The Marketing Plan 2 Assignment Example | Topics and Well Written Essays - 2500 words

The Marketing Plan 2 - Assignment Example This is due to increased demand from young adults across the globe. Abundant experience in the energy drink market, red bull was founded in Austria in 1987 and since then has grown to be the world’s most popular energy drink. The red bull brand is known all over and the high energy it represents is a hit with consumers Recently there has been issues raised about the health effects of consuming energy drink and this might impact consumer purchases. People take keen interest in health and such news are received by alarm by the masses The emerging markets – there are developing countries in the world such as those in Africa and these provide a ready market for red bull products. There is an increase in purchasing power in these nations and the people are readily adopting global brands. A potential large target group – the target consumers for red bull are young people and young adults. This represents majority of the population and given that these numbers are growing the future looks positive for red bull. The use of energy drinks is gaining favour-in the past some people thought that energy drinks were alcoholic. But this is fast changing and the use of energy drinks is gaining favour among the general population. Below is a table showing the competitors of Red Bull and their market shares. Red Bull still has a lead in global market share but Monster is closely behind. In this regard, there should be a massive campaign so as to increase this lead (Ferrell, 2011). The key to success is offering customers a quality product that reflects a true value for their money. The Red Bull gives you wings are a popular phrase around the world and this should be used to maintain brand loyalty. The use of red bull has raised some controversy over the years. This is due to the caffeine content that is in the drink. Some countries have certain restrictions on the amount of

Pixel and Edge Based Lluminant Color Estimation

Pixel and Edge Based Lluminant Color Estimation Pixel and Edge Based Lluminant Color Estimation for Image Forgery Detection Shahana N youseph  and Dr.Rajesh Cherian Roy ABSTRACT Digital images are one of the powerful tools for communication. So Image security is a key issue when use digital images. With the development of powerful photo-editing software, such as Adobe Photoshop Light room 4, Apple Aperture 3, Corel PaintShop Pro X5, GIMP 2.8, photo manipulation is becoming more common. In this paper mainly detecting forged peoples in images. The main idea for the detection is, different images are captured under different illuminant condition, when combining these image fragments from different images, it is difficult to match the illumination conditions. This inconsistency of illumination leads to forgery detection. The main contribution of this method of forgery detection is how illuminant color can be used as a clue for forgery detection. The proposed method will be able to detect forgery using Linear SVM classification, with 70%-75% of accuracy. Keywords Pixel based illuminant color estimation; Edge based illuminant color estimation, I. INTRODUCTION Every day, millions of digital documents are produced by a variety of devices. They are distributed by newspapers, magazines, websites and television etc. In all these information channels, images are a powerful way for communication. It is not difficult to use computer graphics and image processing techniques to manipulate or to forge images. Video footage, scanned images, as well as digital and analogue images can be the target for manipulations. From a forensics perspective, several changes in a photograph are widely acceptable for improve the quality of images, e. g. to enhance the contrast, denoise an image, or highlight important regions etc.Forensics Science is a department for criminal investigation in distinct areas such as digital forensics, analogue forensics, multimedia forensics, network forensics etc.Image Forgery is the process of creating doctored/fake images, with the development of advanced image processing software’s such as Adobe Photoshop Light room 4, App le Aperture 3, Corel PaintShop Pro X5, GIMP 2.8 etc forgeries in images is easy process. Image Forgery detection is Active and Passive. Digital watermarking is an example of active. The passive image forgery detection is a blind approach, which means it does not have any prior knowledge of input image. There are various methods used for the checking of authenticity of images. In this paper the method used is based on illumination. When light fall on an object color of the object is reflected, depends on illuminant