We have found the first optimal solutions to random instances of the Twenty-Four Puzzle, the 5 x 5 version of the well-known sliding-tile puzzles. Our new contribution to this problem is a more powerful admissible heuristic function. We present a general theory for the automatic discovery of such heuristics, which is based on considering multiple subgoals simultaneously. In addition, we apply a...

Manhattan distance is mainly used to calculate the total absolute wheelbase of two points in standard coordinate system. The secure computation a new geometric problem multi-party computation. At present, existing research computing protocols for cannot resist attack malicious participants. In real scene, existence participants makes it necessary study solution that can attacks. This paper firs...

Mobile communication has grown quickly in the last two decades. Connections can be wirelessly established from almost any habitable place in the earth, leading to a plethora of connection-based tracking mechanisms, such as GPS, GSM, RFID, etc. Trajectories representing the movement of people are consequently being gathered and analysed in a daily basis. However, a trajectory may contain sensiti...

Path selection in multihomed nodes can be enhanced by optimization techniques that consider multiple criteria. With NP-Hard problems, MADM techniques have the flexibility of including any number of benefits or costs criteria and are open regarding the functions that can be employed to normalize data or to determine distances. TOPSIS uses the Euclidean distance (straight line) while DiA employs ...

Received Mar 23, 2017 Revised Sep 8, 2017 Accepted Sep 25, 2017 In Round Robin Scheduling the time quantum is fixed and then processes are scheduled such that no process get CPU time more than one time quantum in one go. The performance of Round robin CPU scheduling algorithm is entirely dependent on the time quantum selected. If time quantum is too large, the response time of the processes is ...

Data mining is the process of extracting previously unknown and valid information from large databases. Clustering is an important data analysis and data mining method. It is the unsupervised classification of objects into clusters such that the objects from same cluster are similar and objects from different clusters are dissimilar. Data clustering is a difficult unsupervised learning problem ...

We present an algorithm for the 2-clustering problem with cluster size constraints in the plane assuming `1-norm, that works in O(n logn) time and O(n) space. Such a procedure also solves a full version of the problem, computing the optimal solutions for all possible constraints on cluster sizes. The algorithm is based on a separation result concerning the clusters of any optimal solution of th...

Vector quantization (VQ) is a well-known method for image compression but its encoding process is very heavy computationally. In order to speed up VQ encoding, it is most important to avoid unnecessary Euclidean distance computations (k-D) as much as possible by a lighter (no multiplication operation) difference check first that uses simpler features (low dimensional) while the searching is goi...

The rapid expansion of the Internet and the wide use of digital data have increased the need for both efficient image database creation and retrieval procedure. The challenge in image retrieval is to develop methods that can capture the important characteristics of an image, which makes it unique, and allow its accurate identification. The focus of this paper is on the image processing aspects ...