ppxscal/embedding_network huggingface dataset:
On Scheduling Exception Handlers in Dynamic, Embedded Real-Time Systems
Authors: Binoy Ravindran, Edward Curley, E. Douglas Jensen
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

We consider the problem of scheduling exception handlers in real-time systems that operate under run-time uncertainties including those on execution times, activity arrivals, and failure occurrences. The application/scheduling model includes activities and their exception handlers that are subject to time/utility function (TUF) time constraints and an utility accrual (UA) optimality criterion. A key underpinning of the TUF/UA scheduling paradigm is the notion of "best-effort" where high importance activities are always favored over low importance ones, irrespective of activity urgency. (This is in contrast to classical admission control models which favor feasible completion of admitted activities over admitting new ones, irrespective of activity importance.) We consider a transactional style activity execution paradigm, where handlers that are released when their activities fail (e.g., due to time constraint violations) abort the failed activities after performing recovery actions. We present a scheduling algorithm called Handler-assured Utility accrual Algorithm (or HUA) for scheduling activities and their handlers. We show that HUA's properties include bounded-time completion for handlers and bounded loss of the best-effort property. Our implementation on a Real-Time Java Virtual Machine demonstrates the algorithm's effectiveness.
Universally Composable Multi-party Computation Using Tamper-Proof Hardware
Authors: Jonathan Katz
Venue: Proceedings of the 26th annual international conference on Advances in Cryptology (2007)

Protocols proven secure within the universal composability (UC) framework satisfy strong and desirable security properties. Unfortunately, it is known that within the "plain" model, secure computation of general functionalities without an honest majority is impossible. This has prompted researchers to propose various "setup assumptions" with which to augment the bare UC framework in order to bypass this severe negative result. Existing setup assumptions seem to inherently require some trusted party (or parties) to initialize the setup in the real world.We propose a new setup assumption -- more along the lines of a physical assumption regarding the existence of tamper-proof hardware -- which also suffices to circumvent the impossibility result mentioned above. We suggest this assumption as potentially leading to an approach that might alleviate the need for trusted parties, and compare our assumption to those proposed previously.
Simulator Implementation of an IF-ISAR System for Studies in Target Glint
Authors: Theodoros G. Kostis, Konstantinos G. Galanis, Socrates K. Katsikas
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

The formation steps leading to the creation of a computer simulator for an extended naval target as viewed by an approaching Interferometric Inverse Synthetic Aperture Radar (IF-ISAR) seeker sensor is presented in this paper. The conceptual model development, the modelling approach, the implementation results and the project success details are outlined. The novelty of this effort is the value-added ability of the simulator to further treat the generated data for rate of change processing leading to the assembly of height information about the target under scrutiny which can be used either for friend-or-foe identification decisions or intelligent expendable decoy programming.
Self-organized Reinforcement Learning Based on Policy Gradient in Nonstationary Environments
Authors: Yu Hiei, Takeshi Mori, Shin Ishii
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

In real-world problems, the environment surrounding a controlled system is nonstationary, and the optimal control may change with time. It is difficult to learn such controls when using reinforcement learning (RL) which usually assumes stationary Markov decision processes. A modular-based RL method was formerly proposed by Doya et al., in which multiple-paired predictors and controllers were gated to produce nonstationary controls, and its effectiveness in nonstationary problems was shown. However, learning of time-dependent decomposition of the constituent pairs could be unstable, and the resulting control was somehow obscure due to the heuristical combination of predictors and controllers. To overcome these difficulties, we propose a new modular RL algorithm, in which predictors are learned in a self-organized manner to realize stable decomposition and controllers are appropriately optimized by a policy gradient-based RL method. Computer simulations show that our method achieves faster and more stable learning than the previous one.
Application of Chebyshev II-Bernstein basis transformations to degree reduction of Bézier curves
Authors: Lizheng Lu, Guozhao Wang
Venue: Journal of Computational and Applied Mathematics (2008)

