ppxscal/embedding_network huggingface dataset:
A massively parallel implementation of the common azimuth pre-stack depth migration
Authors: H. Calandra, F. Bothorel, P. Vezolle
Venue: IBM Journal of Research and Development (2008)

When accompanied by the appropriate algorithmic approach, seismic imaging is an application that can take advantage of massively parallel computer systems. Three-dimensional (3D) pre-stack time migration (PSTM) and pre-stack depth migration (PSDM) are key components of seismic imaging and require very large computing resources. In this paper, we show that execution of these algorithms can be dramatically accelerated by massive parallelism. Many oil exploration and service companies purchase supercomputing clusters for performing 3D PSTM and PSDM seismic imaging. The common azimuth migration (CAM) algorithm, ported to many architectures, is particularly well suited to offshore marine applications. This paper describes the porting of the CAM algorithm to the IBM Blue Gene/L™ supercomputer, which requires introducing a second level of parallelism, building a parallel 3D-FFT (fast Fourier transform) routine, optimizing a tridiagonal solver for SIMD (single-instruction, multiple-data) floating-point units, and addressing various I/O concerns. We present results obtained by using up to 16, 368 processors for actual data provided from a marine seismic acquisition. Finally, we provide recommendations for porting other pre-stack algorithms to a massively parallel environment.
Optimizing irregular shared-memory applications for clusters
Authors: Seung-Jai Min, Rudolf Eigenmann
Venue: Proceedings of the 22nd annual international conference on Supercomputing (2008)

Irregular applications pose challenges in optimizing communication, due to the difficulty of analyzing irregular data accesses accurately and efficiently. This challenge is especially big when translating irregular shared-memory applications to message-passing form for clusters. The lack of effective irregular data analysis in the translation system results in unnecessary or redundant communication, which limits application scalability. In this paper, we present a Lean Distributed Shared Memory (LDSM) system, which features a fast and accurate irregular data access (IDA) analysis. The analysis uses a region-based diff method and makes use of a runtime library that is optimized for irregular applications. We describe three optimizations that improve the LDSM system performance. A parallel array reduction transformation reduces overheads in the analysis. A packed communication optimization and a differential communication optimization effectively eliminate unnecessary and redundant messages. We evaluate the performance of the optimized LDSM system on a set of representative irregular benchmarks. The optimized LDSM executes irregular applications on average 45% faster than the hand-tuned MPI applications.
trNon-greedy active learning for text categorization using convex ansductive experimental design
Authors: Kai Yu, Shenghuo Zhu, Wei Xu, Yihong Gong
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

In this paper we propose a non-greedy active learning method for text categorization using least-squares support vector machines (LSSVM). Our work is based on transductive experimental design (TED), an active learning formulation that effectively explores the information of unlabeled data. Despite its appealing properties, the optimization problem is however NP-hard and thus--like most of other active learning methods--a greedy sequential strategy to select one data example after another was suggested to find a suboptimum. In this paper we formulate the problem into a continuous optimization problem and prove its convexity, meaning that a set of data examples can be selected with a guarantee of global optimum. We also develop an iterative algorithm to efficiently solve the optimization problem, which turns out to be very easy-to-implement. Our text categorization experiments on two text corpora empirically demonstrated that the new active learning algorithm outperforms the sequential greedy algorithm, and is promising for active text categorization applications.
System reliability and weighted lattice polynomials
Authors: Alexander Dukhovny, Jean-luc Marichal
Venue: Probability in the Engineering and Informational Sciences (2008)

The lifetime of a system of connected units under some natural assumptions can be represented as a random variable Y defined as a weighted lattice polynomial of random lifetimes of its components. As such, the concept of a random variable Y defined by a weighted lattice polynomial of (lattice-valued) random variables is considered in general and in some special cases. The central object of interest is the cumulative distribution function of Y. In particular, numerous results are obtained for lattice polynomials and weighted lattice polynomials in the case of independent arguments and in general. For the general case, the technique consists in considering the joint probability generating function of “indicator” variables. A connection is studied between Y and order statistics of the set of arguments.
STRATUM: A METHODOLOGY FOR DESIGNING HEURISTIC AGENT NEGOTIATION STRATEGIES
Authors: Iyad Rahwan, Liz Sonenberg, Nicholas R. Jennings, Peter McBurney
Venue: Applied Artificial Intelligence (2007)

