pinecone/core-2020-05-10-deduplication huggingface dataset:
Efficient cross-validation in ILP

Cross-validation is a technique used in many different machine learning approaches. Straightforward implementation of this technique has the disadvantage of causing computational overhead. However, it has been shown that this overhead often consists of redundant computations, which can be avoided by performing all folds of the cross-validation in parallel. In this paper we study to what extent such a parallel algorithm is also useful in ILP. We discuss two issues: a) the existence of dependencies between parts of a query that limit the obtainable efficiency improvements and b) the combination of parallel cross-validation with query-packs. Tentative solutions are proposed and evaluated experimentally.status: publishe
From shell logs to shell scripts

Analysing the use of a Unix command shell is one of the classic applications in the domain of adaptive user interfaces and user modelling. Instead of trying to predict the next command from a history of commands, we automatically produce scripts that automate frequent tasks. For this we use an ILP association rule learner. We show how to speedup the learning task by dividing it into smaller tasks, and the need for a preprocessing phase to detect frequent subsequences in the data. We illustrate this with experiments with real world data.status: publishe
Agents’ interaction in virtual storytelling

In this paper the authors describe a fully implemented prototype for interactive storytelling using the Unreal™ engine. Using a sit-com like scenario as an example of how the dynamic interactions between agents and/or the user dramatise the emerging story. Hierarchical Task Networks (HTNs) are formalised using AND/OR graphs, which are used to describe the many possible variations of the story at a sub-goal level, and the set of all behaviours (from a narrative perspective) of the primary actors at a terminal action level. The authors introduce real-time variant of the heuristic search algorithm AO✻ that has been implemented to provide a mechanism for planning (and re-planning) and discuss how the chosen heuristic evaluation function is used to describe narrative concepts. They provide early results of several examples of how the same basic plot can have many differing story instantiations as a result of the dynamic interaction within the virtual set and the personalities of the primary characters, and detail the steps required in the plan generation
Fast adaptive selection of best views

Automatic computation of best views of objects is very useful. For example, they can be used as the starting point of a scene exploration, or to enrich galleries of objects available through Internet by adding an image a model that may help to decide if it is worth downloading. To select the most interesting viewpoint of an object, we use\ud
the so-called viewpoint entropy. The best view is the one which gives the most information of the object being inspected. In this paper we present an adaptive method to compute best views. Our adaptive scheme allows to improve over previous approaches the time of the selection of best views by an order of magnitude, and achieve a nearly interactive rate.Postprint (published version
COPLINK agent: An architecture for information monitoring and sharing in law enforcement

In this paper, we report our work on developing and evaluating a prototype system aimed at addressing the information monitoring and sharing challenges in the law enforcement domain. Our system, called COPLINK Agent, is designed to provide automatic information filtering and monitoring functionalities. This system also supports knowledge sharing by proactively identifying officers who are working on the same or similar cases on a real-time basis. To accommodate the mobile needs of law enforcement officers who are constantly in the field, COPLINK Agent can deliver messages through a variety of communications channels including e-mail, pager, and mobile phones. In order to assess the effectiveness of COPLINK Agent, we conducted a pilot user study at the Tucson Police Department. Overall, COPLINK Agent was shown to be an effective tool for improving the effectiveness and efficiency of criminal investigations in crimes such as gang, theft, and fraud. © Springer-Verlag Berlin Heidelberg 2003.postprin
Replicated ambient Petri nets

Recently we have introduced Ambient Petri nets, as a multilevel extension of the Elementary Object Systems, that can be used to model the concept of nested ambients from the Ambient Calculus. Both mobile computing and mobile computation are supported by that calculus, and then by means of our Ambient Petri nets we get a way to introduce in the world of Petri nets these important features of nowadays computing. Nevertheless, our basic proposal does not yet provide the suitable background for the modeling of replication, one of the basic operators from the original calculus, by means of which infinite processes are introduced and treated in a very simple way. In this paper we enrich our framework by introducing that operator. We obtain a simple and nice model in which the basic nets are still static and finite, since the dynamics of the systems can be covered by the adequate notion of marking, where all the copies generated by the application of the replication operator will live together, without interfering in an inadequate way
Multi-agent approach for visualisation of fuzzy systems

Complex fuzzy systems exist in many applications and effective visualisation is required to gain insights in the nature and working of these systems, especially in the implication of impreciseness, its propagation and impacts on the quality and reliability of the outcomes.  This paper presents a design of a visualisation system based on multi-agent approach with the aim to facilitate the organisation and flow of complex tasks, their inter-relationships and their interactions with users.  This design extends our previous work on the analysis of the fundamental ontologies which underpin the structure and requirements of fuzzy systems
Evolutionary approach to overcome initialization parameters in classification problems

