Order relation correction experiments for probability kriging

1994 ◽  
Vol 26 (5) ◽  
pp. 605-621 ◽  
Author(s):  
James R. Carr
Keyword(s):  
Order Relation ◽  
Probability Kriging

scholarly journals Homomorphisms and congruences on ωα-bisimple semigroups

1973 ◽  
Vol 15 (4) ◽  
pp. 441-460 ◽  
Author(s):  
J. W. Hogan
Keyword(s):  
Partial Order ◽  
Ordered Set ◽  
Order Relation ◽  
Natural Partial Order ◽  
Partial Order Relation

Let S be a bisimple semigroup, let Es denote the set of idempotents of S, and let ≦ denote the natural partial order relation on Es. Let ≤ * denote the inverse of ≦. The idempotents of S are said to be well-ordered if (Es, ≦ *) is a well-ordered set.

scholarly journals Applications of Fixed Point Theorems to Generalized Saddle Points of Bifunctions on Chain-Complete Posets

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Jinlu Li ◽  
Ying Liu ◽  
Hongya Gao
Keyword(s):  
Fixed Point ◽  
Fixed Point Theorem ◽  
Topological Structure ◽  
Fixed Point Theorems ◽  
Equilibrium Problems ◽  
Saddle Points ◽  
Order Relation ◽  
Partial Order Relation ◽  
Chain Complete ◽  
Set Valued Mappings

We apply the extensions of the Abian-Brown fixed point theorem for set-valued mappings on chain-complete posets to examine the existence of generalized and extended saddle points of bifunctions defined on posets. We also study the generalized and extended equilibrium problems and the solvability of ordered variational inequalities on posets, which are equipped with a partial order relation and have neither an algebraic structure nor a topological structure.

scholarly journals New Hermite–Hadamard-type inequalities for "Equation missing" No EquationSource Format="TEX", only image -convex fuzzy-interval-valued functions

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Muhammad Bilal Khan ◽  
Muhammad Aslam Noor ◽  
Khalida Inayat Noor ◽  
Yu-Ming Chu
Keyword(s):  
Order Relation ◽  
Interval Space ◽  
Fuzzy Order ◽  
Interval Valued ◽  
Fuzzy Interval

AbstractIn this paper, we introduce the non-convex interval-valued functions for fuzzy-interval-valued functions, which are called "Equation missing"-convex fuzzy-interval-valued functions, by means of fuzzy order relation. This fuzzy order relation is defined level-wise through Kulisch–Miranker order relation given on the interval space. By using the "Equation missing"-convexity concept, we present fuzzy-interval Hermite–Hadamard inequalities for fuzzy-interval-valued functions. Several exceptional cases are debated, which can be viewed as useful applications. Interesting examples that verify the applicability of the theory developed in this study are presented. The results of this paper can be considered as extensions of previously established results.

A refined LEED structural determination for the surface designated Ni (111)–(2 × 2)–S

1989 ◽  
Vol 67 (11) ◽  
pp. 1975-1979 ◽  
Author(s):  
Y. K. Wu ◽  
K. A. R. Mitchell
Keyword(s):  
Bond Length ◽  
Surface Structure ◽  
Order Relation ◽  
Normal Incidence ◽  
Intensity Analysis ◽  
Ion Scattering ◽  
Low Energy Electron Diffraction ◽  
Adsorption Sites ◽  
Low Energy Electron ◽  
A Current

A new intensity analysis with low-energy electron diffraction is reported for the (2 × 2) surface structure obtained by the adsorption of H2S on the (111) surface of nickel. Intensity-versus-energy curves were measured with a video LEED analyzer for 10 diffracted beams at normal incidence, and comparisons were made with intensity curves calculated with multiple-scattering methods for models in which S atoms chemisorb at three-fold coordinated adsorption sites, but with the possibilities of both lateral and vertical relaxations in the local metallic structure. Small adsorbate-induced relaxations are found, but the dominant structural feature is that the S atoms adsorb above the "expected" adsorption sites (i.e. those which continue the regular fee packing) with a 1.50 Å spacing between the S layer and the top-most Ni layer. The S–Ni bond length of 2.10 Å agrees to within 0.02 Å of a prediction using a current bond length – bond order relation, but this value is smaller than two other recent measurements by SEXAFS and ion scattering by 0.06 and 0.10 Å, respectively. This analysis also finds the first two Ni layer spacings are expanded from the bulk value by 2 to 3%. Keywords: LEED, surface structure, S chemisorption, Ni(III) surface.

scholarly journals Some Inequalities for LR-$$\left({h}_{1}, {h}_{2}\right)$$-Convex Interval-Valued Functions by Means of Pseudo Order Relation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Muhammad Bilal Khan ◽  
Muhammad Aslam Noor ◽  
Khalida Inayat Noor ◽  
Kottakkaran Sooppy Nisar ◽  
Khadiga Ahmed Ismail ◽  
...  
Keyword(s):  
Applied Mathematics ◽  
Critical Role ◽  
Order Relation ◽  
Strong Relationship ◽  
New Class ◽  
Starting Point ◽  
Interval Valued Function ◽  
Fejér Inequality ◽  
Definition Of ◽  
Interval Valued

