COMPLETE KAHLER METRICS WITH POSITIVE HOLOMORPHIC SECTIONAL CURVATURES ON CERTAIN LINE BUNDLES(RELATED TO A COHOMOGENEITY ONE POINT OF VIEW ON A YAU CONJECTURE)

In this article,we study Kahler metrics on a certain line bundle over some compact Kahler manifolds to find complete Kahler metrics with positive holomorphic sectional(or bisectional)curvatures.Thus,we apply a strategy to a famous Yau conjecture with a co-homogeneity one geometry.

Navigation Finsler metrics on a gradient Ricci soliton

In this paper,we study a class of Finsler metrics defined by a vector field on a gradient Ricci soliton.We obtain a necessary and sufficient condition for these Finsler metrics on a compact gradient Ricci soliton to be of isotropic S-curvature by establishing a new integral inequality.Then we determine the Ricci curvature of navigation Finsler metrics of isotropic S-curvature on a gradient Ricci soliton generalizing result only known in the case when such soliton is of Einstein type.As its application,we obtain the Ricci curvature of all navigation Finsler metrics of isotropic S-curvature on Gaussian shrinking soliton.

The Correct Reissner-Nordstrøm, Kerr and Kerr-Newman Metrics

In a very recent article of mine I have corrected the traditional derivation of the Schwarzschild metric thus arriving to formulate a correct Schwarzschild metric different from the traditional Schwarzschild metric. In this article, starting from this correct Schwarzschild metric, I also propose corrections to the other traditional Reissner-Nordstrøm, Kerr and Kerr-Newman metrics on the basis of the fact that these metrics should be equal to the correct Schwarzschild metric in the borderline case in which they reduce to the case described by this metric. In this way, we see that, like the correct Schwarzschild metric, also the correct Reissner-Nordstrøm, Kerr and Kerr-Newman metrics do not present any event horizon (and therefore do not present any black hole) unlike the traditional Reissner-Nordstrøm, Kerr and Kerr-Newman metrics.

MAXWELL-EINSTEIN METRICS ON COMPLETIONS OF CERTAIN C* BUNDLES

In this paper,we prove that for some completions of certain fiber bundles there is a Maxwell-Einstein metric conformally related to any given Kahler class.

Evaluating grant proposals:lessons from using metrics as screening device

Purpose:This study examines the effects of using publication-based metrics for the initial screening in the application process for a project leader.The key questions are whether formal policy affects the allocation of funds to researchers with a better publication record and how the previous academic performance of principal investigators is related to future project results.Design/methodology/approach:We compared two competitions,before and after the policy raised the publication threshold for the principal investigators.We analyzed 9,167 papers published by 332 winners in physics and the social sciences and humanities(SSH),and 11,253 publications resulting from each funded project.Findings:We found that among physicists,even in the first period,grants tended to be allocated to prolific authors publishing in high-quality journals.In contrast,the SSH project grantees had been less prolific in publishing internationally in both periods;however,in the second period,the selection of grant recipients yielded better results regarding awarding grants to more productive authors in terms of the quantity and quality of publications.There was no evidence that this better selection of grant recipients resulted in better publication records during grant realization.Originality:This study contributes to the discussion of formal policies that rely on metrics for the evaluation of grant proposals.The Russian case shows that such policy may have a profound effect on changing the supply side of applicants,especially in disciplines that are less suitable for metric-based evaluations.In spite of the criticism given to metrics,they might be a useful additional instrument in academic systems where professional expertise is corrupted and prevents allocation of funds to prolific researchers.

Novel Metrics for Mutation Analysis

A measure of the“goodness”or efficiency of the test suite is used to determine the proficiency of a test suite.The appropriateness of the test suite is determined through mutation analysis.Several Finite State Machine(FSM)mutants are produced in mutation analysis by injecting errors against hypotheses.These mutants serve as test subjects for the test suite(TS).The effectiveness of the test suite is proportional to the number of eliminated mutants.The most effective test suite is the one that removes the most significant number of mutants at the optimal time.It is difficult to determine the fault detection ratio of the system.Because it is difficult to identify the system’s potential flaws precisely.In mutation testing,the Fault Detection Ratio(FDR)metric is currently used to express the adequacy of a test suite.However,there are some issues with this metric.If both test suites have the same defect detection rate,the smaller of the two tests is preferred.The test case(TC)is affected by the same issue.The smaller two test cases with identical performance are assumed to have superior performance.Another difficulty involves time.The performance of numerous vehicles claiming to have a perfect mutant capture time is problematic.Our study developed three metrics to address these issues:FDR/|TS|,FDR/|TC|,and FDR/|Time|;In this context,most used test generation tools were examined and tested using the developed metrics.Thanks to the metrics we have developed,the research contributes to eliminating the problems related to performance measurement by integrating the missing parameters into the system.

