Statistical Process Control for the Fairness of Network Resource Distribution

The purpose of this research is to develop a statistical method to monitor the fairness of network resource distribution. The newly developed fairness score function allows users to have the same or different priority levels. Especially, this function possesses all the necessary properties required as a quality characteristic for the purpose of statistical process control. The main objective is to find the critical values for the statistical test. Monte Carlo simulation is used to find the critical values. When the users have the same priority level, a table of the critical values is given for different sample sizes and different significance levels. When the users have different priority levels, it is difficult to generate a similar table since the users’ priority levels vary. Therefore, the critical values are computed for given priority levels. In both cases, an example is given to demonstrate the approach developed in this study

Coupling Heat Transfer and Fluid Flow Solvers for Multi-Disciplinary Simulations

The purpose of this study is to build, test, validate, and implement two heat transfer models, and couple them to an existing fluid flow solver, which can then be used for simulating multi-disciplinary problems. The first model is for heat conduction computations, the other one is a quasi-one-dimensional cooling channel model for water-cooled jacket structural analysis. The first model employs the integral, conservative form of the thermal energy equation, which is discretized by means of a finite-volume numerical scheme. A special algorithm is developed at the interface between the solid and fluid regions, in order to keep the heat flux consistent. The properties of the solid region materials can be temperature dependent, and different materials can be used in different parts of the domains, thanks to a multi-block gridding strategy. The cooling channel flow model is developed by using uasi-one-dimensional conservation laws of mass, momentum, and energy, taking into account the effects of heat transfer and friction. It is possible to have phase changes in the channel, and a mixture model is applied, which allows two phases to be present, as long as they move at the same bulk velocity and vapor quality does not exceed relatively small values. The coupling process of both models (with the fluid solver and with each other) is handled within the Loci system, and is detailed in this study. A hot-air nozzle wall problem is simulated, and the computed results are validated with available experimental data. Finally, a more complex case involving the water-cooled nozzle of a Rocket Based Combined Cycle(RBCC) gaseous oxygen/gaseous hydrogen thruster is simulated, which involves all three models, fully coupled. The calculated temperatures in the nozzle wall and at the cooling channel outlet compare favorably with experimental data

A Trustworthy Approach to the Adaptive Composition of GeoServices

AbstractFor the automatic generation of geographical information service chain, this article defines the quality of service (QoS) metrics based on service response time, reliability, and matching degree, among others, and the error propagation model. Based on the semantic matching and trustworthiness assessment of the geographical information services, this article proposes a trustworthy adaptive composition framework and implementation algorithm for geographical information services, ensuring the composition of service chains to better meet various QoS constraints. The effectiveness of this approach is proven in the simulation experiments

Searching for a DNAzyme version of the leadzyme

The final publication is available at Springer via http://dx.doi.org/10.1007/s00239-015-9702-zThe leadzyme refers to a small ribozyme that cleaves a RNA substrate in the presence of Pb2+. In an optimized form, the enzyme strand contains only two unpaired nucleotides. Most RNA-cleaving DNAzymes are much longer. Two classical Pb2+-dependent DNAzymes, 8–17 and GR5, both contain around 15 nucleotides in the enzyme loop. This is also the size of most RNA-cleaving DNAzymes that use other metal ions for their activity. Such large enzyme loops make spectroscopic characterization difficult and so far no high-resolution structural information is available for active DNAzymes. The goal of this work is to search for DNAzymes with smaller enzyme loops. A simple replacement of the ribonucleotides in the leadzyme by deoxyribonucleotides failed to produce an active enzyme. A Pb2+-dependent in vitro selection combined with deep sequencing was then performed. After sequence alignment and DNA folding, a new DNAzyme named PbE22 was identified, which contains only 5 nucleotides in the enzyme catalytic loop. The biochemical characteristics of PbE22 were compared with those of the leadzyme and the two classical Pb2+-dependent DNAzymes. The rate of PbE22 rises with increase in Pb2+ concentration, being 1.7 h−1 in the presence of 100 μM Pb2+ and reaching 3.5 h−1 at 500 µM Pb2+. The log of PbE22 rate rises linearly in a pH-dependent fashion (20 µM Pb2+) with a slope of 0.74. In addition, many other abundant sequences in the final library were studied. These sequences are quite varied in length and nucleotide composition, but some contain a few conserved nucleotides consistent with the GR5 structure. Interestingly, some sequences are active with Pb2+ but none of them were active with even 50 mM Mg2+, which is reminiscent of the difference between the GR5 and 8–17 DNAzymes.University of Waterloo || Ontario Ministry of Research & Innovation || Natural Sciences and Engineering Research Council |

