text:
A computer information processing system utilizes parallel processors for organizing and clustering a large number of documents into a large number of clusters for information analysis and retrieval. After the documents are translated into electronic digital documents, each document is converted into a vector based on weighted list of the occurence of different words and terms that appear in the document. The document vectors are grouped together into cluster vectors on different parallel processors according to similarities. New document vectors are simultaneously compared with existing cluster vectors in the different parallel processors.
1. In an arrangement of parallel processors in a computer information processing system, a parallel clustering method for examining preselected documents and grouping similar documents in the parallel processors for subsequent retrieval in an electronic digital format from the computer information processing system, the steps comprising:
converting each preselected document into an electronic document in digital format;
converting each electronic document into a vector, whereby a vector is a weighted list of the occurence of different words and terms that appear in the document;
selecting a first electronic document and designating the vector of the first electronic document as a first cluster vector whereby a cluster vector is the mathematical average of all of the document vectors having similar characteristics, and assigning the first cluster vector to a first processor of the parallel processors;
selecting a second electronic document and comparing the vector of the second electronic document with the first cluster vector to determine if the second document vector has similar characteristics, and assigning the second document vector to the first cluster vector if they have similar characteristics or designating the second document vector as a second cluster vector and assigning the second cluster vector to a second processor of the parallel processors if there are different characteristics; and
selecting each subsequent electronic document and comparing the vector of each subsequent electronic document with all existing cluster vectors simultaneously on each processor having a cluster vector, and assigning each subsequent document vector to a parallel processor having the most similar characteristics or designating the subsequent document vector as a subsequent cluster vector and assigning the subsequent cluster vector to a processor of the parallel processors if there are different characteristics.
The present invention relates to a clustering process to organize a vast amount of text-based documents into related groups of generally accepted clusters for subsequent query-driven retrieval and information analysis.
CHEN92! Chen, H., K. Lynch (1992) "Automatic Construction of Networks of Concepts Characterizing Document Databases," IEEE Transactions on Systems, Man, and Cybernetics, 22(5), pp 885-902.
DAHL92! Dahlhaus, E. (1992) "Fast Parallel Algorithm for the Single Link Heuristics of Hierarchial Clustering," Proceedings of the Fourth IEEE Symposium on Parallel and Distributed Processing, pp 184-187.
JAIN88! Jain, A. K and R. C. Dubes (1988), Algorithms for Clustering Data, Englewood Cliffs, N.J.: Prentice Hall.
LI90! Li, X. (1990) "Parallel Algorithms for Hierarchial Clustering and Cluster Validation," IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(11), pp 1088-1092.
MURT92! Murtagh, F. (1992), "Comments on `Parallel Algorithms for Hierarchial Clustering and Cluster Validation`", IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(10), pp 1056-1057.
SALT83! Salton, Gerald and Michael J. McGill (1983). Introduction to Modern Information Retrieval. New York, N.Y.: McGraw-Hill.
SALT89! Salton, Gerald (1989). Automatic Text Processing. Reading, Mass.: Addison-Wesley.
TIBE93! Tiberio, P. and P. Zezula (1993). "Selecting Signature Files for Specific Applications," Information Processing and Management, 29(6), pp 487-498.
A complete appreciation of the invention and its advantages can be attained by reference to the background leading to the invention and the summary and detailed description of the invention when considered in conjunction with the accompanying drawings:
FIG. 1 shows the formation of a signature file.
FIG. 2 shows the formation of a keyword-Boolean matrix and inverted index.
FIG. 3 provides a general overview of the invention's operation
FIG. 4 provides a generalized result of the invention.
FIG. 5 shows time to form clusters on 1 processor.
FIG. 6 shows time to form clusters and speedup for 2 processors.
FIG. 7 shows time to form clusters and speedup for 4 processors.
FIG. 8 shows time to form clusters and speedup for 16 processors.
FIG. 9 shows times to form clusters and speedup across processors.
Table 1 is the number of clusters for each permutation of the Wall Street Journal Set.
Table 2 is the time to make the clusters with 1 processor.
Table 3 is the time to make the clusters with 2 processors.
Table 4 is the time to make the clusters with 4 processors.
Table 5 is the time to make the clusters with 16 processors.
Table 6 represents the speedup of 2 processors over 1 processor.
Table 7 represents the speedup of 4 processors over 1 processor.
Table 8 represents the speedup of 16 processors over 1 processor.
Table 9 represents the efficiency of using 2 processors.
Table 10 represents the efficiency of using 4 processors.
Table 11 represents the efficiency of using 16 processors.
Information retrieval is the process of retrieving documents which are relevant to a query generated by a user. There are four dominate models for information retrieval: full-text scanning, keyword-Boolean operations, signature files, and vector-space. The models can be characterized as either formatted or unformatted. An unformatted model takes each document exactly as it appears in the document set. In other words, the document does not undergo any processing into a different form. Formatted models process the documents into a separate form or data structure. Query processing is done with separate forms or data structures.
One model is full-text scanning. This model takes a phrase from the user and searches each document in a collection for an exact match. This model is unformatted, hence each document must be completely scanned with each query. There are some efficient algorithms for text scanning. However this model, in general, is only used in small document sets where the user is familiar with the documents, i.e., personal files.
Formatted models take a document and convert them to some other form. Usually, this form is based on an ability to discriminate among documents. One way to discriminate is to identify words within the documents and build the formatted structure from discriminating words. These words are frequently referred to as descriptors. In many cases, descriptors are reduced to word stems. In other words, terms like "engineer", "engineering", or "engineered" would all reduce to the stem "engineer".
A signature file is formed from the signatures of a document set. To form a signature, each term in a document is converted to a standard size term consisting of 0's and 1's. Once each term is converted, the document signature is formed by performing an ORing operation. FIG. 1 details the formation of a document signature. To perform a query, the query is converted to a query signature. This signature is compared to each document signature. A match occurs if a "1" in the query signature can be aligned with a "1" in a document query. Unfortunately, if there is a match it is unknown if the match occurs because the document matches the query or simply because the process of conversions attributed to the alignment. A document which is retrieved due to alignment based on the conversion process yet does not match the actual query is called a "false hit". Signature files tend to be used as a filtering process which retrieves potential matches with some other process use to screen false hits from the retrieved set.
Keyword-Boolean models typically are represented by a matrix where the columns represent documents and the rows represent keywords. If a keyword appears in a document then the row corresponding to the term and the column corresponding to the document has a "1" placed in it. FIG. 2a shows a typical Boolean model matrix. A query is formulated using the Boolean operators AND, OR, NOT. Each term in the query is compared to the matrix. If a "1" appears in the row, column! corresponding to the term, document! that document is placed into a set of potential documents. Once documents are placed in the set the Boolean operations are performed. In effect the set of potential documents is pared down to the final set presented to the user. However, for each query, each term must be tested for in each document. Searching can be made more efficient by the use of an inverted index, An inverted index for information retrieval is much the same as the index of a textbook. It identifies keywords and indicates which documents contain those keywords. FIG. 2b shows a scheme for an inverted index. While improving searching time, the indices themselves can be very large. Keyword-Boolean systems are dependent on the indexing scheme. If a term is not a keyword, there is no way to query for that term within documents. If a new word is added to the index, each document may need to be re-examined to identify if the document contains the new term. Assigning the keywords as descriptors of documents is a complex problem TIBE93!. It has been shown that the probability of two people using the same descriptors to categorize a document is low (10-20%) CHEN92!.
The last model to be discussed is the vector-space model. In this model, each document is considered to be a collection of terms. The number of times each word occurs is considered that term's weight. The terms and weights for each document can be organized into a document vector consisting of n-dimensions, where n is the number of terms. A query is also a collection of terms. A query can be converted into a query-vector and the query vector is compared to the document vector. Document and query vectors are compared using vector operations and if some threshold of similarity is reached, the document is considered for retrieval. Typical measures of similarity are the Cosine, Dice, or Jacquard similarity measures.
The formatted models (signature files, keyword-Boolean Operations, Vector-Space) process the documents to form different data structures. These data structures ignore the relationships between the words in a document. If word concordance is a concern, some additional data structure must be maintained. Word count, or the number of times a given word occurs in a document, is lost in signature files, and in Boolean models. Word count can be considered as inherent in the value of attributes in the vector-space model.
All the models have been described in terms of how documents compare to a query. However, none of the models describe how documents relate to each other. The signature file model, the text scanning model, and the Boolean models simply do not have capabilities to relate documents to each other. The Vector-space model, with its ability to measure similarity is readily capable of determining how documents compare to each other. This ability forms the underlying premise of the idea of clustering.
The basic idea of clustering is that items which are similar can be grouped together. Each group, or cluster, has a centroid vector, which is the average of the document vectors making up the cluster. Query vectors are compared to the cluster centroids, if a match is determined, the entire cluster is retrieved. Clusters can reduce the search requirement as each centroid contains information about numerous documents.
Clustering has been used in retrieval systems. However, it has always been done in a sequential fashion. As new documents are added to a collection they are not immediately available to the user. Instead they are held until such time as a sufficient number of new documents have been acquired. Then, in an off line process, the new documents and old documents go through the clustering process. This results in a new set of cluster centroids. The new set of cluster centroids is eventually provided to the user as a new release or version. As document sets increase, the amount of time between versions increases as well. However, if a document set doubles, it takes four times as long to form the new clusters. This can result in an unacceptable time delay from the time a new document is acquired to the time a user actually has access to that document. The Parallel Document Clustering Process can greatly reduce this time.
It is the object of this invention to provide an efficient method of organizing a large body of documents into clusters for subsequent retrieval.
It is a further object of the invention to provide a fast method of clustering to reduce the amount of time a document waits from its receipt into the document set until it is available for retrieval by users.
