Meiden vingeren neukende lesbies

meiden vingeren neukende lesbies

Een truc om toch op te kunnen treden, was besloten feesten organiseren waarbij het toegangskaartje tevens contributie was voor de fanclub. Dit werd onder andere toegepast in Beursgebouw te Eindhoven. Eindhoven was een persoonlijke victorie nadat de burgemeester officieel te kennen had gegeven geen optreden te zullen tolereren, hetgeen Rockbitch met succes aanvocht.

Ook in München , waar men de bereden oproerpolitie buiten de concerthal stationeerde om te voorkomen dat Rockbitch zou optreden, moesten de autoriteiten uiteindelijk capituleren en een paar weken later speelde Rockbitch daar voor een uitverkochte zaal.

In beide gevallen speelde het publiek een belangrijke rol, zowel mannen als vrouwen protesteerden luidkeels dat als volwassenen zij het recht hadden te kiezen wat zij zouden zien: De show gaf aan voor boven de achttien te zijn, personen die het er niet mee eens waren hadden de keus weg te blijven, maar niet om anderen te veroordelen. De optredens zelf hadden weinig met softe erotiek van doen, het was vooral rechttoe rechtaan seks; Rockbitch geloofde dat het nodig was te laten zien dat vrouwen niet alleen maar lieflijk in bed waren, maar af en toe een goed robbertje zweterige seks nodig hadden, zoals elk gezonddenkend mens volgens hen meerdere seksuele aspecten in zich had.

Dit uitte zich in plasseks , vuistseks en seks met voorbinddildo 's. Daarnaast leefden zij hun wereldvisie uit door middel van rituelen op het podium: Zij droegen altijd een godinnenbeeld met zich mee dat tijdens de concerten een ereplaats op het podium innam; wijn werd over naakte vrouwenlichamen gegoten en gedronken als heilig offer.

Dit zorgde vooral in Engeland voor controverse, waar met hen als Satanisch betitelde. Rockbitch zelf stelde echter dat het geen Satanisme was, maar meer een vorm van aanbidding van het vrouwelijke principe in al haar vormen. De Bisschop van Canterbury veroordeelde hen openlijk en probeerde hen zo veel mogelijk het optreden te beletten. Wat vooral opviel was het publiek: De diversiteit was enorm, mannen en vrouwen uit alle legale leeftijdsgroepen bezochten de concerten; al gaven de media er de voorkeur aan te melden dat het voornamelijk hitsige alleenstaande mannen waren die in Rockbitch geïnteresseerd waren.

Ook het feit dat zij samenleefden in een commune bracht menig journalist ertoe deze groep nader te onderzoeken; een van de bekendste voorbeelden is de documentaire This is Rockbitch van het Engelse Channel 4 , die nog steeds regelmatig op televisie herhaald wordt, net zoals in Japan en op het Amerikaanse netwerk HBO. In Nederland waren het vooral de optredens in Enschede en in Eindhoven die veel bezoekers trokken Een persoonlijk hoogtepunt was voor Rockbitch een 'Women only' concert tijdens de Gay Games in Amsterdam, waar een vrouwen sterk publiek hun waardering liet blijken.

Bitchcraft en The Bitch O'Clock News, die bestaan uit Live concert muziek en interviews plus een documentaire over hun communale leven. Tot zover hebben ze 1 officieel studio- album op hun naam staan: Dit album verkreeg veel positieve reportages en meerdere muziekbladen stelden vast dat, wat Rockbitch ook deed op het podium, hun muzikale talent onmiskenbaar was.

Na Motor Driven Bimbo verbrak hun platenmaatschappij het contract dat voor drie albums zou zijn met de band, omdat Rockbitch de seksualiteit niet uit hun optredens wilde bannen.

Een tweede voorbeeld dat, hoe men het ook interpreteert; zijzelf beslist achter hun show en levensbeschouwing stonden. Zij bleven optreden en breidden hun podium act uit met twee 'Sex Magick Priestesses', Kali en Chloe en voor korte tijd Erzulie, die de seksuele rituelen uitvoerden. De originele Stage-Slut Luci nam de plaats over van de mannelijk gitarist, zodat de band voor de laatste vier of vijf jaar uitsluitend uit vrouwen bestond. Uiteindelijk besloten zij unaniem in een punt achter de publieke uitleving van hun ideeën te zetten.

