วันอังคารที่ 24 มีนาคม พ.ศ. 2558

art block & bore

I feel down I don't even know
myself even in down
try to find inspire
my mind gone blank
again again again

hah i wonder why
where and how
to find my new inspire
Time still running
and pass

I hope to enjoy
and maybe there still hope  for me
to find

i have to open my mind
and my world
I hope it
soon.....

วันเสาร์ที่ 7 มีนาคม พ.ศ. 2558

Another day of feeling down

So today I really felt like I was empty

My mind all gone blank

Maybe because many things I have to do and manage

so that is the reason why

I just wondering why am I here

And why am I still here

No purpose and no reason

like a feeling down a moment or it for a long way stack

hah maybe I just need someone I can really trust to share

so this is my day story

วันจันทร์ที่ 9 กุมภาพันธ์ พ.ศ. 2558

GIS by Prof.Tul

Topology 

-adjacency
-connectivity
-containment
-direction
-proximity

why topology is importance ?
 - ensures data and enchance GIS analyse

The Coverage
 three basic topological
-connectivity
-line coverage


so this is for today next for lab work

วันจันทร์ที่ 10 พฤศจิกายน พ.ศ. 2557

Computer Intelligence by Pro.Chu

Artificial Bee colony (ABC)

  • Employed bees phase - search for dimension 
  • Onlooker bees phase - search the area where the place that employee point to,exploitation, search the area
  • Scout bees phase - random search , exploration for more diversity prevents local minimum

วันอังคารที่ 4 พฤศจิกายน พ.ศ. 2557

Computer Intelligence by Pro.Chu

So today I have take my computer intelligence class again haha
now I am studying about an Artificial Neuron Network (ANN)
so an ann is a layered network of artificial neurons the common properties are:

  • directed graph (with or without cycles)
  • nodes are(primitive) computing devices(call neurons)
  • edges carry (weighted) information  - called weights
Inside of a neural network
  • the interconnection pattern of the neurons or the ANN architecture
  • The learning process for updating weights of the interconnection
  • The activation function of each neuron that converts a neuron's inputs into its outputs
Supervise learning
  • Supply the network with inputs and the desired output the weight are modified
Unsupervised
  • Only supply inputs
  • The neural network adjusts its own weights so that similar inputs cause similar outputs
  • The system is supposed to discovery statistically salient features of the input population

วันอังคารที่ 28 ตุลาคม พ.ศ. 2557

Computer Intelligence Ant colony by Pro.Chu

Ant colony optimize (ACO)

Inherent features

  • Inherent parallelism
  • Stochastic nature
  • Adaptivity
  • use of feedback
  • Autocatalytic in nature
Double bridge experiments: different lengths - the majority ant go though the short path

p1 = (m1+k)^h /(m1+k)^h + (m2+k)^h

p2=1-p1

Basic ideal of ACO
  • inspired by the food foraging behavior of ants
  • Ants are agents that: - move along between nodes in a graph
  • They choose where to go based on pheromone strength (and maybe other things)
  • An ant's path represents a specific candidate solution.
  • When an ant has finished a solution, pheromone is laid on its path, according to quality of solution.
  • This pheromone trail affects behavior of other ants, and this is called 'stigmergy' -a communication method amongst ants
How to implement in program
  • Ants: Simple computer agents
  • Move ant: Pick next component in the construction of solution
  • Trace: Pheromone, delta thor ^k where i,j a global  type of infomation
  • Memory: mk or tabu k
Genetic ACO algorithm
  1. Initialize
  2. repeat // called each iteration
  3.  each ant is positioned on the initial node
  4.  repeat // called each step
  5.     Each ant applied a state transition rule
  6.     Apply the pheromone local update rule // optional
  7.  until all ants have build a complete solution
  8.  apply a local search procedure // optional 
  9.  Apply a pheromone global update rule
  10. until any stopping criterion is met
  11. Return the best route
 ACO for the traveling salesman problem

  • TSP is a metaphor problem for the ant colony
  • Is is one of the most studied NP-hard* problems in the combinatorial optimization
  • It is easy to explain. So that the algorithm behavior is not obscured by too many technicalities.
*Np-hard are at least as hard as the hardest problems in NP, which can be solved with Non-deterministic Turing machine in Polynomial time.

Ant Colony Optimization (ACO) for TSP
  • Each edge is associated a static value based on the edge-cost n(i,j) = 1/Li,j , heuristic information indicating a chance or likeliness to move from node i to j

Well see you again, @MySimpleDiary my note story teller

วันเสาร์ที่ 18 ตุลาคม พ.ศ. 2557

HTML5 Beginner Seminar @Silom by khadev

HTML5

Html 5 device : เป็นมาตรฐานเอกสารแสดงเนื้อหาบนเว็บ ซึ่งรองรับทุกอุปกรณ์ เช่น คอม แท็ปเล็ต

Browser : โปรแกรมที่ใช้ในการเปิด เช่น chrome , ie , firefox

เอกสาร html จะอยู่บนเครื่องแม่ข่ายเรียกว่่า server

HTML 5 ประกอบไปด้วย Container , Forms , Graphic , Media , API

จากนั้นไปที่ folder กด shift + right click เลือก open command prompt here แล้วพิม node file.js ก็จะได้ port มา จากนั้น ก็ไป ที่ browser ที่ address   พิม 127.0.0.1:port no. หรือ localhost:port no. ก็จะเข้าไปที่ server

HTML5 with new syn tag like header section footer just like div

so next all input type in html5   data list type
phone : regular expression  for .... your would like to know


flat design (Window) and material design (Google)

new attribute for auto complete  , submit novalidate , auto focus syn tag , from attribute

htmlcanvasstudio.com

svg-edit.googlecode.com

Geolocation ,

drag and drop ondrop="drop(event)" ondragover="allowDrop(event)

local storage and web server storage
and then web worker process


and this all for today see you again