Ⅹ. Harbor

AbstractThis note collect all terms occur in SEPP Lecture 6/7/9. It would be helpful to recap what has learnt and what has already been abstracted away. Pool of atomic termsplan-driven development process, heavy documentation, formal documentation, iteration, agile development process, individual, interaction, working software, customer collaboration, responding to change, design, implementation, unfinished feature, requirement engineering, requirement specification document, omniprese ...

AbstractionThis note collect all terms occur in SEPP Lecture 1/2/4/5. It would be helpful to recap what has learnt and what has already been abstracted away. Pool of atomic termssmall system, budget, reliability, complex interface, software development, requirement capture, design, construction, implementation, testing, debugging, maintenance, evolution, management, software engineering activity needs, issues, stakeholder, prioritization, maintenance, evolving requirement, modelli ...

AbstractionThis note collect all terms occur in SEPP Lecture 1/2/4/5. It would be helpful to recap what has learnt and what has already been abstracted away. Pool of atomic termssmall system, budget, reliability, complex interface, software development, requirement capture, design, construction, implementation, testing, debugging, maintenance, evolution, management, software engineering activity needs, issues, stakeholder, prioritization, maintenance, evolving requirement, modelli ...

Key discussionIs the singleton design pattern an antipattern? The singleton pattern is controversial. Some people go so far as to say singletons are evil. Others have likened singletons to sharks; they cruise along unnoticed under the surface, then pop up and bite you. We’re going to argue that it is an antipattern to be avoided at all costs. There are only a few legitimate uses for it –– we’ll go over these, too. Negative side The singleton pattern is creational. The biggest problem with t ...

QuestionDP vs Recursion with memorization I am wondering if that for any recursive function that can be translated into dynamic programming, is it always possible to also simply leave the function in its recursive form and apply a memorise wrapper to it as well? While we have clearly been shown there are many benefits to turning something into dynamic programming, I feel like some functions may be a lot easier to understand if they are in a recursive form and using a memorise function should hel ...

The purpose of this test is to show that there is correlation between modifiable argument in Vocaloid project file and quality of tuning. What is Vocaloid? Here is a link to wiki page. Vocaloid: Vocaloid (ボーカロイド, Bōkaroido) is a singing voice synthesizer software product. Its signal processing part was developed through a joint research project led by Kenmochi Hideki at the Pompeu Fabra University in Barcelona, Spain, in 2000 and was not originally intended to be a full commercial project. Back ...

What is Waterfall methodology?Waterfall Model methodology which is also known as Liner Sequential Life Cycle Model. Waterfall Model followed in the sequential order, and so project development team only moves to next phase of development or testing if the previous step completed successfully. What is the Agile methodology?Agile methodology is a practice that helps continuous iteration of development and testing in the software development process. In this model, development and testing activitie ...

All these information are from college homepage. Discrete Mathematics and Probability (INFR08031)KEYWORDS: SEM1 fundamental topics in discrete mathematics Mathematical Reasoning presents standard mathematical reasoning and proof techniques such as proof by induction. THIS HAS ALREADY BEEN TAUGHT IN PPS discrete and continuous probability theory Feedback is given weekly in tutorials, when students can discuss their solutions to homework questions. EXAM HOUR: 2h READING LIST: Discrete Mathemati ...

拼图筛选流程： 抓出一把拼图 注：一把的数量允许动态得调整 铺展在桌面上 并行对非字母信息筛选并处理 优质连块拼图 取出 形状是边界拼图 取出 字母向下 翻面 并行对字母信息筛选并处理 相似字母XY 收集 相似字母不再出现 取出 注：随机查找n次无结果 边界拼图 取出 已出现过的字母 取出 最后一组字母 相似字母X 收集X 相似字母不再出现 取出X 直接收集Y 取出Y 注：随机查找n次无结果 注释：仅支持两只手，左手字母靠前，右手字母靠后 注释：XY集合的选择靠特征，可选的组合有：AH、BDCG、EF 拼图拼接流程 筛选最外边 拼接里边 开始拼 拼接部分

OOP和AOPOOP面向对象编程，针对业务处理过程的实体及其属性和行为进行抽象封装，以获得更加清晰高效的逻辑单元划分。而AOP则是针对业务处理过程中的切面进行提取，它所面对的是处理过程的某个步骤或阶段，以获得逻辑过程的中各部分之间低耦合的隔离效果。这两种设计思想在目标上有着本质的差异 https://www.jianshu.com/p/2d634f128d3e AOP出现的更深层次的原因可能是java只能继承单一父类这个性质 计算机竞赛 ACM leetcode 牛客网 阿里云天池 谷歌云kaggle 华为杯数学建模 Jupyter NoteBook Installationhttps://www.jianshu.com/p/91365f343585在使用前一定要找配置文件，修改默认存储路径。 常规的情况下，Windows和Linux/macOS的配置文件所在路径和配置文件名如下所述： Windows系统的配置文件路径：C:\Users<user_name>.jupyter\ Linux/macOS系统的配置文件路径：/Users/ ...

