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  • how to get SOURCE

    - by laknath27
    i do some development with jena ontology API.my ontology file in my local machine..when i'm going to read the model.. there is an error.. and i made ontology with protege and tried to read that file. String SOURCE = "http://www.owl-ontologies.com/Ontology1275995702";(it's XML:base value) //String NS = SOURCE + "#"; //InputStream in = FileManager.get().open("tourism.owl"); OntModel model = ModelFactory.createOntologyModel(OntModelSpec.OWL_MEM); model.read(SOURCE,"RDF/XML"); OntClass paper = model.getOntClass( SOURCE + "srilanka" ); how can i fix this?

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  • Trabajando el redireccionamiento de usuarios/Working with user redirect methods

    - by Jason Ulloa
    La protección de las aplicaciones es un elemento que no se puede dejar por fuera cuando se elabora un sistema. Cada parte o elemento de código que protege nuetra aplicación debe ser cuidadosamente seleccionado y elaborado. Una de las cosas comunes con las que nos topamos en asp.net cuando deseamos trabajar con usuarios, es con la necesidad de poder redireccionarlos a los distintos elementos o páginas dependiendo del rol. Pues precisamente eso es lo que haremos, vamos a trabajar con el Web.config de nuestra aplicación y le añadiremos unas pequeñas líneas de código para lograr dar un poco mas de seguridad al sistema y sobre todo lograr el redireccionamiento. Así que veamos como logramos lo deseado: Como bien sabemos el web.config nos permite manejar muchos elementos dentro de asp.net, muchos de ellos relacionados con la seguridad, asi como tambien nos brinda la posibilidad de poder personalizar los elementos para poder adaptarlo a nuestras necesidades. Así que, basandonos en el principio de que podemos personalizar el web.config, entonces crearemos una sección personalizada, que será la que utilicemos para manejar el redireccionamiento: Nuestro primer paso será ir a nuestro web.config y buscamos las siguientes líneas: <configuration>     <configSections>  </sectionGroup>             </sectionGroup>         </sectionGroup> Y luego de ellas definiremos una nueva sección  <section name="loginRedirectByRole" type="crabit.LoginRedirectByRoleSection" allowLocation="true" allowDefinition="Everywhere" /> El section name corresponde al nombre de nuestra nueva sección Type corresponde al nombre de la clase (que pronto realizaremos) y que será la encargada del Redirect Como estamos trabajando dentro de la seccion de configuración una vez definidad nuestra sección personalizada debemos cerrar esta sección  </configSections> Por lo que nuestro web.config debería lucir de la siguiente forma <configuration>     <configSections>  </sectionGroup>             </sectionGroup>         </sectionGroup> <section name="loginRedirectByRole" type="crabit.LoginRedirectByRoleSection" allowLocation="true" allowDefinition="Everywhere" /> </configSections> Anteriormente definimos nuestra sección, pero esta sería totalmente inútil sin el Metodo que le da vida. En nuestro caso el metodo loginRedirectByRole, este metodo lo definiremos luego del </configSections> último que cerramos: <loginRedirectByRole>     <roleRedirects>       <add role="Administrador" url="~/Admin/Default.aspx" />       <add role="User" url="~/User/Default.aspx" />     </roleRedirects>   </loginRedirectByRole> Como vemos, dentro de nuestro metodo LoginRedirectByRole tenemos el elemento add role. Este elemento será el que posteriormente le indicará a la aplicación hacia donde irá el usuario cuando realice un login correcto. Así que, veamos un poco esta configuración: add role="Administrador" corresponde al nombre del Role que tenemos definidio, pueden existir tantos elementos add role como tengamos definidos en nuestra aplicación. El elemento URL indica la ruta o página a la que será dirigido un usuario una vez logueado y dentro de la aplicación. Como vemos estamos utilizando el ~ para indicar que es una ruta relativa. Con esto hemos terminado la configuración de nuestro web.config, ahora veamos a fondo el código que se encargará de leer estos elementos y de utilziarlos: Para nuestro ejemplo, crearemos una nueva clase denominada LoginRedirectByRoleSection, recordemos que esta clase es la que llamamos en el elemento TYPE definido en la sección de nuestro web.config. Una vez creada la clase, definiremos algunas propiedades, pero antes de ello le indicaremos a nuestra clase que debe heredar de configurationSection, esto para poder obtener los elementos del web.config.  