hugo to v4

content/.trash/Homework_1.md

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+---
+title: Homework 1, student's Problem
+tags:
+  - work-about
+---
+
+# 0780
+

content/.trash/Problem.md

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+---
+title: Problem
+tags:
+  - research-about
+---
+* UWB signal ejection
+* S parameter -> Frequency spectrum
+* Know why VNA don't have time domain (circuit view)

content/.trash/Untitled.canvas

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+{}

content/.trash/VNA/IFBW.md

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+---
+title: Intermediate Frequency Bandwidth
+tags:
+  - equipment
+  - VNA
+  - research-about
+---
+

content/.trash/equip_res_MOC.md

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+---
+title: Equipment Research MOC
+tags:
+  - MOC
+---
+

content/.trash/experiment_design.md

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+---
+title: UWB signal characterization experiment by VNA demo
+tags:
+  - experiment
+---
+
+
+# Experiment Graph Overview
+
+![](research_career/attachments/Untitled-1.png)
+
+
+In this experiment, we use VNA Port 1 to eject signal and port2 to receive the signal reflecting by the reflection medium, such as burned tissue.
+
+And we can use VNA to get scattering parameter to do analysis in frequency spectrum, including amplitude information and phase information.
+
+# Experiment Explanations
+
+## What is VNA
+
+![](research_career/attachments/Pasted%20image%2020231016082202.png)
+
+A Vector Network Analyzer (VNA) is a sophisticated electronic instrument used in the field of radio frequency (RF) and microwave engineering. Its primary function is to measure and characterize the electrical behavior of high-frequency components, such as antennas, cables, and passive RF devices like filters and amplifiers. VNAs are essential tools in the design, testing, and maintenance of RF and microwave systems.
+## Ejecting Signal
+
+The VNA generates an "ejecting signal," also known as the "incident signal" or "test signal", which is usually be a continuous wave (CW) or narrowband signal. In our VNA equipment, the signal is CW signal, which is at discrete frequencies sweeping in the specific frequency range.
+
+Here I want to name the signal, which is at discrete frequencies sweeping in the specific frequency range, **frequency sweeping signal**
+
+**So we can not acquire UWB signal directly in VNA.**
+
+Here are two possible solutions:
+
+1. Modem our sweep signal to UWB signal.
+	* I have already find the way to modem chirp signal to UWB signal, here:
+		[Chirp BOK BPSK.pdf](https://pinktalk.online/research_career/attachments/CN101267424A.pdf)
+	* Not sure if we can modem our frequency sweeping signal to UWB signal. 
+
+2. Direct using our frequency sweeping signal.
+	* Though we don't directly eject UWB signal, our ejecting signal also contains discrete frequencies, which are composition of UWB signal. In this way, we can analysis different frequencies component in UWB separately.
+	* Speculatively, we guess the high frequency part's phase information can provide the range detection function. The low frequency part's amplitude information will have a relation with the reflecting medium.
+
+In this experiment demo, we use solution 2.
+
+## Data we get
+
+In this experiment, we can only get scattering parameter, S11 and S12.
+
+![](research_career/attachments/Pasted%20image%2020231016091540.png)
+
+Using this parameter, considering incident as a constant we can get frequency spectrum information, though the signal is not UWB signal
+
+# Experiment Step
+
+## 1. Set up Experiment equipment
+
+*  Prepare the experimental apparatus
+	* VNA, Keysight E5063A 100kHz - 6.5GHz
+	* UWB antennas
+	* N, male - SMA male
+
+* VNA calibration
+* Load the UWB antennas to VNA port1 and port2
+
+
+## 2. Set reference data
+
+* In antenna's near field and far filed, such as 20cm and 40cm, we need to set a specified medium and get S11 and S12 trace data.
+* This two experiments will be our reference. Later we can get other S11 and S12 to compare with this data get range and material.
+
+
+## 3. Data collection
+
+Collect S11 and S12 trace in different reflection mediums and distances between antennas and mediums. 
+
+## 4. Data analysis
+
+We want to build relationship between our data with distance and reflection mediums to show that UWB can have the ability to detect burning tissue level.

