Sreram K sreramk

## keycloak_db_overview_4.0.0.CR1-SNAPSHOT.svg

      
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                sreramk
                / keycloak_db_overview_4.0.0.CR1-SNAPSHOT.svg
            
            
              Created
              October 15, 2020 12:58
                — forked from thomasdarimont/keycloak_db_overview_4.0.0.CR1-SNAPSHOT.svg
            
              
                Keycloak Database Overview 4.0.0.CR1-SNAPSHOT (06bb6f00e5)
              
          
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## BestTimetoBuyandSellStockIII.cc
/// This is a new kind of solution to that problem.

struct Range {
    int buy;
    int sell;
    int maxPrice;
    Range() : buy (0), sell (0), maxPrice(0) {}
};


## minimum_trips_problem.cc
#include <bits/stdc++.h>

struct Result {
  int minTrips;
  std::map<std::vector<bool>, std::vector <int>>* sequence;
  std::vector <int> optimalVec;
  Result() : minTrips(0),
    sequence(new std::map<std::vector<bool>, std::vector <int>>) {}

  ~Result () {

## spiral.cc
#include <iostream>
#include <vector>

void set_matrix (std::vector<std::vector<int>>& mat, int lenght ) {
  mat.resize(lenght);
  for (int i = 0; i < lenght; i++) {
    mat[i].resize(lenght);
  }
}

## arraypairs.cc
 /* Solution by K Sreram.
  * Original question: https://www.hackerrank.com/challenges/array-pairs/submissions/code/71255248
  * tested with C++14 (g++)
  */

#include <cmath>
#include <cstdio>
#include <vector>
#include <iostream>
#include <algorithm>

## containsTheTrainingAlgorithm.java
package neuralNetwork;
/*
 * Copyright (c) 2016 K Sreram, All rights reserved.
 */

import java.util.ArrayList;

import neuralNetwork.neuralInterface.TrainingDataSet;

/**

## MainMethodForNeuralNetwork.java
/*
 * copyright (c) 2016 K Sreram, All rights reserved
 */
package mainFnc;

import neuralNetwork.activationFunctions.*;
import neuralNetwork.graphicalAnalysis.ErrorGraph;
import neuralNetwork.ioHandler.WeightIOHandler;
import neuralNetwork.neuralInterface.NeuralNetworkInterface;

## bellman.cpp
/**
    program author: K Sreram
    Author E-mail: sreramk@outlook.com
    License: GNU public license
*/
#include <limits>
#include <stdlib.h>
#include "bellman.h"
#include <iostream>
BellmanAlgorithm::BellmanAlgorithm()

## bellman.h
/**
    program author: K Sreram
    Author E-mail: sreramk@outlook.com
    License: GNU public license
*/
#ifndef BELLMAN_H
#define BELLMAN_H

#include <queue>
#include <list>

## main.cpp
/**
    program author: K Sreram
    Author E-mail: sreramk@outlook.com
    License: GNU public license
*/
#include "bellman.h"
#include <iostream>
#include <stdlib.h>
int main()
{
	/// This is a new kind of solution to that problem.

	struct Range {
	int buy;
	int sell;
	int maxPrice;
	Range() : buy (0), sell (0), maxPrice(0) {}
	};
	#include <bits/stdc++.h>

	struct Result {
	int minTrips;
	std::map<std::vector<bool>, std::vector <int>>* sequence;
	std::vector <int> optimalVec;
	Result() : minTrips(0),
	sequence(new std::map<std::vector<bool>, std::vector <int>>) {}

	~Result () {
	#include <iostream>
	#include <vector>

	void set_matrix (std::vector<std::vector<int>>& mat, int lenght ) {
	mat.resize(lenght);
	for (int i = 0; i < lenght; i++) {
	mat[i].resize(lenght);
	}
	}
	/* Solution by K Sreram.
	* Original question: https://www.hackerrank.com/challenges/array-pairs/submissions/code/71255248
	* tested with C++14 (g++)
	*/

	#include <cmath>
	#include <cstdio>
	#include <vector>
	#include <iostream>
	#include <algorithm>
	package neuralNetwork;
	/*
	* Copyright (c) 2016 K Sreram, All rights reserved.
	*/

	import java.util.ArrayList;

	import neuralNetwork.neuralInterface.TrainingDataSet;

	/**
	/*
	* copyright (c) 2016 K Sreram, All rights reserved
	*/
	package mainFnc;

	import neuralNetwork.activationFunctions.*;
	import neuralNetwork.graphicalAnalysis.ErrorGraph;
	import neuralNetwork.ioHandler.WeightIOHandler;
	import neuralNetwork.neuralInterface.NeuralNetworkInterface;
	/**
	program author: K Sreram
	Author E-mail: sreramk@outlook.com
	License: GNU public license
	*/
	#include <limits>
	#include <stdlib.h>
	#include "bellman.h"
	#include <iostream>
	BellmanAlgorithm::BellmanAlgorithm()