Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

Service Function Chain Deployment Algorithm Based on Multi-Agent Deep Reinforcement Learning

Aiming at the rapid growth of network services,which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain(SFC)under 5G networks,this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment(MADDPG-SD).Initially,an optimization model is devised to enhance the request acceptance rate,minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case.Subsequently,we model the dynamic problem as a Markov decision process(MDP),facilitating adaptation to the evolving states of network resources.Finally,by allocating SFCs to different agents and adopting a collaborative deployment strategy,each agent aims to maximize the request acceptance rate or minimize latency and costs.These agents learn strategies from historical data of virtual network functions in SFCs to guide server node selection,and achieve approximately optimal SFC deployment strategies through a cooperative framework of centralized training and distributed execution.Experimental simulation results indicate that the proposed method,while simultaneously meeting performance requirements and resource capacity constraints,has effectively increased the acceptance rate of requests compared to the comparative algorithms,reducing the end-to-end latency by 4.942%and the deployment cost by 8.045%.

Modeling and Analysis of Data Dependencies in Business Process for Data-Intensive Services

With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependencies, resulting in the inflexibility of the design and implement for the processes. This paper proposes a novel data-aware business process model which is able to describe both explicit control flow and implicit data flow. Data model with dependencies which are formulated by Linear-time Temporal Logic(LTL) is presented, and their satisfiability is validated by an automaton-based model checking algorithm. Data dependencies are fully considered in modeling phase, which helps to improve the efficiency and reliability of programming during developing phase. Finally, a prototype system based on j BPM for data-aware workflow is designed using such model, and has been deployed to Beijing Kingfore heating management system to validate the flexibility, efficacy and convenience of our approach for massive coding and large-scale system management in reality.

Analysis and Related Suggestions on the Whole Process Engineering Consulting Service Mode at Home and Abroad

This paper first introduces the basic connotation of China’s whole-process engineering consulting.Immediately,analyze the organization model,service procurement model and charging standards of foreign whole-process engineering consulting(international terminology full-life cycle engineering consultant).Second,discuss the government’s role in the development of engineering consulting from two aspects:service management and market access.Finally,combined with the above analysis,the specific problems faced in the implementation process of the whole process engineering consulting are compared.Provide relevant suggestions on how companies and individuals respond to industry development trends.

Coordination-theoretic approach to modelling grid service composition process

A grid service composite process is made up of complex coordinative activities.Developing the appropriate model of grid service coordinative activities is an important foundation for the grid service composition.According to the coordination theory,this paper elaborates the process of the grid service composition by using UML 2.0,and proposes an approach to modelling the grid service composition process based on the coordination theory.This approach helps not only to analyze accurately the task activities and relevant dependencies among task activities,but also to facilitate the adaptability of the grid service orchestration to further realize the connectivity,timeliness,appropriateness and expansibility of the grid service composition.

Evaluation and Optimization of the Logistics Service of Agricultural Products:an Empirical Analysis Based on Analytic Hierarchy Process

This research,from the theories of management science,supply chain management and logistics engineering,on the basis of extensive investigations,and using the method of analytic hierarchy process(AHP),evaluates the present situation of logistics service of agricultural products.Taking Nanping City(Nanping)as a case,it explores the obstacles existing in current logistics service system and the factors limiting the development of agricultural product logistics service.Combining with the theory of modern logistics system,it reveals the problems in the logistics system and the causes,and then constructs the strategy of optimization for agricultural product logistics service in Nanping.The conclusion of the study can be references for the government to make scientific strategies for the development of the agricultural product logistics service and help logistics enterprises improve their service level.

Service and Environment for the Enterprise Business Processes in CIM Integrating Infrastructure

The controlling and processing service and supporting environment for the enterprise business processes in HIT-IIS, a prototype of the CIM-OSA-IIS, are introduced.The detailed design about the business process services and the front-end services of HIT-IIS art given. It is focused on the structure, organization and workflow of the services ard environment.

SCP-Trust Reasoning Strategy Based on Preference and Its Service Composition Process of Context-Aware Process

Before providing services to the user, user preference considerations are the key conditions to achieve the self-adaptive decision-making about service selection and composition process, which is the flexible concerned aspect provided by massive cloud computing environment data. Meanwhile, during the whole services’ providing process, achieving the capturing and forming of service aggregation units’ topology logic, building the context environment’s process-aware of service composition, ensuring the trust and adaptation among service aggregation units, which are the important reasons to express timely requirement preference. This paper designs SCP-Trust Reasoning strategy about the integration of user preference and trust, with process algebra, it is to achieve the context process-aware logic for service composition process, in order to improve the autonomous optimization and evolution of service implementation system.

Model checking web services choreography in process analysis toolkit

Web service （WS） is an emerging software technology, especially acting an important role in cloud computing. The WS choreography description language （WS-CDL） is the standard for modeling the observable behavior of WS composition across multiple participants from a global point of view. However, it lacks of a formal semantics and could easily lead to misunderstanding and different implementations. In this paper, the WS-CDL based specifications are formally extracted in a communicating sequential process supporting a formal approach to checking WS models. In addition, formalisms and model checking are explicitly illustrated through a simple but non-trivial example with the help of model checker process analysis toolkit （PAT）.