content/.trash/log_06072023.md

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+---
+title: Log 2023.07.06 - 路过人间，谁有意见
+tags:
+- log
+- music
+---
+
+![](文学/log/2023/7/attachments/7JEC(63A65[8JFI[G6O`IIK_tmb.jpg)

content/.trash/log_11092023.md

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+---
+title: Log 2023.09.11 - Get some interesting blog here
+tags:
+  - log
+  - front-end
+---
+* [_Building a Frontend Framework; Reactivity and Composability With Zero Dependencies_. https://18alan.space/posts/how-hard-is-it-to-build-a-frontend-framework.html. Accessed 11 Sept. 2023.](https://18alan.space/posts/how-hard-is-it-to-build-a-frontend-framework.html)

content/.trash/log_18092023.md

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+---
+title: Log 2023.09.18 - A Normal Learning Day
+tags:
+  - log
+---
+
+* learn 红色高棉 by wiki
+* try to use [TXYZ](https://txyz.ai/) to read paper

content/.trash/spectrum_analyzer.md

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+---
+title: Spectrum Analyzer
+tags:
+  - equipment
+  - research-about
+---
+
+# What is spectrum analyzer?
+
+Measure input signal power spectrum
+# Spectrum Analyzer for UWB
+
+## Papers
+
+### Measurements of UWB through-the-wall propagation using spectrum analyzer and the Hilbert transform
+
+
+[*pdf* - Measurements of UWB through-the-wall propagation using spectrum analyzer and the Hilbert transform](https://pinktalk.online/equipment_research/attachments/mop.23107.pdf)
+
+![Architect](signal_processing/equipment/attachments/Pasted%20image%2020230918104114.png)
+
+
+# Reference
+
+* [_Understanding Basic Spectrum Analyzer Operation_. _www.youtube.com_, https://www.youtube.com/watch?v=P5gxNGckjLc. Accessed 13 Sept. 2023.](https://pinktalk.online/%E6%96%87%E5%AD%A6/%E5%8F%A5%E5%AD%90/Feeling/)
+* https://www.bilibili.com/video/BV1kG4y1q72V/?spm_id_from=333.337.search-card.all.click&vd_source=c47136abc78922800b17d6ce79d6e19f

content/Math/MOC.md

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+---
+title: Math MOC
+tags:
+- math
+- MOC
+---
+
+# Statistics
+
+## Basic concept
+
+* [Quantile](Math/Statistics/Basic/Quantile.md)
+
+# Discrete mathematics
+
+## Set theory
+
+* [Cantor Expansion](Math/discrete_mathematics/set_theory/cantor_expansion/cantor_expansion.md)
+
+
+# Optimization Problem
+
+
+* [Quadratic Programming](Math/optimization_problem/Quadratic_Programming.md)

content/Math/Statistics/Basic/Quantile.md

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+---
+title: Quantile
+tags:
+- math
+- statistics
+- basic
+---
+
+**分位数**（英语：Quantile），亦称**分位点**，是指用分割点（cut point）将一个随机变量的概率分布范围分为几个具有相同概率的连续区间。分割点的数量比划分出的区间少1，例如3个分割点能分出4个区间。
+
+常见的分位数包括中位数（二分位数）、四分位数（四分位数）和百分位数。
+
+1.  中位数：中位数是将一组数据按照大小排序后，处于中间位置的值。将数据分成两部分，有一半的观察值小于中位数，另一半的观察值大于中位数。
+    
+2.  四分位数：四分位数将数据分成四个等分，分别是下四分位数（25%分位数）、中位数（50%分位数）和上四分位数（75%分位数）。下四分位数是将数据排序后，处于25%位置的值；中位数是处于50%位置的值；上四分位数是处于75%位置的值。
+    
+3.  百分位数：百分位数将数据分成100个等分，可以表示某个特定百分比处的数据值。例如，75%的百分位数表示将数据排序后，处于75%位置的值

content/Math/discrete_mathematics/set_theory/cantor_expansion/cantor_expansion.md

