ppxscal/embedding_network huggingface dataset:
Integrated Data and Task Management for Scientific Applications
Authors: Jarek Nieplocha, Sriram Krishamoorthy, Marat Valiev, Manoj Krishnan, Bruce Palmer, P. Sadayappan
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Several emerging application areas require intelligent management of distributed data and tasks that encapsulate execution units for collection of processors or processor groups. This paper describes an integration of data and task parallelism to address the needs of such applications in context of the Global Array (GA) programming model. GA provides programming interfaces for managing shared arrays based on non-partitioned global address space programming model concepts. Compatibility with MPI enables the scientific programmer to benefit from performance and productivity advantages of these high level programming abstractions using standard programming languages and compilers.
A Novel Ensemble Approach for Cancer Data Classification
Authors: Yaou Zhao, Yuehui Chen, Xueqin Zhang
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Micorarray data are often extremely asymmetric in dimensionality, such as thousands or even tens of thousands of genes and a few hundreds of samples. Such extreme asymmetry between the dimensionality of genes and samples presents several challenges to conventional clustering and classification methods. In this paper, a novel ensemble method based on correlation analysis is proposed. Firstly, in order to extract useful features and reduce dimensionality, different feature selection methods based on correlation analysis are used to form different feature subsets. Then a pool of candidate base classifiers is generated to learn the subsets which are re-sampling from the different feature subsets. At last, appropriate classifiers are selected to construct the classification committee using EDA (Estimation of Distribution Algorithms) algorithm. Experiments show that the proposed method produces the best recognition rates on two benchmark databases.
Quantifying Resistance to the Sybil Attack
Authors: N. Boris Margolin, Brian Neil Levine
Venue: Financial Cryptography and Data Security: 12th International Conference, FC 2008, Cozumel, Mexico, January 28-31, 2008. Revised Selected Papers (2008)

Sybil attacks have been shown to be unpreventable except under the protection of a vigilant central authority. We use an economic analysis to show quantitatively that some applications and protocols are more robust against the attack than others. In our approach, for each distributed application and an attacker objective, there is a critical value that determines the cost-effectiveness of the attack. A Sybil attack is worthwhile only when the critical value is exceeded by the ratio of the value of the attacker's goal to the cost of identities. We show that for many applications, successful Sybil attacks may be expensive even when the Sybil attack cannot be prevented. Specifically, we propose the use of a recurring fee as a deterrent against the Sybil attack. As a detailed example, we look at four variations of the Sybil attack against a recurring fee based onion routing anonymous routing network and quantify its vulnerability.
DTP: Double-Pairwise Time Protocol for Disruption Tolerant Networks
Authors: Qing Ye, Liang Cheng
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Network time synchronization (NTS) is essential for any distributed systems, including Disruption Tolerant Networks (DTNs). The feature of frequent contact disruptions and discontinuous network connections in DTNs raises a new challenge in providing the NTS service: synchronization operations may be interrupted for a long period of time when links between the time synchronization peers are opportunistic. To address this challenge, we propose Double pairwise Time Protocol (DTP) that can achieve better clock estimations and synchronization results in DTNs than NTP-Core, which models the major functionality of processing synchronization messages in Network Time Protocol (NTP) that is the time-keeping standard in the Internet. The characteristics of DTP include: i) DTP achieves approximately half of the maximum time error achieved by NTP-Core; and ii) DTP only requires minor modifications to be implemented in the current architecture of NTP. Simulation results based on trace data collected from existing DTN testbeds validate such characteristics of DTP.
A bound on the approximation of a Catmull--Clark subdivision surface by its limit mesh
Authors: Zhangjin Huang, Jiansong Deng, Guoping Wang
Venue: Computer Aided Geometric Design (2008)

A Catmull-Clark subdivision surface (CCSS) is a smooth surface generated by recursively refining its control meshes, which are often used as linear approximations to the limit surface in geometry processing. For a given control mesh of a CCSS, by pushing the control points to their limit positions, another linear approximation-a limit mesh of the CCSS is obtained. In general a limit mesh might approximate a CCSS better than the corresponding control mesh. We derive a bound on the distance between a CCSS patch and its limit face in terms of the maximum norm of the second order differences of the control points and a constant that depends only on the valence of the patch. A subdivision depth estimation formula for the limit mesh approximation is also proposed. For a given error tolerance, fewer subdivision steps are needed if the refined control mesh is replaced with the corresponding limit mesh.
An Undergraduate Computational Science Curriculum
Authors: Angela B. Shiflet, George W. Shiflet
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

