基于B/S和SOA架构的LIMS系统设计与研究

为提升水质检测业务的专业化、智能化、系统化、自动化水平,针对新发展阶段下水利高质量发展对水质信息管理的需求,研究并开发基于B/S系统架构和SOA设计架构的新型综合性水质信息管理系统(LIMS),运用仪器谱图识别及数据提取、PHP与MySQL融合、仪器谱图与原始记录自动关联等技术,在一定程度上提高水质数据的电子化无纸化获取、处理、传输及应用等方面的管理水平,实现水质检测业务流程与资源的动态关联和闭环追溯,提升水质监测评价工作的管理效率和质量管理能力。基于B/S和SOA架构的LIMS在前沿高新技术中的应用研究,为水质检测和管理的各项活动提供智能、高效的数据支持平台,也为水利行业信息系统管理建设及水域功能监测监管提供技术支撑。

基于SOA架构的电炉企业财务与采购全链条数据管理平台设计

目前电炉企业财务和采购全链条业务数据管理平台没有对数据库进行实时更新处理,存在财务和采购业务数据管理整体耗时长、读取操作次数多和元数据迁移范围大的问题。提出基于SOA架构的财务与采购全链条业务数据管理平台设计,在SOA架构的基础上设计整体框架,并将平台划分财务与采购数据管理模块、采购数据基本信息管理模块、库存管理模块、采购信息查询模块以及用户登录系统模块五大模块。其次为加强数据管理效率,设计出数据处理软件系统,即可实现财务与采购全链条业务数据管理。实验表明,所提方法整体耗时短、读取操作次数少和元数据迁移范围小。

基于SOA框架的高校人事管理系统设计与实现

文章通过JDK开发工具设计基于SOA框架的高校人事管理系统,该系统采用三层结构,表示层使用GUI图形用户界面优化人机交互体验,数据层选用SQL Server数据库实现数据的分类存储。从功能上看,高校人事管理系统可支持招聘管理、培训管理、薪资管理以及部门管理等功能;设计访问认证保护系统安全,能满足高校人事管理的基本需要。

基于SOA架构的纯电动汽车电源管理系统设计

随着我国大力推进纯电动汽车发展,汽车制造企业对纯电动汽车相配套的电源管理系统提出了更高的要求。该文对纯电动汽车电源管理系统进行概述,基于SOA架构设计纯电动汽车电源管理系统,包括硬件及软件,并对电源管理系统功能进行测试。实践表明,基于SOA架构的纯电动汽车电源管理系统能够对电池充放电进行科学有效的管理,大大延长纯电动汽车的使用寿命,具有一定的推广应用价值。

一套SOA架构的高校人事信息管理系统分析与设计

首先对现有高校人事管理系统进行了分析,并基于SOA架构模型设计了一套人事管理信息系统,以此来提高人事管理者的工作效率。系统涵盖了教职工从入职到退休的每一个环节,并和现有的校园网数据平台集成,方便进行统一的信息化管理,满足了人事管理工作的信息化建设需求,提高了人事管理效率。

