Risk Analysis of Passalora sequoiae Invasion to China with Imported Coniferous Wood

According to international standard plant quarantine measures and principle risk analysis(ISPM No.11),a risk assessment was carried out for Passalora sequoiae through geographical distribution,possibility of colonization,probability of diffusion,economic importance and difficulty in risk management.Results show that P.sequoiae has a greater risk of introduction and diffusion,and it has distributed in parts of China.It is suggested that P.sequoiae should be added to the list of forest dangerous pests in China.Besides,porting departments should focus on the pathogen on imported host seedlings like Cryptomeria.

Cusp Model for Risk Analysis

Aim To assess simultaneously various risk states of a system. Methods\ Using the catastrophe and fuzzy theory, the energy and uncertainty in a system are set as two control variables and the function of the system is used as the state variable for analysis. Results and Conclusion\ A risk analysis model named the cusp model is presented. Various states regarding the safety of the system such as the accident state, no accident state and miss state can be represented at will on the cusp model.

Risk analysis system of geo-hazard based on GIS technique

The socio-economic attribute of geo-hazard made us distinguish it from the traditional engineering geology study. It will get more social benefit from the analysis of the geo-hazard in the socio-economic attribute. The hazard and the vulnerability of the element controls the risk level of the regional geo-hazard. The risk analysis supported by GIS in geo-hazard study is one of the most important directions. Based on the author’s studies in recent years, a risk analysis system of regional geo-hazard (RiskAnly) has been developed on the basis of software MAPGIS. The paper introduces the train of system design, the structure and the workflow of RiskAnly. As a case study, the paper also deals with the risk zonation of the regional landslide hazard of China.

Rough Outlier Detection Based Security Risk Analysis Methodology

Security is a nonfunctional information system attribute that plays a crucial role in wide sensor network application domains. Security risk can be quantified as the combination of the probability that a sensor network system may fail and the evaluation of the severity of the damage caused by the failure. In this paper, we devise a methodology of Rough Outlier Detection (ROD) for the detection of security-based risk factor, which originates from violations of attack requirements (namely, attack risks). The methodology elaborates dimension reduction method to analyze the attack risk probability from high dimensional and nonlinear data set, and combines it with rough redundancy reduction and the distance measurement of kernel function which is obtained using the ROD. In this way, it is possible to determine the risky scenarios, and the analysis feedback can be used to improve the sensor network system design. We illustrate the methodology in the DARPA case set study using step-by-step approach and then prove that the method is effective in lowering the rate of false alarm.

Risk analysis of extended reach wells in the Liuhua Oilfield,South China Sea,based on comprehensive fuzzy evaluation method

Drilling engineering has great uncertainty and it always involves huge investment and high risk. Risk analysis of extended reach drilling （ERD） is very important to prevent complex failures and to improve drilling efficiency. Nowadays there are few reports on how to analyze quantitatively the drilling risk for extended reach wells （ERWs）. Based on the fuzzy set theory, a comprehensive fuzzy evaluation model for analyzing risks of ERD is proposed in this paper. Well B6ERW07 is a planned 8,000-meter ERW with a high ratio of horizontal displacement （HD） to vertical depth （VD） in the Liuhua Oilfield, the South China Sea, China. On the basis of the evaluation model developed in this study, the risk for drilling Well B6ERW07 was evaluated before drilling. The evaluation result shows that the success rate of drilling this well is predicted to be 51.9%, providing important rational and scientific information for the decisionmakers.

Fuzzy Risk Analysis of Harbour Engineering Investment by Hierarchy System Approach

The present risk analysis model of engineering investment is built by fuzzy hierarchy approach under the assumption of maximizing the revenues of the project during its whole life cycle of operation. It can reasonably be expressed by a system evaluation analysis. As a matter of fact, the system, aimed by its system goal can be modelled by a set of factors, constitutively structured by certain links between them, to form a factorial network chart, which represents the essentials of the system behaviours, the nodes of which represent the factors concerned. The weight distribution between factors located at the same level can be determined by the eigen-value problem of a 'pair comparison' relation matrix. The weight distribution of factors at each level is successively manipulated until the fuzzy synthetic risk assessment. As an example of risk analysis of engineering investment, a harbour construction project is presented for illustration.

