Event Management ( portfolio work) Essay Example | Topics and Well Written Essays - 2500 words

Event Management ( portfolio work) - Essay Example or the seminar Innovation without Boundaries for Summit Solvay a training firm.   The seminar will entail training participants on Simple steps to make innovation work ,myths and misconceptions about innovation, how to avoid common pitfalls of innovative thinking, best practices to quickly launch projects to prove creative concepts, how to harness existing corporate culture to drive innovation and growth. boundaries.   The main objective is to make profit from the money invested and returns on investment.   The second objective is to ensure that participants gain skills that they can easily implement in the work place.   The third objective is to ensure continued growth of organizations through adaption of latest innovation strategies.   Ã‚  Ã‚  Ã‚  Ã‚  Ã‚     Ã‚  Ã‚  Ã‚  The first objective will be achieved by having 200 plus participants attend the seminar. The second objective will be achieved by the quality of the presentations and interaction by the participants. A measure on the success of the seminar will be evaluated by participants being asked to respond to an evaluation questionnaire at the end of the seminar, Ramsborg et al (eds) (2008),. The success of the third objective will be assessed by the evaluation of the changes implemented in their organizations in a period of six months after the seminar.   Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚     The seminar will take place on 25th August 2012. 8.30 am to 5.00pm at Intercontinental Hotel in London.   The target audiences for the seminar are c-level management, middle management, supervisors and all individuals involved in the innovative process in their organizations.   The seminar will give organizations a platform to discuss the strategies they need to adopt for their innovative future. embrace change and remain abreast of the competition. This is especially important for organizations that operate in more than one country. The seminar on Innovation without boundaries gives these organizations to empower its staff with cutting edge skills to

The Attitudes toward the role of women from a religious standpoint Research Paper

The Attitudes toward the role of women from a religious standpoint - Research Paper Example This alludes to the fact that women in Buddhist Asia were, from quite early on, treated much better than their counterparts in other parts of Asia. Most observations on Buddhist women in the late 19th and early 20th century are made by Europeans who found themselves in Asia around this period. The most remarkable feature about Buddhist women to these early writers was their privilege. Sir Charles Bell a British Political Representative in Tibet, Bhutan and Sikkim, wrote in 1928 that travelling to Tibet from India and China presents the visitor with an impression that Tibetan women are not kept in isolation as their Indian counterparts. In fact, the Tibetan women mingle with the opposite sex and are consequently at ease with men (Dewaraja 4). The most important thing to note is that the statement women in the world is a reference to European women at that time in history. These women are still struggling to walk shoulder to shoulder with their male counterparts. In Buddhism, subordination of women is given a religious sanction. According to the Law of Karma, one’s actions in the past will determine one’s position of wealth, power, talent and even sex in future births. One is reborn a woman because of one’s bad Karma. Because of such religious laws, attitudes towards women are not easily changed. Today women in Buddhism much like their predecessors 100 years ago struggle with such challenges. At the forefront of this campaign is Sakyadhita or daughters of Buddha. This is a global network of Buddhist women aimed at improving their status through conferences, dinners and discussion groups. At the turn of the 20th century, the attitude towards the role of women in Christianity was much like that in Buddhism as observed by European Asian settlers. However, women in Christianity during this period were associated with education.