汾渭平原非采暖期和采暖期大气挥发性有机物的污染特征、来源解析及对SOA的生成潜势:以运城市为例

为探究汾渭平原非采暖期和采暖期大气环境挥发性有机物(VOCs)的污染特征差异及对二次有机气溶胶(SOA)生成的影响因素,本文以运城市为例在城区站点开展了为期5个月(2021年9月−2022年1月)的小时分辨率VOCs连续在线观测实验,采用PMF(Probabilistic Matrix Factorization)源解析模型、随机森林模型和SOA评估等方法,全面对比分析了运城市非采暖期和采暖期VOCs的体积分数、来源差异和对SOAP(SOA生成潜势)的贡献,同时量化了气象和排放因素对TVOCs(总挥发性有机化合物)体积分数整体变化的影响.结果表明:①运城市非采暖期和采暖期TVOCs平均体积分数分别为35.39×10^(-9)±17.79×10^(-9)和59.88×10^(-9)±31.56×10^(-9),表现出采暖期TVOCs体积分数升高的特征.②烷烃和OVOCs(含氧挥发性有机物)为两个时期VOCs的主要组分,燃烧源和工业源在采暖期是VOCs的主要贡献者,相比非采暖期其贡献率分别上升了13.3%和2.7%.③随机森林模型运行结果表明,排放因素对TVOCs体积分数的贡献高于气象因素,其对采暖期TVOCs体积分数的贡献为非采暖期的1.41倍,且采暖期不利的气象因素也促进了TVOCs体积分数的上升.④芳香烃虽然对非采暖期和采暖期TVOCs体积分数的贡献率分别为5.5%和7.0%,但对两个时期SOAP的贡献率分别达85.5%和87.9%,其中间/对-二甲苯、邻-二甲苯和乙苯是对SOAP贡献率较大的物种.研究显示,芳香烃及人为活动的燃烧源分别是运城市采暖期需要VOCs重点管控的组分和潜在来源.

基于SOA架构的汽车热管理控制系统设计

当前汽车热管理控制系统大多数为传统嵌入式控制器集成驱动的开发方式,该方式典型的特征是需要按照行业标准AutoSar架构要求将应用层软件和底层驱动软件集成在一起,软件版本迭代的过程会造成应用层和底软件需要绑定在一起才能完成整体软件升级更新。文章基于一种面向服务的架构(SOA),设计了一种可灵活调用及组合应用层功能的热管理控制系统,阐述了一种先进的面向服务化的热管理控制软件开发原理,重点介绍了基于SOA架构下如何进行更为有效地将软硬件进行解耦合设计方案,将应用层软件和底层驱动软件进行分离,并结合奇瑞实际项目开发验证了SOA控制系统的灵活性及可靠性。

基于Levy-SOA自适应阈值分割和改进引导滤波的NSST图像增强

针对电气设备红外图像对比度不高、含噪声等问题,提出了一种非下采样剪切波变换(non-subsampled shearlet transform,NSST)域下的红外图像增强算法。首先,通过NSST将图像分解为低频分量和高频分量。然后,利用基于Levy-海鸥优化算法(Levy-seagull optimization algorithm,Levy-SOA)的自适应阈值分割算法将低频分量分割成背景区域和目标设备区域,并分别对其进行直方图均衡化处理和线性增强;利用改进引导滤波算法对高频分量进行去噪处理。最后,对处理后的低频分量和高频分量进行NSST重构,得到最终的增强图像。实验结果表明,所提算法在一定程度上改善了图像视觉效果,保证了图像本身的质量,有助于后续电气设备的温度状态评估、异常分析、故障定位和诊断。

基于SOA的医院设备控制系统设计

SOA作为一种非常流行的系统架构设计思想,在各个领域的系统设计中得到了广泛使用;研究对象是一套基于SOA开发的医院设备控制系统;该设备控制系统具备了医疗设备实时监控功能,历史设备使用信息、状态信息、维护信息等的可视化展示功能,以及对医院全部设备的实时监控功能;该系统采用基于web service技术实现SOA架构思想,通过分布式的架构设计方法实现了对系统内部功能模块之间复杂逻辑关系的服务治理;此外,为解决医疗设备控制中关键的设备状态感知和故障预警问题,研究设计了一个基于actor-critic强化学习算法的设备状态感知和故障预警算法,实验表明,经过多轮迭代,该算法的预测准确率高达到97.9%,可以有效实现对医疗设备的状态感知和故障预警;经过对系统的部署、测试和验证,证明了该系统可以有效完成项目开始之初设定的功能性和非功能性需求,可以有效承担医院医疗设备管理的任务。

Neural Network-Based State Estimation for Nonlinear Systems With Denial-of-Service Attack Under Try-Once-Discard Protocol

Dear Editor,This letter deals with state estimation issues of discrete-time nonlinear systems subject to denial-of-service(DoS)attacks under the try-once-discard(TOD)protocol.More specifically,to reduce the communication burden,a TOD protocol with novel update rules on protocol weights is designed for scheduling measurement outputs.In addition,unknown nonlinear functions vulnerable to DoS attacks are considered due to the openness and vulnerability of the network.

