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A system and method for determining the classification of a signal, or the identification of an object is provided. Based on rough set theory, or data mining, a training data set is partitioned and labeled with a multi-class entropy method. Reducts are calculated from a subset of the best-performing columns of the partitioned and labeled training set data. These reducts are applied to test signals and combined for each signal classification. The present system and method produces a more accurate, robust and efficient classification result.
1. A system for determining the classification of an unclassified signal comprising:
a computer system having a processor;
an input for receiving one or more unclassified signals having one or more attributes;
a plurality of training signals associated with one or more known classifications, wherein each of the training signals has a plurality of training signal attributes;
the computer system further comprising a first reduct calculator for calculating one or more reducts that include the minimum number of training signal attributes that are required to correctly classify the plurality training signals;
the computer system further comprising a classifier for classifying a plurality of unclassified signals as a function of the one or more reducts and one or more attributes of the unclassified signals;
the computer system further comprising a marginal reduct identifier for determining if one or more reducts provided one or more marginal classifications;
the computer system further comprising a reduct classification fuser for combining one or more marginal reducts if identified by the marginal reduct identifier to determine a final classification; and
an output for providing an output indicative of the final classification of one or more of the plurality of unclassified signals.
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17. A method of determining to what classification a signal belongs, the method comprising the steps of:
providing a subset of training signals and a plurality of reducts, determining the classification to which a signal belongs by the steps of:
providing a training information set in the form of a table of data, the table having a plurality of columns and rows, wherein each column of the table represents an attribute of the classification and wherein each row of the table is a training signal and represents attributes associated with a specific classification;
partitioning the training signals;
wavelet transforming signals in each of the training signal partitions and appending wavelet coefficients as additional signal values;
labeling signals resulting from the wavelet transforming step;
selecting a subset of the plurality of columns by removing duplicate and ambiguous signals;
calculating the plurality of reducts;
providing a set of test signals in the form of a table with a plurality of columns of attributes and rows of test signals;
determining a classification of each test signal of the plurality of test signals using the classification system; and
providing an output indicative of a classification of one or more test signals of the plurality of test signals.
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This is a divisional continuation of U.S. patent application Ser. No. 10/362,004, filed Feb. 19, 2003, now U.S. Pat. No. 7,035,754 for SYSTEM AND METHOD FOR IDENTIFYING AN OBJECT, which is a U.S. national stage (35 U.S.C. § 371(c)) application from PCT Pat. App. No. PCT/US01/22852 filed Jul. 20, 2001, for SYSTEM AND METHOD FOR IDENTIFYING AN OBJECT, which claims the benefit of U.S. provisional patent application Ser. No. 60/220,768 filed on Jul. 21, 2000 for OBJECT IDENTIFICATION SYSTEM, the entire disclosures of which are fully incorporated herein by reference.
The invention relates generally to a new organization of knowledge discovery in the information system described by a rough set theory. It provides a method and system for interpreting data and transforming it into useful information. The invention finds particular application to an information system and a method for solving or identifying pattern recognition problems, such as speech recognition, character recognition and fingerprint recognition. The system and method are also applicable to data mining and knowledge discovery in any data base where knowledge is described by a discrete set of features, such as radar signature data, data from non-destructive inspection techniques used in industrial quality control operations, medical test data, the stock market as represented by indices such as the Dow Jones Index and other financial parameters, among numerous other possible uses.
Different techniques have been used in the past to extract useful information from a data set. In a data set or information system that can be represented as a table, with rows representing objects or signals associated with a specific class, and columns representing attributes of the objects, a number of methods have been used to identify or classify those objects in the past.
For example, High Range Resolution (HRR) radar imaging data, that can be used for an Automatic Target Recognition (ATR) system for military aircraft, can be represented as a table of data having rows representing signals with columns representing range bins (this example will be further discussed and described below). In the past, one of the most frequently chosen techniques to classify these HRR signatures (or identify the target aircraft represented by these HRR signals) has been to use a constrained quadratic classifier. This classifier is based on computing the mean and variance estimation for each range bin, or column entry, in the signal. A variant of this technique is to use the mean square error instead of the variance term.
This approach works best when there is a small class of targets to be identified, or classified—such as five or ten targets. In addition, this approach does very poorly at rejecting or not declaring on unknown targets. Further, it is not robust due to the fact that it tries to match range bins (column entries) in the signal which contain little or no information about the target. Typically, these range bins are at the beginning or at the end of the signal.
It has become apparent that there was room for significant improvement in the area of statistical pattern recognition. Applying emerging machine intelligence and data mining techniques to overcome the errors with estimations and assumptions in current statistical classifiers is highly desirable.
Rough set theory is an approach to data mining that has been around since the early 1980's. It was believed this theory had the potential to produce a more robust classifier. Rough Set Theory assumes that the training data set is all that is known and all that needs to be known to do the classification problem. Techniques to find the minimal set of attributes (columns, or range bins for the HRR problem example) to do the classification are available in the theory. Further, the theory should be robust since it will find all the classifiers.
A workable, robust classifier using machine learning and data mining techniques is needed. Specifically, the approach should determine which features, or attributes (columns) are important; generate a multiplicity of classifiers; be robust; and be computationally appropriate for real world problem solving.
Once the data is labeled, Rough Set Theory guarantees that all possible classifiers using that training data set will be found. There is no equivalent statement using statistical pattern recognition techniques that can be made. However, in the known Rough Set Theory method, generating all the classifiers is an NP-hard (non-polynomial time complexity) problem. In summary, all known methods are either subject to error, are computationally inefficient and therefore inappropriate for large problem sets, or both.
The present invention overcomes the above-described problems and others. It provides a computationally efficient, robust classification system and method that can be used on a wide variety of pattern recognition problems and for other types of data mining tasks.
According to one embodiment of the present invention, a system for identifying an object represented by a signal is provided. The system includes a computer system, training and testing information data sets, a labeler, a reduct classifier and a reduct classification fuser. The data sets are in tabular form with multiple rows and columns of data. Each row represents a signal—one or more known signals, or objects, in the training data set, and one or more signals, or objects, to be identified or classified in the testing data set. The system provides more accurate solutions for the object classification problem by use of the reduct classification fuser, as will become apparent from a reading of the detailed description and figures that follow.
According to another aspect of the invention, a partitioner and a column selector are provided which enable larger, problems (which would be computationally intractable with current methods) to be solved quickly, even with standard, commercially-available, personal computers.
In accordance with a more limited aspect of the present invention, the system includes normalization logic to reduce the effects of scale between and within a signal. Furthermore, depending on the data being identified or classified, a wavelet transformer may be provided to wavelet transform each signal in a partition using a multi-level wavelet transform. The wavelet coefficients become additional signal attributes that are appended to the end of the signals thereby creating more columns of data for each row.
According to another embodiment of the present invention, a system for classifying a signal is provided. The system includes a computer system, a training and a testing data set and a reduct classification fuser. The reduct classification fuser combines otherwise marginal reducts to gain a better result for the signals classified. The data sets are presented in tabular form with each data set having a plurality of rows and columns of data. Each of the rows represents a signal.
As in the first embodiment, the system can also include a core calculator, a labeler, normalization logic, a partitioner and a wavelet transformer. The labeler can include fuzz factor logic (used on the test or actual data to be classified) that will be further described below.
