Wyniki wyszukiwania - Biblioteka Nauki

1

Optimal Wirelength of Balanced Complete Multipartite Graphs onto Cartesian Product of {Path, Cycle} and Trees

100%

Arockiaraj M. , Delaila J. N. , Abraham J.

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tom Vol. 178, nr 3

187--202

EN

In any interconnection network, task allocation plays a major role in the processor speed as fair distribution leads to enhanced performance. Complete multipartite networks serve well for this purpose as the task can be split into different partites which improves the degree of reliability of the network. Such an allocation process in the network can be done by means of graph embedding. The optimal wirelength of a graph embedding helps in the distribution of deterministic algorithms from the guest graph to other host graphs in order to incorporate its unique deterministic properties on that chosen graph. In this paper, we propose an algorithm to compute the optimal wirelength of balanced complete multipartite graphs onto the Cartesian product of trees with path and cycle. Moreover, we derive the closed formulae for wirelengths in specific trees like (1-rooted) complete binary tree and sibling graphs.

2

Decision making support system for managing advertisers by ad fraud detection

100%

Gabryel M. , Scherer M. M. , Sułkowski Ł. , Damaševičius R.

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tom Vol. 11, No. 4

331--339

EN

Efficient lead management allows substantially enhancing online channel marketing programs. In the paper, we classify website traffic into human- and bot-origin ones. We use feedforward neural networks with embedding layers. Moreover, we use one-hot encoding for categorical data. The data of mouse clicks come from seven large retail stores and the data of lead classification from three financial institutions. The data are collected by a JavaScript code embedded into HTML pages. The three proposed models achieved relatively high accuracy in detecting artificially generated traffic.

3

Extending Maps in Hilbert Manifolds

100%

Niemiec P.

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tom Vol. 60, no 3

295--306

EN

Certain results on extending maps taking values in Hilbert manifolds by maps which are close to being embeddings are presented. Sufficient conditions on a map under which it is extendable by an embedding are given. In particular, it is shown that if X is a completely metrizable space of topological weight not greater than α≥ℵ0, A is a closed set in X and f:X→M is a map into a manifold M modelled on a Hilbert space of dimension α such that f(X∖A)∩f(∂A)=∅, then for every open cover U of M there is a map g:X→M which is U-close to f (on X), coincides with f on A and is an embedding of X∖A into M. If, in addition, X∖A is a connected manifold modelled on the same Hilbert space as M, and f(∂A) is a Z-set in M, then the above map g may be chosen so that g|X∖A be an open embedding.

4

Universes and simulations: Civilizational development in nested embedding

88%

Komosinski M.

Foundations of Computing and Decision Sciences

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2018

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tom Vol. 43, No. 3

181--205

EN

The rapid development of technology has allowed computer simulations to become routinely used in an increasing number of fields of science. These simulations become more and more realistic, and their energetic efficiency grows due to progress in computer hardware and software. As humans merge with machines via implants, brain-computer interfaces and increased activity involving information instead of material objects, philosophical concepts and theoretical considerations on the nature of reality are beginning to concern practical, working models and testable virtual environments. This article discusses how simulation is understood and employed in computer science today, how software, hardware and the physical universe unify, how simulated realities are embedded one in another, how complicated it can get in application, practical scenarios, and the possible consequences of these situations. A number of basic properties of universes and simulations in such multiply nested structures are reviewed, and the relationship of these properties with a level of civilizational development is explored.

5

A Paraconsistent Linear-time Temporal Logic

75%

Kamide N. , Wansing H.

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2011

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tom Vol. 106, nr 1

1-23

EN

Inconsistency-tolerant reasoning and paraconsistent logic are of growing importance not only in Knowledge Representation, AI and other areas of Computer Science, but also in Philosophical Logic. In this paper, a new logic, paraconsistent linear-time temporal logic (PLTL), is obtained semantically from the linear-time temporal logic LTL by adding a paraconsistent negation. Some theorems for embedding PLTL into LTL are proved, and PLTL is shown to be decidable. A Gentzentype sequent calculus PLT! for PLTL is introduced, and the completeness and cut-elimination theorems for this calculus are proved. In addition, a display calculus äPLT! for PLTL is defined.

6

Steganography in Audio Files: COTS Software Analysis

51%

Marszałek P. , Bilski P.

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2023

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tom Vol. 69, No. 1

121--126

EN

The paper presents the analysis of the Commercial Off-The-Shelf (COTS) software regarding the ability to be used in audio steganography techniques. Such methods are a relatively new tool for hiding and transmitting crucial information, also being used by hackers. In the following work, the publicly available software dedicated to audio steganography is examined. The aim was to provide the general operating model of the information processing in the steganographic effort. The embedding method was analyzed for each application, providing interesting insights and allowing classifying the methods. The results prove that it is possible to detect the hidden message within the specific audio file and identify the technique that was used to create it. This may be exploited further during the hacking attack detection and prevention.

7

A strong and efficient baseline for vehicle re-identification using deep triplet embedding

51%

Kumar R. , Weill E. , Aghdasi F. , Sriram P.

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2020

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tom Vol. 10, No. 1

27--45

EN

In this paper we tackle the problem of vehicle re-identification in a camera network utilizing triplet embeddings. Re-identification is the problem of matching appearances of objects across different cameras. With the proliferation of surveillance cameras enabling smart and safer cities, there is an ever-increasing need to re-identify vehicles across cameras. Typical challenges arising in smart city scenarios include variations of viewpoints, illumination and self occlusions. Most successful approaches for re-identification involve (deep) learning an embedding space such that the vehicles of same identities are projected closer to one another, compared to the vehicles representing different identities. Popular loss functions for learning an embedding (space) include contrastive or triplet loss. In this paper we provide an extensive evaluation of triplet loss applied to vehicle re-identification and demonstrate that using the recently proposed sampling approaches for mining informative data points outperform most of the existing state-of-the-art approaches for vehicle re-identification. Compared to most existing state-of-the-art approaches, our approach is simpler and more straightforward for training utilizing only identity-level annotations, along with one of the smallest published embedding dimensions for efficient inference. Furthermore in this work we introduce a formal evaluation of a triplet sampling variant (batch sample) into the re-identification literature. In addition to the conference version [24], this submission adds extensive experiments on new released datasets, cross domain evaluations and ablation studies.