Wofford College instituted one of the first undergraduate programs in computational science, the Emphasis in Computational Science (ECS). Besides programming, data structures, and calculus, ECS students take two computational science courses (Modeling and Simulation for the Sciences, Data and Visualization) and complete a summer internship involving computation in the sciences. Materials written for the modeling and simulation course and developed with funding from National Science Foundation served as a basis the first textbook designed specifically for an introductory course in the computational science and engineering curriculum. The successful ECS has attracted a higher percentage of females than in most computer science curricula. The SIAM Working Group on Undergraduate Computational Science and Engineering Education summarized features of Wofford's ECS and other computational science programs. Besides its established curriculum, Wofford has incorporated computational science in other courses, such as in a sequence of three microbiology laboratories on modeling the spread of disease.
A Software Component Model with Spatial and Temporal Compositions for Grid Infrastructures
Authors: Hinde Lilia Bouziane, Christian Pérez, Thierry Priol
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Grids are very complex and volatile infrastructures that exhibit parallel and distributed characteristics. To harness their complexity as well as the increasing intricacy of scientific applications, modern software engineering practices are needed. As of today, two major programming models dominate: software component models that are mainly based on a spatial composition and service oriented models with their associated workflow languages promoting a temporal composition. This paper tends to unify these two forms of composition into a coherent spatio-temporal software component model while keeping their benefits. To attest the validity of the proposed approach, we describe how the Grid Component model, as defined by the CoreGRID Network of Excellence, and the Askalon-AGWL workflow language have been adapted.
Using Asymmetric Single-ISA CMPs to Save Energy on Operating Systems
Authors: Jeffrey C. Mogul, Jayaram Mudigonda, Nathan Binkert, Parthasarathy Ranganathan, Vanish Talwar
Venue: IEEE Micro (2008)

CPUs consume too much power. Modern complex cores sometimes waste power on functions that are not useful for the code they run. In particular, operating system kernels do not benefit from many power-consuming features intended to improve application performance. We advocate asymmetric single-ISA multicore systems, in which some cores are optimized to run OS code at greatly improved energy efficiency.
A Hybrid Algorithm Based on Evolution Strategies and Instance-Based Learning, Used in Two-Dimensional Fitting of Brightness Profiles in Galaxy Images
Authors: Juan Carlos Gomez, Olac Fuentes
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

The hybridization of optimization techniques can exploit the strengths of different approaches and avoid their weaknesses. In this work we present a hybrid optimization algorithm based on the combination of Evolution Strategies (ES) and Locally Weighted Linear Regression (LWLR). In this hybrid a local algorithm (LWLR) proposes a new solution that is used by a global algorithm (ES) to produce new better solutions. This new hybrid is applied in solving an interesting and difficult problem in astronomy, the two-dimensional fitting of brightness profiles in galaxy images.The use of standardized fitting functions is arguably the most powerful method for measuring the large-scale features (e.g. brightness distribution) and structure of galaxies, specifying parameters that can provide insight into the formation and evolution of galaxies. Here we employ the hybrid algorithm ES+LWLR to find models that describe the bi-dimensional brightness profiles for a set of optical galactic images. Models are created using two functions: de Vaucoleurs and exponential, which produce models that are expressed as sets of concentric generalized ellipses that represent the brightness profiles of the images.The problem can be seen as an optimization problem because we need to minimize the difference between the flux from the model and the flux from the original optical image, following a normalized Euclidean distance. We solved this optimization problem using our hybrid algorithm ES+LWLR. We have obtained results for a set of 100 galaxies, showing that hybrid algorithm is very well suited to solve this problem.
Mastermind: an augment reality approach: [porting a legacy game to new interaction paradigms]
Authors: Pedro Abreu, Pedro Mendes
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

Mastermind was created in the seventies, when an Israeli telecommunications expert called Mordecai Meirowitz created a new cunning and logic game. A Mastermind session played by human players is typically short as it takes about twenty minutes. Such feature is ideal for online implementations but one of the problems of traditional board games like Mastermind is its poor attractiveness comparing to the new generation of video games. In order to reduce this gap, the main goal of this research was to port the Mastermind game to a 3D environment increasing the possible interest for players. This goal has been successfully achieved as this implementation presents a fully functional game logic module, a conventional 3D interface that has also been ported to an AR (augmentation reality) environment using ARToolKit. This platform proved to be efficient, because relevant requisites in this domain were satisfactorily met when tested on homogeneous lit environments. The obtained results were quite good, mainly in what concerns taking a hugely popular game to a completely new interaction paradigm. In terms of pattern recognition the AR solution proved to be suitable for the case at a hand. These results were achieved even with low brand webcams and computing platforms. In fact memory consumption was kept to a minimum due to the usage of appropriate data-structures.
Performance evaluation of a novel time hopping multiple access UWB system
Authors: Ye-Shun Shen, Fang-Biau Ueng, Jun-Da Chen, Shen-Tian Huang
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

