ROS2 Real-time Performance Optimization and Evaluation

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are required.The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application prototypes.Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system.However,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time computing.To achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2.The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT master.This paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems.This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.

Real-time lane departure warning system based on principal component analysis of grayscale distribution and risk evaluation model

A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.

Distribution,risk evaluation,and source analysis of the heavy metals in the sediment deposition of the lower Shichuanhe River,Shaanxi,China

In this study, 30 sediment samples were collected from the lower reaches of the Shichuanhe River in Xi’an, Shaanxi Province, China, to test the distribution of heavy metal elements in this area and for an analysis of the pollution levels of this area, hope to provide guidance on agricultural production activities in this region. The results show that the heavy metal elements in this area are mainly concentrated at the Qinghe River and Shichuanhe River confluences. Furthermore, the element contents are higher than that of the background levels of the continental crust(UCC) and close to the background levels of the soil from Shaanxi Province;the two most enriched elements are Cd and As, with contents of 0.79 and 22.7 mg·kg-1, respectively, and their contents are 3.8 and 1.72 times higher than that of the background values. Herein, the heavy metal pollution assessment methods applied indicated that Cd and As are the two most abundant pollutant elements in the area’s soils. As has a peak geo-accumulation index value of 3, and the pollution level is high, while Cd exhibits high potential ecological risks due to its high toxicity(potential risk index of 143) and an active fraction of more than 64%.In addition, a principal component analysis and hierarchical cluster analysis study showed that there are two sources of the heavy metals in this area. The Zn, As, Ni, Cu, Pb,and Cr are mainly from natural sources, and the Cd likely comes from a discharge of untreated agricultural wastewater in the region. The Cd which poses a high potential risk and mainly results from human activities, needs to be further monitored.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Establishment and evaluation of a risk prediction model for gestational diabetes mellitus

BACKGROUND Gestational diabetes mellitus(GDM)is a condition characterized by high blood sugar levels during pregnancy.The prevalence of GDM is on the rise globally,and this trend is particularly evident in China,which has emerged as a significant issue impacting the well-being of expectant mothers and their fetuses.Identifying and addressing GDM in a timely manner is crucial for maintaining the health of both expectant mothers and their developing fetuses.Therefore,this study aims to establish a risk prediction model for GDM and explore the effects of serum ferritin,blood glucose,and body mass index(BMI)on the occurrence of GDM.AIM To develop a risk prediction model to analyze factors leading to GDM,and evaluate its efficiency for early prevention.METHODS The clinical data of 406 pregnant women who underwent routine prenatal examination in Fujian Maternity and Child Health Hospital from April 2020 to December 2022 were retrospectively analyzed.According to whether GDM occurred,they were divided into two groups to analyze the related factors affecting GDM.Then,according to the weight of the relevant risk factors,the training set and the verification set were divided at a ratio of 7:3.Subsequently,a risk prediction model was established using logistic regression and random forest models,and the model was evaluated and verified.RESULTS Pre-pregnancy BMI,previous history of GDM or macrosomia,hypertension,hemoglobin(Hb)level,triglyceride level,family history of diabetes,serum ferritin,and fasting blood glucose levels during early pregnancy were determined.These factors were found to have a significant impact on the development of GDM(P<0.05).According to the nomogram model’s prediction of GDM in pregnancy,the area under the curve(AUC)was determined to be 0.883[95%confidence interval(CI):0.846-0.921],and the sensitivity and specificity were 74.1%and 87.6%,respectively.The top five variables in the random forest model for predicting the occurrence of GDM were serum ferritin,fasting blood glucose in early pregnancy,pre-pregnancy BMI,Hb level and triglyceride level.The random forest model achieved an AUC of 0.950(95%CI:0.927-0.973),the sensitivity was 84.8%,and the specificity was 91.4%.The Delong test showed that the AUC value of the random forest model was higher than that of the decision tree model(P<0.05).CONCLUSION The random forest model is superior to the nomogram model in predicting the risk of GDM.This method is helpful for early diagnosis and appropriate intervention of GDM.

