ppxscal/embedding_network huggingface dataset:
An Energy-Aware Routing Scheme with Node Relay Willingness in Wireless Sensor Networks
Authors: Huifang Chen, Hiroshi Mineno, Tadanori Mizuno
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Energy efficiency has been known as the most significant problem in all facets of the wireless sensor network operations. For energy-aware routing scheme for the wireless sensor networks, it is necessary to use sub-optimal paths occasionally to increase the survivability of networks. In this paper, we present a new network lifetime definition and formulate the energy-aware routing problem with defined network lifetime. And then we propose an energy-aware routing scheme with the node relay willingness for wireless sensor networks. It considers not only to route packets through sensor nodes that have sufficient energy reserves, but also to route packets through lightloaded nodes. Simulation results show that the proposed routing algorithm can achieve longer network lifetime than that of the routing algorithm only considering the energy reserves.
The Anatomy Study of Load Balancing in Distributed System
Authors: K. Q. Yan, S. C. Wang, C. P. Chang, L. Y. Tseng
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

In recent years, network bandwidth and quality has been drastically improved in a speed even much faster than the enhancement of computer performance. Various communication and computing tasks in the fields can be integrated and applied in a distributed system in nowadays. However, those resources are heterogeneous and dynamic in distributed systems connecting a broad range of resources. This study proposed a hybrid load balancing policy to maintain performance and stability of distributed system.
Towards an automatic complexity analysis for generic programs
Authors: Kyle D. Ross
Venue: Proceedings of the 2006 ACM SIGPLAN workshop on Generic programming (2006)

Generic libraries, such as the C++ Standard Template Library (STL), provide flexible, high-performance algorithms and datatypes, along with functional specifications and performance guarantees. It is left as a nontrivial task to the library user to choose appropriate algorithms and data types for a particular problem. In the present paper, we describe an automatic analysis to aid library users in selecting types for use in generic programs. The analysis is based on manipulation and comparison of symbolic complexity expressions, constructed using cost-bound functions and abstract interpretation of program behaviour. Our analysis serves to detect and rectify "performance bugs" by recommending type selections that will improve performance.
Events and Sightings
Authors: Chigusa Kita
Venue: IEEE Annals of the History of Computing (2006)

This department article features stories about conference reports on "Computers in Use: Historical and Social Perspectives," obituaries of William Norris and Kazuhiro Fuchi, the PC's 25th birthday, and the 50th anniversary of the hard disk drive.
Support Vector Machine-Based Feature Selection for Classification of Liver Fibrosis Grade in Chronic Hepatitis C
Authors: Zheng Jiang, Kazunobu Yamauchi, Kentaro Yoshioka, Kazuma Aoki, Susumu Kuroyanagi, Akira Iwata, Jun Yang, Kai Wang
Venue: Journal of Medical Systems (2006)

Although liver biopsy is currently regarded as the gold standard for staging liver fibrosis in chronic hepatitis C, it is a costly invasive procedure and carries a small risk for complication. Our aim in this study was to construct a simple model to distinguish between patients with no or mild fibrosis (METAVIR F0---F1) versus those with clinically significant fibrosis (METAVIR F2---F4). We retrospectively studied 204 consecutive CHC patients. Thirty-four serum markers with age, gender, duration of infection were assessed to classify fibrosis with a classifier known as the support vector machine (SVM). The method of feature selection known as sequential forward floating selection (SFFS) was introduced before the performance of SVM. When four serum markers were extracted with SFFS-SVM, F2---F4 could be predicted accurately in 96%. Our study showed that application of this model could identify CHC patients with clinically significant fibrosis with a high degree of accuracy and may decrease the need for liver biopsy.
Maximum likelihood technique to quadrature parameter estimation
Authors: J. W. Pierre, R. A. Green
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

In array processing applications, quadrature receiver gain imbalance can significantly degrade the performance of direction-finding algorithms and adversely affect the received signal quality. These errors are present, to some degree, when quadrature receivers are used with sensor arrays, and can be partially compensated for by estimating these error parameters and correcting for them during array calibration. Of particular interest is finding the best estimator possible to ensure proper and accurate calibration. This paper derives the maximum likelihood (ML) estimator for the quadrature gain errors, based on a measured array manifold. The bias and variance of the estimators are derived and simulations are incorporated to demonstrate estimator effectiveness.
A statistical framework for fusing mid-level perceptual features in news story segmentation
Authors: H. Winston, H.-M. Hsu, Shih-Fu Chang
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

