ppxscal/embedding_network huggingface dataset:
Named entity tagged language models
Authors: Y. Gotoh
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

We introduce named entity (NE) language modelling, a stochastic finite state machine approach to identifying both words and NE categories from a stream of spoken data. We provide an overview of our approach to NE tagged language model (LM) generation together with results of the application of such a LM to the task of out-of-vocabulary (OOV) word reduction in large vocabulary speech recognition. Using the Wall Street Journal and Broadcast News corpora, it is shown that the tagged LM was able to reduce the overall word error rate by 14%, detecting up to 70% of previously OOV words. We also describe an example of the direct tagging of spoken data with NE categories.
An Architectural Approach to Preventing Code Injection Attacks
Authors: Ryan Riley, Xuxian Jiang, Dongyan Xu
Venue: Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (2007)

Code injection attacks, despite being well researched, continue to be a problem today. Modern architectural solutions such as the NX-bit and PaX have been useful in limiting the attacks, however they enforce program layout restrictions and can often times still be circumvented by a determined attacker. We propose a change to the memory architecture of modern processors that addresses the code injection problem at its very root by virtually splitting memory into code memory and data memory such that a processor will never be able to fetch injected code for execution. This virtual split memory system can be implemented as a software only patch to an operating system, and can be used to supplement existing schemes for improved protection. Our experimental results show the system is effective in preventing a wide range of code injection attacks while incurring acceptable overhead.
Multi-image reconstruction from aerial images and sequences
Authors: Allen R. Hanson
Venue:  (2006)

Three-dimensional models of the environment have many current uses and great potential applications for intelligence operations, biological sciences, and city planning. How best to accurately and efficiently recover the three-dimensional structure of a scene from a number of two-dimensional aerial images and additional contextual information, however, represents a significant and challenging problem. Sensor data are now widely available from aerial surveys, autonomous aerial vehicles, or other sources. Traditionally, image-space stereo algorithms have been used to turn this data into usable three-dimensional information such as digital elevation models. We contend that a better methodology should involve the use of all available images simultaneously, as well as additional information from other sources, and propose a matching scheme that adjusts a surface model in a world coordinate system (object space) via an optimization process. A cost function is applied in a local surface optimization to minimize the differences between the object-space model and the image data at each location on the surface, taking into account other constraints. We apply constraints due to prior knowledge about the scene as well as resource constraints imposed by limited computational resources. Our model is recovered in a flexible and powerful representation that has already seen wide use in modeling for Computer Aided Design and Manufacturing (CAD/CAM): non-uniform rational B-splines (NURBS).
Build-and-Test Workloads for Grid Middleware: Problem, Analysis, and Applications
Authors: Alexandru Iosup, Dick Epema
Venue: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid (2007)

The Grid promise is starting to materialize today: largescale multi-site infrastructures have grown to assist the work of scientists from all around the world. This tremendous growth can be sustained and continued only through a higher quality of the middleware, in terms of deployability and of correct functionality. A potential solution to this problem is the adoption of industry practices regarding middleware building and testing. However, it is unclear what good build-and-test environments for grid middleware should look like, and how to use them efficiently. In this work we address both these problems. First, we study the characteristics of the NMI build-and-test environment, which handles millions of testing tasks annually, for major Grid middleware such as Condor, Globus, VDT, and gLite. Through the analysis of a system-wide trace covering the past two years we find the main characteristics of the workload, as well as the performance of the system under load. Second, we propose mechanisms for more efficient test management and operation, and for resource provisioning and evaluation. Notably, we propose a generic test optimization technique that reduces the test time by 95%, while achieving 93% of the maximum accuracy, under real conditions.
Optimistic deltas for WWW latency reduction
Authors: Gaurav Banga, Fred Douglis, Michael Rabinovich
Venue: Proceedings of the annual conference on USENIX Annual Technical Conference (1997)

When a machine is connected to the Internet via a slow network, such as a 28.8 Kbps modem, the cumulative latency to communicate over the Internet to World Wide Web servers and then transfer documents over the slow network can be significant. We have built a system that optimistically transfers data that may be out of date, then sends either a subsequent confirmation that the data is current or a delta to change the older version to the current one. In addition, if both sides of the slow link already store the same older version, just the delta need be transferred to update it. Our mechanism is optimistic because it assumes that much of the time there will be sufficient idle time to transfer most or all of the older version before the newer version is available, and because it assumes that the changes between the two versions will be small relative to the actual document. Timings of retrievals of random URLs in the Internet support the former assumption, while experiments using a version repository of Web documents bear out the latter one. Performance measurements of the optimistic delta system demonstrate that deltas significantly reduce latency when both sides cache the old version, and optimistic deltas can reduce latency, to a lesser degree, when content-provider service times are in the range of seconds or longer.
Valgrind: a framework for heavyweight dynamic binary instrumentation
Authors: Nicholas Nethercote, Julian Seward
Venue: ACM SIGPLAN Notices (2007)