Physical books Essay Example for Free

Physical books Essay The answer to this question is a simple yes. We shall prove in our discussion why we have chosen this answer. With advances in technology the word ‘paper’ no longer implies a material made of cellulose pulp, derived mainly from wood. As we make further advances, we see that the definition of paper has changed. Physical books that were made of paper have morphed into digital copies called e-books that are available over various mediums of communication such as the Internet or even our very mobile phones. We know that everything has a certain shelf life and if continue to use it beyond that period we will cause ourselves harm, this is also true for physical paper books, time has come to move over the paper books and to enter the world of e-books. Two of the most important factors supporting the cause of the e-book are that it saves: 1. Time and 2. Money 1. Time: In this rapid moving world we are all constantly on the move and we require information immediately, with e-books we can find the information we want immediately. Money: We all want to save money; e-books will be available at only a fraction of the price of the paper books since it will be cheap for the publishers to produce and this benefit will in turn be passed on to the consumer. Reasons for decline of paper books and the popularity of e-books are obvious: 1. E-books can be view almost instantaneously: One can browse through the thousands of e-books available on the Internet by just typing the keywords and purchase the e-book we want by using our credit cards and download the e-book immediately, thus we are saving a lot of overhead costs. 2. E-books cheaper for the publisher to publish as various overhead costs are minimized: Various overheads costs such as huge and expensive printing machinery and their maintenance will disappear; also there will not be need of a large work force to manufacture e-books. 3. E-books cheaper for the consumer to purchase than physical paper books: Since the manufacturing costs of the publishers will be minimized, this will be passed down to the consumer. Thus the consumer will enjoy great savings. 4. E-books can reach a much larger audience worldwide: E-books can be launched instantaneously through out the world; there will be no waiting to buy our copy of the e-book. Also many times a physical paper book is not available in all parts of the world, but this will not be a problem with e-books. 5. E-books are environment friendly: Unlike physical books made from paper, which is derived from timber, e-books don’t need the resources of nature to be made. Thus we will be saving thousands of trees every year and thus reducing the greenhouse effect and making the earth a green place to live in. 6. We can have thousands e-books in our digital device: We can literally have thousands of e-books in our digital device such as a laptop or a computer. The number of e-books is only limited by the storage capacity of our computer or laptop. This is impossible with physical paper books. Can you imagine a person moving around with a library of paper books? But we can move around with our library of e-books on our laptop anywhere! Conclusion: We as humans should be ready to accept the change of books from the physical to the virtual. Are we truly ready to leave the paper copies of the great novels and instead view them as e-books? Some have even said that if we do this we’ll be disrespecting the great authors and poets, but as we wait, the world around us rapidly changing. In the end we may have no choice but to accept the e-book as it gains popularity and following every passing day. This it’s only a matter of time before the paper books are replaced by e-books. Thus we have observed and noted from the above examples that the books made of paper are on their way out and the time of the e-book has arrived. (Sam Kleinman 2007) Works Cited 1. ZATZ Publishing (2007) Print books vs. e-books by Sam Kleinman, page 1[last updated 2007] [Online] Available from: http://www. palmpower. com/issues/issue200206/ebook0602001. html 2. ZATZ Publishing (2007) ZATZ Publishing (2007) Print books vs. e-books by Sam Kleinman, page 2 [last updated 2007] [Online] Available from: http://www. palmpower. com/issues/issue200206/ebook0602002. html

Optimization of Benchmark Functions using VTS-ABC Algorithm

