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Aggregation of data in an interlocking trees datastore, especially when the interlocking datastore is a KStore is described. It details consolidating data into a summary or aggregation so that some particular desired analytic type of operation may easily be performed on the data. It uses a set of data constraints across the entire data set. This redefines the data set, which may be for example, individual receipts granular by week or month. When data is learned into a KStore, aggregation parameters may be collected and these parameters may be used to constrain the dataset recorded in K, and direct performance of an analytic on a particular a field value(s). Additional features and details are provided within.
1. A computer implemented method for obtaining desired information from an interlocking trees datastore comprising:
establishing aggregation parameters from received input,
traversing said interlocking trees datastore comprising elemental root nodes, subcomponent nodes and end-product nodes using asCase and asResult bidirectional links for determining paths within the interlocking trees datastore structure, with said established aggregation parameters so as to establish a set of paths within said interlocking trees datastore in accord with said established aggregation parameters,
wherein said interlocking trees data store has already recorded a collection of data such that relationships of said collection of data are modeled by said interlocking trees datastore, said interlocking trees datastore situated within memory accessible to a process running in a computer, said interlocking trees datastore comprising a structured collection of nodes connected by links of said nodes having pointers to other nodes of said interlocking trees datastore, wherein said nodes containing a count field, said nodes including at least nominally different kinds of nodes, a first kind called root nodes of which there are at least one primary root node and at least one elemental root node and which may include other root nodes, a second kind of node called an end of thought (EOT) node, at least one node of a third kind of node called a subcomponent node, and at least one node of a kind of node called an end product node, and wherein there exist at least two kinds of said links, Result and Case links, wherein said Result links point between a one of said root nodes and any other node, and wherein said bi-directional Result links point between a Result field of one node and an asResult list of another node, and wherein said bi-directional Case links point between the Case field of one node and an asCase list of another node.
2. A computer implemented method as set forth in
building an interlocking trees datastore via a Learn Engine reading data from a selected data set, and recording the relationships within said data set into said interlocking trees datastore.
3. The method of
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identifying any field variables needed to satisfy the fields,
traversing said interlocking trees datastore to root nodes having values for said identified any field variables, and
constructing variables from variable fields in said root nodes having said values.
15. The method of
16. The method of
sum, average, distinct count, distinct count percentage, distinct count ratio, record count, record count percentage, record count ratio, probability, Bayesian Classification analysis, decision tree, inultivariate analysis, association rules, market basket.
17. The method of
18. A computer system having software and hardware therein which when operating in said computer system:
establishes aggregation parameters from received input,
traverses an interlocking trees datastore comprising elemental root nodes, subcomponent nodes and end-product nodes using asCase and asResult bidirectional links for determining paths within the interlocking trees datastore structure, with said established aggregation parameters so as to establish a set of paths within said interlocking trees datastore in accord with said established aggregation parameters,
wherein said interlocking trees data store has already recorded a collection of data such that relationships of said collection of data are modeled by said interlocking trees datastore, said interlocking trees datastore situated within memory accessible to a process running in a computer, said interlocking trees datastore comprising a structured collection of nodes connected by links of said nodes having pointers to other nodes of said interlocking trees datastore, wherein said nodes containing a count field, said nodes including at least nominally different kinds of nodes, a first kind called root nodes of which there are at least one primary root node and at least one elemental root node and which may include other root nodes, a second kind of node called an end of thought (EOT) node, at least one node of a third kind of node called a subcomponent node, and at least one node of a kind of node called an end product node, and wherein there exist at least two kinds of said links, Result and Case links, wherein said Result links point between a one of said root nodes and any other node, and wherein said bi-directional Result links point between a Result field of one node and an asResult list of another node, and wherein said bi-directional Case links point between the Case field of one node and an asCase list of another node.
1. Field of Invention
The present invention relates to computing and in particular to the process in which data within an interlocking tree datastore is aggregated for expression in summary form, for various purposes such as performing distinct counts and statistical analysis.
2. Description of Related Art
Data aggregation is any process in which information is gathered and expressed in a summary form, to facilitate various purposes such as statistical analysis. Data aggregation methods for consolidating large amounts of complex data are fairly common in the art. For example, U.S. Pat. No. 6,768,995, entitled "Real-time aggregation of data within an enterprise planning environment," U.S. Patent Application Publication Nos. 2002/0143783 and 2005/0060325, both entitled "Method of a system for data aggregation employing dimensional hierarchy transformation," and 2003/0009443, entitled "Generic data aggregation" teach methods for aggregating data that is stored in relational databases. The techniques taught in these references include mechanisms to consolidate data as new data sets or within OLAP cubes so that analysis can be performed through scripts and algorithms.
U.S. Pat. No. 6,768,995, entitled "Real-time aggregation of data within an enterprise planning environment," mentioned above, teaches how to divide a database into the relational data area, the transactional data area, and server. The server publishes data from the transactional area to the relational area. The transactional area supports real-time interaction and the relational area allows detailed statistical analysis and report generation.
U.S. Patent Application Publication Nos. 2002/0143783 and 2005/0060325, mentioned above, teach a method of aggregating data having at least one dimension logically organized into multiple hierarchies of items, whereby such multiple hierarchies of items are transformed into a single hierarchy that is functionally equivalent to the multiple hierarchies. In the hierarchy transformation process, a given child item is linked with a parent item in the single hierarchy when no other child item linked to the parent item has a child item in common with the given child item.
U.S. Patent Application Publication No. 2003/0009443, entitled "Generic data aggregation," and also mentioned above, teaches methods, devices for increasing the speed of processing data by filtering, classifying, and generically applying logical functions to the data without data-specific instructions.
The forgoing systems and methods can often produce satisfying results. However, they all appear to use relational databases and methods in attempts to increase the speed of data aggregation. They also appear to teach how to design structures within relational databases that enable the user to separate transactional from relational (stored) data.
The KStore technology addresses many common problems associated with relational databases and the aggregation of data, by modeling that data into a structure with a predefined process that relates all new data to existing data within the interlocking trees datastore model. As described in U.S. patent application Ser. Nos. 10/385,421, entitled "System and method for storing and accessing data in an interlocking trees datastore" published as U.S. Patent Application Publication number 20040181547 on Sep. 16, 2004 and 10/666,382, entitled "System and method for storing and accessing data in an interlocling trees datastore" published as U.S. Patent Application Publication number 20050076011 on Apr. 7, 2005 the KStore data structure does not require any distinction between transactional data and stored (relational) data. A system for efficiently using an interlocking trees datastore as described in the '421 and '382 applications just mentioned was also described in U.S. patent application Ser. No. 10/879,329.
All references cited herein are incorporated herein by reference in their entireties.
This patent teaches a method to aggregate data in an interlocking trees datastore, especially when the interlocking datastore is a KStore. It particularly describes details of consolidating data into a summary or aggregation so that some particular desired analytic type of operation may easily be performed on the data. For example, the daily sales data may be aggregated so as to compute monthly and annual sales total amounts. Data may be summarized at multiple granularities.
The KStore Data Aggregation algorithm uses a set of data constraints across the entire data set. This redefines the data set, which may be for example, individual receipts granular by week or month. When data is learned into a KStore, aggregation parameters may be collected and these parameters may be used to constrain the dataset recorded in K, and direct performance of an analytic on a particular a field value(s).
This invention is unique in that it is the only process currently known that can perform the data aggregation and calculations on the unique interlocking trees datastore of the KStore.
Available relational database data aggregation tools do not support analysis on data recorded within the KStore datastore.
There is no need to design and build additional costly complex structures, as in the previous art, to hold transaction data for real-time interaction, and complex tables and OLAP cubes to hold relational data on which to perform statistical analysis if one is using the KStore technology.
The invention will be described in conjunction with the following drawings in which like reference numerals designate like elements and wherein:
Because the KStore represents its records in a unique structure unlike that of traditional databases, it requires a matched method to aggregate (summarize) records so that analytics may be performed upon data.
Within this patent, we use the terms "algorithm," "analytic," and "real-time analytic" to mean an organized procedure for evaluating data which may include some visual display, generating a report, performing a given type of calculation for example.
Data aggregation is any process in which information is gathered and expressed in a summary (or aggregated) form, for purposes such as statistical analysis. For example, daily sales data may be aggregated so as to compute monthly or annual total amounts. Likewise, individual components of the data may be used for different aggregations (such as by sales-person or by location) to get different kinds of knowledge from the same data, and the aggregation may be used to assist in generating such information.
Using our invention, data is read into KStore, aggregation parameters are collected or determined either from queries or automatically, and these parameters are used to constrain the dataset and perform an analytic on a particularfield(s). The KStore Data Aggregation analytic can find whether there is a co-occurrence of variables sought in a single record and it may also perform numeric calculations on data as identified in user-defined queries. In a preferred embodiment, it performs a summation calculation, but is not limited to that calculation; in other embodiments of the invention, it may perform analytics or calculations, such as averaging, distinct count, distinct count percentage, distinct count ratio, record count, record count percentage, record count ratio, among others.
(A "Distinct Count" analytic for example returns as results, a count of each distinct value in a given data set. With distinct count, duplicates are not counted. Distinct count is used when an exact count is needed. For example, if a sales manager wants to determine the number of items sold by a given salesperson, he would only seek the exact number of each different item sold by that salesperson. Thus, the ID of the salesperson of interest (his name or other indicator) would be the limiting focus for the distinct count).
Other ways to use the data pulled from this process are also accommodated. For example, if a salesperson in the above parenthetical were making sales of fungible goods by weight, adding up the total number of grams sold may be of interest as opposed to a distinct count, and in doing this, one would want to add the actual variables rather than the distinct count of items he sold.
