ppxscal/embedding_network huggingface dataset:
Characterizing and Understanding the Bandwidth Behavior of Workloads on Multi-core Processors
Authors: Guoping Long, Dongrui Fan, Junchao Zhang
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

An important issue of current multi-core processors is the off-chip bandwidth sharing. Sharing is helpful to improve resource utilization and but more importantly and it may cause performance degradation due to contention. However and there is not enough research work on characterizing the workloads from bandwidth perspective. Moreover and the understanding of the impact of the bandwidth constraint on performance is still limited. In this paper and we propose the phase execution model and and evaluate the arithmetic to memory ratio (AMR) of each phase to characterize the bandwidth requirements of arbitrary programs. We apply the model to a set of SPEC benchmark programs and obtain two results. First and we propose a new taxonomy of workloads based on their bandwidth requirements. Second and we find that prefetching techniques are useful to improve system throughput of multi-core processors only when there is enough spare memory bandwidth.
Sojourn times in polling systems with various service disciplines
Authors: Onno Boxma, Josine Bruin, Brian Fralix
Venue: Performance Evaluation (2009)

We consider a polling system of N queues Q"1,...,Q"N, cyclically visited by a single server. Customers arrive at these queues according to independent Poisson processes, requiring generally distributed service times. When the server visits Q"i, i=1,...,N, it serves a number of customers according to a certain polling discipline. This discipline is assumed to belong to the class of branching-type disciplines, which includes the gated and exhaustive disciplines. The special feature of our study is that, within each queue, we do not restrict ourselves to service in order of arrival (FCFS); we are interested in the effect of different service disciplines, like Last-Come-First-Served, Processor Sharing, Random Order of Service, and Shortest Job First, on the sojourn time distribution of a typical customer that arrives to the system during steady-state. After a discussion of the joint distribution of the numbers of customers at each queue at visit epochs of the server to a particular queue, we determine the Laplace-Stieltjes transform of the cycle-time distribution, viz., the time between two successive visits of the server to, say, Q"1. This yields the transform of the joint distribution of past and residual cycle time, w.r.t. the arrival of a tagged customer at Q"1. Subsequently concentrating on the case of gated service at Q"1, we use that cycle-time result to determine the (Laplace-Stieltjes transform of the) sojourn-time distribution at Q"1, for each of the scheduling disciplines mentioned above. Next to locally gated polling disciplines, we also consider the globally gated discipline. Again, we consider various non-FCFS service disciplines at the queues, and we determine the (Laplace-Stieltjes transform of the) sojourn-time distribution at an arbitrary queue.
Graded Security Expert System
Authors: Jüri Kivimaa, Andres Ojamaa, Enn Tyugu
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

A method for modeling graded security is presented and its application in the form of a hybrid expert system is described. The expert system enables a user to select security measures in a rational way based on the Pareto optimality computation using the dynamic programming for finding points of Pareto optimality curve. The expert system provides a rapid and fair security solution for a class of known information systems at a high comfort level.
Research of Value-Added Service Operation of Third Generation
Authors: Chun Wang, Zhong Xie, Shi-cai Xu, Hai-ying Zhang
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

It marks that China steps into the 3G era formally by the third telecommunication reorganization. The operator will transfer from "speech emphasis communication operation" into “value-added service primarily of information operation, "income mostly transfers" from "primary speech service & secondary value-added service" into "primary value-added service & secondary speech service". How will the effective operation value-added service become the major issue which the operator must face? The article firstly made a brief introduction of the 3G technical superiority, then proposed ten kind of value-added services provided by 3G, and from the focus of the organization, the industrial chain of construction, operations support, new business development and marketing aspects of the five operators on how to do a good job in the era of 3G value-added business operations.
Non-locality all the way through: emergent global constraints in the Italian morphological lexicon
Authors: Vito Pirrelli, Ivan Herreros, Basilio Calderone, Michele Virgilio
Venue: Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology (2004)

The paper reports on the behaviour of a Kohonen map of the mental lexicon, monitored through different phases of acquisition of the Italian verb system. Reported experiments appear to consistently reproduce emergent global ordering constraints on memory traces of inflected verb forms, developed through principles of local interactions between parallel processing neurons.
Local search for optimal global map generation using mid-decadal landsat images
Authors: Robert A. Morris, John Gasch, Lina Khatib, Steven Covington
Venue: Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3 (2008)

