The availability of devices that can be used to track moving objects has increased dramatically leading to a great growth in movement data from almost every application domain. Therefore, there has been an increasing interest in proposing new methodologies for indexing, classifYing, clustering, querying and measuring similarity between moving objects' data. One of the main functions for a wide range of application domains is to measure the similarity between two moving objects' trajectories. in this paper, we present a comparative study between widely used trajectory similarity measures observing the advantages and disadvantages of these measures.

Cloud computing offers several computing service. Among these services is the Database Service, which stores outsourced databases and provides all the database services to users. However, despite, the attractiveness of the database services to users, security issues remain a main concern to database owners, as the data and the execution of database is out of their control. To ensure the outsourced database confidentiality and integrity, which are two of the most important security concerns in data outsourcing, we propose the design and implementation of an efficient Secure scheme to provide Confidentiality and Integrity of Query results for Cloud Databases based on Merkle B-Tree (SCIQ-CD). We develop a technique to convert the Merkle B-Tree into data authentication tables and store it within the relational database in DSP. We have implement query rewrite algorithms for trusted third party to generate the SQL statements to speed up the query processing, which will be sent within the query by the user to DSP. The performance analysis shows that our proposed scheme is secure and efficient for practical deployment. The experimental results show that our scheme imposes a low overhead for queries executions with confidentiality and integrity assurance.

Abstruct -Given a database of images and their associated data, we want to search the database for a known image so as to retrieve the data associated with that image. This paper proposes a new imagebased indexing scheme which enables the retrieval of data associated with an image The approach proposed here is based on using a hierarchy of color moments and offers a compromise between methods based on multiple color moments of segmented regions and those based on global color moments. The method retains positional iuformation better than the a h o n schemes and naturally leads to a multi-level comparison strategy where mismatches are quickly discarded at higher levels. Contrary to other schemes where t h m moments were used, the proposed methods provide better storage efficiency and less computational efforts as it o d y employs the fmt two moments. Simulation results show the efficiency and accuracy of the proposed scheme.

In this paper, we present a new indexing scheme for improving the execution speed of high cost queries in large databases, the generated indices require small storage size while has a great impact on performance. The proposed indexing scheme is applied on one of the largest existing electronic components database. We tested and compared the pe$ormance of the library's queries with and without the generated index. Experiments highlighted how positively the proposed index was in terms of speed enhancement and space consumption.

In this paper, two major improvements are applied to the Conditional Signal Adaptive Median (CSAM) filter to accommodate for high density impulsive noise with significant dynamic range. Homogeneity level of a pixel gives a good estimate in separating noisy pixels from pixels belonging to an edge or a fine detail in an image, but the proper choice of a threshold of homogeneity is highly affected by the noise density and range. A more robust method is developed for choosing such a threshold than in the original CSAM filter which extends the application of the filter to impulsive noise not only salt and pepper noise. Results are also compared for both low and high density impulsive noise.