Mitre (United States)

ABSTRACT This paper develops a general framework for analyzing corporate risk management policies. We begin by observing that if external sources of finance are more costly to corporations than internally generated funds, there will typically be a benefit to hedging: hedging adds value to the extent that it helps ensure that a corporation has sufficient internal funds available to take advantage of attractive investment opportunities. We then argue that this simple observation has wide ranging implications for the design of risk management strategies. We delineate how these strategies should depend on such factors as shocks to investment and financing opportunities. We also discuss exchange rate hedging strategies for multinationals, as well as strategies involving “nonlinear” instruments like options.

Over the last couple of years, face recognition researchers have been developing new techniques. These developments are being fueled by advances in computer vision techniques, computer design, sensor design, and interest in fielding face recognition systems. Such advances hold the promise of reducing the error rate in face recognition systems by an order of magnitude over Face Recognition Vendor Test (FRVT) 2002 results. The face recognition grand challenge (FRGC) is designed to achieve this performance goal by presenting to researchers a six-experiment challenge problem along with data corpus of 50,000 images. The data consists of 3D scans and high resolution still imagery taken under controlled and uncontrolled conditions. This paper describes the challenge problem, data corpus, and presents baseline performance and preliminary results on natural statistics of facial imagery.

As communications technology continues its rapid transition from analog to digital, more functions of contemporary radio systems are implemented in software, leading toward the software radio. This article provides a tutorial review of software radio architectures and technology, highlighting benefits, pitfalls, and lessons learned. This includes a closer look at the canonical functional partitioning of channel coding into antenna, RF, IF, baseband, and bitstream segments. A more detailed look at the estimation of demand for critical resources is key. This leads to a discussion of affordable hardware configurations, the mapping of functions to component hardware, and related software tools. This article then concludes with a brief treatment of the economics and likely future directions of software radio technology.>

Increasingly, network applications must communicate with counterparts across disparate networking environments characterized by significantly different sets of physical and operational constraints; wide variations in transmission latency are particularly troublesome. The proposed Interplanetary Internet, which must encompass both terrestrial and interplanetary links, is an extreme case. An architecture based on a "least common denominator" protocol that can operate successfully and (where required) reliably in multiple disparate environments would simplify the development and deployment of such applications. The Internet protocols are ill suited for this purpose. We identify three fundamental principles that would underlie a delay-tolerant networking (DTN) architecture and describe the main structural elements of that architecture, centered on a new end-to-end overlay network protocol called Bundling. We also examine Internet infrastructure adaptations that might yield comparable performance but conclude that the simplicity of the DTN architecture promises easier deployment and extension.

Wireless multimedia applications require significant bandwidth, some of which will be provided by third-generation (3G) services. Even with substantial investment in 3G infrastructure, the radio spectrum allocated to 3G will be limited. Cognitive radio offers a mechanism for the flexible pooling of radio spectrum using a new class of protocols called formal radio etiquettes. This approach could expand the bandwidth available for conventional uses (e.g. police, fire and rescue) and extend the spatial coverage of 3G in a novel way. Cognitive radio is a particular extension of software radio that employs model-based reasoning about users, multimedia content, and communications context. This paper characterizes the potential contributions of cognitive radio to spectrum pooling and outlines an initial framework for formal radio-etiquette protocols.

This paper is an expository survey of results on integral representations and discrete sum expansions of functions in $L^2 ({\bf R})$ in terms of coherent states. Two types of coherent states are considered: Weyl–Heisenberg coherent states, which arise from translations and modulations of a single function, and affine coherent states, called ’wavelets,’ which arise as translations and dilations of a single function. In each case it is shown how to represent any function in $L^2 ({\bf R})$ as a sum or integral of these states. Most of the paper is a survey of literature, most notably the work of I. Daubechies, A. Grossmann, and J. Morlet. A few results of the authors are included.

The draft IEEE 802.11 wireless local area network (WLAN) specification is approaching completion. In this article, the IEEE 802.11 protocol is explained, with particular emphasis on the medium access control sublayer. Performance results are provided for packetized data and a combination of packetized data and voice over the WLAN. Our performance investigation reveals that an IEEE 802.11 network may be able to carry traffic with time-bounded requirements using the point coordination function. However, our findings suggest that packetized voice traffic must be handled in conjunction with an echo canceler.

ABSTRACT Standard models of informed speculation suggest that traders try to learn information that others do not have. This result implicitly relies on the assumption that speculators have long horizons, i.e., can hold the asset forever. By contrast, we show that if speculators have short horizons, they may herd on the same information, trying to learn what other informed traders also know. There can be multiple herding equilibria, and herding speculators may even choose to study information that is completely unrelated to fundamentals.

