KnowGo: An Adaptive Learning-Based Multi-model Framework for Dynamic Automotive Risk Assessment

Crude distillation unit (CDU) generally exists severe corrosion. Risk-based inspection (RBI) technology can effectively assess risk of stationary equipment in petrochemical industry. Meanwhile, integrity operating window (IOW) can effectively control risk by establishing standard and critical limits. Limited of data integrated analysis and the complexity of interfaces connecting in different systems, current risk assessment of complete sets of equipment mainly adopted static method. API 584-2021describes the IOW parameters of the crude distillation unit, but there are few reports about how to apply the dynamic RBI and IOW in the field engineering to achieve real-time risk assessment and warning control of the safety operation boundary. Combining RBI and IOW technology, we recently developed a dynamic risk assessment and IOW warning system by interacting three types dynamic interface data, i.e., medium composition in laboratory information management system (LIMS), real-time process operation parameters in distributed control system (DCS) and equipment thickness in corrosion monitoring system (CMS). The developed system was further applied to the crude distillation unit. Taking three typical corrosion circuits of crude oil circuit before desalting, atmospheric tower overhead circuit and second-line circuit of vacuum tower as examples, the variation of dynamic indicators and risk were investigated. Firstly, the damage modes were analyzed according to API 581 and GB/T 30579. And then the monitoring points including medium compositions, process operation parameters and wall thickness were respectively established by analyzing the corresponding data in LIMS, DCS and CMS. Thus, the risk results will update dynamically with the variations of abovementioned data. Based on dynamic risk results, the critical IOW operation boundaries in typical circuits were also displayed. This research will facilitate grasping the equipment risk state in real-time with dynamic RBI technology while ensuring the equipment steady operation by IOW warning technology.

Despite the general agreement that a firm embodies its own culture, there is still a lack of empirical research on how a firm’s culture affects its value. Another caveat on previous studies is that they implicitly assume that a firm’s culture does not vary over time. In this paper, we examine the following two questions to address this lack: (1) Does a firm’s culture affect the firm’s value? (2) If a firm’s culture varies at different life cycle stages, do these changes have an impact on firm value? By using a competing values framework, we identify four types of corporate culture—adhocracy, market, clan, and hierarchy—and use life cycle stages to proxy for changes in a firm’s environment. The results reveal that adhocracy culture has a positive effect on a firm’s value. In contrast, we find a negative association between hierarchy culture and a firm’s value. This can be interpreted as the features of adhocracy culture, which gives autonomy to its members (flexible and discretion) and keeps challenging a firm to grow (external focus and differentiation), positively impacting firm value more than the other cultures. Furthermore, at a growth stage in which a firm faces dynamic environmental changes, both adhocracy and clan cultures have an incrementally positive effect on firm value. This implies that firms in mature or decline stages lose dynamic changes in their operational environment, therefore, the effect of culture on firm value is restricted in those stages.

In this study we present a comprehensive forward-looking portfolio simulation methodology for assessing the correlated impacts of market risk, private sector and Sovereign credit risk, and inter-bank default risk. In order to produce better integrated risk assessment for banks and systemic risk assessments for financial systems, we argue that reasonably detailed modeling of bank asset and liability structures, loan portfolio credit quality, and loan concentrations by sector, region and type, as well as a number of financial and economic environment risk drivers, is required. Sovereign and inter-bank default risks are increasingly important in the current economic environment and their inclusion is an important model extension. This extended model is demonstrated through an application to both individual Brazilian banks (i.e., 28 of the largest banks) and groups of banks (i.e., the Brazilian banking system) as of December 2004. When omitting Sovereign risk, our analysis indicates that none of the banks face significant default risk over a 1-year horizon. This low default risk stems primarily from the large amount of government securities held by Brazilian banks, but also reflects the banks' adequate capitalizations and extraordinarily high interest rate spreads. We note that none of the banks which we modeled failed during the very stressful 2007-2008 period, consistent with our results. Our results also show that a commonly used approach of aggregating all banks into one single bank, for purposes of undertaking a systemic banking system risk assessment, results in a misestimate of both the probability and the cost of systemic banking system failures. Once Sovereign risk is considered and losses in the market value of government securities reach 10% (or higher), we find that several banks could fail during the same time period. These results demonstrate the well known risk of concentrated lending to a borrower, or type of borrower, which has a non-zero probability of default (e.g., the Government of Brazil). Our analysis also indicates that, in the event of a Sovereign default, the Government of Brazil would face constrained debt management alternatives. To the best of our knowledge no one else has put forward a systematic methodology for assessing bank asset, liability, loan portfolio structure and correlated market and credit (private sector, Sovereign, and inter-bank) default risk for banks and banking systems. We conclude that such forward-looking risk assessment methodologies for assessing multiple correlated risks, combined with the targeted collection of specific types of data on bank portfolios, have the potential to better quantify overall bank and banking system risk levels, which can assist bank management, bank regulators, Sovereigns, rating agencies, and investors to make better informed and proactive risk management and investment decisions.