Although we have described in the previously mentioned patent applications a system and method for creating an interlocking trees datastore, which we now call KStore, we feel it necessary to repeat some of the description in order to familiarize the reader with the concepts which the present invention takes for granted as existing technology, but we believe these concepts are found nowhere else in the computer data arts. We also describe the system it is used herein sufficient detail for this disclosure, but such a system was outlined in great detail in U.S. patent application Ser. No. 10/879,329 filed Jun. 29, 2004.
For convenient reference we generally describe the KStore data model structure here, although it can be found in more detail in the above-incorporated patent references. The KStore datastore is composed of multilevel interlocking trees. Construction of each level of the forest of interlocking trees captures information about a data stream by creating new nodes representing sequences of elements from an elemental dataset. The interlocking tree datastore itself generally comprises a first tree that depends from a first root node and may include a plurality of branches. Each of the branches of the first tree ends in a leaf node, which we now call an "end product node." A second root of the same tree-based datastore is linked to each leaf node representing an end product. Finally, the tree-based datastore comprises a plurality of trees in which the root node of each of these trees can be described as an elemental node. The root node of each of these trees may be linked to one or more nodes in one or more branches of the first tree. The nodes of the tree-based datastore contain (mostly) only pointers (usually bidirectional) to other nodes in the tree-based datastore, instead of data per se, and may also contain additional fields wherein one such additional field may be a "count field."
Refer to FIG. 12a of US Patent Application Publication Number 20050076011, also published as related publication WO 2004081710, which defines the specific fields in a generalized node structure. Note that the bi-directional Result links point between a Result field of one node and an asResult list of another node, and the bi-directional Case links point between the Case field of one node and an asCase list of another node
In earlier applications we did not distinguish forward looking from backward looking links by terminology. Hence, we may have used Case links or asCase links to refer to links between BOT nodes and the paths of nodes that were on the asCase list indiscriminately. Now, however, we prefer to refer to asCase links as links pointing from the BOT nodes and subcomponent nodes toward their EOT nodes and Case links pointing back toward the BOT node from EOT or subcomponent nodes, thus giving directionality to the terminology. We have adopted similar terminology for asResult and Result links, with the asResult links pointing from the root nodes toward their Results (subcomponent nodes, typically) and Result links pointing back toward their root nodes.
It will be appreciated that the aforementioned relational information is actually recorded within the structure of the interlocking trees datastore that is built, rather than explicitly stored in the subcomponent and end product nodes of the tree. Because only the elemental root nodes of the interlocking trees datastore may include "data" or values, links can be followed back to the root nodes to determine or reconstruct the original data from the data stream from which a KStore is constructed.
Referring now to
Generally, if it is a user whose request is being facilitated, the Data Aggregation GUI 503 will be most likely be displayed on the user's computer screen, although any type of interface including at least audio or graphic input is useful for receiving input into the process. The output or display 505 which will convey the results to the user will also be available to the user through a computer interface of some kind. If the request is being done through an application, the component 503 will be an interface for receiving input from the application rather than a user interface, but the activity to which it is put will be analogous. The data aggregation analytic 508 will generally be on the same computer system in which the KStore 511 is present; however, given the nature of networked computing today, this is certainly not a requirement. The channel 506 may have various hardware and/or software components in it, based on the implementation. If this is a network, clearly different protocols would be needed to support this communication channel than if the user is accessing a KStore through a single computer.
The communications channels 509 and 510 too will be populated with various important and necessary components which are not necessary to discuss here in detail as they are already understood to one who has read and understood our prior published patent applications. For example, a K Engine is generally used to communicate between any application and a KStore. Various other components such a Learn Engines and Query functions can also be within this channel, supporting, formatting, and aiding with their own assigned memories the completion of the task at hand. Refer to
The KStore 71 is in a server computer system 73. The server can be any kind of general purpose computing system; the ones we have used are multiprocessor systems that allow for multiple partitions. The physical data store 74 can be any kind of data storage system preferably closely tied to or part of a computer system (or server) 73 for convenient access.
The API Utilities are the Utilities portions 98 (U1-Un) that handle the calls to the K Engine and provide the interface to the data stores that track the lists of addresses that may be needed to organize the individual calls to satisfy a query. The segments 97 may be a set of analytic applications that are provided to queries through the API. These queries are selected or constructed either by a user through solution specific screens 92, or directly through any means of access, such as a GUI or other program and the like. There are two types of U portions in the API Utilities. Note that U2 and U3 connect directly to K 71. This is drawn so as to call attention to the functionality in which some few, but generally not all, API Utilities are able to directly access K. API Utility calls to KEngine.
Referring back to
The GUI 503 communicates with the Data Aggregation analytic 508 by way of the bi-directional channel 506, 507 in order to provide input from the user 501 to the analytic 508. The results of the aggregation analytic, an aggregated data set, may be stored or used in different ways. In one preferred embodiment of this invention, the results of the analytic may be displayed on a graphical display device 505. In another embodiment the results may be directed to store the aggregated data set as summary records, which could be produced in some proprietary or other useful or open format such as XML. In yet another, they may be used to create different an entirely new KStore data structure 511 from the summary records. The results could also be held as the (or copies of the) K paths from the original KStore data structure from which the summary record if desired, which itself could be stored in a new KStore structure or other data record format. The input of the user 501 consists of constraints to be used to limit access to only the data of interest from the KStore 511 in order to obtain answers to queries entered and aggregation parameters. The constraints and parameters collected by the analytic block 508 are discussed in more detail below.
Refer to
Collect Aggregation Parameters
This step in this process is to collect the data aggregation parameters 521. These will likely be or have been user-defined to constrain the data to only the information that is needed. This patent will explain how data may come into the Data Aggregation user interface and analytic from another KStore application through XML. (eXtensible Markup Language.) XML is a subset of SGML constituting a particular text markup language for interchange of structured data. It should be noted thatwhile this patent explains Data Aggregation using the input via XML, that this is not the only way aggregation parameters can be defined nor transmitted to the Data Aggregation user interface and analytic; this is one method. Programmers versed in other methods could write a program to define the aggregation parameters and to transmit parameters to the analytic.
One type of aggregation parameter is field groups. Field Groups are user-defined groupings of field variables that can be used to associate data that isn't inherently associated within the KStore data structure. Another type of aggregation parameter can be inherent groups in the data, such as field names to field values. Depending on what information the user (or program or system) may want from the data, the user (or program or system) will select such groupings that may be appropriate.
There is an infinite range of groupings possible, but we will start with a description of a basic one for example purposes, and, for ease of illustration and understanding, use a K with its data tabularized. The data set consists of 15 records, composed of 5 fields. These example records are:
Refer to
Because aggregation parameters, such as field variable groupings are actually user-defined, they do not appear in the diagram representation of a KStore. One such user-defined group might be "Area" where geographic areas of the United States might be defined as "East," "West," North," and "South." It should be noted that a user may further constrain the data by nesting field groups within other field groups. For example, such nested user-defined groups within the "Area" field group might be "East" and "South," where states such as NJ, NY, and PA are grouped into "East" and "SC" and "GA" are grouped into "South."
Thus if we were constrained to find the number of "Sold" records for the grouping "East," the answer is in the "Sold" node on those records that include NJ, NY, or PA. In this example there are eight such records. Note that this is done without reference to any tables, without having to characterize or reorganize the data, and without having to recompile any data or any subset thereof to get these kinds of answers.
In a preferred embodiment
Define the Set of Queries
The second step in the process is for a user to define a query 522 or a set of queries using the Data Aggregation user interface. These queries will be processing the data in a KStore structure in accordance with data groupings defined by the data aggregation parameters. Also, these queries may be processed on a static KStore, a KStore that is not learning, or a dynamic (real time) KStore, a KStore that is continuing to learn.
A Data Aggregation query is structured in a unique way to enable the Data Aggregation analytic to process the aggregation parameters, locate the data within the KStore's forest of interconnected trees, constrain the records, and process the summations (or other analytic computation as the case may be). The Data Aggregation analytic uses the knowledge recorded by the KStore Engine in the KStore structure and implements special scripts that capitalize on this information. Different from the prior art, KStore analytics use information contained within the KStore structure, such as the number of occurrences of a variable and the relationship of that variable with the rest of the data in the data store and do not require additional data structures such as tables and indexes to be constructed or maintained.
Although we demonstrate only a single analytic, that is, a sum analytic, we also mention the distinct count analytic, and note that there are numerous others. We are not foreclosing the use of any other analytic with this invention, many of which we are currently developing, and some of which are versions of commonly known analytics used for Business Intelligence, Data Mining, or statistical data analysis projects. Such analytics commonly go by names such as Bayesian Classification analysis, decision trees, multivariate analysis, association rules, market basket, and so on.
Building a Query
Refer to
In effect, the components in the channel 509, 510 of
The user may also apply a global filter on the field group. A global filter defines a sub-set of the original record set, as a base. In effect, this adds an additional layer of constraint to the aggregation analytic processes. In
This is consistent with the concept of further determining a context as also defined in published U.S. patent application Ser. No. 10/666,382 (which has US Publication number 20050076011).
