• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础
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For instance, there is a project, which is called SESAMO (Security and Safety Modelling) and focuses on safety and security requirements, aiming “to develop a component-oriented design methodology based upon model-driven technology,jointly addressing safety and security aspects and their interrelation for networked embedded systems in multiple domains” [1]. This project focuses on identifying safety and security hazards in order to calculate a trade-off between contradicting safety and security issues. Furthermore, another project concerning safety is called SafeCer (Safety Certification of Software-Intensive Systems with Reusable Components). The purpose of this project is to increase “[…] efficiency and reduce(d) time-to-market by composable safety certification of safetyrelevant embedded systems.” [9] The main focus of this project is to provide a procedure of composing safety arguments for a system by reusing of already certificated arguments of subsystems. In this way, it enhances efficient safety assurance and certification. Furthermore, there is the work of Lohmüller et al. $[12]$, which proposes an approach for calculating trade-offs between contradicting safety-critical concerns. These include safety, security and timing. However, it aims to guarantee an optimal solution, which is as safe as possible. When comparing these works, one will realize that all of them cover safety and security. The work of [1] and [12] even combines safety with security or security and timing. In contrast to this paper, no scientific work integrates a FIA or CIA in their approaches.

So far, it has not been scientifically evaluated how to combine the results of a FIA with a CIA in context of safety-critical systems. Therefore, the approach, which will be presented in this paper, is innovative.

## 商科代写|商业建模代写Business Modeling代考|Failure Mode and Effects Analysis

Nowadays, the software development process in context of safety-critical systems requires risk assessment. The FMEA is a widely used and established technique and is applied in different domains like, e.g., medical information science, automotive, avionics and railway industry. It is purpose of the FMEA to mitigate risks as much as possible. This is done by detecting and preventing failures. For the failure prevention, it is essential to indicate and to prevent failures in early stages of product cycle. The later a failure will be indicated the more expensive the development costs. Accordingly, the costs will increase about 10 times for each posterior stage [2]. The failure detection has four essential goals:

1. Detection of possible fault sources, which can cause failures
2. All causes and consequences must be identified, mitigated or avoided
3. Faultless organization of process during the development cycle
4. Vulnerabilities of the system, products or processes must be identified in order that a constructive revision can be performed.
5. To prevent and detect failures it is necessary to determine potential risks by means of the FMEA. whereas occurrence complies with the probability whether a hazard occurs. Severity corresponds to the severity of hazard. The detection complies with the probability that a hazard will be detected. Each of the three factors can range between 1 and 10, i.e., the RPN can range between 1 and 1000 . In general, the lower the RPN the better the potential risk. Depending on the value of the RPN, the degree of risk and the necessity of CMs can be identified by means of Table $1[2]$.

BBN are highly complex networks which represent the probabilities of conditional dependencies of variables. Many research approaches of plenty research fields used or described BBN, e.g., [8], [17] or [4]. As a detailed description is out of scope in this paper, the most important parts are described afterwards. The formulas and theorems are abstracted from [14]. BBN are probabilistic, graphical models which are used to represent and calculate the conditional probabilities of model elements. Important characteristics are directed and acyclic relations, random variables with discrete states and dependencies to ancestor and descendant nodes. These networks are not restricted to a specific field. The majority of use cases for BBN are networks with questions about dependent probabilities of nodes with different possible states, e.g., the determination of correctness of a disease test. To determine the corresponding conditional probability distribution of every node in the graph a Conditional Probability Table (CPT) has to be defined. This table contains all possible combinations of the diverse states of ancestor nodes to determine the probability of these combinations. Depending on the leading question a model can be analyzed with different approaches and formulas. However, these are the required formulas of our approach:
Bayesian Theorem: $P(B \mid A)=P(A \mid B) * P(B) / P(A)$
Conditional Independencies: $P(A B)=P(A) * P(B)$
Markov Assumption/Joint Probability: $P(X)=\prod_{i=1}^{n} P\left(X_{i} \mid\right.$ ancestor $\left.\left(X_{i}\right)\right)$.

## 商科代写|商业建模代写Business Modeling代考|Failure Mode and Effects Analysis

1. 检测可能导致故障的可能故障源
2. 必须识别、减轻或避免所有原因和后果
3. 在开发周期中完美的流程组织
4. 必须识别系统、产品或流程的漏洞，以便进行建设性的修订。
5. 为了预防和检测故障，有必要通过 FMEA 确定潜在风险。而发生符合危险是否发生的概率。严重性对应于危险的严重性。检测符合将检测到危险的概率。三个因子中的每一个都可以在 1 到 10 之间，即 RPN 可以在 1 到 1000 之间。一般来说，RPN 越低，潜在风险就越大。根据 RPN 的值，风险程度和 CM 的必要性可以通过表来确定1[2].

BBN 是高度复杂的网络，表示变量条件依赖的概率。许多研究领域的许多研究方法都使用或描述了BBN，例如[8]、[17]或[4]。由于详细描述超出了本文的范围，因此最重要的部分将在后面描述。公式和定理是从[14]中抽象出来的。BBN 是概率图形模型，用于表示和计算模型元素的条件概率。重要特征是有向和非循环关系、具有离散状态的随机变量以及对祖先和后代节点的依赖性。这些网络不限于特定领域。BBN 的大多数用例是具有不同可能状态的节点的相关概率问题的网络，例如，确定疾病测试的正确性。为了确定图中每个节点的相应条件概率分布，必须定义条件概率表 (CPT)。该表包含祖先节点的不同状态的所有可能组合，以确定这些组合的概率。根据主要问题，可以使用不同的方法和公式分析模型。但是，这些是我们方法所需的公式：根据主要问题，可以使用不同的方法和公式分析模型。但是，这些是我们方法所需的公式：根据主要问题，可以使用不同的方法和公式分析模型。但是，这些是我们方法所需的公式：

## 有限元方法代写

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。