Optimization of Benchmark Functions using VTS-ABC Algorithm Performance Optimization of Benchmark Functions using VTS-ABC Algorithm Twinkle Gupta  and Dharmender Kumar Abstract  A new variant based on tournament selection called VTS-ABC algorithm is provided in this paper. Its performance is compared with standard ABC algorithm with different size of data on several Benchmark functions and results show that VTS-ABC provides better quality of solution than original ABC algorithm in every case. Keywords— Artificial Bee Colony Algorithms, Nature-Inspired Meta-heuristics,Optimizations, Swarm Intelligence Algorithms, Tournament selection. NOMENCLATURE ABC – Artificial Bee Colony ACO – Ant Colony Optimization BFS – Blocking Flow-Shop Scheduling DE – Differential Evolution EA – Evolutionary Algorithm GA – Genetic Algorithm MCN – Maximum Cycle Number PSO – Particle Swarm Optimization TS – Tournament size TSP – Travelling Salesman Problem 1.INTRODUCTION For optimization problems, various algorithms havebeendesigned which are basedonnature-inspiredconcepts [1].Evolutionary algorithms(EA) and swarmoptimizationalgorithmsare two different classes in which nature inspired algorithms are classified.Evolutionary algorithms like Geneticalgorithms (GA)andDifferentialevolution (DE) attempt to carry out the phenomenon ofnaturalevolution [2]. However, a swarm like ant colony, a flock of birds can be described as collection of interacting agents and their intelligence lieintheir way of interactions with other individuals andtheenvironment [3]. Swarm optimization includes Particle swarm optimization (PSO) modelon socialbehaviorofbirdflocking [4], Antcolony optimization (ACO) model on swarmofants and Artificial Bee Colony (ABC) model on the intelligent foraging behaviour of honey bees [5]. Some important characteristics of ABC algorithm which makesitmoreattractivethanotheroptimizationalgorithms are: Employs only three control parameters (population size, maximum cycle number and limit) [6]. Fastconvergencespeed. Quite simple, flexible and robust [7] [8]. Easyintegrationwithotheroptimizationalgorithms. Therefore, ABC algorithm is a very popular nature inspired meta-heuristic algorithm used to solve various kinds of optimization problems. In recent years, ABC has earned so much popularity and used widely in various application such as: Constrained optimization, Image processing, Clustering, Engineering Design, Blocking flow shop scheduling (BFS), TSP, Bioinformatics, Scheduling and many others [9]-[18].Similar to other stochastic population-based approaches like GA, Ant Colony etc. ABC algorithm also applied Roulette Wheel selection mechanism which chooses best solution always with high selection pressure and leads the algorithm into premature convergence. With ever-growing size of dataset, optimization of algorithm has become a big concern. This calls for a need of better algorithm. The aim of this paper is to create such an algorithm named VTS-ABC algorithm. This new variant is based on tournament selection mechanism and selects variable tournament size each time in order to select the employed bees sharing their information with onlooker bees. Onlooker bees select solution from selected tournament size of solutions with less selection pressure so that high fitness solutions can’t dominate and give better quality of solutions with large data set as well. A worst solution is also replaced by better solution generated randomly in each cycle. Rest of the paper is divided in different sections as follows: Introduction to standard ABC algorithm is described in section 2. Section 3 describes the proposed VTS-ABC algorithm. Experiments and its simulation results to show performance on several Benchmark functions are described in section 4 and in the last; Conclusion of the paper is discussed. 2.ARTIFICIAL BEE COLONY ALGORITHM In 2005, Karaboga firstly proposed Artificial Bee Colony algorithm for optimizing numerical problems [19] which includes employed bees, onlooker bees and scouts. The bee carrying out search randomly is known as a scout. The bee going to the food source visited by it before and sharing its information with onlooker bees is known as employed bee and the bee waiting on the dance area called onlooker bee. ABC algorithm as a collective intelligence searching model has three essential components: Employed bees, Unemployed bees (onlooker and scout bees) and Food sources. In the view of optimization problem, a food source represents a possible solution. The position of a good food source indicates the solution providing better results to the given optimization problem. The quality of nectar of a food source represents the fitness value of the associated solution. Initially, a randomly distributed food source position of SNsize, the size of employed bees or onlooker bees is generated. Each solution xi is a D-dimensional vector that represents the number of optimized parameters and produced usingthe equation 1: where,xmaxandxminare the upper and lower bound of the parameterxi,respectively and j denotes the dimension. The fitness of food sources to find the global optimal is calculated by the following formula: where, fm(xm)is the objective function value of xm. Then the employed bee phase starts. In this phase, each employed bee xi finds a new food source viin its neighborhood using the equation 3: where, t: Cycle