Deep Reinforcement Learning-Based Task Offloading and Service Migrating Policies in Service Caching-Assisted Mobile Edge Computing

Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.

Detection of Real-Time Distributed Denial-of-Service (DDoS) Attacks on Internet of Things (IoT) Networks Using Machine Learning Algorithms

The primary concern of modern technology is cyber attacks targeting the Internet of Things.As it is one of the most widely used networks today and vulnerable to attacks.Real-time threats pose with modern cyber attacks that pose a great danger to the Internet of Things(IoT)networks,as devices can be monitored or service isolated from them and affect users in one way or another.Securing Internet of Things networks is an important matter,as it requires the use of modern technologies and methods,and real and up-to-date data to design and train systems to keep pace with the modernity that attackers use to confront these attacks.One of the most common types of attacks against IoT devices is Distributed Denial-of-Service(DDoS)attacks.Our paper makes a unique contribution that differs from existing studies,in that we use recent data that contains real traffic and real attacks on IoT networks.And a hybrid method for selecting relevant features,And also how to choose highly efficient algorithms.What gives the model a high ability to detect distributed denial-of-service attacks.the model proposed is based on a two-stage process:selecting essential features and constructing a detection model using the K-neighbors algorithm with two classifier algorithms logistic regression and Stochastic Gradient Descent classifier(SGD),combining these classifiers through ensemble machine learning(stacking),and optimizing parameters through Grid Search-CV to enhance system accuracy.Experiments were conducted to evaluate the effectiveness of the proposed model using the CIC-IoT2023 and CIC-DDoS2019 datasets.Performance evaluation demonstrated the potential of our model in robust intrusion detection in IoT networks,achieving an accuracy of 99.965%and a detection time of 0.20 s for the CIC-IoT2023 dataset,and 99.968%accuracy with a detection time of 0.23 s for the CIC-DDoS 2019 dataset.Furthermore,a comparative analysis with recent related works highlighted the superiority of our methodology in intrusion detection,showing improvements in accuracy,recall,and detection time.

基于SOA的数字商务招商引资项目管理平台研究

招商引资是吸引投资引进先进技术和管理经验,促进经济社会全面发展的重要手段,数字经济背景下以市场需求为导向,精准定位招商对象,主动推介储备项目成为招商引资的发展方向。本文基于面向服务的架构,通过将功能模块服务化拆分与深度解耦设计,有效地应对了数字化招商引资过程中所面临的跨领域广泛、业务逻辑繁复,以及市场与政策需求快速变化等诸多难题。优化数字化招商引资的模式机制和流程,研发基于SOA的数字商务招商引资项目管理平台,实现招商大数据自动汇聚,招商过程精准匹配,签约项目全周期服务监管,提高了招商引资的成功率和时效性。

Sharing Smart Services,Jointly Promoting Trade Development

In 2024,the China International Fair for Trade in Services (hereinafter referred to as CIFTIS) opened in the China National Convention Center and Shougang Park on September 12th.The theme of the CIFTIS this time was"global services,shared prosperity",which is not only a window for allowing the world to discover the development of China's service trade,but is also a bridge for promoting global cooperation with regards to the service trade.As one of the world-famous service trade events,the CIFTIS has become an important business card allowing China to open up.The CIFTIS has attracted the attention of the whole world and become a bridge for all parties to share development opportunities,promote industrial growth,and strengthen communication.

