ppxscal/embedding_network huggingface dataset:
An Infrastructure for Mining Medical Multimedia Data
Authors: Sara Colantonio, Ovidio Salvetti, Marco Tampucci
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

Biomedical research processes related to disease diagnosis, prognosis and monitoring would great benefit from advanced tools able not exclusively to store and manage multimodal data but also to process and extract significant relations and then novel knowledge from them. Indeed, making a prediction on a disease outcome usually requires considering heterogeneous pieces of information obtained from several sources which should be compared and related. Mining medical multimedia objects is aimed at discovering and making available the hidden useful knowledge embedded in collections of data and is, then, of key importance for supporting clinical decision-making. In this paper, we report current results of a medical warehouse we are developing in an integrated environment for mining clinical data acquired by different media. In particular, focus is herein given to the infrastructure of the warehouse and its current functionalities not limited to storage and management but including intelligent representation and annotation of multimedia objects.
Grid Services for Parallel Molecular Dynamics with NAMD and CHARMM
Authors: Siegfried Benkner, Christian Schröder, Maria Lucka, Othmar Steinhauser
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

High-end computing facilities are key to enabling molecular dynamics simulation of biological relevant systems for a sufficiently long simulation period. On the one hand, the trajectory production necessitates a high-performance parallel computer architecture. On the other hand, hundreds of jobs, both trajectory production and analysis, have to be supervised and started more or less automatically. Although high performance computers are now available to a broad scientific community, users are often forced to cope with many low-level details when using these machines for scientific investigations. Grid computing technologies promise to provide seamless access to parallel computers through the abstraction of services hiding the details of the underlying software and hardware infrastructure. In this article, we describe the provision of Grid services for parallel molecular dynamics simulations based on NAMD and CHARMM within the Vienna Grid Environment.
A MultiAgent System for Physically Based Rendering Optimization
Authors: Carlos Gonzalez-Morcillo, Gerhard Weiss, Luis Jimenez, David Vallejo, Javier Albusac
Venue: Proceedings of the 11th international workshop on Cooperative Information Agents XI (2007)

Physically based rendering is the process of generating a 2D image from the abstract description of a 3D Scene. Despite the development of various new techniques and algorithms, the computational requirements of generating photorealistic images still do not allow to render in real time. Moreover, the configuration of good render quality parameters is very difficult and often too complex to be done by non-expert users. This paper describes a novel approach called MAgarRO (standing for "Multi-Agent AppRoach to Rendering Optimization") which utilizes principles and techniques known from the field of multi-agent systems to optimize the rendering process. Experimental results are presented which show the benefits of MAgarRO-based rendering optimization.
From cells to organisms: long-term guarantees on service provisioning in peer-to-peer networks
Authors: Kalman Graffi, Aleksandra Kovacevic, Nicolas Liebau, Ralf Steinmetz
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

The peer-to-peer paradigm gained more and more impact in the last years. The reason for P2P arising now is related to the continuous development of device capabilities in the last years, like CPU power, storage space and bandwidth. However, the demand for services and resources is permanently increasing, although the peers have a variety of other resources themselves. In this paper we present the idea of a P2P system acting as a service provider using the resources of participating peers and stating guarantees on the quality of the service it provides. In order to fulfill these service level agreements, the peers confederate to a distributed supervisor of peer resources (DISPRO), monitoring the network, predicting trends on resource availabilities and deciding on resource allocation strategies. This paper discusses the challenges and a solution draft of the concept of DISPRO.
An Improved Double Byte Error Correcting Code Using Cellular Automata
Authors: Jaydeb Bhaumik, Dipanwita Roy Chowdhury, Indrajit Chakrabarti
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

Cellular Automata(CA) based VLSI implementation of t-byte errors correcting code has been established by previous research to be superior to the other existing techniques employed for realizing Reed-Solomon(RS) code. However, the scheme suffers from the limitation that it can correct t ¿byte errors (t ¿ 2) provided errors are confined either wholly to the information bytes or entirely to the check bytes. The work reported in the present paper overcomes this limitation and corrects the errors likely in both information and check bytes. Moreover one weakness found in an earlier similar work has been identified and rectified using a modified check symbol expressions.
Neuro-fuzzy System for Road Signs Recognition
Authors: Bogusław Cyganek
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