A more specific object of the invention is to perform the process on any available multiple processor (parallel) machine.
The invention is a process for forming clusters of large document sets using multiple processor machines. The process is useful for identifying similarity amongst documents and for subsequent use in document retrieval systems. For demonstration purposes, the Single-Pass Heuristic is used as the clustering method. This method is generally accepted within the information retrieval community.
Text documents are converted to document vectors. Clusters of documents are represented by cluster vectors which have the same format as document vectors. A cluster vector is made by taking the numerical average of all the documents which comprise the cluster. A document vector is compared to each cluster vector. As soon as a determination is made that the document is similar to a cluster, the comparisons stop and the document is added to that cluster. In the event a document is not similar to any cluster, a new cluster is formed.
The invention follows the same tenets of forming a document vector which is compared to cluster vectors. However, the key innovation is that instead of comparing a document vector to a single cluster, it compares the document vector simultaneously with P clusters, where P is the number of processors within the system. Each processor is responsible for creating and maintaining certain clusters. Each processor uses the same document vector. The processor compares this document vector to each of its clusters. When a sufficient threshold of similarity is exceeded, the processor records which cluster vector is similar to the document vector. When all processors have compared the document vector, a decision is reached to determine to which cluster the document vector is added to. If a determination is made that the document was not similar to any existing cluster, a processor is designated to create a new cluster.
By way of example, the process begins by converting the first document vector into a cluster vector. This vector is stored in processor 1. The next document is compared to this vector. Assuming the threshold is not exceeded, the process forms cluster 2 on processor 2. The third document is now compared simultaneously with cluster 1 and 2. If the document cannot be added to either cluster, then cluster 3 is formed on processor 3. The next document is now compared simultaneously with cluster 1, cluster 2 and cluster 3. This process continues until all documents in the set are placed into appropriate clusters. FIG. 3 shows this process. While there is no theoretic limit to the number of processors, a claim of the invention is that it performs on realistic, existing machines. Therefore, each processor may be responsible for more than one cluster. FIG. 4 shows the overall effect of the process on a machine with 4 processors.
Each text document is scanned to create a document vector, Stop words are removed and the number of times each word appears in a document is counted. Each unique word in a document is given an administrative number based on a master dictionary. The document vector is basically a set of paired numbers. The first pair indicates the total number of words in the document and the second number of the pair represents the number of unique words within the document. Each subsequent pair is made of up the number of appearances of a word and the administrative number of that word. Formation of the document vector is done off line and is not part of the invention. Each cluster has a uniquely designated global number. The cluster centroid vector has the same form as a document vector. That is a series of paired numbers. The first pair represents the total number of words in the cluster and the total number of unique words in the cluster. Each subsequent pair is made of up the number of appearances of a word and the administrative number of that word. The cluster vector is formed as the mathematical average of the document vectors within the cluster. The following formula shows how each element of a document vector is added to its corresponding element in a cluster vector: ##EQU1##
Clusters are formed based on a similarity measure between the cluster centroid and a document vector. One popular similarity measure is the COSINE measure based on the formula: ##EQU2## If COSINE(Cj,Y) exceeds a threshold (ranging from 0 to 1), the document and cluster are considered to be similar. The document is added to the cluster using equation 1. Every cluster C is compared to document Y until either the threshold is exceeded or all clusters have been checked. In the latter case, a new cluster is formed. Forming a new cluster is very simple. The document vector is simply redesignated as a cluster and given a number. To put the threshold into perspective, a threshold of 0 implies that any document will match a cluster. A threshold of 1 implies that only documents which have exactly the same words and exactly the same number of appearances of those words will be considered similar.
Each processor accesses the same document vector at the same time. Using equation (2), a processor determines if a document is similar to any of its clusters. It is possible for a document vector to be similar to more than one cluster. However, the tenets of the Single-Pass method are such that a document is only placed into the first cluster which exceeds the threshold. For the invention to produce the same results as the Single-Pass, there must be communications among the processors to determine which cluster was the first to have the threshold exceeded. It is important to note that the use of the term "first cluster" is based on the order the clusters were formed. Cluster 1 is formed before cluster 2, which is formed before cluster 3, etc. Since the clusters are numbered globally, the cluster with the lowest global number is determined to be the cluster which incorporates the document. So if processor 2 reports the threshold was exceeded with cluster 7 and processor 5 reports that the threshold was exceeded on cluster 5 then the document is added to cluster 5. This assignment occurs even if the actual computations by processor 2 where finished ahead of processor 5. If no cluster is found, the system generates a new cluster and one of the processors takes responsibility for the cluster. Clusters are apportioned to processors in a modulus fashion, that is: ##EQU3##
The invention was used with a set of articles from the Wall Street Journal. The articles were written at different times of the year, by different reporters, and cover an assortment of topics. They are also of varying lengths. In other words, the document set is not categorized into any preestablished category, such as, computer oriented, financially oriented, legally oriented, etc. The documents were formed into individual document vectors and each is stored as a separate file with a unique file name. There is a master file which contains the file names of the document vectors. When the vectors were formed stop words were removed but there was no stemming. Stemming can be easily incorporated into the scheme if desired as all conversion from text format to vector format is outside the scope of the invention.
There are several parameters which must be established prior to executing the process. These are:
a) D, the number of documents in the document set.
b) O, the order in which document vectors are accessed for comparison.
c) C, the threshold value of the COSINE coefficient.
d) P, the number of processors in the actual system.
The Single-Pass method places a document into the first cluster which exceeds the threshold. This has two very characteristic results. The first characteristic is that the clusters which are formed first tend to be larger (contain more documents) than clusters which are formed later in the process. The second characteristic is that the process is order-dependent. That means if the order in which the document vectors are compared changes, the clusters may change as well. These two characteristics are known and generally accepted as a by-product of the Single-Pass method. To show the generality of the invention, results are based on five different orderings of the document set. The ordering of the document vectors is done through manipulation of the master file of document vectors.
The first runs were done with a random ordering (R) of the documents. Basically, this can be considered as taldng the documents in the order in which they arrived to the system. While the document vectors are formed, little is known about their content. However, once a document vector is formed, it is very easy to identify two characteristics. The first characteristic is the total number of words in the vector and the second characteristic is the number of unique words in the document vector. These values are provided by the first numbered pair of the document vector. With this information, it is possible to arrange the document vectors based on total words or number of unique words. This being the case, the document vectors were ordered by total words in ascending order (TA) and descending order (TD). Ordering was also done based on number of unique words in ascending order and descending order, UA, and UD, respectively.
The threshold coefficient is the basis of comparison between a document and a cluster. If the cosine exceeds this threshold, the document and cluster are deemed to be similar. The coefficient can range from 0.0 to 1.0. The higher the value, the more similar a document must be in order to be added to a cluster. While the range can be 0.0 to 1.0, values at the extremes have little meaning. A value of 0.0 implies that there will be a single cluster incorporating all the documents. A value of 1.0 would basically filter all the documents and only cluster those which are duplicates. The invention was run on coefficients of 0.2, 0.4, 0.6, and 0.8.
The intent of the invention is to be used with large document sets. To show the effect of the invention as document set size increases, document sets of 32, 64 and 128 were used. These sets were run at each of the four coefficients and in each of the five different orders.
The last parameter to be established is the number of processors to use. While there is no theoretic limit to the number of processors, the intent of the invention is to show the effectiveness on a real, practical, and commercially available machine. The process was run initially on 1 processor. This indicates the time the process would take on a regular, sequential machine. The process was run on machines consisting of 1, 2, 4, and 16 processors. A run then consists of a combination of the four parameters D, O, C, P !. In total, there were 240 permutations run, each permutation was run 5 times. Results are based on the average of these runs.
The initial runs were used to establish the number of clusters. In general, the fewer the clusters, the broader the scope of those clusters. The more clusters there are, the more specific the scope of the clusters. Correspondingly, there tend to be more clusters at higher values of the coefficient. There is no direct link between selecting a coefficient and the desire to form a specific number of clusters. Table 1 provides the results of the clustering process itself. It is evident that the value of the coefficient is the major determining factor in the number of clusters formed. In the Single-Pass method, the number of processors used has no effect on the number or composition of the clusters formed. In other words, the 6 clusters formed with the 32 document set, in random order with a coefficient of 0.2 are the same whether the process was run on 1 processor or 16 processors. It is interesting to note that the ordering scheme TA and UA tend to provide the most clusters while the schemes TD and UD provide the least. It should be made clear that it has yet to be determined if there is a combination of D, O, C! which results in an optimal clustering of any document set.
Tables 2, 3, 4, and 5, represent the time it takes to do the process on 1, 2, 4, and 16 processors. Table 2 is the process time on one processor. As such, it reflects the process time on the typical sequential machine. This is the basis for comparison as more processors are added to a system. The time it takes to perform the process on multiple processors has two main components. The first component is the time it takes to do actual processing, e.g. mathematical operations. The second component is the time it takes to do internal message passing. The times depicted in tables 3, 4, and 5 are the combined total of the two components for each D, O, C, P ! combination. The effects of the components will be explained in accompanying narrative. There are three factors which are used in evaluating the process. The first is simply the time to perform the algorithm. The second factor is speedup which indicates how much faster an algorithm runs as more processors are added. It is a value ranging from 1 to P, the number of processors. The third factor is efficiency, or how much effort is each processor contributing to the accomplishment of a task. Efficiency is a value of 0 to 1. In general, the higher the speedup and efficiency the better an algorithm performs. It is also generally accepted that the best speedup which can be attained is when speedup is the same as the number of processors and the best that efficiency can be is 1. Speedup and efficiency can be mathematically defined by: ##EQU4##
