Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications

The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to frame multiple users per transmission and the per-antenna transmit power limitations, are addressed. To this end, the so-called frame-based precoding problem is optimally solved using the principles of physical layer multicasting to multiple co-channel groups under per-antenna constraints. In this context, a novel optimization problem that aims at maximizing the system sum rate under individual power constraints is proposed. Added to that, the formulation is further extended to include availability constraints. As a result, the high gains of the sum rate optimal design are traded off to satisfy the stringent availability requirements of satellite systems. Moreover, the throughput maximization with a granular spectral efficiency versus SINR function, is formulated and solved. Finally, a multicast-aware user scheduling policy, based on the channel state information, is developed. Thus, substantial multiuser diversity gains are gleaned. Numerical results over a realistic simulation environment exhibit as much as 30% gains over conventional systems, even for 7 users per frame, without modifying the framing structure of legacy communication standards.Comment: Accepted for publication to the IEEE Transactions on Wireless Communications, 201

Transmission Pricing of Distributed Multilateral Energy Transactions to Ensure System Security and Guide Economic Dispatch

Transmission Pricing of Distributed Multilateral Energy Transactions to Ensure System Security and Guide Economic Dispatc

{iFair}: {L}earning Individually Fair Data Representations for Algorithmic Decision Making

People are rated and ranked, towards algorithmic decision making in an increasing number of applications, typically based on machine learning. Research on how to incorporate fairness into such tasks has prevalently pursued the paradigm of group fairness: ensuring that each ethnic or social group receives its fair share in the outcome of classifiers and rankings. In contrast, the alternative paradigm of individual fairness has received relatively little attention. This paper introduces a method for probabilistically clustering user records into a low-rank representation that captures individual fairness yet also achieves high accuracy in classification and regression models. Our notion of individual fairness requires that users who are similar in all task-relevant attributes such as job qualification, and disregarding all potentially discriminating attributes such as gender, should have similar outcomes. Since the case for fairness is ubiquitous across many tasks, we aim to learn general representations that can be applied to arbitrary downstream use-cases. We demonstrate the versatility of our method by applying it to classification and learning-to-rank tasks on two real-world datasets. Our experiments show substantial improvements over the best prior work for this setting

Animal-Computer Interaction: a Manifesto (2011) and sections from Towards an Animal-Centred Ethics for Animal-Computer Interaction (2016)

Reprint of journal article "Animal-Computer Interaction: a Manifesto" (2011) and of sections of journal article "Towards an Animal-Centred Ethics for Animal-Computer Interaction" (2016

Business process management tools as a measure of customer-centric maturity

In application of business process management (BPM) tools in European commercial sectors, this paper examines current maturity of customer centricity construct (CC) as an emerging dimension of competition and as a potential strategic management direction for the future of business. Processes are one of the key components of transformation in the CC roadmap. Particular departments are more customer orientated than others, and processes, customer-centric expertise, and approach can be built and utilized starting from them. Positive items within a current business process that only involve minor modification could be the basis for that. The evidence of movement on the customer-centric roadmap is found. BPM in European telecommunications, banking, utility and retail sector supports roadmap towards customer-centricity in process view, process alignment and process optimization. However, the movement is partial and not flawless, as BPM hasn’t been inquired for supporting many of customer-centric dimensions

Paving the Way to Simpler: Experiencing from Maximizing Enrollment States in Streamlining Eligibility and Enrollment

Since 2009, the eight states (Alabama, Illinois, Louisiana, Massachusetts, New York, Utah, Virginia, and Wisconsin) participating in the Robert Wood Johnson Foundation's Maximizing Enrollment program have worked to streamline and simplify enrollment systems, policies, and processes for children and those eligible for health coverage in 2014. The participating states aimed to reduce enrollment barriers for consumers and administrative burdens in processing applications and renewals for staff by making improvements and simplifications at every step of the enrollment process. Although the states began their work before the enactment of the Affordable Care Act (ACA), their efforts positioned them well for implementation in 2014, and offer experiences and lessons that other states may find useful in their efforts to improve efficiency, lower costs, and promote responsible stewardship of limited public resources