A finite state model for on-line analytical processing in triadic contexts

About ten years ago, triadic contexts were presented by Lehmann and Wille as an extension of Formal Concept Analysis. However, they have rarely been used up to now, which may be due to the rather complex structure of the resulting diagrams. In this paper, we go one step back and discuss how traditional line diagrams of standard (dyadic) concept lattices can be used for exploring and navigating triadic data. Our approach is inspired by the slice & dice paradigm of On-Line-Analytical Processing (OLAP). We recall the basic ideas of OLAP, and show how they may be transferred to triadic contexts. For modeling the navigation patterns a user might follow, we use the formalisms of finite state machines. In order to present the benefits of our model, we show how it can be used for navigating the IT Baseline Protection Manual of the German Federal Office for Information Security.

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

An observing system simulation experiment for climate monitoring with GNSS radio occulation data: setup and testbed study

The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

GODIVA2: interactive visualization of environmental data on the Web

GODIVA2 is a dynamic website that provides visual access to several terabytes of physically distributed, four-dimensional environmental data. It allows users to explore large datasets interactively without the need to install new software or download and understand complex data. Through the use of open international standards, GODIVA2 maintains a high level of interoperability with third-party systems, allowing diverse datasets to be mutually compared. Scientists can use the system to search for features in large datasets and to diagnose the output from numerical simulations and data processing algorithms. Data providers around Europe have adopted GODIVA2 as an INSPIRE-compliant dynamic quick-view system for providing visual access to their data.

The world at one's fingertips: interactive interpretation of environmental data

This chapter introduces the latest practices and technologies in the interactive interpretation of environmental data. With environmental data becoming ever larger, more diverse and more complex, there is a need for a new generation of tools that provides new capabilities over and above those of the standard workhorses of science. These new tools aid the scientist in discovering interesting new features (and also problems) in large datasets by allowing the data to be explored interactively using simple, intuitive graphical tools. In this way, new discoveries are made that are commonly missed by automated batch data processing. This chapter discusses the characteristics of environmental science data, common current practice in data analysis and the supporting tools and infrastructure. New approaches are introduced and illustrated from the points of view of both the end user and the underlying technology. We conclude by speculating as to future developments in the field and what must be achieved to fulfil this vision.

Case study on the maintenance of a construction monitoring using USN-based data acquisition

In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations.

A cross layer protocol for energy aware and critical data delivered applications using Wireless Sensor Networks

Environment monitoring applications using Wireless Sensor Networks (WSNs) have had a lot of attention in recent years. In much of this research tasks like sensor data processing, environment states and events decision making and emergency message sending are done by a remote server. A proposed cross layer protocol for two different applications where, reliability for delivered data, delay and life time of the network need to be considered, has been simulated and the results are presented in this paper. A WSN designed for the proposed applications needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from source nodes to the sink. A cross layer based on the design given in [1] has been extended and simulated for the proposed applications, with new features, such as routes discovery algorithms added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability.

Escalabilidade Paralela de um Algoritmo de Migração Reversa no Tempo (RTM) Pré-empilhamento

The seismic method is of extreme importance in geophysics. Mainly associated with oil exploration, this line of research focuses most of all investment in this area. The acquisition, processing and interpretation of seismic data are the parts that instantiate a seismic study. Seismic processing in particular is focused on the imaging that represents the geological structures in subsurface. Seismic processing has evolved significantly in recent decades due to the demands of the oil industry, and also due to the technological advances of hardware that achieved higher storage and digital information processing capabilities, which enabled the development of more sophisticated processing algorithms such as the ones that use of parallel architectures. One of the most important steps in seismic processing is imaging. Migration of seismic data is one of the techniques used for imaging, with the goal of obtaining a seismic section image that represents the geological structures the most accurately and faithfully as possible. The result of migration is a 2D or 3D image which it is possible to identify faults and salt domes among other structures of interest, such as potential hydrocarbon reservoirs. However, a migration fulfilled with quality and accuracy may be a long time consuming process, due to the mathematical algorithm heuristics and the extensive amount of data inputs and outputs involved in this process, which may take days, weeks and even months of uninterrupted execution on the supercomputers, representing large computational and financial costs, that could derail the implementation of these methods. Aiming at performance improvement, this work conducted the core parallelization of a Reverse Time Migration (RTM) algorithm, using the parallel programming model Open Multi-Processing (OpenMP), due to the large computational effort required by this migration technique. Furthermore, analyzes such as speedup, efficiency were performed, and ultimately, the identification of the algorithmic scalability degree with respect to the technological advancement expected by future processors

Processamento e interpretação de dados 2D e 3D de GPR :aplicações no imageamento de feições kársticas e estruturas de dissolução no campo de petróleo de Fazenda Belém-CE

