scholarly journals A C-BiLSTM Approach to Classify Construction Accident Reports

2020 ◽  
Vol 10 (17) ◽  
pp. 5754
Author(s):  
Jinyue Zhang ◽  
Lijun Zi ◽  
Yuexian Hou ◽  
Da Deng ◽  
Wenting Jiang ◽  
...  
Keyword(s):  
Occupational Safety ◽  
Short Term Memory ◽  
Management Strategies ◽  
Working Environment ◽  
Support Vector ◽  
Health Administration ◽  
Construction Sites ◽  
Domain Experts ◽  
Risk Management Strategies ◽  
Construction Accidents

The construction sector is widely recognized as having the most hazardous working environment among the various business sectors, and many research studies have focused on injury prevention strategies for use on construction sites. The risk-based theory emphasizes the analysis of accident causes extracted from accident reports to understand, predict, and prevent the occurrence of construction accidents. The first step in the analysis is to classify the incidents from a massive number of reports into different cause categories, a task which is usually performed on a manual basis by domain experts. The research described in this paper proposes a convolutional bidirectional long short-term memory (C-BiLSTM)-based method to automatically classify construction accident reports. The proposed approach was applied on a dataset of construction accident narratives obtained from the Occupational Safety and Health Administration website, and the results indicate that this model performs better than some of the classic machine learning models commonly used in classification tasks, including support vector machine (SVM), naïve Bayes (NB), and logistic regression (LR). The results of this study can help safety managers to develop risk management strategies.

Recent Developments in Health Law

1994 ◽  
Vol 22 (1) ◽  
pp. 83-92
Author(s):  
Keyword(s):  
Health Care ◽  
Occupational Safety ◽  
Medical Personnel ◽  
The United States ◽  
Occupational Safety And Health ◽  
Working Environment ◽  
Health Administration ◽  
Bloodborne Pathogens ◽  
Work Related ◽  
Safety And Health

In American Dental Association v. Martin, the United States Court of Appeals for the Seventh Circuit reviewed a challenge to a rule of the Occupational Safety and Health Administration (OSHA). In December, 1991, OSHA passed a standard to protect health care workers from viruses transmitted by blood—bloodborne pathogens—including the hepatitis B virus (HBV) and the human immunodeficiency virus, the virus known to cause AIDS. Three health care organizations, whose members are dentists, medical personnel firms, and home health employers, petitioned the court to review OSHA's rule.The Occupational Safety and Health Act was passed to assure employees that they would have as safe and healthy a working environment as feasible. Congress sought to ensure this by vesting the Secretary of Labor for Occupational Safety and Health with the authority to promulgate mandatory safety and health standards. In promulgating standards concerning toxic materials or harmful physical agents, the secretary sets rules that most adequately assure that an employee will not suffer a material impairment of health or functional capacity while performing work-related duties.

scholarly journals Hard-Hat Detection for Construction Safety Visualization

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Kishor Shrestha ◽  
Pramen P. Shrestha ◽  
Dinesh Bajracharya ◽  
Evangelos A. Yfantis
Keyword(s):  
Fall Prevention ◽  
Occupational Safety ◽  
The United States ◽  
Health Administration ◽  
Construction Sites ◽  
Warning Messages ◽  
Detection Tool ◽  
Safety And Health ◽  
Processing Techniques ◽  
Hard Hat

In 2012, 775 fatalities were recorded, and many more were injured at construction sites in the United States. Of these, 415 fatalities (54%) were due to fall, slips, and trips as well as being struck by falling objects. In order to decrease fatalities at construction sites to these types of events, the Occupational Safety and Health Administration (OSHA) provides Fall Prevention and OSHA-10 trainings to construction workers. Moreover, safety personnel monitor whether the workers use personal protective equipment (PPE) properly. Data shows that construction fatalities have decreased by 2% annually since 1994; however, the owners still are not satisfied with this result. Various studies have shown that fall is the biggest contributor for construction fatalities. One study showed that half of the fall fatalities were because the workers either had not used PPEs or had not used them properly. In addition, studies showed that, with proper use of hard hats, the fatalities due to fall, slips, trips, and being struck by falling objects could be reduced. This study developed and tested a hard-hat detection tool that uses image-processing techniques to identify whether workers are wearing hard hats. The tool dispatches warning messages if the workers do not use hard hats.

scholarly journals Nature of Occupational Incidents among Electrical Contractors

2019 ◽  
Author(s):  
Pouya Gholizadeh ◽  
Behzad Esmaeili
Keyword(s):  
Content Analysis ◽  
Occupational Safety ◽  
Body Parts ◽  
Health Administration ◽  
Contributing Factors ◽  
Statistical Probability ◽  
Construction Accidents ◽  
The Impact ◽  
Electrical Contractors ◽  
Fatal Injuries

