ppxscal/embedding_network huggingface dataset:
Peer-to-Peer Private Information Retrieval
Authors: Josep Domingo-Ferrer, Maria Bras-Amorós
Venue: Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases (2008)

Private information retrieval (PIR) is normally modeled as a game between two players: a user and a database. The user wants to retrieve some item from the database without the latter learning which item. Most current PIR protocols are ill-suited to provide PIR from a search engine or large database: i) their computational complexity is linear in the size of the database; ii) they assume active cooperation by the database server in the PIR protocol. If the database cannot be assumed to cooperate, a peer-to-peer user community is a natural alternative to achieve some query anonymity: a user submits a query on behalf of another user in the community. A peer-to-peer PIR system is described in this paper which relies on an underlying combinatorial structure to reduce the required key material and increase availability.
Performance and Dependability Evaluation: Successes, Failures and Challenges
Authors: Boudewijn R. Haverkort
Venue: Proceedings of the 5th European Performance Engineering Workshop on Computer Performance Engineering (2008)

Over the last 40 years, the field of model-based performance and dependability evaluation has seen important developments, successes and scientific breakthroughs. However, the field has not matured into a key engineering discipline which is heavily called upon by computer system and software engineers, even though it is well-known that already the use of simple analytical models can result in better insight in system performance. In the area of communication system design, performance evaluation has become more of a mainstream activity, albeit almost exclusively using discrete-event simulation techniques.What circumstances made that almost all of our excellent work on analytical performance and dependability evaluation did not find the acceptance and use we think it deserves?On the basis of an historical account of the major developments in the area over the last 40 years, I will address probable reasons for the relatively moderate success and acceptance of model-based performance and dependability evaluation. What did we do right, what did we do wrong? Which circumstances led to successes, and where did we fail?Based on the gathered insights, I will discuss upcoming challenges for the field and recommend research directions for the decade to come.
Content-Based Shape Search of 3D CAD Models with Relevance Feedback
Authors: Jiale Wang, Hongming Cai, Yuanjun He, Yi Zhang
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Engineers and designers often need to search out similar CAD models to make reference to and reuse the previous designs. For most of CAD models, both geometrical information and topological information are important for similarity assessment. We proposed two shape signatures to describe the geometry and the topology of a CAD model respectively. A relevance feedback mechanism is introduced to combine the two dissimilarity distances measured by the two signatures. Experiments are conducted to evaluate the performance of the proposed method.
LSP Trajectory Analysis for Speech Recognition
Authors: J. Onshaunjit, J. Srinonchat
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

Speech signal is the continuous signal which has the characteristics in its own. For recognizing the speech signal, the system must be able to classify and recognize the speech feature. Almost of this system is speaker-independent speech system. This paper presents statistical methods for speech recognition by extracting the features of the speech and analyzing their trajectory. The speech feature has been extracted to Line Spectral Pairs (LSP) coefficients and then uses the statistic model to pattern the trajectory for recognizing the signal. The result shows that the using technique usually works well which the maximum accuracy of recognition is 99.67% at number 1 of male speech and the minimum accuracy of recognition is 82.33% at number 5 of female speech.
Behavioral Cloning for Simulator Validation
Authors: Robert G. Abbott
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

Behavioral cloning is an established technique for creating agent behaviors by replicating patterns of behavior observed in humans or other agents. For pragmatic reasons, behavioral cloning has usually been implemented and tested in simulation environments using a single nonexpert subject. In this paper, we capture behaviors for a team of subject matter experts engaged in real competition (a soccer tournament) rather than participating in a study. From this data set, we create software agents that clone the observed human tactics. We place the agents in a simulation to determine whether increased behavioral realism results in higher performance within the simulation and argue that the transferability of real-world tactics is an important metric for simulator validation. Other applications for validated agents include automated agent behavior, factor analysis for team performance, and evaluation of real team tactics in hypothetical scenarios such as fantasy tournaments.
Data Reduction by Applying an Image-Based Modeling and Rendering Technique to CG Models
Authors: H. Miyachi, N. Sakamoto
Venue: Journal of Visualization (2005)

