Secure Mobile-Server Communications Using Vector Decomposition Problem

2020 ◽  
pp. 219-227
Author(s):  
P. Arjun Gopinath ◽  
I. Praveen
Keyword(s):  
Decomposition Problem ◽  
Vector Decomposition

The Vector Decomposition Problem

2010 ◽  
Vol E93-A (1) ◽  
pp. 188-193 ◽  
Author(s):  
Maki YOSHIDA ◽  
Shigeo MITSUNARI ◽  
Toru FUJIWARA
Keyword(s):  
Decomposition Problem ◽  
Vector Decomposition

An Authenticated Key Agreement Scheme using Vector Decomposition

2016 ◽  
Vol 66 (6) ◽  
pp. 594 ◽  
Author(s):  
I. Praveen ◽  
K. Rajeev ◽  
M. Sethumadhavan
Keyword(s):  
Key Agreement ◽  
Discrete Logarithm ◽  
Dimensional Subspace ◽  
Dimensional Vector ◽  
Authenticated Key Agreement ◽  
Decomposition Problem ◽  
One Dimensional ◽  
Diffie Hellman ◽  
Vector Decomposition ◽  
Higher Dimensional

Encryption using vector decomposition problem (VDP) on higher dimensional vector spaces is a novel method in cryptography. Yoshida has shown that the VDP on a two-dimensional vector space is at least as hard as the computational Diffie-Hellman problem on a one-dimensional subspace under certain conditions. Steven Galbraith has shown that for certain curves, the VDP is at most as hard as the discrete logarithm problem on a one-dimensional subspace. Okomoto and Takashima proposed encryption scheme and signature schemes using VDP. An authenticated key agreement scheme using vector decomposition problem is proposed in this paper

scholarly journals Hyperelliptic Curves for the Vector Decomposition Problem over Fields of Even Characteristic

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Seungkook Park
Keyword(s):  
Finite Field ◽  
Infinite Family ◽  
Hyperelliptic Curves ◽  
Decomposition Problem ◽  
Vector Decomposition ◽  
Genus Two

We present an infinite family of hyperelliptic curves of genus two over a finite field of even characteristic which are suitable for the vector decomposition problem.

scholarly journals Retrieving Sun-Induced Chlorophyll Fluorescence from Hyperspectral Data with TanSat Satellite

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4886
Author(s):  
Shilei Li ◽  
Maofang Gao ◽  
Zhao-Liang Li
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Spectrum ◽  
Singular Vector ◽  
Low Frequency ◽  
Information Criterion ◽  
Hyperspectral Data ◽  
High Spectral Resolution ◽  
Remotely Sensed Data ◽  
Spectral Window ◽  
Vector Decomposition

A series of algorithms for satellite retrievals of sun-induced chlorophyll fluorescence (SIF) have been developed and applied to different sensors. However, research on SIF retrieval using hyperspectral data is performed in narrow spectral windows, assuming that SIF remains constant. In this paper, based on the singular vector decomposition (SVD) technique, we present an approach for retrieving SIF, which can be applied to remotely sensed data with ultra-high spectral resolution and in a broad spectral window without assuming that the SIF remains constant. The idea is to combine the first singular vector, the pivotal information of the non-fluorescence spectrum, with the low-frequency contribution of the atmosphere, plus a linear combination of the remaining singular vectors to express the non-fluorescence spectrum. Subject to instrument settings, the retrieval was performed within a spectral window of approximately 7 nm that contained only Fraunhofer lines. In our retrieval, hyperspectral data of the O2-A band from the first Chinese carbon dioxide observation satellite (TanSat) was used. The Bayesian Information Criterion (BIC) was introduced to self-adaptively determine the number of free parameters and reduce retrieval noise. SIF retrievals were compared with TanSat SIF and OCO-2 SIF. The results showed good consistency and rationality. A sensitivity analysis was also conducted to verify the performance of this approach. To summarize, the approach would provide more possibilities for retrieving SIF from hyperspectral data.

Efficient Scalable Video Coding Method Using Discrete Bandelet Transform

2020 ◽  
Vol 34 (14) ◽  
pp. 2055023
Author(s):  
Yogananda Patnaik ◽  
Dipti Patra
Keyword(s):  
Video Coding ◽  
Scalable Video Coding ◽  
Research Area ◽  
Set Partitioning ◽  
Scalable Video ◽  
Vector Decomposition ◽  
Coding Method ◽  
Benchmark Datasets ◽  
Spatio Temporal ◽  
Ordered Data

Video coding is an imperative part of the modern day communication system. Furthermore, it has vital roles in the fields of video streaming, multimedia, video conferencing and much more. Scalable Video Coding (SVC) is an emerging research area, due to its extensive application in most of the multimedia devices as well as public demand. The proposed coding technique is capable of eliminating the Spatio-temporal regularity of a video sequence. In Discrete Bandelet Transform (DBT), the directions are modeled by a three-directional vector field, known as structural flow. Regularity is decided by this flow where the data entropy is low. The wavelet vector decomposition of geometrically ordered data results in a lesser extent of significant coefficients. The directions of geometrical regularity are interpreted with a two-dimensional vector, and the approximation of these directions is found with spline functions. This paper deals with a novel SVC technique by exploiting the DBT. The bandelet coefficients are further encoded by utilizing Set Partitioning in Hierarchical Trees (SPIHT) encoder, followed by global thresholding mechanism. The proposed method is verified with several benchmark datasets using the performance measures which gives enhanced performance. Thus, the experimental results bring out the superiority of the proposed technique over the state-of-arts.

RESTRICTED SETS OF TRAJECTORIES AND DECIDABILITY OF SHUFFLE DECOMPOSITIONS

2005 ◽  
Vol 16 (05) ◽  
pp. 897-912 ◽  
Author(s):  
MICHAEL DOMARATZKI ◽  
KAI SALOMAA
Keyword(s):  
Regular Languages ◽  
Decomposition Problem ◽  
Open Question ◽  
Free Set ◽  
Context Free ◽  
Undecidability Result

The decidability of the shuffle decomposition problem for regular languages is a long standing open question. We consider decompositions of regular languages with respect to shuffle along a regular set of trajectories and obtain positive decidability results for restricted classes of trajectories. Also we consider decompositions of unary regular languages. Finally, we establish in the spirit of the Dassow-Hinz undecidability result an undecidability result for regular languages shuffled along a fixed linear context-free set of trajectories.

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