Electrical contractors have experienced a rise in occupational fatalities in recent years. In 2017, electrical contractors also had the second highest number of non-fatal injuries among specialty trade contractors. Identifying statistically significant dependencies between these catastrophic outcomes and a handful of well-defined contributing factors in construction accidents offers a first step in mitigating the risks of construction accidents in this trade. Therefore, this study used methodologies of descriptive and quantitative statistics to identify the contributing factors most affecting occupational accident outcomes among electrical contracting enterprises, given an accident occurred. Accident reports were collected from the Occupational Safety and Health Administration’s fatality and catastrophe database. To ensure the reliability of the data, the team manually codified more than 600 incidents through a comprehensive content analysis using injury-classification standards. Inclusive of both fatal and non-fatal injuries, the results showed that most accidents happened in nonresidential buildings, new construction, and small projects (i.e., $50,000 or less). The main source of injuries manifested in parts and materials (46%), followed by tools, instruments, and equipment (19%), and structure and surfaces (16%). The most frequent types of injuries were fractures (31%), electrocutions (27%), and electrical burns (14%); the main injured body parts were upper extremities (25%), head (23%), and body system (18%). Among non-fatal cases, falls (37%), exposure to electricity (36%), and contact with objects (19%) caused most injuries; among fatal cases, exposure to electricity was the leading cause of death (50%), followed by falls (28%) and contact with objects (19%). The analysis also investigated the impact of several accident factors on the degree of injuries and found significant effects from such factors such as project type, source of injury, cause of injuries, injured part of body, nature of injury, and event type. In other words, the statistical probability of a fatal accident—given an accident occurrence—changes significantly based on the degree of these factors. Beyond these outcomes, the described content-analysis methodology contributes to the accident-analysis body of knowledge by providing a framework for codifying data from accident reports to facilitate future analysis and modeling attempts (e.g., developing logistic regression models) to subsequently mitigate more injuries in other fields.

scholarly journals The Forensic Engineers Relationship to Manufacturers in Product Cases

1992 ◽  
Vol 9 (1) ◽  
Author(s):  
Richard M. Ziernicki
Keyword(s):  
Indirect Cost ◽  
Construction Industry ◽  
Occupational Safety ◽  
Civil Law ◽  
Occupational Safety And Health ◽  
Health Administration ◽  
The Third ◽  
Safety And Health ◽  
Heavy Construction ◽  
Construction Accidents

Accidents are the third largest cause of death in America, taking 140,000 lives per year. Construction accidents kill about 1000 workers every year. There were nearly 640,000 construction injuries in 1989. Accidents related to highway and heavy construction account for a third of all construction fatalities according to the Occupational Safety and Health Administration (OSHA). OSHA inspectors handled 45,000 investigations in 1990, about half of them in the construction industry. Automotive accidents take 44,000 lives a year. The direct and indirect cost of all automotive accidents is approximately $60 billion dollars per year. Many of the product accidents will result in civil law suits. Many will result in litigation against the designer and manufacturer.

scholarly journals Intelligent Platform Based on Smart PPE for Safety in Workplaces

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4652
Author(s):  
Sergio Márquez-Sánchez ◽  
Israel Campero-Jurado ◽  
Jorge Herrera-Santos ◽  
Sara Rodríguez ◽  
Juan M. Corchado
Keyword(s):  
Short Term Memory ◽  
Area Under The Curve ◽  
Working Environment ◽  
Support Vector ◽  
Protective Equipment ◽  
Short Term ◽  
Gaussian Models ◽  
Occupational Illness ◽  
Wearable Technologies ◽  
Long Short Term Memory

It is estimated that we spend one-third of our lives at work. It is therefore vital to adapt traditional equipment and systems used in the working environment to the new technological paradigm so that the industry is connected and, at the same time, workers are as safe and protected as possible. Thanks to Smart Personal Protective Equipment (PPE) and wearable technologies, information about the workers and their environment can be extracted to reduce the rate of accidents and occupational illness, leading to a significant improvement. This article proposes an architecture that employs three pieces of PPE: a helmet, a bracelet and a belt, which process the collected information using artificial intelligence (AI) techniques through edge computing. The proposed system guarantees the workers’ safety and integrity through the early prediction and notification of anomalies detected in their environment. Models such as convolutional neural networks, long short-term memory, Gaussian Models were joined by interpreting the information with a graph, where different heuristics were used to weight the outputs as a whole, where finally a support vector machine weighted the votes of the models with an area under the curve of 0.81.

scholarly journals Technological Aspects in Construction Safety with Applicability to Hazards in India

2020 ◽  
Vol 4 (10) ◽  
pp. 6-13
Keyword(s):  
Occupational Safety ◽  
Safety Management ◽  
Developed Countries ◽  
Hazard Identification ◽  
Construction Site ◽  
Human Beings ◽  
Health Administration ◽  
Construction Sites ◽  
Safety Measures ◽  
Technological Tools