Dynamic binary instrumentation (DBI) frameworks make it easy to build dynamic binary analysis (DBA) tools such as checkers and profilers. Much of the focus on DBI frameworks has been on performance; little attention has been paid to their capabilities. As a result, we believe the potential of DBI has not been fully exploited. In this paper we describe Valgrind, a DBI framework designed for building heavyweight DBA tools. We focus on its unique support for shadow values-a powerful but previously little-studied and difficult-to-implement DBA technique, which requires a tool to shadow every register and memory value with another value that describes it. This support accounts for several crucial design features that distinguish Valgrind from other DBI frameworks. Because of these features, lightweight tools built with Valgrind run comparatively slowly, but Valgrind can be used to build more interesting, heavyweight tools that are difficult or impossible to build with other DBI frameworks such as Pin and DynamoRIO.
Nearest-neighbor-preserving embeddings
Authors: Piotr Indyk, Assaf Naor
Venue: ACM Transactions on Algorithms (TALG) (2007)

In this article we introduce the notion of nearest-neighbor-preserving embeddings. These are randomized embeddings between two metric spaces which preserve the (approximate) nearest-neighbors. We give two examples of such embeddings for Euclidean metrics with low &ldquo;intrinsic&rdquo; dimension. Combining the embeddings with known data structures yields the best-known approximate nearest-neighbor data structures for such metrics.
Grid-enpowered Optical Burst Switched Network: Architecture, Protocols and Testbed
Authors: Georgios Zervas, Reza Nejabati, Dimitra Simeonidou
Venue: Proceedings of the Third International Conference on Networking and Services (2007)

This paper presents a novel architecture for Gridenabled optical burst switched networks. We suggest an overall Grid network architecture and we propose a Grid Optical User Network Interface (G.OUNI) able to bridge Grid and OBS network environment. G.OUNI functionalities such as resource availability, discovery, and reservation required to integrate local Grid and OBS domains are presented. Furthermore, extended OBS protocols to support aforementioned services are being described and implemented on an application-aware asynchronous optical burst switched network demonstrator. Fully functional edge and core OBS routers as well as their algorithms and functionalities are being presented.
An efficient algorithm for multidimensional convolution
Authors: A. Elnaggar
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

This paper presents a novel recursive algorithm for generating higher-order multidimensional (or m-D for short) convolution by combining the computation of 3/sup m/ identical lower-order (smaller size) convolution computations, and its implementation in parallel VLSI networks. We show that for 2-D convolutions, with careful design, the number of lower-order 2-D convolutions can be reduced from nine to six with a computation saving of 35%. The resulting VLSI architectures have very simple modular structure, highly regular topology, and use simple arithmetic units.
Ergodic multigram HMM integrating word segmentation and class tagging for Chinese language modeling
Authors: M. Tamoto, Chorkin Chan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

A novel ergodic multigram hidden Markov model (HMM) is introduced which models sentence production as a doubly stochastic process, in which word classes are first produced according to a first order Markov model, and then single or multi-character words are generated independently based on the word classes, without word boundary marked on the sentence. This model can be applied to languages without word boundary markers such as Chinese. With a lexicon containing syntactic classes for each word, its applications include language modeling for recognizers, and integrated word segmentation and class tagging. Pre-segmented and tagged corpus are not needed for training, and both segmentation and tagging are trained in one single model. In this paper, relevant algorithms for this model are presented, and experimental results on a Chinese news corpus are reported.
Statically detecting likely buffer overflow vulnerabilities
Authors: David Larochelle, David Evans
Venue: Proceedings of the 10th conference on USENIX Security Symposium - Volume 10 (2001)

Buffer overflow attacks may be today's single most important security threat. This paper presents a new approach to mitigating buffer overflow vulnerabilities by detecting likely vulnerabilities through an analysis of the program source code. Our approach exploits information provided in semantic comments and uses lightweight and efficient static analyses. This paper describes an implementation of our approach that extends the LCLint annotation-assisted static checking tool. Our tool is as fast as a compiler and nearly as easy to use. We present experience using our approach to detect buffer overflow vulnerabilities in two security-sensitive programs.
Enhance Self-managing Grids by Risk Management
Authors: Kerstin Voss
Venue: Proceedings of the Third International Conference on Networking and Services (2007)