A method of determining what classification a signal belongs to is also provided by the present invention. The method includes the steps of: providing a training information set; binary labeling the signals of the training information set; selecting a subset of the columns of the training information set that were binary labeled; calculating the reducts; determining the classification of the test signals using the reducts calculated for the training information set; and determining a final classification of each of the testing signals by combining, or fusing, the separate reduct classifications for each of the test signals. As will be explained in more detail below, this method of signal classification provides a better, more efficient and robust result than known Rough Set Theory methods or statistical methods.
In accordance with another aspect of the invention, a method step for partitioning the training information set into a plurality of partitions of columns is provided. This allows for more computationally efficient problem solving.
In accordance with a more limited aspect of the present invention, the method can include the step of binary labeling each of the test signals which may include the substep of using fuzz factor logic to screen columns from the classification where the labeling may be in doubt due to round-off error, noise, or other effects.
One advantage of the present invention is that the systems and method can automatically solve pattern recognition problems with high dimensional data sets by reducing computational cost.
Another advantage of the present invention is that the systems and method provide better accuracy of the classification solutions.
Yet another advantage of the present invention is that the systems and method are directly transferable to real time computing hardware structures, although a particular hardware organization is not a subject of this invention.
Still further advantages of the present invention will become apparent to those of ordinary skill in the art upon reading and understanding the following detailed description of the preferred embodiments.
In the accompanying drawings which are incorporated in and constitute a part of the specification, embodiments of the invention are illustrated, which, together with a general description of the invention given above, and the detailed description given below, serve to example the principles of this invention.
The following includes definitions of exemplary terms used throughout the disclosure. Both singular and plural forms of all terms fall within each meaning:
"Software", as used herein, includes but is not limited to one or more computer executable instructions, routines, algorithms, functions, modules or programs including separate applications or from dynamically linked libraries for performing functions as described herein. Software may also be implemented in various forms such as a servlet, applet, stand-alone, plug-in or other type of application.
"Logic", as used herein, includes but is not limited to hardware, software and/or combinations of both to perform one or more functions.
"Network", as used herein, includes but is not limited to the internet, intranets, Wide Area Networks (WANs), Local Area Networks (LANs), and transducer links such as those using Modulator-Demodulators (modems). "Internet", as used herein, includes a wide area data communications network, typically accessible by any user having appropriate software. "Intranet", as used herein, includes a data communications network similar to an Internet but typically having access restricted to a specific group of individuals, organizations, or computers.
"Object", as used herein, includes any item to be determined in a pattern recognition task. It is synonymous with a "signal" to be classified, or identified. The object may be a target, from radar imaging data, or any other item that can be represented as a one-dimensional signal for a recognition task to be solved. Fingerprint recognition, voiceprints, sonar data, etc., are all possible uses for the inventive method and systems described and claimed herein. Any object that can be readily represented as a one-dimensional signal, or be mathematically approximated by one or more one-dimensional signals, is a candidate problem that can be solved with the systems and method described and claimed herein based on rough set theory.
The invention presents a new organization of knowledge discovery in the information system described by a rough set theory and therefore is applicable to a number of pattern recognition problems like speech recognition, character recognition, and fingerprint recognition. It is also applicable to data mining and knowledge discovery in data bases where knowledge is described by a discrete set of features.
The determination of classifiers using rough set theory is a difficult problem whose computational expense increases exponentially with the number of attributes. The invention describes a partitioning method which improves computational efficiency for rough set analysis. As a result of partitioning, a set of classifiers is created. A method of fusing the individual classifiers is developed. The fused classifier outperforms any of the individual classifiers.
Thus, the invention has two distinctive features—(1) it provides means to solve pattern recognition problems with high dimensional data sets by reducing computational cost; and (2) it provides better accuracy of the solution. The method is directly transferable to a real time computing hardware structure, although a particular hardware organization is not a subject of this invention.
The inventive method and systems was driven by a need to create an efficient hardware realization for a target recognition system, as will be further described below, but again we stress that is but one example of the use of the inventive systems and method described herein. In summary, existing statistical methods suffer from a lot of problems when used for high dimensional data sets. This invention uses a local group of features for the object recognition task, that otherwise may be easily overlooked when statistical characterization of the recognition task takes place in the entire set of features. The invention described further below uses the idea of marginal classifiers and fusing them to achieve a more accurate result. In an example of the inventive systems and method that will be further described herein, the MATLAB® program was used for rough set generation and a High Range Resolution radar data set for a target recognition problem was solved.
This invention performs a function known as data mining. Data mining uses a set of information (training data set, or training information set) that is assumed to be all that is known. The information is organized as a table or array. Each column of the tale is an attribute (something known about the item to be classified) and the rows represent all the attributes that are associated with a given object or class and are called signals. Each signal in the training set must have a correct classification associated with it. This invention will determine the sub-set of attributes that are capable of determining which class a signal belongs to. In other words, the information has been reduced without giving up the classification ability. This process is automatic and requires no human intervention or intuition. This invention is applicable to any sort of classification problem (especially to any 1-D type of signal such as high range resolution radar) where the problem can be represented as a table of attributes.
The invention can be implemented on a general-purpose computer system, such as 100 in
In the past, in order to determine the reduced sets of attributes in accordance with rough set theory, all combinations of attributes had to be tried. This process grew exponentially with the number of attributes according to the following formula:
Illustrated in
A training information data set 105 and a testing information data set 105 are provided. The training and testing information data sets 105 are presented to the computer system 100 as an array, or table. The values in a row are associated with each other and are called a signal. The values in each column of a signal can come from any source as long as the values are related to the classification of that signal. These column values are attributes of the signals.
For training and testing purposes, the correct classification of the training information data set's 105 signals must be provided. When the system is in use, a test signal is provided from the testing information data set 105 and the computer system 100 provides the classification if possible.
The computer system 100 can use normalization logic 110 to normalize each signal in the training information data set 105, thereby reducing the effects of scale between and within a signal. The normalization process used is of course dependent on the particular application, as will be appreciated by one of skill in the art. For HRR radar signature data, where the signals values can be integers in the range of 0 to 255 a 2-Norm can be used. The 2-Norm is defined as:
In order to handle large data sets and to obtain the best results, the training information data set or training data 105 can be partitioned. A partitioner 115 is provided for this function and there are at least two types of partitions that can be used, block and interleave.
Referring now to
Referring now to
A wavelet transformer 120 can be provided for use by the computer system 100. For each partition (see
As an example of partitioned data being wavelet transformed via a computer system 100 using a wavelet transformer 120 with the appropriate logic for a Haar wavelet transform, HRR signals having 128 range bins, or columns, become signals with 1,024 pseudo range bins. A signal with 64 range bins (2 partitions) becomes a signal with 448 pseudo range bins. The signals with 32 range bins (4 partitions) become signals with 192 pseudo range bins. And finally, signals divided into eight partitions and thus having 16 range bins, become signals with 80 pseudo range bins.
For a rough set analysis, the signals, now supplemented by the wavelet coefficient, must be labeled. An analogy to fuzzy sets using a picture would be that fuzzy sets are concerned with how gray the pixels are whereas rough sets are concerned with how large the pixels are. Computer system 100 includes a labeler 125 for this purpose. Labeler 125 has a logic that uses a multi-class entropy method. Each column of the training set of signals is searched sequentially to establish the optimum point (threshold) which best separates signals of the various training classes. The quality of partition is measured by the entropy based information index defined as follows:
An example of labeling of the training signals is shown in
An example of the labeled HRR data of
A column selector 130 is used by the computer system 100 to select a subset of the best columns. For example, in our HRR example, we would typically desire the 50 best columns, meaning the columns that have the highest information index, to be selected. These are the columns that should do the best job of classifying the signals or identifying the targets. The number 50 was chosen as this is the largest practical size that can be computed on 400 MHz processor with 256 MB of memory. Faster computers with larger memories would permit a much larger number of columns to be considered for real time analysis.
