Analytical Essay Sample on Harry Potter

Analytical Essay Sample on Harry Potter Many children around the world can proudly say that the popular Harry Potter series are the best books that they have ever read. However, because of the recent controversy from some parents and several Christians, children might not have the chance to read or watch Harry Potter. They believe that it teaches witchcraft, which is extremely absurd. Harry Potter does not teach witchcraft, it actually gives children characters to relate to and learn from, it expands their imagination, and it helps them to read more. J.K. Rowlings characters are realistic and many children can understand and learn from them. The main character, Harry Potter, illustrates to the reader how anyone can be a hero without the significance of his or her appearance. Although Harry is physically small and scrawny, he is able to defeat the all-powerful enemy, Voldemort. He is capable of doing this because he believes in himself and has bravery. Harry shows bravery not just in his dangerous adventures, but when he stands up to bullies, which is a major problem to most kids during that age. Children can learn a great deal from Harry because he is an extraordinary hero that is identical to their age. In addition, numerous kids today know the experience of growing up without parents. Orphans know of the jealousy that Harry feels towards Ron and his enormous family. Harry is also an orphan and many foster children can have a character that they can relate and comprehend. His best friend Ron is also another character that many c an associate to. Ron comes from a family with financial problems and he is always left with hand-me-downs from his older brothers, which causes him to be a laughing stock at school. Several children in this world are familiar with this experience and through Ron, they can see that they are not alone. Ron also helps children with economic difficulties to learn that family is much more important than material needs. Hermoine completes the circle of the three best friends. Her special trait is her knowledge and her willingness to learn. Her character is one that everyone knows as the nerd. HermioneÐ ±Ã ¿s role proves how important knowledge can be and especially useful in hard times. She also shows that there is nothing bizarre about wanting to learn. Her motivation and the way she uses her knowledge is so powerful that she can inspire others to go out to educate themselves. These characters resemble the people that one sees in everyday life. They offer children familiar experiences and many beneficial morals. During the early years of ones life is when one has the broadest imagination. Harry Potter helps expand that imagination even greater. Even though Harry Potter has witches and warlocks doing witchcraft, it is all just fantasy and is like any other fantasy movie or book, except better. Things like a three-headed dog, a flying broomstick, and an invisibility cloak allows the reader to leave the reality world and go into a different world of their own. During the peak time of the Harry Potter booksÐ ±Ã ¿ popularity, a mother decided to read the series to her six-year old daughter who was going through cancer. The child, named Catie Hoch, fell in love with the books and became a huge fan. This is probably because of the storyÐ ±Ã ¿s magic and how it lets oneÐ ±Ã ¿s mind go off into fantasy. There is no doubt that the books gave happiness to this little girl during the hardest point of her short-lived life. J.K. Rowling actually got in contact with Catie and even got to read to her from her fourth book, which at that time was not yet released to the public. Sadly, however, she died before Rowling could finish reading the book to her. It is stories like these that the anti-supporters of the Harry Potter books should know about. Lastly, in a period where technology rules the earth, it is difficult for children to get their eyes off the TV. Reading Harry Potter was more fun than watching TV or playing video games (Kwon). If a child would prefer to read a book then watch TV, then the book must be very well written and extremely interesting, Harry Potter is just that. Although there are now Harry Potter movies, many can say that they have read the book and the book was even better than the movie(Kwon). By having children read rather than watching TV, it can help them to be better readers and writers which will help them in the future, while watching TV will just make them obese and lethargic. On the other hand, many believe that the Harry Potter books do nothing but show people how to do witchcraft. One pastor claimed, The books are going to destroy the lives of young people (Locals’). The churchÐ ±Ã ¿s Herculean opposition is nonsense. In December 2001, the Harry Potter series were among the books burned in a churchs holy bonfire. Many Christians explain: God says in Deuteronomy that witchcraft is an abomination† (Gibbs’). Although they are right about Gods saying on witchcraft, Harry Potter was not written to teach people to be witches and warlocks. Its main point is to entertain people. The author of the books said almost sarcastically: I have met thousands of children and not even one time has a child come up to me and said: Ms Rowling, Im so glad IÐ ±Ã ¿ve read these books because now I want to be a witch (Potter). One can tell that she is not serious about this topic, so why should we even be arguing over this ludicrous issue? Why can we not let children read books that they love and enjoy? Although some churches and priests are strongly against Harry Potter and tell people not to read it, it can actually be a good sermon topic. A conservative Vanguard Church in Colorado with 1,100 members actually used Harry Potter to teach Sunday school for the children. The teachers were dressed as wizards, and the church was entirely decorated, with darkened rooms and glow-in-the-dark props (Gibbs). They had the children put on the Sorting Hat that decides the fate of the young wizards in the book. The children were all put in the Slytherin House, the house of evil Voldemort; the way out, they were taught, could only come from following what God teaches (Gibbs). If other churches were more lenient and understanding, they would see, how using Harry Potter can be a beneficial way to learn. In conclusion, Harry Potter books do not teach people witchcraft and they do not encourage them to become witches or warlocks. The books actually give characters for children to learn and relate to, expand their imagination, and allow them to read more. If one could just try to be more considerate, they can enjoy and actually learn a few things from the books.

Jimenez Surname Meaning and Family History

Jimenez Surname Meaning and Family History The Jimenez surname most commonly means son of Jimeno or Simà ³n, given names meaning gracious hearkening; snub-nosed. Jimenez is a very common surname in Asturias, Aragà ³n, Castile, Navarre, Extremadura, Murcia and Andalusia; most anciently in Navarre and Aragà ³n. Jimenez is the 26th most common Hispanic surname. Surname origin:  SpanishAlternate surname spellings:  Jimenes Famous People With the Surname Hà ©ctor Jimà ©nez: Mexican actorMelissa Jimenez: Mexican American singer and songwriter Where Is This Surname Most Common? As of January 2019, the Jimenez surname is the 173rd most common surname in the world, according to surname distribution information from  Forebears. It is most prevalent, based on a percentage of the population, in Costa Rica, where it ranks as the 3rd most common surname. It is also extremely common in the Dominican Republic (9th), Spain (11th), Colombia (17th), Mexico (20th) and Panama (23rd). WorldNames PublicProfiler  includes data from countries not included in Forebears, including Spain where Jimenez is extremely popular. Jimenez is particularly prevalent in Andalucia and La Rioja, Spain, followed by the Spanish regions of Castilla-La Mancha, Navarra, Madrid, Murcia, Extremadura, Castilla y Leà ³n, and Cataluà ±a. Genealogy Resources Jimenez family crest: Contrary to what you may hear, there is no such thing as a Jimenez family crest or coat of arms for the Jimenez surname.  Coats of arms are granted to individuals, not families, and may rightfully be used only by the uninterrupted male-line descendants of the person to whom the coat of arms was originally granted.Jimenez family genealogy forum: This free message board is focused on the descendants of Jimenez ancestors around the world. Search the forum for posts about your Jimenez ancestors, or join the forum and post your own queries.  FamilySearch: Explore over 3.6  million  results from digitized  historical records and lineage-linked family trees related to the Jimenez surname on this free website hosted by the Church of Jesus Christ of Latter-day Saints.GeneaNet: Includes archival records, family trees, and other resources for individuals with the Jimenez surname, with a concentration on records and families from France and other European countrie s.The Jimenez genealogy and family tree page: Browse genealogy records and links to genealogical and historical records for individuals with the Jimenez surname from the website of Genealogy Today. Ancestry.com: Explore over 4  million digitized records and database entries, including census records, passenger lists, military records, land deeds, probates, wills and other records for the Jimenez surname on the subscription-based website, Ancestry.com References Cottle, Basil.  Penguin Dictionary of Surnames. Baltimore, MD: Penguin Books, 1967.Dorward, David.  Scottish Surnames. Collins Celtic (Pocket edition), 1998.Fucilla, Joseph.  Our Italian Surnames. Genealogical Publishing Company, 2003.Hanks, Patrick and Flavia Hodges.  A Dictionary of Surnames. Oxford University Press, 1989.Hanks, Patrick.  Dictionary of American Family Names. Oxford University Press, 2003.Reaney, P.H.  A Dictionary of English Surnames. Oxford University Press, 1997.Smith, Elsdon C.  American Surnames. Genealogical Publishing Company, 1997.

