Most of the functionality provided by the Sparksee API is included in the com.sparsity.sparksee.gdb package or namespace in Sparkseejava and Sparkseenet respectively, and in the sparksee::gdb namespace in Sparkseecpp. If not, the specific package or namespace is indicated.
Initialize the configuration. The basic default configuration only requires the instantiation of the SparkseeConfig class. See the 'Configuration' chapter for a more detailed explanation of this instantiation & also check the advanced configuration options.
Second, a new instance of Sparksee must be created. The configuration previously created is set-up during this instantiation. Sparksee is a Database factory which allows a Sparksee graph database to be opened or created.
Now it is time to create the database itself. A single Sparksee instance can open or create N different databases, but a database can only be concurrently accessed once - take a look at the 'Processing' section of the 'Graph database' chapter for more information. Each database created must have a unique path. Database is considered the Session factory.
A Graph instance must be obtained from the Session, to perform graph-based operations on the graph database.
Sparksee, Database and Session must be closed (deleted in the case of C++) when they are no longer in use, to ensure all data is successfully flushed and persistently stored. Moreover, it is important that they are closed in the correct order, which is the reverse of their creation.
// The license key is required for mobile versions.
// may want to release the cfg here, when it's no longer needed.
// may want to release the sparksee here , when it's closed.
Once an Sparksee instance is created using a SparkseeConfig (see the 'Configuration' chapter), most configuration settings can not be modified. The Cache maximum size is an exception. In a server dedicated to running the Sparksee graph database, once the Sparksee instance is created, you may never need to modify your initial settings. But in a device were Sparksee is not it's main process, a dynamic modification of the maximum cache in use may be required.
For example, in a mobile platform the OS may require an application to release memory in order to give this scarce resource to another application. If you fail to release the memory, the process can be stopped. To handle this dynamic change there are a few new Database methods that can be helpful.
GetCacheMaxSize Returns the current cache maximum setting in megabytes.
SetCacheMaxSize Sets a new value for the cache maximum size (in megabytes). It may fail if the new value is too big or too small.
FixCurrentCacheMaxSize The current cache in use may have not reached the maximum setting yet. If it's less than the maximum and more than the minimum required for the current pools, the current cache usage will be set as the maximum, so it will not grow anymore.
A graph database is a set of objects (nodes and edges) where each object belongs to a type. Node and edge types define the schema of the graph database and they are required to create new objects.
All types have a unique user-provided string identifier, the type name as well as a unique and immutable Sparksee-generated numeric identifier, the type identifier. The method Graph#newNodeType creates a new type of node.
The type identifier will be used to refer that type in all of the APIs requiring that information. For example: the Graph#newNode method, that creates a new node object, needs a single argument which is the node type identifier to establish that the new object will belong to that type.
Whereas node types only require a name for their construction, edge types have other options. Edge types can be directed or undirected and restricted or non-restricted. These topics are explained in the 'Types' section of the 'Graph database' chapter. Check out the parameters of Graph#newEdgeType and Graph#newRestrictedEdgeType methods in the reference guides to see how to set the different options. In addition, a specific index to improve some operations (such as neighbor retrieval) can be defined for edge types. To fully understand the benefits of this index, see the 'Indexing' section of the 'Graph database' chapter.
When a node or edge object is created (with Graph#newNode or Graph#newEdge respectively), a unique and immutable Sparksee-generated numeric identifier is returned. This identifier is known as the object identifier or OID. Thus, all operations on a node or edge object will require this OID as a parameter.
Note that on certain languages the api methods and classes may have slightly different names in order to conform to the language conventions. For instance, all the classes in Objective-C have a STS prefix (from Sparsity Technologies Sparksee), so the Graph#newNode and Graph#newEdge methods become STSGrah#createNode and STSGrah#createEdge. In the document explanations we will usually reference the classes and methods using the most common names (without prefixes), but the exact names can be seen on the code samples and can easily be found on the specific api language reference documentation.
The following examples include the creation of types and objects. We are creating 2 "PEOPLE" which have a relationship between them, "FRIEND".
Complementary to adding new node or edge types or adding new node or edge objects, Sparksee allows the removal of node or edges types and objects. Specifically, the method Graph#removeType removes a type and the method Graph#drop removes an object.
Other methods to interact with the schema are Graph#findType to discover if a type already exists, TypeList Graph#findTypes to retrieve all existing types and Type Graph#getType to get a specific type to be used in other operations.
It can not have any attribute. If it has attribute, you have to remove it's attributes first.
If it's a node type, It can not exist any restricted edge type using using the node type as head or tail. If that's the case, you have to remove the restricted edge type first.
If it's a node type, It can not exist any edge from an unrestricted edge type using any node of this type as a head or tail. If that's the case, you have to drop the edge before trying to remove the node type.
In the following example, we could use FindTypes and try to remove all the types in one loop. But if we try to remove a node type with any of the previous restrictions before removing the conflicting edge types (or edges), the operation would fail.
So we will first get only the edge types (with FindEdgeTypes) instead of getting all the types (with FindTypes) to remove only the edge types. The procedure could then be safely repeated for the node types (with FindNodeTypes or with FindTypes because only node types remain) without the risk of any operation failing for the previous restricions because all the edge types would have been removed before. But we don't show it in the sample code because it would be exactly the same changing only the method to get the types (FindNodeTypes).
print "Type", type_data.get_name(), " with ", type_data.get_num_objects(), " objects"
All node and edge types can have a set of attributes which are part of the schema of the graph database. An attribute should have a single value, and once created it is possible to set and get that value multiple times for each object.
In general, attributes are defined within the scope of a node or edge type and identified by a unique string identifier provided by the user. As is explained in the 'Attributes' section of the 'Graph database' chapter, it is possible to have two attributes with the same name but defined for two different types. For example, we could define the attribute "Name" for two different node types "PEOPLE" and "MOVIE", resulting in two different attributes. Since attributes are defined within the scope of a type, only objects belonging to that type will be able to set and get values for that attribute.
The method to define a new attribute is Graph#newAttribute. As well as the parent type and the name, the definition of an attribute includes the datatype and the index-capabilities.
Boolean TRUE or FALSE values.
Integer 32-bit signed integer values.
Long 64-bit signed integer values.
Double 64-bit signed double values.
Timestamp Distance from Epoch (UTC) with millisecond precision. Valid timestamps must be in the range ['1970-01-01 00:00:01' UTC, '2038-01-19 03:14:07' UTC].
String Unicode string values. Maximum length is restricted to 2048 characters.
Text Large unicode character object. See 'Text attributes' section in this chapter.
OID Sparksee object identifier values.
The indexing-capabilities of an attribute determine the performance of the query operations on that attribute as is explained in the 'Indexing' section of the 'Graph Database' chapter. Different index options are defined in the AttributeKind enum class which includes basic, indexed and unique attributes.
The indexing-capabilities of an attribute can be updated later using the Graph#indexAttribute method.
When an object is created it will have the default value for all the attributes defined for the type of the new object (by default the attribute value is null). This default value can also be defined afterwards by using the method Graph#setAttributeDefaultValue.
Analogously to node and edge types, when an attribute is defined a unique and immutable Sparksee-generated numeric identifier is returned. This identifier is the attribute identifier and will be used for all those APIs requiring an attribute as a parameter, like the Graph#setAttribute method which sets a value for a given attribute and object (explained in next section).
Although the most common type of attributes are those whose scope is defined as type specific - Objects (node or edge objects) belonging to that type are the only ones allowed to set and get values for that attribute - we can also create attributes with a wider scope.
