Service-oriented smart home applications: composition, code generation, deployment, and execution

A smart home usually has a variety of devices or home appliance, instead of designing software for a specific home, this paper proposes a service-oriented framework with a set of ontology systems to support service and device publishing, discovery of devices and their services, composition of control software using existing control services that wrap devices, deployment, and execution of the composed service in an computing environment, monitoring the execution, and recovery from device failure. The ontology systems specify semantic information about devices, services, and workflows used in various smart home, and users can compose and recompose services for their specific needs. New devices, workflows, and services can be added into ontology. Most of the steps in this process can be automated including code generation. For example, service composition will be carried out in three steps: abstract workflow design, function construction, and device discovery, and different codes can be generated for different computing platforms such as Java and Open Services Gateway initiative environments. In this way, a variety of smart home can be constructed rapidly using the framework by discovery and composition using existing services and workflows. This paper illustrates this framework using a media control example to illustrate the ontology, discovery, composition, deployment, execution, monitoring, and recovery.     

信息技术课堂有效管理的策略探索

随着社会信息化的发展,信息素养日益成为信息社会公民素养不可或缺的组成部分,对课堂管理提出了更高的要求。信息技术课程具有独特的学科特点以及特有的教学环境,给课堂的管理带来了困难和不便。从建立课堂常规、固定上机位置、设置门禁门槛等方面,探索了信息技术课堂有效管理的方法。     

济南市1972─2016年降水特性

运用线性滑动平均、Mann-Kendall非参数趋势检验、Sen′s坡度、小波分析及多元线性回归方法,选取济南市24个降水站点45年(1972—2016年)逐日降水资料,分析了济南市在年和季节尺度上的降水特征以及降水量的决定性影响因素。结果表明:年降水量以8.23mm/(10a)的速率增加,且呈现出丰枯交替的变化周期,最大主周期为10a;降水量主要集中在夏季,占全年降水量的64.5%,冬季降水占比最小,占全年降水量的3.4%,春、夏和冬季降水具有不显著增加趋势,秋季的降水量具有不显著下降趋势;降水量的年际、春夏季变化主要受降水强度变化的影响;秋冬季变化则主要受降水频率变化的影响。     

Stock Price Forecasting: An Echo State Network Approach

Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean absolute error (MAE) was used to present the accuracy results. The MAEs of the data forecast by ESN were 0.024, 0.024, and 0.025, which were, respectively, 0.065, 0.007, and 0.009 less than those of LSTM. In terms of convergence, ESN has a reservoir state-space structure, which makes it perform faster than other models. Root-mean-square error (RMSE) was used to present the convergence time. In our experiment, the RMSEs of ESN were 0.22, 0.27, and 0.26, which were, respectively, 0.08, 0.01, and 0.12 less than those of LSTM. In terms of network structure, ESN consists only of input, reservoir, and output spaces, making it a much simpler model than the others. The proposed ESN was found to be an effective model that, compared to others, converges faster, forecasts more accurately, and builds time-series analyses more easily.     

Activity of Bromelain with Cationic Surfactants and the Correlation with the Change of 1H NMR Signals

This study observed the activities of bromelain in the presence of various cationic surfactants at different temperatures and the conformational changes in bromelain by ¹H NMR spectroscopy. We found that the bromelain activity was enhanced by tens to hundreds of micromoles per liter of the surfactant. In the presence of the surfactants, bromelain exhibited good tolerance to a range of substrate temperatures and its thermal stability was also increased. The ¹H NMR experiments indicated that when the temperature was increased from 25.0 to 45.0 °C, the protons of bromelain having chemical shifts (δ) between 3.7 and 5.2 ppm moved upfield, while those having δ values between 3.2 and 3.7 ppm moved downfield. In the bromelain/cationic surfactant mixture, the values of δ for the protons in both bromelain and the cationic surfactants decreased, accompanied by the broadening of the half-peak width of the surfactant protons. These results indicated that both increasing temperature and adding a cationic surfactant made the bromelain chain more flexible and hence, increased the bromelain activity. To the best of our knowledge, this was the first time that the relationship between the protein activity and the ¹H NMR data was expounded.     

