A Formal Framework for Incremental Model Slicing

2018 ◽  
pp. 3-20
Author(s):  
Gabriele Taentzer ◽  
Timo Kehrer ◽  
Christopher Pietsch ◽  
Udo Kelter
Keyword(s):  
Incremental Model ◽  
Formal Framework

Learning Verb Classes in an Incremental Model

2014 ◽  
Author(s):  
Libby Barak ◽  
Afsaneh Fazly ◽  
Suzanne Stevenson
Keyword(s):  
Verb Classes ◽  
Incremental Model

scholarly journals Three Ways of Being Non-Material

Studia Logica ◽  
2021 ◽  
Author(s):  
Vincenzo Crupi ◽  
Andrea Iacona
Keyword(s):  
Probabilistic Analysis ◽  
Quantitative Measure ◽  
Strict Interpretation ◽  
Formal Framework ◽  
Evidential Support ◽  
Ways Of Being

AbstractThis paper develops a probabilistic analysis of conditionals which hinges on a quantitative measure of evidential support. In order to spell out the interpretation of ‘if’ suggested, we will compare it with two more familiar interpretations, the suppositional interpretation and the strict interpretation, within a formal framework which rests on fairly uncontroversial assumptions. As it will emerge, each of the three interpretations considered exhibits specific logical features that deserve separate consideration.

scholarly journals On the relation between keys and link keys for data interlinking

Semantic Web ◽  
2020 ◽  
pp. 1-21
Author(s):  
Manuel Atencia ◽  
Jérôme David ◽  
Jérôme Euzenat
Keyword(s):  
Description Logics ◽  
The Other ◽  
Formal Framework ◽  
Precise Relationship

Both keys and their generalisation, link keys, may be used to perform data interlinking, i.e. finding identical resources in different RDF datasets. However, the precise relationship between keys and link keys has not been fully determined yet. A common formal framework encompassing both keys and link keys is necessary to ensure the correctness of data interlinking tools based on them, and to determine their scope and possible overlapping. In this paper, we provide a semantics for keys and link keys within description logics. We determine under which conditions they are legitimate to generate links. We provide conditions under which link keys are logically equivalent to keys. In particular, we show that data interlinking with keys and ontology alignments can be reduced to data interlinking with link keys, but not the other way around.

scholarly journals Actively revealing card attack on card-based protocols

2021 ◽  
Author(s):  
Ken Takashima ◽  
Daiki Miyahara ◽  
Takaaki Mizuki ◽  
Hideaki Sone
Keyword(s):  
Secure Computation ◽  
Malicious Attack ◽  
Formal Framework ◽  
Almost All ◽  
And Function

AbstractIn 1989, den Boer presented the first card-based protocol, called the “five-card trick,” that securely computes the AND function using a deck of physical cards via a series of actions such as shuffling and turning over cards. This protocol enables a couple to confirm their mutual love without revealing their individual feelings. During such a secure computation protocol, it is important to keep any information about the inputs secret. Almost all existing card-based protocols are secure under the assumption that all players participating in a protocol are semi-honest or covert, i.e., they do not deviate from the protocol if there is a chance that they will be caught when cheating. In this paper, we consider a more malicious attack in which a player as an active adversary can reveal cards illegally without any hesitation. Against such an actively revealing card attack, we define the t-secureness, meaning that no information about the inputs leaks even if at most t cards are revealed illegally. We then actually design t-secure AND protocols. Thus, our contribution is the construction of the first formal framework to handle actively revealing card attacks as well as their countermeasures.

scholarly journals A formal framework for robot to understand compound concepts

2021 ◽  
Vol 1846 (1) ◽  
pp. 012035
Author(s):  
Yuanxiu Liao ◽  
Mingrui Yan ◽  
Xinqiao Li
Keyword(s):  
Formal Framework ◽  
Compound Concepts

scholarly journals Distance variable improvement of time-series big data stream evaluation

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Ari Wibisono ◽  
Petrus Mursanto ◽  
Jihan Adibah ◽  
Wendy D. W. T. Bayu ◽  
May Iffah Rizki ◽  
...  
Keyword(s):  
Time Series ◽  
Standard Deviation ◽  
Standard Method ◽  
Time Series Data ◽  
Series Data ◽  
Percentage Error ◽  
Traffic Demand ◽  
Incremental Model ◽  
Chernoff Bound ◽  
The Mean

Abstract Real-time information mining of a big dataset consisting of time series data is a very challenging task. For this purpose, we propose using the mean distance and the standard deviation to enhance the accuracy of the existing fast incremental model tree with the drift detection (FIMT-DD) algorithm. The standard FIMT-DD algorithm uses the Hoeffding bound as its splitting criterion. We propose the further use of the mean distance and standard deviation, which are used to split a tree more accurately than the standard method. We verify our proposed method using the large Traffic Demand Dataset, which consists of 4,000,000 instances; Tennet’s big wind power plant dataset, which consists of 435,268 instances; and a road weather dataset, which consists of 30,000,000 instances. The results show that our proposed FIMT-DD algorithm improves the accuracy compared to the standard method and Chernoff bound approach. The measured errors demonstrate that our approach results in a lower Mean Absolute Percentage Error (MAPE) in every stage of learning by approximately 2.49% compared with the Chernoff Bound method and 19.65% compared with the standard method.

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