Next, computer system 100 includes duplicate and ambiguous signal removal logic 135 to remove duplicate and ambiguous signals. This applies only to training information data set 105. Duplicate signals are defined as signals that are identical and are from the same classification. Ambiguous signals are signals which are identical and from different classifications.
Computer system 100 next uses a core calculator 140 for calculating the core, as will be further described below. The set of training signals is sometimes referred to as an information system composed of attributes (columns) and a decision attribute (a column which contains the correct classification of the signal or row). After labeling, if it is possible to properly classify all signals using a sub-set of the attributes, that sub-set of attributes is called a reduct (a reduction in the size of the information system without losing any information; the ability to classify all the signals). It should be noted that there may be many reducts for a given information system. The attributes that are common to all reducts are known as the core. The core is determined by removing one column at a time. After the column is removed, the training set is examined to determine if there are any ambiguous signals. If there are, that means that that column (or attribute) is the only column of values that can distinguish the ambiguous signals. It must therefore be part of the core. For example,
Computer system 100 then uses a reduct calculator 145 calculating the reducts. Starting with the core, columns are added one at a time and the signal comprised of only those columns is examined to determine how many ambiguous signals there are. The set of all columns with the minimum number of ambiguous signals is set aside. If there is only one column with the minimum number of ambiguities that column is added to the core set of columns. The process repeats with the remaining columns. When the number of ambiguities becomes zero, that set of columns comprise a reduct. We now go back and replace the columns where there were several columns with the same number of minimum ambiguities and continue the process to determine the other reducts. Reduct determination is also done in known rough set theory.
Once all the reducts are calculated for the partitioned and reduced training information data set 105, computer system 100 can be used to test the performance of the full set of training signals in the training information data set 105. The full training set including duplicate and ambiguous signals is tested to determine performance of each reduct. Obviously there will be some misclassifications due to ambiguous signals. The reduced set of training signals (without duplicates and ambiguities), the reducts, and the performance of each reduct on the full training set is saved. This comprises the classification system. When classifying, a reduct specifies which columns of a signal are to be used for classification. These columns are selected from the training set 105. If a match is found then the signal is assigned the class of the training signal it matches. If no match is found the signal is marked as unclassified. In the training and test sets 105, where the correct answer is known, the performance of a reduct (a value called the probability of correct classification, Pcc) can be calculated from a confusion matrix. A confusion matrix C is constructed as follows. For each known signal, if the signal is known to be of class a and the reduct classifies it as class a then Caa is incremented by one. If the reduct classifies the signal as class b then Cab is incremented by one. Pcc is then computed as:
The test signals may also be normalized, such as with normalization logic 110, and wavelet transformed, such as with a wavelet transformer 120, by computer system 100 as already described above for the training signals of the training information data set 105.
The labeling of the test signals 105 is slightly different than for the training set 105. The computer system 100 uses a labeler 125 as well as fuzz factor logic 126 to label the test signals of the test data set 105. Each column of the training set had a threshold value determined by information index. The training threshold is used for labeling the test set. However, if the signal value in the test set falls too close to the threshold value it is given a label associated with "don't care". This means that this value will not be used in the classification processing of that signal. This "don't care" region is established by the user with a 'fuzz factor'. If the minimum value of a column from the training set is called ymin, the maximum value called ymax, the threshold value called yt, and the fuzz factor called f then the don't care distance δ is defined as:
The last step in the classification, or object identification, performed by computer system 100 is to use a novel Reduct Classification Fuser 150 having logic to fuse or combine what may be some otherwise marginal reducts. By this system and method, the combination of the marginal reducts, as well as some strong ones, results in an improved result for the final classification of each signal or object in the test data set 105. Each test signal is evaluated using every reduct to determine classification. All of these classifications are combined, based on the reduct's performance on the training set, to yield the final classification. The formula for combining the various results is:
Illustrated in
The methodology of
The method steps represented in
Training signals 205 are provided in the form of a table or an array, similar to the training information data set 105 in
The training signals may then be normalized as is shown in block 210 labeled "normalize signals." This method step may be done in accordance with the normalization logic 110 described above for the
The method step for partitioning the signals of the training signals 205 into a plurality of partitions of columns may be performed in accordance with the process block 215, labeled "partition signals." Of course, the number and type of partitioning scheme, such as block or interleave, described above (and see
The method may also include the step of wavelet transforming each of the signals in each of the partitions. This is illustrated in the
The method step of binary labeling the signals is illustrated in block 225. Binary labeling may be accomplished with the multi-class entropy method as described above for labeler 125 (
Next, the method includes the step of removing the duplicate and ambiguous signals from the training signals or training information set. This step is depicted in block 235 of
The step of calculating the core is represented at 240. This was thoroughly described above with reference to core calculator 140 in
Calculating each of the reducts is illustrated at 245 in
Once the reducts are calculated on the training signals of the partitions, as described hereinabove, the full training set of signals 205 is tested to determine the performance of each reduct. Stated another way, method step 205 involves performing the classification of each signal in the training signals 205, or training information set, by using each of the reducts. This, too, was described further above. The reduced set of training signals, the reducts, and the performance of each reduct on the full set of training signals 205 can be saved, such as by block 250 in
Next, a set of test signals are provided as at step 305. They may similarly take the form of a table or array with a plurality of columns of attributes and rows of test signals. These test signals can be normalized and wavelet transformed, such as via method steps indicated in
The test signals 305 may be binary labeled, as at process block 325. The binary labeling of the test signals is slightly different than that for the training signals, and may use fuzz factor logic to identify a "don't care" region for some column values that lie close to the labeling point and thus may lead to erroneous labeling due to noise, round off error, or other factor. This was described more fully above with reference to
Now, for each of the reducts, represented at 3MSS, the inventive method includes the step of determining a separate reduct classification for each of the test signals using each of the reducts 355. This is represented at process step 360 in
The final classification results can be outputted, as at 370, and the method finished as at end 375.
With the present invention, an object or signal from a set of test data full of unknown signals can be identified, or classified, based on information extracted from a known set of training data. Although not unlike Rough Set Theory, or data mining techniques, in this regard, the present inventive systems and method have a number of highly desirable features that permit real time use on high dimensional data sets. Accuracy of the solution is substantially strengthened—not sacrificed. The invention has wide ranging applicability to all types of classification problems—not just the HRR example for aircraft ATR systems. The inventive systems and method will automatically solve the recognition, classification or identification problems. The concept of multi-class entropy labeling to find the best labeling point in the data has been shown. The concept of using two data partitioning schemes (block and interleave) to reduce the computational time and improve classification accuracy was also described and illustrated. This also makes the methodology and system less sensitive to noise in the data and makes the system less sensitive to registration of the data. The method used to compute the minimal reducts in a reasonable time (quadratic instead of exponential time complexity) allows larger (real world) problems to be solved. The method used to fuse the results vastly increases the accuracy of the system. The method of fuzzifying the test data when values are close to the dividing point makes the system less sensitive to noise.
