Comprehensive Risk Evaluation Research Articles

Placental transfer of bisphenol diglycidyl ethers (BDGEs) and its association with maternal health in a population in South of China

Despite high production and usage, little is known about exposure to bisphenol diglycidyl ethers (BDGEs) and their derivatives in pregnant women and fetuses. In this study, we determined nine BDGEs in 106 paired maternal and cord serum samples collected from e-waste dismantling sites in South of China. Bisphenol A bis (2,3-dihydroxypropyl) glycidyl ether (BADGE·2H2O), bisphenol A (3-chloro-2-hydroxypropyl) (2,3-dihydroxypropyl) glycidyl ether (BADGE·HCl·H2O), and bisphenol F diglycidyl ether (BFDGE) were the major BDGEs, with median concentrations of 0.57, 4.07, and 1.60 ng/mL, respectively, in maternal serum, and of 3.58, 5.61, and 0.61 ng/mL, respectively, in cord serum. The transplacental transfer efficiencies (TTEs) were estimated for BDGEs found in samples, and median values were in the range of 0.98 (BFDGE) to 5.91 (BADGE·2H2O). Our results suggested that passive diffusion plays a role in the placental transfer of BADGE·HCl·H2O and BFDGE, whereas several mechanisms contribute to the high accumulation of BADGE·2H2O in cord serum. Multiple linear regression analysis indicated significant associations between maternal serum concentrations of BDGEs and blood clinical biomarkers, especially those related to liver injuries, such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and adenosine deaminase (ADA) (P < 0.05). To our knowledge, this is the first study to report the occurrence of BDGEs in paired maternal–fetal serum samples and provide new insights into prenatal and fetal exposures. The newly discovered TTEs in maternal–fetal pairs contribute to a fuller inventory of the transmission activity of pollutants in the human body, ultimately adding to a more significant comprehensive risk evaluation.

Evaluation Cloud Model of Spontaneous Combustion Fire Risk in Coal Mines by Fusing Interval Gray Number and DEMATEL

Coal still occupies a key position in China’s energy consumption structure, and ensuring safe production in coal mines is a key focus for ensuring energy security. Spontaneous combustion fires in coal mines are a serious threat to the sustainability of safe production in coal mines. In order to prevent coal mine fire risk scientifically and effectively and to assess the level of disaster risk effectively and rationally, a study was conducted on the risk of spontaneous combustion fires in underground coal mines. An evaluation cloud model of spontaneous combustion fire risk in coal mines integrating the interval gray number with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) was established. Seventeen representative risk evaluation indicators were selected, and a coal mine spontaneous combustion fire risk evaluation index system was constructed based on four aspects: personnel, machinery, environment, and management. The interval gray number theory was introduced to improve the classical DEMATEL analysis method, which fully expresses the expert empirical knowledge and solves the problem of ambiguity and randomness in the semantic expression of expert evaluation. The relative importance of each indicator was determined by analyzing the influence relationships between risk evaluation indicators through the improved DEMATEL. A cloud model capable of transforming quantitative descriptions and qualitative concepts was used for comprehensive evaluation of risk, and based on the results of DEMATEL analysis, a comprehensive evaluation cloud model of coal mine spontaneous combustion fire risk was formed. Finally, the validity and practicality of the model were verified by using a mine in Shenmu City, Shaanxi Province, China as an example. This study provides a powerful tool to prevent spontaneous combustion fires in coal mines and makes a positive contribution to the sustainable development of coal mine safety management.

Comprehensive Risk Assessment of Satellite on-Orbit Operation

Aiming at the lack of research on quantitative evaluation of satellite on-orbit operation risk, this paper from two aspects: the special features and general quality characteristics analysis and identify factors that influence the satellite provide services, and on the basis build satellite on-orbit operation risk comprehensive evaluation index system. By combining analytic hierarchy process (AHP) and satellite availability evaluation model, this paper complete the research on comprehensive evaluation of satellite on-orbit operation risk. The results of the case show that the satellite is in good operating condition and capable of providing services normally. Thus, this method can realize the comprehensive quantitative evaluation of the actual operational risks of satellites on-orbit, find out the weak points of risks according to the evaluation results, and provide effective support for the operational health management of satellites on-orbit.

