Analysis of innovation management in German enterprises

Abstract: In the drive towards economic globalization, companies are faced with both opportunities and challenges. As the global landscape changes, company and by extension countries increasingly grasp the level of importance innovation has to their survival and continued development. The element of innovation, within the business environment, has become the necessary condition for sustainable development of a country or nation. In the case of Germany, the authors acknowledge the country's fascinating ability in innovation management; therefore have sought to gain a better understanding through a sampled analysis of German private enterprises. In the process, quantitative model and qualitative model were utilized together. On the one hand, a qualitative method is adopted to collect primary data. On the other hand, a quantitative process is used to collect secondary data. According to the data analysis of the sampled corporations and businesses, the indices of each factor vary across the different industries. Results also suggested that stronger enterprises give greater attention to innovation (factors) and therefore reap higher gains. In such companies, various rules and regulations are designed to stimulate the employees' creativity; while communication is established across all parts of companies. Similarly, the company would be design on the basis of adapting different market strategies. Worthy of note is that companies in each industr

Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing

International audienceBig data processing at the production scale presents a highly complex environment for resource optimization (RO), a problem crucial for meeting performance goals and budgetary constraints of analytical users. The RO problem is challenging because it involves a set of decisions (the partition count, placement of parallel instances on machines, and resource allocation to each instance), requires multi-objective optimization (MOO), and is compounded by the scale and complexity of big data systems while having to meet stringent time constraints for scheduling. This paper presents a MaxCompute based integrated system to support multi-objective resource optimization via ne-grained instance-level modeling and optimization. We propose a new architecture that breaks RO into a series of simpler problems, new ne-grained predictive models, and novel optimization methods that exploit these models to make effective instance-level RO decisions well under a second. Evaluation using production workloads shows that our new RO system could reduce 37-72% latency and 43-78% cost at the same time, compared to the current optimizer and scheduler, while running in 0.02-0.23s

Effects of solar wind density and velocity variations on the Martian ionosphere and plasma transport - a MHD model study

Solar wind dynamic pressure, consisting solar wind density and velocity , is an important external driver that controls Martian plasma environment. In this study, a 3D magnetohydrodynamic model is applied to investigate the separate influences of solar wind density and velocity on the Martian ionosphere. The spatial distributions of ions in the dayside and near nightside ionosphere under different and are analyzed, as well as the ion transport process. We find that for the same dynamic pressure condition, the ionosphere extends to higher altitudes under higher solar wind density, indicating that a solar wind velocity enhancement event is more efficient at compressing the Martian ionosphere. A higher will result in a stronger induced magnetic field, shielding the Martian ionosphere, preventing the penetration of solar wind particles. For the same dynamic pressure, increasing (decreasing ) leads to a higher horizontal ion velocity, facilitating day-to-night plasma transport. As a result, the ionosphere extends farther into the nightside. Also, the ion outflow flux is larger for high , which may lead to a higher escape rate. Moreover, the strong crustal fields in the southern hemisphere also cause significant effect to the ionosphere, hindering horizontal ion transport. An additional outflow channel is also provided by the crustal field on the southern dayside, causing different responses of flow pattern between local and global scale while the solar wind condition is varied

Analysis of innovation management in German enterprises

In the drive towards economic globalization, companies are faced with both opportunities and challenges. As the global landscape changes, company and by extension countries increasingly grasp the level of importance innovation has to their survival and continued development. The element of innovation, within the business environment, has become the necessary condition for sustainable development of a country or nation. In the case of Germany, the authors acknowledge the country’s fascinating ability in innovation management; therefore have sought to gain a better understanding through a sampled analysis of German private enterprises. In the process, quantitative model and qualitative model were utilized together. On the one hand, a qualitative method is adopted to collect primary data. On the other hand, a quantitative process is used to collect secondary data. According to the data analysis of the sampled corporations and businesses, the indices of each factor vary across the different industries. Results also suggested that stronger enterprises give greater attention to innovation (factors) and therefore reap higher gains. In such companies, various rules and regulations are designed to stimulate the employees’ creativity; while communication is established across all parts of companies. Similarly, the company would be design on the basis of adapting different market strategies. Worthy of note is that companies in each industry treat technological innovation as an important element to their development. Such emphasis on the importance of innovation management is a vital factor that can aid in explaining why German enterprises have gained such success to date. Hence, companies in other world economies, including fast pace China should take note of the German companies and strengthen their own management structure regarding innovation

Three-dimensional urban thermal effect across a large city cluster during an extreme heat wave: observational analysis