We applied an image-based modeling and rendering technique to reduce the data size of a CG model to be obtained as a visualization result. To date, this technique has been applied to the reconstruction of 3D graphical models from real objects; the size of the models can be reduced effectively because both color information and geometric information can be reduced. We applied a silhouette-and-voxel method that does not require design data for geometric simplification. Using our system, we simplified two models, one of which, involving medical data, was reduced by about 85% in file size. An accompanying subjective quality test showed that our approach maintains approximately the same visual quality as the geometric simplification method traditionally used.
Creating Boundary Curves of Point-Set Models in Interactive Environment
Authors: Pei Xiao, Ming-Yong Pang
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

Extracting boundary curve from point-sampled model is one of key operations in interactive point-cloud modelling. In this paper, an interactive algorithm of creating boundary curves automatically for point-sampled models is proposed based on our analysis about process of selecting boundary points from point-sets in interactive environment. According to a candidate boundary-point set, in which points are selected by user gradually and interactively, our algorithm first calculate the distance from each new candidate point in the set to current boundary, and then add the point to suitable position in the boundary strategically, while the algorithm keeps the integrity of boundary structure and proximately optimizes the length of the boundary curve. The experiment results show that, our method can extract characteristic areas of point-set models or perform model segmentation with general interactive interface efficiently. The algorithm can be used in interactive parameterization and model editing of point-sampled models, etc.
Personalized Learning Path Delivery: Models and Example of Application
Authors: Hend Madhour, Maia Wentland Forte
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

In this article we present the Lausanne Model: a learning object based reference model that: (i) considers learning issues such as granularity level, description formalism,(ii) organizes learning objects in a network where links are explicated, (iii) enhances user mobility from one environment to another and (iv) considers both individual and social adaptation.
Dynamic Bayesian Networks for Real-Time Classification of Seismic Signals
Authors: Carsten Riggelsen, Matthias Ohrnberger, Frank Scherbaum
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

We present a novel method for automatic classification of seismological data streams, focusing on the detection of earthquake signals. We consider the approach as being a first step towards a generic method that provides for classifying a broad range of seismic patterns by modeling the interrelationships between essential features of seismograms in a graphical model. Through a continuous Wavelet transform the features are extracted, yielding a time-frequency-amplitude decomposition. The extracted features obey certain Markov properties, which allows us to form a joint distribution in terms of a Dynamic Bayesian Network. We performed experiments using real seismic data recorded at different stations in the European Broadband Network, for which we achieve an average classification accuracy of 95%.
Advances in Wireless Ad Hoc and Sensor Networks, 1 edition
Authors: Maggie Xiaoyan Cheng, Deying Li
Venue:  (2008)

Wireless ad hoc networks, mobile or static, have special resource requirements and topology features, which make them different from classic computer networks in resource management, routing, media access control, and QoS provisioning. Some of our day-to-day situations directly relate to ad hoc wireless network applications, such as self-organization, mobility management, and energy efficient design. Within thirteen self-contained chapters, this volume provides a complete survey of the state-of-the-art research that encompasses all areas of ad hoc and sensor networks. Written by distinguished researchers in the field, these chapters focus on the theoretical and experimental study of advanced research topics involving security and trust, broadcasting and multicasting, power control and energy efficiency, and QoS provisioning. This book is a great reference tool for graduate students, researchers, and mathematicians interested in studying mobile ad hoc and sensor networks.
Multi-scale Representation and Persistency for Shape Description
Authors: Davide Moroni, Mario Salvetti, Ovidio Salvetti
Venue: Proceedings of the 3rd international conference on Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry (2008)

Extraction, organization and exploitation of topological features are emerging topics in computer vision and graphics. However, such kind of features often exhibits weak robustness with respect to small perturbations and it is often unclear how to distinguish truly topological features from topological noise. In this paper, we present an introduction to persistence theory, which aims at analyzing multi-scale representations from a topological point of view. Besides, we extend the ideas of persistency to a more general setting by defining a set of discrete invariants.
Graph Cuts Segmentation with Statistical Shape Priors for Medical Images
Authors: Jie Zhu-Jacquot, Ramin Zabih
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Segmentation of medical images is an important step in many clinical and diagnostic imaging applications. Medical images present many challenges for automated segmentation including poor contrast at tissue boundaries. Traditional segmentation methods based solely on information from the image do not work well in such cases. Statistical shape information for objects in medical images are easy to obtain. In this paper, we propose a graph cuts-based segmentation method for medical images that incorporates statistical shape priors to increase robustness. Our proposed method is able to deal with complex shapes and shape variations while taking advantage of the globally efficient optimization by graph cuts. We demonstrate the effectiveness of our method on kidney images without strong boundaries.
Analysis of mathematical models of current-voltage characteristics for plate-type electrostatic precipitators
Authors: Gabriel Nicolae Popa, Ioan Sora, Victor Vaida, Sorin Deaconu, Iosif Popa
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