Risk analysis for earth dam overtopping

In this paper, a model of overtopping risk under the joint effects of floods and wind waves, which is based on risk analysis theory and takes into account the uncertainties of floods, wind waves, reservoir capacity and discharge capacity of the spillway, is proposed and applied to the Chengbihe Reservoir in Baise City in Guangxi Zhuang Autonomous Region. The simulated results indicate that the flood control limiting level can be raised by 0.40 m under the condition that the reservoir overtopping risk is controlled within a mean variance of 5×10-6. As a result, the reservoir storage will increase to 16 million m3 and electrical energy generation and other functions of the reservoir will also increase greatly.

Debris Flows Risk Analysis and Direct Loss Estimation:the Case Study of Valtellina di Tirano,Italy

andslide risk analysis is one of the primary studies providing essential instructions to the subsequent risk management process. The quantification of tangible and intangible potential losses is a critical step because it provides essential data upon which judgments can be made and policy can be formulated. This study aims at quantifying direct economic losses from debris flows at a medium scale in the study area in Italian Central Alps. Available hazard maps were the main inputs of this study. These maps were overlaid with information concerning elements at risk and their economic value. Then, a combination of both market and construction values was used to obtain estimates of future economic losses. As a result, two direct economic risk maps were prepared together with risk curves, useful to summarize expected monetary damage against the respective hazard probability. Afterwards, a qualitative risk map derived using a risk matrix officially provided by the set of laws issued by the regional government, was prepared. The results delimit areas of high economic as well as strategic importance which might be affected by debris flows in the future. Aside from limitations and inaccuracies inherently included in risk analysis process, identification of high risk areas allows local authorities to focus their attention on the “hot-spots”, where important consequences may arise and local （large） scale analysis needs to be performed with more precise cost-effectiveness ratio. The risk maps can be also used by the local authorities to increase population’s adaptive capacity in the disaster prevention process.

A Bayesian Network Approach for Offshore Risk Analysis Through Linguistic Variables

This paper presents a new approach for offshore risk analysis that is capable of dealing with linguistic probabilities in Bayesian networks （ BNs）. In this paper, linguistic probabilities are used to describe occurrence likelihood of hazardous events that may cause possible accidents in offshore operations. In order to use fuzzy information, an f-weighted valuation function is proposed to transform linguistic judgements into crisp probability distributions which can be easily put into a BN to model causal relationships among risk factors. The use of linguistic variables makes it easier for human experts to express their knowledge, and the transformation of linguistic judgements into crisp probabilities can significantly save the cost of computation, modifying and maintaining a BN model. The flexibility of the method allows for multiple forms of information to be used to quantify model relationships, including formally assessed expert opinion when quantitative data are lacking, or when only qualitative or vague statements can be made. The model is a modular representation of uncertain knowledge caused due to randomness, vagueness and ignorance. This makes the risk analysis of offshore engineering systems more functional and easier in many assessment contexts. Specifically, the proposed f-weighted valuation function takes into account not only the dominating values, but also the a-level values that are ignored by conventional valuation methods. A case study of the collision risk between a Floating Production, Storage and Off-loading （FPSO） unit and the anthorised vessels due to human elements during operation is used to illustrate the application of the proposed model.

Risk Analysis and Assessment of Overtopping Concerning Sea Dikes in the Case of Storm Surge

Risk analysis and assessment relating coastal structures has been one of the hot topics in the area of coastal protection recently. In this paper, from three aspects of joint return period of multiple loads, dike failure rate and dike continuous risk prevention respectively, three new risk analysis methods concerning overtopping of sea dikes are developed. It is worth noting that the factors of storm surge which leads to overtopping are also considered in the three methods. In order to verify and estimate the effectiveness and reliability of the newly developed methods, quantified mutual information is adopted. By means of case testing, it can be found that different prior variables might be selected dividedly, according to the requirement of special engineering application or the dominance of loads. Based on the selection of prior variables, the correlating risk analysis method can be successfully applied to practical engineering.

