Current Issue : October - December Volume : 2016 Issue Number : 4 Articles : 6 Articles
Generating execution plans is a costly operation for the DataBase Management System\n(DBMS). An interesting alternative to this operation is to reuse the old execution plans, that were\nalready generated by the optimizer for past queries, to execute new queries. In this paper, we present\nan approach for execution plan recommendation in two phases. We firstly propose a textual\nrepresentation of our SQL queries and use it to build a Features Extractor module. Then, we present\na straightforward solution to identify query similarity.This solution relies only on the comparison\nof the SQL statements. Next, we show how to build an improved solution enabled by machine\nlearning techniques. The improved version takes into account the features of the queries� execution\nplans. By comparing three machine learning algorithms, we find that the improved solution using\nClassification Based on Associative Rules (CAR) identifies similarity in 91% of the cases....
Soft computing is a combination of methods that complement each other when dealing with ambiguous\nreal life decision systems. Rough Set Theory (RST) is a technique used in soft computing\nthat enhances the idea of classical sets to deal with incomplete knowledge and provides a mechanism\nfor concept approximation. It uses reducts to isolate key attributes affecting outcomes in decision\nsystems. The paper summarizes two algorithms for reduct calculation. Moreover, to automate\nthe application of RST, different software packages are available. The paper provides a survey of\npackages that are most frequently used to perform data analysis based on Rough Sets. For benefit\nof researchers, a comparison of based on functionalities of those software is also provided....
In this paper, Self-OrganizingMap (SOM) for theMultiple Traveling Salesman Problem (MTSP) with minmax objective is applied\nto the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is\ndetermination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection\nphase of unsupervised learning.Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted\ntowards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue\nand solve the roboticMTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection,\nwhere cities represent sensing locations that guarantee to ââ?¬Å?seeââ?¬Â the whole robotsââ?¬â?¢ workspace. The inspection task formulated\nas the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The\nresults indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic\nmultigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with\nunsupervised learning opens further applications of SOM in the field of robotic planning....
A chaotic map-based mutual authentication scheme with strong anonymity is proposed in this paper, in which the real identity\nof the user is encrypted with a shared key between the user and the trusted server. Only the trusted server can determine the real\nidentity of a user during the authentication, and any other entities including other users of the system get nothing about the user�s\nreal identity. In addition, the shared key of encryption can be easily computed by the user and trusted server using the Chebyshev\nmap without additional burdensome key management. Once the partnered two users are authenticated by the trusted server, they\ncan easily proceed with the agreement of the session key. Formal security analysis demonstrates that the proposed scheme is secure\nunder the random oracle model....
The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total\nnumber of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant ofVRPs that minimizes\nthe total vehicle fuel consumption has gainedmuch attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly\nimportant yet difficult.We present a mixed integer programmingmodel for the FCVRP, and fuel consumption ismeasured through\nthe degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle\nthe FCVRP�s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS). TOHLS\nis based on a hybrid local search algorithm (HLS) that is also used to solve FCVRP. Based on the Golden CVRP benchmarks,\n60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly\noutperforms the HLS....
Image re-ranking is a very effective technique to improve the results of web based image search. Most of the current commercial search engines (Bing, Google) are adopted this technique. In this paper new technique is proposed to improve the results of web based image search. In this technique, at the offline stage, different semantic spaces for a different query keyword are learned automatically. After that semantic signatures are obtained by projecting visual features of the images in to their related semantic spaces and hashing technique is used to compact obtained semantic signatures. At the online stage, compacted semantic signatures of the images are compared to re-rank images. This new technique improves accuracy and precision of web image search....
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