A new approach to content-based file type detection

File type identification and file type clustering may be difficult tasks that have an increasingly importance in the field of computer and network security. Classical methods of file type detection including considering file extensions and magic bytes can be easily spoofed. Content-based file type detection is a newer way that is taken into account recently. In this paper, a new content-based method for the purpose of file type detection and file type clustering is proposed that is based on the PCA and neural networks. The proposed method has a good accuracy and is fast enough.Comment: 6 Pages, 5 Figure, 2 Table

Comprehensive experimental analysis of nonlinear dynamics in an optically-injected semiconductor laser

We present the first comprehensive experimental study, to our knowledge, of the routes between nonlinear dynamics induced in a semiconductor laser under external optical injection based on an analysis of time-averaged measurements of the optical and RF spectra and phasors of real-time series of the laser output. The different means of analysis are compared for several types of routes and the benefits of each are discussed in terms of the identification and mapping of the nonlinear dynamics. Finally, the results are presented in a novel audio/video format that describes the evolution of the dynamics with the injection parameters. © 2011 Author(s)

Fast Recompilation of Object Oriented Modules

Once a program file is modified, the recompilation time should be minimized, without sacrificing execution speed or high level object oriented features. The recompilation time is often a problem for the large graphical interactive distributed applications tackled by modern OO languages. A compilation server and fast code generator were developed and integrated with the SRC Modula-3 compiler and Linux ELF dynamic linker. The resulting compilation and recompilation speedups are impressive. The impact of different language features, processor speed, and application size are discussed

FAST : a fault detection and identification software tool

The aim of this work is to improve the reliability and safety of complex critical control systems by contributing to the systematic application of fault diagnosis. In order to ease the utilization of fault detection and isolation (FDI) tools in the industry, a systematic approach is required to allow the process engineers to analyze a system from this perspective. In this way, it should be possible to analyze this system to find if it provides the required fault diagnosis and redundancy according to the process criticality. In addition, it should be possible to evaluate what-if scenarios by slightly modifying the process (f.i. adding sensors or changing their placement) and evaluating the impact in terms of the fault diagnosis and redundancy possibilities. Hence, this work proposes an approach to analyze a process from the FDI perspective and for this purpose provides the tool FAST which covers from the analysis and design phase until the final FDI supervisor implementation in a real process. To synthesize the process information, a very simple format has been defined based on XML. This format provides the needed information to systematically perform the Structural Analysis of that process. Any process can be analyzed, the only restriction is that the models of the process components need to be available in the FAST tool. The processes are described in FAST in terms of process variables, components and relations and the tool performs the structural analysis of the process obtaining: (i) the structural matrix, (ii) the perfect matching, (iii) the analytical redundancy relations (if any) and (iv) the fault signature matrix. To aid in the analysis process, FAST can operate stand alone in simulation mode allowing the process engineer to evaluate the faults, its detectability and implement changes in the process components and topology to improve the diagnosis and redundancy capabilities. On the other hand, FAST can operate on-line connected to the process plant through an OPC interface. The OPC interface enables the possibility to connect to almost any process which features a SCADA system for supervisory control. When running in on-line mode, the process is monitored by a software agent known as the Supervisor Agent. FAST has also the capability of implementing distributed FDI using its multi-agent architecture. The tool is able to partition complex industrial processes into subsystems, identify which process variables need to be shared by each subsystem and instantiate a Supervision Agent for each of the partitioned subsystems. The Supervision Agents once instantiated will start diagnosing their local components and handle the requests to provide the variable values which FAST has identified as shared with other agents to support the distributed FDI process.Per tal de facilitar la utilització d'eines per la detecció i identificació de fallades (FDI) en la indústria, es requereix un enfocament sistemàtic per permetre als enginyers de processos analitzar un sistema des d'aquesta perspectiva. D'aquesta forma, hauria de ser possible analitzar aquest sistema per determinar si proporciona el diagnosi de fallades i la redundància d'acord amb la seva criticitat. A més, hauria de ser possible avaluar escenaris de casos modificant lleugerament el procés (per exemple afegint sensors o canviant la seva localització) i avaluant l'impacte en quant a les possibilitats de diagnosi de fallades i redundància. Per tant, aquest projecte proposa un enfocament per analitzar un procés des de la perspectiva FDI i per tal d'implementar-ho proporciona l'eina FAST la qual cobreix des de la fase d'anàlisi i disseny fins a la implementació final d'un supervisor FDI en un procés real. Per sintetitzar la informació del procés s'ha definit un format simple basat en XML. Aquest format proporciona la informació necessària per realitzar de forma sistemàtica l'Anàlisi Estructural del procés. Qualsevol procés pot ser analitzat, només hi ha la restricció de que els models dels components han d'estar disponibles en l'eina FAST. Els processos es descriuen en termes de variables de procés, components i relacions i l'eina realitza l'anàlisi estructural obtenint: (i) la matriu estructural, (ii) el Perfect Matching, (iii) les relacions de redundància analítica, si n'hi ha, i (iv) la matriu signatura de fallades. Per ajudar durant el procés d'anàlisi, FAST pot operar aïlladament en mode de simulació permetent a l'enginyer de procés avaluar fallades, la seva detectabilitat i implementar canvis en els components del procés i la topologia per tal de millorar les capacitats de diagnosi i redundància. Per altra banda, FAST pot operar en línia connectat al procés de la planta per mitjà d'una interfície OPC. La interfície OPC permet la possibilitat de connectar gairebé a qualsevol procés que inclogui un sistema SCADA per la seva supervisió. Quan funciona en mode en línia, el procés està monitoritzat per un agent software anomenat l'Agent Supervisor. Addicionalment, FAST té la capacitat d'implementar FDI de forma distribuïda utilitzant la seva arquitectura multi-agent. L'eina permet dividir sistemes industrials complexes en subsistemes, identificar quines variables de procés han de ser compartides per cada subsistema i generar una instància d'Agent Supervisor per cadascun dels subsistemes identificats. Els Agents Supervisor un cop activats, començaran diagnosticant els components locals i despatxant les peticions de valors per les variables que FAST ha identificat com compartides amb altres agents, per tal d'implementar el procés FDI de forma distribuïda.Postprint (published version