It is also possible to define the scope of an attribute as node specific using Type#NodesType as the parent type identifier argument when calling the Graph#newAttribute method. Whereas regular attributes are restricted to those objects belonging to the specified parent type, node attributes may be used for any node type in the graph. Therefore, any node of the graph, no matter which node type it belongs to, can set and get the values of a node attribute.
Analogous to the former kind is the user may define the scope of an attribute as edge specific using Type#EdgesType as the parent type identifier argument when calling the Graph#newAttribute method. Whereas regular attributes are restricted to those objects belonging to the specified parent type, node attributes may be used for any edge type in the graph. Therefore, any edge of the graph, no matter which edge type it belongs to, can set and get the values of a node attribute.
Finally, it is also possible to define the scope of an attribute as global using Type#GlobalType as the parent type identifier argument when calling the Graph#newAttribute method. Global attributes may be used for any object (node or edge) in the graph. Therefore, any object of the graph, no matter which type it belongs to, can set and get the values of a global attribute.
They can only be seen and used within the session. Therefore other concurrent sessions cannot set, get or perform any operation with that attribute.
They are temporary and are automatically removed when the session is closed.
As they cannot be accessed outside the scope of a session or after it finishes, they are anonymous and do not require a name. Session attributes are created using the Graph#newSessionAttribute which returns the attribute identifier. Despite the restrictions, these attributes can be used in any method just like any other attribute.
Graph#removeAttribute removes the attribute and its values.
AttributeList Graph#findAttributes(int type) retrieves all attributes defined for the given type.
AttributeList Graph#getAttributes(long object) retrieves all the attributes for the given object which have a non-null value.
AttributeStatistics Graph#getAttributeStatistics(long attr) and long Graph#getAttributeIntervalCount retrieve some statistics for the given attribute (this is explained more in detail in the 'Statistics' section of the 'Maintenance and monitoring' chapter).
Graph#indexAttribute updates the index-capability of the given attribute.
Attribute Graph#getAttribute retrieves all the metadata associated with an existing attribute.
String attribute values are restricted to a maximum length of 2048 characters, thus in case of storing larger strings, text attributes should be used instead. However, it is important to notice that whereas string attributes are set and got using the Value class, text attributes are operated using a stream pattern.
They cannot be used in query operations, which are explained in the 'Query operations' section of this chapter. They only can get and set the value for a given object identifier.
Graph#getAttributeText gets the value for a given object identifier by means of a TextStream instance instead of the Graph#getAttribute method and a Value instance.
Graph#setAttributeText sets the value for a given object identifier by means of a TextStream instance instead of the Graph#setAttribute method and a Value instance.
It retrieves a read/write/append stream for a text attribute and object identifier.
It reads or writes chunks of data on the stream as many times as required.
It closes the stream to ensure all data is correctly flushed.
str1 = u"This is the first chunk of the text stream"
str2 = u"This is the second chunk of the text stream"
//[tstrm release]; // You may need to release it here.
It's important to always close the TextStream object retrieved, even if it's content is Null.
As we are going to see later, most of the query or navigational operations return a collection of object identifiers or OIDs as the result of the operation. The Objects class is used for the management of these collections of object identifiers. Actually, Objects is considered a set, as duplicated elements are not allowed and it does not follow a defined order.
The user can create as many Objects instances as may be required for use by calling Objects Session#newObjects. Please note that the Objects class has been designed to store a large collection of object identifiers. Therefore, for smaller collections it is strongly recommended that a common class provided by the chosen language is used.
Also, it is important to note that this class is not thread-safe, so it cannot be used by two different threads at the same time.
The Objects class can add object identifiers to a collection (Objects#add), check if an object identifier exists (Objects#exists), remove an object identifier from the set (Objects#remove) or retrieve the number of elements of a collection (Objects#count). Take a look at the Objects class reference documentation to get a comprehensive list of all the available methods.
As seen in the previous examples, all Objects instances need to be closed (deleted in the case of C++) just like Sparksee, Database and Session instances. Moreover, collections must be closed as soon as possible to free internal resources and ensure a higher performance of the application.
Furthermore, as these collections are retrieved from the Session they are only valid while the parent Session instance remains open. In fact, when the Session is closed (deleted in the case of C++), it checks out if there are still any non-closed Objects instances, and if detected an exception is thrown.
It is important to notice that ObjectsIterator instances must be closed (deleted in the case of C++) as soon as possible to ensure better performance. Nevertheless, non-closed iterators will be automatically closed when the collection is closed.
When traversing Objects instances it is important to have in mind that the Objects instance cannot be updated; elements cannot be added or removed from the collection.
Objects instances can be efficiently combined with the following methods. Note that there are two versions for the same call, because whereas the instance method performs the resulting operation on the calling instance, the static method creates a new instance as a result of the operation.
The resulting collection contains the union of both collections with no repeated objects. It contains all the object identifiers from the first collection together with all the object identifiers from the second one.
The resulting collection contains the intersection of both collections. It contains only those object identifiers from the first collection that also belong to the second one.
The resulting collection contains the difference of both collections. It contains those object identifiers from the first collection that do not belong to the second one.
Sparksee has different methods to retrieve data from the graph. Most of them return an instance of the Objects class.
The most simple query method is the select operation Objects Graph#select(int type), which retrieves all the objects belonging to the given node or edge type, so it is a type-based operation.
The method Objects Graph#select(int attribute, Condition cond, Value v) is more specific than the previous selection, being able to retrieve all the objects satisfying a condition for a given attribute. This select is an attribute-based operation.
Note that the second select operation requires the datatype of the given value to be the same as the datatype of the attribute.
Equal: retrieves those objects that have a value for the attribute equal to the given value.
NotEqual: retrieves those objects that have a value for the attribute not equal to the given value.
GreaterEqual: retrieves those objects that have a value for the attribute greater than or equal to the given value.
GreaterThan: retrieves those objects that have a value for the attribute strictly greater than the given value.
LessEqual: retrieves those objects that have a value for the attribute less than or equal to the given value.
LessThan: retrieves those objects that have a value for the attribute strictly less than the given value.
Between: retrieves those objects that have a value for the attribute within the range defined for the two given values. This condition can only be used in the specific signature of the selected method where there are two argument values instead of one: Objects Graph#select(int attribute, Condition cond, Value lower, Value higher). Note that lower and higher define an inclusive range [lower,higher], also null values cannot be used in the specification of the range.
Like: retrieves those objects having a value which is a substring of the given value.
LikeNoCase: retrieves those objects having a value which is a substring (not case sensitive) of the given value.
RegExp: retrieves those objects having a value for the given attribute that matches a regular expression defined by the given string value. In fact, Like and LikeNoCase are simply two specific cases of regular expressions. More details on how Sparksee regular expressions work are given in a later section.
// Woody Allen, Tim Allen or Allen Leech, or other similar if they are present in the graph.
# Woody Allen, Tim Allen or Allen Leech, or other similar if they are present in the graph.
The method long Graph#findObject(long attr, Value v) is a special case of the attribute-based select operation. In this case, instead of returning a collection of objects, this method returns a single object identifier. Moreover, in this case, findObject assumes the condition Equal. Thus, it randomly returns the object identifier of any of the objects having the given value for the given attribute. Although it can be used with any kind of attribute (Basic, Indexed, Unique) it may be better to use it with Unique attributes, as they ensure that two objects will not have the same attribute value (except for the null value).