This memo provides information for the Internet community. It does not specify an Internet standard of any kind. Distribution of this memo is unlimited. Copyright Notice Copyright (C) The IETF Trust (2007). IESG Note

Upon defining vector spherical partial waves {${\mathbf{\ensuremath{\Psi}}}_{n}$} as a basis, a matrix equation is derived describing scattering for general incidence on objects of arbitrary shape. With no losses present, the scattering matrix is then obtained in the symmetric, unitary form $S=\ensuremath{-}{\stackrel{^}{Q}}^{\ensuremath{'}*}{\stackrel{^}{Q}}^{*}$, where (perfect conductor) $\stackrel{^}{Q}$ is the Schmidt orthogonalization of ${Q}_{n{n}^{\ensuremath{'}}}=(\frac{k}{\ensuremath{\pi}})\ensuremath{\int}d\mathbf{\ensuremath{\sigma}}\ifmmode\cdot\else\textperiodcentered\fi{}[(\ensuremath{\nabla}\ifmmode\times\else\texttimes\fi{}\mathrm{Re}{\mathbf{\ensuremath{\Psi}}}_{n})\ifmmode\times\else\texttimes\fi{}{\mathbf{\ensuremath{\Psi}}}_{{n}^{\ensuremath{'}}}]$, integration extending over the object surface. For quadric (separable) surfaces, $Q$ itself becomes symmetric, effecting considerable simplification. A secular equation is given for constructing eigenfunctions of general objects. Finally, numerical results are presented and compared with experimental measurements.

Subband coding has become quite popular for the source encoding of speech. This paper presents a simple yet efficient extension of this concept to the source coding of images. We specify the constraints for a set of two-dimensional quadrature mirror filters (QMF's) for a particular frequency-domain partition, and show that these constraints are satisfied by a separable combination of one-dimensional QMF's. Bits are then optimally allocated among the subbands to minimize the mean-squared error for DPCM coding of the subbands. Also, an adaptive technique is developed to allocate the bits within each subband by means of a local variance mask. Optimum quantization is employed with quantizers matched to the Laplacian distribution. Subband coded images are presented along with their signal-to-noise ratios (SNR's). The SNR performance of the subband coder is compared to that of the adaptive discrete cosine transform (DCT), vector quantization, and differential vector quantization for bit rates of 0.67, 1.0, and 2.0 bits per pixel for 256 × 256 monochrome images. The adaptive subband coder has the best SNR performance.

If patterns are good ideas that can be re-applied to new situations, AntiPatterns: Refactoring Software, Architectures, and Projects in Crisis looks at what goes wrong in software development, time and time again. This entertaining and often enlightening text defines what seasoned developers have long suspected: despite advances in software engineering, most software projects still fail to meet expectations--and about a third are cancelled altogether. The authors of AntiPatterns draw on extensive industry experience, their own and others, to help define what's wrong with software development today. They outline reasons why problem patterns develop (such as sloth, avarice, and greed) and proceed to outline several dozen patterns that can give you headaches or worse. Their deadliest hit list begins with the Blob, where one object does most of the work in a project, and Continuous Obsolescence, where technology changes so quickly that developers can't keep up. Some of the more entertaining antipatterns include the Poltergeist (where do-nothing classes add unnecessary overhead), the Boat Anchor (a white elephant piece of hardware or software bought at great cost) and the Golden Hammer (a single technology that is used for every conceivable programming problem). The authors then proceed to define antipatterns oriented toward management problems with software (including Death by Planning and Project Mismanagement, along with several miniature antipatterns, that help define why so many software projects are late and overbudget). The authors use several big vendors' technologies as examples of today's antipatterns. Luckily, they suggest ways to overcome antipatterns and improve software productivity in refactored solutions that can overcome some of these obstacles. However, this is a realistic book, a mix of Dilbert and software engineering. A clever antidote to getting too optimistic about software development, AntiPatterns should be required reading for any manager facing a large-scale development project. --Richard Dragan

International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international cancer registry collecting data from 19 cancer centers, makes data from >130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional real-world longitudinal clinical data, including treatment and outcome data, are being collected by the AACR Project GENIE Biopharma Collaborative using the PRISSMM data curation model. Several thousand of these cases are now also available in cBioPortal. We have significantly enhanced the functionalities of cBioPortal to support the visualization and analysis of this rich clinico-genomic linked dataset, as well as datasets generated by other centers and consortia. Examples of these enhancements include (i) visualization of the longitudinal clinical and genomic data at the patient level, including timelines for diagnoses, treatments, and outcomes; (ii) the ability to select samples based on treatment status, facilitating a comparison of molecular and clinical attributes between samples before and after a specific treatment; and (iii) survival analysis estimates based on individual treatment regimens received. Together, these features provide cBioPortal users with a toolkit to interactively investigate complex clinico-genomic data to generate hypotheses and make discoveries about the impact of specific genomic variants on prognosis and therapeutic sensitivities in cancer. SIGNIFICANCE: Enhanced cBioPortal features allow clinicians and researchers to effectively investigate longitudinal clinico-genomic data from patients with cancer, which will improve exploration of data from the AACR Project GENIE Biopharma Collaborative and similar datasets.