number; : Randomly chosen employed bee and k is not equal to i ; ( ): A series of random variable in the range [-1, 1]. The fitness of new solution produced is compared with that of current solution and memorizes the better one by means of a greedy selection mechanism. Employed bees share their information about food sources with onlooker bees waiting in the hive and onlooker bees probabilistically choose their food sources using fitness based selection technique such as roulette wheel selection shown in equation 4: where, Pi: Probability of selecting the ith employed bee, S: Size of employed bees, ÃŽ ¸i: Position of the ith employed bee and F : Fitness value. Afterthatonlookerbeescarried outrandomly searchintheirneighborhood similar to employed bees and memorize the better one. Employed bees whose solutions can’t be improved through a predetermined number of cycles, called limit, become scouts and their solutions are abandoned. Then, they find a new random food source position using the following equation 5: Where, r: A random number between 0 and 1 and these steps are repeated through a predetermined number of cycles called Maximum Cycle Number (MCN). 3.PROPOSED WORK: VTS-ABC ALGORITHM In every meta-heuristic algorithm mainly two factors need to be balanced for global optimization outcome i.e. Exploration and Exploitation but ABC is a poor balance of these two factors. Various variants of ABC have been modelled for its improvement in different phases by number of researchers like Sharma and Pant have proposed a variant of ABC called RABC for solving the numerical optimization problem [20] and Tsai et al. have presented an interactive ABC optimization algorithm to solve combinational optimization problem [21] in which the concept of universal gravitational force for the movement of onlooker bees is introduced to enhance the exploration ability of the ABC algorithm. D. Kumar and B. Kumar also reviewed various papers on ABC and give a modified RABC algorithm based on topology for optimization of benchmark functions [22] [23]. Intelligence of ABC algorithm mainly depends upon the communication between individual agents. Employed beesshare their information with onlooker bees waiting in the hive and flow of this information from one individual to another depends on the selection mechanism used. Different selection schemes select different individuals to share the information which affect the communication ability of individuals and primarily the outcome of the algorithm. ABC algorithm uses Roulette wheel selection mechanism in which each onlooker bee selects the food source based on certain probability. Each onlooker bee selects the best food source with high selection pressure and lead to premature convergence. To overcome this problem, its new variant is proposed in which Tournament Selection method is applied based on Cycle number and number of employed bees. In Tournament selection, a tournament size (TS) is chosen to select the number of employed bees sharing the information with onlooker bees. For better exploration, TS=2 i.e. Binary Tournament is applied in early stages and for better exploitation, variable tournament size is applied based on the current cycle number (CYL) and size of employed bee in middle stages. As the stages grow, this method works similar to Roulette wheel method in the end. Hence, the selection pressure is less in early stages and more in final stages which provide us better quality of solution. As variable size of tournament is used at different stages of the algorithm, hence the algorithm named VTS-ABC (Variable Tournament Size Artificial Bee Colony) algorithm. Method used for calculating TS is shown in equation 6 and equation 7: If SN >= 20 If SN Where Here, two equations are shown for calculating tournament size of tournament selection method. The purpose of using these two equations is to increase the speed of algorithm. When the size of employed bee i.e. given population of food source positions is small like 10, a solution can be easily found by changing the tournament size by 1 but as the size grows i.e. when best food source position is to be found in large set of population for example when SN=40 or more than 40, increasing size of tournament by 1 and 2 only is a very tedious task as it will take more time to run the algorithm. Hence, in order to increase speed of algorithm, the tournament size based on current cycle and size of population is increased. One more concept is applied to increase its convergence speed. At each iteration or cycle, a new solution is generated randomly similar to scout and its fitness value is calculated. Greedy selection mechanism is applied between new solution and worst one and the better solution is memorized. Hence, it helps in finding good quality of solution as well as improving the convergence speed and provides better balance between exploration and exploitation. 