Zij brachten een laatste docu-video uit: SexDeathMagick; Live beelden afgewisseld met seksuele rituelen zoals zij die in hun commune vorm gaven.

De Channel 4 documentaire was aanwezig bij hun laatste concert in de Marrs Bar in Worcester, Engeland. Rockbitch gaf te kennen na zo lang op de barricades te hebben gestaan voor waar zij het meest in geloofden, het nu tijd was om zich wat meer naar binnen te richten. Roughly speaking, it classifies on the basis of noticeable over- and underuse of specific features.

Before being used in comparisons, all feature counts were normalized to counts per words, and then transformed to Z-scores with regard to the average and standard deviation within each feature.

Here the grid search investigated: As the input features are numerical, we used IB1 with k equal to 5 so that we can derive a confidence value. The only hyperparameters we varied in the grid search are the metric Numerical and Cosine distance and the weighting no weighting, information gain, gain ratio, chi-square, shared variance, and standard deviation.

However, the high dimensionality of our vectors presented us with a problem. For such high numbers of features, it is known that k-nn learning is unlikely to yield useful results Beyer et al. This meant that, if we still wanted to use k-nn, we would have to reduce the dimensionality of our feature vectors. For each system, we provided the first N principal components for various N.

In effect, this N is a further hyperparameter, which we varied from 1 to the total number of components usually , as there are authors , using a stepsize of 1 from 1 to 10, and then slowly increasing the stepsize to a maximum of 20 when over Rather than using fixed hyperparameters, we let the control shell choose them automatically in a grid search procedure, based on development data.

When running the underlying systems 7. As scaling is not possible when there are columns with constant values, such columns were removed first. For each setting and author, the systems report both a selected class and a floating point score, which can be used as a confidence score. In order to improve the robustness of the hyperparameter selection, the best three settings were chosen and used for classifying the current author in question.

For LP, this is by design. A model, called profile, is constructed for each individual class, and the system determines for each author to which degree they are similar to the class profile. For SVR, one would expect symmetry, as both classes are modeled simultaneously, and differ merely in the sign of the numeric class identifier. However, we do observe different behaviour when reversing the signs. For this reason, we did all classification with SVR and LP twice, once building a male model and once a female model.

For both models the control shell calculated a final score, starting with the three outputs for the best hyperparameter settings. It normalized these by expressing them as the number of non-model class standard deviations over the threshold, which was set at the class separation value.

The control shell then weighted each score by multiplying it by the class separation value on the development data for the settings in question, and derived the final score by averaging. It then chose the class for which the final score is highest. In this way, we also get two confidence values, viz. Results In this section, we will present the overall results of the gender recognition.

We start with the accuracy of the various features and systems Section 5. Then we will focus on the effect of preprocessing the input vectors with PCA Section 5.

After this, we examine the classification of individual authors Section 5. For the measurements with PCA, the number of principal components provided to the classification system is learned from the development data. Below, in Section 5. Starting with the systems, we see that SVR using original vectors consistently outperforms the other two. For only one feature type, character trigrams, LP with PCA manages to reach a higher accuracy than SVR, but the difference is not statistically significant.

For SVR and LP, these are rather varied, but TiMBL s confidence value consists of the proportion of selected class cases among the nearest neighbours, which with k at 5 is practically always 0. The class separation value is a variant of Cohen s d Cohen Where Cohen assumes the two distributions have the same standard deviation, we use the sum of the two, practically always different, standard deviations.

Accuracy Percentages for various Feature Types and Techniques. In fact, for all the tokens n-grams, it would seem that the further one goes away from the unigrams, the worse the accuracy gets. An explanation for this might be that recognition is mostly on the basis of the content of the tweet, and unigrams represent the content most clearly.

Possibly, the other n-grams are just mirroring this quality of the unigrams, with the effectiveness of the mirror depending on how well unigrams are represented in the n-grams. For the character n-grams, our first observation is that the normalized versions are always better than the original versions. This means that the content of the n-grams is more important than their form. This is in accordance with the hypothesis just suggested for the token n-grams, as normalization too brings the character n-grams closer to token unigrams.

The best performing character n-grams normalized 5-grams , will be most closely linked to the token unigrams, with some token bigrams thrown in, as well as a smidgen of the use of morphological processes. However, we cannot conclude that what is wiped away by the normalization, use of diacritics, capitals and spacing, holds no information for the gender recognition. To test that, we would have to experiment with a new feature types, modeling exactly the difference between the normalized and the original form.

