scholarly journals Characteristic Analysis of Unsafe Behavior by Coal Miners: Multi-Dimensional Description of the Pan-Scene Data

2018 ◽  
Vol 15 (8) ◽  
pp. 1608 ◽  
Author(s):  
Ruipeng Tong ◽  
Yanwei Zhang ◽  
Pengcheng Cui ◽  
Cunli Zhai ◽  
Meng Shi ◽  
...  
Keyword(s):  
Data Analysis ◽  
Safety Management ◽  
Safety Data ◽  
Characteristic Analysis ◽  
Coal Miners ◽  
Unsafe Behavior ◽  
Basic Characteristics ◽  
Explosion Accidents ◽  
Behavior Characteristics ◽  
Realistic Scenes

As a high-risk occupation, coal mining has many accidents, primarily due to the unsafe behavior of coal miners. Based on the research of analysis of unsafe behavior and pan-scenario data of miners, a theoretical framework for the analysis of unsafe behavior characteristics was proposed in this paper. The collected data were divided into realistic scenes and abstract scenes according to different manifestations; the pan-scene data were described from the eight dimensions of time, behavioral trace, location, behavioral property, behavioral individual, degree, unsafe action, and specialty using a quantitative method for the structure conversion; and the rules were discovered through cluster analysis and association analysis. A total of 225 coal mine gas explosion accidents were used for analysis, and the pan-scene data description and structure conversion of unsafe behavior that caused these accidents were realized. In a certain cluster, the distribution rules of dimensions and the interaction between different dimensions of unsafe behavior were explored after analysis. The results show that the proposed eight dimensions can fully explain the basic characteristics and attributes of the unsafe behavior of coal miners. The structure conversion can reduce the workload of managers and effectively improve the safety data processing capabilities, and the result of data analysis can provide data support and a management basis for safety management. A new method and thought for the data analysis of miners’ unsafe behavior is provided.

Data Mining in Aviation Safety Data Analysis

2011 ◽  
pp. 178-198 ◽  
Author(s):  
Reima Suomi ◽  
Olli Sjöblom
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Safety Management ◽  
Safety Data ◽  
Aviation Safety ◽  
Important Application ◽  
Civil Aviation ◽  
Basic Concepts ◽  
In The Beginning ◽  
Mining Tools

This chapter introduces aviation safety data analysis as an important application area for data mining. In the beginning of the chapter, the reader is introduced to the basic concepts of data mining. After that, the field of aviation safety management is discussed, and in that connection data mining is identified as a key technology to study through flight incidents reports. Afterwards the test runs for four data mining products, for possible use in the Finnish civil aviation authority, are described in detail. However, before the testing of tools the preparation of the test data for the tools is described in detail. The chapter ends with conclusions that tell that even sophisticated data mining tools are just tools: they do not provide any automatic tools, but skilled users can use them for searching clues in the data.

Market of Insurance in Russia: Major Tendencies and Problems of Development

2006 ◽  
pp. 115-127
Author(s):  
T Natkhov
Keyword(s):  
Data Analysis ◽  
Statistical Data ◽  
Statistical Data Analysis ◽  
Medium Term ◽  
Insurance Sector ◽  
Different Types ◽  
Basic Characteristics

The article considers recent tendencies in the development of the market of insurance in Russia. On the basis of statistical data analysis the most urgent problems of the insurance sector are formulated. Basic characteristics of different types of insurance are revealed, and measures on perfection of the insurance institution in the medium term are proposed.

scholarly journals Research on the Behavior Characteristics of Pedestrian Crowd Weaving Flow in Transport Terminal

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Liya Yao ◽  
Lishan Sun ◽  
Zhiyong Zhang ◽  
Shuwei Wang ◽  
Jian Rong
Keyword(s):  
Field Investigation ◽  
Evolution Law ◽  
The Poor ◽  
Urban Public Transport ◽  
Behavioral Parameters ◽  
Multiple Indicator ◽  
Basic Characteristics ◽  
Behavior Characteristics ◽  
Transfer Flow ◽  
Pedestrian Crowd