Survey Description Essay Example | Topics and Well Written Essays - 250 words

Survey Description - Essay Example The demographic questions only focused on the gender and educational level of the participants. The informational questions focused on getting participants opinion on what their thought was about their major, their satisfaction level of the major they are undertaking and whether it was easy for the members to choose their major. For example, the last informational question ask the students whether the preparatory year in college can help a student in selecting the major to pursue. The survey was conducted through writing questionnaires and sending them to students and faculty at English Language Center, using the well-known survey website Survey Monkey. The small number of questions encouraged the students to take part in the survey since it did not consume a lot of their time. There was a total of 16 students taking part with a majority, 14, being female, and only two male students participated in the survey. From the survey 6 were graduate students, 4 were undergraduate and the remaining 6 specified other as their educational level. The major finding from the survey are as follows: Many people start thinking about the major they are going to take at elementary school level. A majority of the student, 71.43%, are satisfied with the major they are taking. Almost half of the participants believe that preparatory year sometimes helps a student choose a

Research Paper (Based on Literature Reviews) Example | Topics and Well Written Essays - 1750 words

(Based on Literature Reviews) - Research Paper Example Currently in legislation is the Fairness in Cocaine Sentencing Act of 2009, which would equalize penalties for crack and powder cocaine, thus correcting the injustice. The previous seven bills similar to the Fairness in Cocaine Sentencing Act of 2009 have not been approved. Congress and the President need to review and pass this bill and make it a reality. The main objective of this paper is to examine the facts or statements of truth that can be examined in the context of racial discrimination in the sentencing of drug offenders and to arrive at conclusions accordingly. It is known that disparities in sentencing are arbitrary for a number of reasons. Before the introduction of the federal compulsory minimum sentencing in 1986 for drugs related violations, the federal drug sentencing in the case of African Americans was higher by 11 percent as compared to whites. After four years this average was higher by 49 percent. In 2000 the proportion of African American people lodged in jails was much more than those in higher education. On the basis of such facts, leading analysts concluded that the country’s crime policy was a significant contributing factor in disrupting African American families. The impact of the compulsory minimum imprisonment for drug offenses contributed in leading to unreasonably high rate of incarceration and a lso separated family members from each other on account of minor crimes amongst their children. Such practices not only created large scale disfranchisement amongst those that were convicted of felony but also prohibited people that were incarcerated earlier, from getting appropriate social services in improving their families (Russel, 2005). These statements will be examined in the light of available sources and efforts will be made to determine the strength in such assertions. As reported recently by the Sentencing Commission, there is a strong need to revise the