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+---
+title: Cantor expansion
+tags:
+- code-design
+- basic
+- math
+- algorithm
+- discrete-mathematics
+- set-theory
+---
+
+
+康托展开（Cantor expansion），也称为康托编码（Cantor encoding），是由德国数学家乔治·康托（Georg Cantor）于19世纪末提出的一种数学技术。它用于将**一个无限序列的数字（或有限序列的数字）映射到一个唯一的实数，从而实现序列的编码和排序。**
+
+# Objective
+
+康托展开与逆展开是*将全排列和它的字典序互相转化*的两种算法
+
+# Application
+
+* 作为枚举问题的hash function
+
+# Step by Step
+
+## Deriving Cantor Expansion
+
+### Lemma1 and Lemma2
+
+以DFS生成的4阶全排列为例~~*(no this algorithm detail here)*~~，带编号：
+
+```text
+0   1 2 3 4
+1   1 2 4 3
+2   1 3 2 4
+3   1 3 4 2
+4   1 4 2 3
+5   1 4 3 2
+6   2 1 3 4
+7   2 1 4 3
+8   2 3 1 4
+9   2 3 4 1
+10  2 4 3 1
+11  2 4 3 1
+12  3 1 2 4
+13  ...
+```
+
+
+可以发现，首位为 1 的全排列表示的数全部在区间 [0,5] ；首位为 2 的全排列全部在区间 [6,11]；首位为 3 的则在 [12,17] ；4 的在 [18,23] 。因为首位有 4 种取值的可能，所以把所有的 4 阶全排列划分成了 4 个长度为 $\frac{4!}{4}=3!=6$ 的区间，首位为 1 的处在第 1 个这样长为 6 的区间，首位为 2 的处在第 2 个，首位为 3 的处在第 3 个……
+
+> [!Lemma1] 
+> 衍生到一般情况，对于首位为$k$的$n$阶全排列，它所在的区间为：$[(k-1) \times (n-1)!,\quad k \times (n-1)!]$ 
+
+在确定大致范围后，如何定位到具体的编号呢？
+
+观察遮住第一位的情况：
+
+```text
+0   X 2 3 4  <==>  1 2 3
+1   X 2 4 3  <==>  1 3 2
+2   X 3 2 4  <==>  2 1 3
+3   X 3 4 2  <==>  2 3 1
+4   X 4 2 3  <==>  3 1 2
+5   X 4 3 2  <==>  3 2 1
+6   X 1 3 4  <==>  1 2 3
+7   X 1 4 3  <==>  1 3 2
+8   X 3 1 4  <==>  2 1 3
+9   X 3 4 1  <==>  2 3 1
+10  X 4 3 1  <==>  3 1 2
+11  X 4 3 1  <==>  3 2 1
+12  X 1 2 4  <==>  1 2 3
+13  ...
+```
+
+观察上表我们发现，**只考虑元素间的相对大小关系**（或者说各个数字——表示相对大小的符号，之间的相对大小关系），*遮掉首位的 4 阶全排列可以认为就是 3 阶全排列*，只不过它们使用的数字（表示大小的符号）不同。
+
+> [!Lemma2] 
+> 所以我们推导$n$阶全排列对应的$(n-1)$阶全排列，如上面所示，去掉首位后，需要对每个能与**首位构成顺序的数字**(*即，比首位数字大的数*)自减少1 
+
+### Calculate Series index by Lemmas
+
+对于任意序列，迭代使用引理1和引理2就可以得到它的index。
+
+#### Step
+1. 利用**引理 1**确定与它同阶同首位的全排列表示的数字的范围，取左边界累加到结果上
+2. 利用**引理 2**将$n$阶全排列转化为$(n-1)$阶全排列
+3. 得到1阶全排列前，重复1，2；得到1阶全排列后输出结果；
+
+#### Example
+
+$$
+35142 \rightarrow 3\dot{5}1\dot{4}2 \rightarrow 34132 \rightarrow 341\dot{3}\dot{2} \rightarrow 34121
+$$
+
+$$
+index = (3-1) \times 4! + (4-1) \times 3! + (1-1) \times 2! + (2-1) \times 1! = 67
+$$
+
+## Definition
+
+> [!hint] 
+>  顺序对是由在两个在序列中的元素组成的有序对，它前项在序列中的位置比后项靠前，且前项小于后项。
+
+$a_{1\cdots n}$表示一个n阶的全排列，$a_i$表示这个全排列的$i$的数字，定义$a_{1\cdots n}$的退位序列为$b_{1\cdots n}$, $b_j$等于$a_j$在全排列中作顺序对后项的顺序对个数，形式为:
+$$
+\forall \ 1 \leq j \leq n, b_j = |\{(a_i, a_j) \ | \ 1 \leq i \leq j \  \text{and} \ a_i \leq a_j\}|
+$$
+
+其康托展开公式为：
+$$
+F(a_{1\cdots n}) = \sum_{i=1}^n (a_i-b_i-1)\times(n-i)!
+$$
+
+
+# Code 
+
+## Method 1
+
+直接用定义写出，但是不生成$b$序列，只在用到时求当时的$b_i$
+
+```python
+class CantorExpansion():