Due to the poor transfer organization in urban public transport terminal, pedestrian crowd are often forced to weaving in their transfer flow lines. Frequent weaving behaviors not only decrease passengers’ transfer comfort, but may also trigger serious crowd disaster such as trampling. In order to get accurate understanding of the weaving features of pedestrian crowd and analyze the relevant evolution law, researches have been conducted on the basis of field investigation. First, the typical weaving phenomenon were defined and classified, and a microscopic parameters system of pedestrian crowd weaving flow was constructed. The detection and quantification methods of multiple indicator parameters were also given. Then, correlation between different behavioral parameters was analyzed based on the survey data of weaving pedestrian crowd on the stairs of DongZhiMen (DZM) hub. The basic characteristics and evolution law of the weaving behaviors were then discussed, and conclusions were drawn.

Exploring the impacts of factors contributing to unsafe behavior of coal miners

2019 ◽  
Vol 115 ◽  
pp. 339-348 ◽  
Author(s):  
Chen Wang ◽  
Jiakun Wang ◽  
Xinhua Wang ◽  
Hao Yu ◽  
Li Bai ◽  
...  
Keyword(s):  
Coal Miners ◽  
Unsafe Behavior

scholarly journals A Framework for an Indoor Safety Management System Based on Digital Twin

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5771
Author(s):  
Zhansheng Liu ◽  
Anshan Zhang ◽  
Wensi Wang
Keyword(s):  
Management System ◽  
Safety Management ◽  
Smart Cities ◽  
Safety Data ◽  
Support Vector ◽  
The Internet ◽  
Safety Management System ◽  
Winter Olympics ◽  
Digital Twins ◽  
Building Information

With the development of the next generation of information technology, an increasing amount of attention is being paid to smart residential spaces, including smart cities, smart buildings, and smart homes. Building indoor safety intelligence is an important research topic. However, current indoor safety management methods cannot comprehensively analyse safety data, owing to a poor combination of safety management and building information. Additionally, the judgement of danger depends significantly on the experience of the safety management staff. In this study, digital twins (DTs) are introduced to building indoor safety management. A framework for an indoor safety management system based on DT is proposed which exploits the Internet of Things (IoT), building information modelling (BIM), the Internet, and support vector machines (SVMs) to improve the level of intelligence for building indoor safety management. A DT model (DTM) is developed using BIM integrated with operation information collected by IoT sensors. The trained SVM model is used to automatically obtain the types and levels of danger by processing the data in the DTM. The Internet is a medium for interactions between people and systems. A building in the bobsleigh and sled stadium for the Beijing Winter Olympics is considered as an example; the proposed system realises the functions of the scene display of the operation status, danger warning and positioning, danger classification and level assessment, and danger handling suggestions.

Contractor and supplier management: mitigating risk by better decision making

2012 ◽  
Vol 52 (2) ◽  
pp. 642
Author(s):  
Dag Yemenu ◽  
Richard Cerenzio
Keyword(s):  
Decision Making ◽  
Oil And Gas ◽  
Safety Management ◽  
Safety Data ◽  
Health And Safety ◽  
Leading Edge ◽  
Third Party ◽  
Driving Safety ◽  
Comprehensive Management ◽  
And Performance

Global industry trends show increased outsourcing of non-core business activities (i.e. construction, maintenance, engineering, etc.) to third-party contractors. Data from several industries show that contractors face 1.5–3 times higher incident rates than in-house employees. This extended abstract covers leading-edge approaches for managing contractor risk, presently implemented by organisations in the oil and gas, mining and manufacturing industries. Using a database of more than 35,000 contracting companies and 220 owner/operator companies, this extended abstract accumulates more than six years of extensive health and safety data to show trends associated with health and safety management and performance improvement. Using statistical analysis methods, actionable leading indicators and insightful trends are discussed. Best practices of contractor management and decision-making tools based on a comprehensive management-system approach to contractor-risk management are also examined. Discussed is a practical model to address the following key elements: Gathering, reviewing and verifying contractor information as part of the due-diligence process. Analysing leading and lagging performance indicators. Driving safety through feedback, benchmarking, and continual improvement.