Automated negotiation is a powerful (and sometimes essential) means for allocating resources among self-interested autonomous software agents. A key problem in building negotiating agents is the design of the negotiation strategy, which is used by an agent to decide its negotiation behavior. In complex domains, there is no single, obvious optimal strategy. This has led to much work on designing heuristic strategies, where agent designers usually rely on intuition and experience. In this article, we introduce STRATUM, a methodology for designing strategies for negotiating agents. The methodology provides a disciplined approach to analyzing the negotiation environment and designing strategies in light of agent capabilities and acts as a bridge between theoretical studies of automated negotiation and the software engineering of negotiation applications. We illustrate the application of the methodology by characterizing some strategies for the Trading Agent Competition and for argumentation-based negotiation.
Scaleability and immortality
Authors: C Gordon Bell
Venue: ACM SIGMOD Record (2008)

James Nicholas Gray's understanding and experimentation gave him a special perspective. From 1995 his commitment was building indefinitely scalable tools by working on really hard data-intensive application problems with other scientific disciplines. His attention to research for both understanding and use made him a unique researcher. Jim pioneered a new kind of 21st century science based on data analytics, requiring computer scientists to collaborate as an equal with scientists in other fields. Gray was an advocate and principal supporter of the MyLifeBits project aimed at extending our memory, memex. The by-product includes digital immortality that we herein speculate and explore.
Learning for mastery in an introductory programming course
Authors: Jana Jacková
Venue: ACM SIGCSE Bulletin (2008)

Teachers always look for new ways to make their teaching more effective. "The data show that mastery learning programs have positive effects on student achievement" [1]. We introduce work in progress of an educational research of teaching/learning (T/L) effectiveness in case the Mastery Learning (ML) approach is used in an introductory course of programming.
Characterization of polymer inks for drop-on-demand printing systems
Authors: Ronald M. Meixner, Dominik Cibis, Klaus Krueger, Holger Goebel
Venue: Microsystem Technologies (2008)

This paper presents a detailed study on the properties of different polymer inks based on poly(3,4ethylenedioxythiophene)/polystyrenesulfonate regarding their processability in an experimental piezo driven drop-on-demand (DoD) micro-feeding system. Based on the rheological properties of the used inks and the mechanical properties of the printing system characteristic values are derived which allow to predict the processability of polymer inks in a given printing system. Beside the printability the influence of different polymer inks on the electrical characteristics of printed organic field effect transistors is investigated.
Pedestrian routing system using genetic algorithms suitable for mobile ad hoc networks
Authors: J. Bravo, I. Soto, R. Carrasco
Venue: Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS (2006)

Mobile Ad Hoc Networks are self configuring networks that not rely in any centralised device. Such a network faces many challenges especially when a routing capability is desired. In this paper the situation in which a mobile pedestrian has to find the way to visit many places once is presented. An optimum mathematical model solution is compared against different solutions obtained via genetics algorithm. Genetic algorithms demonstrate that acquire a good result in a high-quality manner with a difference of 13.84% respect to the optimal solution. Also complexity studies are carry out.
Stereo cloud-top heights and cloud fraction retrieval from ATSR-2
Authors: J. -P. Muller, M. -A. Denis, R. D. Dundas, K. L. Mitchell, C. Naud, H. Mannstein
Venue: International Journal of Remote Sensing (2007)

An operational processing system is described for the automated retrieval of cloud-top heights (CTHs) and amounts from the Gridded Brightness Temperature (GBT) 1 km product derived from the dual view of the Along Track Scanning Radiometer (ATSR-2) instrument onboard the ESA ERS-2 satellite. A new stereo matching algorithm, called M4 is described together with the overall processing chain for retrieving cloud-top heights and amounts. M4 is based on the successful stereo matchers, M2 and M3 which have been in operation with the NASA MISR sensor since March 2000 and which have also been applied to mapping cloud fraction in the polar region using ATSR-2 (Cawkwell and Bamber 2002, Cawkwell et al. 2001). Results in companion papers (Naud et al., Denis et al. 2007) describe the accuracy achieved using this algorithm and detailed scene-by-scene results are available from http://cloudmap.org under results->UCL->ATSR-2 Validation. We assess the impact of cloud-top winds on the accuracy of the retrieved cloud-top heights and conclude that for most middle and lower tropospheric clouds, cloud-top winds will have little, if any, noticeable impact. We show how ATSR-2 cloud-top heights at the different wavelengths (particularly visible compared with thermal IR) can sometimes yield information on multi-layer clouds which is unique to ATSR-2. The processing system has recently been applied to three years of ASTR-2 GBT data and results are shown. These results are available from the British Atmospheric Data Centre (http://badc.nerc.ac.uk/data/list_all_datasets.html?source = data).
Micro-aggregation-based heuristics for p-sensitive k-anonymity: one step beyond
Authors: Agusti Solanas, Francesc Sebé, Josep Domingo-Ferrer
Venue: Proceedings of the 2008 international workshop on Privacy and anonymity in information society (2008)