Risk management (RM) processes are used in various application fields since often possible threats should be identified, evaluated, and avoided. In the Grid resource failures are common and likely threats which slow down the establishment of Service Level Agreements (SLAs). Introducing RM into the self-managing Grid is beneficial to estimate and react on such threats. The assessed probabilities for resource failures can be used as a decisive factor in different scenarios. In particular, the resource allocation profits from risk information since jobs can be mapped under consideration of their importance and the stability of available resources. Each RM process is particularly developed for one application field since the threats, the consequences, and the retaliatory actions are individual. The difference between conventional RM processes and the Grid integrated one is that the Grid should be self-managing. This implies that after the configuration RM processes have to be performed totally automatical. This paper presents the Grid RM process which bases on the standard for RM processes developed from the Federation of European Risk Management Associations (FERMA).
Physics-based classification of targets in SAR imagery using subaperture sequences
Authors: L. Carin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

It is well known that radar scattering from an illuminated object is often highly aspect dependent. We have developed a multiaspect target classification technique for SAR imagery that incorporates matching-pursuits feature extraction from each of a sequence of subaperture images, in conjunction with a hidden Markov model that explicitly incorporates the target-sensor motion represented by the image sequence. This approach exploits the aspect dependence of the signal features to facilitate maximum-likelihood identification. We consider SAR imagery containing targets concealed by foliage.
The development of bucketing operators and a supporting operator framework for relational database management systems
Authors: John V. Carlis
Venue:  (2007)

Many researchers rely on relational database management systems (RDBMSs) for storage, retrieval, and analysis of their data. Commercial RDBMSs provide rudimentary pattern matching capabilities to find data items via an exact matching of values, a range of values, or using a pattern string with wild cards. These rudimentary capabilities are insufficient to meet the needs of researchers who wish to perform more sophisticated data analysis. Our focus is in the area of bucketing analysis, where techniques such as clustering, ranking, Ntile, and cross-tabulation associate data items with buckets to provide insight into similarities and differences among the data items. Given the variety of techniques, the researcher is still left with little guidance on how to choose an analysis technique appropriate for his data set or her research questions. After choosing a technique, researchers are still left with the vexing problem of determining how many buckets to use. The contributions of this work are as follows: (1) We designed and implemented a suite of bucketing operators in the form of PL/SQL extensions to the Oracle DBMS. (2) We have developed a parametric framework to compare and contrast bucketing operators using twenty-five different aspects. (3) From the framework we created three operator taxonomies to help researchers choose an operator appropriate to their data sets and research questions. (4) We created a heuristic, RSQRT, to estimate the number of buckets in a data set and show a high correlation between the number of buckets estimated by RSQRT and the number actually reported by researchers using bucketing analysis. We offer a statistical analysis showing that RSQRT and leading alternate estimating technique, the Bayesian information criteria (BIC), generate the same estimates, with RSQRT being less computationally intensive O(log log n) as compared to BIC O(n2).
Two Application languages in software production
Authors: David A. Ladd, J. Christopher Ramming
Venue: Proceedings of the USENIX 1994 Very High Level Languages Symposium Proceedings on USENIX 1994 Very High Level Languages Symposium Proceedings (1994)

PRL5 is an application-oriented language used to maintain the integrity of databases in the AT&T 5ESSTM telecommunications switch. PRL5 is unusual in that it was explicitly designed to eliminate a number of different coding and inspection steps rather than simply to improve individual productivity. Because PRL5 replaced an earlier high-level language named PRL, which in turn replaced a combination of English and C on the same project, it is possible to trace the effect of several fundamentally different languages on this single project. The linguistic evolution has been away from languages describing computation toward a "declarative" high-level language that has been deliberately restricted to accommodate the requirements of certain analyses. Algorithms for checking database constraints are no longer specified by human developers; instead, code is generated from static representations of the constraints themselves. These constraint descriptions can be used in more than one way, whereas a program to check constraints is useful only for performing that particular computation. In effect, PRL5 allows the re-use of project information at a high level, before it has been specialized into particular implementations. The effects of this re-use on quality, interval, and cost are tangible. A key lesson is that application-oriented languages should not be designed to describe computation, they should be designed to express useful facts from which one or more computations can be derived.
The WSDM of Autonomic Computing: Experiences in Implementing Autonomic Web Services
Authors: P. Martin, W. Powley, K. Wilson, W. Tian, T. Xu, J. Zebedee
Venue: Proceedings of the 2007 International Workshop on Software Engineering for Adaptive and Self-Managing Systems (2007)

