pinecone/core-2020-05-10-deduplication huggingface dataset:
Evolutionary approaches for strain optimization using dynamic models under a metabolic engineering perspective

One of the purposes of Systems Biology is the quantitative
modeling of biochemical networks. In this effort, the use of dynamical
mathematical models provides for powerful tools in the prediction of the
phenotypical behavior of microorganisms under distinct environmental
conditions or subject to genetic modifications.
The purpose of the present study is to explore a computational environment
where dynamical models are used to support simulation and optimization
tasks. These will be used to study the effects of two distinct
types of modifications over metabolic models: deleting a few reactions
(knockouts) and changing the values of reaction kinetic parameters. In
the former case, we aim to reach an optimal knockout set, under a defined
objective function. In the latter, the same objective function is used, but
the aim is to optimize the values of certain enzymatic kinetic coefficients.
In both cases, we seek for the best model modifications that might lead to
a desired impact on the concentration of chemical species in a metabolic
pathway. This concept was tested by trying to maximize the production
of dihydroxyacetone phosphate, using Evolutionary Computation approaches.
As a case study, the central carbon metabolism of Escherichia
coli is considered. A dynamical model based on ordinary differential equations
is used to perform the simulations. The results validate the main
features of the approach
Chern character, loop spaces and derived algebraic geometry.

International audienceIn this note we present a work in progress whose main purpose is to establish a categorified version of sheaf theory. We present a notion of derived categorical sheaves, which is a categorified version of the notion of complexes of sheaves of modules on schemes, as well as its quasi-coherent and perfect versions. We also explain how ideas from derived algebraic geometry and higher category theory can be used in order to construct a Chern character for these categorical sheaves, which is a categorified version of the Chern character for perfect complexes with values in cyclic homology. Our construction uses in an essential way the derived loop space of a scheme X, which is a derived scheme whose theory of functions is closely related to cyclic homology of X. This work can be seen as an attempt to define algebraic analogs of elliptic objects and characteristic classes for them. The present text is an overview of a work in progress and details will appear elsewhere
On a taxonomy of delegation

Delegation, from the technical point of view, is widely considered as a potential approach in addressing the problem of providing dynamic access control decisions in activities with a high level of collaboration, either within a single security domain or across multiple security domains. Although delegation continues to attract significant attention from the research community, presently, there is no published work that presents a taxonomy of delegation concepts and models. This paper intends to address this gap by presenting a set of taxonomic criteria relevant to the concept of delegation and applies the taxonomy to a selection of significant \ud
delegation models published in the literature
Design of Composable Services

Service composition methods range from industry standard approaches based on Web Services and BPEL to Semantic Web approaches that rely on AI techniques to automate service discovery and composition. Service composition research mostly focuses on the dynamic (workflow) aspects of compositions. In this paper we consider the static component of service composition and discuss the importance of compatibility of service interfaces in ensuring the composability of services. Using a flight booking scenario example we show that reducing the granularity of services by decomposition into service operations with normalized interfaces produces compatible interfaces that facilitate service assembly. We then show how relational algebra can be used to represent service operations and provide a framework for service assembly
Evolving communication in embodied agents: Assessment and open challenges

In this Chapter we summarize the progresses that have recently been made in the study of the emergence of communication in artificial embodied agents along different dimensions, including the understanding of the adaptive roles of communication, the expressive power and organization complexity of signalling systems, the stability, robustness, and evolvability of communication, and the knowledge gain obtained with such models. Finally, we briefly discuss which we think are the most important open challenges for future research in this area
Asynchronous Multi-objective Optimisation in Unreliable Distributed Environments

This chapter examines the performance characteristics of both asynchronous and synchronous parallel particle swarm optimisation algorithms in heterogeneous, fault-prone environments. The chapter starts with a simple parallelisation paradigm, the Master-Slave model using Multi-Objective Particle Swarm Optimisation (MOPSO) in a heterogeneous environment. Extending the investigation to general, distributed environments, algorithm convergence is measured as a function of both iterations completed and time elapsed. Asynchronous particle updates are shown to perform comparably to synchronous updates in fault-free environments. When faults are introduced, the synchronous update method is shown to suffer significant performance drops, suggesting that at least partly asynchronous algorithms should be used in real-world environments. Finally, the issue of how to utilise newly available nodes, as well as the loss of existing nodes, is considered and two methods of generating new particles during algorithm execution are investigated.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Uncertainty based MDO of UAS using HAPMOEA

