ppxscal/embedding_network huggingface dataset:
DejaVu: declarative pattern matching over live and archived streams of events
Authors: Nihal Dindar, Baris Güç, Patrick Lau, Asli Ozal, Merve Soner, Nesime Tatbul
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

DejaVu is an event processing system that integrates declarative pattern matching over live and archived streams of events on top of a novel system architecture. We propose to demonstrate the key aspects of the DejaVu query language and architecture using two different application scenarios, namely a smart RFID library system and a financial market data analysis application. The demonstration will illustrate how DejaVu can uniformly handle one-time, continuous, and hybrid pattern matching queries over live and archived stream stores, using highly interactive visual monitoring tools including one that is based on the Second Life virtual world.
What Evidence Matters? A randomized field trial of Cognitive Tutor Algebra I
Authors: Steven Ritter, Jonna Kulikowich, Pui-Wa Lei, Christy L. McGuire, Pat Morgan
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

Efforts to improve performance in mathematics have put pressure on educational evaluators to improve the rigor of their evaluation designs. This paper reports the results of a rigorous evaluation of the Cognitive Tutor Algebra I curriculum, which is substantially based on an intelligent tutoring system. We emphasize the importance of presenting details of the design, implementation and analysis of the study in order to ensure the best possibility of improvement over time.
Optimisation of RunBefore decoder and first one detector for MPEG-4 AVC&#47;H.264 CAVLC decoding
Authors: So-Jin Lee, Joo-Yul Park, Ki-Seok Chung
Venue: International Journal of Information and Communication Technology (2009)

In this paper, we propose a novel RunBefore decoder and a new FOD (first one detector) for MPEG-4 AVC&#47;H.264 CAVLC decoding. By reusing common blocks aggressively, the proposed FOD has smaller area and less power consumption. Also, a new RunBefore decoder which decodes two values in one clock has been designed to improve the decoding performance. The proposed CAVLC decoder has been designed in Verilog HDL and synthesised by Synopsys' design compiler using MagnaChip 0.18&mu;m CMOS cell library. Performance evaluation results show that our design has on average 48&#37; faster than conventional designs.
Innovative Technologies for Information Resources Management
Authors: Mehdi Khosrow-Pour, Mehdi Khosrow-Pour
Venue:  (2007)

As information resources management becomes increasingly dependent on emerging technologies to combat its challenges and decipher its effective strategies, the demand builds for a critical mass of research in this area. Innovative Technologies for Information Resources Management brings together compelling content related to the continually emerging technologies in areas of information systems such as Web services, electronic commerce, distance learning, healthcare, business process management, and software development. Focusing on the implications innovative technologies have on the managerial and organizational aspects of information resources management, this book provides academicians and practitioners with a requisite and enlightening reference source.
Comparative analysis of SRTM-NED vegetation canopy height to LIDAR-derived vegetation canopy metrics
Authors: L. W. Kenyi, R. Dubayah, M. Hofton, M. Schardt
Venue: International Journal of Remote Sensing (2009)

Vegetation canopy heights derived from the SRTM 30 m grid DEM minus USGS National Elevation Data (NED) DTM were compared to three vegetation metrics derived from a medium footprint LIDAR data (LVIS) for the US Sierra Nevada forest in California. Generally the SRTM minus NED was found to underestimate the vegetation canopy height. Comparing the SRTM-NED-derived heights as a function of the canopy percentile height (shape/vertical structure) derived from LVIS, the SRTM SAR signal was found to penetrate, on average, into about 44% of the canopy and 85% after adjustment of the data. On the canopy type analysis, it was found that the SRTM phase scattering centres occurred at 60% for red fir, 53% for Sierra mixed conifer, 50% for ponderosa pine and 50% for montane hardwood-conifer. Whereas analysing the residual errors of the SRTM-NED minus the LVIS-derived canopy height as a function of LVIS canopy height and cover it was observed that the residuals generally increase with increasing canopy height and cover. Likewise, the behaviour of the RMSE as a function of canopy height and cover was observed to initially increase with canopy height and cover but saturates at 50 m canopy height and 60% canopy cover. On the other hand, the behaviour of the correlation coefficient as a function of canopy height and cover was found to be high at lower canopy height (
Deep Sequencing of a Genetically Heterogeneous Sample: Local Haplotype Reconstruction and Read Error Correction
Authors: Osvaldo Zagordi, Lukas Geyrhofer, Volker Roth, Niko Beerenwinkel
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