In Fazenda Belém oil field (Potiguar Basin, Ceará State, Brazil) occur frequently sinkholes and sudden terrain collapses associated to an unconsolidated sedimentary cap covering the Jandaíra karst. This research was carried out in order to understand the mechanisms of generation of these collapses. The main tool used was Ground Penetrating Radar (GPR). This work is developed twofold: one aspect concerns methodology improvements in GPR data processing whilst another aspect concerns the geological study of the Jandaíra karst. This second aspect was strongly supported both by the analysis of outcropping karst structures (in another regions of Potiguar Basin) and by the interpretation of radargrams from the subsurface karst in Fazenda Belém. It was designed and tested an adequate flux to process GPR data which was adapted from an usual flux to process seismic data. The changes were introduced to take into account important differences between GPR and Reflection Seismic methods, in particular: poor coupling between source and ground, mixed phase of the wavelet, low signal-to-noise ratio, monochannel acquisition, and high influence of wave propagation effects, notably dispersion. High frequency components of the GPR pulse suffer more pronounced effects of attenuation than low frequency components resulting in resolution losses in radargrams. In Fazenda Belém, there is a stronger need of an suitable flux to process GPR data because both the presence of a very high level of aerial events and the complexity of the imaged subsurface karst structures. The key point of the processing flux was an improvement in the correction of the attenuation effects on the GPR pulse based on their influence on the amplitude and phase spectra of GPR signals. In low and moderate losses dielectric media the propagated signal suffers significant changes only in its amplitude spectrum; that is, the phase spectrum of the propagated signal remains practically unaltered for the usual travel time ranges. Based on this fact, it is shown using real data that the judicious application of the well known tools of time gain and spectral balancing can efficiently correct the attenuation effects. The proposed approach can be applied in heterogeneous media and it does not require the precise knowledge of the attenuation parameters of the media. As an additional benefit, the judicious application of spectral balancing promotes a partial deconvolution of the data without changing its phase. In other words, the spectral balancing acts in a similar way to a zero phase deconvolution. In GPR data the resolution increase obtained with spectral balancing is greater than those obtained with spike and predictive deconvolutions. The evolution of the Jandaíra karst in Potiguar Basin is associated to at least three events of subaerial exposition of the carbonatic plataform during the Turonian, Santonian, and Campanian. In Fazenda Belém region, during the mid Miocene, the Jandaíra karst was covered by continental siliciclastic sediments. These sediments partially filled the void space associated to the dissolution structures and fractures. Therefore, the development of the karst in this region was attenuated in comparison to other places in Potiguar Basin where this karst is exposed. In Fazenda Belém, the generation of sinkholes and terrain collapses are controlled mainly by: (i) the presence of an unconsolidated sedimentary cap which is thick enough to cover completely the karst but with sediment volume lower than the available space associated to the dissolution structures in the karst; (ii) the existence of important structural of SW-NE and NW-SE alignments which promote a localized increase in the hydraulic connectivity allowing the channeling of underground water, thus facilitating the carbonatic dissolution; and (iii) the existence of a hydraulic barrier to the groundwater flow, associated to the Açu-4 Unity. The terrain collapse mechanisms in Fazenda Belém occur according to the following temporal evolution. The meteoric water infiltrates through the unconsolidated sedimentary cap and promotes its remobilization to the void space associated with the dissolution structures in Jandaíra Formation. This remobilization is initiated at the base of the sedimentary cap where the flow increases its abrasion due to a change from laminar to turbulent flow regime when the underground water flow reaches the open karst structures. The remobilized sediments progressively fill from bottom to top the void karst space. So, the void space is continuously migrated upwards ultimately reaching the surface and causing the sudden observed terrain collapses. This phenomenon is particularly active during the raining season, when the water table that normally is located in the karst may be temporarily located in the unconsolidated sedimentary cap

Aquisição, processamento e análise de dados de sísmica de alta resolução na plataforma continental norte do Rio Grande do Norte: Vale inciso do rio açu

