ppxscal/embedding_network huggingface dataset:
tacTiles for Ambient Intelligence and Interactive Sonification
Authors: Thomas Hermann, Risto Kõiva
Venue: Proceedings of the 3rd international workshop on Haptic and Audio Interaction Design (2008)

In this paper we introduce tacTiles, a novel wireless modular tactile sensitive surface element attached to a deformable textile, designed as a lay-on for surfaces such as chairs, sofas, floor or other furniture. tacTiles can be used as interface for human-computer interaction or ambient information systems. We give a full account on the hardware and show applications that demonstrate real-time sonification for process monitoring and biofeedback. Finally we sketch ideas for using tacTiles paired with sonification for interaction games.
Note: The number of possibilities for random dating
Authors: Aaron Abrams, Rod Canfield, Andrew Granville
Venue: Journal of Combinatorial Theory Series A (2008)

Let G be a regular graph and H a subgraph on the same vertex set. We give surprisingly compact formulas for the number of copies of H one expects to find in a random subgraph of G.
Axiomatic Specifications in Firmware Development Systems
Authors: S. Dasgupta
Venue: IEEE Software (1986)

Some key ideas originating in the domain of software technology have been used in the design of the architecture description language S*M.
Consumer Behaviors in Taiwan Online Shopping -- Case Study of A Company
Authors: Lily Lin, Huey-Ming Lee, Li-Hsueh Lin
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

This paper focuses on the customer behaviors of Taiwan "Internet Commerce/e-shopping". The member consumption records of A company in 2006 were employed and cross-analyzed to find out the distribution of member variables. We applied RFM model to cluster customers and understand the contribution of each group, and used the decision tree technique, CHAID (Chi-squared Automatic Interaction Detection) to explore member variables and product classifications groups.
A Map of Trust between Trading Partners
Authors: John Debenham, Carles Sierra
Venue: Proceedings of the 5th international conference on Trust, Privacy and Security in Digital Business (2008)

A pair of `trust maps' give a fine-grained view of an agent's accumulated, time-discounted belief that the enactment of commitments by another agent will be in-line with what was promised, and that the observed agent will act in a way that respects the confidentiality of previously passed information. The structure of these maps is defined in terms of a categorisation of utterances and the ontology. Various summary measures are then applied to these maps to give a succinct view of trust.
Approximation Algorithms for 2-Stage Stochastic Scheduling Problems
Authors: David B. Shmoys, Mauro Sozio
Venue: Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization (2007)

There has been a series of results deriving approximation algorithms for 2-stage discrete stochastic optimization problems, in which the probabilistic component of the input is given by means of "black box", from which the algorithm "learns" the distribution by drawing (a polynomial number of ) independent samples. The performance guarantees proved for such problems, of course, is generally worse than for their deterministic analogue. We focus on a 2-stage stochastic generalization of the problem of finding the maximum-weight subset of jobs that can be scheduled on one machine where each job is constrained to be processed within a specified time window. Surprisingly, we show that for this generalization, the same performance guarantee that is obtained for the deterministic case can be obtained for its stochastic extension.Our algorithm builds on an approach of Charikar, Chekuri, and Pál: one first designs an approximation algorithm for the so-called polynomial scenario model (in which the probability distribution is restricted to have the property that there are only a polynomial number of possible realizations of the input that occur with positive probability); then one shows that by sampling from the distribution via the "black box" to obtain an approximate distribution that falls in this class and approximately solves this approximation to the problem, one nonetheless obtains a near-optimal solution to the original problem. Of course, to follow this broad outline, one must design an approximation algorithm for the stochastic optimization problem in the polynomial scenario model, and we do this by extending a result of Bar-Noy, Bar-Yehuda, Freund, Naor, and Schieber.Furthermore, the results of Bar-Noy et al. extend to a wide variety of resource-constrained selection problems including, for example, the unrelated parallel-machine generalization R|r j | ¿ w j U j and point-to-point admission control routing in networks (but with a different performance guarantee). Our techniques can also be extended to yield analogous results for the 2-stage stochastic generalizations for this class of problems.
Firing Pattern Estimation of Synaptically Coupled Hindmarsh-Rose Neurons by Adaptive Observer
Authors: Yusuke Totoki, Kouichi Mitsunaga, Haruo Suemitsu, Takami Matsuo
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

