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Guest Editorial——Special Issue on Advanced Algorithms

Deepak Garg
Creative Computer Society
    Due to increasing complexity and heterogeneity of applications the importance of efficient algorithms is increasing day by day. The size of the input is increasing. More and more machines are now supporting parallel and distributed computations which also forms the need for more sophisticated algorithms. This special issue on Advanced Algorithms tries to handle few issues out of this domain.
In the first paper author has proposed a differential geometry approach to detect changes from remotely sensed images. It can detect the change using the geometric property of the pixels with respect to its surroundings. It can compute and filter the changed pixels having high curvature from that of flat (2D) changed pixels.
Author of the second author has proposed Voting algorithm with Soft Dynamic Threshold for safety critical systems.
    In the third paper author improves upon the decryption/signature generation time for cryptosystem applications.
   Fourth paper is related to recommender systems and the author has proposed an improved algorithm which helps to get more effective and quality recommendations for the active users.
   Fifth paper gives new distributed scheduling algorithm for independent tasks to be assigned optimally amongst available machines. The approach works in two phases. In first phase, it assigns a task according to the Min-min heuristic and in second phase, it improves the scheduling by using efficient refinery scheduling heuristic.
   Sixth paper proposes a solution for the first open problem using the property of forward-security. It gives a forwardsecure proxy re-signature scheme which is based on the hardness of factoring translates one person’s signature to another person’s signature and additionally facilitates the signers as well as the proxy to guarantee the security of messages signed in the past even if their secret key is exposed today.
   Last paper recommends that the RL model has a generic decision-making structure that is well suited to explaining human behavior in dynamic tasks. The RL model is used to model human behavior in a popular dynamic control task called Dynamic Stock and Flows (DSF) that was used in a recent Model Comparison Challenge (MCC). The RL model’s performance is compared to a winner model that won the MCC, that also uses the RL mechanism, and that is the best known model to explain human behaviour in the DSF task.
   As Guest Editor, I will like to thank all the contributors for submitting their work in this special issue.

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