color/light color. Objects having different color in different illumination condition. So when we forge an image or making composite of various images it is very difficult to maintain the consistency of illumination. Illumination is one of the criteria for forgery detection. Some other criteria’s are used for passive image forgery detection such as, JPEG compression properties, Projective geometry, Chromatic aberration, Color filter array (CFA) and inter pixel corre lation etc. Literature Survey Table1. Illuminant Color Based methods Proposed Method First step is cropping face of the input image. This proposed method is mainly detecting forged peoples in an image. The estimation of the illuminant color is error-prone and it is affected by the materials in the scene, the illuminant color estimates on objects of similar material exhibit a lower relative error.Thus,the illuminant color detection to skin, mainly to faces. Pigmentation is the most obvious difference in skin characteristics. Second step is illuminant colour estimation, explained in next section. Fourth step is generation of illuminant map. Image is segmented with graph cut segmentation. Illuminant color is estimated using static methods on each segmented output with same index number. Based on the estimated illuminant color, apply it for the segments with same index number. The resulting output will be RGB components. This coloured representation of image with R G B components is termed as Illuminant Map. Fifth step is shape and colour feature extraction. For shape fe ature HOG Edge feature is used. An edge of illuminant map is extracted using various edge detection methods. Histogram of Oriented Gradients of edge points. For colour feature extraction. Colour Moments feature is used. Moments with first and second moments are extracted. Last step is SVM classification. Classify the illumination for each pair of faces in an image as either consistent or inconsistent. Assuming all selected faces are illuminated by the same light source, Train the SVM with two class with one class is for forged image and other for original image.When testing operation performed based on the test feature value image is classify either forged or original. ILLUMINANT COLOR ESTIMATION Pixel Based Illuminant Color Estimation Pixel values of the entire are taken for illuminant color estimation. In this methods focussed on low level features. Such as Grey World, Max-RGB, Shades of grey. Simple and less complex calculation is used for the estimation, with the help of some static variables. So it is also known as static illuminant color estimation. Grey World Hypothesis: In Grey World, Illuminant color is estimated from Average Pixel values of images. Under a neutral light source or white light source, Average reflectance of the entire image is achromatic (Having no colors), if any deviation from this condition is due to color of illumination. This average reflected color will be the color of the light source. Max-RGB Hypothesis: In Max-RGB, illuminant color estimated from maximum response of Red Green Blue (RGB) channel. Maximum response is obtained from perfect reflectance. A surface having perfect reflectance property will respond (reflect) for the full range of light colors it captures, when light incident on it. Then this reflected color is actually the color of light source. Shades of Grey: Grey world and the max-RGB illuminant color estimation in terms of Minkowski norm, is called shades of gray. , If p=1 Grey World Estimation If p=∞ Max-RGB Estimation If p=6 Shades of Grey Estimation Edge Based Illuminant Color Estimation Edge based illuminant color estimation is use low or higher order derivatives. In this methods edges and colors towards illuminant direction. In order to accurately estimate color of light source is use the pixel and edge points that coincide the illuminant direction. Highlights produce such types of points. In edge based estimation contains Grey edge and Weighted Grey edge estimation are used. In Weighted grey edge methods, using some weighting fuction to the edges. For that classifying the edges based on the photometric properties, material edges (e.g. edges between objects and object-background edges), shadow/shading edges (e.g. edges caused by the shape or position of an object with respect to the light source) and specular edges (i.e. highlights).These edges perform better influence on illuminant estimation. In Weighted Grey edge methods computing weighted average of edge points. The iterative weighting scheme is proposed, and by assigning this weighting scheme in to the grey ed ge method, the color of the light source is estimated. Edge based illuminant color estimation mainly contain, †¢ First Order Grey Edge †¢ Second Order Grey Edge †¢ Weighted Grey Edge First Order Grey Edge: The pth Minkowski norm of the first derivative of the reflectance in a scene is estimated. Computed by, Second Order Grey Edge: The pth Minkowski norm of the second derivative of the reflectance in a scene is estimated. Weighted Grey-Edge: Weighted Grey-Edge algorithm is computed by assigning a weighting function to the illuminant estimate. This weighting function is estimated by classifying edges based on the photometric properties and an iterative edge weighting scheme is generated. †¢ Derivative order x: the assumption that the average of the illuminants is achromatic can be extended to the absolute value of the sum of the derivatives of the image. †¢ Minkowski norm p: instead of simply adding intensities or derivatives, respectively, greater robustness can be achieved by computing the p-th Minkowski norm of these values. †¢ Gaussian smoothing ÏÆ': to reduce image noise, one can smooth the image prior to processing with a Gaussian kernel of standard deviation. Specular Edge Weighting scheme: Specular weighting scheme is the ratio of the energy in the specular variant versus the total amount of derivative energy. This ratio translates to the specular edge weighting scheme given by: , where , Results To check the accuracy of forgery detection using SVM classifier with SVM is trained with 50 forged and 50 original images and SVM is tested using total of 50 images where 25 are original and 25 are composite images downloaded from different websites in the Internet.SVM is trained several times for several testing process. First set of forgery detection testing is done with various illuminant estimation methods such as Grey World, MAX-RGB, Shades Of Grey and Grey Edge First and Second Order and weighted grey edge with shape feature and color feature extraction separately. In shape feature called HOG Edge use various edge detection methods such as Canny, Roberts, Prewitt, and Sobel for the comparative study. And finally the combination of color moment and HOG Edge is tested for forgery detection. Confusion matrix is generated accuracy is calculated. Accuracy=TP+TN/(TP+TN+FP+FN) Where, True Positive (TP) input-Forged, Output-Forged True Negative (TN)- input-not forged ,output-not forged False Positive (FP) -input-forged, output-not forged False Negative (FN)-input-not forged, output-forged . Table 2. Estimated Accuracy Of fogery detection with Various Illuminant Color Estimation Methods From the above result, when using all static illuminant color estimation method for forgery detection Weighted grey edge peform well when compare with other methods. Feature extraction used is HOG Edge and Color moments features for shape and color feature extraction. If use one feature extraction method only get 50%-64% of accuracy. If use combined HOG Edge and Color Moments features accuracy is improved to 66%-74%. Conclusions Presented a new method for detecting forged images of people using the illuminant color Estimation. Estimate the illuminant color using Pixel and Edge based Illuminant estimation method, and generation of illuminant map. Canny edge detector are used to obtain edges of illuminant map for the extraction of shape features using HOG Edge descriptor, which is used to get Histogram of oriented Gradients of edge points. For color feature extraction use color moments features. These two features are tested separately with different illuminant estimation method for the comparative study. Combination of these two features is also used for forgery detection for the comparative study.From the result it is clear that combined HOG Edge and color features get more accuracy than method used shape and color features separately.Accuracy is Estimated using SVM Classifier.The Combined feature extraction with Weighted grey edge testing process get 74% of accuracy. The proposed method requires only a mini mum amount of human interaction and provides a crisp statement on the authenticity of the image. Additionally, it is a significant advancement in the exploitation of illuminant color as a forensic cue. Prior color-based work either assumes complex user interaction or imposes very limiting assumptions. FUTURE WORK The accuracy of the classification can be improved by using adding more content based features. Use of training based illuminant color estimation also improves accuracy. References [1] Hany Farid ,à ¢Ã¢â€š ¬-Image Forgery Detection [A survey]à ¢Ã¢â€š ¬-, IEEE signal processing magazine March- 2009 [2] C. Riess and E. Angelopoulou, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Scene illumination as an indicator of image manipulation,à ¢Ã¢â€š ¬- Inf. Hiding, vol. 6387, pp. 66–80, 2010. [3] Gajanan K. Birajdar ,Vijay H. Mankar ,à ¢Ã¢â€š ¬-Digital image forgery detection using passiv techniques: A surveyà ¢Ã¢â€š ¬-Elsevier 2013 . [4] J. van de Weijer, T. Gevers, and A. Gijsenij, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Edge-based color constancy,à ¢Ã¢â€š ¬- IEEE Trans. Image Process., vol. 16, no. 9, pp. 2207–2214, Sep. 2007. [5] M. Johnson and H. Farid, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Exposing digital forgeries by detecting inconsistencies in lighting,à ¢Ã¢â€š ¬- in Proc. ACM Workshop on Multimedia and Security, New York, NY, USA, 2005, pp. 1–10. [6] Yingda Lv Xuanjing Shen Haipeng Chen, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢An improved image blind identification based on inconsistency in light source directionà ¢Ã¢â€š ¬- in Springer Science+Business Media, LLC 2010 [7] M. Johnson and H. Farid, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Exposing digital forgeries in complex lighting environments,à ¢Ã¢â€š ¬- IEEE Trans. Inf. Forensics Security, vol. 3, no. 2, pp. 450–461, Jun. 2007 [8] M. Johnson and H. Farid, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Exposing digital forgeries through specular highlights on the eye,à ¢Ã¢â€š ¬- in Proc. Int. Workshop on Inform. Hiding, 2007, pp. 311–325. [9] E. Kee and H. Farid, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Exposing digital forgeries from 3-D lighting environments,à ¢Ã¢â€š ¬- in Proc. IEEE Int. Workshop on Inform. Forensics and Security (WIFS), Dec. 2010, pp. 1–6. [10] W. Fan, K. Wang, F. Cayre, and Z. Xiong, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢3D lighting-based image forgery detection using shape-from-shading,à ¢Ã¢â€š ¬- in Proc. Eur. Signal Processing Conf. (EUSIPCO), Aug. 2012, pp. 1777– 1781. [11] E. Kee and H. Farid, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Exposing digital forgeries from 3-D lighting environments,à ¢Ã¢â€š ¬- in Proc. IEEE Int. Workshop on Inform. Forensics and Security (WIFS), Dec. 2010, pp. 1–6. [12] S. Gholap and P. K. Bora, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Illuminant colour based image forensics,à ¢Ã¢â€š ¬- in Proc. IEEE Region 10 Conf., 2008, pp. 1–5. [13] X.Wu and Z. Fang, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Image splicing detection using illuminant color inconsistency,à ¢Ã¢â€š ¬- in Proc. IEEE Int. Conf. Multimedia Inform. Networking and Security, Nov. 2011, pp. 600– [14] P. Saboia, T. Carvalho, and A. Rocha, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Eye specular highlights telltales for digital forensics: A machine learning approach,à ¢Ã¢â€š ¬- in Proc. IEEE Int. Conf. Image Processing (ICIP), 2011, pp. 1937– 1940. [15] C. Riess and E. Angelopoulou, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Physics-based illuminant color estimation as an image semantics clue,à ¢Ã¢â€š ¬- in Proc. IEEE Int. Conf. Image Processing, Nov. 2009, pp. 689–692. [12] S. Gholap and P. K. Bora, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Illuminant colour based image forensics,à ¢Ã¢â€š ¬- in Proc. IEEE Region 10 Conf., 2008, pp. 1–5. [16] K. Barnard, V. Cardei, and B. Funt, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢A comparison of computational color constancy algorithms–Part I: Methodology and Experiments With Synthesized Data,à ¢Ã¢â€š ¬- IEEE Trans. Image Process., vol. 11, no. 9, pp. 972–983, Sep. 2002. [17] K. Barnard, L. Martin, A. Coath, and B. Funt, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢A comparison of computational color constancy algorithms – Part II: Experiments With Image Data,à ¢Ã¢â€š ¬- IEEE Trans. Image Process., vol. 11, no. 9, pp. 985–996, Sep. 2002. [18] A. Gijsenij, T. Gevers, and J. van deWeijer, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Computational color constancy: Survey and experiments,à ¢Ã¢â€š ¬- IEEE Trans. Image Process., vol. 20, no. 9, pp. 2475–2489, Sep [19] P. F. Felzenszwalb and D. P. Huttenlocher, à ¢Ã¢â€š ¬Ã¢â‚¬ ¢Efficient graph-based image segmentation,à ¢Ã¢â€š ¬- Int. J. Comput. Vis., vol. 59, no. 2, pp. 167–181, 2004

Lyrical Violence :: essays research papers