On the modern Continental Shelf to the north of Rio Grande do Norte state (NE Brazil) is located a paleo-valley, submerged during the last glacial sea-level lowstand, that marks continuation of the most important river of this area (Açu River). Despite the high level of exploration activity of oil industry, there is few information about shallow stratigraphy. Aiming to fill this gap, situated on the Neogene, was worked a marine seismic investigation, the development of a processing flow for high resolution data seismic, and the recognition of the main feature morphology of the study area: the incised valley of the River Açu. The acquisition of shallow seismic data was undertaken in conjunction with the laboratory of Marine Geology/Geophysics and Environmental Monitoring - GGEMMA of Federal University of Rio Grande do Norte UFRN, in SISPLAT project, where the geomorphological structure of the Rio paleovale Açu was the target of the investigation survey. The acquisition of geophysical data has been over the longitudinal and transverse sections, which were subsequently submitted to the processing, hitherto little-used and / or few addressed in the literature, which provided a much higher quality result with the raw data. Once proposed for the flow data was developed and applied to the data of X-Star (acoustic sensor), using available resources of the program ReflexW 4.5 A surface fluvial architecture has been constructed from the bathymetric data and remote sensing image fused and draped over Digital Elevation Models to create three-dimensional (3D) perspective views that are used to analyze the 3D geometry geological features and provide the mapping morphologically defined. The results are expressed in the analysis of seismic sections that extend over the region of the continental shelf and upper slope from mouth of the Açu River to the shelf edge, providing the identification / quantification of geometrical features such as depth, thickness, horizons and units seismic stratigraphyc area, with emphasis has been placed on the palaeoenvironmental interpretation of discordance limit and fill sediment of the incised valley, control by structural elements, and marked by the influence of changes in the sea level. The interpretation of the evolution of this river is worth can bring information to enable more precise descriptions and interpretations, which describes the palaeoenvironmental controls influencing incised valley evolution and preservation to provide a better comprehensive understanding of this reservoir analog system

Aplicação de softwares livres no Processamento de dados sísmicos de alta resolução

The increasing use of shallow seismic methods of high resolution, for investigations of geological problems, environmental or industrial, has impelled the development of techniques, flows and computational algorithms. The practice of applying techniques for processing this data, until recently it wasn t used and the interpretation of the data was made as they were acquired. In order to facilitate and contribute to the improvement of the practices adopted, was developed a free graphical application and open source, called OpenSeismic which is based on free software Seismic Un*x, widely used in the treatment of conventional seismic data used in the exploration of hydrocarbon reservoirs. The data used to validate the initiative were marine seismic data of high resolution, acquired by the laboratory of Geology and Marine Geophysics and Environmental Monitoring - GGEMMA, of the Federal University of Rio Grande do Norte UFRN, for the SISPLAT Project, located at the region of paleo-valley of the Rio Acu. These data were submitted to the processing flow developed by Gomes (2009), using the free software developed in this work, the OpenSeismic, as well other free software, the Seismic Un*x and the commercial software ProMAX, where despite its peculiarities has presented similar results

Caracterização geomorfológica e paleogeográfica da plataforma continental adjacente a foz do Rio Apodi-Mossoró, RN/Brasil

The brazilian marginal basins have a huge potential to generate and accumulate petroleum. Incised valleys which are eroded in response to a fall of relative sea level are related to potential reservoir as well, modern drowned-valley estuaries serve as harbors to petroleum and salt industries, fisheries, waste-disposal sites and recreational areas for a significant fraction of the world s population. The combined influence of these factors has produced a dramatic increase in research on modern and ancient incised-valley systems. This research is one expression of this interest. The integrated use of satellites images and high resolution seismic (bathymetry, sides scan sonar) was used on the Apodi River mouth-RN to characterizes the continental shelf This area is located at the Potiguar Basin in the NE Brazilian Equatorial Atlantic margin. Through bathymetric and side scan sonar data processing, a digital Terrain Model was developed, and a detailed geomorphologic analysis was performed. In this way was possible to recognize the geomorphologic framework and differents sismofacies, which may influence this area. A channel extending from the ApodiMossoró river mouth to the shelf edge dominates the investigated area. This structure can be correlated with the former river valley developed during the late Pleistocene sea level fall. This channel has two main directions (NW-SE and NE-SW) probably controlled by the Potiguar Basin structures. The western margin of the channel is relatively steep and pronounced whereas the eastern margin consists only of a gentle slope. Longitudinal bedforms and massive ridges also occur. The first are formed doe to the shelf sediment rework and the reef-like structures probably are relics of submerged beachrock-lines indicating past shoreline positions during the deglacial sea-level rise. The sub-bottom seismic data allow the identification of different sismic patterns and a marcant discontinuity, interpreted as the Upper

A software to process daily solar radiation data

This work presents one software developed to process solar radiation data. This software can be used in meteorological and climatic stations, and also as a support for solar radiation measurements in researches of solar energy availability allowing data quality control, statistical calculations and validation of models, as well as ease interchanging of data. (C) 1999 Elsevier B.V. Ltd. All rights reserved.

Control of thermal damage in grinding by digital signal processing of raw acoustic emission

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

Common architecture for discrete wavelet transform analysis and synthesis with sequential and constant processing elements

This paper adresses the problem on processing biological data such as cardiac beats, audio and ultrasonic range, calculating wavelet coefficients in real time, with processor clock running at frequency of present ASIC's and FPGA. The Paralell Filter Architecture for DWT has been improved, calculating wavelet coefficients in real time with hardware reduced to 60%. The new architecture, which also processes IDWT, is implemented with the Radix-2 or the Booth-Wallace Constant multipliers. Including series memory register banks, one integrated circuit Signal Analyzer, ultrasonic range, is presented.