ppxscal/embedding_network huggingface dataset:
Maintaining the Maximum Normalized Mean and Applications in Data Stream Mining
Authors: Jan Peter Patist
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

In data stream mining many algorithms are based on fixed size sliding windows to cope with the aging of data. This despite of some flaws of fixed size windows. Namely, it is difficult to set the size of the window and there does not exist an optimal window size due to different types of changes in the underlying distribution of the data stream. Because of these reasons the algorithm performance degrades. We propose some initial steps toward efficiently equipping sliding window algorithms with flexible windowing. This is done by the efficient maintenance of a statistic called, the maximum normalized mean. This statistic is maximized over all time windows and thus uses flexible windowing. We show that several algorithms can be restated such that it uses the maximum normalized mean as a building block. The usefulness of the normalized mean in the context of these algorithms is shown by means of experiments.
Can We Increase the Usability of Real Time Scheduling Theory? The Cheddar Project
Authors: Frank Singhoff, Alain Plantec, Pierre Dissaux
Venue: Proceedings of the 13th Ada-Europe international conference on Reliable Software Technologies (2008)

The Cheddar project deals with real time scheduling theory. Many industrial projects do not perform performance analysis with real time scheduling theory even if the demand for the use of this theory is large. The Cheddar project investigates why real time scheduling theory is not used and how its usability can be increased. The Cheddar project was launched at the University of Brest in 2002. This article presents a summary of its contributions and ongoing works.
A User-Item Predictive Model for Collaborative Filtering Recommendation
Authors: Heung-Nam Kim, Ae-Ttie Ji, Cheol Yeon, Geun-Sik Jo
Venue: Proceedings of the 11th international conference on User Modeling (2007)

Collaborative Filtering recommender systems, one of the most representative systems for personalized recommendations in E-commerce, enable users to find the useful information easily. But traditional CF suffers from some weaknesses: scalability and real-time performance. To address these issues, we present a novel model-based CF approach to provide efficient recommendations. In addition, we propose a new method of building a model with dynamic updates, when users present explicit feedback. The experimental evaluation on MovieLens datasets shows that our method offers reasonable prediction quality as good as the best of user-based Pearson correlation coefficient algorithm.
Comparing Assessment Methodologies for Free/Open Source Software: OpenBRR and QSOS
Authors: Jean-Christophe Deprez, Simon Alexandre
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

Many organizations using Free/Open Source Software (FlOSS) are dealing with the major problem of selecting the most appropriate software product corresponding to their needs. Most of theses companies are currently selecting FlOSS projects using ad-hoc techniques. However, in the last couple of years, two methodologies for assessing FlOSS project have emerge, namely QSOS and OpenBRR. The objective of this work is, through a detailed and rigorous assessment methodology comparison, to allow companies to have a better understanding of these two assessment methodologies content and limitation. This work compares both methodologies on several aspects, among others, their overall approaches, their scoring procedures and their evaluation criteria.
Formal Analysis of Trust Dynamics in Human and Software Agent Experiments
Authors: Tibor Bosse, Catholijn M. Jonker, Jan Treur, Dmytro Tykhonov
Venue: Proceedings of the 11th international workshop on Cooperative Information Agents XI (2007)

Recognizing that trust states are mental states, this paper presents a formal analysis of the dynamics of trust in terms of the functional roles and representation relations for trust states. This formal analysis is done both in a logical framework and in a mathematical framework based on integral and differential equations. Furthermore, the paper presents formal specifications of a number of relevant dynamic properties of trust. The specifications provided were used to perform automated formal analysis of empirical and simulated data from two case studies, one involving two experiments with humans, and one involving simulation experiments in the context of an economic game.
Determining the regularization parameters for super-resolution problems
Authors: Marcelo V. W. Zibetti, Fermín S. V. Bazán, Joceli Mayer
Venue: Signal Processing (2008)

We derive a novel method to determine the parameters for regularized super-resolution problems, addressing both the traditional regularized super-resolution problem with single- and multiple-parameters and the simultaneous super-resolution problem with two parameters. The proposal relies on the joint maximum a posteriori (JMAP) estimation technique. The classical JMAP technique provides solutions at low computational cost, but it may be unstable and presents multiple local minima. We propose to stabilize the JMAP estimation, while achieving a cost function with a unique global solution, by assuming a gamma prior distribution for the hyperparameters. The resulting fidelity is similar to the quality provided by classical methods such as GCV, L-curve and Evidence, which are computationally expensive. Experimental results illustrate the low complexity and stability of the proposed method.
Reputation markets
Authors: Xiang Yan, Benjamin Van Roy
Venue: Proceedings of the 3rd international workshop on Economics of networked systems (2008)