The user may also identify which field name contains the values he wants the summation calculation to be performed on for the selected field group ("Area"). To do this the user selects the numeric field, which can be summed, from those data fields in the Category box 532. In this example the user selects to sum sales for Fridays within the East and South "Areas." He does this by selecting "sales" in the "Category" box 532 and pressing the "Add" button 535. The "Display" 536 reflects that the user has chosen, for the "Category" "Sales," to perform the function: "Sum." The last column "Display Column" is a user-defined field that is used to identify what is being calculated. The results will be stored in a column with the same name as the display column. In this example, the "Display Column" for the "Category" "Sales" displays "Total Sales" 537. Thus, the count of Friday's sales records within this context will be determined in accord with the description of how a focus is identified within each K path, in published U.S. patent application Ser. No. 10/666,382, referenced above. If the value of the focus is required, as it is for a sum analytic, the value may be reconstructed from the sensor nodes as described in US Patent application No. 10,385,421, published as 20040181547. Then the summation is the selected analytic, and the sum is produced based on the data from the constrained and focused part of the KStore being queried, yielding the result desired.
Refer to
The user can further constrain the data for a particular display category by adding a "display filter." In this example, the user wants to see Friday sales (for the same areas as above) but only for the months June and July of the given year. To do this the user selects a display row such as 541. The user then selects the category "Month" 542 and the month to associate with the given display row—in this example, it is "Jun: 543. The user then presses the Add button 544 and the filter "Month/Jun" displays 545.
In this example, the user has built two queries; one will calculate the total number of sales for the field group "Area" (East and South) for Fridays in May, and another similar one for June.
Before explaining what happens when the user presses the "Aggregate" button 546, we will explain how queries are structured to take advantage of the KStore's unique data structure.
The Structure of a Query
For the aggregation analytic to process a query, it is laid out in a structure that recognizable by the KStore system, which supplies the elements of the query to the KStore through the K Engine. As the user defines the query, the query is built. The structure of the query consists of two components: Field Group Definitions and Processing Directives. Each is discussed below.
Field Group Definitions
The field groups, which may be created using either KStore tools or other software, are transmitted to the Data Aggregation analytic via XML (or some other communication protocol,) and are an early component of the query.
For every field group record that comes into the Data Aggregation analytic, there is a field name and field value pair. Conceptually, as this data comes into the analytic, a table is constructed that contains the data for field group each record.
Refer to
The second column is the "Field Type" column. There are three field type options: "Field Group", "K," and a "Mask." The "Field Group" option tells the analytic that the incoming data has been grouped into a user-defined category and must be treated as a group within a group.
The "K" option indicates that the field name/field value pair represents only one field name/field value in the KStore data structure. Table 555 in
The "Mask" option indicates that the field name/field value pair may represent more than one field name/field value in the KStore data structure. In a preferred embodiment, the masking directive may be the computational "regular expression," which is commonly known as a wildcard (*). For example, fora zip code, the "mask" value would be a portion of the zip code and an asterisk (*), or 19*. This tells the analytic to include "all" zip codes that begin with the digits "19". Other masking options are described in our U.S. patent application Ser. No. 11/132,490 filed May 19, 2005 and entitled Variable Masking, incorporated herein by reference for background on masks.
The third column is the "Field Name" that identifies the field within the field group. The fourth column identifies the field value, as explained above. The fifth and sixth columns identify any associated attributes and attribute values for the field group. Attributes allow filtering of fields within a field group.
Processing Directives
A query is also composed of the processing directives, or a command telling the analytic how to process the field group definitions and global filter constraints that are associated with the query. In effect, it is telling the analytic what to do with the data coming in.
There are currently three preferred embodiment processing command directives: the "Global Filter Commands," "Group By" groupings and the "Display Directives."
Global Filter Commands
The global filter commands define the sub-set of the records to consider. These commands tell the analytic what data to filter out and which data to process. In effect, these commands act to constrain the data in the K that are processed. For example, in our explanation of building a query, we created a global filter "DayofWeek" with the constraint "Friday."
The Global Filter Command has three options: Field Name, Field Type, and Field Value.
The Field Name is simply the name of the field on which to constrain the data.
The Field Type option tells the analytic how to interpret the meaning of the field name and the field value. There are four ways that the field type can be used, each identified by a separate command option.
The first field type command option is "K," which tells the analytic to interpret the field name as exactly whatever appears in the field name and the field value as whatever appears in the field value field.
The second field type command option is "mask." The "Mask" option indicates that the field name/field value pair may represent more than one field nametfield value in the KStore data structure. In a preferred embodiment, the masking directive may be the computational "regular expression," which is commonly known as a wildcard (*). For example, for a zip code, the "mask" value would be a portion of the zip code and an asterisk (*), or 19*. This tells the analytic to include "all" zip codes that begin with the digits "19". Other masking options are described in the aforementioned our U.S. patent application Ser. No. 11/132,490 filed May 19, 2005 and entitled Variable.
The third field type command option is "field group." A field grouping is a constraint set having a user defined logical relation between them. In
The fourth field type is "attribute." If the field type is set to "attribute," this tells the analytic to interpret the attribute name as whateverappears as the field name and the attribute value as whatever appears in the field value field. Attributes allow filtering of fields within a field group.
Group by Commands
The "Group By" Command tells the analytic how to process the field group definitions and the global filters that were defined by the user when the query is constructed.
The preferred embodiment "Group By" Command has the same options as the Global Filter Commands, with one additional option: Field Name, Field Value, Field Type, and display name. Refer to the explanation of each option under Global Filter Commands above.
There are two components of process "Group Bys." The first is that the analytic will attempt to resolve the "group by" items and the second is thatthe analytic will attempt to resolve the constraints associated with the group by items.
Resolving "Group by" Items
If the query contains "Group By" items, the analytic will look up in the field group definitions all of the immediate values within the field group. For example, fora field group called "Area," the analytic will look up all the values within the data layout that are within the "Area" field group, in this example that might be two user-defined values: "East" and "South." In effect, the analytic must first identify the data set on which to perform the aggregation and calculation.
Resolving Constraints
The second component of processing "Group By" items is to resolve the constraints within the field group. The constraints are applied in addition to the global filters for that field group item. When processing actually occurs, the smallest constraints are preferably applied first.
Display Directives
The next type of processing directive is the display directive. In a preferred embodiment there may be one display directive, "sum," however, there are no limitations on the number of additional analytic directives such as averaging, distinct count, distinct count percentage, distinct count ratio, record count, record count percentage, record count ratio, among others, that may be used.
Refer back to
The user may further constrain what will be summed by adding filters to the categories as explained in the previous discussion on building queries.
Still referring to
It should be noted that this could all be done automatically by a software process, which itself does an aggregation when it has all the other information for defining query parameters by simply calling the process that a user calls by pressing the button 538.
Run Aggregation Analytic
The third step in the overall Data Aggregation process flow 520 is to run the Aggregation Analytic against the KStore data structure 523.
The Aggregation Analytic process is preferably composed of the following: optionally build internal "K," determine type of analytic, constrain records based on global filters, build output records, and output query response.
Build Internal K of Field Groups
First the Data Aggregation analytic reads the field group records that, in this discussion are input in XML format from the Data Aggregation user interface. It is important to note, as mentioned above, that XML is only one way to transmit data within Data Aggregation and that other formats and input means could be used. The Data Aggregation analytic then converts the records to KStore defined records, and builds a temporary K. The temporary K is preferably built in the exactway that primary K is built by invoking the "Learn" utility previously referred to in U.S. patent application Ser. Nos. 10/385,421. In our following example we use the field group "Area" which contains both "South" and "East" defined by zip code records.
Of course, this build step can be skipped if the temporary K is already built from some previous processing.
Determine Type of Analytic to Perform
Second, the type of analytic is parsed from the data set returned from the Data Aggregation user interface. In our example it is the analytic "Sum". As mentioned previously, forthis current patent, the SUM function is the only mathematical function implemented in Data Aggregation, but as mentioned earlier, other possible functions can be created, such as averaging, distinct count, distinct count percentage, distinct count ratio, record count, record count percentage, record count ratio, among others. Also note that the user can opt to just aggregate data and not perform any type of mathematical function, or even to display it in some particular manner that makes the information easier to see or use.
Constrain Records Based on Global Filters
Third, the Data Aggregation analytic continues to read the data returned from the Data Aggregation user interface an item at a time and builds "Group By" lists used to perform the analytic against. Each "Group By" list is a list of all permutations of "Group By" items constrained by the Global Filters if they exist. The "Group By" list is used to traverse the K and the analytic is performed against the set of records defined in the "Group By" list.
Build Output Records
Fourth, the response to data aggregation is constructed in the format of a result summary record. These records are used to build output responses for data aggregation, may be stored, as in a file, directed to a different or entirely new K (interlocking data structure), or directed to a charting application. These records may also be output to a standard record processing application, such as a spreadsheet, for further analysis.
Output Query Response
Fifth, the results of the query are output to the user 524 as shown in the process flow 520. In our example, the response to the query is automatically displayed in the KStore Record Explorer 560. However, it may also be displayed, charted, or stored in a simple file format to disk.
Refer to
Generally then, Once the group data is passed to the Data Aggregation user interface, the user is able to define the global filters (constraints), the directives by which to group and the directives by which to calculate.
Once the query is built, it can be sent to a chosen or predetermined Data Aggregation analytic within the K Server. The K Server receives the filters, field group definitions, aggregation directives, and sum directives in XML. The Data Aggregation analytic processes the aggregation and returns the resulting summary records, in XML and/or redirects the output to another K. The results, in tabular format, contain only the constrained information and a total sum of the mathematical fields identified. In one preferred embodiment, the calculations that can be performed include mathematical summation (the sum of one or many values). Other versions of Data Aggregation may allow performing other mathematical calculations (such as averaging).
Once the analytics are performed, the KStore Record Explorer displays the results table (including the column headings of the field groups and the associated calculated (summed) fields.
Believing that the invention has been fully described above in sufficient detail to enable those of ordinary skill in these arts to make and use the same, the scope of this invention is limited only by the following claims.
Patent Citations
Non-Patent Citations
Referenced by
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Original Image


