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In order to get around the JBI Lifecycle Classpath limitation in the application server, a new JBI jar file is being created called esb_jbi_framework.jar. This jar file will contain a MANIFEST.MF file that contains Class-Path: entries that point towards the jbi_rt.jar (JBI Runtime) and jbi_tests.jar (Scaffolding Registry et al) . This way we dont have to combine the throwaway jbi_tests.jar with the main jbi_rt.jar later. We would simply have to dereference it from jbi_framework.jar. Likewise adding a new JAR to the same classpath would simply mean adding a new entry to the ClassPath: header field.

Package for loading a directory containing MRI data in NIfTI format. The directory to be loaded must contain as many subdirectories as there are classes of MRI data. Each subdirectory name will be used as the class label for the corresponding .nii files in that subdirectory. (This is the same strategy as the one used by WEKA's TextDirectoryLoader.) Currently, the package only reads volume information for the first time slot from each .nii file. The readDoubleVol(short ttt) method from the Nifti1Dataset class (http://niftilib.sourceforge.net/java_api_html/Nifti1Dataset.html) is used to read the data for each volume into a sparse WEKA instance (with ttt=0). For an LxMxN volume (the dimensions must be the same for each .nii file in the directory!), the order of values in the generated instance is [(z_1, y_1, x_1), ..., (z_1, y_1, x_L), (z_1, y_2, x_1), ..., (z_1, y_M, x_L), (z_2, y_1, x_1), ..., (z_N, y_M, x_L)]. If the volume is an image, then only x and y coordinates are used.

RBFNetwork implements a normalized Gaussian radial basisbasis function network. It uses the k-means clustering algorithm to provide the basis functions and learns either a logistic regression (discrete class problems) or linear regression (numeric class problems) on top of that. Symmetric multivariate Gaussians are fit to the data from each cluster. If the class is nominal it uses the given number of clusters per class. RBFRegressor implements radial basis function networks for regression, trained in a fully supervised manner using WEKA's Optimization class by minimizing squared error with the BFGS method. It is possible to use conjugate gradient descent rather than BFGS updates, which is faster for cases with many parameters, and to use normalized basis functions instead of unnormalized ones.

Evaluates the worth of a subset of attributes by the level of consistency in the class values when the training instances are projected onto the subset of attributes. The consistency of any subset can never be lower than that of the full set of attributes, hence the usual practice is to use this subset evaluator in conjunction with a Random or Exhaustive search which looks for the smallest subset with consistency equal to that of the full set of attributes. See: H. Liu, R. Setiono: A probabilistic approach to feature selection - A filter solution. In: 13th International Conference on Machine Learning, 319-327, 1996.

Spring JdbcTemplate did very convient and useful, but it also has some disadvantages or in another word “inconvenient”. For example, you can’t just pass an object and tell JdbcTemplate to turn it into a sql and save to database just like hibernate does. Alright, you may say “JdbcTemplate doesn’t need you to write hbm.xml , so it’s understandable”. But is it true that this thing is impossible to achieve? And also you know JdbcTemplate can auto turn the result of a query to a list of persistent object a.k.a PO, but when you want to do this you will meet a problem: “How to ?”.Because you can’t find any function of JdbcTemplate to pass a sql and a PO class as we expected. After you google for it, you’ve been told you can create a BeanPropertyRowMapper to deal with this. But isn’t it could be more easier? Based on those questions I create JdbcTemplateTool which can provide these features.

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sendings request to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

Provides basic support of servlet filter. Boilerplate code etc. It provides a boilerplate implementation of the Filter interface. The GenericFilter provides a getter and setter for the FilterConfig object and ensures that this is set when init is called. The init method also calls the configureFilter method after the FilterConfig object is set and can be used by subclasses to process the filter config during initiation. It also provides an empty implementation of the destory method. The only method that requires implementation is the doFilter method. The GenericHTTPFilter extends the GenericFilter class, it provides a doFilter method that attempts to cast the ServletRequest and ServletResponse objects to HttpServletRequest and HttpServletResponse objects. If these objects can be cast successfuly then it calls the doHTTPFilter method and passes the cast objects references. If the objects cannot be cast a ServletException is thrown. The doHTTPFilter method is abstract and must be implemented by subclasses.