Risk Analysis on Groundwater Resources Carrying Capacity Based on Blind Number Theory

Blind numbers of evaluation indices about groundwater resources carrying capacity are defined from the concomitancy of randomness, fuzziness, grey property and unascertainment of groundwater system. Based on fuzzy theory, a comprehensive evaluation model on groundwater resources carrying capacity is constructed with blind information. Then a risk assessment model of surcharge about groundwater resources carrying capacity is established on blind reliability theory. The probable value ＂＊＂ matrix of fuzzy membership degree about carrying capacity corresponding to each judgment level can be obtained with the aid of blind algorithm as well as the subjective reliability ＂×＂ matrix. And then a graph of ＂groundwater carrying capacity v.s. accumulative reliability＂ can be gained Based on the graph, fuzzy membership degree of groundwater resources carrying capacity to each judgment level under different risk probability can be got. Thus, a comparatively reasonable judgment to groundwater resources carrying capacity might be obtained, with comprehensive analysis to the state of society, economy technology and ecology.

Risk analysis of slope instability of levees under river sand mining conditions

Levees are affected by over-exploitation of river sand and river adjustments after the formation of sand pits. The slope stability is seriously threatened, drawing wide concern among experts and scholars in the area of water conservancy. This study analyzed the uncertainties of slope stability of levees under river sand mining conditions, including uncertainty caused by interest- driven over-exploitation by sand mining contractors, and uncertainty of the distance from the slope or sand pit to the bottom of the levee under the action of cross-flow force after the sand pit forms. Based on the results of uncertainty analysis, the distribution and related parameters of these uncertainties were estimated according to the Yangtze River sand mining practice. A risk model of the slope instability of a levee under river sand mining conditions was built, and the possibility of slope instability under different slope gradients in a certain reach of the Yangtze River was calculated with the Monte Carlo method and probability combination method. The results indicated that the probability of instability risk rose from 2.38% to 4.74% as the pits came into being.

Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.

Risk Analysis of Big Data Based on Cloud Computing for the Inspection and Testing of Toxic and Hazardous Substances in Meat Products

Large-scale data emerge in food safety inspection and testing industry with the development of Internet technology in China.This paper was aimed at designing toxic and hazardous substance big data risk analysis algorithm in food safety inspection and testing based on cloud computing^([1]).Cloud computing platform was set up to store the massive extensive data with geographical distribution,dynamic and high complexity from the Internet,and MapReduce^([2]) computational framework in cloud computing was applied to process and compute parallel data.The risk analysis results were obtained by analyzing 1000000 meat products testing data collected from the laboratory management information system based on web.The results show that food safety index IFS < 1,which proves that the food safety state is in good condition.

Study on risk analysis of supply chain enterprises

The sources of supply chain enterprise risk from different aspects including material flow, information flow, cash flow and partner relationship is analyzed. Measures for risk reduction have also been summarized from the aspects of risk sharing, information sharing, change of inventory control mode, and supply chain flexibility. Finally, problems in current research on supply chain risk management are pointed out and a discussion on future research trend is presented.

Risk Analysis of Sulfites Used as Food Additives in China

This study was to analyze the risk of sulfites in food consumed by the Chinese people and assess the health protection capability of maximum-permitted level （MPL） of sulfites in GB 2760-2011. Sulfites as food additives are overused or abused in many food categories. When the MPL in GB 2760-2011 was used as sulfites content in food, the intake of sulfites in most surveyed populations was lower than the acceptable daily intake （ADI）. Excess intake of sulfites was found in all the surveyed groups when a high percentile of sulfites in food was intaken. Moreover, children aged 1-6 years are at a high risk to intake excess sulfites. The primary cause for the excess intake of sulfites in Chinese people is the overuse and abuse of sulfites by the food industry. The current MPL of sulfites in GB 2760-2011 protects the health of most populations.