NASA and the US Geological Survey (USGS) are generating image maps of the entire Earth using Landsat 5 Thematic Mapper (TM) and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensor data from the period of 2004 through 2007. The map is comprised of thousands of scene locations and, for each location, there are tens of different images of varying quality to chose from. Constraints and preferences on map quality make it desirable to develop an automated solution to the map generation problem. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving It usmg local search. The paper also describes the integration of a GMG solver into a user interface for visualizing and comparing solutions.
Automated Sleep Staging Using Single EEG Channel for REM Sleep Deprivation
Authors: Yu-Hsun Lee, Yong-Sheng Chen, Li-Fen Chen
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

In medical literatures, it has been reported that the increased REM (rapid eye movement) density is one of the characters of depressed sleep. Some experiments were conducted to confirm that REM sleep deprivation (REM-SD) for a period of time is therapeutic for endogenous depressed patients. However, because of its high complexity and intensive labor requirement, this therapy has not yet been proved validity by a sufficient amount of depressed patients. Therefore, we propose to develop an automated sleep staging system using only single EEG channel to achieve on-line detection for REM state during sleep. For classifier design, we use a dataset of 25 subjects and the staging accuracy can achieve 80%. Once the REM state is detected by the system, the system will alarm the subject to deprive the REM sleep. The effect of REM sleep deprivation can be examined by hypnogram and the proposed system will be applied for clinical trials of depression therapy.
Radius Restrained Distributed Breadth First Search Flooding in Large-Scale Multimedia Communication
Authors: Rui Li, Shaoming Pan, Hao Wang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

This paper proposed an algorithm of radius restrained distributed breadth first search flooding for call routing in multimedia communication. By knowing the information of neighbor nodes in finite scope, this algorithm does breadth first search and selects the least number of next forwarding neighbor nodes to reduce redundant information in broadcasting routing information. Simulation results demonstrate that the proposed algorithm lessens the average forwarding times and shortens the delay in transferring routing information. Especially, it can decrease the redundant information to the greatest extent in large scale multimedia communication.
A more precise analysis of punctuation for broad-coverage surface realization with CCG
Authors: Michael White, Rajakrishnan Rajkumar
Venue: Proceedings of the Workshop on Grammar Engineering Across Frameworks (2008)

This paper describes a more precise analysis of punctuation for a bi-directional, broad coverage English grammar extracted from the CCGbank (Hockenmaier and Steedman, 2007). We discuss various approaches which have been proposed in the literature to constrain overgeneration with punctuation, and illustrate how aspects of Briscoe's (1994) influential approach, which relies on syntactic features to constrain the appearance of balanced and unbalanced commas and dashes to appropriate sentential contexts, is unattractive for CCG. As an interim solution to constrain overgeneration, we propose a rule-based filter which bars illicit sequences of punctuation and cases of improperly unbalanced apposition. Using the OpenCCG toolkit, we demonstrate that our punctuation-augmented grammar yields substantial increases in surface realization coverage and quality, helping to achieve state-of-the-art BLEU scores.
Accurate parsing of the proposition bank
Authors: Gabriele Musillo, Paola Merlo
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

