Free kindle book and epub digitized and proofread by Project Gutenberg. El prisionero de Zenda, el gran clásico de la novela de capa y espada, en una cuidada edición especial con introducción de Arturo. El prisionero de Zenda (en inglés, The Prisoner of Zenda) es una novela escrita en el año por el autor británico Sir Anthony Hope.

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Sign in with Facebook Other Sign in options. See this year’s top trailers in under a minute, including Avengers: Infinity War and Aquaman. Search for ” The Prisoner of Zenda ” on Amazon. The Prisoner of Zenda Dee Englishman on a Ruritarian prisinero must impersonate the king when the rightful monarch, a distant cousin, is drugged and kidnapped.

In France during the late 18th Century, a man sets out to avenge the death of his friend at the hands of a master swordsman.

Anthony Hope’s classic tale gets a decidedly ‘un-classic’ treatment at the hands of Peter Sellers. Following the story somewhat, friends of the new King Rudolph of Ruritania fear for his Adventurer Allan Quartermain leads an expedition into uncharted African territory in an attempt to locate an explorer who went missing during his search for the fabled diamond mines of King Solomon.

The King of Ruritania is kidnapped by his scheming brother: A young Viking prince strives to become a knight in King Arthur’s Court and restore his exiled father to his rightful throne.

Dardo, a Robin Hood-like figure, and his loyal followers use a Roman ruin in Medieval Lombardy as their headquarters zendq they conduct an insurgency against their Hessian conquerors. King Arthur’s rule is threatened by the adulterous love between Sir Lancelot and Queen Guinevere, a relationship the king’s enemies hope to exploit.

When the king is drugged and abducted by his ambitious brother, a lookalike relative must take his place to keep the evil sibling off the zdnda. A young orphan is sent to the village of Moonfleet, in Dorset, England to stay with his mother’s former lover, who has the facade of a gentleman but is a leader of a gang of swashbuckling bootleggers. The duo went on a treasure hunt.

English trout fisher Rudolf Rassendyll is about the only tourist not coming for the coronation of Central-European King Rudolf V at Strelsau, but happens to be a distant relative and is approached on account of their canning resemblance to stand in for the drunken king, in order to prevent his envious half-brother Michael, who arranged spiking his wine to seize the throne when the reputedly less then dutiful Rudolf stays away.

The ceremony goes well, and he gets acquainted with the charming royal bride, related princess Flavia, but afterward the king is found to be abducted; he must continue the charade and once the hiding place, the castle of Zenda, is found is involved in the fight between political parties for control over Rudolf V, his throne and his bride, for which a formidable third candidate, Michael’s disloyal co-conspirator Rupert of Hentzau, was waiting in the curtains.

Written by KGF Vissers. If it doesn’t quite have the panache of the Colman film, it makes up for it with the introduction of some nice color cinematography. The casting of Stewart Granger in the double role of Rudolph Rassendyll and his royal cousin, the Crown Prince Rudolph of Ruritania and James Mason as the villainous Rupert of Hentzau is hardly some stock company casting. If Granger doesn’t quite have Colman’s flair for the spoken word and very few ever have, he makes a fine and dashing hero which parts he played very well, too well in his opinion on his career.

As for Mason, Douglas Fairbanks, Jr. Mason who has also played some of the best villains on screen keeps up the fine tradition for that role.

The version benefited from having the world wide publicity of the constitutional crisis in the United Kingdom over Edward VIII choice of consort.

Which begs the question whether we’ll get yet another version when Prince Charles eventually assumes the throne. We’ve seen over ten versions so far going back to the silent screen. I’ve always thought that Greer as Antoinette plays one of the most tragic characters in popular literature.

She loves a cold and forbidding man in Prince Michael, especially when played by Robert Douglas. But he’s her man and when she does ever so slightly give in to the scheming Hentzau she regrets it when it means the death of her beloved.

Personally why she falls for a cold fish that Michael is who can figure. But the heart does have its reasons. As for Kerr her best scene is at the end when she realizes she has been hoodwinked, but in a scheme for the greater good of the kingdom. She knows what her obligations are and she too can’t afford to follow her heart. Something tells me we’re far from done with The Prisoner Of Zenda. Try and figure out who could play these roles today with the flair of the players in this version, let alone the one from Start your free trial.