In India as well as in the global scenario Construction industry is viewed as one of the largest employment and economy generating sector, which in turn increases the probability of hazard & risks in the industry. Many developed countries have adopted technological interventions as safety measures to minimize these risks. Comparing to the safety scenarios in Indian construction sites, the hazards are twenty times higher than in United Kingdom and thirty times than in U.S.A. In developing countries like India, the completion of the project is given more importance than the safety rules and regulations. Most of the hazards in Indian Construction site arises due to the carelessness of human beings, improper safety trainings, and lack of technology as well as communication. This study aims to find the applicable technological tools that can be utilised for ensuring safety at construction sites. The study also gives the information about various hazards and applicable technological tools for a particular kind of hazard. The study utilizes the data from the existing literature available with OSHA (Occupational Safety and Health Administration) and research papers & journals to find the most commonly occurring hazards and also the technological tools that are existing in the market and employed to cope with the identified hazards. The data collected is then analysed and on basis of the hazard identification, a comprehensive list of technological tools used for the preventive or safety measures for that particular hazard at construction site are formulated. The findings of this research will be helpful to produce a better safety management plan for construction sites in India.

ASSIGNMENT OF RESPONSIBILITY AND ROLE TO CONSTRUCTION CLIENT IN OCCUPATIONAL SAFETY AND HEALTH SYSTEM

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Jeong-Hun Won ◽  
Nam-Gwon Jang ◽  
Sang-Seom Ko ◽  
Tae-Sang Kim
Keyword(s):  
Health System ◽  
Management System ◽  
Occupational Safety ◽  
Health Management ◽  
Occupational Safety And Health ◽  
Average Score ◽  
Construction Sites ◽  
Safety And Health ◽  
Survey Results ◽  
Construction Accidents

This study investigated the client's duty and role to prevent construction accidents by participating construction client into the occupational safety and health management system. Since the fatal accidents of the construction sites in Korea are higher than other OECD countries and approximately 500 workers annually have died on construction sites, various efforts have been performed to prevent construction accidents. Recently, in Korea, the client’s participation in the safety and health management system has been focused as a fundamental method to prevent serious accidents. To examine the necessity of client’s participation, the survey was performed for construction participants. And, survey results and existing studies about client's role were analyzed to assign responsibility and role to the client. Results showed that safety managers and supervisors were strongly agreed for imposing client's duty (average scores of 4.373 and 4.107 in likert 5point scale) while clients showed the lowest agreement (average score of 3.153). In addition, the detailed role was proposed in the whole project stage, that is plan, design, and construction stage. Client can be a key player in reducing the fatal construction accidents by doing the accurate roles proposed in this study.

scholarly journals Components of Effective Safety and Health Management System towards the Awareness of Occupational Safety and Health Administration (OSHA) at Government Owned Company Kuala Lumpur

2018 ◽  
Vol 3 (1) ◽  
pp. 37
Author(s):  
Noorlaila Hj Yunus ◽  
Nur ‘Aliya Hj Abdullah Tahmidi
Keyword(s):  
Management System ◽  
Occupational Safety ◽  
Health Management ◽  
Occupational Safety And Health ◽  
Working Environment ◽  
Management Systems ◽  
Health Administration ◽  
Kuala Lumpur ◽  
Safety And Health ◽  
Owned Company

Every organization should put safety and health of employees at the top of priority. A safety and health management system or safety program can help the employees to improve job performance, boost employee’s motivation and satisfaction. The most important is employers and employees will feel secure and safe at the workplace. Occupational Safety and Health Administration (OSHA) in an organization could help to prevent any possible i llnesses, injuries and accidents happen in working environment. Several studies have been conducted that clarified some of the components of effective safety and health management systems towards the awareness of OSHA. The focus of this study is to identify the most influential components of effective safety and health management systems towards the awareness of OSHA and also to examine the relationship between the components of effective safety and health management systems towards the awareness of OSHA. Thus, the researcher chooses correlational research design in order to achieve the objectives of the study. In this study, 250 employees who are working in GOC, Kuala Lumpur have been involved in a survey.

Using Machine Learning Algorithms on Prediction of Stock Price

2020 ◽  
Vol 12 (2) ◽  
pp. 84-99
Author(s):  
Li-Pang Chen
Keyword(s):  
Machine Learning ◽  
Stock Price ◽  
Short Term Memory ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Short Term ◽  
Learning Techniques ◽  
Historical Database ◽  
Long Short Term Memory

In this paper, we investigate analysis and prediction of the time-dependent data. We focus our attention on four different stocks are selected from Yahoo Finance historical database. To build up models and predict the future stock price, we consider three different machine learning techniques including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN) and Support Vector Regression (SVR). By treating close price, open price, daily low, daily high, adjusted close price, and volume of trades as predictors in machine learning methods, it can be shown that the prediction accuracy is improved.

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