In this paper, we present adaptive observers for synaptically coupled Hindmarsh-Rose(HR) neurons with the membrane potential measurement under the assumption that some of parameters in an individual HR neuron are known. Using the adaptive observers for a single HR neuron, we propose a two-stage merging procedure to identify the firing pattern of a model of synaptically coupled HR neurons. The procedure allows us to recover the internal states and to distinguish the firing patterns of the synaptically coupled HR neurons, with early-time dynamic behaviors.
Functional Availability Analysis of Discrete Transport System Realized by SSF Simulator
Authors: Tomasz Walkowiak, Jacek Mazurkiewicz
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

The paper describes a novel approach to functional availability analysis of discrete transport systems realized using Scalable Simulation Framework (SSF). The proposed method is based on modeling and simulating of the system behavior by Monte Carlo simulation. No restriction on the system structure and on a kind of distribution is the main advantage of the method. The paper presents some exemplar system modeling. The authors stress the problem of influence of the functional parameters on final system availability. The problem described in the paper is practically essential for defining an organization of vehicle maintenance and transport system logistics.
On the Move Towards the European Digital Library: BRICKS, TEL, MICHAEL and DELOS Converging Experiences
Authors: Massimo Bertoncini
Venue: Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries (2007)

In the last few years, a deep paradigm shift has taken place in the Digital Library domain. From several independent online systems and closed library "silos" that store digital heritage content, digital library systems are evolving towards a networked service-based architecture built as a set of fully interoperable local digital library systems. 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
Analysis of Energy Consumption in Direct Transmission and Multi-hop Transmission for Wireless Sensor Networks
Authors: Jin Wang, Yu Niu, Jinsung Cho, Sungyoung Lee
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

In this paper, we primary focus on prolonging the network lifetime of Wireless Sensor Networks (WSN), since the small, portable batteries integrated into the sensor chips can not be re-charged easily from an economical point of view. We first made a further analysis about the relationship between energy consumption and hop number. Then, an optimal hop number is deduced for minimizing the energy consumption during the multi-hop transmission. The importance of hop number to the energy consumption is usually neglected by many routing protocols. In fact, a considerable amount of energy can be saved if the relationship between hop number and energy consumption is carefully studied. After further analysis about the energy consumption of different transmission manner as well as design parameters, we presented our judging criterion of transmission manner. Also, an energy efficient routing scenario is presented with diagram so as to illustrate how the network lifetime can be prolonged.
WSMO Studio --- A Semantic Web Services Modelling Environment for WSMO
Authors: Marin Dimitrov, Alex Simov, Vassil Momtchev, Mihail Konstantinov
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

The Web Service Modelling Ontology (WSMO) provides a unique, highly innovative perspective onto the Semantic Web Services domain. Robust and easy-to-use tools play crucial role for the adoption of any technological innovation and indeed the overall value of the innovation can be severely undermined by the lack of proper tools supporting it. In this paper we present a prototype of an integrated modelling environment that supports and elaborates the innovative WSMO perspective.
Closing the Complexity Gap between FCFS Mutual Exclusion and Mutual Exclusion
Authors: Robert Danek, Wojciech Golab
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

First-Come-First-Served (FCFS) mutual exclusion (ME) is the problem of ensuring that processes attempting to concurrently access a shared resource do so one by one, in a fair order. In this paper, we close the complexity gap between FCFS ME and ME in the asynchronous shared memory model where processes communicate using atomic reads and writes only, and do not fail. Our main result is the first known FCFS ME algorithm that makes O(logN) remote memory references (RMRs) per passage and uses only atomic reads and writes. Our algorithm is also adaptive to point contention. More precisely, the number of RMRs a process makes per passage in our algorithm is ¿( min (k,logN)), where k is the point contention. Our algorithm matches known RMR complexity lower bounds for the class of ME algorithms that use reads and writes only, and beats the RMR complexity of prior algorithms in this class that have the FCFS property.
From Model Driven Engineering to Verification Driven Engineering
Authors: Fabrice Kordon, Jérôme Hugues, Xavier Renault
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

