High Luxury Fashion Management Essay

High Luxury Fashion Management Essay High Luxury Fashion Management Essay High Luxury Fashion Management Essay This paper compares two high-end fashion stores based on various aspects. The fashion stores chosen are Saks Fifth Avenue and Bergdorf Goodman. For better comparison, a shoe brand and a handbag brand have to be chosen and compared respectively. The shoe brand chosen is Valentino sneakers. Both Saks and Bergdorf offer Valentino sneakers in their stores. However, Bergdorf offers more floor space to the shoe brand compared to Saks. For the type of counter space employed, both stores are the same. Each store uses the shoe-in-glass design of counter space. Given the higher amount of floor space given to Valentino sneakers by Bergdorf, the store offers more types of the sneakers than Saks. In fact, Bergdorf offers all the available types of Valentino sneakers . The materials and fabrications used in both stores more or less depend on the brand of shoes. The standard materials used include soft leather, synthetic leather, and canvas. There are more types of shoes in Bergdorf than Saks. To be specific, Bergdorf offers all types of low-top sneakers as opposed to Saks. Saks mostly offers rockrunner sneakers. While Saks favors bright colors of sneakers such as white and gray, Bergdorf offers sneakers of all colors in equal amounts. The prices of the shoes are similar in both stores. However, each store seems to have a different price structure depending on demand for a specific type of shoes. The low-top sneakers are the most favored given that they are light and comfortable to wear in the city. In summary, Saks and Bergdorf are direct competitors as far as sneakers are concerned. They offer similar products to the same group of people. However, Valentino sneakers are more demanded in Bergdorf as evidenced by the bigger space provided to the bra nd. As for the handbags, Bottega Veneta handbags were chosen for comparison purposes. Bottega Veneta is a premium brand offering a wide range of fashion items. When comparing the two stores, it was found that Bergdorf Goodman offers 142 types of handbags compared to only 50 by Saks Fifth Avenue. Bergdorf, therefore, gives more space to the handbag brands. Like in the case with the shoes, Bottega Veneta handbags in both stores are put behind clear glass to be easily viewed by customers. Bergdorf presented all the major product presentation styles including giving of offers on certain handbags. The only type of offer given in Saks was that of buying three bags at the price of two. The bags found in Bergdorf are made of faux fur, leather and suede, linen, polyester fabrics and their blends, rayon, silk, tapestry, velvet, and velveteen. Saks did not have bags made of rayon and velvet. Bergdorf offered, among many other styles, A-shaped woven tote bags and small pillow woven cross body bags. Saks focused more on hobo bags. Both stores, however, focused on the major feminine colors such as pink, beige, blue and black in their various versions. The color emphasis did not make a big difference between the stores. The price structure was based more on the manufacturer (or designer) than on a particular store. However, given that both stores offered products to the upper class, the prices were relatively higher than bags of other brands offered in other stores. Both Saks and Bergdorf offer high-quality products and customer services. They also ship goods to locations outside the United States. They both record high levels of customer demand given that New York has the highest concentration of high-class people. Besides the differences in the amount of floor space given to each premium brand, both stores have almost similar methods of presentation of their products. Having visited the two stores, it was concluded that Bergdorf had a bigger selection of both Bottega Veneta Handbags and Valentino sneaker shoes as compared to Saks. However, Saks had better customer service. First of all, Bergdorf Goodman has a bigger store in general in New York. Thus, it can afford to give more space to both Bottega Veneta Handbags and Valentino sneaker shoes. Besides, the two brands are among the most sought after in the luxury fashion realm. Though not based on facts, Bergdorf can be said to be making more from its sales of Bottega Handbags and Valentino sneakers. Of the two items selected, the most demanded items in both stores are Bottega Veneta handbags. The handbags are favored for their high quality and unique design. In both stores there were more loyal and return customers in regard to handbags as com pared to Valentino sneakers The presentation of the two products, as stated above, is almost similar. Bottega Veneta handbags and Valentino sneakers are placed in glass stands. An interested customer can ask to touch the products as a way of deciding whether he/she wants to buy them or not. Besides, some highly-priced handbags had offers attached to them to encourage customers to buy them. During a conversation, a department manager stated that Valentino low-top sneakers were highly favored for various reasons. First of all, they were fairly priced. Secondly, they were light as city life requires brisk walking. Thirdly, they lasted long and could be used for various purposes such as jogging and days out with families. The reason why Saks is considered to have better customer service was that while at the store, a sales associate approached the author asking if she could be of any help. The author took that opportunity to gauge the real quality of customer service in the store. First of all, there were no signs of discrimination against customers in the store as far as their appearance was concerned. In some other luxury stores, prejudgment is made based on the customers` appearance; if a customer is poorly dressed, it could be assumed that he/she is not be able to afford items being sold. Saks (as well as Bergdorf) had none of that. The sales associate in Saks asked questions and answered mine in the politest manner possible. The author endeavored to ask about the types of celebrities who frequented the store regularly. The sales associate stated that they served some famous people including hip hop musicians like Jay-Z and J Cole. They also serve movie actors and actresses the most recent of whic h were Idris Elba and Kate Beckinsale starring at the Pacific Rim and Underworld respectively. Given the chance to improve the two stores, the author would majorly increase the campaign advertisements to have a bigger customer base. However, these advertisements should be made cautiously given that premium fashion brands are cheapened whenever they are advertised too much. Besides, it is advisable that the two stores expand their international reach given that rich people have no problem spending a lot of money as long as the product is of high quality. Saks should also endeavor in offering more products either by replacing the poorly-performing brands or opening more stores to offer all the products available. In conclusion, both Bergdorf Goodman and Saks Fifth Avenue are among the best fashion stores around the world. Valentino Garavani was born on May, 11th 1932 in Voghera, Italy. Fashion design was his passion from a young age. He studied it until he started his personal line of clothes in 1959 in Rome. A few years later, thanks to his distinctive talent he became one of the most recognized cloth designers in the world. He became the most favorite designer of many women around the world. One of his most famous customers was Jacqueline Kennedy, the wife of the 35th president of the United States (John Fitzgerald Kennedy). Others include Elizabeth Taylor, Marie-Helene de Rothschild, Queen Paola of Belgium, Begum Aga Khan, and Audrey Hepburn. One of Valentino’s early influencers was his aunt Rosa under whom he worked. Besides her, Valentino worked under several other local designers before his formal training in Paris (Chambre Syndicale de la Couture Parisienne and Ecole des Beaux-Arts). His had an apprenticeship with Guy Laroche and Jean Desses before he embarked on a personal career. Howev er, Valentino`s first choice for an apprenticeship was Jacques Fath and then Balenciaga. He attested to have learned a lot from his masters as observed from his borrowing of a few ideas from his teachers. Valentino is famous for a distinctive shade of red color known as â€Å"Valentino Red†. Valentino left Jean Desses under controversial circumstances and endeavored to make a name for himself in 1959 in Rome. A part of his success is attributed to his first partner Giancarlo Giammetti. Giametti was an architecture student who helped Valentino build his brand and distinctive â€Å"Valentino Red†. Valentino gained popularity after having participated in a show in Florence in the Pitti Palace. The show made him famous among the rich and the famous. He quickly became the summit of Italian fashion design. When Valentino moved to New York in the 1970s, he had effectively expanded into the American market following his high profile clients in America. Before his retirement, Valentino had various names under his original house. They included Valentino R.E.D., Valentino Roma, Valentino and Valentino Garavani. All names represent a part of his line of wares serving a specific mark et. Currently, Valentino is interested in shoes, bags and belts. As a result, Valentino is a household name. Valentino’s life is very interesting. Now aged 82, Valentino met his wife in 1950 but separated from her in 1972. However, they remained close and maintain homes in various countries including France, Spain and Switzerland. Valentino and Giammetti have filed their homes with art given that it is their ultimate passion. In 1998, Giammetti and Valentino announced their retirement from the fashion industry. They did this by selling off their company for around $300to HdP, an Italian conglomerate. Four years later, HdP sold the company to Marzotto Apparel. The changes in ownership were overseen by Valentino himself since his advice is considered invaluable. As a special way to say goodbye to the fashion industry, Valentino organized a final haute couture in Paris at the Musee Rodin in January 2007. It featured such household names as Eva Herzigova, Claudia Schiffer, and Naomi Campbell. All in all, Valentino’s lines of clothes and shoes have become a household name among the rich and the famous all around the world. Italy is famous for luxury. To make a name in such a market in the same way as Valentino did requires talent and dedication.

The Most LGBTQ-Friendly Colleges in The Country

The Most LGBTQ-Friendly Colleges in The Country SAT / ACT Prep Online Guides and Tips In general, colleges are consistently becoming more LGBTQ (Lesbian, Gay, Bisexual, Transgender, and Queer) friendly. Young people are more accepting of different sexual orientations and gender identities, and those attitudes are reflected at a growing number of US colleges. However, there are still many college campuses that have reputations for not being inclusive or safe for members of the LGBTQ community. If it's important to you to be at a school with a vibrant LGBTQ community, you should consider looking at specifically LGBTQ-friendly schools. In this article, I'll do the following: Define an LGBTQ-friendly school Explain why you should consider an LGBTQ-friendly college Provide lists of LGBTQ-friendly colleges and universities Give advice for how to use those lists and do effective research to determine if a school is LGBTQ-friendly What Is an LGBT-Friendly College? An LGBT-friendly college makes its LGBTQ students feel safe, accepted, and comfortable on campus. It offers plentiful resources to provide support and counsel for LGBTQ students. Furthermore, the students at LGBTQ-friendly colleges are accepting and supportive of members of the LGBTQ community. LGBTQ students feel at ease expressing themselves around non-LGBTQ students, and the student body treats LGBTQ students with tolerance and respect. If you're looking for specific orientations like gay friendly colleges, generally colleges that I say are LGBTQ-friendly are gay friendly as well. Why Should You Consider an LGBTQ-Friendly College? If You're an LGBTQ Student If you go to an LGBTQ-friendly college as an LGBTQ student, you'll be in a more accepting, supportive environment. Being in an inclusive place can have a positive impact on your quality of life and academic performance while you're in college. Also, you'll be around more LGBTQ students who are out. LGBTQ students at LGBTQ-unfriendly colleges often don't feel comfortable coming out and expressing their sexual or gender identities. Perhaps most importantly, at an LGBTQ-friendly college you'll have more support services, organizations, and programs designed to help you as an LGBTQ student. You'll be able to befriend other LGBTQ students in LGBTQ student groups and get mentorship and counseling from an LGBTQ resource center. Many LGBTQ-friendly colleges even have orientation programs specifically for LGBTQ students to help them get acclimated to college life. If You're Not an LGBTQ Student If you support LGBTQ rights, you're more likely to be around like-minded people at an LGBTQ-friendly college. Generally, people tend to be happier if they're in a community with others who share their political and social views. For many college students, equality for and acceptance of LGBTQ people are important social issues. Even if you're not an active ally of the LGBTQ community, you can benefit from attending an LGBTQ-friendly college. Ideally, the college experience should broaden your horizons and expose you to diverse people and communities. At an LGBTQ-friendly college, you're more likely to learn about LGBTQ issues and befriend LGBTQ students. Lists of LGBTQ-Friendly Colleges I'm providing you with two lists of LGBTQ-friendly colleges from two different sources. Both have clearly defined criteria for their rankings, and they're reputable sources. The first list from Campus Prideis more reflective of the available resources for LGBTQ students. The second list from Princeton Review is more reflective of on-campus attitudes and treatment of members of the LGBTQ community. The only school that made both lists is Macalester College in St. Paul, Minnesota. Campus Pride Campus Pride is a non-profitdedicated to creating safer, more inclusive LGBTQ-friendly colleges and universities. The top 25 LGBTQ-friendly colleges are based on scores from the Campus Pride Index. The Campus Pride Index includes more than 50 self-assessment questions sent to colleges that correspond to 8 different LGBTQ-friendly factors: LGBTQ Policy Inclusion LGBTQ Support and Institutional Commitment LGBTQ Academic Life LGBTQ Housing LGBTQ Campus Safety LGBTQ Counseling and Health LGBTQ Recruitment and Retention Efforts The List The top 25 LGBTQ-friendly colleges are listed in alphabetical order. Cornell University (Ithaca, NY) Elon University (Elon, NC) Indiana University-Bloomington (Bloomington, IN) Ithaca College (Ithaca, NY) Macalester College (St. Paul, MN) Montclair State University (Montclair, NJ) Penn State University (State College, PA) Princeton University (Princeton, NJ) Rutgers-New Brunswick (New Brunswick, NJ) San Diego State University (San Diego, CA) Southern Oregon University (Ashland, OR) The Ohio State University (Columbus, OH) Tufts University (Medford, MA) University of Colorado at Boulder (Boulder, CO) University of Louisville (Louisville, KY) University of Maine at Machias (Machias, ME) University of Maryland-College Park (College Park, MD) University of Massachusetts-Amherst (Amherst, MA) University of Minnesota-Twin Cities (Minneapolis, MN) University of Oregon (Eugene, OR) University of Pennsylvania (Philadelphia, PA) University of Vermont (Burlington, VT) University of Washington (Seattle, WA) University of Wisconsin-Green Bay (Green Bay, WI) Williams College (Williamstown, MA) Cornell is LGBTQ-friendly. Princeton Review The Princeton Review rankings of the most LGBTQ-friendly colleges are based on students' answers to the survey question "Do students, faculty, and administrators at your college treat all persons equally regardless of their sexual orientations and gender identity/expression?" The List Schools are ranked from 1-20 with #1 being the most LGBTQ-friendly school. However, there don't seem to be any major differences between the environments at #1 and #20. 1. Emerson College (Boston, MA) 2. Warren Wilson College (Asheville, NC) 3. Sarah Lawrence College (Bronxville, NY) 4. Bryn Mawr College (Bryn Mawr, PA) 5. Oberlin College (Oberlin, OH) 6. Yale University (New Haven, CT) 7. Stanford University (Stanford, CA) 8. College of the Atlantic (Bar Harbor, ME) 9. Wellesley College (Wellesley, MA) 10. University of Wisconsin-Madison (Madison, WI) 11. Smith College (Northampton, MA) 12. New College of Florida (Sarasota, FL) 13. Franklin W. Olin College of Engineering (Needham, MA) 14. Macalester College (St. Paul, MN) 15. Pitzer College (Claremont, CA) 16. Brandeis University (Waltham, MA) 17. Prescott College (Prescott, AZ) 18. Grinnell College (Grinnell, IA) 19. Mills College (Oakland, CA) 20. Bard College (Annandale-on-Hudson, NY) How Should You Use These Lists? If you want to go to an LGBTQ-friendly college, you should research the schools that interest you on the Campus Pride or Princeton Review list to determine if you want to apply to them. Keep in mind that some of these colleges have a specific focus. Mills, Smith, Bryn Mawr, and Wellesley are women's colleges. Also, Emerson is devoted to the study of communication and performing arts. Besides the school being LGBTQ-friendly, think of other factors that are important to you in a college including cost, size, selectivity, location, and the majors offered. Look at the school's website, and use guidebooks, college finders, search websites, and other ranking lists to help you in the college selection process. If possible, consult with teachers, counselors, parents, current students, and alumni. Research colleges to find the right one for you! What Should You Do if a School You're Considering Didn't Make the Cut? Just because a school didn't make either list doesn't necessarily mean that it's LGBTQ-unfriendly. If there's a school you're interested in, you can look up its score on the Campus Pride Index. The Campus Pride Index scores schools from 1-5 stars. Schools that get a 5-star rating are the most LGBTQ-friendly. However, many schools don't take part in the Campus Pride Index, including Stanford, which ranks as the #7 most LGBTQ-friendly school in the Princeton Review rankings. Contact a representative from the LGBTQ resource center or student group to get more information about the atmosphere on campus. Usually, you can find those contacts on college websites. If there isn't an LGBTQ resource center or student group, it's probably not an LGBTQ-friendly school. Also, you can consult other sources that evaluate how LGBTQ-friendly a college is. On Niche, you can search for a specific college. Under "diversity" for each school's guide, there is a category called "gay pride" that describes the atmosphere for LGBTQ students on campus. Similarly, on the College View finder, you can search for schools that are LGBTQ-friendly. Additionally, if you look at a specific college's profile, you can see whether the school has gay and lesbian organizations. Finally, The Gay and Lesbian Guide to College Life is a good resource. This book from the Princeton Review doesn't identify LGBTQ-friendly colleges, but it does offer advice from students and administrators at more than 70 of the nation's top colleges about how to excel on campus as an LGBTQ student. What's Next? Because financial concerns often influence the college selection process, check out this list of colleges that meet 100% of students' financial need. Also, learn more about the 28 best liberal arts colleges in the country, many of which are LGBTQ-friendly. Finally, to make sure you get into the college of your dreams, read this post on the important college application deadlines you can't miss. Want to improve your SAT score by 160 points or your ACT score by 4 points?We've written a guide for each test about the top 5 strategies you must be using to have a shot at improving your score. Download it for free now:

Why do you want to work at tenet Hospital Essay Example | Topics and Well Written Essays - 500 words

Why do you want to work at tenet Hospital - Essay Example I have always been a hardworking person and have the quality of working devotedly towards achieving a goal. Due to my attribute to work whole heartedly I was able to achieve a presidential distinction and became the member of Phi Theta Kappa which is the global respected society of universities and educational programs. The membership of this prestigious society provided me with opportunities for the growth and development of management, leadership and assistance, for a cerebral atmosphere for trading of thoughts, for active association for researchers and for motivation of attraction in carrying on with academic brilliance. To polish my skills I joined Jackson North Hospital which gave me the necessary experience required for this respected profession. The practicum in the Medical Surgery Department provided me with a well administered practical use of material studied in the past. I can speak in different languages and I believe that being fluent in these languages will help me to socialize and understand the problem of my patients more effectively. I have also worked as a Nursing assistant in the well known institution GRANNIE NANNIES which contributed in the learning of how to maintain hygiene, bath, dress transport, assist with feeding, and other things to provide a good level of nursing and treatment for the old, disabled grown-ups, or persons of every age with particular needs. Apart from that I have also provided my services in Boca Raton Community Hospital as a patient care assistant and monitor tech. I assisted with personal care, ambulation, distinguishing vital signs, Accu-chek and was respo nsible for tracking electrical impulses of patient’s heart. If given a chance to work as a nurse in Tenet Hospital, I believe I will leave no stone unturned to prove my worth. Because of my great collection of knowledge and exposure to different situations I am sure that I have the necessary stamina and

History of Judasim Essay Example | Topics and Well Written Essays - 750 words

History of Judasim - Essay Example However, after three months she was no longer able to hide him and was forced to throw him in the river. In a strange turn of events, pharaoh’s daughter picked up Moses and she decided to keep him as her son. The royal family adopted Moses and he was raised as a prince. However, Moses soon find out he was Hebrew. He one day killed an Egyptian for mistreating a Hebrew. He was forced to run away and was adopted by Hobab after he rescued his daughter from rude shepherds. One day as Moses was grazing his fathers in laws sheep on MT Horeb, he came across a burning bush (Neusner, 2010). Moses went and talked to the burning bush and this marked the start of his relationship with God. Moses was instructed to go return to Egypt and free the Hebrews. He would then lead them to the Promised Land. One key event that is associated with Moses is that he was sent by God to free the Hebrews for slavery. Moses went back to Egypt and met with the pharaoh telling him of God’s wishes. However, pharaoh was reluctant to free the Hebrews. He turned his rod into a snake as to show that he was sent by God. What transpired is that God sent ten plagues and Moses predicted each one of them. Moses turned river Nile into blood and this killed all the fish. This marked the first plague. In the second plague, Moses was able to bring all the frogs from river Nile to Egypt. Later, Moses infested Egypt with lice and flies. The pharaoh would still not allow freeing the Israelites. Moses inflicted a disease that killed all the Egyptians livestock. He then caused Egyptians to suffer from incurable boils and brought thunderstorms and hails. In the eighth plague, Egypt was covered by locusts which all the food they had planted. Moses initiated a total darkness in the ninth plague. After all this plagues, pharaoh was still standing strong on his resolve of not freeing the Hebrews. The 10th and final

Weather Forecasting with Digital Signals

Weather Forecasting with Digital Signals INTRODUCTION: Digital signal processing (DSP) is concerned with the representation of the signals by a sequence of numbers or symbols and the processing of these signals. Digital signal processing and analog signal processing are subfields of signal processing. The analog waveform is sliced into equal segments and the waveform amplitude is measured in the middle of each segment. The collection of measurements makes up the digital representation of the waveform. Converting a continuously changing waveform (analog) into a series of discrete levels (digital) Applications of DSP DSP technology is nowadays commonplace in such devices as mobile phones, multimedia computers, video recorders, CD players, hard disc drive controllers and modems, and will soon replace analog circuitry in TV sets and telephones. An important application of DSP is in signal compression and decompression. Signal compression is used in digital cellular phones to allow a greater number of calls to be handled simultaneously within each local cell. DSP signal compression technology allows people not only to talk to one another but also to see one another on their computer screens, using small video cameras mounted on the computer monitors, with only a conventional telephone line linking them together. In audio CD systems, DSP technology is used to perform complex error detection and correction on the raw data as it is read from the CD. some of the mathematical theory underlying DSP techniques, such as Fourier and Hilbert Transforms, digital filter design and signal compression, can be fairly complex, the numerical operations required actually to implement these techniques are very simple, consisting mainly of operations that could be done on a cheap four-function calculator. The architecture of a DSP chip is designed to carry out such operations incredibly fast, processing hundreds of millions of samples every second, to provide real-time performance: that is, the ability to process a signal live as it is sampled and then output the processed signal, for example to a loudspeaker or video display. All of the practical examples of DSP applications mentioned earlier, such as hard disc drives and mobile phones, demand real-time operation. Weather forecasting- is the science of making predictions about general and specific weather phenomenon for a given area based on observations of such weather related factors as atmospheric pressure, wind speed and direction, precipitation, cloud cover, temperature, humidity, frontal movements, etc. Meteorologists use several tools to help them forecast the weather for an area. These fall under two categories: tools for collecting data and tools for coordinating and interpreting data. Weather forecasting- is the science of making predictions about general and specific weather phenomenon for a given area based on observations of such weather related factors as atmospheric pressure, wind speed and direction, precipitation, cloud cover, temperature, humidity, frontal movements, etc. Meteorologists use several tools to help them forecast the weather for an area. These fall under two categories: tools for collecting data and tools for coordinating and interpreting data. In a typical weather-forecasting system, recently collected data are fed into a computer model in a process called assimilation. This ensures that the computer model holds the current weather conditions as accurately as possible before using it to predict how the weather may change over the next few days. Weather forecasting is an exact science of data collecting, but interpretation of the data collected can be difficult because of the chaotic nature of the factors that affect the weather. These factors can follow generally recognized trends, but meteorologists understand that many things can affect these trends. With the advent of computer models and satellite imagery, weather forecasting has improved greatly. Weather forecasting- is the science of making predictions about general and specific weather phenomenon for a given area based on observations of such weather related factors as atmospheric pressure, wind speed and direction, precipitation, cloud cover, temperature, humidity, frontal movements, etc. Meteorologists use several tools to help them forecast the weather for an area. These fall under two categories: tools for collecting data and tools for coordinating and interpreting data. * Tools for collecting data include instruments such as thermometers, barometers, hygrometers, rain gauges, anemometers, wind socks and vanes, Doppler radar and satellite imagery (such as the GOES weather satellite). * Tools for coordinating and interpreting data include weather maps and computer models. In a typical weather-forecasting system, recently collected data are fed into a computer model in a process called assimilation. This ensures that the computer model holds the current weather conditions as accurately as possible before using it to predict how the weather may change over the next few days. Weather forecasting is an exact science of data collecting, but interpretation of the data collected can be difficult because of the chaotic nature of the factors that affect the weather. These factors can follow generally recognized trends, but meteorologists understand that many things can affect these trends. With the advent of computer models and satellite imagery, weather forecasting has improved greatly. Since lives and livelihoods depend on accurate weather forecasting, these improvements have helped not only the understanding of weather, but how it affects living and non living things on Earth. Weather forecasting is the science of making predictions about general and specific weather phenomena for a given area based on observations of such weather related factors as atmospheric pressure, wind speed and direction, precipitation, cloud cover, temperature, humidity, frontal movements, etc. Meteorologists use several tools to help them forecast the weather for an area. These fall under two categories: tools for collecting data and tools for coordinating and interpreting data. Tools for collecting data include instruments such as thermometers, barometers, hygrometers, rain gauges, anemometers, wind socks and vanes, Doppler radar and satellite imagery (such as the GOES weather satellite). Tools for coordinating and interpreting data include weather maps and computer models. In a typical weather-forecasting system, recently collected data are fed into a computer model in a process called assimilation. This ensures that the computer model holds the current weather conditions as accurately as possible before using it to predict how the weather may change over the next few days. Weather forecasting is an exact science of data collecting, but interpretation of the data collected can be difficult because of the chaotic nature of the factors that affect the weather. These factors can follow generally recognized trends, but meteorologists understand that many things can affect these trends. With the advent of computer models and satellite imagery, weather forecasting has improved greatly. Since lives and livelihoods depend on accurate weather forecasting, these improvements have helped not only the understanding of weather, but how it affects living and nonliving things on Earth. Weather forecasting is the application of science and technology to predict the state of the atmosphere for a future time and a given location. Human beings have attempted to predict the weather informally for millennia, and formally since at least the nineteenth century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere and using scientific understanding of atmospheric processes to project how the atmosphere will evolve. Once an all-human endeavor based mainly upon changes in barometric pressure, current weather conditions, and sky condition, forecast models are now used to determine future conditions. Human input is still required to pick the best possible forecast model to base the forecast upon, which involves pattern recognition skills, teleconnections, knowledge of model performance, and knowledge of model biases. The chaotic nature of the atmosphere, the massive computational power required to solve the equations that describe the atmosphere, error involved in measuring the initial conditions, and an incomplete understanding of atmospheric processes mean that forecasts become less accurate as the difference in current time and the time for which the forecast is being made (the range of the forecast) increases. The use of ensembles and model consensus help narrow the error and pick the most likely outcome. There are a variety of end uses to weather forecasts. Weather warnings are important forecasts because they are used to protect life and property. Forecasts based on temperature and precipitation are important to agriculture, and therefore to traders within commodity markets. Temperature forecasts are used by utility companies to estimate demand over coming days. On an everyday basis, people use weather forecasts to determine what to wear on a given day. Since outdoor activities are severely curtailed by heavy rain, snow and the wind chill, forecasts can be used to plan activities around these events, and to plan ahead and survive them. History of weather control If we dispense with legends, at least Native American Indians had methods which they believed to induce rain. The Finnish people, on the other hand, were believed by others to be able to control all weather. Thus Vikings refused to take Finns on their raids by sea. Remnants of this belief lasted well into the modern age, with many ship crews being reluctant to accept Finnish sailors. The early modern era saw people observe that during battles the firing of cannons and other firearms often precipitated precipitation. The first example of weather control which is still considered workable is probably the lightning conductor. For millennia people have tried to forecast the weather. In 650 BC, the Babylonians predicted the weather from cloud patterns as well as astrology. In about 340 BC, Aristotle described weather patterns in Meteorologica. Later, Theophrastus compiled a book on weather forecasting, called the Book of Signs. Chinese weather prediction lore extends at least as far back as 300 BC. In 904 AD, Ibn Wahshiyyas Nabatean Agriculture discussed the weather forecasting of atmospheric changes and signs from the planetary astral alterations; signs of rain based on observation of the lunar phases; and weather forecasts based on the movement of winds. Ancient weather forecasting methods usually relied on observed patterns of events, also termed pattern recognition. For example, it might be observed that if the sunset was particularly red, the following day often brought fair weather. This experience accumulated over the generations to produce weather lore. However, not all of these predictions prove reliable, and many of them have since been found not to stand up to rigorous statistical testing. It was not until the invention of the electric telegraph in 1835 that the modern age of weather forecasting began. Before this time, it had not been possible to transport information about the current state of the weather any faster than a steam train. The telegraph allowed reports of weather conditions from a wide area to be received almost instantaneously by the late 1840s. This allowed forecasts to be made by knowing what the weather conditions were like further upwind. The two men most credited with the birth of forecasting as a scienc e were Francis Beaufort (remembered chiefly for the Beaufort scale) and his protà ©gà © Robert FitzRoy (developer of the Fitzroy barometer). Both were influential men in British naval and governmental circles, and though ridiculed in the press at the time, their work gained scientific credence, was accepted by the Royal Navy, and formed the basis for all of todays weather forecasting knowledge. To convey information accurately, it became necessary to have a standard vocabulary describing clouds; this was achieved by means of a series of classifications and, in the 1890s, by pictorial cloud atlases. Great progress was made in the science of meteorology during the 20th century. The possibility of numerical weather prediction was proposed by Lewis Fry Richardson in 1922, though computers did not exist to complete the vast number of calculations required to produce a forecast before the event had occurred. Practical use of numerical weather prediction began in 1955, spurred by the development of programmable electronic computers. * Modern aspirations There are two factors which make weather control extremely difficult if not fundamentally intractable. The first one is the immense quantity of energy contained in the atmosphere. The second is its turbulence. Effective cloud seeding to produce rain has always been some 50 years away. People do utilize even the most expensive and experimental types of it, but more in hope than confidence. Another even more speculative and expensive technique that has been semiseriously discussed is the dissipation of hurricanes by exploding a nuclear bomb in the eye of the storm. It is questionable that it will ever even be tried, because if it failed, the result would be a hurricane bearing radioactive fallout along with the destructive power of its winds and rain. * Modern day weather forecasting system Components of a modern weather forecasting system include: Data collection Data assimilation Numerical weather prediction Model output post-processing Forecast presentation to end-user * Data collection Observations of atmospheric pressure, temperature, wind speed, wind direction, humidity, precipitation are made near the earths surface by trained observers, automatic weather stations or buoys. The World Meteorological Organization acts to standardize the instrumentation, observing practices and timing of these observations worldwide. Stations either report hourly in METAR reports, or every six hours in SYNOP reports. Diurnal (daily) rhythm of air pressure in northern Germany (black curve is air pressure) Atmospheric pressure is the pressure at any point in the Earths atmosphere. For other uses, see Temperature (disambiguation). An AWS in Antarctica An automatic weather station (AWS) is an automated version of the traditional weather station, either to save human labour or to enable measurements from remote areas. Weather buoys are instruments which collect weather and ocean data within the worlds oceans. WMO flag The World Meteorological Organization (WMO, French: , OMM) is an intergovernmental organization with a membership of 188 Member States and Territories. METAR (for METeorological Aerodrome Report) is a format for reporting weather information. SYNOP (surface synoptic observations) is a numerical code (called FM-12 by WMO) used for reporting marine weather observations made by manned and automated weather stations. Measurements of temperature, humidity and wind above the surface are found by launching radiosondes (weather balloon). Data are usually obtained from near the surface to the middle of the stratosphere, about 30,000 m (100,000 ft). In recent years, data transmitted from commercial airplanes through the AMDAR system has also been incorporated into upper air observation, primarily in numerical models. radiosonde with measuring instruments A radiosonde (Sonde is German for probe) is a unit for use in weather balloons that measures various atmospheric parameters and transmits them to a fixed receiver. Rawinsonde weather balloon just after launch. Atmosphere diagram showing stratosphere. Aircraft Meteorological Data Relay (AMDAR) is a program initiated by the World Meteorological Organization. Increasingly, data from weather satellites are being used due to their (almost) global coverage. Although their visible light images are very useful for forecasters to see development of clouds, little of this information can be used by numerical weather prediction models. The infra-red (IR) data however can be used as it gives information on the temperature at the surface and cloud tops. Individual clouds can also be tracked from one time to the next to provide information on wind direction and strength at the clouds steering level. Polar orbiting satellites provide soundings of temperature and moisture throughout the depth of the atmosphere. Compared with similar data from radiosondes, the satellite data has the advantage that coverage is global, however the accuracy and resolution is not as good. A weather satellite is a type of artificial satellite that is primarily used to monitor the weather and/or climate of the Earth. Sounding The historical nautical term for measuring dept h. Meteorological radar provide information on precipitation location and intensity.. Additionally, if a Pulse Doppler weather radar is used then wind speed and direction can be determined.. * Data assimilation Data assimilation (DA) is a method used in the weather forecasting process in which observations of the current (and possibly, past) weather are combined with a previous forecast for that time to produce the meteorological `analysis; the best estimate of the current state of the atmosphere. Weatherman redirects here. Modern weather predictions aid in timely evacuations and potentially save lives and property damage. More generally, Data assimilation is a method to use observations in the forecasting process. In weather forecasting there are 2 main types of data assimilation: 3 dimensional (3DDA) and 4 dimensional (4DDA). In 3DDA only those observations are used available at the time of analyses. In 4DDA the past observations are included (thus, time dimension added). The first data assimilation methods were called the objective analyses (e.g., Cressman algorithm). This was in contrast to the subjective analyses, when (in the past practice) numerical weather predictions (NWP) forecasts were arbitrarily corrected by meteorologists. The objective methods used simple interpolation approaches, and thus were the kind of 3DDA methods. The similar 4DDA methods, called nudging also exist (e.g. in MM5 NWP model). They are based on the simple idea of Newtonian relaxation. The idea is to add in the right part of dynamical equations of the model the term, proportional to the difference of the calculated meteorological variable and the observation value. This term, that has a negative sign keeps the calculated state vector closer to the observations. The first breakdown in the field of data assimilation was introducing by L.Gandin (1963) with the statistical interpolation (or optimal interpolation ) method. It developed the previous ideas of Kolmogorov. That method is the 3DDA method and is the kind of regression analyses, which utilizes the information about the spatial distributions of covariance functions of the errors of the first guess field (previous forecast) and true field. These functions are never known. However, the different approximations were assumed. In fact optimal interpolation algorithm is the reduced version of the Kalman filtering (KF) algorithm, when the covariance matrices are not calculated from the dynamical equations, but are pre-determined in advance. The Kalman filter (named after its inventor, Rudolf Kalman) is an efficient recursive computational solution for tracking a time-dependent state vector with noisy equations of motion in real time by the least-squares method. When this was recognised the attempts to introduce the KF algorithms as a 4DDA tool for NWP models were done. However, this was (and remains) a very difficult task, since the full version of KF algorithm requires solution of the enormous large number of additional equations. In connection with that the special kind of KF algorithms (suboptimal) for NWP models were developed. Another significant advance in the development of the 4DDA methods was utilizing the optimal control theory (variational approach) in the works of Le Dimet and Talagrand, 1986, based on the previous works of G. Marchuk. The significant advantage of the variational approaches is that the meteorological fields satisfy the dynamical equations of the NWP model and at the same time they minimize the functional, characterizing their difference from observations. Thus, the problem of constrained minimization is solved. The 3DDA variational methods also exist (e.g., Sasaki, 1958). Optimal control theory is a mathematical field that is concerned with control policies that can be deduced using optimization algorithms. As it was shown by Lorenc, 1986, the all abovementioned kinds of 4DDA methods are in some limit equivalent. I.e., under some assumptions they minimize the same cost functional. However, these assumptions never fulfill. The rapid development of the various data assimilation methods for NWP is connected to the two main points in the field of numerical weather prediction: 1. Utilizing the observations currently seems to be the most promicing challange to improve the quality of the forecasts at the different scales (from the planetary scale to the local city, or even street scale) 2. The number of different kinds of observations (sodars, radars, sattelite) is rapidly growing. The DA methods are currently used not also in weather forecasting, but in different environmental forecasting problems, e.g. in hydrological forecasting. Basically the same types of DA methods, as those, described above are in use there. Data assimilation is the challange for the every forecasting problem. Numerical weather prediction Numerical weather prediction is the science of predicting the weather using mathematical models of the atmosphere. Manipulating the huge datasets and performing the complex calculations necessary to do this on a resolution fine enough to make the results useful can require some of the most powerful supercomputers in the world. Image File history File links NAM_500_MB.PNGà ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€¦Ã‚ ½ File links The following pages on the English Wikipedia link to this file (pages on other projects are not listed): Numerical weather prediction Block (meteorology) Image File history File links NAM_500_MB.PNGà ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€¦Ã‚ ½ File links The following pages on the English Wikipedia link to this file (pages on other projects are not listed): Numerical weather prediction Block (meteorology) A millibar (mbar, also mb) is 1/1000th of a bar, a unit for measurement of pressure. Geopotential height is a vertical coordinate referenced to Earths mean sea level an adjustment to geomet ric height (elevation above mean sea level) using the variation of gravity with latitude and elevation. Weather is a term that encompasses phenomena in the atmosphere of a planet. A mathematical model is an abstract model that uses mathematical language to describe the behaviour of a system. A supercomputer is a computer that leads the world in terms of processing capacity, particularly speed of calculation, at the time of its introduction. An example of 500 mbar geopotential height prediction from a numerical weather prediction model Model output post processing The raw output is often modified before being presented as the forecast. This can be in the form of statistical techniques to remove known biases in the model, or of adjustment to take into account consensus among other numerical weather forecasts. For other senses of this word, see bias (disambiguation). In the past, the human forecaster used to be responsible for generating the entire weather forecast from the observations. However today, for forecasts beyond 24hrs human input is generally confined to post-processing of model data to add value to the forecast. Humans are required to interpret the model data into weather forecasts that are understandable to the end user. Additionally, humans can use knowledge of local effects which may be too small in size to be resolved by the model to add information to the forecast. However, the increasing accuracy of forecast models continues to decrease the need for post-processing and human input. Examples of weather model data can be found on Vigilant Weathers Model Pulse. Presentation of weather forecasts The final stage in the forecasting process is perhaps the most important. Knowledge of what the end user needs from a weather forecast must be taken into account to present the information in a useful and understandable way. * Public information One of the main end users of a forecast is the general public. Thunderstorms can cause strong winds, dangerous lightning strikes leading to power outages, and widespread hail damage. Heavy snow or rain can bring transportation and commerce to a stand-still, as well as cause flooding in low-lying areas. Excessive heat or cold waves can kill or sicken those without adequate utilities. The National Weather Service provides forecasts and watches/warnings/advisories for all areas of the United States to protect life and property and maintain commercial interests. Traditionally, television and radio weather presenters have been the main method of informing the public, however increasingly the internet is being used due to the vast amount of information that can be found. * Air traffic The aviation industry is especially sensitive to the weather. Fog and/or exceptionally low ceilings can prevent many aircraft landing and taking off. Similarly, turbulence and icing can be hazards whilst in flight. Thunderstorms are a problem for all aircraft, due to severe turbulence and icing, as well as large hail , strong winds, and lightning , all of which can cause fatal damage to an aircraft in flight. On a day to day basis airliners are routed to take advantage of the jet stream tailwind to improve fuel efficiency. Air crews are briefed prior to take off on the conditions to expect en route and at their destination. * Utility companies Electricity companies rely on weather forecasts to anticipate demand which can be strongly affected by the weather. In winter, severe cold weather can cause a surge in demand as people turn up their heating. Similarly, in summer a surge in demand can be linked with the increased use of air conditioning systems in hot weather. * Private sector Increasingly, private companies pay for weather forecasts tailored to their needs so that they can increase their profits. For example, supermarket chains may change the stocks on their shelves in anticipation of different consumer spending habits in different weather conditions. a) =Ensemble forecasting= Although a forecast model will predict realistic looking weather features evolving realistically into the distant future, the errors in a forecast will inevitably grow with time due to the chaotic nature of the atmosphere. The detail that can be given in a forecast therefore decreases with time as these errors increase. There becomes a point when the errors are so large that the forecast is completely wrong and the forecasted atmospheric state has no correlation with the actual state of the atmosphere. However, looking at a single forecast gives no indication of how likely that forecast is to be correct. Ensemble forecasting uses lots of forecasts produced to reflect the uncertainty in the initial state of the atmosphere (due to errors in the observations and insufficient sampling). The uncertainty in the forecast can then be assessed by the range of different forecasts produced. They have been shown to be better at detecting the possibility of extreme events at long range. Ensemble forecasts are increasingly being used for operational weather forecasting (for example at ECMWF , NCEP , and the Canadian forecasting center). b) =Nowcasting= The forecasting of the weather in the 0-6 hour timeframe is often referred to as nowcasting . It is in this range that the human forecaster still has an advantage over computer NWP models. In this time range it is possible to forecast smaller features such as individual shower clouds with reasonable accuracy, however these are often too small to be resolved by a computer model. A human given the latest radar, satellite and observational data will be able to make a better analysis of the small scale features present and so will be able to make a more accurate forecast for the following few hours. Signal Processing Generating imagery for forecasting terror threats Intelligence analysts and military planners need predictions about likely terrorist targets in order to better plan the deployment of security forces and sensing equipment. We have addressed this need using Gaussian-based forecasting and uncertainty modeling. Our approach excels at indicating the highest threats expected for each point along a travel path and for a global war on terrorism mission. It also excels at identifying the greatest-likelihood collection areas that would be used to observe a target. 1 on geospatial analysis and asymmetric-threat forecasting in the urban environment. He showed how to extract distinct signatures from associations made between historical event information and contextual information sources such as geospatial and temporal political databases. We have augmented this to include uncertainty estimates associated with historical events and geospatial information layers.2 Event Forecasting Spatial Preferences The notion of spatial preferences has been used to find potential crime1 and threat3 hot spots. The premise is that a terrorist or criminal is directed toward a certain location by a set of qualities, such as geospatial features, demographic and economic information, and recent political events. Focusing on geospatial information, we assume the intended target is associated with features a small distance from the event location. We assign the highest likelihoods to the distances between each key feature and the event, and taper them away from these distances. This behavior is modeled using a kernel function centered at each of these distances. For a Gaussian kernel applied to a discretized map, the probability density function à Ã‚  for a given grid cell g and uncertainty estimates u is given by Dig is the distance from feature i to the grid cell, Din is the distance from the feature to event location n, c is a constant, ÃŽÂ ¦E and ÃŽÂ ¦F are the position uncertainty for event and features respectively, I is the total number of features, and N is the total number of events. Figure 1(a) shows a sample forecast image based on this approach, denoting threat level with colors ranging from blue for lowest threat, through red for highest threat. For the same set of features and events, Figure 1(b) shows a more manageable forecast-in terms of allocating security resources-determined by aggregating feature layers prior to generating the likelihood values. Modeling Uncertainty One of the most important aspects of forecasting is having an estimate of the confidence in the supporting numerical values. In numerical weather prediction, there is always a value of confidence assigned with each forecast. For example, predicting an 80% chance of rain implies that numerical weather models given input parameter variations, predicted eight o

Opium War: Was Britain completely in the wrong? Essay

The British were wrong by taking the option of trading opium because by trading opium, they would be jeopardising the wellbeing of an entire country. But they only did it because the Chinese were refusing to trade, so therefore it is only partially Britains fault. The â€Å"Opium War† also known as the Anglo-Chinese war began in 1839. It started as a conflict over trading between Britain and China. China was refusing to trade because they didn’t need anything. Eventually the British were able to trade opium on the black market. China did nearly everything to stop the opium being traded but nothing could stop it. This eventually caused the war. Was Britain Completely in the wrong? No. Although they were the ones that started the opium trade, China is still partially to blame. The following points will be argued for the fact that both sides contributed and neither were completely wrong:  · The introduction of trading opium by Britain  · The stupidity of the Chinese stimulating the British and judging them to be bad at war.  · And The greedy treaty made by the British But firstly, the refusal for trade and the cruel regulations that China put upon the British traders. There was a demand for Chinese tea, silk and porcelain in the west, though there was practically nothing that the west could offer to trade with China, because of the simple reason that they didn’t want anything and were refusing to trade for things they didn’t need. The Chinese didn’t realise how hard they were making the situation. A British man, Lord William John Nappier was sent to China to try and extend British trading interests. He was told that he could only address himself to the Hong Merchants and that he could only live in Guangzhou during trading season. When he refused to leave, Lu Kun, Governor of Guangzhou prohibited all the buying and selling to the English and then ordered all the withdrawal of all Chinese labour from them. What were the British to do? The regulations were too harsh and the British couldn’t trade no matter what  they tried. In this situation, The Chinese were obviously in the wrong because they didn’t consider the needs of the British and they were to stubborn to trade because they thought they were more superior. Secondly, Britain introduced the opium to China because they ran out of choices. Since China ignored Britain’s proposal to trade, Britain had to find some other way they could get the bits and pieces that they required. They started to illegally export opium on the black market, aware of the consequences. The result was a widespread addiction throughout China causing serious social and economic disruption in China. Britain was most definitely in the wrong with this choice because nothing can make the trading of opium justifiable. The cost is too painful. But it was China’s fault in the fist place that they didn’t want to establish trading with Britain. Thirdly, the stupidity of the Chinese stimulating the British and judging them to be hopeless at fighting caused them the loss of the war. The Chinese were ignorant, and they thought that the British were bad compared to them. Lin Zexu says, â€Å"Besides guns, the barbarian soldiers do not know how to use fist or swords†¦ Therefore, what is called their power can be controlled without difficulty.† Unfortunately Lin Zexu was wrong about this. The underestimation of the British made the Chinese disadvantaged because they weren’t prepared enough and much unorganised. Their weapons were completely useless against those of the British. Chinese cities were then captured and Chinese citizen’s soldiers were forced to surrender. Therefore China’s stupidity and bad organisation skills in this case were to blame for the opium war and their loss. So China was, in this case was in the wrong. The last factor is the greedy treaty made by the British. Once the Chinese had lost the war, they had no choice but to sign a treaty written by the British. Many unreasonable discissions were made in favour of the British including many unjust payments. China was completely demoralised and Britain was in the wrong for making them sign such an unfair treaty. They took advantage of China when they shouldn’t have. To conclude this argument, neither China nor Britain was completely wrong or  right with all their decisions. They both contributed to the war and therefore it was both their fault. China’s refusal for trade was wrong because they were being selfish and stubborn and they weren’t considering the welfare of others. Britain was wrong in introducing opium because nothing can justify the trading of opium and it shouldn’t have even been an option to trade it. Britain was also in the wrong by creating a treaty in their favour because China was in a weak position.

Erica Carter - Young Women and their Relationship to...

Erica Carter Erica Carter teaches Cultural Studies at the University of Warwick. Recently, she published How German is She? Postwar West German Reconstruction and the consuming Woman (1996), in which she explores how the development of a social market economy after 1949 gave a new centrality to consumers as key players in the economic life of the (German) nation and in that process gave women a new public significance. Carter argues that concepts of nationhood survived in the rhetorics of public policy and in popular culture of the period. Carters (1984) interesting argument regarding young women and their relationship to consumerism and the market owes much to early feminist critique. Carter insists that the image industries†¦show more content†¦Girls are written into youth cultural theory in the language of consumption--initially, as objects for consumption by men. At first, British cultural theorists thought of girls as an absence, a silence, a silence which could only be filled in some separate world of autonomous female culture. Feminist researchers turned to the family as the pivotal point. In following working-class girls into the closed arena of the family, researchers of female culture gained insight into the possibilities of specifically female cultural forms. In this way, they thought of so-called bedroom culture as analogous to male subcultures (p. 105). Searching for autonomous female cultural forms in the bedroom hideaways of teenage girls has been problematic--in terms of the creative, productive, and potentially subversive power of this mode of femininity. Researchers thought that studying teeny bopper culture was the key which would unlock the potentialities of specifically female forms. Subculture theory proved to be an inadequate starting point for studies of female culture. The spectacle of working-class subcultures erupted into a gap between class relations as they are lived by working-class youth and the classless categories according to which capitalist markets are structured. Ever since W.L. Warners (1960) classic study of social class in America, the marketing establishment has measured consumers against typological grids on