A Wireless Mesh Network NS-3 Simulation Model: Implementation and Performance Comparison With a Real Test-Bed

Wireless mesh networks present an attractive communication solution for various research and industrial projects. However, in many cases, the appropriate preliminary calculations which allow predicting the network behavior have to be made before the actual deployment. For such purposes, network simulation environments emulating the real network operation are often used. Within this paper, a behavior comparison of real wireless mesh network (based on 802.11s amendment) and the simulated one has been performed. The main objective of this work is to measure performance parameters of a real 802.11s wireless mesh network (average UDP throughput and average one-way delay) and compare the derived results with characteristics of a simulated wireless mesh network created with the NS-3 network simulation tool. Then, the results from both networks are compared and the corresponding conclusion is made. The corresponding results were derived from simulation model and real-worldtest-bed, showing that the behavior of both networks is similar. It confirms that the NS-3 simulation model is accurate and can be used in further research studies.

Comunicación entre los componentes de un sistema de detección de ataques coordinados

Aquest projecte consisteix en la implementació i avaluació d’una infraestructura de comunicacions per a una plataforma de detecció d’atacs coordinats, basada en el paradigma publicador/subscriptor per a l’intercanvi de missatges IDMEF. Per implementar aquest sistema s’ha fet servir xmlBlaster i s’han desenvolupat les interfícies necessàries per a fer transparent l’accés a la informació de la xarxa de comunicacions. El resultat és una plataforma escalable que permet l’intercanvi eficient de informació entre els diferents elements distribuïts del sistema de detecció.

Artificial neural network study of whole-cell bacterial bioreporter response determined using fluorescence flow cytometry.

Genetically engineered bioreporters are an excellent complement to traditional methods of chemical analysis. The application of fluorescence flow cytometry to detection of bioreporter response enables rapid and efficient characterization of bacterial bioreporter population response on a single-cell basis. In the present study, intrapopulation response variability was used to obtain higher analytical sensitivity and precision. We have analyzed flow cytometric data for an arsenic-sensitive bacterial bioreporter using an artificial neural network-based adaptive clustering approach (a single-layer perceptron model). Results for this approach are far superior to other methods that we have applied to this fluorescent bioreporter (e.g., the arsenic detection limit is 0.01 microM, substantially lower than for other detection methods/algorithms). The approach is highly efficient computationally and can be implemented on a real-time basis, thus having potential for future development of high-throughput screening applications.

An approach to vision-based station keeping for an unmanned underwater vehicle

This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

Disentangling the attention network test: behavioral, event related potentials, and neural source analyses.

BACKGROUND The study of the attentional system remains a challenge for current neuroscience. The "Attention Network Test" (ANT) was designed to study simultaneously three different attentional networks (alerting, orienting, and executive) based in subtraction of different experimental conditions. However, some studies recommend caution with these calculations due to the interactions between the attentional networks. In particular, it is highly relevant that several interpretations about attentional impairment have arisen from these calculations in diverse pathologies. Event related potentials (ERPs) and neural source analysis can be applied to disentangle the relationships between these attentional networks not specifically shown by behavioral measures. RESULTS This study shows that there is a basic level of alerting (tonic alerting) in the no cue (NC) condition, represented by a slow negative trend in the ERP trace prior to the onset of the target stimuli. A progressive increase in the CNV amplitude related to the amount of information provided by the cue conditions is also shown. Neural source analysis reveals specific modulations of the CNV related to a task-related expectancy presented in the NC condition; a late modulation triggered by the central cue (CC) condition and probably representing a generic motor preparation; and an early and late modulation for spatial cue (SC) condition suggesting specific motor and sensory preactivation. Finally, the first component in the information processing of the target stimuli modulated by the interaction between orienting network and the executive system can be represented by N1. CONCLUSIONS The ANT is useful as a paradigm to study specific attentional mechanisms and their interactions. However, calculation of network effects is based in subtractions with non-comparable experimental conditions, as evidenced by the present data, which can induce misinterpretations in the study of the attentional capacity in human subjects.

Guiding students through competence-based educational material

Student guidance is an always desired characteristic in any educational system, butit represents special difficulty if it has to be deployed in an automated way to fulfilsuch needs in a computer supported educational tool. In this paper we explorepossible avenues relying on machine learning techniques, to be included in a nearfuture -in the form of a tutoring navigational tool- in a teleeducation platform -InterMediActor- currently under development. Since no data from that platform isavailable yet, the preliminary experiments presented in this paper are builtinterpreting every subject in the Telecommunications Degree at Universidad CarlosIII de Madrid as an aggregated macro-competence (following the methodologicalconsiderations in InterMediActor), such that marks achieved by students can beused as data for the models, to be replaced in a near future by real data directlymeasured inside InterMediActor. We evaluate the predictability of students qualifications, and we deploy a preventive early detection system -failure alert-, toidentify those students more prone to fail a certain subject such that correctivemeans can be deployed with sufficient anticipation.