Find showtimes, watch trailers, browse photos, track your Watchlist and rate your favorite movies and TV shows on your phone or tablet! Keep track of everything you watch; tell your friends. Full Cast and Crew. On Disc at Amazon. An Englishman vacationing in a Ruritarian kingdom is recruited to impersonate his cousin, the soon-to-be-crowned king when the monarch is drugged and kidnapped. Watch the Top Trailers of Longest Film Career Ever?

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King Solomon’s Mines Passed Action Adventure Romance. Prisoner of Zenda The Flame and the Arrow Sinbad, the Sailor Knights of the Round Table Edit Cast Complete credited cast: Princess Flavia Louis Calhern Antoinette de Mauban Lewis Stone The Cardinal Robert Douglas Michael, Duke of Strelsau Robert Coote Fritz von Tarlenheim Peter Brocco Edit Storyline English trout fisher Rudolf Rassendyll is about the only tourist not coming for the coronation of Central-European King Rudolf V at Strelsau, but happens to be a distant relative and is approached on account of their canning resemblance to stand in for the drunken king, in order to prevent his envious half-brother Michael, who arranged spiking his wine to seize the throne when the reputedly less then dutiful Rudolf stays away.

Mono Western Electric Sound System. Edit Did You Know? Goofs When the conductor conducts the waltz at the ball, his hand movements bear no relation to the music played. Crazy Credits The opening credits are listed on parchment or velum-looking pages.

The Prisoner of Zenda – Wikipedia

The top, blank page has a silver sword upon it, which is piercing the page. When lifted, the credits start on the page below. The pages are ornately done with colorful ink letters and designs.

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El Prisionero de Zenda [The Prisoner of Zenda]

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Karapapaklar: Karapapak Hamidiye Alaylari ve Mihrali Bey. 4 likes. Book. Osmanlı İmparatorluğu’nun son döneminde oluşturulan Hamidiye Alayları, hedefleri ve etkileri bakımından ilgi çekici bir tarihî vakadır. Somut etkileri ‘ dan. : Hamidiye Alaylari Agri Kurt Direnisi Ve Zilan Katliami ( ) by Kemal Süphandag and a great selection of similar New, Used and.

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Hamidian massacres

To see what your friends thought of this book, please sign up. Lists with This Book. This study is more than hamiriye description of Ottoman Kurdish militia units.

It is an examination of the twinned modern practices of statecraft and nation-building. However, as this text shows, all too often these noble-sounding concepts involve little more than passing out guns to unscrupulous young men. Hamidiyd is because states are hamidiyye rational or monolithic actors, and even when they do posses a modicum of rationality and unity of action, their movement is constricted and their options are limite This study is more than a description of Ottoman Kurdish militia units.

Hamidian massacres – Wikipedia

This is because states are rarely rational or monolithic actors, and even when they do posses a modicum of rationality and unity of hamdiye, their movement is hanidiye and their options are limited by circumstances beyond alatlari control. Klein does a fine job of distinguishing and highlighting these problematics of state power through the prism of the history of the Kurdish “Hamidiye” cavalry-militia movement, underscoring the contradictions in Ottoman domestic governance – the fact that the Sublime Porte wanted at once to pacify and sedentarize the intractable Kurds by bringing them into a closer union with the state “keep your enemies even closer”yet alaylqri up empowering them in the process.

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Read the libretto, translated to english, of the Italian opera La Gazza ladra by Giaochino Rossini on With links to other information and other . Libretti. Complete Libretto · *# – MB, 34 pp. – /10 2 4 6 8 10 (-) – V/ C/V – 6×⇩ – JacopoTore · PDF scanned by Jacopo Tore. La gazza ladra =​ The thieving magpie: opera semiseria in two acts /​ [music by ] Gioacchino Rossini ; libretto by Giovanni Gherardini ; produced by WDR in.

