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Although efficient processing of probabilistic databases is a well-established field, a wide range of applications are still unable to benefit from these techniques due to the lack of means for creating probabilistic databases. In fact, it is a challenging problem to associate concrete probability values with given time-series data for forming a probabilistic database, since the probability distributions...
The study of skylines and their variants has received considerable attention in recent years. Skylines are essentially sets of most interesting (undominated) tuples in a database. However, since the skyline is often very large, much research effort has been devoted to identifying a smaller subset of (say k) “representative skyline” points. Several different definitions of representative skylines have...
This paper proposes a novel technique to do probabilistic inference by using simple Fuzzy logic System (FlS), especially ethnic information in DNA profile matching algorithm. By using the allele marker's distribution probability density function as the membership function in the FlS, the new technique makes it possible to tell the ethnic similarity between two DNA profiles in a fast and simple way...
In this paper we present results of the new monitoring network for spectrum governance. The network is based on the RFeye system of CRFS where the data is collected employing mobile monitoring vehicles. The measurement data, obtained from a frequency sweep between 10 MHz and 6 GHz, is further analyzed. For this purpose a tool is made, tailored for the needs of the spectrum regulator. Initial results...
Verification of the person's identity using the database, which contains outcomes of his biometric measurements, is considered. The verification algorithm is proposed and its performance is evaluated with the assumption that the input data represent the vector of values of a random variable generated according to the Gaussian probability distribution and observed under an additive white Gaussian noise...
Automatic personal identification using biometric information is playing a more and more important role in applications such as public security, access control, banking, etc. Palmprint identification is a subcategory of biometrics identification, which can efficiently used to identify the people. It is for this reason that palmprint-based identification is becoming increasingly popularity in recent...
Biometrics is emerging as the most foolproof method of automated personal identification. And fusing the scores of several biométrie systems is a very promising approach to improve the overall system's accuracy. Fusion operators, which contain sum rule, product rule, max rule and min rule, are considered to be one of the most useful schemes at score-level fusion, while the optimal fusion operator...
The aim of signal decomposition in wavelet bases is to represent a signal as a sequence of wavelet coefficients sets. There is proposed a multistage classification rule using on every stage only one set of the signal coefficients. The hierarchical construction of wavelet multiresolution analysis was an inspiration for the multistage classification rule. The algorithm makes an optimal decision for...
The goal of top-k ranking is to rank individuals so that the best k of them can be determined. The definition of top-k ranking is easy for certain data. But for uncertain data, the problem becomes challenging, both semantically and computationally. In this paper, we study semantic issues with top-k ranking for objects modeled by uncertain data in databases. Uncertain data of objects have different...
In this paper, we address the texture retrieval problem using wavelet distribution. We propose a new statistical scheme to represent the marginal distribution of the wavelet coefficients using a mixture of generalized Gaussian distributions (MoGG). The MoGG allows to capture a wide range of histogram shapes, which provides a better description of texture and enhances texture discrimination. We propose...
In this paper we present several information-theoretic similiarity measures for shape retrieval in combination with non-rigid registration processes. The challenging property of these measures is that they are bypass divergences, that is, do not require the estimation of the probability density function for each shape. After presenting the dissimilarities and proposing some new ones, we analyze their...
As a result of the research and design of reconfiguration router unit (RRU), the producing of network equipment is turned into component composition as building block. Based on the component composition and the character of RRU, this paper proposes the concept-CCS (component candidate set). The scheme of creating component candidate set is based on the BP neural network. The CSS is proposed to resolve...
Many theories used for uncertainty problems are strongly complementary to each other because they focus on different aspects. First,this study proposes a new relative reduction algorithm by combing two theories which are frequently used to process incomplete information; and then the obtained rules is optimized. It has been proved by example that the result is reliable.
The pairwise mining problem is to discover pairwise objects having measures greater than the user-specified minimum threshold from a collection of objects. It is essential in a large variety of database and data-mining applications. Of late, there has been increasing interest in applying a Locality-Sensitive Hashing (LSH) scheme for pairwise mining. LSH-type methods have shown themselves to be simply...
A great portion of data on the Web lies in the hidden databases of the Deep Web. These databases can only be accessed through the query interfaces. The data information in these databases can only be obtained by data sampling. Efficient and uniform data sampling approach is very important to other research work, such as data source selection and ranking, for the data samples can give insight into...
For interactive software, function is executed through complicated human-machine interactions. Current test case generation methods of function testing usually consider software interface, while ignoring software requirement and inner performance process. With these testing methods, test cases are generated ignorantly, and testing process may be disordered. In this paper, considering both of function's...
Retrieving similar data has drawn many research efforts in the literature due to its importance in data mining, database and information retrieval. This problem is challenging when the data is incomplete. In previous research, data incompleteness refers to the fact that data values for some dimensions are unknown. However, in many practical applications (e.g., data collection by sensor network under...
The application of intelligent optimization algorithm in data mining has become widespread already. However, it's still a brand new research area in the application of Ant Colony Algorithm(ACA) in data mining. This paper thus proposes a fuzzy data mining algorithm which is based on MAX-MIN Ant System(MMAS). In this algorithm, the membership functions which are extracted from the classification rule...
In this paper, we propose a pre-processing technique to improve existing string similarity join algorithms using fuzzy clustering. Our approach first identifies groups of related attributes and then, using this information, we apply existing string similarity join algorithms on these attributes. To identify the clustered attributes we use fuzzy techniques. This approach can be applied to the integration...
Field soil investigation prior to the foundation design of any structure is a must for the design engineer. Since the cost of such operation is rather high, then it is sometimes impractical. The design and the preliminary cost estimation of the construction are then impossible to be prepared. This paper applies Geographical Information System - GIS all over Bangkok area thus enable engineer to retrieve...
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