In this paper a hybrid neuro-fuzzy system for the real-time recognition of the road-signs is presented. For tracking an improvement to the continuously adaptive mean shift method is proposed. It consists in substitution of the probabilistic density for the especially formed membership function. Classification of binary pictograms of the detected signs is done with the kernel morphological neural network which is robust to noise, missing data, and small geometrical deformations of the patterns.
Simulation and Measurement of Complex Network Growth: the Interplay of Uniform and Preferential Attachment
Authors: Hongwei Luo, Kathy Horadam
Venue: Fundamenta Informaticae (2008)

The main discovery of the paper is the introduction and study of a new U-P complex network model, which aims to describe and analyze many common-featured real-world complex networks. This model employs a new functional form of the network growth rule: a linear combination of preferential and uniform attachment. In particular, the degree distribution of the model is first studied by using the computer simulation method, while the exact solution is also obtained analytically.
Implementation of Multi-valued Logic Based on Bi-threshold Neural Networks
Authors: Qiuxiang Deng, Zhigang Zeng
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

The implementation of multi-valued logic with a three layers forward neural network is proposed. The hidden layer is constituted by bi-threshold neurons compared with traditional simple threshold neurons. According to the obtained results in this paper, if a perception with a simple threshold neuron is used in the output layer, then the logical map of {0,1, ¿ ,n} to {0,1} can be gained. In addition, if a linear neuron is used in the output layer, then the logical map of {0,1, ¿ ,n} to {0,1, ¿ ,m} can be obtained. The arithmetic, which is used to design the three layers forward neural network, improves on the traditional digital logic of two values. An example shows that the designable procedure of the network is simple and effective.
A Data Management Framework for Urgent Geoscience Workflows
Authors: Jason Cope, Henry M. Tufo
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

The emerging class of urgent geoscience workflows are capable of quickly allocating computational resources for time critical tasks. To date, no urgent computing capabilities for data services exists. Since urgent geoscience and Earth science workflows are typically data intensive, urgent data services are necessary so that these urgent workflows do not bottleneck on inappropriately managed or provisioned resources. In this paper we examine emerging urgent Earth and geoscience workflows, the data services used by these workflows, and our proposed urgent data management framework for managing urgent data services.
The Verified Software Challenge: A Call for a Holistic Approach to Reliability
Authors: Thomas Ball
Venue: Verified Software: Theories, Tools, Experiments: First IFIP TC 2/WG 2.3 Conference, VSTTE 2005, Zurich, Switzerland, October 10-13, 2005, Revised Selected Papers and Discussions (2005)

The software analysis community has made a lot of progress in creating software tools for detecting defects and performing proofs of shallow properties of programs. We are witnessing the birth of a virtuous cycle between software tools and their consumers and I, for one, am very excited about this. We understand much better how to engineer program analyses to scale to large code bases and deal with the difficult problem of false errors and reducing their number. We understand better the tradeoffs in sound vs. unsound analyses. The software tools developed and applied over the last eight years have had impact. This list of tools includes Blast [HJMS02], CCured [NMW02], CQual [FTA02], ESC/Java [FLL + 02], ESP [DLS02], Feaver [Hol00], MAGIC [CCG + 04], MC [HCXE02], MOPS [CDW04], Prefast [LBD+04], Prefix [BPS00], SLAM [BR01], Splint [EL02] and Verisoft [God97], to name a few.This bottom-up approach to improving code quality will continue to be successful because it deals with a concrete artifact (programs) that people produce, has great economic impact and longevity. Furthermore, because many of the tools listed above are specification-based, they are easy to extend to new classes of bugs. Finally, a lot of the science to support the development of these tools has been done; there is now before us a long road of engineering to make these tools truly useful and useable by a wide audience.
On the Influence of the Packet Marking and Injection Control Schemes in Congestion Management for MINs
Authors: Joan-Lluís Ferrer, Elvira Baydal, Antonio Robles, Pedro López, José Duato
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Several Congestion Management Mechanisms (CMMs) have been proposed for Multistage Interconnection Networks (MINs) in order to avoid the degradation of network performance when congestion appears. Most of them are based on Explicit Congestion Notification (ECN). For this purpose, switches detect congestion and, depending on the applied mechanism, some flags are marked to warn the source hosts. In response, source hosts apply corrective actions to adjust their packet injection rate. These mechanisms have been evaluated by analyzing whether they are able to manage a congestion situation but there is not a comparison study among them. Moreover, marking effects are not separately analyzed from corrective actions. In this paper, we analyze the current proposals for CMMs, showing the impact of the applied packet marking techniques as well as the corrective actions they apply.
An Introduction to Transfer Learning
Authors: Qiang Yang
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Many existing data mining and machine learning techniques are based on the assumption that training and test data fit the same distribution. This assumption does not hold, however, as in many cases of Web mining and wireless computing when labeled data becomes outdated or test data are from a different domain with training data. In these cases, most machine learning methods would fail in correctly classifying new and future data. It would be very costly and infeasible to collect and label enough new training data. Instead, we would like to recoup as much useful knowledge as possible from the old data. This problem is known as transfer learning. In this talk, I will give an overview of the transfer learning problem, present a number of important directions in this research, and discuss our own novel solutions to this problem.
When Ignorance Helps: Graphical Multicast Cost Sharing Games
Authors: Vittorio Bilò, Angelo Fanelli, Michele Flammini, Luca Moscardelli
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