When retrieving an Objects from the graph and traversing the collection, as it is not a copy but directly access to Sparksee internal structures, any object cannot be removed or added from that collection. For example, if we traverse a collection of objects belonging to a certain type, we cannot remove elements from that type at the same time.
As explained previously, a regular expression can be used in query operations to search for objects having a value for an attribute matching the given regular expression. RegExp is the Condition value to set a matching regular expression condition in an attribute-based select operation. Of course, this condition can only be applied for string attributes.
Regular expression format conforms to most of the POSIX Extended Regular Expressions and therefore they are case sensitive.
A detailed reference for the syntax of the regular expressions can be found in the POSIX Extended Regular Expressions reference guide.
Explode-based methods: these methods visit the edges of a given node identifier. Check out Graph#explode in the reference documentation for details.
Neighbor-based: these methods visit the neighbor nodes of a given node identifier. A neighbor is an adjacent node 1-hop away from the source node (distance 1). Check out Graph#neighbor in the reference documentation for details.
Outgoing: Only out-going edges, starting from the source node, will be valid for the navigation.
Ingoing: Only in-going edges will be valid for the navigation.
Any: Both out-going and in-going edges will be valid for the navigation.
Note that in case of undirected edges the direction restriction has no effect as we may consider undirected edges as bidirectional edges, which do not have a restriction on the direction of the navigation.
Although both methods return an Objects instance as a result, for explode the resulting Objects instance contains edge identifiers whereas for neighbors it contains node identifiers.
Note that in the previous examples we have performed the neighbors call setting Any as the direction because FRIEND is an undirected relationship. In fact, any other direction (Ingoing or Outgoing) would have retrieved the same result.
For both navigation methods there is a more general implementation where instead of having a source node identifier as the first argument, there is an Objects instance. This Objects instance is the collection of object identifiers to perform the operation. The result will be an Objects instance with the union of all the results of performing the operation for each of the objects in the argument instance.
Actually, by default the neighbors method is solved internally by performing an explode-based implementation, firstly visiting the edges themselves and then visiting the other side of the edge. Additionally a specific index may be created to improve the performance of the neighbors query. More details are in the 'Indexing' section of the 'Graph database' chapter.
This index can be set when creating an edge type (Graph#newEdgeType). Using the index, all neighbors-based operations involving that edge type will be internally performed faster. As expected, the management of an index introduces a small penalty when creating new edge instances. Nevertheless, it is strongly recommended to set an index for those applications making intensive use or critical use of the neighbors method, as the small penalty is more than compensated for the improvement in performance.
The 'Processing' section in the 'Graph database' chapter explains the execution model and Sparksee transactions in detail.
begin - which starts a transaction.
commit - which ends a transaction.
rollback - which ends the transaction aborting all the changes enclosed in the transaction.
Take in to accunt that the rollback mechanism can be disabled to improve the performance when there is not any active transaction. The following example shows how to enable and disable the rollback.
//The license key is required for mobile versions.
Note that the previous codes are also valid without the begin/commit calls because they are automatically executed in autocommit mode, where a transaction is created for each one of the calls.
Sparksee provides utilities to export a graph into visual format or import/export data from external data sources.
Data stored in a Sparksee graph database can be exported to a visual-oriented representation format.
this is an open-source graph visualization software. The Graphviz layouts take descriptions of graphs in a text language and make diagrams in useful formats, such as images and SVG for web pages or PDF and Postscript for inclusion in other documents. The resulting formats can also be displayed in an interactive graph browser (also supports GXL, an XML dialect). Graphviz has many useful features to personalize the diagrams, such as options for colors, fonts, tabular node layouts, line styles, hyperlinks and rolland custom shapes.
GraphML is a file format for graphs based on XML, so it is especially suitable as a common denominator for all kinds of services that generate, archive, or process graphs. This is the reason it is considered a standard for graph exportation. Its core language describes the structural properties of a graph while the extensions add application-specific data. Its main features include support of directed, undirected, and mixed graphs, hypergraphs, hierarchical graphs, graphical representations, references to external data, application-specific attribute data, and light-weight parsers.
YGraphML is a format based in GraphML that has some exclusive extensions for yEd Graph Editor. yED is a desktop application that can be used to generate graphs or diagrams which can be browsed with the application and then imported or exported to different data formats.
The file where the data is to be exported.
An implementation of the ExportManager class.
GraphExport: a global label can be defined for the graph.
NodeExport: label, label color, color, shape, width, font, font size, as well as other properties can be set for a node.
EdgeExport: label, label color, width, font, font size, arrows, as well as other properties can be set for an edge.
Note that only some of these properties are meaningful for some of the available export type formats.
getNodeType: the user can set the properties to export all nodes belonging to a given type by setting the NodeExport in/out parameter.
getNode: the user can override the previous NodeExport definition for the specific given node instance.
getEdgeType: the same as getNodeType but for edge types.
getEdge: the same as getNode but for edge instances.
enableType: the user can skip a whole node or edge type from the export process.
getGraph: the user can set certain global properties for the graph.
prepare: this is called when the export process starts.
release: this is called when the export process ends (the method name is close in Objective-C).
Instead of manually creating node and edge objects, data can be imported following a certain schema, in bulk.
This functionality is provided by classes in the com.sparsity.sparksee.io package for Sparkseejava, the com.sparsity.sparksee.io namespace for Sparkseenet, and in the sparksee::io namespace in Sparkseecpp.
The main classes for importing data into Sparksee are the RowReader class, which reads data from external data sources and shows this data to the user with a row-based logical format, and the TypeLoader class, which imports data into a Sparksee graph.
To read data Sparksee has a CSVReader class that is a RowReader implementation to retrieve data from a CSV file. Alternatively, users could implement a different RowReader in order to retrieve data from other specific data sources.
The most important method defined by the RowReader is the bool RowReader#read(StringList row) method which returns true if a row has been read or false otherwise. If a row has been read, the output argument row is a list of strings, each string being a column within the row. The RowReader#close method must be called once the processing ends.
CSVReader#open sets the path of the CSV file to be read.
Set the locale of the file by means of a case in-sensitive string argument with the following format: an optional language, a dot ('.') character and a coding specification.
Thus, valid locale arguments are: "en_US.UTF8", "es_ES.ISO88591", ".UTF8", etc. If not specified, "en_US.iso88591" is the default locale.
Set a separator character (to limit columns) with CSVReader#setSeparator or set the quote character for strings with CSVReader#setQuotes. For quoted strings it is also possible to set a restriction for them to be single-lined or allow them to be multi-lined. In the second case the user should limit the maximum number of lines.
Finally, it is possible to skip some lines at the beginning of the file (CSVReader#setStartLine) or fix a maximum number of lines to be read (CSVReader#setNumLines).
Note that the separator and the first line to be read have been set in the first place.
There are two implementations for the TypeLoader class, regarding whether the element to be included in the graph is a node, the NodeTypeLoader class, or an edge, the EdgeTypeLoader class.
TypeLoader#run. The CSV file is read once and the objects are created in the graph.
TypeLoader#runTwoPhases. The CSV file is read twice: once to create the objects and once again to set the attribute values.
TypeLoader#runNPhases(int num). The CSV file is read N times: once to create the objects and then once for each attribute column. Each attribute column is logically partitioned, so the data column is loaded in num partitions.
It is possible to register listeners to receive progress events from the TypeLoader (TypeLoader#register). This requires the user to implement the TypeLoaderListener class. The frequency with which these events are generated can also be configured (TypeLoader#setFrequency).
