abortion5 essays

abortion5 essays Of all of the issues being debated in the world today, perhaps the most controversial and intensely debated is abortion. This issue has forced its way into living rooms across the country through television, newspapers, and especially political campaigns. It has divided the community on many principles including peoples morals, ethnic background, and especially religious beliefs. However, many times people are too quick to jump on the bandwagon with one side or the other. They do not study the issue in order to develop a better understanding of what it is and why it may, or may not, be needed. This may be because of the fact that most people do not wish to go against public opinion. Perhaps they do not give the issue the attention it deserves, because someone has told them that it is a sin and should be banned from the face of the earth. Either way, this is a foolish course of action to take. Without looking at the history, uses, and the actual course of a procedure, it is impossible to give a valid and educated opinion on whether or not it should be practiced in todays medical field. Should they choose to look into the issue for themselves, people will realize that there are many methods of abortion practiced in todays medical field. Of the many different methods of abortion practiced in modern medicine, the most successful and safe procedures are carried out during the first trimester, or twelve-week period of fetal development. Of course birth control pills are the safest form of avoiding pregnancy. However, when this fails operations are necessary to prevent giving birth. The most common procedure, making up around 98% of the first trimester abortions, is Suction Aspiration. This is an operation in which the cervix is dilated, and a vacuum is used to remove the undeveloped fetus from the mothers womb. This is usually the most successful, as well as the safest procedure put to use these days. Howeve...

Critical Analysis of Huck Finn essays

Critical Analysis of Huck Finn essays Case Study of The Adventures of Huckleberry Finn The articles that are presented below explore adverse techniques of criticizing literary works. These critiques will be broken down to identify what technique of criticism is being used and what aspects correspond with the guidelines of that specific criticism. The criticisms identified below are psychoanalytic, cultural, and formalism criticisms. Society and Conscience in Huckleberry Finn: This article explores the depths of Hucks unconscious acting on the influence of his super ego. Levy examines the realms of the river signifying freedom and the banks symbolizing societal conformity and bondage, which Huck is reluctant to submit to. Also, this criticism fixes Pap as a symbol of natures depravity being conformed by community itself, which is the reason for a major part of Hucks scorn. Without the influential parental figure Huck resorts to establishing a relationship with Jim to compensate for his fathers incapabilities. Hucks relationship with Jim is, in this criticism, a result of his father having a lack of influence in his life, and Jim in a way replaces that kinship. Their relationship is shaped also by their lack of freedom and their struggle to obtain this right. Huck and Jims escape is explained as a release from the restrictions and pressures of conformity within society. Obviously there are racial tensions throughout this novel, but Huck and Jim ov ercome this obstacle by overlooking their differences and developing a close relationship. Both of these characters exhibit rebellious tendencies, which also contributes to their relationship. Hucks freedom is psychologically based rather than geographical. This freedom is a need to elude those stern guardians of authority and also the influence society has on people. Hucks conscious forces the effect of alienation caused by not only depression but also problems with his se...

Neural Networks for handwriting recognition Essay

Neural Networks for handwriting recognition - Essay Example In fact, a large number of researches have forecasted that in future billions of mobile and wireless systems will integrate handwriting recognition facilities. However, it is straightforward and uncomplicated to recognize handwriting when it appears in the form of isolated handwritten symbols as compared to un-segmented linked handwriting (with unidentified initial stages and ends of particular letters). Though, whatever the case is, we need excellent and high speed algorithmic capabilities (Ciresan et al., 2012; Schmidhuber, 2010). In addition, there are many scenarios where conventional techniques of computer vision and digital machine learning are not able to replace human capabilities, for example identification of traffic signs and handwritten digits. ... Additionally, simply winner neurons are qualified. In fact, a large number of deep neural columns turn out to be specialized on inputs preprocessed in diverse means; their forecasts are averaged. In this scenario, graphics cards should facilitate speedy training (Ciresan et al., 2012; Schmidhuber, 2010). Without a doubt, present automatic handwriting recognition tools and algorithms are not bad at learning to distinguish handwritten aspects and characters. However, convolutional neural Networks (CNNs) are believed to be highly appropriate and supportive architectures for handwriting recognition based systems. In this scenario, current convolutional neural networks pay particular attention to a wide variety of issues especially that relate to computer vision such as detection of natural images, traffic signs image segmentation, identification of 3D objects and image denoising. Additionally, CNN handwriting recognition techniques and architectures as well appear to offer a large number of advantages to unsupervised learning techniques and algorithms implemented to image data. In this scenario, several researchers have demonstrated an error rate of 0.4 percent of the worldwide MNIST (The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image) handwritten character based recognition dataset, with a reasonably straightforward Convolutional Neural Networks, in addition to elastic training image twists to increase the training data size. However, this handwriting recognition error rate further decreased to 0.35 percent in the 2010,