Spatio-temporal evaluation of electricity price risk considering multiple uncertainties under extreme cold weather

The increasing frequency of long-lasting price spikes in electricity markets caused by extreme weather has brought unbearable economic burdens to both electricity consumers and retailers, attracting wide attention on price risk evaluation and prevention. However, the precise and comprehensive evaluation of price risks has been hindered by the lack of spatio-temporal feature analysis and multi-uncertainty fusion modeling, including random failures, rapid surges in electricity demands and natural gas prices under extreme cold weather. To address this, a spatio-temporal evaluation model of electricity price risk considering the synthetic effects of multiple uncertainties is proposed based on the universal generating function (UGF) technique. Firstly, the UGF representations of standardized probabilistic models for different uncertainty factors induced by freezing temperatures are developed. On this basis, the market price calculation (MPC) operator is proposed to obtain the probabilistic model of the electricity market by aggregating these UGFs. Moreover, the spatio-temporal price risk indices are proposed to comprehensively evaluate the market risk level. Furthermore, the impact analysis based on sensitivity calculation is introduced to identify the most critical factor from multiple uncertainties. Case studies demonstrate that the extremely high price risks mainly occur during severe icing intervals and locate in the region away from major energy resources. Moreover, the surge in electricity demand is identified as the major factor for extremely high electricity prices. The findings can provide effective references for risk prevention and hedging for market operators and participants.

FIRE: A Finely Integrated Risk Evaluation Methodology for Life-Critical Embedded Systems

Life-critical embedded systems, including medical devices, are becoming increasingly interconnected and interoperable, providing great efficiency to the healthcare ecosystem. These systems incorporate complex software that plays a significantly integrative and critical role. However, this complexity substantially increases the potential for cybersecurity threats, which directly impact patients’ safety and privacy. With software continuing to play a fundamental role in life-critical embedded systems, maintaining its trustworthiness by incorporating fail-safe modes via a multimodal design is essential. Comprehensive and proactive evaluation and management of cybersecurity risks are essential from the very design to deployment and long-term management. In this paper, we present FIRE, a finely integrated risk evaluation methodology for life-critical embedded systems. Security risks are carefully evaluated in a bottom-up approach from operations-to-system modes by adopting and expanding well-established vulnerability scoring schemes for life-critical systems, considering the impact to patient health and data sensitivity. FIRE combines a static risk evaluation with runtime dynamic risk evaluation to establish comprehensive risk management throughout the lifecycle of the life-critical embedded system. We demonstrate the details and effectiveness of our methodology in systematically evaluating risks and conditions for risk mitigation with a smart connected insulin pump case study. Under normal conditions and eight different malware threats, the experimental results demonstrate effective threat mitigation by mode switching with a 0% false-positive mode switching rate.

The role of employee psychological stress assessment in reducing human resource turnover in enterprises.

In this paper, the model is constructed by measuring the psychological stress condition of employees; the psychological stress condition measurement model analyzes and tests the reasons for reducing human resource turnover in enterprises. In this paper, through the research related to the problem of talent loss in enterprises, we found that enterprises of other ownership often use the talent loss early warning model, to measure the possibility of talent loss in enterprises and issue an early warning, which enables enterprises to solve the talent loss crisis in time and minimize the negative impact of talent loss on enterprises. In this paper, we analyze the causes of human resource attrition risk from a theoretical point of view, construct a system of human resource attrition risk indicators for enterprises, and explain the content of each technical indicator and its measurement method. The PLS structural equation of the HR attrition risk evaluation model is established based on the constructed risk index system. In addition, the analysis of the causes of human resources turnover risk in the company also proposes strategies to avoid and prevent the threat. The PLS structural equation evaluation model of HR turnover risk is applied to various situations of human resource management to analyze the case of the comprehensive evaluation of HR turnover risk to guide the practical application of the model. Therefore, the research results of this paper have significant reference value for enterprises to solve similar human resource attrition problems. At the same time, it will provide a reference for enterprises to improve their human resource diagnostic capability and promote the development of human resource management.