A reputation system should incentivize users to obtain and reveal estimates of content quality. It should also aggregate these estimates to establish content reputation in a way that counters strategic manipulation. Mechanisms have been proposed in recent literature that offer financial incentives to induce these desirable outcomes. In this paper, to systematically study what we believe to be fundamental characteristics of these mechanisms, we view them as information markets designed to assess content quality, and refer to them as reputation markets. Specifically, we develop a rational expectations equilibrium model to study how incentives created by reputation markets should influence community behavior and the accuracy of assessments. Our analysis suggests that reputation markets offer a number of desirable features: - As the quality of information improves or the cost of information acquisition decreases, reputation assessments become increasingly robust to manipulation. - If users can pay to acquire information, errors in reputation assessments do not depend on uncertainty in the manipulator's intent. - Reputation distortion incurs cost to the manipulator, resulting in cash transfers to other users. - Pseudonyms do not help a manipulator distort reputations.
Towards Consistent Specifications of Product Families
Authors: Alexander Harhurin, Judith Hartmann
Venue: Proceedings of the 15th international symposium on Formal Methods (2008)

Addressing the challenges faced today during the development of multi-functional system families, we suggest a service-oriented approach to formally specifying the functionality and, in particular, the functional variability already in the requirement engineering phase. In this paper, we precisely define the underlying concepts, such as the notion of individual services, the combination of services, inter-service dependencies, and variability. Thereby, we especially focus on establishing the consistency of the overall specification. To that end, we formally define conflicts between requirements and describe how they can be detected and resolved based on the introduced formal concepts.
A Hierarchic Method for Footprint Segmentation Based on SOM
Authors: Marco Mora Cofre, Ruben Valenzuela, Girma Berhe
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

In this study we propose a new approach for solving the problem of segmenting the footprint in color images. Previous studies have presented direct and supervised methods for segmenting the footprint pattern. This new approach proposes, in comparison to the previous methods, a hierarchic segmentation method, the use of different color models to represent the image pixels, and the non-supervised classification based on SOM. The characteristics of the method allow a robust footprint segmentation with a high level of autonomy.
Anonymity-proof Shapley value: extending shapley value for coalitional games in open environments
Authors: Naoki Ohta, Vincent Conitzer, Yasufumi Satoh, Atsushi Iwasaki, Makoto Yokoo
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

Coalition formation is an important capability for automated negotiation among self-interested agents. In order for coalitions to be stable, a key question that must be answered is how the gains from cooperation are to be distributed. Coalitional game theory provides a number of solution concepts for this. However, recent research has revealed that these traditional solution concepts are vulnerable to various manipulations in open anonymous environments such as the Internet. To address this, previous work has developed a solution concept called the anonymity-proof core, which is robust against such manipulations. That work also developed a method for compactly representing the anonymity-proof core. However, the required computational and representational costs are still huge. In this paper, we develop a new solution concept which we call the anonymity-proof Shapley value. We show that the anonymity-proof Shapley value is characterized by certain simple axiomatic conditions, always exists, and is uniquely determined. The computational and representational costs of the anonymity-proof Shapley value are drastically smaller than those of existing anonymity-proof solution concepts.
Studying Timing Analysis on the Internet with SubRosa
Authors: Hatim Daginawala, Matthew Wright
Venue: Proceedings of the 8th international symposium on Privacy Enhancing Technologies (2008)

Timing analysis poses a significant threat to anonymity systems that wish to support low-latency applications like Web browsing, instant messaging, and Voice over IP (VoIP). Research into timing analysis so far has been done through simulations or unrealistic local area networks. We developed SubRosa, an experimental platform for studying timing analysis attacks and defenses in low-latency anonymity systems. We present results of experiments on PlanetLab, a globally distributed network testbed. Our experiments validate the major conclusions, but not the detailed results, obtained by prior simulation studies. We also propose a new lightweight defense based on the principles of mix design called ¿-buffering and show the limitations of this approach. Finally, motivated by our experimental results, we introduce spike analysis, a new timing analysis technique that takes advantage of unusual delays in a stream to substantially reduce errors over prior techniques.
Source Localization of Subtopographies Decomposed by Radial Basis Functions
Authors: Adil Deniz Duru, Ahmet Ademoglu
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