Micro-data protection is a hot topic in the field of Statistical Disclosure Control (SDC), that has gained special interest after the disclosure of 658000 queries by the AOL search engine in August 2006. Many algorithms, methods and properties have been proposed to deal with micro-data disclosure, p-Sensitive k-anonymity has been recently defined as a sophistication of k-anonymity. This new property requires that there be at least p different values for each confidential attribute within the records sharing a combination of key attributes. Like k-anonymity, the algorithm originally proposed to achieve this property was based on generalisations and suppressions; when data sets are numerical this has several data utility problems, namely turning numerical key attributes into categorical, injecting new categories, injecting missing data, and so on. In this article, we recall the foundational concepts of micro-aggregation, k-anonymity and p-sensitive k-anonymity. We show that k-anonymity and p-sensitive k-anonymity can be achieved in numerical data sets by means of micro-aggregation heuristics properly adapted to deal with this task. In addition, we present and evaluate two heuristics for p-sensitive k-anonymity which, being based on micro-aggregation, overcome most of the drawbacks resulting from the generalisation and suppression method.
Optimization of Circular Ring Microstrip Antenna Using Genetic Algorithm
Authors: R. Ganjehmarzy, M. Davoody
Venue: Proceedings of the Communication Networks and Services Research Conference (2008)

Circular ring microstrip antennas have several interesting properties that make it attractive in wireless applications. Although several analysis techniques such as cavity model, generalized transmission line model, Fourier-Hankel transform domain and the method of matched asymptotic expansion have been studied by researchers, there is no efficient design tool that has been incorporated with a suitable optimization algorithm. In this paper, the cavity model analysis along with the genetic optimization algorithm is presented for the design of circular ring microstrip antennas. The method studied here is based on the well-known cavity model and the optimization of the dimensions and feed point location of the circular ring antenna is performed via the genetic optimization algorithm, to achieve an acceptable antenna operation around a desired resonance frequency. The antennas designed by this efficient design procedure were realized experimentally, and the results are compared. In addition, these results are also compared to the results obtained by the commercial electromagnetic simulation tool, the FEM based software, HFSS by ANSOFT.
An Efficiency Security Model of Routing Protocol in Wireless Sensor Networks
Authors: Jing Chen, Huanguo Zhang, Junhui Hu
Venue: Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS) (2008)

Routing security is one of the most important considerations in Wireless Sensor Networks (WSNs). Currently, more and more people pay attention to this issue. But most of the secure protocols must use public key and symmetric cryptographies which induce heavy load to nodes in the whole routing stage. In this paper, we propose an Efficiency Security Model of Routing (ESMR). In routing stage, ESMR only uses public key cryptography when new nodes enter the wireless sensor network and does not use symmetric cryptography at all. Through the security analyzing, we find our cryptography method only can resist the outside attackers, but it is helpless to inside attackers. Therefore, reputation mechanism is proposed against inside attackers in ESMR. The simulation result shows that the performance of ESMR is not as good as LEACH(Low-Energy Adaptive Clustering Hierarchy routing protocol) in no attacker environment, but it becomes better and better with the number of attackers increasing.
Tailoring density estimation via reproducing kernel moment matching
Authors: Le Song, Xinhua Zhang, Alex Smola, Arthur Gretton, Bernhard Schölkopf
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distributions into a reproducing kernel Hilbert space, and performing moment matching in that space. This allows us to tailor density estimators to a function class of interest (i.e., for which we would like to compute expectations). We show our density estimation approach is useful in applications such as message compression in graphical models, and image classification and retrieval.
Acoustic and Phoneme Modeling Based on Confusion Matrix for Ubiquitous Mixed-Language Speech Recognition
Authors: Po-Yi Shih, Jhing-Fa Wang, Hsiao-Ping Lee, Hung-Jen Kai, Hung-Tzu Kao, Yuan-Ning Lin
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

This work presents a novel approach to acoustic and phoneme modeling in order to recognize ubiquitous mixed-language speech. The conventional approaches to perform multilingual speech recognition are the usage of a multilingual phone set. A confusion matrix combining acoustic between every two phonetic is built for phonetic unit clustering. In this work, we are interested in speaker independent voice command recognition. The IPA representation is adapted for phonetic unit modeling. The EAT is applied to construct speaker independent acoustic models. The experimental results show that the proposed method can perform 70~80% lexicon recognition accuracy.
A Secure and Energy-Efficient Scheme for Group-Based Routing in Heterogeneous Ad Hoc Sensor Networks and Its Simulation Analysis
Authors: Chandrasekar Ramachandran, Mohammad S. Obaidat, Sudip Misra, Feniosky Peña-Mora
Venue: Simulation (2008)