COVID-19 medical waste transportation risk evaluation integrating type-2 fuzzy total interpretive structural modeling and Bayesian network

With the amount of medical waste rapidly increasing since the corona virus disease 2019 (COVID-19) pandemic, medical waste treatment risk evaluation has become an important task. The transportation of medical waste is an essential process of medical waste treatment. This paper aims to develop an integrated model to evaluate COVID-19 medical waste transportation risk by integrating an extended type-2 fuzzy total interpretive structural model (TISM) with a Bayesian network (BN). First, an interval type-2 fuzzy based transportation risk rating scale is introduced to help experts express uncertain evaluation information, in which a new double alpha-cut method is developed for the defuzzification of the interval type-2 fuzzy numbers (IT2FNs). Second, TISM is combined with IT2FNs to construct a hierarchical structural model of COVID-19 medical waste transportation risk factors under a high uncertain environment; a new bidirectional extraction method is proposed to describe the hierarchy of risk factors more reasonably and accurately. Third, the BN is integrated with IT2FNs to make a comprehensive medical waste transportation risk evaluation, including identifying the sensitive factors and diagnosing the event's causation. Then, a case study of COVID-19 medical waste transportation is displayed to demonstrate the effectiveness of the proposed model. Further, a comparison of the proposed model with the traditional TISM and BN model is conducted to stress the advantages of the proposed model.

Fire safety assessment for older adults in high-rise residential buildings in India: a comprehensive study

PurposeThe statistics show that older adults have been major fire victims in high-rise buildings. However, the fire safety building codes in most countries are not inclusive and do not reflect provisions for older adults. The research aims to develop a fire risk assessment index system for older adults living in high-rise residential buildings in India. The study further develops a fire rating system to improve fire safety provisions in high-rise buildings in India.Design/methodology/approachThe paper employs Delphi, analytic hierarchy process (AHP) and fuzzy comprehensive risk evaluation techniques. It considers 18 in-depth interviews and group discussions with builders, developers, architects, policymakers, and fire safety experts and consultants to develop a fire risk assessment system for older occupants living in high-rise residential buildings in India.FindingsThe fire protection systems and fire management systems are not as per the needs of older adults. The egress system components need improvisation considering the challenges of older adults.Research limitations/implicationsThe study is limited to older adults living in high-rise residential buildings in the capital city of Gujarat, Ahmedabad.Practical implicationsThis study will assist policymakers in developing fire safety standards that are targeted to the needs of older persons living in high-rise residential buildings during a fire evacuation.Originality/valueWhile several approaches for measuring fire risk in high-rise residential buildings exist, no such system has been developed specifically for older adults in India.

Implementing comprehensive pharmacogenomics in a community hospital–associated primary care setting

