Job opportunities in performing arts Essay Example for Free

Job opportunities in performing arts Essay The below information is a rough guide based on the information from the jobs4you website. There are over 500,000 people that work in the creative and cultural skills area of work, there are over 62,000 creative businesses in the UK, and 94% of the businesses only employ 10 people a year, so being an arts administrator is a very competitive area of work to get into. There are opportunities throughout the whole of the UK, in public and private organisations. You can get a job in theatre, concert halls, galleries, museums, exhibitions and festivals, etc. Jobs for admin are advertised in the local and national press, and through magazines such as the Arts Professional and The Stage. Qualifications Most of the employers ask for GCSEs at A-C in English and Maths, also it helps to have some relevant work experience. Some arts administrators have gone on to complete a degree, there are many degrees that offer relevant experience, for example business studies, arts management, music, drama or visual arts. The degrees normally last for 3 years, entry for a degree is normally at least two A levels. Entry for adults is a bit harder, so relevant work experience is required, for example: Administration or secretarial work, marketing or public relations, finance, performing arts, for example as a dancer or performer. Access courses are available for people that dont have the relevant qualifications, and who would like to study a degree. In this job, many people train on the job, but they can take short courses to help develop or to produce new skills. There are many NVQs and SVQs that are relevant, these include: * NVQ/SVQ levels 3 and 4 in business and administration * NVQ/SVQ levels 2,3,4 and 5 in cultural heritage. A promotions manager in the music industry is specialised in finding any opportunities in publicity, this can be for all types of artists, for example a singer or instrumentalist. promotions managers may work with record labels and individual musicians or bands.

K Means Clustering With Decision Tree Computer Science Essay

K Means Clustering With Decision Tree Computer Science Essay The K-means clustering data mining algorithm is commonly used to find the clusters due to its simplicity of implementation and fast execution. After applying the K-means clustering algorithm on a dataset, it is difficult for one to interpret and to extract required results from these clusters, until another data mining algorithm is not used. The Decision tree (ID3) is used for the interpretation of the clusters of the K-means algorithm because the ID3 is faster to use, easier to generate understandable rules and simpler to explain. In this research paper we integrate the K-means clustering algorithm with the Decision tree (ID3) algorithm into a one algorithm using intelligent agent, called Learning Intelligent Agent (LIAgent). This LIAgent capable of to do the classification and interpretation of the given dataset. For the visualization of the clusters 2D scattered graphs are drawn. Keywords: Classification, LIAgent, Interpretation, Visualization 1. Introduction The data mining algorithms are applied to discover hidden, new patterns and relations from the complex datasets. The uses of intelligent mobile agents in the data mining algorithms further boost their study. The term intelligent mobile agent is a combination of two different disciplines, the agent is created from Artificial Intelligence and code mobility is defined from the distributed systems. An agent is an object which has independent thread of control and can be initiated. The first step is the agent initialization. The agent will then start to operate and may stop and start again depending upon the environment and the tasks that it tried to accomplish. After the agent finished all the tasks that are required, it will end at its complete state. Table 1 elaborates the different states of an agent [1][2][3][4]. Table 1. States of an agent Name of Step Description Initialize Performs one-time setup activity. Start Start its job or task. Stop Stops its jobs or tasks after saving intermediate results. Complete Performs completion or termination activity. There is link between Artificial Intelligence (AI) and the Intelligent Agents (IA). The data mining is known as Machine Learning in Artificial Intelligence. Machine Learning deals with the development of techniques which allows the computer to learn. It is a method of creating computer programs by the analysis of the datasets. The agents must be able to learn to do classification, clustering and prediction using learning algorithms [5][6][7][8]. The remainder of this paper is organized as followos: Section 2 reviews the relevant data mining algoritms, namely the K-means clustering and the Decision tree (ID3). Section 3 is about the methodology; a hybrid integration of the data mining algorithms. In section 4 we discuss the results and dicussion. Finally section 5 presents the conclusion. 