While the present invention has been illustrated by the description of embodiments thereof, and while the embodiments have been described in considerable detail, it is not the intention of the applicants to restrict or in any way limit the scope of the appended claims to such detail. Additional advantages and modifications will readily appear to those skilled in the art. The invention, in its broader aspects, is not limited to the specific details, the representative apparatus, and illustrative examples shown and described. Accordingly, departures may be made from such details without departing from the spirit or scope of the applicant's general inventive concept.
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Triple 5 Soul - (LFL-3897) VOLTAGE OUTER PARKA
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subset: commoncrawl


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Tag Archives: Compromise
NEWS FLASH: Lindsey Graham is a "top conservative"!
Jonathan Karl, Richard Coolidge, Gregory Lemos and Sherisse Pham, part of the collective, useful spokes-tools employed by ABC News and the "progressive" Party Pravda's online misinformation outlet known as Yahoo News are at it again.
To begin with, this "progressive" misinformation's "headline" is pure, pre-fabricated nonsense that reads:
"Top conservative says read my lips: Don't sign 'no new tax' pledge".
This "headline" is garbage.
First of all, save for his consistently patriotic support for the United States military and for American troops, Senator Lindsey Graham is about as moderate as Republicans come. Some Conservatives might characterize him as a "progressive" Republican. Even more may openly label him a RINO. The thought of his being a "top conservative" comes from the minds of institutionalized "progressive" leftists, not reality. Secondly, not once in the interview does Graham ever utter the words "read my lips". Again, readers are witnessing fabricated "progressive" wishful fiction, not fact. Furthermore, never did he say "don't sign the 'no new tax' pledge. Not even once. Not ever.
The entire headline is a total lie. It's a complete falsehood. The "news" presented in this "headline" is "progressive" fabrication that goes light years beyond the outer limits of "spin".
Thanks to a "headline" that's contains not one ounce of truth, the article is automatically discredited in the minds of informed voters, those who are obviously not the target audience of Karl, Coolidge, Lemos and Pham.
What Graham did say is that he is willing to be flexible on applying one fourth of revenue collected by the IRS through elimination of tax loopholes and subsidies towards reducing the nations nearly $16 trillion in debt. The other three fourths would continue to follow the No New Tax Pledge's formula for applying such revenues solely towards tax cuts. For Graham to accept this compromise, Democrats would be required to respond in kind to work in a bipartisan fashion towards reducing the national debt via "entitlement" program reforms.
That such inaccurate "reporting" could be considered, even for a fleeting moment, as real journalism, that these liars are actually getting paid to propagandize pure fiction as fact shows how low are today's standards for journalistic integrity. This "headline" is going to give a large number of low-information, "sound bite news voters" a completely incorrect image of reality. It's not even close to being true. All visible evidence points to clear intent to mislead misinform and indoctrinate masses of online readers.
How about giving this story a more objective headline, a headline that reflects the truth while accurately respects the content of the story? One more like: Graham Willing to Discuss Tax, Entitlement Compromise.
How difficult was that?
Perhaps for self imagined, self-appointed members of the "progressive" intellectual elite, it's just too simple for their brilliant minds.
A Difference of Definition
Have you noticed the difference in the definitions used by Washington D.C. and those that are found in the dictionary?
[kom-pruh-mahyz] Show IPA noun,verb, -mised, -mis·ing.
a settlement of differences by mutual concessions; anagreement reached by adjustment of conflicting or opposingclaims, principles, etc., by reciprocal modification of demands.
From this viewpoint, there are two different definitions coming out of D.C. Let's take a look at these two definitions.
Compromise according to Republicans– To hold out until the last minute then buckle to the wants and demands of the Democrat Party; To lose the spine you once spoke of on the campaign trail when you promised to fight for America.
Compromise according to Democrats– The act of waiting long enough on issues that the Republicans give in to your demands and holding daily news conferences demonizing Republicans.
We have seen multiple examples of these definitions play out over the past year or so. A couple such examples are the federal shutdown can they continue to kick down the road little by little, and the recent payroll tax extension. The Republican Party has played right into the hands of the Democrat Party each time and let the liberals hold our nation hostage. They've allowed the Democrats to threaten the American people with suspension of the Medicare benefits for the elderly, increased taxes and even the suspension of pay for our fighting men and women, all while the pay of Congress was insured.
The "compromise" the Republicans have demonstrated on such issues has been nothing but embarrassing to Conservative Republicans of this great nation. With their actions, they have proven they too must be voted out and replaced with someone that is willing to stand up and fight for what is right. Their constituents hired them to do a job and they are not performing up to standards.
The time is pass due for We the American People to hand everybody in Congress and the President their pink slips and send them packing. Our nation fought the Revolutionary War to end tyranny and to free the people of this great nation. The first Revolution our patriots fought with guns, swords and cannons. Today's revolution will be fought with votes at the ballot box. As the old saying goes:
" The pen is mightier than the sword."
We must make our mark in history with our pens in November 2012. We patriots do not have an official war cry, but for now, "Remember the Constitution" sounds quite fitting!
For those of you that own firearms, train hard and well and teach those that do not know how.
Be good stewards of the right to bear arms, for we are the last line of defense against tyranny.
-Benjamin Wallace
Advice From Newt Gingrich
Back in the mid-1980s I had the opportunity to spend a brief amount of time with Speaker Newt Gingrich.
He offered some fascinating advice to those of us present (A group of only fifteen people nationwide that were training to become congressional campaign managers). He said in essences "The responsibility of a Congressman is not to explain Washington to the voters, but rather to represent the voters to Washington DC."
The implications of that comment are very insightful when thought about. It demonstrates why Newt Gingrich is never really out of the race for president. But that is another story.
I receive, on a regular basis, communications from federally elected officials. I also am friends with some on various social networking sites on the internet. I monitor the Senate and House members that represent the State of Utah, as well as few others.
Senator Orrin Hatch of Utah is on Facebook and frequently makes posts that convey to the conservative wing of the Republican Party (about 65% of the total membership) his relentless efforts to carry the conservative message to Washington. This effort may be intensified by the fact that for years he was more moderate, like Senator Bennett who was unceremoniously ousted by the right wing even before the primary in 2010. Senator Hatch needs to earn back their trust.
To many of the Senator's posts I have responded to him stating that he simply isn't getting what the people are looking for. He is still a regulationalist at heart. That means his answer to every challenge, problem or difficulty is resolved with yet another regulation being imposed.
Before I continue I must make a confession. In my mind Senator Orrin hatch is the most moral man in the US Senate. On a personal level I trust him beyond any other US Senator. In terms of personal character, in my mind, he overshadows all the rest. That means a great deal to me, yet not my vote.
Today on Facebook Senator Hatch, speaking of the Yuan Bill, posted this "Before the Senate moves forward, it's imperative that Congress have a full understanding of the Administration's views on this legislation." At first blush this looks absolutely reasonable. At any level, having a clear understanding of the issues, is a reasonable thing to do. However…
At the second consideration, where wisdom joins with first impressions, this says something quite different. When the President has made it abundantly clear that he has no intention of ever working in a cooperative manner with the Congress I genuinely question the logic of waiting for it to be forthcoming on this issue.
Secondly, what Senator Hatch is doing is subtly proposing is that there is a means to "compromise." Compromise to accomplish part of a goal can sometimes work for the greater good. Unfortunately with Congress, particularly the Senate, compromise has not been to move toward a greater good but rather toward a greater personal satisfaction among individuals dependent upon popularity, to remain popular.
In short, given Senator Hatch's, and the entire senate's reputation, his comment translated for accuracy should read "We need to know where the president is at so we can accommodate his wishes with our future popularity." That sounds harsh, but it appears to be the means by which the senate works.