We present a computational method for analyzing deep sequencing data obtained from a genetically diverse sample. The set of reads obtained from a deep sequencing experiment represents a statistical sample of the underlying population. We develop a generative probabilistic model for assigning observed reads to unobserved haplotypes in the presence of sequencing errors. This clustering problem is solved in a Bayesian fashion using the Dirichlet process mixture to define a prior distribution on the unknown number of haplotypes in the mixture. We devise a Gibbs sampler for sampling from the joint posterior distribution of haplotype sequences, assignment of reads to haplotypes, and error rate of the sequencing process to obtain estimates of the local haplotype structure of the population. The method is evaluated on simulated data and on experimental deep sequencing data obtained from HIV samples.
CocoViz with ambient audio software exploration
Authors: Sandro Boccuzzo, Harald C. Gall
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

For ages we used our ears side by side with our ophthalmic stimuli to gather additional information, leading and supporting us in our visualization. Nowadays numerous software visualization techniques exist that aim to facilitate program comprehension. In this paper we discuss how we can support such software comprehension visualization with environmental audio and lead users to identify relevant aspects. We use cognitive visualization techniques and audio concepts described in our previous work to create an ambient audio software exploration (AASE) out of program entities (packages, classes …) and their mapped properties. The concepts where implemented in a extended version of our tool called CocoViz. Our first results with the prototype shows that with this combination of visual and aural means we can provide additional information to lead users during program comprehension tasks.
A tool for identification of genes expressed in patterns of interest using the Allen Brain Atlas
Authors: Fred P. Davis, Sean R. Eddy
Venue: Bioinformatics (2009)

Motivation: Gene expression patterns can be useful in understanding the structural organization of the brain and the regulatory logic that governs its myriad cell types. A particularly rich source of spatial expression data is the Allen Brain Atlas (ABA), a comprehensive genome-wide in situ hybridization study of the adult mouse brain. Here, we present an open-source program, ALLENMINER, that searches the ABA for genes that are expressed, enriched, patterned or graded in a user-specified region of interest. Results: Regionally enriched genes identified by ALLENMINER accurately reflect the in situ data (95–99% concordance with manual curation) and compare with regional microarray studies as expected from previous comparisons (61–80% concordance). We demonstrate the utility of ALLENMINER by identifying genes that exhibit patterned expression in the caudoputamen and neocortex. We discuss general characteristics of gene expression in the mouse brain and the potential application of ALLENMINER to design strategies for specific genetic access to brain regions and cell types. Availability: ALLENMINER is freely available on the Internet at http://research.janelia.org/davis/allenminer. Contact: davisf@janelia.hhmi.org Supplementary information:Supplementary data are available at Bioinformatics online.
Common Criteria Approach to J2ME CLDC Security Requirements
Authors: M. Debbabi, M. Saleh, Chamseddine Talhi, Sami Zhioua
Venue: Proceeding of the 2006 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fifth SoMeT_06 (2006)

This paper represents a careful study of the security aspects of Java 2 Micro-Edition (J2ME) with Connected Limited Device Configuration (CLDC) and Mobile Information Device Profile (MIDP). This Java platform is intended for resource-constrained devices, with the purpose of expanding the range of applications available for these devices, by enabling them to run Java programs. Using a Common Criteria approach, our objective is to propose a set of security requirements that should be followed by any implementation of the platform.
Competitive motion synthesis based on hybrid control
Authors: Zhang Liang, Jun Xiao, Yueting Zhuang, Cheng Chen
Venue: Computer Animation and Virtual Worlds (2009)

We propose a simple and effective framework to deal with the problem of synthesizing interactive and competitive motions while reflecting the interactions. Two nontrivial issues are addressed in synthesizing two-character motions in competitive environment: how to reveal the embedded routines while keeping visual reality and how to build interactive models based on singly captured motions. To solve these issues, we employ a hierarchical framework: the finite state machine (FSM) controls the state transition in the higher layer, and the hybrid approach controls the action selection in the lower layer. The proposed approach contains two folds: first, a rule-based control scheme is proposed to simulate routine steps based on statistical analysis. Second, the interactive models are designed for simulating dense interactions between two players. The Relevance Vector Machine (RVM) algorithm is adopted to select attack styles and coupled with motion transition graph to determine combination blows. Here we apply the proposed framework of hybrid paradigm to boxing sport as an example. Copyright &copy; 2009 John Wiley & Sons, Ltd. This paper proposes a simple and effective framework to deal with the problem of synthesizing interactive and competitive motions while reflecting the interactions.
Design and performance of speculative flow control for high-radix datacenter interconnect switches
Authors: Cyriel Minkenberg, Mitchell Gusat
Venue: Journal of Parallel and Distributed Computing (2009)

