The Aztec Empire History Essays - Aztec Gods, Aztec, Tenochtitlan

The Aztec Empire History annon The center of the Aztec civilization was the Valley of Mexico, a huge, oval basin about 7,500 feet above sea level. The Aztecs were formed after the Toltec civilization occurred when hundreds of civilians came towards Lake Texcoco. In the swamplands there was only one piece of land to farm on and it was totally surrounded by more marshes. The Aztec families somehow converted these disadvantages to a mighty empire known as the Aztec Empire. People say the empire was partially formed by a deeply believed legend. As the legend went, it said that Aztec people would create an empire in a swampy place where they would see an eagle eating a snake, while perched on a cactus, which was growing out of a rock in the swamplands. This is what priests claimed they saw when entering the new land. By the year 1325 their capital city was finished. They called it Tenochtitlan. In the capital city, aqueducts were constructed, bridges were built, and chinapas were made. Chinapas were little islands formed by pilled up mud. On these chinapas Aztecs grew their food. The Aztec Empire included many cities and towns, especially in the Valley of Mexico. The early settlers built log rafts, then covered them with mud and planted seeds to create roots and develop more solid land for building homes in this marshy land. Canals were also cut out through the marsh so that a typical Aztec home had its back to a canal with a canoe tied at the door. In the early 1400s, Tenochtitlan joined with Texcoco and Tlacopan, two other major cities in the Valley of Mexico. Tenochtitlan became the most powerful member of the alliance. Montezuma I ruled from 1440 to 1469 and conquered large areas to the east and to the south. Montezuma's successors expanded the empire until it extended between what is now Guatemala and the Mexican State of San Luis Potosi. Montezuma II became emperor in 1502 when the Aztec Empire was at the height of its power. In 1519, the Spanish explorer Hernando Cortes landed on the East Coast of Mexico and marched inland to Tenochtitlan. The Spaniards were joined by many of the Indians who were conquered and forced to pay high taxes to the emperor. Montezuma did not oppose Cortes because he thought that he was the God Quetzalcoatl. An Aztec legend said that Quetzalcoatl was driven away by another rival god and had sailed across the sea and would return some day. His return was predicted to come in the year Ce Acatl on the Aztec Calendar. This corresponded to the year 1519. Due to this prediction, Montezuma II thought Quetzalcoatl had returned when Cortes and his troops invaded. He did not resist and was taken prisoner by Cortes and his troops. In 1520, the Aztecs rebelled and drove the Spaniards from Tenochtitlan, but Montezuma II was killed in the battle. Cortes reorganized his troops and resurged into the city. Montezuma's successor, Cuauhtemoc, surrendered in August of 1520. The Spaniards, being strong Christians, felt it was their duty to wipe out the temples and all other traces of the Aztec religion. They destroyed Tenochtitlan and built Mexico City on the ruins. However, archaeologists have excavated a few sites and have uncovered many remnants of this society. Language: The Aztec spoke a language called Nahuatl (pronounced NAH waht l). It belongs to a large group of Indian languages, which also include the languages spoken by the Comanche, Pima, Shoshone and other tribes of western North America. The Aztec used pictographs to communicate through writing. Some of the pictures symbolized ideas and others represented the sounds of the syllables. Food: The principal food of the Aztec was a thin cornmeal pancake called a tlaxcalli. (In Spanish, it is called a tortilla.) They used the tlaxcallis to scoop up foods while they ate or they wrapped the foods in the tlaxcalli to form what is now known as a taco. They hunted for most of the meat in their diet and the chief game animals were deer, rabbits, ducks and geese. The only animals they raised for meat were turkeys, rabbits, and dogs. Arts and Crafts: The Aztec sculptures, which adorned their temples and other buildings, were among the most elaborate in all of the Americas. Their purpose was to please the gods and they attempted to do that in everything they did. Many of the sculptures reflected their perception of their gods and how they interacted in their lives. The most famous surviving Aztec sculpture is the

Racial Discrimination In the Work Place essays

Racial Discrimination In the Work Place essays Throughout the United States, more minorities are being hired; however, minorities continually face barriers to advancement once the hiring process is complete. Therefore, the cure all solution instituted by Human Resource departments to sponsor diversity training initiatives has not addressed the predicament of minorities being overlooked for regular As the world continues to become smaller through the use of new technologies like the Internet and the business community also is facing all new challenges because of the highly competitive global economy, America's labor markets continue to tighten. Human Resource departments have addressed these twenty- first century concerns by hiring more minorities than at any other point in our nation's history. But, once hired, minorities find that there could be clear and observable barriers blocking growth related to their career path. "It sounds like an employer's worst nightmare. A minority employee fails to receive a promotion. He sues the company, charging racial discrimination. His white supervisor who has already resigned to take a job with higher pay at another company joins in the suit. The supervisor claims that he was first pressured not to promote his subordinate and then, after he supported the subordinate's complaint of discrimination, was denied a promotion himself." (Barrier Basically, racial discrimination in the work place means that far too often qualified minorities are stopped from moving up corporate ladders within their organization. In other words, when minorities are getting jobs they cannot automatically assume that the job also entails future promotion to the next job level through regular promotions. This issue is at the forefront of racially motivated problems that Human Resource professionals will have to contend with as globalization demand a more diverse labor Organizations like the...