Table 2 indicates the time, in seconds, it takes to form the clusters for each configuration using 1 processor. This becomes the basis for comparison of the process as more processors are added. Each time represents a combination of the four parameters D, O, C, P ! so conclusions are described in terms of isolating parameters. As D, O, and P are held constant, it is clear that increasing C causes an increase in execution time. For example 32,R,0.2,1! takes 0.937 seconds whereas 32,R,0.4,1! takes 1.354 seconds, 32,R,0.6,1! takes 2.361 seconds and 32,R,0.8,1! takes 2.495 seconds. In general, it can be seen that the time increases as C increases. In other words, it takes longer to make more clusters which is intuitive. It is also intuitive that it takes one processor longer to perform the algorithm as the number of documents increase. This is evident in holding O, C, P constant and allowing D to change from 32 to 64 and then to 128.
Table 3 is the time to perform the algorithm for each permutation with two processors or D, O, C, 2!. It can be seen that for permutations where C=0.2, the algorithm does worse than with 1 processor. This is to be expected given the nature of the Single-Pass method. As previously stated, the Single-Pass tends to put documents into the first clusters. So the first processor is initially doing work while the second processor is idle. This accounts for poor speedup and efficiency as well. In effect, only one of the processors is working. Note, however, that as the value of C increases, so does the number of clusters. As these clusters are apportioned, there is more work to do and each processor takes on a more even distribution of the load. This is especially seen as both D and C increase.
Table 4 shows the times to perform clustering with four processors, and Table 5 represents the results of using 16 processors. Tables 6 through 8 reflect the speedup for P=2, 4, and 16, respectively. By definition, there is no speedup when only one processor is used. The values in these tables were derived from equation (4)(a). Equation (4)(b) was used to determine the efficiency of the invention as the number of processors increases. The results are available for 2, 4, and 16 processors in Tables 9 through 11. A graphic representation of the results is presented in FIGS. 5 through 9. For clarity, the results of O=TA has been isolated.
To show the effects of the invention over a range of document set sizes, various graphs are superimposed over the same set of axis. To allow for superimposing the graphs, a special notation has been adopted. "T" represents time, the digit represents the number of processors and the number following the underscore represents the size of the document set. So TI-- 32 represents the time needed for 1 processor operating on 32 documents. In a similar fashion, T16-- 128 represents the time for 16 processors operating on 128 documents. The use of "C" along the bottom axis represents the value of the coefficient (0.2 through 0.8). The subscripted letter, j, serves as a counter to ensure the alignment of results of the documents sets with the appropriate value of the coefficient. "S" is used to represent speedup. S32 represents speedup for 32 documents, S64 is speedup for 64 documents etc. Again, the subscripted letter, j, ensures proper alignment of speedup based on the document sets and the coefficient. In the final figure, the "P" represents the number of processors used with "j" aligning results for each value of "P".
FIG. 5 shows the time to cluster the document sets for each value of C and D. As intuition would indicate, it longer to cluster a larger number of documents into a larger number of clusters. The significance of FIG. 5 is in how it compares to the performance as the number of processors increases. The subsequent figures represent time with various values of P. The speedup chart which accompanies each time chart reflects the performance of a given value of P compared P=1.
FIG. 6 displays the results of using 2 processors. The chart shows a decrease in time using the 2 processors versus using 1 processor. The speedup chart reflects how much faster the invention is performing. To determine the speedup select the coefficient of interest, for example 0.6. Draw a line straight up until that line intersects with the lines representing the document set of interest, for example, S128. From the intersection point draw a line straight to the left. The point where this line intersects the vertical axis is the speedup. With the values of C=0.6, and D=128 (S128) the speedup is 1.79. In other words, 128, TA,0.6,2! is 1.79 times faster than 128,TA,0.6,1!.
The next figures represent results for P=4 and P=16. In all cases it can be seen that the speedup is better as D and C increase. It is clear from FIG. 8 that there is a marked increase in the performance of the invention as D, C, and P have increased.
FIG. 9 isolates O=TA and C=0.8 to better show time to perform the clustering and the invention's speedup across an increase in P. FIG. 9 shows several things. First it is clear that speedup will decrease if D is constant and P is allowed to increase. Clearly, the invention takes less time as the number of processors increase. However, note that the curve for D=128 continues to decrease. It is important to note that speedup is increasing as both D and P increase. For example, the D=32 has a break point at P=4. This break point indicates it takes longer to perform the clustering as the number of processors increases. This increase is caused because the document set is not large enough to keep each processor productively employed. Also, as the number of processors increases, so to does the amount of time spent passing messages. The breakpoint is an indicator of when the messaging overhead takes longer than the processing time to perform the clustering. The break point is not yet reached for D=64 but is flattening out. The figure clearly shows that D=128 is still rising at P=16 which indicates P can increase and still provide reasonable speedup performance. More importantly, the figure shows two significant trends. The first is that performance is better if D increases while P is held constant. The other trend is the increased performance of the algorithm for increases in D and P. These results clearly show the invention does as stated: that is efficient clustering of large document sets in a practical parallel environment.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 6 19 30 32 TA 9 20 30 32 TD 5 17 30 32 UA 9 19 30 32 UD 5 17 30 3264 R 6 34 53 56 TA 10 38 53 58 TD 4 32 53 58 UA 10 37 53 58 UD 4 34 53 58128 R 8 52 97 120 TA 11 60 101 122 TD 6 49 94 122 UA 11 57 100 122 UD 6 53 96 122______________________________________ Table 1 represents number of clusters based on number of documents, order of documents and coefficient of similarity.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 0.937 1.354 2.361 2.495 TA 0.560 1.530 2.138 2.241 TD 1.270 1.770 2.719 2.795 UA 0.551 1.535 2.124 2.239 UD 1.280 1.761 2.712 2.78964 R 2.651 5.488 8.377 8.680 TA 1.432 5.019 6.470 7.058 TD 3.429 6.287 9.131 9.456 UA 1.592 4.898 6.393 7.019 UD 3.438 6.330 9.114 9.458128 R 7.278 17.913 27.252 29.419 TA 3.591 10.354 20.219 24.969 TD 8.881 16.749 27.561 32.071 UA 3.538 9.686 19.435 24.937 UD 8.938 15.521 28.184 32.152______________________________________ Table 2 represents the time required to form clusters using D = 1. Time includes the processing time and the messaging time.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 1.115 1.273 1.541 1.525 TA 0.815 1.087 1.310 1.362 TD 1.577 1.317 1.671 1.693 UA 0.766 1.064 1.363 1.357 UD 1.477 1.372 1.690 1.69064 R 3.028 4.131 4.657 5.148 TA 1.729 3.259 3.717 3.886 TD 3.860 4.492 5.168 5.266 UA 1.719 3.230 3.731 3.958 UD 3.821 4.041 5.158 5.251128 R 5.955 12.279 14.580 16.227 TA 4.002 8.069 11.297 13.015 TD 9.561 12.068 15.792 17.384 UA 3.937 8.002 11.152 13.312 UD 9.617 10.554 15.885 16.951______________________________________ Table 3 represents the time required to form clusters using D = 2. Time includes the processing time and messaging time.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 1.204 1.014 1.087 1.089 TA 0.803 0.829 0.943 0.944 TD 1.489 1.148 1.201 1.172 UA 0.896 0.850 0.956 1.040 UD 1.511 1.219 1.156 1.18164 R 2.981 2.844 2.867 3.141 TA 1.751 2.157 2.288 2.392 TD 3.841 3.55 3.031 3.146 UA 1.846 1.973 2.288 2.408 UD 3.849 2.857 3.050 3.138128 R 7.951 8.529 8.450 9.463 TA 4.023 5.303 6.469 7.243 TD 9.670 8.560 8.618 9.428 UA 4.020 5.084 6.405 7.305 UD 9.672 7.209 8.707 9.258______________________________________ Table 4 represents the time required to form clusters using D = 4. Time includes the processing time and the messaging time.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 1.474 1.252 1.216 1.237 TA 1.292 1.071 1.170 1.192 TD 1.740 1.371 1.303 1.257 UA 1.315 1.252 1.158 1.231 UD 1.776 1.400 1.247 1.21964 R 3.250 2.071 2.145 2.138 TA 2.209 1.911 1.922 1.903 TD 3.919 2.557 2.376 2.144 UA 2.253 1.952 1.957 1.916 UD 3.950 2.450 2.178 2.069128 R 8.076 4.500 4.410 4.549 TA 4.624 3.884 3.760 4.004 TD 9.649 4.802 4.435 4.683 UA 4.491 3.987 3.812 3.945 UD 9.587 4.740 4.510 4.491______________________________________ TabIe 5 represents the time required to form clusters using D = 16. Time includes the processing time and the messaging time.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 0.840 1.064 1.532 1.636 TA 0.687 1.408 1.632 1.645 TD 0.805 1.344 1.627 1.651 UA 0.710 1.443 1.558 1.650 UD 0.867 1.284 1.605 1.65064 R 0.875 1.328 1.799 1.686 TA 0.828 1.540 1.741 1.816 TD 0.888 1.400 1.767 1.796 UA 0.926 1.516 1.713 1.773 UD 0.9 1.566 1.767 1.801128 R 1.222 1.459 1.869 1.813 TA 0.897 1.283 1.790 1.918 TD 0.929 1.388 1.745 1.845 UA 0.899 1.210 1.743 1.873 UD 0.929 1.471 1.774 1.897______________________________________ Table 6 represents the speedup attained using D = 2.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 0.778 1.335 2.172 2.291 TA 0.697 1.846 2.267 2.374 TD 0.853 1.542 2.264 2.385 UA 0.615 1.806 2.222 2.153 UD 0.847 1.445 2.346 2.36264 R 0.889 1.930 2.922 2.763 TA 0.818 2.327 2.828 2.951 TD 0.893 1.771 3.013 3.006 UA 0.862 2.483 2.794 2.915 UD 0.893 2.216 2.988 3.014128 R 0.915 2.100 3.225 3.109 TA 0.893 1.952 3.126 3.447 TD 0.918 1.957 3.198 3.402 UA 0.880 1.905 3.034 3.414 UD 0.924 2.153 3.237 3.473______________________________________ Table 7 represents the speedup attained using D = 4.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 0.636 1.081 1.942 2.017 TA 0.433 1.429 1.827 1.880 TD 0.730 1.291 2.087 2.224 UA 0.419 1.226 1.834 1.819 UD 0.721 1.258 2.175 2.28864 R 0.816 2.650 3.905 4.060 TA 0.648 2.626 3.366 3.709 TD 0.875 2.459 3.843 4.410 UA 0.707 2.509 3.267 3.663 UD 0.870 2.584 4.185 4.571128 R 0.901 3.981 6.180 6.467 TA 0.777 2.666 5.377 6.236 TD 0.920 3.488 6.214 6.848 UA 0.788 2.429 5.098 6.321 UD 0.932 3.274 6.249 7.159______________________________________ Table 8 represents the speedup attained using D = 16.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 0.420 0.532 0.766 0.818 TA 0.343 0.704 0.816 0.822 TD 0.403 0.672 0.813 0.826 UA 0.359 0.721 0.779 0.825 UD 0.433 0.642 0.803 0.82564 R 0.438 0.664 0.900 0.843 TA 0.414 0.770 0.871 0.908 TD 0.444 0.700 0.883 0.898 UA 0.463 0.758 0.857 0.887 UD 0.450 0.783 0.883 0.900128 R 0.611 0.729 0.934 0.906 TA 0.449 0.641 0.895 0.959 TD 0.465 0.694 0.873 0.923 UA 0.449 0.605 0.872 0.937 UD 0.465 0.735 0.887 0.948______________________________________ Table 9 represents the efficiency attained using D = 2.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 0.194 0.334 0.543 0.573 TA 0.174 0.461 0.567 0.594 TD 0.213 0.386 0.566 0.596 UA 0.154 0.451 0.555 0.538 UD 0.212 0.361 0.586 0.59064 R 0.222 0.482 0.730 0.691 TA 0.205 0.582 0.707 0.738 TD 0.223 0.443 0.753 0.752 UA 0.215 0.621 0.698 0.729 UD 0.223 0.554 0.747 0.753128 R 0.229 0.525 0.806 0.777 TA 0.223 0.488 0.781 0.862 TD 0.229 0.489 0.799 0.850 UA 0.220 0.476 0.758 0.854 UD 0.231 0.538 0.809 0.868______________________________________ Table 10 represents the efficiency attained using D = 4.
______________________________________D O CDocuments Order Coef = 0.2 Coef = 0.4 Coef = 0.6 Coef = 0.8______________________________________32 R 0.040 0.068 0.121 0.126 TA 0.027 0.089 0.114 0.117 TD 0.046 0.081 0.130 0.139 UA 0.026 0.077 0.115 0.114 UD 0.045 0.079 0.136 0.14364 R 0.051 0.166 0.244 0.254 TA 0.041 0.164 0.210 0.232 TD 0.55 0.154 0.240 0.276 UA 0.044 0.157 0.204 0.229 UD 0.054 0.162 0.262 0.286128 R 0.056 0.249 0.386 0.404 TA 0.049 0.167 0.336 0.390 TD 0.058 0.218 0.388 0.428 UA 0.049 0.152 0.319 0.395 UD 0.058 0.205 0.391 0.447______________________________________ Table 11 represents the efficiency attained using D = 16.
Patent Citations
Non-Patent Citations
Referenced by
Legal Events
Original Image


