Ammar-Ishfaq

data class Doctor(
    val id: Int,
    val name: String,
    val avgConsultationTime: Int,
    var nextAvailableTime: Int = 0
)

fun calculateWaitingTime(doctors: List<Doctor>, patientPosition: Int): Int {
    val doctorList = doctors.map { it.copy() }
    var currentTime = 0

Ammar-Ishfaq

### Python script to split a labeled image dataset into Train, Validation, and Test folders.
# Author: Evan Juras, EJ Technology Consultants
# Date: 4/10/21

# Randomly splits images to 80% train, 10% validation, and 10% test, and moves them to their respective folders. 
# This script is intended to be used in the TFLite Object Detection Colab notebook here:
# https://colab.research.google.com/github/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi/blob/master/Train_TFLite2_Object_Detction_Model.ipynb

from pathlib import Path
import random

Ammar-Ishfaq

fun main() {
    val sportStats = listOf(
        Summary(Sport.HIKE, 92),
        Summary(Sport.RUN, 77),
        Summary(Sport.TOURING_BICYCLE, 322),
        Summary(Sport.E_TOURING_BICYCLE, 656)
    )

    val nonEBikeStats = sportStats.filter { it.sport != Sport.E_TOURING_BICYCLE }