Characterisation of Meteorological Drought in Northern Nigeria Using Comparative Rainfall-Based Drought Metrics

Meteorological droughts occur when there is deficiency in rainfall;i.e. rainfall availability is below some acclaimed normal values. Hence, the greater challenge is to be able to obtain suitable methods for assessing drought occurrence, its onset or initiation and termination. Thus, an attempt was made in this paper to evaluate the performance of Standardised Precipitation Index (SPI) and Standardised Precipitation Anomaly Index (SPAI) to characterise drought in Northern Nigeria for purposes of comparison and eventual adoption of probable candidate index for the development of an Early Warning System. The findings indicated that despite the fact that the annual timescale may be long, it can be employed to obtain information on the temporal evolution of drought especially, regional behaviour. However, monthly timescale can be more appropriate if emphasis is on evaluating the effects of drought in situations relating to water supply, agriculture and groundwater abstractions. The SPAI can be employed for periodic rainfall time series though;it accentuates drought signatures and may not necessarily dampen high fluctuations due to implications of high climatic variability considering the stochastic nature and state transition of drought phenomena. On the other hand, the temporal evolution of SPI and SPAI were not coherent at different temporal accumulations with differences in fluctuations. However, despite the differences between the SPI and SPAI, generally at some timescales, for instance, 6-month accumulation, both spatial and temporal distributions of drought characteristics were seemingly consistent. In view of the observed shortcomings of both indices, especially the SPI, the Standardised Nonstationary Precipitation Index (SnsPI) should be looked into and too, other indexes that take into consideration the implications of global warming by incorporating potential evapotranspiration may be deemed more suitable for drought studies in Northern Nigeria.

MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection

In a competitive digital age where data volumes are increasing with time, the ability to extract meaningful knowledge from high-dimensional data using machine learning (ML) and data mining (DM) techniques and making decisions based on the extracted knowledge is becoming increasingly important in all business domains. Nevertheless, high-dimensional data remains a major challenge for classification algorithms due to its high computational cost and storage requirements. The 2016 Demographic and Health Survey of Ethiopia (EDHS 2016) used as the data source for this study which is publicly available contains several features that may not be relevant to the prediction task. In this paper, we developed a hybrid multidimensional metrics framework for predictive modeling for both model performance evaluation and feature selection to overcome the feature selection challenges and select the best model among the available models in DM and ML. The proposed hybrid metrics were used to measure the efficiency of the predictive models. Experimental results show that the decision tree algorithm is the most efficient model. The higher score of HMM (m, r) = 0.47 illustrates the overall significant model that encompasses almost all the user’s requirements, unlike the classical metrics that use a criterion to select the most appropriate model. On the other hand, the ANNs were found to be the most computationally intensive for our prediction task. Moreover, the type of data and the class size of the dataset (unbalanced data) have a significant impact on the efficiency of the model, especially on the computational cost, and the interpretability of the parameters of the model would be hampered. And the efficiency of the predictive model could be improved with other feature selection algorithms (especially hybrid metrics) considering the experts of the knowledge domain, as the understanding of the business domain has a significant impact.

ISO25000-Related Metrics for Evaluating the Quality of Complex Information Systems

Evaluating complex information systems necessitates deep contextual knowledge of technology, user needs, and quality. The quality evaluation challenges increase with the system’s complexity, especially when multiple services supported by varied technological modules, are offered. Existing standards for software quality, such as the ISO25000 series, provide a broad framework for evaluation. Broadness offers initial implementation ease albeit, it often lacks specificity to cater to individual system modules. This paper maps 48 data metrics and 175 software metrics on specific system modules while aligning them with ISO standard quality traits. Using the ISO25000 series as a foundation, especially ISO25010 and 25012, this research seeks to augment the applicability of these standards to multi-faceted systems, exemplified by five distinct software modules prevalent in modern information ecosystems.

Altmetrics工具的起源、质疑、改进与发展

对Altmetrics的发展过程及现状进行了较为系统的总结,主要包括Altmetrics工具的起源、危机和转型三方面,厘清Altmetrics工具的产生背景,系统阐释了其面对来自科学共同体内、外的质疑和挑战,采取的积极应答、改进和发展的具体策略。

Comparative Study of Trace Metrics between Bibliometrics and Patentometrics

Purpose： To comprehensively evaluate the overall performance of a group or an individual in both bibliometrics and patentometrics. Design/methodology/approach： Trace metrics were applied to the top 30 universities in the2014 Academic Ranking of World Universities（ARWU） — computer sciences, the top 30 ESI highly cited papers in the computer sciences field in 2014, as well as the top 30 assignees and the top 30 most cited patents in the National Bureau of Economic Research（NBER） computer hardware and software category.Findings： We found that, by applying trace metrics, the research or marketing impact efficiency, at both group and individual levels, was clearly observed. Furthermore, trace metrics were more sensitive to the different publication-citation distributions than the average citation and h-index were.Research limitations： Trace metrics considered publications with zero citations as negative contributions. One should clarify how he/she evaluates a zero-citation paper or patent before applying trace metrics.Practical implications： Decision makers could regularly examinine the performance of their university/company by applying trace metrics and adjust their policies accordingly.Originality/value： Trace metrics could be applied both in bibliometrics and patentometrics and provide a comprehensive view. Moreover, the high sensitivity and unique impact efficiency view provided by trace metrics can facilitate decision makers in examining and adjusting their policies.

