Our comprehensive suite of pension risk management solutions help you achieve your plan objectives. The tracking system of heavy core TANH equilibrium array is used to obtain the abnormal data range. Privacy-aware cross-platform service recommendation based on enhanced locality-sensitive hashing. Dashpivot has a bunch of digital templates and procedures pre-built for companies looking to improve how they and their workers manage and complete processes, and you can edit and customise them to fit your needs. Insider Intelligence maximizes your return on information by providing expert analysis and insights. How to obtain 2 batches of heavy core clustering data fromSERIALNO_CT and how to trace the original data. The risk management plan is often the first stage of risk control on any project. Nearly one-third of respondents cite a lack of sponsorship or buy-in from executives or other stakeholders in prioritizing risk-identification and management activities. Therefore, the reliability increment index of uCT528 is controlled between (12.5%, 25%).\({if arctg\left[\frac{Sin\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}i\cdot {y}_{j}/2\right)}{Cos\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}\right]}_{P}\in \left(\frac{\pi }{4},\frac{\pi }{2}\right)\) . Risk matrices list only security vulnerabilities that are newly addressed by the patches associated with this advisory. If done well, this is very good news for risk managers, given the inherent risk-mitigating structures and culture of early identification and remediation of defects inherent in well-implemented agile teams. Within the framework, organizations design transformation activities and make appropriate interventions. And build the complexity dependent parameter group from low-end equipment to high-end equipment. iCT256 exposure time [comprehensive reliability 92.937%]. Companies in all industries are launching digital and analytics transformations to digitize services and processes, increase efficiency via agile and automation, improve customer engagement, and capitalize on new analytical tools. And form a [1, 10] heavy core clustering table, which can compute the percentage of reliability through the above programming process, store it in the [1, 10] clustering table, and finally send it to the image database for KNN display, and embed the web for HTML display. Heat capacity machine internal index and domain value of CT [weight kernel clustering tanh equilibrium big data risk control high-dimensional data] polar graph (2021-09-14 16:59:04). They now have one excavator available, and there is a 4-week turnaround to getting a new one in. Z. DarBoux Transformation in Solition Theory and Its Geometric Applications 2nd edn, 1271 (Shanghai Science and Technology Press, 2005). One common goal of digital and analytics transformations is to better serve end users, who are often the weakest link in a risk-management chain. Explore our media centre for all your reporting needs. Secure global bank communications, operational efficiency and control, regulatory compliance, and effective liquidity and risk management are essential to support growth and create competitive advantage. Risk Matrix Content. Big Data 1, 1 (2017). This tool is designed to help companies better identify, assess, mitigate, and measure the nonfinancial risks generated and exacerbated by digital and analytics transformations at both the enterprise and product level. Click the button to register and select the date that works best for you. The creation of comprehensive and supportive governance, risk and control (GRC) frameworks should be a top priority for all organisations and can no longer be a reactive process. Enterprise risk management typically consists of several common activities, including the following: These activities are critically important to digital and analytics transformations. Swift is a global member-owned cooperative and the worlds leading provider of secure financial messaging services. The abnormal data range is obtained through the traceability system of heavy core TANH equilibrium array. One such example might be the working at heights risk assessment template you see below (which is an exported version), and