News story segmentation is essential for video indexing, summarization and intelligence exploitation. In this paper, we present a general statistical framework, called exponential model or maximum entropy model that can systematically select the most significant mid-level features of various types (visual, audio, and semantic) and learn the optimal ways in fusing their combinations in story segmentation. The model utilizes a family of weighted, exponential functions to account for the contributions from different features. The Kullbak-Leibler divergence measure is used in an optimization procedure to iteratively estimate the model parameters, and automatically select the optimal features. The framework is scalable in incorporating new features and adapting to new domains and also discovers how these feature sets contribute to the segmentation work. When tested on foreign news programs, the proposed techniques achieve significant performance improvement over prior work using ad hoc algorithms and slightly better gain over the state of the art using HMM-based models.
Secure Collaborative and Distributed Services in the Java Card Grid Platform
Authors: Serge Chaumette, Achraf Karray, Damien Sauveron
Venue: Proceedings of the International Symposium on Collaborative Technologies and Systems (2006)

Ensuring the security of services in a distributed system requires the collaboration of all the elements involved in providing this service. In this paper we present how the security of collaborative distributed services is ensured in the Java CardTM1 Grid project carried out at LaBRI, Laboratoire Bordelais de Recherche en Informatique. The aim of this project is to build a hardware platform and the associated software components to experiment on the security features of distributed applications. To achieve this goal, we use the hardware components that offer the highest security level, i.e. smart cards. We do not pretend that the resulting platform can be efficient, but we believe that it is a good testbed to experiment on the security features that one would require for real distributed applications. The kind of applications (and the services they use) that we run on our platform are those that require a high level of confidentiality regarding their own binary code, the input data that they handle, and the results that they produce. This paper focuses on the collaboration aspect of the secure services in our platform.
Active Coevolutionary Learning of Deterministic Finite Automata
Authors: Josh Bongard, Hod Lipson
Venue: The Journal of Machine Learning Research (2005)

This paper describes an active learning approach to the problem of grammatical inference, specifically the inference of deterministic finite automata (DFAs). We refer to the algorithm as the estimation-exploration algorithm (EEA). This approach differs from previous passive and active learning approaches to grammatical inference in that training data is actively proposed by the algorithm, rather than passively receiving training data from some external teacher. Here we show that this algorithm outperforms one version of the most powerful set of algorithms for grammatical inference, evidence driven state merging (EDSM), on randomly-generated DFAs. The performance increase is due to the fact that the EDSM algorithm only works well for DFAs with specific balances (percentage of positive labelings), while the EEA is more consistent over a wider range of balances. Based on this finding we propose a more general method for generating DFAs to be used in the development of future grammatical inference algorithms.
Relational Ensemble Classification
Authors: Christine Preisach, Lars Schmidt-Thieme
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Relational classification aims at including relations among entities, for example taking relations between documents such as a common author or citations into account. However, considering more than one relation can further improve classification accuracy. In this paper we introduce a new approach to make use of several relations as well as both relations and attributes for classification using ensemble methods. To accomplish this, we present a generic relational ensemble model, that can use different relational and local classifiers as components. Furthermore, we discuss solutions for several problems concerning relational data such as heterogeneity, sparsity, and multiple relations. Finally, we provide empirical evidence, that our relational ensemble methods outperform existing relational classification methods, even rather complex models such as relational probability trees (RPTs), relational dependency networks (RDNs) and relational Bayesian classifiers (RBCs).
Agile Procurement and Dynamic Value for Money to Facilitate Agile Software Projects
Authors: Diane Jamieson, Kevin Vinsen, Guy Callender
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

In situations where software systems are developed under formal contractual arrangements it is common for the buyer and supplier to dispute whether value for money is being delivered, even though it is unlikely that either party will be capable of measuring this outcome. This problem is exacerbated by a basic incompatibility between the buyer's linear or sequential procurement process and the supplier's agile software development methodology. At the commencement of a software development contract it is probable that a supplier will have accepted terms and conditions relating to scope and price that are philosophically in opposition to agile principles, particularly in respect of an iterative elaboration of requirements. A range of suboptimal project outcomes, including budget and schedule blowouts, typically result in these situations. This paper proposes an agile procurement process that can operate in conjunction with an agile software development methodology to improve many aspects of software project delivery. This process is supported by a mechanism designed to give the buyer and supplier the ability to define and agree the value for money proposition at various milestones within the project - dynamic value for money.
Active Learning in Face Recognition: Using Tracking to Build a Face Model
Authors: Robin Hewitt, Serge Belongie
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