Symbolic Learning Methods Essay Example for Free

Symbolic Learning Methods Essay Abstract In this paper, performance of symbolic learning algorithms and neural learning algorithms on different kinds of datasets has been evaluated. Experimental results on the datasets indicate that in the absence of noise, the performances of symbolic and neural learning methods were comparable in most of the cases. For datasets containing only symbolic attributes, in the presence of noise, the performance of neural learning methods was superior to symbolic learning methods. But for datasets containing mixed attributes (few numeric and few nominal), the recent versions of the symbolic learning algorithms performed better when noise was introduced into the datasets. 1. Introduction The problem most often addressed by both neural network and symbolic learning systems is the inductive acquisition of concepts from examples [1]. This problem can be briefly defined as follows: given descriptions of a set of examples each labeled as belonging to a particular class, determine a procedure for correctly assigning new examples to these classes. In the neural network literature, this problem is frequently referred to as supervised or associative learning. For supervised learning, both the symbolic and neural learning methods require the same input data, which is a set of classified examples represented as feature vectors. The performance of both types of learning systems is evaluated by testing how well these systems can accurately classify new examples. Symbolic learning algorithms have been tested on problems ranging from soybean disease diagnosis [2] to classifying chess end games [3]. Neural learning algorithms have been tested on problems ranging from converting text to speech [4] to evaluating moves in backgammon [5]. In this paper, the current problem is to do a comparative evaluation of the performances of the symbolic learning methods which use decision trees such as ID3 [6] and its revised versions like C4.5 [7] against neural learning methods like Multilayer perceptrons [8] which implements a feed-forward neural network with error back propagation. Since the late 1980s, several studies have been done that compared the performance of symbolic learning approaches to the neural network techniques. Fisher and McKusick [9] compared ID3 and Backpropagation on the basis of both prediction accuracy and the length of training. According to their conclusions, Backpropagation attained a slightly higher accuracy. Mooney et al., [10] found that ID3 was faster than a Backpropagation network, but the Backpropagation network was more adaptive to noisy data sets. Shavlik et al., [1] compared ID3 algorithm with perceptron and backpropagation neural learning algorithms. They found that in all cases, backpropagation took much longer to train but the accuracies varied slightly depending on the type of dataset. Besides accuracy and learning time, this paper investigated three additional aspects of empirical learning, namely, the dependence on the amount of training data, the ability to handle imperfect data of various types and the ability to utilize distributed output encodings. Depending upon the type of datasets they worked on, some authors claimed that symbolic learning methods were quite superior to neural nets while some others claimed that accuracies predicted by neural nets were far better than symbolic learning methods. The hypothesis being made is that in case of noise free data, ID3 gives faster results whose accuracy will be comparable to that of back propagation techniques. But in case of noisy data, neural networks will perform better than ID3 though the time taken will be more in case of neural networks. Also, in the case of noisy data, performance of C4.5 and neural nets will be comparable since C4.5 too is resistant to noise to an extent due to pruning. 2. Symbolic Learning Methods In ID3, the system constructs a decision tree from a set of training objects. At each node of the tree the training objects are partitioned by their value along a single attribute. An information theoretic measure is used to select the attribute whose values improve prediction of class membership above the accuracy expected from a random guess. The training set is recursively decomposed in this manner until no remaining attribute improves prediction in a statistically significant manner when the confidence factor is supplied by the user. So, ID3 method uses Information Gain heuristic which is based on Shannon’s entropy to build efficient decision trees. But one dis advantage with ID3 is that it overfits the training data. So, it gives rise to decision trees which are too specific and hence this approach is not noise resistant when tested on novel examples. Another disadvantage is that it cannot deal with missing attributes and requires all attributes to have nominal values. C4.5 is an improved version of ID3 which prevents over-fitting of training data by pruning the decision tree when required, thus making it more noise resistant. 3. Neural Network Learning Methods Multilayer perceptron is a layered network comprising of input nodes, hidden nodes and output nodes [11]. The error values are back propagated from the output nodes to the input nodes via the hidden nodes. Considerable time is required to build a neural network but once it is done, classification is quite fast. Neural networks are robust to noisy data as long as too many epochs are not considered since they do not overfit the training data. 4. Evaluation Design For the evaluation purposes, a free and popular software tool called Weka (Waikato Environment for Knowledge Acquisition) is used. This software has the implementations of several machine learning algorithms made easily accessible to the user with the help of graphical user interfaces. The training and the test datasets have been taken from the UCI machine learning repository. Two different types of datasets will be used for the evaluation purposes. One type of datasets contain only symbolic attributes (Symbolic Datasets) and the other type contain mixed attributes (Numeric Datasets). Performance of the different learning methods will be evaluated using the original datasets which do not contain any noise and after introducing noise into them. Noise is introduced in the class attributes of the datasets by using the ‘AddNoise’ filter option in Weka which adds the specified percentage of noise randomly into the datasets. Symbolic Datasets are those which contain only symbolic attributes. Symbolic learning methods like ID3 and its recent developments can be run only on datasets where all the attributes are nominal. In Weka, these nominal attributes are automatically converted to numeric ones for neural network learning methods. So, preprocessing is not required in this type of datasets. Numeric Datasets are those which contain few nominal and few numeric attributes. Since symbolic learning methods like ID3 and its recent developments can be run only on datasets where all the attributes are nominal, these datasets first need to be preprocessed. A ‘Discretize’ filter option available in Weka is used to discretize all the non-symbolic attribute values into individual intervals so that each attribute can now be treated as a symbolic one. Initially, the entire data being considered is randomized. Two types of evaluation techniques are being used to analyze the data. (a) Percentage Split: In general, the data will be split up randomly into training data and test data. In the experiments conducted, the data will be split such that training data comprises 66% of the entire data and the rest is used for testing. (b) K-fold Cross-validation: In general, the data is split into k disjoint subsets and one of it is used as testing data and the rest of them are used as training data. This is continued till every subset has been used once as a testing dataset. In the experiments conducted, 5-fold cross validation was done. 5. Experimental Results Experiments were conducted on two symbolic datasets and two numeric datasets. The two symbolic datasets are tic-tac-toe and chess. The two numeric datasets are segment and teacher’s assistant evaluation (tae). DataSet 1 : TIC-TAC-TOE (a) 5-fold cross validation (i)Without any noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii) Percentage of noisy data = 10% Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 Time to build 0.03 6.16 0.02 0.06 0.01 % correct 67.4322 81.8372 75.8873 73.5908 71.2944 % incorrect 28.0793 18.1628 24.1127 26.4092 28.7056 % not classified 4.4885 0 0 0 0 Time to build 0.06 6.35 0.06 0.01 0.02 % correct 86.1169 97.4948 85.8038 87.5783 83.1942 % incorrect 11.691 2.5052 14.1962 12.4217 16.8058 % not classified 2.1921 0 0 0 0 (b) Percentage split with training data being 66% and the rest is testing data (i)Without Noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii)Percentage of Noisy data = 10% Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 