In the original Constitutional Convention the delegate were firm and pounded home views with force and resolve. Yet, in the end the Constitution was adopted because the compromise was for a better nation, not better poll ratings. Today's Congress should be no less.
I return to the advice of Speaker Gingrich. These men are not sent to Washington to later come home and explain Washington to their voters. They are to represent the people and then be "Statesmen" capable of wise decisions rather than popular assent.
Band Jockeying
Paul Ryan's solution for our debt solution held up only with the Conservative segments of the Republican coalition. Reid's plan only appealed to Democrats and the remaining plans garnered support or disdain from many different factions within Congress, but none of them had the votes to pass.
Now, 11th hour negotiations have been happening in the offices of Congressional leaders and at the White House to find an 11th hour deal that can get the 60 votes needed in the Senate and the 214 votes needed in the house.
With prior plans appealing only to left or right segments of Congress, the current negotiations look to be forming a plan that will focus on creating a large coalition of members of Congress. It will however leave out the far-left and far-right.
By pandering to the middle, Congressional leaders can garner the number of votes that they need without kowtowing to the staunchest factions in their parties. They are actually writing off a portion of their base to achieve the end goal – a debt ceiling deal.
As expected, the Tea Party Conservatives and the Progressive Caucus won't vote for the compromise. As long as they can keep enough of their centrist factions together, a coalition made up of both parties can pass a negotiated deal.
Compromise is a good thing!
Compromise can be a good thing, but let me tell you what I thought yesterday about the happenings on the Hill.
I still wondered why Speaker Boehner, who was on the Sean Hannity show a few days ago, stated, "The Mack Penny Bill was worth looking at" had done absolutely nothing with regard to that bill? Even the media is saying very little about it. Why is that?
Instead of Cut, Cap and Balance or the Mack Penny Bill, Speaker Boehner's bill passed. If compromises were made, then surely the essentials of cut, cap, and balance or even parts of Mack's Penny bill were in the bill – or not.
Like many others, I had just assumed that the compromise would bring parts of all the different legislation into a bill that would garner support. Seeing what actually passed – he sold-out.
I felt bad for Speaker Boehner, and all he is going though. But, isn't that what he is paid to do? Talking with Democrats is a necessary part of creating legislation, but NOT doing what the American people have hired him to do is unacceptable.
Yes, it is hard to take a stand. No one said it would be easy, but deal with it Boehner! This entire issue is about the deficit and more specifically .. spending.
2012 is not that far away, Mr. Speaker – time to get to work!


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Celebrities who are vile in real life?
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01-02-2013, 17:03
Forum Member
Join Date: Jul 2012
Posts: 206
Originally Posted by
Anthony Ainley may have been a lovey but apparently according to the DW Livejournal thread I was on for a bit was well liked by fans whom he treated well - one lady even had a massive crush on him.
Oh yes, I didn't mean to suggest otherwise. I don't use the word "luvvie" pejoratively, but rather as a description of a certain personality-type. I met him a couple of times at conventions and he was always charming. I have friends who knew him quite well from Dr Who fandom, and they speak very affectionately of him. There are some people who say that he had a very miserly streak - always charging for appearances, even at charity events where other actors waived their fees, but I've only heard this from a few sources, some of whom have their own reasons to dislike him.
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It's my birthday again (better to have them then not too), and I still feel the same way. Although, I conveniently can't remember which birthday it is. Shhh, don't tell me, sometimes ignorance is bliss. Enjoy this reprise of some solid advice to keep that youthful spirit! —S.H. It's my birthday today, woot, woot for…Published on May 30, 2015
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Is There An Appropriate Dress Length For An Older Woman
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Our latest reader style question asks what to wear to a wedding after menopausal weight gain. How can she look age appropriate in dressy clothing? What can she wear to hide her slight bump in size? And not look like an old lady? Let's discuss… I am 55 years old. I am 5 ft 8″…Published on June 27, 2013
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Fairytale Flowerpot Dessert
|Fresh pineapple
|1 , cut into 12 round slices
|Seedless grapes
|1⁄2 Cup (8 tbs) (Use Both Red And Green Varieties)
|2 Tablespoon
|2 Tablespoon
|Angel food cake/Pound cake
|1 Pound, cut into 2-inch cubes (Purchased)
|Ice cream/Your favorite frozen confection
|1 Quart (Any Flavor)
|1 Cup (16 tbs)
|Chocolate syrup
|1 Cup (16 tbs)
|2 Tablespoon (Use Assorted)
1. Line 2 cookie sheets with foil or parchment paper and set aside.
2. To make fruit flowers, cut out the center of each pineapple slice with a small melon baller. Cut each slice into a flower shape with a 2- to 3-inch flower-shaped metal cookie cutter. Place a grape, raspberry, or blackberry in the cut-out center of the pineapple flower.
3. Insert a wooden skewer starting at the bottom of the pineapple flower, carefully pushing it through the fruit in the center and through the top portion of the pineapple flower, making sure the skewer is not sticking out the top of the flower. Place the flowers on a cookie sheet in the refrigerator.
4. Place the flowerpots in their saucers and set on the other cookie sheet. Put several cubes of cake into each pot, filling it halfway to the top. Press down on the cake, making sure to cover the hole in the bottom of each pot. Fill each flowerpot with a scoop of ice cream. Drizzle with chocolate syrup and garnish with sprinkles.
5. Insert a straw into the center of the ice cream. Store the flowerpots in the freezer until you are ready to serve.
6. When you are ready to serve, remove the flowerpots from the freezer and the fruit flowers from the refrigerator. Insert a flower into the straw in each flowerpot and serve immediately.
May be stored covered up to 8 hours.
This recipe has been excerpted from Barbara Beery's Pink Princess Party Cookbook. To purchase this book visit, KidsCookingShop.com.


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Big Hook Floating Wall Shelf
The Big Hook shelf is the perfect multi function piece for your bathroom or entryway. The shelf provides horizontal storage space while the big hooks give you a place to hang towels, coats, umbrellas and more.
Mounting hardware and brackets included.
24" w x 6" d x 0.375" h
36" w x 6" d x 0.375" h
Materials & Measurements
Shelf: clear tempered glass
Bracket: brushed chrome
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The 2015 Chill Season Passes and Anytime Passes are available now!
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Central PA Friends of Jazz Presents The Jackie Ryan Trio, Nov 11, 2013
Central PA Friends of Jazz Presents "The Jackie Ryan Trio" on Sunday, November 11, 2013 at 4:00 PM (with a special pre-show appearance of Met4 at 3 PM) at The Ware Center, Millersville University Lancaster, 42 N. Prince St, Lancaster, Penn.
Jazz vocalist Jackie Ryan, who currently lives in San Francisco, has thrilled audiences across the globe with her powerful 3½ octave range and her amazing stage presence. She has a style that is uniquely her own. Born of a Mexican mother who sang in Operettas and an Irish father who sang classical tenor in many languages, she was, as one critic put it, "simply born to sing."
She has sung all over the world from the famous Ronnie Scott's Club in London (where she was asked to record for their label) to Jazz at Lincoln Center and Birdland in NYC, as well as many major jazz festivals.
Jackie Ryan's 2009 CD, Doozy has garnered overwhelmingly positive reviews as well as 4-stars from both DownBeat Magazine and All Music Guide, and held the #1 position nationwide on JazzWeek's industry-standard chart for 7 solid weeks - an extraordinarily rare achievement (only one vocal recording ever matched that: Diana Krall's, "From This Moment On").
