scholarly journals Risk Assessment in Urban Large-Scale Public Spaces Using Dempster-Shafer Theory: An Empirical Study in Ningbo, China

2019 ◽  
Vol 16 (16) ◽  
pp. 2942 ◽  
Author(s):  
Jibiao Zhou ◽  
Xinhua Mao ◽  
Yiting Wang ◽  
Minjie Zhang ◽  
Sheng Dong
Keyword(s):  
Risk Assessment ◽  
Empirical Study ◽  
Large Scale ◽  
Public Spaces ◽  
Primary Objective ◽  
Theory And Practice ◽  
Risk Level ◽  
Safety Risk ◽  
Dempster Shafer Theory ◽  
Shafer Theory

Urban Large-scale Public Spaces (ULPS) are important areas of urban culture and economic development, which are also places of the potential safety hazard. ULPS safety assessment has played a crucial role in the theory and practice of urban sustainable development. The primary objective of this study is to explore the interaction between ULPS safety risk and its influencing factors. In the first stage, an index sensitivity analysis method was applied to calculate and identify the safety risk assessment index system. Next, a Delphi method and information entropy method were also applied to collect and calculate the weight of risk assessment indicators. In the second stage, a Dempster-Shafer Theory (DST) method with evidence fusion technique was utilized to analyze the interaction between the ULPS safety risk level and the multiple-index variables, measured by four observed performance indicators, i.e., environmental factor, human factor, equipment factor, and management factor. Finally, an empirical study of DST approach for ULPS safety performance analysis was presented.

Constructing and Utilizing Video Ontology for Accurate and Fast Retrieval

2011 ◽  
Vol 2 (4) ◽  
pp. 59-75 ◽  
Author(s):  
Kimiaki Shirahama ◽  
Kuniaki Uehara
Keyword(s):  
Knowledge Base ◽  
Large Scale ◽  
Video Retrieval ◽  
Computational Cost ◽  
Semantic Content ◽  
Video Data ◽  
Experimental Results ◽  
Huge Number ◽  
Dempster Shafer Theory ◽  
Shafer Theory

This paper examines video retrieval based on Query-By-Example (QBE) approach, where shots relevant to a query are retrieved from large-scale video data based on their similarity to example shots. This involves two crucial problems: The first is that similarity in features does not necessarily imply similarity in semantic content. The second problem is an expensive computational cost to compute the similarity of a huge number of shots to example shots. The authors have developed a method that can filter a large number of shots irrelevant to a query, based on a video ontology that is knowledge base about concepts displayed in a shot. The method utilizes various concept relationships (e.g., generalization/specialization, sibling, part-of, and co-occurrence) defined in the video ontology. In addition, although the video ontology assumes that shots are accurately annotated with concepts, accurate annotation is difficult due to the diversity of forms and appearances of the concepts. Dempster-Shafer theory is used to account the uncertainty in determining the relevance of a shot based on inaccurate annotation of this shot. Experimental results on TRECVID 2009 video data validate the effectiveness of the method.

scholarly journals Public Safety Risk Assessment of Power Investment Project Based on Fuzzy Set and DS Evidence Theory

2020 ◽  
Vol 143 ◽  
pp. 02009
Author(s):  
Tai-hua Yang ◽  
Jing Qin ◽  
Zhi-xiang Li
Keyword(s):  
Risk Assessment ◽  
Fuzzy Set ◽  
Public Safety ◽  
Evidence Theory ◽  
Investment Project ◽  
Public Security ◽  
Risk Level ◽  
Security Risk ◽  
Safety Risk ◽  
Assessment Index

In recent years, the international situation has become more and more complex, and the regional conflicts have been escalating, and the risks of overseas public security have been increasing. Based on the four types of public security events, a public safety risk assessment index system of "one belt and one road" electric power investment project is established. Combining the Bayesian network model, and using fuzzy set and DS evidence theory, the public security risk level of the “Belt and Road” countries can be this method has been effectively verified and put forward countermeasures by an example.

scholarly journals MEVA - a new method of occupational health and safety risk assessment

2019 ◽  
Vol 290 ◽  
pp. 12008
Author(s):  
Doru-Costin Darabont ◽  
Eduard Smîdu ◽  
Alina Trifu ◽  
Vicențiu Ciocîrlea ◽  
Iulian Ivan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Occupational Health ◽  
Deductive Reasoning ◽  
Health And Safety ◽  
Occupational Health And Safety ◽  
New Method ◽  
Risk Level ◽  
Simple Method ◽  
Safety Risk

The paper describes a new method of occupational health and safety risk assessment. This method, called MEVA, unlike the old ones, focuses more on reduce or eliminate subjective issues in determining the probability of manifestation of risk factors and is based on a deductive reasoning, with the help of which is studied the chain between two or more events. The novelty of the method consists in combining risk assessment techniques with evaluation of compliance with legal and other requirements, aiming to provide a more objective results of the risk assessment. In the MEVA method, the risk matrix is defined by 5 classes of severity and 5 probability classes, resulting in 5 levels of risk. After quantifying the risk factors, prevention measures are proposed for all the identified risk factors and each partial risk level is recalculated as a result of the proposed measures. The five levels of risk were grouped into three categories: acceptable, tolerable and unacceptable. The MEVA method is a simple method and it can be used for assessing various workplaces, with different characteristics of complexity, activity domain or occupational health and safety recordings.

