ppxscal/embedding_network huggingface dataset:
Complex Interacting Infrastructure Systems
Authors: Ian Dobson
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

The infrastructures on which our society depends not only can have failures propagating within the infrastructure but also between infrastructures. For example, Cleveland lost its water supply during the August 2003 blackout of the Northeastern USA and the loss of the twin towers in New York in September 2001 impacted both subway transport and communications. Multiple dependent and cascading failures occur when humans make honest errors in operating infrastructures. Recovering from failures spanning multiple infrastructure is complicated and expensive. While these interdependencies are becoming increasingly recognized and described qualitatively, this session explores methods to quantify the complex interactions of failures within and between infrastructures. Advances in modeling and analyzing these interactions are needed.
Auxiliary functions and optimal scanning for road detection by dynamic programming
Authors: N. Merlet
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

Shape information is useful for road detection to improve the correctness and smoothness of the results. Within the frame of dynamic programming, the proposed method stores in an auxiliary image the global direction V(M) followed in the current shortest path. The potential is a function of this image, so that pixels prolongating the current shortest path are favored. The auxiliary image is updated recursively at the same time as the energy, during the optimization. A variant of this method stores in the auxiliary image the center of the circle tangent to the current shortest path. Another application presented herein computes the average of the potential instead of its sum. The optimality principle is not verified anymore with the auxiliary functions but they give smoother results without increasing the complexity. Furthermore, several improvements w.r.t. the scanning allow gains of up to 50% for the computational time.
On Multi-Stage Sequential Coding of Correlated Sources
Authors: Jia Wang, Xiaolin Wu, Jun Sun, Songyu Yu
Venue: Proceedings of the 2007 Data Compression Conference (2007)

We study the problem of multi-stage sequential coding (MSSC), which is an extension of sequential coding of correlated sources. Consider two correlated random variables X and Y to be coded in two stages. The first stage is sequential coding as referred to in the existing literature. At the second stage, the Y encoder refines the information of Y without any knowledge of X, and X encoder refines the information of X with the knowledge of Y , while all previous outputs are known at the decoder. As the sequential coding problem provides a theoretical abstraction of video coding, the MSSC model is a theoretical abstraction of scalable video coding, which is an important application of network communications. We give an achievable region for the MSSC system. The given achievable region is tight when Y is required to be reconstructed perfectly in the usual Shannon sense at the second stage. We also study the minimum total rate MSSC problem, and derive the minimum total rate for Gaussian sources. This result disproves the possibility that the minimum total rate of one stage sequential coding can be achieved at both stages even for correlated Gaussian sources. Thus we offer a theoretical explanation for the performance loss of scalable video coding widely noted by practitioners.
EIPP Data Management Task Team Architecture
Authors: Paul Myrda, Erich Gunther, Mel Gehrs, Jerry Melcher
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

The Eastern Interconnection Phasor Project (EIPP) is advancing the state of the art in power system monitoring and shares information deemed to be valuable in enhancing the reliability of the bulk power grid. Within the project various teams have been assembled to address activities essential to the successful deployment of the project. One of the teams is the Data Management Task Team. This paper will describe both the current and future states of data management and especially how the future state will support the long term vision of the EIPP that calls for delivering value within the operations environment using new inter-regional information and measurement systems.
Topics in Organizational Systems & Technology Minitrack
Authors: Kelly Rainer, Mark Frolick
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

The Topics in Organizational Systems and Technologies is a track for papers that often do not fit well in other tracks due to the leading edge nature of the topics. We look for paper that are innovative and thought provoking.
Issues and challenges in compiling for the CBEA
Authors: Kathryn O'Brien
Venue: ACM SIGPLAN Notices (2007)

It has been demonstrated that expert programmers can develop and hand tune applications to exploit the full performance potential of the CBE architecture. We believe that sophisticated compiler optimization technology can bridge the gap between usability and performance in this arena. To this end we have developed a research prototype compiler targeting the Cell processor. In this talk we describe a variety of compiler techniques to exploit the Cell processor. These techniques are aimed at automatically generating high quality codes for the heterogeneous parallelism available on the Cell processor. In particular we will focus the discussion on managing the small local memories of the SPEs and discuss our approach to presenting the user with a single shared memory image through our compiler controlled software cache. We will also report and discuss the results we have achieved to date, which indicate that significant speedup can be achieved on this processor with a high level of support from the compiler.
Latency management in storage systems
Authors: Rodney Van Meter, Minxi Gao
Venue: Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4 (2000)

