The 2008 crash has left all the established economic doctrines - equilibrium models, real business cycles, disequilibria models - in disarray. Part of the problem is due to Smith’s "veil of ignorance": individuals unknowingly pursue society’s interest and, as a result, have no clue as to the macroeconomic effects of their actions: witness the Keynes and Leontief multipliers, the concept of value added, fiat money, Engel’s law and technical progress, to name but a few of the macrofoundations of microeconomics. A good viewpoint to take bearings anew lies in comparing the post-Great Depression institutions with those emerging from Thatcher and Reagan’s economic policies: deregulation, exogenous vs. endoge- nous money, shadow banking vs. Volcker’s Rule. Very simply, the banks, whose lending determined deposits after Roosevelt, and were a public service became private enterprises whose deposits determine lending. These underlay the great moderation preceding 2006, and the subsequent crash.

The Economic Institutions of Capitalism

Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

Introduction to stochastic programming

In this paper, we introduce an efficient conditional privacy preservation (ECPP) protocol in vehicular ad hoc networks (VANETs) to address the issue on anonymous authentication for safety messages with authority traceability. The proposed protocol is characterized by the generation of on-the-fly short-time anonymous keys between on-board units (OBUs) and roadside units (RSUs), which can provide fast anonymous authentication and privacy tracking while minimizing the required storage for short-time anonymous keys. We demonstrate the merits gained by the proposed protocol through extensive analysis.

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ECPP: Efficient Conditional Privacy Preservation Protocol for Secure Vehicular Communications

For privacy concerns to be addressed adequately in today's machine-learning (ML) systems, the knowledge gap between the ML and privacy communities must be bridged. This article aims to provide an introduction to the intersection of both fields with special emphasis on the techniques used to protect the data.

Privacy-Preserving Machine Learning: Threats and Solutions

Cloud computing provides scalable computing and storage resources. More and more data-intensive applications are developed in this computing environment. Different applications have different quality-of-service (QoS) requirements. To continuously support the QoS requirement of an application after data corruption, we propose two QoS-aware data replication (QADR) algorithms in cloud computing systems. The first algorithm adopts the intuitive idea of high-QoS first-replication (HQFR) to perform data replication. However, this greedy algorithm cannot minimize the data replication cost and the number of QoS-violated data replicas. To achieve these two minimum objectives, the second algorithm transforms the QADR problem into the well-known minimum-cost maximum-flow (MCMF) problem. By applying the existing MCMF algorithm to solve the QADR problem, the second algorithm can produce the optimal solution to the QADR problem in polynomial time, but it takes more computational time than the first algorithm. Moreover, it is known that a cloud computing system usually has a large number of nodes. We also propose node combination techniques to reduce the possibly large data replication time. Finally, simulation experiments are performed to demonstrate the effectiveness of the proposed algorithms in the data replication and recovery.

QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing Systems

Inter-Vehicle Communications (IVC) and Roadside-to-Vehicle Communications (RVC) in vehicular networks based on IEEE 802.11 are emerging technologies for future Intelligent Transportation Systems (ITS). This paper presents a new efficient routing approach, called RAR (Roadside-Aided Routing), that is the first one to exploit the unique characteristics of vehicular networks. A novel affiliation method is proposed to affiliate a vehicle to several Roadside Units based on road constraints. This scheme allows (a) agent advertisement to be broadcast in one hop (instead of multi-hop), (b) routing to be done in single phase, comparing to two phases, (c) to eliminate the use of hierarchical addressing which is commonly used in single-phase schemes. Simulation results of ns-2 show that RAR approach can provide a high packet delivery rate in vehicular networks with a low and constant overhead.

Roadside-Aided Routing (RAR) in Vehicular Networks

Block-based reversible data embedding

The increasing penetration of renewable energy has become a critical issue in recent years. The future power system is foreseen to depend on distributed energy resource (DER) excessively for continuous load support. Yet, DER providers are also facing limited choices in their produced renewable energy. Massive information and complicated cooperation emerging from involvers intensify issues in terms of efficiency, reliability, and scalability. In this paper, a cloud-based framework is proposed to provide a customer-oriented energy management as a service (EMaaS) for green communities, which are formed as virtual retail electricity providers (REPs) by involved DERs providers. It can be adopted by existing REPs or utilities. For each green community, the multiperiod global cost is minimized to promote renewable energy, and renewable energy consumption is stabilized to enhance integration. A solvable linear programming model is formulated for EMaaS. The case studies results reveal the proposed EMaaS retains satisfactory performances.

J. Morris Chang

Papers

Privacy-Preserving Machine Learning: Threats and Solutions

QoS-Aware Data Replication for Data-Intensive Applications in Cloud Computing Systems

Roadside-Aided Routing (RAR) in Vehicular Networks

Block-based reversible data embedding

EMaaS: Cloud-Based Energy Management Service for Distributed Renewable Energy Integration