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La gazza ladra (Rossini, Gioacchino)

Creative Commons Attribution-NonCommercial 4. Retrieved from ” http: Opera semiseria ; Theatrical Works ; Operas ; For voices, mixed chorus, orchestra ; Scores featuring the voice ; Scores featuring mixed chorus ; Scores featuring the orchestra ; For voices and chorus with orchestra ; Italian language ; For flute, violin, viola, cello arr ; For 4 players ; Scores featuring the flute ; Scores featuring the violin ; Scores featuring the viola ; Scores featuring the libretgo ; For 2 violins, viola, cello arr ; For harp arr ; For 1 player ; Scores featuring the harp ; For flute, harp arr ; For 2 players ; For piano arr ; Scores featuring the piano ; For flute arr ; For flute, violin, piano arr ; For 3 players ; Libetto violin, piano arr ; For piano 4 hands arr ; Scores featuring the piano 4 hands ; For clarinet arr ; Scores featuring the clarinet.

Pieces based on ‘La gazza ladra’. Contents 1 Performances 1. Vieni fra queste braccia 2. Javascript is required for this feature. Ernst EulenburgNo. Dover Publications Title added by Jawher Matmati This score includes measure numbers.

La gazza ladra – Wikipedia

Part of the research project Romantic Overtures, These files are part of the Orchestra Parts Project. Arranger Maximilian Joseph Leidesdorf Almost the entire opera in its original version. Ouverturen — Piano und Violine pp.

Edition PetersNo. This file is part of the Sibley Mirroring Project. Edition Petersn.

Universal Editionn. This file is from the MIT archive project. Alburm of 6 Overtures for Piano New York: Mss score 2 volsparts. La cambiale di matrimonio L’equivoco stravagante Demetrio e Polibio L’inganno felice Ciro in Babilonia La scala di seta La pietra del paragone L’occasione fa il ladro Il signor Bruschino Tancredi L’italiana in Algeri Aureliano in Palmira Il turco in Italia


Applying the Mahalanobis–Taguchi System to. Improve Tablet PC Production Processes. Chi-Feng Peng 2,†, Li-Hsing Ho 3,†, Sang-Bing Tsai. The purpose of this paper is to present and analyze the current literature related to developing and improving the Mahalanobis-Taguchi system (MTS) and to. ABSTRACT. The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to.

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To receive news and publication updates for Computational Intelligence and Neuroscience, enter your email address in the box eystem. BoxAmmanJordan. Correspondence should be addressed to Mahmoud El-Banna ; moc. This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Mahalanobis Taguchi System MTS is considered one of the most promising binary classification algorithms to handle imbalance data.

Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. MMTS outperforms the benchmarked algorithms especially when taguhci imbalance ratio is greater than A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to nahalanobis its performance with Mahalanobis Genetic Algorithm MGA.

Classification is one of the supervised learning approaches mahakanobis which a new observation needs to be assigned to one of the predetermined classes or categories.

If the number of the predetermined classes is more than two, it is a multiclass classification problem; otherwise, the problem is known as the binary classification problem.

At present, these problems have found applications in different domains such as product quality [ 1 ] and speech recognition [ 2 ]. The classification accuracy depends on both the classifier and the data types. The classifier types can be categorized according to supervised versus unsupervised learning, linear versus nonlinear hyperplane, and feature selection versus feature extraction based approach [ 3 ].

On the other hand, Sun et al. If the data distribution of one class is different from distributions of others, then the data is considered imbalance. The border that separates balance from imbalance data is vague; for example, imbalance ratio, which is the ratio between the major to minor class observations, is reported from small values of to 1 to The assumption of an equal number of observations in each class is elementary in using the common classification methods such as decision tree analysis, Support Vector Machines, discriminant analysis, and neural networks [ 6 ].

Imbalance data occurs often in real life such as text classification [ 7 ]. The problem of treating the applications that have imbalance data with the common classifiers leads to bias in the classification accuracy i.

To handle the classification of imbalanced data problem, the research community uses data and algorithmic or both approaches. For the data approach, the main idea is to balance the class density randomly or informatively i. While at the algorithmic approach, the main idea is to adapt the classier algorithms towards the small class, a combination of the data and algorithmic levels approaches is also used and known as cost-sensitive learning solutions.

The problems reported [ 4 ] using data approach are as follows: While the problem reported [ 4 ] using the algorithmic approach is that it needs a deep understanding about the classier used itself and the application area i. Finally, the problem in using the cost-sensitive learning approach is the assumption of previous knowledge for many errors types and imposing a higher cost to the minority class to improve the prediction accuracy.