Functional neuroimaging methods give the opportunity of investigating human brain functioning. Mostly used functional neuroimaging techniques include Electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and optical imaging. Among these techniques EEG has the best time resolution, while fMRI has the best spatial resolution. High temporal resolution of EEG is an attractive property for neuroimaging studies. EEG inverse problem is needed to be solved in order to identify the locations and the strength of the electrical sources forming EEG/ERP topographies. Low spatial resolution of the scalp topography causes this localization problem more complicated. In this paper, a spatial preprocessing method, which separates a topography into two or more subtopographies is proposed. The decomposition procedure is based on defining a spatial map with radial basis functions which forms the subtopographies. A simulated data is used to exhibit the advantage of using this decomposition technique prior to EEG source localization. It is shown that the accuracy of the source localization problem is improved by using the subtopographies instead of using the raw topography.
Texture Feature Application in Oil Spill Detection by Satellite Data
Authors: Lijian Shi, Chaofang Zhao, Kaiguo Fan, Yingni Shi, Peng Liu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Oil spills in the ocean are one of major environmental concerns, especially in the costal waters. Many satellite sensors, including optical sensors and microwave sensors, have been used to detect oil spills which often exhibit different feature in the satellite images compared with the surrounding waters. In this study, we used texture feature analysis to detect oil spill using MODIS and SAR images. The MODIS images of one incident were analyzed and the results proved the efficiency of algorithm. However, in very near shore regions, delineation of water and oil boundary is noisy due to a similar spectral signature across land-water boundary. The SAR image of Prestige accident was segmented with our method and result is better than the result from the single threshold method.
A Pattern and Rule-Based Approach for Reusing Adaptive Hypermedia Creator's Models
Authors: Nadjet Zemirline, Chantal Reynaud, Yolaine Bourda, Fabrice Popineau
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

The design of Adaptive Hypermedia is a difficult task which can be made easier if generic systems and AH creators' models are reused. We address this design problem in the setting of the GLAM platform only made up of generic components. In this paper, we assume the GLAM platform is used to create a specific adaptive hypermedia. We present a pattern and a rule-based approach helping a AH creator in reusing its user and domain models and instances in order to make them taken into account. This semi-automatic approach takes the creator's models as specialisations of GLAM generic models and requires the creator to express a minimum set of mappings between his models and the generic ones. The process results in a merged model consisting of the generic and the corresponding specific model, being fully compliant with the GLAM adaptation model. A plug-in and experimentations in the e-learning domain have been partially designed.
Integrating Data Sources and Network Analysis Tools to Support the Fight Against Organized Crime
Authors: Luigi Ferrara, Christian Mårtenson, Pontus Svenson, Per Svensson, Justo Hidalgo, Anastasio Molano, Anders L. Madsen
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

We discuss how methods from social network analysis could be combined with methodologies from database mediator technology and information fusion in order to give police and other civil security decision-makers the ability to achieve predictive situation awareness. Techniques based on these ideas have been demonstrated in the EU PASR project HiTS/ISAC.
The 2-Terminal-Set Path Cover Problem and Its Polynomial Solution on Cographs
Authors: Katerina Asdre, Stavros D. Nikolopoulos
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

In this paper we study a generalization of the path cover problem, namely, the 2-terminal-set path cover problem, or 2TPC for short. Given a graph G and two disjoint subsets $\mathcal{T}^1$ and $\mathcal{T}^2$ of V(G), a 2-terminal-set path cover of G with respect to $\mathcal{T}^1$ and $\mathcal{T}^2$ is a set of vertex-disjoint paths $\mathcal{P}$ that covers the vertices of G such that the vertices of $\mathcal{T}^1$ and $\mathcal{T}^2$ are all endpoints of the paths in $\mathcal{P}$ and all the paths with both endpoints in $\mathcal{T}^1 \cup \mathcal{T}^2$ have one endpoint in $\mathcal{T}^1$ and the other in $\mathcal{T}^2$. The 2TPC problem is to find a 2-terminal-set path cover of G of minimum cardinality; note that, if $\mathcal{T}^1 \cup \mathcal{T}^2$ is empty, the stated problem coincides with the classical path cover problem. The 2TPC problem generalizes some path cover related problems, such as the 1HP and 2HP problems, which have been proved to be NP-complete even for small classes of graphs. We show that the 2TPC problem can be solved in linear time on the class of cographs. The proposed linear-time algorithm is simple, requires linear space, and also enables us to solve the 1HP and 2HP problems on cographs within the same time and space complexity.
New Abstraction for Optimal Real-Time Scheduling on Multiprocessors
Authors: Kenji Funaoka, Shinpei Kato, Nobuyuki Yamasaki
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