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Aberdeen Caledonian Thistle Celtic Dundee United Hearts Hibernian Kilmarnock Motherwell Partick Thistle Ross County St Johnstone St Mirren
Birmingham City Blackburn Rovers Blackpool Bolton Wanderers Bournemouth Brentford Brighton & Hove Albion Cardiff City Charlton Athletic Derby County Fulham Huddersfield Town Ipswich Town Leeds United Middlesbrough Millwall Norwich City Nottingham Forest Reading Rotherham United Sheffield Wednesday Watford Wigan Athletic
Emmanuel Adebayor and Rafael van der Vaart boost for Tottenham
TOTTENHAM will be boosted by the return of Emmanuel Adebayor and Rafael van der Vaart when they face Arsenal.
I'm recovering well from my injury. I will start to focus on the match against Arsenal
Both men missed last weekend's FA Cup draw with Stevenage but are fit for Sunday's north London derby.
Emmanuel Adebayor, who has been out with a knee injury, will run a gauntlet of hate on his return to his former club.
Van der Vaart missed Tottenham's last three games with a calf injury.
He said: "I'm recovering well from my injury. I will start to focus on the match against Arsenal.
"I'll be happy to play Arsenal. I can't wait."Ade 'n Vaart boost

subset: commoncrawl


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Plans for fifth large solar farm in South Hams village
Posted: July 09, 2014|
Plans have been unveiled by a German company to build the fifth large-scale solar farm in a tiny corner of South Devon.
The renewable firm New Energy for the World wants to construct a ground-mounted array of panels on a farmer's field on the outskirts of Harberton, near Totnes.
Opponents gathered outside the village hall wearing sunglasses yesterday in protest at what they call the industrialisation of the countryside.
Nearby land at Marley Head, Blue Post, Hazard, and Dartington has already been covered with photo-voltaic (PV) panels and another scheme by AEE Renewables to install 45,000 panels at Diptford is now in the hands of the Secretary of State, amid concerns at the cumulative impact of the projects. The scheme at Coombeshead Farm, Diptford, prompted Tory MP Sarah Wollaston to lament more "beautiful landscape lost to large-scale solar industrialisation". Campaigners say covering a "prominent hilltop" site with a further 24 acres of productive farmland is akin to a "solar eclipse" of the countryside.
The developers, attracted by easy availability of connection to the national grid, say the impact on the landscape has been "hyped up".
Shona Duncan, spokesman for the Campaign Against the Harberton Solar Industrial Estate (CAHSIE), said "green fields should be for growing food, not harvesting government subsidies".
"This isn't just about the desecration of a huge field in Harberton. People from throughout the South Hams have had enough of this industrialisation of our countryside," she added.
"Government policy is that solar PV arrays should be concentrated on roofs, along main roads and on brownfield sites. "It's up to South Hams District Council now to enforce that policy and stop the desecration of the countryside."
The annual report of renewable industry body Regen South West revealed a record surge in solar panels last year, accounting for 67% of all new installed electricity capacity in the South West.
Conservative South Hams council is said to have approved 25 out of the 28 applications for large scale solar PV developments it received up until last year, with two withdrawn by the developers and one turned down.
New Energy for the World, which is based in the Bavarian town of Regensburg, says the 5MW scheme had already been scaled back by 1,200 panel to satisfy residents.
Project manager Jimmy Offley said claims the Belsford site was widely visible were "hyped". "The solar park cannot be seen from anywhere, it is nicely tucked away on a south facing hillside," he added. "There are so many hedgerows that it cannot be overseen apart from a couple of glimpses."
Penny Mills, from the Campaign to Protect Rural England, said more than 3,400 acres of Devon farm land was taken by solar farms.


text:
Application Information
Scholarship Overview
This scholarship is for graduating seniors from Trinity Christian High School in Lubbock, Texas. To qualify for this scholarship, applicants must be recipients of the Trinity Christian High School Lion Heart Award.
How easy is it to apply?
Not too bad
This scholarship's application process may have items such as essays that could take a couple hours.
How much competition is there?
Relatively little!
This scholarship has a relatively low number of applicants.
Class Year: Is this you?
- High school senior
Home State: Is this you?
- Texas
High School: Is this you?
- Trinity Christian High School
More Requirements:
Must be the recipient of the Lion Heart Award.


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Hotels in 08050 - Manahawkin NJ
Only hotels in 08050 zip code are listed below. Search for cheap and discount hotel rates in Manahawkin, NJ for your upcoming leisure or conference / group travel. We list the best 08050 hotels and motels so you can review the Manahawkin hotel list below to find the perfect lodging. Hotels in Ocean county and area code 609 are also listed.
08050 Hotels/Accommodations
Next: Show All Available 08050 Hotels with Pricing >


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Combining the clean aesthetic of sleek glass-topped steel tins with the functionality of keeping seeds fresh, Potting Shed Creations' Pocket Gardens create distinctive theme-based gardens for the yard, containers or window boxes.
Herbal Tea Garden (lavender, anise, German chamomile, peppermint, and wild bergamot) A unique selection of the finest herbal teas ready to grow in your garden or window box . Growing herbs in your own garden will ensure that they are chemical-free and weed-free at harvest. Many of these herbs would also grow well indoors. Includes: recycled US steel tin, 5 seed varieties, garden stakes, directions with tips. Tin 5" diam.
Made by Potting Shed Creations, celebrating the art of gardening and the art of design.


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Part one of the Basketball Wives reunion is over so…What did you think?? We're surprised it wasn't more heated (although hearing Evelyn yell for security was pretty hilarious), but no punches were thrown and there were no major attacks to speak of. We did want to highlight a few of the biggest moments though, so just to recap, here's a list of the biggest issues that were touched on and some of the best images from the show.
1. What's Gotten Into Royce?
Right off the bat, host John Salley asked the question that had been on everyone's mind all season, "What was Royce's deal during the season two reunion?" While Royce speaks to that a bit more extensively in our upcoming interview with her, she "got to the point where [she] was sick of them talking all sorts of sideways" and decided to start standing up for herself. But the real kicker was when she explained "Now that their time is up and my time is now, it's a problem." Tell us how you really feel, girl.
2. Jennifer Williams Vs. Eric Williams
After a finale like the one we saw which culminated with Eric Williams throwing a drink in Jennifer's face, she addressed the issue diplomatically on-air, saying she's just ready "to leave that life behind." Tami, always to the point, called what Eric did "a bitch move." Of course the issue we really want addressed is what Jen said to (or about?) Eric's mother, which seemed to cause Eric to fly off the handle to begin with. Alas, we won't be privy to those details any time soon. As I mentioned in my preview post last week, Eric did indeed have a dressing room set aside backstage in case he decided to come to the reunion, but at the last minute, he decided not to.
3. Suzie's Foot In Mouth Disease, Part I
It wouldn't be an episode of Basketball Wives if Suzie didn't say a little too much. Our favorite example of this during the reunion was when she explained: "Honestly, I care about everyone…even you, Meeka." Meeka's like…"Thanks?" It's not especially dramatic, but that's our Suzie! Suzie has an even bigger "taking it too far" moment in part two, though, so just you wait.
4. Meeka's Thirsty and Wearing Bootleg Earrings
"Thirsty means you want attention," Evelyn said when she pointed out that that's exactly what she thinks Meeka is. The girls ganged up on Meeka at the end of the show calling her out for possibly hiring her own paparazzi and trying to be a star on the show. And that of course led to the earring conversation. When Meeka started talking about her style, that's when Evelyn took offense. "You were rocking the same earrings as we wore since season one, you were trying so hard to be a part!" Evelyn said.
Meeka then claimed all her earrings were custom made by her stylist who she then brought out.
"They're bootleg, then," Evelyn said before Meeka actually brought out her stylist to back her up. That didn't help her case, unfortunately.
5. Tami Hoodrat Roman Vs. Meeka Liar Claxton
"You can ask me 20,000 times if I like you, the answer's still no!" Tami told Meeka at the beginning of their very special segment. These women, it's safe to say, will never solve their differences, especially not when they keep having exchanges like this:
Tami: "From the time you came into the situation, all you did was lie! That's like Meeka Liar Claxton. MLC!"
Meeka: "And you're THR, Tami Hoodrat Roman."
John Salley's face says it all:
And of course, this is just part one. Part two of the Basketball Wives reunion special airs on Monday, August 22 at 8 p.m. ET/PT. Tami Roman and Shaunie O'Neal will also be appearing on Extra on Tuesday, August 16, so be sure to check your local listings for even more of their commentary and reaction to the reunion.


