ppxscal/embedding_network huggingface dataset:
Procrastination determination for periodic real-time tasks in leakage-aware dynamic voltage scaling systems
Authors: Jian-Jia Chen, Tei-Wei Kuo
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

Many computing systems have adopted the dynamic voltage scaling (DVS) technique to reduce energy consumption by slowing down operation speed. However, the longer a job executes, the more energy in leakage current the processor consumes for the job. To reduce the power/energy consumption from the leakage current, a processor can enter the dormant mode. Existing research results for leakage-aware DVS scheduling perform procrastination of real-time jobs greedily so that the idle time can be aggregated as long as possible to turn off the processor. This paper proposes algorithms for the procrastination determination of periodic real-time tasks in uniprocessor systems. Instead of greedy procrastination, the procrastination procedures are applied only when the evaluated energy consumption is less than not procrastination. Evaluation results show that our proposed algorithms could derive energy-efficient solutions and outperform existing algorithms.
An Improved Resource Discovery Algorithm for Gnutella Networks
Authors: Yu-Tang Guo, Wan-Li Lv, Bin Luo
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

In this paper, we summarize the characteristics of message search mechanism of Gnutella P2P network model. By analyzing its disadvantages, an improvement of resource discovery algorithm is proposed, it can more effectively reduce network traffic than the existing search methods in Gnutella system, and it can also improve Gnutella network's integrity, availability and scalability.
Adaptive Fragmentation for Latency Control and Energy Management in Wireless Real-time Environments
Authors: Dinesh Rajan, Christian Poellabauer
Venue: Proceedings of the International Conference on Wireless Algorithms,Systems and Applications (2007)

Wireless environments are typically characterized by unpredictable and unreliable channel conditions. In such environments, fragmentation of network-bound data is a commonly adapted technique to improve the probability of successful data transmissions and reduce the energy overheads incurred due to re-transmissions. The overall latencies involved with fragmentation and consequent re-assembly of fragments are often neglected which bear significant effects on the real-time guarantees of the participating applications. This work studies the latencies introduced as a result of the fragmentation performed at the link layer (MAC layer in IEEE 802.11) of the source device and their effects on end-to-end delay constraints ofmobile applications (e.g., media streaming). Based on the observed effects, this work proposes a feedback-based adaptive approach that chooses an optimal fragment size to a) satisfy end-to-end delay requirements of the distributed application and b) minimize the energy consumption of the source device by increasing the probability of successful transmissions, thereby reducing re-transmissions and their associated costs.
Piecewise Approximation of Pictures Using Maximal Neighborhoods
Authors: N. Ahuja
Venue: IEEE Transactions on Computers (1978)

Suppose that we are given a picture having approximately piecewise constant gray leveL Each point P has a largest neighborhood N(P) that is entirely contained in one of the constant regions, and the set of maximal N(P)'s (i.e., N(P)'s not contained in other N(P)'s) constitutes an economical description of the picture, generalizing the Blum "skeleton" or medial axis transformation. This description can be used to construct approximations to the picture (e.g., by discarding small N(P)'s). The picture can be smoothed, without excessive blurring, by averaging over each N(P). By taking differences between pairs of touching maximal N(P)'s, the edges between the regions can be detected; since this edge detection scheme is not based on symmetrical detection operators, it is not handicapped when two adjacent regions differ greatly in size.
Google, Profiling, and Privacy
Authors: Daniel J. Weitzner
Venue: IEEE Internet Computing (2007)

Today, US and European policy makers are taking a hard look at the proposed merger between Google and Doubleclick. Although antitrust regulators are examining the merger's details to determine whether it could negatively affect the market, the spotlight has shifted to the deal's privacy implications.
Extraction of Vectorized Graphical Information from Scientific Chart Images
Authors: W. Huang, R. Liu, C.-L. Tan
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

