Individual Risk Management for Digital Payment Systems

Despite existing security standards and security technologies, such as secure hardware, gaps between users’ demand for security and the security offered by a payment system can still remain. These security gaps imply risks for users. In this paper, we introduce a framework for the management of those risks. As a result, we present an instrument enabling users to evaluate eventual risks related with digital payment systems and to handle these risks with technical and economic instruments.Payment Systems, Digital Money

Beyond Bond Markets 2000: The Electronic Frontier and Regulation of the Capital Markets for Debt Securities

On Oct 18-19, 1999, more than fifty securities lawyers, representatives of ratings agencies, regulators and academics gathered in Washington DC for a conference on the regulation of capital markets for debt securities. Some of the recurrent themes and conclusions arising from deliberations by conference participants are discussed

On Internal Knowledge Markets

In large organizations, knowledge can move rapidly or slowly, usefully or unproductively. Those who place faith in internal knowledge markets and online platforms to promote knowledge stocks and flows should understand how extrinsic incentives can crowd outintrinsic motivation

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

Cycle Accurate Energy and Throughput Estimation for Data Cache

Resource optimization in energy constrained real-time adaptive embedded systems highly depends on accurate energy and throughput estimates of processor peripherals. Such applications require lightweight, accurate mathematical models to profile energy and timing requirements on the go. This paper presents enhanced mathematical models for data cache energy and throughput estimation. The energy and throughput models were found to be within 95% accuracy of per instruction energy model of a processor, and a full system simulator?s timing model respectively. Furthermore, the possible application of these models in various scenarios is discussed in this paper

Framing the collaborative economy - Voices of contestation

Within the context of multiple crises and change, a range of practices discussed under the umbrella term of collaborative (or sharing) economy have been gaining considerable attention. Supporters build an idealistic vision of collaborative societies. Critics have been stripping the concept of its visionary potential, questioning its revolutionary nature. In the study, these debates are brought down to the local level in search for common perceptions among the co-creators of the concept in Vienna, Austria. Towards this aim a Q study is conducted, i.e. a mixed method enabling analyses of subjective perceptions on socially contested topics. Four framings are identified: Visionary Supporters, Market Optimists, Visionary Critics, and Skeptics, each bringing their values, visions, and practical goals characteristic of different understanding of the collaborative economy. The study questions the need for building a globally-applicable definition of the concept, calls for more context-sensitivity, exploratory studies, and city-level multi-stakeholder dialogues