We integrate PropBank semantic role labels to an existing statistical parsing model producing richer output. We show conclusive results on joint learning and inference of syntactic and semantic representations.
Development of the Automated Impedance Measurement System Based on the Slotted Line
Authors: Shuhong Chen, Xiaofeng Yuan, Chuanqiang Yu, Qiuwen Zhao
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A computer-based impedance measurement system coupled by means of General Purpose Instrumentation Bus (GPIB) is developed in this paper. Besides GPIB card and communication cables, the devices in the system include a computer, a slotted line, a signal generator, a standing-wave indicator and a digital multimeter. Many functions are provided by the computer in the system, such as standing-wave distribution display, automated calibration, UUT information management, certification printing, etc. The new system is more effective and stable than the currently used system in terms of positioning of standing-wave crest or trough, reading acquirement of standing-wave indicator, etc.
Dynamics and Evolution Patterns of Business Networks
Authors: Brigitte Gay, Eloïse Loubier
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Using complex network theories for studies of business partnerships has recently been demonstrated. In this study, taking as example the biopharmaceutical industry, we handle network data and visualization in ways that explicitly deal with its time-based nature. Using this analysis, we offer managers insights into the best ways to dynamically evaluate their local and global environment as well as their own position and its strategic relevance. An algorithm called VisuGraph is used here to give the overall network dynamics in a clockwise manner and also allows graph display of specific evolving network subsets.
A Framework for Semi-supervised Clustering Based on Dimensionality Reduction
Authors: Peng Cui, Ru-bo Zhang
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In machine learning and pattern recognition fields, collecting labeled examples costs human efforts, while vast amounts of unlabelled data are often readily available and offer some additional information. In practice, many applications require a dimensionality reduction method to deal with the partially labeled problem. In this paper, we propose a semi-supervised clustering framework, which is based on feature projection and semi-supervised fuzzy clustering. High dimensional data is mapped into a low dimensional space with feature projection. A mapping of learning data is generalized to a new datum which is classified in the low dimensional space with constrained fuzzy clustering. With the experiment on different datasets, the results show the method has good clustering performance for handling data of high dimensionality.
Technology and Workflows for Multiple Channel Content Distribution: Infrastructure implementation strategies for converged production
Authors: Philip J. Cianci
Venue: Focal Press Media Technology Professional Series (2009)

This book addresses the emergence of multi-channel broadcasting. Televisions, PCs, handheld and mobile reception devices now all receive content hat was once solely distributed by broadcast TV.No book currently on the market addresses the production infrastructure necessary to efficiently produce content for multi-channel delivery to a variety of reception platforms/devices.Readers will acquire an overview of not just the technology, but processes that impact the creative process and new cross-platform advertising sale/buy model. *Integrated, parallel production workflows design techniques for multi-channel distribution are discussed*Facilitates an understanding of the inherent challenges in producing and distributing content for multiple consumption devices*Connects consumer technology with production infrastructure*Ties together all other technical books that deal with each topic individually: i. e DTV, IPTV, Internet, Mobile TV The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
How Mobile Money Can Drive Financial Inclusion for Women at the Bottom of the Pyramid (BOP) in Indian Urban Centers
Authors: Apala Lahiri Chavan, Sarit Arora, Anand Kumar, Praneet Koppula
Venue: Proceedings of the 3rd International Conference on Internationalization, Design and Global Development: Held as Part of HCI International 2009 (2009)

This paper looks at challenges and opportunities on how mobile money can drive financial inclusion for women at the BOP (Bottom of the Pyramid) in urban Indian centers. We explore the current ecosystem of financial transactions and the role of women in a BOP household. Specifically we look at how this ecosystem differs based on how long ago they migrated from rural India and how that impacts their financial transactions. By understanding the gaps and the barriers, we outline specific challenges and opportunities for driving financial inclusion for women, through mobile money. We also posit that the success of mobile money depends on whether the 'solution' moves away from the paradigms used for designing mobile money solutions for those at the top of pyramid.
Application of artificial intelligence to operational real-time clear-air turbulence prediction
Authors: Jennifer Abernethy, Robert Sharman, Elizabeth Bradley
Venue: Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3 (2008)

Turbulence prediction is an important challenge to the aviation community because accurate forecasts are critical for the safety of the millions of people who fly every year. This paper details work in applying two AI techniques, support vector machines and logistic regression, to clear-air turbulence prediction. We show not only improved forecast accuracy over the current product performance, but also complete feasibility as part of a real-time operational turbulence forecasting system.
Robust single-view geometry and motion reconstruction
Authors: Hao Li, Bart Adams, Leonidas J. Guibas, Mark Pauly
Venue: ACM Transactions on Graphics (TOG) (2009)

We present a framework and algorithms for robust geometry and motion reconstruction of complex deforming shapes. Our method makes use of a smooth template that provides a crude approximation of the scanned object and serves as a geometric and topological prior for reconstruction. Large-scale motion of the acquired object is recovered using a novel space-time adaptive, non-rigid registration method. Fine-scale details such as wrinkles and folds are synthesized with an efficient linear mesh deformation algorithm. Subsequent spatial and temporal filtering of detail coefficients allows transfer of persistent geometric detail to regions not observed by the scanner. We show how this two-scale process allows faithful recovery of small-scale shape and motion features leading to a high-quality reconstruction. We illustrate the robustness and generality of our algorithm on a variety of examples composed of different materials and exhibiting a large range of dynamic deformations.
Natural strategies for search
Authors: Alec Banks, Jonathan Vincent, Keith Phalp
Venue: Natural Computing: an international journal (2009)