2. Overview of Data Mining Algorithms The K-means clustering data mining algorithm is used for the classification of a dataset by producing the clusters of that dataset. The K-means clustering algorithm is a kind of unsupervised learning of machine learning. The decision tree (ID3) data mining algorithm is used to interpret these clusters by producing the decision rules in if-then-else form. The decision tree (ID3) algorithm is a type of supervised learning of machine learning. Both of these algorithms are combined in one algorithm through intelligent agents, called Learning Intelligent Agent (LIAgent). In this section we will discuss both of these algorithms. 2.1. K-means clustering Algorithm The following steps explain the K-means clustering algorithm: Step 1: Enter the number of clusters and number of iterations, which are the required and basic inputs of the K-means clustering algorithm. Step 2: Compute the initial centroids by using the Range Method shown in equations 1 and 2. (1) (2) The initial centroid is C(ci, cj).Where: max X, max Y, min X and min Y represent maximum and minimum values of X and Y attributes respectively. k represents the number of clusters and i, j and n vary from 1 to k where k is an integer. In this way, we can calculate the initial centroids; this will be the starting point of the algorithm. The value (maxX minX) will provide the range of X attribute, similarly the value (maxY minY) will give the range of Y attribute. The value of n varies from 1 to k. The number of iterations should be small otherwise the time and space complexity will be very high and the value of initial centroids will also become very high and may be out of the range in the given dataset. This is a major drawback of the K-means clustering algorithm. Step 3: Calculate the distance using Euclideans distance formula in equation 3. On the basis of the distances, generate the partition by assigning each sample to the closest cluster. Euclidean Distance Formula: (3) Where d(xi, xj) is the distance between xi and xj. xi and xj are the attributes of a given object, where i and j vary from 1 to N where N is total number of attributes of a given object. i,j and N are integers. Step 4: Compute new cluster centers as centroids of the clusters, again compute the distances and generate the partition. Repeat this until the cluster memberships stabilizes [9][10]. The strengths and weaknesses of the K-means clustering algorithm are discussed in table 2. Table 2. Strengths and Weakness of the K-means clustering Algorithm Strengths Weaknesses Time complexity is O(nkl). Linear time complexity in the size of the dataset. It is easy to implement, it has the drawback of depending on the initial centre provided. Space complexity is O(k + n). If a distance measure does not exist, especially in multidimensional spaces, first define the distance, which is not always easy. It is an order-independent algorithm. It generates same partition of data irrespective of order of samples. The Results obtained from this clustering algorithm can be interpreted in different ways. Not applicable All clustering techniques do not address all the requirements adequately and concurrently. The following are areas but not limited to where the K-means clustering algorithm can be applied: Marketing: Finding groups of customers with similar behavior given large database of customer containing their profiles and past records. Biology: Classification of plants and animals given their features. Libraries: Book ordering. Insurance: Identifying groups of motor insurance policy holders with a high average claim cost; identifying frauds. City-planning: Identifying groups of houses according to their house type, value and geographically location. Earthquake studies: Clustering observed earthquake epicenters to identify dangerous zones. WWW: Document classification; clustering web log data to discover groups of similar access patterns. Medical Sciences: Classification of medicines; patient records according to their doses etc. [11][12]. 