Holocaust Dissertation Example | Topics and Well Written Essays - 1250 words

Holocaust - Dissertation Example (Langer, 1975) Being moved from one language to another, particularly from German into English, then into French, is bound to change some of the meanings as well as lose some of them. Language is such an ambiguous concept that denotations are simply never sufficient in translating the exact intended meaning of the author. Authors utilize connotations of words in the language as they know it, however, the implied meaning may be lost to the translator. It is a fact that in research, there is only an average of approximately 80 percent of success in the translation of the meaning the original written works. Though the exact percentage of accuracy of the â€Å"Night† is not provided, there were some things that the author did not intend in the English version of the book. Rodway's use of words were a little too strong and graphic, bordering on crude, with her description of certain sensitive scenes in the book. The original work written by Elie used a little bit of Hebrew and Germ an, wherein some of the definitions would have most probably been lost along the process of translation. There are implied meanings in a language that could be overlooked by a translator no matter how fluent or efficient they are. Records state that Elie have in fact used some Hebrew characters originating from ancient customs which necessitates even more expertise in translating his texts in order to perceive his true meaning. Throughout the book, particularly the English translation, there were some implications of objections to Christianity as a religion, as well as similar objections to Judaism. The main title of the book, â€Å"Night†, was made in reference to how Elie's family, and other Jews alike, used to pray to God to get the night over with a lot faster. The author wrote his frustrations and his inability to contemplate how a loving God can allow tragedies as such can happen. This version of the book has brought on outrage from the Jewish people as well as other gr oups. The first translation written by Stella Rodway received a both positive and negative reviews. However, the sales remained unaffected by the attention it did receive. In contrast to Anne Frank's diary, this book was received as a fiction rather than an actual chronological account of what has happened during the holocaust. The book was intensely personal, and some of the events did not quite tally with records of events that has occurred, which makes it an easy for critiques to question the validity of his stories. (Berenbaum, 1979) The book tackled life to death stories as it began with the foreboding doom by Moshe the Beadle, who was an escapee then to the stories of a prophet who was on the train to the camp and was only capable of having visions of fire. Certain analogies pertaining to how eyes filled with pain goes blank and all those eyes would be is two open wounds that are now just an abyss filled with expressions of terror. In one part of the book in particular, a stor y of a little boy who was hung to die with two grown men gripped a lot of readers in the past few decades that the book has been in publication. Again, condemning statements such as of how God, for all the flowery phrases used to describe him, can allow such cruelty and evil come upon his people was perceived as an insult by certain readers. Christianity, as

Why did Radical Republicans Abandoned Women Seeking Rights after the Essay

Why did Radical Republicans Abandoned Women Seeking Rights after the Civil War - Essay Example The purpose of this paper is to explore some of the reasoning and events that took place that drove radical Republicans from acknowledging women's rights and why women in general stopped supporting the Republican Party. As Anna Yeatman (1993) explains it, "the dominant discourses of modern citizenship are predicated on systemic exclusions of those who are othered by these discourses" (quoted in Kingfisher, 1998, p. 128). When "woman" is added to the previously mentioned descriptors, another layer of exclusion is added. For example, the Fifteenth Amendment to the U.S. Constitution, enacted after the Civil War, granted suffrage rights to black men, but excluded women of all races.i The famous line from the Constitution that "All men are created equal" was written completely literally; this line did not include women or slaves as they were considered property. The founding fathers did not think twice when it came to denying the freedoms they had fought for to others, and it has been a long struggle since then to reclaim equal rights for all. Even with constitutional amendments making discrimination based on sex or skin color illegal, it still seems as though the white men in their suits have some sort of advantage over everyone not exactly like them. This undoubtedly is one of the reasons why Barack Obama and Hillary Clinton have seemed