For a plate-type electrostatic precipitators must know the current-voltage characteristics to obtain the optimal control of the amplitude, the voltage shape, the input power and the collection efficiency. The paper presents the maximum ionization distance, analytic and graphic, near discharge wires depending on the voltage supply frequency and the discharge wires radius. With comparative analyze of the measured and computed, with different mathematical model of current-voltage characteristics, it can be found which models better estimate the current-voltage characteristics for plate-type electrostatic precipitators.
A New Fuzzy Supervised Classification Method Based on Aggregation Operator
Authors: Saroj K. Meher
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

A new fuzzy supervised classification method based on aggregation operator is proposed in the present article. The proposed classifier aggregates the information extracted by exploring feature-wise degree of belonging to classes. I uses a π-type membership function and MEAN (average) aggregation reasoning rule (operator). The effectiveness of the proposed classifier is verified with four benchmark data sets including a realtime financial domain data. Various performance measures are used for quantitative evaluation of the classifier. Experimental results on these data sets illustrate significant improvement in the classification performance of the proposed method compared to three other fuzzy classifiers, namely, explicit fuzzy, fuzzy k-nearest neighbor and fuzzy maximum likelihood.
Test Plan Generation for Concurrent Real-Time Systems Based on Zone Coverage Analysis
Authors: Farn Wang, Geng-Dian Huang
Venue: Proceedings of the 20th IFIP TC 6/WG 6.1 international conference on Testing of Software and Communicating Systems: 8th International Workshop (2008)

The state space explosion due to concurrency and timing constraints of concurrent real-time systems (CRTS) presents significant challenges to the verification engineers. In this paper, we investigate how to use coverage techniques to generate efficient test plans for such systems. We first discuss how to use communicating timed automata to model CRTS. We present a new coverage technique, AZC (active zone coverage), based on the zone equivalence relation between states of CRTS. We discuss techniques to estimate AZC values of active zones represented in BDD-like diagrams. We explain how to construct zone trees and map their root-to-leaf paths to test cases. We then present an algorithm to generate test plans by prioritizing the test cases. The test plans that we generate can efficiently achieve full coverage in AZC. We have implemented our ideas with our TCTL model-checker RED. Experiment report with the Bluetooth L2CAP showed improvement of the coverage growth rate in the test plan execution.
Performance modeling and resource allocation for adaptive agent-based systems
Authors: Shanmuga-Nathan Gnanasambandam
Venue:  (2007)

