Proof-carrying code and typed assembly languages aim to minimize the trusted computing base by directly certifying the actual machine code. Unfortunately, these systems cannot get rid of the dependency on a trusted garbage collector. Indeed, constructing a provably type-safe garbage collector is one of the major open problems in the area of certifying compilation. Building on an idea by Wang and Appel, we present a series of new techniques for writing type-safe stop-and-copy garbage collectors. We show how to use intensional type analysis to capture the contract between the mutator and the collector, and how the same method can be applied to support forwarding pointers and generations. Unlike Wang and Appel (which requires whole-program analysis), our new framework directly supports higher-order funtions and is compatible with separate compilation; our collectors are written in provably type-safe languages with rigorous semantics and fully formalized soundness proofs. 1.

Proof-carrying code and typed assembly languages aim to minimize the trusted computing base by directly certifying the actual machine code. Unfortunately, these systems cannot get rid of the dependency on a trusted garbage collector. Indeed, constructing a provably type-safe garbage collector is one of the major open problems in the area of certifying compilation. Building on an idea by Wang and Appel, we present a series of new techniques for writing type-safe stop-and-copy garbage collectors. We show how to use intensional type analysis to capture the contract between the mutator and the collector, and how the same method can be applied to support forwarding pointers and generations. Unlike Wang and Appel (which requires whole-program analysis), our new framework directly supports higher-order funtions and is compatible with separate compilation; our collectors are written in provably type-safe languages with rigorous semantics and fully formalized soundness proofs. 1.

This paper describes the concept of sensor networks which has been made viable by the convergence of microelectro-mechanical systems technology, wireless communications and digital electronics. First, the sensing tasks and the potential sensor networks applications are explored, and a review of factors influencing the design of sensor networks is provided. Then, the communication architecture for sensor networks is outlined, and the algorithms and protocols developed for each layer in the literature are explored. Open research issues for the realization of sensor networks are

Since 1984, the Condor project has enabled ordinary users to do extraordinary computing. Today, the project continues to explore the social and technical problems of cooperative computing on scales ranging from the desktop to the world-wide computational grid. In this chapter, we provide the history and philosophy of the Condor project and describe how it has interacted with other projects and evolved along with the field of distributed computing. We outline the core components of the Condor system and describe how the technology of computing must correspond to social structures. Throughout, we reflect on the lessons of experience and chart the course traveled by research ideas as they grow into production systems.

Recent advancement in wireless communica- tions and electronics has enabled the develop- ment of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments in this field.

A retroviral vector system based on the human immunodeficiency virus (HIV) was de-veloped that, in contrast to a murine leukemia virus-based counterpart, transduced heterologous sequences into HeLa cells and rat fibroblasts blocked in the cell cycle, as well as into human primary macrophages. Additionally, the HIV vector could mediate stable in vivo gene transfer into terminally differentiated neurons. The ability of HIV-based viral vectors to deliver genes in vivo into nondividing cells could increase the applicability of retroviral vectors in human gene therapy. Until now, gene therapy protocols have often relied on vectors derived from retro-viruses such as murine leukemia virus (MLV) (1, 2). These vectors are useful because the genes they transduce are inte-grated into the genome of the target cells, a desirable feature for long-term expression. However, these retroviral vectors can only

We study the problem of object classification when training and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly been studied in computer vision research, but it is the rule rather than the exception, because the world contains tens of thousands of different object classes and for only a very few of them image, collections have been formed and annotated with suitable class labels. In this paper, we tackle the problem by introducing attribute-based classification. It performs object detection based on a human-specified high-level description of the target objects instead of training images. The description consists of arbitrary semantic attributes, like shape, color or even geographic information. Because such properties transcend the specific learning task at hand, they can be pre-learned, e.g. from image datasets unrelated to the current task. Afterwards, new classes can be detected based on their attribute representation, without the need for a new training phase. In order to evaluate our method and to facilitate research in this area, we have assembled a new largescale dataset, “Animals with Attributes”, of over 30,000 animal images that match the 50 classes in Osherson’s classic table of how strongly humans associate 85 semantic attributes with animal classes. Our experiments show that by using an attribute layer it is indeed possible to build a learning object detection system that does not require any training images of the target classes. 1.

ConceptNet is a freely available commonsense knowledgebase and natural-language-processing toolkit which supports many practical textual-reasoning tasks over real-world documents including topic-jisting (e.g. a news article containing the concepts, "gun," "convenience store," "demand money" and "make getaway" might suggest the topics "robbery" and "crime"), affect-sensing (e.g. this email is sad and angry), analogy-making (e.g. "scissors," "razor," "nail clipper," and "sword" are perhaps like a "knife" because they are all "sharp," and can be used to "cut something"), and other contextoriented inferences. The knowledgebase is a semantic network presently consisting of over 1.6 million assertions of commonsense knowledge encompassing the spatial, physical, social, temporal, and psychological aspects of everyday life. Whereas similar large-scale semantic knowledgebases like Cyc and WordNet are carefully handcrafted, ConceptNet is generated automatically from the 700,000 sentences of the Open Mind Common Sense Project -- a World Wide Web based collaboration with over 14,000 authors.

Abstract. We examine the sensitivity of a climate model to a wide range of radiative forcings, including changes of solar irradiance, atmospheric CO2, 03, CFCs, clouds, aerosols, surface •bedo, and a "ghost " forcing introduced at arbitrary heights, latitudes, longitudes, seasons, and times of day. We show that, in general, the climate response, specifically the global mean temperature change, is sensitive to the altitude, latitude, and nature of the forcing; that is, the response to a given forcing can vary by 50 % or more depending upon characteristics of the forcing other than its magnitude measured in watts per square meter. The consistency of the response among different forcings is higher, within 20 % or better, for most of the globally distributed forcingsuspected of influencinglobal mean temperature in the past century, but exceptions occur for certain changes of ozone or absorbing aerosols, for which the climate response is less well behaved. In •1 cases the physic • basis for the variations of the response can be understood. The principal •nechanisms involve •terations of lapse rate and decrease (increase) of large-sc•e cloud cover in layers that are preferentially heated (cooled). Although the magnitude of theseffects must be model-dependent, the existence and

Software reuse is the process ofcreating software systems from existing software rather than building software systems from scratch. ‘l’his simple yet powerful vision was introduced in 1968. Software reuse has, however, failed to become a standard software engineering practice. In an attempt to understand why, researchers have renewed their interest in software reuse and in the obstacles to implementing it. This paper surveys the different approaches to software reuse found in the research literature. It uses a taxonomy to describe and compare the different approaches and make generalizations about the field of software reuse. The taxonomy characterizes each reuse approach interms of its reusable artifacts and the way these artifacts are abstracted, selected, speciahzed, and integrated. Abstraction plays a central role in software reuse. Concise and expressive abstractions are essential if software artifacts are to be effectively reused. The effectiveness of a reuse technique can be evaluatedin terms of cognztzue dwtance-an intuitive gauge of the intellectual effort required to use the technique. Cognitive distance isreduced in two ways: (l) Higher level abstractions ina reuse technique