§5-1 Basic principle of polarograpy §5-2 Equation of diffusion current A basis of polarographically quantitative analysis §5-3 Halfwave potential —polarographic qualitative analysis §5-4 Interference currents and their removing methods §5-5 Characteristics and disadvantages of polarographic analysis §5-6 Polarographic Catalytic Wave §5-7 Single-sweep polarography(单扫描极谱法） (Oscillographic polarography，示波极谱法) § 5-8 Squar-wave polarography §5-9 Pulse polarography §5-10 Stripping voltammetry §5-11 单指示电极安培滴定（Amperometric titration with single indicating electrode, polarographic titration) §5-12 双指示电极安培滴定（永停滴定） （Dead-stop end point titration） §5- 13 双指示电极电位滴定 （potentiometric titration with double indicating electrodes)

6.1 Non-asymptotic Analysis: Concentration inequality 6.2 Non-asymptotic Analysis: extreme singular values

• MSC.EASY5 Overview • Getting Started • Help and Documentation • Model Building & Simulation • Operating Point and Steady State Analysis • Linear Analyses • Data Tables and the Matrix Editor • Analysis Tools & Methodology • Simulation and Integration • Interactive Simulation • Miscellaneous Topics • MSC.EASY5 Architecture • Writing Code in MSC.EASY5 • Summary

Lyapunov analysis, which uses monotonicity of a given function of system state along trajectories of a given dynamical system, is a major tool of nonlinear system analysis It is possible, however, to use monotonicity of volumes of subsets of the state space to predict certain properties of system behavior. This lecture gives an introduction to suc methods

2.1 Analysis 2.2 Asymptotic Order of Growth(渐进分析) 2.3 Three Techniques for Designing Algorithms 1. Greedy Algorithms 2. Divide and Conquer 3. Dynamical Programming

一、库仑滴定 coulometric titration 二、自动库仑滴定 automated coulometric titration 三、微库仑分析 microcoulometric analysis electrolytic and coulometric analysis

 3.1 Learning Problems  3.2 The least square method (LSM)  3.3 Linear regression analysis  1 Simple Linear Regression  2 Multiple Regression  3 Understanding the Regression Output  4 Coefficient of Determination R2  5 Validating the Regression Model

 2.1 Overview of data types  2.2 Review of Data pre-processing tools and platforms  2.3 Clean, storage and management of raw data  2.4 Collections of data analysis and data mining

 1.1 What’s big data?  1.2 Overview of data analysis  1.3 Overview of data mining  1.4 Make requirement for different professional applications

一、电解分析基础 fundament of electrolytic analysis 二、理论分解电压与析出电位 theoretical decomposition voltage and deposited potential 三、浓差极化与电化学极化 concentration polarization and electrochemical polarization 四、电重量分析与电解分离 electrogravimetric analysis and electrolytic separation