McDonald Expansion in China

Across the Barricades - The good and the bad essays

Across the Barricades - The good and the bad essays Across the Barricades is a novel full of prejudice and different opinions on certain things in life Therefor the characters that Lingard presents have a lot of different personality traits. Lingard tries to remote and repress certain characteristics by presenting different characters. Sadie, one of the main characters in the novel, is a Protestant girl. She is a determined and independent girl with strong opinions and she has got a strong will. Another characteristic of Sadie is that she is not afraid of speaking up for herself and others. She fights for what she believe in and does not care what other people say. Another main character is Kevin. He is a catholic boy. He is more afraid of what people think than Sadie is and sees the consequences of their relationship clearer. As a person Kevin can be described as calm, serious and hardworking He is kind and will not hurt a fly unless he is badly provoked. Kevin thinks that the fights between the Catholics and Protestants are unreasonable and unnecessary. Although Brain Rafferty betrays Kevin, Kevin stays loyal to his old friend. He does not give Brain away when the police accused him of owning the gun. Although Kevin and Sadie comes from different religions one can see they share most of their believes. They both believe they can be friends even if they belong to different religions. Mr Blake appears in a crucial point in the novel. He gives Kevin and Sadie hope and helps them in their relationship. He himself is a Catholic, but he did not care if people were Catholic or Protestant. He held no prejudice against those who had a different religion than his own. Mr Blake thinks of others before he thinks of himself. He fights for what he believes in and refuses to give into terrorism. People like Mr Blake and the Hendersons are ideal characters. If everybody in Northern Ireland shared their attitude there would be no conflict. ...

Theology paper Essay Example | Topics and Well Written Essays - 1000 words - 1

Theology paper - Essay Example The four noble truths are; The Nature of Suffering, Sufferings Origin, Sufferings Cessation, and The Path Leading to the Cessation of Suffering. The path leading to cessation is an eight fold path set out by Buddha. These are related to faith, morality and meditation. The Heart Sutra emphasizes wisdom and emptiness. This sutra teaches us that the thing which looks like something much is nothing much. Form outside; it appears to be a lot, but there is really nothing behind. A swelled head as we know is an empty head (Conze, p.85). Heart Sutra reveals that most of the big things in this world are just like inflated balloons. From outside, the balloon may look like big, but we know that only air is inside the balloon. In other words, this sutra tries to educate us that whatever we perceive as big in this world are noting really meaningful. For example, many people may think that earning wealth and fame is a good achievement in this world. But according to Heart Sutra teachings, such things are just like inflated balloons. When we die, we cannot take anything with us and hence the physical achievements in this world are meaningless. According to Christian belief, salvation can be obtained only through Jesus Christ. Jesus is the son of God who has sacrificed his life for saving the life of sinners. All the people in the world are sinners according to Christian belief. As per the rules of God, death is the punishment for sinners. But the sin has arrived in this world because of Adam’s sin. In other words, we, the children of Adam, are sinners traditionally because of the sins committed by Adam. God has given the verdict that in order to wipe off the punishment of sin from the world, person without free from sins should sacrifice his life. But in this world no saints are there. So God has sent his only son Jesus to the world in order to sacrifice his life to save our lives. Jesus’ sacrifice enabled him to attain full control or authority over the human

History of the Middle East Research Paper Example | Topics and Well Written Essays - 3000 words