T-R Plane Abstraction (TRPA) proposed in this paper is an abstraction technique of real-time scheduling on multiprocessors. This paper presents that NNLF (No Nodal Laxity First) based on TRPA is work-conserving and optimally solves the problem of scheduling periodic tasks on a multiprocessor system. TRPA can accommodate to dynamic environments due to its dynamic time reservation, while T-N Plane Abstraction (TNPA) and Extended TNPA (E-TNPA) reserve processor time statically at every task release.
Fair Exchange Is Incomparable to Consensus
Authors: Simona Orzan, Mohammad Torabi Dashti
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

In asynchronous systems where processes are prone to crash failures, we show that fair exchange is incomparable to distributed consensus. By incomparability we mean there exist failure detector classes that solve fair exchange and not distributed consensus, and vice versa. Remarkably, this is in contrast to the folklore belief that solving fair exchange is generally harder than solving distributed consensus.
Improvement of Data Warehouse Optimization Process by Workflow Gridification
Authors: Goran Velinov, Boro Jakimovski, Darko Cerepnalkoski, Margita Kon-Popovska
Venue: Proceedings of the 12th East European conference on Advances in Databases and Information Systems (2008)

Generalized problem optimization of the relational data warehouses ,i.e., selection of the optimal set of views, their optimal fragmentation and their optimal set of indexes is very complex and still a challenging problem. Therefore, choice of optimization method and improvements of optimization process are essential. Our previous research was focused on utilization of Genetic Algorithms for problem optimization. In this paper we further optimize our solution by applying our novel Java Gid framework for Genetic Algorithms (GGA) in the process of relational data warehouses optimization. Obtained experimental results have shown, that for different input parameters, GGA dramatically improves efficiency of the optimization process.
Automatic generation of generalized event sequence diagrams for guiding simulation based dynamic probabilistic risk assessment of complex systems
Authors: Ali Mosleh
Venue:  (2007)

Dynamic probabilistic risk assessment (DPRA) is a systematic and comprehensive methodology that has been used and refined over the past two decades to evaluate the risks associated with complex systems such as nuclear power plants, space missions, chemical plants, and military systems. A critical step in DPRA is generating risk scenarios which are used to enumerate and assess the probability of different outcomes. The classical approach to generating risk scenarios is not, however, sufficient to deal with the complexity of the above-mentioned systems. The primary contribution of this dissertation is in offering a new method for capturing different types of engineering knowledge and using them to automatically generate risk scenarios, presented in the form of generalized event sequence diagrams, for dynamic systems. This new method, as well as several important applications, is described in detail. The most important application is within a new framework for DPRA in which the risk simulation environment is guided to explore more interesting scenarios such as low-probability/high-consequence scenarios. Another application considered is the use of the method to enhance the process of risk-based design.
Performance Evaluation of the Route Optimization Scheme in Mobile IPv6
Authors: In-Hye Shin, Gyung-Leen Park, Junghoon Lee, Jun Hwang, Taikyeong T. Jeong
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The paper presents the performance comparison between the triangle routing and the route optimization. The paper presents not only the analytical models to compare the performance but also the threshold value to decide whether the mobile node had better use the route optimization or not. The model provides the approximate guideline when a network administrator is to implement mobile IPv6 with the route optimization under the given network environments.
A performance tuning methodology with compiler support
Authors: Oscar Hernandez, Barbara Chapman, Haoqiang Jin
Venue: Scientific Programming (2008)

We have developed an environment, based upon robust, existing, open source software, for tuning applications written using MPI, OpenMP or both. The goal of this effort, which integrates the OpenUH compiler and several popular performance tools, is to increase user productivity by providing an automated, scalable performance measurement and optimization system. In this paper we describe our environment, show how these complementary tools can work together, and illustrate the synergies possible by exploiting their individual strengths and combined interactions. We also present a methodology for performance tuning that is enabled by this environment. One of the benefits of using compiler technology in this context is that it can direct the performance measurements to capture events at different levels of granularity and help assess their importance, which we have shown to significantly reduce the measurement overheads. The compiler can also help when attempting to understand the performance results: it can supply information on how a code was translated and whether optimizations were applied. Our methodology combines two performance views of the application to find bottlenecks. The first is a high level view that focuses on OpenMP/MPI performance problems such as synchronization cost and load imbalances; the second is a low level view that focuses on hardware counter analysis with derived metrics that assess the efficiency of the code. Our experiments have shown that our approach can significantly reduce overheads for both profiling and tracing to acceptable levels and limit the number of times the application needs to be run with selected hardware counters. In this paper, we demonstrate the workings of this methodology by illustrating its use with selected NAS Parallel Benchmarks and a cloud resolving code.