Silicon Valley versus Corporate Welfare

The estimated $65 billion a year that the federal government now spends on corporate welfare programs harms U.S. industry in general and Silicon Valley companies in particular. The competitiveness of America's semiconductor firms and other high-technology industries would benefit if corporate subsidies were eliminated altogether and the savings were devoted to reducing corporate income taxes, the capital gains tax, or the personal income tax. Given Congress's reluctance to vote down corporate pork, one strategy for eliminating corporate welfare would be to form an independent commission to identify unnecessary subsidies. That would force Congress to vote yes or no on a package of corporate spending subsidies. More than 50 Silicon Valley CEOs agree with this critical assessment of federal subsidies to industry and have signed a "Declaration of Independence" from corporate welfare. In the statement, which appears in the Appendix of this study, the CEOs urge Congress to end corporate welfare "even if it means funding cuts to my own company.

Adaptive Neuro-Fuzzy Inference System for Dynamic Load Balancing in 3GPP LTE

ANFIS is applicable in modeling of key parameters when investigating the performance and functionality of wireless networks. The need to save both capital and operational expenditure in the management of wireless networks cannot be over-emphasized. Automation of network operations is a veritable means of achieving the necessary reduction in CAPEX and OPEX. To this end, next generations networks such WiMAX and 3GPP LTE and LTE-Advanced provide support for self-optimization, self-configuration and self-healing to minimize human-to-system interaction and hence reap the attendant benefits of automation. One of the most important optimization tasks is load balancing as it affects network operation right from planning through the lifespan of the network. Several methods for load balancing have been proposed. While some of them have a very buoyant theoretical basis, they are not practically implementable at the current state of technology. Furthermore, most of the techniques proposed employ iterative algorithm, which in itself is not computationally efficient. This paper proposes the use of soft computing, precisely adaptive neuro-fuzzy inference system for dynamic QoS-aware load balancing in 3GPP LTE. Three key performance indicators (i.e. number of satisfied user, virtual load and fairness distribution index) are used to adjust hysteresis task of load balancing

Loser Pays in Patent Examination

Many scholars and practitioners believe there are too many “weak” patents—those that should not have issued but somehow get approved by the U.S. Patent and Trademark Office (PTO). To the extent they exist, such patents unnecessarily tax real innovation and generate welfare losses for society. Some commentators have focused on the PTO’s failure to exclude weak patents, or the damage caused by these patents in litigation, often by patent trolls. But this scholarly discussion misses the point. The present Article argues that weak patents largely stem from a pricing problem: namely, a patent applicant pays higher patent fees when she succeeds (i.e., receives PTO approval) than when she fails (i.e., is rejected by the PTO). The Article explains why such pricing is precisely backwards, penalizing good patent applications instead of bad ones. It then proposes a novel remedy: import “loser pays” concepts from litigation into patent examination. By forcing unsuccessful patent applicants to pay more, a loser-pays system disincentivizes weak applications and improves application quality. The Article also describes how a loser-pays system could lower patent examiners’ burden and discourage continuation applications, both of which slow down patent examination. In doing so, the Article sketches out a new patent system that is at once more efficient and more effective in weeding out weak patents

Network industries in the new economy

In this paper we discuss two propositions: the supply and demand of knowledge, and network externalities. We outline the characteristics that distinguish knowledge- intensive industries from the general run of manufacturing and service businesses. Knowledge intensity and knowledge specialisation has developed as markets and globalisation have grown, leading to progressive incentives to outsource and for industries to deconstruct. The outcome has been more intensive competition. The paper looks at what is potentially the most powerful economic mechanism: positive feedback, alternatively known as demand-side increasing returns, network effects, or network externalities. We present alternative demand curves that incorporate positive feedback and discuss their potential economic and strategic consequences. We argue that knowledge supply and demand, and the dynamics of network externalities create new situations for our traditional industrial economy such that new types of economies of scale are emerging and "winner takes all" strategies are having more influence. This is the first of a pair of papers. A second paper will take the argument further and look at the nature of firms' strategies in the new world, arguing that technology standards, technical platforms, consumer networks, and supply chain strategies are making a significant contribution to relevant strategies within the new economy

A Noise-Shifting Differential Colpitts VCO

A novel noise-shifting differential Colpitts VCO is presented. It uses current switching to lower phase noise by cyclostationary noise alignment and improve the start-up condition. A design strategy is also devised to enhance the phase noise performance of quadrature coupled oscillators. Two integrated VCOs are presented as design examples