Lyrical Violence Music is a prominent force in adolescent lives; according to the American Medical Association, American adolescents spend a total of four and a half hours a day listening to music and watching music videos. Parents are increasingly weary of suggestive, violent, lyrical content in popular music. A University of California study recently showed that 48% of Americans, including the younger generation, say that violence in popular music should be regulated. In Paducah, the affect of violent lyrical content in popular music has been an ongoing debate since the Heath High School shooting. Another case of a school shooting has shook up a small town in Arkansas called Jonesboro. One of the teen murderers admitted to law enforcement officers that the rap music he listened to might have contributed to his state of mind before the murders, if not his overall decision to gun down his classmates. Mitchell Johnson, the student, said, â€Å"It puts you in a certain state of mind.† This is not only relevant to the music/violence debate but it is a crucial element in understanding what is going on with the modern youth. Clearly, it can not be stated that the sole contributing factor in the student’s decision to commit murder was rap music; but it was a contributing factor. I b elieve that there is a painful and direct correlation between violence in popular music and violence in youth. I do not believe that government regulation, or censorship, is going to fix this problem. For those who debate the adverse effect of violent music on a person’s mind-state, I offer this example. In the early days of jazz, African-Americans would listen to, and play, the music as a release from the racial climate in which they lived. The music, if only for a while, removed their problems. This being the case, how can we deny that music, even without lyrics, has an overwhelming impact on our mind-state. Popular music affects everyone. Some people find that they can’t get a song out of their head after hearing it on the way to work. Other individuals discover that they get sentimental if they hear a song which they danced to at their prom. At funerals, people are brought to tears at the first note of Amazing Grace. While there are almost always other reasons behind the emotion, it is the music that triggers that particular mind state.

The Ira

The Irish Republican Army or IRA is Northern Ireland’s most notorious terrorist organization. Like many other groups, the IRA is a militant nationalist group with Marxist tendencies. They use violent attacks such as bombings, assassinations, kidnappings, extortion, and robberies that they used . to send their message. The ultimate goal of the IRA is to use militant behavior to make British rule in Northern Ireland obsolete, thus letting Northern Ireland become an independent republic, instead of two separate countries with different governments.The IRA was founded in 1919 as a successor to the Irish Volunteers, a militant nationalist organization that was founded in 1913. One of the alias’s for the group is Direct Action Against Drugs, or DADD. The IRA operates independently of any political control or party, and† in some periods actually took the upper hand in the independence movement. †(Britannica) Unlike some terrorist groups, the IRA does not carry out attacks on countries that are not in close vicinity of Northern Ireland. The majority of their operations are based out if Great Britain, and Ireland.Some of their most favored targets were senior British Government officials, British military and police in Northern Ireland, and Northern Irish Loyalist paramilitary groups. By attacking these individuals they hoped to demoralize Great Britain to the point of turning Ireland over to the people. The IRA did not want to overthrow the government and run it themselves, they simply wanted to see a change in the government so that it would benefit the people of Northern Ireland. The IRA is organized into small, tightly knit cells under the leadership of the Army Council.While they only have a few hundred members, they have thousands of sympathizers who contribute by donating money, supplies, shelter, and even weapons. â€Å"The IRA Is suspected of receiving funds, arms, and other terrorist-related materiel from sympathizers in the United S tates. †(Britannica) the IRA also received a large amount of support at one point from the PLO, a â€Å"freedom fighter† group from Libya. Not only do they receive aid from other terrorist groups with similar agendas, but in 2002 three suspected IRA members were arrested in Colombia on charges of assisting the FARC to improve its explosives capabilities.The IRA was in their prime during the late 1950’s and 1960’s, though they did play a big part in the Irish Civil war of 1922. As a result of this war, the IRA became more closely related to Sinn Fein, which is the Irish Nationalist party. â€Å"In December 1969, the IRA divided into â€Å"Official† and â€Å"Provisional† wings. Although both factions were committed to a united socialist Irish republic, the Officials preferred parliamentary tactics and eschewed violence after 1972, whereas the Provisionals, or â€Å"Provos,† believed that violence— particularly terrorism—w as a necessary part of the struggle to rid Ireland of the British. (Global Security) This was a result of a Sinn Fein conference that had