BackgroundPharmacogenomics (PGx) is an emerging field. Many drug-gene interactions are known but not yet routinely addressed in clinical practice. Therefore, there is a significant gap in care, necessitating development of implementation strategies. ObjectiveThe objective of the study was to assess the impact of implementing a PGx practice model which incorporates comprehensive pharmacogenomic risk evaluation, testing and medication optimization administered by 7 PGx-certified ambulatory care pharmacists embedded across 30 primary care clinic sites. MethodsPharmacogenomic services were implemented in 30 primary care clinics within the Cincinnati, Ohio area. Patients are identified for pharmacogenomic testing using a clinical decision support tool (CDST) that is fully integrated in the electronic medical record (EMR) or by provider designation (e.g., psychotropic drug failure). Pharmacogenomic testing is performed via buccal swab using standardized clinic processes. Discrete data results are returned directly into the EMR/CDST for review by PGx-certified ambulatory care pharmacists. Recommendations and prescriptive changes are then discussed and implemented as a collaborative effort between pharmacist, primary care provider, specialists, and patient. ResultsA total of 422 unique interactions were assessed by the embedded ambulatory care PGx pharmacists (N = 7) during this interim analysis. About half (213) were pharmacogenomic interactions, and of these, 124 were actionable. When an intervention was actionable, 82% of the time a change in medication was recommended. The underlying reasons for recommending therapy alterations were most commonly ineffective therapy (43%), adverse drug reaction prevented (34%), or adverse drug reaction observed (13%). ConclusionVariations in drug metabolism, response, and tolerability can negatively impact patient outcomes across many disease states and treatment specialties. Incorporation of pharmacogenomic testing with accessible clinical decision support into the team-based care model allows for a truly comprehensive review and optimization of medications. Our initial analysis suggests that comprehensive PGx testing should be considered to enhance medication safety and efficacy in at-risk patients.

C. elegans toxicant responses vary among genetically diverse individuals

The genetic variability of toxicant responses among indisviduals in humans and mammalian models requires practically untenable sample sizes to create comprehensive chemical hazard risk evaluations. To address this need, tractable model systems enable reproducible and efficient experimental workflows to collect high-replication measurements of exposure cohorts. Caenorhabditis elegans is a premier toxicology model that has revolutionized our understanding of cellular responses to environmental pollutants and boasts robust genomic resources and high levels of genetic variation across the species. In this study, we performed dose-response analysis across 23 environmental toxicants using eight C. elegans strains representative of species-wide genetic diversity. We observed substantial variation in EC10 estimates and slope parameter estimates of dose-response curves of different strains, demonstrating that genetic background is a significant driver of differential toxicant susceptibility. We also showed that, across all toxicants, at least one C. elegans strain exhibited a significantly different EC10 or slope estimate compared to the reference strain, N2 (PD1074), indicating that population-wide differences among strains are necessary to understand responses to toxicants. Moreover, we quantified the heritability of responses (phenotypic variance attributable to genetic differences between individuals) to each toxicant exposure and observed a correlation between the exposure closest to the species-agnostic EC10 estimate and the exposure that exhibited the most heritable response. At least 20% of the variance in susceptibility to at least one exposure level of each compound was explained by genetic differences among the eight C. elegans strains. Taken together, these results provide robust evidence that heritable genetic variation explains differential susceptibility across an array of environmental pollutants and that genetically diverse C. elegans strains should be deployed to aid high-throughput toxicological screening efforts.

Cancer risk assessment models versus National Comprehensive Cancer Network guidelines: What is the most comprehensive method to assess cancer risk and triage for genetic testing? (373)

Cancer risk assessment models versus National Comprehensive Cancer Network guidelines: What is the most comprehensive method to assess cancer risk and triage for genetic testing? (373)

Structure identification and toxicity evaluation of one newly-discovered dechlorinated photoproducts of chlorpyrifos.