The definition and construction of complex computer-based systems require not just software engineering knowledge, but also many other domain-specific techniques to ensure many system's functional and non-functional properties. Hence, there is a trend to move away from programming languages to models on which one can reason: model-driven engineering. Yet, this remains a complex task: one need to master many techniques. In this paper, we claim that MDE is incomplete: it is "just" an implementation framework to support advanced model-based techniques, verification of systems non-functional properties, code generation, etc. There is a conceptual gap to fill to know "what" to do with models. We propose to switch from MDE to VDE: Verification-Driven Engineering, so that the user knows how to model a system to analyze it. We sum up existing techniques and their relevant application domains.
Hiding Data in Halftone Images
Authors: Hsien-Wen Tseng, Chin-Chen Chang
Venue: Informatica (2005)

Most recent papers about visual cryptography for halftone images are dedicated to get a higher contrast decoded image. However, the hidden visual pattern often blends into the background image and leads to a confused image. In this paper, we propose an improved method for halftone image hiding. By using the proposed method, the background image can be eliminated and the hidden visual pattern can be revealed precisely. Experimental results show that the decoded visual patterns could reveal good visual quality under various kinds of input patterns. Furthermore, better visual quality can be obtained when more halftone images are overlaid.
Fuzzy Ensemble Clustering for DNA Microarray Data Analysis
Authors: Roberto Avogadri, Giorgio Valentini
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact that classes of examples or classes of functionally related genes are sometimes not clearly defined. To face these items, we propose a fuzzy ensemble clustering approach to both improve the accuracy of clustering results and to take into account the inherent fuzziness of biological and bio-medical gene expression data. Preliminary results with DNA microarray data of lymphoma and adenocarcinoma patients show the effectiveness of the proposed approach.
Sigma point policy iteration
Authors: Michael Bowling, Alborz Geramifard, David Wingate
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear value function approximation. These algorithms rely on policy-dependent expectations of the transition and reward functions, which require all experience to be remembered and iterated over for each new policy evaluated. We propose to summarize experience with a compact policy-independent Gaussian model. We show how this policy-independent model can be transformed into a policy-dependent form and used to perform policy evaluation. Because closed-form transformations are rarely available, we introduce an efficient sigma point approximation. We show that the resulting Sigma-Point Policy Iteration algorithm (SPPI) is mathematically equivalent to LSPI for tabular representations and empirically demonstrate comparable performance for approximate representations. However, the experience does not need to be saved or replayed, meaning that for even moderate amounts of experience, SPPI is an order of magnitude faster than LSPI.
New Multiparty Signature Schemes for Network Routing Applications
Authors: Alexandra Boldyreva, Craig Gentry, Adam O'Neill, Dae Hyun Yum
Venue: ACM Transactions on Information and System Security (TISSEC) (2008)

We construct two new multiparty digital signature schemes that allow multiple signers to sequentially and non-interactively produce a compact, fixed-length signature. First, we introduce a new primitive that we call ordered multisignature (OMS) scheme, which allows signers to attest to a common message as well as the order in which they signed. Our OMS construction substantially improves computational efficiency and scalability over any existing scheme with suitable functionality. Second, we design a new identity-based sequential aggregate signature scheme, where signers can attest to different messages and signature verification does not require knowledge of traditional public keys. The latter property permits savings on bandwidth and storage as compared to public-key solutions. In contrast to the only prior scheme to provide this functionality, ours offers improved security that does not rely on synchronized clocks or a trusted first signer. We provide formal security definitions and support the proposed schemes with security proofs under appropriate computational assumptions. We focus on applications of our schemes to secure network routing, but we believe that they will find other applications as well.
Autonomic Provisioning Model for Digital Home Services
Authors: José A. Lozano, Alfonso Castro, Juan M. González, Jorge E. López De Vergara, Víctor A. Villagrá, Vicente Olmedo
Venue: Proceedings of the 3rd IEEE international workshop on Modelling Autonomic Communications Environments (2008)

Digital Home services provisioning is becoming one of the main challenges for telecommunications operators as the heterogeneity and complexity of end users devices grows dramatically. Moreover, home network topology and composition can be changed by end users without any control from the service provider side.Traditional centralized management paradigms are not valid for this kind of dynamic and unpredictable environments as they have been thought for more static scenarios. Autonomic Communication (AC) can help in solving this problems building a knowledge based management solution for this scenario. Autonomic Agents are able to locally deal with most of the configuration tasks as they use inference to decide the most suitable device configuration. This paper shows an autonomic provisioning model for the dynamic configuration of end user devices. The model is validated by a proof of concept.
Detecting sensitive data exfiltration by an insider attack
Authors: Yali Liu, Cherita Corbett, Ken Chiang, Rennie Archibald, Biswanath Mukherjee, Dipak Ghosal
Venue: Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead (2008)