2.2. Decision Tree (ID3) Algorithm The decision tree (ID3) produces the decision rules as an output. The decision rules obtained from ID3 are in the form of if-then-else, which can be use for the decision support systems, classification and prediction. The decision rules are helpful to form an accurate, balanced picture of the risks and rewards that can result from a particular choice. The function of the decision tree (ID3) is shown in the figure 1. Figure 1. The Function of Decision Tree (ID3) algorithm The cluster is the input data for the decision tree (ID3) algorithm, which produces the decision rules for the cluster. The following steps explain the Decision Tree (ID3) algorithm: Step 1: Let S is a training set. If all instances in S are positive, then create YES node and halt. If all instances in S are negative, create a NO node and halt. Otherwise select a feature F with values v1,,vn and create a decision node. Step 2: Partition the training instances in S into subsets S1, S2, , Sn according to the values of V. Step 3: Apply the algorithm recursively to each of the sets Si [13][14]. Table 3 shows the strengths and weaknesses of ID3 algorithm. Table 3. Strengths and Weaknesses of Decision Tree (ID3) Algorithm Strengths Weaknesses It generates understandable rules. It is less appropriate for a continuous attribute. It performs classification without requiring much computation. It does not perform better in problems with many class and small number of training examples. It is suitable to handle both continuous and categorical variables. The growing of a decision tree is expensive in terms of computation because it sorts each node before finding the best split. It provides an indication for prediction or classification. It is suitable for a single field and does not treat well on non-rectangular regions. 3. Methodology We combine two different data mining algorithms namely the K-means clustering and Decision tree (ID3) into a one algorithm using intelligent agent called Learning Intelligent Agent (LIAgent). The Learning Intelligent Agent (LIAgent) is capable of clustering and interpretation of the given dataset. The clusters can also be visualized by using 2D scattered graphs. The architecture of this agent system is shown in figure 2. Figure 2. The Architecture of LIAgent System The LIAgent is a combination of two data mining algorithms, the one is the K-means clustering algorithm and the second is the Decision tree (ID3) algorithm. The K-means clustering algorithm produces the clusters of the given dataset which is the classification of that dataset and the Decision tree (ID3) will produce the decision rules for each cluster which are useful for the interpretation of these clusters. The user can access both the clusters and the decision rules from the LIAgent. This LIAgent is used for the classification and the interpretation of the given dataset. The clusters of the LIAgent are further used for visualization using 2D scattered graphs. Decision tree (ID3) is faster to use, easier to generate understandable rules and simpler to explain since any decision that is made can be understood by viewing path of decision. They also help to form an accurate, balanced picture of the risks and rewards that can result from a particular choice. The decision rules are obta ined in the form of if-then-else, which can be used for the decision support systems, classification and prediction. A medical dataset Diabetes is used in this research paper. This is a dataset/testbed of 790 records. The data of Diabetes dataset is pre-processed, called the data standardization. The interval scaled data is properly cleansed. The attributes of the dataset/testbed Diabetes are: Number of times pregnant (NTP)(min. age = 21, max. age = 81) Plasma glucose concentration a 2 hours in an oral glucose tolerance test (PGC) Diastolic blood pressure (mm Hg) (DBP) Triceps skin fold thickness (mm) (TSFT) 2-Hour serum insulin (m U/ml) (2HSHI) Body mass index (weight in kg/(height in m)^2) (BMI) Diabetes pedigree function (DPF) Age Class (whether diabetes is cat 1 or cat 2) [15]. We create the four vertical partitions of the dataset Diabetes, by selecting the proper number of attributes. This is illustrated in tables 4 to 7. Table 4. 1st Vertically partition of Diabetes Dataset NTP DPF Class 4 0.627 -ive 2 0.351 +ive 2 2.288 -ive Table 5. 2nd Vertically partition of Diabetes Dataset DBP AGE Class 72 50 -ive 66 31 +ive 64 33 -ive Table 6. 3rd Vertically partition of Diabetes Dataset TSFT BMI Class 35 33.6 -ive 29 28.1 +ive 0 43.1 -ive Table 7. 4th Vertically partition of Diabetes Dataset PGC 2HIS Class 148 0 -ive 85 94 +ive 185 168 -ive Each partitioned table is a dataset of 790 records; only 3 records are exemplary shown in each table. For the LIAgent, the number of clusters k is 4 and the number of iterations n in each case is 50 i.e. value of k =4 and value of n=50. The decision rules of each clusters is obtained. For the visualization of the results of these clusters, 2D scattered graphs are also drawn. 