4.experiments and simulation results 4.1 Benchmark Functions The Benchmark Functions used to compare the performance of VTS-ABC algorithm with original ABC algorithm are illustrated below: Sphere Function: Schwefel Function: Griewank Function: Where Ackley Function: Here, ObjVal is the function value calculated for each food source position. A food source is represented by X and population size is taken of n*p matrix where n is the no. of possible food source positions and p represents the dimension of each position. 4.2 Performance Measures Simulation Result The experimental results of VTS-ABC and ABC algorithm in MATLAB are taken under the parameter of size of food source positions (n*p) i.e. different size of population with different dimensions are taken to run and compare both algorithms. MCN is set as 2000 and each algorithm is run for 3 iteration i.e. Runtime=3. Limit for scouts is set equals to 300. In order to provide the quantitative assessment of the performance of an optimization algorithm, Mean of Global Minimum i.e. mean of minimum objective function value at each cycle of all iterations are taken as performance measure whose values are shown in table1and figure 1-4. Table1: Mean of Global minimum on different size of data Fig. 1: Mean of Sphere function values on different size of data Fig. 2: Mean of Schwefel function values on different size of data Fig. 3: Mean of Griewank function values on different size of data Fig. 4: Mean of Ackley function values on different size of data Figure 1 to 4 show simulation results of ABC and VTS-ABC algorithm with different size of data on Sphere, Schwefel, Griewank, Ackley respectively and reveal that VTS-ABC algorithm provides us better quality of solution than original ABC algorithm by minimizing objective function value or producing higher fitness solutions. 5. DISCUSSION AND CONCLUSION In this paper, a new algorithm VTS-ABC is presented. In this algorithm, firstly variable tournament size (TS) is applied to select the food source position for onlooker bees which helps to achieve diversity in solution. Then to increase convergence speed, a new solution is generated in each cycle which replaced the worst one. In order to demonstrate the performance of proposed algorithm, it is applied on several Benchmark functions with different size of data set as input. Simulation results show that it provides better quality of solution than original ABC algorithm in every case. Therefore, it can be applied in different fields of optimization with large and higher dimensions data set efficiently. References Yugal Kumar and Dharmender Kumar, â€Å"Parametric Analysis of Nature Inspired Optimization Techniques†International Journal of Computer Applications, vol. 32, no. 3, pp. 42-49, Oct. 2011. P. J. Angeline, J. B. Pollack and G.M. Saunders, â€Å"An evolutionary algorithm that constructs recurrent neural networks,† Neural Networks in IEEE Transactions on, vol. 5, no. 1, 1994, pp. 54-65. J. Kennedy and R. Eberhart, â€Å"Particle swarm optimization,† in Proceedings of IEEE international conference on neural networks, 1995, vol. 4, pp. 1942–1948. E. Bonabeau, M. Dorgio, and G. Theraulaz, â€Å"Swarm intelligence: from neural network to artificial intelligence,† NY: oxford university press, New York, 1999. D. Karaboga, â€Å"An idea based on honey bee swarm for numerical optimization,† Techn.Rep. TR06, Erciyes Univ. Press, Erciyes, 2005. D. Karaboga and B. Akay, â€Å"A comparative study of artificial bee colony algorithm,† Applied Mathematics and Computation, vol. 214, no. 1, pp. 108–132, 2009. R. S. Rao, S. V. L. Narasimham, and M. Ramalingaraju, â€Å"Optimization of distribution network configuration for loss reduction using artificial bee colony algorithm,† International Journal of Electrical Power and Energy Systems Engineering, vol. 1, no.2, pp. 116–122, 2008. A. Singh, â€Å"An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem,† Applied Soft Computing, vol. 9, no. 2, pp. 625–631, Mar. 2009. D. Karaboga and B. Basturk, â€Å"Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems,† in Foundations of Fuzzy Logic and Soft Computing, Springer, 2007, pp. 789–798. C. Chidambaram and H. S. Lopes, â€Å"A new approach for template matching in digital images using an Artificial Bee Colony Algorithm,† in World Congress on Nature Biologically Inspired Computing, 2009. NaBIC 2009, IEEE, 2009, pp. 146–151. N. K. Kaur Mann, â€Å"Review Paper on Clustering Techniques,† Global Journal of Computer Science and Technology, vol. 13, no. 5, 2013. S. Okdem, D. Karaboga, and C. Ozturk, â€Å"An application of Wireless Sensor Network routing based on Artificial Bee Colony Algorithm,† in 2011 IEEE Congress on Evolutionary Computation (CEC), 2011, pp. 326–330. T. K. Sharma, M. Pant, and J. C. Bansal, â€Å"Some modifications to enhance the performance of Artificial Bee