text: Michael Shalayeff > Making, drinking tea and reading an opus magnum from Greg Thomas: > >> My real name is there for everyone to see. I use getbsd@ for the >> OpenBSD >> lists. Is that a problem? Not everyone can have mickey_(_at_)__(_dot_)_ > > so can you explain how do i get some bsd? > Dude, can't you read your own site? http://www.openbsd.org/mail.html Cheers, getbsd


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Food Flashes
Food Flashes focuses on what's happening in the dining community, from restaurant openings and closings, to chef changes, to heart-healthy menus to kids' specials.
Posts by Author
Beer tasting tonight – 4/22, Earth Day stuff
The Cove's monthly beer tasting is tonight starting at 7:30 p.m. and will set you back a whole $5. They are featuring four Saint Arnold beers with appetizers and music from King Pelican too. Not sure which beers, but Saint Arnold Pils is fresh out of the brewery so this might be your first chance […] [Read More]
Texans among Top 50 brewers
The Brewers Association released their list of the Top 50 craft (and overall) brewers in the nation in terms of beer sales volume. Spoetzel Brewery, "the little brewery in Shiner" came in fourth among craft brewers and ninth overall Rank Brewing Company City State 1 Boston Beer Co. Boston MA 2 Sierra Nevada Brewing Co. […] [Read More]
Alamo City Cerveza Fest Winners
Winners for this past weekend's Alamo City Cerveza Fest, hosted by the Bexar Brewers, have been released. The big winner was Maibock from J & J Brew Crew who were part of the Foam Rangers home brew club from Houston. Funkiest of Show went to Mark Schoppe of the Austin Zealots. The head brewer at […] [Read More]
Texans take home medals at World Beer Cup
The Brewer's Association's World Beer Cup was held this past weekend in Chicago and a couple of breweries from our fair state pulled in medals. In the Kellerbier/Zwickelbier category the Hell In Keller from Uncle Billy's Brew & Que in Austin took the Bronze in a group of 32 entries. [Read More]
Beer news roundup
The press releases are piling up here on the beer desk. Here's a rundown of what's going on at our area breweries. Real Ale Devil's Backbone – It's out and on store shelves all around the area. It's mighty fine and will be around through late July. Mysterium Verum – Real's barrel-aging program is rolling […] [Read More]
Freetail April calendar
I just happened to be at Freetail the other night and was sad to see the Buffalo Hump IPA was all gone. They are actually a little low on beer right now with no IPAs on the board. From their facebook page: Inventory Day… looks you folks drank all the beer! Guess we'll have to […] [Read More]
Rahr Brewing coming back to life
You may recall that during a recent snow storm in Fort Worth Rahr Brewing's roof collapsed under the weight. From a recent posting on Reddit.com it looks like their well on their way to recovery and keeping their sense of humor intact. More videos after the jump. [Read More]
Southern Star on the rise
Over at our sister site Chron.com, Chronicle beer writer Ronnie Crocker wrote about the expansion going on at Southern Star Brewing in Conroe. Southern Star produced about 700 barrels of beer in 2008, and Fougeron and Hutchins figure they gave away 300 of those. Production climbed to 1,500 barrels last year, however, and the company […] [Read More]
Beer tasting tonight – 3/25
The monthly beer tasting at The Cove is upon us once again tonight. From their e-mail: The 4th Thursday of every month is Beer Tasting time here at The Cove! Come and join us tomorrow evening, March 25th @ 7:30pm, taste some brew, snack on some great appetizers, and have a rocking time while listening […] [Read More]
Freetail going strong, calendar packed
On the heals of yesterday's announcement that craft beer sales were up in spite of overall beer sales being in decline, Freetail Brewing released their own statistics. They say that they "posted an increase of 282 percent in beer sales for the year after normalizing 2008 results to account for partial year operations in 2008. […] [Read More]
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UTSA Sports
E-N coverage of the San Antonio institution.
Monthly Archive for March, 2012
UTSA looks to Katy with anticipation
Though UTSA junior Kannon Burrage did not play on last year's NCAA tournament team, the reminders of the finest postseason in school history are impossible to escape. Teammates still talk about the run, in which the Roadrunners knocked off the top three seeds at the Southland Conference tournament before beating Alabama State for their first NCAA victory. […] [Read More]
2012 football schedule revealed (updated)
Update, 8:30 p.m.: Texas State athletic director Larry Teis sounds less than enthused about a permanent move to the Alamodome for the Bobcats/UTSA game. "Why would we give up a home game?" he said. "Why would we? I've got 13 people paying $30,000 a year for suites and 360 people paying $2,000 (annually) for club […] [Read More]
Recap: UTSA 97, UT Arlington 88
Where has that been over the past five weeks? OK, so UTSA's 97-88 victory over UT Arlington at the Convocation Center wasn't perfect. But even after squandering most of what should have been an insurmountable 18-point lead with 4:33 remaining, the Roadrunners appeared to finally shake off the rust that plagued them for most of […] [Read More]
Podcast with Kevin Brown
Sorry for the extreme lateness — to quote Carl Spackler, I was unavoidably detained — but I had a chance to speak with newly christened UTSA offensive coordinator Kevin Brown for about 15 minutes before last Saturday's home basketball game. I had very, very few dealings with Brown last year in his rather anonymous duties […] [Read More]
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I figured I would forgo the traditional birthday cake and make it a pretty celebration. "Cup cakes again!!!", you ask? Why, yes! Cup cakes are fun and make celebrating more interesting.
I used coconut cake (from scratch) with buttercream icing, then dipped some in coconut, or dropped the flakes on top. I added some blue sugar crystals in the flakes, to give more bling!
Step 1:
For some heavenly reason, this way of eating this cupcake tasted the best of all! Maybe because it was sweet, but just the right amount of sweetness :) I cut up a few cup cakes, put some in the tube, then some icing and a sprinkle of coconut flakes, then repeated until I ended with icing. Topped that with coconut by dipping into a fluffy pile of flakes! Oh how sweet it was!
Step 2: Fill'em up!
I know, I'm silly - but these pretty things were so delicious! Sometimes a cup cake looks so good, but when you finally plunge in with a big bite - disappointment takes over. No disappointment here, peeps.
With bag and tip in hand (that would be the baggy and decorating tip I used to dispense this creamy blue sweetness), my creations were alive!


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Technology update
Jul 5, 2013
A nanohole in one
Fluorescent molecules placed exactly at the centre of a nanoaperture appear to emit light more strongly than those placed haphazardly anywhere inside such a nanostructure. This is the new result from researchers at the University of Munich in Germany whose finding could help improve DNA sequencing and single-molecule bioassays.
Nanoholes (or zero-mode waveguides) and arrays of these nanostructures have many intriguing optical properties: For instance, they can confine light at dimensions down to a tenth of its wavelength. A team led by Hermann Gaub at Munich has now shown that the light emitted by fluorescent DNA molecules also varies depending on their position inside these nanoapertures – a result that will be important for single-molecule sequencing.
Modern-day DNA sequencing consists of breaking molecules of DNA into fragments of different lengths and adding fluorescent tags to the broken ends so that they can be monitored. Current single-molecule sequencing randomly places molecules in nanoapertures so that many holes are either unoccupied or doubly occupied, explains team member Philip Tinnefeld. However, the problem is that only holes with exactly one molecule can be used for sequencing. What is more, data quality can be substantially improved if single molecules are placed in the nanoapertures' centre.
In their work, the Munich researchers have succeeded in using a single-molecule cut-and-paste technique to place fluorescent DNA molecules in the centre of nanoapertures that were around 375 nm across. By comparing the amount of light emitted by molecules that had been randomly placed anywhere inside a nanoaperture compared to those placed exactly in the centre allowed them to prove that the latter fluoresced much brighter.
Pick and paste
"Our technique allows us to 'pick up' single fluorophore-labelled DNA molecules from a 'depot' and deposit them exactly where we want," says Tinnnefeld. "The pick and paste works using molecular forces and the depot and target areas are pre-functionalized by microfluidic systems."
The team used a fast, non-invasive custom-built optical microscope in their experiments. "Since the size of the molecules and nanoapertures are beyond the optical diffraction limit, we used super-resolution techniques in which the position of the microscope cantilever that picks up the DNA molecules is localized by 'gauss-fitting' the point-spread function of a DNA molecule's fluorescent label," Tinnefeld told nanotechweb.org. "Similarly, we localized the nanoaperture's centre by gauss fitting to the (plasmonic) light transmitted by the nanohole. In this way, we were able to position the DNA molecule to a precision of just 20 nm inside the nanohole."
The centre of the nanoaperture appears to be a hot spot, say the researchers, and it is here that the fluorophores emit most light.
DNA molecule "anchor"?
The centrally placed DNA molecule might also, in principle, be used as an "anchor" to immobilize other molecules of interest, such as enzymes, adds Tinnefeld – something that might help improve the efficiency of a particular bioassay. "Parallel loading of different enzymes on the DNA molecules might also allow for parallel screening of a variety of targets – such as those required in drug testing, for example," he says. "More generally, other single-molecule assays based on, say 'nanoantennas' or other nanoparticle structures could also benefit."
The team now hopes to directly transport molecules like enzymes into nanoapertures using so-called co-expressed force handles – as has already been done on plain surfaces without nanoholes. "This will help make it easier to load nanoapertures because it would avoid us having to use the DNA as an anchor to pull down the enzyme molecules," explains Tinnefeld.
The researchers also plan to use their technique to try and analyze the electrodynamics environment of nanostructures (such as nanoantennas) and localize specific hot spots for enhanced light emission in these structures.
The present work is detailed in Nano Letters.
About the author
Belle Dumé is contributing editor at nanotechweb.org.


