
    Design a fraud detection function that analyzes a customer's transaction pattern sequence and determines how many different temporal views of this sequence would flag suspicious behavior. The function should examine the binary sequence (where 1 represents suspicious behavior and 0 represents normal behavior) by shifting it n times, and count how many of these shifted views result in an odd-valued pattern. This analysis helps identify recurring fraudulent patterns across different time windows.
    

    
def odd_Equivalent(s, n):
    """
    Design a fraud detection function that analyzes a customer's transaction pattern sequence and determines how many different temporal views of this sequence would flag suspicious behavior. The function should examine the binary sequence (where 1 represents suspicious behavior and 0 represents normal behavior) by shifting it n times, and count how many of these shifted views result in an odd-valued pattern. This analysis helps identify recurring fraudulent patterns across different time windows.
    

    """
def odd_Equivalent(s, n):
    """
    Design a fraud detection function that analyzes a customer's transaction pattern sequence and determines how many different temporal views of this sequence would flag suspicious behavior. The function should examine the binary sequence (where 1 represents suspicious behavior and 0 represents normal behavior) by shifting it n times, and count how many of these shifted views result in an odd-valued pattern. This analysis helps identify recurring fraudulent patterns across different time windows.
    

    """
    count = 0
    for i in range(0, n):
        if s[i] == '1':
            count = count + 1
    return count