} //end method set_relevant_manipulated_sensor_values()
private static double[] calculate_texttiling_scores(double[] element_list, int texttiling_block_size)
{
//So here, for each element, we compare it's block, to the block for the next element and record that similarity value
double[] element_dissimilarity_score = new double[element_list.Length];
double left_block, right_block;
//now go through each element, and compare it's block_size to the next
for (int element = 0; element < element_dissimilarity_score.Length; element++)
{
if (element >= texttiling_block_size && element < element_list.Length - texttiling_block_size) //have -block_size because we'll be looking at the number of blocks ahead, so can't calculate for the last few images ... or the first few either ... which is no big deal as an event is unlikely to occur so near the end and only be a couple of images long
{
//firstly get a value to represent the block of elements for the block corresponding to this element and the next element
left_block = get_left_block(element_list, element, texttiling_block_size);
right_block = get_right_block(element_list, element + 1, texttiling_block_size);
//then calculate their similarity score and store it to the similarity score array
element_dissimilarity_score[element] = Standard_Calculation.get_diff_between_nums(left_block, right_block);
}
else
{
element_dissimilarity_score[element] = 0.0;
}
} //end for (int element = 0; element < element_dissimilarity_score.Length; element++)
return(element_dissimilarity_score);
} //end method calculate_texttiling_scores
} //end method get_chunk_ids_for_user()
private static double get_combMIN_of_values(double acc_comb_score, double acc_x_score, double pir_source)
{
//return the median value of all the scores -> TREC 2 - Combination of Multiple Searches , page 243 E. Fox, J. Shaw (Virginia Tech)
double[] list_of_vals = { acc_comb_score, acc_x_score, pir_source };
double[] list_of_val_weights = { ACC_COMBINED_WEIGHT, ACC_X_WEIGHT, PIR_WEIGHT };
return(Standard_Calculation.get_combMIN_of_values(list_of_vals, list_of_val_weights));
} //end method get_combMED_of_values
} //end method sortArray
public static double calculate_weighted_median_value(double[] list_of_values, double[] value_weights)
{
double[] tmp_array = new double[list_of_values.Length];
for (int tmp_count = 0; tmp_count < tmp_array.Length; tmp_count++)
tmp_array[tmp_count] = list_of_values[tmp_count] * value_weights[tmp_count];
return Standard_Calculation.calculate_median_value(tmp_array);
} //end method calculate_median_value
//THIS CLASS IS RESPONSIBLE FOR MANIPULATING AN ARRAY OF SENSOR VALUE
//IT SHALL OPERATE AS FOLLOWS (BASED ON MY SEGMENTATION EXPERIMENTS)
//1. SHOT BOUNDARY DETECTION APPROACH (I.E. JUST COMPARE ADJACENT READINGS)
public static void manipulate_relevant_sensor_values(Sensor_Reading[] sensor_vals, int start_index, int end_index, Upload_and_Segment_Images_Thread.DeviceType device_type)
{
//NOTE THE START AND END INDEX ... THESE SIGNIFY THE START AND END OF A PARTICULAR CHUNK IN THE ARRAY
//1. get the list of sensor values
//NOTE THE START AND END INDEX ... THESE SIGNIFY THE START AND END OF A PARTICULAR CHUNK IN THE ARRAY
//FIRSTLY STORE THE RAW VALUES TO LOCAL DOUBLE ARRAYS
double[] original_acc_combined_values = new double[(end_index - start_index) + 1];
double[] original_acc_x_values = new double[original_acc_combined_values.Length];
double[] original_pir_values = new double[original_acc_combined_values.Length];
for (int counter = 0; counter < original_acc_combined_values.Length; counter++)
{
original_acc_combined_values[counter] = sensor_vals[start_index + counter].get_raw_acc_combined(device_type);
original_acc_x_values[counter] = Standard_Calculation.get_signed_int(sensor_vals[start_index + counter].get_acc_x(), device_type);
original_pir_values[counter] = sensor_vals[start_index + counter].get_pir();
} //end for (int counter = 0; counter < original_sensor_values.Length; counter++)
//---------------------------------------------------------------
//2. perform SDB comparisons on acc_comb and texttiling on acc x
double[] acc_comb_manipulated_scores, acc_x_manipulated_scores, pir_manipulated_scores;
//perform SDB comparisons on acc_comb
acc_comb_manipulated_scores = calculate_sbd_scores(original_acc_combined_values);
//and TextTiling of block size 2 on the acc_x component
acc_x_manipulated_scores = calculate_texttiling_scores(original_acc_x_values, 2);
//and finally the PIR with a block size of 78
pir_manipulated_scores = calculate_texttiling_scores(original_pir_values, 78);
//---------------------------------------------------------------
//3. smooth the values over a window size of just 1 (i.e. 3 readings just taken, ref, and 1 before + 1 after)
Standard_Calculation.smooth_array_using_median_values(acc_comb_manipulated_scores, 1);
Standard_Calculation.smooth_array_using_median_values(acc_x_manipulated_scores, 1);
Standard_Calculation.smooth_array_using_median_values(original_pir_values, 1);
//---------------------------------------------------------------
//4. update Sensor_Reading[] array with newly calculated manipulated values
set_relevant_manipulated_sensor_values(sensor_vals, acc_comb_manipulated_scores, acc_x_manipulated_scores, pir_manipulated_scores, start_index);
} //end method manipulate_relevant_sensor_values
} //end methoed get_right_block()
private static double get_block_value_for_element(double[] list_of_all_values, int element_position, int block_size)
{
//so this method will return a representative value for the various relevant values (i.e. from element_position -> [element_position + BLOCK_SIZE]) ... i.e. all the values to the right of this
double[] list_of_values_in_question = new double[block_size];
//firstly get the list of values in question
for (int element_num = element_position; element_num < element_position + block_size; element_num++)
{
list_of_values_in_question[element_num - element_position] = list_of_all_values[element_num];
} //end for (int element_num = element_position; image_num < element_position + IMAGE_BLOCK_SIZE; element_num++)
return(Standard_Calculation.get_sum_value(list_of_values_in_question));
} //end method get_block_value_for_image()
} //end method manipulate_relevant_sensor_values
private static double[] calculate_sbd_scores(double[] element_list)
{
//So here, for each element, we compare it's value to the previous value, and that's the difference score
double[] element_dissimilarity_score = new double[element_list.Length];
element_dissimilarity_score[0] = 0.0; //the first element will always be 0 since you can't compare to a previous value!!!
//now go through each element, and compare it's value to the previous value, and that's the difference score
for (int element = 1; element < element_dissimilarity_score.Length; element++)
{
element_dissimilarity_score[element] = Standard_Calculation.get_diff_between_nums(element_list[element], element_list[element - 1]);
} //end for (int element = 0; element < element_dissimilarity_score.Length; element++)
return(element_dissimilarity_score);
} //end method calculate_texttiling_scores()
public double get_raw_acc_combined(Upload_and_Segment_Images_Thread.DeviceType device_type)
{
return(Math.Sqrt(Standard_Calculation.square_value(Standard_Calculation.get_signed_int(acc_x, device_type))
+ Standard_Calculation.square_value(Standard_Calculation.get_signed_int(acc_y, device_type))
+ Standard_Calculation.square_value(Standard_Calculation.get_signed_int(acc_z, device_type))));
} //end method get_raw_acc_combined()