A categorical approach to the semantics of argumentation

1996 ◽  
Vol 6 (2) ◽  
pp. 167-188 ◽  
Author(s):  
Simon Ambler
Keyword(s):  
Large Scale ◽  
Formal Semantics ◽  
Reasoning Under Uncertainty ◽  
Enriched Category ◽  
Closed Category ◽  
Dempster Shafer Theory ◽  
Medical Expert System ◽  
Shafer Theory ◽  
Theory Of Evidence ◽  
Cartesian Closed

Argumentation is a proof theoretic paradigm for reasoning under uncertainty. Whereas a ‘proof’ establishes its conclusion outright, an ‘argument’ can only lend a measure of support. Thus, the process of argumentation consists of identifying all the arguments for a particular hypothesis φ, and then calculating the support for φ from the weight attached to these individual arguments. Argumentation has been incorporated as the inference mechanism of a large scale medical expert system, the ‘Oxford System of Medicine’ (OSM), and it is therefore important to demonstrate that the approach is theoretically justified. This paper provides a formal semantics for the notion of argument embodied in the OSM. We present a categorical account in which arguments are the arrows of a semilattice enriched category. The axioms of a cartesian closed category are modified to give the notion of an ‘evidential closed category’, and we show that this provides the correct enriched setting in which to model the connectives of conjunction (&) and implication (⇒).Finally, we develop a theory of ‘confidence measures’ over such categories, and relate this to the Dempster-Shafer theory of evidence.

scholarly journals Construction Safety Risk Assessment of Large-Sized Deep Drainage Tunnel Projects

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Hu ◽  
Junwu Wang ◽  
Han Wu
Keyword(s):  
Risk Assessment ◽  
Fuzzy Comprehensive Evaluation ◽  
Construction Safety ◽  
Assessment Model ◽  
Economic Losses ◽  
Risk Level ◽  
Deep Drainage ◽  
Safety Risk ◽  
Drainage Tunnel ◽  
Weight Method

Frequent extreme climate events and rapid global urbanization have amplified the occurrence of accidents such as waterlogging or the overflow of pollution in big cities. This has increased the application scenarios of large-sized deep drainage tunnel projects (LSDDTPs). The scientific and accurate evaluation of the construction safety risks of LSDDTP can effectively reduce the corresponding economic losses and casualties. In this paper, we employed the hierarchical holographic model to construct the safety risk list of LSDDTPs in terms of the risk source and construction unit. Based on social network analysis, we then screened key indicators and calculated the weights of all secondary indicators from the correlation between risk factors. We subsequently developed a construction safety risk assessment model of LSDDTPs based on the matter-element extension method. The Donghu Deep Tunnel Project in Wuhan, China, was selected as a case study for the proposed method. The results of empirical research demonstrated that eight indicators (e.g., failure to effectively detect the change of the surrounding environment of the tunnel project) were key factors affecting the construction safety risk of IV, which is within the acceptable risk level. Our proposed model outperformed other methods (the fuzzy comprehensive evaluation, analytic hierarchy process, entropy weight method, and comprehensive weight method) in terms of scientific validity and research advancements.

Research on Safety Risk Assessment of Large-Scale Railway Passenger Station

2013 ◽  
Vol 361-363 ◽  
pp. 1923-1926 ◽  
Author(s):  
Ya Jing Lan ◽  
Bao Ming Han ◽  
De Wei Li
Keyword(s):  
Risk Assessment ◽  
Risk Analysis ◽  
Large Scale ◽  
Railway Station ◽  
Safety Risk ◽  
Analysis Phase ◽  
Preparation Phase ◽  
Railway Passenger ◽  
Definition Phase ◽  
Passenger Station

Firstly, this paper expounds the concept of the safety risk assessment of large-scale railway passenger station. Then this paper introduces the overall process of safety risk assessment of passenger station, included assessment preparation phase, factors definition phase and Risk analysis phase. At last, as Beijing South Railway Station as an example, it expounds how to assess the risks and put forward some suggestions.

Sign in / Sign up

Export Citation Format

Share Document