Comparison of delay compensation methods for real-time hybrid simulation using frequency-domain evaluation index

The delay compensation method plays an essential role in maintaining the stability and achieving accurate real-time hybrid simulation results. The effectiveness of various compensation methods in different test scenarios, however, needs to be quantitatively evaluated. In this study, four compensation methods （i.e., the polynomial extrapolation, the linear acceleration extrapolation, the inverse compensation and the adaptive inverse compensation） are selected and compared experimentally using a frequency evaluation index （FEI） method. The effectiveness of the FEI method is first verified through comparison with the discrete transfer fimction approach for compensation methods assuming constant delay. Incomparable advantage is further demonstrated for the FEI method when applied to adaptive compensation methods, where the discrete transfer function approach is difficult to implement. Both numerical simulation and laboratory tests with predefined displacements are conducted using sinusoidal signals and random signals as inputs. Findings from numerical simulation and experimental results demonstrate that the FEI method is an efficient and effective approach to compare the performance of different compensation methods, especially for those requiring adaptation of compensation parameters.

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.

Risk-based evaluation on geological environment carrying capacity of mountain city - A case study in Suide County, Shaanxi Province, China

With the rapid development and expansion of the cities in China, the carrying capacity of resource and environment has become a huge concern for local governments. From the perspective of geological environment, geological disasters are the main restraining factor of the development in mountain cities. This study was conducted in Suide County of Shaanxi Province with a risk-based approach as followed: a hazard analysis on geological disasters based on a slope geological survey at a scale of 1:10,000; a consequence analysis based on unmanned aerial vehicle(UAV) aerial survey data; integrating the results of hazard analysis and consequence analysis, a risk zonation and analysis of geological disasters in urban areas were completed considering urban planning, land use planning and the safety of infrastructure and major engineering. Subsequently, taking the acceptable levels of human life and property risks incurred by landslides as the criteria of the evaluation of geological environment carrying capacity, a comprehensive assessment of current and future urban carrying capacity was conducted based on the results of the risk analyses. Accordingly, the prior development zone, the restricted development zone and the prohibited zone were delineated, with corresponding suggestions for future urban development. The technological and methodological system used in the study can be applied to geological environment carrying capacity evaluation of other important mountain cities, which can provide scientific basis for the optimization of land and space.

Improved AHP–TOPSIS model for the comprehensive risk evaluation of oil and gas pipelines

A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)is established to identify potential hazards in time.First,a barrier model and fault tree analysis are used to establish an index system for oil and gas pipeline risk evaluation on the basis of five important factors:corrosion,external interference,material/construction,natural disasters,and function and operation.Next,the index weight for oil and gas pipeline risk evaluation is computed by applying the improved AHP based on the five-scale method.Then,the TOPSIS of a multi-attribute decision-making theory is studied.The method for determining positive/negative ideal solutions and the normalized equation for benefit/cost indexes is improved to render TOPSIS applicable for the comprehensive risk evaluation of pipelines.The closeness coefficient of oil and gas pipelines is calculated by applying the improved TOPSIS.Finally,the weight and the closeness coefficient are combined to determine the risk level of pipelines.Empirical research using a long-distance pipeline as an example is conducted,and adjustment factors are used to verify the model.Results show that the risk evaluation model of oil and gas pipelines based on the improved AHP–TOPSIS is valuable and feasible.The model comprehensively considers the risk factors of oil and gas pipelines and provides comprehensive,rational,and scientific evaluation results.It represents a new decision-making method for systems engineering in pipeline enterprises and provides a comprehensive understanding of the safety status of oil and gas pipelines.The new system engineering decision-making method is important for preventing oil and gas pipeline accidents.

Seismic risk evaluation for a planning mountain tunnel using improved analytical hierarchy process based on extension theory

Seismic risk evaluation(SRE) in early stages(e.g., project planning and preliminary design)for a mountain tunnel located in seismic areas has the same importance as that in final stages(e.g.,performance-based design, structural analysis, and optimization). SRE for planning mountain tunnels bridges the gap between the planning on the macro level and the design/analysis on the micro level regarding the risk management of infrastructural systems. A transition from subjective or qualitative description to objective or quantitative quantification of seismic risk is aimed to improve the seismic behavior of the mountain tunnel and thus reduce the associated seismic risk. A new method of systematic SRE for the planning mountain tunnel was presented herein. The method employs extension theory(ET)and an ET-based improved analytical hierarchy process. Additionally, a new risk-classification criterion is proposed to classify and quantify the seismic risk for a planning mountain tunnel. This SRE method is applied to a mountain tunnel in southwest China, using the extension model based on matter element theory and dependent function operation.The reasonability and flexibility of the SRE method for application to the mountain tunnel are illustrated.According to different seismic risk levels and classification criteria, methods and measures for improving the seismic design are proposed, which can reduce the seismic risk and provide a frame of reference for elaborate seismic design.