scholarly journals Developing A Case-Based Reasoning Model for Safety Accident Pre-Control and Decision Making in the Construction Industry

2019 ◽  
Vol 16 (9) ◽  
pp. 1511 ◽  
Author(s):  
Yikun Su ◽  
Shijing Yang ◽  
Kangning Liu ◽  
Kaicheng Hua ◽  
Qi Yao
Keyword(s):  
Decision Making ◽  
Safety Management ◽  
Construction Safety ◽  
Case Based Reasoning ◽  
Prevention Measures ◽  
Proposed Model ◽  
Unsafe Behavior ◽  
Safety Accident ◽  
Construction Safety Management ◽  
Case Based

Case-based reasoning (CBR) has been extensively employed in various construction management areas, involving construction cost prediction, duration estimation, risk management, tendering, bidding and procurement. However, there has been a dearth of research integrating CBR with construction safety management for preventing safety accidents. This paper proposes a CBR model which focuses on case retrieval and reuse to provide safety solutions for new problems. It begins with the identification of case problem attribute and solution attribute, the state of hazard is used to describe the problem attribute based on principles of people’s unsafe behavior and objective’s unsafe state. Frame-based knowledge representation method is adopted to establish the case database from dimensions of slot, facet and facet’s value. Besides, cloud graph method is introduced to determine the attribute weight through analyzing the numerical characteristics of expectation value, entropy value and hyper entropy value. Next, thesaurus method is employed to calculate the similarity between cases including word level similarity and sentence level similarity. Principles and procedures have been provided on case revise and case retain. Finally, a real-world case is conducted to illustrate the applicability and effectiveness of the proposed model. Considering the high potential for pre-control and decision-making of construction safety accident, the proposed model is expected to contribute safety managers to take decisions on prevention measures more efficiently.

scholarly journals Formulasi dan karakteristik nutrimat bar berbasis tepung kacang kedelai (glycine max. L) dan tepung kacang merah (phaseolus vulgaris. L) sebagai makanan pasien kemoterapi

2017 ◽  
Vol 5 (2) ◽  
pp. 133-139
Author(s):  
I Gusti Agung Gede Wiranata ◽  
Dylla Hanggaeni Dyah Puspaningrum ◽  
I Gusti Ayu Wita Kusumawati
Keyword(s):  
Content Analysis ◽  
Data Analysis ◽  
Nutrient Content ◽  
Real Difference ◽  
Phaseolus Vulgaris L ◽  
Characteristic Analysis ◽  
Good Characteristic ◽  
Antioxidant Agents ◽  
Glycine Max L ◽  
Chemotherapy Patients

Background : The potency of soybeans and red beans as the source of antioxidant agents is very interesting to be developed as snack bar for chemotherapy patients. Nutrimat bar is made with addition of soybeans flour and red beans flour. The correct formulation will result in good characteristic of nutrimat bar. Methods : This research used Complete Random Design (RAL) with five types of treatment and three times of repetition. The formulations of soybeans flour and red beans flour being used were P1 (0:100); P2 (25:75); P3 (50:50); P4 (75:25); and P5 (100:0). Analysis to nutrimat bar was sensory characteristic analysis (taste, flavor, color and texture) and nutrient content analysis (protein, fat, carbohydrate and antioxidant). Data analysis used ANOVA with further testing of Smallest Real Difference (BNT). Results : The result of research shows that formulation with addition of soybeans flour and read beans flour has an effect towards characteristic of nutrimat bar quality being produced. Conclusion : The best nutrimat bar is made from formulation of P2 (soybeans flour of 25% and red beans flour of 75%) which producing characteristic of savory taste, non-rotten flavor, brown color and tender texture, with nutrient content value of protein at 12.75 g, fat at 4.71 g, carbohydrate at 35.36 g and antioxidant at 84.69 mg/L Galic Acid Equivalent Antioxidan Capacity (GAEAC).

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