SUPERVISOR COMMUNICATION IN TRAINING PROGRAM: AN EMPIRICAL STUDY IN MALAYSIA

A thorough review of human resource development literature shows that the ability of supervisors to use good communication styles in managing programs will invoke employees’ motivation to learn, this may lead to increased positive individual attitudes and behaviors. The nature of this relationship is interesting, but little is known about the influence of employees’ motivation to learn in training management literature. Therefore, this study was conducted to examine the effect of supervisor communication in training program and motivation to learn on individual attitudes and behaviors using 100 usable questionnaires gathered from technical employees who have worked in one city based local authority in East Malaysia (CLAEASTMALAYSIA). Outcomes of stepwise regression analysis showed that relationship between motivation to learn and supervisor communication had been an important predictor of transfer of competency and job performance. Statistically, this result confirms that motivation to learn does act as a full mediating role in the training model of the in the organizational sample. In addition, implications and limitations of the study, as well as directions future research are discussed.supervisor communication, motivation to learn, individual attitudes and behaviors

Variable selection for BART: An application to gene regulation

We consider the task of discovering gene regulatory networks, which are defined as sets of genes and the corresponding transcription factors which regulate their expression levels. This can be viewed as a variable selection problem, potentially with high dimensionality. Variable selection is especially challenging in high-dimensional settings, where it is difficult to detect subtle individual effects and interactions between predictors. Bayesian Additive Regression Trees [BART, Ann. Appl. Stat. 4 (2010) 266-298] provides a novel nonparametric alternative to parametric regression approaches, such as the lasso or stepwise regression, especially when the number of relevant predictors is sparse relative to the total number of available predictors and the fundamental relationships are nonlinear. We develop a principled permutation-based inferential approach for determining when the effect of a selected predictor is likely to be real. Going further, we adapt the BART procedure to incorporate informed prior information about variable importance. We present simulations demonstrating that our method compares favorably to existing parametric and nonparametric procedures in a variety of data settings. To demonstrate the potential of our approach in a biological context, we apply it to the task of inferring the gene regulatory network in yeast (Saccharomyces cerevisiae). We find that our BART-based procedure is best able to recover the subset of covariates with the largest signal compared to other variable selection methods. The methods developed in this work are readily available in the R package bartMachine.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS755 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

New insights into pedestrian flow through bottlenecks

Capacity estimation is an important tool for the design and dimensioning of pedestrian facilities. The literature contains different procedures and specifications which show considerable differences with respect to the estimated flow values. Moreover do new experimental data indicate a stepwise growing of the capacity with the width and thus challenge the validity of the specific flow concept. To resolve these differences we have studied experimentally the unidirectional pedestrian flow through bottlenecks under laboratory conditions. The time development of quantities like individual velocities, density and individual time gaps in bottlenecks of different width is presented. The data show a linear growth of the flow with the width. The comparison of the results with experimental data of other authors indicates that the basic assumption of the capacity estimation for bottlenecks has to be revised. In contradiction with most planning guidelines our main result is, that a jam occurs even if the incoming flow does not overstep the capacity defined by the maximum of the flow according to the fundamental diagram.Comment: Traffic flow, pedestrian traffic, crowd dynamics, capacity of bottlenecks (16 pages, 8 figures); (+ 3 new figures and minor revisions

Magnetism in f electron superlattices

We analyze antiferromagnetism in $f$ electron superlattices. We show that the competition between the Kondo effect and the RKKY interaction in $f$ electron materials is modified by the superlattice structure. Thus, the quantum critical point which separates the magnetic phase and the Fermi liquid phase depends on the structure of the $f$ electron superlattice. The competition between the Kondo effect and the RKKY interaction is also reflected in the magnetic interlayer coupling between different $f$ electron layers. We demonstrate that in the case of weak Kondo effect the magnetic interlayer coupling behaves similar to other magnetic heterostructures without Kondo effect. However, close to the quantum phase transition, the dependence of the interlayer coupling on the distance between the $f$ electron layers is modified by the Kondo effect. Another remarkable effect, which is characteristic for $f$ electron superlattice, is that the magnetic interlayer coupling does vanish stepwise depending on the distance between different $f$ electron layers. As a consequence, the quantum critical point depends also stepwise on this distance