Inherits ConfigurationSection Ahora nuestra primer propiedad   <ConfigurationProperty("roleRedirects")> _         Public Property RoleRedirects() As RoleRedirectCollection             Get                 Return DirectCast(Me("roleRedirects"), RoleRedirectCollection)             End Get             Set(ByVal value As RoleRedirectCollection)                 Me("roleRedirects") = value             End Set         End Property     End Class Esta propiedad será la encargada de obtener todos los roles que definimos en la metodo personalizado de nuestro web.config Nuestro segundo paso será crear una segunda clase (en la misma clase LoginRedirectByRoleSection) a esta clase la llamaremos RoleRedirectCollection y la heredaremos de ConfigurationElementCollection y definiremos lo siguiente Public Class RoleRedirectCollection         Inherits ConfigurationElementCollection         Default Public ReadOnly Property Item(ByVal index As Integer) As RoleRedirect             Get                 Return DirectCast(BaseGet(index), RoleRedirect)             End Get         End Property         Default Public ReadOnly Property Item(ByVal key As Object) As RoleRedirect             Get                 Return DirectCast(BaseGet(key), RoleRedirect)             End Get         End Property         Protected Overrides Function CreateNewElement() As ConfigurationElement             Return New RoleRedirect()         End Function         Protected Overrides Function GetElementKey(ByVal element As ConfigurationElement) As Object             Return DirectCast(element, RoleRedirect).Role         End Function     End Class Nuevamente crearemos otra clase esta vez llamada RoleRedirect y en este caso la heredaremos de ConfigurationElement. Nuestra nueva clase debería lucir así: Public Class RoleRedirect         Inherits ConfigurationElement         <ConfigurationProperty("role", IsRequired:=True)> _         Public Property Role() As String             Get                 Return DirectCast(Me("role"), String)             End Get             Set(ByVal value As String)                 Me("role") = value             End Set         End Property         <ConfigurationProperty("url", IsRequired:=True)> _         Public Property Url() As String             Get                 Return DirectCast(Me("url"), String)             End Get             Set(ByVal value As String)                 Me("url") = value             End Set         End Property     End Class Una vez que nuestra clase madre esta lista, lo unico que nos queda es un poc de codigo en la pagina de login de nuestro sistema (por supuesto, asumo que estan utilizando  los controles de login que por defecto tiene asp.net). Acá definiremos nuestros dos últimos metodos  Protected Sub ctllogin_LoggedIn(ByVal sender As Object, ByVal e As System.EventArgs) Handles ctllogin.LoggedIn         RedirectLogin(ctllogin.UserName)     End Sub El procedimiento loggeding es parte del control login de asp.net y se desencadena en el momento en que el usuario hace loguin correctametne en nuestra aplicación Este evento desencadenará el siguiente procedimiento para redireccionar.     Private Sub RedirectLogin(ByVal username As String)         Dim roleRedirectSection As crabit.LoginRedirectByRoleSection = DirectCast(ConfigurationManager.GetSection("loginRedirectByRole"), crabit.LoginRedirectByRoleSection)         For Each roleRedirect As crabit.RoleRedirect In roleRedirectSection.RoleRedirects             If Roles.IsUserInRole(username, roleRedirect.Role) Then                 Response.Redirect(roleRedirect.Url)             End If         Next     End Sub   Con esto, nuestra aplicación debería ser capaz de redireccionar sin problemas y manejar los roles.  Además, tambien recordar que nuestro ejemplo se basa en la utilización del esquema de bases de datos que por defecto nos proporcionada asp.net.

