AN ONLINE REVIEWS INFORMATION FUSION METHOD AND ITS APPLICATION TO PUBLIC PROPERTY SERVICE QUALITY EVALUATION

With the rapid development of computer networking technology, people pay more and more attention to the role of online reviews in management decision making. The existing methods of online reviews fusion are limited to rational decision-making behavior, which does not accord with the characteristics of evaluators’ behavior characteristics in the real environment. In order to solve the online reviews fusion problem based on bounded rational behavior which is closer to the reality of property service quality evaluation, the multi-index and multi-scale (MIMS) method is extended into the generalized form, the online reviews are quantified by using the adverb structure scaling method, and an online reviews fusion method based on the improved TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) model is proposed. The feasibility and effectiveness of the proposed method are verified by an example analysis of property service quality evaluation. The research results are as follows: the adverb structure scaling method is suitable for a large number of online reviews processing, the proposed method improves the efficiency of online reviews information fusion, and it is feasible and effective to evaluate property service quality based on the bounded rationality of evaluator’s behavior.

High-energy bow tie multi-pass cells for nonlinear spectral broadening applications

Multi-pass cells have emerged as very attractive tools for spectral broadening and post-compression applications. We discuss pulse energy limitations of standard multi-pass cells considering basic geometrical scaling principles and introduce a novel energy scaling method using a multi-pass cell arranged in a bow tie geometry. Employing nonlinear pulse propagation simulations, we numerically demonstrate the compression of 125mJ, 1 ps pulses to 50 fs using a compact 2 m long setup and outline routes to extend our approach into the Joule-regime.

Evaluating Scaling Frameworks for Multiscale Geomorphometric Analysis

Multiscale methods have become progressively valuable in geomorphometric analysis as data have become increasingly detailed. This paper evaluates the theoretical and empirical properties of several common scaling approaches in geomorphometry. Direct interpolation (DI), cubic convolution resampling (RES), mean aggregation (MA), local quadratic regression (LQR), and an efficiency optimized Gaussian scale-space implementation (fGSS) method were tested. The results showed that when manipulating resolution, the choice of interpolator had a negligible impact relative to the effects of manipulating scale. The LQR method was not ideal for rigorous multiscale analyses due to the inherently non-linear processing time of the algorithm and an increasingly poor fit with the surface. The fGSS method combined several desirable properties and was identified as an optimal scaling method for geomorphometric analysis. The results support the efficacy of Gaussian scale-space as a general scaling framework for geomorphometric analyses.

Hölder regularity for degenerate parabolic equations with variable exponents

In this paper, we discuss a class of degenerate parabolic equations with variable exponents. By using the Steklov average and Young's inequality, we establish energy and logarithmicestimates for solutions to these equations. Then based on the intrinsic scaling method, we provethat local weak solutions are locally continuous.

Investigation on Damping Characteristics of Hydrostatic Bearing Film by Using Scale Method

The resonant peaks can be suppressed by damping, those effects is dependent on damping ratio of system. In this paper, we propose a scaling method to evaluate the damping ratio of hydrostatic bearings for the data from model test. This method fits specifically for the overdamping of all hydrostatic bearing. This is direct and the easiest method to obtain the damping characteristics of oil film for the lowest band before the first resonant peak. The frequency responses of acceleration per force for a single-degree-of-freedom mass-spring-damper model is used to generate the evaluation scales for the damping ratios of the modal test results of worktable mounting on hydrostatic bearing. The case study for experimental results of the impact response are evaluated for damping ratio of the hydrostatic film by these method. Furthermore, using this scaling method, the influences of three types of compensations on the damping ratio of a hydrostatic bearing are compared. The results reveal that the constant flow has the largest damping ratio, and the capillary restrictor has the smallest one.

Efficiency Scaling - Influence of Reynolds and Mach Number on Fan Performance

The efficiency, pressure ratio and shaft power of a fan depends on type, size, working medium and operating condition. For acceptance tests, a dissimilarity in Reynolds number, Mach number, relative roughness and relative blade tip clearance of the scaled model and prototype is unavoidable. Hence, the efficiency differs between model and prototype. This difference is quantified by scaling methods. This paper presents a validated and physics based, i. e. reliable scaling method for the efficiency, pressure ratio and shaft power of axial and centrifugal fans operating at subsonic conditions. The method is validated using test results gained on standardized test rigs for different fan types, sizes and operating conditions. For all scenarios the presented scaling method provides a much reduced scaling uncertainty compared to the reference method described in ISO 13348.

A Fine-Grained Horizontal Scaling Method for Container-Based Cloud

The container scaling mechanism, or elastic scaling, means the cluster can be dynamically adjusted based on the workload. As a typical container orchestration tool in cloud computing, Horizontal Pod Autoscaler (HPA) automatically adjusts the number of pods in a replication controller, deployment, replication set, or stateful set based on observed CPU utilization. There are several concerns with the current HPA technology. The first concern is that it can easily lead to untimely scaling and insufficient scaling for burst traffic. The second is that the antijitter mechanism of HPA may cause an inadequate number of onetime scale-outs and, thus, the inability to satisfy subsequent service requests. The third concern is that the fixed data sampling time means that the time interval for data reporting is the same for average and high loads, leading to untimely and insufficient scaling at high load times. In this study, we propose a Double Threshold Horizontal Pod Autoscaler (DHPA) algorithm, which fine-grained divides the scale of events into three categories: scale-out, no scale, and scale-in. And then, on the scaling strength, we also employ two thresholds that are further subdivided into no scaling (antijitter), regular scaling, and fast scaling for each of the three cases. The DHPA algorithm determines the scaling strategy using the average of the growth rates of CPU utilization, and thus, different scheduling policies are adopted. We compare the DHPA with the HPA algorithm under different loads, including low, medium, and high. The experiments show that the DHPA algorithm has better antijitter and antiload characteristics in container increase and reduction while ensuring service and cluster security.