Graphical components information extraction is a crucial step in the chart recognition and understanding process. However, existing methods of information extraction from chart images either are type-dependent or rely on certain assumptions. In this paper, we present a general method to extract vectorized graphical information from scientific chart images. Our algorithm firstly constructs a data structure called directional single-connected chains (DSCC). It then employs ellipse-specific fitting and orthogonal diagonalization to calculate the curvatures of the chains and classify the chains into either straight lines or arcs. Finally we combine all straight lines and all arcs accordingly and use linear regression to compute their attributes. The DSCC has a good property in that it is less susceptible to noise. The experiment results show that our algorithm is efficient, robust and accurate.
A Robust Extraction Algorithm Based on a Specific Kurtosis Value Range
Authors: Yalan Ye, Zhi-Lin Zhang, Jia Chen, Duojiao Wu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Independent component analysis (ICA), blind source separation (BSS) and related methods like blind source extraction (BSE) have been considered as a fundamental data analysis tool in the fields of neural network and signal processing. In this paper, we propose a robust algorithm based on a specific kurtosis value range that can extract a desired source signal as the first output signal with a specific kurtosis value range. That is to say, if we know that the kurtosis value of the desired signal generally lies in a specific range, while the values of other unwanted source signals do not belong to this range, we can use the proposed algorithm to extract the desired signal successfully. Moreover, the algorithm can work well in some poor situation (when the kurtosis values of some source signals are very close to each other). In addition, because of adopting an interior point penalty function method, the algorithm is robust to the estimation error of the kurtosis value range. Finally, we use the proposed algorithm to extract the accurate and reliable fetal electrocardiogram (FECG).
Delocalized Plans and Program Comprehension
Authors: S. Letovsky
Venue: IEEE Software (1986)

A maintainer's understanding can go awry when it is based on purely local clues. How can we spell out the intentions behind a piece of code?
Multi-Issue Negotiation Research Based On Niched Co-evolutionary Genetic Algorithm
Authors: Yong Yuan, Yong-quan Liang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

This paper presents a simulation algorithm called SANCGA for bilateral multi-issue negotiation based on co-evolutionary genetic algorithm and isolated niche technique, and designs an experiment to simulate the co-evolutionary strategy learning process in an alternating offer negotiation scenario. The experiment results validate that SANCGA algorithm can form local niches in the strategy populations and generate an approximate Pareto optimal strategy set.
Current Multimedia Data Formats and Semantic Computing: A Practical Example and the Challenges for the Future
Authors: Gerald Friedland
Venue: Proceedings of the International Conference on Semantic Computing (2007)

Research is doing exciting progress in understanding images as more than just a set of pixels, videos as more than just an even greater set of pixels synchronized with time, or audio streams as more than just an array of samples. Current implementations of multimedia data formats, such as MPEG, however, still focus on the storage of pixels and samples. This article uses a straightforward example of a system where a pixel-based video stream is superimposed on a vector-based animation to show that the lack of capability to store higher-level semantic information leaves the developers only two choices: Either accept suboptimal quality or design a new non-standard format. The paper presents an in-depth discussion of a practical example and draws conclusions for the future directions of multimedia data formats.
A navigational guidance system for web-based education
Authors: So-Jung Lee, Hyosook Jung, Seongbin Park
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

When a user is navigating inside a complex hyperspace that consists of a lot of informational units, the user may get lost in the hyperspace. In this paper, we propose a navigational guidance system that provides a contextual information for a user so that the user can be guided towards relevant information while freely navigating in a hyperspace. The system analyzes user's browsing activities and provides appropriate messages when it appears that the user is getting disoriented. One application of the proposed system is Web-based education where teachers prepare informational units that students need to visit in order to understand the learning materials. If a student is following a path that is far from the suggested path prepared by a teacher the system generates a guidance message.
Leveraging a Commercial Mutation Analysis Tool For Research
Authors: Mark Hampton, Stephane Petithomme
Venue: Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (2007)

A presentation of Certitude, which is a commercial software tool performing mutation analysis (MA). The product has been deployed within the microelectronics industry. Certitude is presented with specific emphasis on the product's standard processing model and feature extension mechanisms to support mutation analysis research an extension of Certitude to news languages.
Agent-Based Modeling of Ambidextrous Organizations: Virtualizing Competitive Strategy
Authors: Nicholas S. P. Tay, Robert F. Lusch
Venue: IEEE Intelligent Systems (2007)

Agent-based modeling is the development of computer simulations in which markets, societies, or other macro structures evolve from the ground up through the actions, interactions, and breeding of digital organisms that mimic real-life economic agents. ABM arrives at an especially appropriate time in the development of economic, marketing, and management thought because competitive markets are increasingly viewed as evolutionary processes and complex adaptive systems. A virtual market where organizations compete for buyers demonstrates ABM's richness for competitive-strategy development. An ambidextrous organization (that is, a firm that both exploits its current competencies and explores new competencies) operating in a turbulent environment is more innovative and responsive to dramatic shifts in consumer preferences, and consequently, more profitable. However, in a stable environment, a nonambidextrous organization (one that exploits its current competencies but doesn't explore new competencies) performs better. This article is part of a special issue on social computing.
A particle swarm optimization approach to nonlinear rational filter modeling
Authors: Yih-Lon Lin, Wei-Der Chang, Jer-Guang Hsieh
Venue: Expert Systems with Applications: An International Journal (2008)

