scispace - formally typeset
Search or ask a question
Topic

Tuple

About: Tuple is a research topic. Over the lifetime, 6513 publications have been published within this topic receiving 146057 citations. The topic is also known as: tuple & ordered tuplet.


Papers
More filters
Proceedings ArticleDOI
14 Feb 1994
TL;DR: A new temporal-join algorithm based on tuple partitioning is introduced that avoids the quadratic cost of nested-loop evaluation methods; it also avoids sorting.
Abstract: Joins are arguably the most important relational operators. Poor implementations are tantamount to computing the Cartesian product of the input relations. In a temporal database, the problem is more acute for two reasons. First, conventional techniques are designed for the optimization of joins with equality predicates, rather than the inequality predicates prevalent in valid-time queries. Second, the presence of temporally-varying data dramatically increases the size of the database. These factors require new techniques to efficiently evaluate valid-time joins. The authors address this need for efficient join evaluation in databases supporting valid-time. A new temporal-join algorithm based on tuple partitioning is introduced. This algorithm avoids the quadratic cost of nested-loop evaluation methods; it also avoids sorting. Performance comparisons between the partition-based algorithm and other evaluation methods are provided. While the paper focuses on the important valid-time natural join, the techniques presented are also applicable to other valid-time joins. >

76 citations

Book ChapterDOI
02 Aug 2002
TL;DR: This paper formalizes the problem of inductive learning using ontologies and data; describes an ontology-driven decision tree learning algorithm to learn classification rules at multiple levels of abstraction; and presents preliminary results to demonstrate the feasibility of the proposed approach.
Abstract: Most learning algorithms for data-driven induction of pattern classifiers (e.g., the decision tree algorithm), typically represent input patterns at a single level of abstraction - usually in the form of an ordered tuple of attribute values. However, in many applications of inductive learning - e.g., scientific discovery, users often need to explore a data set at multiple levels of abstraction, and from different points of view. Each point of view corresponds to a set of ontological (and representational) commitments regarding the domain of interest. The choice of an ontology induces a set of representatios of the data and a set of transformations of the hypothesis space. This paper formalizes the problem of inductive learning using ontologies and data; describes an ontology-driven decision tree learning algorithm to learn classification rules at multiple levels of abstraction; and presents preliminary results to demonstrate the feasibility of the proposed approach.

75 citations

Proceedings Article
01 Sep 2005
TL;DR: FTM is the basis of several sets of modules for Max/MSP specialized on score following, sound analysis/re-synthesis, statistical modeling and data bank access, designed for particular applications in automatic accompaniment, advanced sound processing and gestural analysis.
Abstract: This article presents FTM, a shared library and a set of modules extending the Max/MSP environment. It also gives a brief description of additional sets of modules based upon FTM. The article particularly addresses the community of researchers and musicians familiar with Max or Max-like programming environments such as Pure Data. FTM extends the signal and message data flow paradigm of Max permitting the representation and processing of complex data structures such as matrices, sequences or dictionaries as well as tuples, MIDI events or score elements (notes, silences, trills etc.). The consequent integration of references to complex data structures in the Max/MSP data flow opens new possibilities to the user in terms of powerful and efficient data representations and modularization of applications. FTM is the basis of several sets of modules for Max/MSP specialized on score following, sound analysis/re-synthesis, statistical modeling and data bank access. Designed for particular applications in automatic accompaniment, advanced sound processing and gestural analysis, the libraries use a common set of basic FTM data structures. They are perfectly interoperable while smoothly integrating into the modular programming paradigm of the host environment Max/MSP.

75 citations

Book ChapterDOI
19 May 2019
TL;DR: This work describes the first volume-hiding STE schemes that do not rely on naive padding; that is, padding all tuples to the same length and achieves these results by leveraging computational assumptions; not just for encryption but, more interestingly, to hide the volumes themselves.
Abstract: We initiate the study of structured encryption schemes with computationally-secure leakage. Specifically, we focus on the design of volume-hiding encrypted multi-maps; that is, of encrypted multi-maps that hide the response length to computationally-bounded adversaries. We describe the first volume-hiding STE schemes that do not rely on naive padding; that is, padding all tuples to the same length. Our first construction has efficient query complexity and storage but can be lossy. We show, however, that the information loss can be bounded with overwhelming probability for a large class of multi-maps (i.e., with lengths distributed according to a Zipf distribution). Our second construction is not lossy and can achieve storage overhead that is asymptotically better than naive padding for Zipf-distributed multi-maps. We also show how to further improve the storage when the multi-map is highly concentrated in the sense that it has a large number of tuples with a large intersection. We achieve these results by leveraging computational assumptions; not just for encryption but, more interestingly, to hide the volumes themselves. Our first construction achieves this using a pseudo-random function whereas our second construction achieves this by relying on the conjectured hardness of the planted densest subgraph problem which is a planted variant of the well-studied densest subgraph problem. This assumption was previously used to design public-key encryptions schemes (Applebaum et al., STOC ’10) and to study the computational complexity of financial products (Arora et al., ICS ’10).

75 citations

Proceedings ArticleDOI
18 Feb 2007
TL;DR: The Shunt is developed, a in-line, FPGA-based IPS ac-celerator coupled to a host PC to handle both cache management and higher level IPS analysis, based on a novel series of caches.
Abstract: The sophistication and complexity of analysis performed by today's network intrusion prevention systems (IPSs) benefits greatly from implementation using general-purpose CPUs. Yet the performance of such CPUs increasingly lags behind that necessary to process today's high-rate traffic streams. A key observation, however, is that much of the traffic comprising a high-volume stream can, after some initial analysis, be qualified as "likely uninteresting." To this end, we have developed an in-line, FPGA-based IPS ac-celerator, the Shunt, using the NetFPGA2 platform. The Shunt functions as the forwarding device used by the IPS; it alone processes the bulk of the traffic, offloading the memory bus and leaving the CPU free to inspect the subset of the traffic deemed germane for security analysis. To do so, the Shunt maintains several large state tables indexed by packet header fields, including IP/TCP flags, source and destination IP addresses, and connection tuples. The tables yield decision values the element makes on a packet-by-packet basis: forward the packet, drop it, or divert it through the IPS. By manipulating table entries, the IPS can specify the traffic it wishes to examine, directly block malicious traffic, and "cut through" traffic streams once it has had an opportunity to "vet" them, all on a fine-grained basis. We base our design on a novel series of caches, with a "fail safe" miss policy, coupled to a host PC to handle both cache management and higher level IPS analysis. The design requires only 2 MB of SRAM for its extensive caches, and can sup-port four Gbps Ethernets on a single Virtex 2 Pro 30.

75 citations


Network Information
Related Topics (5)
Graph (abstract data type)
69.9K papers, 1.2M citations
86% related
Time complexity
36K papers, 879.5K citations
85% related
Server
79.5K papers, 1.4M citations
83% related
Scalability
50.9K papers, 931.6K citations
83% related
Polynomial
52.6K papers, 853.1K citations
81% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023203
2022459
2021210
2020285
2019306
2018266