Refinement and validation of a comprehensive scale for measuring HR practices aimed at performance-enhancement and employee-support

The purpose of this paper is to refine and validate a Human Resource practices (HRP) scale to measure employees' perceptions and test a two-tier model structured in eight practices and two bundles. In a sample of 554 employees, an EFA (Exploratory Factor Analysis) offered six factors that explained about 70% of the variance. Then, with 1647 employees (from 41 Spanish organizations), first- and second-order models were tested with Confirmatory Factor Analysis (CFA). The former encompasses eight practices. The latter grouped the practices in two bundles, one on enhancing performance and the other on supporting employees. The Cronbach's alpha, Rho coefficient (Composite Reliability Coefficient), Omega coefficient, and Spearman-Brown split half coefficient showed good reliability. Validity evidence was found for construct, criterion, convergent, content, discriminant, and predictive validity. Moreover, the paper integrates different ways of approaching the study of HR management based on employees' perceptions, using a two-tier approach. The two-bundle model showed better fit, pointing out the importance of paying attention to multiple outcomes for employees and organizations. The study makes a relevant theoretical contribution about the role and aims of HRM practices for organizational success and employees' performance and well-being.     

Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

冲激噪声环境中LFM信号的特征参数估计

SαS稳定分布是一类非常重要的非高斯随机分布,具有这类分布的噪声称为冲激噪声。在冲激噪声情况下,α阶以上的矩均不存在,导致基于二阶矩的高斯模型算法性能下降,甚至不能正常工作。该文提出了一种在冲激噪声环境下线性调频信号特征参数估计的算法,通过分析冲激噪声的具体特点,给出了修正的低阶矩模糊函数,并结合Radon变换估计了冲激噪声环境下LFM信号的参数。该算法既可应用于冲激噪声下,又可应用于高斯噪声环境,故具有较好的鲁棒性。最后用计算机仿真验证了该算法的有效性。     

交流电路参数的实用测量法研究

探讨了二端交流电路的R,L,C元件参数的测定,并研究了工频电路的等效电阻、等效电抗的测量方法。     

K_2PdX_4:Cu~(2+)超超精细参量研究

利用离子簇模型,建立了四角伸长八面体中3d9体系超超精细参量的微扰公式;在理论上得到了轨道混合系数、未配对自旋密度、平均共价因子等参量的关系,并应用于K2PdX4(X=Cl,Br)中的四角[CuX4]2?中心,理论与实验比较符合。与文献[4]相比,该文在计算公式上有所简化,并且调节参量数目进一步地减少,因而具有较好的适用性。     

The Impact of Items and Anchors on Parent–Child Reports of Problem Behavior

Research has repeatedly demonstrated that parent and child reports of child behavior and emotional functioning often do not agree in terms of symptom severity or even symptom presence. Given the potential clinical impact that discrepant reports may have on the therapeutic process, a significant amount of research has addressed the factors influencing this observed discrepancy. Traditionally, this research has evaluated the impact of demographic factors on mean differences and obtained correlation coefficients between parent and child reports. The current research improves upon previous research in this area in two ways. First, the current research uses parent and child measures with identical rather than similar items as is commonly found in previous research. Second, the current research moves beyond identifying demographic influences on discrepant reports by explaining observed discrepancies in terms of differences in parent and child perceptions of typical child behavior.David Carlston and Benjamin Ogles are affiliated with Department of Psychology, Ohio University, Athens, USA.Funding for this project was provided by the Ohio Department of Mental Health.     

Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.     

Improving flexibility and efficiency by adding parallelism to genetic algorithms

In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our motivation is to bring some uniformity to the proposal, comparison, and knowledge exchange among the traditionally opposite kinds of serial and parallel GAs. We comparatively analyze the properties of steady-state, generational, and cellular genetic algorithms. Afterwards, this study is extended to consider a distributed model consisting in a ring of GA islands. The analyzed features are the time complexity, selection pressure, schema processing rates, efficacy in finding an optimum, efficiency, speedup, and resistance to scalability. Besides that, we briefly discuss how the migration policy affects the search. Also, some of the search properties of cellular GAs are investigated. The selected benchmark is a representative subset of problems containing real world difficulties. We often conclude that parallel GAs are numerically better and faster than equivalent sequential GAs. Our aim is to shed some light on the advantages and drawbacks of various sequential and parallel GAs to help researchers using them in the very diverse application fields of the evolutionary computation.     

结构材料重点核素^60Ni的共振参数评价

利用多能级Breit-Wigner公式对^60Ni的全截面进行了计算，并将计算结果与BNL－325（四版）进行比较。利用实验核数据库EXFOR提供的全截面数据及实验条件，对^60Ni的可分辩区实验全截面进行了评价，推荐出一套可用于校验共振参数的实验全截面数据并与计算结果进行了比较。