Substantial strides have been made in the field of violence risk assessment. Numerous robust risk factors have been identified and incorporated into structured violence risk assessment instruments. The concepts of violence prevention, management, and treatment have been infused into contemporary thinking on risk assessment. This conceptual development underscores the necessity of identifying, measuring, and monitoring changeable (dynamic) risk factors--the most promising targets for risk reduction efforts. However, empirical investigation of dynamic risk is virtually absent from the literature. In this article, the authors (a) differentiate risk status (interindividual risk level based largely on static risk factors) from risk state (intraindividual risk level determined largely by current status on dynamic risk factors), (b) analyze the relevance of contemporary risk assessment measures for capturing dynamic risk, and (c) distill potentially important dynamic risk factors from the literature in order to facilitate future research. Suggestions for theory development and research design are provided.

BackgroundThe aim of this study is to build a risk assessment system for central lymph node metastasis (CLNM) in papillary thyroid microcarcinoma (PTMC) of stage cN0 and to explore its application value in clinical practice.MethodsA total of 500 patients with PTMC who underwent thyroid operation from 2013 to 2015 in Ningbo First Hospital were selected as the model group. Independent risk factors related to CLNM in PTMC were analyzed and determined, and a risk assessment system for CLNM was preliminarily established. Furthermore, the clinicopathological data from 328 PTMC patients with the same conditions as the model group from 2016 to 2017 were further collected as the validation group to verify the diagnostic value of the risk assessment system.ResultsThe risk assessment system was based on the score rating (score ≤ 5 was classified as low risk, 6–8 was classified as medium risk, and ≥9 was classified as high-risk). The area under the receiver operating characteristic curve (ROC) was 0.687 (95% CI: 0.635–0.783). According to the risk assessment system, 328 PTMC patients in the validation group were scored. Among the low-risk group, the moderate-risk group, and the high-group, 96.8%, 58.1%, and 43.2% were the CLNM (-) patients, and 3.1%, 41.9%, and 65.8% were CLNM (+) patients, respectively. The area under ROC was 0.837 (95% CI: 0.778–0.869).ConclusionsThe risk assessment system in this study is of diagnostic value and can provide a theoretical foundation for intraoperative decision-making of prophylactic central neck dissection (pCND).

Too much of a good thing: How varying levels of automation impact user performance in a simulated intrusion detection task

In order to solve the problems of low-risk assessment accuracy and long time-consuming assessment of current wireless mobile communication systems, a wireless mobile communication system based on artificial intelligence algorithms is proposed. First, the research status of risk assessment of wireless mobile communication system at home and abroad is analyzed, and the risk assessment index system of wireless mobile communication system is established; then, the learning samples are collected according to the risk assessment index system of wireless mobile communication system, and artificial intelligence algorithm is used to optimize the neural network. Build the wireless mobile communication system risk assessment model; finally, carry out the wireless mobile communication system risk assessment simulation comparison test. The experimental results show that the accuracy rate of the risk assessment of the wireless mobile communication system by the artificial intelligence algorithm is over 95%, and the assessment error is smaller than in other models. The risk assessment time of the wireless mobile communication system is significantly reduced, the real-time performance is better, and it has a higher practical application value.

In recent years, ammonia leakage accidents occur frequently, which causes a great concern in China. Based on traditional risk analysis methods and the equipment characteristics, a risk evaluation method for small ammonia refrigeration units is proposed. The method includes a risk assessment model based on area division, a failure probability assessment method based on expert scoring system, a failure consequence assessment method based on regional population density and consequence mitigation measures, and a HAZOP risk correction method. Based on the proposed method, a risk assessment system of small ammonia refrigeration units is developed. This risk assessment method and system will provide a scientific basis to carry out the cold storage management in China.

