Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Abstract    present efficient algorithms for two problems concerning the discrepancy of a set  S  of  n  points in the unit square in the plane. First,  describe an algorithm for maintaining the half-plane discrepancy of  S  under insertions and deletions of points. The algorithm runs in O( n log n ) worst-case time per update, and it requires only relatively simple data structures. Second,  give an algorithm that computes the strip discrepancy of  S  in O( n  2  α ( n )log n ) time, where  α ( n ) is the extremely slowly growing functional inverse of Ackermann's function.
['Mark de Berg']
I am writing a research paper on a idea Computing half-plane and strip discrepancy of planar point sets
[{"from": "human", "value": "I am writing a research paper on a idea Computing half-plane and strip discrepancy of planar point sets"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Abstract    present efficient algorithms for two problems concerning the discrepancy of a set  S  of  n  points in the unit square in the plane. First,  describe an algorithm for maintaining the half-plane discrepancy of  S  under insertions and deletions of points. The algorithm runs in O( n log n ) worst-case time per update, and it requires only relatively simple data structures. Second,  give an algorithm that computes the strip discrepancy of  S  in O( n  2  \u03b1 ( n )log n ) time, where  \u03b1 ( n ) is the extremely slowly growing functional inverse of Ackermann's function."}]