Building a Productive Domain-Specific Cloud for Big Data Processing and Analytics Service

Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.

Crossing the Growth Threshold： Service-Based Economy, Knowledge Process and Reshaping of Efficiency Model

The transition from middle-income to high-income stage is fraught with risks of growth divergence. Economic transition is clouded by the following possibilities： （1）falling share of industrial seetor through industrial depression and weakening growth momentum caused by the large urbanization costs; （2） the subordination of service sector as a result of nearly irreversibly industrial professional, which falters the process of service sector transition and upgrading,＂ （3） inefficient knowledge production allocation and human capital upgrade due to the absence of incentivized compensation of knowledge consumption. We suggest that a country should reshape its efficiency model by upgrading knowledge factor and human capital as the pre-requisite. Given the dilemmas of transition, China should take the faetorization trend of service sector and reshape efficiency model through institutional reform, ensuring that service sector will develop in tandem with industrial sector.

Web Service运行管理平台的研究与实现

WebService技术为异构应用之间的集成和互操作提供了有效的解决手段 ,目前多数WebService平台仅支持SOAP消息的解析 ,尚未考虑SOAP的多种绑定方式、安全扩展保证和多种功能实现方式的集成等共性处理需求 因此 ,提出并研制一个层次化的WebService运行管理平台 ,通过抽象出运行时对象作为WebService共性问题处理的基础 ,设计可配置、可扩展的链式处理结构满足WebService处理需求的变化 ,并提供集成不同业务功能的统一接入方式 。

基于Web Service和工作流技术的CAPP系统研究

针对目前CAPP系统存在的难以解决的集成化与可重构问题,提出一种基于Web Service技术和工作流技术的CAPP系统解决方案,成功实现了工艺设计流程的自动化、系统重组与系统集成。详细阐述了Web Service和工作流技术相结合的CAPP系统三层分布式体系结构、功能结构以及基于知识规则的工艺智能化生成的推理机制。重点介绍了Web Service技术在CAPP系统集成中的应用与实现机制,以及工作流技术在工艺设计流程管理中的应用。

基于Web Service的分布式电子商务系统设计与实现

文章仔细分析了现有电子商务系统在构架上存在的不足和远程访问协议上存在的局限性,创设了基于Web Service的分布式构架。该构架充分利用了Web Service的优势,将商务事件逻辑分布在多台服务器上,提高了系统的可靠性、稳定性、可扩展性以及维护性。在现有商务系统设施和技术平台的基础上,该系统充分利用松散耦合的服务程序集成了多种业务活动,初步构建了大型电子商务系统的架构。

基于WebServices的网络管理业务流程管理系统交互接口

该文分析了Wf-XML定义的工作流管理系统之间的互操作机制,分析了基于WebServices技术的网络管理服务描述方法的特点,借鉴MUWS给出的网络管理服务描述方法对Wf-XML尚存的不足进行了改进,定义了网络管理业务流程管理系统交互接口,给出了网络管理业务流程管理系统交互接口的实现及应用场景,该交互接口具有清晰的接口功能划分和良好的可扩展性。

用Web Services实现遥感图像分布式处理

随着遥感科学的发展,遥感图像的分布式处理的任务变得越来越迫切。该文以遥感图像分布式处理为主线,在分析了当前此方向的主要研究方法及WebServices的特点后,指出了应用WebServices技术实现遥感图像分布式处理的可行性,进而对应用WebServices技术实现遥感图像分布式处理的流程进行了设计,并针对某遥感图像的图像分割任务对其进行了实现。

基于Web Services技术的数据申报实现

介绍了电力市场数据申报系统的作用和Web Services技术的特点,分析了Web Services技术应用于电力市场数据申报系统的优点。提出Web Services技术与Java 2平台企业版(J2EE)技术相结合的数据申报实现方式。利用J2EE技术实现数据申报业务,Web Services技术封装对外调用接口。详细介绍了数据申报系统的运行环境和数据服务层、业务管理层和调用管理层的实现过程,分析了数据申报系统实现中的重点和难点。

基于BPEL的Web Service组合的数据流分析测试方法(英文)

随着Web Service组合变得越来越复杂,通过测试来保证服务质量和可靠性也变得越来越重要.将传统数据流分析方法扩展用于Web Service组合测试,提出了一种基于BPEL的Web Service组合的数据流分析测试方法.该方法基于一个测试模型:Web Service组合测试模型WSCTM,该测试模型可以捕获Web Service组合的数据流接口.采用基于服务的模型WSCTM,数据流可以从3个视点来分析:服务间、服务内和服务实现构件间.从而,Web Service组合的数据流测试可以在三层上得到实现.基于以上方法,可得到Web Service组合的定义-使用链,最终可产生满足既定测试标准以获得需求Web服务组合质量要求的测试路径.

Web Services框架中的面向业务管理方法

面向业务环境中的基础业务,以JMX作为基础结构,提出了相应的管理准则和管理模式,生成与原有业务相关联的管理业务。以流模型为基础,以业务级约定SLA为驱动,该业务管理结构可以实现基础业务的协作,构建复杂的合成业务,实现特定的商业应用,给出了过程拓扑结构,说明了相关商业过程管理问题。最后,给出了用于监视和控制业务的度量模型的模块化构建方法。