Detecting and mitigating insider threat is a critical element in the overall information protection strategy. By successfully implementing tactics to detect this threat, organizations avoid the loss of sensitive information and also potentially protect against future attacks. Within the broader scope of mitigating insider threat, we focus on detecting exfiltration of sensitive data through the high speed network. We propose a multilevel approach that consists of three main components: 1) network level application identification, 2) content signature generation and detection, and 3) covert communication detection. The key scientific approach used for all the above components is applying statistical and signal processing techniques on network traffic to generate signatures and/or extract features for classification purposes. We provide a summary of the approaches used in network level application identification and content signature generation and detection and briefly describe our approach in detecting covert communications. This paper touches on these issues and outlines overall directions for our research.
Efficient, automated Monte Carlo methods for radiation transport
Authors: Rong Kong, Martin Ambrose, Jerome Spanier
Venue: Journal of Computational Physics (2008)

Monte Carlo simulations provide an indispensible model for solving radiative transport problems, but their slow convergence inhibits their use as an everyday computational tool. In this paper, we present two new ideas for accelerating the convergence of Monte Carlo algorithms based upon an efficient algorithm that couples simulations of forward and adjoint transport equations. Forward random walks are first processed in stages, each using a fixed sample size, and information from stage k is used to alter the sampling and weighting procedure in stage k+1. This produces rapid geometric convergence and accounts for dramatic gains in the efficiency of the forward computation. In case still greater accuracy is required in the forward solution, information from an adjoint simulation can be added to extend the geometric learning of the forward solution. The resulting new approach should find widespread use when fast, accurate simulations of the transport equation are needed.
Optimized Algorithms for Traffic Information Collecting in an Embedded System
Authors: Zhiwei He, Yuanyuan Liu, Haibin Yu, Xueyi Ye
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In an embedded system, the hardware resources are limited. In order to obtain such traffic information as traffic volume and vehicle speed in an embedded system, a series of efficient video processing algorithms and optimization techniques are proposed. The key algorithm to detect vehicles is the background subtraction method, in which the approximated median filter is applied to obtain the simulated background. Parallelogrammatic "virtual loop" is used to restrict the calculation in an interested region in the traffic scene. Tracking of a vehicle is done by the detection and tracking of the front of it. Results show that the system can detect and track vehicles effectively and efficiently with these optimized algorithms.
Combining Semantic Web technologies with Multi-Agent Systems for integrated access to biological resources
Authors: Francisco García-Sánchez, Jesualdo Tomás Fernández-Breis, Rafael Valencia-García, Juan Miguel Gómez, Rodrigo Martínez-Béjar
Venue: Journal of Biomedical Informatics (2008)

The increasing volume and diversity of information in biomedical research is demanding new approaches for data integration in this domain. Semantic Web technologies and applications can leverage the potential of biomedical information integration and discovery, facing the problem of semantic heterogeneity of biomedical information sources. In such an environment, agent technology can assist users in discovering and invoking the services available on the Internet. In this paper we present SEMMAS, an ontology-based, domain-independent framework for seamlessly integrating Intelligent Agents and Semantic Web Services. Our approach is backed with a proof-of-concept implementation where the breakthrough and efficiency of integrating disparate biomedical information sources have been tested.
Stream Scheduling: A Framework to Manage Bulk Operations in Memory Hierarchies
Authors: Abhishek Das, William J. Dally
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

With the emergence of streaming and multi-core architectures, there is an increasing demand to map parallel algorithms efficiently across all architectures. This paper describes a platform-independent optimization framework called Stream Scheduling, that orchestrates parallel execution of bulk computations and data transfers, and allocates storage at multiple levels of a memory hierarchy. By adjusting block sizes, and applying software pipelining on bulk operations, it ensures computation-to-communication ratio is maximized on each level. We evaluate our framework on a diverse set of Sequoia applications, targeting systems with different memory hierarchies: a Cell blade, a distributed-memory cluster, and the Cell blade attached to a disk.