Traditional deterministic methods usually applied to the most severe and low probability events in power system risk assessment, computation results are therefore much conservative accordingly. Considering both probability and their impact of the effects, risk assessment methods can provide comprehensive effect on the whole power system. The status quo related to risk assessment is reviewed. The meaning and main research aspects of risk assessment are discussed, and the risk indexes based on engineering presented besides. The essential flow chart and key problems to be resolved concerning risk assessment of power system are studied.

The article provides a comprehensive analysis of the role of special physical training in shaping the professional readiness of police officers to perform tactical and fire tasks in the course of law enforcement activities. It is substantiated that special physical training is not an auxiliary, but a system-forming component of professional training, which ensures the effective implementation of tactical decisions and the lawful and safe use of firearms under conditions of increased physical load, time deficit, and psycho-emotional stress. The study emphasizes that real service situations faced by police officers are characterized by dynamic changes in the operational environment, high levels of physical exertion, and the need to make prompt and responsible decisions. Under such conditions, the effectiveness of tactical actions and fire engagement largely depends on the level of development of special physical qualities, including strength endurance, coordination, speed of reaction, and resistance to fatigue. The interrelationship between special physical, tactical, and fire training is revealed, demonstrating that insufficient physical preparedness significantly reduces the practical value of tactical knowledge and shooting skills acquired in standard training conditions. Particular attention is paid to the influence of physical fatigue on psychophysiological processes, such as attention, accuracy of movements, emotional stability, and decision-making quality. It is determined that systematic special physical training contributes to the formation of stress resistance, enhances control over motor actions during firearm use, and increases the reliability of professional behavior in extreme situations. The article also highlights the importance of developing unit-level interaction skills, as coordinated actions within tactical groups require a high level of physical readiness and functional stability. The feasibility of implementing an integrated approach to police training in higher education institutions with specific training conditions is substantiated. This approach involves combining special physical, tactical, and fire training within unified training scenarios that simulate real combat situations. It is concluded that the integration of these components creates prerequisites for forming a professionally reliable police officer capable of acting effectively, lawfully, and safely in modern law enforcement challenges.

In the article, a taxonomic method for selecting the optimal vectorization approach for processing current images in the optical-electronic module of unmanned aerial vehicles (UAVs) was developed. The primary goal of this method is to optimize UAV navigation systems, which is particularly relevant due to the need to improve data processing efficiency in conditions of limited access to satellite navigation systems. This is critically important for ensuring high autonomy and accuracy of UAVs during the performance of various tasks. The need for such a method arose from the specific challenges faced by UAVs when operating in complex and unpredictable conditions. Analysis has shown that the use of vector images can significantly reduce the time required for information processing. This is possible due to the smaller volume of data that needs to be processed compared to traditional raster images. Reducing information processing time is critically important for the operational capability of UAVs to respond to dynamic changes in the operational environment, especially in critical situations. The taxonomic approach applied in the study allows for systematic classification and evaluation of different vectorization methods in terms of their processing speed, accuracy of results, and data retention efficiency. This enables the identification of the most suitable method for the specific operational conditions in which the UAV is used, thereby optimizing the overall system performance. Furthermore, the results of this research are significant not only in the scientific field but also in practical applications. By improving autonomous navigation systems for UAVs, the study directly contributes to enhancing their effectiveness in complex and unpredictable conditions. This is particularly relevant for missions that require a high level of precision and reliability, such as those performed by military UAVs and emergency response. Enhanced navigation capabilities allow these UAVs to perform complex maneuvers and make real-time decisions based on processed vectorized images, thereby reducing the risk of errors and increasing mission success rates. An improved vectorization method could lead to significant enhancements in UAV navigation systems, making them more resistant to failures and capable of operating in less structured environments without heavy reliance on satellite signals. This enhancement is vitally important for both military and civilian UAV applications, where operational flexibility and reliability are extremely important.

Dairy and dairy processing industries are included in the group of food products and high-risk industries. Decision making in relation to risk management in dairy industry supply chain is significant. This study aimed at designing a Intelligent decision support system (DSS) for risk assessment of dairy agroindustry supply chain and the estimation of dairy price in the risk-based farmer level. The risk assessment is analyzed by fuzzy logic approach which is Fuzzy Inference System (FIS) and Fuzzy Assosiative Memories (FAMs). The basic knowledge of this system is obtained through the preparation of rule base of risk assessment and the relation of production cost and risks at the farm based on the expert arguments variables. There are six outputs yielded from RSDA, that is risk assessment in accordance with priority issue, risk assessment for delivery activity, risk source exploration, risk performance, risk management partially and the estimation of production cost and price with risks. The system provides several alternatives which will help decision making in preparing risk management in dairy agroindustry supply chain. Moreover, this system also provides several scenarios of dairy price estimation at the level of farmer who includes risk factor in the farmer. By this system, it is expected that the opportunity of risk and risk impact of dairy agroindustry supply chain can be minimized.