like such a breath of fresh air in this year's political landscape. Of course, with this year's main democratic candidates being a black man and a white women running for president, it's easy to forget that it was President Lincoln's Republican Party that emancipated the slaves and supported women's rights. So why exactly were the slaves freed in 1865 and women weren't given the right to vote until 1920 The women's rights movement and the abolition movement were conjoined before the Civil War, but afterwards, the Republican Party that had been given so much support by women in the abolition movement promptly dropped their support for equal rights for women. To begin explaining how all of this took place, it is necessary to go back one hundred years before the emancipation of the slaves to obtain a more complete story. The society of 1750's was still highly centered on the farm. Since there was so much work required to be done around a farm, men and women had to invest there full time into the work required. As factories began to become more prominent, many of the traditional jobs delegated to women began to change. These factories took the place of many jobs, such spinning and weaving, and this left women with much more time on their hands. With this extra time, they searched for ways to be more productive. They formed different organizations, some social, and these organizations became the foundations of many women's rights groupsii. The accepted notion of the time was that men and women belonged to different "spheres" of work and socializing, and that it was inappropriate for either men or women to cross the boundaries of these spheres. Men were supposed to work and engage in politics, while women were supposed cook, clean, and take care of the children. It is important to remember that at this time men thought that women should remain submissive. They were thought to have weak constitutions and needed men to take care of them. Throughout the history of the women's rights movement, this attitude was so prevalent that some women even spoke out against being given the right to vote, thinking that it gave too much responsibility. After being told that they were inferior for so long, they apparently began to think that the way they were treated was fair. It took a lot of courage for a woman during this time period

Evaluation of Code Smells Detection Using Meta-heuristics

Evaluation of Code Smells Detection Using Meta-heuristics Evaluation of code smells detection using Meta-heuristics  Optimization algorithm Ragulraja.M Abstract-The development of software systems over many years leads to needless complexity and inflexibility in  design which leads to a large amount of effort for enhancements and maintenance. To take code smells detection as a  distributed optimization problem. The intention is that to aggregates different methods in parallel way to achieve a  common goal detection of code smells. To this conclusion, it utilized Parallel Evolutionary algorithms (P-EA) where  numerous evolutionary algorithms with adaptation are executed in parallel cooperative manner, to find unanimity  between detection of code smells. An experimental results to compare the execution of our cooperative P-EA method with  random search, two genetic based approaches and two bad designs detection techniques are found to provide the  statistical measure of results witness to support the claim that cooperative P-EA is more economic and potential than the  art detection approaches based on benchmark of open source systems, whereas the results are generated in terms of  precision and recall incurred on various code smells types. In this approach should corroborate on an extra code smells  types with the objective of resolve the common applicability of our methodology. Keywords-Parallel Evolutionary Algorithm, Software Metrics, Code smells, Software Quality Engineering. I.INTRODUCTION Software maintenance projects are very  costly. The total maintenance costs of Software  project are estimated to 40%-70% of the total cost of the lifecycle of the project consequently, reducing the  effort spent on maintenance can be seen as a natural  way of reducing the overall costs of a software  project. This is one of the main reasons for the recent  interest in concepts such as refactoring and code  smells. Hence, researchers have proposed several  approaches to reduce defects in software .Suggested  solutions include improvement of clarity in software  design, effective use of process and product metrics,  achievement of extensibility and adaptability in the  development process. The research focusing on the  study of bad software designs also called bad smells  or code smells. To avoid these codes smells  developers to understand the structure of source code. The large systems of existing work in bad  smells or code smells detection relies on declarative  rule specification. In these specifications, rules are  manually