+    def cantor_encode(self, s:list) -> int:
+
+        '''
+        Encode a list of integers to a single integer using Cantor expansion.
+        '''
+
+        count  = 0
+
+        for i in range(len(s)):
+            count += self.factorial(len(s) - i - 1) * (s[i] - self.count_smaller(s, i) - 1)
+
+        return count
+
+    def factorial(self, x:int) -> int:
+        if x == 1 or x == 0:
+            return 1
+        else:
+            return self.factorial(x - 1) * x
+        
+    def count_smaller(self, s:list, i:int) -> int:
+        count = 0
+        for j in range(i):
+            if s[j] < s[i]:
+                count += 1
+        return count
+```
+
+python file goto: [cantor_expansion.py](https://github.com/PinkR1ver/Jude.W-s-Knowledge-Brain/blob/master/Math/discrete_mathematics/set_theory/cantor_expansion/code/cantor_expansion.py)
+
+复杂度会是$\varTheta(n^2)$
+
+## Method 2
+
+再次明确顺序对的概念：
+
+> [!tip]
+>  顺序对是指数组中的一对元素arr[i]和arr[j]，其中i < j且arr[i] > arr[j]
+
+遍历每一个数的时候，需要计算`count_smaller(s,i)`，因此复杂度被提升到$\varTheta(n^2)$。
+
+其实`count_smaller(s,i)`这个方法的目的就是计算数组的顺序对，提高计算数组顺序对的高速算法可以提高算法的复杂度。
+
+树状数组（Fenwick Tree）是一种用于高效计算[前缀和（Prefix Sum）](tmp_script/prefix_sum.md)的数据结构，它可以在$O(\log{n})$的时间复杂度内完成前缀和的计算和更新操作。
+
+### Trick - 使用树状数组求顺序对的详细步骤
+
+Step 1: 离散化 为了方便处理，我们首先对值域数组进行离散化处理，将其转化为一个以0为起始索引的连续整数数组。离散化的目的是将原始的值域映射到一个连续的范围内，以便于在树状数组中使用。
+
+Step 2: 初始化树状数组 创建一个长度为n+1的树状数组bit，并将所有元素初始化为0。这个额外的元素bit[0]不会被使用，我们只是为了方便计算。
+
+Step 3: 统计顺序对 从右往左遍历离散化后的值域数组arr，对于每个元素arr[i]，我们需要统计在其左侧且比它大的元素的个数。
+
+在树状数组中，我们可以通过查询前缀和的方式来计算某个位置的值。因此，对于当前的元素arr[i]，我们查询树状数组中索引为arr[i]的前缀和，得到的结果就是arr[i]左侧比它大的元素的个数。
+
+Step 4: 更新树状数组 在统计完当前元素的顺序对后，我们需要更新树状数组，以便下一次查询能够正确计算前缀和。具体操作如下：
+
+- 在树状数组中，将索引为arr[i]的位置的值加1，表示arr[i]的出现次数加1。
+- 重复上述操作，直到遍历完所有元素。
+
+Step 5: 计算总顺序对数 完成整个遍历后，树状数组中的每个位置的值表示该值在原始数组中的出现次数。通过查询树状数组的前缀和，我们可以计算出总的顺序对数。
+
+--- 
+
+利用上述使用树状数组求顺序对的算法就可以将Cantor Expansion复杂度降低到$\varTheta(n\log{n})$
+
+
+# Inverse Cantor Expansion
+
+逆康托展开的思想是用引理1去定位每一个位置
+
+Example:
+
+`inverse_cantor_expansion(n=5, x=96)`:
+
+* Step 1. 如果是字典序从1开始，则(x - 1) = 95，说明在这个数已经有95个数
+* Step 2. floor(95 / (n-1)!) = floor(95 / 4!) = 3，说明有3个数比第一位小，所以第一位被定位为4，余数为23
+* Step 3. 剩下数字被23定位，floor(23 / 3!) = 3，余数为5，说明有3个数比第二位小，被定位为4，但是4已经出现过，因此是5 
+* Step 4. 剩下的数字用5定位，floor(5 / 2!) = 2，余数为1，说明有2个数比第三位小，被定位为3。
+* Step 5. 同理，剩下第四位被定位为2，最后一位被定位为1
+
+# Generalized Cantor Expansion
+
+TODO ... ...
+
+Generalized Cantor Expansion可能并不能满足双射条件
+
+# Reference
+
+* ChatGPT
+* [“【给初心者的】康托展开.” 知乎专栏, https://zhuanlan.zhihu.com/p/39377593. Accessed 6 July 2023.](https://zhuanlan.zhihu.com/p/39377593)
+