This paper describes a method by which a computer can autonomously acquire training data for learning to recognize a user's face. The computer, in this method, actively seeks out opportunities to acquire informative face examples. Using the principles of co-training, it combines a face detector trained on a single input image with tracking to extract face examples for learning. Our results show that this method extracts well-localized, diverse face examples from video after being introduced to the user through only one input image. In addition to requiring very little human intervention, a second significant benefit to this method is that it doesn't rely on a statistical classifier trained on a preexisting face database for face detection. Because it doesn't require pre-training, this method has built-in robustness for situations where the application conditions differ from the conditions under which training data were acquired.
Flexible integration of XML into modeling and simulation systems
Authors: Mathias Röhl, Adelinde M. Uhrmacher
Venue: Proceedings of the 37th conference on Winter simulation (2005)

As the effort towards standardization of formalism representations increases so does the need for verifying whether models do or do not follow a standard. Data binding allows to systematically exploit XML and its associated technologies for modeling and simulation purposes. Based on the schema definition of a formalism, a binding compiler generates model classes that support the user in constructing models according to the formalism. Most constraints can be checked automatically, few require separate efforts by the designer of the simulation system. Although simulators could be build for these declarative model descriptions, they would be hardly efficient. To this and, a separate transformation component is required. In this overall process, both model specifications that are consistent with a formalism definition and models that can be executed efficiently are supported equally.
Securing the AODV protocol using specification-based intrusion detection
Authors: Hoda M. Hassan, Mohy Mahmoud, Sherif El-Kassas
Venue: Proceedings of the 2nd ACM international workshop on Quality of service security for wireless and mobile networks (2006)

This paper presents an implementation of an Intrusion Detection System (IDS) aiming to secure the AODV protocol designed for MANET. The IDS is designed as multiple static agents that run on a subset of the nodes in the network and executes a monitoring protocol that observes the process of route establishment. The monitoring protocol uses specification based intrusion detection to identify misuses to the routing messages. The IDS design is a correlation of previous work done in the field of MANET security. The IDS is implemented using ns-2 simulator and its ability to detect attacks was tested using previously devised attack scripts. Detailed specification for the runtime behavior of the AODV protocol was derived in the process of implementation
Hyper hamiltonian laceability of Cayley graphs generated by transpositions
Authors: Toru Araki
Venue: Networks (2006)

Suppose that G(V0 &cup;V1,E) is a bipartite graph with partite sets of equal size. G is called hyper hamiltonian laceable if (1) it has a hamiltonian path between any pair of vertices in different partite sets, and (2) for any vertex v &isin; Vi, there is a hamiltonian path in G - v between any two vertices in V1 - i. Star and bubble-sort graphs have been considered as interconnection networks for parallel and distributed systems, and these graphs are known to be hyper hamiltonian laceable. Furthermore, it is well known that these graphs belong to the class of Cayley graphs on symmetric groups generated by a set of transpositions. In this article, we generalize those results by showing that any Cayley graph generated by transpositions is hyper hamiltonian laceable. &copy; 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 48(3), 121&ndash;124 2006
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation
Authors: Leonid Sigal, Michael J. Black
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

Part-based tree-structured models have been widely used for 2D articulated human pose-estimation. These approaches admit efficient inference algorithms while capturing the important kinematic constraints of the human body as a graphical model. These methods often fail however when multiple body parts fit the same image region resulting in global pose estimates that poorly explain the overall image evidence. Attempts to solve this problem have focused on the use of strong prior models that are limited to learned activities such as walking. We argue that the problem actually lies with the image observations and not with the prior. In particular, image evidence for each body part is estimated independently of other parts without regard to self-occlusion. To address this we introduce occlusion-sensitive local likelihoods that approximate the global image likelihood using per-pixel hidden binary variables that encode the occlusion relationships between parts. This occlusion reasoning introduces interactions between non-adjacent body parts creating loops in the underlying graphical model. We deal with this using an extension of an approximate belief propagation algorithm (PAMPAS). The algorithm recovers the real-valued 2D pose of the body in the presence of occlusions, does not require strong priors over body pose and does a quantitatively better job of explaining image evidence than previous methods.
On-Chip Testing Techniques for RF Wireless Transceivers
Authors: Alberto Valdes-Garcia, Jose Silva-Martinez, Edgar Sanchez-Sinencio
Venue: IEEE Design Test (2006)