In case of parsing a string column to load a Timestamp attribute, the timestamp format can be set by the user.
yy: Year without century interpreted. Within 80 years before or 20 years after the current year. For example, if the current year is 2007, the pattern MM/dd/yy for the value 01/11/12 parses to January 11, 2012, while the same pattern for the value 05/04/64 parses to May 4, 1964.
setHeadPosition and setTailPosition set which columns from the RowReader contain information about the target and source nodes respectively.
For the referenced columns, setHeadAttribute and setTailAttribute indicate the attribute identifier to be used to find the target and source node respectively. Thus, the value in that column will be used to find an object with that value for that attribute. That node will be the target or the source node, accordingly, for the new edge.
Analogously to the data import, this functionality is provided by classes in the com.sparsity.sparksee.io package for Sparkseejava, the com.sparsity.sparksee.io namespace for Sparkseenet, and in the sparksee::io namespace in Sparkseecpp.
The main classes for exporting data from Sparksee are the RowWriter class, which writes data from a row-based logical format to an external data source, and the TypeExporter class, which exports data from a Sparksee graph.
The CSVWriter class is a RowWriter implementation for writing data from a Sparksee graph into a CSV file. Alternatively, users may implement a different RowWriter to export data into other data sources.
The most important method defined by the RowWriter is the bool RowWriter#write(StringList row) method which writes data to an external storage. The RowWriter#close method must be called once the processing ends.
CSVWriter#open sets the path of the CSV file to be written.
The locale of the file is set by means of a case in-sensitive string argument with the following format: an optional language, a dot ('.') character and a coding specification.
A separator character is set (to limit columns) with CSVWriter#setSeparator or the quote character is set for strings with CSVWriter#setQuotes. Quoted strings can also be forced with the CSVwriter#setForcedQuotes method, or managed automatically with the CSVwriter#setAutoQuotesmethod.
The TypeExporter class exports a specific type of the graph to a external storage. There are two implementations for the TypeExporter class, regarding whether the element to be exported from the graph is a node, the NodeTypeExporter class, or an edge, the EdgeTypeExporter class. A TypeExporter retrieves all the data from the instances belonging to a node or edge type and writes it using a RowWriter.
TypeExporter#run executes the export process.
It is possible to register listeners to receive progress events from the TypeExporter (TypeExporter#register). This requires the user to implement the TypeExporterListener class. The frequency with which these events are generated can also be configured (TypeExporter#setFrequency).
TypeExporter#setAttributes sets the list of attributes to be exported.
setHeadPosition and setTailPosition set which columns from the RowWriter will be used to export the target and source node respectively.
For the referenced columns, setHeadAttribute and setTailAttribute indicate the attribute identifier to be used to export the source and target node respectively. Thus, the value in that column of the current row will correspond to the value of that object for that attribute.
This functionality is provided by classes in the com.sparsity.sparksee.script package for Sparkseejava, the com.sparsity.sparksee.script namespace for Sparkseenet, and in the sparksee::script namespace in Sparkseecpp.
Users can also interact with Sparksee through a script file, mainly to create or delete objects. Although the grammar and examples of Sparksee script language are explained in the 'Scripting' chapter, this section explains how to execute those scripts.
The ScriptParser class is in the com.sparsity.sparksee.script package or namespace in Sparkseejava or Sparkseenet respectively, or in the sparksee::script namespace in Sparkseecpp.
Once instantiated, this class allows the parsing and/or executing of a Sparksee script file with the method ScriptParser#parse.
The ScriptParser class sets the output and error log paths, and also sets the locale of the file to be processed. More information about the locale formats can be found in the 'Data import' and 'Data export' sections of this chapter.
Finally, the static method ScriptParser::generateSchemaScript generates and dumps the schema of a Sparksee database into an output Sparksee script file path.
In the case of Sparkseejava, the jar library includes a static main method together with the ScriptParser class. It just calls the ScriptParser class to provide a command-line interface to that class.
In the case of Sparkseenet and Sparkseecpp, the distribution includes a ScriptParser executable that calls the ScriptParser class to provide a command-line interface to that class.
In all cases, the application has one required argument, a Sparksee script file path, and one optional argument, a case-insensitive boolean (true or false) to force the execution of the Sparksee script file or to just parse it; true (execute) is the default.
script_file.des Is the required file containing the script commands.
bool_run: True (default) = run the commands / False = just check the script.
This functionality is provided by classes in the com.sparsity.sparksee.algorithms package for Sparkseejava, the com.sparsity.sparksee.algorithms namespace for Sparkseenet, and in the sparksee::algorithms namespace in Sparkseecpp.
Traversal: for visiting the nodes in a graph.
Shortest path: for computing the shortest path between two nodes in a graph.
Connectivity: for computing the connected components, those connected to each other forming a subgraph.
Community detection: for computing communities of nodes densely connected.
Restrict which node types can be traversed. The user can specify which node types are valid for the traversal, so nodes belonging to other node types will be ignored.
Restrict which edge types can be traversed and the direction. The user can specify which edge types are valid for the traversal plus the direction of the navigation, so the user can set to navigate only through out-going, in-coming or both types of edges.
Exclude a collection of node identifiers. The user can specify a collection of node identifiers to be ignored during the traversal.
Exclude a collection of edge identifiers. The user can specify a collection of edge identifiers to be ignored during the traversal.
Set a maximum number of hops. The user can specify the maximum distance to be visited, so nodes further from that will be ignored.
TraversalBFS class implements the traversal using a breadth-first search strategy.
TraversalDFS class implements the traversal using a depth-first search strategy.
All previous traversal classes have an iterator pattern. Once instantiated and configured, the user must call Traversal#hasNext and Traversal#next in order to visit the next node. Take into account that is strongly recommended to close (delete for Sparkseecpp) the traversal instance as soon as it is no longer needed.
The Context is a complementary class that has a very similar interface and provides the same functionality as the Traversal class. Instead of visiting each node using an iterator pattern, Context class returns an Objects instance which contains all the "visited" nodes. Similarly to what happens with the Traversal instances, all Context instances must be closed (or deleted in the case of Sparkseecpp) when they are no longer in use.
Restrict which node types can be traversed: the user can specify which node types are valid for the computation of the shortest path, so nodes belonging to other node types will be ignored.
Restrict which edge types can be traversed and the direction: the user can specify which edge types are valid for the shortest path plus the direction of the navigation, so the user can set to navigate only through out-going, in-coming or both type of edges.
Exclude a collection of node identifiers: the user can specify a collection of node identifiers to be ignored during the computation of the shortest path.
Exclude a collection of edge identifiers: the user can specify a collection of edge identifiers to be ignored during the computation of the shortest path.
Set a maximum number of hops: the user can specify the maximum distance to be visited, so paths longer than this distance will be discarded.
SinglePairShortestPath#getPathAsEdges: returns the computed shortest path as an edge identifier sequence.
SinglePairShortestPath#getPathAsNodes: returns the computed shortest path as a node identifier sequence.
SinglePairShortestPathBFS class which solves the problem using a breadth-first search strategy. This implementation solves the problem of unweighted graphs, as it assumes all edges have the same cost.
SinglePairShortestPathDijkstra class which solves the problem based on the well-known Dijkstra's algorithm. This algorithm solves the shortest path problem for a graph with positive edge path costs, producing a shortest path tree.