content/Math/discrete_mathematics/set_theory/cantor_expansion/code/cantor_expansion.py

@@ -0,0 +1,63 @@
+class CantorExpansion():
+    def cantor_encode(self, s:list) -> int:
+
+        '''
+        Encode a list of integers to a single integer using Cantor expansion.
+        '''
+
+        count  = 0
+
+        for i in range(len(s)):
+            count += self.factorial(len(s) - i - 1) * (s[i] - self.count_smaller(s, i) - 1)
+
+        return count
+    
+    def cantor_decode(self, x:int, n:int) -> list:
+            
+            '''
+            Decode a single integer to a list of integers using Cantor expansion.
+            '''
+
+            s = [None] * n
+            used_dict = {}
+
+            for num in range(1, n + 1):
+                used_dict[num] = False
+
+
+            iter = 0
+            for i in range(n - 1, -1, -1):
+
+                smaller = x // self.factorial(i)
+                x %= self.factorial(i)
+
+                count = 0
+                for i in range(1, n + 1):
+                    if not used_dict[i]:
+                        count += 1
+                        if count == smaller + 1:
+                            s[iter] = i
+                            used_dict[i] = True
+                            iter += 1
+                            break
+                
+            return s
+
+    def factorial(self, x:int) -> int:
+        if x == 1 or x == 0:
+            return 1
+        else:
+            return self.factorial(x - 1) * x
+        
+    def count_smaller(self, s:list, i:int) -> int:
+        count = 0
+        for j in range(i):
+            if s[j] < s[i]:
+                count += 1
+        return count
+
+        
+if __name__ == '__main__':
+    s = CantorExpansion()
+    print(s.cantor_encode([3, 5, 7, 4, 1, 2, 9, 6, 8]))
+    print(s.cantor_decode(0, 9))

