一种新型有机非线性光学材料的光折效应及其产生机理

本文介绍了一种新近研制的光折聚合物。实验表明，除去吸收和反射，入射光束经聚合物后的第一布拉格衍射效率高达８６％，材料也显示出双光束耦合的净增益高于２４０ｃｍ＾－１。这些结果表明，这种新型研制的光折聚合物材料是替代无机光折晶体的实用材料。     

改善准分子激光光强分布的一种方法

介绍了一种改善准分子激光输出光束光强均匀性的新方法，给出了实验结果和简要的分析。     

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。     

高校资产管理系统的设计与研究

设计了适合衢州职业技术学院固定资产日常管理工作的资产管理系统.对该系统作了需求分析和详细设计,采用了ASP.NET框架技术和SQL Server后台数据库相结合的设计方法.系统基本实现了资产的登记、审核、查询、变更、统计、打印报表、上报数据等功能,有效地解决了资产管理工作的数据混乱、不准确、处理流程不规范等问题,有效地提高了管理人员的工作效率.     

计算机网络技术的发展现状和趋势分析

文章首先概述了计算机网络发展的历程与现状,并分析当今计算机网络发展中存在的一些问题,然后对计算机网络的发展趋势及策略进行总结分析,为当今计算机网络的良性发展出谋划策。     

基于呼叫中心的客户关系管理系统服务流程优化研究

针对钢铁企业物流公司客户关系管理现状,及其客户服务请求处理流程中的不足,提出了基于呼叫中心的钢铁企业最优化客服请求处理流程及其技术实现,给出了平台功能设计,探讨了平台实现的关键技术。该系统充分满足客户满意度以及服务请求处理的及时性,快速性,确切性,可操作性等方面要求。     

阿姆河流域耕地变化及水土匹配特征分析

基于中亚阿姆河流域4个分区1990—2015年间土地利用变化和水资源等数据,运用耕地变化速率、洛伦兹曲线和基尼系数法以及水土资源匹配系数对阿姆河流域耕地变化和水土匹配状况进行了综合分析。结果表明:1990—2015年阿姆河流域耕地以146.74 km²/a的速度在扩张,且各时期、各分区扩张的速度不同;在不考虑咸海来水不断减少、生态持续恶化的前提下,绿洲区匹配状况属比较公平和相对合理状况;阿姆河流域水土资源空间分布存在明显的错位现象;全流域生态用水被农业用水严重挤占,阿姆河流域灌溉面积、灌溉用水量成为影响咸海水量及面积变化的重要因素,是一种不可持续的用水方式。     

北京安河泄洪闸金属结构安全检测与评价

水闸安全运行,会受到水工金属结构安全性状影响.京密引水渠安河泄洪闸已投入运行54年.为保障水闸运行安全,需对其金属结构进行全面的安全检测.文章采用多种检测手段对安河泄洪闸金属结构开展现场检测,对结构病害进行梳理,对金属结构的安全状态进行综合评价,为水闸安全运行提供技术支撑.     

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.