This number was treated as just another hyperparameter to be selected. As a result, the systems accuracy was partly dependent on the quality of the hyperparameter selection mechanism. In this section, we want to investigate how strong this dependency may have been. Recognition accuracy as a function of the number of principal components provided to the systems, using token unigrams.

Figures 1, 2, and 3 show accuracy measurements for the token unigrams, token bigrams, and normalized character 5-grams, for all three systems at various numbers of principal components. For the unigrams, SVR reaches its peak Interestingly, it is SVR that degrades at higher numbers of principal components, while TiMBL, said to need fewer dimensions, manages to hold on to the recognition quality. LP peaks much earlier However, it does not manage to achieve good results with the principal components that were best for the other two systems.

Furthermore, LP appears to suffer some kind of mathematical breakdown for higher numbers of components. Although LP performs worse than it could on fixed numbers of principal components, its more detailed confidence score allows a better hyperparameter selection, on average selecting around 9 principal components, where TiMBL chooses a wide range of numbers, and generally far lower than is optimal.

We expect that the performance with TiMBL can be improved greatly with the development of a better hyperparameter selection mechanism. For the bigrams Figure 2 , we see much the same picture, although there are differences in the details. SVR now already reaches its peak TiMBL peaks a bit later at with And LP just mirrors its behaviour with unigrams.

LP keeps its peak at 10, but now even lower than for the token n-grams However, all systems are in principle able to reach the same quality i. Even with an automatically selected number, LP already profits clearly Recognition accuracy as a function of the number of principal components provided to the systems, using token bigrams. And TiMBL is currently underperforming, but might be a challenger to SVR when provided with a better hyperparameter selection mechanism. We will focus on the token n-grams and the normalized character 5-grams.

As for systems, we will involve all five systems in the discussion. However, our starting point will always be SVR with token unigrams, this being the best performing combination. We will only look at the final scores for each combination, and forgo the extra detail of any underlying separate male and female model scores which we have for SVR and LP; see above. When we look at his tweets, we see a kind of financial blog, which is an exception in the population we have in our corpus.

The exception also leads to more varied classification by the different systems, yielding a wide range of scores. SVR tends to place him clearly in the male area with all the feature types, with unigrams at the extreme with a score of SVR with PCA on the other hand, is less convinced, and even classifies him as female for unigrams 1.

Figure 4 shows that the male population contains some more extreme exponents than the female population. The most obvious male is author , with a resounding Looking at his texts, we indeed see a prototypical young male Twitter user: From this point on in the discussion, we will present female confidence as positive numbers and male as negative.

Recognition accuracy as a function of the number of principal components provided to the systems, using normalized character 5-grams. All systems have no trouble recognizing him as a male, with the lowest scores around 1 for the top function words. If we look at the rest of the top males Table 2 , we may see more varied topics, but the wide recognizability stays.

Unigrams are mostly closely mirrored by the character 5-grams, as could already be suspected from the content of these two feature types. For the other feature types, we see some variation, but most scores are found near the top of the lists. Feature type Unigram 1: Top Function 4: On the female side, everything is less extreme. The best recognizable female, author , is not as focused as her male counterpart. There is much more variation in the topics, but most of it is clearly girl talk of the type described in Section 5.

In scores, too, we see far more variation. Even the character 5-grams have ranks up to 40 for this top Another interesting group of authors is formed by the misclassified ones. Taking again SVR on unigrams as our starting point, this group contains 11 males and 16 females. We show the 5 most Confidence scores for gender assignment with regard to the female and male profiles built by SVR on the basis of token unigrams.

The dashed line represents the separation threshold, i. The dotted line represents exactly opposite scores for the two genders. Top rankingfemales insvr ontokenunigrams, with ranksand scoresforsvr with various feature types. Top Function 9: With one exception author is recognized as male when using trigrams , all feature types agree on the misclassification.

This may support ourhypothesis that allfeature types aredoingmore orlessthe same. But it might alsomean that the gender just influences all feature types to a similar degree. In addition, the recognition is of course also influenced by our particular selection of authors, as we will see shortly.