Time to build 0.05 6.5 0.01 0.01 0.02 % correct 85.5828 97.546 83.1288 88.0368 82.2086 % incorrect 11.0429 2.454 16.8712 11.9632 17.7914 % not classified 3.3742 0 0 0 0 Time to build 0.04 6.15 0.02 0.02 0.01 % correct 68.4049 80.6748 73.9264 72.3926 71.4724 % incorrect 28.2209 19.3252 26.0736 27.6074 28.5276 % not classified 3.3742 0 0 0 0 For the tic-tac-toe dataset, in the presence of noise, neural nets had better prediction accuracies than all the other algorithms as expected. Though C4.5 gives better accuracy than ID3, its accuracy is still lower in comparison to Neural Nets. If the pruning factor (confidence factor was lowered) was increased, the prediction accuracies of C4.5 dropped a little. But in the absence of noise, the performances of ID3 and Multilayer Perceptron should have been comparable. But the performance of Multilayer Perceptron is quite superior to ID3. DataSet 2 : CHESS (a) 5-fold cross validation (i)Without any noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii) Percentage of noisy data = 10% Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 Time to build 0.36 47.75 0.21 0.18 0.19 % correct 81.1952 86.796 89.0488 84.6683 88.4856 % incorrect 18.8048 13.204 10.9512 15.3317 11.5144 % not classified 0 0 0 0 0 Time to build 0.21 47.67 0.15 0.05 0.1 % correct 99.562 97.4656 99.3742 99.3116 99.2178 % incorrect 0.438 2.5344 0.6258 0.6884 0.7822 % not classified 0 0 0 0 0 (b) Percentage split with training data being 66% and the rest is testing data (i)Without Noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii)Percentage of Noisy data = 10% Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 Time to build 0.33 41.73 0.24 0.19 0.19 % correct 80.1288 85.7406 87.5805 82.6127 87.6725 % incorrect 19.8712 14.2594 12.4195 17.3873 12.3275 % not classified 0 0 0 0 0 Time to build 0.13 43.55 0.06 0.06 0.08 % correct 99.448 97.1481 99.08 98.988 99.08 % incorrect 0.552 2.8519 0.92 1.012 0.92 % not classified 0 0 0 0 0 For the chess dataset, in the absence of noise, the performance of ID3 is better than that of Multilayer perceptron and takes lesser time. For the noisy data, back propagation predicts better accuracies than that of ID3 as expected, but the performance of C4.5 is slightly higher than back propagation. The reason for this could be that the feature space in this dataset is more relevant. So, C4.5 builds a tree and prunes it to get a more efficient tree. DataSet 3 : SEGMENT (a) 5-fold cross validation (i) Without any noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii) Percentage of noisy data = 10% Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 Time to build 0.07 9.64 0.04 0.04 0.03 % correct 68.9333 80.8667 81.2667 79.6 80.5333 % incorrect 21.3333 19.1333 18.7333 20.4 19.4667 % not classified 9.7333 0 0 0 0 Time to build 0.05 10.3 0.02 0.23 0.12 % correct 88.0667 90.6 91.6 94 94.3333 % incorrect 5.2 9.4 8.4 6 5.6667 % not classified 6.7333 0 0 0 0 (b) Percentage split with training data being 66% and the rest is testing data (i) Without Noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii) Percentage of Noisy data = 10% Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 Time to build 0.07 11.73 0.03 0.04 0.03 % correct 72.9412 82.549 82.1569 82.549 81.3725 % incorrect 19.6078 17.451 17.8431 17.451 18.6275 % not classified 7.451 0 0 0 0 Time to build 0.06 9.87 0.03 0.02 0.03 % correct 89.8039 87.6471 92.1569 93.7255 90.1961 % incorrect 4.1176 12.3529 7.8431 6.2745 9.8039 % not classified 6.0784 0 0 0 0 Segment, being a numeric dataset, all the attribute values had to be discretized before running the algorithms. In the absence of noise, ID3 performs slightly better than back propagation and the performance of J48 (implementation of C4.5 in Weka) is much better than ID3 and backpropagation. But a very interesting observation was found. In the absence of noise, the performance of an unpruned tree generated by C4.5 was quite superior to the rest. In the presence of noise, the performances of back propagation and C4.5 were comparable. DataSet 4 : TAE (a) 5-fold cross validation (i) Without any noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii) Percentage of noisy data = 10% Time to % % build correct incorrect ID3 0.02 53.6424 37.0861 Multilayer Perceptron 0.16 38.4106 61.5894 J48 0.02 52.9801 47.0199 C4.5 unpruned 0.01 56.2914 43.7086 C4.5 confidence factor = 0.1 0.01 54.3046 45.6954 (b) Percentage split with training data being 66% and the rest is testing data (i) Without Noise: Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 (ii) Percentage of Noisy data = 10% Classifiers ID3 Multilayer Perceptron J48 C4.5 unpruned C4.5 confidence factor = 0.1 Time to build 0.01 0.17 0.01 0.01 0.01 % correct 38.4615 44.2308 44.2308 50 44.2308 % incorrect 40.3846 55.7692 55.7692 50 55.7692 % not classified 21.1538 0 0 0 0 Time to build 0.02 2.23 0.03 0.02 0.01 % correct 44.2308 57.6923 51.9231 55.7692 42.3077 % incorrect 34.6154 42.3077 48.0769 44.2308 57.6923 % not classified 21.1538 0 0 0 0 Classifiers % not classified 0 0 0 0 0 Time to build 0.02 0.18 0.02 0.01 0.01 % correct 54.3046 54.9669 48.3444 50.9934 47.0199 % incorrect 35.0993 45.0331 51.6556 49.0066 52.9801 % not classified 10.596 0 0 0 0 TAE, being a numeric dataset, its attribute values had to be discretized too before running the algorithms. But after observing the results, it is very clear that the random discretization provided by Weka did not generate good intervals due to which the overall accuracy predicted by all the methods is quite poor. Again, interestingly an unpruned tree built by C4.5 seems to give high prediction accuracies relative to the rest in most of the cases. In this case, for cross-validation approach and noisy data, surprisingly the performance of back-propagation was very poor. One reason for this could be that only few epochs of the training data were run to build the neural network. In the absence of noise, accuracy prediction of Multilayer perceptron was either comparable or greater than that of ID3. 6. Conclusion No single machine learning algorithm can be considered superior to the rest. The performance of each algorithm depends on what type of dataset is being considered, whether the f eature space is relevant and whether the data contains noise. In the absence of noise, in some cases, the performance of ID3 was comparable or sometimes better than back-propagation and was faster but in some cases Multilayer perceptron performed better. When noisy datasets were considered, back propagation definitely did better than ID3 though it took more time to build the neural network. But in the presence of noise, in some cases, C4.5 gave faster and better results when the attributes being considered were relevant. But some surprising observations were made when the attribute values of the numeric datasets were discretized, the prediction accuracy of an unpruned tree generated by C4.5 algorithm was much higher than the rest. This shows that the unpruned tree generated by C4.5 is not the same as that generated by ID3. References: 1.Mooney, R., Shalvik, J., and Towell, G. (1991): Symbolic and Neural Learning Algorithms An experimental comparison, in Machine Learning 6, pp. 111-143. 2. Michalski, R.S., Chilausky, R.L. (1980): Learning by being told and learning from examples An experimental comparison of two methods of knowledge acquisition in the context of developing an expert system for soybean disease diagnosis, in Policy Analysis and Information Systems, 4, pp. 125-160. 3. Quinlan, J.R. (1983): Learning efficient classification procedures and their application to chess end games in R.S. Michalski, J.G. Carbonell, T.M. Mitchell (Eds.), in Machine learning: An artificial intelligence approach (Vol. 1). Palo Alto, CA: Tioga. 4. Sejnowski, T.J., Rosenberg, C. (1987): Parallel networks that learn to pronounce English text, in Complex Systems, 1, pp. 145-168. 5. Tesauro, G., Sejnowski, T.J. (1989): A p arallel network that learns to play backgammon, in Artificial Intelligence, 39, pp. 357-390. 6. Quinlan, J.R. (1986): Induction on Decision Trees, in Machine Learning 1, 1 7. Quinlan, J.R. (1993): C4.5 – Programs for Machine Learning. San Mateo: Morgan Kaufmann. 8. Rumelhart, D., Hinton, G., Williams, J. (1986): Learning Internal Representations by Error Propagation, in Parallel Distributed Processing, Vol. 1 (D. Rumelhart k J. McClelland, eds.). MIT Press. 9. Fisher, D.H. and McKusick, K.B. (1989): An empirical comparison of ID3 and backpropagation, in Proc. of the Eleventh International Joint Conference on Artificia1 Intelligence (IJCAI-89), Detroit, MI, August 20-25, pp. 788-793. 10. Mooney, R., Shavlik, J., Towell, G., and Gove, A.(1989): An experimental comparison of symbolic and connectionist learning algorithms, in Proc. of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), Detroit, MI, August 20-25, pp. 775-780. 11. McClelland, J. k Rumelhart, D. (1988). Explorations in Parallel Distributed Processing, MIT Press, Cambridge, MA.

