of glass beads, ranging from 359 to 553 grams per square meter on an asphaltic concrete, have been tested. The reflective efficiency data was collected at the beginning and at a specific time interval for a total of 8 months. It was found that the difference in glass beads quantity affects the rate of retro-reflectivity but does not affect the diffuse reflectivity. It was also found that other factors affect retro-reflectivity, such as duration, the position of road marking, traffic density, the quantity of glass beads, and dirt coating on top. The dirt coating on top is the most crucial factor that deteriorating retro-reflectivity.

Keywords: thermoplastic pavement marking, retro-reflectivity, diffuse reflectivity, asphalt concrete

Procedia PDF Downloads 108

Authors: Duygu Çelgin

Abstract:

Until the new Occupational Health and Safety Law of Turkey, most of the workers were excluded from the mandatory occupational health and safety services. This new law, made the OHS services mandatory for all workers from all sectors including both public and private. However, in the application some problems and disadvantageous cases are occurred and the government also considered these cases. In this study, the new OHS law of Turkey and the regulations prepared according to the law are studied with the literature search.

Keywords: occupational health and safety in Turkey, OHS servicing in Turkey, safety experts, OHS support

Procedia PDF Downloads 436