A Six Cell Services Comparison Model for Healthcare

2014 ◽  
pp. 74-84
Author(s):  
Saradhi Motamarri
Keyword(s):  
Comparison Model

On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria

2016 ◽  
Vol 2 (3) ◽  
pp. 54
Author(s):  
G. Marimuthu ◽  
G. Ramesh
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Decision Models ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analysis Method ◽  
Analytic Hierarchy ◽  
Comparison Model ◽  
Hierarchy Process

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

Personal Identification by the Comparison of Facial Profiles: Testing the Reliability of a High-Resolution 3D-2D Comparison Model

2011 ◽  
Vol 57 (1) ◽  
pp. 182-187 ◽  
Author(s):  
Cristina Cattaneo ◽  
Angela Cantatore ◽  
Romina Ciaffi ◽  
Daniele Gibelli ◽  
Alfredo Cigada ◽  
...  
Keyword(s):  
High Resolution ◽  
Personal Identification ◽  
Comparison Model

Transforming comparison model lower bounds to the parallel-random-access-machine

1997 ◽  
Vol 62 (2) ◽  
pp. 103-110 ◽  
Author(s):  
Dany Breslauer ◽  
Artur Czumaj ◽  
Devdatt P. Dubhashi ◽  
Friedhelm Meyer auf der Heide
Keyword(s):  
Lower Bounds ◽  
Random Access ◽  
Comparison Model ◽  
Random Access Machine ◽  
Parallel Random Access Machine

Diagnosability and Diagnostic Algorithm for Pancake Graph under the Comparison Model

2015 ◽  
Vol 15 (01n02) ◽  
pp. 1550005
Author(s):  
WENJUN LIU ◽  
CHENG-KUAN LIN
Keyword(s):  
Fault Diagnosis ◽  
Interconnection Networks ◽  
Linear Time ◽  
Hamiltonian Path ◽  
Diagnostic Algorithm ◽  
Efficient Algorithms ◽  
Comparison Model ◽  
Diagnosis Model

Fault diagnosis is important for the reliability of interconnection networks. This paper addresses the fault diagnosis of n-dimensional pancake graph Pn under the comparison diagnosis model. By the concept of local diagnosability, we first prove that the diagnosabitly of Pn is n − 1, and it has strong local diagnosability property even if there are n − 3 faulty edges. Furthermore, we present efficient algorithms to locate extended star and Hamiltonian path structures in Pn, respectively. According to the works of Li et al. and Lai, the extended star and Hamiltonian path structures can be used to identify all faulty vertices in linear time, provided the number of faulty vertices is no more than n − 1.

Adaptive Diagnosis of Hamiltonian Networks under the Comparison Model

2021 ◽  
pp. 2150015
Author(s):  
Wenjun Liu ◽  
Wenjun Li
Keyword(s):  
Fault Diagnosis ◽  
Upper Bound ◽  
Multiprocessor Systems ◽  
Major Goal ◽  
Comparison Model ◽  
A Value ◽  
Pmc Model ◽  
Diagnosis Algorithm ◽  
Test Outcomes

Adaptive diagnosis is an approach in which tests can be scheduled dynamically during the diagnosis process based on the previous test outcomes. Naturally, reducing the number of test rounds as well as the total number of tests is a major goal of an efficient adaptive diagnosis algorithm. The adaptive diagnosis of multiprocessor systems under the PMC model has been widely investigated, while adaptive diagnosis using comparison model has been independently discussed only for three networks, including hypercube, torus, and completely connected networks. In addition, adaptive diagnosis of general Hamiltonian networks is more meaningful than that of special graph. In this paper, the problem of adaptive fault diagnosis in Hamiltonian networks under the comparison model is explored. First, we propose an adaptive diagnostic scheme which takes five to six test rounds. Second, we derive a dynamic upper bound of the number of fault nodes instead of setting a value like normal. Finally, we present an algorithm such that at least one sequence obtained from cycle partition can be picked out and all nodes in this sequence can be identified based on the previous upper bound.

scholarly journals Leadership Style, Intellectual Capital and Corporate Social Responsibility on Performance, a Comparison Model of Listed Companies in Indonesia

2020 ◽  
Vol 5 (3) ◽  
pp. 110-120
Author(s):  
Rilla Gantino ◽  
Endang Ruswanti ◽  
Taufiqur Rachman
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Leadership Style ◽  
Intellectual Capital ◽  
Stock Exchange ◽  
Negative Relationship ◽  
Listed Companies ◽  
Primary Data ◽  
Comparison Model ◽  
Corporate Social

Objective – This paper aims to examine the influence of Leadership Style, Intellectual Capital, and Corporate Social Responsibility on Performance in companies in the sub-sectors of Mining, Pharmacy and Consumption and Household, Basic Industry, Chemical and Infrastructure, Utility and Telecommunication listed on Indonesia Stock Exchange (IDX) 2012-2018. Methodology/Technique – In this research, leadership style is measured transformationally and transactionally. Meanwhile, Intellectual Capital is measured using VAICTM. Furthermore, Corporate Social Responsibility is measured using GRI G4, and Financial Performance is proxied by ROA, ROE, and sales growth. The method used is a saturated sample. The sample in this research was 50 companies in the Basic and Chemical Industry sub-sector, 28 companies in the infrastructure, utilities, and telecommunications sub-sectors, 38 mining sub-sector companies, and 17 companies in the consumer goods sub-sector listed on the Indonesia Stock Exchange (IDX). This research used secondary data taken from financial and annual reports and primary data obtained through questionnaires for leadership style. The analysis method used is simple regression analysis. Findings & Novelty –The results show that the influence of leadership style, intellectual capital, and corporate social responsibility in the four sectors varies with a positive or negative relationship direction. Intellectual capital has a positive significant influence on ROA, ROE and SG in four sectors. Previous research has focused on only one sector. This study compares the influence of leadership style, intellectual capital, and corporate social responsibility in four sectors Type of Paper: Empirical. JEL Classification: M41, M49. Keywords: Comparison; Leadership Style; Intellectual Capital; CSR; Performance Reference to this paper should be made as follows: Gantino, R; Ruswanti, E; Rachman, T. 2020. Leadership Style, Intellectual Capital and Corporate Social Responsibility on Performance, a Comparison Model of Listed Companies in Indonesia., Acc. Fin. Review, 5 (3): 110 – 120. https://doi.org/10.35609/afr.2020.5.3(3)