Potential of ALOS2 and NDVI to estimate forest above-ground biomass, and comparison with lidar-derived estimates

Remote sensing supports carbon estimation, allowing the upscaling of field measurements to large extents. Lidar is considered the premier instrument to estimate above ground biomass, but data are expensive and collected on-demand, with limited spatial and temporal coverage. The previous JERS and ALOS SAR satellites data were extensively employed to model forest biomass, with literature suggesting signal saturation at low-moderate biomass values, and an influence of plot size on estimates accuracy. The ALOS2 continuity mission since May 2014 produces data with improved features with respect to the former ALOS, such as increased spatial resolution and reduced revisit time. We used ALOS2 backscatter data, testing also the integration with additional features (SAR textures and NDVI from Landsat 8 data) together with ground truth, to model and map above ground biomass in two mixed forest sites: Tahoe (California) and Asiago (Alps). While texture was useful to improve the model performance, the best model was obtained using joined SAR and NDVI (R2 equal to 0.66). In this model, only a slight saturation was observed, at higher levels than what usually reported in literature for SAR; the trend requires further investigation but the model confirmed the complementarity of optical and SAR datatypes. For comparison purposes, we also generated a biomass map for Asiago using lidar data, and considered a previous lidar-based study for Tahoe; in these areas, the observed R2 were 0.92 for Tahoe and 0.75 for Asiago, respectively. The quantitative comparison of the carbon stocks obtained with the two methods allows discussion of sensor suitability. The range of local variation captured by lidar is higher than those by SAR and NDVI, with the latter showing overestimation. However, this overestimation is very limited for one of the study areas, suggesting that when the purpose is the overall quantification of the stored carbon, especially in areas with high carbon density, satellite data with lower cost and broad coverage can be as effective as lidar

Homemade yeast by using tropical fruits through fermentation process

Yeast is one type of bacteria that is used in baking industry and as the crucial parameters to determine the softness of the bread. Many tropical fruits can be used as a medium to produce yeast. The main goal of this study is to produce homemade yeast by different types of fruits. The methods used to produce yeast are fermentation and separation process, where tropical fruits such as the banana, pineapple and raisin were used. The fruits are fermented for seven days, and they are supplied daily with calculated amount of sugar and flour. The yeast produced are then used in making apam, where three parameters are measured which are the volume of apam, the flavour and the aroma of apam. The best tropical fruits to produce yeast, arranged in order are raisin, banana and pineapple. We are unable to study further on the starfruit because it is seasonally unavailable during the research period. The result of the present study would provide knowledge and information about tropical fruits as homemade yeast. Additionally, this study will produce significant and relevant information for future studies regarding to homemade yeast

Do Government Policies Foster Environmental Performance of Enterprises from CEE Region?

In recent years, EU countries, including these from the Central Eastern European (CEE) region has recognised, that eco-innovation should be treated as strategic priority of their economies. The aim of this paper is to present a cross-country analysis of the connection between eco-innovation and its main drivers within firms from selected CEE countries (Bulgaria, Czech Republic, Romania) and Germany. The empirical part is based on micro-data for Community Innovation Survey (CIS) 2006-2008. Based on the results of stepwise regression between main policy actions sustaining innovation activity and eco-innovation performance we can conclude, that financial support for innovation activities has a rather limited role in promoting eco-innovation. At the same time enterprises from the CEE region regard environmental regulations as the most important drivers of eco-innovation. In Germany, a country ranked in the highest category in the Eco-Innovation Scoreboard, the variety of forces that influence eco-innovation is much more wide-ranging. This indicates that government actions should take a broader look and lay the more general bases fostering the model of a green growth