With the explosion in the quantity of on-line text and multimedia information in recent years, there has been a renewed interest in automatic summarization. This book provides a systematic introduction to the field, explaining basic definitions, the strategies used by human summarizers, and automatic methods that leverage linguistic and statistical knowledge to produce extracts and abstracts. Drawing from a wealth of research in artificial intelligence, natural language processing, and information retrieval, the book also includes detailed assessments of evaluation methods and new topics such as multi-document and multimedia summarization. Previous automatic summarization books have been either collections of specialized papers, or else authored books with only a chapter or two devoted to the field as a whole. This is the first textbook on the subject, developed based on teaching materials used in two one-semester courses. To further help the student reader, the book includes detailed case studies, accompanied by end-of-chapter reviews and an extensive glossary. Audience: students and researchers, as well as information technology managers, librarians, and anyone else interested in the subject.

A method of forming synthetic aperture radar (SAR) images of moving targets without using any specific knowledge of the target motion is presented. The new method uses a unique processing kernel that involves a one-dimensional interpolation of the deramped phase history which we call keystone formatting. This preprocessing simultaneously eliminates the effects of linear range migration for all moving targets regardless of their unknown velocity. Step two of the moving target imaging technique involves a two-dimensional focusing of the movers to remove residual quadratic range migration errors. The third and last step removes cubic and higher order defocusing terms. This imaging technique is demonstrated using SAR data collected as part of DARPA's Moving Target Exploitation (MTE) program.

Reporting on the SWEBOK project, the authors-who represent the project's editorial team-discuss the three-phase plan to characterize a body of knowledge, a vital step toward developing software engineering as a profession.

This note describes a scoring scheme for the coreference task in MUC6. It improves on the original approach by: (1) grounding the scoring scheme in terms of a model; (2) producing more intuitive recall and precision scores; and (3) not requiring explicit computation of the transitive closure of coreference. The principal conceptual difference is that we have moved from a syntactic scoring model based on following coreference links to an approach defined by the model theory of those links.

Abstract As a method of sharing a secret, e.g., a secret key, Shamir's (k, n) threshold method is well known. However, Shamir's method has a problem in that general access structures cannot be realized. This paper shows that by providing the trustees with several information data concerning the distributed information of the (k, n) threshold method, any access structure can be realized. the update with the change of the secret trustees and the relation to the threshold graph are also discussed.

Twitter is a new web application playing dual roles of online social networking and microblogging. Users communicate with each other by publishing text-based posts. The popularity and open structure of Twitter have attracted a large number of automated programs, known as bots, which appear to be a double-edged sword to Twitter. Legitimate bots generate a large amount of benign tweets delivering news and updating feeds, while malicious bots spread spam or malicious contents. More interestingly, in the middle between human and bot, there has emerged cyborg referred to either bot-assisted human or human-assisted bot. To assist human users in identifying who they are interacting with, this paper focuses on the classification of human, bot, and cyborg accounts on Twitter. We first conduct a set of large-scale measurements with a collection of over 500,000 accounts. We observe the difference among human, bot, and cyborg in terms of tweeting behavior, tweet content, and account properties. Based on the measurement results, we propose a classification system that includes the following four parts: 1) an entropy-based component, 2) a spam detection component, 3) an account properties component, and 4) a decision maker. It uses the combination of features extracted from an unknown user to determine the likelihood of being a human, bot, or cyborg. Our experimental evaluation demonstrates the efficacy of the proposed classification system.

Accurate prediction of demographic attributes from social media and other informal online content is valuable for marketing, personalization, and legal in-vestigation. This paper describes the construction of a large, multilingual dataset labeled with gender, and investigates statistical models for determining the gender of uncharacterized Twitter users. We explore several different classifier types on this dataset. We show the degree to which classifier accuracy varies based on tweet volumes as well as when various kinds of profile metadata are included in the models. We also perform a large-scale human assessment us-ing Amazon Mechanical Turk. Our methods signifi-cantly out-perform both baseline models and almost all humans on the same task. 1