Analysis of Hawthornes Young Goodman Brown Essay -- Young Goodman Bro

Analysis of Young Goodman Brown "Young Goodman Brown" by Nathanial Hawthorne is a short story that is very interesting, as well as entertaining. This essay will first provide a brief summary of the story, followed by an analysis of the importance of symbolism. The nature of evil will then be discussed as it relates to the control of the mind of a once naive and innocent goodman Brown. The climax of the story will be analyzed and the evil within this passage will be discussed and related to the final downfall of goodman Brown. As "Young Goodman Brown" begins, we are introduced to goodman Brown and his wife Faith as they bid farewell to one another on the streets of Salem village. It is sunset and goodman Brown is setting off on a journey to run a secret errand. We later find out that he is planning on meeting Satan and sacrificing his soul to pure evil. Throughout the story, goodman Brown is tormented by the idea of evil and he is doubtful of weather or not he should continue on his journey. He is finally persuaded, however, when he hears Faith turn herself over to Satan. Toward the end of the story we find out that this whole excursion may have been a dream, but even so, goodman Brown was so impacted by it that he will never recover to live a peaceful, happy life. He will die a miserable death, with no hopeful verse carved upon his tomb, for as we are told in the final line of the story, `his dying hour was gloom'(pg.585). Symbolism plays an important role in this story, as it does in many of Hawthornes stories. First of all, the fact that goodman Brown's wife is named Faithis... ...good and evil as he has been throughout the story, but here it is different because it is the moment of truth in which he would either choose good over evil or evil over good. We never know which he ended up choosing, but it appears that he chose evil because for the rest of his life, he can see no good in anything or anybody. Evil rules his existence as he is haunted by guilt that will not let him enjoy the beautiful things in this world. This choice signifies goodman Brown's final downfall into the arms of evil, as he will be destined to live a life of misery. No good will ever be seen, heard, or understood by goodman Brown again, for he only sees the evil in this world. As we are told in the final passage of this story, when goodman Brown finally leaves this world, "they carved not a hopeful verse upon his tombstone; for his final hour was gloom."(pg.585) Analysis of Hawthorne's Young Goodman Brown Essay -- Young Goodman Bro Analysis of Young Goodman Brown "Young Goodman Brown" by Nathanial Hawthorne is a short story that is very interesting, as well as entertaining. This essay will first provide a brief summary of the story, followed by an analysis of the importance of symbolism. The nature of evil will then be discussed as it relates to the control of the mind of a once naive and innocent goodman Brown. The climax of the story will be analyzed and the evil within this passage will be discussed and related to the final downfall of goodman Brown. As "Young Goodman Brown" begins, we are introduced to goodman Brown and his wife Faith as they bid farewell to one another on the streets of Salem village. It is sunset and goodman Brown is setting off on a journey to run a secret errand. We later find out that he is planning on meeting Satan and sacrificing his soul to pure evil. Throughout the story, goodman Brown is tormented by the idea of evil and he is doubtful of weather or not he should continue on his journey. He is finally persuaded, however, when he hears Faith turn herself over to Satan. Toward the end of the story we find out that this whole excursion may have been a dream, but even so, goodman Brown was so impacted by it that he will never recover to live a peaceful, happy life. He will die a miserable death, with no hopeful verse carved upon his tomb, for as we are told in the final line of the story, `his dying hour was gloom'(pg.585). Symbolism plays an important role in this story, as it does in many of Hawthornes stories. First of all, the fact that goodman Brown's wife is named Faithis... ...good and evil as he has been throughout the story, but here it is different because it is the moment of truth in which he would either choose good over evil or evil over good. We never know which he ended up choosing, but it appears that he chose evil because for the rest of his life, he can see no good in anything or anybody. Evil rules his existence as he is haunted by guilt that will not let him enjoy the beautiful things in this world. This choice signifies goodman Brown's final downfall into the arms of evil, as he will be destined to live a life of misery. No good will ever be seen, heard, or understood by goodman Brown again, for he only sees the evil in this world. As we are told in the final passage of this story, when goodman Brown finally leaves this world, "they carved not a hopeful verse upon his tombstone; for his final hour was gloom."(pg.585)

Homework Is Bad

Homework is harmful to my health? When I first read the topic, a big question mark appeared in my mind. I haven’t thought that homework is harmful to my health because I have been taught that doing homework is students’ duty. However, in my opinion, too much homework is really harmful to my health according to the following reasons. First of all, too much homework exhausts brains and bodies, so I can’t have a good rest.I stay in school almost ten hours from 7 a. m. to 5 p. m. on weekdays. When getting home, I am extremely tired, but I still have to cheer up to finish daily homework. As a result, I don’t have any time to take a rest. Second, too much homework leads to insufficient sleep. I have different homework from different subjects. Take me for example, as a second grader in senior high school, on average I usually spend 2 or 3 hours on homework every day.When having lots of homework to do, I will stay up late to complete homework. Unfortunately, I sti ll have to get up early next morning, so I can’t get enough sleep. Third, too much homework causes stress, especially so-called difficult homework. When I can’t solve difficult problems by myself, such as problems in math, chemistry, and physics, I am absolutely obsessed with these difficult problems and then they become my heavy burdens and pressure.Fourth, doing too much homework makes eyes extremely tired and eventually it may cause near-sighted. I wear glasses because I ignore the importance of right gestures and bright light while doing homework. According to these above reasons, I firmly believe that too much homework is harmful to my health. Although too much homework may be harmful to my health, adequate homework is beneficial to my studies. After all, doing homework is one of my duties.

Organizational Design and Structure Essay

People are interested in great stories of great success. Lincoln Electric uses such practices as Intensive employee involvement (Advisory committee, Suggestions plan); Job security; Compensation (Piece-rate system, Bonuses, Report cards); Points for process improvements; Strong management control; No paid sick days; No paid training. General Electric is committed to equal employment opportunity, a basic of a free society. By continuing to extend equal opportunity and provide fair treatment to all employees on the basis of merit, we will improve GE’s success while enhancing the progress of individuals and the communities where our businesses are located. These two companies have different structures. But they are both successful. A narrow span of control consists of only a few employees; a wide span of control includes many employees. The tendency nowadays is to flatten organizations by widening the span of control and decreasing the layers of management (hierarchy), and by relying more on employee teams to take on many of the roles formerly performed only by managers. There is a limit to number of employees any one manager can properly supervise. If a supervisor has a wide span-of-control she is supervising activities of many people. If span-of-control is narrow few subordinates report to her. Wide span-of-control is possible in most assembly line situations where each employee has only a few repetitive tasks to perform. Wide span-of-control is possible in situations where subordinates are highly educated. Narrow span-of-control is advisable when cost of making an error or wrong decision is high. History indicates that a wide span-of-control is more productive in long-run. While different, Gen X and Gen Y have some similarities. Both will demand a more innovative workplace, with flexible hours, state-of-the-art resources, cooperative scheduling and supervisors who listen. One of the reasons Gen X and Y will be so valuable is that there will be a shortage of skilled managers to replace the retiring Traditionalists and Boomers. Developing experienced and skilled young managers will become vital to any organization hoping to compete in the future. The Apprentice. I will advice for women and men to improve the following features: Leadership takes courage and initiative. (Initiative is a critical component of good leadership. ); Self-awareness and self-correcting leadership; High energy. (A great leadership rule: if you want it, model it); No direction (clarity of roles and expectations), protection or order. A successful leader with a new team needs to set the stage for success by facilitating an initial session (order) to determine how the team will work together most effectively to achieve their task or goal. A leader should inspire confidence by creating a safe container (protection) for the team to elicit the highest of collaboration, creativity and effective strategy. All components of organisational design and structure were taken up. Organizational Redesign is structuring an organization, division or department to optimize how it supplies products and services to its clients and customers. The process of organization design matches people, information, and technology to the purpose, vision, and strategy of the organization. Structure is designed to enhance communication and information flow among people. Systems are designed to encourage individual responsibility and decision making. Technology is used to enhance human capabilities to accomplish meaningful work. The end product is an integrated system of people and resources, tailored to the specific direction of the organization.

