ppxscal/embedding_network huggingface dataset:
An application analysis framework for polymorphic chip multiprocessors
Authors: Oyekunle Olukotun
Venue:  (2005)

An emerging class of architectures, polymorphic chip multiprocessors (CMP), exploits both data and thread parallelism simultaneously in a reconfigurable chip multiprocessor. In order to maximize the efficiency of the architecture, the programmer must not only select the appropriate regions to parallelize&mdash;a problem that continues to plague even traditional parallel programming, but also determine how to configure the architecture for optimal performance. To meet the unique programming challenges posed by polymorphic architectures and minimize programmer effort, we present the design and implementation of the SAPIENT parallel analysis framework. SAPIENT is a profile-based analysis tool that facilitates the efficient manual transformation of uniprocessor applications into multilevel parallel applications that can be executed on polymorphic CMP architectures. We demonstrate how application characteristics are used to detect thread and data level parallelism in sequential applications and analyze application behavior. We further demonstrate how SAPIENT successfully estimates parallel performance and identifies the combinations of parallel regions and corresponding architecture configurations that perform optimally. However, many applications do not attain sufficient performance based solely on uniprocessor code and optimizations are often required. Therefore, we develop a technique for identifying source code optimizations and providing detailed feedback to the programmer to enable the efficient evaluation and implementation of optimizations. Consequently, programmer effort is greatly reduced by SAPIENT analysis, speeding up the manual parallelization process and increasing the number of applications that can be considered for polymorphic execution.
Proceedings of the 12th ACM conference on Computer and communications security
Venue: Conference on Computer and Communications Security (2005)

It is a pleasure and honor to welcome you to the 12th ACM Conference on Computer and Communications Security. This year's conference will continue its tradition of being a premier forum for the presentation of results in security research. We have an excellent program comprising of the research track, industry track, eight workshops and four tutorials that cover a variety of interests and disciplines in the area of computer and communications security.
mCLOVER: mobile content-based leaf image retrieval system
Authors: Suckchul Kim, Yoonsik Tak, Yunyoung Nam, Eenjun Hwang
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

This demonstration presents a content-based leaf image retrieval system that supports wired/wireless access. For example, if we want to know about a plant that we encounter in a mountain or field, we might look it up in an illustrated book. But, it will take a long time to search due to the lack of appropriate indexing or search clues and huge amounts of similar plants. In order to solve this problem, we developed a content-based leaf image retrieval system called mCLOVER that supports both wired and wireless access and includes a set of novel features for easy querying and efficient retrieval.
Stealth Breakpoints
Authors: Amit Vasudevan, Ramesh Yerraballi
Venue: Proceedings of the 21st Annual Computer Security Applications Conference (2005)

Microscopic analysis of malicious code (malware) requires the aid of a variety of powerful tools. Chief among them is a debugger that enables runtime binary analysis at an instruction level. One of the important services provided by a debugger is the ability to stop execution of code at an arbitrary point during runtime, using breakpoints. Software breakpoints support an unlimited number of breakpoint locations by changing the code being debugged so that it can be interrupted during runtime. Most, if not all, malware are very sensitive to code modification with self-modifying and/or self-checking (SM-SC) capabilities, rendering the use of software breakpoints limited in their scope. Hardware breakpoints supported by the underlying processor, on the other hand, use a subset of the processor register set and exception mechanisms to provide breakpoints that do not entail code modification. This makes hardware breakpoints the most powerful breakpoint mechanism for malware analysis. However, current processors provide a very limited number of hardware breakpoints (typically 2-4 locations). Thus, a serious restriction is imposed on the debugger to set a desired number of breakpoints without resorting to the limited alternative of software breakpoints. Also, with the ever evolving nature of malware, there are techniques being employed that prevent the use of hardware breakpoints. This calls for a new breakpoint mechanism that retains the features of hardware breakpoints while providing an unlimited number of breakpoints, which cannot be detected or countered. In this paper, we present the concept of stealth breakpoints and discuss the design and implementation of VAMPiRE 1, a realization of this concept. VAMPiRE cannot be detected or countered and provides unlimited number of breakpoints to be set on code, data, and I/O with the same precision as that of hardware breakpoints. It does so by employing a subtle combination of simple stealth techniques using virtual memory and hardware single-stepping mechanisms that are available on all processors, old and new. This technique makes VAMPiRE portable to any architecture, providing powerful breakpoint ability similar to hardware breakpoints for microscopic malware analysis.
A Mobile Agent-based P2P Model for Autonomous Security Hole Discovery
Authors: Xin Wang, Ji Zheng, Kun Xiao, Xiangyang Xue, CK Toh
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

