β-Naphthyl aceate was synthesized with acetic anhydride and naphthol using aminosulfonic acid as catalyst.The yield of β-naphthyl acetate was 97.8% under the optimum conditions: β-naphthlol 7.2 g(0.05 mol),acetic anhydride 6 mL(0.06 mol),aminosulfonic acid 1.0 g,reaction time 30 min,80 ℃.The reaction time was short and the catalyst could be recovered and reused for more than 4 times.
In view of the existing seismic signal analysis model there are some problems is Analysis of the result is bad, the accuracy is not high. This paper puts forward an algorithm based on discrete wavelet and generalized the ICA model of seismic signal analysis. First for continuous Wavelet transform exists redundant of problem, on standard small wave transform algorithm of transform domain in the variable for discrete of, and building based on discrete optimization Wavelet algorithm of earthquake signal drop noise model, then in used Discrete Wavelet transform algorithm on signal for drop noise Hou, used ICA algorithm on its for blind separation optimization, and introduced general Gaussian distribution model, on ICA algorithm for Diego generation operation of optimization. Simulation experiments show that presented Discrete Wavelet transform algorithm relative to the standard Wavelet has better noise reduction ability, and is based on discrete wavelets and generalized seismic signal analysis of ICA algorithm model shows good results.
<p>Proactively caching content at the network edge is particularly effective in high-mobility vehicular networks, where intermittent connection is the major challenge for seamless content transmission. The objective of this paper is to achieve proactive caching in vehicular networks by mobility prediction, specifically by predicting the next roadside unit (RSU) for a vehicle with reinforcement learning techniques. The paper proposes two proactive caching algorithms based on multi-armed bandit (MAB) learning, non-contextual MAB and contextual MAB, respectively. This paper fills the void in the literature regarding the application of MAB learning to mobility-prediction based proactive caching. Their feasibility, superiority, and applicability are evaluated with simulation in two modern cities: Las Vegas, USA with a grid road layout, and Manchester, UK with a more historical layout. Additionally, this paper is the first that proposes to investigate the uncertainty associated with proactive caching systems in the form of entropy with a specifically extended Subjective Logic framework, in order to provide an insight into the underlying link between prediction accuracy and uncertainty. </p>
This paper applies an adaptive method for regulating the proportional resonance (PR) controller for frequency and phase synchronization in 500 kW photovoltaic grid-connected inverter. First, this paper determines the mathematical model of the three-phase voltage source inverter (VSI) in the coordinate system, and presents an automatic way for parameter tuning in proposed PR controller framework. Second, the frequency variation is detected via minimizing the error signal using a frequency locked loop (FLL) mechanism which consists of a resonant adaptive filter and a perturbation-based extreme seeking (PES) method. Unlike the widely used proportional-integral (PI) controller and phase locked loop (PLL)-based frequency detection, the proposed adaptive PR (APR) controller shows high performance in items of steady-state error of current, frequency fluctuation tracking, phase shift error, and harmonic order compensation. At last, the simulation and experimental results demonstrate that the photovoltaic grid-connected inverter embedded with APR controller realizes the static-free tracking adjustment more quickly, and has stronger grid voltage anti-disturbance capability than the traditional PI-based voltage/current loop applications.
<p>Proactive edge caching has been regarded as an effective approach to satisfy user experience in mobile networks by providing seamless content transmission and reducing network delay. This is particularly useful in rapidly changing vehicular networks. This paper addresses the proactive edge caching (at roadside unit (RSU)) problem in vehicular networks by mobility prediction, i.e., next RSU prediction. Specifically, the paper proposes a \textit{Hybrid cMAB Proactive Caching System} that implements two parallel online reinforcement learning-based mobility prediction algorithms and allows RSUs to adaptively finalize their predictions to identify as proactive caching nodes. The two parallel prediction algorithms are based on <em>Contextual Multi-armed bandit</em> (cMAB) learning, called <em>Dual-context cMAB</em> and <em>Single-context cMAB</em>. The hybrid system is further developed into two variants: <em>Vehicle-Centric</em> and <em>RSU-Centric</em>. In addition, the paper also conducts comprehensive simulation experiments to evaluate the prediction performance of the proposed hybrid system. They include three traffic scenarios: <em>Commuting traffic</em>, <em>Random traffic</em> and <em>Mixed traffic</em> in Las Vegas, USA and Manchester, UK. With the different road layouts in the two urban areas, the paper aims to generalize the application of the system. Simulation results show that the hybrid Vehicle-Centric system can reach nearly 95% cumulative prediction accuracy in the Commuting traffic scenario and outperform the other methods used for comparison by reaching nearly 80% accuracy in Mixed traffic scenario. Even in the completely Random traffic scenario, it also guarantees a minimum accuracy of nearly 60%.</p>
Iso-amyl acetate was synthesized with ammonium ceric sulfate as catalyst using partially neutralized acetic acid and iso-amyl alcohol.The influence of molar ratio of iso-amyl alcohol to acetic acid,catalyst,the reaction time was discussed.The results show ammonium ceric sulfate is an excellent catalyst.The yield of iso-amyl acetate could reach 91.4% under the molar ratio of iso-amyl alcohol to acetic acid of 1.8∶1,ammonium ceric sulfate 1.5 g,the reaction time of 3.0 h.
cyclohexanone 1,2-propanediol ketal(Ⅰ)was synthesized from cyclohexanone(Ⅱ) and 1,2-propanediol(Ⅲ) in the presence of aminosulfonic acid(Ⅳ).Factors influencing the product yield were discussed and the best reaction conditions were found.Experimental result showed that Ⅳ is an excellent catalyst.With n(Ⅱ)∶n(Ⅲ)=1∶1.5,w(Ⅳ)=1 g,the carrying water reagent is 15 mL,and the reaction time=60 min,yield of Ⅰ can reach 71.15%.
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