Why You Shouldnt Trust US News College Rankings

Why You Shouldn't Trust US News College Rankings SAT / ACT Prep Online Guides and Tips US News is probably the most popular source out there for college rankings. While US News rankings of colleges purport to be highly accurate, they can be misleading in certain important respects. If you make decisions based purely on the US News college rankings, you might end up being miserable. In this article, I’ll go over why you shouldn’t make judgments about colleges solely based on their rankings in US News. What Types of Rankings Does US News Provide? US News divides its college rankings into four different categories.The categories are based on the 2010 Basic Classification system developed by the Carnegie Foundation for the Advancement of Teaching.This system has 12 categories of schools, but US News condenses them into four.These include: National Universities These are schools that offer master's and doctoral degrees along with a full range of undergraduate majors.This category contains â€Å"research universities†, where there is a strong emphasis on research and government subsidies are often provided for research endeavors.There are 280 universities that fall into this category, including 173 public schools, 100 private schools, and 7 for-profit schools. National Liberal Arts Colleges These are colleges that emphasize undergraduate education and give out at least half of their degrees in liberal arts disciplines including languages and literature, biology and life sciences, philosophy, cultural studies, and psychology.There are 227 of these colleges, 221 private, 27 public, and one for profit. Regional Universities These colleges are similar to National Universities in that they offer both a full range of undergraduate majors and master’s programs.However, they offer limited or nonexistent doctoral programs.There are 620 Regional Universities, including 262 public, 346 private, and 12 for profit. Regional Colleges These are colleges that focus on undergraduate education but have less of a liberal arts emphasis (award less than half of their degrees in liberal arts disciplines).There are 364 regional colleges that include 94 public schools, 253 private schools, and 17 for-profit schools. It’s important to consider these categories because they should affect how you view the rankings.US News specifically states that you shouldn’t compare the rankings of two colleges across two different categories; the schools are so different that making a direct comparison is not logical.You can compare the actual statistics (such as admissions rate, student retention, and average class size), but in terms of rank itself, a school that’s ranked 40th in the National Universities category is not objectively â€Å"worse† than a school that’s ranked 32nd in the National Liberal Arts Colleges category. Very liberal art How Does US News Rank Colleges? There is a strong methodology behind the ranking system that US News uses for colleges, and it changes often to adapt to changing conditions in higher education.Many factors are considered, and percentage weights are given to each component of the assessment. A total weight of 30% is given to factors related to student retention and graduation rates (meaning this is the most highly considered single factor in the ranking process) Graduation and retention measures are given a weight of 22.5% A 7.5% weight is devoted to a measure of whether a school is over or underperforming based on the number of students that graduate (comparing the expected vs. actual graduation rate) US News gives a 22.5% percentage weight to a school’s academic reputation scores For National Universities and National Liberal Arts Colleges, this is based on a peer survey of academics (weighted 15%) and a survey of high school counselors (weighted 7.5%) For Regional Universities and Regional Colleges, it is based solely on a survey of the academic peer group for the full 22.5% The remaining weight of 47.5% is devoted to hard statistics about the school including measures of academic quality such as selectivity, faculty information, financial resources, and alumni giving. To create school scores, US News gathers statistics in 16 areas related to the academic quality of the school. Each is assigned a percentage based on US News’ â€Å"judgments about which measures of quality matter most†. US News publishes the numerical rank of the top 75% of schools in each of the four categories. Remaining schools are placed in the â€Å"second tier† of rankings where specific numerical ranking is not listed (they’re just put in alphabetical order). The gold star that US News gives to colleges in the second tier. What’s Not to Trust? When I say you shouldn’t trust the rankings, I don’t mean that US News is deliberately misleading students.What I mean is that you shouldn’t put ALL your trust in these rankings and disregard your other preferences about college.You should also be aware of some shortcomings that may cause the rankings to exclude certain schools or rank colleges lower than they would be ranked on a list of â€Å"Best Colleges for You, Student Reading This Article†.Here are some things you should know before consulting the US News rankings in your college search: Some schools won’t be ranked if they don't meet the criteria In fact, there are 148 colleges that are â€Å"unranked† within the four categories listed above.These schools may be unranked for a variety of reasons - these include: Lack of regional accreditation Fewer than 200 students enrolled Do not use the SAT or ACT in admissions decisions Not enough responses on the US News peer assessment survey US News lists unranked schools, but they are put in alphabetical order at the end of each college category without any value judgment.This means that if you’re interested in very small colleges or colleges that don’t use the SAT or ACT in admissions decisions, the rankings may not help you much. The most common reason for a school to be unranked is that it doesn’t use standardized tests.US News argues that there isn’t enough data to compare the school to other institutions in the category without test scores, so it has to remain unranked.This may be a valid point, but it means that schools that may otherwise have solid academics are excluded from rankings, leaving you with a slightly less complete picture of the college landscape. There is an emphasis on ultimate results and academic rigor over quality of student life On the website for US News, it states, â€Å"over time, the ranking model has put less emphasis on input measures of quality – which look at characteristics of the students, faculty and other resources going into the educational process – and more emphasis on output measures, which look at the results of the educational process, such as graduation and freshman retention rates.