History of the Middle East - Research Paper Example The increased developments in Middle East had been pronounced since early decades, and can be traced back in the second half of 1500s when Ottoman Empire started expanding its domain (Fischbach 2013, 56). From inception, Islam had shaped politics in regions where it dominated, especially in Middle East. Despite the fragmentation of the political authority in Muslim land, Islam continued to be powerful and had a strong political solidarity bond. Collapse of Ottoman Empire facilitated the entry of Europeans in Middle East who aimed at colonizing them. British domination of local politics remained effective until early 1970s. Emergence of independent and sovereign states between 1940s and 1050s altered traditional foundations and domestic power equations in state-society relations. The modern states were unprepared for any competitive international environment and offer substantial support to the growing nationalist aspirations. Such aspirations appeared in response to political develop ments and Palestinian-Israeli conflicts that served as the catalyst for regional instability and conflict. This led to the political environment in 20th century characterized by political turmoil, extremism and conquests. Therefore, this paper investigates why the creation of the state of Israel failed to solve the Jewish problems (Gettleman 2012, 145). Creation of state of Israel The creation of state of Israel was predicated on the constitution of Jews as people of special identity and placed the nation on specific territory, as well as the juridical and territorial independence of the nation in modern country. The formation of state of Israel was enhanced by Zionism and deliberated by articulation from individuals who set to revive the ancient kingdom in a modern approach. This called for territorial and political independence for it to be successful. Soon after the end of World War II, the British evacuated Palestine and recommended partitioning of the Palestine into two states. Arabs rejected while Jewish accepted, though they advocated that they be given more than 55 percent of the land. This facilitated the War of control during which Israel declared its statehood in 1948. Such victory over the Arabs facilitated an influx of Jewish refugees from Europe and other Muslim word and outflow of fleeing Arab Palestinians (Klieman 1990, 63) One year after the partition plan by the general assembly, the resolution 94 was issued to offer right of return of the Arabs to the post-mandate Palestine. However, UN possessed no powers to enforce such resolutions since Israel was determined to prohibit Arabs to return to their homes after fleeing. Such unresolved problems remain the major source of conflicts for quite some time. In 1950, Israel’s parliament passed the law of return (Gettleman 2012, 148). Partition Plan Most states in UN General Assembly voted in the partition plan for the Palestine in 1947. Such a resolution called for the termination of the manda te by Britons and created two states; one for Arabs and the other one for Jews. City of Jerusalem was entitled to the enjoyment of special status under the international administration. The resolution was voted in by thirty one countries while seven voted against the resolution. Zionists accepted the resolution while Arabs opposed it since it advocated for a single state dominated by Arab majority. Traditionally, the twin objectives of the foreign policy in Israel of

The impact of technology on society(electrification(electricity)) Research Paper

The impact of technology on society(electrification(electricity)) - Research Paper Example Since the evolution of electricity is a complex phenomenon, its makeover is done by various personalities at various span of time at different stages. If we look at who identified electricity in an elaborate way, then the credit can be given to Benjamin Franklin who recognized electricity by flying kite on the occasion of lightning. It was in 1752, June 15th that Benjamin Franklin propagated that lightning is the pure form of electricity. He founded through experiment that electricity could pass through metals and this gave way to the great discovery of many electrical appliances and gadgets. 2.1.1 The Phenomenon of Electricity Surprisingly, the electricity as a scientific phenomenon did not gain recognition until the last quarter of eighteenth century. The early civilization to probe in to the discovery of electricity was the Greek personalities. The word electricity itself is connected to the Greek word â€Å"Elektron† or amber as rubbing of amber with cloth produced electri city. The electricity which was once a frightening element of nature, changed in to the most beneficial gift of nature as man discovered its immense potentiality and usability in his daily life. Electricity being a secondary form of energy source is obtained by converting primary sources of energies like coal, oil, natural gas, nuclear power and other natural sources. The electricity consists of electrons which are tiny particles of energy and are the smallest unit of energy. These electrons which are energy particle, when passed through metals like copper and iron aids in use of electricity in electrical appliances. However the production and supply of electricity is the most perplexing procedure and capital intensive program, which the industrial sector has ever experienced. The electricity is produced in extensive power plants with the help of huge turning turbines. Here the turbines are turned with the help of steam produced by coal. However, if electricity is produced by water then the rushing of water moves the turbine. The voltage of electricity is increase with the help of transformers which is later passed to the electrical equipments for use. 2.2 The status of pre- electricity period. 2.2.1 Quality of life The quality of life before the invention of electricity was considerably dull and dark. The period prior to the last quarter of 18th century was a duration of strive and struggle due to the absence of electricity. The life during those times was murky and was entirely depended on the dim light of the candle. Unlike 21st century, the age before electricity was limited in luxury and amenities. People were not in a position to take maximum benefit of natural resources and had to struggle hard to conduct their daily life. Moreover, the night life of people were less exciting because as the night fell, people resorted to their homes keeping in mind their personal security and safety. During those times, people depended on bee wax, cow dung and animal fa t to illuminate their houses and other personal and public spaces. 2.2.2. Performing task Before the invention of electricity, all the house hold chores and productive works were outcome of manual labor. People like poets and