taken place in August.After 1970, the IRA was slowly slipping into the darkness, as they had stopped attacking as much, and was not as big of a concern anymore. Because of â€Å"Bloody Sunday’, when thirteen innocent Catholic protestors were killed by British soldiers, the IRA gained support from the Catholic Church, which gave them their reputation back for a while. Eventually though, they were back where they had left off before Bloody Sunday. The IRA reorganized in 1977 into detached cells to protect against infiltration† and their arms dealing was back in full force. It was said that â€Å"in the late 1990s that the IRA had enough weapons in its arsenal to continue its campaign for at least another decade. †(Britannica) For a long time the IRA tried to use peaceful methods to gain equal treatment for the Catholic minority in the Protestant Northern Ireland. But they were were met with resistance. The Protestants and the British government met the peaceful attempts of the IRA with violence i. e. Bloody Sunday.The IRA had no other choice but to employ violent methods to gain equality and civil rights for the Catholic Minority in Ulster. The IRA began implementing methods such as Bombings, sniper attacks, and assassinations on British citizens. (www. CFR. org) The afore mentioned Sinn Fein, which means â€Å"We Ourselves† first emerged in the early 1900s. It is the oldest political party in Ireland’s history. It was a â€Å"federation of nationalist clubs and eventually, all nationalists to the left of the Irish Parliamentary Party at Westminster came to be popularly known as Sinn Feiners. (SinnFein. org) The party, like the IRA, was based on the demand for an Irish Republic. It won the 1918 election by a landslide and set up Dail Eireann which is translated to â€Å"Assembly of Ireland. † Following three years of war, led by an underground republican government, the party split in 1922 on the issue of the Treaty which partitioned Ireland into two separate provinces. The leader of Sinn Fein left the party in 1926, causing the party to lose a lot of credibility.However, its fortunes recovered and flourished in the late 1950s and early 1960s with its new association to the IRA and their border campaign. During this time the group experienced a substantial amount of electoral success. In present day, Sinn Fein is split into two parties, Sinn Fein and Republican Sinn Fein. The Provisional Irish Republican Army (PIRA) was formed in 1969 as the covert armed wing of Sinn Fein. The members of this group, called, â€Å"Provos† were formed from the Official Sinn Fein and the Official IRA.The Provisional IRA was the largest of the three republican armed resistance groups (Sinn Fein, IRA and PIRA). The policies of Sinn Fein under the new leadership of Gerry Adams led to a split in the Provisional Irish Republican Army in 1997. One side accepted the new â€Å"Good Friday Agreement† and the New or Real IRA continuing armed resistance against the British. The PIRA has at this point accepted the ceasefire and is still most commonly confused with the real IRA because of their similar connections and name.The IRA and PIRA are not totally different groups, but they are actually two groups that used to function as one. It is my opinion that the split of the IRA into two factions is one of the major reasons why their goal was never accomplished. The army was in need of a way to make money and fundraise to support their cause. They became adept at raising money in Northern Ireland through â€Å"extortion, racketeering, and other illegal activities† and they policed their own neighborhoods through mock trials and beatings.As a result of this Mafia like enforcement, Sinn Fein began to play a more prominent role in trying to end the arms pr oblem that the IRA was causing. â€Å"Sinn Fein leaders Gerry Adams and Martin McGuiness, together with John Hume, head of the Social Democratic and Labour Party (SDLP), sought ways to end the armed struggle and bring republicans into democratic politics. They were successful in doing so, and in 1994 the IRA declared a cease fire with Britain so that Sinn Fein was able to legally engage in politics with the Irish Parliament.This ceasefire was shortly ended in 1996 when a bomb that was suspected to be from the IRA killed two civilians. However it was reinstated the following year, returning things back to being civilized between the IRA and Great Britain. Technically the IRA is still a functioning terrorist group, but due to the ceasefire they have been dormant since around 2002 when the final ceasefire was laid out and agreed upon. The IRA has a very important place in Irish history, as well as the history of terrorism because of their prominence in the 1950’s and 1960â€⠄¢s.

A Creative Response to Belonging

Ryan’s Story – Untitled so far You stay in your room like a locked away Rapunzel. Well not locked in fact – matter of the choice rather. It’s like fiery dragons attack you every time you attempt to escape your temple. You study, you work, study again, read some, then you study some more. It’s the same repetitive routine throughout your days between the same four egg-white walls. ‘No common sense! ’ you are told. ‘None what-so-ever’, burns your delicate skin. What are you supposed to do? Visit the Wizard of Oz and ask for a glass brain? Or maybe obsess with Thomas Paine for a week or two? No, only the flame throwers presented at the exit is awaiting your so called ‘enlightenment’ – and even the pain isn’t crossed knuckles with humiliation. You feel trapped but simultaneously free – free from any such connection with the fire you have been accustomed to or rather such societal dictatorship controlling your every thought, presenting a more confused, liberated Rapunzel. You are somewhat connected with surrounding people despite the closed door. An interconnected spider’s web comes to mind, perhaps behind a series of branches and scuffled leaves. Even though you are somewhat acquainted with these people, you can never seem physically ‘connected’ with them. Maybe it’s the closed door? Or maybe it’s the fact that you over-analyse everything until the point where self-disappointment slaps your red hard across the face. All you want is to be alone, far from what these people think, but yet want to be a part of the envious spider’s web large enough for your contribution but possibly not strong enough. You think of a similar case of Emily Dickinson. She wants to post her letter, she wants to publish her poetry but in the end she doesn’t because of fear. Fear of what other people may think if it, ever so lonely in her secluding room. That similar closed door painful to think about, but comforting to realise collectively. What people think of you, it’s a scary thought really. What thoughts scatter around in other’s brains, without your control or prejudice. You look outside your window, rather similar to the day before. A sky filled with cloud secluding the sun’s precious touch. The lime tree half dying, half growing in the midst of an insect infested environment. The green grass connected to the thin line of stalk, reaches higher to the sky then your window does, awkwardly enough. You refrain from such a scene and reach back into one of your books awaiting another life far from here – rather to the City of Invention you are peculiar about. If ever you yourself were to write a novel, short story, poem, script or anything of the sort – it would be one of such power and profit. The antagonist would be a devilish character, somewhat misunderstood in more ways than one Then maybe your dragons could have spot for fame – a Rocky Horror show without the horror†¦Ã¢â‚¬ ¦. wait, maybe with the horror as well. The devilish character’s name would be Thomothius, Thom for short. He would attempt to escape the cannibalistic village he was forced to inhabit. A woman, always admired by Thom would stop him in his tracks and lure him underground. There she would drill question upon answer into Thom’s poor glass brain until Thom were to surface again as a farfetched Steven King character. From this point in time, villagers notice this strange happening and fear for their lives. (Cannibals fearing their lives, who could imagine? ) The King and Queen Dragonheart would encompass their power upon the false notions of their people and hang poor Thom for the villagers to see like the mouldy and grass infested socks pegged to the clothes line in the corner of your window. This of course will create peace and prosperous tranquillity to roam around the various blood-stained streets, never really understanding what evil was present. Not really profitable when rethought about. Here you fall out of this novel and back into the silent pages you hold. Your silent tear will continue to rise like condensation, above all morals and belief that confide in your pride. From this, what is needed to be understood? It is that you will not find your Mr Darcy stuck between the space between your window and your room. It is that you will not have a happy ending unless you face your demons, or in this case dragons. Yet you remain silent in your room, thinking of how this Thom could be the only person you can really connect with.