Storage Latency Estimation Descriptors, or SLEDs, are an API that allow applications to understand and take advantage of the dynamic state of a storage system. By accessing data in the file system cache or high-speed storage first, total I/O workloads can be reduced and performance improved. SLEDs report estimated data latency, allowing users, system utilities, and scripts to make file access decisions based on those retrieval time estimates. SLEDs thus can be used to improve individual application performance, reduce system workloads, and improve the user experience with more predictable behavior. We have modified the Linux 2.2 kernel to support SLEDs, and several Unix utilities and astronomical applications have been modified to use them. As a result, execution times of the Unix utilities when data file sizes exceed the size of the file system buffer cache have been reduced from 50% up to more than an order of magnitude. The astronomical applications incurred 30-50% fewer page faults and reductions in execution time of 10-35%. Performance of applications which use SLEDs also degrade more gracefully as data file size grows.
Personal Video Coding for Very Low Bit Rate Applications
Authors: Cataldo Guaragnella
Venue: Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services (2007)

In personal video communications, the postures assumed by the speaker during the connection are very similar. In past works the possible exploitation of inherent voice and video correlation has been proposed for the generation of a likely animation of a speaker, driven by audio information only. In this paper, a novel video coding technique is presented, based on the decomposition of the sequence spanned hyperspace in orthogonal components. Good quality video can be reconstructed at the receiver, particularly for very low bit rate applications, with low residual error and smooth appearance both in motion reconstruction and in the complete absence of crisp coding artifacts such as blocking structures, basing on a few proper selected examples of the speaker and a multidimensional interpolation algorithm. Principal Component Analysis exploited by Singular Value Decomposition has been used to decompose the video sequence into eigen-images. A limited set of eigen-images is chosen to span the whole video sequence subspace. Only coefficients to be used in the interpolation procedure are transmitted along the communication channel. Preliminary results are presented for Akyio QCIF video sequence.
Open Source Software in Health Care and Open Three Example
Authors: Dejan Dinevski, Paolo Inchingolo, Ivan Krajnc, Peter Kokol
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

The Open Source model has got a serious momentum over last few years and has proven its benefits also in complex (especially horizontal) applications. The time of Open Source in health care is yet to come though several successful stories has been marked already. There are some specifics of Open Source in health care that are investigated in the paper. On the basis of these specifics some recommendations are proposed to reach the interoperability and integration effect. A concrete example of O3 project is presented which is promoting Open Source adoption in e-health at regional, European and World-wide levels. This project aims to give a contribution to the development of e-health through the study of Healthcare Information Systems and the contemporary proposal of new concepts, designs and solutions for the management of health data in an integrated environment: hospitals, Regional Health Information Organizations and citizens (home-care, mobile-care and ambient assisted living).
Model-based optimization of Medical Test Strips
Authors: O. Nussen, D. Peters, H. Bolte, R. Laur
Venue: Proceedings of the Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (2003)

Medical Test Strips made from plastics can provide a cheap and reliable analysis of body liquids. The underlying microsystem contains structured micro-channels to adjust the filling time as an important parameter for chemical reactions. Columns or lamellae of some /spl mu/m dimensions are placed in the channel to define the fluidic resistance, which is influenced by the pitch between these structure elements as well as by their shape. As no analytic solution exists to describe the microfluidic interaction, the authors have been following approaches based on discrete partial differential equations and behavioural descriptions to obtain a simulation model. Model-based optimization has been performed to get useful sets of parameters to be handed to the industrial partner for manufacturing and therefore verification of the calculated results.
Interactive classification using a granule network
Authors: Yan Zhao, Yiyu Yao
Venue: Proceedings of the Fourth IEEE International Conference on Cognitive Informatics (2005)

Classification is one of the main tasks in machine learning, data mining and pattern recognition. Compared with the extensively studied data-driven approaches, the interactively user-driven approaches are less explored. A granular computing model is suggested for re-examining the classification problems. An interactive classification method using the granule network is proposed, which allows multi-strategies for granule tree construction and enhances the understanding and interpretation of the classification process. This method is complementary to the existing classification methods.
Intelligent 3D Car-Body Deformation Modeling
Authors: R. Annamaria Varkonyi-Koczy, Andras Rovid, Peter Varkonyi
Venue: Proceedings of the Second International Conference on Systems (2007)