constructed to identify symptoms that can  be used for categorization code smells with object  oriented metrics information. Each code smell, rules  are defined in the form of metrics combinations. Many studies reported that manual categorization  with declarative rule specification can be large. These  need a threshold value to specify the code smells. Further problem is that translation from symptoms to  rules is not obvious because there is no unanimity  symptom based description of bad smells. When unanimity occurs, the correlation of symptoms could  be consociated with code smells types, it leads to  precise identification of code smells types. To handle these problems, we plan to extend  an approach based on use of genetic programming to  provide detection rules from the examples of code  smells detection with metric combinations. However,  the quality of the rules depends on the behavioral  aspects of code smells, and it is not easy to confirm  that coverage also because there is still some  precariousness involves in detected code smells due  to the difficulty to evaluate the coverage of the base  of code smell examples. In another past work, we proposed technique  based on an artificial immune system metaphor to  detect code smells by deviation with well designed  systems. Thus, we believe in that an effective method  will be to merge with detection algorithms to  discover consensus when detecting code smells. We intend to provide code smells detection as a  distributed optimization problem.The implementation  of our approach can be established by combining  Optimization process in parallel manner to encounter  consensus involving detection of code smells. II. RELATED WORKS: There are various studies that have mainly  based on the code smells detection in software  engineering using different methods. These  methodologies range from fully automatic detection  to direct manual inspection. However,there is no  work that focuses on merging various detection  algorithms to find unanimity when identifying code  smells. In this work, the classification existing  approach for detection of code smells into various  broad categories: symptom based approaches, manual  approaches, metric based approaches, search based  approaches and cooperative based approaches. 2.1 Manual approaches: The software maintainers should manually  inspect the program to detect existing code  anomalies. In addition, they mentioned particular  refactoringà ¢Ã¢â€š ¬Ã… ¸s for each code smells type. The  technique is to create a set of â€Å"reading techniques†Ã‚  which help a reviewer to â€Å"read† a design artifact for  calculating related information. The demerits of  existing manual approaches is that they are finally a  human centric process which involves a great human  effort and strong analysis and interpretation attempt  from software maintainers to find design fragments  that are related to code smells.Furthermore, these  methods are time consuming, error prone and focus  on programs in their contexts. Another significant  issue is that locating code smells manually has been  prescribed as more a human intuition than an accurate  science. 2.2 Metric based approaches: The â€Å"detection strategy†mechanism for  formulating metric based rules for finding deviations  from well design code. Detection strategies permits to  maintainer to directly find classes or methods  subjected by a particular design smells. These  detection strategies for capturing about ten important  flaws of object oriented design found in literature. It  is accomplished by evaluating design quality of an  object oriented system via quantifying deviations  from good design heuristics and principles by  mapping these design defects to class level metrics  such as complexity, coupling and cohesion by defining rules. Unfortunately, multi metrics neither  encapsulate metrics in a more abstract construct,nor  do they permit a negotiable combination of metrics. In common, the effectiveness of combining metric or  threshold is not clear, that is for each code smell,  rules that are declared in terms of metric  combinations need an important calibration effort to  find the fixing of threshold values for each metric. 2.3 Search based approaches: This approach is divined by contributions in  the domain of search based software engineering. SBSE uses search based approaches to resolve  optimizations problems in software engineering. Once the task is consider as a search problem, several  search algorithms can be employed to solve that  problem. Another approach is based on search based  techniques, for the automatic identification of  potential code smells in code. The detection focused  on thenotion that more code deviates from good  codes, the more likely it is bad. In another work,  detections rule will be produced and is described as a  combination of metrics or thresholds that better  similar to known an examples of bad smells. Then,  the correction solutions, a combination of refactoring  operations, should reduce the number of bad smells  detected using the detection rules. 