Cloud Computing with Machine Learning for Cancer Diagnosis

Cloud Computing with Machine Learning for Cancer Diagnosis Cloud computing with Machine Learning could help us in the early diagnosis of breast cancer Junaid Ahmad Bhat, Prof. Vinai George and Dr. Bilal Malik Abstract— The purpose of this study is to develop tools which could help the clinicians in the primary care hospitals with the early diagnosis of breast cancer diagnosis. Breast cancer is one of the leading forms of cancer in developing countries and often gets detected at the lateral stages. The detection of cancer at later stages results not only in pain and agony to the patients but also puts lot of financial burden on the caregivers. In this work, we are presenting the preliminary results of the project code named BCDM (Breast Cancer Diagnosis using Machine Learning) developed using Matlab. The algorithm developed in this work is based on adaptive resonance theory. (Explain the results of this work here ..). The aim of the project is to eventually run the algorithm on a cloud computer and a clinician at a primary healthcare can use the system for the early diagnosis of the patients using web based interface from anywhere in the world. Keywords— Adaptive Resonance theory, Breast Cancer Diagnosis, FNA I. Introduction The breast cancer is one of the common cancers and ranked second in the world after the lung cancer. (1)This type of cancer also ranked second in northern India. (1)Breast cancer is one of the leading cancers found in Kashmir (1) .Classifying the cells into the malignant and benign is the main goal in the diagnoses of breast cancer and misclassification could cost pain to the patients and extra burden to health care providers. Due to noise in the data, the problem to classify becomes non-trivial and has thus attracted researchers from machine learning to improve the classification.(2) Researchers have used different machine learning algorithms to improve the diagnosis of breast cancer. (3) And Neural Networks is one of the machine learning algorithms, which has been widely used for diagnosis of breast cancer. In order to achieve the exactness Adaptive Resonance theory that is one of the variants of Neural Network been used for prediction purposes. Neural Network gained importance in 505 till late 60s due to its accuracy and learning capabilities but got diminished in 80s due to its computational cost. With the advancement in technology (4) Neural Networks are becoming popular due to their ability to achieve non-linear hypotheses even when input feature scale is large (4). This work proposes to use a variant of neural networks based on adaptive resonance theory to improve the breast cancer diagnosis. This algorithm has been developed and tested in Matlab 2012.has been tested on lot of real life problems that include automated automobile control, for classification purposes and for the detection of intruders in the battlefield. II. Adaptive Resonance Theory (ART) The Adaptive Resonance Theory (ART) is a neural network architecture that generates suitable weights (parameter) by clustering the pattern space. . The motive for adapting ART instead of a conventional neural network is to solve the stability and plasticity problem. (5) ART networks and algorithms keep the plasticity to learn new patterns and prevent the amendment of patterns that it learned earlier. The stable network will not return the previous cluster. The operation of ART works as it accepts an input vector and classifies it into one of the clusters depending on to which cluster it resembles. If it will not match with any of the category then a new category is created by storing that pattern. When a store pattern is, bring into being that matches the input vector within a specified tolerance that made it to look like the input vector. The pattern will not be modified if it doesnt match the current input pattern within the vigilance parameter. With the help of it the problems associated with stability and plasticity can be resolved. (5) Figure 4 Art 1Neural Network Architecture A. Types of Adaptive Resonance Theory 1) Adaptive Resonance Theory 1 It is the first neural network of Adaptive Resonance theory. It consists of two layers that cluster the pattern from the input binary vector. It accepts the input in the form of binary values (6). 2) Adaptive Resonance Theory 2 It is the second type of neural Network of Adaptive Resonance theory .It is complex than that of ART1 network and accepts the values in the form of continuous valued vector. The reason of complexity for ART 2 is that it possesses the normalization combination and noise inhibition alongside it compares the weights needed for the reset mechanism. (6) B. Working of ART 1 Neural Network The art Neural Networks works in the following fashion, which comprises of three layers and each layer has its own role to play. 1) Input layer 2) Interface layer 3) Cluster layer The parameters used in algorithm are as: Num = Number of Symptoms M = Clusters as {benign ,Malignant} bwij =Bottom up weights Twij = Top down weights P =Vigilance parameter S = Binary forms of the input symptoms X = Activation vector for interface ||x|| =norm of x or sum of the components of x Step 1: Initialize Parameters L > 1 and 0 Initialize weights 0 ij (0) ij (0)=1 Step 2: While stop condition is false, perform step 3 to 14 Step 3: For each training input do step 4 to 13 Step 4: Set Activation of all F2 units to 0 Set Activation of F1(a) units to binary forms of Symptoms vector Step 5: Compute the sum of the symptoms ||s|| = ∑ i Si Step 6: Send the symptom vector from input layer to interface layer xi = si Step7: The cluster node that is not inhibited If yj != -1 then yj = ∑ bij *xi Step8: While reset is true, perform step 9-12 Step 9: Find J such that yi >= yj for all nodes j If yj = -1 then All then odds are inhibited thus cannot be clustered Step 10: Recomputed activation vector x of interface unit Xi= si *tji Step 11: Compute the sum of the components of vector x ||x||= ∑I Xi Step 12: Test for reset condition if ||x|| / ||s|| Yj = -1 (inhibited node j) Move to step step 8 again if ||x|| / ||s|| >= p then move to next step Step 13: Update the bottom up weights and top up weights as: bij (new)=L*xi / L 1 +| |x|| and Tji (new)=xi Step 14: Test for the stopping condition if((bij(new_val)==bij(previous_vreeal)))(tij(new_val)==tij(previous_val))) III. Classifying