In recent years a considerable amount of natural computing research has been undertaken to exploit the analogy between, say, searching a given problem space for an optimal solution and the natural process of foraging for food. Such analogies have led to useful solutions in areas such as optimisation, prominent examples being ant colony systems and particle swarm optimisation. However, these solutions often rely on well defined fitness landscapes that are not always be available in more general search scenarios. This paper surveys a wide variety of behaviours observed within the natural world, and aims to highlight general cooperative group behaviours, search strategies and communication methods that might be useful within a wider computing context, beyond optimisation, where information from the fitness landscape may be sparse, but new search paradigms could be developed that capitalise on research into biological systems that have developed over millennia within the natural world.
Collage: A Declarative Programming Model for Compositional Development of Web Applications
Authors: Bruce Lucas, Rahul Akolkar, Charlie Wiecha
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

Collage is a declarative programming model and runtime expressly targeted at building and deploying cross-organizational software as compositions of web components. Collage is based on an RDF data model, data-driven execution model, and flexible support for cross-organizational composition of both application and UI components. In this paper we outline a uniform set of Collage language features addressing end-to-end application design, including business objects, but with particular focus on user interaction, and adaptation to current interaction platforms such as web browsers.
Cross-Site Management of User Online Attributes
Authors: Jin Liu
Venue: Proceedings of the 9th International Conference on Smart Spaces and Next Generation Wired/Wireless Networking and Second Conference on Smart Spaces (2009)

People spend time on web 2.0 sites to contribute contents and make connections with each other. On these sites a user wants to selectively reveal parts his attributes to other users, and he also wants to know more attributes of another user. Users' online attributes are often distributed across multiple sites since most users visit more than one web sites. Currently only the attributes within a specific web site can be queried on that site. This paper proposes a new solution, based on federated identity management, to enable an end user to query the cross-site attributes of another person as easily as possible.
A Method for Storing Historical Stream Data Based on Degree of Interest
Authors: Zhi-Kai Zhao, Jian-Sheng Qian, Jian Cheng, Nan-Nan Lu
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

The query time was shortened efficiently by adopting sampling method for storing historical stream data. However, important information was discarded in a large possibility because all data were treated non-discriminately with same sampling probability. In this paper, we addressed the problem by introducing a method for storing historical stream data based on degree of interest. The method used parameter Q to indicate the importance of each data, based on which a sampling algorithm had better effect on maintaining the important information. The experimental results showed that the degree of interest based method had fine performance in the query accuracy, especially for simple query on the historical stream data.
Information Extraction as Link Prediction: Using Curated Citation Networks to Improve Gene Detection
Authors: Andrew Arnold, William W. Cohen
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

In this paper we explore the usefulness of various types of publication-related metadata, such as citation networks and curated databases, for the task of identifying genes in academic biomedical publications. Specifically, we examine whether knowing something about which genes an author has previously written about, combined with information about previous coauthors and citations, can help us predict which new genes the author is likely to write about in the future. Framed in this way, the problem becomes one of predicting links between authors and genes in the publication network. We show that this solely social-network based link prediction technique outperforms various baselines, including those relying only on non-social biological information.
Sample Clustering for Fast Classification by Using the Mean Shift Procedure
Authors: Liang Lie-quan, Liang Ying-hong
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

Most classification methods are limited by speed particularly when the training data set is large, such as artificial neural networks (ANNs) and support vector machines (SVMs). In this article, we explore the possibility of utilizing the Mean Shift algorithm, which is a mode seeking procedure that estimates the gradient of the data density, to decrease the sample size. We found that in a large number of samples to be trained, most samples can be clustered into a small number of mode centroids (extreme values of density), therefore, the original samples can be reduced by means of using the results of the Mean Shift procedure. To verify the validity of this method, several classifiers including the linear discriminant analysis (LDA), k nearest neighbor (kNN) and SVMs have been tested. Experimental results prove that when the parameters are selected appropriately, the proposed method is capable of reducing the computational complexity of above classification methods, with minimum effects on the classification accuracy.