A Computer Based Information System for County Equipment Cost Records, Interim Report, HR-173, 1975

This report describes the work accomplished to date on research project HR-173, A Computer Based Information System for County Equipment Cost Records, and presents the initial design for this system. The specific topics discussed here are findings from the analysis of information needs, the system specifications developed from these findings, and the proposed system design based upon the system specifications. The initial system design will include tentative input designs for capturing input data, output designs to show the output formats and the items to be output for use in decision making, file design showing the organization of information to be kept on each piece of equipment in the computer data file, and general system design explaining how the entire system will operate. The Steering Committee appointed by Iowa Highway Research Board is asked to study this report, make appropriate suggestions, and give approval to the proposed design subject to any suggestions made. This approval will permit the designer to proceed promptly with the development of the computer program implementation phase of the design.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

Tietoturvainformaation ja -tapahtumien hallinta PCI DSS -standardissa

Työn keskeisimpänä tavoitteena on tutkia SIEM-järjestelmien (Security Information and Event Management) käyttömahdollisuuksia PCI DSS -standardissa (Payment Card IndustryData Security Standard) lähtökohtaisesti ratkaisutoimittajan näkökulmasta. Työ on tehty Cygate Oy:ssä. SIEM on uusi tietoturvan ratkaisualue, jonka käyttöönottoa vauhdittavat erilaiset viralliset sääntelyt kuten luottokorttiyhtiöiden asettama PCI DSS -standardi. SIEM-järjestelmien avulla organisaatiot pystyvät keräämään valmistajariippumattomasti verkon systeemikomponenteista tapahtumatietoja, joiden avulla pystytään näkemään keskitetysti, mitä verkossa on tapahtunut. SIEM:ssa käsitellään sekä historiapohjaisia että reaaliaikaisia tapahtumia ja se toimii organisaatioiden keskitettynä tietoturvaprosessia tukevana hallintatyökaluna. PCI DSS -standardi on hyvin yksityiskohtainen ja sen vaatimusten täyttäminen ei ole yksinkertaista. Vaatimuksenmukaisuutta ei saavuteta hetkessä, vaan siihen liittyvä projekti voi kestää viikoista kuukausiin. Standardin yksi haasteellisimmista asioista on keskitetty lokien hallinta. Maksukorttitietoja käsittelevien ja välittävien organisaatioiden on kerättävä kaikki audit-lokit eri järjestelmistä, jotta maksukorttitietojen käyttöä pystytään luottamuksellisesti seuraamaan. Standardin mukaan organisaatioiden tulee käyttää myös tunkeutumisen ja haavoittuvuuksien havainnointijärjestelmiä mahdollisten tietomurtojen havaitsemiseksi ja estämiseksi. SIEM-järjestelmän avulla saadaan täytettyä PCI DSS -standardin vaativimpia lokien hallintaan liittyviä vaatimuksia ja se tuo samallamonia yksityiskohtaisia parannuksia tukemaan muita standardin vaatimuskohtia. Siitä voi olla hyötyä mm. tunkeutumisen ja haavoittuvuuksien havainnoinnissa. SIEM-järjestelmän hyödyntäminen standardin apuna on kuitenkin erittäin haasteellista. Käyttöönotto vaatii tarkkaa etukäteissuunnittelua ja kokonaisuuksien ymmärtämistä niin ratkaisutoimittajan kuin ratkaisun käyttöönottajan puolelta.

Sensitive photonic system to measure oxidative potential of airborne nanoparticles and ROS levels in exhaled air

A photonic system has been developed that enables sensitive quantitative determination of reactive oxygen species (ROS) - mainly hydrogen peroxide (H2O2) - in aerosol samples such as airborne nanoparticles and exhaled air from patients. The detection principle relies on the amplification of the absorbance under multiple scattering conditions due to optical path lengthening [1] and [2]. In this study, the presence of cellulose membrane that acts as random medium into the glass optical cell considerably improved the sensitivity of the detection based on colorimetric FOX assay (FeII/orange xylenol). Despite the loss of assay volume (cellulose occupies 75% of cell volume) the limit of detection is enhanced by one order of magnitude reaching the value of 9 nM (H2O2 equivalents). Spectral analysis is performed automatically with a periodicity of 5 to 15 s, giving rise to real-time ROS measurements. Moreover, the elution of air sample into the collection chamber via a micro-diffuser (impinger) enables quantitative determination of ROS contained in or generated from airborne samples. As proof-of-concept the photonic ROS detection system was used in the determination of both ROS generated from traffic pollution and ROS contained in the exhaled breath as lung inflammation biomarkers.

