46574197
On Natural Joins in Object-Oriented Databases
In this paper, we introduce a recursively-defined natural join operation for composing complex objects. The notable features of our natural join are (1) Operand types are generalized into atomic-type, set-type, and tuple-type objects, and (2) The elements of set-type objects are allowed to be heterogenous. Then, we discuss how to realize the natural join by the message passing computing mechanism. Finally, we investigate some mathematical properties about the natural join. Especially, we provide a condition under which the sub-object relationship defined by Bancilhon and Khoshafian is preserved under our natural join and investigate the relationship between their intersection and our natural join.
1810071
Testing of Join Dependency Preserving by a Modified Chase Method
5408151
Alternative Objects in Object-oriented Databases
22236580
OVID: Design and Implementation of a Video-Object Database System
A video-object data model and the design and implementation of a prototype video-object database system named OVID based on the model are described. Notable features of the video-object data model are a mechanism to share common descriptional data among video-objects, called interval-inclusion based inheritance, and operations to composite video-objects. The OVID system offers a browsing/inspection tool called VideoChart, and adhoc query facility called VideoSQL, and a video-object definition tool. >
205099974
Organization of quasi-consecutive retrieval files
Abstract In 1972, Ghosh introduced the consecutive retrieval (CR) file organization. It is an efficient file organization in which all records pertinent to a query are consecutively stored on linear storage locations. In this paper, we introduce the quasi-consecutive retrieval (QCR) file organization. The QCR file organization is an extension of Ghosh's CR file organization and normally offers less redundancy. In the QCR file, all the records pertinent to each query are not necessarily stored consecutively, but rather they are stored within an area of the buffer size. In this paper, we discuss graph theoretic properties of CR files and QCR files by using the properties of interval graphs well known in graph theory. We provide a basic condition for the existence of a QCR file without redundancy for a given buffer size. By introducing redundant queries, such a condition is simplified. Furthermore, a heuristic computer algorithm is given to organize a QCR file with less redundancy for a given buffer size.
46335278
Tree-Structured Data Organization with Consecutive Retrieval Property
COMP2011 Aleksandar Ignjatovic 2005 c 2 Figure 1: A medieval copy of arguably the most influential textbook ever written, Eu-clid's Elements (Στoι χε´ια), from about 300 BC. It contains the oldest known algorithm recorded, Euclid's algorithm for computing the Greatest Common Divisor (GCD) of two natural numbers. Figure 2: First data structures: a Mesopotamian cuneiform tablet from about 3000 BC with an inventory list. Preface This booklet is not meant to be a textbook, but only a companion to the textbook that we use in this course, Cormen, Leiserson, Rivest and Stein's Introduction to Algorithms, the second edition. Its purpose is to help you read the appropriate sections of the textbook, and integrate it better with the rest of the course. It also adds a number of exercises not present in the textbook. Please read the textbook and do not rely on this supplement only.
120935286
Automatic hyperparameter estimation in probabilistic image restoration algorithm based on Gibbs microcanonical distribution
For an original image given as an 8-gray-level image, the framework for image restoration is composed of Bayes statistics for the a priori probability distribution based on the microcanonical distribution. In this process, the a priori probability distribution serving as the microcanonical distribution is formulated on the basis of the variables characterizing the spatial flatness and smoothness of the image in terms of the number of nearest pixel pairs with different gray levels and the number of nearest pixel pairs with gray levels differing by 1. In the present paper, we propose a new method of estimation, from a degraded image, of the number of nearest pixel pairs with different gray levels and the number of nearest pixel pairs with gray levels differing by 1 in the original image. Then, based on that formulation, an iterative computation algorithm for the restoration of a 256-gray-level image is presented from the viewpoint of statistical mechanics. Through some numerical experiments, we investigate how the proposed method can improve the quality of the restored image. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 36(1): 68–78, 2005; Published online in Wiley InterScience (). DOI 10.1002sscj.10365
35660731
Some Properties of Fuzzy Sets of Type 2
The concept of fuzzy sets of type 2 has been defined by L. A. Zadeh as an extension of ordinary fuzzy sets. The fuzzy set of type 2 can be characterized by a fuzzy membership function the grade (or fuzzy grade) of which is a fuzzy set in the unit interval [0, 1] rather than a point in [0, 1]. This paper investigates the algebraic structures of fuzzy grades under the operations of join ⊔, meet ⊔, and negation ┐ which are defined by using the extension principle, and shows that convex fuzzy grades form a commutative semiring and normal convex fuzzy grades form a distributive lattice under ⊔ and ⊓. Moreover, the algebraic properties of fuzzy grades under the operations and which are slightly different from ⊔ and ⊓, respectively, are briefly discussed.
7133208
Statistical Learning Procedure in Loopy Belief Propagation for Probabilistic Image Processing
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model and maximum likelihood estimation. Although hyperparameters in the probabilistic model are determined so as to maximize a marginal likelihood, a practical algorithm is described for the EM algorithm with the loopy belief propagation which is one of approximate inference algorithms in artificial intelligence
43363560
Adaptive Dynamic Voltage Scaling for Real-Time Systems
16332479
Preferential Urn Model on a Random Network
A preferential urn model on a random network and a complete graph is studied. The preferential urn model is based on the concept "the rich get richer", and has simple dynamics of ball-transfers. The model is considered as a simple socio-economic system. From analytical treatments, it has been revealed that the preferential urn model on the complete graph gives a fat-tailed occupation distribution in the case with randomness for fitness parameters. In the present paper, using numerical experiments, we show that the model on the random network gives a fat-tailed occupation distribution in the case without randomness for fitness parameters; hence, we would consider that the local ball-transfer process on the random network includes effects corresponding to the randomness for fitness parameters. This simple game would give a valuable insight into various phenomena from socio-economic point of view