†There is no doubt that graduation rates are important, and they do say a lot about the quality of a college.However, they will tell you very little about whether a school is a nice place to spend four years, especially if the school is very academically rigorous and prestigious. Most students will graduate because they’re very driven, but that doesn't tell you whether or not they enjoyed their time there. The US News rankings are based on hard statistics and information gleaned from academic peer reviews about the quality of the school.While this is very useful in determining how favorably the school is viewed from the heights of the academic Ivory Tower, it isn’t always the best metric for conducting your search process.Even though focusing on outcome does make sense to a certain degree, it also fails to fully evaluate the quality of the student experience.This can contribute to a somewhat harmful â€Å"ends justify the means† mindset that leads students to spend years in places where they are outwardly successful but inwardly unhappy. The official motto of both US News and your one friend who won't shut up about CrossFit Prestige plays an important role For many students, prestige remains an important factor in deciding whether to attend a college.It’s hard to resist the allure of a school that will impress other people and potentially get you good jobs down the road based on its name recognition. This is the reason why prestige is considered so strongly by US News in its rankings (in the form of ratings from academic peer groups and guidance counselors).Of course, prestige correlates with selectivity in admissions and respect from the higher education community at large, so it does indicate some measure of academic quality. However, measuring schools based on prestige can have the unfortunate consequence of discounting some up and coming colleges or colleges that may have a unique focus and be less well-known.Make sure youuse other resources to research schools that have the criteria you’re looking for - even if they’re not ranked especially high, they may be a much better fit for your goals. Private schools always rank higher In the US News rankings, private schools are always more highly ranked than public schools.This can be misleading, and shouldn’t dissuade you from attending a public school!The reason this happens is because the ranking model US News uses is naturally kinder to private schools: they usually score higher on measures of selectivity, student retention rates, and small class sizes.Since public schools tend to be larger and less selective, they end up with lower rankings, but that means very little for high achieving students who choose to attend public schools. Though the statistics are often less impressive than those of private schools, the public college experience may allow many students to thrive.For students who are willing to seek out resources, public schools are often good choices because of the amount of different programs and high-level research facilities they offer.Rankings also don’t consider the diversity of social life at schools and the opportunities in the form ofextracurricular activities. Hi! I'm Chase, your new roommate. I like sailing and refusing to look at the world from anyone else's perspective. The rankings won’t help you to find an affordable school If you’re trying to avoid debt in college, you’ll need to look at other lists to figure out which schools are the most affordable.Rankings in US News have nothing to do with the cost of schools, so they won’t give you the perspective you’re looking for if cost is a major issue. I Feel So Adrift in the Sea of Colleges without My US News Ranking Water Wings - What Do I Do? You don’t have to ignore the US News rankings just because they’re not totally well-rounded in terms of their assessment metrics and inclusivity.What you should do is make sure that you are aware of what they can and can’t tell you about a college.It’s important that you supplement your views on schools with other resources that will give you a more complete picture of what student life is like and how you might fare at the college. To their credit, US News fully acknowledges this fact:â€Å"the editors of U.S. News believe rankings are only one of many criteria students should consider in choosing a college. Simply because a school is top in its category does not mean it is the top choice for everyone. The rankings should not be used as the sole basis to choose one school over another.†Academics are very important, but your life at college will be so much more than just the quality of your classes and how impressive your degree looks in a frame.You should make sure that you like the location of the school, the housing options, the food, the campus life, and the price tag before you make a decision. And in case you don't like the food, bring a bottle of sriracha. You could put sriracha on woodchips and I would probably eat them. Use the rankings as a rough guide to the quality of schools. The top five schools are the most reputable, then the next set of ten, then the next set of ten, and so on. A school that's in the top 20 is going to provide a more intellectual community and more opportunities in general than a school that's ranked in the 40s. However, within each group of ten there won't be much variability in terms of academic quality and reputation.This might help you to make a decision about where to apply after doing some outside research. However, even if you're trying to decide between two schools that are ranked very differently, you shouldn't just go by rankings. If the lower ranked school is a great fit for you, and the higher ranked school is a poor fit, you should choose the better fit regardless of ranking! As US News also says on its website: â€Å"A prospective student's academic and professional ambitions, personal preferences, financial resources and scholastic record, as well as a school's size, cost, programs, atmosphere and location, should play major roles in determining a college choice.†Once you’ve considered the other factors the are most important to you, you can move on to potentially comparing schools based on the academic rankings presented in US News. What's Next? When you apply to college, it's important to have both reach and safety schools so that you don't sell yourself short or end up without any options. Learn more about how to choose reach schools and safety schools. If you're planning on consulting the US News rankings, you should figure out whether you're more interested in public or private colleges first. Find out the differences between the two. Size and location are also very important factors to consider before looking at rankings. These articles will tell you about the pros and cons of going to college close to home and the main differences between large and small colleges. Want to improve your SAT score by 240 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:

Ultimate Guide to Marketing Resource Management Organize Every Asset

Ultimate Guide to Marketing Resource Management Organize Every Asset Marketing departments don’t have it easy these days. If you’re a Marketing Manager it can often feel like you’re trying to tame a multi-headed beast. Back in the day, Marketing Managers had only a couple of channels to manage. Today, there’s about a hundred things you *could* be doing and endless channels vying for your limited attention and resources. And it’s all further complicated by complex team structures, collaboration hurdles, and the necessity to pivot at the drop of a hat. It can kinda feel like you’re expected to move mountains AND be the goose that lays the golden egg WHILE juggling fire. Enter Marketing Resource Management†¦ or MRM if you’re into acronyms. So What is Marketing Resource Management Anyway? Marketing Resource Management sounds like something reserved for mega-corporations planning global domination. In reality, it’s a solution that can help marketing teams both large and small accomplish more, in less time. Everything a Marketer needs to know about Marketing Resource Management.MRM software is designed to assist teams in navigating and managing the complexity of today’s marketing environment. (It has also been known to keep Marketing Managers from pulling all their hair out in frustration.) MRM tools usually help solve the following marketing problems: Strategic planning Budgeting Project management Creative content development Asset distribution Collaboration Download Your Free Marketing Management Templates Before committing to an MRM tool, check out some of these free templates to get your team organized. Marketing Strategy Guide (PDF):  Plan an entire marketing strategy efficiently (with team collaboration in mind from the start). Marketing Project Calendar Template (Excel):  Collaborate on project timelines with a single version of truth. Marketing Project Management Plan (Doc):  Get all of your team on the same page before every project starts. Marketing Project Checklist (Excel):  Keep track of due dates and workflows with this spreadsheet. Spreadsheets are made for strategic planning. Get on board with Marketing Resource Management,...Strategic Planning For Marketing Resource Management Spreadsheets just aren’t made for the needs of marketers and strategic planning. Marketers need to see interactive views, updated in real-time of how each activity fits into a larger campaign. Not static rows in a complex spreadsheet that only you, the manager, can make sense of. MRM tools allow marketing managers to easily communicate with everyone (from intern to CMO) how each task, project, and campaign contributes to accomplishing a higher strategic goal. Things to think about You may want your MRM tool to have read-only access. Just because your boss wants to see everything that’s going on, doesn’t mean they should be able to edit and reassign tasks on a granular level. Many Marketing Managers like to see an agile view of what each person on their team is working on that day, week, month etc. AND a calendar view of campaign duration and overlap. Budgeting Managing your marketing budget isn’t just about tracking media spend or CPC on paid search. While that is undoubtedly an important part, MRM is also about maximizing your team’s output. By improving visibility into team tasks on a micro level, you can maximize task allocations AND ensure individuals aren’t being overloaded. As the old adage goes, watch the pennies and the dollars will take care of themselves. Things to think about Your MRM tool should have some team reporting capabilities to track task output, etc. From a monetary expenditure standpoint, what type of tracking capabilities do you need and for what channels? Project Management Marketing Managers are de facto project managers. Aside from all your day-to-day marketing tasks, you’re also responsible for coordinating internal resources, developing detailed project plans AND monitoring progress of all your campaigns. This is one of the biggest benefits of MRM. An MRM tool will give you a firm grasp on your team’s progress and workload - at any given moment. Allowing you to delegate, assign, and reassign projects tasks, so you can effectively manage your team’s week in a more effective way. No more lost emails, endless chat threads and unnecessary meetings. Things to think about Can you templatetize a workflow? This ability can save you a ton of time by auto-assigning tasks and due dates to each member of your team. You won’t have to think through each project’s steps time and time again. Is there an easy way to suss out what everyone is working on an when? MRM should solve your issues with visibility into who is working on what and when.Creative Content Development Producing great content and visuals take a lot more than just a designer. There are often several people involved in editing, approving and mocking-up until something is ready to be seen by an external audience. Does the lack of a clear approval process cause bottlenecks for your team and slow down time to market? MRM can help solve this by creating a central hub where everyone knows who is responsible for what and where a project is within its lifecycle. One of the best parts about this you no longer have to endlessly chase down approvals. Things to think about Are individuals notified when something is ready for approval? Do external clients or agencies need to be involved in the process? Asset Distribution Have you ever spent way more time than necessary trying to track down an image or logo? Even with your entire organization using Dropbox or Office 365 it can be a challenge. Different naming conventions coupled with a folder structure that no one follows can make someone want to bang their head against the wall. Most MRM systems also have built-in Digital Asset Management (DAM) capabilities. DAM components centralize a company’s digital assets, which eliminates the need to spend hours tracking down logos, images, header graphics, etc. Things to think about There can always be a bit of pushback from your team when changing the status quo.   This is often one of the more difficult areas of MRM to implement since people are used to looking for things in a certain place. Collaboration Collaboration is often one of the biggest challenges faced by marketing teams. The challenge usually stems from the need to have many specialities involved in the production process. Copywriters, designers, social media strategists, bloggers, email specialists, project managers, maybe even an agency or a client†¦ Solving the collaboration conundrum without an MRM tool usually means†¦ †¦ meetings on top of meetings†¦ †¦ countless emails flying back and forth†¦ †¦ and little time for working on *actual* marketing projects. Using MRM software creates a central repository for all project related communication, assets, tasks, and timelines for better and more efficient collaboration. Things to think about In Cella’s 2018 study of the creative industry, 71% of creative leaders named not enough time to complete work in a quality manner as their number one challenge. By simply implementing better collaboration/workflow processes, teams could reduce work by 30-50%. What a Marketing Manager Should Know About MRM Tools A time-strapped marketer’s problem is exacerbated by what we call Makeshift Marketing. You’re hacking multiple tools to manage your resources and marketing projects†¦ none of which are made for a marketing team. You need one tool that’s made for you. Here’s a list of some MRM tools to check out is an all-in-one marketing project management platform. Claim to fame? Task social templates: Save time using workflow templates and social sharing templates so you never have to reinvent the wheel. Built-in social media scheduling: Plan all your social media sharing directly in for one less tool to manage. ReQueue - smart social automation: Automatically re-share social campaigns to drive more traffic to your site. Agile view (Team Management Dashboard): See daily scrum summaries of each team member’s tasks. Calendar view: High-level views of every campaign, email, social message, etc. in an easy to see calendar view. Percolate Percolate is a cloud-based Content Marketing platform designed for enterprise customers. It integrates with enterprise CMSs and business intelligence platforms. Claim to fame? Kanban style workboards DAM Content metadata Integrated campaigns NewsCred NewsCred is an enterprise Content Marketing platform specializing in integrated marketing campaigns. Newscred enhances productivity with content workflows designed for an integrated team. The platform’s workflow allows for assigning tasks and deadlines to ensure your team is on track with their content marketing. Here are a few other features: Integrated campaigns In-app keyword research DAM Content advisory services Kapost Kapost is a software solution for B2B enterprise organizations aiming to solve their content marketing and content creation hurdles. Kapost does not operate as a calendar-based platform. It has a visual timeline to plan and create content. Customer insights ensure teams are driving their content strategy in the right direction. Features include: Content consulting Kanban board style overview Custom tagging by persona/buyer stage MRM Challenges Marketers May Face Marketing Resource Management aims to solve a lot of challenges facing modern marketing teams†¦ *BUT* implementing an MRM system and sticking to it has challenges in and of itself. Firstly, gaining internal support from the C-suite and your marketing team can be your first hurdle. Teams grow accustomed to the status quo, even if it’s broken and a total time suck. Your C-suite might be reluctant to open the purse strings for yet ANOTHER tool. They’ve grown weary of every tool promising the world only to be slowly phased out in favor of the status quo. This brings us to the first challenge†¦ overcoming the status quo.

Annotated bibliography Example | Topics and Well Written Essays - 500 words - 8

Annotated Bibliography Example Recently, the US foreign policy has been geared at eliminating the proliferation of nuclear weapons and prevention of human rights violation by dictatorial regimes. This book provides a detailed review of American involvement in world politics including the historical developments in Middle East countries. The book dwells on the ongoing American intervention in Afghanistan and the political uprisings in Middle East where the US has backed the end of dictatorial regimes (Cox and Stokes 40). This book provides a chronology of post World War II US foreign policy. The book provides the democratic controls and sanctions that US has imposed on various countries that have ignored calls for human rights protection. The book reviews the changes of US foreign policy after the September 11th terrorism attacks (Dobson and Marsh 158). Hunt provides and excellent analysis of ideological principles of US foreign policy and the criticism of US involvement in the Middle East. According to Hunt, three factors that have shaped US foreign policy are the zeal to provide liberty abroad, the hostility towards historical revolutions and racial view of the world which perceives a battle between Anglo-Saxons and darker races (Hunt 256). This book provides the measures that the US government has taken in its approach towards global terrorism. The counterterrorism and foreign policies are geared at eliminating any deals between Americans and terrorists, bring the terrorist organizations to justice and imposing sanctions to countries that harbor and sponsor terrorists (Pillar 179). This book provides a review how the Vietnam War shaped the attitudes of American authorities towards its foreign policy. The book offers steps which were undertaken by both Carter and Clinton to restore a democratic foreign policy. The book provides for foreign policy actions that were undertaken to contain the growing Soviet Union power and communism in Middle East in