Generally an agent-based security system is constructed hierarchical, with a central manager acting as head of the whole system. However, the manager becomes a bottleneck for being connected by each client. It can even overload when too many clients request service simultaneously. The whole system may collapse when the central manager is attacked. And these systems are passive to detect and deal with the secure problem. Hereby we present a mobile agent-based P2P Model for Autonomous Security Hole Discovery (MASHD). It can detect infection and network intrusion based on knowledge of the local host. Viruses will be removed and connection will be refused after identification. In case of a suspicious activity, MASHD initiates a voting approach to make a collective decision and take further action. The integration of peer-to-peer behavior with mobile agents reduces latency and load; however, flexibility, effectivity, security and cooperation of the system are enhanced.
Physically based models for liquid sounds
Authors: Kees van den Doel
Venue: ACM Transactions on Applied Perception (TAP) (2005)

A physically based liquid sound synthesis methodology is developed. The fundamental mechanism for the production of liquid sounds is identified as the acoustic emission of bubbles. After reviewing the physics of vibrating bubbles as it is relevant to audio synthesis, a sound model for isolated single bubbles is developed and validated with a small user study. A stochastic model for the real-time interactive synthesis of complex liquid sounds such as produced by streams, pouring water, rivers, rain, and breaking waves is based on the synthesis of single bubble sounds. It is shown how realistic complex high dimensional sound spaces can be synthesized in this manner.
Distributed Computing Middleware for Small and Medium-Size Enterprise
Authors: Toshiaki Ohkuma, Yoichi Suzuki, Yoshitaka Kojima, Yoshio Tago
Venue: Proceedings of the First International Conference on e-Science and Grid Computing (2005)

A middleware named EnGrid for distributed computing has been developed. The EnGrid employs the notion of pure peer-to-peer (P2P) for ease of use, not for sharing computer resources across the world as in conventional P2P. We have also developed three PSE systems on EnGrid for civil engineering applications: parameter sweep system for finite element method (FEM), parameter optimization system for FEM, and the visualization system for geological sections of 3 dimensional models. We show that the calculation time of these systems can be shortened by distributed computing on EnGrid. Due to its general nature, EnGrid will be useful not only for civil engineering but also in other fields as well.
Proposal of a neuro-fuzzy model of a WWWserver
Authors: Krzysztof Zatwarnicki
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

This paper presents the ways of designing simulation models of web servers. At the beginning Queuing Network models are introduced, those models are generally known and often used in the initial phase of research on particular technical solutions. Next, an entirely new approach to the issue discussed is presented - neuro-fuzzy models, thanks to which it is possible to automate the process of designing simulation models. In Section 4 results of comparative tests of these two models are presented. Based on these results it can be concluded that neuro-fuzzy models are accurate and can be used in simulation research.
Fast Runge-Kutta approximation of inhomogeneous parabolic equations
Authors: Mar&#x00ed;a L&#x00f3;pez-Fern&#x00e1;ndez, Christian Lubich, Cesar Palencia, Achim Sch&#x00e4;dle
Venue: Numerische Mathematik (2005)

The result after N steps of an implicit Runge-Kutta time discretization of an inhomogeneous linear parabolic differential equation is computed, up to accuracy &#x025b;, by solving only**linear systems of equations. We derive, analyse, and numerically illustrate this fast algorithm.
Improving Scalability of Data-Centric Services using In-Network Traffic Inspection
Authors: Congchun He, Vijay Karamcheti
Venue: Proceedings of the 10th International Workshop on Web Content Caching and Distribution (2005)

A growing number of network services are being constructed using the XML Web Services architecture. By design, client interactions with such services are governed by open protocols such as UDDI, WSDL, and SOAP that permit programmatic discovery and functionality invocation. Additionally, for a large number of currently deployed services, it is possible to interpret service requests as structured accesses against a (physical or virtual) database. These two trends suggest the possibility of building network intermediaries that can inspect traffic flowing between clients and services, infer models for service access patterns, and potentially improve service scalability by taking actions such as replication, request redirection, or admission control. This paper reports on our experience designing and implementing such a network intermediary architecture. Experiments on an emulated WAN using synthetic workloads show that our approach achieves significant performance improvements in client-perceived response time.
Cognitive difficulties and access to information systems: an interaction design perspective
Authors: Peter Gregor, Anna Dickinson
Venue: Issue 83 (September 2005) (2005)