a company will likely have individual templates and frameworks for all of the individual components of risk management - which combine to form the entire safety management system. When people talk about risk monitoring and control tools, they are usually talking about one of two things: In terms of the theoretical tools which can be used for risk monitoring and control, we have: While some companies manage these processes manually, other companies streamline these processes using smart risk monitoring and control tools. But they are embracing these risks, updating their risk functions and sharing risk intelligence to generate fresh value through dynamic innovation that gives them a competitive advantage. This kind of AI big data risk control improves the intelligent management ability of medical institutions. We'll email you when new articles are published on this topic. Artificial intelligence is also poised to redefine how businesses work and is already unleashing the power of data across a range of crucial functions. Overall, most respondents assess their risk-management maturity as average, but more than 75 percent have not conducted a formal, holistic risk assessment for half of their digital and analytics transformations. They wanted to ensure privacy remained fully protected within the machine learning / AI context that produces these signals. The regular fluctuation of the energy of the edge lens with dual core and heavy core analyzes the high-dimensional information field of CT and MR similar to the exposure lens to obtain high-definition images. The reliability boundary is 40.01%, and reference to Figs. Privacy-preserving collaborative filtering algorithm based on local differential privacy. To support the framework and put its approach into practice, companies will need to also define these roles and responsibilities for digital and analytics transformation risks: In most cases, defining such roles will not require adding head count. We love a good conversation. The companies spend, on average, 12 percent of their IT budgets on digital and analytics transformations. AI / ML Analytics & Reporting API Gateway App Designer Cloud Technology Data Fabric Governance, Risk & Compliance Marketplace Unified Experience. Navigate the Libor Transition with confidence and precision, Unlock best-in-class analytics with Python. And reference to Figs. We are the first place to look when you need actionable data to make confident business decisions. At the same time, TANH equilibrium of heavy core clustering is based on the hierarchical fuzzy clustering system based on differential incremental equilibrium theory. Risk generalists are involved early in design processeseven sitting with agile development teams as necessary. 1.Universal Design and Robust Predictive Maintenance Articles, news, products, blogs and videos from Control Global. These risk registers are usually created at the start of the project, and then updated with new risks as they are identified on site using a risk assessment app like this or hazard or risk identification sheets. But they are embracing these risks, updating their risk functions and sharing risk intelligence to generate fresh value through dynamic innovation that gives them a competitive advantage. Never miss an insight. Partial normal heavy kernel weight probability density gradient (1,2)quasi normal topological stability structure projection conjugate wavelet neural network image reflection risk control p-value image. The cookie is used to store the user consent for the cookies in the category "Analytics". Risk matrices list only security vulnerabilities that are newly addressed by the patches associated with this advisory. The cross platform big data development platform will successfully establish AI3d mathematical model scientific computing and image display, and form image cognition and matching. It provides a decision analysis system for hospital intelligent management. A bank was in the midst of a digital transformation, and the early stages were going well. Control Risks is the specialist global risk consultancy that helps organisations succeed in a volatile world. Get the most important science stories of the day, free in your