The relationship between velocity utilization rate and pole vault performance

In the pole vault event, the velocity of approach is a highly vital factor. As velocity of approach improvements highly impact performance improvements. This study analysed the relationships between sprint running’s speed (SR), pole running (PR, without jump), and the pole vault approach (PVA, with real jump). Analysed too were the relationships between both the approach and performance’s respective running distance, velocity, and velocity utilization rates. Methods: Ten male pole vaulters were recruited. Measured was each 5-meter segment’s average velocity of his respective SR, PR, and PVA, along with the distance to maximum velocity. Results: The maximum average velocity of the PR’s 5m segments altogether was significantly positively correlated with pole vault (PV) performance; The maximum average velocity of the PR’s 5m segments altogether was significantly positively correlated with the last 5m PVA average velocity; The PVA velocity’s utilization rate was significantly negatively correlated with the difference between the distance to the PR’s maximum velocity and the PVA’s distance. Conclusion: The PR segment’s maximum speed capability can evaluate both a pole vaulter’s potential and pole vault-specific abilities. This study’s recruited pole vaulters’ respective approach distances were generally insufficient that resulted in a lower velocity utilization rate. Suggested is that in training, the pole vaulter could first find the distance required to reach the highest velocity upon starting from the PR test. Thus, this subsequently known distance could be applied in tandem with the pole vault’s approach to both improve the PVA’s utilization rate and reach the individual highest speed level

Intraclass reliability for assessing how well Taiwan constrained hospital-provided medical services using statistical process control chart techniques

BACKGROUND: Few studies discuss the indicators used to assess the effect on cost containment in healthcare across hospitals in a single-payer national healthcare system with constrained medical resources. We present the intraclass correlation coefficient (ICC) to assess how well Taiwan constrained hospital-provided medical services in such a system. METHODS: A custom Excel-VBA routine to record the distances of standard deviations (SDs) from the central line (the mean over the previous 12 months) of a control chart was used to construct and scale annual medical expenditures sequentially from 2000 to 2009 for 421 hospitals in Taiwan to generate the ICC. The ICC was then used to evaluate Taiwan’s year-based convergent power to remain unchanged in hospital-provided constrained medical services. A bubble chart of SDs for a specific month was generated to present the effects of using control charts in a national healthcare system. RESULTS: ICCs were generated for Taiwan’s year-based convergent power to constrain its medical services from 2000 to 2009. All hospital groups showed a gradually well-controlled supply of services that decreased from 0.772 to 0.415. The bubble chart identified outlier hospitals that required investigation of possible excessive reimbursements in a specific time period. CONCLUSION: We recommend using the ICC to annually assess a nation’s year-based convergent power to constrain medical services across hospitals. Using sequential control charts to regularly monitor hospital reimbursements is required to achieve financial control in a single-payer nationwide healthcare system

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Exploring the Influence of corporate social responsibility on efficiency : An extended dynamic data envelopment analysis of the global airline industry

Corporate social responsibility (CSR) has received significant attention from practitioners, encouraging companies to consider it as a business model for their sustainable development. This study examines the effect of CSR on the dynamic efficiency of the global airline industry from 2013 to 2017. The study integrates DuPont and two-stage network data envelopment analyses to evaluate global airline efficiency and its relationship with CSR. Multiple proxies are used to establish a performance evaluation method and analyze the performance of global airlines from the perspectives of their financial structure, production performance and CSR. The study examines the influence of CSR to global airlines’ production efficiency and CSR is measured according to environmental, social and governance activities. The findings are as follows: (1) the profitability of low-cost carriers (LCCs) is superior to that of full-service carriers (FSCs); (2) the energy and wealth-creation efficiencies of LCCs are superior to those of FSCs; (3) FSCs are more committed to CSR activities, and their CSR is positively correlated with overall production efficiency; and (4) environmental and social elements in CSR improve airline efficiency levels. Overall, this study suggests that global airlines should practice CSR to address challenges in the dynamic global airline industry

Temperature Swing Adsorption Process for CO2 Capture Using Polyaniline Solid Sorbent

AbstractTo capture carbon dioxide from power plant flue gas which consists of 15% CO2 and 85% N2, with a temperature swing adsorption (TSA) by using polyaniline solid sorbent as the adsorbent, is explored experimentally and theoretically. First, single component adsorption equilibrium data of carbon dioxide on polyaniline solid sorbent is obtained by using Micro-Balance Thermo D-200. Then isotherm curves and the parameters are obtained by numerical method. The adsorption is expressed by the Langmuir-Freundlich isotherm. After accomplishment of isotherm curves, the breakthrough curve experiment is investigated with single adsorption column. The experiments test the change in adsorbed gas concentration at the outlet by adsorbed gas, CO2, and non-adsorbed gas, helium. Finally, this study accentuates the TSA experiments on CO2 purity and recovery by operation variable discussion which includes feed pressure, adsorption temperature and desorption temperature to find optimal operation condition. The results of optimal operation condition are CO2 purity of 47.65% with a 92.46% recovery