In this paper we discuss our human computer interaction research on improving the accessibility and supportiveness of information systems for people with cognitive difficulties, whether these are developmental impairments, such as dyslexia, or acquired difficulties, most often an effect of the ageing process. The aetiology and symptoms of these conditions are diverse, yet the challenges they pose to the design of information systems can be addressed using a similar approach (see, for example, Dickinson et al., 2003). The concept of accessibility for this group cannot be an extension of traditional accessibility approaches, which focus on the provision of opportunities to the technically adept: accessibility for this group demands new approaches and a reconsideration of the design of information systems.
A second order primitive preconditioner for solving all speed multi-phase flows
Authors: Samet Y. Kadioglu, Mark Sussman, Stanley Osher, Joseph P. Wright, Myungjoo Kang
Venue: Journal of Computational Physics (2005)

In this paper, we present a new second order primitive preconditioner technique for solving all speed multi-phase flow problems. With this technique, one can compute both compressible and incompressible flows with Mach-uniform accuracy and efficiency (i.e., accuracy and efficiency of the method are independent of Mach number). The new primitive preconditioner can handle both strong and weak shocks, providing highly resolved shock solutions together with correct shock speeds. In addition, the new technique performs very well at the zero Mach limit. In the case of multi-phase flow, the new primitive preconditioner technique enables one to accurately treat phase boundaries in which there is a large impedance mismatch. The present method is tested on a variety of problems from low (low speed) to high Mach number (high speed) flows including multi-phase flow tests, i.e., computing the growth and collapse of adiabatic bubbles for study of underwater explosions. The numerical results show that the newly proposed method supersedes existing up-to-date numerical techniques in its category.
Face Identification by a Cascade of Rejection Classifiers
Authors: Quan Yuan, Ashwin Thangali, Stan Sclaroff
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

Nearest neighbor search is commonly employed in face recognition but it does not scale well to large dataset sizes. A strategy to combine rejection classifiers into a cascade for face identification is proposed in this paper. A rejection classifier for a pair of classes is defined to reject at least one of the classes with high confidence. These rejection classifiers are able to share discriminants in feature space and at the same time have high confidence in the rejection decision. In the face identification problem, it is possible that a pair of known individual faces are very dissimilar. It is very unlikely that both of them are close to an unknown face in the feature space. Hence, only one of them needs to be considered. Using a cascade structure of rejection classifiers, the scope of nearest neighbor search can be reduced significantly. Experiments on Face Recognition Grand Challenge (FRGC) version 1 data demonstrate that the proposed method achieves significant speed up and an accuracy comparable with the brute force Nearest Neighbor method. In addition, a graph cut based clustering technique is employed to demonstrate that the pairwise separability of these rejection classifiers is capable of semantic grouping.
Error Estimation for Reduced-Order Models of Dynamical Systems
Authors: Chris Homescu, Linda R. Petzold, Radu Serban
Venue: SIAM Journal on Numerical Analysis (2005)

The use of reduced-order models to describe a dynamical system is pervasive in science and engineering. Often these models are used without an estimate of their error or range of validity. In this paper we consider dynamical systems and reduced models built using proper orthogonal decomposition. We show how to compute estimates and bounds for these errors by a combination of small sample statistical condition estimation and error estimation using the adjoint method. Most importantly, the proposed approach allows the assessment of regions of validity for reduced models, i.e., ranges of perturbations in the original system over which the reduced model is still appropriate. Numerical examples validate our approach: the error norm estimates approximate well the forward error, while the derived bounds are within an order of magnitude.
Multi-Stage Classification
Authors: Ted E. Senator
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

While much research has focused on methods for evaluating and maximizing the accuracy of classifiers either individually or in ensembles, little effort has been devoted to analyzing how classifiers are typically deployed in practice. In many domains, classifiers are used as part of a multi-stage process that increases accuracy at the expense of more data collection and/or more processing resources as the likelihood of a positive class label increases. This paper systematically explores the tradeoffs inherent in constructing these multi-stage classifiers from a series of increasingly accurate and expensive individual classifiers, considering a variety of metrics such as accuracy, cost/benefit ratio, and lift. It suggests architectures appropriate for both independent instances and for highly linked data.
Localized content based image retrieval
Authors: Rouhollah Rahmani, Sally A. Goldman, Hui Zhang, John Krettek, Jason E. Fritts
Venue: Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval (2005)