Residents’perceptions of ecosystem services in an urbanizing basin:A case study in the Guanting Reservoir basin,China

Understanding stakeholders’differences in perceptions of ecosystem services(ES)is crucial for guiding ecolog-ical conservation and planning.However,the variations of ES perception amongst different types of residents in urbanizing areas along an urban-rural gradient are still poorly understood.Combining a questionnaire-based survey,redundancy analysis,and statistical tests,we delineated the urban-rural gradient according to local res-idents’socio-economic characteristics,and investigated the differences in local residents’perceptions of ES and potential factors affecting them in the Guanting Reservoir basin,a rapidly urbanizing basin in China.The results showed that residents living in urban-rural transitional areas attached great importance to provisioning services of providing food and domestic water,regulating services of carbon sequestration and air purification,and cul-tural services of providing education and training,which were 0.7%-13.1%,0.7%-9.1%and 2.5%-21.2%higher than that of residents in other areas,respectively.Age and occupation were major factors affecting residents’perceptions.In terms of land-use types that deliver ES,the difference in perceptions of ES delivered by grassland was the greatest amongst residents.Our results support recommendations for policymakers to take into account the stakeholders’diverse perceptions,thus promoting residents’sense of gain on ES.

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

Dynamical distribution of continuous service time model involving non-Maxwellian collision kernel and value functions

The distribution of continuous service time in call centers is investigated.A non-Maxwellian collision kernel combining two different value functions in the interaction rule are used to describe the evolution of continuous service time,respectively.Using the statistical mechanical and asymptotic limit methods,Fokker–Planck equations are derived from the corresponding Boltzmann-type equations with non-Maxwellian collision kernels.The steady-state solutions of the Fokker–Planck equation are obtained in exact form.Numerical experiments are provided to support our results under different parameters.

Research progress and future prospects in the service security of key blast furnace equipment

The safety and longevity of key blast furnace(BF)equipment determine the stable and low-carbon production of iron.This pa-per presents an analysis of the heat transfer characteristics of these components and the uneven distribution of cooling water in parallel pipes based on hydrodynamic principles,discusses the feasible methods for the improvement of BF cooling intensity,and reviews the pre-paration process,performance,and damage characteristics of three key equipment pieces:coolers,tuyeres,and hearth refractories.Fur-thermoere,to attain better control of these critical components under high-temperature working conditions,we propose the application of optimized technologies,such as BF operation and maintenance technology,self-repair technology,and full-lifecycle management techno-logy.Finally,we propose further researches on safety assessments and predictions for key BF equipment under new operating conditions.

Healthcare Services Interoperability in Kenya: Challenges and Opportunities

In an attempt to assess the Kenyan healthcare system, this study looks at the current efforts that are already in place, what challenges they face, and what strategies can be put into practice to foster interoperability. By reviewing a variety of literature and using statistics, the paper ascertains notable impediments such as the absence of standard protocols, lack of adequate technological infrastructure, and weak regulatory frameworks. Resultant effects from these challenges regarding health provision target enhanced data sharing and merging for better patient outcomes and allocation of resources. It also highlights several opportunities that include the adoption of emerging technologies, and the establishment of public-private partnerships to strengthen the healthcare framework among others. In this regard, the article provides recommendations based on stakeholder views and global best practices addressed to policymakers, medical practitioners, and IT specialists concerned with achieving effective interoperability within Kenya’s health system. This research is relevant because it adds knowledge to the existing literature on how healthcare quality can be improved to make it more patient-centered especially in Kenya.

Exact Tail Asymptotics for a Queueing System with a Retrial Orbit and Batch Service

This paper discusses a queueing system with a retrial orbit and batch service, in which the quantity of customers’ rooms in the queue is finite and the space of retrial orbit is infinite. When the server starts serving, it serves all customers in the queue in a single batch, which is the so-called batch service. If a new customer or a retrial customer finds all the customers’ rooms are occupied, he will decide whether or not to join the retrial orbit. By using the censoring technique and the matrix analysis method, we first obtain the decay function of the stationary distribution for the quantity of customers in the retrial orbit and the quantity of customers in the queue. Then based on the form of decay rate function and the Karamata Tauberian theorem, we finally get the exact tail asymptotics of the stationary distribution.