A novel time-hopping (TH) multiple access ultra-wideband (UWB) system employing M-ary orthogonal pulse position modulation (PPM) is proposed and investigated. A concept of removing the usage of time slots within a frame period is applied in the proposed TH/M-ary PPM UWB system. The transmitter of each user exploits a pseudorandom TH address to produce the TH-coded symbols, which are inputted to the M- ary PPM modulator. Based on the derived characteristic function (CF) of multiple access interference, the symbol error rate (SER) expression is obtained for the proposed system in an additive white Gaussian noise environment. Some simulation examples are given to verify the effectiveness of the SER analysis. It is shown that the proposed system outperforms the conventional TH and direct-sequence UWB systems for medium and large value of signal-to-noise ratio.
Reengineering a software system implementing parallel methods for differential equations
Authors: Dana Petcu, Andrei Eckstein, Claudiu Giurgiu
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

The efficient use of existing software for scientific computing in the context of the new software and hardware technologies, like Web services and multicore systems, imposes a redesign of their software architecture. We describe the path that was followed in the case of an expert system for ordinary differential equations including facilities for parallel computing. The approach can be easily applied to other tools used in scientific computing.
Head-mounted displays and new technologies for firefighting and rescue in a post 9/11 world
Authors: Paul Wright
Venue:  (2007)

Emergency first response at large urban and industrial incidents is an extremely challenging and important job. Information at the incident scene is often lacking, and the tools responders must use to communicate information are inadequate. Much of this information is spatial in nature, and efficiently navigating through an unknown environment is a common and critical task for a firefighter. Moreover, the National Institute for Standards and Technology (NIST) found that localization of first responders is one of the most important challenges at current incidents (NIST, 2007). This dissertation describes a communication and information relay system that strives to supplement and improve the efficacy and safety of incident operations. Specifically, the design process and the experiments conducted for head-mounted displays (HMDs) for firefighters are presented. An HMD is a technology that can give critical helpful information, especially regarding navigation in buildings, in a hands-free manner. Eight prototypes are presented, each being either an improvement on the lessons learned from the previous design, or a design variation used for comparison. A user needs study that included many interviews and research demonstrations identifies current systems and methods used in firefighting, challenges in implementing new technologies, specific needs for more capability at large and challenging incidents, and feedback on proposed technologies. A series of human subjects experiments were conducted, where subjects navigated through two large unknown buildings to target locations with and without the HMD. The hypothesis was that a head-mounted display improves the efficacy of a user navigating through an unknown challenging indoor environment to target locations. It was found that use of the HMD reduced navigation time by 62%, reduced the search distance traveled by 55%, and improved subjects' understanding of the building layout and ability to map target locations by 55%.
FIRE in ImageCLEF 2007: Support Vector Machines and Logistic Models to Fuse Image Descriptors for Photo Retrieval
Authors: Tobias Gass, Tobias Weyand, Thomas Deselaers, Hermann Ney
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

Submissions to the photographic retrieval task of the ImageCLEF 2007 evaluation and improvements of our methods that were tested and evaluated after the official benchmark. We use our image retrieval system FIRE to combine a set of different image descriptors. The most important step in combining descriptors is to find a suitable weighting. Here, we evaluate empirically tuned linear combinations, a trained logistic regression model, and support vector machines to fuse the different descriptors. Additionally, clustered SIFT histograms are evaluated for the given task and show very good results --- both, alone and in combination with other features. A clear improvement over our evaluation performance is shown consistently over different combination schemes and feature sets.
AwarePen - Classification Probability and Fuzziness in a Context Aware Application
Authors: Martin Berchtold, Till Riedel, Michael Beigl, Christian Decker
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