text:
Spirometry 360®
Spirometry 360® is an educational and skill-improvement program that employs a variety of training techniques yet is focused and flexible enough to fit into providers' busy schedules. The program is comprised of three synergistic components:
- Spirometry Fundamentals: A basic guide to lung function testing
- Spirometry Learning Lab: Case-based teaching of spirometry in practice
- Spirometry Feedback: Personalized analysis of providers' spirometry curves
The current version of Spirometry 360® is not compatible with mobile devices such as smart phones and tablet computers. A desktop or notebook computer with a high speed Internet connection is required to use the software.
For more information: http://www.spirometry360.org/
Licensing Information
Spirometry 360® is one of the many software programs and tools created at the University of Washington available through our Express Licensing Program. These agreements have standard terms and conditions that allow for rapid licensing by companies, organizations, or individuals
Spirometry 360® can be licensed by clicking the button on the right.
Spirometry 360® IPCRGLicense
Spirometry 360® -IPCRG can be licensed by clicking the button on the right.
Spirometry 360® -PCORI ClinicsLicense
Spirometry 360® -PCORI Clinics can be licensed by clicking the button on the right.
The conditions and financial terms of this license apply only to those who download the license, sign it and return it "as is" to the UW Center for Commercialization. Some Express Licenses may be modified for an additional cost. Other licensing arrangements may be available.
For Descriptive and Technical Information
University of Washington
Box 354920
Seattle, WA 98195-4920
Email: email@example.com
For Licensing Information/Customer Service
UW CoMotion
4311 11th Avenue NE, Suite 500
Seattle, WA 98105-4608
Phone: (206) 543-3970
Fax: (206) 616-3322
Email: email@example.com