Apart from the general agreement on the final decision, the feature types vary widely in the scores assigned, but this also allows for both conclusions. The male which is attributed the most female score is author On re examination, we see a clearly male first name and also profile photo.

However, his Twitter network contains mostly female friends. This apparently colours not only the discussion topics, which might be expected, but also the general language use. The unigrams do not judge him to write in an extremely female way, but all other feature types do. When looking at his tweets, we This has also been remarked by Bamman et al. There is an extreme number of misspellings even for Twitter , which may possibly confuse the systems models.

The most extreme misclassification is reserved for a female, author This turns out to be Judith Sargentini, a member of the European Parliament, who tweets under the 14 Although clearly female, she is judged as rather strongly male In this case, it would seem that the systems are thrown off by the political texts.

If we search for the word parlement parliament in our corpus, which is used 40 times by Sargentini, we find two more female authors each using it once , as compared to 21 male authors with up to 9 uses.

Apparently, in our sample, politics is a male thing. We did a quick spot check with author , a girl who plays soccer and is therefore also misclassified often; here, the PCA version agrees with and misclassified even stronger than the original unigrams versus. In later research, when we will try to identify the various user types on Twitter, we will certainly have another look at this phenomenon.

Are they mostly targeting the content of the tweets, i. In this section, we will attempt to get closer to the answer to this question. Again, we take the token unigrams as a starting point.

However, looking at SVR is not an option here. Because of the way in which SVR does its classification, hyperplane separation in a transformed version of the vector space, it is impossible to determine which features do the most work. Instead, we will just look at the distribution of the various features over the female and male texts. Figure 5 shows all token unigrams. The ones used more by women are plotted in green, those used more by men in red.

The position in the plot represents the relative number of men and women who used the token at least once somewhere in their tweets. However, for classification, it is more important how often the token is used by each gender.

We represent this quality by the class separation value that we described in Section 4. As the separation value and the percentages are generally correlated, the bigger tokens are found further away from the diagonal, while the area close to the diagonal contains mostly unimportant and therefore unreadable tokens.

On the female side, we see a representation of the world of the prototypical young female Twitter user. And also some more negative emotions, such as haat hate and pijn pain. Next we see personal care, with nagels nails , nagellak nail polish , makeup makeup , mascara mascara , and krullen curls. Clearly, shopping is also important, as is watching soaps on television gtst. The age is reconfirmed by the endearingly high presence of mama and papa.

As for style, the only real factor is echt really. The word haar may be the pronoun her, but just as well the noun hair, and in both cases it is actually more related to the Identity disclosed with permission.

And by TweetGenie as well. An alternative hypothesis was that Sargentini does not write her own tweets, but assigns this task to a male press spokesperson. However, we received confirmation that she writes almost all her tweets herself Sargentini, personal communication. Percentages of use of tokens by female and male authors. The font size of the words indicates to which degree they differentiate between the gender when also taking into account the relative frequencies of occurrence.

Spelling Bestuderen Inleiding Op B1 niveau gaan we wat meer aandacht schenken aan spelling. Je mag niet meer zoveel fouten maken als op A1 en A2 niveau.

We bespreken een aantal belangrijke. Understanding and being understood begins with speaking Dutch Begrijpen en begrepen worden begint met het spreken van de Nederlandse taal The Dutch language links us all Wat leest u in deze folder?

Als je een onderdeel. List of variables with corresponding questionnaire items in English used in chapter 2 Task clarity 1. I understand exactly what the task is 2. I understand exactly what is required of. Please use the latest firmware for the router. The firmware is available on http: Wouldn t it be great to create your own funny character that will give.

Dus ik durfde het niet aan om op de fiets naar. Quick scan method to evaluate your applied educational game light validation 1. Assessing writing through objectively scored tests: My family Main language Dit is de basiswoordenschat. Deze woorden moeten de leerlingen zowel passief als actief kennen.

Aim of this presentation Give inside information about our commercial comparison website and our role in the Dutch and Spanish energy market Energieleveranciers. Invloed van het aantal kinderen op de seksdrive en relatievoorkeur M. Eshuis Oktober Faculteit Psychologie en Onderwijswetenschappen.

Firewall van de Speedtouch wl volledig uitschakelen? De firewall van de Speedtouch wl kan niet volledig uitgeschakeld worden via de Web interface: De firewall blijft namelijk op stateful staan.