This article describes a set of on-chip testing techniques and their application to integrated wireless RF transceivers. The objective is to reduce final product cost and accelerate time to market by providing means of testing the entire transceiver system as well as its major building blocks without using off-chip analog or RF instrumentation. On-chip test devices fabricated in a standard CMOS process and experimentally evaluated support the proposed test strategy.
A New Approach for Solving the Noncooperative Fuzzy Game
Authors: N. Javadian, Y. Maali
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Systems that involve more than one decision maker are often optimized by using the game theory. In the traditional game theory, it is assumed that each player has a well-defined result of each strategy (payoff) and quantitative utility function over a set of the player decision space. Each player attempts to maximize his/her own expected utility. At present, it cannot be claimed that the first assumption which has been shown to be correct in a wide variety of situations involving complex problems in economics, engineering, social and political sciences .This could be due to the difficulty inherent in defining a crisp payoff in these types of problems. In this paper, fuzzy numbers have been utilized, in order to incorporate the result of strategies, and then credibility measure has been used for these payoffs.
A Peer-to-Peer Based Framework of InterLibrary Cooperation for Digital Libraries
Authors: Wen-Chung Shih, Chao-Tung Yang, Shian-Shyong Tseng, Chun-Jen Chen
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

Traditionally, InterLibrary Cooperation is an important interaction between libraries. Nevertheless, the emerging digital library architecture has not explicitly supported this requirement. In this paper, we proposed an InterLibrary Cooperation Framework for digital libraries using P2P technology. An application of this framework to Faculty Publication Sharing System was presented. Besides, a reputation model based on data mining is utilized to provide libraries with incentives to join this framework.
Personal authentication using hand images
Authors: Ajay Kumar, David C. M. Wong, Helen C. Shen, Anil K. Jain
Venue: Pattern Recognition Letters (2006)

This paper presents a new approach for personal authentication using hand images. The proposed method attempts to improve the performance of palmprint-based verification system by integrating hand geometry features. Unlike prior bimodal biometric systems, the users do not have to undergo the inconvenience of using two different sensors in our system since the palmprint and hand geometry images are acquired simultaneously using a single camera. The palmprint and handshape images are used to extract salient features and are then examined for their individual and combined verification performances. The image acquisition setup used here is inherently simple and it does not employ any special illumination nor does it use any alignment pegs to cause any inconvenience to the users. Our experiments on an image database of 100 users achieve promising results and suggest that the fusion of matching scores can achieve better performance than the fusion at representation.
The Nature of the Cyber Firm-2006: Building An Affordance Architecture
Authors: Ravindra Dastikop
Venue: Proceedings of the 2006 International Conference on Cyberworlds (2006)

[1] Recognized web data stream as a source of new business creation and proposed a contextual business model that creates business value by converting the disparate data stream into meaningful context and serves its contextual customers. In this paper, we develop our model further and exemplify with an application that is currently in progress. Our contribution is two fold: use of affordance [2] as the basis of business value creation, and use of controlled vocabulary as a means of creating affordance for a specific domain of contextual users.
Broadband maximum energy array with user imposed spatial and frequency constraints
Authors: D. Korompis, Kung Yao, F. Lorenzelli
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

We consider an optimum broadband equally spaced linear array of R sensors each having L taps based on maximum energy concentration over some desired spatial "look" and frequency regions subject to user imposed spatial and frequency attenuation constraints. This problem is first expressed as a constrained maximization of a generalized Rayleigh ratio where the matrices in the ratio are specified by the spatial and frequency domains and the constraining subspace is specified by the array values, derivative values, and spatial locations. The optimum array weight vector is then obtained as a solution of a transformed computationally tractable unconstrained full-rank lower-dimensional generalized eigenvalue problem. Numerical examples are given to illustrate the usefulness of this approach.
Hypermedia for Portable Video Players (PVP)
Authors: Mike Leggett, Shigeki Amitani
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

In this paper we propose the exploitation of high mobility portable battery operated Video Players (PVP) for the retrieval of video associated with the location in which it may be used. Reporting on an earlier interactive multimedia location-based prototype, we assess the possibilities for specific ontologies of a taxonomy of indexing procedure which avoids text-based retrieval methods, using instead the mnemonics of image association. We outline the proposed development of PVP firmware and a related user application enabling users to construct indexing procedures appropriate to their needs, using a metadesign approach,.