Breast Cell The data set for this research was taken from Mangasarian and Wolberg. This data set was obtained by taking Fine Needle Aspirates (FNA) approach. (7) This data set is available for public in UCI repository. (7) It contains 699 samples of patients consists of two classes 458 as benign cases and 451 malignant cases. The following are the attributes of the database: Sample Code Number Clump Thickness Uniformity of Cell Size Uniformity of Cell Shape Marginal Adhesion Single Epithelial Cell Size Bare Nuclei Bland Chromatin Normal Nucleoli Mitosis Class We have taken this data in its original form. This dataset is available in UC Irvine Machine Learning Repository (7) IV. Experiment Our Experiment consists of four different modules which is further divided and does work in the following sequence as given in the figure 5 below. Figure 5: Modules of the Algorithm A. Modules of the Experiment 1) Pre processing In our dataset, not all the features are taking part in the classification process thus; we remove patients id feature. Then we left with ten attributes so we separate the feature set from the class values as Xij and Yi. a) Data Normalization After preprocessing stage Normalization of Xij (nine feature vectors) need to perform by using this equation: New_val = (current _val min value) / (Max value min value) Where, New_val = New value after scaling current_val = Current value of the feature vector Max_val = Maximum value of each feature vector Minvalue = Minimum value of each feature vector b) Data Conversion The new values (New_val) after getting from the previous step are truncated and converted into binary format. Then grouping was done on the base of range; the values falling in the range of 0 to 5 assigned as 0. Whereas, values in the range from 5 to 10 are assigned as 1.Then each sample as an input is given to ART1 network for training and testing purpose. 2) Recognition Stage Initially all components of the input vector were assigned to zero because no sample was applied to the input layer. This sets the other two layers to zero there by disabling all the neurons and results in zero output. Since all neurons are at the same stage, thus every neuron has an equal chance to win. The input vector then applied in the recognition layer, at each neuron performs a dot product between the input vector and its weight vector. A neuron that comes with the greatest dot product possesses the weights that most excellent matches input vector. It inhibits all the other outputs from that neuron from that layer. This indicates the recognition layer stores the patterns in the form of weights associated with neurons one for each class. 3) Comparison Stage In the recognition layer the network fired passes one back to the comparison layer when it passes the output signal. The comparison neurons that will fire are the one those receive simultaneously from the input feature vector and the comparison layer excitation vector. If there is a mismatch between these two, few neurons in the comparison layer will fire to the next layer until X got over. This means that the pattern P being feedback is not the one sought and neuron firing in the recognition layer should be inhibited. Then comparison of the symptoms vector and the inner layer vector and if the value is less then vigilance parameter, the network causes reset which causes the firing neuron in the recognition layer to zero and disable it for the current classification. 4) Search Stage The classification process finishes if the reset signal is not generated. Otherwise other patterns were researched to find the correct match. This method continues until either all the stored pattern has been tried or all recognition neurons are inhibited. V. Results The performance of the Algorithm studied is as under: The Training percentage and testing percentage total time taken and the relative efficiency when vigilance parameter is 0.5 is given by the chart. Figure 6 : The classification performance on Vigilance parameter 0.5 The efficiency of the Network with vigilance parameter 0.7 on different percentage of training and testing sets given in figure 7. And on taking the vigilance parameter as 0.7 but on different percentage of training and testing dataset we got better efficiency than that of in figure 7 as shown in figure 8. Figure 7: The Classification performance on Epoch 0.7 Figure 8: Calculation of Efficiency on different proportion of data The efficiency of the Network with vigilance parameter 0.9 on different percentage of training and testing sets given as under: Figure 9 : The Efficiency of the Network on Vigilance Parameter 0.9 The Maximum and Minimum time for training the Network on different tolerance factors is in the table as: Table 1: Calculation of Training time VI. Conclusion In this paper, we evaluated the adaptive resonance theory for the diagnosis of breast cancer using Wisconsin as data set. Several tests has been taken on different proportion of training and testing dataset and we concluded that by taking the vigilance parameter as 0.5 and taking the ratio of data as 90% for training and 10 % for testing we could achieve the better results. Although we have taken into account all the parameters in the further scope of research, we use the feature selection process so that we can reduce the time and improve the accuracy. In addition to that, we take the dataset from the local hospital so that we use that for the benefit of the society. References Journal of Cancer Research and Therapeutics. Afroz, Fir, et al. 2012, Vol. 8. Heart Disease Diagnosis using Support Vector. Shashikant Ghumbre, Chetan Patil,Ashok Ghatol. Pattaya: International Conference on Computer Science and Information Technology, Dec. 2011. Stefan Conrady, Dr. Lionel Jouffe. Breast Cancer Diagnostics with Bayesian Networks. s.l.: Bayesia, 2013. DONG, Yiping. A Study on Hardware Design for High Performance Artificial Neural Network by using FPGA and NoC . s.l.: Waseda University Doctoral Dissertation, July -2011. S N Sivanandan, S Sumathi , S N Deepa. Introduction to Neural Network and Matlab 6.0. s.l.: Tata Mc-Graw -Hill, 2006. Evaluation of Three Neural Network Models using Wisconsin Breast Cancer. K. Mumtaz, S. A. Sheriff,K. Duraiswamy. UCL Wisconsin data set. [Online] [Cited: 30 10 2014.] http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(.