4. Results and Discussion The results of the LIAgent are discussed in this section. The LIAgent produces the two outputs, namely, the clusters and the decision rules for the given dataset. The total sixteen clusters are obtained for all four partitions, four clusters per partition. Not all the clusters are good for the classification, only the required and useful clusters are discussed for further information. The sixteen decision rules are also generated by LIAgent. We are presenting three decision rules of three different clusters. The number of decision rules varies from cluster to cluster; it depends upon the number of records in the cluster. The Decision Rules of the 4th partition of the dataset Diabetes: Rule: 1 if PGC = 165 then Class = Cat2 else Rule: 2 if PGC = 153 then Class = Cat2 else Rule: 3 if PGC = 157 then Class = Cat2 else Rule: 4 if PGC = 139 then Class = Cat2 else Rule: 5 if HIS = 545 then Class = Cat2 else Rule: 6 if HIS = 744 then Class = Cat2 else Class = Cat1 Only six decision rules are for the 4th partition of the dataset. It is easy for any one to take the decision and interpret the results of this cluster. The Decision Rules of the 1st partition of the dataset Diabetes: Rule: 1 if DPF = 1.32 then Class = Cat1 else Rule: 2 if DPF = 2.29 then Class = Cat1 else Rule: 3 if NTP = 2 then Class = Cat2 else Rule: 4 if DPF = 2.42 then Class = Cat1 else Rule: 5 if DPF = 2.14 then Class = Cat1 else Rule: 6 if DPF = 1.39 then Class = Cat1 else Rule: 7 if DPF = 1.29 then Class = Cat1 else Rule: 8 if DPF = 1.26 then Class = Cat1 else Class = Cat2 The eight decision rules are for the 1st partition of the dataset. The interpretation of the cluster is easy through the decision rules and it also helps to take the decision. The Decision Rules of the 3rd partition of the dataset Diabetes: Rule: 1 if BMI = 29.9 then Class = Cat1 else Rule: 2 if BMI = 32.9 then Class = Cat1 else Rule: 3 if TSFK = 23 then Rule: 4 if BMI = 25.5 then Class = Cat1 else Rule: 5 if BMI = 30.1 then Class = Cat1 else Rule: 6 if BMI = 28.4 then Class = Cat1 else Class = Cat2 else Rule: 7 if BMI = 22.9 then Class = Cat1 else Rule: 8 if BMI = 27.6 then Class = Cat1 else Rule: 9 if BMI = 29.7 then Class = Cat1 else Rule: 10 if BMI = 27.1 then Class = Cat1 else Rule: 11 if BMI = 25.8 then Class = Cat1 else Rule: 12 if BMI = 28.9 then Class = Cat1 else Rule: 13 if BMI = 23.4 then Class = Cat1 else Rule: 14 if BMI = 30.5 then Rule: 15 if TSFK = 18 then Class = Cat2 else Class = Cat1 else Rule: 16 if BMI = 26.6 then Rule: 17 if TSFK = 18 then Class = Cat2 else Class = Cat1 else Rule: 18 if BMI = 32 then Rule: 19 if TSFK = 15 then Class = Cat2 else Class = Cat1 else Rule: 20 if BMI = 31.6 then Class = Cat2 , Cat1 else Class = Cat2 The twenty decision rules are for the 3rd partition of the dataset. The number of rules for this cluster is higher than the other two clusters discussed. The visualization is important tool which provides the better understanding of the data and illustrates the relationship among the attributes of the data. For the visualization of the clusters 2D scattered graphs are drawn for all the clusters. We are presenting the four 2D scattered graphs of four different clusters of different partitions. Figure 3. 2D Scattered Graph between NTP and DPF attributes of Diabetes dataset The distance between NTP and DPF attributes of Diabetes dataset varies at the beginning of the graph but after some interval the distance becomes constant. Figure 4. 2D Scattered Graph between DBP and AGE attributes of Diabetes dataset There is a variable distance between DBP and AGE attributes of the dataset. It remains variable throughout this graph. Figure 5. 2D Scattered Graph between TSFT and BMI attributes of Diabetes dataset The graph shows almost constant distance between TSFT and BMI attributes of the dataset. It remains constant throughout the graph. Figure 6. 2D Scattered Graph between PGC and 2HIS attributes of Diabetes dataset There is a variable distance between PGC and 2HIS attributes of the dataset. But in the middle of this graph there is some constant distance between these attributes. The structure of this graph is similar to the graph of figure 5. 5. Conclusion It is not simple for all the users that they can interpret and extract the required results from these clusters, until some other data mining algorithms or other tools are not used. In this research paper we have tried to address the issue by integrating the K-means clustering algorithm with the Decision tree (ID3) algorithm. The choice of the ID3 is due to the decision rules in the form of if-then-else as an output, which are easy to understand and help to take the decision. It is a hybrid combination of supervised and unsupervised machine learning, using intelligent agent, called a LIAgent. The LIAgent is helpful in the classification and prediction of the given dataset. Furthermore, 2D scattered graphs of the clusters are drawn for the visualization.