Input characteristics and risk analysis of ballast water from offshore entry ships in China

Large quantities of ballast water discharge from ocean going ships in sea ports of China is one of the important factorswhich cause the spread of aquatic nonindigenous harmful species isolated geographically by waters,the deteriorating environment of the near-shore water area and the frequent outbreaks of red tides.In this paper,the total amount of the ballast water input estimation model for entry ships in Chinese ports was established.The information of foreign trade shipping and the import and export goods released publicly by the State Department of Transportation and the State General Administration of Customs were investigated.And then,the input features and its ecological environment risk of ballast water in China's offshore entry ships from2007to2012were analyzed based on the established total input amounts of ballast water from entry ships to Chinese sea ports together with the ballast water input ratio of the five major port-groups in China.The results show that:the total ballast water input amounts from entry ships of the five major port-groups in China are extremely imbalanced.The most developed Yangtze River Delta in economy has the biggest total ballast water input amounts,103.61million tons in2012.The second is the Circum-Bohai Sea Region(73.66million tons)and the third is the Pearl River Delta(67.24million tons).The total ballast water input amounts of the northwest and the southwest coastal areas are less,only16.57and5.71million tons respectively.The large quantity of entry ships’ballast water discharge has been an enormous threat to ecological environment of our country's sea areas,especially to economically developed regions.

Sensitive Resource and Traffic Density Risk Analysis of Marine Spill Accidents Using Automated Identification System Big Data

This study developed a new methodology for analyzing the risk level of marine spill accidents from two perspectives,namely,marine traffic density and sensitive resources.Through a case study conducted in Busan,South Korea,detailed procedures of the methodology were proposed and its scalability was confirmed.To analyze the risk from a more detailed and microscopic viewpoint,vessel routes as hazard sources were delineated on the basis of automated identification system(AIS)big data.The outliers and errors of AIS big data were removed using the density-based spatial clustering of applications with noise algorithm,and a marine traffic density map was evaluated by combining all of the gridded routes.Vulnerability of marine environment was identified on the basis of the sensitive resource map constructed by the Korea Coast Guard in a similar manner to the National Oceanic and Atmospheric Administration environmental sensitivity index approach.In this study,aquaculture sites,water intake facilities of power plants,and beach/resort areas were selected as representative indicators for each category.The vulnerability values of neighboring cells decreased according to the Euclidean distance from the resource cells.Two resulting maps were aggregated to construct a final sensitive resource and traffic density(SRTD)risk analysis map of the Busan–Ulsan sea areas.We confirmed the effectiveness of SRTD risk analysis by comparing it with the actual marine spill accident records.Results show that all of the marine spill accidents in 2018 occurred within 2 km of high-risk cells(level 6 and above).Thus,if accident management and monitoring capabilities are concentrated on high-risk cells,which account for only 6.45%of the total study area,then it is expected that it will be possible to cope with most marine spill accidents effectively.

Seismic risk analysis of coastal area of Pakistan

Estimation of seismic hazard for the fast developing coastal area of Pakistan is carried out using deterministic and probabilistic approaches. On the basis of seismotectonics and geology, eleven faults are recognized in five seismic provinces as potential hazard sources. Maximum magnitude potential for each of these sources is calculated. Peak ground acceleration (PGA) values at the seven coastal cities due to the maximum credible earthquake on the relevant source are also obtained. Cities of Gwadar and Ormara with acceleration values of 0.21g and 0.25g respectively fall in the high seismic risk area. Cities of Turbat and Karachi lie in low seismic risk area with acceleration values of less than 0.1g. The Probabilistic PGA maps with contour interval of 0.05g for 50 and 100 years return period with 90% probability of non-exceedance are also compiled.

Risk Analysis of Industrial Internet Identity System

The risks of the current identity system represented by Domain Name System(DNS)and Object Identifier(OID)are studied.According to the characteristics of the industrial Internet Identity(Ⅲ)system,four open ecosystem planes are divided,and a corresponding risk analysis view is established to analyze risks for various planes.This paper uses Isaiah Berlin’s definition of liberty to more generally express the concept of security as positive rights and negative rights.In the risk analysis view,the target system is modeled from four dimensions:stakeholders,framework,architecture,and capability delivery.At last,three defensive lines are proposed to establish the identity credit system.