2.4 Cooperative based approaches: Some cooperative approaches to reference  software engineering problems have been proposed  recently, in this program and test cases co-evolve,  regulating each other with the aim of fixing the  maximum number of bugs in the programs. The  objective is to improve the effectiveness of obtained  test cases by evaluating their capabilities to avoid  mutants.The P-EA proposal is vary from existing coevolutionary  approaches, this proposal based on two  populations that are referencing the same problem  from various perspectives. Finally, the genetic based  approaches are executed in parallel in our P-EA  framework. III. PROPOSED SCHEME In this paper, we suggested a new search  based approach for detection of code smells. In this  approach a parallel metaheuristic optimization  algorithm adaptation, two genetic populations are  involves simultaneously with the target of each  depending on the current population of other in a  parallel cooperative manner. Both populations are  generated, on the similar open source systems to  evaluate, and the solutions are punished based on the  intersection between the results of two populations  are found. We extend our approach to various code  smells types in order to resolve about common  applicability ofcooperative parallel search based  software engineering. Moreover, in this work we not  only focus on the detection of code smells but also  concentrate automated the correction of code smells. Furthermore, in this paper we consider the  essential need of code smells during the detection  procedure using existing code changes, classes and  coupling complexity. Hence, the detected code smells  will be ranked based on the severity score and also an  important score. We will measure also the use of  more than two algorithms executed in parallel  manner as a part our work to generate results of more  accuracy than art detection approach. The negative  impact on the code smells can be removed by  applying more than two algorithms in cooperative  manner ità ¢Ã¢â€š ¬Ã… ¸s difficult to find the consensus between  the code smells. The research work will direct our  approach to several software engineering problems  such as software testing and quality assurance. IV. PROPOSED ARCHITECTURE Fig 1:system architecture 1. Metrics Evaluation 2. Evolutionary Algorithms 3. Code Smell Detection 4.1 METRICS EVALUATION 4.1.1 CK METRIC SUITE Chidember and kemerer proposed a six metric  suite used for analyzing the proposed variable. The six  metric suite are: 1. Weighted Method Per Class(WMC): Consider a class C1 with methods M1†¦.Mn  that are included in class. Let C1,C2†¦Cn be the sum of  complexity. WMC=ÃŽ £ M 2. Depth Of Inheritance(DIT): The maximum length from the node to the  root of the tree. 3. Number Of Children(NOC): Number of immediate subclasses subordinated  to a class in the class hierarchy. 4. Coupling Between Objects(CBO): It is a count of the number of other classes to  which it is coupled. 5. Response For a Class (RFC) It is the number of methods of the class plus  the number of methods called by any of those  methods. 4.1.2 Lack Of Cohesion of Methods (LCOM)  Measure the dissimilarity of methods in a  class via instanced variables. 4.2 EVOLUTIONARY ALGORITHMS The fundamental think of both algorithms is  to explore the search space by devising a population  of candidate solutions, also called individuals,  germinate towards a â€Å"good† solution of a unique  problem. To measure the solutions, the fitness  function in both algorithms has two components. For  the first component of the fitness function, GP  evaluates the detection rules based on the coverage of  code-smells examples. In GP, a solution is combined  of terminals and functions. Hence, while applying GP  to clear particular problem, they should be carefully  collected and fashioned to fulfil the requirements of  the current problem. Afterwards, evaluating large  parameters concerned to the code-smells detection  problem, the terminal set and the function set are  recognized as follows. The terminals fit to different  quality metrics with their threshold values (constant  values). The functions that can be used between these  metrics ar e Union (OR) and Intersection (AND). The second algorithm run in parallel is  genetic algorithm that generates detectors from welldesigned  code examples. For GA, detectors defend  generated artificial code fragments dignified by code  elements. Thus, detectors are mentioned as a vector  where each dimension is a code element. We defend  these elements as sets of predicates. All predicate  type represents to a construct type of an objectoriented  system. Then, a set of best solutions are  collected from P-EA algorithms in each iteration,  Bothalgorithms interact with one other victimizing  the second component of the fitness function called  intersection function. 