AbstractIn both theoretical and applied mathematics fields, integral inequalities play a critical role. Due to the behavior of the definition of convexity, both concepts convexity and integral inequality depend on each other. Therefore, the relationship between convexity and symmetry is strong. Whichever one we work on, we introduced the new class of generalized convex function is known as LR-$$\left({h}_{1}, {h}_{2}\right)$$ h 1 , h 2 -convex interval-valued function (LR-$$\left({h}_{1}, {h}_{2}\right)$$ h 1 , h 2 -IVF) by means of pseudo order relation. Then, we established its strong relationship between Hermite–Hadamard inequality (HH-inequality)) and their variant forms. Besides, we derive the Hermite–Hadamard–Fejér inequality (HH–Fejér inequality)) for LR-$$\left({h}_{1}, {h}_{2}\right)$$ h 1 , h 2 -convex interval-valued functions. Several exceptional cases are also obtained which can be viewed as its applications of this new concept of convexity. Useful examples are given that verify the validity of the theory established in this research. This paper’s concepts and techniques may be the starting point for further research in this field.

scholarly journals Some fixed point theorems via partial order relations without the monotone property

2015 ◽  
Vol 31 (3) ◽  
pp. 389-394
Author(s):  
WARUT SAKSIRIKUN ◽  
◽  
NARIN PETROT ◽  
Keyword(s):  
Fixed Point ◽  
Partial Order ◽  
Fixed Point Theorems ◽  
Metric Spaces ◽  
Coupled Fixed Point ◽  
Order Relation ◽  
Monotone Mappings ◽  
Complete Metric Spaces ◽  
Nonlinear Anal ◽  
Monotonic Properties

The main aim of this paper is to consider some fixed point theorems via a partial order relation in complete metric spaces, when the considered mapping may not satisfy the monotonic properties. Furthermore, we also obtain some couple fixed point theorems, which can be viewed as an extension of a result that was presented in [V. Berinde, Generalized coupled fixed point theorems for mixed monotone mappings in partially ordered metric spaces, Nonlinear Anal., 74 (2011), 7347–7355].

scholarly journals On the Meaning of Medical Evidence Hierarchies

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Jesper Jerkert
Keyword(s):  
Order Relation ◽  
Treatment Recommendations ◽  
Medical Evidence ◽  
Strength Of Evidence ◽  
Evidence Aggregation ◽  
Evidence Hierarchies

Evidence hierarchies are investigative strategies ordered with regard to the claimed strength of evidence. They have been used for a couple of decades in EBM, particularly in assessing evidence for treatment recommendations, but remain controversial. An under-investigated question is what the order in the hierarchy means. Four interpretations are discussed here. The two most credible are “typically stronger” or “ideally stronger.” The well-known GRADE framework seems to assume some “typically stronger” reading. Even if the interpretation of an evidence hierarchy were established, hierarchies are rather unhelpful for the task of evidence aggregation. Specifying the intended order relation may help to sort out disagreements.

scholarly journals A CAUSAL HIERARCHICAL MARKOV FRAMEWORK FOR THE CLASSIFICATION OF MULTIRESOLUTION AND MULTISENSOR REMOTE SENSING IMAGES

2020 ◽  
Vol V-3-2020 ◽  
pp. 269-277
Author(s):  
A. Montaldo ◽  
L. Fronda ◽  
I. Hedhli ◽  
G. Moser ◽  
S. B. Serpico ◽  
...  
Keyword(s):  
High Resolution ◽  
Markov Chain Model ◽  
Computational Cost ◽  
Order Relation ◽  
Boosted Regression Trees ◽  
Chain Model ◽  
Remotely Sensed Data ◽  
Space Filling Curve ◽  
Very High

Abstract. In this paper, a multiscale Markov framework is proposed in order to address the problem of the classification of multiresolution and multisensor remotely sensed data. The proposed framework makes use of a quadtree to model the interactions across different spatial resolutions and a Markov model with respect to a generic total order relation to deal with contextual information at each scale in order to favor applicability to very high resolution imagery. The methodological properties of the proposed hierarchical framework are investigated. Firstly, we prove the causality of the overall proposed model, a particularly advantageous property in terms of computational cost of the inference. Secondly, we prove the expression of the marginal posterior mode criterion for inference on the proposed framework. Within this framework, a specific algorithm is formulated by defining, within each layer of the quadtree, a Markov chain model with respect to a pixel scan that combines both a zig-zag trajectory and a Hilbert space-filling curve. Data collected by distinct sensors at the same spatial resolution are fused through gradient boosted regression trees. The developed algorithm was experimentally validated with two very high resolution datasets including multispectral, panchromatic and radar satellite images. The experimental results confirm the effectiveness of the proposed algorithm as compared to previous techniques based on alternate approaches to multiresolution fusion.

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