Multimedia Applications

Multimedia Applications MULTIMEDIA APPLICATIONS 1.0 THE PROJECT OVERVIEW v Develop an interactive animated movie that contains specified title and story. You are given the freedom of choosing the titles specified in Section 4.0. The focus of this multimedia application is to help the general public to be aware or to be educated about the current issue, or fields of interest you have chosen. The animated movie that you are yet to develop is to be used as an informative or educational tool. The scope and contents of the title chosen are to be entirely determined by the students. 2.0 OBJECTIVES OF THIS PROJECT: v Develop the students practical ability to implement and document multimedia application. v Introduce student to the current technical issues in the area of multimedia. 3.0 LEARNING OUTCOMES: At the end of this project, the students should be able to: Ø Develop multimedia presentation relating to a specific topic using the multimedia tools. Ø Distinguish the difference between effective and ineffective use of multimedia. Ø Have an impressive portfolio piece, and a thorough understanding of multimedia fundamentals. 4.0 PROJECT TITLE: v List of project topics for you to choose are as follows: Title Albert Einstein Stephen Hawking The life of DaVincci President Lincoln President Kennedy President George Washington Thomas Edinson Apollo 13 Political system in any country French Revolution Greatest Invention in Malaysia Prime Minister in any country Robot Terrorism Richest man in the world About the great artist, Picasso Russian Revolution Story about police Van Gogh Micheal Angelo Queen Elizabeth of England Human cloning Any Fairy Tales The greatest artists in Malaysia William Shakespeare Nielson Mandela Story about diamond The greatest literature of England Story about firemen Story about FBI Living beings in the sea Living beings in the desert Great Philosopher in the world 5.0 TYPE: v Individual work 6.0 REGISTRATION v You need to register the chosen titles with your lecturer, and get these approved. A proposal form of the project chosen is to be handed to me three weeks from today (submit on or before 18th October 2009; Total number of pages: half page) 7.0 PROJECT DESCRIPTION v Your application must have significant use of the following elements so that you get some practice with them: Element 1 Text and animated text 2 Graphic 3 Audio 4 Animation v All elements mentioned above might not be able to be covered in lecture before the submission due date, therefore you must learn yourself first so that you can apply them on your application. No doubt there will be further clarifications as the days progress! 8.0 DELIVERABLES: v The documents (project report in printed form; Assignment 1) and Multimedia Application (animated movie) in the form of a CD-ROM (assignment 2). 8.1 MULTIMEDIA APPLICATION IN CD FORM: v The completed animated movie must be compiled into an (*.exe) executable file and burned into a CD-ROM. Do not submit some other format like *.html, *.dir, etc. v The CD-ROM should also consist of raw media files (e.g. *.jpg, *.gif, *.psd, .mov etc.) and all Flash working files (*.fla). v The running time of your movie should not less than 1 minutes 8.2 DOCUMENTS: PROJECT REPORT v As part of your assessment, you will have to submit the project report in printed form which include the followings: * Table of contents * Acknowledgement Section * Objectives of your animated movie * Targeted users background * Targeted users requirements * Concepts art and character design * Abstract * Application structure * Storyboard * Creative and unique features in your movie * References (Use Harvard Naming Convention; Refer notes below) Note: v You may source pictures and information from the Internet. If you have accessed the Internet, reference the resources used carefully in your document. v All references must be made using the Harvard Naming Convention as shown below: The theory was first propounded in 1970 (Larsen, A.E. 1971), but since then has been refuted; M.K. Larsen (1983) is among those most energetic in their opposition†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. List of references at the end of your document must be specified in the following format: Larsen, A.E. 1971, A Guide to the Aquatic Science Literature, McGraw-Hill, London. Larsen, M.K. 1983, British Medical Journal (Online), Available World Wide Web: URL: http://libinfor.ume.maine.edu/acquatic.htm (Accessed 19 November 1995) Further information on other type of citation is available in Li, X. and Crane (1993), Electronic Style: A Guide to Citing Electronic Information, Meckler, Westport. v Total number of pages for the documents is in the range of 20 to 40 pages 9.0 PROJECT ASSESSMENT CRITERIA v Criteria for assessment will be based on: Ø Documentation (Assignment 1): Criteria Marks Allocated 1 Objectives 10 2 Target users background and their requirements 20 3 Concepts Art and character design 20 4 Storyboard (Inclusive of abstract, application structure and layout of application) 30 5 Creative and unique features in your movie 15 6 Originality (Reflected from Referencing of materials and Summary of what you have created or what effects have you made on multimedia elements) 5 Total 100 Ø Implementation (Assignment 