inbox. Rongrong, Z. Contactless medical equipment AI big data risk control and quasi thinking iterative planning. AI risk control of its heavy core clustering TANH equilibrium secondary processing data is less than 67.348%, so it needs AI re iteration. This is why establishing a risk-based control to protect the integrity, confidentiality, and accessibility of business Read more. Risk Matrix Content. J. Inf. Eng. With different parameters, supersymmetry projection linear narrow-band tp distribution is formed. The CEO threatened to end the initiative and return the teams to waterfall development if they couldnt improve application development security. Some traditional risks are more common to most projectsincluding those arising from budget and schedule overruns, talent (employees and third parties, including contractors, suppliers, and partners), IT performance, and compliance and regulatory issues. Companies in our survey with the highest risk-management maturity are more comfortable with managing digital and analytics transformations. Transforming your data for secondary uses and access. An English text version of the risk matrices provided in this document is here. It consists of four steps that define, operationalize, embed, and reinforce the elements of the transformation. Correspondence to And reference to Fig. Few, however, had established detailed policies or training on how to safely set up a remote work space or think through other risks associated with the rapid acquisition and deployment of new tools. The cookie is used to store the user consent for the cookies in the category "Analytics". Ensure the performance of your cybersecurity program achieves the performance standards set by your organization with evidence-based cyber risk monitoring, continuous measuring of security control effectiveness, remediation of gaps and vulnerabilities, and effective assurance to Comprehensive evaluation indexes: 69.730%, 62.940%, 74.716%, its core boundary is 40.01%, and the image is more scientific. AI big data risk control and quasi thinking iterative planning cross platform web software will be started automatically, and display the risk control data and image display of its whole life cycle. Digital and analytics transformation risk owner: This role is responsible for all transformation risks. By understanding the insights from our research and taking the approach outlined here, companies can achieve the value of digital and analytics transformations while also safeguarding their organizations and customers. Companies have found that existing team members are ready and eager to take on these responsibilities. J. IEEE Trans. Successful organizations know that risk can come from every angle upside, downside and outside and can be hard to see, anticipate and respond to. For example, KNN is used to obtain the reliability learning form of the adjacent domain, successfully capture the abnormal phenomena of the original data, and judge whether it is false positive through AI mathematical model risk control model. Fut. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. FINCAD provides reliable and accurate independent bond prices and allows us to respond swiftly to market changes. Companies rated their risk-management capabilities from 1 to 5, with 5 representing the most advanced in effectiveness and efficiency. Secure global bank communications, operational efficiency and control, regulatory compliance, and effective liquidity and risk management are essential to support growth and create competitive advantage. Read this case study and find out how Fresenius Medical Care and its affiliates are leveraging sensitive data safely and responsibly to deliver significant benefits to business and society under GDPR. These data are then used in different parts of the organization to generate insights. Gu Chaohao, Hu. 22, 23. We strive to provide individuals with disabilities equal access to our website. The risk register is the single source of truth when it comes to tracking risks on a project, as it stores every risk associated with the project as well as some additional detail on those risks. 