High-radix switches are desirable building blocks for large computer interconnection networks, because they are more suitable to convert chip I/O bandwidth into low latency and low cost than low-radix switches [J. Kim, W.J. Dally, B. Towles, A.K. Gupta, Microarchitecture of a high-radix router, in: Proc. ISCA 2005, Madison, WI, 2005]. Unfortunately, most existing switch architectures do not scale well to a large number of ports, for example, the complexity of the buffered crossbar architecture scales quadratically with the number of ports. Compounded with support for long round-trip times and many virtual channels, the overall buffer requirements limit the feasibility of such switches to modest port counts. Compromising on the buffer sizing leads to a drastic increase in latency and reduction in throughput, as long as traditional credit flow control is employed at the link level. We propose a novel link-level flow control protocol that enables high-performance scalable switches that are based on the increasingly popular buffered crossbar architecture, to scale to higher port counts without sacrificing performance. By combining credited and speculative transmission, this scheme achieves reliable delivery, low latency, and high throughput, even with crosspoint buffers that are significantly smaller than the round-trip time. The proposed scheme substantially reduces message latency and improves throughput of partially buffered crossbar switches loaded with synthetic uniform and non-uniform bursty traffic. Moreover, simulations replaying traces of several typical MPI applications demonstrate communication speedup factors of 2 to 10 times.
Strong Relevant Logic as the Universal Basis of Various Applied Logics for Knowledge Representation and Reasoning
Authors: Jingde Cheng
Venue: Proceeding of the 2006 conference on Information Modelling and Knowledge Bases XVII (2006)

In many applications in computer science and artificial intelligence, in order to represent, specify, verify, and reason about various objects and relationships among them, we often need a right fundamental logic system to provide us with a criterion of logical validity for reasoning as well as a formal representation and specification language. Although different applications may require different logic systems, the fundamental logics must be able to underlie truth-preserving and relevant reasoning in the sense of conditional, ampliative reasoning, paracomplete reasoning, and paraconsistent reasoning. Based on our experiences, this paper shows that strong relevant logic can be used as the universal basis to construct various applied logics to satisfy the requirements. The paper discusses why any of the classical mathematical logic, its various classical conservative extensions, and its non-classical alternatives is not a suitable candidate for the universal basis to construct various applied logics, shows that strong relevant logic is a more hopeful candidate for the purpose, and presents our experiences on constructions of temporal relevant logics, deontic relevant logics, spatial relevant logics, and spatial-temporal relevant logics.
Pairwise document similarity in large collections with MapReduce
Authors: Tamer Elsayed, Jimmy Lin, Douglas W. Oard
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper presents a MapReduce algorithm for computing pairwise document similarity in large document collections. MapReduce is an attractive framework because it allows us to decompose the inner products involved in computing document similarity into separate multiplication and summation stages in a way that is well matched to efficient disk access patterns across several machines. On a collection consisting of approximately 900,000 newswire articles, our algorithm exhibits linear growth in running time and space in terms of the number of documents.
The application of random vortex method in the analysis of heat conduction in a slab
Authors: A. A. Dare, O. Ofi
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

Thermal conduction problems have traditionally been solved using analytical or numerical tools. Deterministic numerical tools such as Finite Element and Finite Difference Methods have been common. However these methods require many mathematical and computational skills. In the light of this, random vortex method which is probabilistic in nature was applied to study heat conduction in a rectangular slab. Two cases were considered: one with the slab boundary held at constant temperature and the other with part of the boundary isothermal and part adiabatic. The generated results were then validated using Taylor's series approximation test. From the results, the maximum deviation from the Taylor's series tests was 0.10 for the purely isothermal boundary slab and 0.07 for slab with partly isothermal and partly adiabatic boundary.
Towards resilient high performance applications through real time reliability metric generation and autonomous failure correction
Authors: Clayton F. Chandler, Chokchai Leangsuksun, Nathan DeBardeleben
Venue: Proceedings of the 2009 workshop on Resiliency in high performance (2009)

One predominant barrier encountered in furthering research and development efforts aimed at facilitating resilient HPC applications is a substantial lack of existing reliability and performance data originating from extreme-scale computing distributions. In order to develop an understanding of how and why highly scaled HPC applications are encountering increasingly frequent performance interruptions, one must conduct extensive trending and analysis on contemporary machines and their associated programs. However, existing HPC application log files are labyrinthine documents that, even with the assistance of intelligent data mining algorithms, translate poorly to human discern. In addition, conventional log filtering processes are limited to execution within a post-mortem, reactive time period, as the enormous size of these documents prevents efficient real time interaction. Thus, there exists a strong need within the HPC field for the provision of accurate-yet-concise real time application information. Moreover, the means of reporting this data must be sufficiently lightweight and non-intrusive, as to successfully-yet-discretely attach itself to the multiple processes running on multiple cores within tens (or in some cases, hundreds) of thousands of compute nodes. Furthermore, this information should in turn be used to facilitate the autonomous correction of application-threatening faults, suspensions, and interruptions. This paper describes a dynamic application instrumentation module (utilizing a combination of Open|SpeedShop software and custom scripting) aimed at successfully achieving these goals.
A scalable synthesis methodology for application-specific processors
Authors: Fei Sun, Srivaths Ravi, Anand Raghunathan, Niraj K. Jha
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2006)