Given extensive and rapid urbanization globally, assessing regional urban thermal effects (UTE) in both canopy and boundary layers under extreme weather/climate conditions is of significant interest. Rapid population and economic growth in the Yangtze River Delta (YRD) have made it one of the largest city clusters in China. Here, we explore the three-dimensional (3D) UTE in the YRD using multi-source observations from high-resolution automatic weather stations, radiosondes, and eddy covariance sensors during the record-setting heat wave (HW) of July–August 2013. It is found that the regional canopy layer UTE is up to 0.6–1.2°C, and the nocturnal UTE (0.7–1.6°C) is larger than daytime UTE (0.2–0.5°C) during the HW. The regional canopy layer UTE is enhanced and expanded northwards, with some rural sites contaminated by the urban influences, especially at night. In the boundary layer, the strengthened regional UTE extends vertically to at least 925 hPa (∼750 m) during this HW. The strengthened 3D UTE in the YRD is associated with an enlarged Bowen ratio difference between urban and non-urban areas. These findings about the 3D UTE are beneficial for better understanding of the thermal environment of large city clusters under HW and for more appropriate adaption and mitigation strategies

Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing

International audienceBig data processing at the production scale presents a highly complex environment for resource optimization (RO), a problem crucial for meeting performance goals and budgetary constraints of analytical users. The RO problem is challenging because it involves a set of decisions (the partition count, placement of parallel instances on machines, and resource allocation to each instance), requires multi-objective optimization (MOO), and is compounded by the scale and complexity of big data systems while having to meet stringent time constraints for scheduling. This paper presents a MaxCompute based integrated system to support multi-objective resource optimization via ne-grained instance-level modeling and optimization. We propose a new architecture that breaks RO into a series of simpler problems, new ne-grained predictive models, and novel optimization methods that exploit these models to make effective instance-level RO decisions well under a second. Evaluation using production workloads shows that our new RO system could reduce 37-72% latency and 43-78% cost at the same time, compared to the current optimizer and scheduler, while running in 0.02-0.23s

Third or fourth branchial pouch sinus lesions: a case series and management algorithm

Abstract Background The purpose of this study was to develop an effective management algorithm for lesions of third or fourth branchial sinuses. Study design Case series with chart review. Methods Data from patients who were identified as having third or fourth branchial pouch sinus lesions in a single institution between January 2014 and December 2018 were retrospectively collected. Results All 67 patients underwent fistulectomy. First, we classified the patients into five types based on their anatomic features. Then, we considered four optimized surgical methods and adopted the appropriate method with full consideration of the patient’s clinical characteristics. The great majority of cases occurred on the left side of the neck (68.7%) and most commonly presented as either a recurrent low-neck abscess or cutaneous discharging fistula with neck infection. Effective preoperative examination included administering contrast agent prior to a computed tomography (CT) scan and in-office laryngoscopy during the quiescent period of inflammation. Ultrasound was also very helpful in determining the presence of thyroiditis. The mean follow-up duration after excision of the lesion was 25.8 months. To date, only 1 (1.5%) recurrence and no obvious complications have been observed. Conclusion Refining fistula subtypes and adopting corresponding treatment measures can reduce the recurrence rate and improve curative effects. We propose and advocate this treatment algorithm for all third and fourth branchial pouch lesions

Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum $p_\mathrm{T}$ and rapidity $y$. The measurement is performed using proton-proton collision data at $\sqrt{s}$ = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb$^{-1}$. The jets are reconstructed with the anti-$k_\mathrm{T}$ algorithm using a distance parameter of $R$ = 0.4, within the rapidity interval $\lvert y\rvert$$\lt$ 2, and across the kinematic range 0.06 $\lt$$p_\mathrm{T}$$\lt$ 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling $\alpha_\mathrm{S}$

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at sNN\sqrt{s_\mathrm{NN}} = 5.02 TeV

Two-particle Bose-Einstein momentum correlation functions are studied for charged-hadron pairs in lead-lead collisions at a center-of-mass energy per nucleon pair of $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV. The data sample, containing 4.27$\times10^{9}$ minimum bias events corresponding to an integrated luminosity of 0.607 nb$^{-1}$, was collected by the CMS experiment in 2018. The experimental results are discussed in terms of a L\'evy-type source distribution. The parameters of this distribution are extracted as functions of particle pair average transverse mass and collision centrality. These parameters include the L\'evy index or shape parameter ($\alpha$), the L\'evy scale parameter ($R$), and the correlation strength parameter ($\lambda$). The source shape, characterized by $\alpha$, is found to be neither Cauchy nor Gaussian, implying the need for a full L\'evy analysis. Similarly to what was previously found for systems characterized by Gaussian source radii, a hydrodynamical scaling is observed for the L\'evy $R$ parameter. The $\lambda$ parameter is studied in terms of the core-halo model.Comment: Submitted to Physical Review C. All figures and tables can be found at http://cms-results.web.cern.ch/cms-results/public-results/publications/HIN-21-011 (CMS Public Pages