## 经济代写|供应链管理代写supply chain management代考|BUSN2046

2022年9月22日

couryes-lab™ 为您的留学生涯保驾护航 在代写供应链管理supply chain management方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写供应链管理supply chain management代写方面经验极为丰富，各种代写供应链管理supply chain management相关的作业也就用不着说。

• 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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## 经济代写|供应链管理代写supply chain management代考|ARTIFICIAL INTELLIGENCE

AI is a branch of technology that aims to simulate the capacity of human thinking, that is, it makes the machines are programmed with algorithms that learn and modify according to the analyzed data and, from that, manage to “think” logically. AI is also known as machine learning, since based on it, devices are able to adapt according to the data they receive, carrying out a process that diverges directly from the system of common computers which always follow the same logical commands [8].
Through AI, cognitive computing and deep learning algorithms collect data, analyze, learn, and make information available for decision-making, making recommendations for more efficient use, and this advance has enabled already routine applications, such as word processing, facial, and voice recognition [9].

With regard to natural language processing, it is an arm of $\mathrm{AI}$ that is dedicated to the translation of human languages for the machine, going beyond the simple transcription of voice by words, this area studies details of human dialog, such as the double meaning in words, the tone of voice, among other aspects that involve the diversity of natural language. Considering that this linguistic processing is present in the analysis of large volumes of voice data, in which virtual intelligence machines learn to identify accents, expressions, vocabulary patterns, with double meaning, tones, and other properties of speech[10].

Big Data is a resource focused on describing the huge amount of data that are generated by current technologies, taking into account that most of the time, these data are unstructured, which at first glance does not make sense. Besides derived from the importance of data for obtaining information, collecting references about users’ routines and data, extracting useful knowledge without AI can be time-consuming in some cases, which would be counterproductive, in this sense through the internet which brought the ease of collecting this data, and together with resources such as processing in Cloud Computing and AI, sincê Big Data is a computing model focused on processing and storing information in high volume, the solution that stores and processes data automatically and in practically real time; being allied with AI with a primary focus on data and image processing, with the aim of making the device or technology more intelligent and capable of reproducing human skills; that is, there is an intersection between AI and Big Data in relation to the AI algorithms that run in the Big Data environment and establish an effective communication between these two fields, which at the same time are different and complementary, that is, AI would be as a powerful digital human brain, which is able to store and process the information it receives from human experience such as reading, travel, crisis situations, among others, and based on this processing, it can suggest solutions on its own [11].
Today, the main advantage of using AI to capture information in Big Data is to be able to identify insights and patterns faster than human analysis, reducing the time spent on this procedure, being crucial in guaranteeing competitive advantages to any type of analysis of scenarios and contexts $[12,13]$.

## 经济代写|供应链管理代写supply chain management代考|INTERNET OF THINGS

IoT is the term created that explains the fact that several objects used in daily life are connected through the internet, generating data and facilitating daily tasks, being a vast, complex, and adaptive network of devices with sensors, microchips, with processing and communication capabilities that interconnect people, machines, infrastructure, computing capacity, and systems over the Internet with security and privacy $[1,14]$.

In addition to being an important resource for collecting information in Big Data, allowing accessories, cameras, sensors, appliances, phones, drones, and many more devices and things to connect to the network, facilitating the daily life of human life, such as residential security that alert residents in real time, via smartphone, in case of break-in and invasion, are forms of IoT, just as this technology is economically and socially impacting different sectors and contexts, making cities smarter, rationalizing, and flexibilities logistics and transportation of goods, production, even providing remote monitoring of patients, in the context of health, the use of wristwatches that measure the number of steps in the day, heart rate, and many other data on the quality of life and health of the patient-user. In the same sense as allowing agribusiness, the optimized use of inputs, improving energy efficiency, reducing the risks of work and operation in an industrial plant, expanding access to services in the financial sector, enabling new business models based on use for insurers and rental companies [15].
IoT sensors can assure the population of the quality of the water supply, the levels of pollution and radiation in each location, among other applications of equal economic and social impact, since its advent there is already more equipment connected to the internet than people on the planet, where the internet stops connecting only people and starts to connect the things that surround them [16].

The information that IoT devices generate, they also make available a large amount of them, from a smoke detector generating sporadic events to a video surveillance system generating several events per minute, which instead of issuing a movement alert in an area, the vision system can recognize shapes, objects, and people and also inform by voice messages regarding the masked individual, where users cannot deal with a large number of events or alert messages, which can cause the human error and increase the level of risk, since combined with the resources of AI, a system can make analyses and learn in a fraction of a second the behaviors of the device, making recommendations to the user, or even taking specific actions instead of just sending alerts to someone who will make the decision [17].

# 供应链管理代考

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## 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。