Classic Content-Based Image Retrieval (CBIR) takes a single non-annotated query image, and retrieves similar images from an image repository. Such a search must rely upon a holistic (or global) view of the image. Yet often the desired content of an image is not holistic, but is localized. Specifically, we define Localized Content-Based Image Retrieval as a CBIR task where the user is only interested in a portion of the image, and the rest of the image is irrelevant. Many classic CBIR systems use relevance feedback to obtain images labeled as desirable or not desirable. Yet, these labeled images are typically used only to re-weight the features used within a global similarity measure. In this paper we present a localized CBIR system, acciop, that uses labeled images in conjunction with a multiple-instance learning algorithm to first identify the desired object and re-weight the features, and then to rank images in the database using a similarity measure that is based upon individual regions within the image. We evaluate our system using a five-category natural scenes image repository, and benchmark data set, SIVAL, that we have constructed with 25 object categories.
Systolic Array-Based String Matching Unit for Spam Blocking
Authors: A. N. M. Ehtesham Rafiq, M. Watheq El-Kharashi, Fayez Gebali
Venue: Proceedings of the Fifth International Workshop on System-on-Chip for Real-Time Applications (2005)

In this paper, we propose a hardware solution to assist spam blocking. We determined the most computationally intensive task in spam blocking, i.e., string matching, and here present a systolic array implementation in hardware for it to increase its efficiency and performance. We also present a technique to embed this systolic array into another array to be implemented on FPGA. We have synthesized our proposed hardware on the vertex-II FPGA to prove the correctness of the hardware and to determine the time and area requirements.
FLUTE: fast lookup table based wirelength estimation technique
Authors: C. Chu
Venue: Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design (2004)

Wirelength estimation is an important tool to guide the design optimization process in early design stages. In this paper, we present a wirelength estimation technique called FLUTE. Our technique is based on pre-computed lookup table to make wirelength estimation very fast and very accurate for low degree nets. We show experimentally that for FLUTE, RMST, and HPWL, the average error in wirelength are 0.72%, 4.23%, and -8.71%, respectively, and the normalized runtime are 1, 1.24, and 0.16, respectively.
MpCCI&mdash;a tool for the simulation of coupled applications
Authors: W. Joppich, M. Kürschner
Venue: Concurrency and Computation: Practice Experience (2006)

Many industrial and scientific applications are characterized by the interaction of different disciplines, such as fluid&ndash;structure interactions. For the individual disciplines sophisticated and validated solvers exist. This paper describes basic ideas, implementation details and application of MpCCI (mesh-based parallel code coupling interface), a tool for the coupling of different simulation codes. Copyright &copy; 2005 John Wiley & Sons, Ltd.
Examples of Low-Level Computer Vision on Media Processors
Authors: Branislav Kisaicanin
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

In this paper we describe a practical approach to processor selection for embedded computer vision applications. This approach is based on expected production volumes and other requirements. We then present several popular lowlevel computer vision techniques that have been algorithmically optimized for implementation on an emerging class of embedded architectures, media processors.
Monitoring the Macroscopic Effect of DDoS Flooding Attacks
Authors: Jian Yuan, Kevin Mills
Venue: IEEE Transactions on Dependable and Secure Computing (2005)

Creating defenses against flooding-based, distributed denial-of-service (DDoS) attacks requires real-time monitoring of network-wide traffic to obtain timely and significant information. Unfortunately, continuously monitoring network-wide traffic for suspicious activities presents difficult challenges because attacks may arise anywhere at any time and because attackers constantly modify attack dynamics to evade detection. In this paper, we propose a method for early attack detection. Using only a few observation points, our proposed method can monitor the macroscopic effect of DDoS flooding attacks. We show that such macroscopic-level monitoring might be used to capture shifts in spatial-temporal traffic patterns caused by various DDoS attacks and then to inform more detailed detection systems about where and when a DDoS attack possibly arises in transit or source networks. We also show that such monitoring enables DDoS attack detection without any traffic observation in the victim network.
The effects of randomly generated disturbances and fiscal policy on an aggregate demand macroeconomic model
Authors: K. A. Klafehn, P. J. Kuzdrall
Venue: ACM SIGSIM Simulation Digest (1980)

This paper examines the effects of stochastic disturbances on the final output (GNP) of an economy. A GPSS econometric model was constructed, tested, and validated. Utilizing the model, various strategies (fiscal policies) were examined in an effort to reduce the variance in GNP that is caused by the random disturbances of the exogenous variable, fixed investment. The policy considerations were incorporated into the model using feedback mechanisms which predict GNP. The resulting impact of the strategies are discussed. This model lends insight to the economic planner to evaluate the alternatives in a dynamic framework as contrasted to the classical comparative static analysis.