4.3 CODE SMELLS DETECTION Code smells are design flaws that can be  solved by refactoringà ¢Ã¢â€š ¬Ã… ¸s. They are considered as flags  to the developer that some parts of the design may be  inappropriate and that it can be improved. For the  purpose of this work, we discuss a few representative  code smells. There are a lot of code smells mentioned  in the development of this work. A thorough catalog  of code smells can be found in Fowlers refactoring  book. As this work focuses on program analysis, code smells discussed in this work include those that  require analyses. Though this work develops only a  subset of the code smells, it provides some grounds  which can be adapted to other types of code smells. The set of best solutions from each algorithm is  stored and a new population of individuals is  generated by repetitively choosing pairs of parent  individuals from population p and employing the  crossover operator to them. We admit both the parent  and child variants in the new population pop. Then,  we apply the mutation operator, with a probability  score, for both parent and child to assure the solution  diversity; this produces the population for the next  generation. While applying change operators, no  individuals are transformed between the parallel  GA/GP. Both algorithms exit when the termination  criterion is met, and issue the best set of rules and  detectors. At last, developers can use the best rules  and detectors to find code-smells on new system to  evaluate. V. EXPERIMENTAL RESULTS Fig 2: The impact of the nmber of code smell example on detection  results Fig 3: Average execution time comparison on the different system. VI. THREATS TO VALIDITY: Conclusion validity related with the  statistical relationship between the treatment and  outcome. The Wilcoxon rank sum test was used with  a 95 percent confidence level to test its important  differences exist between the measurements for  different treatments. This test makes no supposition  that the data is normally distributed and is suitable for  ordinal data, so we can be assured that the statistical  relationships observed are significant. The  comparison with other techniques not based on  heuristic search; consider the parameters obtained  with the tools. This can be regarded as a threat that  can be addressed in the future by developing the  impact of various parameters on the quality of results  of DÉCOR and JDeodorant. Internal validity is related with the casual  relationship between the treatment and outcome. To  consider the internal threats to validity in the  utilization of stochastic algorithms since this  experimental work based on 51 independent  simulation runs for each problem instance and the  obtained results are statistically analyzed by using the  Wilcoxon rank sum test with a 95 percent fair  comparison between CPU times. VII. CONCLUSION AND FUTURE WORK In this approach a parallel metaheuristic  optimization algorithm adaptation, two genetic  populations are involves simultaneously with the  target of each depending on the current population of  other in a parallel cooperative manner. Both  populations are generated, on the similar open source  systems to evaluate, and the solutions are punished  based on the intersection between the results of two  populations are found.Moreover, in this work we not  only focus on the detection of code smells but also  concentrate automated the correction of code  smells.Furthermore, in this paper we consider the  essential need of code smells during the detection  procedure using existing code changes, classes and  coupling complexity. Hence, the detected code smells  will be ranked based on the severity score and also an  important score. We will measure also the use of  more than two algorithms executed in parallel  manner as a part our work to generate result s of more  accuracy than art detection approach. Future work  should corroborate our method with remaining code  smell types with the objective conclude about the  common applicability of our methodology. We will  assess also the use of more than the algorithm  accomplish simultaneously as a part of our rest of our  future work. Another future issue direction attached  to our approach is to adapt our cooperative parallel  evolutionary approach to various software  engineering problems such as software testing and  the following release problem. VIII. REFERENCES 1) WaelKessentini,MarouaneKessentini,HouariSahrao  ui, Slim Bechikh:†A Cooperative Parallel Search-Based Software Engineering Approach for Code-Smells Detection† IEEE Trans. Softw. Eng.,vol. 40,  no. 9, Sep 2014. 2) N. Moha, Y. G. Gu_eh_eneuc, L. Duchien, and A.  F. Le Meur, â€Å"DECOR: A method for the specification  and detection of code and design smells,† IEEE  Trans. Softw. Eng., vol. 36, no. 1, pp. 20–36,  Jan./Feb. 2010. 