Colony,† in 2012 IEEE Congress on Evolutionary Computation (CEC), 2012, pp. 1–8. L. Bao and J. Zeng, â€Å"Comparison and analysis of the selection mechanism in the artificial bee colony algorithm,† in Hybrid Intelligent Systems, 2009. HIS’09. Ninth International Conference on, 2009, vol. 1, pp. 411–41. C. M. V. Benà ­tez and H. S. Lopes, â€Å"Parallel Artificial Bee Colony Algorithm Approaches for Protein Structure Prediction Using the 3DHP-SC Model,† in Intelligent Distributed Computing IV, M. Essaaidi, M. Malgeri, and C. Badica, Eds. Springer Berlin Heidelberg, 2010, pp. 255–264. D. L. Gonzà ¡lez-à lvarez, M. A. Vega-Rodrà ­guez, J. A. Gà ³mez-Pulido, and J. M. Sà ¡nchez-Pà ©rez, â€Å"Finding Motifs in DNA Sequences Applying a Multiobjective Artificial Bee Colony (MOABC) Algorithm,† in Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, C. Pizzuti, M. D. Ritchie, and M. Giacobini, Eds. Springer Berlin Heidelberg, 2011, pp. 89–100. L. Wang, G. Zhou, Y. Xu, S. Wang, and M. Liu, â€Å"An effective artificial bee colony algorithm for the flexible job-shop scheduling problem,† Int J Adv Manuf Technol, vol. 60, no. 1–4, pp. 303–315, Apr. 2012. S.-W. Lin and K.-C. Ying, â€Å"Increasing the total net revenue for single machine order acceptance and scheduling problems using an artificial bee colony algorithm,† J Oper Res Soc, vol. 64, no. 2, pp. 293–311, Feb. 2013. D. Karaboga, â€Å"An idea based on honey bee swarm for numerical optimization,† Techn.Rep. TR06, Erciyes Univ. Press, Erciyes, 2005. T. K. Sharma, M. Pant, and J. C. Bansal, â€Å"Some modifications to enhance the performance of Artificial Bee Colony,† in 2012 IEEE Congress on Evolutionary Computation (CEC), 2012, pp. 1–8. TSai, Pei-Wei, et al. , Enhanced artificial bee colony optimization.International Journal of Innovative Computing, Information and Control,vol. 5, no. 12, 2009, pp.5081-5092. B. K. Verma and D. Kumar, â€Å"A review on Artificial Bee Colony algorithm,† International Journal of Engineering Technology, vol. 2, no. 3, pp. 175–186, 2013. D. Kumar and B. Kumar, â€Å"Optimization of Benchmark Functions Using Artificial Bee Colony (ABC) Algorithm,† IOSR Journal of Engineering, vol. 3, no. 10, pp. 09-14, October 2013.

Response to Article about Cystic Fibrosis Essay -- Biology

Cystic Fibrosis - Summary of Article It has been known for quite some time that CFTR is a cAMP regulated chloride ion channel whose mutation is intimately linked to cystic fibrosis (CF). However, the abnormality in the chloride ion channels is not the only biochemical peculiarity associated with the disease. Of particular interest to researchers is the finding that sodium ion (Na+) absorption in the cells of CF patients is both elevated and positively related to the cAMP concentration, whereas, in normal cells, cAMP concentration is inversely related to the rate of Na+ absorption. The malfunction of the Na+ pump becomes immediately apparent, for the primary symptom of CF is a chronic bacterial infection of the lungs, due to the abnormally low viscosity of the fluid which bathes the cellular epithelium; by pumping ions into the airway, rather than into the cell, a thermodynamically unfavorable concentration gradient of sodium ions is is established, in which the airway is hypotonic and osmosis is kinetically favored. In the case of CF, the local chloride pump is inoperative, and the sodium pumps are incredibly overactive, importing Na+ from the airway, and taking water out of the fluid inside the lungs in the process. Therefore, is is inappropriate to place the sole responsibility for the low fluid viscosity directly upon the mutation of the CFTR protein. Studies have demonstrated that the elevated Na+ absorption is not due to an overexpression of the Na+ transport protein, ENaC, in the membrane, nor can cAMP sensitivity be linked to a genetically mutated ENaC. The possibility that the altered CFTR indirectly led to the Na+ channel phenomena by altering the functionality of normal ENaC formed the basis of a hypothesis which ... ...The use of amiloride as a form of treatment is significant because amiloride actually helps the body in correcting the chloride and sodium ion concentration, thereby rehydrating the cells and thinning the mucus. This process differs from current treatments which loosen the mucus or dilute it so the patients can rids their lungs of the infectious substance more easily. Works Cited 1.) Purves, WK, Orians GH, Heller HC. Life: the Science of Biology. Sunderland: Sinauer Associates, Inc.; 1995. Chapter 15, Genetic Disease and Modern Medicine; pages 334-352. 2.) "CF-FAQ Part 1." Ed. Ron Trueworthy. CF-WEB. Internet. 10 September 1996. 3.) S. H. Wright, interview by group members. Tucson, Arizona, 22 October 1996. 4.) M. J. Stutts, C. M. Canessa, J. C. Olsen, M. Hamrick, J. A. Cohn, B. C. Rossier, R. C. Boucher, Science, v. 269, 11 August 1995, pages 847-850.