2): Criteria Marks Allocated 1 Title and content: * Implementation suitable for intended audience? * Interesting? * Unique? * Clear? * Originality 5 2 Level of originality and innovation of graphics: * Amount of graphics self developed * Amount of graphics extracted directly from external source. * Amount of graphics extracted from external source and further innovated (like adding special effects added on the graphics) * Graphics quality * Quality of effects and innovation 20 3 Animations: * Amount of animations self developed * Amount of animations extracted directly from external source. * Amount of animations extracted from external source and further innovated (like adding special effects added on the graphics) * Depth and quality of animations 20 4 Sound: * Sound effect used? * Voice recorded? * Music used? * Sound quality 20 5 Technicality: * Level of interactivity (full interactivity? Or merely click and display) * Special Effects done on the system * Use of ActionScripts (ActionScript is strongly encouraged to use. If you have done so, remember to put the full script in your document. However, absent of ActionScript will not deduct your marks) * Full screen? * Able to run smoothly? 20 6 System development (compliant with the documents e.g. storyboard submitted earlier) 5 7 Presentation: * Professional style * Good use of language * Capability in answering questions addressed by lecturer * Proper referencing and citations. 10 Total 100% v Documentation contributes 40% and Implementation contributes 60% of the overall marks. 10.0 FRONT COVER OF PROJECT: v All reports must be prepared with a front cover. A protective transparent plastic sheet can be placed in front of the report to protect the front cover. The front cover should be presented with the following details: a) Names. b) Intake code. c) Subject. d) Project Title. e) Date Assigned (the date the report was handed out). f) Date Completed (the date the report is due to be handed in). 11.0 PLANNING: v You are advised to analyse your audience and survey the existing materials before starting out. Then, brainstorm, flowchart your ideas to see the general flow and finally, develop. Planning saves you a tot of heartache and headache later on. 12.0 MULTIMEDIA TOOLS v You have the options of developing the multimedia application using one of the following multimedia tools for your project: Element Tools 1 Text and animated text Win Word, Notepad 2 Graphic Editing Photoshop 3 Audio Any Sound editing tools like Audacity 4 Video (Optional) Windows Movie Maker 5 Animation Macromedia Suite (Flash, Director) 13.0 ACADEMIC INTEGRITY v You are expected to maintain the utmost level of academic integrity during the duration of the course. v Plagiarism is a serious offence and will be dealt with according to APIITs regulations on plagiarism. 7 Multimedia Applications in-course assessment handout

Methods of Fusion :: Nuclear

Methods of Fusion Abstract Nuclear fusion was discussed in this paper. First, the reader is given an introduction to nuclear power and is then led to fission/fusion. Fusion is discussed as being better than fission and reasons are given as to why that is so. Fusion methods are then discussed and current and planned machines are placed for discussion. Lastly, the machines are summarized. Introduction Today, you hear news about nuclear power. But what is nuclear power? Well, in an atom, there is a force known as the strong nuclear force, which exists in atoms. The first way is fission, which breaks the atom apart using some method. This is the method that is currently providing 20% of the power in the power grid. The other less developed method is still in the testing stage but the basic concept is fusion. Hydrogen isotopes (atoms with different numbers of neutrons) are combined together using several different methods which will be discussed later. This results in bonds, which generate energy (Jensen 2006). Discussion Now you know how fission is being utilized throughout the world, and you have a basic idea of how nuclear power works. However, there is a problem with nuclear fission being that there are many dangers. For one, nuclear fission creates nuclear waste, which cannot be destroyed and must be stored somewhere. Also, this waste is radioactive which makes the life surrounding the waste exposed to radiation and as a result, the waste destroys the nearby ecosystem. Also, if there happens to be a meltdown, radiation could spread for miles depending on the wind and kill many people. Take Chernobyl for example. There was a nuclear reactor there that meltdown. As a result, the area in a 20- Methods of Fusion mile radius around the plant had to be evacuated because the radiation levels were so high. The fuel is uncommon and takes time to purify in some cases. The solution to this problem is to use nuclear fusion. Through this, humankind has a much better way to create energy on the scale of MW. Not to mention, the fuel needed for nuclear fusion is only deuterium and tritium, which is an isotope of hydrogen, the most common element on Earth. Also, the energy output is very high. For example, JET, the Joint European Tokomak can produce 16 MW in one pulse. That’s 16 million watts. Also, the waste product of the fusion reactor is not radioactive but is instead helium.