Evaluation on the Risks of Agricultural Industrial Chain Based on FAHP——A Case of Regions Inhabited by Ethnic Groups in Wuling Mountain

Through recognizing the risking factors of industrial chain and selecting appropriate evaluation method, the index system on evaluating risking factors including market risk, natural risk, contact risk and efficiency risk in industrial chain is constructed,26 weighting indicators under the four layers are set up. Taking regions inhabited by ethnic groups in Wuling Mountain as an example, the risking factors of agricultural industrial chain in the area are analyzed by adopting the FAHP. The influencing degree of each risking factor on credit risks is analyzed. The results assume that with the market risk, contract risk, natural risk and efficiency risk. The natural risks become the principal risks of agricultural industrial chain and it should be paid much attention to. The low credit risk is a major factor that causes the contract between enterprise and rural households. The flood, pests, diseases and disasters also should be paid high attention to that is regarded as risking factors. The risking factors that come from the efficiency risk layer, for example, the unequal profit distribution among enterprises has little effect on enterprises in industrial chain. The research results provide evidence for stipulating risk prevention measures.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Reliability Risk Evaluation Method for Complex Mechanical System Based on Optimal Bayesian Network

In order to reduce the calculation of the failure probability in the complex mechanical system reliability risk evaluation,and to implement importance analysis of system components effectively,the system fault tree was converted into five different Bayesian network models. The Bayesian network with the minimum conditional probability table specification and the highest computation efficiency was selected as the optimal network. The two heuristics were used to optimize the Bayesian network. The fault diagnosis and causal reasoning of the system were implemented by using the selected Bayesian network. The calculation methods of Fussel-Vesely( FV),risk reduction worth( RRW),Birnbaum measure( BM) and risk achievement worth( RAW) importances were presented. A certain engine was taken as an application example to illustrate the proposed method. The results show that not only the correlation of the relevant variables in the system can be accurately expressed and the calculation complexity can be reduced,but also the relatively weak link in the system can be located accurately.

Health evaluation method for degrading systems subject to dependent competing risks

This paper proposes a health evaluation method for degrading systems subject to competing risks of dependent soft and hard failures. To characterize the time-varying degradation rate, the degradation process is determined by a non-stationary Gamma process and the soft failure is encountered when it exceeds a predefined critical level. For the hard failure, a Cox’s proportional hazard model is applied to describe the hazard rate of the time to system failure. The dependent relationship is modeled by incorporating the degradation process as a time-varying covariate into the Cox’s proportional hazard model. To facilitate the health characteristics evaluation, a discretization technique is applied both to the degradation process and the monitoring time.All health characteristics can be obtained in the explicit form using the transition probability matrix, which is computationally attractive for practical applications. Finally, a numerical analysis is carried out to show the effectiveness and the performance of the proposed health evaluation method.

Risk Evaluation on Logistics Finance of Agricultural Products Based on Fuzzy-AHP Model

The development of logistics finance business for agricultural products is the best way to realize the common interests of logistics enterprises,small and medium-sized agricultural product enterprises and financial institutions,which will contribute to the development of China's new socialist rural economy and the construction of " two-oriented society". As the agricultural products have some special attributes,it's easy to create the risk in carrying out the logistics finance business. The paper constructs a risk evaluation indicator system for logistics finance of agricultural product,and uses the Fuzzy-AHP model to evaluate. The results show that the comprehensive risk level is normal risk,which shows that third-party logistics enterprises can carry out the logistics financial business of agricultural products,but the risks from logistics enterprises and agricultural collateral need to be prevented.

Drought risk assessment in China:Evaluation framework and influencing factors

Global warming and rapid economic development have led to increased levels of disaster risk in China.Previous attempts at assessing drought risk were highly subjective in terms of assessment methods and selection of the assessment indicators and which resulted in appreciable uncertainty in the results of these risk assessments.Based on the assumption that areas with historically high drought losses are more likely to suffer future high drought losses,we develop a new drought risk assessment model that includes historical drought loss data.With this model,we map the regional differentiation of Chinese drought risk.Regions with high(extreme high)drought risk account for 4.3%of China’s area.Five significant high-risk areas have been identified:Northeast China,North China,the east part of Northwest China,the east part of Southwest China and a small part in the west of Northwest China.Areas with high and extreme high drought risk are dominant in the Heilongjiang Province,accounting for 32%of the total area,followed by the Ningxia Hui Autonomous Region,with 26%of total area.The contribution of each influencing factor has been quantified,which indicates that high-exposure and high-vulnerability account for the high-risk of drought.We recommend that measures like strengthening the protection of cultivated land and reducing dependence on the primary industry should be taken to mitigate to drought-induced losses.