过零率 零率体现的是信号过零点的次数，体现的是频率特性。因为需要过零点，所以信号处理之前需要中心化处理。 短时能量 短时能量体现的是信号在不同时刻的强弱程度。 短时自相关函数 学过信号处理的都应该知道，信号A与信号B翻转的卷积，就是二者的相关函数。 短时平均幅度差 音频具有周期特性，平稳噪声情况下利用短时平均幅度差可以更好地观察周期特性。 语谱图 ~ 频谱图（基于FFT） 语音分帧→每一帧分别FFT→求取FFT之后的幅度/能量，这些数值都是正值，类似图像的像素点，显示出来就是语谱图。 短时功率谱密度 音频信号可以看作短时间的平似平稳（如一帧信号），对每一帧利用周期图法分析，这个就是短时功率谱密度的思路。 谱熵 熵体现的是不确定性，例如抛骰子一无所知，每一面的概率都是1/6，信息量最大，也就是熵最大。 基频 也就是基频周期。人在发音时，声带振动产生浊音(voiced)，没有声带振动产生清音（Unvoiced）。浊音的发音过程是：来自肺部的气流冲击声门，造成声门的一张一合，形成一系列准周期的气流脉冲，经过声道（含口腔、鼻腔）的谐振及唇齿的辐射形成最终的语音信号。故浊音 ...

our main character: o, ω, O, Ω and Θ DEFINITIONAsymptotic NotationAsymptotic notations are the mathematical notations used to describe the running time of an algorithm when the input tends towards a particular value or a limiting value.Why we use asymptotic notation instead of detailed run-time function? :fire: TRIGGER: The function describe algorithm is too complicate to see how an algorithm performs. We’re only interested in the broad headlines of how some function behaves。 :star: MOTIVATION ...

our main character: o, ω, O, Ω and Θ DEFINITIONAsymptotic NotationAsymptotic notations are the mathematical notations used to describe the running time of an algorithm when the input tends towards a particular value or a limiting value.Why we use asymptotic notation instead of detailed run-time function? :fire: TRIGGER: The function describe algorithm is too complicate to see how an algorithm performs. We’re only interested in the broad headlines of how some function behaves。 :star: MOTIVATION ...

项目概要机器人对话，根据上文得到下文这么个东西。推测也是使用滑窗来做的，但具体不清楚了。 我的任务给 pred 进行打分，评分规则如下： 打分区间都是0–3，0最差，3最好 “input”: 这个输入文本，有非常多的种类。 “gold”: 参考的解释，可以和 pred 比较得到分数。 注意：gold只是一个参考，pred可以跟gold不同意思。 “pred”: 预测出来的内容。 “hs_specificity”: 具体性，是否给出了具体的内容。 没有任何有价值的信息的给0，如I don’t know就可以给0。 有具体内容，但具体为虚的给1。 如果有表示具体事物的词给2。 2分档次特征出现次数大于2的都可以考虑给3。 注意：出现一些OOV可以看做是specificity的一种表现，比如 I paid $ <unk> dollars already。 “hs_fluency”: pred 本身的属性，字面义，是否流畅。 如果整体都很烂，尤其是有重复给0 如果有主要问题但整体上还算通顺给1。 基本流畅但有个别词的瑕疵一般给2。 完全流畅的给3，比如I do ...

StackoverflowColorize Voronoi Diagram https://stackoverflow.com/questions/20515554/colorize-voronoi-diagram/20678647#20678647 IPython Cookbook, Second Edition (2018)14.5. Computing the Voronoi diagram of a set of points https://ipython-books.github.io/145-computing-the-voronoi-diagram-of-a-set-of-points/ template12345678910111213141516171819202122232425262728293031323334353637383940414243import numpy as npimport pandas as pdimport matplotlib.pyplot as pltfrom scipy.spatial import Voronoi, vorono ...