Usage of Network Simulators in Machine-Learning-Assisted 5G/6G Networks

Without any doubt, Machine Learning (ML) will be an important driver of future communications due to its foreseen performance when applied to complex problems. However, the application of ML to networking systems raises concerns among network operators and other stakeholders, especially regarding trustworthiness and reliability. In this paper, we devise the role of network simulators for bridging the gap between ML and communications systems. In particular, we present an architectural integration of simulators in ML-aware networks for training, testing, and validating ML models before being applied to the operative network. Moreover, we provide insights on the main challenges resulting from this integration, and then give hints discussing how they can be overcome. Finally, we illustrate the integration of network simulators into ML-assisted communications through a proof-of-concept testbed implementation of a residential Wi-Fi network

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Stimulating the Division of Innovative Labor by Regional Competition for R&D Subsidies – A New Approach in German Innovation Policy

The paper deals with a new approach in German innovation policy that organizes contests of initiatives for public funds. Based on an overview of the different programs we investigate the advantages and problems of such an approach. We find that this type of policy may have a large impact and can, therefore, be regarded a rather efficient instrument of innovation policy. Compared to conventional policies implementation is a much more critical issue. The contest approach may require more flexibility on the side of the administration, particularly with regard to the design of the assistance. The main disadvantage is the additional time that is required for conducting the contest. As a distinct “picking the winner” instrument it is not suited as a means for achieving a leveling-out of welfare levels. Keywords: Innovation policy, regional competition, innovation networks JEL-classification: H32, O18, O38, R11

Social Bots: Human-Like by Means of Human Control?

Social bots are currently regarded an influential but also somewhat mysterious factor in public discourse and opinion making. They are considered to be capable of massively distributing propaganda in social and online media and their application is even suspected to be partly responsible for recent election results. Astonishingly, the term `Social Bot' is not well defined and different scientific disciplines use divergent definitions. This work starts with a balanced definition attempt, before providing an overview of how social bots actually work (taking the example of Twitter) and what their current technical limitations are. Despite recent research progress in Deep Learning and Big Data, there are many activities bots cannot handle well. We then discuss how bot capabilities can be extended and controlled by integrating humans into the process and reason that this is currently the most promising way to go in order to realize effective interactions with other humans.Comment: 36 pages, 13 figure

Contests for Cooperation: A New Approach in German Innovation Policy

A new approach in German innovation policy organizes contests of proposals for developing innovation networks. Based on an overview of the different programs, we investigate the advantages, problems and limitations of such an approach. We find that this type of policy may have a relatively large impact and can, therefore, be regarded as a rather efficient instrument of innovation policy. Compared to conventional policies, administration of the program is a much more critical issue. The contest approach may stimulate learning effects on the side of the administration but may also require a high degree of flexibility. The main disadvantage is the additional time that is required for conducting the contest. As a distinct 'picking the winner' approach, the contest approach is not suited as a means for achieving a leveling-out of regional welfare levels.Innovation policy; Regional competition; Innovation networks

A GRID-BASED E-LEARNING MODEL FOR OPEN UNIVERSITIES

E-learning has grown to become a widely accepted method of learning all over the world. As a result, many e-learning platforms which have been developed based on varying technologies were faced with some limitations ranging from storage capability, computing power, to availability or access to the learning support infrastructures. This has brought about the need to develop ways to effectively manage and share the limited resources available in the e-learning platform. Grid computing technology has the capability to enhance the quality of pedagogy on the e-learning platform. In this paper we propose a Grid-based e-learning model for Open Universities. An attribute of such universities is the setting up of multiple remotely located campuses within a country. The grid-based e-learning model presented in this work possesses the attributes of an elegant architectural framework that will facilitate efficient use of available e-learning resources and cost reduction, leading to general improvement of the overall quality of the operations of open universities

Degrees of Freedom: Expanding College Opportunities - for Currently and Formerly Incarcerated Californians

This report begins with a background on the higher education and criminal justice systems in California. This background section highlights the vocabulary and common pathways for each system, and provides a primer on California community colleges. Part II explains why California needs this initiative. Part III presents the landscape of existing college programs dedicated to criminal justice-involved populations in the community and in jails and prisons. This landscape identifies promising strategies and sites of innovation across the state, as well as current challenges to sustaining and expanding these programs. Part IV lays out concrete recommendations California should take to realize the vision of expanding high-quality college opportunities for currently and formerly incarcerated individuals. It includes guidelines for developing high-quality, sustainable programs, building and strengthening partnerships, and shaping the policy landscape, both by using existing opportunities and by advocating for specific legislative and policy changes. Profiles of current college students and graduates with criminal records divide the sections and offer first-hand accounts of the joys and challenges of a college experience