Analysis of Francis Bacons The Four Idols Essay -- Four Idols Essays

Analysis of Francis Bacon's The Four Idols   Ã‚  Ã‚  Ã‚   In "The Four Idols," Francis Bacon discusses the concept of what fundamentally stands in the way of a human using the correct way of arriving upon a conclusion. Bacon believes there are four falsehoods that delay people from uncovering what they need to: the idols of the tribe, cave, marketplace and theater. At first I thought that these idols did not apply to humans at all, but now, after careful consideration, I understand how each idol relates to humankind.    The Idols of the Tribe represent the illusions of human nature: it refers to the idea that our everyday problems arise simply because we are humans. For example, it is human nature to think that there is more order in the world than there really is, to accept things as they are without question, and to not rest until we discover the truth about a certain subject. Humans tend to believe what they want to believe, even if there is evidence for the opposing theory; this is due to human free will as well as our emotional needs and responses. A prime illustration of these characteristics is that of the earth moving around the sun. At one point in time, many humans thought that the earth was the center of the universe and all things revolved around it (the earth). Though many philosophers and astronomers proposed alternate theories, the popular opinion stood. Even when evidence was presented in favor of the sun being the primary object the planets circled around, a great number of people stubbornly stuck with the old ways of thought.    The Idols of the Cave represent the illusions of the individual. Everyone has their own "cave" which alters their opinions differently, depending upon their... ...ecause I do not have experience concerning that culture. On the other hand when discussing any type of minority, I can contribute a great deal of the information I have gained from my childhood adventures.    In brief, I agree that we, as humans, tend to be set in our ways and many of our problems are related to miscommunication, along with the fact that our judgments are biased because of our experiences and education. Even though I believe that it is human nature to lean towards the more interesting argument, I do not agree that all humans follow the individual in command without questioning as well as disagreeing with their views on at least one subject.    Works Cited Bacon, Francis. "The Four Idols." Jacobus, 379-393. Jacobus, Lee A. A World of Ideas: Essential Readings for College Writers, 5th ed. Boston: Bedford Books, 1999.