A polynomial curve on [0,1] can be expressed in terms of Bernstein polynomials and Chebyshev polynomials of the second kind. We derive the transformation matrices that map the Bernstein and Chebyshev coefficients into each other, and examine the stability of this linear map. In the p=1 and ~ norms, the condition number of the Chebyshev-Bernstein transformation matrix grows at a significantly slower rate with n than in the power-Bernstein case, and the rate is very close (somewhat faster) to the Legendre-Bernstein case. Using the transformation matrices, we present a method for the best multi-degree reduction with respect to the t-t^2-weighted square norm for the unconstrained case, which is further developed to provide a good approximation to the best multi-degree reduction with constraints of endpoints continuity of orders r,s (r,s>=0). This method has a quadratic complexity, and may be ill-conditioned when it is applied to the curves of high degree. We estimate the posterior L"1-error bounds for degree reduction.
Automatability of Coupled Evolution of Metamodels and Models in Practice
Authors: Markus Herrmannsdoerfer, Sebastian Benz, Elmar Juergens
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Model-based software development promises to increase productivity by offering modeling languages tailored to a problem domain. Such modeling languages are often defined by a metamodel. In consequence of changing requirements and technological progress, these modeling languages and thus their metamodels are subject to change. Manually migrating models to a new version of their metamodel is tedious, error-prone and heavily hampers cost-efficient model-based development practice. Automating model migration in response to metamodel adaptation promises to substantially reduce effort. Unfortunately, little is known about the types of changes occurring during metamodel adaptation in practice and, consequently, to which degree reconciling model migration can be automated. We analyzed the changes that occurred during the evolution history of two industrial metamodels and classified them according to their level of potential automation. Based on the results, we present a list of requirements for effective tool support for coupled evolution of metamodels and models in practice.
Extracting the Components of Elderly People's Capacity in Electrical Appliances and Grasping Relationship with the Components
Authors: Kanji Tanaka, Toshiki Yamaoka
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

The purpose of this study is to extract the components of capacity which elderly people have in electrical appliances and grasp the relationship with the components. In this research, we interviewed elderly people for the impression and experience of electrical appliances and conducted the tests, for example, card sorting, tasks using digital video camera and so on. We used Boolean algebra with tests data to simplify items. As a result, we found the relationship with the components in electrical appliances.
A General Framework for Designing Approximation Schemes for Combinatorial Optimization Problems with Many Objectives Combined into One
Authors: Shashi Mittal, Andreas S. Schulz
Venue: Proceedings of the 11th international workshop, APPROX 2008, and 12th international workshop, RANDOM 2008 on Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques (2008)

In this paper, we propose a general framework for designing fully polynomial time approximation schemes for combinatorial optimization problems, in which more than one objective function are combined into one using any norm. The main idea is to exploit the approximate Pareto-optimal frontier for multi-criteria optimization problems. Using this approach, we obtain an FPTAS for a novel resource allocation problem, for the problem of scheduling jobs on unrelated parallel machines, and for the Santa Claus problem, when the number of agents/machines is fixed, for any norm, including the l ¿ -norm. Moreover, either FPTAS can be implemented in a manner so that the space requirements are polynomial in all input parameters. We also give approximation algorithms and hardness results for the resource allocation problem when the number of agents is not fixed.
Revisiting Lexical Signatures to (Re-)Discover Web Pages
Authors: Martin Klein, Michael L. Nelson
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

A lexical signature (LS) is a small set of terms derived from a document that capture the "aboutness" of that document. A LS generated from a web page can be used to discover that page at a different URL as well as to find relevant pages in the Internet. From a set of randomly selected URLs we took all their copies from the Internet Archive between 1996 and 2007 and generated their LSs. We conducted an overlap analysis of terms in all LSs and found only small overlaps in the early years (1996 ¿ 2000) but increasing numbers in the more recent past (from 2003 on). We measured the performance of all LSs in dependence of the number of terms they consist of. We found that LSs created more recently perform better than early LSs created between 1996 and 2000. All LSs created from year 2000 on show a similar pattern in their performance curve. Our results show that 5-, 6- and 7-term LSs perform best with returning the URLs of interest in the top ten of the result set. In about 50% of all cases these URLs are returned as the number one result and in 30% of all times we considered the URLs as not discoved.
Estimating available bandwidth for real-time supermedia applications
Authors: Matt Mutka
Venue:  (2007)

