What are the Best Practices to Groom Gen Y\u27ers in an Organization?

It had been debatable whether Gen Y workers really deserve more of companies’ attention or is it better to let them just grow up (Appendix 3). However, it is axiomatic that Gen Y is nearly as large as the baby boomer generation and is expected to have nearly as big an impact on business and society. By 2020, nearly half (46 percent) of all U.S. workers will be Gen Y. Not surprisingly, business leaders are realizing this generation’s unique competencies and perspective, and employers are looking for ways to harness their strengths through new style of development and training programs. This paper will provide examples of what leading-edge organizations are doing to leverage this generation’s strengths and to integrate them into a multi-generational workforce

What Ways Can We Use Big Data to Offer More Personalized and Tailored HR Services to our Employees?

Big data analytics—analytic techniques operating on big data—is continuing to disrupt the way decision-making is occurring. Instead of relying on intuition, decisions are made based on statistical analysis, emerging technologies and massive amounts of current and historical data. Predictive analytics, which will be featured in much of the research below, is a type of big data analytics that predicts an outcome by correlating the relationships of various factors. These predictions can be made utilizing a variety of organized structured data and disorganized unstructured data (i.e. social media posts, surveys, etc.

How Can Companies Harness a Learning Organization to Lead the Collaborative Culture?

Employees in multinational companies tend to become departmentalized by business processes, and are increasingly losing touch with their organizations’ goals and strategies. Learning Organization is a concept that focuses on the interconnectedness among employees in the same organizations by collaborating interdepartmentally and maintaining knowledge on new strategies, products, services, industries, and their macro-environment in order to give their organizations the competitive advantages over competitors. Our research investigated the best practices and made conclusions on how to implement the mentioned cross-functional concept

SOHO design in the near future

Not Include

ShortcutFusion: From Tensorflow to FPGA-based accelerator with reuse-aware memory allocation for shortcut data

Residual block is a very common component in recent state-of-the art CNNs such as EfficientNet or EfficientDet. Shortcut data accounts for nearly 40% of feature-maps access in ResNet152 [8]. Most of the previous DNN compilers, accelerators ignore the shortcut data optimization. This paper presents ShortcutFusion, an optimization tool for FPGA-based accelerator with a reuse-aware static memory allocation for shortcut data, to maximize on-chip data reuse given resource constraints. From TensorFlow DNN models, the proposed design generates instruction sets for a group of nodes which uses an optimized data reuse for each residual block. The accelerator design implemented on the Xilinx KCU1500 FPGA card significantly outperforms NVIDIA RTX 2080 Ti, Titan Xp, and GTX 1080 Ti for the EfficientNet inference. Compared to RTX 2080 Ti, the proposed design is 1.35-2.33x faster and 6.7-7.9x more power efficient. Compared to the result from baseline, in which the weights, inputs, and outputs are accessed from the off-chip memory exactly once per each layer, ShortcutFusion reduces the DRAM access by 47.8-84.8% for RetinaNet, Yolov3, ResNet152, and EfficientNet. Given a similar buffer size to ShortcutMining [8], which also mine the shortcut data in hardware, the proposed work reduces off-chip access for feature-maps 5.27x while accessing weight from off-chip memory exactly once.Comment: 12 page

Reconstituting ring-rafts in bud-mimicking topography of model membranes.

During vesicular trafficking and release of enveloped viruses, the budding and fission processes dynamically remodel the donor cell membrane in a protein- or a lipid-mediated manner. In all cases, in addition to the generation or relief of the curvature stress, the buds recruit specific lipids and proteins from the donor membrane through restricted diffusion for the development of a ring-type raft domain of closed topology. Here, by reconstituting the bud topography in a model membrane, we demonstrate the preferential localization of cholesterol- and sphingomyelin-enriched microdomains in the collar band of the bud-neck interfaced with the donor membrane. The geometrical approach to the recapitulation of the dynamic membrane reorganization, resulting from the local radii of curvatures from nanometre-to-micrometre scales, offers important clues for understanding the active roles of the bud topography in the sorting and migration machinery of key signalling proteins involved in membrane budding