高职院校顶岗实习监控与管理平台设计与实现

顶岗实习是高职院校教学计划的重要组成部分,顶岗实习周期一般为一年。传统的顶岗实习管理模式以填写纸质顶岗实习日志为主。根据高职院校对顶岗实习学生管理的需求,设计开发了基于Web的高职院校顶岗实习监控与管理平台,克服了地域和时间的限制。     

面向船舶运动控制仿真的网络数据库系统

构建一个基于JSP+JavaBean的B/S体系结构的船舶运动的网络数据库,给船舶仿真提供一个与用户交互的平台,使用SQL Server 2005,结合Ajax+JavaScript技术,主要采集模拟船舶运动仿真过程所需的参数、显示船舶运动状态参数以及运行轨迹,并可以方便地对船舶、操舵员(用户)等进行信息管理.     

数据库压缩功能实现方法

在VFP开发的应用中利用第三方压缩软件,实现对数据的压缩和解压缩操作。通过WinRAR压缩软件的一般调用方法,编程实现了对选择的任意数据文件进行压缩和解压缩的操作。     

网上购物系统数据库与数据仓库的比较分析

比较了数据库及数据仓库,通过网上购物系统平台的研究,分析了两者在数据信息处理中的异同,从而达到让网上购物更加完善、更加便捷地为用户服务的目的。     

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.     

中医方剂与图集的转换方法

中药复方数据挖掘研究是将我国丰富的中药信息资源和现代最新信息技术相结合的重要内容,它意味着基于中医理论,利用知识发现技术,对传统中药新药、中医组方理论及规律、中药作用机制、有效成分构效关系等多个方面进行全面、系统的研究。图作为一种经典的数据结构,被广泛用于复杂数据结构分析与建模。文章探讨了图建模技术并实现了中医方剂与图集的转换。     

海量数据库迁移与升级

目前数据库中数据越来越多,应用对数据库在线时间的要求也越来越高,使得数据库迁移和数据库升级成为了一件非常困难的事情.为此,介绍了几种迁移和升级的方法,用以实现以尽可能少的停机时间对TB级数据库完成数据库的迁移和升级.     

Hash算法在数据库安全中的应用

介绍了Hash算法在数据库加密系统中的应用,包括在用户身份验证中的应用,在数据库完整性认证中的应用,以及在密文检索中的应用。     

Electronic locking devices based on microcontrollers and chaotic maps using Model-Matching Control

In this work a real-time communication system using Arduino® microcontrollers, applied to electronic locking devices, is implemented. Model-Matching Control is used to achieve synchronization between transmitter and receiver Arduino® microcontrollers using only one transmission channel. Model-Matching Control is fed with dynamics from both Arduinos. Transmitter Arduino® is used also to generate in real-time an encrypted chaotic code key based on the Chen map. Receiver Arduino® recover in real-time the chaotic code key that is a binary signal key of an electronic locking device and where wireless communication is made between the two Arduinos using Bluetooth modules. System evaluation in terms of performance, randomness, and time complexity, are shown, as well as experimental results and some discussions are presented.     

Towards sustainable industry 4.0: A green real-time IIoT multitask scheduling architecture for distributed 3D printing services

As the keystones of the personalized manufacturing, the Industrial Internet of Things (IIoT) consolidated with 3D printing pave the path for the era of Industry 4.0 and smart manufacturing. By resembling the age of craft manufacturing, Industry 4.0 expedites the alteration from mass production to mass customization. When distributed 3D printers (3DPs) are shared and collaborated in the IIoT, a promising dynamic, globalized, economical, and time-effective manufacturing environment for customized products will appear. However, the optimum allocation and scheduling of the personalized 3D printing tasks (3DPTs) in the IIoT in a manner that respects the customized attributes submitted for each model while satisfying not only the real-time requirements but also the workload balancing between the distributed 3DPs is an inevitable research challenge that needs further in-depth investigations. Therefore, to address this issue, this paper proposes a real-time green-aware multi-task scheduling architecture for personalized 3DPTs in the IIoT. The proposed architecture is divided into two interconnected folds, namely, allocation and scheduling. A robust online allocation algorithm is proposed to generate the optimal allocation for the 3DPTs. This allocation algorithm takes into consideration meeting precisely the customized user-defined attributes for each submitted 3DPT in the IIoT as well as balancing the workload between the distributed 3DPs simultaneously with improving their energy efficiency. Moreover, meeting the predefined deadline for each submitted 3DPT is among the main objectives of the proposed architecture. Consequently, an adaptive real-time multi-task priority-based scheduling (ARMPS) algorithm has been developed. The built ARMPS algorithm respects both the dynamicity and the real-time requirements of the submitted 3DPTs. A set of performance evaluation tests has been performed to thoroughly investigate the robustness of the proposed algorithm. Simulation results proved the robustness and scalability of the proposed architecture that surpasses its counterpart state-of-the-art architectures, especially in high-load environments.