The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

Background Lactobacillus reuteri is a gut symbiont of a wide variety of vertebrate species that has diversified into distinct phylogenetic clades which are to a large degree host-specific. Previous work demonstrated host specificity in mice and begun to determine the mechanisms by which gut colonisation and host restriction is achieved. However, how L. reuteri strains colonise the gastrointestinal (GI) tract of pigs is unknown. Results To gain insight into the ecology of L. reuteri in the pig gut, the genome sequence of the porcine small intestinal isolate L. reuteri ATCC 53608 was completed and consisted of a chromosome of 1.94 Mbp and two plasmids of 138.5 kbp and 9.09 kbp, respectively. Furthermore, we generated draft genomes of four additional L. reuteri strains isolated from pig faeces or lower GI tract, lp167-67, pg-3b, 20-2 and 3c6, and subjected all five genomes to a comparative genomic analysis together with the previously completed genome of strain I5007. A phylogenetic analysis based on whole genomes showed that porcine L. reuteri strains fall into two distinct clades, as previously suggested by multi-locus sequence analysis. These six pig L. reuteri genomes contained a core set of 1364 orthologous gene clusters, as determined by OrthoMCL analysis, that contributed to a pan-genome totalling 3373 gene clusters. Genome comparisons of the six pig L. reuteri strains with 14 L. reuteri strains from other host origins gave a total pan-genome of 5225 gene clusters that included a core genome of 851 gene clusters but revealed that there were no pig-specific genes per se. However, genes specific for and conserved among strains of the two pig phylogenetic lineages were detected, some of which encoded cell surface proteins that could contribute to the diversification of the two lineages and their observed host specificity. Conclusions This study extends the phylogenetic analysis of L. reuteri strains at a genome-wide level, pointing to distinct evolutionary trajectories of porcine L. reuteri lineages, and providing new insights into the genomic events in L. reuteri that occurred during specialisation to their hosts. The occurrence of two distinct pig-derived clades may reflect differences in host genotype, environmental factors such as dietary components or to evolution from ancestral strains of human and rodent origin following contact with pig populations