Proceeding of: 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003 Maó, Menorca, Spain, June 3–6, 2003.The design of nearest neighbour classifiers is very dependent from some crucial parameters involved in learning, like the number of prototypes to use, the initial localization of these prototypes, and a smoothing parameter. These parameters have to be found by a trial and error process or by some automatic methods. In this work, an evolutionary approach based on Nearest Neighbour Classifier (ENNC), is described. Main property of this algorithm is that it does not require any of the above mentioned parameters. The algorithm is based on the evolution of a set of prototypes that can execute several operators in order to increase their quality in a local sense, and emerging a high classification accuracy for the whole classifier
Towards reactive navigation and attention skills for 3D intelligent characters

This paper presents a neural design which is able to provide
the necessary reactive navigation and attention skills for 3D embodied
agents (virtual humanoids or characters). Based on Grossberg’s
neural model of conditioning [6], as recently implemented by Chang
and Gaudiando [7], and according to the Adaptative Resonance Theory
(ART) and the neuroscientific concepts associated, the neural design
introduced has been divided in two main phases. Firstly, an environmentcategorization
phase, where an on-line pattern recognition and categorization
of the current agent sensory input data is carried out by a self
organizing neural network, which will finally provide the agent’s short
term memory layer(STM). Secondly, and based on the classical conditioning
paradigm, the model will associate the interesting STM states,
from the navigation or attention points of view, to finally simulate these
necessary skills for 3D characters or humanoids. Finally, we will show
some experimental navigational results, through the integration of the
model presented in 3D virtual environments.Partially supported by the GVA-project CTIDIB-2002-182 (Spain)
From continous behaviour to discrete knowledge

Proceeding of: 7th InternationalWork-Conference on Artificial and Natural Neural Networks, IWANN 2003, Maó, Menorca, Spain, June 3-6, 2003, Proceedings, Part IINeural networks have proven to be very powerful techniques for solving a wide range of tasks. However, the learned concepts are unreadable for humans. Some works try to obtain symbolic models from the networks, once these networks have been trained, allowing to understand the model by means of decision trees or rules that are closer to human understanding. The main problem of this approach is that neural networks output a continuous range of values, so even though a symbolic technique could be used to work with continuous classes, this output would still be hard to understand for humans. In this work, we present a system that is able to model a neural network behaviour by discretizing its outputs with a vector quantization approach, allowing to apply the symbolic method
Trusting collaboration in global computing systems

A significant characteristic of global computing is the need for secure interactions between highly mobile entities and the services in their environment. Moreover, these decentralised systems are also characterised by partial views over the state of the global environment, implying that we cannot guarantee verification of the properties of the mobile entity entering an unfamiliar domain. Secure in this context encompasses both the need for cryptographic security and the need for trust, on the part of both parties, that the interaction will function as expected. In this paper, we explore an architecture for interaction/collaboration in global computing systems. This architecture reflects the aspects of the trust lifecycle in three stages: trust formation, trust evolution and trust exploitation, forming a basis for risk assessment and interaction decisions
Proving Temporal Properties of Z Specifications Using Abstraction

This paper presents a systematic approach to proving temporal properties of arbitrary Z specifications. The approach involves (i) transforming the Z specification to an abstract temporal structure (or state transition system), (ii) applying a model checker to the temporal structure, (iii) determining whether the temporal structure is too abstract based on the model checking result and (iv) refining the temporal structure where necessary. The approach is based on existing work from the model checking literature, adapting it to Z
Compositional verification for object-Z

This paper presents a framework for compositional verification of Object-Z specifications. Its key feature is a proof rule based on decomposition of hierarchical Object-Z models. For each component in the hierarchy local properties are proven in a single proof step. However, we do not consider components in isolation. Instead, components are envisaged in the context of the referencing super-component and proof steps involve assumptions on properties of the sub-components. The framework is defined for Linear Temporal Logic (LTL
Composing Specifications Using Communication.