Car body deformation modeling plays a very important role in crash accident analyses, as well as in safe car body design. The determination of the energy absorbed by the deformation and the corresponding Energy Equivalent Speed (EES) can be of key importance in both cases, however their precise determination is a very difficult task. Although, using the results of crash tests, intelligent methods offer an automatic way to model the deformation of the carbody as well as the crash process itself, based on which we can determine the absorbed energy, the before-crash speed of the car, and other important features of crashes. In this paper a modeling technique and an intelligent expert system are introduced which together are able to follow the deformation process of carbodies in car crashes and to analyze the strength of the different parts without any human intervention, thus can significantly contribute to the improvement of the modeling, (automatic) design, and safety of car-bodies.
A fast algorithm for DCT-domain inverse motion compensation
Authors: N. Merhav
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

One of the important tasks of a multiuser video network server is to composite compressed video streams from several sources into a single compressed video stream. A great deal of the computational load can be saved if this composition is performed directly in the compressed domain rather than using the brute-force approach of converting back to the uncompressed domain, compositing pixel-by-pixel in the spatial domain, and re-compressing the composite stream. We propose a fast algorithm that converts motion compensated compressed video into a sequence of DCT-domain blocks corresponding to the spatial domain blocks of the current frame alone, without prediction based on other frames, i.e., removing the inter-frame element of the compression-decompression. This step enables video compositing in the DCT compressed domain as well as several compositing operations, e.g., scaling, overlapping, translation, filtering, etc. The proposed algorithm saves about 47% of the computations compared to the brute-force approach even without assuming sparseness of the DCT blocks. For typical sparse DCT blocks, where only the top-left 4/spl times/4 quadrant is nonzero, the reduction in computational complexity is about 68%.
Extracting Coarse-Grained Parallelism in Program Loops with the Slicing Framework
Authors: Anna Beletska, Wlodzimierz Bielecki, Pierluigi San Pietro
Venue: Proceedings of the Sixth International Symposium on Parallel and Distributed Computing (2007)

A novel approach for extracting coarse-grained parallelism being represented with independent and synchronization-requiring slices is presented. Each slice is composed of dependent iterations of perfectly nested loops. Presented algorithms work for both uniform and non-uniform loops. Our approach, based on operations on relations and sets, requires exact dependence analysis. Examples illustrating the proposed algorithm and results of experiments are presented.
Benefits of Clustering in Landmark-Aided Positioning Algorithms
Authors: Balasubramaneyam Maniymaran, Muthucumaru Maheswaran, Yuanyuan Gao
Venue: Proceedings of the 21st International Symposium on High Performance Computing Systems and Applications (2007)

In this paper, we propose simple and practical strategies to improve the trustworthiness of network positioning schemes. In particular, our strategies make network positioning immune to non-random perturbations such as denial-of-service attacks and localized network congestion. Additionally, we studied the overhead generated by existing network positioning algorithms and propose an algorithm that results in low overhead while retaining very high accuracies. We performed extensive simulations and implementations on PlanetLab to examine the performance trade-offs.
Optimal k-Anonymity with Flexible Generalization Schemes through Bottom-up Searching
Authors: Tiancheng Li, Ninghui Li
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

In recent years, a major thread of research on kanonymity has focused on developing more flexible generalization schemes that produce higher-quality datasets. In this paper we introduce three new generalization schemes that improve on existing schemes, as well as algorithms enumerating valid generalizations in these schemes. We also introduce a taxonomy for generalization schemes and a new cost metric for measuring information loss. We present a bottom-up search strategy for finding optimal anonymizations. This strategy works particularly well when the value of k is small. We show the feasibility of our approach through experiments on real census data.
Contract-based load management in federated distributed systems
Authors: Magdalena Balazinska, Hari Balakrishnan, Mike Stonebraker
Venue: Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1 (2004)

This paper focuses on load management in loosely-coupled federated distributed systems. We present a distributed mechanism for moving load between autonomous participants using bilateral contracts that are negotiated offline and that set bounded prices for moving load. We show that our mechanism has good incentive properties, efficiently redistributes excess load, and has a low overhead in practice. Our load management mechanism is especially well-suited for distributed stream-processing applications, an emerging class of data-intensive applications that employ a "continuous query processing" model. In this model, streams of data are processed and composed continuously as they arrive rather than after they are indexed and stored. We have implemented the mechanism in the Medusa distributed stream processing system, and we demonstrate its properties using simulations and experiments.
Karma: know-it-all replacement for a multilevel cache
Authors: Gala Yadgar, Michael Factor, Assaf Schuster
Venue: Proceedings of the 5th USENIX conference on File and Storage Technologies (2007)