With the same class the user may add weights to the edges of the graph using the addWeightedEdgeType method. That attribute will be used during the computation of the algorithm to retrieve the cost of that edge. The class also includes the getCost method to retrieve the cost of the computed shortest path.
The ShortestPath class and all its subclasses have a close method which must be called once the instances are no longer in use in order to free internal resources (or delete them in the case of Sparkseecpp).
Discovering the connected components is a common problem in graph theory. A connected component is a subgraph where any two nodes are connected to each other by paths, whilst at the same time it is not connected to any additional node in the supergraph.
Restrict which node types can be traversed: the user can specify which node types are valid for the computation, so nodes belonging to other node types will be ignored.
Exclude a collection of node identifiers: the user can specify a collection of node identifiers to be ignored during the computation.
Exclude a collection of edge identifiers: the user can specify a collection of edge identifiers to be ignored during the computation.
Attribute for the materialization of the computation: the user can specify an attribute where the results of the computation are persistently store. The identifier of the connected component will be stored for each node as the value of that attribute. The connected component identifier is a numeric value in the range [0..C-1] where C is the number of different connected components. Note that the results are not automatically updated in the case that the graph topology is updated (node or edge object added or removed).
StrongConnectivity class solves the connected components problem for directed graphs. This class provides methods for restricting which edge types can be traversed during the computation as well as the direction of those edges. The implementation for this class is the StrongConnectivityGabow class that uses the Gabow's algorithm strategy.
WeakConnectivity class solves the connected components problem for undirected graphs, where all edges are considered as undirected. Note that if the graph contains directed edge types, these edges will be managed as if they were simply undirected edge types. The implementation for this class is the WeakConnectivityDFS class that use the DFS strategy.
Additionally the ConnectedComponents class helps the user manage the result of a connectivity computation. It retrieves the number of connected components, the connected component identifier for each node, and the size of a certain connected component or all the elements in a connected component.
All the connectivity classes and subclasses have a close method in order to free resources as soon as the instances are no longer in use (deleted in the case of Sparkseecpp).
Detecting communities is a common problem in graph theory. A community is a subgraph where the set of nodes are densely connected.
Attribute for the materialization of the computation: the user can specify an attribute where the results of the computation are persistently stored. The identifier of the community will be stored for each node as the value of that attribute. The community identifier is a numeric value in the range [0..C-1] where C is the number of different communities. Note that the results are not automatically updated in the case that the graph topology is updated (node or edge objects added or removed).
The only community detection algorithm currently implemented is an algorithm for undirected graphs. As a result, the operations to set the valid EdgeTypes does not have a direction argument. All the added types will be used in both directions even when the edge type is directed.
CommunitiesSCD class solves the not overlapping community detection problem for undirected graphs. This class provides methods for restricting which edge types can be traversed during the computation. The implementation for this class uses the Scalable Community Detection algorithm based on the paper High quality, scalable and parallel community detection for large real graphs by Arnau Prat-Perez, David Dominguez-Sal, Josep-Lluis Larriba-Pey - WWW 2014.
Additionally the DisjointCommunities class helps the user manage the result of a disjoint community detection algorithm. It retrieves the number of communities, the community identifier for each node, and the size of a certain community or all the elements in a community.
All the community classes and subclasses have a close method in order to free resources as soon as the instances are no longer in use (deleted in the case of Sparkseecpp).
print "Community ", ii, " has ", dcs.get_size(ii), " nodes."


Your home is your haven, it's where you relax, where you raise your family, and you have probably spent a lot of time and money to get your home just the way that you want it. That can all be ruined the moment that you realise that you have unwanted visitors in your home, whether it's noticing a bees nest in the eaves, seeing a mouse run across your kitchen, having to clean your car and windows constantly because of gulls, starlings, or pigeons, or simply having all your plants chewed to bits, or your lawn lifted by an infestation of ants or moles.
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SWOYERSVILLE — The future laid out at a meeting Wednesday night regarding a project to remove hundreds of thousands of tons of waste coal from a former mining site in Swoyersville looked promising: No more millions of tons of coal refuse piled high behind homes in the borough, a 7-acre parcel donated to the town and the possibility of future development.
But before that distant future is the near future, and that looked less enticing to some of the residents gathered at Swoyersville Hose Company No. 2 to learn more.
Kathe Aulisio, whose home is across the street from the site, was worried about the 35 to 40 trucks expected to visit the site between 7 a.m. and 3 or 4 p.m. on weekdays during the project.
Aulisio paid thousands of dollars to replace a water line from her home she blamed on trucks driving down the street. Other people at Wednesday's meeting who also lived on Slocum Street said they had the same problem and they were worried that trucks would cause the lines to burst again.
The project will turn the massive pile of waste coal into electricity by burning it at cogeneration plants. Keystone Reclamation, a subsidiary of Olympus Power in Morristown, New Jersey, will haul away the coal from the Harry E. Colliery culm pile to burn at facilities owned by Northampton Generating Company. Pagnotti Enterprises owns the land on which the waste coal sits.
The first phase of the project will remove about 500,000 tons of coal and rock from about 25 acres. The entire 55-acre site holds about four million tons of waste coal and rock.
Olympus Power will pay about $8 million toward the project. An abandoned mineland reclamation program will pay another $4 million.
The site is next to Main Street, known as the Back Road, and next to houses on Slocum, Tripp and Perrin streets.
The proposed route for hauling away waste coal goes down Slocum Street in Swoyersville and Welles Street in Forty Fort before accessing the North Cross Valley Expressway off Rutter Avenue.
Keystone plans to begin building an access road on the site later this month. But before trucks loaded with coal roll out of town, Department of Environmental Protection Deputy Secretary John J. Stefanko said he would hold another meeting to address residents' concerns.
The site is not the agency's first abandoned coal mine. There are regulations to guide projects and resources for residents who have problems if those regulations aren't followed. Officials said residents can call district mining operations at 570-621-3118 to report problems. The Department of Environmental Protection northeast regional office also has a hotline for environmental complaints at 570-826-2511.
As the coal mining industry developed decades ago, communities built up around the infrastructure to mine or process coal. That's why situations exist today in which homes are close to the refuse, said Eric E. Cavazza, director of the Bureau of Abandoned Mine Reclamation.
Slocum Street resident Ken Rosa, 62, summarized the dilemma: "We're going to remove an eyesore, but nobody wants it removed." Or rather, he said, nobody wants to deal with living on the street during the removal.
People don't want trucks on their road, he said. He was hoping that another road could also take some of the traffics, to spread the pain.
Altering the route is a possibility, but Keystone Reclamation will have to study it, said Matt Cochran, an asset manager with Olympus Power. His company drafted the proposed route and it was approved by the Pennsylvania Department of Transportation.
In the meantime, PennDOT, which is responsible for the road, should see that it is properly maintained, he said.
After the meeting, Stefanko talked about two Pennsylvania towns that offered possible glimpses into the future.
One was Ehrenfeld, a Cambria County borough that also had millions of tons of waste coal piled high next to houses before another abandoned mine reclamation project reclaimed a 62-acres of coal refuse.
The other was Simpson, located in Fell Twp., Lackawanna County, where a coal refuse bank caught fire and took more than five months and $2 million to extinguish.


Animals regularly need to be captured and moved from one place to another; this is known as translocation. For many reasons, translocation of wild animals becomes necessary from time to time. In this story the animals concerned are impala being relocated to a more appropriate place for their survival.