Jackie Ryan was a featured artist on NPR, Voice of America, CNN Español, and Primetime A&E.
Ms. Ryan is scheduled to appear at the Ware Center, 42 North Prince Street, Sunday, November 11 at 4 PM. The Trio will be preceded by Meta4, a working jazz quartet consisting of teenagers who play classic tunes by jazz's best artists, such as MiLes Davis and Sonny Rollins, and popular standards. The band's members, all seniors in high school, are John Gingerich (bass), Ted Groth (guitar) and Colin Mekeel (alto sax, piano) from Manheim Township, plus Fred Griggs (drums) from Carlisle. All four placed first in this year's District Jazz Band auditions, while Ted and Fred placed first in the 2012 All-State Jazz Ensemble competition.
Tickets are $22 Adult, $18 CPFJ Member, $10 Student. Call 717.872.3811 or 717.871.2308. Buy online at www.muticketsonline.com. Or, in person at the Ware Center, 42 North Prince Street, Lancaster, Penn., Mon-Fri. 9 AM to 4 PM. Advance reservations are strongly encouraged.
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RELATED: State reviewers recommend training for Youngstown school board, staff
Ohio's state superintendent isn't happy with the progress of Youngstown City Schools, and he is asking the community to step forward and help.
"I'm disappointed with the lack of progress," Richard Ross, state superintendent of public instruction, said in a telephone interview Thursday with The Vindicator. "Whether it be the school board, the administration or staff or the academic distress commission, the bottom line is they haven't gotten done what needs to get done."
The Youngstown School District Academic Distress Commission was appointed four years ago after the city school district failed to meet adequate yearly progress for four consecutive years on the state report card.
It was the first district in the state to operate under an ADC. Lorain schools now also has one.
Ross briefly served as chairman of the Youngstown ADC before leaving to work as Gov. John Kasich's director of 21st Century Education. Kasich later appointed Ross state superintendent after the resignation of Stan Heffner.
"The community at large, the faith-based community, the business community has to say, 'Enough. We have to make dramatic change, whether that's open enrollment or community schools, we have to make dramatic improvement,'" he said. "My call to action to the broad community is we need your help. We're asking them to step forward."
He said he has no date in mind.
Connie Hathorn, Youngs-town schools superintendent, said he would support such an effort.
"The schools belong to the community," he said. "As long as what they want is what's best for the kids, I would support it."
Ross called it a "philosophical predisposition" he has that formulas for lasting change are more effective when they come from a community that's bonded together than from a prescription written by another entity.
"I'm not pleased with the progress in Youngstown," he said.
The closest model in the state for the type of action he's talking about is the Cleveland Plan, Ross said.
Although he's said he's not looking for a copy of that city's plan, community groups in that city got together because they weren't happy with what was happening with the schools and made changes.
That city's plan, which required state legislation, involves a system of district and charter schools under the leadership of a chief executive officer and nine school board members who are appointed by the Cleveland mayor. At least four of those members must have expertise in education, finance or business.
The board members hire the CEO.
"The bottom line is this has to be for the boys and girls," Ross said. "There's got to be a change and improvement for the opportunities for these young people. If they're limited by what their opportunities are in education, then shame on us."
If you think the school system is a failure just wait. They'll be even more disappointing once the school year starts.
This goes to show everyone how uneducated and unprofessional are the people that Gov. Kasich has put in charge in Columbus. Everyone in the State except this guy knows what is wrong with all inner city schools. It is the parents and community. Nothing to do with the schools. Struthers and Boardman schools are almost identical to the Youngstown schools in terms of what they teach and how educated and experienced the staff is. The difference in the schools is the kids. The difference in the kids is the parents. Stop waisting everyone's time pretending that the schools can perform miracles. Stop blaming the wrong people for political points. The only inner city program that ever worked was the one in New York City that took the kids away from the parents and community and put them in boarding schools. Then they did as well in school as kids in the suburbs.
Parents need to step up. It's their responsibility to make sure kids arrive at school on time, fed, clean, well rested and ready to start the day. If your kid is failing, especially young kids, you better look in the mirror and ask yourself what your problem is.
The only people left within Youngstown are the lower class. There is no lower-middle or middle or upper class.
The lower class is this way because of lack of education, motivation, or poor health. They cannot lead themselves, they must be pushed or prodded into a better life. The government must step in and fix the problem.
I don't really know where to start to address these comments. Let me just say that it's not "poverty" alone that necessarily affects achievement, rather the risk factors that accompany living in poverty in modern society.
Today's poverty is different in many ways from poverty experienced by previous generations. As is the student population - in previous generations, poor kids often dropped out or never attended school and thus were not included in any assessments of "school quality".
Some links to research you should consider while pondering this topic:
The web-site is nothing more than Teacher Union propaganda. There is nothing wrong with the tests. Until you admit what the problem is, you will never solve it.


text: Idaho Kids Count Report: More Idaho Children Live In Poverty, Education Outcomes Slide By Adam Cotterell • Jul 22, 2014 IlmicrofonoOgglono / Flickr Creative Commons The number of Idaho kids living in poverty has risen to 21 percent, that's a 3 percent increase since 2005. That means at least 87,000 Idaho children were living in poverty in 2012. The poverty statistic is just one of the findings in the annual Kids Count report from the Annie E. Casey Foundation. Little Change In National 12th-Grade Math, Reading Scores By Chris Lehman • May 8, 2014 Listen Listening... / The federal government just released its latest national test scores for high school seniors and it's not good news. A significant number of graduates are below standard for math and reading. Idaho Teacher Pay For Performance: Research Vs. Experience By Adam Cotterell • Nov 5, 2012 idahokidscount.org Tuesday Idahoan's will vote on propositions 1, 2, and 3. Those ask if the state should keep the controversial education laws known as Students Come First. The laws limit collective bargaining rights and seek to increase technology use in schools. One of the laws also creates a pay for performance plan where teachers can earn bonuses. Now that law has drawn criticism from an unexpected source. Stepping Up For Kids By Samantha Wright • May 23, 2012 Samantha Wright / Boise State Public Radio A new report out today says one in every eleven children will spend a portion of their lives without their parents, living instead with a relative. That number is growing both in the U-S and in Idaho. These kids often don't get all the services that are available to them. The study hopes to change that.


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Mar 18, 2014
Bob Buskirk
All News, Gaming News, Hardware News
Corsair, a designer and supplier of high-performance components to the PC hardware market, today announced the Carbide Series SPEC range of gaming PC cases in three models: the SPEC-01, SPEC-02, and SPEC-03. Characterized by aggressive styling, modern features, superior air cooling, and expandability, the SPEC range offers everything gamers need from a case and nothing they don't.
Jul 28, 2013
Bob Buskirk
All News, Hardware News
Rosewill has just released their latest gaming cases the Galaxy Series. These mid towers are designed to be more of budget cases but still offer great features as well as styling. There are three different mid towers, the Galaxy-01, Galaxy-02, and Galaxy-03. While all three cases are very similar they have their own unique design.
Jul 06, 2015
Jul 02, 2015
Jun 30, 2015
Jun 29, 2015
Jun 24, 2015


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With snow peaked mountains and fjords carved by glacial activity, Norway is no place for sniffly, colds-prone vacationers. Besides, it's 3000 miles away. With today's Groupon, you don't have to look very far for a dream destination.
