[NKPR 0] Building Caffe on Window (for anaconda environment)

I recall that installing Caffe on Window was one of the hardest steps on this project.

 

  • However,  some (small) problems arises depending on the different environment one has.  For me, installing VS 2015 raised error ;  a setup package is either missing or damaged, but no perfect help for this problem exists on the web. (Spend two days repeating shredding the whole VS 2015/reinstalling)

 

  • In addition, building PyCaffe requires python 3.5, while I have been using python 3.6 (anaconda) for my previous works. Since I do not want to change my working environment, I tried to install PyCaffe using anaconda environment setting(python 3.5). There are some settings that should be modified before installing.

 

  1. Create new environment for python 3.5. (e.g. conda create -n py35 python = 3.5.0 anaconda)
  2. Before using cmd, call the anaconda environment (e.g. conda activate py35)
  3. When modifying caffe\caffe\scripts\build_win.cmd according to the video above, set CONDA_ROOT variable as location to the python 3.5. environment conda
  4. Now follow the video!
  5. Done!

[USVC] Drawing Supply Chain 2 – US Listed Domestic Firms

이 슬라이드 쇼에는 JavaScript가 필요합니다.

<Histogram of firm out nodes, clockwise from left top: 2000, 2005, 2010, 2015>

numbers

  • Total Sample number decreased through 1998 to 2016:{1998: 9062, 1999: 8906, 2000: 8512, 2001: 8167, 2002: 7692, 2003: 7447, 2004: 7498, 2005: 7015, 2006: 6690, 2007: 6676, 2008: 7448, 2009: 7792, 2010: 7427, 2011: 7223, 2012: 6943, 2013: 6783, 2014: 6640, 2015: 6231, 2016: 5850}
  • The number of edges(linking firms), however, further decreased in the same period
  • The average shortest length of all possible linkages: {2000: 1.638, 2005: 1.531, 2010: 1.284, 2015: 1.322}

 

Possible explanations

  • The (trained natural language) model may be over-fitted to early 2000’s
  • Supply Chain among U.S. firms might be actually decreasing due to economic uncertainty

 

10 Firms with the most in-nodes

(year 2000) : [[‘Walmart Inc’, 0.027717626678215677], [‘Lucent Technologies Inc’, 0.026634906886097875], [‘Hewlett Packard Enterprise Co’, 0.023170203551320916], [‘AT&T Corp’, 0.018189692507579038], [‘Ford Inc’, 0.0173235166738848], [‘Cisco Systems Inc’, 0.01602425292334344], [‘Siemens AG’, 0.013858813339107838], [‘Boeing Corp’, 0.013642269380684278], [‘Intel Corp’, 0.012126461671719359], [‘Target Inc’, 0.01169337375487224]]

(year 2015) : [[‘Walmart Inc’, 0.020942408376963352], [‘AT&T Corp’, 0.010732984293193719], [‘Ford Inc’, 0.010209424083769635], [‘Shell Oil Co’, 0.009947643979057593], [‘Target Inc’, 0.00968586387434555], [‘Home Depot Inc. ‘, 0.009162303664921467], [‘Cisco Inc’, 0.008638743455497384], [‘Microsoft Corp’, 0.008638743455497384]]