Applications are increasingly becoming networks of individual application components spread over an infrastructure of physical resources (servers and computing entities). Such distributed agent-based applications are not only prevalent in military domains but also in commercial domains such as data centers. To assure the survivability of a distributed application, repeatedly estimating what sort of multi-dimensional guarantees (such as response time or availability) can be made as a function of the offered load and environmental conditions is paramount. This thesis studies how such guarantees can be computed and negotiated in a distributed MAS that is situated on an unreliable infrastructure. Firstly, this work concentrates on identifying relevant service-level attributes that can be estimated for the failure-prone infrastructure. Queueing models with single and multi-class traffic are studied in scenarios with breakdown, repair and catastrophic failure, and are utilized for the estimation of performance and reliability attributes in steady state. These analytical results serve as internal models for the agents which aid them in evaluating the quality of service that can be attained given the environmental conditions (stresses and information load). Secondly, two resource allocation mechanisms are studied that are used to assign the agents to the nodes forming the infrastructure which are constrained by capacity, and are non-homogeneous in terms of their capability and the stresses experienced. Since the assignment problem is in general NP-hard, a few allocation heuristics with varying roles on the part of the agents and the infrastructure are proposed. Finally, in order to use resources efficiently, a usage price is computed based on the applications demand for the service-level attributes (which are the information goods sold by the infrastructure). The main contributions of this work are the analytical solutions for the queueing models which include multi-class traffic, service disruption (both temporary and catastrophic failure) and non-preemptive priority scheduling. The analytical models pave the way for rapid negotiation between the MAS and the infrastructure as opposed to relatively slower simulation models. The analytical solutions are applicable to other domains including web-servers and hosting. The other contribution is the study of decentralized mechanisms that aid in the negotiation of quantitative service-level agreements in multi-agent systems and, in general, service-oriented architectures. While negotiation protocols and methods are widely studied, automatic negotiation using internal models are novel to this work, especially to distributed MAS. 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
MLP-Based Detection of Targets in Clutter: Robustness with Respect to the Shape Parameter of Weibull-Disitributed Clutter
Authors: Raul Vicen-Bueno, Eduardo Galán-Fernández, Manuel Rosa-Zurera, Maria P. Jarabo-Amores
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Obtaining analytical expressions for coherent detection of known signals in Weibul-distributed clutter and white Gaussian noise has been a hard task since the last decades. In fact, nowadays, these expressions have not been found yet. This problem lead us to use suboptimum solutions to solve this problem. Optimum approximations can be done by using Multilayer Perceptrons (MLPs) trained in a supervised way to minimize the mean square error. So, MLP-based detectors are constructed and compared with one of the suboptimum detectors commonly used to solve the detection problem under study. First, a study of the dimensionality of the MLP is done for typical values of the target and clutter conditions. And finally, a deep study is done according to the variations of the most important parameters of the target and clutter signals. The last study let us to be conscious about the importance of the selection of the parameters to design both detectors. Moreover, the difference of performances between each other and the superiority of the MLP-based detector against the suboptimum solution is emphasized.
A class of fuzzy rough expected value multi-objective decision making model and its application to inventory problems
Authors: Jiuping Xu, Lihui Zhao
Venue: Computers Mathematics with Applications (2008)

In this paper, we concentrate on developing a fuzzy rough multi-objective decision-making model, according to fuzzy rough theory. Then we prove the existence of a solution of the fuzzy rough multi-objective decision-making model formulated. Next, we develop an effective algorithm to solve the fuzzy rough expected value multi-objective decision-making model concerning the inventory problem, and prove the convergence of the proposed algorithm. Finally these are applied to practical inventory problem in which all inventory costs, purchasing and selling prices in the objectives and constraints are assumed to be fuzzy rough in nature. Comparing the results with those from the fuzzy multi-objective decision-making model, we reach that the proposed fuzzy rough multi-objective decision-making model and algorithm, which will be of much use to management, and provide significant solutions to construct other inventory models with fuzzy rough variables in real life.
Adaptation of Connectionist Weighted Fuzzy Logic Programs with Kripke-Kleene Semantics
Authors: Alexandros Chortaras, Giorgos Stamou, Andreas Stafylopatis, Stefanos Kollias
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

Weighted fuzzy logic programs extend the expressiveness of fuzzy logic programs by allowing the association of a different significance weight with each atom that appears in the body of a fuzzy rule. The semantics and a connectionist representation of these programs have already been studied in the absence of negation; in this paper we first propose a Kripke-Kleene based semantics for the programs which allows for the use of negation as failure. Taking advantage of the increased modelling capabilities of the extended programs, we then describe their connectionist representation and study the problem of adapting the rule weights in order to fit a provided dataset. The adaptation algorithm we develop is based on the subgradient descent method and hence is appropriate to be employed as a learning algorithm for the training of the connectionist representation of the programs.
Social Rhythms and Nocturnal Routines in Community Dwelling Older Adults
Authors: Julie Behan, David Prendergast, Lorcan Walsh, Brenda Quigley
Venue: Proceedings of the 6th international conference on Smart Homes and Health Telematics (2008)

This paper describes a pilot carried out by The Digital Health Group in Intel, in which daily social rhythms of community dwelling older adults were examined and related to objectively and subjectively recorded sleep measurements. Ten relatively healthy independently living older adults were interviewed using ethnographic processes to determine a baseline of social activities, behaviours and nocturnal sleeping routines. Each home was fitted with six sensing elements to establish and monitor daily and nocturnal activities. Sociality behaviours were explored through social contact through phone conversation and human interaction, through mobility, inside and outside the home, and through a person's self reported internal state (how they feel each day). Nocturnal rhythms were examined through actigraph watches and bed pressure sensing devices. A preliminary sub set of the results are presented in this paper in the form of case studies showing subjective and objective data sets and their comparison to social routines.