GraphSTGAN:Situation understanding network of slow-fast high maneuvering targets for maritime monitor services of IoT data

With the rapid growth of the maritime Internet of Things(IoT)devices for Maritime Monitor Services(MMS),maritime traffic controllers could not handle a massive amount of data in time.For unmanned MMS,one of the key technologies is situation understanding.However,the presence of slow-fast high maneuvering targets and track breakages due to radar blind zones make modeling the dynamics of marine multi-agents difficult,and pose significant challenges to maritime situation understanding.In order to comprehend the situation accurately and thus offer unmanned MMS,it is crucial to model the complex dynamics of multi-agents using IoT big data.Nevertheless,previous methods typically rely on complex assumptions,are plagued by unstructured data,and disregard the interactions between multiple agents and the spatial-temporal correlations.A deep learning model,Graph Spatial-Temporal Generative Adversarial Network(GraphSTGAN),is proposed in this paper,which uses graph neural network to model unstructured data and uses STGAN to learn the spatial-temporal dependencies and interactions.Extensive experiments show the effectiveness and robustness of the proposed method.

A Web Service Framework for Environmental and Carbon Footprint Monitoring in Construction Supply Chains

With the growing environmental concerns, green supply chain management （GSCM） is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the participating members along a supply chain is important to GSCM. The GreenSCOR model developed by the Supply Chain Council provides a generic framework for measuring the total carbon footprint and environmental footprint in a supply chain. The model is based on the Supply Chain Operations Reference （SCOR） model, which represents a supply chain network in a hierarchically structured manner. This paper describes the GreenSCOR framework and its potential application to the construction industry. This paper also presents a web services approach to incorporate the GreenSCOR model to the implementation of collaborative information systems. Each process element in the SCOR model is represented and delivered as individual web service units, which can be reused and integrated using standard web services technologies. The service units are combined and managed in a prototype web service collaborative framework, called SC Collaborator, which is designed and developed for supporting construction supply chain management. An illustrative example is presented to demonstrate the implementation of the GreenSCOR-based SC Collaborator framework.

Adaptive Runtime Monitoring of Service Level Agreement Violations in Cloud Computing

The cloud service level agreement(SLA)manage the relationship between service providers and consumers in cloud computing.SLA is an integral and critical part of modern era IT vendors and communication contracts.Due to low cost and flexibility more and more consumers delegate their tasks to cloud providers,the SLA emerges as a key aspect between the consumers and providers.Continuous monitoring of Quality of Service(QoS)attributes is required to implement SLAs because of the complex nature of cloud communication.Many other factors,such as user reliability,satisfaction,and penalty on violations are also taken into account.Currently,there is no such policy of cloud SLA monitoring to minimize SLA violations.In this work,we have proposed a cloud SLA monitoring policy by dividing a monitoring session into two parts,for critical and non-critical parameters.The critical and non-critical parameters will be decided on the interest of the consumer during SLA negotiation.This will help to shape a new comprehensive SLA based Proactive Resource Allocation Approach(RPAA)which will monitor SLA at runtime,analyze the SLA parameters and try to find the possibility of SLA violations.We also have implemented an adaptive system for allocating cloud IT resources based on SLA violations and detection.We have defined two main components of SLA-PRAA i.e.,(a)Handler and(b)Accounting and Billing Manager.We have also described the function of both components through algorithms.The experimental results validate the performance of our proposed method in comparison with state-of-the-art cloud SLA policies.

Management Mode of Rural Credit Cooperatives

Cooperative financing, with existing problems involving legal person man-agement and property supervision is highly demanded by farmers in China. It is fea-sible to explore a shareholding system to resolve the management mode issue of rural credit cooperatives in order to introduce investments, formulate the right struc-ture for rational stock and to establish effective monitoring mechanism for property right. Hence, information issuing would be reinforced and a rural credit cooperative would be established to be a modern financial enterprise with transparent property rights.