In non-cooperative games played on highly decentralized networks the assumption that each player knows the strategy adopted by any other player may be too optimistic or even unfeasible. In such situations, the set of players of which each player knows the chosen strategy can be modeled by means of a social knowledge graph in which nodes represent players and there is an edge from i to j if i knows j. Following the framework introduced in [3], we study the impact of social knowledge graphs on the fundamental multicast cost sharing game in which all the players wants to receive the same communication from a given source. Such a game in the classical complete information case is known to be highly inefficient, since its price of anarchy can be as high as the total number of players ρ. We first show that, under our incomplete information setting, pure Nash equilibria always exist only if the social knowledge graph is directed acyclic (DAG). We then prove that the price of stability of any DAG is at least $\frac 1 2\log\rho$ and provide a DAG lowering the classical price of anarchy to a value between $\frac 1 2\log\rho$ and log2 ρ. If specific instances of the game are concerned, that is if the social knowledge graph can be selected as a function of the instance, we show that the price of stability is at least $\frac{4\rho}{\rho+3}$, and that the same bound holds also for the price of anarchy of any social knowledge graph (not only DAGs). Moreover, we provide a nearly matching upper bound by proving that, for any fixed instance, there always exists a DAG yielding a price of anarchy less than 4. Our results open a new window on how the performances of non-cooperative systems may benefit from the lack of total knowledge among players and can be considered, in some sense, as another evidence of the famous Braess' paradox.
Application and comparison of several artificial neural networks for forecasting the Hellenic daily electricity demand load
Authors: L. Ekonomou, D. S. Oikonomou
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

This paper introduces an approach based on artificial neural networks in order to forecast the Hellenic daily electricity demand load. Several structures, learning algorithms and transfer functions were tested in order to produce a model with the best generalising ability. Actual input and output data collected from the Hellenic power network were used in the training, validation and testing process. Different factors such as economical, seasonality and weather conditions which indisputably affect the daily electricity demand load were taken into account in this approach. The produced results were compared with real electricity demand load records showing a great accuracy. The proposed approach can be useful in the studies of electricity providers, retailers and regulatory authorities aiming mainly in the uninterrupted supply of energy, maintaining at the same time a low cost.
Tailoring the Interpretation of Spatial Utterances for Playing a Board Game
Authors: Andrea Corradini
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

In order to build an intelligent system that allows human beings to cooperate with a computing machine to perform a given task it is important to account for the individual characteristics of each user. In this work, we describe a flexible and adaptive user interface that is capable of interpreting spatial linguistic expressions according to the peculiar preferences and use of language of the user. As a proof of concept, we have implemented a graphics board game in which players can move, remove and spatially manipulate in 2D various game pieces on the computer screen by issuing speech commands during a dialogue session with the application. After an initial guided interaction, the system analyzes on the fly subjective interpretations of several linguistic relationships that form the basis for spatial expressions to tune a set of system's parameters. We tested the system with different human subjects. Automatic judgment of spatial expressions based on each user's interaction behavior over-performed sentence interpretation of a model that we previously created to tailor the characteristics of some abstract typical player. Post interaction informal talks also indicated a higher level of user satisfaction in subjects playing with the customized application rather than the more general one.
A New Type of Feature --- Loose N-Gram Feature in Text Categorization
Authors: Xian Zhang, Xiaoyan Zhu
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

This paper introduces a new type of feature in text categorization. Based on an interesting linguistic observation, Loose N-gram feature, defined as co-occurring words within limited range, is quite different from traditional features, such as words, phrases or n-grams. Not only retaining useful context information, this kind of feature also has considerable classification ability. The features generated by our algorithm have acceptable statistical characteristics, thus can effectively avoid the sparseness problem. Experiment results show that the Loose N-gram feature is helpful and promising in statistical text categorization systems, especially for the categorization tasks which rely on more semantic information. Our new type of feature could also be helpful in Information Retrieval research.
ICGT 2008 Doctoral Symposium
Authors: Andrea Corradini, Emilio Tuosto
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