Chlorpyrifos (CPF) is an extensively used organophosphorus pesticide. Recently, it has attracted increasing attention due to environmental health problems caused by it. Although numerous studies have discovered the dechlorinated photoproduct of CPF, its structure and toxicity remain largely unknown. In this study, we systematically investigated the structure and toxicity of dechlorinated photoproduct of CPF. The CPF degradation experiment was performed, and its products were identified by ultra high performance liquid chromatography-orbitrap fusion tribid mass spectrometer (UHPLC-Orbitrap Fusion TMS). Additionally, bond dissociation energy (BDE) calculations and photoproduct chemical synthesis were employed to determine the structure of dechlorinated photoproduct of CPF. The toxicity of CPF photoproduct was evaluated through the Ecological Structure Activity Relationships (ECOSAR) Class Program, the Toxicity Estimation Software Tool (T.E.S.T.) software, and acute toxicity testing. The results indicated that the dechlorinated photoproduct of CPF was identified as O,O-Diethyl-O-(3,5-dichloro-2-pyridyl) phosphorothioate (Dechloro-CPF), which was produced in large quantity within the first 30min of photodegradation experiment. The acute and chronic toxicity values of Dechloro-CPF were obviously higher than those for the other two photoproducts. The median lethal dose (LD50) of Dechloro-CPF was 31.6mg/kg for female mice and 58.4mg/kg for male mice. This study reveals the photodegradation mechanism of CPF and confirms that Dechloro-CPF was dechlorinated photoproduct of CPF with potential acute toxicity to aquatic species and mammalian (including human). Our findings will contribute to a more comprehensive risk evaluation of CPF in food and the environment.

Investigating transport kinetics of polystyrene nanoplastics in saturated porous media

Understanding the fate and transport of polystyrene nanoparticles (PSNPs) in porous media under various conditions is necessary for evaluating and predicting environmental risks caused by microplastics. The transport kinetics of PSNPs are investigated by column experiment and numerical model. The surface of DLVO interaction energy is calculated to analyze and predict the adsorption and aggregation of PSNPs in porous media, which the critical ionic strength of PSNPs can be accurately investigated. The results of the DLVO energy surface suggest that when the concentration of Na+ increases from 1 mM to 50 mM, the DLVO energy barrier of PSNPs-silica sand (SS) decreases from 78.37 kT to 5.46 kT. As a result, PSNPs are easily adsorbed on the surface of SS and the mobility of PSNPs is reduced under the condition of a high concentration of Na+ (PSNPs recovery rate decreases from 62.16% to 3.65%). When the concentration of Ca2+ increases from 0.1 mM to 5 mM, the DLVO energy barrier of PSNPs-SS decreases from 12.10 kT to 1.90 kT, and PSNPs recovery rate decreases from 82.46% to 4.27%. Experimental and model results showed that PSNPs mobility is enhanced by increasing initial concentration, flow velocity and grain size of SS, while the mobility of PSNPs with larger particle diameter is lower. Regression analysis suggests that kinetic parameters related to PSNPs mobility are correlated with DLVO energy barriers. The environmental behavior and mechanism of PSNPs transport in porous media are further investigated in this study, which provides a scientific basis for the systematic and comprehensive evaluation of the environmental risk and ecological safety of nano-plastic particles in the groundwater system.

Flood risk analysis of reservoirs based on full-series ARIMA model under climate change

• A novel full-series ARIMA stochastic model has been built. • This model can reflect the statistical characteristics of past and future floods. • The BMA method was utilized to analyze the uncertainty of flood frequency curves. • More comprehensive and reliable flood risks considering the weight of each GCM have been obtained. To assess the flood risks of reservoirs in a changing environment, this study considers the uncertainty of future floods and argues that the future flood projected by Global Climate Models (GCMs) is only one of the possibilities. This possibility contains some main statistical characteristics of future floods. The autoregressive integrated moving average (ARIMA) model was used to extract such statistical characteristics of the future flood series. Moreover, the initial values of the model were assumed to obey the probability distribution derived from historical floods. Hence, a novel full-series ARIMA stochastic model which can simultaneously reflect the statistical characteristics of past and future floods has been built to simulate the possible future extreme floods. Synthetic flood series under different future climate scenarios were randomly generated by the proposed model. Then the flood risks exceeding the design flood and check flood can be obtained. The Bayesian model averaging (BMA) method was used to weight the flood risks projected by each GCM to better incorporate the uncertainty of GCMs. The Yangfanggou Reservoir in Yalong River basin of China was selected as a case study. The future flood risks under three Representative Concentration Pathways (RCPs) were assessed. The results highlight that future flood risks have an increasing trend. Under future RCP2.6, RCP4.5 and RCP8.5 scenarios, the risk rates of exceeding design flood are in the range of 0.63%–0.74%, 1.31%–4.58% and 2.63%–5.23%, respectively. The risk rates of exceeding check flood are in the range of 0.20%–0.25%, 0.41%–2.14% and 0.97%–2.48%, respectively. This study provides a comprehensive evaluation of flood risk and could be useful when planning to fortify existing structures and update design standards.