content/Math/optimization_problem/Quadratic_Programming.md

@@ -0,0 +1,77 @@
+---
+title: Quadratic Programming
+tags:
+  - math
+  - optimize
+  - optimization
+---
+
+# Why I write this note?
+
+[猪熊一波. _帮女朋友降维打击领导！_哔哩哔哩_bilibili_. https://www.bilibili.com/video/BV1ZN411T7c9/. Accessed 30 Nov. 2023.](https://www.bilibili.com/video/BV1ZN411T7c9/?spm_id_from=333.999.0.0&vd_source=c47136abc78922800b17d6ce79d6e19f)
+
+# Tips
+
+> [!tip] 
+> "Programming" in this context refers to a formal procedure for solving mathematical problems. This usage dates to the 1940s and is not specifically tied to the more recent notion of "computer programming." To avoid confusion, some practitioners prefer the term "optimization" — e.g., "quadratic optimization."
+> 
+> "Programming" 在中文中的翻译可以为“规划”， “Quadratic Programming”的翻译为“二次规划”
+
+> [!Summary] 
+> A Quadratic Program(QP) has a  quadratic objective function and linear constrains
+
+# Problem Formulation
+
+The quadratic programming problem with $n$ variables and $m$ constraints can be formulated as follows. Given:
+
+* a real-valued, n-dimensional vector $c$,
+* an $n\times n$-dimensional real symmetric matrix $Q$,
+* an $m \times n$-dimensional real matrix $A$, and
+* an $m-dimensional$ real vector $b$
+
+the objective of quadratic programming is to find an $n$-dimensional vector $x$, that will
+
+$$
+\text{minimize} \quad \mathup{\frac{1}{2} x^{T}Qx + c^{T}x}\quad 
+$$
+$$
+\text{subject to} \quad A\mathup{x} \preceq b
+$$
+$$
+\mathup{x} = \begin{bmatrix}
+x_1 \\
+x_2 \\
+\vdots \\
+x_n
+\end{bmatrix}, \mathup{Q} = 
+\begin{bmatrix}
+Q_{11} & Q_{12} & \cdots & Q_{1n} \\
+\vdots & \vdots & \ddots & \vdots \\
+Q_{n1} & Q_{n2} & \cdots & Q_{nn}
+\end{bmatrix},
+\mathup{c} = \begin{bmatrix}
+c_1 \\
+c_2 \\
+\vdots \\
+c_n
+\end{bmatrix},
+\mathup{A} = 
+\begin{bmatrix}
+A_{11} & A_{12} & \cdots & A_{1m} \\
+\vdots & \vdots & \ddots & \vdots \\
+A_{n1} & A_{n2} & \cdots & A_{nm}
+\end{bmatrix},
+\mathup{b} = \begin{bmatrix}
+b_1 \\
+b_2 \\
+\vdots \\
+b_n
+\end{bmatrix}
+$$
+
+
+# Reference
+
+
+* [猪熊一波. _帮女朋友降维打击领导！_哔哩哔哩_bilibili_. https://www.bilibili.com/video/BV1ZN411T7c9/. Accessed 30 Nov. 2023.](https://www.bilibili.com/video/BV1ZN411T7c9/?spm_id_from=333.999.0.0&vd_source=c47136abc78922800b17d6ce79d6e19f)
+* [“Quadratic Programming.” _Wikipedia_, 25 Nov. 2023. _Wikipedia_, https://en.wikipedia.org/w/index.php?title=Quadratic_programming&oldid=1186784717.](https://en.wikipedia.org/wiki/Quadratic_programming#:~:text=Quadratic%20programming%20(QP)%20is%20the,linear%20constraints%20on%20the%20variables.)