2, 1352 (2008). The quasi thinking iterative planning of heavy core clustering TANH equilibrium structure in the risk control of iCT 256 equipment finds a special stable AI standard computation model. Treasury plays a crucial role in supporting financial objectives and informing strategic decisions. While the benefits of digitization and advanced analytics are well documented, the risk challenges often remain hidden. Stay up-to-date on the latest from SWIFT via personalised insights sent straight to your inbox. The McKinsey Global Survey on digital and analytics transformations in risk management, 2020. Accelerate your procurement transformation with intelligence that gives your organisation an edge. Manage pricing and risk with confidence and precision. Situation: Novartis digital transformation in drug R&D drives their need to maximize value from vast stores of clinical study data for critical internal research enabled by their data42 platform. Because of these changes in data-handling processes, the transformation was delayed by four weeks, triggering a loss of more than $20 milliona financial risk directly connected to a new digital way of working. Systems Integration. Midwest Summit + Forum Cleveland, OH | April 18-19, 2022; Southern California Summit + Forum San Diego, CA | May 2-3, 2022; Florida Summit + Forum Sibos is the annual conference, exhibition and networking event organised by SWIFT for the financial industry. Find out more. If you would like information about this content we will be happy to work with you. Digital and analytics transformation lead: This lead is accountable for delivering the digital and analytics transformation activities. Treasury plays a crucial role in supporting financial objectives and informing strategic decisions. MR peak SAR big data heavy core clustering high-dimensional information maps. The Youth Risk Behavior Surveillance System (YRBSS) monitors six types of health-risk behaviors that contribute to the leading causes of death and disability among youth and adults, including behaviors that contribute to unintentional injuries and violence; sexual behaviors that contribute to unintended pregnancy and sexually transmitted disease, including HIV infection; The other force which always makes its way into the risk monitoring and control process is new project information and communications. When big data reaches a certain degree, it can completely distinguish the old and new models and service time of iCT256, so it plays a key role in predicting CT life. Please email us at: How does Gen Z see its place in the working world? 26, 27, 28, which also reflects another important basis for high-end MR. MR peak SAR RF (core data of heavy core clustering TANH equilibrium state is similar to CT exposure time), high-dimensional signal image, and AI Mathematical model risk control image similar to CT exposure time. Articles, news, products, blogs and videos from Control Global. More than half of participants face resource limitations when improving risk management with needed talent and capacity. Save my name, email, and website in this browser for the next time I comment. Trust your business decisions. Available on campus and online, the Master of Science in Project Management (MSPM) degree program at Boston Universitys Metropolitan College (MET) is a unique opportunity to combine a broad and industry-rooted knowledge of business and management principles with a mastery of successful project-based Ensure data ethics & compliance in your data models and results. View Solutions. INFOGRAPHICS. As mentioned, the risk monitoring and control process continues throughout the life of a project, but there are some distinct stages of the risk monitoring and control process which are generally aligned with the phase of a project. All rights reserved. The framework enables companies to manage the risks of a digital and analytics transformation systematically, so that it keeps pace with an organizations innovation. Our comprehensive suite of pension risk management solutions help you achieve your plan objectives. After optimizing the algorithm, hundreds of thousands of nonlinear random vibrations are performed in the operation and maintenance database every second, and at least 30 concurrent operations are formed, which