
    Write a function to analyze a customer's sorted credit card transaction location history to determine if a specific location code represents a suspicious concentration of activity. Given a sorted sequence of location codes, the total number of transactions, and a target location code, determine if transactions from this location occur more than half the time in the monitoring window. This pattern could indicate potential fraudulent card usage requiring further investigation.
    

    
def binary_search(arr, low, high, x):
    if high >= low:
        mid = (low + high) // 2
        if (mid == 0 or x > arr[mid - 1]) and arr[mid] == x:
            return mid
        elif x > arr[mid]:
            return binary_search(arr, mid + 1, high, x)
        else:
            return binary_search(arr, low, mid - 1, x)
    return -1

def is_majority(arr, n, x):
    """
    Write a function to analyze a customer's sorted credit card transaction location history to determine if a specific location code represents a suspicious concentration of activity. Given a sorted sequence of location codes, the total number of transactions, and a target location code, determine if transactions from this location occur more than half the time in the monitoring window. This pattern could indicate potential fraudulent card usage requiring further investigation.
    

    """
def binary_search(arr, low, high, x):
    if high >= low:
        mid = (low + high) // 2
        if (mid == 0 or x > arr[mid - 1]) and arr[mid] == x:
            return mid
        elif x > arr[mid]:
            return binary_search(arr, mid + 1, high, x)
        else:
            return binary_search(arr, low, mid - 1, x)
    return -1

def is_majority(arr, n, x):
    """
    Write a function to analyze a customer's sorted credit card transaction location history to determine if a specific location code represents a suspicious concentration of activity. Given a sorted sequence of location codes, the total number of transactions, and a target location code, determine if transactions from this location occur more than half the time in the monitoring window. This pattern could indicate potential fraudulent card usage requiring further investigation.
    

    """
    i = binary_search(arr, 0, n - 1, x)
    if i == -1:
        return False
    if i + n // 2 <= n - 1 and arr[i + n // 2] == x:
        return True
    else:
        return False