This paper develops a case study using the process algebra CSP to enable controlled interaction between B machines. This illustrates how B machines are essential components within a combined communicating system. The development steps used to build the case study are new: they are applications of theoretical results which allow us to focus on the external interface of a combined communicating system, compositionally verify it, and show that it is a refinement of a more abstract specification described in CSP. This allows safety and liveness properties to be established for combinations of communicating B machines
Transport in nanostructures: A comparison between nonequilibrium Green
  functions and density matrices

Stationary electric transport in semiconductor nanostructures is studied by
the method of nonequilibrium Green functions. In the case of sequential
tunneling the results are compared with density matrix theory, providing almost
identical results. Nevertheless, the method of Green functions is easier to
handle due to the availability of an absolute energy scale. It is demonstrated,
that the transport in complicated structures, like quantum cascade lasers, can
be described in reasonable agreement with experiment.Comment: 12 pages, to be published in Advances in Solid State Physics, ed. by
  B. Kramer (Springer, Berlin 2001
LILI Keystream Generator

A family of keystream generators, called the LILI keystream generators, is proposed for use in stream cipher applications and the security of these generators is investigated with respect to currently known attacks. The design is simple and scalable, based on two binary linear feedback shift registers combined in a simple way, using both irregular clocking and nonlinear functions. The design provides the basic security requirements such as a long period and high linear complexity, and is resistant to known cryptanalytic attacks
Finding secure curves with the Satoh-FGH algorithm and an early-abort strategy

International audienceThe use of elliptic curves in cryptography relies on the ability to count the number of points on a given curve. Before 1999, the SEA algorithm was the only efficient method known for random curves. Then Satoh proposed a new algorithm based on the canonical p-adic lift of the curve for p>=5. In an earlier paper, the authors extended Satoh's method to the case of characteristics two and three. This paper presents an implementation of the Satoh-FGH algorithm and its application to the problem of finding curves suitable for cryptography. By combining Satoh-FGH and an early-abort strategy based on SEA, we are able to find secure random curves in characteristic two in much less time than previously reported. In particular we can generate curves widely considered to be as secure as RSA-1024 in less than one minute each on a fast workstation
Decidability of properties of timed-arc Petri nets

Timed-arc Petri nets (TAPN’s) are not Turing powerful, because, in particular, they cannot simulate a counter with zero testing. Thus, we could think that this model does not increase significantly the expressiveness of untimed Petri nets. But this is not true; in a previous paper we have shown that the differences between them are big enough to make the reachability problem undecidable. On the other hand, coverability and boundedness are proved now to be decidable. This fact is a consequence of the close interrelationship between TAPN’s and transfer nets, for which similar results have been recently proved. Finally, we see that if dead tokens are defined as those that cannot be used for firing any transition in the future, we can detect these kind of tokens in an effective way
A hybrid MLP-PNN architecture for fast image superresolution

Proceedings of Joint International Conference ICANN/ICONIP 2003 Istanbul, Turkey, June 26–29, 2003The final publication is available at Springer via http://dx.doi.org/10.1007/3-540-44989-2_50Image superresolution methods process an input image sequence of a scene to obtain a still image with increased resolution. Classical approaches to this problem involve complex iterative minimization procedures, typically with high computational costs. In this paper is proposed a novel algorithm for superresolution that enables a substantial decrease in computer load. First, a probabilistic neural network architecture is used to perform a scattered-point interpolation of the image sequence data. The network kernel function is optimally determined for this problem by a multi-layer perceptron trained on synthetic data. Network parameters dependence on sequence noise level is quantitatively analyzed. This super-sampled image is spatially filtered to correct finite pixel size effects, to yield the final high-resolution estimate. Results on a real outdoor sequence are presented, showing the quality of the proposed method.This work has been partially supported by TIC2001-0572-C02-02 gran
Extracting Performers' Behaviors to Annotate Cases in a CBR System for Musical Tempo Transformations

Best Paper Award.\ud
\ud
The original publication is available at www.springerlink.comIn this paper we describe a method, based on the edit distance, to construct cases of musical performances by annotating them with the musical behavior of the performer. The cases constructed with this knowledge are used in Tempo-Express, a CBR system for applying tempo transformations to musical performances, preserving musical expressiveness.This research has been partially supported by the Spanish Ministry of Science and Technology under the project TIC 2000-1094-C02 "Tabasco: Content-based Audio Transformation using CBR"Peer reviewe
Refinement of higher-order logic programs

A refinement calculus provides a method for transforming specifications to executable code, maintaining the correctness of the code with respect to its specification. In this paper we extend the refinement calculus for logic programs to include higher-order programming capabilities in specifications and programs, such as procedures as terms and lambda abstraction. We use a higher-order type and term system to describe programs, and provide a semantics for the higher-order language and refinement. The calculus is illustrated by refinement examples
Towards a Generic Model for Situational Method Engineering

International audienceThe work presented in this paper is related to the area of Situational Method Engineering (SME), which focuses on project-specific method construction. We propose a generic process model supporting the integration of different existing SME approaches. This model shall help the method engineer either selecting one SME approach or combining several approaches that best fit the situation of the method engineering project at hand. The generic model presented in this paper already contains three SME techniques: (1) to assemble method chunks (2) to extend an existing method and (3) to generate a method by abstraction/instantiation of a model/meta-model. The paper presents and illustrates these three techniques and show how other SME techniques could be integrated in the model
Adaptive agents applied to intrusion detection