greatly improves and shortens the operation time (Yanwei et al. A risk management plan is a document that a project manager and company prepare and use to foresee risks on the project. Articles, news, products, blogs and videos from Control Global. Organizations are also changing their operating models to support the changes. Advanced Research Center Reports Adversarial & Vulnerability Research. Links with this icon indicate that you are leaving the CDC website.. For AI big data risk control, high precision, multi-sample and high dimension are proposed. And reference to Fig. All data generated or analysed during this study are included in this published article [and its supplementary information files]. Only RFID Journal provides you with the latest insights into whats happening with the technology and standards and inside the operations of leading early adopters across all industries and around the world. We need technical proposal for Social Risk Monitoring solution. Sources of risk to operational resilience include new IT services and migration to the cloud. Vegard Annweiler, CEO, Nordic Bond Pricing (NBP). With proven technology and unmatched expertise, well empower your organization to gain new insight from its most sensitive data, while alleviating privacy concerns throughout your data life cycle. Other companies implementing digital and analytics transformations should consider adopting a similar model. These companies are more likely to centralize or automate their risk-management functions, and they report using an array of practices and tools to identify and reduce the risks of their digital and analytics transformations (Exhibit 3). CT tubes exposure time big data additive heavy core cluster image. Optimize trading and hedging with accurate valuations. Our solutions combine strategic research, advanced analytics and best of breed technology to provide the actionable insights you need, delivered straight to your desktop. Rogers, C. & Schief, W. K. Bcklund and Darboux Transformations: Geometry and Modern Applications in Solition Theory 1292 (Cambridge University, 2015). Another simple risk monitoring and control example would be if there has been some unexpected weather forecast. Measure Calibration Flow Level Pressure Temperature Vibration Weight Analyzers. 1, 1. https://doi.org/10.1109/tnse.2020.2969489 (2020). Risk matrices for previous security patches can be found in previous Critical Patch Update advisories and Alerts. In a sense, the pandemic has set off the largest wave of digital and analytics transformations in history, compressing transformations that would have taken years into a few hectic months (or even weeks), often with little advance planning. Low risk-awareness can expose the enterprise to significant risks associated with the new digital and analytics tools and processes. This paper is not waiting to be published in other journals. Sign up for webinars, and come meet us at one of many events around the world. In this way, it is very easy to analyze the comprehensive evaluation index domain of reliability between different CT / MR and the same equipment type. Strategic services and solutions to help healthcare, pharmaceutical, life sciences and medical device organizations compete in an evolving health market and improve cost-efficiency and profitability. uCT528heat capacity MHU% [comprehensive reliability 57.45%]. Measure Calibration Flow Level Pressure Temperature Vibration Weight Analyzers. For Non-profit Organizations. Digital and analytics transformation risk owner: This role is responsible for all transformation risks. Source: McKinsey Global Survey on Digital and Analytics Transformations in Risk Management, 2020. 