不同基质配比对银毛野牡丹扦插的影响

银毛野牡丹是优良的园林观赏性植物,但是繁殖有性结实率低。通过为期30天的扦插试验,对比不同基质（原土、草炭土、蛭石、珍珠岩）配比对银毛野牡丹插穗生长的影响,分析插穗生根时间、生根数目、最长根长、生根率、生长状态以及基质变化,找出适合其生长发育的优良基质,为银毛野牡丹的繁殖提供技术支撑。研究表明：试验组T8（原土：细沙：草炭土：蛭石：珍珠岩=1：1：2：1：1）的插穗生根率、最长根长、插穗长势为最佳,试验组T2（草炭土）效果次之,在条件有限的情况下可以作为备用方案以供生产所需。     

不同溶液浓度下气液两相介质阻挡放电特性实验及仿真研究

采用实验与仿真结合的方式研究高频激励下柱-板电极结构在不同溶液浓度条件下的放电特性.通过实验方式测量气液两相介质阻挡放电(DBD)的放电特性,得到了不同溶液浓度和外加电压幅值条件下的电学特性和发光特性.在此基础上,结合气液两相放电物理过程,建立了与本实验对应的等效电路模型,通过实验与电场仿真结合的方式确定了模型参数,并在Simulink中建立电路仿真模型.通过仿真得到不同浓度和电压幅值下的电压电流波形及Lissajous图形,经仿真与实验结果对比,验证了仿真模型的正确性.利用上述模型进一步提取实验中无法直接获取的放电参量,如气隙电压、液相电压、放电通道电流及能量占比等.结果表明:溶液浓度对于实验得到的回路电压电流波形及发光特性影响不显著,然而通过仿真发现,气相及液相消耗能量的占比受其影响较大.随着溶液浓度的升高,尽管气相和液相功率都增大,但液相功率增加速度更快,导致液相能量占比显著增加,而通过提升激励源电压可提高气相能量占比,从而在一定程度上抑制液相获得的能量.     

Energy and economic analysis of a hydrogen and ammonia co-generation system based on double chemical looping

In this work, a model of hydrogen production by double chemical looping is introduced. The efficiency benefit obtained was investigated. The chemical looping hydrogen generation unit is connected in series to the downstream of a chemical looping gasification unit as an additional system for 100 MW·h coal gasification, with the function of supplementary combustion to produce hydrogen. Using Aspen Plus software for process simulation, the production of H_2 and N_2 in the series system is higher than that in the independent Chemical looping gasification and Chemical looping hydrogen generation systems, and the production of hydrogen is approximately 25.63% and 12.90% higher, respectively; The study found that when the gasification temperature is 900 °C, steam-carbon ratio is 0.84 and oxygen-carbon ratio is 1.5,the hydrogen production rate of the system was the maximum. At the same time, through heat exchange between logistics, high-pressure steam at 8.010×10~4 kg·h~(-1) and medium-pressure steam at 1.101×10~4 kg·h~(-1) are generated, and utility consumption is reduced by 61.58%, with utility costs decreasing by 48.69%. An economic estimation study found that the production cost of ammonia is 108.66 USD·(t NH_3)~(-1). Finally, cost of equipment is the main factors influencing ammonia production cost were proposed by sensitivity analysis.     

3D Printing Conductive Composites with Poly(ionic liquid) as a Noncovalent Intermedia to Fabricate Carbon Circuits

In this study, a kind of imidazole type poly(ionic liquid) ([PEP-MIM]Cl) is synthesized, which can disperse carbon effectively. [PEP-MIM]Cl is used as an intermediate to coat carbon on the poly(acrylic acid)(PAA-co-MBA) via ion exchange to obtain conductive polymer composite (CPC). A series of characterizations are performed. Experiments show that carbon can be coated on the PAA-co-MBA uniformly, and compared with using carbon as filler, this method requires less carbon to achieve good conductive performance. The carbon layer on the polymer's surface is enriched via the swelling-shrinking properties of PAA-co-MBA according to the SEM images. Furthermore, in combination with 3D printing technology, PAA-co-MBA can be designed into different shapes to achieve various functions such as pressure-sensing element. Finally, a new type of CPC named carbon clad polymeric laminate (CCPL) is prepared by using the carbon coating method and 3D printing technology. It has the potential to replace copper clad laminate (CCL) and printed circuit board (PCB), to a certain extent. This technology expands the preparation method and application of the CPC such as flexible and wearable conductive fabrics.     

旋转填料床精馏过程流体力学性能研究

在对旋转填料床精馏特性研究的基础上,以塑料多孔板为填料,乙醇-水为体系,在全回流操作条件下,进一步研究了气相动能因子F、超重力因子β和回流量L对旋转填料床流体力学特性的影响,证明了旋转填料床的低耗能特性。