Fuzzy inference has been proven a candidate technology for context recognition systems. In comparison to probability theory, its advantage is its more natural mapping of phenomena of the real world as context. This paper reports on our experience with building and using monolithic fuzzy-based systems (a TSK-FIS) to recognize real-world events and to classify these events into several categories. It will also report on some drawbacks of this approach that we have found. To overcome these drawbacks a novel concept is proposed in this paper. The concept incorporates fuzzy-based approaches with probabilistic methods, and separates the monolithic fuzzy-based system into several modules. The core advantage of the concept lays in the separation of detection complexity into distinct modules, each of them using fuzzy-based inference for context classification. Separation of detection functionality is supported by an automatic process using transition probabilities between context classifiers to optimize detection quality for the resulting detection system. This way our approach incorporates the advantages of fuzzy-based and probabilistic systems. This paper will show results of experiments of an existing system using a monolithic FIS approach, and reports on advantages when using a modular approach.
Reasoning under Uncertainty in On-Line Auditing
Authors: Gerardo Canfora, Bice Cavallo
Venue: Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases (2008)

We propose a Bayesian approach to reasoning under uncertainty in on-line auditing of Statistical Databases. A Bayesian network addresses disclosures based on probabilistic inferences that can be drawn from released data. In particular, we deal with on-line max and min auditing. Moreover, we show how our model is able to deal with the implicit delivery of information that derives from denying the answer to a query and to manage user prior-knowledge.
DISC 20th Anniversary: Invited Talk Provably Unbreakable Hyper-Encryption Using Distributed Systems
Authors: Michael O. Rabin
Venue: Proceedings of the 21st international symposium on Distributed Computing (2007)

Encryption is a fundamental building block for computer and communications technologies. Existing encryption methods depend for their security on unproven assumptions. We propose a new model, the Limited Access model for enabling a simple and practical provably unbreakable encryption scheme. A voluntary distributed network of thousands of computers each maintain and update random pages, and act as Page Server Nodes. A Sender and Receiver share a random key K. They use K to randomly select the same PSNs and download the same random pages. These are employed in groups of say 30 pages to extract One Time Pads common to S and R. Under reasonable assumptions of an Adversary's inability to monitor all PSNs, and easy ways for S and R to evade monitoring while downloading pages, Hyper Encryption is clearly unbreakable. The system has been completely implemented.
The University of Amsterdam's Question Answering System at QA@CLEF 2007
Authors: Valentin Jijkoun, Katja Hofmann, David Ahn, Mahboob Alam Khalid, Joris Rantwijk, Maarten Rijke, Erik Tjong Kim Sang
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We describe a new version of our question answering system, which was applied to the questions of the 2007 CLEF Question Answering Dutch monolingual task. This year, we made three major modifications to the system: (1) we added the contents of Wikipedia to the document collection and the answer tables; (2) we completely rewrote the module interface code in Java; and (3) we included a new table stream which returned answer candidates based on information which was learned from question-answer pairs. Unfortunately, the changes did not lead to improved performance. Unsolved technical problems at the time of the deadline have led to missing justifications for a large number of answers in our submission. Our single run obtained an accuracy of only 8% with an additional 12% of unsupported answers (compared to 21% in the last year's task).
Automatic Categorization of Human-Coded and Evolved CoreWar Warriors
Authors: Nenad Tomašev, Doni Pracner, Miloš Radovanović, Mirjana Ivanović
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

CoreWar is a computer simulation devised in the 1980s where programs loaded into a virtual memory array compete for control over the virtual machine. These programs are written in a special-purpose assembly language called Redcode and referred to as warriors. A great variety of environments and battle strategies have emerged over the years, leading to formation of different warrior types. This paper deals with the problem of automatic warrior categorization, presenting results of classification based on several approaches to warrior representation, and offering insight into ambiguities concerning the identification of strategic classes. Over 600 human-coded warriors were annotated, forming a training set for classification. Several major classifiers were used, SVMs proving to be the most reliable, reaching accuracy of 84%. Classification of an evolved warrior set using the trained classifiers was also conducted. The obtained results proved helpful in outlining the issues with both automatic and manual Redcode program categorization.
Comparison of Local Higher-Order Moment Kernel and Conventional Kernels in SVM for Texture Classification
Authors: Keisuke Kameyama
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Use of local higher-order moment kernel (LHOM kernel) in SVMs for texture classification was investigated by comparing it with SVMs using other conventional kernels. In the experiments, it became clear that SVMs with LHOM kernels achieve better trainability and give stable response to the texture classes when compared with those with conventional kernels. Also, the number of support vectors were kept low which indicates better class separability in the nonlinearly-mapped feature space.