CFD has been successfully used in the optimisation of aerodynamic surfaces using a given set of parameters such as Mach numbers and angle of attack. While carrying out a multidisciplinary design optimisation one deals with situations where the parameters have some uncertain attached. Any optimisation carried out for fixed values of input parameters gives a design which may be totally unacceptable under off-design conditions. The challenge is to develop a robust design procedure which takes into account the fluctuations in the input parameters. In this work, we attempt this using a modified Taguchi approach. This is incorporated into an evolutionary algorithm with many features developed in house. The method is tested for an UCAV design which simultaneously handles aerodynamics, electromagnetics and maneuverability. Results demonstrate that the method has considerable potential. \u
Thai word segmentation with hidden Markov Model\ud
and decision tree\ud

The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper\ud
develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods
Clustering documents using a Wikipedia-based concept representation

This paper shows how Wikipedia and the semantic knowledge it contains can be exploited for document clustering. We first create a concept-based document representation by mapping the terms and phrases within documents to their corresponding articles (or concepts) in Wikipedia. We also developed a similarity measure that evaluates the semantic relatedness between concept sets for two documents. We test the concept-based representation and the similarity measure on two standard text document datasets. Empirical results show that although further optimizations could be performed, our approach already improves upon related techniques
Aggregated subset mining

acceptance rate = 33%The usual data mining setting uses the full amount of data to derive patterns for different purposes. Taking cues from machine learning techniques, we explore ways to divide the data into subsets, mine patterns on them and use post-processing techniques for acquiring the result set. Using the patterns as features for a classification task to evaluate their quality, we compare the different subset compositions, and selection techniques. The two main results -- that small independent sets are better suited than large amounts of data, and that uninformed selection techniques perform well -- can to a certain degree be explained by quantitative characteristics of the derived pattern sets.status: publishe
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data

Detecting outliers which are grossly different from or inconsistent
with the remaining dataset is a major challenge in real-world
KDD applications. Existing outlier detection methods are ineffective
on scattered real-world datasets due to implicit data patterns and
parameter setting issues. We define a novel Local Distance-based Outlier
Factor (LDOF) to measure the outlier-ness of objects in scattered
datasets which addresses these issues. LDOF uses the relative location
of an object to its neighbours to determine the degree to which
the object deviates from its neighbourhood. We present theoretical
bounds on LDOF’s false-detection probability. Experimentally, LDOF
compares favorably to classical KNN and LOF based outlier detection.
In particular it is less sensitive to parameter values
An Automated Meeting Assistant: A Tangible Mixed Reality Interface for the AMIDA Automatic Content Linking Device

We describe our approach to support ongoing meetings with an automated meeting assistant. The system based on the AMIDA Content Linking Device aims at providing relevant documents used in previous meetings for the ongoing meeting based on automatic speech recognition. Once the content linking device finds documents linked to a discussion about a similar subject in a previous meeting, it assumes they may be relevant for the current discussion as well. We believe that the way these documents are offered to the meeting participants is equally important as the way they are found. We developed a mixed reality, projection based user interface that lets the documents appear on the table tops in front of the meeting participants. They can hand them over to others or bring them onto the shared projection screen easily if they consider them relevant. Yet, irrelevant documents don't draw too much attention from the discussion. In this paper we describe the concept and implementation of this user interface and provide some preliminary results
MPLS label stacking on the line network