subset: commoncrawl


text:
Recent Posts
The Occasional Tweet
Error: Twitter did not respond. Please wait a few minutes and refresh this page.
Raphael: A Passionate Life by Antonio Forcellino
translated by Lucinda Byatt. Polity June 2012
Available from Book Depository
Wherever possible I have acknowleged the use of copyright material that I have included when writing the posts featured on this website. I would appreciate it if others did the same.
Please ask me before you copy text from my posts and pages. You can contact me through the website or email:
mail (at) lucindabyatt (dot) com
Blogs worth a visit (or two)
Holiday cottage in Argyll
ITI Italian Network
Research interests
Monthly Archives: March 2009
The BBC World Service is at a turning point
I'm sorry that I haven't posted on this earlier but – like many interesting topics – I came across the whole question by chance. Having read a little more about the issues involved, the whole subject seems so fundamental that … Continue reading
One hundred years of (Inter)National Women's Day (NWD)
In a year that seems to have been one anniversary after another, yesterday – 28 February – marked the centenary of the first National Women's Day. Officially, however, the centenary celebrations won't be held until 2011 because National Women's Day … Continue reading


text:
How I had four kids in 4 years after 7 years of a barren marriage-Asu Ekiye
Recounting his life story to challenge any audience he faces with his unique gospel music has become part of the inspirational brand award winning artiste, Asu Ekiye. In this chat with SHOLA O'NEIL and WILSON YAFUGBORHI, the Ijaw born "Prince of the Niger Delta" spoke on a number of issues including his marital challenge and initial struggles to break into the limelight.
TELL us a bit about growing up? Asu Ekiye is the Prince of the Niger Delta. I am from Bayelsa, and I have Delta roots. I am a gospel musician. I had my primary education in different parts of the country because of my father's frequent posting as a military officer. My secondary school was at the Hussey College Warri, and I studied Accountancy at the University of Science and Technology, Port-Harcourt. I did my youth service in Ramat Polytechnic, Maiduguri. I returned to Port-Harcourt and joined a firm of chartered accountants. It was in the firm I responded to the call to go into music. I have won several awards, travelled far and wide playing music since over a decade ago.
What's your background in music?
Actually, my background was hip pop and R&B. There was desperation to put out something of international standard and generally accepted style of music which I did. People appreciated it but it never translated into any meaningful return to my wallet. The collection enjoyed airplay, but it never made instant hit. On the 10th year, I tasked myself to develop something international, but with local uniqueness.
I set my heart on it. So, I had the inspiration to widely explore local songs, traditional roots lyrics, folk tales songs, across ethnic backgrounds concentrated in the Niger Delta. I put them together and I have associates paving the way for me. In one year, we took further stride to go into the grassroots of the Niger Delta, exploring the diverse and rich tradition and culture of the people for a musical video. That hit made a bang and made the nation to be on high. Everyone wanted to hear Asu Ekiye. There has not been any looking back since then.
The dramatics of your brand is so unique at a time when everyone wants to be Western. How do you sustain the ability to captivate your audience in such a unique fashion?
You know the world generally is Americanized. This is even more evident in entertainment. America dictates everything. The most celebrated musicians, actors and producers are Americans. Even our mode of dressing is dictated by America. Everyone wants to copy America. And I thought it would reward my dignity for us to institutionalize a homegrown brand that would appeal to international audience. Thank God, we have made quite a resounding impact. On top of that you have a new wave of dancehall music making a lot of impact. And we strive to reinvent and fine tune to meet the demands of time without shutting out our roots content which gave us a break.
And then what followed? It seems you were in limbo for a while.
Why would you think I was in limbo? When you release a song with such overwhelming impact and acceptance, you need time to take full advantage of the promotion. We were very much on ground. We released a second album and it gave us the Channel O Awards in South Africa. Twice, we got the awards. It shot us as a unique brand in the whole of Africa. And then our second and third albums took us round the world, to Europe, America and beyond. We were appreciated everywhere we went, but we did not lose sight of being committed to fashioning out the next hit. At the moment, we have something unique. It's an 11 tracker album titled "Eniye". In a matter of weeks, it should hit the market. It hosts some of the most entertaining fusion of music. We are red hot to blow and it will blow your mind.
You shocked your Ijaw brothers recently when you said they were less supportive of your music than other tribes. Put that in perspective.
I meant that if it were for my Ijaws brothers alone, I would not have survived in the industry. Most of the people who patronized me are non Ijaws. It could be because of the Ijaws relatively lower numerical strength. But I know they have not supported me enough however I did not mean it in absolute terms. There are few Ijaws who have given me outstanding support over the years. Of course, none of them compares to my highly regarded former governor of Bayelsa, Alameisiegha. There are Orubebe, a young man named Wari and Goodluck Jonathan, when he was Governor; these are very powerful people who have supported me. The situation is getting better but I needed to make a statement about it.
Recounting the personal challenges you have faced in your private life have formed part of the inspirations that drives you as a brand. You want to share that here?
Yes. I was married for seven years without a child. My wife also happens to be an accountant. In our peculiar African tradition, the long stay without a child came with a lot of challenges and antagonism. We tried everything, went everywhere yet respite did not come. But we were in agreement as a family and we trusted seriously in God when every other option failed. Today, all that is history. By our faith in the unlimited favour of God, the children have come. We are even doing family planning. They are too much already. So, I do not forget motivating my audience with my faith in God, using the better forgotten difficulties of yesteryears as an example. As the children have come so has material provisions come. We have no reason to complain at all.
A word for the younger generation aspiring to emulate you?
Rate this article
What Boko Haram and NADECO have in common
As we watched troubled President Goodluck Ebele Jonathan in his black kaftan with black cap behind the distraught emir of Kano last week, it was ... Full story


text:
Two days ago an email came from an Iraqi doctor in Baghdad in response to a brief greeting I sent for the month of Ramadan.
"Thanks so much for remembering us…In fact we are the same if not worse. Our hearts are broken at the organized ruining of our country. We are targeted by those criminals and gangs coming from everywhere, even from the west who are all witnessing this drama and, if not supporting it, are keeping silent. We wonder what sin we committed to face this gloomy black fate. In fact, what is going on is beyond words."
This courageous woman doctor never left the side of gravely ill children despite the great exodus of doctors due to kidnappings, assassinations and threats to their lives and families. Sadly she reports that another of her siblings has cancer, and she needs to leave the medical students for some days. This happens she says regretfully in "the critical time of final exams." She herself is a cancer survivor and both her mother and sister had cancer. They have no choice, she says, but to go on and try to survive.
Another longtime friend is working in southern Iraq in a job that will soon end. He is away from his family in Baghdad, and it is dangerous for him in the south, but he has no choice with a wife and seven children to support. There was already an assassination attempt on his life in Baghdad and houses near their own have been bombed. There are nightly explosions and gunfire, assassinations and kidnappings. Approximately 200 people across Iraq have been killed each day in this month alone.
We have been frantically trying to find a safe place for him and his family to escape to. If they could go to Kurdistan they would join the ranks of the already three million IDPs (Internally Displaced Persons) within Iraq. If they could get to Turkey, they might eventually get refugee status. But it is expensive there, they don't speak the language, are not allowed to work and resettlement could take years.


text:
1. Preheat oven to 375 degree.
2. For top decoration, slice apple as shown in the video.
3. On a large baking tray, lay apple slices, and sprinkle flour, sugar, and cinnamon on it. With your hands break apple slices, and toss to coat evenly.
4. Cover it with another pan, pop it in oven, and bake for 15-30 minutes or until apples are tender.
5. Take tray out of oven, and break them down with pastry cutter. Do not mash it just chop it finely with cutter.
6. Place the tray again in oven and let some moisture from the apple steam off.
7. Into a bowl, put baked apples, and keep it aside.
8. Roll pie dough, lay it on an 11-inch pie pan, and cover it with foil as shown in the video.
9. Put beans on it, and pop it in the oven for 10 minutes, just to bring a light brown colour.
10. Remove tart shell from oven, lift the beans from it, and allow it to rest for about 5 minutes.
11. Scoop baked apples into the shell. Spread it evenly.
12. Lay sliced apples on the tart as shown in the video.
13. With a brush, gently apply margarine on the apple slices.
14. Sprinkle sugar on top.
15. Pop it oven and bake for 30 minutes.
16. Take tart out of the oven, and apply apricot jam on it as glaze. Remove the pan, and allow it to cool.
17. Cut into slices and serve French apple tart immediately.
Apple edges will get blackened, so don't worry and allow it to cook.


text:
This site is developed from the Renaissance Popular Culture course at Duke University taught by Kelly A. Amienne in spring 2006. (Course numbers: ENG 139BS-01/MEDREN 139BS-01)
Over the course of the semester, students worked in small groups to research, design, and publish scholarly websites on topics related to our focus of inquiry: Renaissance popular culture. In preparation, they wrote short essays on our course texts and gave presentations to contextualize our readings in the cultural forces of a period ranging roughly 1500-1680. They developed the sites you find here out of our class discussions as well as from research using Duke's Special Collections, electronic resources such as Early English Books Online, academic journals, and traditional print monographs, among a variety of materials.
Please follow the link to a list of materials covered in the course
We owe many thanks to others in the university who helped make the creation of these projects possible. To Sarah Seten Berghausen (Librarian for Literature and Theater Studies) for instructing students in library and online research at Duke and remaining an on-call resource throughout the semester. To Linda McCurdy (Director of Research Services at the Rare Book, Manuscript, and Special Collections Library) for introducing students to the pleasures or centuries-old books and walking them through archival research procedures. And to Deen Freelon (Training Coordinator/Manager, MPS East & West, OIT - Student Technology Services) for teaching students how to create websites and for remaining a tireless support in countless lab sessions.


text:
About TicketCity
TicketCity is a great source to buy STP Gas Booster 500 tickets. We buy and sell STP Gas Booster 500 tickets for all events. TicketCity provides detailed information so that you are well informed in making your STP Gas Booster 500 ticket purchase. Our office is open 7 days a week, so please contact us if you have ticket questions.
Rick has been my guy for years now and never disapoints. I buy 8 to 10 times a year from TicketCity.Steve - Austin, TX


text: http://androidforums.com – I'm on Vodafone in the UK with a 500mb/month data package. I've had the Desire for 18 months now, and although I've been happy with it, recently the data usage on mobile (3g etc) has been going through the roof. After doing a bit of research it appeared to be a bug with the OS when WiFi and mobile data were enabled simultaneously. So, last Friday before leaving the office WiFi goes off and mobile data comes on. During a 2 hour meal with friends the handset manages to consume 128mb of data! I have Traffic Monitor installed (as well as Traffic Counter to verify usage) which shows what app (General)


text:
Victoria Defrancesco Soto: Gingrich is in that sweet spot to the right of Romney and to the left of Santorum. It is in this spot that Romney needs to concern himself.
Progressive Media Advocates
Treva Brandon Scharf: Confident people don't bash themselves; they don't let negative thinking and self-loathing screw up a good workout or undermine their progress.
Edward Wasserman: The larger question, to me, was less why she did what she did, but why everybody seemed to care so much, and why her case provoked so much anger.
Joe Mathews: But with immigration flatlining and the climate drying up, it may soon be.