Objectives: Exposure Assessment for workplace hazards where the exposure level is below occupational exposure limits(OELs) has been performed without considering either the degrees of risk or exposure levels and has failed to lead to intervention in many cases. The objective of this study was to suggest and test an application framework for risk assessment methodology under the current exposure assessment system in Korea. Materials: First, we investigated the exposure assessment systems in Korea and other countries. To adopt some risk assessment techniques, we also analyzed risk assessment systems and compared them to exposure assessment systems. A few suggestions were made. We held a public hearing during an industrial hygiene conference and took surveys using a questionnaire. Results: The first suggestion was to implement the risk assessment and exposure assessment through a "one-stop" system. In that case, one expected question would be who has been doing the jobs so far. In most cases, industrial hygiene consulting services or laboratories have been performing exposure assessment for business owners. Business owners are required to perform risk assessment. As two different groups of people will be required to implement two things in a one-stop system, they need to share information. As an information vehicle to share information, commonly filed survey checklists were suggested. The second suggestion was to categorize exposure level into four groups instead of the current binary divisions based on OELs. In the risk assessment system, exposure level is divided into four groups utilizing the cut-points of 10%, 50%, and 100% of OELs. The same schema can be adopted in the exposure assessment system and different levels of requirements can be assigned for each group. The third suggestion was regarding the regulation system. To provide the suggestions some thrust toward being implemented in the field, changes should be made in the legal system. Two different types of new exposure assessment result reporting forms were suggested. Some investigations such as an ergonomic survey are officially accepted as risk assessment under the current legal system. A few items were suggested to be included in the exposure assessment result reporting to be accepted as risk assessment. A pilot study in two small factories was performed and pointed out the strengths and weakness of our suggestions. Conclusions: Discussions and studies on the improvement of the exposure assessment system have been held for decades and no tangible changes have yet been made. We hope this result can help realize healthy lives for workers in Korea.

This article aims to shed light on the meaning of complexity for risk assessment of sociotechnical systems. The point of departure is that complexity is related to uncertainty as an indication of confidence in risk assessment. Complexity science points to limitations in risk analysis that owe to a mismatch between the nature of sociotechnical systems and how we approach them in search of prediction and control. Complexity complements uncertainty in three ways: as a source of uncertainty, as an additional type of uncertainty concerning deviations from what is designed, planned or assumed, and as an overall indication of limitations in the analysis with respect to potential for surprise. A new framework is suggested to clarify and make the concept of practical value to risk assessment. The framework consists of a definition, a conceptual map, an ontological and epistemological position, and a set of indicators. Complexity is explained in the conjunction of an analyst, a system, and a chosen model and is conditioned on the state of knowledge and the assessment context. It is epistemic in the sense that it resides in the analyst’s understanding of the system and not in the system as such. A challenging implication is that complexity is relative in many respects, but this also provides opportunities for approaching it in risk assessment. The indicators can help to acknowledge, reduce, and describe complexity in pre-assessment, risk analysis, and risk evaluation.

In Flanders and by extension in the whole world, accidents involving the transport of dangerous goods occur. Therefore, Flanders is developing a risk analysis and assessment system for the external human risks of transporting dangerous goods. The general outline of the system has now been established, based on a number of external research projects. The system allows to obtain a profile of the risks of serious accidents with the transportation of dangerous goods on roads, railways, waterways, pipelines and in ports. In brief, the risk analysis system consists of the following major elements: dividing of the transport routes into segments, determining the probability of a major accident per segment, determining the damage per segment, determining the risks for each segment and determining the risks per route. The next step was the developing of a risk assessment system to be able to decide whether or not the risk of the transport of dangerous goods is acceptable, whether or not extra safety measures have to be taken and which of the alternative routes is the most favourable one for external safety. The system consists of two major steps. First, the risk per segment is studied and if necessary, the ALARP principle is applied. Second, the risk of the total route is calculated for all alternative routes and is compared.