The emerging development of remote sensing and control technology gives rise to new types of real-time networking applications that require "pro-active" quality of service guarantees. This dissertation specifies Quality of Service parameters characterizing requirements for successful execution of a given real-time tele-operation over the Internet. The dissertation also provides a statistical model that outputs the likelihood of a failure of remote real-time task execution based on the history of behavior of an end-to-end network path and the task requirements. We provided and compared both parametric and non-parametric approaches, conducted their experimental evaluation and also introduced some mechanisms for improvement of present measurement technologies of an end-to-end quality of a network path. Available bandwidth (spare capacity) of a network path is a key characteristic of the network path quality. We regard available bandwidth as a random time-series with an existing auto-correlation structure that is realistic and makes channel quality estimation accurate on real paths over the Internet. We also consider a set of pro-active measures to save remote real-time task execution from a failure once the likelihood of such a failure exceeds an acceptable threshold. In particular, we give a solution to the Reroute Sequence Planning problem: to choose an optimal sequence of data-streams reallocations across different network paths once the QoS of old paths are unacceptable. Optimal reallocation minimizes extra capacity of a network link that is required for carrying out the reallocation procedure.
Cue Integration for Medical Image Annotation
Authors: Tatiana Tommasi, Francesco Orabona, Barbara Caputo
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper presents the algorithms and results of our participation to the image annotation task of ImageCLEFmed 2007. We proposed a multi-cue approach where images are represented both by global and local descriptors. These cues are combined following two SVM-based strategies. The first algorithm, called Discriminative Accumulation Scheme (DAS), trains an SVM for each feature, and considers as output of each classifier the distance from the separating hyperplane. The final decision is taken on a linear combination of these distances. The second algorithm, that we call Multi Cue Kernel (MCK), uses a new Mercer kernel which can accept as input different features while keeping them separated. The DAS algorithm obtained a score of 29.9, which ranked fifth among all submissions. The MCK algorithm with the one-vs-all and with the one-vs-one multiclass extensions of SVM scored respectively 26.85 and 27.54. These runs ranked first and second among all submissions.
A semantic-based service matching approach for service-based systems
Authors: Junwei Liu
Venue:  (2008)

A major advantage of the emerging service-oriented computing technology is its ability to enable rapid and flexible development of large-scale distributed systems achieving various system goals. Such service-based systems are composed of loosely coupled services implemented in various programming languages, deployed over multiple service platforms across various organizational boundaries and over heterogeneous networks. Service matching is a basic critical building block in service-based systems. It mediates between service providers and service requesters to efficiently locate suitable services to perform dynamic tasks. Little work has been done in traditional syntax-based and parameter-based service matching approaches to handle the rich semantics of services. Advanced semantic-based service matching capabilities are desirable to provide more precise and relevant matching results. In this dissertation, a semantic-based service matching approach is presented to provide accurate, relevant, privacy-preserving and efficient service matching capabilities. This approach is based on the semantic modeling, specification, interpretation and analysis of service functionalities, attributes, situational data and access control policies. This approach first extends existing service semantic model OWL-S with situation, access control policy, and service discovery ontologies to model and specify more complete service semantics for service matching. By interpreting and analyzing the service semantics specified based on the modeled ontologies, this approach ensures that the matching results will have compatible functionalities, similar characteristics and relevant situational data to the service discovery request. A privacy-preserving mechanism is also incorporated in this approach to protect the shared privacy-related information from being leaked to unauthorized parties during service matching process.
Early Forest Fire Detection with Sensor Networks: Sliding Window Skylines Approach
Authors: Krešimir Pripužić, Hrvoje Belani, Marin Vuković
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Wireless sensor networks are widely used in environmental applications, like forest fire detection. Although forest fires occur relatively rarely, their number is increasing in Europe in the last years, so their manifestation must be early detected in order to prevent higher damages. To minimize needless communication between the sensor nodes for this usage, new data suppression technique using sliding window skylines is described in this paper. We experimentally evaluate our algorithm for continuous sliding windows skylines computation, and show its usability in practice.
Design Abstractions for Innovative Web Applications: The Case of the SOA Augmented with Semantics
Authors: Stefano Ceri, Marco Brambilla, Emanuele Valle
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

This work presents a retrospective analysis of how we have addressed new challenges in Web technologies and applications. WebML, which was first defined about 10 years ago, has been an incubator for research concerning abstractions, methods, tools, and technologies, acting as a glue within a group of people spread among universities, technology transfer centres, and a spin-off. In this paper, we first illustrate the common approach to innovation, and then show such approach at work in two contexts. One of them, dealing with "Service-Oriented Architectures" (SOA), has reached a mature state; the other one, "Semantic Web Services" (SWS), is at its infancy, but promises to deliver very interesting results in the forthcoming years.
The Relationship between Graph Comprehension and Spatial Imagery: Support for an Integrative Theory of Graph Cognition
Authors: Brandie M. Stewart, Aren C. Hunter, Lisa A. Best
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

Trickett and Trafton [7,8] suggested an integrative model of graph comprehension that accounts for the role that spatial cognition plays in comprehension. This paper presents a preliminarily examination of spatial and object imagery abilities in relation to Trickett and Trafton's three levels of graph comprehension [8]. Results confirmed Trickett and Trafton's levels of comprehension and suggested that spatial imagers have higher levels of graph comprehension.
Semantic Learning Space: An Infrastructure for Context-Aware Ubiquitous Learning
Authors: Zhiwen Yu, Xingshe Zhou, Yuichi Nakamura
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

