A Semantic Model to Assist Policy Refinement Mechanisms for NFV-MANO Systems

Management in NFV scenarios is a complex task. In this scenario, automated policy refinement can be used to enforce NFV-MANO functions to deal with the increased complexity. However, existing solutions do not perform policy analysis. Therefore, in this work, we propose a semantic model in OWL 2, named Onto-Planner, to assist the policy refinement process for NFV-MANO systems. Preliminary results show that Onto-Planner provides policy analysis when a DL reasoner is applied.

Cloud doctrine: impact on cloud adoption in the government organizations of India

Purpose Government is the biggest spender on cloud computing technology but a very limited study and data sets are available to assess the cloud adoption trends in government organizations in India. As India is ushering towards “Digital India” it becomes essential for the government to embrace the cloud to enhance governance and meet the citizen expectations. This paper aims to discuss the evolution of cloud computing (Meghraj) in government organizations by examining the various information technology (IT) and cloud policies, thereby focusing on the policy gaps. The second part of this study assesses the cloud adoption trend by analyzing adopted cloud services, deployments models, leading sectors in cloud adoption and cloud approach. Eventually, in consultation with experts, a conceptual framework for cloud adoption in the government organizations of India is developed for wider cloud adoption. Design/methodology/approach The authors reviewed various IT/cloud policies and related literature to find the policy gaps for slow cloud adoption in government organizations. Authors have researched to collect the data from the various government procurement portals and analysed the tender and contracts of 500 organizations for cloud requirements to infer the cloud adoption trends. Based on the review of policy gaps, adoption trends and by consulting the experts a conceptual cloud adoption framework has been developed for wider cloud adoption in government organizations. Findings This study can be a pathfinder where the most innovative findings are about the cloud adoption trends in the government organizations in the time frame from 2013 till 2020. Several key findings are – the public cloud are the most widely adopted, infrastructure as a service model is the most used services, the majority of the applications migrating to the cloud are legacy applications, the leading sector in cloud adoption are – IT, transport and education. It is observed that the pandemic Covid-19 has acted as a catalyst and accelerated cloud adoption in government organizations. Eventually, a conceptual cloud adoption framework has been suggested addressing the policy gaps, deficiencies, overcoming the gaps and their related outcomes for the wider cloud adoption in the government organizations. Practical implications The findings of this work highlight the cloud adoption trends in government organizations which can prove vital to the policymakers. This work will assist policymakers, government organizations, researchers, IT professionals and others interested in analyzing the state of cloud adoption. The conceptual cloud adoption framework developed endeavours to uncover the policy gaps, suggest the gap resolution mechanism and outcomes which may assist the organization for wider cloud adoption. This research work effectively connects the policies to practice by stimulating the interest in understanding the policies, strategies and thereby creating the enabling environment for cloud adoption. This study provides feedback on cloud adoption trends which can assist in policy refinement and further strengthen policy/strategies. Originality/value As of date, there is limited data available for cloud adoption in government organizations. This work uniquely presents the cloud projections which helps to gain insights on cloud adoption trends in government organizations. This study is the first of its kind, focusing on cloud adoption in the unexplored government sector. This study provides a comprehensive summary of adoption statistics, policy analysis and practice in government organizations of India.

Analysis of Methods for Incremental Policy Refinement by Kinesthetic Guidance

Traditional robot programming is often not feasible in small-batch production, as it is time-consuming, inefficient, and expensive. To shorten the time necessary to deploy robot tasks, we need appropriate tools to enable efficient reuse of existing robot control policies. Incremental Learning from Demonstration (iLfD) and reversible Dynamic Movement Primitives (DMP) provide a framework for efficient policy demonstration and adaptation. In this paper, we extend our previously proposed framework with improvements that provide better performance and lower the algorithm’s computational burden. Further, we analyse the learning stability and evaluate the proposed framework with a comprehensive user study. The proposed methods have been evaluated on two popular collaborative robots, Franka Emika Panda and Universal Robot UR10.

Conclusion

This chapter concludes the book by first summarizing its key arguments, which relate to the effectiveness of inquiries and the ways in which we conceptualize them. It then then moves on to discuss some ways in which inquiries might be designed more effectively to enhance their lesson-learning functions. This discussion focuses upon five areas: institutional amnesia and the loss of lessons over time; problematic forms of policy transfer; street-level resistance to inquiry lessons; the dangers of policy refinement; and the need to properly synthesize legal-judicial logics into inquiry formats. In each of these areas, recommendations are proposed for those who design, staff, and implement future public inquiries.

The Moscow Central Circle as a Catalyst for Change of Residential Mobility

Upgrading of a city planning structure, development of its infrastructure and implementation of integrated programs for transport policy refinement cause changes in the scenarios of the behavior of residents. Scenarios of transport behavior are one of the most important aspects that are taken into account in the process of city model formation and in turn, are used to develop scenarios of the urban area development One of the most important ways of tracking changes in the behavior of residents is a sociological survey of the transport services consumers. This publication is devoted to the survey of passengers on a new type of high-speed city rail in Moscow - the Moscow Central ring (formerly known as the Small ring of the Moscow railway), statistical and analytical processing of the obtained results.