Comparing The Withered Arm by Thomas Hardy and Turned by Charlotte Perk

Comparing The Withered Arm by Thomas Hardy and Turned by Charlotte Perkins Gilman This essay is aimed at discussing the differences between two short stories, called ‘The Withered Arm’ by Thomas Hardy and ‘Turned’ by Charlotte Perkins Gilman. These stories have similar plots and both deliver and contrast these in their very own clever ways. They are both based on the idea of triangular relationships, involving two women and a man. In the story ‘Turned’ there is a couple named Mr. and Mrs. Marroner, and their employee who is a young and beautiful Swedish maid who goes by the name of Gerta. In ‘The Withered Arm’ the relationship is between a lady called Rhoda Brook and a farmer called Farmer Lodge and his wife who is called Gertrude. This essay will discuss the similarities and differences between the two stories and their characters, I will also discuss the language used, and the way the same image is effectively conveyed in the two stories. The author of ‘Turned’ is Charlotte Perkins Gilman who was from a poor background and was born in Connecticut, USA, in 1860. The first story she wrote was called ‘The Yellow Wallpaper’ which she wrote in 1892. She then went on to write her best-known book, which was called ‘Women and Economics.’ Gilman was a feminist writer who believed that women had the right to their own independence. This is demonstrated in the character of Marion in ‘Turned’, as she is a clever woman with a degree and has a title of doctor. Gilman published ‘Turned’ in 1911 at the time where issues surrounding women rights was becoming more serious and common. On the other hand, Thomas Hardy wrote his novel ‘The Withered Arm’ with men in the powerful positions. For instance Farmer Lodg... ...ld and frail and died and Farmer Lodge became a kind, caring and thoughtful man! Gertrude died three days later in the town â€Å"Her blood had been turned indeed, too far.† After this Rhoda had lost her friend and her son so she decided to resume where she had started where â€Å"Her monotonous milking at the dairy was resumed.† Farmer Lodge on the third corner of this triangular relationship gave up his farms and became a member of the parish after he overcame his remorse and moodiness. â€Å"He eventually changed for the better, and appeared as a chastened and thoughtful man† To conclude this essay, triangular relationships happen and probably always will happen for years to come. It doesn’t make any difference about what century it happens in or if it is from a rich or poor background because affairs, unwanted babies and complicated relationships are part of life.

Crime Scene Investigation

Research Paper: Crime Scene Investigation (first draft) If a murder, a homicide and or a suicide occur, the crime scene investigator(s) collects the clues and evidence that will be analyzed by the forensic scientist(s) which can lead them to their suspect(s). The purpose of a Crime Scene Investigation is to help victims find justice. When a crime has been reported, the responding officer and/or detective have to note the dispatch information such as address/location, time, date, type of call, parties involved. The officer(s)/detective(s) have to be observant when approaching, entering and exiting a crime scene such as look, listen and smell.Next thing they have to do is to secure the crime scene. Officers have to scan the area for sights, sounds and smell that may cause danger to personnel and other individuals such as gasoline and explosives. They also have to survey for any dangerous civilian around the scene and control the situation. If there are any dangerous civilian, officer w ill immediately call for back-up and while the officer(s) are waiting for the back-up, they have to handle the situation thoroughly. They would first position the â€Å"Crime Scene DO NOT CROSS† tape around the perimeter, this allows authorized personnel to cross the area of the crime scene.Following this procedure will preserve the scene with minimal contamination. Officers and detectives have to be alert and attentive about their surroundings. The detective(s) have to identify all the individuals around the crime scene. They have to identify the witnesses and secure them. Identify possible suspects and secure them and also separate them from the witnesses. They also secure and separate the victims/family/friends and show compassion to them. They must also exclude the media, bystanders that are just watching what is going on and the law enforcements that are off duty.When the crime scene investigator(s) arrive at the crime scene, they have to do a â€Å"walk-through†. Investigators have to avoid contaminating the crime scene by using the established path of way. They have to make sure that before they entered the crime scene, nothing in the scene should have been moved. While