text:
- News
- Premium
- Lifestyle
- Tech
- Communities
- Video
- Multimedia
- More
Schools get children talking the Stellar way
Role play helps to hone pupils' ability to speak clearly and confidently
Published on Mar 31, 2014 8:12 AM
Four pupils sit facing their classmates, their lips tightly pursed, looking ready and certain of what is to come.
"How did you feel when you met your long-lost daughter?" "Who did you decide to stay with in the end: your foster or birth parents?" Questions poured forth.
The Primary 6 pupils from Punggol Primary were having a mock press conference, with some posing as reporters and others as characters in a story about Sallamah, a Chinese girl adopted by a Malay family.
"Sometimes I got stuck but I used my imagination to answer questions, based on how I thought the character would feel," said Nivrithi Ganesh, 12, who played Sallamah.
To continue reading, log in if you are a subscriber
Enjoy 2 weeks of unlimited digital access to The Straits Times. Get your free access now!
Background story
"I pick up interesting phrases as I read and use them in my compositions."
- Da Qiao Primary pupil Celyna Teo, 11, said she has learnt to read the news through a weekly 30-minute segment where everyone presents newspaper articles
"I used to be very shy in lower primary, especially during show-and-tell when everyone was looking at me. But presenting in front of my class helps me to be brave. I can now talk to people I'm not familiar with like some relatives."
- Punggol Primary pupil Lim Jin Kai
"We're looking at a new economy in Singapore, where communication skills - the ability to express what you know - are really important."
- Dr Elizabeth Pang, MOE's programme director for literacy development
"We're testing pupils on their ability to speak off the cuff and think on their feet, which are critical life skills."
- Madam Shakila Jamal Mohamed, 45, an English teacher at Da Qiao Primary


text:
The looming spectrum crunch (and one possible solution)
By: SGN Staff
Editor's note: Getting more spectrum is one of the two biggest issues facing utilities, Connie Durcsak, CEO of the Utilities Telecom Council (UTC), said recently. (Enhancing cybersecurity is the other.) Durcsak rightly pointed out that distribution automation applications require a lot of redundancy and have low tolerance for latency. Substantially more bandwidth is required because "it's about transporting a vast amount of data needed to manage this complicated environment and we have gone from one-way communications to multi-way," she said.
UTC is pursuing one partial solution - namely, getting utilities included in plans for the nationwide public safety network, a broadband network that will operate in the 700 MHz band. But when a small company wrote me with another solution, I asked CEO Brian Andrew to contribute the short article below.
Brian had previously submitted a piece asking whether free spectrum can deliver the "ultimate" network. He is not without bias, since his company is one of the few that can perform the trick described below - namely, aggregating several small channels to create the equivalent of one big one. Whether or not you agree with this particular solution, I wanted to be sure you were alerted to the problem. Take a look, and use the Talk Back form to comment on its potential. - Jesse Berst
By Brian Andrew
Every utility I speak with is concerned about spectrum availability and achieving higher bandwidth throughputs. Today, many utilities are experiencing interference with their unlicensed installations and/or are researching or investing in their own spectrum to add to their capacity.
The issue presented with purchasing licensed spectrum in the 200 or 900 MHz frequency range (besides cost) is that they are typically small chunks from 25-50 kHz and are rarely, if ever, contiguous.
The aggregation solution
25 kHz will give you about 20 Kbps throughput and 50 kHz top ends around 40 Kbps. Multiple networks of 10-40 Kbps throughput may not meet the need. For higher bandwidth throughput the only solution is to aggregate (bring together) those non-contiguous narrow band channels.
Aggregation works great whether you have purchased spectrum that is noncontiguous or are thinking of utilizing FCC Part 90 secondary licenses.
For those of you not up-to-speed on Part 90 secondary licensees; you get protection from any secondary license holders that are licensed after you. First in gets priority. So the message here is "GET IN EARLY".
Spectrum on a secondary basis
If you investigate, I expect you will find there is plenty of available spectrum in the 217-220 MHz range to use on a secondary basis. This can be beneficial if you have not purchased any spectrum or you have "some" spectrum but not enough. If you don't have enough you can supplement your purchased, licensed channels with secondary use licenses.
For instance our Parseous "Aggi" radio (Aggi as in aggregating) in the 217-220 MHz frequency range, aggregates up to 40 non-contiguous channels (6.25 kHz wide) to dynamically deliver up to 200 Kbps throughput in an on-demand basis. There are 240 12.5 kHz channels in the 217-220 MHz frequency range for the radio to select from. If you own spectrum, you can set your channels as priority channels to be used by the radio and increase bandwidth throughput capacity by adding in channels on a secondary basis.
To operate under the secondary licensing rules, the radio must dynamically stop using that frequency and automatically switch channels if another licensed user with priority is sensed, if necessary to avoid interference and eliminate any service interruption.
Consider channel aggregation to increase throughput. In addition, consider radio management of time, space, frequency and power to improve reuse and eliminate interference in a high-density network. A frequency-hopping technique is a good choice to minimize the amount of time that any frequency is utilized. Radios should also dynamically regulate their transmit power so they utilize the minimum amount of power needed to establish solid communications.
Brian Andrew is the CEO of Parseous Systems, whose radio systems are deployed for power utilities, water municipalities, farming, security and government and military installations.


text:
2 Reviews
4 star
3 star
2 star
1 star
Average Customer Review
Share your thoughts with other customersCreate your own review
Most Helpful First | Newest First
5.0 out of 5 stars A High Call To Exemplary Leadership,
C. R. Merola (Sterling, VA) - See all my reviews
This review is from: Christian Reflections on the Leadership Challenge (Hardcover)
I just read Christian Reflections on the Leadership Challenge edited by Jim Kouzes and Barry Posner, and am I glad I did. This is a fantastic book-both informative and inspiring.
Kouzes, Posner, and the five others whose chapters are included in this book offer invaluable insight as to how we can join with Jesus in exercising leadership within the framework of our faith. In so doing, they touch upon such themes as passion, service, and sacrifice. Consider, for instance, these lines from Patrick Lencioni, the author of Chapter 5: "Before setting out on a quest to challenge the process and change the world, Christian leaders should probably ask themselves two questions: 'Who am I really serving?' and 'Am I ready to suffer?'" This chapter, I think, brings us right to the heart of what it really means to be a Christian in a country where so many have forgotten.
Throughout each of the chapters, these same themes sound in one way or another. Whether it is a willingness to sacrifice time, credit, power, position, prestige, comfort, or even money, it is clear that suffering and sacrifice are at the very heart of the leadership enterprise. That is perhaps the chief reason why leadership is rightly described as a challenge in the first place. Though it is within the reach of everyone, it will not come easily or without cost. Nobody knew this better than Jesus.
There are, of course, other themes discussed, as well as the "The Five Practices of Exemplary Leadership" for which Kouzes and Posner are best known. In fact, Chapter 2, which discusses the Five Practices specifically applied within a Christian context, is one of the best in the book. I also thoroughly enjoyed Chapter 6 by Nancy Ortberg. Though trained as a nurse, she answered God's call to ministry in a way that would put many with advanced theological degrees to shame. Very inspiring! And Chapter 8, again by Kouzes and Posner, really brings it all into focus in a very practical way.
I have found much to ponder in this book, and I have every confidence that anyone wishing to better emulate Jesus will too.
5.0 out of 5 stars This book offered a transformational leadership model that has been ...,
Verified Purchase(What's this?)
This review is from: Christian Reflections on The Leadership Challenge (Paperback)
This book offered a transformational leadership model that has been endorsed for a Christian audience. I believe church and para-church organizations will be blessed by reading and more importantly, implementing the 5 practices and 10 commitments of the Leadership Challenge.
Most Helpful First | Newest First
Christian Reflections on The Leadership Challenge by John C. Maxwell (Paperback - April 14 2006)
In Stock


text:
Find A Screenplay
Deadlocked, is written of the short story, Deadlocked by A.R. Wise.
Created by LilyxMasacre on 06/10/2012. Last change by kitana 13 days ago.
11 writers have written 11 pages in 2 scenes.
The book Huntress basically
Created by rdar97 two years ago. Last change by rdar97 two years ago.
1 writer has written 0 pages in 1 scene.


text:
Florida woman gets 24 years after tweeting '2 drunk 2 care' moments before fatal car crash
What are the most-tweeted foods in D.C., Virginia and Maryland?
Joshua Starr gets offensive tweets during winter storm
Montgomery County's superintendent says he received offensive tweets during last week's winter weather from students urging him to close schools.
American Academy of Pediatrics: Unrestricted media is bad for kids
The American Academy of Pediatrics has new advice many kids will find hard to swallow: It wants limits on tweeting, texting and other social media. The group says smartphones and laptops should stay out of children's bedrooms.
Tweeting about healthComment
A tweet that might seem like too much information can actually be used for the greater good, experts said.
RecommendedRecent Facebook Activity
Only On 7
Watch ABC7 News at 4!ABC7 gives you MORE news in your afternoons with an extra hour, an hour earlier! Watch to see what's trending in your community and world every weekday afternoon at 4pm right after back to back "Hot Bench" shows at 3pm on ABC7.