Proceeding of: Multi-agent systems and applications III : 3rd International Central and Eastern European Conference on Multi-Agent Systems, CEEMAS 2003 Prague, Czech Republic, June 16–18, 2003This paper proposes a system of agents that make predictions over the presence of intrusions. Some of the agents act as predictors implementing a given Intrusion Detection model, sniffing out the same traffic. An assessment agent weights the forecasts of such predictor agents, giving a final binary conclusion using a probabilistic model. These weights are continuously adapted according to the previous performance of each predictor agent. Other agent establishes if the prediction from the assessor agent was right or not, sending him back the results. This process is continually repeated and runs without human interaction. The effectiveness of our proposal is measured with the usual method applied in Intrusion Detection domain: Receiver Operating Characteristic curves (detection rate versus false alarm rate). Results of the adaptive agents applied to intrusion detection improve ROC curves as it is shown in this paper.Publicad
Improving genetic algorithms' efficiency using intelligent fitness functions

This article was accepted for publication in the series Lecture Notes in Computer Science. The final publication is available at http://link.springer.com/Genetic Algorithms are an effective way to solve optimisation\ud
problems. If the fitness test takes a long time to perform then the\ud
Genetic Algorithm may take a long time to execute. Using conventional\ud
fitness functions Approximately a third of the time may be spent testing\ud
individuals that have already been tested. Intelligent Fitness Functions\ud
can be applied to improve the efficiency of the Genetic Algorithm by\ud
reducing repeated tests. Three types of Intelligent Fitness Functions are\ud
introduced and compared against a standard fitness function The Intelligent\ud
Fitness Functions are shown to be more efficient
A study of order based genetic and evolutionary algorithms in combinatorial optimization problems

In Genetic and Evolutionary Algorithms (GEAs) one is faced with a given number of parameters, whose possible values are coded in a binary alphabet. With Order Based Representations (OBRs) the genetic information is kept by the order of the genes and not by its value. The application of OBRs to the Traveling Salesman Problem (TSP) is a well known technique to the GEA community. In this work one intends to show that this coding scheme can be used as an indirect representation, where the chromosome is the input for the decoder. The behavior of the GEA's operators is compared under benchmarks taken from the Combinatorial Optimization arena
Quantum Search on Bounded-Error Inputs

Suppose we have n algorithms, quantum or classical, each computing some
bit-value with bounded error probability. We describe a quantum algorithm that
uses O(sqrt{n}) repetitions of the base algorithms and with high probability
finds the index of a 1-bit among these n bits (if there is such an index). This
shows that it is not necessary to first significantly reduce the error
probability in the base algorithms to O(1/poly(n)) (which would require
O(sqrt{n}log n) repetitions in total). Our technique is a recursive
interleaving of amplitude amplification and error-reduction, and may be of more
general interest. Essentially, it shows that quantum amplitude amplification
can be made to work also with a bounded-error verifier. As a corollary we
obtain optimal quantum upper bounds of O(sqrt{N}) queries for all
constant-depth AND-OR trees on N variables, improving upon earlier upper bounds
of O(sqrt{N}polylog(N)).Comment: 9 pages Latex. To appear in Proceedings of ICALP 03. 2nd version:
  corrected affiliation of 2nd author (no other changes
A Novel Use of RBAC to Protect Privacy in Distributed Health Care Information Systems

This paper examines the access control requirements of distributed health care information networks. Since the electronic sharing of an individual's personal health information  requires their informed consent, health care information networks need an access control framework that can capture and enforce individual access policies tailored to the specific circumstances of each consumer. Role Based Access Control (RBAC) is examined as a candidate access control framework. While it is well suited to the task in many regards, we identify number of shortcomings, particularly in the range of access policy expression types that it can support. For efficiency and comprehensibility, access policies that grant access to a broad range of entities whilst explicitly denying it to subgroups of those entities need to be supported in health information networks. We argue that RBAC does not support policies of this type with sufficient flexibility and propose a novel adaptation of RBAC principles to address this shortcoming. We also describe a prototype distributed medical information system that embodies the improved RBAC model
WebML+ for Communication of Information Flows: An Empirical Study

In this paper, we have presented an empirical evaluation of WebML+, a high-level specification language for defining Web system information flows. The results provided an initial indication that WebML+ was indeed a useful tool. In brief, we found that participants could answer questions about information flows more correctly when they read the WebML+ model as compared to participants who read a textual description of the system. This led to our conclusion that users are able to understand a system based on a WebML+ model more consistently than when based on a textual description