There is a strong relationship between proposed frameworks for autonomic computing, such as the IBM Blueprint for Autonomic Computing, and the Web Services Distributed Management (WSDM) standard proposed by OASIS. We examine this relationship through a description of our efforts to implement an autonomic Web service using WSDM. The example autonomic Web service is based on our Autonomic Web Service Environment (AWSE) framework. We explain how WSDM is used to implement the AWSE components and evaluate the results of the exercise. We present the lessons we learned in carrying out the implementation effort and draw general conclusions concerning the relationship between autonomic computing and WSDM.
The hotspotTM serviceability agent: an out-of-process high level debugger for a JavaTM virtual machine
Authors: Kenneth Russell, Lars Bak
Venue: Proceedings of the 2001 Symposium on JavaTM Virtual Machine Research and Technology Symposium - Volume 1 (2001)

The HotSpotTM Serviceability Agent (SA) is a set of APIs for the Java programming language which model the state of Sun Microsystems' JavaTM HotSpot Virtual Machine. Unlike most previous debugging systems for dynamic languages which assume a "cooperative" model in which the target process runs code to assist in the debugging process, the SA requires no code to be run in the target VM. Instead, it uses primitives like symbol lookup and reading of process memory to implement its functionality. The SA can transparently examine either live processes or core files, making it suitable for debugging both the VM itself and Java programs in production. We describe the design and implementation of the SA, comparing it to other debugging systems for both statically compiled and dynamic languages, and illustrate future directions for this architecture.
Accelerating Yield Ramp through Real-Time Testing
Authors: Sanjiv Taneja
Venue: Proceedings of the 13th IEEE International On-Line Testing Symposium (2007)

With the increasing need for design specific yield optimization in nanometer technologies, it is becoming increasingly important to accelerate the identification of the root cause of systematic defects under very tight test cost constraints. This talk will give a high level overview of addressing these demanding challenges through a mix of cross-disciplinary EDA technologies spanning scan diagnostics, DFT, ATPG, BIST, DFM and real-time monitoring from ATE systems
A pipeline framework for dependency parsing
Authors: Ming-Wei Chang, Quang Do, Dan Roth
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

Pipeline computation, in which a task is decomposed into several stages that are solved sequentially, is a common computational strategy in natural language processing. The key problem of this model is that it results in error accumulation and suffers from its inability to correct mistakes in previous stages. We develop a framework for decisions made via in pipeline models, which addresses these difficulties, and presents and evaluates it in the context of bottom up dependency parsing for English. We show improvements in the accuracy of the inferred trees relative to existing models. Interestingly, the proposed algorithm shines especially when evaluated globally, at a sentence level, where our results are significantly better than those of existing approaches.
From the Editor in Chief: The Search for Jim, and the Search for Altruism
Authors: Fred Douglis
Venue: IEEE Internet Computing (2007)

When computer scientist Jim Gray disappeared in his sailboat in January, several in the community began trying to locate him through computing technology.
Infrastructure assessment, rehabilitation, and reconstruction
Authors: G. J. Rix, N. C. Baker, L. J. Jacobs, J. Vanegas, A. H. Zureick
Venue: Proceedings of the Frontiers in Education Conference, on 1995. Proceedings., 1995 - Volume 02 (1995)

The United States has allowed much of its civil infrastructure to deteriorate due to age, increased demand on infrastructure systems, and inadequate investment. We must now reverse this decline and "rebuild America"" if the United States is to remain competitive. An important part of this effort is education; it is imperative that we train a new generation of civil engineers with the skills to provide effective solutions to infrastructure problems. With support from an NSF Combined Research Curriculum Development award, the Georgia Tech School of Civil and Environmental Engineering is developing an undergraduate civil engineering curriculum track to address this need Georgia Tech's existing track oriented civil engineering undergraduate curriculum provides an ideal environment for developing a new track that focuses on deterioration science, assessment technologies, renewal engineering, and project management. Using existing isolated courses as a foundation, the curriculum development effort will: introduce several new courses which supplement the existing courses; incorporate cognitive science and educational technologies into the curriculum; implement an educational assessment program to measure the effectiveness of the curriculum development effort; and disseminate the resulting curriculum to a wide audience via multimedia information servers such those on the World Wide Web and through continuing education courses to educate practicing engineers in the public and private sectors.