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.

Linda in space-time: an adaptive coordination model for mobile ad-hoc environments

Abstract: We present a vision of distributed system coordination as a set of activities affecting the space-time fabric of interaction events. In the tuple space setting that we consider, coordination amounts to control of the spatial and temporal configuration of tuples spread across the network, which in turn drives the behaviour of situated agents. We therefore draw on prior work in spatial computing and distributed systems coordination, to define a new coordination language that adds to the basic Linda primitives a small set of space-time constructs for linking coordination processes with their environment. We show how this framework supports the global-level emergence of adaptive coordination policies, applying it to two example cases: crowd steering in a pervasive computing scenario and a gradient-based implementation of Linda primitives for mobile ad-hoc networks.

Robust detector of fuzzy duplicates

Abstract: At least one implementation, described herein, detects fuzzy duplicates and eliminates such duplicates. Fuzzy duplicates are multiple, seemingly distinct tuples (i.e., records) in a database that represent the same real-world entity or phenomenon.

Some q‐rung orthopair fuzzy 2‐tuple linguistic Muirhead mean aggregation operators and their applications to multiple‐attribute group decision making

Abstract: Multiple‐attribute group decision making (MAGDM) under linguistic environment is an important part of modern decision sciences, and information aggregation operator plays an import role in solving MAGDM problems. In this paper, an approach for solving MAGDM problem with q‐rung orthopair fuzzy 2‐tuple linguistic information is developed. First, the q‐rung orthopair fuzzy 2‐tuple linguistic weighted averaging (q‐ROFTLWA) operator and the q‐rung orthopair fuzzy 2‐tuple linguistic weighted geometric (q‐ROFTLWG) operator are presented. Furthermore, the q‐rung orthopair fuzzy 2‐tuple linguistic Muirhead mean (q‐ROFTLMM) operator and the q‐rung orthopair fuzzy 2‐tuple linguistic dual Muirhead mean (q‐ROFTLDMM) operator are proposed on the basis of Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator. Then, an approach is developed to deal with MAGDM problem under q‐rung orthopair fuzzy 2‐tuple linguistic environment based on the proposed operators. Finally, a numerical example for selecting desirable emergency alternative(s) in the process of designing emergency preplan is given to illustrate the application of the developed method and demonstrate its effectiveness.

Provenance-Aware Knowledge Representation: A Survey of Data Models and Contextualized Knowledge Graphs

Abstract: Expressing machine-interpretable statements in the form of subject-predicate-object triples is a well-established practice for capturing semantics of structured data. However, the standard used for representing these triples, RDF, inherently lacks the mechanism to attach provenance data, which would be crucial to make automatically generated and/or processed data authoritative. This paper is a critical review of data models, annotation frameworks, knowledge organization systems, serialization syntaxes, and algebras that enable provenance-aware RDF statements. The various approaches are assessed in terms of standard compliance, formal semantics, tuple type, vocabulary term usage, blank nodes, provenance granularity, and scalability. This can be used to advance existing solutions and help implementers to select the most suitable approach (or a combination of approaches) for their applications. Moreover, the analysis of the mechanisms and their limitations highlighted in this paper can serve as the basis for novel approaches in RDF-powered applications with increasing provenance needs.