Enjoy an unforgettable day cruising along the Fjords of Musandam on board a traditionally decorated Omani Dhow for 225 AED instead of 450 AED from Afridi Travels and Tourism. Situated on the Northern tip of the Arabian Peninsula, Musandam is replete with irregular mountain peaks rising out of waters and surrounded by wadis. The tour starts from Burjuman Centre in Dubai through the famous green farms and beautiful scenery of Dibba, Fujeirah and the Straits of Hormuz, discovering traditional villages along the way. The tour includes soft drinks and lunch buffet. You can also enjoy a swim, go snorkeling or diving, try your hand at hand line fishing or experience a banana boat ride while the dhow is anchored. If you're lucky, a dolphin will take time out of its busy swimming schedule and welcome you to its turf. Discover the real Arabia with this Groupon.


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HSBC "lift" by Grey London
Agency: Grey London
Rating: 5.0
By John Reynolds, marketingmagazine.co.uk, Tuesday, 19 February 2013 09:24AM
Burger King's first Tweet today following the hijacking was "Interesting day here at BURGER KING, but we're back! Welcome to our new followers. Hope you all stick around."
Yesterday's hackers put up the McDonalds logo and sent out messages for over an hour, before the account was shut down by Twitter.
The hackers told Burger King's 89,000-plus followers that the company had "just got sold to McDonald's because the whopper flopped".
Further posts on the account contained racial slurs, obscenities and references to drug use. No one has admitted to being behind the stunt but the hacking group Anonymous tweeted about the incident extensively.
A Burger King spokesman said: "We apologise to our followers who have been receiving erroneous tweets about other members of our industry and additional inappropriate topics."
Before the hacking, the Burger King Twitter feed had 89,000 followers, which has now grown to over 110,000.
McDonald's posted a message on its own Twitter feed which read: "We empathise with our @BurgerKing counterparts. Rest assured, we had nothing to do with the hacking."
The incident is similar to the messages sent out by a HMV employee after the struggling retailer fell into administration.Follow @johnreynolds10
This article was first published on marketingmagazine.co.uk
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Agency: Grey London
Rating: 5.0


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While the Peugeot 3008 looks like a people carrier, raised suspension and the option to fit four-wheel drive mean it could just as easily be an SUV. Thankfully, Peugeot has made our life easier by designating the car as a crossover – a model that blends the looks of an SUV with the driving characteristics of a normal car. That puts it into direct competition with the excellent new Nissan Qashqai and also head-to-head with models such as the Kia Sportage and Skoda Yeti. To keep it competitive with these rivals, the Peugeot was given a light facelift in 2014, which included a few tweaks to the exterior and the use of higher-quality plastics inside.
A practical interior lies at the heart of the Peugeot 3008, but stick a couple of six-foot adults in the back and they'll soon feel cramped. If that's not a problem, then the Peugeot scores well with a boot that's bigger than a family hatchback's and more versatile, too. Storage space is also on the generous side, with plenty of nooks and crannies to hide away the clutter that goes hand in hand with family life.
Peugeot offers the 3008 with a choice of six engines – four diesels and two petrols – and there's also the option of a diesel-electric hybrid. It's expensive to buy, though, so we'd recommend the basic 1.6-litre diesel. While it's certainly not quick, it can return nearly 70mpg, something that's bound to be a higher priority for most families.
Peugeot offers the car in Access, Active, Allure and limited-edition Crossway trim levels, and all models come with alloy wheels, air-conditioning, Peugeot's functional Multiflex interior, as well as front and rear electric windows. We'd be inclined to splash out on the Allure mode. It gets desirable features including front parking sensors and a rear-view camera (handy on a big car like this), a sat-nav system, climate control and a panoramic glass sunroof. Last but not least is the head-up display, which can project vital information (such as your current speed) onto the windscreen, allowing you to keep your eyes on the road.


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Jamaica Inn (original 1936; edition 2008)
by Daphne Du Maurier
Work details
Jamaica Inn by Daphne du Maurier (1936)
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A fun book for adults or teens. Although I never got to the actual Inn, I read the book while hiking through Cornwall on the Coast Path. Twas easy to see how smuggling became so big w/ a coast like the Cornish coast! Read April 2015
On a bitter November evening, young Mary Yellen journeys to the windswept Cornish coast to stay at the foreboding Jamaica Inn. She arrives at her aunt and uncle's inn to fulfill her mother's dying wish. Although the coachman tries to warn her to stay away from the ramshackled, ruined place, Mary chooses to stay and honor her late mother's final request.
So, Mary will join her relatives - her frightened Aunt Patience and her imposing Uncle Joss Merlyn - and do her best to ignore the various rumors swirling about the place. With the coachman's dire warning still echoing in her ears, Mary will witness her Aunt Patience cowering in fear before her dour Uncle Joss. Terrified by the inn's looming shadow and its brooding darkness, Mary gradually finds herself becoming ensnared in the various devious schemes being enacted behind its crumbling walls - and tempted to love a man she dares not trust.
I really enjoyed reading this book very much; in my opinion, the story was certainly very good and I wanted to find out what would happen next. Although, I will say that I found the story just the slightest bit overly theatrical for me. I absolutely love Daphne du Maurier's writing style; she certainly knew how to create a frightening and suspenseful atmosphere.
I would always literally get lost in Ms. Du Maurier's books every time I read one. However, Jamaica Inn was a slightly different reading experience for me; I never entirely lost myself along the wild Cornish moors while I read this particular book. In my opinion, while this was still a very good story, I don't think it was Daphne du Maurier's best work. Although, I would still give Jamaica Inn by Daphne du Maurier an A!
Mary Yellan's mother dies. Her final request was that Mary seek shelter with her Aunt Patience. Mary soon discovers that Jamaica Inn is not respectable and that her aunt is putting up with a despicable husband who is both an alcoholic and a smuggler. While wandering on the moors, Mary encounters an albino clergyman. She finds herself falling in love with her uncle's horse-thieving brother. The characters are well drawn. The novel is dark. It's far from my favorite DuMaurier, but it was nice to revisit this book I'd read about 35 to 40 years ago.
When young Mary Yellan's mother, lying on her deathbed, makes her daughter promise she will seek out her aunt Patience for shelter, the dying woman can have no idea of the curse she is putting on her daughter. On the way to Jamaica Inn by coach, where Mary Yellan has learned her aunt has been living with her husband, she learns that the inn has earned a terrible reputation and that no proper lady or gentleman dare approach the place. Upon arrival, she discovers her aunt Patience is half mad with fear and that her uncle Joss Merlyn is a violent drunken brute who threatens her to keep her place and to take no notice of the nightly goings on; that she is to keep her eyes and ears shut and ignore any strange noises or risk bodily harm. But Mary is curious and headstrong and soon finds out her uncle is a smuggler involved in terrible crimes. She resolves to bring him to justice, putting herself in great peril, though she doesn't want to put her aunt at risk as well. An exciting adventure with truly evil characters and a surprising plot twist near the end. I really enjoy Rebecca du Maurier and only seem to grow fonder of her writing with every book of hers I read—her unique mixture of strange human behaviour with beautiful descriptions of the wilds of Cornwall make for an irresistible combination.
The writing in this is so very atmospheric that whilst I was tucked up warm in bed I could swear I felt the cold and shivered.