A Component Selection Framework of Cohesion and Coupling Metrics

Component-based software engineering is concerned with the develop-ment of software that can satisfy the customer prerequisites through reuse or inde-pendent development.Coupling and cohesion measurements are primarily used to analyse the better software design quality,increase the reliability and reduced system software complexity.The complexity measurement of cohesion and coupling component to analyze the relationship between the component module.In this paper,proposed the component selection framework of Hexa-oval optimization algorithm for selecting the suitable components from the repository.It measures the interface density modules of coupling and cohesion in a modular software sys-tem.This cohesion measurement has been taken into two parameters for analyz-ing the result of complexity,with the help of low cohesion and high cohesion.In coupling measures between the component of inside parameters and outside parameters.Thefinal process of coupling and cohesion,the measured values were used for the average calculation of components parameter.This paper measures the complexity of direct and indirect interaction among the component as well as the proposed algorithm selecting the optimal component for the repository.The better result is observed for high cohesion and low coupling in compo-nent-based software engineering.

NATURALLY REDUCTIVE(α_(1),α_(2))METRICS

Letting F be a homogeneous(α_(1),α_(2))metric on the reductive homogeneous manifold G/H,we first characterize the natural reductiveness of F as a local f-product between naturally reductive Riemannian metrics.Second,we prove the equivalence among several properties of F for its mean Berwald curvature and S-curvature.Finally,we find an explicit flag curvature formula for G/H when F is naturally reductive.

模糊Credit Metrics模型及其在信用风险评估中的应用

在经典的Credit Metrics模型中,通常假设具有相同信用评级的债务人的贷款是同质的,即具有相同的信用等级转移概率,且在实际应用中这种概率难以精确估计。这些局限性大大限制了该方法在实际中的应用。为了更好地描述和处理关于信用等级转移的模糊信息,借鉴经典Credit Metrics模型的思想,提出了模糊Credit Metrics模型,通过将传统的确定的信用转移矩阵模糊化,从而利用二型模糊变量来对信贷资产的远期价值进行描述和刻画,在此基础上对信贷资产的期望值和在险价值等量化指标进行计算,为基于不确定信息或专家主观判断的信用风险评估提供了一种系统的有效方法。

电子资源使用评估与E-Metrics

E-Metrics 项目是美国研究图书馆协会新评估计划的5个子项目之一。本文对E-Metrics 项目的产生背景及发展历程进行较为详细的介绍,并对整个项目进行简要的评价。

Effect of slice scope on data slice-based class cohesion metrics

This paper suggests that a single class rather than methods should be used as the slice scope to compute class cohesion. First, for a given attribute, the statements in all methods that last define the attribute are computed. Then, the forward and backward data slices for this attribute are generated by using the class as the slice scope and are combined to compute the corresponding class data slice. Finally, the class cohesion is computed based on all class data slices for the attributes. Compared to traditional cohesion metrics that use methods as the slice scope, the proposed metrics that use a single class as slice scope take into account the possible interactions between the methods. The experimental results show that class cohesion can be more accurately measured when using the class as the slice scope.

基于Credit Metrics的城投公司结构性风险评价研究

随着我国城市基础设施建设规模的快速扩大,城市基础设施建设投资公司项目类型多元化与融资方式多元化匹配造成的结构性风险已经成为影响其健康发展的主要问题.在分析了城投公司结构性风险的发生机理及传导机制的基础上,针对城投公司债务的信用转移问题,运用Credit Metrics模型对城投公司结构性风险进行评价研究.结果表明,城投公司存在结构性风险且隐患巨大.一旦资金链出现问题,城投公司的债务将出现严重的违约情况.

基于Credit Metrics模型的汽车消费贷款业务信用风险管理分析

汽车消费贷款业务的蓬勃发展要求商业银行加强对该业务的信用风险管理。Credit Metrics模型是世界上第一个评估信用风险的量化度量模型,并为改善商业银行被动的信用风险管理提供了一种有效的管理思路和基础。

Adapted Metrics for a Modified Coulomb/Newton’s Potential

Modified Theories of Gravity include spin dependence in General Relativity, to account for additional sources of gravity instead of dark matter/energy approach. The spin-spin interaction is already included in the effective nuclear force potential, and theoretical considerations and experimental evidence hint to the hypothesis that Gravity originates from such an interaction, under an averaging process over spin directions. This invites to continue the line of theory initiated by Einstein and Cartan, based on tetrads and spin effects modeled by connections with torsion. As a first step in this direction, the article considers a new modified Coulomb/Newton Law accounting for the spin-spin interaction. The physical potential is geometrized through specific affine connections and specific semi-Riemannian metrics, canonically associated to it, acting on a manifold or at the level of its tangent bundle. Freely falling particles in these “toy Universes” are determined, showing an interesting behavior and unexpected patterns.

Credit Metrics模型计算信用风险的实例分析

CreditMetrics作为计算资产组合信用风险的模型,是一个联系信用和证券市场的简单、动态的架构。本文从此模型出发,分别讨论了单个贷款和资产组合基于违约率,信用迁移概率的计算原理和实例,并对违约率的测算作了进一步的分析和讨论。