IELTS writing practices

Read-Read-Read;

IELTS WP0001A (29Jun2017)

The first figure provided reveals the global water consumption by sector between 1900 and 2000. The first figure provided reveals the variations of water consumption worldwide between 1900 and 2000.

The agricultural usage has the most significant volume in Km3, and it grew from 500 Km3 in 1900 and rose gently to 1000 in 1950, then its demand soared to 3000 Km3 until 2000. Throughout the century, the largest quantity of water was used for agricultural purposesand it grew gently from 500 Km3  to 1000 Km3 between 1900 and 1950, then its soared to 3000 Km3 in 2000.

On the other hand, industrial and domestic consumption stayed at low usage level from nearly 0 between 1900 and 1940. Then, the industrial grew to 1000 Km3 and domestic rose to around 2000 Km3 in 2000 respectively. Water used in the industrial and domestic sectors also increased, but consumption was minimal until mid-century.  From 1950 onwards, industrial usage grew steadily to just over 1000 Km3, while domestic use rose more slowly to only 300Km3, both far below the levels of consumption by agriculture.

The second table reveals a comparison of water usage by Brazil and Congo in 2000. Brazil has the highest population at 176 million and 16500 km2 of irrigated land. In contrast, Congo has less number of citizens at 5.2 million and 100 km2 of farmland. As expected, Brazil has a higher figure of water consumption per person at 359m3 and the number in Congo in 8m3. The table illustrates the differences in agricultural consumption in some areas of the world by contrasting the amount of irrigated land in Brazil (26500km2) with that in the DRC (100km2). This means that a huge amount of water is used in agriculture in Brazil, and this is reflected in the figures for water consumption per person: 359m3 compared with only 8m3 in the Congo. With a population of 176 million, the figures for Brazil indicate how high agricultural water consumption can be in some countries.

IELTS WP0002A (11JuL2017)

 

IELTS writing practices

Learning Augmented Reality (AR)

  1. Objectives
  2. Contents
    1. Learn AR for scratch: https://www.quora.com/I-am-a-non-programmer-How-can-I-learn-to-make-Augmented-Reality-apps-from-scratch-Which-programming-languages-to-learn-which-AR-frameworks-to-use-etc
  3. References
    1. AR for Learning. http://ar-learn.com/ar-for-learning/
    2. 6 exciting apps for student learning: https://www.edutopia.org/blog/ar-apps-for-student-learning-monica-burns
Learning Augmented Reality (AR)

Diets and vegetables

  1. Favorable vegetables for working out: https://hkstylemen.yahoo.com/post/162145420521/%E5%81%A5%E8%BA%AB%E4%B8%89%E5%88%86%E7%B7%B4%E4%B8%83%E5%88%86%E5%90%83%E5%81%A5%E8%BA%AB%E6%84%9B%E5%A5%BD%E8%80%85%E5%BC%B7%E5%8A%9B%E6%8E%A8%E8%96%A69%E5%A4%A7%E8%B6%85%E7%B4%9A%E9%A3%9F%E7%89%A9%E8%AE%93%E4%BD%A0%E9%81%8B%E5%8B%95%E5%BE%8C%E4%B9%9F%E8%83%BD%E5%A4%A7%E5%90%83%E5%AE%8C%E5%85%A8%E9%9B%B6%E7%BD%AA%E6%83%A1%E6%84%9F
Diets and vegetables

Book – Computer Science Distilled, Learn the Art of Solving Computational Problems

  1. Objectives:
    1. Stimulate interest in CS
  2. Contents
    1. Basics
      1. Ideas
      2. Logic
        1. Logic gates -> transistors -> CPUs
      3. Counting
        1. Multiplying
        2. Permutations (factorial)
        3. Combination
        4. Sums
      4. Probability
        1. Counting outcomes
        2. Independent events
        3. Mutually Exclusive Events
        4. Complementary Events – cover all possible events – 100%
          1. Advanced probabilities – look for more tools (eg. Googling) when tackling complex problems
    2. Complexity
      1. Method – a list of unambiguous instructions to achieive goal;
      2. Algorithmsa finite series of operations contained in method;
      3. Time complexity T(n) – or running cost
        1. to analyze when designing a system that handle very large inputs;
      4. Counting Time
        1. Understanding growth – dominant term;
        2. Big notation; aviod exponential and factorial time algorithms unless NP-complete problem;
      5. Space Complexity – calculate working space needed;
    3. Strategy
    4. Data
    5. Algorithms
    6. Databases
    7. Computers
    8. Programming
  3. References:
    1. Zebra Puzzles: https://code.energy/solving-zebra-puzzle/
      1. rules / clues to boolean statements
      2. logic (esp XOR operator)
      3. Truth table
      4. assumption and examine
    2. http://bigocheatsheet.com/
Book – Computer Science Distilled, Learn the Art of Solving Computational Problems