Impala are referred to by nature fundis as bushveld fast food. Hmmm… well, fast food if you're a lion, leopard, hyena or wild dog. They're known as the McDonald's of the bush because they form a large part of these predators' diets and they are fast and food. Even the young are often taken by pythons.
Our bush is teeming with impala. Here, there are few predators and herds of these graceful buck can be seen all over. What's really remarkable is that these reddish brown and white and fawn creatures can melt away unseen into full green cover or dry twigs and sticks in a moment.
To look at one of these buck, you'd never believe the grunts, growls, snorts and rumbling they're capable of making, some people even think they sound like leopard. Then there's the leaping and pronking that goes on if they panic. Should they spot danger, their snort in alarm is all it takes and the whole herd will scatter.
"K joined the capture and really got stuck in. Unfortunately while hand-catching the adult impala rams from the boma crush (for tranquillization, blood sampling and horn-piping) he discovered that he is very allergic to impala (surprisingly a large percentage of people are)!
You may find you're allergic to impala but watch out for the vet!


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text:
Department of Industrial
and Systems Engineering
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Operations research is the application of scientific and especially mathematical methods to the study and analysis of problems involving complex systems.
PhD and MS students interested in Operations Research apply methods such as mathematical programming, stochastic modeling, and discrete-event simulation to the solution of problems in complex systems such as logistics, supply chain optimization, long-range planning, energy and environmental systems, urban and health systems, and manufacturing.
ISE faculty and students conduct OR funded by such agencies as the National Science Foundation, the Office of Naval Research, the Air Force Office of Scientific Research, the Department of Homeland Security , the Department of Transportation and the National Institute of Justice, as well as national and local corporations and foundations such as United Airlines, Praxair, Lockheed Martin, Boeing, and the Fire Protection Research Foundation. We often work in teams with faculty and students with research interests in manufacturing, production systems and human factors to solve problems beyond the expertise of any single discipline.
We have an active student body - in fact, UB hosts one of the founding chapters of Omega Rho, the National Operations Research Honor Society. Students are also active participants in the Institute for Operations Research and the Management Sciences (INFORMS).
Graduating students regularly take positions in national and international corporations, academic institutions and research laboratories.
Courses Required for OR PhD Research
ISE PhD students who wish to conduct dissertation research in the area of Operations Research should complete (at a minimum) the following courses:
IE 572 Linear Programming
IE 573 Discrete Optimization
IE 575 Stochastic Methods
IE 576 Applied Stochastic Processes
IE 5xx/6xx Operations Research/IE Elective
IE 555 Programming for Analytics (Must be completed within the first two years of the program)
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The Operations Research core qualifying exam questions are the following:
IE 572
IE575
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Course Required for OR MS Research
ISE MS students who wish to conduct thesis research in the area of Operations Research should complete the following courses:
IE 576 Applied Stochastic Processes.
In addition, students are required to take two additional IE courses in Operations Research, as approved by the faculty.
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Our ISE graduate program ranks 19th across public universities, according to the U.S. News & World Report graduate program rankings.
We have a long history of interdisciplinary research activities aimed at optimizing the efficiency and effectiveness of security and defense systems.
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We have unique research strengths in Health and Medical Systems applications. Faculty research has focused on modeling emergency operations in hospitals, rapid product prototyping and nano-manufacturing methods for biomedical engineering, modeling the functional abilities of wheeled mobility device uses for rehabilitation engineering, and injury risk reduction to promote health.
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redpajama_set_name: RedPajamaCommonCrawl


text:
Office of the President records on associations and organizations, 1974-1975
Identifier: UA 1085 Series 4 Sub-Series 4
Aeon Request
L. Tom Perry Special Collections
Office of the President records
From the Series: Contains material related to associations and organizations that had dealings with President Oaks. Organizations include on campus student body organizations, performing art groups and presentations, and alumni groups and publications like BYU Today. Other groups that have extensive correspondence include American Association of Presidents of Independent Colleges and Universities (AAPICU) and National Association of Independent Colleges and Universities (NAICU). Correspondence to other members, newsletters, and invitations to events are included. Correspondence to news outlets such as Deseret News and the Salt Lake Tribune in response to questions or inquiries are also included. Dates range from 1971 to 1980.
Restricted. Closed for 100 years from the date of creation of the records, and thereafter open to the public in accordance with the L. Tom Perry Special Collections Restriction Policy. Requests to access restricted materials in the University Archives should be submitted to the University Archivist.
It is the responsibility of the researcher to obtain any necessary copyright clearances. Permission to publish material from Office of the President records must be obtained from the Supervisor of Reference Services and/or the L. Tom Perry Special Collections Board of Curators.
From the Collection: The Brigham Young University President (1903- ) is the chief executive officer and general manager of the University.
Brigham Young University has had a president since Brigham Young Academy was changed to Brigham Young University in 1903. While the school was still called Brigham Young Academy the head officer was titled principal.
The Board of Trustees delegates to the University President the responsibility to conduct the operations of the institution and administer the policies enacted by the board. Since 1996, the President of the university has also been a General Authority of the Church.
Past and present Brigham Young University presidents include George H. Brimhall (1903-1921), Franklin S. Harris (1921-1945), Howard S. McDonald (1945-1949), (acting president) Christian Jensen (1949-1951), Ernest L. Wilkinson (1951-1971), Dallin H. Oaks (1971-1980), Jeffrey R. Holland (1980-1989), Rex E. Lee (1989-1995), Merrill J. Bateman (1996-2003), and Cecil O. Samuelson (2003- ).
From the Collection: Dallin H. Oaks (born 1932) a native of Provo, Utah, served as president of Brigham Young University, a Utah Supreme Court justice, and apostle of the Church of Jesus Christ of Latter-day Saints.
Dallin H. Oaks was born on August 12, 1932 in Provo, Utah. He Oaks was married on June 24, 1952 to June Dixon. They had six children. June passed away in July 1998 of cancer. Oaks remarried on August 25, 2000 to Kristen Meredith McMain. Oaks graduated from Brigham Young University in 1954 with a degree in accounting. He went on to graduate from the University of Chicago Law School in 1957. He practiced law and taught law in Chicago, including working on the University of Chicago Law faculty in 1961.
He was nominated president of Brigham Young University and served from 1971 to 1980. Following his presidency he served as a justice of the Utah Supreme Court from 1980 until 1984. Upon his resignation from the Utah Supreme Court Oaks began service as an apostle of the Church of Jesus Christ of Latter-day Saints.
From the Series: 22 boxes
File-level inventory available online. http://files.lib.byu.edu/ead/XML/UA1085.xml
Brigham Young University -- Students
Performing arts -- Utah -- Provo
Brigham Young University. Office of the President (Creator, Organization)
Oaks, Dallin H. (Contributor, Person)
Part of the L. Tom Perry Special Collections Repository
http://sc.lib.byu.edu/
Provo Utah 84602 United States
UA 1085 Series 4 Sub-Series 4, Office of the President records on associations and organizations, 1974-1975. Office of the President records, UA 1085. L. Tom Perry Special Collections. http://archives.lib.byu.edu/repositories/14/archival_objects/248356 Accessed January 18, 2021.


About 400 Laurens County friends and neighbors are diagnosed with cancer a year. As of April 30, 2017, we have 214 active clients on record.
We want to reach many more people and we need your help.
We would encourage you to join in the fun of the 2017 Run Like a Mann on September 16. We need business sponsorship's and run and walk participants so we can continue to provide support to those battling cancer.
