IBM

About: IBM is a company organization based out in Armonk, New York, United States. It is known for research contribution in the topics: Layer (electronics) & Signal. The organization has 134567 authors who have published 253905 publications receiving 7458795 citations. The organization is also known as: International Business Machines Corporation & Big Blue.

The influence of the surface migration of gold on the growth of silicon nanowires

Abstract: Silicon nanowires hold great promise as components of tiny electronic devices, but the usual method of growing them is poorly understood. New work shows that excessive cleanliness can actually stunt a nanowire's growth. They are made by the ‘vapour–liquid–solid’ method, in which a tiny liquid droplet of a metal such as gold absorbs silicon atoms from a gaseous precursor molecule. As the droplet saturates with silicon, it grows a solid, cylindrical silicon crystal whose diameter is determined by the size of the droplet. But in conditions of extreme cleanliness, gold atoms from the droplet can migrate over the surface of the growing nanowire, resulting in misshapen structures. Interest in nanowires continues to grow, fuelled in part by applications in nanotechnology1,2,3,4,5. The ability to engineer nanowire properties makes them especially promising in nanoelectronics6,7,8,9. Most silicon nanowires are grown using the vapour–liquid–solid (VLS) mechanism, in which the nanowire grows from a gold/silicon catalyst droplet during silicon chemical vapour deposition10,11,12,13. Despite over 40 years of study, many aspects of VLS growth are not well understood. For example, in the conventional picture the catalyst droplet does not change during growth, and the nanowire sidewalls consist of clean silicon facets10,11,12,13. Here we demonstrate that these assumptions are false for silicon nanowires grown on Si(111) under conditions where all of the experimental parameters (surface structure, gas cleanliness, and background contaminants) are carefully controlled. We show that gold diffusion during growth determines the length, shape, and sidewall properties of the nanowires. Gold from the catalyst droplets wets the nanowire sidewalls, eventually consuming the droplets and terminating VLS growth. Gold diffusion from the smaller droplets to the larger ones (Ostwald ripening) leads to nanowire diameters that change during growth. These results show that the silicon nanowire growth is fundamentally limited by gold diffusion: smooth, arbitrarily long nanowires cannot be grown without eliminating gold migration.

Knowledge and common knowledge in a distributed environment

Abstract: Reasoning about knowledge seems to play a fundamental role in distributed systems. Indeed, such reasoning is a central part of the informal intuitive arguments used in the design of distributed protocols. Communication in a distributed system can be viewed as the act of transforming the system's state of knowledge. This paper presents a general framework for formalizing and reasoning about knowledge in distributed systems. It is shown that states of knowledge of groups of processors are useful concepts for the design and analysis of distributed protocols. In particular, distributed knowledge corresponds to knowledge that is “distributed” among the members of the group, while common knowledge corresponds to a fact being “publicly known.” The relationship between common knowledge and a variety of desirable actions in a distributed system is illustrated. Furthermore, it is shown that, formally speaking, in practical systems common knowledge cannot be attained. A number of weaker variants of common knowledge that are attainable in many cases of interest are introduced and investigated.

Studying cooperation and conflict between authors with history flow visualizations

Abstract: The Internet has fostered an unconventional and powerful style of collaboration: "wiki" web sites, where every visitor has the power to become an editor. In this paper we investigate the dynamics of Wikipedia, a prominent, thriving wiki. We make three contributions. First, we introduce a new exploratory data analysis tool, the history flow visualization, which is effective in revealing patterns within the wiki context and which we believe will be useful in other collaborative situations as well. Second, we discuss several collaboration patterns highlighted by this visualization tool and corroborate them with statistical analysis. Third, we discuss the implications of these patterns for the design and governance of online collaborative social spaces. We focus on the relevance of authorship, the value of community surveillance in ameliorating antisocial behavior, and how authors with competing perspectives negotiate their differences.

Trellis-coded modulation with redundant signal sets Part I: Introduction

Abstract: rellis-Coded Modulation (TCM) has evolved over the past decade as a combined coding and modulation technique for digital transmission over band-limited channels. Its main attraction comes from the fact that it allows the achievement of significant coding gains over conventional uncoded multilevel modulation without compromising bandwidth efficiency. T h e first TCM schemes were proposed in 1976 [I]. Following a more detailed publication [2] in 1982, an explosion of research and actual implementations of TCM took place, to the point where today there is a good understanding of the theory and capabilities of TCM methods. In Part 1 of this two-part article, an introduction into TCM is given. T h e reasons for the development of TCM are reviewed, and examples of simple TCM schemes are discussed. Part I1 [I51 provides further insight into code design and performance, and addresses. recent advances in TCM. TCM schemes employ redundant nonbinary modulation in combination with a finite-state encoder which governs the selection of modulation signals to generate coded signal sequences. In the receiver, the noisy signals are decoded by a soft-decision maximum-likelihood sequence decoder. Simple four-state TCM schemes can improve. the robustness of digital transmission against additive noise by 3 dB, compared to conventional , uncoded modulation. With more complex TCM schemes, the coding gain can reach 6 dB or more. These gains are obtained without bandwidth expansion or reduction of the effective information rate as required by traditional error-correction schemes. Shannon's information theory predicted the existence of coded modulation schemes with these characteristics more than three decades ago. T h e development of effective TCM techniques and today's signal-processing technology now allow these ,gains to be obtained in practice. Signal waveforms representing information sequences ~ are most impervious to noise-induced detection errors if they are very different from each other. Mathematically, this translates into therequirement that signal sequences should have large distance in Euclidean signal space. ~ T h e essential new concept of TCM that led to the afore-1 mentioned gains was to use signal-set expansion to I provide redundancy for coding, and to design coding and ' signal-mapping functions jointly so as to maximize ~ directly the \" free distance \" (minimum Euclidean distance) between coded signal sequences. This allowed the construction of modulation codes whose free distance significantly exceeded the minimum distance between uncoded modulation signals, at the same information rate, bandwidth, and signal power. The term \" …

Thumbs up? Sentiment Classification using Machine Learning Techniques

Abstract: We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three machine learning methods we employed (Naive Bayes, maximum entropy classification, and support vector machines) do not perform as well on sentiment classification as on traditional topic-based categorization. We conclude by examining factors that make the sentiment classification problem more challenging.