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  • A Guided Tour of Complexity

    - by JoshReuben
    I just re-read Complexity – A Guided Tour by Melanie Mitchell , protégé of Douglas Hofstadter ( author of “Gödel, Escher, Bach”) http://www.amazon.com/Complexity-Guided-Tour-Melanie-Mitchell/dp/0199798109/ref=sr_1_1?ie=UTF8&qid=1339744329&sr=8-1 here are some notes and links:   Evolved from Cybernetics, General Systems Theory, Synergetics some interesting transdisciplinary fields to investigate: Chaos Theory - http://en.wikipedia.org/wiki/Chaos_theory – small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for chaotic systems, rendering long-term prediction impossible. System Dynamics / Cybernetics - http://en.wikipedia.org/wiki/System_Dynamics – study of how feedback changes system behavior Network Theory - http://en.wikipedia.org/wiki/Network_theory – leverage Graph Theory to analyze symmetric  / asymmetric relations between discrete objects Algebraic Topology - http://en.wikipedia.org/wiki/Algebraic_topology – leverage abstract algebra to analyze topological spaces There are limits to deterministic systems & to computation. Chaos Theory definitely applies to training an ANN (artificial neural network) – different weights will emerge depending upon the random selection of the training set. In recursive Non-Linear systems http://en.wikipedia.org/wiki/Nonlinear_system – output is not directly inferable from input. E.g. a Logistic map: Xt+1 = R Xt(1-Xt) Different types of bifurcations, attractor states and oscillations may occur – e.g. a Lorenz Attractor http://en.wikipedia.org/wiki/Lorenz_system Feigenbaum Constants http://en.wikipedia.org/wiki/Feigenbaum_constants express ratios in a bifurcation diagram for a non-linear map – the convergent limit of R (the rate of period-doubling bifurcations) is 4.6692016 Maxwell’s Demon - http://en.wikipedia.org/wiki/Maxwell%27s_demon - the Second Law of Thermodynamics has only a statistical certainty – the universe (and thus information) tends towards entropy. While any computation can theoretically be done without expending energy, with finite memory, the act of erasing memory is permanent and increases entropy. Life & thought is a counter-example to the universe’s tendency towards entropy. Leo Szilard and later Claude Shannon came up with the Information Theory of Entropy - http://en.wikipedia.org/wiki/Entropy_(information_theory) whereby Shannon entropy quantifies the expected value of a message’s information in bits in order to determine channel capacity and leverage Coding Theory (compression analysis). Ludwig Boltzmann came up with Statistical Mechanics - http://en.wikipedia.org/wiki/Statistical_mechanics – whereby our Newtonian perception of continuous reality is a probabilistic and statistical aggregate of many discrete quantum microstates. This is relevant for Quantum Information Theory http://en.wikipedia.org/wiki/Quantum_information and the Physics of Information - http://en.wikipedia.org/wiki/Physical_information. Hilbert’s Problems http://en.wikipedia.org/wiki/Hilbert's_problems pondered whether mathematics is complete, consistent, and decidable (the Decision Problem – http://en.wikipedia.org/wiki/Entscheidungsproblem – is there always an algorithm that can determine whether a statement is true).  Godel’s Incompleteness Theorems http://en.wikipedia.org/wiki/G%C3%B6del's_incompleteness_theorems  proved that mathematics cannot be both complete and consistent (e.g. “This statement is not provable”). Turing through the use of Turing Machines (http://en.wikipedia.org/wiki/Turing_machine symbol processors that can prove mathematical statements) and Universal Turing Machines (http://en.wikipedia.org/wiki/Universal_Turing_machine Turing Machines that can emulate other any Turing Machine via accepting programs as well as data as input symbols) that computation is limited by demonstrating the Halting Problem http://en.wikipedia.org/wiki/Halting_problem (is is not possible to know when a program will complete – you cannot build an infinite loop detector). You may be used to thinking of 1 / 2 / 3 dimensional systems, but Fractal http://en.wikipedia.org/wiki/Fractal systems are defined by self-similarity & have non-integer Hausdorff Dimensions !!!  