In order to facilitate the development and proliferation of context-aware ubiquitous learning services, there is a need for architectural support in the user context processing and learning content management. In this paper, we propose a context-aware ubiquitous learning infrastructure called Semantic Learning Space. It leverages the Semantic Web technologies to support explicit knowledge representation, flexible context reasoning, interoperable content integration, expressive knowledge query, and adaptive content recommendation. The architectural design and enabling technologies are described in detail. Several applications and experiments are presented to illustrate and evaluate the key features of the infrastructure.
Parallelism Increases Iterative Learning Power
Authors: John Case, Samuel E. Moelius,  Iii
Venue: Proceedings of the 18th international conference on Algorithmic Learning Theory (2007)

Iterative learning ($\textbf{It}$-learning) is a Gold-style learning model in which each of a learner's output conjectures may depend only upon the learner's current conjecture and the current input element. Two extensions of the $\textbf{It}$-learning model are considered, each of which involves parallelism. The first is to run, in parallel, distinct instantiations of a single learner on each input element. The second is to run, in parallel, n individual learners incorporating the first extension, and to allow the n learners to communicate their results. In most contexts, parallelism is only a means of improving efficiency. However, as shown herein, learners incorporating the first extension are more powerful than $\textbf{It}$-learners, and, collective learners resulting from the second extension increase in learning power as n increases. Attention is paid to how one would actually implement a learner incorporating each extension. Parallelism is the underlying mechanism employed.
Web Usage Mining in Noisy and Ambiguous Environments: Exploring the Role of Concept Hierarchies, Compression, and Robust User Profiles
Authors: Olfa Nasraoui, Esin Saka
Venue: From Web to Social Web: Discovering and Deploying User and Content Profiles: Workshop on Web Mining, WebMine 2006, Berlin, Germany, September 18, 2006. Revised Selected and Invited Papers (2007)

Recent efforts in Web usage mining have started incorporating more semantics into the data in order to obtain a representation deeper than shallow clicks. In this paper, we review these approaches, and examine the incorporation of simple cues from a website hierarchy in order to relate clickstream events that would otherwise seem unrelated, and thus perform URL compression. We study their effect on data reduction and on the quality of the resulting knowledge discovery. Web usage data is also notorious for containing moderate to high amounts of noise, thus motivating the use of robust knowledge discovery algorithms that can resist noise and outliers with various degrees of resistance or robustness. Therefore, we also examine the effect of robustness on the final quality of the knowledge discovery. Our experimental results conclude that post-processed and robust user profiles have better quality than raw profiles that are estimated through optimization alone. However URL compression, as expected, tends to reduce the quality, but also can drastically reduce the size of the data set, resulting in faster mining.
General Algorithms for Testing the Ambiguity of Finite Automata
Authors: Cyril Allauzen, Mehryar Mohri, Ashish Rastogi
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

This paper presents efficient algorithms for testing the finite, polynomial, and exponential ambiguity of finite automata with ¿-transitions. It gives an algorithm for testing the exponential ambiguity of an automaton A in time $O(|A|_E^2)$, and finite or polynomial ambiguity in time $O(|A|_E^3)$, where |A| E denotes the number of transitions of A. These complexities significantly improve over the previous best complexities given for the same problem. Furthermore, the algorithms presented are simple and based on a general algorithm for the composition or intersection of automata. We also give an algorithm to determine in time $O(|A|_E^3)$ the degree of polynomial ambiguity of a polynomially ambiguous automaton A. Finally, we present an application of our algorithms to an approximate computation of the entropy of a probabilistic automaton.
The Ackermann Award 2008
Authors: J. A. Makowsky, D. Niwinski
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

The fourth Ackermann Award is presented at this CSL'08. This is the second year in which the EACSL Ackermann Award is generously sponsored. Our sponsor for the remaining two years is the worlds leading provider of personal peripherals, Logitech S.A., situated in Romanel, Switzerland.Eligible for the 2008 Ackermann Award were PhD dissertations in topics specified by the EACSL and LICS conferences, which were formally accepted as PhD theses at a university or equivalent institution between 1.1. 2006 and 31.12. 2007. The Jury received 13 nominations for the Ackermann Award 2008. The candidates came from 8 different nationalities from Europe, Russia and India, and received their PhDs in 8 different countries in Europe and North America.