Mary Yellan's family has died and she can no longer run the farm in Southern Cornwall by herself. She goes to live with her aunt, who is married to the landlord of an Inn on the loneliest part of Bodmin. Before she arrives she hears the bad reputation of the place. The reality is every bit as bad as the stories. Her aunt is no longer the gay women she remembers, instead Patience is a broken woman, browbeaten as well as actually beaten, and mentally broken down. The landlord is clearly involved in nefarious activity and Mary is told, in no uncertain terms, to close her eyes and stop her ears and to keep her mouth shut. However Mary doesn't exactly do as she is told. She stands up to her uncle in several small ways, while being unable to, yet, turn him in and escape the place.
While staying at the Inn she meets two men, Jem, the landlord's younger brother & horse thief and Frances Davy, the vicar of the nearest village. They are both unknown quantities, and Mary is not certain if she can trust herself in her reaction to them. The climax takes place over the space of a few days around Christmas. It is quite fast moving and quite violent. It doesn't all end happily, and there is a final twist of the plot in the last few chapters that I didn't see coming at all. The final chapter is less of a surprise, after the denouement, Mary does escape, and she will live again.
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3-in-1: Rebecca + Frenchman's Creek + Jamaica Inn by Daphne du Maurier
Four Great Cornish Novels: Jamaica Inn, Rebecca, Frenchman's Creek, My Cousin Rachel by Daphne du Maurier
Jamaica Inn / The Birds and Other Stories by Daphne du Maurier
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Wikipedia in English
Amazon.com Amazon.com Review (ISBN 0380725398, Mass Market Paperback)Jamaica Inn is a true classic. After the death of her mother, Mary Yellan travels to Jamaica Inn on the wild British moors to live with her Aunt Patience. The coachman warns her of the strange happenings there, but Mary is committed to remain at Jamaica Inn. Suddenly, her life is in the hands of strangers: her uncle, Joss Merlyn, whose crude ways repel her; Aunt Patience, who seems mentally unstable and perpetually frightened; and the enigmatic Francis Davey. But most importantly, Mary meets Jem Merlyn, Joss's younger brother, whose kisses make her heart race. Caught up in the danger at this inn of evil repute, Mary must survive murder, mystery, storms, and smugglers before she can build a life with Jem.
(retrieved from Amazon Thu, 12 Mar 2015 18:12:13 -0400)
The inn is derelict, and no decent folks will come to it, speaking of it in fearful whispers. When Mary Yellan joins her aunt, married to the owner, she soon finds she has but two friends on the wild moors--the mysterious parson and an insolent, likeable horsethief.… (more)
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The psychometric properties of three self-report screening instruments for identifying frail older people in the community
Author affiliations
1 Department of Health Care and Nursing Science, School for Public Health and Primary Care (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
2 Centre of Research on Autonomy and Participation for Chronically Ill, Zuyd University of Applied Sciences, Heerlen, The Netherlands
3 Faculty of Health and Care, Zuyd University of Applied Sciences, Heerlen, The Netherlands
4 Centre of Research on Technology in Care, Zuyd University of Applied Sciences, Heerlen, The Netherlands
5 Department of Health Sciences, University Medical Centre Groningen, Groningen, The Netherlands
Citation and License
BMC Public Health 2010, 10:176 doi:10.1186/1471-2458-10-176Published: 31 March 2010
Frailty is highly prevalent in older people. Its serious adverse consequences, such as disability, are considered to be a public health problem. Therefore, disability prevention in community-dwelling frail older people is considered to be a priority for research and clinical practice in geriatric care. With regard to disability prevention, valid screening instruments are needed to identify frail older people in time. The aim of this study was to evaluate and compare the psychometric properties of three screening instruments: the Groningen Frailty Indicator (GFI), the Tilburg Frailty Indicator (TFI) and the Sherbrooke Postal Questionnaire (SPQ). For validation purposes the Groningen Activity Restriction Scale (GARS) was added.
A questionnaire was sent to 687 community-dwelling older people (≥ 70 years). Agreement between instruments, internal consistency, and construct validity of instruments were evaluated and compared.
The response rate was 77%. Prevalence estimates of frailty ranged from 40% to 59%. The highest agreement was found between the GFI and the TFI (Cohen's kappa = 0.74). Cronbach's alpha for the GFI, the TFI and the SPQ was 0.73, 0.79 and 0.26, respectively. Scores on the three instruments correlated significantly with each other (GFI - TFI, r = 0.87; GFI - SPQ, r = 0.47; TFI - SPQ, r = 0.42) and with the GARS (GFI - GARS, r = 0.57; TFI - GARS, r = 0.61; SPQ - GARS, r = 0.46). The GFI and the TFI scores were, as expected, significantly related to age, sex, education and income.
The GFI and the TFI showed high internal consistency and construct validity in contrast to the SPQ. Based on these findings it is not yet possible to conclude whether the GFI or the TFI should be preferred; data on the predictive values of both instruments are needed. The SPQ seems less appropriate for postal screening of frailty among community-dwelling older people.


text: My husband and I only stayed one night, but the next morning, my husband asked me, "Can we stay another night?" Farm stays are not just for kids. So, what's not to like? The room was big and comfy and very, very quiet. There were local guides to view and read. The farm is only a twenty-minute drive from Port... More


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Description: Seventeen year old Aaron Duval's life turns around when the new neighbours move in. Spencer Smith is a rebellious, intimidating and quite frankly, scary teenager. Weirdly enough, they become friends, but for poor Aaron, after her death, she just doe...
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Friday, September 25, 2009
© Copyright 2015 Newton Citizen
There is a good amount of bickering going on in the land of the free and the home of the brave. Take your pick of topics - war, the economy, jobs, health care reform or whatever.Into this mix recently came political appointees called czars. They have been around for many years, are not elected, and require no Senate confirmation. Some of us first became aware of members of this shadow cabinet when a fellow named Van Jones resigned under fire. He said he was a victim of a vicious smear and that his opponents were being divisive. Under distractions, he felt he could no longer effectively serve the president. So what caused Mr. Jones to fall into public disfavor? It could have been his background, his claim to be a Communist, or his calling Republicans a-holes. Nothing will raise the hair on a Republican's neck quicker than calling him or her an a-hole! Yes, unless you also proclaim that the Bush administration was responsible for 9-11. Anyway, regardless of Mr. Jones' talents, his reputation and public acclamations brought about his resignation. Questions arose. Since he was acting as a presidential advisor helping reshape America by working on clean energy incentives, trying to create jobs and improve energy efficiency, who checked his background? Could he have survived a full field FBI investigation or a Senate confirmation? He was reported to have a solidarity with Muslims and believed they were victims of U.S. imperialism. Mr. Jones had a radical reputation. Czars are appointed to handle the presidential agenda. Their jobs offer ways to bring more power into the White House where party loyalists may be rewarded. Czars have no congressional oversight and may subvert the authority of the House and Senate. Have all of their backgrounds seen public light? Czars, now numbering over 30 in the White House, have not gone unnoticed. At least one prominent senator, Robert C. Byrd (D-W.Va) has cautioned President Obama saying the Constitutional checks and balances are threatened by these political appointees, these presidential advisors. With all of these unconfirmed cooks in the White House kitchen, many members of Congress would like more information, disclosure and accountability of czars who are helping to make policy and recommend the spending of tax dollars. Why not have these appointees Senate confirmed? Society might be better served by knowing who stands at the elbow to the president and whispers in his ear about policy and the allocation of public monies. Legislators should exercise authority to review budgets. Jack Simpson is a former educator, veteran, author and a law enforcement officer. His column appears each Friday.
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