text:
The screen, developed by Sara Sukumar, Ph.D. and Mary Jo Fackler, Ph.D., first separates cells from fluid, then sifts through the cells' DNA for chemical tags on certain genes associated with cancer.
Reporting in the June 1 issue of Clinical Cancer Research, the scientists say they have tested their screening tool on breast fluid, in search of cells shed from growing tumors.
"This screening method can see what the eye cannot see," says Sukumar, who is the Barbara B. Rubenstein Professor of Oncology at the Johns Hopkins Kimmel Cancer Center. "It can be a valuable tool, in combination with pathological review, for breast cancer as well as other diseases where fluid can be obtained relatively easily, such as lung, head and neck cancers, pancreatic and cervical cancers."
Pathologists look for telltale shapes of cells to determine if cancer is present, but molecular changes in cells, especially for early cancers, are beyond the reach of even the most powerful microscopes.
Sukumar's test searches for unusually high amounts of chemical tags embedded by a process called methylation within critical regions of DNA. The tags attach to the "on" switch of genes which starts the message-manufacturing process. Cancer cells have abnormal levels of methylation, which turns the gene switch off halting the assembly line of critical proteins found in normal cells.
The Hopkins test, called quantitative multiplex methylation-specific PCR or QM-MSP, determines the percentage of methylation present in each of five to ten cancer genes. The percentages are added together for a cumulative score, which is compared to a threshold value. Levels above the threshold indicate the potential presen
Source:Johns Hopkins Medical Institutions


text:
Bush's trip to the Middle East was not exactly a victory lap
President Bush's five-day Mideast trip fell far short of success. Indeed. "failure" might not be too strong a word. For the second time this year, he went to Saudi Arabia as a public supplicant to convince Saudi Arabia to increase the flow of oil, and for the second time he was rebuffed by King Abdullah. If Bush didn't know this would be the result, his advisers should have alerted him. Making the indignity worse was that oil futures then set a new record.
He sought, with indifferent results, to build support for his policy of further isolating Iran. The U.S. lack of progress on Iran was underscored Sunday when he had to cancel a meeting with Lebanese Prime Minister Fouad Siniora, a U.S. ally, because of an ongoing crisis with Iranian-backed Hezbollah.
An audience of 1,500 Arab political and business leaders reacted stiffly to a Bush lecture urging them to adopt sweeping political, economic and cultural reforms. He got in an indirect dig at his host, Egypt's autocratic Hosni Mubarak, who in fact does have the opposition leader in jail: "Too often in the Middle East, politics has consisted of one leader in power and the opposition in jail." This would have had more resonance if the U.S. hadn't quit nudging him toward democracy once we needed his support on Iraq.
He told the Arab dignitaries "we must stand with the Palestinian people who have suffered for decades and earned the right to have a homeland of their own." That, too, might have had more resonance had he not just come from a fulsome embrace of Israel during which he made only passing reference to the Palestinians.
Bush's goal was a Palestinian state by the end of his presidency but now, his advisers say, it will be counted a success if a "process" is in place.
Some of the coolness with which Bush was greeted was surely because he has only a short time left in office and the Arab leadership calculates that the wiser course is to wait it out and deal with his successor. In the headily optimistic days of 2001-2002, Bush surely thought that a swing through the Mideast in the last year of his presidency would be a victory lap. Instead, it was a reminder of how far his policies have fallen short.
Subscribe to the Caller-Times
Need Help? Call us at 1-800-566-8098.
Monday-Friday: 6am-3pm / Saturday: 7am-11am / Sunday: 7am-11am


text:
Deviant Art
all because of one sheet (Johnlock)"John?"all because of one sheet (Johnlock)3 years ago in General Fiction More Like This
"Mhm?" John looked up from his laptop and raised one eyebrow at his flatmate. "What i-..." He blinked and tried not to concentrate on the completely naked detective in front of him. "Sherlock? What the hell are you doing?"
"I can't find my sheet."
"Put on some clothes!" John stared at his laptop, he didn't dare to look up again, even as Sherlock was laughing.
"I just wanted to ask you, if you have seen my sheet somewhere. But as a result of your reaction I deduce that you haven't. You are ashamed to see your flatmate naked, or possibly like it, because you blushed and you can hardly keep yourself from looking at me again."
"Would you please shut up, Sherlock?"
"I'm right, am I not?"
"Damn, no, Sherlock! You aren't right! And I don't like this experiment very much! I'm begging you, put on some clothes!"
"Why do you think it's an experiment, John? I'm just looking for my sheet, but I can't find it. Maybe Mrs. Hudson put it away..."
"Yeah, maybe." John grumbled. "Go and ask her!"
|Sta.sh Submit


text:
The standard line about the Hermitage Museum on the banks of St. Petersburg's Neva River is that you can spend days wandering its rooms and only see a small fraction of the millions of masterpieces under its roof. But glance out the window next to that ancient Roman statue and you may see something as much a fixture of the museum, but not nearly as celebrated: cats.
Dozens of cats roam the grounds of the Hermitage, living in the museum's gardens and labyrinthian basement, cared for by a designated staff. They've lived here for centuries, first brought in by the imperial family to rid the Winter Palace of rats, and for the last 10 years cared for by the office of the director of the Hermitage.
"We joke that if [our director] permits us to have 50 cats, so we [technically] have 50 cats. But really we have around 60 cats," says Maria Khaltunin, the director's assistant and head of the cat program.
Tsarina Elizabeth, daughter of Tsar Peter the First, first demanded cats in 1774 to keep the palace's rats and mice in check. Legend has it she sent a special transport to the city of Kazan to bring back these cats, supposedly especially good hunters.
The love of -- and need for -- cats got passed down from one generation of the imperial family to the next. During the siege of Leningrad (St. Petersburg's former name) during World War II, all the cats died. They were brought back to the museum soon after the blockade ended to cull the vermin population that had exploded over three cat-free years.
Thanks to poison, the days of relying on cats as the museum's hunters are long gone. But the tradition of cats at the Hermitage is more structured and stronger than ever.
"Now we have people in charge, people who came here only 10 years ago when we started to organize this work," says Khaltunin. "There were just the cats, the common street cats, the common yard cats who were not so nice, so clean and so brave. In 10 years, they became more kind and more gentle."
The galleries - home to priceless works by Raphael, Monet and Renoir - are strictly off limits to the cats, and consequently not seen by most visitors. But otherwise the cats have the run of the place.
In the Old Hermitage Yard, a tabby darts behind a pile of columns. Another chews the grass in the Dog's Yard (where nary a dog is to be found). Under the statues of Shuvalov's Way, a large, grumpy fellow nestled behind a drainpipe hisses at this reporter for getting too close while nearby a small black and white cat guards a northern gate.
Many of the green service entrances feature smaller cat doors so they can go between the gardens and basement at will. The space under the Hermitage is best known to house vaults that contain many times the number of artifacts on display on the floors above. But tucked away in one corner of the basement is cat headquarters.


text:
2011 Kenworth T660
Gulfport, MS
2016 Freightliner BUSINESS CLASS M2 106
Somerville, NJ
2013 Chevrolet 3500HD
New Hampton, IA
2013 Dodge RAM 3500
Jacksonville, FL
2007 International 9400i
Lake Butler, FL
2009 Freightliner CST120
Des Moines , IA
Trailer for 2016 Dorsey 60 Ton Steel Drop Decks
Voorhees, NJ
2011 Freightliner CA12564DC - CASCADIA
Healdsburg, CA
2001 Western Star 4964FX
Ocala, FL
2010 International PROSTAR
Tampa, FL
Description: 2007 IHC 9400I, ISX Cummins Engine, Engine Brake, FROF 16210C Transmission,
40K Rears, 3:58 Ratio, 234" Wheelbase, Good Tires and Brakes,
Tire Size 295/75R 22.5, PS/AC/Cruise, 847K Miles.
HAS THERMO KING APU.More Information
Description: NoneMore Information
Didn't find what you were looking for? Click here to request availability from our dealer network.