Knowing the cost matrices in most cases is practically difficult. While data and algorithmic approaches constitute the majority efforts in the area of imbalanced data, several other approaches have also been conducted, which will be reviewed in Literature Review. To overcome the pitfalls of data and algorithmic approaches to solve the problem of imbalanced data classification, the classification algorithm needs to be capable of dealing with imbalance data directly without resampling and should have a systematic foundation for determining the cost matrices or the threshold.

One of the promising classifiers is the Mahalanobis Taguchi System MTSwhich has shown good classification results for imbalance data without resampling, it does not require any distribution assumption for the input variables, and it can be used to measure the degree of abnormality i.

Three operating point selection criteria, shortest distance, harmonic mean, and antiharmonic mean, have been compared, and the results in [ 9 ] showed that there is no difference among classifiers performances. The aim of this work is to enhance the Mahalanobis Taguchi System MTS classifier performance by providing a scientific, rigorous, and systematic method using the ROC curve for determining the threshold that discriminates between the classes.

The organization of the paper is as follows: Section 2 reviews the previous work of imbalance data classifications methods, the Mahalanobis Taguchi System, and its applications. Section 5 presents a case study to demonstrate the applicability of the proposed research. And in Section 6the results obtained from this research are summarized. In this section, an overview of the imbalance classification approaches, the Mahalanobis Taguchi System concept, its different areas of applications, weakness points, and its variants is presented.

Solutions to deal with the imbalanced learning problem can be summarized into the following approaches [ 10 ]: Data level approach [ 11 ] is mainly returning the balance distribution between the classes through resampling techniques. It includes the following types: The problems reported in data approaches are as follows: Algorithmic level approach solutions are based upon creating a biased algorithm towards positive class.

The algorithmic level approach has been used in many popular classifiers such as decision trees, Support Vector Machines SVMsassociation rule mining, back-propagation BP neural network, one-sample learning, active learning methods, and the Mahalanobis Taguchi System MTS.

The adaptation of decision tree classifier to suit the imbalance data can be accomplished by adjusting the probabilistic estimate of the tree leaf or developing new trimming approaches [ 14 ]. Support Vector Machines SVMs showed good classification results for slightly imbalanced data [ 15 ], while for highly imbalanced data researchers [ 1617 ] reported poor performance classification results, since SVM try to reduce total error, which will produce results shifted towards the negative majority class.

Modified Mahalanobis Taguchi System for Imbalance Data Classification

To handle the imbalance data, there are proposals such as using penalty constants for different classes found in Lin et al. Therefore, in this paper, SVM was selected as one of the benchmarked algorithms to compare with ours; the results showed that SVM classification performance largely degrades with a high imbalance ratio, which supports the previous findings of the researchers more details will be presented in Results. Association rule mining is a recent classification approach combining association mining and classification into one approach [ 20 — 22 ].

To handle the imbalance data, determining many minimal supports for different classes to present their varied recurrence is required [ 23 ]. On the other hand, one-class learning [ 2425 ] used the target class only to determine if the new observation belongs to this class or not.

BP neural network [ 26 ] and SVMs [ 27 ] are examined as one-class learning approach. In the case of highly imbalanced data, one-class learning showed good classification results [ 28 ]. Unfortunately, one-class learning algorithms drawbacks are that the size of the training data is relatively larger than those for multiclass approaches, and it is also hard to reduce the dimension of features used for separation.

Active learning approach is used to handle the problems related to the unlabeled training data. Research on active learning for imbalance data reported by Ertekin et al. Unfortunately one of the bit falls for using this approach is that it can be computationally expensive [ 30 ]. The problem with the algorithmic approach is that it needs an extensive knowledge of specific classifier i. Cost-sensitive methods use both data and algorithmic approaches, where the objective is to optimize i.

Cost-sensitive methods used different costs or penalties for different misclassification types. For example, let be the cost of wrongly classifying positive instant as a negative one, while is the cost of the contrary case. In imbalance data classification, usually, the revealing of the positive instant is more important than the negative one; hence, the cost of positive instance misclassification outweighs the cost of negatives ones i.

Different types of cost-sensitive approaches have been reported in the literature: The problem of using the cost-sensitive approach is that it is based on previous knowledge of the cost matrix for the misclassification kinds, while in most cases it is unavailable.