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1. accommodate - verb
· be agreeable or acceptable to; "This suits my needs"
Hypernym(s): fit, conform_to, meet, satisfy, fill, fulfill, fulfil
2. accommodate - verb
· make fit for, or change to suit a new purpose; "Adapt our native cuisine to the available food resources of the new country"
Synonym(s): adapt
Hypernym(s): change, alter, vary
3. accommodate - verb
· provide with something desired or needed; "Can you accommodate me with a rental car?"
Hypernym(s): provide, supply, ply, cater
4. accommodate - verb
· have room for; hold without crowding; "This hotel can accommodate 250 guests"; "The theater admits 300 people"; "The auditorium can't hold more than 500 people"
5. accommodate - verb
· provide housing for; "We are lodging three foreign students this semester"
Synonym(s): lodge
Hypernym(s): house, put_up, domiciliate
6. accommodate - verb
· provide a service or favor for someone; "We had to oblige him"
Synonym(s): oblige
Hypernym(s): comply, follow, abide_by
7. accommodate - verb
· make (one thing) compatible with (another); "The scientists had to accommodate the new results with the existing theories"
Synonym(s): reconcile, conciliate
Hypernym(s): harmonize, harmonise
8. accommodating - adjective
· helpful in bringing about a harmonious adaptation; "the warden was always accommodating in allowing visitors in"; "made a special effort to be accommodating"
Synonym(s): accommodative
Antonym(s): unaccommodating
9. accommodating - adjective
· obliging; willing to do favors; "made a special effort to be accommodating"
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text:
That's what the doctor told me yesterday.
We discussed in detail what has been going on the last month or so, and he said that "clicking" feeling I've been concerned about is actually more normal than I realize and it's good to be proactive, but I shouldn't be overly concerned about this one.
He bent my leg every which way it would go (I'm not that flexible, so it didn't take long), he thinks the pain I had been experiencing was just overuse and not related to the pop he felt during one rotation. When that happens, he said to take some time off and I shouldn't be concerned until the specific "ache" just doens't get better.
Well ok then. It was an expensive 15 minutes of my life, but the reassurance was nice. After dealing with crutches and taking 8 weeks off at the beginning of last year, I was starting to work myself up in a tizzy of all the things that could possibly be wrong with it.
Even though I'm still obviously cutting back on running quite a bit, at least we know my leg won't be falling off any time soon. Whew.
At least one good thing of it all? I've been focusing a little more on my strength training. Or at least on my Jillian Michaels dvds- which may not be hard core to some, but it's about as good as it gets for me. When it comes to weights, I lack any kind of motivation to do them. Someone needs to be barking orders.
To celebrate my non-injury (I guess?), I met up with Mon at the gym after work. We needed to catch up on each other's weekends, and because of the threat of rain, we chose to walk side by side on the treadmills. Cute, right?
We're nerds.
What was not cute was the skunk that ran out in front of me on the way home. He's been around for a while now. My friend Bailey has lovingly named it Petunia.
And then she called the office building and lovingly said, "Petunia needs to die".
Clearly that has not been taken care of just yet. Because we had a stare down in the parking lot- both parties frozen in terror. After about 10 seconds, he bolted to the right. And I promptly bolted to the left.
My heart is still recovering.
Had it already been Tuesday, the worst day of the week, god knows what might have gone down.
But instead, it's Tuesday now. Let's hope my planned run tonight will go well. And that I don't run into Petunia on the way home.
Because we're not friends. And he's got fire in his eyes. I've seen it.
Your turn- scariest/funniest/weirdest run-in with a wild animal.
Aaaaannnndddd go!
Filed under: Fitness Randomness Tagged: | exercise, fitness, health, Healthy Living, injury, running


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Buy Item $141.49 Add To Cart
Add To Wishlist
Accelerated Christian Education (ACE) curriculum has Scripture as its foundation, fully integrating biblical principles, wisdom, and character-building concepts into education. Students move at their own speed through the self-instructional "PACE" workbooks. Following the mastery approach, PACEs are formatted for students to complete the exercises found throughout the workbook, take a practice "self test," and conclude with a "final test" (removed from the center) to measure understanding.
PACE SCORE Key answers are sold-separately and are not included in this set.
This kit contains the following PACE sets:
|Grade 6 Math PACEs 1061-1072
|Grade 6 English PACEs 1061-1072
|Grade 6 Social Studies PACEs 1061-1072 (4th Edition)
|Grade 6 Science PACES 1061-1072 (4th Edition)
|Format: Other
Vendor: Accelerated Christian Education
|Availability: In Stock
Series: ACE PACEs


text:
By Gerry J. GilmoreAmerican Forces Press Service
WASHINGTON, Jan. 30, 2003 Life is improving in today's Afghanistan, a nation recovering from widespread damage caused by the militants who ran it for five years, a senior DoD official said here Jan. 28.
Just over a year ago Afghanistan "was ruled by the Taliban, which has to be one of the most ignorant, repressive and ineffective governments ever to have ruled on earth," Joseph Collins, deputy undersecretary of defense for stability operations, remarked in a briefing to business and community leaders at the Pentagon.
The Taliban are militant Muslim fundamentalists who ruled Afghanistan from 1996 until December 2001, when U.S., Afghan and other coalition forces ejected them from the capital city of Kabul -- and from power. The Taliban are allies of terrorist Osama bin Laden, the Saudi exile accused of masterminding the Sept. 11, 2001, terrorist attacks on the United States.
After the Taliban departed, "the U.S. and its partners faced an exhausted nation on the brink of a humanitarian disaster," Collins said. Afghan society had reached a "bottom-of-the-barrel" condition, he noted, because of the inept, brutal Taliban government, which routinely practiced public executions and whipped women for not being in "proper garb."
In fact, Taliban rule in Afghanistan is marked by a horrific lack of consideration for human rights and basic community services. Collins noted that in 1996, the year the Taliban took over, Afghanistan ranked 169 out of 174 countries rated on the United Nations' index of human development. Under Taliban rule and the experience of a four-year drought, he said, the country fell off the scale.
Today, after 23 years of warfare, Afghanistan enjoys relative peace, Collins remarked. The country now has a leadership that was democratically chosen by a national assembly, the Loya Jirga, and that government is developing its powers under the leadership of President Hamid Karzai, he pointed out.
Afghanistan's laws and economic system, he said, are being modernized to provide a free-trade, capitalist economy.
"Afghanistan today has defined the master plan for its own reconstruction, and that's great progress in one year," Collins declared, noting that more than 65 nations -- led by the United States, Japan, Saudi Arabia and the European Union -- have pledged $6.5 billion for Afghan reconstruction.
During 2002-2003 the United States will spend nearly $1 billion for economic issues in Afghanistan, he said, not counting a few hundred million dollars going toward security reconstruction. The United Nations, he noted, is also heavily involved in Afghan reconstruction efforts.
Collins said the lead American agency for Afghan reconstruction isn't DoD, but the U.S. Agency for International Development. In one year in Afghanistan, he said, that agency has refurbished more than 600 schools and provided 10 million textbooks, 7,000 metric tons of seed, and more than $150 million for refugees.
U.S. military civil affairs experts in Afghanistan, he added, have accounted for another 127 schools, 400 wells, 26 medical clinics, as well as refurbishing a national veterinary center and a teachers college.
Subcontracts for such work have provided employment for 40,000 to 50,000 Afghans, Collins said.
He said a top Afghan projects for 2003 is constructing a set of five maternity care centers. This project is highly important, he explained, because 25 percent of all Afghan children don't reach their fifth birthday.
A lot of "heavy lifting" for Afghan reconstruction is also being done by 260 nongovernmental organizations, he pointed out.
Security in Afghanistan is also "coming along pretty well," Collins said, although he noted that, as he was speaking, U.S. forces were battling terrorist forces near Spin Boldak, southeast of Kandahar. That area, he explained, contains "a rat's nest of terrorists."
Yet, security must be much better these days, Collins noted, because 2 million refugees "voted with their feet" and have returned home to Afghanistan.
U.S. and coalition forces, including the International Security Assistance Force, still patrol Afghanistan. But the Afghans are making good progress in providing their own security, Collins said, adding the newly formed, multiethnic Afghan national army now boasts six battalions. The army's first battalion completed training just seven months ago.
Parts of that Afghan force have already been deployed in combat, he added.