content/Math/real_analysis/cauchy_principal_value.md

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+---
+title: Cauchy Principal Value
+tags:
+  - math
+  - real-analysis
+---
+# Notation
+
+
+$$
+\text{p.v.} \int_{-\infty}^{\infty} f(x)dx = \lim_{a\rightarrow+\infty} \int_{-a}^{a} f(x) dx = \lim_{a\rightarrow+\infty}[f(a) - f(-a)]
+$$
+
+
+
+![](Math/real_analysis/attachments/6BC0B163CEFCF127E1D70326AB7D1648%201.png)
+
+
+![](Math/real_analysis/attachments/78DC2683DB0DF2EFEB6215DAB8C18C25.png)
+
+the Cauchy principal value is the method for assigning values to *certain improper integrals* which would otherwise be undefined. In this method, a singularity on an integral interval is avoided by limiting the integral interval to the non singular domain.
+
+# Reference
+
+* [_Real Analysis 64 | Cauchy Principal Value_. _www.youtube.com_, https://www.youtube.com/watch?v=0SP2b0nFpwI. Accessed 3 Jan. 2024.](https://www.youtube.com/watch?v=0SP2b0nFpwI)
+* [“Cauchy Principal Value.” _Wikipedia_, 31 Dec. 2023. _Wikipedia_, https://en.wikipedia.org/w/index.php?title=Cauchy_principal_value&oldid=1192842366.](https://en.wikipedia.org/wiki/Cauchy_principal_value)

content/Photography/Aesthetic/Landscape/Landscape_MOC.md

@@ -0,0 +1,9 @@
+---
+title: Landscape Photography MOC
+tags:
+- photography
+- landscape
+- MOC
+---
+
+* [🌊Sea MOC](Photography/Aesthetic/Landscape/Sea/Sea_MOC.md)

content/Photography/Aesthetic/Landscape/Sea/Fujifilm_Blue_by_小红书_Philips谢骏.md

@@ -0,0 +1,29 @@
+---
+title: Sea in Fujiflm Blue
+tags:
+- photography
+- landscape
+- photography
+---
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/Pasted%20image%2020230420014349.png)
+
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/Pasted%20image%2020230420014354.png)
+
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/Pasted%20image%2020230420014401.png)
+
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/Pasted%20image%2020230420014613.png)
+
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/Pasted%20image%2020230420014622.png)
+
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/Pasted%20image%2020230420014634.png)
+
+# Reference
+
+* [太绝了！我拍出了富士蓝！- 小红书，Philips谢骏](https://www.xiaohongshu.com/user/profile/6272c025000000002102353b/641299a200000000130129bb)
+

content/Photography/Aesthetic/Landscape/Sea/Sea_MOC.md

@@ -0,0 +1,11 @@
+---
+title: 🌊Sea MOC
+tags:
+ - landscape
+ - sea
+ - photography
+ - aesthetic
+---
+
+* [Fujifilm Blue🌊, 小红书-Philips谢骏](Photography/Aesthetic/Landscape/Sea/Fujifilm_Blue_by_小红书_Philips谢骏.md)
+* [豊島🏝, Instagram-shiifoncake](Photography/Aesthetic/Landscape/Sea/豊島_Instagram_shiifoncake.md)

content/Photography/Aesthetic/Landscape/Sea/豊島_Instagram_shiifoncake.md

@@ -0,0 +1,24 @@
+---
+title: 豊島🏝
+tags:
+ - photography
+ - sea
+ - landscape
+ - aesthetic
+---
+![](Photography/Aesthetic/Landscape/Sea/attachments/shiifoncake_338949220_771246770941652_287141902256013940_n.jpg)
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/shiifoncake_339164445_155642070453847_6842139942547564019_n%20(1).jpg)
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/shiifoncake_339164445_155642070453847_6842139942547564019_n.jpg)
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/shiifoncake_338803198_1141886276488589_5464974698780309052_n%20(1).jpg)
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/shiifoncake_338803198_1141886276488589_5464974698780309052_n.jpg)
+
+![](Photography/Aesthetic/Landscape/Sea/attachments/shiifoncake_338758486_601356648715316_3737336679741136784_n.jpg)
+
+
+# Reference
+
+* (https://www.instagram.com/p/Cqh4Ci8vV5u/)[https://www.instagram.com/p/Cqh4Ci8vV5u/]