3) Chidamber, S., Kemerer, C.: „A metrics suite for  object oriented designà ¢Ã¢â€š ¬Ã… ¸,IEEE Trans. Softw. Eng.,  1994, 20, (6), pp. 476–493.   4) Mark Harman and AfshinMansouri.:†Search Based  Software Engineering: Introduction to the Special  Issue of the IEEE Transactions on Software  Engineering†,† IEEE Trans. Softw. Eng., vol. 36, no.  6,Nov./Dec. 2010.   5) F. Khomh, S. Vaucher, Y. G. Gu_eh_eneuc, and H.A. Sahraoui, â€Å"A bayesian approach for the detection  of code and design smells,† in Proc. Int. Conf.  Quality Softw., 2009, 305–314. 6) R. Marinescu, â€Å"Detection strategies: Metrics-based  rules for detecting design flaws,† in Proc. 20th Int.  Conf. Softw. Maintenance, 2004, pp. 350–359. 7) M. Kessentini, W. Kessentini, H. A. Sahraoui, M.  Boukadoum, and A. Ouni, â€Å"Design defects  detection and correction by example,† in Proc. IEEE  19th Int. Conf. Program Comprehension, 2011, pp.  81–90. 8) T. Burczy_nskia, W. Ku_sa, A. D »ugosza, and P.  Oranteka,â€Å"Optimization and defect identification  using distributed evolutionary algorithms,† Eng.  Appl. Artif. Intell., vol. 4, no. 17, pp. 337–344, 2004. 9) A. Ouni, M. Kessentini, H. A. Sahraoui, and M.  Boukadoum, â€Å"Maintainability defects detection and  correction: A multiobjective approach,† Autom.  Softw. Eng., vol. 20, no. 1, pp. 47–79, 2012. 10) O. Ciupke, â€Å"Automatic detection of design  problems in objectoriented reengineering,† in Proc.  Int. Conf. Technol. Object-OrientedLanguage Syst.,  1999, pp. 18–32. 12) G. Travassos, F. Shull, M. Fredericks, and V. R.  Basili, â€Å"Detecting defects in object-oriented designs:  Using reading techniques to increase software  quality,† in Proc. Int. conf. Object-Oriented  Program.,Syst., Languages, Appl., 1999, pp. 47–56. 13) M. Harman, S. A. Mansouri, and Y. Zhang,  Ã¢â‚¬Å"Search-based software engineering: Trends,  techniques and applications,† ACM Comput. Surv.,  vol. 45, no. 1, 61 pages. 14) A. Arcuri, X. Yao, â€Å"A novel co-evolutionary  approach to automatic software bug fixing,† in Proc.  IEEE Congr. Evol. Comput., 2008, pp. 162–168. 15) M. J. Munro, â€Å"Product metrics for automatic  identification of „Bad Smellà ¢Ã¢â€š ¬Ã… ¸ design problems in Java  source-code,† in Proc. IEEE 11th Int. Softw. Metrics  Symp., 2005, pp. 15–15.   16) W. Banzhaf, â€Å"Genotype-phenotype-mapping and  neutral variation: A case study in genetic  programming,† in Proc. Int. Conf. Parallel Problem  Solving from Nature, 1994, pp. 322–332. 17) W. H. Kruskal and W. A. Wallis, â€Å"Use of ranks in  one-criterion variance analysis,† J. Amer. Statist.  Assoc., vol. 47, no. 260, pp. 583–621, 1952. 18) W. J. Brown, R. C. Malveau, W. H. Brown, and  T. J. Mowbray, â€Å"Anti Patterns: Refactoring Software,  Architectures, and Projects in Crisis†. Hoboken, NJ,  USA: Wiley, 1998. 19) N. Fenton and S. L. Pfleeger, â€Å"Software Metrics:  A Rigorous and Practical Approach†. Int. Thomson  Comput. Press, London, UK, 1997.   20) Emerson Murphy-Hill, Chris Parnin, and Andrew  P. Black† How We Refactor, and How We Know  It†,IEEE Trans. Softw. Eng.,vol. 38,no. 1, Jan./Feb.  2012. 21) M. Fowler, K. Beck, J. Brant, W. Opdyke, and D.  Roberts, â€Å"Refactoring: Improving the Design of  Existing Code†. Reading, MA,USA: Addison  Wesley, 1999.

Dim Lighting Co. Essay

1. Problems Company is not in a position to spend the capital necessary to fund the project. The potential resignation of Robert Spinks if the project is not funded. If the project were to be funded, the extended time for development and the 30% chance that it might not be a success. 2. Causes Organizational culture is not consistent throughout all the departments. Accounting and manufacturing departments focus on increasing profits while R&D and marketing departments are open to new innovation and growth. Management is reactive rather than proactive. The company has not produced a new product in the past to capture the market. The history of Robert Spinks leaving companies due to the lack of creativity. 3. System affected The structural system is affected by not being encouraging towards innovation. The psychosocial system is affected by other departments being intimidated by Robert Spinks. Jim West is under pressure to improve profits. The technical system is affected because the technology of the Micro-miniaturization of lighting sources could bring about major  innovation. 4. Alternatives Ignore the concerns of the accounting and manufacturing departments and go ahead with the micro-miniaturization of lighting sources project. Discard the micro-miniaturization of lighting sources project and invest on the improvements of the current equipment. 5. Recommendations Invest capital on the new micro-miniaturization of light sources project. Although there is a considerable amount of time until the benefits can be reaped, such an innovation will be helpful to defeat the competition and capture the market. If Robert Spinks leaves the company and takes this technology to a competitor, Din Lighting Co. will be seriously affected.

