5288493
Indexing of variable length multi-attribute motion data
Haptic data such as 3D motion capture data and sign language animation data are new forms of multimedia data. The motion data is multi-attribute, and indexing of multi-attribute data is important for quickly pruning the majority of irrelevant motions in order to have real-time animation applications. Indexing of multi-attribute data has been attempted for data of a few attributes by using R-tree or its variants after dimensionality reduction. In this paper, we exploit the singular value decomposition (SVD) properties of multi-attribute motion data matrices to obtain one representative vector for each of the motion data matrices of dozens or hundreds of attributes. Based on this representative vector, we propose a simple and efficient interval-tree based index structure for indexing motion data with large amount of attributes. At each tree level, only one component of the query vector needs to be checked during searching, comparing to all the components of the query vector that should get involved if an R-tree or its variants are used for indexing. Searching time is independent of the number of pattern motions indexed by the tree, making the index structure well scalable to large data repositories. Experiments show that up to 91∼93% irrelevant motions can be pruned for a query with no false dismissals, and the query searching time is less than 30 μ <i>s</i> with the existence of motion variations.
15797731
A Novel Indexing Approach for Efficient and Fast Similarity Search of Captured Motions
Indexing of motion data is important for quickly searching similar motions for sign language recognition and gait analysis and rehabilitation. This paper proposes a simple and efficient tree structure for indexing motion data with dozens of attributes. Feature vectors are extracted for indexing by using singular value decomposition (SVD) properties of motion data matrices. By having similar motions with large variations indexed together, searching for similar motions of a query needs only one node traversal at each tree level, and only one feature needs to be considered at one tree level. Experiments show that the majority of irrelevant motions can be pruned while retrieving all similar motions, and one traversal of the indexing tree takes only several microseconds with the existence of motion variations.
8468902
Segmentation and recognition of multi-attribute motion sequences
In this work, we focus on fast and efficient recognition of motions in multi-attribute continuous motion sequences. 3D motion capture data, animation motion data, and sensor data from gesture sensing devices are examples of multi-attribute continuous motion sequences. These sequences have multiple attributes rather than only one attribute as time series data has. Motions can have different rates and durations, and the resulting data can thus have different lengths. Also, motion data can have noises due to transitions between successive motions. Hence, traditional distance measuring approaches used for time series data (such as Euclidean distances or dynamic time-warped distances) are not suitable for recognition in multi-attribute motion sequences. Hence, we have defined a similarity measure based on the analysis of singular value decomposition (SVD) properties of similar multi-attribute motions. A five-phase algorithm has then been proposed that gives good pruning power by exploiting the proximity of continuous motion data. We experimented this algorithm with data from different sources: 3D motion capture devices, animation motions, and CyberGlove gesture sensing device. These experiments show that our algorithm can segment and recognize long motion streams with high accuracy and in real time without knowing beforehand the number of motions in a stream.
22734385
On cubic Cayley graphs of finite simple groups
For a finite group G, a Cayley graph Cay(G,S) is said to be normal if the group GR of right translations on G is a normal subgroup of the full automorphism group of Cay(G,S). In this paper, we prove that, for most finite simple groups G, connected cubic Cayley graphs of G are all normal. Then we apply this result to study a problem related to isomorphisms of Cayley graphs, and a problem regarding graphical regular representations of finite simple groups. The proof of the main result depends on the classification of finite simple groups.
6241358
Executing SQL over encrypted data in the database-service-provider model
Rapid advances in networking and Internet technologies have fueled the emergence of the "software as a service" model for enterprise computing. Successful examples of commercially viable software services include rent-a-spreadsheet, electronic mail services, general storage services, disaster protection services. "Database as a Service" model provides users power to create, store, modify, and retrieve data from anywhere in the world, as long as they have access to the Internet. It introduces several challenges, an important issue being data privacy. It is in this context that we specifically address the issue of data privacy.There are two main privacy issues. First, the owner of the data needs to be assured that the data stored on the service-provider site is protected against data thefts from outsiders. Second, data needs to be protected even from the service providers, if the providers themselves cannot be trusted. In this paper, we focus on the second challenge. Specifically, we explore techniques to execute SQL queries over encrypted data. Our strategy is to process as much of the query as possible at the service providers' site, without having to decrypt the data. Decryption and the remainder of the query processing are performed at the client site. The paper explores an algebraic framework to split the query to minimize the computation at the client site. Results of experiments validating our approach are also presented.
2062689
Optimizing Large Join Queries in Mediation Systems
In data integration systems, queries posed to a mediator need to be translated into a sequence of queries to the underlying data sources. In a heterogeneous environment, with sources of diverse and limited query capabilities, not all the translations are feasible. In this paper, we study the problem of finding feasible and efficient query plans for mediator systems. We consider conjunctive queries on mediators and model the source capabilities through attribute-binding adornments. We use a simple cost model that focuses on the major costs in mediation systems, those involved with sending queries to sources and getting answers back. Under this metric, we develop two algorithms for source query sequencing - one based on a simple greedy strategy and another based on a partitioning scheme. The first algorithm produces optimal plans in some scenarios, and we show a linear bound on its worst case performance when it misses optimal plans. The second algorithm generates optimal plans in more scenarios, while having no bound on the margin by which it misses the optimal plans. We also report on the results of the experiments that study the performance of the two algorithms.
7468422
On Containment of Conjunctive Queries with Arithmetic Comparisons
We study the following problem: how to test if Q 2 is contained in Q 1 , where Q 1 and Q 2 are conjunctive queries with arithmetic comparisons? This problem is fundamental in a large variety of database applications. Existing algorithms first normalize the queries, then test a logical implication using multiple containment mappings from Q 1 to Q 2 . We are interested in cases where the containment can be tested more efficiently. This work aims to (a) reduce the problem complexity from Π P 2-completeness to NP-completeness in these cases; (b) utilize the advantages of the homomorphism property (i.e., the containment test is based on a single containment mapping) in applications such as those of answering queries using views; and (c) observing that many real queries have the homomorphism property. The following are our results. (1) We show several cases where the normalization step is not needed, thus reducing the size of the queries and the number of containment mappings. (2) We develop an algorithm for checking various syntactic conditions on queries, under which the homomorphism property holds. (3) We further reduce the conditions of these classes using practical domain knowledge that is easily obtainable. (4) We conducted experiments on real queries, and show that most of the queries pass this test.
17199559
Data Mining for Direct Marketing: Problems and Solutions
Direct marketing is a process of identifying likely buyers of certain products and promoting the products accordingly. It is increasingly used by banks, insurance companies, and the retail industry. Data mining can provide an effective tool for direct marketing. During data mining, several specific problems arise. For example, the class distribution is extremely unbalanced (the response rate is about 1%), the predictive accuracy is no longer suitable for evaluating learning methods, and the number of examples can be too large. In this paper, we discuss methods of coping with these problems based on our experience on direct-marketing projects using data mining.