content/Photography/Aesthetic/Polaroid/Polaroid_aesthetic_MOC.md

@@ -0,0 +1,9 @@
+---
+title: Polaroid Aestheic MOC
+tags:
+- photography
+- Polaroid
+- MOC
+---
+
+* [🖼How to show Polaroid photo in a great way](Photography/Aesthetic/Polaroid/Polaroid_showcase.md)

content/Photography/Aesthetic/Polaroid/Polaroid_showcase.md

@@ -0,0 +1,25 @@
+---
+title: How to show Polaroid photo in a great way
+tags:
+- photography
+- Polaroid
+- share
+---
+
+
+
+![](Photography/Aesthetic/Polaroid/attachments/IMG_5330.jpg)
+
+
+
+![](Photography/Aesthetic/Polaroid/attachments/IMG_5329.jpg)
+
+
+
+![](Photography/Aesthetic/Polaroid/attachments/IMG_5327.jpg)
+
+
+
+![](Photography/Aesthetic/Polaroid/attachments/IMG_5334.jpg)
+
+Credits to  [比扫描仪更easy的宝丽来翻拍解决方案 -BonBon的Pan](https://www.xiaohongshu.com/user/profile/6272c025000000002102353b/6331af53000000001701acfd)

content/Photography/Aesthetic/Portrait/Flower_and_Girl.md

@@ -0,0 +1,53 @@
+---
+title: 🌸Flower & Girl
+tags:
+- photography
+- portrait
+- 摘抄
+---
+
+Credits to [Marta Bevacqua](https://www.martabevacquaphotography.com/), 
+Thanks🌸
+
+![](Photography/Aesthetic/Portrait/attachments/14.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/15.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/16.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/17.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/18.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/19.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/20.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/21.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/22.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(1).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(2).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(3).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(4).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(5).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(6).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(7).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(8).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(9).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(11).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content%20(12).jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/content.jpg)
+

content/Photography/Aesthetic/Portrait/From Korean MV Todays_Mod.md

@@ -0,0 +1,35 @@
+---
+title: Cute Portrait from Korean MV <Today's Mood>
+tags:
+- photography
+- portrait
+- korean
+- cute
+- 摘抄
+---
+
+Credits to [MV - CHEEZE(치즈) _ Today's Mood(오늘의 기분)](https://www.youtube.com/watch?v=zRq_DlEzygk),
+Thanks
+
+Also, I see this in [摄影灵感｜那有一点可爱 - by   
+小八怪](https://www.xiaohongshu.com/explore/63f0a27e0000000013002b05)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_4_2023-03-27_23-53-20.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_5_2023-03-27_23-53-20.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_6_2023-03-27_23-53-20.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_7_2023-03-27_23-53-20.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_8_2023-03-27_23-53-20.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_9_2023-03-27_23-53-20.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_1_2023-03-27_23-53-20%201.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_2_2023-03-27_23-53-20%201.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_3_2023-03-27_23-53-20%201.jpg)
+
+![](Photography/Aesthetic/Portrait/attachments/photo_2023-03-27_23-55-45.jpg)

content/Photography/Aesthetic/Portrait/Portrait_MOC.md

@@ -0,0 +1,11 @@
+---
+title: 👧Portrait
+tags:
+- photography
+- portrait
+- 摘抄
+- MOC
+---
+
+* [🌸Flower & Girl](Photography/Aesthetic/Portrait/Flower_and_Girl.md)
+* [👧🇰🇷Cute Portrait from Korean MV <Today's Mood>](Photography/Aesthetic/Portrait/From%20Korean%20MV%20Todays_Mod.md)