they are going through a walk-through, they may have to construct theories about what happened in the crime scene based on visual examination. Investigators have to take photographs of the scene and will later on be collected. Taking photographs of the scene will help them solve the crime ecause there are some points of the investigation that investigators may have overlooked evidence, and that evidence could be found in the photographs. After taking photographs of the scene, they will start to collect clue and evidence that may lead them to their possible suspect(s). What they may find in the crime scene are fingerprints which can be done using colored powder and a brush, other thizngs such as blood, firearms, hair, glass and many more things that can be found in the crime scenes. After doing their job in he crime scene, the evidence they took will be taken to the forensic scientist.Crime scene investigators will look at the photographs and connect their theories based on the crime that occurred. The forensic scientists will also examine the victim’s clothes, while the medical examiner will analyze the victim’s body for more clues and evidence that they may find and they will all be doing this in the crime lab. The things they may find could be hair, fiber, semen, blood, another person’s DNA, bruises and many more. After the forensic scientists have done their job, they will give their report to the crime scene investigators. Just if he forensic scientists could not find any trace that can lead them to their suspect, then the investigators have to go back to the crime scene and find fore more clues and evidence that could help them. The new evidence will be taken to the forensics for them to be examined. When the crime scene inve stigators receive the report from the forensic scientists, they will invite their possible suspect(s) for questioning or if they could not reach the suspect, they could question the suspect through the phone. After this, the investigators need to go to the suspect(s) place.The investigators may ask the suspect(s) about the victim on what they know about the crime and may also ask for names that are may be connected to the crime that occurred. If it may also help, investigators and detectives may ask the victim’s family, friends, co-workers or anybody who knows the victim that could help them solve the crime that was committed. Investigators may ask them if the victim has enemies that may want the victim to be killed. The crime scene investigators will do the same procedure until they get the right person who committed the crime and be placed in jail.The suspect may still deny what is being accused of committing a crime and asked for a lawyer, the investigators and witnesses h ave to be prepared with strong evidence so that they can place the suspect in jail and pay for the consequences from what the suspect has done. When the crime scene in no longer needed to be processed for any evidence, the crime scene cleaners/Biohazard Technicians will start to clean the scene. They have to clean the place like nothing happened. Like gathering all the blood, brains and bugs then casting them in the extractor.What the extractor does is kill to the bacteria in bodily fluids with a special enzyme. They also need to eliminate the horrible smell in the scene and may have to cut off things like the mattress, curtains and many more. The crime scene cleaners are dedicated to assist the law enforcement, public service agencies and property owners/managers in restoring property that has been contaminated as a result of crime, disaster or misuse. If there’s a murder, a homicide or a suicide, the CSI investigators are to call.In Crime Scene Investigation a lot of things will happen, but mainly it is about collecting physical evidence. The process of what be revealed at a crime scene is very difficult. It involves a number of different searches and collections that help to solve a crime. After solving the crime, this means that the victim received justice for that happened to them. No body deserves to die and no body has the right to kill someone. Being a crime scene investigator is a hero, they used their knowledge for good reason and not for bad. The good reason is solving a crime that should have not happened.Work Cited Crose, Nicholas. â€Å"Extreme Careers: Detectives : Life Investigation Crime†. New York: Rosen Central, 2003. Print Cooperman, Stephanie. â€Å"Extreme Careers: Biohazard Technicians†. New York: Rosen Central, 2004. Print â€Å"Encyclopedia of Careers and Vocational Guidance†. New York: Ferguson, 2005. Print Murdico, Suzanne J. Extreme Careers Forensic Scientists: Life Investigating Sudden Death. New York: R osen Central, 2004. Print Technical Working Group on Crime Scene Investigation. †Crime Scene Investigation: A Guide for a Law Enforcement†. January 2000. Web. December 12, 2009