Sustainability risk assessment of blockchain adoption in sustainable supply chain: An integrated method

Blockchain technology improves the transparency and traceability of sustainable supply chain management (SSCM). The merits of introducing blockchain technology are fully discussed. However, the potential sustainability risks of introducing blockchain technology to SSCM, such as excessive energy consumption and additional operating training costs, are less considered. This paper aims to ascertain and evaluate the sustainability risk factors of applying blockchain technology to SSCM. Based on the triple bottom line, the risk factors are grouped into three categories, i.e., environmental risk factors, economic risk factors, and social risk factors. This paper proposes a comprehensive risk evaluation framework for adopting blockchain to SSCM considering severity (S), occurrence (O), detection (D), and response(R) of risk factors. Then, a new risk analysis method is developed. The proposed new approach integrates the strength of Best-Worst Method (BWM) in reducing the decision makers’ burden of pairwise comparisons of risk criteria importance, and the merit of rough Combined Compromise Solution method (CoCoSo) in flexibly handling incomplete and vague information without much priori information, which makes the results of risk analysis more accurate. The results demonstrate that increased training costs, and resource waste due to repeated audits and certifications are the two most prominent risk factors. These findings give practitioners managerial insights on blockchain technology application in SSCM.

A new and integrated approach to evaluate the environmental and ecotoxicological impact of herbicide mixtures: A case study in maize

An index-based approach for a comprehensive evaluation of the potential risk for active substances and their mixtures to impact the environment was developed. Some of the indices considered already exist (PRISW-1, Priority Index), while others were created ex novo from indicators available on open-source platforms (PESTi, ECOi, AGROi). These indices maybe used for an evaluation before use of pesticides by farmers and advisers. The present approach was initially validated for herbicides in maize crops, but it can readily be applied to other PPPs and crops. PESTi index underline the physical and chemical characteristics as a whole, not considering the impact of other factors such as application rate or period of application. Hence, this index may underestimate the risk associated to a certain chemical. AGROi has a precautionary approach. The risk associated to a specific mixture derives from a combination of intrinsic characteristics of the chemicals, agronomic impacts, regulation restrictions and potential hazard to water compartment. The ECOi index is focused on the ecotoxicological impact against non-target organisms. The helpfulness of this index stands in its ability to easily discriminate the ecotoxicological impact of chemicals using indicators commonly available in literature and without making complex calculations. PRISW-1 Index discriminate active substances according to their risk against three representative non-target organisms. However, due to the intrinsic characteristics of each pesticide, a high PRISW-1 value could not always mean an easy movement of the chemical via runoff waters. The information deriving from Priority index may certainly help public authorities to select chemicals to be detected in water monitoring campaigns.The application of these indices may represent a valid decision tool for public stakeholders in defining agricultural measures to reduce the externalities of pest control.

Comprehensive risk assessment of algae and shellfish in the middle route of South-to-North Water Diversion Project.