For the first time in the history of the ICGT conference series, this year a specific event, the ICGT 2008 Doctoral Symposium, is explicitly dedicated to Ph.D. students and young researchers who completed their doctoral studies within the past two years. In fact, the Doctoral Symposium consists of some technical sessions, held during the main conference, dedicated to presentations by doctoral students and young researchers, and giving them a unique opportunity to present their work and to interact with established researchers of the graph transformation community and with other students.
TS Fuzzy Rule-Based Systems with Polynomial Membership Functions
Authors: Jacek Kluska
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

The work presents some results concerning analytical modeling using the Takagi-Sugeno fuzzy rule-based system, which can be used for exact fuzzy modeling of some class of conventional systems. A special attention was paid to the so called P2-TS systems, which use the polynomial membership functions of the second degree. Theorems provide necessary and sufficient conditions for transformation of fuzzy rules into the crisp model of the system and vice-versa. 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
Theoretical Analysis of a Rigid Coreset Minimum Enclosing Ball Algorithm for Kernel Regression Estimation
Authors: Xunkai Wei, Yinghong Li
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

A rigid coreset minimum enclosing ball training machine for kernel regression estimation was proposed. First, it transfers the kernel regression estimation machine problem into a center-constrained minimum enclosing ball representation form, and subsequently trains the kernel methods using the proposed MEB algorithm. The primal variables of the kernel methods are recovered via KKT conditions. Then, detailed theoretical analysis and main theoretical results of our new algorithm are given. It can be concluded that our proposed MEB training algorithm is independent of sample dimension and the time complexity is linear in sample numbers, which greatly cuts down the complexity level and is expected to speedup the learning process obviously. Finally, comments about the future development directions are discussed.
Preliminary design of rowing simulator for in-door skill training
Authors: Antonio Frisoli, Emanuele Ruffaldi, Leonardo Bagnoli, Alessandro Filippeschi, Carlo Alberto Avizzano, Federico Vanni, Massimo Bergamasco
Venue: Proceedings of the 2008 Ambi-Sys workshop on Haptic user interfaces in ambient media systems (2008)

In this paper we report on the preliminary design of a rowing simulator to be integrated in a VR sport training system for rowing. The proposed simulator aims at bringing in an indoor location the specific features and situations of outdoor rowing, by means of an enhanced Virtual Environment (VE) that combines visual, haptic, acoustic flows to proprio- and exteroception of user status. This paper describes the experimental activities carried out on in-door rowing to characterize the main features of the stroke gesture, the design and analytical study of a fluidodynamic dissipator for force rendering and an overview of graphic simulation and of the overall system architecture.
An Accidental Simula User
Authors: Luca Cardelli
Venue: Proceedings of the 21st European conference on ECOOP 2007: Object-Oriented Programming (2007)

It was a simple choice, really, on an IBM 370 in the 70's, between APL, Fortran, Lisp 1.5, PL/1, COBOL, and Simula'67. Nothing could come close to Simula's combination of strong typing, garbage collection, and proper string processing. Separate compilation (prefix classes) and coroutines were nice bonuses. And then there were these ... "objects" but, well, nothing is perfect. Hot topics in those days were the freshly invented denotational semantics (which Simula didn't have), formal type systems (which objects didn't have), and abstract data types (which seemed to have confusingly little to do with classes). Still, Simula was the obvious choice to get something done comfortably because, after all, it was an improved Algol. It even had the functional programming feature of call-by-name by default. So, it became my first favorite language, for every reason other than it being object-oriented.The story I am going to tell is the very, very slow realization that Simula was the embodiment of a radically different philosophy of programming, and the gradual and difficult efforts to reconcile that philosophy with the formal methods that were being developed for procedural and functional programming. Along the way, domain theory helped rather unexpectedly, at least for a while. Type theory had to be recast for the task at hand. Landin's lambda-reductionism had to be partially abandoned. Always, there seemed to be a deep fundamental mismatch between objects and procedures, well described by Reynolds, that made any unification impossibly complicated. But in the end, both object-oriented and procedural programming have benefited from the clash of cultures. And the story is far from over yet, as witnessed by the still blooming area of program verification for both procedural and object-oriented languages.