We present Fuzzy Group-Based Routing Algorithm (FGRA), a secure, energy-efficient scheme for routing in sensor networks. In this scheme, we consider the formation of multipaths for routing. Using fuzzy logic for generating decisions of forwarding or withholding packets, we show that our scheme is robust, efficient and scalable for a large number of nodes. In our scheme, routing takes place with the help of groups of nodes, which includes situations when the nodes are disconnected. We incorporate security in the design of our routing algorithm by using a mobile-agents-based approach. Our scheme is data-centric where named data packets are considered as the focal point of the system, and in this way it can be adapted for any application. We perform some simulations in NS2, and demonstrate that our scheme shows good performance results with scope for additional research.
Creating tools for emerging display technologies
Authors: Carolina Cruz-Neira
Venue: Proceedings of the 2008 workshop on Immersive projection technologies/Emerging display technologiges (2008)

Today we have a wide range of display technologies to visualize, explore, and interact with virtual worlds. From large multi-screen installations to desktop autostereo displays, the choices are many; today's challenge is not so much what display to use or how to build it, but what set of tools are available to drive a particular display. As the hardware technology has advanced rapidly, it seems that the software has lagged behind it and the acceptance of displays is tightly dependent on the availability of software tools to create applications that can make efficient use of the display and the associated interactive devices. This panel explores the current state of software tools for advanced displays, the challenges to create such tools, and the directions toolset development are taking for the near to medium term. A group of experts will participate in the discussions, sharing their lessons learned as well as their visions for better and more rapidly available tools for exciting emerging displays.
Solving large protein secondary structure classification problems by a nonlinear complementarity algorithm with {0, 1} variables
Authors: C. Cifarelli, G. Patrizi
Venue: Optimization Methods Software (2007)

The aim of this paper is to present a nonlinear complementarity algorithm, limited to binary variables, to implement a classification algorithm, which will be applied to the determination of the secondary structure of proteins, and to present its statistical and mathematical convergence properties. Extensive application results will be given on the available test data sets of proteins and the results will be compared with those of other implementations. The increase in the recognition accuracy, which will be in evidence, will be shown to be attributable to the adoption of a strict statistical methodology, which will permit to obtain unbiased results, without requiring extraneous assumptions.
Semi-quantitative Modeling for Managing Software Development Processes
Authors: He Zhang, Jacky Keung, Barbara Kitchenham, Ross Jeffery
Venue: Proceedings of the 19th Australian Conference on Software Engineering (2008)

Software process modeling has become an essential technique for managing software development processes. However, purely quantitative process modeling requires a detailed understanding and accurate measurement of software process, which relies on reliable and precise history data. This paper presents a semi-quantitative process modeling approach to model and manage software development processes. It allows for the existence of uncertainty and contingency during software development, and facilitates a manager’s qualitative and quantitative estimates and assessments of process progress. We demonstrate its value and flexibility by developing semi-quantitative models of the test-and-fix process of incremental software development. Results conclude that the semi-quantitative process modeling approach can support process or project management activities, including estimating, planning, tracking and decision making throughout the software development cycle.
ECG Based Recognition Using Second Order Statistics
Authors: Foteini Agrafioti, Dimitrios Hatzinakos
Venue: Proceedings of the Communication Networks and Services Research Conference (2008)

This paper investigates the applicability of Electrocardiogram (ECG) signals for human recognition. Current approaches apply feature extraction on a fiducial points basis. In this paper we demonstrate an autocorrelation based feature extraction approach, in conjunction with the Discrete Cosine Transform or Linear Discriminant Analysis. As an optimization, we introduce a Template Matching technique that substantially improves the classification performance while also acting as an intruder detector. The experimental results show considerably high recognition rates, rendering identification applications based on ECG very promising.
Java projects motivated by student interests
Authors: Mirela Djordjevic
Venue: ACM SIGCSE Bulletin (2008)

We present four Java projects suggested by our student that were developed in Java CS1/CS2 course. What is in interest of our students who start programming? The answer might be different from the teachers or textbook approach. The themes include games, drawing, colors, measuring time, etc. Questions can be raised if we can just monitor a process of studying by watching the development of projects and simply making directions in different ways, or can we as teachers learn what major interests of our students are when learning to program. We share our finding of interesting examples.
Development of the Universal Safety Information Registration System for Vulnerable People Using a Mobile Phone
Authors: Hiroaki Yuze, Zhengyi Zhang, Yuki Yoshida, Takashi Kawada, Chaoqun Wang
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

When an earthquake occurs, in order to get safety information, the safety information registration system (SIRS) is most frequently used. Today, almost all SIRS can be accessed from personal computer but they can access from PDA, such as mobile phones. However, access of the current SIRS is more difficult, especially for visual disabled and aged people, also for the non-Japanese natives. In this study, we developed the universal SIRS with easy access for disaster vulnerable such as physically handicapped and people with language barrier. Our newly developed system enables registration of safety information by with simple operation by pushing buttons with guidance of bigger characters and multi-lingual audio assistance, so forth.