1 Those engaged in prohibited and outlawed Systems Integration. Ready to connect to the SWIFT network? Most companies appear to do little about the nonfinancial risks generated and exacerbated by digital and analytics transformations. Contactless medical equipment AI big data risk control and quasi thinking iterative planning, $${{P}_{({A}_{i} , { A}_{j})}^{(1)}=\left(\frac{1}{4}\right)}^{n}{\left[Sin\left({A}_{1}+\sum_{i=2}^{m}A+n\cdot \frac{\pi }{4}\right)+Sin\left({A}_{1}-\sum_{i=2}^{m}A+n\cdot \frac{\pi }{4}\right)\right]}_{{P}_{i(x,y)}^{*}}^{n-1}$$, $${{P}_{(A , B)}^{(2)}=\left(\frac{1}{4}\right)}^{n-1}\sqrt{2}{\left[Sin\left(\frac{{A}_{1}}{2}+\frac{\pi }{4}+n\cdot \frac{\pi }{4}\right)Cos\left(\sum_{i=2}^{m}{A}_{i}+\sum_{i=1}^{m}i\cdot \frac{{A}_{i}}{2}\right)-Sin\left(\frac{{B}_{1}}{2}+\frac{\pi }{4}+n\cdot \frac{\pi }{4}\right)Cos\left(\sum_{i=2}^{m}{B}_{i}+\sum_{i=1}^{m}i\cdot \frac{{B}_{i}}{2}\right)\right]}_{{P}_{ij}^{*}({x}_{i},{y}_{j})}^{n-1}$$, \({t}_{i}=\left({x}_{i},{y}_{i}\right),\overline{{t }_{i}}=\stackrel{-}{\left({x}_{i},{y}_{i}\right)}\), \({\left[Tanh\times Ctanh\right]}^{\nabla }\), \({\left[Tanh\left({t}_{i}-\overline{{t }_{i}}\right)\times Ctanh\left({t}_{i}+\overline{{t }_{i}}\right)\right]}^{\nabla }\), $$\begin{aligned}&&\left[Tanh\left(A\right)\times Ctanh\left(\overline{A }\right)\right]d(A\overline{A })=\frac{\left[{\frac{{{k}^{2}\sigma }_{1}}{\sqrt[3]{\frac{{\pi }^{2}}{4}}}\times e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{+2}\left({\overline{A} }_{ij}{A}_{i+1,j+1}\right)}^{\frac{1}{8}{\left[{\left({A}_{i}-i\overline{A }\right)}_{i}-\frac{\mu }{\sigma }\right]}^{3}}-\frac{{k}^{2}{\sigma }_{2}}{\sqrt[3]{{\pi }^{2}}}\times {e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{+2}\left({\overline{A} }_{i+1, j+1}{A}_{ij}\right)}^{-\frac{1}{8}{\left[{\left({A}_{i}+i\overline{A }\right)}_{j}-\frac{\mu }{\sigma }\right]}^{3}}\right]}{\left[\frac{{k}^{2}{\sigma }_{3}}{\sqrt[3]{{\pi }^{2}}}{\times e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{+2}\left({\overline{A} }_{ij}{A}_{i+1,j+1}\right)}^{\frac{1}{8}{\left[{\left({A}_{i}-i\overline{A }\right)}_{i}-\frac{\mu }{\sigma }\right]}^{3}}+ \frac{{k}^{2}{\sigma }_{4}}{\sqrt[3]{\frac{{\pi }^{2}}{4}}}{\times e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{+2}\left({\overline{A} }_{i+1, j+1}{A}_{ij}\right)}^{-\frac{1}{8}{\left[{\left({A}_{i}+i\overline{A }\right)}_{j}-\frac{\mu }{\sigma }\right]}^{3}}\right]}\otimes \frac{\left[\frac{{{k}^{2}\sigma }_{5}}{\sqrt[3]{{\pi }^{2}}}\times {e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{-2}\left({A}_{ij}{\overline{A} }_{i+1, j+1}\right)}^{\frac{1}{8}{\left[{\left({A}_{i}-i\overline{A }\right)}_{i}-\frac{\mu }{\sigma }\right]}^{3}}+{\frac{{{k}^{2}\sigma }_{6}}{\sqrt[3]{\frac{{\pi }^{2}}{4}}}\times e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{-2}\left({\overline{A} }_{ij}{A}_{i+1,j+1}\right)}^{-\frac{1}{8}{\left[{\left({A}_{i}+i\overline{A }\right)}_{j}-\frac{\mu }{\sigma }\right]}^{3}}\right]}{\left[{\frac{{k}^{2}{\sigma }_{7}}{\sqrt[3]{\frac{{\pi }^{2}}{4}}}\times e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{-2}\left({A}_{ij}{\overline{A} }_{i+1, j+1}\right)}^{\frac{1}{8}{\left[{\left({A}_{i}-i\overline{A }\right)}_{i}-\frac{\mu }{\sigma }\right]}^{3}}-{\frac{{k}^{2}{\sigma }_{8}}{\sqrt[3]{{\pi }^{2}}}\times e}_{{}^{ij}{\theta }_{\sqrt{\pi }}^{-2}\left({\overline{A} }_{ij}{A}_{i+1,j+1}\right)}^{-\frac{1}{8}{\left[{\left({A}_{i}+i\overline{A }\right)}_{j}-\frac{\mu }{\sigma }\right]}^{3}}\right]}\\ && ,and\; \sigma \left( {\pi ,\frac{\pi }{4},\frac{\pi }{2},2\pi } \right)^{{ - T^{2} }} \to \sigma \left( {\pi ,\frac{\pi }{4},\frac{\pi }{2},2\pi } \right)^{{T^{2} }} ,{\text{ form a high}} - {\text{dimensional information field}}\end{aligned}$$, \(\stackrel{\mathrm{heavy core lens}}{\to }\), $$\mathrm{Assume }\delta =center\_frequency/imagein{g}_{frequency}, and\omega =\left(TR\otimes TE\right), \mathrm{MR}=\mathrm{Image Definition}.$$, $${A}^{\left(x,y,z\right)}\to \frac{\delta }{\omega }\times {Matrix\left[\begin{array}{ccc}{E}_{x}& & \\ & {S}_{y}& \\ & & {M}_{z}\end{array}\right]},and {A}^{\left(x,y,z\right)}\to Imag{e}_{Definite}$$, $$\begin{aligned} & \left( {A_{{\left( {x,y,z} \right)}}^{MR} ,\overline{{A_{{\left( {x,y,z} \right)}}^{MR} }} } \right)^{{H_{ij} Q_{i} H_{ji}^{H} }} = \\ & \quad \mathop \sum \limits_{i = 1}^{k} \frac{{\varvec{\delta}}}{{\omega_{i} }} \times log\left| {I + R^{ - 1} \times H_{ij} \times Matrix\left[ {\begin{array}{*{20}c} {E_{x} } & {} & {} \\ {} & {S_{y} } & {} \\ {} & {} & {M_{z} } \\ \end{array} } \right]_{i}^{Q} \left( {A_{{}}^{E,S,M} ,\overline{{A_{{}}^{E,S,M} }} } \right) \times H_{ji}^{H} } \right|,and \\ & \quad R^{ - 1} interference signal, \\ & \quad