Military Essay -- Department of Defense, ASVAB

According to the DOD, (2011) the department of defense doesn’t allow any third party anything in association with the military or any of it’s governmental functioning counter parts ala... national guards, reserves, commission corpse, naval reserves , marines reserves etc†¦ DODD rule 8750 insures that all military servicemen must be certified in their prospective fields and be proficient in their MOS field after boot camp and AIT. (DoDD, 2011) To become a soldier one must first visit a local recruiting office; there a person may engage in talks with a recruiter, the recruiter’s main job is to help assess the civilian enquires about their military desires, the recruiter must talk to a recruit and his legal guardian or parents as no one under 18 can’t make decisions for themselves without their parents/ guardians permission. The recruiter then will start the process, one of the recruiter’s first assignments is to get the civilian ASVAB scores from their local high school or if the recruit is from out of town they can be retested on the ASVAB. The ASVAB stands for Armed Services Vocational Aptitude Battery test and it accesses a recruit’s probability for enlistment, military job placement and career exploration after the military. ASVAB scoring is based on (IRT) Item Response Theory, this model is used because it measures the examinee’s ability to be placed on the same scale as everyone else and each test is tailored to a specific ability level needed when the examinee picks their military job. The IRT model uses the (3pl) in which measures a examinee’s level of ability to respond to a individual item or characteristics, especially those characteristics that represents difficulty, discrimination (How an item discriminates among ex... ...any part of the (PRT) they’ll be giving more intense exercises to perform this is to increase their stamina, and get them ready for the next phase of Army training as each phase last 3 weeks and get’s more intense until the last phase. Boot Camp Continued, The 2nd phase of boot camps consists of recruits performing tactical foot marches, learning basic rifleman marksmanship, field training exercises and engaging in skills and situational training exercises as well as the confidence obstacle course. Recruits at this point are being drilled daily on the rank & insignia badges as well as their chain of command from their drill instructor to the President of the United States; and they still have to pass (PRT) for phase II and with only 3 weeks left any recruit that fails has to devote their own free time into running and training to pass the final PRT in phase 3.

Tma01

There are various ways in which we can organise our thinking. These can be helpful when we are trying to improve our memory or when trying to recall things from the past. The three ways I am about to explain are all similar in the way we organise our thinking, and can be a powerful aid to our memory. Each point is backed up with evidence to support this. One of the ways we organise our thinking is by using mental images. By forming a mental image, we are thinking about something by constructing a mental picture of it in our mind.There are various ways of constructing mental images which can lead to better recall when trying to remember things. The mental image will give us a cue when we come to recalling the information. We will have spent time and effort studying the information previously and formed an image which we will have fixed in our memory. This will then help us to recall the information more easily. One technique for improving memory would be by using Mnemonics, which are based on the construction of mental images.An example of a mnemonic would be ‘Never Eat Shredded Wheat’ which would help us to remember ‘North, East, South and West’ in the right order. Another technique for improving memory would be the key word technique. The key word technique is useful when trying to learn a foreign language. To form the key word, you would find an English word or words that sound like the foreign word. Then you would make a mental image of the key word, along with the English translation, and this would be the key word technique.To prove that this technique is successful, Michael Raugh and Richard Atkinson (1975) carried out an experiment on two groups of participants using the key word technique. The participants were asked to memorise sixty Spanish words, but only one group were taught to use the key word technique. The participants using the key word technique scored much higher than the participants that did not use it. Another way we can organise our thinking is by forming concepts. A concept formation is a way of organising our thoughts by putting them into categories.One example of this would be ‘food’ which is a concept that has sub-concepts, such as fruit, meat and vegetables. We could then divide these sub-concepts into further sub-concepts; for example, fruit would be divided into pears, grapes, bananas, apples, etc. The use of concepts can improve memory by helping us when recalling information by putting them into categories. Take a practical situation for example, such as finding an item in a messy drawer. Trying to extract the item from the drawer would prove difficult and would take quite some time to find.However if this drawer was organised into different sections, then it would be a lot easier to find what you are looking for. We develop the same system when using concepts to organise our thinking when recalling information, thus improving our memory. An experiment to prove how con cepts can improve our recall was developed by Weston Bousfield (1953). Participants were asked to learn sixty words that could be placed into four categories. The words were mixed up, but the