scholarly journals Approaches to improve the robustness of the Comparison Model Method for the inverse problem of groundwater hydrology

2021 ◽  
Author(s):  
Alessandro Comunian ◽  
Mauro Giudici
Keyword(s):  
Geometric Mean ◽  
Optimization Methods ◽  
Forward Problem ◽  
Data Sets ◽  
Direct Inversion ◽  
Model Method ◽  
Comparison Model ◽  
Multiple Data ◽  
Hydraulic Gradients ◽  
Multiple Data Sets

<p>Indirect inversion approaches are widely used in Geosciences, and in particular also for the identification of the hydraulic properties of aquifers. Nevertheless, their application requires a substantial number of model evaluation (forward problem) runs, a task that for complex problems can be computationally intensive. Reducing this computational burden is an active research topic, and many solutions, including the use of hybrid optimization methods, the use of physical proxies or again machine-learning tools <span>allow to avoid</span> considering the full physics of the problem when running a numerical implementation of the forward problem.</p><p>Direct inversion approaches represent computationally frugal alternatives to indirect approaches, because in general they require a smaller number of runs of the forward problem. The classical drawbacks of these methods can be alleviated by some implementation approaches and in particular by using multiple sets of data, when available.</p><p>This work is an effort to improve the robustness of the Comparison Model Method (CMM), a direct inversion approach aimed at the identification of the hydraulic transmissivity of a confined aquifer. The robustness of the CMM is here ameliorated by (i) improving the parameterization required to handle small hydraulic gradients; (ii) investigating the role of different criteria aimed at merging multiple data-sets corresponding to different flow conditions.</p><p>On a synthetic case study, it is demonstrated that correcting a small percentage of the small hydraulic gradients (about 10%) allows to obtain reliable results, and that a criteria based on the geometric mean is adequate to merge the results coming from multiple data-sets. In addition, the use of multiple-data sets allows to noticeably improve the robustness of the CMM when the input data are affected by noise.</p><p>All the tests are performed by using open source and widely <span>used</span> tools like the USGS Modflow6 and its Python interface flopy to foster the application of the <span>CMM. The scripts and corresponding package</span>, named <em>cmmpy</em>, is available on the Python Package Index (PyPI) and on bitbucket at the following address: https://bitbucket.org/alecomunian/cmmpy.</p>

scholarly journals Genetic Variations in Inflammatory Response Genes and Their Association with the Risk of Prostate Cancer

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Xin Cui ◽  
Hao Yan ◽  
Tong-Wen Ou ◽  
Chun-Song Jia ◽  
Qi Wang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Inflammatory Response ◽  
Prostate Cancer Risk ◽  
Genetic Variations ◽  
Odds Ratios ◽  
Comparison Model ◽  
Pcr Rflp ◽  
Cox 2 ◽  
Cox 1

Prostate cancer is a common cancer in men. Genetic variations in inflammatory response genes can potentially influence the risk of prostate cancer. We aimed to examine the association betweenPPARGPro12Ala,NFKB1-94 ins/del,NFKBIA-826C/T,COX-1(50C>T), andCOX-2(-1195G>A) polymorphisms on prostate cancer risk. The genotypes of the polymorphisms were ascertained in 543 prostate cancer patients and 753 controls through PCR-RFLP and the risk association was evaluated statistically using logistic regression analysis. TheNFKB1-94 polymorphism was shown to decrease prostate cancer risk in both heterozygous and homozygous comparison models (odds ratios of 0.74 (95% CI = 0.58–0.96) (P=0.02) and 0.57 (95% CI = 0.42–0.78) (P<0.01), resp.). An opposite finding was observed forCOX-2(-1195) polymorphism (odds ratios of 1.58 (95% CI = 1.15–2.18) (P<0.01) for heterozygous comparison model and 2.08 (95% CI = 1.48–2.92) (P<0.01) for homozygous comparison model). No association was observed for other polymorphisms. In conclusion,NFKB1-94 ins/del andCOX-2(-1195G>A) polymorphisms may be, respectively, associated with decreased and increased prostate cancer risk in the Chinese population.

Diagnosability of Bubble-Sort Star Graphs with Missing Edges

2019 ◽  
Vol 19 (02) ◽  
pp. 1950002 ◽  
Author(s):  
SHIYING WANG ◽  
YINGYING WANG
Keyword(s):  
Multiprocessor System ◽  
Star Graph ◽  
Star Graphs ◽  
Comparison Model ◽  
Model Following ◽  
Strong Property

The diagnosability of a multiprocessor system plays an important role. The bubble-sort star graph BSn has many good properties. In this paper, we study the diagnosis on BSn under the comparison model. Following the concept of the local diagnosability, the strong local diagnosability property is discussed. This property describes the equivalence of the local diagnosability of a node and its degree. We prove that BSn (n ≥ 5) has this property, and it keeps this strong property even if there exist (2n − 5) missing edges in it, and the result is optimal with respect to the number of missing edges.

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