E_{x} = Excitions\_number,S_{y} = Spacing\_between\_slices,M_{z} = Magnet\_field\_strength, \\ & \quad \omega_{i} = \left( {TR \otimes TE} \right) \\ \end{aligned}$$, \({\omega }_{i}=\left(TR\otimes TE\right)\), \({Q}_{core}=E\left\{{X}_{k}{X}_{k}^{H}\right\}\), $$\begin{aligned} & Q_{core}^{{}} \left( {A_{{}}^{{X_{E} ,X_{S} ,X_{M} }} ,\overline{{A_{{}}^{{X_{E} ,X_{S} ,X_{M} }} }} } \right) = Matrix\left[ {\begin{array}{*{20}c} {E_{{X_{E} }}^{k} \otimes X_{k}^{H} } & {} & {} \\ {} & {E_{{X_{S} }}^{k} \otimes X_{k}^{H} } & {} \\ {} & {} & {E_{{X_{M} }}^{k} \otimes X_{k}^{H} } \\ \end{array} } \right]_{i}^{Q} ,and E_{{X_{E} }}^{k} \otimes X_{k}^{H} ,E_{{X_{S} }}^{k} \otimes X_{k}^{H} ,E_{{X_{M} }}^{k} \\ & \quad \otimes X_{k}^{H} {\text{Sub core energy structure}} \\ \end{aligned}$$, $$\begin{aligned} & \left( {A_{{\left( {x,y,z} \right)}}^{core} ,\overline{{A_{{\left( {x,y,z} \right)}}^{core} }} } \right)_{MR}^{{H_{ij} Q_{i} H_{ji}^{H} }} = \mathop \sum \limits_{i = 1}^{k} \frac{\delta }{{\omega_{i} }} \times log\left| {I + R^{ - 1} \times H_{ij} \times Q_{core}^{{}} \left( {A_{{}}^{{X_{E} ,X_{S} ,X_{M} }} ,\overline{{A_{{}}^{{X_{E} ,X_{S} ,X_{M} }} }} } \right) \times H_{ji}^{H} } \right| \\ & \quad ,and R^{ - 1} Interference signal,\omega_{i} = \left( {TR \otimes TE} \right) \\ \end{aligned}$$, \(\upomega =\left(\mathrm{TR}\otimes \mathrm{TE}\right)\), \(K=1-\frac{{\left[Ker\right]}_{{\left({A}_{i}\otimes {B}_{i}\right)}_{*}^{{\Delta }^{2}}}}{{S}^{2}}+\dots ,{\left[Ker\right]}_{{\left({A}_{i}\otimes {B}_{i}\right)}_{*}^{{\Delta }^{2}}}\), $${KER}_{P}^{{i\cdot \left(Sin,Cos\right)}^{2}}=\left[{Sin}^{2}\left(\sum_{i=2}^{m}{A}_{i}+\sum_{i=1}^{m}i\cdot \frac{{A}_{i}}{2}\right)+{Cos}^{2}\left(\sum_{i=2}^{m}{B}_{i}+\sum_{i=1}^{m}i\cdot \frac{{B}_{i}}{2}\right)\right]$$, $$\left\{\begin{array}{c}K=1-i\cdot \frac{{\lambda }_{i}{\left[{KER}_{P}^{{i\cdot \left(Sin,Cos\right)}^{2}}\right]}^{s-1}}{{S}^{2}}-{i}^{2}\frac{{\lambda }_{i+1}{\left[{KER}_{P}^{{i\cdot \left(Sin,Cos\right)}^{2}}\right]}^{s-2}}{{S}^{2}}+{i}^{3}\cdot \frac{{\lambda }_{i+2}{\left[{KER}_{P}^{{i\cdot \left(Sin,Cos\right)}^{2}}\right]}^{s-3}}{{S}^{2}}-\dots \\ \\ K=1-\frac{{\lambda }_{i}{\left[{KER}_{P}^{{i\cdot \left(Cos,-Sin\right)}^{2}}\right]}^{s-1}}{{S}^{2}}-\frac{{\lambda }_{i+1}{\left[{KER}_{P}^{{i\cdot \left(Cos,-Sin\right)}^{2}}\right]}^{s-2}}{{S}^{2}}+\frac{{\lambda }_{i+2}{\left[{KER}_{P}^{{i\cdot \left(Cos,-Sin\right)}^{2}}\right]}^{s-3}}{{S}^{2}}-\dots \end{array}\right.$$, $$\sum_{j=1}^{m}\sum_{i=1}^{m}{\nabla }_{ker}{P}_{(2)}^{+}\left({x}_{i},{y}_{j}\right)={\left[\frac{{}_{G}{P}_{{x}_{i}}^{2}}{{Cos}^{2}\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}+\frac{{}_{G}{P}_{{y}_{j}}^{2}}{{Sin}^{2}\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}j\cdot {y}_{j}/2\right)}\right]}_{(2)}^\frac{1}{2}$$, $$\times {arctg\left[\frac{Sin\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}j\cdot {y}_{j}/2\right)}{Cos\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}\right]}_{P}$$, $$1={\left[\frac{{}_{G}{P}_{{x}_{i}}^{2}}{{Cos}^{2}\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}+\frac{{}_{G}{P}_{{y}_{j}}^{2}}{{Sin}^{2}\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}j\cdot {y}_{j}/2\right)}\right]}_{(2)}^\frac{1}{2}{arctg\left[\frac{Sin\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}j\cdot {y}_{j}/2\right)}{Cos\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}\right]}_{P}$$, \(arctg\phi \left({x}_{i},{y}_{j}\right)\), \({if arctg\left[\frac{Sin\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}i\cdot {y}_{j}/2\right)}{Cos\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}\right]}_{P}\in \left(\frac{\pi }{4},\frac{\pi }{2}\right)\), $$1={\left[\frac{{}_{P}{G}_{{x}_{i}}^{2}}{{Cos}^{2}\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}+\frac{{}_{P}{G}_{{y}_{i}}^{2}}{{Sin}^{2}\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}j\cdot {y}_{j}/2\right)}\right]}_{(2)}^\frac{1}{2}\times {arctg\left[\frac{Sin\left(\sum_{j=2}^{m}{y}_{j}+\sum_{j=1}^{m}i\cdot {y}_{j}/2\right)}{Cos\left(\sum_{i=2}^{m}{x}_{i}+\sum_{i=1}^{m}i\cdot {x}_{i}/2\right)}\right]}_{P}$$, https://doi.org/10.1038/s41598-022-18724-5.
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risk control analytics