And especially truths that at first sight are concrete, tangible and proven. Om een realistisch beeld te krijgen van uw niveau,vragen we u niet langer dan één uur te besteden aan de toets. De toets bestaat uit twee. Wat kan je er mee? Hoe werkt het Gibbs sampling? Na de pauze Achterliggende concepten à Dirichlet distribu5e. Dutch survival kit This Dutch survival kit contains phrases that can be helpful when living and working in the Netherlands.

There is an overview of useful sentences and phrases in Dutch with an English. De bijsluiter in beeld Een onderzoek naar de inhoud van een visuele bijsluiter voor zelfzorggeneesmiddelen Oktober Mariëtte van der Velde De bijsluiter in beeld Een onderzoek naar de inhoud van een.

Woordenlijst bij hoofdstuk 4 de aanbieding reclame, korting De appels zijn in de a Ze zijn vandaag extra goedkoop. Hij woont helemaal a, zonder familie. Iris marrink Klas 3A. Ik kreeg als opdracht om een dagverslag te maken over Polen.

Whether they are a pair of sneakers, new mascara or the latest smartphone, they all seem to. Een chroma bestaat uit 4 zones. Uit elke zone is een bepaald kwaliteitsaspect.

Voeg aan het antwoord van een opgave altijd het bewijs, de berekening of de argumentatie toe. Don t you worry There s an eternity behind us And many days are yet to come, This world will turn around without us Yes all the work will still be done. Look at ever thing God has made See the birds above. But the Real Issue is: Ontpopping Veel deelnemende bezoekers zijn dit jaar nog maar één keer in het Van Abbemuseum geweest. De vragenlijst van deze mensen hangt Orgacom in een honingraatpatroon.

Bezoekers die vaker komen worden. Schrijf op wat je dan gaat doen. Alle opgaven hebben gelijk gewicht. Veronderstel dat de contante waarde van deze kasstroom gegeven wordt door P. Dit gebeurt bij het lectoraat. Vragenlijst in te vullen en op te sturen voor de meeloopochtend, KABK afdeling fotografie Questionnaire to be filled in and send in before the introduction morning, KABK department of Photography Stuur.

Veertien leesteksten Leesvaardigheid A1 Te gebruiken bij: Appel, Aerdenhout Verkoopprijs: Welke Engelse woorden hoor je? Please note that the Dutch version. Knelpunten in Zelfstandig Leren: Verliefd Savannah 11 Verliefd zijn is dat je iemand meer dan aardig vindt, eigenlijk véél meer dan aardig. Massimo 11 Dat je iemand ziet die je heel mooi vindt. Dan wil je gewoon bij haar zijn.

Dat is over twee dagen. Grammatica uitleg voor de toets van Hoofdstuk 1 Vraagzinnen: Je kunt in het Engels vraagzinnen maken door vaak het werkwoord vooraan de zin te zetten. Consumer survey on personal savings accounts April 04 GfK 04 Consumer survey on personal savings accounts April 04 Table of contents. Research findings GfK 04 Consumer. Wat is Interaction Design? Wat is interaction design? Designing interactive products to support the way people communicate and interact in their everyday and working lives.

Preece, Sharp and Rogers Mentaal Weerbaar Blauw de invloed van stereotypen over etnische minderheden cynisme en negatieve emoties op de mentale weerbaarheid van politieagenten begeleiders: British Journal of Ophthalmology ; Ik zag hier wel erg tegenop met 6 maanden zwangerschap zo,n lange reis.

Samenvatting voor onderwijsgevenden Laatst bijgewerkt op 25 november Nederlandse samenvatting door TIER op 5 juli Onderwijsondersteunende. Het functioneel ontwerp van de ilands applicatie voor op de iphone is gebaseerd op het iphone Human Interface Guidelines handboek geschreven door Apple Inc Deze flexibiliteit zorgt voor een zeer brede toepasbaarheid.

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Mijn vrouw wil neuken mollige geile meiden

During this Nadere informatie. Bitchcraft en The Bitch O'Clock News, die bestaan uit Live concert muziek en interviews plus een documentaire over hun communale leven. Artikel mist referentie sinds juli Wikipedia: Net s88sdn wordt dikkememmen verkrachting sex één van de L. The control shell then weighted each score by multiplying it by the class separation value on the development data for the settings in question, and derived the final score by averaging.

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