International audienceAll-Optical Label Switching (AOLS) is a new technology that performs forwarding without any Optical-Electrical-Optical (OEO) conversions. In this report, we study the problem of routing a set of requests in AOLS networks with the aim of minimizing the number of labels required to ensure the forwarding. In order to spare the label space, we consider label stacking, allowing the configuration of tunnels. We study particularly this network design problem when the network is a line. We provide an exact algorithm for the case in which all the requests have a common source and present some approximation algorithms and heuristics when an arbitrary number of sources are distributed over the line. We contrast the performance of our proposed algorithms by simulations., OPTx-editorial-board=yes, OPTx-proceedings=yes, OPTx-international-audience=ye
Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments

This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful calibration of simulation model parameters, the inevitable gap between simulation models and real-world conditions can be reduced. It concludes with guidelines for a methodology for model calibration and validation of sensor network simulation models
Backup Path Classification Based on Failure Risks for Efficient Backup Path Computation

In Lecture Notes in Computer Science n° 5550International audienceWe propose a new approach exploiting the failure risk (node, link or Shared Risk Link Group) structures to enhance the backup path computation. Upon failure, our approach classifies the backup paths into two categories: operative backup paths and inoperative backup paths. An operative backup path is an active backup path which really receives traffic of some affected communications while an inoperative backup path does not receive any traffic. With the observation that only the operative backup paths really participate to the recovery procedure, we enhance the backup path computation (1) by limiting the concurrence for the protection bandwidth allocations to the operative backup paths (instead of all the active backup paths like in the classical approaches) and (2) by reducing the set of failure risks that a backup path must bypass. Simulations shows that our approach improves the protection bandwidth allocations and decreases the ratio of rejected backup paths
Impact of misbehaviour on QoS in wireless mesh networks

Proceedings of: 8th International IFIP-TC 6 Networking Conference (Networking 2009), Aachen, Germany, May 11-15, 2009This paper analyzes the impact of misbehaviour on QoS provisioning in wireless mesh networks. Misbehaviour occurs when a network participant decides not to cooperate. Since cooperation is fundamental for distributed environments such as mesh networks, misbehaviour can be a serious threat to them. In this work, the authors focus on the IEEE 802.11 EDCA medium access function which provides QoS in mesh networks. Simulation studies have been performed to determine what realistic forms of misbehaviour can occur and what their impact is. From these results the most beneficial forms of MAC layer misbehaviour in multihop mesh networks are derived.European Community's Seventh Framework ProgramThe research leading to these results has received funding from the European Community's
Sixth Framework Programme under grant agreement n° 0384239 (NoE CONTENT). The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 214994.Publicad
CHAP : Enabling efficient hardware-based multiple hash schemes for IP lookup

Building a high performance IP lookup engine remains a challenge due to increasingly stringent throughput requirements and the growing size of IP tables. An emerging approach for IP lookup is the use of set associative memory architecture, which is basically a hardware implementation of an open addressing hash table with the property that each row of the hash table can be searched in one memory cycle. While open addressing hash tables, in general, provide good average-case search performance, their memory utilization and worst-case performance can degrade quickly due to bucket overflows. This paper presents a new simple hash probing scheme called CHAP (Content-based HAsh Probing) that tackles the hash overflow problem. In CHAP, the probing is based on the content of the hash table, thus avoiding the classical side effects of probing. We show through experimenting with real IP tables how CHAP can effectively deal with the overflow. © IFIP International Federation for Information Processing 2009
Automatic Methods for Analyzing Non-repudiation Protocole with an Active Intruder

International audienceNon-repudiation protocols have an important role in many areas where secured transactions with proofs of participation are necessary. Formal methods are clever and without error, therefore using them for verifying such protocols is crucial. In this purpose, we show how to partially represent non-repudiation as a combination of authentications on the Fair Zhou-Gollmann protocol. After discussing the limitations of this method, we define a new one based on the handling of the knowledge of protocol participants. This second method is general and of natural use, as it consists in adding simple annotations in the protocol specification. It is very easy to implement in tools able to handle participants knowledge. We have implemented it in the AVISPA Tool and analyzed the optimistic Cederquist-Corin-Dashti protocol, discovering two attacks. This extension of the AVISPA Tool for handling non-repudiation opens a highway to the specification of many other properties, without any more change in the tool itself
The Append-only Web Bulletin Board