http://en.wikipedia.org/wiki/List_of_fractals_by_Hausdorff_dimension – the fractal dimension quantifies the number of copies of a self similar object at each level of detail – eg Koch Snowflake - http://en.wikipedia.org/wiki/Koch_snowflake Definitions of complexity: size, Shannon entropy, Algorithmic Information Content (http://en.wikipedia.org/wiki/Algorithmic_information_theory - size of shortest program that can generate a description of an object) Logical depth (amount of info processed), thermodynamic depth (resources required). Complexity is statistical and fractal. John Von Neumann’s other machine was the Self-Reproducing Automaton http://en.wikipedia.org/wiki/Self-replicating_machine  . Cellular Automata http://en.wikipedia.org/wiki/Cellular_automaton are alternative form of Universal Turing machine to traditional Von Neumann machines where grid cells are locally synchronized with their neighbors according to a rule. Conway’s Game of Life http://en.wikipedia.org/wiki/Conway's_Game_of_Life demonstrates various emergent constructs such as “Glider Guns” and “Spaceships”. Cellular Automatons are not practical because logical ops require a large number of cells – wasteful & inefficient. There are no compilers or general program languages available for Cellular Automatons (as far as I am aware). Random Boolean Networks http://en.wikipedia.org/wiki/Boolean_network are extensions of cellular automata where nodes are connected at random (not to spatial neighbors) and each node has its own rule –> they demonstrate the emergence of complex  & self organized behavior. Stephen Wolfram’s (creator of Mathematica, so give him the benefit of the doubt) New Kind of Science http://en.wikipedia.org/wiki/A_New_Kind_of_Science proposes the universe may be a discrete Finite State Automata http://en.wikipedia.org/wiki/Finite-state_machine whereby reality emerges from simple rules. I am 2/3 through this book. It is feasible that the universe is quantum discrete at the plank scale and that it computes itself – Digital Physics: http://en.wikipedia.org/wiki/Digital_physics – a simulated reality? Anyway, all behavior is supposedly derived from simple algorithmic rules & falls into 4 patterns: uniform , nested / cyclical, random (Rule 30 http://en.wikipedia.org/wiki/Rule_30) & mixed (Rule 110 - http://en.wikipedia.org/wiki/Rule_110 localized structures – it is this that is interesting). interaction between colliding propagating signal inputs is then information processing. Wolfram proposes the Principle of Computational Equivalence - http://mathworld.wolfram.com/PrincipleofComputationalEquivalence.html - all processes that are not obviously simple can be viewed as computations of equivalent sophistication. Meaning in information may emerge from analogy & conceptual slippages – see the CopyCat program: http://cognitrn.psych.indiana.edu/rgoldsto/courses/concepts/copycat.pdf Scale Free Networks http://en.wikipedia.org/wiki/Scale-free_network have a distribution governed by a Power Law (http://en.wikipedia.org/wiki/Power_law - much more common than Normal Distribution). They are characterized by hubs (resilience to random deletion of nodes), heterogeneity of degree values, self similarity, & small world structure. They grow via preferential attachment http://en.wikipedia.org/wiki/Preferential_attachment – tipping points triggered by positive feedback loops. 2 theories of cascading system failures in complex systems are Self-Organized Criticality http://en.wikipedia.org/wiki/Self-organized_criticality and Highly Optimized Tolerance http://en.wikipedia.org/wiki/Highly_optimized_tolerance. Computational Mechanics http://en.wikipedia.org/wiki/Computational_mechanics – use of computational methods to study phenomena governed by the principles of mechanics. This book is a great intuition pump, but does not cover the more mathematical subject of Computational Complexity Theory – http://en.wikipedia.org/wiki/Computational_complexity_theory I am currently reading this book on this subject: http://www.amazon.com/Computational-Complexity-Christos-H-Papadimitriou/dp/0201530821/ref=pd_sim_b_1   stay tuned for that review!

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