Study of evaluation method for the overseas oil and gas investment based on risk compensation

The overseas oil and gas investment evaluation is one of the core tasks in overseas investment of oil and gas companies,among which risk evaluation and benefit evaluation are the most important.This paper sets forth transmission paths of risk factors to the investment benefit by identifying 14 overseas oil and gas investment risks in four categories.On the basis of the concept of risk compensation,different compensation mechanisms specific to each risk are designed.The risk and benefit are integrated objectively to develop a comprehensive evaluation model by correcting the recoverable reserve,adjusting benefit evaluation parameters such as investments on exploration and development,and compensating for the changes in risk factors with time through dynamic discount rate.Moreover,two cases studies,namely the evaluations of Project A in Sudan and comparison among Blocks A–G,are used to describe usage method and applicable scope of such evaluation model,respectively.According to the results,oil price is a key influencing factor for enterprise internal risk and industrial risk.Risk compensation reduces comprehensive benefit of overseas oil and gas investment and undermines the investment feasibility and priority of blocks.The research findings of this paper are free from the effects of some subject factors and avoid multi-objective decision making,and also avoid the undesired repeated calculation of risk factors.

Analysis and evaluation of enterprise risk management capability elements

Research on enterprise risk management capability is conducted with a view of discerning and processing risks, in which an evaluation index system and an evaluation model of enterprise risk management capabilities are constructed. The risk management capability consists of four aspects, i.e. risk identification capability, risk assessment capability, risk planning capability and risk control capability. Risk identification and assessment capabilities reflect the level of enterprises on finding and analyzing risks efficiently, while risk planning and control capabilities reflect the level of enterprises on resolving risks effectively. Each of capabilities is then further divided into more detailed elements based on the characteristics of enterprise development for a quantitative analysis of enterprise risk management capability. The approach adopted is a quantitative technique based on the use of fuzzy comprehensive evaluation. Finally, a case is pulled in to illustrate the feasibility of the method from an empirical perspective. This study is expected to be helpful for enterprises in cultivating their core capabilities.

Risk evaluation of natural disasters based on connection function

There are many uncertain factors,such as stochastic,fuzzy and gray information in the risk analysis on natural hazard.The set pair analysis(SPA)deals effectively with the various uncertain factors contributing to evaluation of the risk level of natural disasters.The evaluation indicators and standards of natural disasters risk are analyzed by identity-discrepancycontrary(IDC).The result,the connection numbers,still has uncertainty information.Thus,yielding the risk evaluation model of natural disasters based on connection function,which construct a set pair relation between the indicators of connection numbers and comprehensive evaluation standards,and describe uncertainty of the connection numbers by using connection function.The study showed that the proposed model takes into account only the uncertainty of risk evaluation indicator identification on natural disasters,also the uncertainty of result connection numbers.This approach gives full consideration to the uncertainty of systematic evaluation process along with the actual meaning of comprehensive evaluation functions.Therefore,this means it is able to reduce the uncertainty of final evaluation results and improve the accuracy and reasonability of evaluation results.This model is capable of reflecting actual situation of the risk evaluation on natural disaster affected by various uncertain factors and has a promotional value in the natural disaster risk assessment.

Researches on Risk Evaluation of Green Agro-product Closed Supply Chain

Closed supply chain is a superior form of management model of chain supply and an effective means of improving the modernization of agro-product circulation. Based on the research results of the current literatures on supply chain risk and agro-product supply chain, related subjects of the agro-product closed supply chain involving production, management and consumption are studied and analyzed and the primary risking factors in the supply chain system are classified as environmental risk, system risk, information risk, management risk and quality risk. Risk of agro-product closed supply chain is evaluated by using the method of fuzzy comprehensive evaluation and the values are acquired. The result shows that risk of agro-product closed supply chain is moderate with relatively high risk, which basically accords with the present actual situations. It can be seen from the index weights of various levels that the key first-level indices influencing the risks are system risk, information risk, quality and safety risk and the key second-level are the coordinating and controlling ability of core enterprises, the implementation of information traceability and the construction of quality safety system. Therefore, risk of agro-product closed supply chain should be reduced by taking prevention and controlling measures mainly from these aspects.