This paper presents a particle swarm optimization (PSO) algorithm to solve the parameter estimation problem for nonlinear dynamic rational filters. For the modeling of the nonlinear rational filter, the unknown filter parameters are arranged in the form of a parameter vector which is called a particle in the terminology of PSO. The proposed PSO algorithm applies the velocity updating and position updating formulas to the population composed of many particles such that better particles are generated. Because the PSO algorithm manipulates the parameter vectors directly as real numbers rather than binary strings, implementing the PSO algorithm into the computer programs becomes fairly easy and straightforward. Finally, an illustrative example for the modeling of the nonlinear rational filter is provided to show the validity, as compared with the traditional genetic algorithm, of the proposed method.
Statistical Consistency of Kernel Canonical Correlation Analysis
Authors: Kenji Fukumizu, Francis R. Bach, Arthur Gretton
Venue: The Journal of Machine Learning Research (2007)

While kernel canonical correlation analysis (CCA) has been applied in many contexts, the convergence of finite sample estimates of the associated functions to their population counterparts has not yet been established. This paper gives a mathematical proof of the statistical convergence of kernel CCA, providing a theoretical justification for the method. The proof uses covariance operators defined on reproducing kernel Hilbert spaces, and analyzes the convergence of their empirical estimates of finite rank to their population counterparts, which can have infinite rank. The result also gives a sufficient condition for convergence on the regularization coefficient involved in kernel CCA: this should decrease as n-1/3, where n is the number of data.
Evolving behaviors in the iterated prisoner's dilemma
Authors: David B. Fogel
Venue: Evolutionary Computation (1993)

Evolutionary programming experiments are conducted to investigate the conditions that promote the evolution of cooperative behavior in the iterated prisoner's dilemma. A population of logical stimulus-response devices is maintained over successive generations with selection based on individual fitness. The reward for selfish behavior is varied across a series of trials. Simulations indicate three distinct patterns of behaviors in which mutual cooperation is inevitable, improbable, or apparently random. The ultimate behavior can be reliably predicted by examining the payoff matrix that defines the reward for alternative joint behaviors.
Hamiltonicity of random graphs produced by 2-processes
Authors: András Telcs, Nicholas Wormald, Sanming Zhou
Venue: Random Structures Algorithms (2007)

Suppose that a random graph begins with n isolated vertices and evolves by edges being added at random, conditional upon all vertex degrees being at most 2. The final graph is usually 2-regular, but is not uniformly distributed. Some properties of this final graph are already known, but the asymptotic probability of being a Hamilton cycle was not known. We answer this question along with some related questions about cycles arising in the process. &copy; 2006 Wiley Periodicals, Inc. Random Struct. Alg., 2007
Incorporation of the Universal Communications Identifier (UCI) to NGN
Authors: Tatiana Kovacikova
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

Electronic communication is becoming increasingly complex. Consumers currently expect to have a new identity for every new communications service -- i.e. one address for e-mail, another for telephone, a third for mobile etc. For a couple of years, ETSI (European Telecommunications Standards Institute) has been working on the development of the Universal Communications Identifier (UCI), a system which aims to bind many services to a single identity and manage the communications with a personal user manager. This technology could see the end of the proliferation of complex addresses, numbers and other user identifiers in use today. The objective of the current work in ETSI on UCI is to increase the chance that the benefits that UCI brings will be made available to all citizens of Europe at the earliest opportunity and would ensure that its realization would be a key differentiator for NGN (Next Generation Network). The paper provides a review and assessment as to what extent existing ETSI TISPAN NGN standards and specifications support elements of a UCI implementation and how, if necessary, they should be adapted in order to more fully support complete UCI implementation. The analysis presented is restricted to UCI incorporation to TISPAN NGN architecture.
MARO - MinDrift affinity routing for resource management in heterogeneous computing systems
Authors: Yu-Tong He, Issam Al-Azzoni, Douglas Down
Venue: Proceedings of the 2007 conference of the center for advanced studies on Collaborative research (2007)

This paper deals with designing effective resource management strategies for systems of heterogeneous computers. Each computer is represented as an abstract server, capable of serving different task demands at different rates. We consider a system with I types of independent Poisson task demand arrival streams and J parallel servers with independent non-identical processing time distributions for each arrival type. The decision of routing each type i task immediately upon arrival to a server j is made by comparing the state information of a subset of the J servers. We show that choosing the subset according to a linear programming (LP) problem which maximizes the system capacity can not only significantly reduce the amount of state information required in making the routing decision, but also yield shorter total mean queue length (and hence mean time in system) compared with the policies requiring global state information. In addition, we explore means of limiting flexibility to further reduce the required state information.
Preserving privacy in association rule mining with bloom filters
Authors: Ling Qiu, Yingjiu Li, Xintao Wu
Venue: Journal of Intelligent Information Systems (2007)