You can register online by clicking here. You can also talk with any LCCA Board Member: G Ramage, Jay Peay, Dr. Joanne Brownlee, Teresa Bussey, Tracy Holland, Cindy Perry, Phyllis Staton, Lynn Mims, Gregg Nibert, or Janice Long You can also call the LCCA office at 833-3976 and talk with Ann Casey.
Hope to see you on September 16th!


We do not sell pirated Painting Life DVDs & VCDs. We recommend you to buy movies of original DVD & VCD.
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text:
Lakewood gets a doctorate in going the extra mile to help kids graduate
by Steve Powell
Thursday, August 30, 2018 2:22pm
LAKEWOOD – The Lakewood School District has become a master at graduating its seniors – with more than 90 percent making the grade the past two years.
But it hasn't always been that way.
In 2014-15, Lakewood was just a little bit better than the state average at 77.9 percent, improving to 86.6 percent the next year and 90.1 percent in 2016-17.
To compare, Marysville schools graduate 74.8 percent within four years, 77.5 percent in five years. Arlington graduates 77.9 percent in four years, 84.3 percent in five. The national average is about 75 percent, with the state average now at 79.1 percent.
Lakewood superintendent Michael Mack said to improve they first had to realize there was a problem.
"The state average was not where we wanted to be," he said.
That first year, administrators, counselors and teachers formed a team to come up with a plan to "lift up the seniors" so they could get the required credits to graduate. They each took three or four students individually, found out their histories, talked to their parents, and found out what they could immediately do to help.
"Just paying attention helped but it wasn't the answer," he said.
They looked at classes the student didn't pass and decided what work needed to be done to earn that credit. Students would do the work anytime they could: mornings, nights, weekends, etc.
One problem at Lakewood is it doesn't have an alternative school.
"There's not place for them to go but us," he said.
So the next year they looked at online programs that many alternative schools offer. They also started looking at juniors so they would have more time to make up the credits. They also started a summer school.
The program has kept growing with even more success. The next year summer school was even bigger and tutors were hired to help during the school year. This year's goal is to graduate at 92 percent.
Mack said being a small district helps. They can get to know the kids and figure out a good match to help them. For some, that means switching to the Open Doors program with the Arlington School District. But that can be a challenge.
"Kids really like us," he said. "They come to school every day and aren't any trouble. But they don't do anything."
Mack said they will push back and promise they will do the work, but he has to convince them Open Doors is a better program for them.
Mack said one thing he has had to overcome is that a student must graduate in four years.
"I was fixated" on that, he said. "But what's it matter if it's four, five or six?"
The most important thing, he added, is that they feel good about their sense of accomplishment by graduating.
"That they chose to invest in me maybe more than I was invested in me," Mack said.
He said Lakewood's district has developed the philosophy to do "all those little things" that their families are unable to do.
For example, they might pick up a student and take them to take their SATs, even paying for it.
"Hey, we need to do this," he said. "That's what we do."
Statewide statistics
•Asians graduate at the highest level at 86.5 percent. Native Americans graduate at 53.7 percent, homeless 46.1 percent and foster kids at 41.5 percent.
•Girls graduate at 81 percent, boys at 73.6 percent.
•The dropout average is 12.3 percent, with Native Americans at 26.6 percent and Asians at 6 percent.
•Boys drop out at 14 percent, girls at 10.5 percent.
•Reasons for dropping out include: Unknown 51.3 percent, unconfirmed transfers 25 percent, school not for me 7.2 percent.
•Advantages of graduating: Higher earnings, lower crime rate, better health.
-2015 annual report OSPI
Teacher negotiations
•Lakewood: Teachers on Wednesday are to ratify salary increases negotiated as an amendment to their present contract. School starts Sept. 5
•Arlington: The contract expires Friday at midnight. The school district and teachers were scheduled to negotiate Tuesday and Thursday. School starts Sept. 5.
•Marysville: A tentative agreement is to be ratified by teachers Thursday. First day of school Sept. 5.
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Ark: Survival Evolved is showing no signs of becoming extinct as it hits 1 million sales and introduces a suite of new Unreal Engine 4 modding tools.
It has taken only 30 days for the dinosaur-survival game to reach 1 million sales on Steam's Early Access Platform.
Riding on the success of its raptors, the game's developer Studio Wildcard has announced that user-generated mods will be coming to the title in the near future.
Powered by Unreal Engine 4 editing tools, the studio is working directly with Epic Games so that players can access these tools for free.
Known as the "Ark Dev Kit", the program features a simplified version of the Unreal Engine 4 Editor, compiled to streamline the process of creating maps and mods specifically for this title.
Content you create can immediately be uploaded to the Steam Workshop, allowing you to share creations with your friends and the wider community in a convenient and accessible fashion.
If we end up being able to make a super Tyrannosaurus rex that can fly and shoot lasers, we'll be more than satisfied. Personally, we can't wait to see how such comprehensive modding tools are utilised by a community as passionate as this one.


We, the Teens 'Nto Technology, are a group of Isanti County 4-H high school students that aspires to improve our community and our lives. We are working hard to organize our team by delegating areas of responsibility to each member. Our team was founded by Andrew Diers because he heard about FIRST and wanted our local community to have their very own team and to give local high school student the opportunity to make friends, learn more about robotics, and make some terrific memories. In the past season we have learned, practiced, and developed many mechanical, electronic, and communication skills, but will need to develop more.
"Seeing the finished product compete in a competition is what makes robotics worth it."
I am 15 and I am currently homeschooled. I live in Stanford Township. I am also in boy scouts and I am at the rank of Star. I am the Senior Patrol Leader of my troop which means I lead meetings and planning. I am in karate and I am one belt away from achieving black belt. I enjoy fishing, hunting, camping, biking, and canoeing.
This is my second year on the team, so far I have learned the importance of component placement on the electrical board how to effectively run wires and detailed electrical techniques. I have learned to trace problems when things go wrong and how to fix my mistakes. I have learned also to mentor new students to the best of my ability and to just have fun.
My name is Shelby Glissmeyer. I am 15 years old and this is my first year ever of robotics. I am a sophomore at St. Francis high school but i am part homeschooled. I joined the team because I wanted to try something new and it seemed really interesting. I am going to work with the electrical part of the robot the most this year I think. I also am working on new team shirts. Outside of robotics, I love to play volleyball and basketball and was on JV for both this year. I am going to continue playing next year. I hope I can learn lots of new things this year as a part of this team and I'm excited to start building!
This season I have learned many electrical terms and processes. I learned how to solder LED lights, crimp and ferrule wires, among many other things. I also learned what it takes to build a robot and how satisfying it is to see it finished.
"I loved helping build the robot this year!"
Hi! My name is Morgan. I am in the eighth grade and new to robotics. I enjoy reading, writing, camping, and all types of sports. I am excited to learn about all the different aspects of making, programming, and designing a robot. I hope to learn a lot of things and do some stuff during the build season.
how to drill holes, cut metal, measure things, and how important communication and organization are to making things run. I loved helping build the robot this year!
"Alone we are one, together we are dynamite. We are TNT."
I am 13 and live and go to school in the Saint Francis area. This is my first year on the team as a cadet member and I hope to learn a lot in this upcoming season. Some of my other interests besides robotics is the Boys Scouts where I am currently the rank of First Class and the Assistant Senior Patrol Leader in my troop. I also enjoy hunting, fishing, swimming, campingand single track mountain biking. I like to read in my spare time and play with my dog Brody.