Since the main canal of the middle route of South-to-North Water Diversion Project was put into operation, the species, quantity, and biomass of algae and shellfish have responded quickly to the environment, and a single dominant species has appeared in the community, demonstrating the remarkably abnormal proliferation property of algae and shellfish. In order to evaluate the safety risk of abnormal proliferation of algae and shellfish in the middle route and realize dynamic analysis of all kinds of influencing factors, a comprehensive risk evaluation system of algae and shellfish in the middle route of South-to-North Water Diversion Project based on comprehensive weighting and four-element connection number was constructed by integrating the analytic hierarchy process (AHP) and the weight assignment theory of criteria importance through intercriteria (CRITIC). The system consists of 21 evaluation indexes selected from risk factors and carriers. Taking Henan section in the middle route as an example, comprehensive risk evaluation system of algae and shellfish in the middle route of South-to-North Water Diversion Project was applied to calculate the partial connection number of each order and obtain the risk development trend of each indicator. The results showed that algae and shellfish in the middle route were in a very safe state at the safety risk level of level I. Finally, reasonable measures to reduce the risks facing algae and shellfish in the middle route of South-to-North Water Diversion Project are given, which effectively make up the deficiency of existing evaluation methods.

Application of RESRAD and ERICA tools to estimate dose and cancer risk for artisanal gold mining in Nigeria

Despite the fact that disruption of the environment through mining of minerals poses severe radiological hazards, there is a dearth of radiological information from gold mining sites in Nigeria. In this study, state-of- the-art computational tools - RESRAD ONSITE, RESRAD OFFSITE and ERICA were applied to a typical representative artisanal goldmining area for a more comprehensive evaluation of radiological risks associated with artisanal gold mining in Nigeria. The estimated doses received by an offsite receptor is within the radiation basic safety limit, while for onsite receptor it is greater than the basic radiation safety limit. It was observed that onsite dwellers of the artisanal goldmining areas may suffer high cancer burden when compared with the US EPA acceptable levels. For non-human biota, the hazard quotient was greater than unity and the total dose rate per organism was greater than the screening dose rate of 10μGy h−1. It was observed that 232Th and 226Ra were the main contributors to the total dose and the pathways that contributed most to the dose were; external exposure (via direct and airborne radiation from soil and Radon) as well as water independent plant, meat and milk consumption. Therefore, monitoring food production will lead to an informed decision making and risk communication towards sustainable mining will contribute in minimizing the level of the anticipated risks as low as reasonably achievable.

Risk Assessment of Building Foundation Pit Construction Based on Fuzzy Hierarchical Comprehensive Evaluation Method

The safety of foundation pit construction is gaining widespread attention. In order to reduce the risks of foundation pit construction and avoid the safety problems brought by the pits, it is necessary to study the risks of foundation pit construction. This paper takes the actual construction of a building as the background. Firstly, the possible main risks of foundation pit construction were identified and summarized, and then, the evaluation index system was formed. Secondly, the risk levels of various types of foundation pit risks were derived through analytic hierarchy process (AHP). In the expert scoring session of the Delphi method, the influences of both the degree of risk consequences and the probability of occurrence are combined. The risk value of the risk event is obtained in combination, which overcomes the bias problem of the traditional single assignment. Finally, an affiliation matrix was established to judge the affiliation of risk indicators to the risk level. The comprehensive risk evaluation level of this foundation pit project construction was assessed as level II. It is the degree of general risk.

Computer Network Information System Security Prevention Methods under the Background of Big Data

With the rapid development of modern society, the administrative information content rapid growth of e-government information resource sharing becomes the key of the government departments for effective social management. The cloud technology Internet big data are widely used and popular, which enable information resources to be shared among government data and are both an opportunity and challenge for effective e-government information resource sharing. It is of great significance to enhance government credibility. Information security risk assessment is a comprehensive evaluation of the potential risk of an uncertain stochastic process, traditional evaluation methods are deterministic models, and it is difficult to measure the security risk of uncertainty. On the other hand, with the opening and complexity of information system business functions, the nonlinearity and complexity of evaluation calculation also increase. By studying the relatively mature assessment criteria and methods in the field of information security, this study analyzes the information security status of small Internet of Things system based on the characteristics of Internet of Things information security. Combining the latest research results of information entropy neural network and other fields with the original risk assessment methods, the improved AHP information security risk assessment model is verified by simulation examples.