Privacy preserving association rule mining has been an active research area since recently. To this problem, there have been two different approaches--perturbation based and secure multiparty computation based. One drawback of the perturbation based approach is that it cannot always fully preserve individual's privacy while achieving precision of mining results. The secure multiparty computation based approach works only for distributed environment and needs sophisticated protocols, which constrains its practical usage. In this paper, we propose a new approach for preserving privacy in association rule mining. The main idea is to use keyed Bloom filters to represent transactions as well as data items. The proposed approach can fully preserve privacy while maintaining the precision of mining results. The tradeoff between mining precision and storage requirement is investigated. We also propose ¿-folding technique to further reduce the storage requirement without sacrificing mining precision and running time.
ChirCor: A new tool for generating synthetic chirp-sonar seismograms
Authors: Giulio Dal Forno, Luca Gasperini
Venue: Computers Geosciences (2008)

The long-term successful use of synthetic seismograms in traditional seismic reflection studies suggests that their implementation for high-resolution non-impulsive seismic sources would also be beneficial. We present here ChirCor v1.0, a program for managing physical-log data (P-wave velocity and density) and chirp-sonar seismograms, also equipped with a synthetic-trace generator, that could be used for correlating real seismograms to synthetics. The software, designed with a user-friendly graphic interface, is intended mainly for oceanographers and marine geologists as a tool for correlating high-resolution seismic images and sediment cores. ChirCor v1.0 will be distributed as freeware for non-commercial purposes. We provide instructions regarding the use of the program together with a description of the algorithms implemented in the code; we also include an example of how to operate with the program based on the data collected during the MARMARA2001 marine geological expedition.
Energy Balancing Routing Algorithms in Wireless Sensor Networks Connected as Grids
Authors: Xiao Chen, Xingde Jia
Venue: Proceedings of the International Conference on Wireless Algorithms,Systems and Applications (2007)

In this paper, we discuss energy balancing routing algorithms for wireless sensor networks connected as grids. The scarcest resource in a sensor network is the energy in each sensor. We deploy the sensors in a grid where environment allows to maximize the lifetime, robustness and fault tolerance of the sensor network by taking advantage of the topology. To the best of our knowledge, no other paper has addressed this so far. We design several routing algorithms to achieve energy balance in the network, which directly influences the lifetime of sensor networks. Through simulations, we discover that the best algorithm takes dynamic traffic into account and uses local information for routing guidance.
Strict partitions and discrete dynamical systems
Authors: Minh Ha Le, Thi Ha Duong Phan
Venue: Theoretical Computer Science (2007)

We prove that the set of partitions with distinct parts of a given positive integer under dominance ordering can be considered as a configuration space of a discrete dynamical model with two transition rules and with the initial configuration being the singleton partition. This allows us to characterize its lattice structure, fixed point, and longest chains as well as their length, using Chip Firing Game theory. Finally, we study the recursive structure of infinite extension of the lattice of strict partitions.
Regression Relevance Models for Data Fusion
Authors: Shengli Wu, Yaxin Bi, Sally McClean
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Data fusion has been investigated by many researchers in the information retrieval community and has become an effective technique for improving retrieval effectiveness. In this paper we investigate how to model rank-probability of relevance relationship in resultant document list for data fusion since reliable relevance scores are very often unavailable for component results. We apply statistical regression technique in our investigation. Different regression models are tried and two good models, which are cubic and logistic models, are selected from a group of candidates. Experiments with 3 groups of results submitted to TREC are carried out and experimental results demonstrate that the cubic and logistic models work better than the linear model and are as good as those methods which use scoring information.
An evolutive algorithm for wind farm optimal design
Authors: José Castro Mora, José M. Calero Barón, Jesús M. Riquelme Santos, Manuel Burgos Payán
Venue: Neurocomputing (2007)

An evolutive algorithm for the optimal design of wind farms is presented. The algorithm objective is to optimize the profits given an investment on a wind farm. Net present value will be used as a figure of the revenue. To work out this figure, several economic factors such as the initial capital investment, the discount rate, the value of the generated energy and the number of the years spanned by the investment are considered. All this factors depends on the preliminary design of the wind park (number, type, tower height and layout situation of wind generators), which are the variables to set.