Transmitter Architectures Based on Near-Field Direct Antenna Modulation

A near-field direct antenna modulation (NFDAM) technique is introduced, where the radiated far-field signal is modulated by time-varying changes in the antenna near-field electromagnetic (EM) boundary conditions. This enables the transmitter to send data in a direction-dependent fashion producing a secure communication link. Near-field direct antenna modulation (NFDAM) can be performed by using either switches or varactors. Two fully-integrated proof-of-concept NFDAM transmitters operating at 60 GHz using switches and varactors are demonstrated in silicon proving the feasibility of this approach

Market fields structure & dynamics in industrial automation

There is a research tradition in the economics of standards which addresses standards wars, antitrust concerns or positive externalities from standards. Recent research has also dealt with the process characteristics of standardisation, de facto standard-setting consortia and intellectual property concerns in the technology specification or implementation phase. Nonetheless, there are no studies which analyse capabilities, comparative industry dynamics or incentive structures sufficiently in the context of standard-setting. In my study, I address the characteristics of collaborative research and standard-setting as a new mode of deploying assets beyond motivations well-known from R&D consortia or market alliances. On the basis of a case study of a leading user organisation in the market for industrial automation technology, but also a descriptive network analysis of cross-community affiliations, I demonstrate that there must be a paradoxical relationship between cooperation and competition. More precisely, I explain how there can be a dual relationship between value creation and value capture respecting exploration and exploitation. My case study emphasises the dynamics between knowledge stocks (knowledge alignment, narrowing and deepening) produced by collaborative standard setting and innovation; it also sheds light on an evolutional relationship between the exploration of assets and use cases and each firm's exploitation activities in the market. I derive standard-setting capabilities from an empirical analysis of membership structures, policies and incumbent firm characteristics in selected, but leading, user organisations. The results are as follows: the market for industrial automation technology is characterised by collaboration on standards, high technology influences of other industries and network effects on standards. Further, system integrators play a decisive role in value creation in the customer-specific business case. Standard-setting activities appear to be loosely coupled to the products offered on the market. Core leaders in world standards in industrial automation own a variety of assets and they are affiliated to many standard-setting communities rather than exclusively committed to a few standards. Furthermore, their R&D ratios outperform those of peripheral members and experience in standard-setting processes can be assumed. Standard-setting communities specify common core concepts as the basis for the development of each member's proprietary products, complementary technologies and industrial services. From a knowledge-based perspective, the targeted disclosure of certain knowledge can be used to achieve high innovation returns through systemic products which add proprietary features to open standards. Finally, the interplay between exploitation and exploration respecting the deployment of standard-setting capabilities linked to cooperative, pre-competitive processes leads to an evolution in common technology owned and exploited by the standard-setting community as a particular kind of innovation ecosystem. --standard-setting,innovation,industry dynamics and context,industrial automation

A Breakdown Voltage Multiplier for High Voltage Swing Drivers

A novel breakdown voltage (BV) multiplier is introduced that makes it possible to generate high output voltage swings using transistors with low breakdown voltages. The timing analysis of the stage is used to optimize its dynamic response. A 10 Gb/s optical modulator driver with a differential output voltage swing of 8 V on a 50 Ω load was implemented in a SiGe BiCMOS process. It uses the BV-Doubler topology to achieve output swings twice the collector–emitter breakdown voltage without stressing any single transistor

A Multi-signal Variant for the GPU-based Parallelization of Growing Self-Organizing Networks

Among the many possible approaches for the parallelization of self-organizing networks, and in particular of growing self-organizing networks, perhaps the most common one is producing an optimized, parallel implementation of the standard sequential algorithms reported in the literature. In this paper we explore an alternative approach, based on a new algorithm variant specifically designed to match the features of the large-scale, fine-grained parallelism of GPUs, in which multiple input signals are processed at once. Comparative tests have been performed, using both parallel and sequential implementations of the new algorithm variant, in particular for a growing self-organizing network that reconstructs surfaces from point clouds. The experimental results show that this approach allows harnessing in a more effective way the intrinsic parallelism that the self-organizing networks algorithms seem intuitively to suggest, obtaining better performances even with networks of smaller size.Comment: 17 page