text:
Privacy and Cookies
Taiwan's civil aviation authority has taken away Far Eastern Air Transport's (FAT) domestic traffic rights but the grounded carrier has retained its international traffic rights for the time being.
A FAT spokeswoman in Taipei says Taiwan's Civil Aeronautics Administration (CAA) has stripped the airline of its domestic traffic rights.
The spokeswoman was responding to news reports in Taiwan quoting from the CAA.
She says even though the CAA has announced its decision to the news media, the airline has yet to receive the decision officially in writing.
The spokeswoman also says the CAA has stopped short of taking away the airline's international traffic rights.
Reports in Taiwan's news media quote the CAA as saying it let FAT retain its international traffic rights for the time being because the airline told the CAA it will receive a cash injection by 15 June.
But the FAT official that ATI, flightglobal.com's sister premium news site, spoke to today was unable to confirm if the airline will in fact receive a cash injection by 15 June and was unaware that the airline had made this claim in its submission to the CAA.
FAT's entire operation has been grounded since 13 May because the airline is in debt and needs an injection of cash.
The current owners are trying to attract new investors to try and revive the business.
FAT was operating domestically as well as internationally to countries such as Cambodia, Japan and South Korea using its fleet of Boeing MD-80 series aircraft and Boeing 757s.
The FAT spokeswoman says the airline has around 15 aircraft but only four that it owns.
Source: flightglobal.com's sister premium news site Air Transport Intelligence news
Aircraft | Aerospace | Aviation | Military | Business aviation | MRO | General aviation | Space | Airports | Engines and propulsion | Flight tests | Accidents and incidents | Flightglobal blogs | E-newsletters |
Flightglobal dashboard | ACAS | MiliCAS | Ascend Fleets | Flightglobal Insight | ICAO | CapStats | Airport charges | Ascend Values | Aviation Exchange | Aircraft Ratings | Helicopter Fleets | Market Commentaries | FlightMaps Analytics | Industry resources
Browse by job role | Career advice | Jobs by email | Jobs search | Recruiter services
Airline Strategy Awards | Air shows | Conferences | Exhibitions | Flightglobal events
… part of Reed Business Information Copyright © 2015


text:
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 68
68 Table 85. P.M. peak-period percent distribution of internal trip origins for entering trips--Country Isles. Percent Internal Trips by Destination Land Use1 Origin Land Use Shopping Centers Gas/ Office Country Indian FF Rest Residential Daycare Subtotal Conv Isles Trace Office -- 6 17 8 6 0 0 0 Shopping Center 2 -- -- -- 25 27 23 0 Gas/Convenience 0 1 5 1 -- 0 0 0 Residential 0 3 3 3 3 3 -- 0 Daycare 0 3 9 4 1 0 2 -- Total Internal 2 13 34 17 36 30 25 0 External 98 87 66 83 64 70 75 100 Total 100 100 100 100 100 100 100 100 1 Calculated to exclude trips within the same land use; totals shown may not equal sums due to rounding. � Of the trips entering the onsite gasoline/convenience stores, Site Composition 36% came from onsite uses--6% from the office, 25% from The Village Commons site has four major development the shopping centers, 3% from residential, and 1% from the areas: the Village Commons Shopping Center, the Brandywine daycare center. Center, various office buildings located throughout the site, � Of the trips that traveled to the onsite, free-standing, fast- and the Pointe multi-family residential community. Total food restaurant, 30% came from onsite uses--27% from commercial square footage in Village Commons was 524,350 the shopping centers and 3% from residential. with 34% retail (179,840 sq ft), 57% office (297,581 sq ft), and � Of the trips entering onsite residential, 25% traveled from 9% health spa. The total number of dwelling units was 317. an onsite origin--23% from the shopping centers and 2% from the daycare. � Of the trips entering the onsite daycare center, 100% trav- Proximity of Commercial Competition eled from outside Country Isles. There were numerous office, restaurant, hotel, and retail land uses (including a regional mall) that were proximate to Village Commons the Village Commons site. The Village Commons site is located within the southwest- ern limits of the City of West Palm Beach in Palm Beach Site Components County. The overall mixed-use site straddles Village Boulevard, The descriptions that follow are grouped according to immediately northwest of Palm Beach Lakes Boulevard. The how land uses are aggregated for the data collection and Village Commons mixed-use site encompasses approximately data analysis. 72 acres, of which 54 are commercial and 18 are residential. Fig- ure 14 shows the general layout of Village Commons. Figure 15 Village Commons Shopping Center. The Village Com- shows the types and locations of tenant land uses. mons Shopping Center included the following: Village Commons was surveyed on July 14, 1993. Origin- destination surveys were conducted at 14 different locations � A supermarket and drug store; within the site. There was no charge for parking anywhere � Eight restaurants ranging from natural foods to Japanese within the site. Additionally, based on field observations, to bagels; there was an adequate parking supply to service all land uses, � Retail stores including computers, clothing, video, fram- with the possible exception of the health spa. There was no ing, gifts, shoes, cards, jewelry, maternity, sporting goods, formal fixed-route transit service provided to the Village consignment, ice cream, paint, cell phones, liquor, and Commons site. flowers; and
OCR for page 68
69 Source: FDOT Trip Characteristics Study of Multi-Use Developments, Tindale-Oliver & Associates, final report, December 1993, p. II-11 Figure 14. Village Commons site layout as depicted in the FDOT report (18).
OCR for page 68
70 Source: FDOT Trip Characteristics Study of Multi-Use Developments, Tindale-Oliver & Associates, final report, December 1993, p. II-14 Figure 15. Village Commons tenant details as depicted in the FDOT report (18).
OCR for page 68
71 � Service establishments such as banks, mail shipping, dry totaled 32,917 sq ft (of which 18% was in a bank). It was cleaning, a leasing office, a weight clinic, a hair salon, a located approximately 800 ft from the Village Commons tanning salon, real estate, a travel agency, an animal clinic, Shopping Center. Persons leaving this office building were insurance, and a mortgage company. not interviewed. The shopping center was 170,740 gross sq ft in size. Its The Pointe. The Pointe development is a residential multi- largest tenant was a supermarket encompassing 23% of the family development containing 317 units. Its occupancy was overall center space. There were a significant number of restau- estimated to be approximately 93% on the survey date. The rants in the shopping center, composing 19% of the center FDOT research project was not allowed to conduct origin- space. Banks composed 6% and office space composed 4%. destination surveys at the Pointe. Village Commons residen- Despite being a large component of the overall shopping cen- tial internal trips were estimated using Village Commons ter, restaurants were not separated in the data analysis because vehicle count data and average residential internal trip rates the pedestrian count data did not separate between restaurant observed at the other two sites. The approximate center of the and non-restaurant volumes, thereby eliminating the possibil- Pointe is located 900 ft from the supermarket at Village Com- ity of developing reasonably accurate survey expansion factors mons Shopping Center. for restaurant and non-restaurant trips. Health Spa. There is a health spa located in the area Brandywine Center: Sit-Down Restaurant. The Brandy- bounded by Village Boulevard and Olympic Place. It encom- wine Center contained four buildings: a sit-down chain res- passes 46,929 sq ft. An origin-destination survey was not taurant, a bank, and two office buildings. The restaurant in conducted at the health spa, and no trips to the health spa Brandywine Center was 9,100 gross sq ft. The bank and office were identified during the surveys conducted at other uses buildings are included in the next section. at the Village Commons site. Office Buildings. Village Commons had a total of nearly 300,000 sq ft in office buildings. The two three-story office Data Collection buildings in Brandywine Center totaled 122,870 sq ft (of which 4% was in a bank) and were located approximately 1,500 ft Origin-destination interviews were conducted at 14 sta- from the Village Commons Shopping Center. Although side- tions throughout Village Commons. Different expansion fac- walks and crosswalks were available for pedestrian use, the tors were developed for each site (i.e., residential, office, and fact that Village Boulevard was a four-lane divided roadway commercial land use categories) based on pedestrian counts, possibly would discourage pedestrian movement between vehicle counts, and vehicle-occupancy counts. Table 86 lists the Brandywine and Village Commons centers. An office the numbers of useable surveys collected at each land use. building was located at the northeast corner of Harvard Circle, approximately 1,800 ft from the Village Commons Analysis of Internal Capture Shopping Center. It totaled 96,270 sq ft. The three office buildings located along Columbia Drive totaled 45,524 sq ft Table 87 summarizes the overall internal capture found at and were approximately 1,800 ft from the Village Commons the individual Country Isles land uses. In order to more fully Shopping Center. A multi-story office/bank building located understand these overall internal capture rates for each land at the southeast corner of Brandywine Road and Village use, it was necessary to investigate internal capture rates for Boulevard bounded by Columbia Drive and Olympic Place pairs of land uses. Those data follow. Table 86. P.M. peak-period usable surveys and sample rate-- Village Commons. Land Use Exit Movements Usable Interviews Percent Interviewed Office 718 78 11% Retail 1,216 253 21% Sit-Down Restaurant 167 27 16% Residential 179 Not Interviewed Not Interviewed Total 2280 358 16%


text:
There was a time when Southwestern Seminary in Fort Worth was busting at the seams trying to accommodate all the men and women who wanted to earn a degree in theology. The school had more than 5,000 students a year in the 1980's.
That was before Fundamentalists consolidated their power at the school and replaced Russell Dilday as president. Now Southwestern Seminary is a mere shadow of what it was when moderates ran the institution.
As enrollments slipped and funding was tied to the number of students enrolled, the school devised a number of "creative" schemes to keep dollars flowing to the school from denominational headquarters. For more than a decade the school has been reporting "Full Time Equivalents" (FTE's) for enrollment figures. FTE's have been described to me as "anything that walks across the campus in the course of a year."
Now,as the Dallas Morning News reports, the school is resorting to teaching homemaking, cooking, and sewing classes for their idea of model minister's wives.
If I still considered myself a Southern Baptist, I would be embarrassed.
Judging from the continued decline in interest in theological study at their seminaries, it looks like a lot of people within their fold are less than enthusiastic about swallowing the pablum they are now serving.


text:
Win a Papa Roach Bar-B-Q!
Would you want a roach handling your burgers and dogs? We got the raid! Q103 presents the Raid The Nation Tour starring Papa Roach, Pop Evil and Escape The Fate at Northern Lights May 24th. Win your chance to go stuff yourself at a BBQ before the show with Papa Roach.