Design and Implementation for the Elevator Public Service Platform Base on Internet of Things

将物联网安全监控应用于电梯,为人们日常生活带来极大便利和安全保障。本论文通过运用软件工程的基本理论,分析和设计了基于物联网技术的电梯公共服务平台的功能与模块。在阐述平台建设意义的基础上,分析了平台的功能性和非功能性需求,并以此为依据建立平台架构、划分平台功能模块并简要论述平台建设所运用到的关键技术。Security Monitoring based on IOT was applied to the elevator-equipment, it provides great convenience and security for People's Daily life.By using the basic theory of Software Engineering, it mainly analyzes and designs functions and modules for the Elevator Public Service Platform Base on IOT in the paper.On the basis of stating the importance of platform construction, it focuses on expounding the function and the non-function requirements.Then the platform structure is established and different functional modules are divided.And it makes simple description about related development technologies in the end of the paper.国家物联网重大应用示范区厦门市物联网示范应用项

甲烷空气催化部分氧化制合成气与含氮合成气制二甲醚的研究

采用常规浸渍法制备了经镧和镁改性的镍基催化剂，以铜锌铝甲醇合成催化剂和HZSM－5分子筛通过机械混合制造了二甲醚合成催化剂，采用固定床流动反应色谱装置研究了甲烷空气催化部分氧化制合成气的催化性能，同时开展了以含氮合成气制备二甲醚的研究，结果说明，镍基催化剂对甲烷空气部分氧化制合成气在常压下具有高的转化率，随压力升高，随压力升高，转化率明显下降，并且催伦剂严重积炭，通过向反应体系添加H2O和CO2可以提高加压条件下的CH4转化率并抑制催化剂积炭，还可获得n(H2)/n(CO)接近2的合成气，满足合成二甲醚的要求，采用含氮合成气制备二甲醚，在压力7．0MPa，空速1000h^-1条件下，催化剂连续使用200h性能基本稳定，CO转化率在93％左右，DME选择性在77％左右，DME收率在72％左右

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies