Thomas Edison Essay Paper Example For Students

Thomas Edison Essay Paper By: Jeff E-mail: emailprotected Thomas Alva Edison Thomas Alva Edison was one of the greatest inventors. He was a smart man. Thomas invented many things such as the light bulb and phonograph. Without the light bulb we would still be using candles and lanterns like they did many years ago. Although Thomas was deaf he worked hard and never gave up. Thomas Alva Edison was born on February 11, 1847 in Milan, Ohio. He had many family members. He had a father named Samuel Odgen Edison and a mother named Nancy Elliott Edison. Thomas mother pulled him from school because Thomas teacher called him a retard. Nancy Edison taught her son at home. Thomas has six siblings and he was the youngest child in the Edison family. We will write a custom essay on Thomas Edison Paper specifically for you for only $16.38 $13.9/page Order now Thomas was interested in many things as a child. At age twelve Thomas got a job at the Grand Trunk Railroad. While working at Grand Trunk Railroad Thomas was a typesetter, press operator, editor, and publisher of his very own newspaper called the Herald. Thomas got his news for his newspaper from telegraphers at other train stations. Thomas liked many things, but mathematics was not one of them. He enjoyed reading books about science and philosophy. His favorite book ever was Isaac Newtowns Principia Mathematica. Thomas was interested in inventing the light bulb. Thomas was a scientist as a kid. He like to test many things. When he was young he built a laboratory in the familys basement. Thomas did experiments he found in science books and got jars and chemicals for experiments from local shopkeepers. Thomas also used a spare train car for another laboratory. Thomas studied books on mechanics, manufacturing, and chemistry at the public library. He spent a long time studying Newtowns Principles. He also read lots of books such as Gibbons Decline and Fall of the Roman Empire, Humes History of England, Sears History of the World, Burtons Anatomy of Melancholy, and The Dictoinaries of Sciences. Thomas Edison invented the light bulb. In October of 1879 Edison patented his incandescent lamp. Edison and his team made a new vacuum pump to make better vacuums in glass light bulbs. It was better known as the glow bulb. Thomas second attempt at the glow bulb successfully lit for forty hours. On New Years Eve Edison lit up Menlo Park with thirty glow bulbs. Electricity would replace gas for lighting purposes. The light bulb gives off light so that we can see with out lanterns and candles. The Edison Lamp Company produced 1,000 light bulbs a day. It has improved since its original version. In 1880, Edison invented the incandescent lamp. In the year 1910, Tungsten filament was discovered giving off white light instead of yellow light. In 1925, lamps were given an inside frosting that had a fine spray of hydrofluoric acid. In the late 19th century, florescent lamps were invented. They are tubes filled with low-pressure neon gas. Thomas Edison invented many things we still used today. I think the light bulb was the greatest invention because it is hard to see with out light bulbs. Without the light bulb we would not be able to have night ball games or light shows. It is a good thing Thomas Edison invented the light bulb. Bibliography 1. Edison, Thomas. Comptons Encylopedia. 1990 ed. vol. 7, p.72-76 2. Ellis, Keith. Thomas Edison, Genius of Electricity. Great Britain: Priory Press Limited, 1974 3. Parker, Steve. Thomas Edison and Electricity. Great Britain: Belitha Press Limited, 1992 Word Count: 541

Bmx Cycle Solutions Essays

Bmx Cycle Solutions Essays Bmx Cycle Solutions Paper Bmx Cycle Solutions Paper Question # I What business is LOCI in? What are the key success factors? How operations can contribute? LOCI BUSINESS: LOCI was founded in 1934 by Mr.. Sheikh Abdullah, a Former Chairman of Pakistan Cycle Cooperative Society Limited. LOCI is located at Ferrous Road, eighteen miles south of Lahore Pakistan. LOCI marketed its bicycles under the brand name Of Leader bicycles. LOCI was in bad shape and financially bankrupt , all shops run by one supervisors , its production was practically zero when Managing director at Deacon Mr.. Razor Atwood acquired LOCI in June 1999. He red new 6 engineers since 1999 in following departments like production planning, production scheduling, inventory control and quality control to set up all the necessary systems and procedures in order to turn LOCI around. In May 2002 Five bicycles -manufacturing companies (competitors) existed in market, combined capacity of these companies producing bicycles were 580,bicycles per annum, and all were running at or near capacity, the competition was very tough, up to May 2002, LOCI was producing 60,000 bicycles/annum, in May 2002, LOCI started producing manufacturing its new product named BMW cycles, for determent in this new product, after a year-long negotiation with Hercules of England, Decision acquired from them the manufacturing and technology right, in Pakistan, for the very popular BMW cycle, Hercules also agreed to send engineers to Lahore tort ten-week periods in order to help in set up the plant, tooling and train the staff KEY SUCCESS FACTORS: ;k Senior Management of LOCI wanted to introduce the BMW Cycle in market before competitors, and Mr.. Monsoon Warwick, Senior Planning Engineer, had a lot of pressure by the top management of LOCI to complete this huge production Of BMW Cycles. That m assive production was carefully planned and all the processes where closely monitored and upgraded. * Mr.. Razor Atwood, Managing Director, of Deacon, took over the LOCI in very bad shape , and he set up all necessary systems and procedures like production planning, production scheduling, inventory control and quality control in order to turn LOCI around , it is also a factor of the success of LOCI * Another key success factor was that Deacon called Hercules of England engineers to train Lolls staff. Lolls staff can also go to England for the same training for a specific period. OPERATIONS CONTRA LOCI is a Production Company so operations plays very important role. Outsourcing and subcontracting of different raw materials is done for the better result of operations. All the plants structure was designed in a way so that they can minimize the wastage and can maximize the production, Manpower was also assigned according to their expertise and labor was hired on daily wage system. Question # 2 What is your Analysis Of the BMW production process? HOW would you characterize this process? ANALYSIS OF BMW PRODUCTION PROCESS: BMW production process is almost in sequence, all processes depends on each there, if one process is skipped then they cannot complete other part of cycle, in Other wards they cannot ignore only a single process, As LOCI wanted to introduce BMW in market before competitors and management wanted to produce huge quantity of BMW cycles so LOCI purchased different finished parts for BMW cycles from several suppliers, like, seats , pedals, handle bars, frame pads, and tires were directly purchased and installed , but other side several parts, like sheet metal, metal coils, steel bars and pipes were manufactured from raw materials acquired locally and abroad. Management hired permanent and daily paid labor in all shops to complete tasks efficiently and in timely, this planning was proved very helpful to complete huge production. First process is cutting shop: This shop having 3 machines for cutting metal pipes into different lengths to use prepare bottom bracket shell, frames and handle bar, this shop run under one supervisor and 4 full time employees Second process is Bottom bracket shell shop: This Shop contained three 600 tons processes and 6 presses ranging from 60 to 00 tons, heavy parts of bicycle like B shell were manufactured in this shop this shop run under supervision of one supervisor and 4 full time employees. Handle Shop: BMW bicycle handles were manufactured at this shop completely, a specific machine automatically bent the placed pipe in a few seconds into appropriate configuration and cut the handle bars to length and knurled. These Knurled to help retain the handle bar grip. BMW enameling and Phosphates Shop: All parts of bicycle were enameling and paginating, phasing treatment enabled the steel surface to retain the enameled paint for a long time and roved a durable finish, all parties were placed on gigs and hang on a conveyer, this conveyer passed through a drying oven at a speed allowing each part to be baked at CISCO for approximately 50 minutes. Rim Shop: Bicycle Rims contained at this shop, One mm thick and 83 mm wide metal coils required to prepare rim and these rims imported trot Brazil or Japan, then front end coil was welded with back end coils and finally, the rims was bent into a required radius and cut after buffing and polishing. Press Shop: A specific machine at press shop for grinding and buffing the parts of rims and woo ends of strips had been welded together Saddle, Brake and Hub Shop: Hubs and saddle for BMW cycle were assembled at this shop, loop clips of were manufactured at LOCI , other parts like saddle frames and saddle covers were procured by vender and assembled manually at other end of same shop. Machine Shop: Pour production lathes like a grinding machine, a milling machine and four drilling machines are contained at this shop, some parts of BMW cycle check-nut, lock-nut and wheel valve produced in machine shop, this machine visas operating 50% of its capacity Electroplating Shop: Some parts Of BMW like Hub flanges, steel rims , lamp brackets, spanners and chain wheels electroplate at this shop, this machine have limited equipment capacity so double shift running six days per week for electroplating. BMW Welding line: This shop have S welding stations and a metering machine , different parts Of cycle welded and metering machine give a smooth curve at the ends of tubes (pipes) once this machine was set then all tubes automatically mitered the tube. Final Assembly Area: This area have 6 work stations, fitting machine and an assembly track conveyor, al manufactured parts of BMW cycle assemble on these 6 stations, finally all the assemblies and accessory packets were packed in a cardboard carton for delivery. Characteristics, All shops worked very efficiently and all work stations busy to prepare assigned parts on same time so its very helpful to produce huge production, management took decisions for daily paid and monthly paid employees, and paid them attractive salary. Question #3 Given the investment in BMW cycle manufacturing line, what is the payback period? Each bicycle price 2400 Gross margin Profit margin for each bicycle Production Capacity 60, coo Profit margin for 60,000 bicycles are = 199. 2 x 60000 = 11952000 Payback on 2 Years 2 Months gross margin Question # 4 Assume the enameling plant capacity is 3000 bicycles per month, as senior planning Engineer, What alternatives are available to increase BMW cycle production? As per upper managements drive to expand operations, a ten year old enameling unit that was purchased for RSI 3 Million in 1999. In order to increase production LOCI in addition to subcontracted enameling should start in house production in parallel by utilizing the unit purchased. It may have to invest on up-gradation of the unit as required to meet the current production standards. Company purchased enameling machine but they did not use it, because outsourcing and subcontracting was present in Lolls tradition so upper management should change it and its better to utilize enameling machine, bring it in use, so BMW production will definitely be increased, Question # S What is your recommendation and why? Following are the Recommendations and the reasons ;k LOCI should do some forecasting for identifying the real need of their product in the market, They should give advertisement though email, news paper and web TV add etc, *They should do SOOT analysis of their own company and their competitors. * They should improve their weaknesses, and they should produce bicycle for elders They should hire some vender for parts of BMW so it is suggested that they should arrange of those machines at their company, its also saving the cost and time. ;k For sustaining the market position more innovation is required, the designs Of bicycles should be upgraded and changed to attract the customers towards the product.

Ethics and Global Warming Assignment Example | Topics and Well Written Essays - 2250 words

Ethics and Global Warming - Assignment Example This study will illustrate how the ethical analysis and evaluation can help to realize the nature of climate problem and restriction on potential solutions. In order to do so, the study will concentrate on how the climate change threatens the essential value. Moreover, this study will raise serious concerns of responsibility and fairness. Global Climate Change and Ethical Action Challenges Global climate change is most serious challenge towards ethical action. Climate change can be described as the appropriate moral storm as it brings several key challenges to the ethical action. Climate change is truly a global phenomenon. Emission of greenhouse gases is the major consequence of global warming. This greenhouse gas emission is affecting the planet. Increasing greenhouse gas emission can increase the average surface temperature of globe. It is true that all countries in the world are collaboratively trying to reduce the level of green house gas emission, but on individual basis, each country prefers to continue greenhouse gas emitting. Several unethical business practices and increasing green house gas emission is one of the major reasons behind the global climate change. Therefore, it is important for all the countries and states to minimize the harmfulness of the climate change in order to save future global generation. Emission of green house gases should be reduced significantly as soon as possible (Jamieson, 1992). Moreover, it is the responsibility of the developed countries to take serious initiatives so that other countries and states can follow the p athway.... Emission of this greenhouse gas is contributing to negative impacts on climate for centuries. It is unfair if these negative impacts are cumulative and severe. Moreover, temporal diffusion can create several collective ethical action problems. It is more challenging comparing to the common traditional tragedy. Underdeveloped theoretical tools in several relevant areas, such as intergenerational ethics, international justice, scientific uncertainty and strong relationship between nature and human being is another significant challenge to the ethical actions. For an example, global climate change can raise questions about the moral value of several nonhuman natures, such as obligations to protect unique place, nonhuman animals and rest of the nature. In addition, potentiality for catastrophic results and existence of scientific uncertainty put pressures internally on several standard and effective economic approaches to several environmental problems. Moreover, these will play an impor tant role in the arguments for the defensive approach in the environmental policy and law. Global climate change is raising several questions about how an individual should relate to the nature and nonhuman animals. Addressing Global Climate Change Environmental damage has become one of the most important global threats. Heating up atmosphere due to deadly methane and carbon dioxide gas emission is affecting modern day civilization. Majority of the individuals feel that acceptance of the global warming is a natural phenomenon. On the other hand, according to various environmental scientists, global climate change is the major consequence of global warming. Several unethical and irresponsible human activities are major key drivers of global

Environmental Article Critique Example | Topics and Well Written Essays - 750 words

Environmental Critique - Article Example This indicates the insufficiency of empirical studies to identify effects of environmental tools on environmental performance. Empirical data for this research was obtained from cross-country data on various environmental tools such as taxation and government involvement as well as the environmental performance of such countries. Statement of Research Procedure Motivated by the need to engage in empirical study to obtain the link between environmental tools and performance, Im and Wonhyuk (2011) decided to obtain cross-country data in order to evaluate their research objectives, which was to evaluate the link between environmental tools and environmental performance through empirical data. Most of the empirical data in this study was obtained from the World’s major economies. The data included mainly the involvement of the various governments through research and development or environmental governance impact of such government. After obtaining such data, Im and Wonhyuk (2011) decided to measure the performance of environmental governance whilst defining the environmental performance through literature review. ... In addition, econometric model was used to identify the correlation between dependent variable (environmental performance) and the independent variables (R&D and taxation). The econometric model included regression analysis, variance analysis; least squares procedures, and QUE estimates to provide the necessary covariance matrix for identification of error. Results of the regression analysis were presented using tables after which a discussions based on such results were conducted. The discussions were linked to various levels of success of applicable environmental policy tools within the global spectrum. Flaws in Procedural Design Despite having a beautiful research procedure in a bid to attaining their objectives, Im and Wonhyuk (2011) research was flawed within the procedural design. Firstly, the researchers did not mention it anyway other than the introduction on the research design. In other words, Im and Wonhyuk (2011) research did not provide for research methodology. Every re search conducted should explicitly provide research methodology, which will guide not only the researchers but also the users of the document into how the study was conducted. Another flaw was on the data analysis. Im and Wonhyuk (2011) just given the analyzed data after stating the statistical tools they had used. It would have been better if such econometric models were included within the research other than just mentioning them. Lastly, despite obtaining empirical data from the selected major countries, which they did not explicitly indicate, there was need to identify the sample size and sampling method of the major countries they though would effectively represent the entire globe. Analysis of Data Analysis of

Gandhi and Wollstonecraft Essay Example | Topics and Well Written Essays - 750 words

Gandhi and Wollstonecraft - Essay Example It firstly could be used to refer to a sovereign ruler’s external power and freedom. However, it is the second definition that applied more so to Gandhi’s perspectives, it a freedom of spirituality, freed from all illusions, and understanding of the great absolute truths. (Gandhi 17-18). The two concepts do have a relationship in Gandhi’s philosophy. He believed that it was not for people to behave violently against others, because only someone or something that had true understanding of all of the great truths has the right to judge another, which we do not. Swaraj could easily be referencing the afterlife and oneness with thought, knowledge, and inevitably God. Regardless of the motivations toward non-violent protest, many have attempted Gandhi-like protests with mixed results. Unfortunately, there may be advantages to non-violent protests, but the disadvantages are also rather extreme. Non-violence has been applied to many political and social struggles throughout history. Dr. Martin Luther King used many forms of non-violent protests to advance the importance of the Civil Rights Movement. One of the most famous and successful expression of non-violent protest was the Bus Boycott in the 1960s that, nearly plummeted the public transportation system (Mach 1). Of course, we cannot forget the actions of Rosa Parks, who peacefully but firmly refused to five up her seat. These non-violent actions contributed greatly to changing the world and ending the discrimination of segregation. In this case, that is what many people remember about his leadership. No matter how unkind, abusive, and ignorant people were his protest would remain non-violent. Another poignant example of non-violent protest is the â€Å"burning monk.† The Vietnam War is a controversial one; even today arguments concerning the actions taken during that time will garner great and heated debate. Protests were common in the

Image To Voice Converter Is Software Computer Science Essay

Image To Voice Converter Is Software Computer Science Essay Image to Voice converter is software or a device to recognize an image and convert it into human voice. The purpose of the conversion is to provide communication aid for blind people to sense what the object in their hand or in front of them. This converter is also suitable for children at the age of three until six years old for early education part. In this project converter, it consists of image processing and sound generation. For an image processing, it is a series of calculation techniques for analyzing, reconstructing, compressing, and enhancing images. When an object is inputting, an image will captured through scanning or webcam; analyze and manipulate of the image, accomplished using various specialized software applications such as MATLAB and output like a printer or a monitor. Image processing has several techniques, including template matching, KNN (K-Nearest Neighbour), thresholding and etc. For the template matching, it is a technique for finding small parts of an image to match with the template image; it is also used to identify printed characters, numbers, and other small, simple objects. KNN (K-Nearest Neighbour) is an algorithm that can work very well in practice and easy to understand. It is also a lazy algorithm that does not use the training data points to do any generalization. Besides, thresholding technique is one of the most important approaches to image segmentation. It is a non-linear operation that can converts a gray-scale image into a binary image. The purpose of image processing in this project is to analysis of a picture using techniques that can identify shades, colours and relationships that cannot be observed by the human eye. Besides that, an image processing is used to solve identification problems, i.e. in forensic medicine or in establishing weather maps from satellite photos. It assigns with images in bitmapped graphics form that have been scanned in or taken with digital cameras. For sound generation is to generate a sound through window sound library or play a wav file from computer. Problem Statement Nowadays, many visually impaired people still using blind mans stick to sense the road of the direction and object in front of them in this society. With just only a plain stick and a pair of covered eye, it is difficult for a human to get sense of their direction. Probably, they would not know what the objects around the people which had been blinded eye. As we can see the economy nowadays is getting worse, most of the people or family members were getting busy on their busy work life; they have no extra time to spend on the handicap people to give them a good care. In this case, for all the handicap people especially blind people, they have to get use to it on their living style. In order than that, this product is also available to help the small kids to improve the ability on distinguishing or differentiate the daily use objects. This is the reason why the product mentioned above was developed. Project Aim and Objective: The aim of this project is to develop an Image to Voice converter which able to recognize an image from the webcam and then convert it into sound by window sound library or wav file with good performance. To achieve the main objective of this project, there are sub-objectives need to be carry through as follows: To develop a unique image recognition algorithms for shapes and colours for real time application using MATLAB. To analyze the performance of the image recognition algorithm in term of accuracy and time processing. To develop an algorithm to convert recognized image to voice using MATLAB. To analyze the performance of image to voice conversion algorithm. Test the performance of the closed loop interface for the image and sound processing converter system. To develop Graphical User Interface (GUI) of the image to voice converter for case of user finding. Project Scope/Limitation The scope of this project is to construct a unique image to voice converter within a period of time at cost not to exceed RM200. Referring to this project, it consists of hardware which is webcam and software which is MATLAB. The system of this project is to capture an image using webcam, then recognize an image and generate a sound using MATLAB with several techniques. This product specially created for visually impaired people or to improve small kids learning capability. There was few limitation of this project which specified as follows: Shape limitation Colour limitation Resolution limitation Distance limitation Literature Review Image processing is a technique to convert an image into digital specification and go through some actions on it, so as to get an enhanced image or to collect some advanced information from it. It is a kind of signal exemption in which input is image, like video frame or photograph and output may be image or features related with that image. Frequently, image processing institution consist of treating images as two dimensional signals while applying already set signal processing techniques to them[1]. For the image recognition process can be divided into several algorithms which are image acquisition, image pre-processing, image segmentation, image representation and image classification. For the image acquisition, it is a digital image that captured by one or a few image sensors, such as various types of light-sensitive cameras, range sensors, tomography devices, radar, ultra-sonic cameras and etc. According to the type of sensor, the outcome of an image data is an generally two dim ensional image, a three dimensional capacity, or an image order. The pixel values usually correspond to strength of light in one or a few spectral bands, but can also be involved many physical measures, such as depth, absorption or reflectance of sonic or electromagnetic waves, or nuclear magnetic resonance. Image pre-processing is one of the algorithms that can increase the dependability of an optical inspection. This algorithm can be categorized into two categories which are image enhancement. Image enhancement requires intensifying the different features of images either for display or analysis targets. The enhancements techniques are edge enhancements, noise filtering, magnifying and sharpening an image. Several filter operations which increase or reduce certain image features allow an easier or faster evaluation. For examples, mean filter, median filter, wiener filter, and etc. With continuous use, an image will becomes degraded and has many errors. Image restoration is the process used to restore the degraded image. This process is also used to correct images read from different sensors that show up murky or out of focus[2]. Next, image segmentation is performed to assemble pixels into salient image areas, for example, areas corresponding to specific surfaces, objects, or inherent sections of objects. Segmentation could be used for object recognition, occlusion boundary estimation within motion or stereo systems, image density, image editing, or image database. The traditional image segmentation method can be divided into several techniques including gray threshold segmentation method, edge extraction method, regional growth method and split consolidation method and etc. Threshold technique was applied in this project. It is a technique that deals with gray-scale images. For the moment of the influence of noise or illumination, it can be assumed that the majority of pixels belonging to the objects will have a relatively low gray-level, whereas the background pixels will have a relatively high gray-level. For example, Black is represented by a gray-level of 0, and White by a gray-level of 255. Based on th is observation, we can divide the pixels in the image into two dominant groups, according to their gray-level. These gray-levels may serve as detectors to distinguish between background and objects in the image. On the other hand, if the image is one of smooth-edged objects, then it will not be a pure black and white image; hence this would not be able to find two distinct gray-levels characterizing the background and the objects. This problem intensifies with the existence of noise[3]. In order to overcome the ill influence of noise and shading, there are two methods that can solve this problem which are Otsu known as Global Threshold and Neighbourhood known as Adaptive Threshold. For the image representation, all information is commonly represented in binary. This is real of images as well as numbers and text. However, an important differentiation needs to be made between how image data is shown and how it is stored. Displaying includes bitmap representation while storing as a file includes many image formats, such as jpeg and png[4]. There are few techniques for image representation which are Roundness ratio known as Circularity, Fourier Descriptors and etc. The intent of the image classification procedure is to sort all pixels in a digital image into one of several land cover categories, or themes. This categorized data may then be used to deliver thematic maps of the land cover present in an image. Ordinarily, multispectral data are used to carry out the classification and truly the spectral pattern present within the data for each pixel is used as the numerical basis for categorization. The purpose of image classification is to determine and describe, as a distinct gray level or colour, the characteristics occurring in an image in terms of the object or kind of land cover these characteristics practically express on the ground[5]. The technique for this algorithm is using template matching and KNN (K-Nearest Neighbour). Table : Comparison of image sensors for image acquisition[6, 7] Types of Image Sensor Strength Weakness 1 Webcam allow face to face interaction low cost easy to use low resolution not portable no optical zoom lenses no auto-focus 2 Digital Camera high resolution portable with batteries has optical zoom lenses has auto-focus high operating speed less durability battery consumption faster high cost many complex function From the Table 1, it can be seen that both image sensors have its own strengths and weaknesses. This research will more focus on webcam due to this image sensor is using for this project. Webcam can be used to connect with computer to capture an image for image recognition. On the other hand, it is easy to use and cheaper compare with digital camera which is more complex and high cost. However, the megapixel of digital camera is higher than webcam. .. Table : Comparison of several types of filter for image pre-processing[2, 8] Types of filter Strength Weakness 1 Median filter more robust more smoothing provide good results memory consuming complex computation 2 Mean filter intuitive simple to use smoothing not good in sharpen images susceptible to negative outliers 3 Wiener filter short computation time controls output error straightforward to design results often too blurred spatially invariant From the Table 2, it can be seen that all filters have its own strengths and weaknesses. This research will focus on two types of filter which are median filter and mean filter. Median filter have been chosen for this project is because median filter is more robust on average than mean filter and so a not representative pixel in a neighbourhood will not influence the median value significantly. Since the median value needs to be the value of one of the pixels in the neighbourhood, the median filter does not establish new unrealistic pixel values when the filter straddles an edge. This is because of the median filter is better at preserving sharp edges than the mean filter. Also, median filter removes the noise level more than mean filter. Table : Comparison of threshold techniques for image segmentation [9, 10] Threshold Techniques Strength Weakness 1 Otsu fast ease of coding easy to use less sensitivity assumption of uniform illumination does not use any object structure or spatial coherence complex computation 2 Neighbourhood produce a good result less computation memory consumption time consumption sensitive From the Table 3, it can be seen that both techniques have its own strengths and weaknesses. Otsus method, named after its inventor Nobuyuki Otsu, is a global threhold that consists of many binarization algorithms[11]. This method involves iterating through all probable threshold values and computing a measure of propagates for the pixel levels each side of the threshold, i.e. the pixels that can be falls in background or foreground. The purpose is to find the threshold value where the total of foreground and background propagate is at its minimum. Neighbourhood which known as adaptive threshold is used to separate desirable foreground image objects from the background based on the difference in pixel intensities of each region. The differences between both methods were Otsu uses a histogram to threshold the image and the Neighbourhood method uses a histogram to threshold the pixels in a small region/neighbourhood around the pixel. In addition, Otsu methods suffer less errors occur t hat are caused by the sensitivity of the local algorithms to image noise compare with the Neighbourhood methods. Table : Comparison of the two techniques for image representation[12] Techniques of Image Representation Strength Weakness 1 Roundness Ratio very fast algorithm scale, position and rotation invariant high accuracy if image shape can be preserved properly after segmentation susceptible to errors if object shape is changed due to improper segmentation 2 Fourier Descriptor medium speed produce a good result low computation cost overcome the weak discrimination ability scale, position and rotation invariant difficult to obtain high order invariant moments cannot deal with disjoint shapes From the Table 4, it can be seen that both techniques have its own strengths and weaknesses. Roundness is defined in term of a surface of revolution like cylinder, cone or sphere where all marks of the surface alternated by any plane vertical to a common axis in case of cylinder and cone are equal in distance from axis. As the axis and centre do not exist, measurements have to be made with consultation to surfaces of the figures of revolution only. The circularity of the outline is to measuring roundness[12]. Fourier Descriptors are used to describe the feature of contour of shape. It was founded in the early sixties last century by Cosgriff and Fritzsche. According to the Fourier analysis theory, Fourier coefficients can be often generated by Fourier transformation. Lower frequency coefficients have the general shape of the signature, and higher frequency coefficients have the more information about the shape. As the harmonic amplitude and the phase angle can represent the Fourier D escriptor, and Fourier coefficients are usually normalized by dividing the first Fourier coefficient separately. Because there are some fast algorithms in computing the coefficient of Fourier series, many recognition systems in machine vision using these coefficients as shape features. Table : Comparison of several techniques for image classification [13-15] Techniques for Image Classification Strength Weakness 1 Template Matching easy to implement high degree of flexibility high accuracy of detection shape limitation computation speed susceptible to scaling and rotation 2 K-Nearest Neighbour easy to implement very effective improve accuracy improve run-time performance poor run-time performance if the training set is large very sensitive outperformed by more exotic techniques 3 Neural Network minimize energy function high accuracy easy to use unstable curse of dimensionality space consumption From the Table 1.5, it can be seen that all techniques have its own strengths and weaknesses. This research will focus on two techniques which are Template Matching and K-Nearest Neighbour. The standard template matching technique is known as simple mechanism, high accuracy of detection, and is used as a general model assessment and error estimation. Hence, it plays a very important role in image processing, and is commonly used in object detection and recognition. But the contradiction between rapidity and accuracy is exceptional. The main factors affecting rapidity are searching calculation, and operations of template matching. Appropriately decreasing positions and similarity computing precision can increase the speed of template matching obviously. That is becoming a focus in this field. Many studies focus on improving the searching algorithm, decreasing the matching times by decreasing the matching points on the template of images, which need to be detected so that rapidity is r ealized. The typical algorithms are pyramid algorithm, genetic algorithm and so on. Each matching operation is based on the template matching, thus it is necessary to pay attention to improving the computation speed of template matching fundamentally[14]. The intuition underlying Nearest Neighbour Classification is quite straightforward, examples are classified based on the class of their nearest neighbours, it is often useful to take more than one neighbour into account so the technique is more commonly referred to as K-Nearest Neighbour (KNN) Classification where k-nearest neighbours are used in determining the class. Since the training examples are needed at run-time, i.e. they need to be in memory at run-time; it is sometimes also called Memory-Based Classification. Because induction is delayed to run time, it is considered a Lazy Learning technique[13]. . Analysis on Similar Products and Paper Literatures Oral Image to Voice Converter by Takaaki HASEGAWA and Keiichi OHTANI[16]: In this paper, the authors propose a new speech communication system to convert oral image into voice, Image input Microphone. This system synthesizes the voice from only the oral image. This system provides high security and is not affected by acoustic noise, because actual utterance is not always necessary to input. Moreover, since the voice is synthesized without recognition, this system is independent of languages. Simulations to convert oral image to voice about Japanese five vowels are carried out as basic investigation. A vocal tract area function is estimated from the oral image, and PARCOR synthesis filter is obtained from the vocal tract area function. The PARCOR synthesis filter is driven by a pulse train. The performance of this system is evaluated by hearing tests of the synthesized voice. As a result, audible voice has been synthesized and the mean recognition rate of Japanese five vowels has been 91%. This paper describes a system to convert oral image into voice with considering humans lip-reading ability. In the proposed system, the voice is directly synthesized only from the oral image without recognition, and actual utterance is not always necessary to input. They use both the feature of a tongue and the feature of lips obtained from the oral image. Therefore this system is not affected by the acoustic noise, and simultaneously, it provides high security because of no utterance input capability. The system structure of this product is using a vocal tract area function which is equivalent to the transfer function of the vocal tract as a parameter. Indirect means synthesis via the vocal tract area function. The vocal tract area function is obtained from the PARCOR analysis of speech signals, and speech signals are synthesized by inverse processing of PARCOR analysis. Therefore if the vocal tract area function is estimated from oral image signals, they can convert the oral image to the corresponding voice. Human utters various voice by changing the vocal tract, and each articulator moves not independently but cooperatively in utterance, It is generally known that the information of articulation is obtained from lip-reading. Software Comparison Table below shows that the two comparison of the software between MATLAB and C++. Table : Comparison of software between MATLAB and C++[17] Types of Software Strength Weakness 1 MATLAB easy to learn fast numerical algorithms inexpensive software fast development slow processing complex computation 2 C++ mature standard large community fast complex computation difficult to debug low level programming From the Table 6, it can be seen that both types of software have its own strengths and weaknesses. MATLAB is software that has been widely used in image processing and computer vision community. Multiple image analysis function has been build into this software; it is very useful image analysis tools for end user. C++ is a standard template library (STL), computer graphics, and image processing. Based on C++ template mechanism, the library accepts all C++ build-in types as the image data, although certain functions are only valid to subset of build-in types. MATLAB has been selected due to the project analysis characteristic. MATLAB version R2010b will be used to analyze the image quality and performance in this project. Project Methodology This project has been divided into hardware and software. For the hardware section is the webcam as the input and speaker as the output. For the software section is using MATLAB to recognize image to sound with several image processing techniques. Block Diagram Webcam Image Segmentation (Thresholding) Image Acquisition (Acquire image) Image Preprocessing (Median filtering) MATLAB Image Representation (Roundness Ratio) Sound Generation (WAV file) Image Classification (Template Matching using KNN) Speaker Figure 1: Block diagram of Image to Voice converter. The block diagram shown in Figure 1 is the basic concept on the system interface that needed to be carried out. Base on the block diagram, first prepared a webcam. Then, capture the image in front of the webcam. After that, perform a median filtering in image pre-processing using MATLAB. It will filtered unwanted signal or noise inside the image. Next is image segmentation, referring to the literature review, the most suitable method is using Otsus method in thresholding techniques to convert grayscale image into binary image to do segmentation. Secondly, find the largest object and do the image representation using roundness ratio to calculate the ratio of the largest object to determine which one is the nearest to the template ratio. Next stage is image classification, using template matching with KNN techniques to find the small part of the image to match with the template image. After matching done, it will automatically generate a sound from the computer with WAV file. Flow Chart Start Acquire image from webcam Perform median filtering Colour Space Conversion Thresholding using Otsu Image labelling Find the largest object Image Representation -roundness ratio Template matching using KNN Is the image matched? No Yes Generate Sound Figure 2: Flow chart of Image to Voice converter. Based on Figure 2, before the beginning of image recognition, first, acquire an image in front of the webcam, and then the acquired image will go through image enhancement process to perform median filtering to filter some unwanted noise and sharpening the image. After that, the image will perform a colour space conversion which is convert the image colour space to another colour space, i.e. RGB, HSV, YCbCr and etc. The purpose of converting the colour space is to ensure that the converted image to be as same as the possible to the original image. Next, perform a threshold technique using Otsus method to calculating a measure of spread for the pixel levels each side of the threshold. The reason of doing this is to separate the objects from the background. Once the thresholding technique is done, perform a image labelling by taking the outside lines in the image and label them as occluding the background. After that, find the largest object and do the image representation using roundn ess ratio to calculate which object is similar to the template ratio. Then, perform a template matching techniques to find a match between the template and a portion of the image. The template that most closely matches the object is then found using the KNN method to do a matching system with the database image. If the data is matched, it will generate a sound automatically by using MATLAB to load the wav file from the computer or laptop. After that, it will repeat the procedure starting from the first step. If the data is unmatched, it wont generate a sound and it will go back to the first step and repeat the procedure again until the data is matched. Projects Method Median Filter Median filters are nonlinear rank-order filters based on replacing each element of the source vector with the median value, taken over the fixed neighbourhood of the processed element. These filters are widely used in image and signal processing applications. The purpose of median filtering is to removes impulsive noise, while keeping the signal blurring to the minimum[18]. Otsu Method Otsus method is a widely used method of segmentation, also known as the maximum infra-class variance method or the minimum inter-class variance method. This method involves iterating through all the possible threshold values and calculating a measure of spread for the pixel levels each side of the threshold, i.e. the pixels that either falls in foreground or background. The aim is to find the threshold value where the sum of foreground and background spreads is at its minimum[11]. Roundness Ratio/Circularity Roundness is defined as a condition of a surface of revolution like cylinder, cone or sphere where all points of the surface intersected by any plane perpendicular to a common axis in case of cylinder and cone. Since the axis and centre do not exist physically, measurements have to make with reference to surfaces of the figures of revolution only. For measuring roundness, it is only the circularity of the contour which is determined[12]. Template Matching The classical template matching method is charactered as simple mechanism, high accuracy of detection, and is used as a general model evaluation and error estimation. Therefore, it plays a very important role in image processing, and is widely used in object detection and recognition. It is a technique for finding small parts of an image to match with a database image[14]. K-Nearest Neighbour (KNN) K-Nearest Neighbour (KNN) is a branch of simple classification and regression algorithms. It can be defined as a lazy method. It does not use the training data points to do any generalization. Although classification remains the primary application of KNN, it can use to do density estimation also. Since KNN is non parametric, it can do calculation for arbitrary assignation[19]. Project Specification This project is divided into 3 main sections which are hardware, software and project estimate cost. Hardware The hardware was using for this project is Logitech HD Webcam C310, below is the basic requirement of the webcam: logitech-hd-webcam-c310.png Figure 3: Logitech HD Webcam C310[20] Windows Vista, Windows 7 (32-bit or 64-bit) or Windows 8 1 GHz 512 MB RAM or more 200MB hard drive space Internet connection USB 1.1 port (2.0 recommended) Software The software for this project is using MATLAB for image recognition and sound generation. Project Estimate Cost The estimate cost for this project is RM89 which was the Logitech HD Webcam C310, because this project was basically software based project and the software to be used is MATLAB from college engineering lab. Gantt Chart

Soliloquies Essay - Importance of the First Soliloquy in Macbeth

Importance of the First Soliloquy in Macbeth      Ã‚  Ã‚  Ã‚   Following king Duncan's arrival at Inverness, Macbeth delivers his first major soliloquy. This speech summarizes his reasons for not wanting to commit murder. It is also an image of the plot of Macbeth, as it foreshadows the chain of events that is to follow the murder of Duncan. Although Macbeth knows that he cannot "trammel up the consequence" of Duncan's murder and that his actions will have repercussions, he commits the murder and continues to kill; thus is Macbeth shown to be a weak character who can be easily convinced to perform terrible deeds. Although this is not apparent before the predictions, the moments following them and his homecoming demonstrate Macbeth's own vulnerability. The important speech that he delivers summarizes the results of Duncan's murder, and the multitude of murders following this all follow suit. Macbeth's eventual deterioration is inevitable.      Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   Near the beginning of the play, Macbeth is portrayed as a brave soldier and a noble officer in the king's army. He successfully leads the attack upon the invading forces of Macdonwald, the Thane of Cawdor, and Sweno, king of Norway. He is killing upon the order of another, in this case, the king: "[Macbeth] Like valour's minion carv'd out his passage/Till he fac'd the slave" (I.ii.19-20). Macbeth here appears as a powerful warlord who, although at times seems bloodthirsty, is effective in destroying the foe. Before his meeting with the witches, we have a rather clean view of him; he is a "good" man.      Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   When Macbeth and Banquo stumble onto the barren plateau where the w... ...e manipulated. While he can figure and rationalize alone, outside influences such as Lady Macbeth and the witches change his actions and skew his thoughts. This weakness of character was particularly unacceptable in Macbeth's time, when men were meant to be full of both mental and physical fortitude. Macbeth was a great man, but his tragic fault was his undoing, for a man of his power could not survive in those times without much more moral strength than he had.    Bibliography    Primary Source:    Shakespeare, William. Macbeth. Coles Total Study Edition. Toronto: Coles, 1992.    Secondary Sources:      Ã‚   1. Coles Editorial Board. "Marginal Notes to Macbeth," Macbeth. Total Study Edition. Toronto: Coles, 1992.      Ã‚   2. Coles Editorial Board. Macbeth Notes. Toronto: Coles, 1992.