LOW COST ANALYZER FOR THE DETERMINATION OF PHOSPHORUS BASED ON OPEN-SOURCE HARDWARE AND PULSED FLOWS

The need for automated analyzers for industrial and environmental samples has triggered the research for new and cost-effective strategies of automation and control of analytical systems. The widespread availability of open-source hardware together with novel analytical methods based on pulsed flows have opened the possibility of implementing standalone automated analytical systems at low cost. Among the areas that can benefit from this approach are the analysis of industrial products and effluents and environmental analysis. In this work, a multi-pumping flow system is proposed for the determination of phosphorus in effluents and polluted water samples. The system employs photometric detection based on the formation of molybdovanadophosphoric acid, and the fluidic circuit is built using three solenoid micropumps. The detection is implemented with a low cost LED-photodiode photometric detection system and the whole system is controlled by an open-source Arduino Uno microcontroller board. The optimization of the timing to ensure the color development and the pumping cycle is discussed for the proposed implementation. Experimental results to evaluate the system behavior are presented verifying a linear relationship between the relative absorbance and the phosphorus concentrations for levels as high as 50 mg L-1.

Identification and characterisation of a novel adhesin of Streptococcus suis and its use as a target of adhesion inhibition and bacterial detection

Streptococcus suis is an important pig pathogen but it is also zoonotic, i.e. capable of causing diseases in humans. Human S. suis infections are quite uncommon but potentially life-threatening and the pathogen is an emerging public health concern. This Gram-positive bacterium possesses a galabiose-specific (Galalpha1−4Gal) adhesion activity, which has been studied for over 20 years. P-fimbriated Escherichia coli−bacteria also possess a similar adhesin activity targeting the same disaccharide. The galabiose-specific adhesin of S. suis was identified by an affinity proteomics method. No function of the protein identified was formerly known and it was designated streptococcal adhesin P (SadP). The peptide sequence of SadP contains an LPXTG-motif and the protein was proven to be cell wall−anchored. SadP may be multimeric since in SDS-PAGE gel it formed a protein ladder starting from about 200 kDa. The identification was confirmed by producing knockout strains lacking functional adhesin, which had lost their ability to bind to galabiose. The adhesin gene was cloned in a bacterial expression host and properties of the recombinant adhesin were studied. The galabiose-binding properties of the recombinant protein were found to be consistent with previous results obtained studying whole bacterial cells. A live-bacteria application of surface plasmon resonance was set up, and various carbohydrate inhibitors of the galabiose-specific adhesins were studied with this assay. The potencies of the inhibitors were highly dependent on multivalency. Compared with P-fimbriated E. coli, lower concentrations of galabiose derivatives were needed to inhibit the adhesion of S. suis. Multivalent inhibitors of S. suis adhesion were found to be effective at low nanomolar concentrations. To specifically detect galabiose adhesin−expressing S. suis bacteria, a technique utilising magnetic glycoparticles and an ATP bioluminescence bacterial detection system was also developed. The identification and characterisation of the SadP adhesin give valuable information on the adhesion mechanisms of S. suis, and the results of this study may be helpful for the development of novel inhibitors and specific detection methods of this pathogen.

Detection of renal dysfunction based on serum creatinine levels in a Brazilian community: the Bambuí Health and Ageing Study

There are few population-based studies of renal dysfunction and none conducted in developing countries. In the present study the prevalence and predictors of elevated serum creatinine levels (SCr > or = 1.3 mg/dl for men and 1.1 mg/dl for women) were determined among Brazilian adults (18-59 years) and older adults (>60 years). Participants included all older adults (N = 1742) and a probabilistic sample of adults (N = 818) from Bambuí town, MG, Southeast Brazil. Predictors were investigated using multiple logistic regression. Mean SCr levels were 0.77 ± 0.15 mg/dl for adults, 1.02 ± 0.39 mg/dl for older men, and 0.81 ± 0.17 mg/dl for older women. Because there were only 4 cases (0.48%) with elevated SCr levels among adults, the analysis of elevated SCr levels was restricted to older adults. The overall prevalence of elevated SCr levels among the elderly was 5.09% (76/1494). The prevalence of hypercreatinemia increased significantly with age (chi² = 26.17, P = 0.000), being higher for older men (8.19%) than for older women (5.29%, chi² = 5.00, P = 0.02). Elevated SCr levels were associated with age 70-79 years (odds ratio [OR] = 2.25, 95% confidence interval [CI]: 1.15-4.42), hypertension (OR = 3.04, 95% CI: 1.34-6.92), use of antihypertensive drugs (OR = 2.46, 95% CI: 1.26-4.82), chest pain (OR = 3.37, 95% CI: 1.31-8.74), and claudication (OR = 3.43, 95% CI: 1.30-9.09) among men, and with age >80 years (OR = 4.88, 95% CI: 2.24-10.65), use of antihypertensive drugs (OR = 4.06, 95% CI: 1.67-9.86), physical inactivity (OR = 2.11, 95% CI: 1.11-4.02) and myocardial infarction (OR = 3.89, 95% CI: 1.58-9.62) among women. The prevalence of renal dysfunction observed was much lower than that reported in other population-based studies, but predictors were similar. New investigations are needed to confirm the variability in prevalence and associated factors of renal dysfunction among populations.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.