Custom processors based on application-specific or domain-specific instruction sets are gaining popularity, and are often used to implement critical architectural blocks in complex systems-on-chip. While several advances have been made in the area of custom processor architectures, tools, and design methodologies, designers are still required to manually perform some critical tasks, such as selection of the custom instructions best suited to the given application and design constraints. We present a scalable methodology for the synthesis of a custom processor from an embedded software program. A key feature of the proposed methodology is its scalability, which is achieved by exploiting the structured, hierarchical nature of large software programs. We motivate the need for such a methodology, and describe the algorithms used for the critical steps, including hardware resource budgeting, local optimizations, and global exploration. Our methodology utilizes the concept of "soft" instruction templates, which can be adapted by adding operations to them or deleting operations from them at any time during the design space exploration process, allowing for global design decisions to be interleaved with fine-grained optimizations. To the best of our knowledge, this is the first work that uses the program hierarchy to derive soft instruction templates to synthesize application-specific processors for scalable applications. We have integrated our methodology in an open-source compiler, and verified it using a commercial extensible processor. Experiments with several benchmarks indicate that our methodology can effectively tackle large programs. It results in the synthesis of high-quality custom processors that demonstrate an average speedup of 2.82 × and a maximum speedup of 6.07 ×. As a side-effect, the processor energy is also reduced. The average and maximum reduction in the energy-delay product for the benchmarks are 7.64 × and 18.85 ×, respectively. The CPU times required for custom processor synthesis are quite small, indicating that the proposed techniques can be applied to embedded software programs of significant complexity.
An OWL ontology for HPSG
Authors: Graham Wilcock
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

The paper presents an OWL ontology for HPSG. The HPSG ontology is integrated with an existing OWL ontology, GOLD, as a community of practice extension. The basic ideas are illustrated by visualizations of type hierarchies for parts of speech.
Optical-flow estimation of dense motion field using robust techniques
Authors: S. Zimeras
Venue: Proceedings of the 2nd conference on European computing conference (2008)

In recent years, interest in motion analysis has increased with advances in processing capabilities. The usual input in a motion analysis system is an image sequence, with a corresponding increase in the amount of processed data. A typical motion problem is to analyze the motion within 2D image data corresponding to a sequence of frames, of a 3D scene. In computer vision a number of techniques are available to estimate the optical flow; the more efficient (in terms of quality) are modulated as the minimization of a global objective function. This cost function includes an observation constraint and a smoothness term. Such models generally assume that the luminance is constant along its trajectory. This assumption is not valid in cases of spatial and temporal distortions as in fluid image sequence. As an extension, a new model is described based on the continuity equation of fluid mechanics and a smoothness function considering the divergence (div) and vorticity (curl) of the motion field. The proposed model is embedded in a multiresolution framework and the minimization is conducted with an efficient multigrid technique. In this paper, the performance of the proposed motion estimation technique is analyzed and compared to similar "standard" methods, using simulated and real satellite data (the last provided by EUMETSAT). Finally, measures as RMSE of the images, number of cuts and number of iterations for the minimization of the energy function are introduced to justify the improvement of the estimation technique.
Pseudo-Riemann-Stieltjes integral
Authors: Ivana Štajner-Papuga, Tatjana Grbić, Martina Daňková
Venue: Information Sciences: an International Journal (2009)

An extension of the classical Riemann-Stieltjes integral to the field of pseudo-analysis is being investigated through this paper. Core of the construction presented here consists of generalized pseudo-operations given by monotone generating function.
Self-organising agent organisations
Authors: Ramachandra Kota, Nicholas Gibbins, Nicholas R. Jennings
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, decentralised approach for structural adaptation in explicitly modelled problem solving agent organisations. Based on self-organisation principles, our method enables the agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. The agents reason on when and how to adapt using only their history of interactions as guidance. We empirically show that, in both closed and dynamic organisations, the performance of organisations using our method is close to that of an upper bound centralised allocation method and considerably better than a random adaptation method.