2-{2,6-Bis[bis(4-fluorophenyl)methyl]-4-chlorophenylimino} -3-aryliminobutylnickel(II) bromide complexes: Synthesis, characterization, and investigation of their catalytic behavior

The series of 2-{2,6-bis[di(4-fluorophenyl)methyl]-4-chlorophenylimino}-3- aryliminobutane derivatives (L1-L5) and their nickel(II) dibromide complexes (Ni1-Ni5) were synthesized, and all organic compounds were fully characterized by the Fourier transform infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopy and by elemental analysis, while the nickel complexes were characterized by FT-IR spectroscopy, elemental analysis, as well as by single-crystal X-ray diffraction for two representative examples, namely Ni1 and Ni4. A distorted tetrahedral geometry was observed for these four-coordinate nickel complexes. Upon the activation with either Methylaluminoxane or modified methylaluminoxane as co-catalyst, all nickel complex precatalysts showed very high activity toward ethylene polymerization with activities of up to 10 7 g(PE)·mol -1 (Ni)·h -1 , and afforded highly branched polyethylene with a bimodal distribution. © 2014 Elsevier B.V

Control Strategy and Simulation of the Regenerative Braking of an Electric Vehicle Based on an Electromechanical Brake

The electromechanical brake (EMB) has very broad prospects for application in the automotive industry, especially in small- and medium-sized vehicles. To extend the endurance range of pure electric vehicles, a regenerative braking control strategy combined with an electromechanical brake model is designed that divides the braking modes according to the braking intensity and controls the regenerative braking force based on fuzzy theory. Considering a front-wheel-drive pure electric vehicle equipped with a floating clamp disc electromechanical brake as the research object, a structural form of electromechanical brake is proposed and a mathematical model of the electromechanical brake is built. Combined with the relevant influencing factors, the regenerative braking force is limited to a certain extent, and the simulation models of the electromechanical brake and the regenerative braking force distribution control strategy are built in MATLAB/Simulink. Co-simulation in MATLAB and AVL CRUISE software is conducted. The simulation results demonstrate that the braking energy recovery rate of the whole vehicle with the fuzzy control strategy put forward in this paper is 28.9% under mild braking and 34.11% under moderate braking. The control method substantially increases the energy utilization rate

Transformation of reverse marketing model for electrical appliances based on Markov chain optimization with information technology support

Inverters are widely used in the military, industrial production and defense fields as current conversion devices that convert direct current to alternating current. If the inverter fails, it can cause damage to other equipment, resulting in financial losses and, in extreme cases, compromising the safety of users. In this study, by integrating neural networks, the input signals of inverters are quickly converted to Fourier spectrum amplitudes, and from fault signals (such as load phase voltage) to feature vectors. In order to realize automatic extraction and fault detection of inverters, an optimization method is used to determine the appropriate number of nodes in the hidden layer of complex neural networks. The ability to efficiently allocate limited computing, storage, and network resources to meet user demand for services; Continuously optimize quality of service (QoS), including reducing latency, improving bandwidth, and increasing reliability. These problems directly affect the performance and user experience of MEC systems. By studying these issues and proposing corresponding solutions, we aim to improve the performance of MEC systems and provide higher quality services. The accuracy of defect diagnosis can reach higher than 99%, and the method has a high remission rate, demonstrating its effectiveness and benefits

Coreset Selection with Prioritized Multiple Objectives

Coreset selection is powerful in reducing computational costs and accelerating data processing for deep learning algorithms. It strives to identify a small subset from large-scale data, so that training only on the subset practically performs on par with full data. When coreset selection is applied in realistic scenes, under the premise that the identified coreset has achieved comparable model performance, practitioners regularly desire the identified coreset can have a size as small as possible for lower costs and greater acceleration. Motivated by this desideratum, for the first time, we pose the problem of "coreset selection with prioritized multiple objectives", in which the smallest coreset size under model performance constraints is explored. Moreover, to address this problem, an innovative method is proposed, which maintains optimization priority order over the model performance and coreset size, and efficiently optimizes them in the coreset selection procedure. Theoretically, we provide the convergence guarantee of the proposed method. Empirically, extensive experiments confirm its superiority compared with previous strategies, often yielding better model performance with smaller coreset sizes