I have learned some basic electrical mechanical and programming concepts while attending team meetings and seminar events like Jumpstart. I have developed public speaking skills through meeting with sponsors. At an off-season competition called Minne Mini I have learned how a robotics team brings together contributions from each member to prepare the robot; support the drive team and develop a winning strategy.
"When I was a boy, my mother made me wear safety glasses and I didn't like it. Now I am drive coach and I still don't like it."
I have always been interested in building things and figuring out how things work. I even dabbled in a little computer programming at the age of 14. I first heard about this program through a very interesting Popular Science article. My reactions to this article were like, "Wow, I wish I could do something like that." The next encounter that I had with FIRST was at an exhibit at the State Fair. Unfortunately, I was not able to attend the 2:00 demonstration, or I probably would have started that year. The final experience before my decision to join a team was the result of a Facebook message from one of my friends about a robotics competition at the U of M. It didn't take much thinking to realize that this was the same program. A couple of friends and I went down to this competition and I came to the conclusion that this was something I definitely wanted to get involved in. I started researching about FIRST and realized that there wasn't a team in our area, so I came to the decision to start my own. How hard could it be? Well, I started by making a poster about FIRST and displaying it at the County Fair as an opportunity to recruit more members. I also took this poster and did demonstrations at the various 4-H clubs in our area. I recruited 6 members that year and the team was able to take 17th out of 40 teams at a regional competition. The next year started out with two kids on the team. We weren't expecting to do too well that year, however we were able to place 6th out of 66. Since then, I have graduated and become a mentor for the team. This team has been good for me and I am currently studying to be a computer engineer.
"Ask not what FIRST can do for you, but what you can do for FIRST."
I bring to the team business management and planning skills. My work history includes accounting and tax preparation. Currently, a stay at home mom I have homeschooled our two boys since the fall of 2003 through Andrew's graduation in 2012. Even before jumping into the world of homeschooling, I have enjoyed teaching my boys and watching them learn. For example, every trip to the grocery store was a math and economics lesson. Our son, Andrew is the founder of this team. We have been a 4-H family since the fall of 1999 and I have been an approved leader since 2008. I have enjoyed watching my two boys learn about various projects, community service, themselves, and others through 4-H and have been involved in such projects as food and nutrition, shooting sports, photography, aerospace, gardening, and now robotics. As a parent of a child who started an invention notebook when he was 9, I was destined to become the leader of the Isanti County 4-H Robotics Team 8 years later. It is wonderful to watch the team discuss and pull ideas together. The satisfaction that is felt when a plan works out or when a month of fund raising nets the team $2,500 is indescribable. There are pitfalls to be sure, but the joy and fulfillment far outweighs the disappointments. Even the pitfalls are something to learn from and another opportunity to teach our youth. Setting this team up as a senior team mentoring a junior team was a way to pass some of the satisfaction of teaching others and watching them learn onto the senior team, helping them to learn valuable leadership skills they are bound to use in the future. It was exciting to see our team recognized as a leader when asked to teach electronics at the Jumpstart event. This year we added a monthly STEM program in which we have a hands activity geared towards 4th-12th graders and invite guest speakers come and share the different aspects of engineering with us. We look forward to seeing our FRC team grow in the future from the youth we have reached through this program.
"We choose to make a removable electric board. We choose this not because it is easy, but because it is hard."
I grew up watching my dad construct amazing things, and I have always been a builder myself, so I guess you could say creativity runs in the family. It just seemed natural when my son, Andrew, wanted to start a robotics team. I have been a machinist/tool and die maker for the first 18 years of my professional life. During this time I have enjoyed various opportunities to train/mentor others in the industry. When new economic realities forced a change in direction, I became a piano tuner/technician. I am currently head technician at Carlson's Piano World, as well as operate my own tuning business. As someone who has spent many years in the precision metalworking industry, I have sadly watched the decline of the manufacturing base of this country. To say that I am passionate about teaching the next generation to build things and work with their hands would be an understatement. Now, as our son graduated years since the team began, I ask myself, "Why am I still doing this?" As we place a high emphasis on service and "giving back" to FIRST we are often seen volunteering at FIRST Events. I, along with most of our mentors, are certified inspectors, and I have also become the "official" choir director of MN FIRST. It is thrilling to see how many students we have gotten to know through the years grown up and are now adult volunteers. We love getting back together with our "volunteer family", and the positive energy that exists there is priceless. We do more than build robots, we are building young people to take on a challenging new world by pushing them out of their comfort zone and exploring new things. I have been "accused" of being a professional. We simply do this because we love it, and believe in the FIRST program.
"Come on gentlemen, we need to prioritize."
As a 4-H member growing up, I loved participating in the electrical, livestock, computer, aerospace and small engine projects. My parents were very involved as leaders in 4-H. Now as a parent of three children who are active 4-H members and an Engineer, I have greatly enjoyed giving back through the years to an organization that has helped me so much. I have an Associate Degree in Laser Electro Technology and a Bachelor in Computer Science. I worked for 5 years in the Laser Industry, but wanted to design and program machines. I pursued my dream by going back to school and have been Engineering in Automation equipment for over 20 years now. This was my third season as a mentor with the Isanti County 4-H FRC Robotics Team 3840 through the FIRST (For Inspiration and Recognition of Science and Technology) organization. The program promotes technology through creativity with a new task each year. The teams learn a variety of individual skills, team problem solving, sportsmanship, and marketing, just to name a few. I think it's important to mentor young people. They are the next generation of Engineers. The FRC (FIRST Robotics Challenge Competition) builds a solid foundation in Industrial Technology. The FRC competition is an excellent experience where the students learn how the everyday Engineer solves industry demands. It was encouraging to mentor young people that share the same passion for the industry that I do. At work, I train newly hired graduates through the concept, design, and build process. As a mentor for the FRC during the build season, I was impressed with the skills and knowledge the team members had already gained through the program in the previous year. We focused on concept, design documentation, making schematics, and proper wiring this year. It would be a pleasure to hire any of these team members after college someday.
"The other teams said our intake motors were small and that may equate to something else. There is no problem, I assure you, there is no problem."
I have been into machines, computers and robots for my whole life. When I was really young I would make articulating mechanisms with paper and tape. When I was 5-7 I would try to make toys like cranes and amphibious boats with homemade electric motors using anything I had access to. None of my purchased electric toys survived very long because I dismembered them to figure out how they worked and use their parts. The older I got the faster my skills caught up with my imagination as I learned circuit design principles and soldering, got into DIY 3D printing in 2012, took welding classes, worked on FIRST teams, and anything else I could find time for.
When I was 11 (6th grade) I joined a 4H FLL team which I stayed on for 4 years. I then joined FIRST team 3840. I went in with the expectation to improve team building skills, but learned so much more. It taught me prioritizing and scheduling of projects in order to finish them on time. I also learned a lot about fabrication from Dean and trial and error during my 3 years as a student on the team. It was difficult to be part of FRC and take PSEO at the same time, but it was worth it. I finished about 12 years in 4H and am currently going to college for engineering. I help mentor the team part time, as well as maintaining and designing the website. Going to school, I have come to realize that many aspiring engineers have little to no experience with actual fabrication and application of principals. FIRST teaches practical skills, and I'm proud to be a part of that.
I am a mechanical engineer. I work at BAE Systems. I have worked on a variety of products using a variety of mechanical engineering disciplines. This is my first year as a mentor. I have enjoyed helping team 3840 on their robot this year.


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