Analyse the dramatic effectiveness in Act 3, Scene 5 Essay

Looking closely at the characters and language in Romeo and Juliet, analyse the dramatic effectiveness in Act 3, Scene 5 William Shakespeare wrote â€Å"Romeo and Juliet† in 1954, although the basic plot can be traced back as early as the third century. In the play, Shakespeare relies heavily on the poem â€Å"The Tragicall History of Romeus and Juliet† by Arthur Brooke. Most of the people in the Elizabethan era were perceptive enough to concentrate on how the play was being performed and engaged themselves in the language the characters were using. Shakespeare’s audiences had different expectations towards his play, as many of them recognised the story already, they were settled enough to watch it providing the dramatist’s interpretation proved to be unique and original. I have been looking closely at Act 3, Scene 5 where Romeo and Juliet have just been secretly married. The scene opens with the two lovers having to part quickly after the Nurse informs Juliet her mother is swiftly approaching. Already a dramatic atmosphere is created, the audience is almost waiting for Romeo and Juliet to be caught out, this they know can simply not happen. Juliet is understandably tearful; Romeo is sympathetic towards her, showing he really cares for her: â€Å"I will omit no opportunity That will convey my greetings, love, to thee† All this is in comparison to later scenes in the play showing Juliet solitary and unsupported. Between the two lovers, there is a great difference, Romeo appears more optimistic than Juliet who is full of fear, sensing premonitions of her next seeing Romeo dead in a tomb. Her premonitions affect the audience, making them apprehensive and tense: â€Å"O God, I have an ill- divining soul! Methinks I see thee, now thou art so low As one dead in the bottom of a tomb. † The audience hears these harsh, severe words and are reminded of Romeo’s earlier startling premonition that he would die young: â€Å"†¦. My mind misgives Some consequence not yet hanging in the stars†¦.. By come vile forfeit of untimely death. † A chilling effect is created on those viewing the play as they start to realise and understand the significance of the two premonitions. By looking back into earlier scenes, dramatic effectiveness is created. Juliet uses language that shows how she is fearful of how her life with Romeo could easily be destroyed. She speaks to him strongly, showing a strong contrast to her soft words used previously. The strong bond that has been created between the two lovers before the audience’s eyes is momentarily going to be destroyed; tension is created as an aftermath of this feeling. This tension carries on and becomes hugely greater as the news of County Paris’ proposal is first heard of. The audience watch, already aware of the proposal, as the news is given to an extremely shocked Juliet. They wait anxiously for Juliet’s sake as she learns of it, and so a dramatic effectiveness is cast over them. The scene is made effective by the use of irony from Lady Capulet. As Lady Capulet refers to her â€Å"joyful tidings† and Juliet’s response is ironically a pleased one: â€Å"And joy comes well in such a needy time† But then the audience sees the real reason of Lady Capulet’s announcement and the hesitation of the crucial words proves to be highly dramatic, â€Å"Shall happily make thee there a joyful bride† Juliet’s intense anger would make great drama on stage, she shows her raging reaction well: â€Å"Now by Saint Peter’s church and Peter too He shall not make me there a joyful bride! † Juliet’s response shows exactly how she is feeling about the matter; she does not hold back at all. The audience knows the dilemma she is facing, one of bigamy, they are deeply involved and show much needed sympathy to Juliet. In the conversation that follows the cold and sharp language both Juliet and her mother used are very effective. Both sides address each other very formally, Juliet calling Lady Capulet, â€Å"My Lady†, â€Å"Mother† where Lady Capulet calls Juliet â€Å"girl† and â€Å"child†. This doesn’t seem to be the language one would expect from a close knit and loving family. This could lead to the conclusion that Juliet’s relationship is far from the relationship she has with Romeo; a loving and stable one. When Lord Capulet enters Juliet’s room, it proves to be a significantly dramatic scene because of the violence and fury portrayed by Lord Capulet. He arrives in her room in a threatening manner; his wife shows fear warning us to expect the worst, â€Å"Here comes your father. Tell him so yourself And see how he will take it at your hands. † Lord Capulet does not expect Juliet to disobey him, he would simply expect grateful thanks and obedience from his daughter. He portrays himself as someone who is used to getting his own way and the way that he regards himself as royalty emphasises to his huge ego and elevated formal language,†Have you delivered to our decree? † He shows great enthusiasm as he enters Juliet’s room, he seems delighted with his plan and congratulates himself on stage. Being the only man on stage, he is showing domination and the audience can see that he likes to be in control. He makes the women afraid; his centre role on stage shows this. The language that he uses is indeed very dramatic and effective. He poses questions to Juliet, being sharp and short when he does so showing how bewildered he is, and he vociferously attacks his daughter overwhelming her with numerous with numerous questions which she does not have time to answer, â€Å"How? Will she none? Doth she not give us thanks? † Capulet’s sentence construction is cleverly disjointed emphasising greatly on his anger that is building up rapidly. He shows more of an interest in finding a way to answer Juliet’s questions and his concern is more about his cleverness than the distress of his only daughter. He uses aggressive terms to Juliet, † you greensickness carrion†, † young baggage†, both examples are very aggressive and devegiating.