A large number of papers on verifiable electronic voting that\ud
have appeared in the literature in recent years have relied heavily on the\ud
availability of an append-only web bulletin board. Despite this widespread\ud
requirement, however, the notion of an append-only web bulletin board\ud
remains somewhat vague, and no method of constructing such a bulletin\ud
board has been proposed.\ud
This paper fills the gap. We identify the required properties of an\ud
append-only web bulletin board, and introduce the concept of certified\ud
publishing of messages to the board. We show how such a board can be\ud
constructed in order to satisfy the properties we have identified.\ud
Finally, we consider how to extend the scheme to make the web bulletin\ud
board robust and able to offer assurance to writers of the inclusion\ud
of their messages.\ud
Although the work presented here has been inspired and motivated\ud
by the requirements of electronic voting systems, the web bulletin board\ud
is sufficiently general to allow use in other contexts
Use of ensemble based on GA for imbalance problem

In real-world applications, it has been observed that class imbalance (significant differences in class prior probabilities) may produce an important deterioration of the classifier performance, in particular with patterns belonging to the less represented classes. One method to tackle this problem consists to resample the original training set, either by over-sampling the minority class and/or under-sampling the majority class. In this paper, we propose two ensemble models (using a modular neural network and the nearest neighbor rule) trained on datasets under-sampled with genetic algorithms. Experiments with real datasets demonstrate the effectiveness of the methodology here propose
Boxed pervasive games: an experience with user-created pervasive games

Pervasive games are rapidly maturing - from early research experiments with locative games we now start to see a range of commercial projects using locative and pervasive technology to create technology-supported pervasive games. In this paper we report on our experiences in transferring the successful involvement of players in computer games to modding for pervasive games. We present the design process, the enabling tools and two sample games provided in boxes to end users. Finally we discuss how our findings inform the design of modding tools for a pervasive game community of the future
Performance issues in optical burst/packet switching

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-01524-3_8This chapter summarises the activities on optical packet switching (OPS) and optical burst switching (OBS) carried out by the COST 291 partners in the last 4 years. It consists of an introduction, five sections with contributions on five different specific topics, and a final section dedicated to the conclusions. Each section contains an introductive state-of-the-art description of the specific topic and at least one contribution on that topic. The conclusions give some points on the current situation of the OPS/OBS paradigms
An empirical evaluation of the effectiveness of different types of predictor attributes in protein function prediction.

Many classification schemes for defining protein functions, such as Gene Ontology (GO), are organised in a hierarchical structure. Nodes near the root of the hierarchy represent general functions while nodes near the leaves of the hierarchy represent more specific functions, giving the flexibility to specify at which level the protein will be annotated. In a data mining perspective, hierarchical structures present a more challenging problem, since the relationship between nodes need to be considered. This chapter presents an empirical evaluation of different protein representations for protein function prediction in terms of maximizing predictive accuracy, investigating which type of representation is more suitable for different levels of the GO hierarchy
Slepian functions and their use in signal estimation and spectral
  analysis

It is a well-known fact that mathematical functions that are timelimited (or
spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the
finite precision of measurement and computation unavoidably bandlimits our
observation and modeling scientific data, and we often only have access to, or
are only interested in, a study area that is temporally or spatially bounded.
In the geosciences we may be interested in spectrally modeling a time series
defined only on a certain interval, or we may want to characterize a specific
geographical area observed using an effectively bandlimited measurement device.
It is clear that analyzing and representing scientific data of this kind will
be facilitated if a basis of functions can be found that are "spatiospectrally"
concentrated, i.e. "localized" in both domains at the same time. Here, we give
a theoretical overview of one particular approach to this "concentration"
problem, as originally proposed for time series by Slepian and coworkers, in
the 1960s. We show how this framework leads to practical algorithms and
statistically performant methods for the analysis of signals and their power
spectra in one and two dimensions, and on the surface of a sphere.Comment: Submitted to the Handbook of Geomathematics, edited by Willi Freeden,
  Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verla