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CLJ Reviews The Good Earth by Pearl S. Buck
What We Read
The Good Earth was published in 1931 and won the Pulitzer Prize in 1932. Generally regarded as a classic, I chose the book for two reasons: 1.) It's my mom's favourite book and I promised her we would read it for Book Club, and 2.) Yann Martel – out of all the books he could have recommended to us in his letter to the CLJ – recommended this one (which of course led to numerous claims of "I told you so!" by my mother). Turns out, it really was a great book suggestion. The Good Earth tells the story of a simple, farm family living in pre-revolutionary China who encounter many trials and tribulations throughout the course of the protagonist, Wang Lung's, life. Facing not just drought, pestilence, and floods, Wang Lung must learn to grapple with conflict within his family, and his own feelings of lust, greed and entitlement.
What We Did (and How We Did It)
One of the major themes within the novel is the importance of being connected to the Earth – when Wang Lung leaves his land, hurt and despair seem to follow closely behind. Within the novel, the cultural belief that various Gods are responsible for the fortunes or misfortunes of the family is also evident. Tying these two themes together, the activity asked CLJ members to spend some time planting seeds of their choices into small pots. They were then asked to take on the persona of a character in the novel and pray to the Gods for their seeds to grow and flourish –with the best depiction of character and plea to the Gods, our newest CLJ member Alison Atkinson took home the trophy.
What We Thought
The group talked a lot about the relevance and appropriateness of a privileged American woman telling this story from the perspective of a Chinese peasant. Given the year of publication and popularity of the novel in America (and around the world), we also talked a lot about this book's probable impact on how many Americans viewed China, as this book was arguably one of the earliest and most realistic depictions of Chinese life that many Americans would have been exposed to. The underlying themes of greed, the social order, and the treatment of women were also explored. Most members of the CLJ thoroughly enjoyed the book – or at the very least, appreciated the opportunity to read a thought-provoking piece of literature they otherwise would not have read.
As told by Michelle Burtnyk-Horn


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The Equestrian Center offers a range of barn amenities. These include eight rubber matted 12x12 stalls with individual lights and electric, and access to attached turn out runs. Additionally, there are four grooming stalls, two wash stalls with hot and cold water, and heated/air conditioned office, feed room, restrooms, lounge area and tack room with washer and dryer. The facility also boasts dozens of acres of pasture, a small cross country course, and a three stall quarantine facility with accompanying pastures.
Our 150x160 foot multipurpose arena offers custom sand mix footing and drainage designed by renowned arena design specialist Bob Kiser. In addition to exceptional footing conditions, we also have a variety of jumps and other training tools available to further expand the riding experience.
Students have the opportunity to explore miles of scenic trails throughout Liberty's mountain property. Trails range from a brief loop around the equestrian property to trekking across the mountain and are suited to the newest beginner, the seasoned rider or the experienced competitor looking for conditioning opportunities.


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Video:Easy Crockpot Swedish Meatballs Recipewith Kaytie Sproul
Crockpot Swedish meatballs are a quick and easy recipe packed with flavor. Watch this video for recipe tips on how to make crockpot Swedish meatballsSee Transcript
Transcript:Easy Crockpot Swedish Meatballs RecipeHi, I'm Kaytie Sproul, here for About.com, and today we're going to take a look at how to make crock pot Swedish meatballs, using a recipe from About.com's southern cooking site. Swedish meatballs are a hearty favorite that often take some effort to prepare. However, with a crock pot and this quick and easy recipe you can enjoy a great meal with minimal effort!
To Make Crockpot Swedish Meatballs, You Will Need:
- 2 12 ounce jars of beef gravy
- 1 pound of sliced mushrooms
- 2 tablespoons of butter
- 1 large onion, cut into chunks
- 1 tablespoon of Worcestershire sauce
- 1/4 teaspoon of Allspice
- 2 pounds of meatballs, frozen or refrigerated
- 1 cup of sour cream.
- Skillet and
- A five-quart crock pot
Prepare and Add Swedish Meatball Ingredients to the CrockpotThis dish, like most crock pot cooking, features modest preparation. You'll first need to clean your mushrooms by wiping them down. Don't clean them under the faucet, as they'll absorb water like a sponge. Once clean, slice them into medium-sized pieces and add them and the butter into a hot skillet. Saute them under medium-to-low heat for ten to 15 minutes or until they are soft.
Then proceed to chopping your onion into medium-sized chunks. You can always make meatballs from scratch, but if you'd like to save a little time, you can purchase pre-made and pre-cooked meatballs at your supermarket. If you do go with a store-bought brand, frozen or refrigerated meatballs will work great with this recipe.
Now, let's begin adding the ingredients to our crock pot, starting with the sauteed mushrooms. Next, add the Allspice, Worcestershire sauce, onion chunks, gravy, and finally, the meatballs. Give everything a good mixing, and then place the lid on your crock pot.
Temper the Sour Cream Before Adding to the CrockpotAfter about five and a half hours, you'll want to finish off the dish by adding the sour cream. During the final 30 minutes of cooking, take about a half cup of the hot gravy from the crock pot, and mix it with the sour cream. Then add the mixture to the rest of the dish, mixing evenly.
You can serve this dish on its own, or over either rice or egg noodles. Swedish meatballs are a comfort food classic and perfect for crock pot cooking; so if you're looking for a great tasting, budget-friendly meal that requires very little prep time, give this recipe a try. Thanks for watching. To learn more, visit us on the web at about.com.
About videos are made available on an "as is" basis, subject to the User Agreement.


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March 7th: ACFW Colorado Springs Chapter Meeting: Peter and Carol Mayberry, speakers
January 5th: ACFW South Denver Chapter Meeting: Published Authors' Panel
January 12th: ACFW North Denver Chapter Meeting: Brandy Vallance, speaker
ACFW Western Slope Prologue Chapter – check their website for meeting date/time
Our mission is to provide encouragement and support to ACFW chapters throughout Colorado.
Colorado currently has chapters located in north Denver, south Denver, and Colorado Springs, as well as prologue chapters in the Loveland/Greeley/Ft. Collins area and on the Western Slope. Each chapter meets on a monthly basis. Feel free to stop by for a visit. We welcome writers in all stages of their writing journey.
For a detailed list of Colorado chapter meetings and locations, click on our chapter websites link.
Not a chapter in your area? No problem! For Colorado, contact Niki Turner, Colorado Area Coordinator, at email@example.com to discuss the possibility of setting one up in where you live. For Wyoming, Utah, Montana, and the Dakotas, contact Kathy Kovach, Rocky Mountain Zone Director, at email@example.com. For all other states, contact the ACFW Zone Officer at firstname.lastname@example.com To see a complete list of chapters and locations nationwide, click here.
"Try before you buy." We are happy to have you attend up to two meetings if you want to "check us out" before taking the plunge. After that, if you decide to join, go to www.acfw.com and click on Member Application, or click on the direct link here.
Once you've signed up and paid your national dues, you can join any chapter you wish. To join, visit one of our chapter meetings or contact the chapter president. Local dues are in addition to national dues and vary by chapter.
Some of our many membership benefits include:
If you would like more information on ACFW, please feel free to stop by one of our meetings.


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More New and Used
from Private Sellers
The Guided Reader to Teaching and Learning Musicby Savage; Jonathan
Nonspecific Binding
Questions About This Book?
Why should I rent this book?
Renting is easy, fast, and cheap! Renting from eCampus.com can save you hundreds of dollars compared to the cost of new or used books each semester. At the end of the semester, simply ship the book back to us with a free UPS shipping label! No need to worry about selling it back.
How do rental returns work?
Returning books is as easy as possible. As your rental due date approaches, we will email you several courtesy reminders. When you are ready to return, you can print a free UPS shipping label from our website at any time. Then, just return the book to your UPS driver or any staffed UPS location. You can even use the same box we shipped it in!
What version or edition is this?
This is the 1st edition with a publication date of 5/29/2013.
What is included with this book?
- The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any CDs, lab manuals, study guides, etc.
- The Rental copy of this book is not guaranteed to include any supplemental materials. You may receive a brand new copy, but typically, only the book itself.
This Guided Readerdraws on extracts from the published work of some of the most influential education writers to provide insight, guidance and clarity about key issues affecting Music teachers. Aimed at trainee and newly qualified teachers including those working towards Masters level qualifications, the book brings together key extracts from classic and contemporary writing and contextualises these in both theoretical and practical terms. Each extract is accompanied by an introduction, a summary of the key points and issues raised, ideas for critical engagement, questions to promote discussion and suggestions for further reading to extend thinking. Taking a thematic approach and including a short introduction to each theme, the chapters include: Analysing your own work as a music teacher; Concepts of musicality; Notions of musical development and progression; Pedagogies for teaching music musically; Music inside and outside the school; Formal, informal and non-formal approaches to music education; Productive methods of assessment and transition for music education; Creativity and music education; Supporting the gifted and talented in music; Using ICT within music education; This accessible, but critically provocative text will be an essential resource for all teachers that wish to deepen their understanding of Music Education.