Multilevel caching, common in many storage configurations, introduces new challenges to traditional cache management: data must be kept in the appropriate cache and replication avoided across the various cache levels. Some existing solutions focus on avoiding replication across the levels of the hierarchy, working well without information about temporal locality-information missing at all but the highest level of the hierarchy. Others use application hints to influence cache contents. We present Karma, a global non-centralized, dynamic and informed management policy for multiple levels of cache. Karma leverages application hints to make informed allocation and replacement decisions in all cache levels, preserving exclusive caching and adjusting to changes in access patterns. We show the superiority of Karma through comparison to existing solutions including LRU, 2Q, ARC, MultiQ, LRU-SP, and Demote, demonstrating better cache performance than all other solutions and up to 85% better performance than LRU on representative workloads.
Modelling Network Memory Servers with Parallel Processors, Break-downs and Repairs
Authors: O. Gemikonakli, G. Mapp, E. Ever, D. Thakker
Venue: Proceedings of the 40th Annual Simulation Symposium (2007)

This paper presents an analytical method for the performability evaluation of a previously reported network memory server attached to a local area network. To increase the performance and availability of the proposed system, an additional server is added to the system. Such systems are prone to failures. With this in mind, a mathematical model has been developed to analyse the performability of the proposed system with break-downs and repairs. Mean queue lengths and the probability of job losses for the LAN feeding the Network Memory Server is calculated and presented.
Allocating online advertisement space with unreliable estimates
Authors: Mohammad Mahdian, Hamid Nazerzadeh, Amin Saberi
Venue: Proceedings of the 8th ACM conference on Electronic commerce (2007)

We study the problem of optimally allocating online advertisement space to budget-constrained advertisers. This problem was defined and studied from the perspective of worst-case online competitive analysis by Mehta et al. Our objective is to find an algorithm that takes advantage of the given estimates of the frequencies of keywords to compute a near optimal solution when the estimates are accurate, while at the same time maintaining a good worst-case competitive ratio in case the estimates are totally incorrect. This is motivated by real-world situations where search engines have stochastic information that provide reasonably accurate estimates of the frequency of search queries except in certain highly unpredictable yet economically valuable spikes in the search pattern. Our approach is a black-box approach: we assume we have access to an oracle that uses the given estimates to recommend an advertiser everytime a query arrives. We use this oracle to design an algorithm that provides two performance guarantees: the performance guarantee in the case that the oracle gives an accurate estimate, and its worst-case performance guarantee. Our algorithm can be fine tuned by adjusting a parameter α, giving a tradeoff curve between the two performance measures with the best competitive ratio for the worst-case scenario at one end of the curve and the optimal solution for the scenario where estimates are accurate at the other en. Finally, we demonstrate the applicability of our framework by applying it to two classical online problems, namely the lost cow and the ski rental problems.
Multichannel image restoration using compound Gauss-Markov random fields
Authors: R. Molina
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

A solution to the multichannel image restoration problem is provided using compound Gauss-Markov random fields. For the single channel deblurring problem the convergence of the simulated annealing (SA) and iterative conditional mode (ICM) algorithms has not been established. We propose two new iterative multichannel restoration algorithms which can be considered as extensions of the classical SA and ICM approaches and whose convergence is established. Experimental results with color images demonstrate the effectiveness of the proposed algorithms.
Wearable System-on-a-Chip Pulse Radar Sensors for the Health Care: System Overview
Authors: Domenico Zito, Domenico Pepe, Bruno Neri, Danilo De Rossi, Antonio Lanata
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

A new system-on-a-chip radar sensor for next generation wearable wireless interface applied to the human health-care and safeguard is presented. The system overview is provided and a summary of the feasibility study of the radar sensor is presented. In detail, the overall system consists of a radar sensor for detecting the heart and breath rates and a low-power IEEE 802.15.4 ZigBee radio interface, which provides a wireless data link with remote data acquisition and control units. Particularly, the pulse radar exploits 3.1-10.6 GHz ultra wide band signals, which allow a significant reduction of the transceiver complexity and, then, of its power consuption. The operating principle is highlighted and the results of the system analysis are summarized. Such a novel system-on-a-chip wireless wearable interface enables low-cost silicon technologies for contactless measuring of the primary vital signs and extends the capability in terms of applications for the emerging wireless body area networks.