MTS is a multivariate supervised learning approach, which aims to classify new observation into one of the two classes i. MTS was used previously in predicting weld quality [ 3 ], exploring the influence of chemicals constitution on hot rolling manufactured products [ 34 ], and selecting the significant features in automotive handling [ 35 ].

The MTS approach starts with collecting considerable observations from the investigated dataset, tailed by separating of the unhealthy dataset i.

Computational Intelligence and Neuroscience

Calculation of the Mahalanobis Distance MD using the negative observation is performed first, followed by scaling i. The scaled MD for the positive date set supposes to be different from MD for those for the mahalanogis dataset. Since many features are used to calculate the MD, so that the probability to have significant features for the multivariable dataset is high, Taguchi orthogonal array is used to screen these features.

The criterion for selecting the appropriate features is determined by selecting the features that possess high MD values for the positive observations. mabalanobis

It is worth noticing that a continuous scale is constructed from the single class observations by using MTS; unlike other classification techniques, learning is done directly from mqhalanobis positive and negative observations.

This characteristic helps the MTS classifier to deal with the imbalance taguch problems. The step of determining the optimal threshold is a critical one for effective MTS classier.

To determine the appropriate threshold, loss function approach was proposed by [ 36 ]; however, it is not a practical approach because of the difficulty in specifying the relative cost [ 37 ]. It has been shown in [ 6 ] that PTM classifier performance outperformed MTS classifier performance; therefore, it has been selected to be benchmarked with the proposed classifier.

Unfortunately, the PTM method is based on previously assumed parameters, and the accuracy of the classification tgauchi was less than the benchmarked classifiers this is one of the findings in this research, which will be discussed in Results.

The other research area in the MTS is related to the modification of the Taguchi method not in the threshold determination. Both the MGA and MTS Particle Swarm Optimization methods deal with the Taguchi system orthogonal array part, while the threshold determination still lacks a solid foundation or is hard to be determined in reality. Finally, the aim of this research is to enhance the Mahalanobis Taguchi System MTS classifier performance through providing a scientific, rigorous, and systematic method of determining the binary classification threshold that discriminates between the two classes, which can be applied to the MTS and its variants i.

The proposed model, Algorithm 1provides an easy, reliable, and systematic way to determine the threshold for the Mahalanobis Taguchi System MTS and its variants i. The currently used approaches either are difficult to use in practice such as the loss function [ 36 ] due to the difficulty in evaluating the cost in each case or are based on previously assumed parameters [ 6 ]. As shown in Figure 1pointrepresents the optimum theoretical solution best performance for mmahalanobis classifier.

The closer the classifier performance to this point is, the better it is. The curve mahalaonbis in the figure represents the MTS classifier performance for different threshold values. Changing the threshold will change the point location on the curve i. Therefore, the problem of finding the optimum threshold can be reformulated into the problem of finding the closest point that lies on the curve to point. Step 1 construction of the initial model stage. Assume there are two classes: A set of data is sampled from both classes.

Using the negative observations only, reference Mahalanobis Distances are calculated using 1 with all features used.

The Mahalanobis Distances MD for the positive observations are also calculated by using the same equation with all features, with the inverse of the correlation matrix of the negative observation used. Selection of the new features is performed by mahalanobid the orthogonal array approach; then a recalculation of MDs for the negative and the positive observation is performed.

An arbitrary threshold is assumed i. Step 2 optimization stage. If the stopping criteria i. Accordingly, new features will be selected using the orthogonal array approach, and true positive rate, false positive rate, and txguchi fitness function will be also updated. If the stopping criteria are met, then the training stage is done, and the model is ready for testing observations.

Step 3 testing stage. In this stage, the optimum threshold and the associated features are determined from the previous stage and the Mahalanobis Distance for the new observation is calculated based on those parameters. If the Mahalanobis Distance for this observation is less than the optimum threshold, then it will be tagucbi as negative; otherwise, it will be classified as positive.


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Adam Lay Ybounden

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We ordered this for our community chorus. The work is beautiful, and we have greatly enjoyed learning it. We will perform this during our upcoming Lessons and Carols concert. We were disappointed in the fact that the scores were back-ordered, I assume because they are printed on demand.

We keep scores to perform again in future concerts, and we need scores that will endure pencil marking and erasing, so it is important for us to have a more durable version.

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