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Evans new Level 360 drum heads
View Single Post
Silver Member
Join Date: Sep 2010
Location: Brooklyn, NY
Posts: 617
Re: Evans new Level 360 drum heads
Originally Posted by
Midnite Zephyr
So let me get this right because I'm thinking of buying a bass drum EMAD head soon. This drum shop I go to will start selling Evans heads next month. I'd imagine everything they get there will be new, so if I buy an EMAD there, will it have the Level 360 now? Because Ben,
, said bass drum heads will be coming later.
Bass drum heads won't be until late 2013/early 2014.
Originally Posted by
Terrence R
I bought a 8", 10", and 14" onyx heads about 3 months ago from the local store. It was stock that's been there for a long while. They didn't have the 12" in stock. So, I threw them in the closet and forgot about them until yesterday. I went to the store, bought a 12" onyx, brought it home, and started installing them on my Pearl Export toms. I noticed the new 12" I picked up was in fact the new 360 design. But, it seemed to fit the shell no different than the others. But, I did notice how much easier it was to tune. I had to play around with the other size toms just a bit to get the sound I wanted. The 12" went where I wanted it to almost effortlessly compared to the others. I was kinda shocked though that it had the same wobbly play as the non-360 heads.
Chances are that the Onyx heads that you picked up a while back did in fact have the Level 360 collar. As I mentioned, we've had this in production since mid-to-late 2012.
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Today we have something REALLY special. Jennifer and Darrell's wedding was over the top gorgeous, and so ridiculously detailed and well thought out, it will bowl you over. The pretty-factor should come as no surprise, given Jennifer's food industry background and the couple's true love of entertaining. Additionally, as a special treat, they are also sharing the photos of their casual picnic event, and holiday cookie baking party in the Cavallo Point Cooking School. Lovely floral design by Kate's Blossoms, photography by Kelly Puleio, and in the spirit of treating you, dear readers, here is a description of the day, in the beautiful bride's own words:
It was a complete surprise when my boyfriend, Darrell Rodriguez, brought me to Cavallo Point on December 30, 2012. We had visited the Lodge a couple of times for drinks and brunch. It had been a dream of mine to stay at the resort. As we pulled up to the lodge that beautiful day, my only hope was to sip champagne, enjoy the view and toast the new year with the love of my life.
As New Years fast approached, Darrell told me to dress up. We were heading to Murray circle for dinner and then to the water front to watch the fire works at the stroke of midnight. Dinner was a beautiful seven course meal with wines paired with each course. At 11:45, Darrell asked me to walk to the water front. I gently requested that we drive. Thinking of saving my beautiful high heels from the "long" walk in the dark. The car was quickly brought from valet. We pulled up just as the fireworks began.
Darrell proposed, in the car, as the fire works began, and not exactly as planned! A water side proposal was much more romantic than the one inside the car, he said. But I was surprised and thrilled nonetheless. New Year's Day, as we enjoyed breakfast on the restaurant patio, we began to discuss where we wanted to get married. Coming back to Cavallo point, exactly one year to the day to mimic the proposal seemed like the most amazing of options.
By March, we were booked. It would be a small wedding for forty special family and friends. An event centered around food, wine and the fireworks of New Year's Eve. It was the fireworks that provided the theme for the wedding. The sparks of the fireworks. The sparks we felt when we met. The sparks that would fly when we got married. "Come See Sparks Fly". And so it began.
We lived in a home of similar style to the lodge. All of the planning, flowers, colors and theme centered around honoring the integrity of the property. We entertain all of the time. Serving multiple coursed dinners paired with wine. That part was easy. The first piece was to ensure that everyone saved the date and booked a room. It was New Year's Eve after all. We didn't want to risk anyone making other plans. The Save the Date notices went out by May. A simple menu card. With a matchbook saying " Save the Date-December 31, 2013-Come See Sparks Fly" It was threaded with three silver sparklers. All hand written, including the fireworks on the top.


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VIDEO: The purple martin man: Grand Forks man puts his passion to work for a causeLike a relatively small but devoted cadre of other purple martin landlords across North America, Perry Vogel of Grand Forks is doing his part to make sure these largest members of the swallow family have a future.
By: Brad Dokken, Grand Forks Herald
Perry Vogel would be the "Purple Martin Man of Grand Forks" if such a title existed.
Vogel, you see, is a purple martin landlord. The backyard of his south Grand Forks home hosts a colony that has sheltered as many as 29 purple martin pairs.
The collection of white, gourd-shaped houses and a stately homemade high-rise with eight martin-sized units teems with life every spring. This time of year, the martins in Vogel's colony show up before dusk like clockwork after daytime insect-feeding forays.
"They're incredible insectivores — they'll eat anything big and ugly that flies," Vogel said. "They sing to you, and they're just a joy to have in your backyard. I couldn't quite imagine what the backyard would be like if I didn't have them in the summer because there's just a life they bring that no other bird brings to your backyard."
Like a relatively small but devoted cadre of other purple martin landlords across North America, Vogel, 39, is doing his part to make sure these largest members of the swallow family have a future.
Call it a passion, he says — a passion with a purpose.
Vogel says purple martins, named for their iridescent purple sheen, have been declining in the northern Midwest since the 1960s, based on findings from the annual North American Breeding Bird Survey. A big reason, he said, is the increasing population of European starlings and house sparrows, non-native species that compete with martins for the cavities, or hollowed-out places, the birds need to nest.
Without human help, the starlings and sparrows usually win.
"They're aggressive," Vogel said. "They're ruthless."
History with humans
According to Vogel, purple martins and humans have a partnership that dates back to when American Indians hung hollowed-out gourds from trees or posts. Naturally curious, the martins were attracted to the gourds and used them to build their nests.
In return, the martins kept populations of flying insects in check and chased crows from the meat the Indians would hang to dry.
Today, gourd-shaped houses are a staple of purple martin colonies along with more traditional homemade nest boxes. Vogel says martins east of the Rockies now are totally dependent on humans for housing.
"If it weren't for humans, there wouldn't be martins" today, Vogel said. "Purple martins like to be near humans because they have evolved that way. We have this opportunity to put up a house, attract a few birds to our backyards and make a difference."
Vogel said there's more to being a good martin landlord than putting up a few houses. The birds are naturally attracted to white, and a house of any other color probably won't draw martins. It's also important, he said, to place the colony in an open area away from trees that harbor predators such as owls and Cooper's hawks.
"Being a purple martin landlord is like being a real estate agent," Vogel said — "location, location, location."
In the 1960s, Vogel said, a company selling purple martin houses spread a myth that the birds ate up to 2,000 mosquitoes a day. The marketing gimmick was good for sales, Vogel said, but it didn't do martins any good because well-meaning people who didn't know any better often attracted starlings and house sparrows, instead.
To manage for house sparrows, Vogel sets box traps in his backyard and kills 80 to 100 of the martin-tormenting birds annually. His martin houses have crescent-shaped openings that are too small for the starlings.
Vogel also conducts weekly nest checks on the houses, which raise and lower with a pulley system, counting the eggs and babies and making sure nothing is in the nest that shouldn't be there.
"It's a lot of work, but it doesn't really feel like work to me," he said.
Way of life
A native of Kulm, N.D., Vogel said purple martins have always been a way of life. His grandmother and father both had purple martin colonies, so when Vogel and his wife, Sheryl, moved to their south Grand Forks home in 2001, putting up purple martin houses just came natural.
He started with four birds that first year, and the colony grew from there. The martins, which winter in Brazil, are programmed to return to the site where they hatched.
Vogel's martin colony since 2001 has fledged more than 600 offspring, including 109 last year.
Vogel's efforts on behalf of the purple martin extend beyond his backyard. Last winter, he co-founded the Purple Martin Association of the Dakotas — a loosely knit group of enthusiasts in the two states — and on Earth Day, April 22, Vogel set up a purple martin house in the Grand Forks Greenway.
He's also working with staff at Turtle River State Park to draw purple martins to a colony at the state park west of Grand Forks.
This year, Vogel reduced his backyard colony from 29 martin units to 14 in hopes of attracting birds to the Greenway. It's working; the first martins began visiting the Greenway house just this week.
"It's going to be an excellent spot for purple martins," he said. "I'm thrilled we're going to be bringing purple martins to the Greenway."
Partners for a cause
Vogel this spring also partnered with the Agassiz Audubon Society based in Warren, Minn., to secure a grant to offset costs for the 14-unit purple martin house in the Greenway and a similar structure at the Agassiz Valley Water Resources Project impoundment, located southeast of Warren.
Last weekend, Vogel and several boy scouts erected the martin house near Warren during an annual Boy Scout Camporee, held at the Audubon Center of the Red River Valley across the road from the impoundment.
Heidi Hughes, manager of the Audubon Center, said the collaboration with Vogel has been a "perfect partnership."
"He's just a wonderful personality," she said. "He's fun to listen to, and with those boy scouts, he was just amazing. I learned a lot from him, too."
The two martin enthusiasts will present workshops at 6:30 p.m. Thursday in the East Grand Forks Campbell Library and at 6:30 p.m. May 21 in the Thief River Falls Library. The goal is to help interested people become good purple martin landlords.
"It's one bird where an individual person can make a big impact on the population," Hughes said. "Martins really need people's help, and you can immediately see the results of your work. You see a huge decline in flying insects, biting insects and flies, so they're really good to have around in terms of comfort."
The only downside, Vogel said, is when the martins leave in late August.
"After they are gone, the yard is quiet," he said. "There's no singing."
Dokken reports on outdoors. Reach him at (701) 780-1148; (800) 477-6572, ext. 148; or send email to email@example.com.
Tags: gf and egf, nongame wildlife, perry vogel, purple martins, outdoorsupdates, birds, northland, outdoors


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From: Mike Glossons
Location: San Diego, CA
Date: 12/17/2008
Was poking around in the Wiki article about you, and saw there was an extended article regarding CITY AT THE END OF TIME.
The header is "Literary significance and reception"
The article is still a stub at this point.
From: Greg Bear
Date: 12/29/2008
Thanks, Mike. All good reviews is a good beginning!