participants seemed to remember the words more easily when knowing they could be grouped with other words in the same category.So taking the word cat, they would remember the words dog, mouse and rabbit. In similar experiments, by being given the category headings, most participants find that this gives them a cue to access more words. Finally, we can organise our thinking by using schemas. A schema is a mental framework of knowledge about certain situations, objects, people, places and even yourself. Schemas are developed as a result of your experiences of the world and how you think about certain things. For example, if you were to think of the word ‘hospital’, your schema would include a list of everything you associate with a hospital.For example, hospital beds, the smell of cl eaning fluids, ambulance sirens, doctors and nurses, etc. Schemas can help provide a cue to prompt our memory when coming to recalling information. We will have stored the information in a specific category so that it can be recalled more easily. One example of this is shown in an experiment carried out by John Bransford and Marcia Johnson (1972). Participants were read a passage which described in detail the process of washing clothes, however they were not told that the title was ‘washing clothes’.Many of the participants found that they had difficulty in understanding the passage and were unable to recall the details. However once the participants were given the title to the passage, this provided the schema which helped them to recall the information more easily. Although schemas are an efficient way of helping us to organise our thinking by providing a cue when recalling information, they can also distort our recall and lead us astray. Evidence to prove this was ca rried out in a study by William Brewer (1981) to prove the distorting effects of schemas on memory.The participants were taken into an office and asked to wait for 35 seconds. They were then taken into another room and asked to recall the contents that they had seen in the office. Participants recalled the items that are fitting with a typical office schema; however they had failed to notice other objects in the room such as a brick and a pair of pliers, even recalling items such as a telephone which were not in the office. This study shows that we often adjust our recalled information so that it is in fitting with our existing schemas.In some cases this could have a detrimental effect, especially if you have witnessed a crime and need to be called to give an eye witness testimony. When coming to recalling events that happened in the past, there is a chance that the gaps in your memory will be unconsciously filled by inferences. In conclusion, mental images can improve our memory by forming a mental image in our mind, concepts by organising our thoughts and putting them into categories and schemas by developing a mental framework of our knowledge of our experiences.Each of these ways can give us a cue when we come to recalling information, thus improving our memory. However, although these ideas of organising our thinking may help us to improve our memory, they can also distort our recall and lead us astray.Word count = 1,095 References Spoors, P. , Dyer, E. , Finlay, L. and Marsh, G. (2011) starting with psychology, Milton Keynes, The Open University.

Ethical Standards and the conflict in schools

Educators function as a member of a squad and have a particular relationship with pupils, parents, other school forces, and the community. The quality of these relationships depends non merely on the work performed, but besides on the ethical behaviour demonstrated on the occupation. Educators are faced with ethical issues on a day-to-day footing, including confidentiality, record direction, and the demands placed upon them with the duty of learning pupils and pull offing a schoolroom. Educators frequently face state of affairss where their ain involvements, a pupil ‘s involvement, or the school ‘s involvement may conflict. Ethical criterions help us to go more cognizant of the right class of action with respect to a assortment of positions instead than our ain. Educators are obligated to be as to the full prepared as possible to work ethically, every bit good as lawfully, in the school environment at all times. Ethical criterions supply a model for reflecting on appropriate behaviour. For this assignment, I have researched four articles that address legal and ethical deductions on schoolroom direction in respects to the rights and duties of pupils, parents, and instructors. I will reflect, place, and sum up each article. Finally, I will reason with how these articles have made a difference in how I will pull off my schoolroom. Article 1 The article that I began with is Public school Law: Teachers ‘ and pupil ‘s rights by Martha McCarthy. McCarthy discusses the legal rights of the instructor and the pupil. The Negligent Tort Law shows that instructors may be considered apt if he or she could hold â€Å" foreseen and prevented hurt by exerting proper attention † ( McCarthy, Cambron-McCabe, 1992 ) . The first component of the Negligent Tort Law states that the responsibility to protect is the duty of the instructor – this responsibility includes all necessary safeguards to protect pupils that are under their supervising ( McCarthy, Cambron-McCabe, 1992 ) . Subsequently, if a pupil hurt could hold been anticipated or foreseeable by the instructor and they did non supply sensible supervising of the incident, so, carelessness on the instructor ‘s behalf has occurred ( McCarthy, Cambron-McCabe, 1992 ) . Yet, if a pupil ‘s action or consequence of a pupil ‘s hapless picks contribu ted to the hurt, so the incident itself is considered conducive carelessness, and the instructor is no longer apt ( McCarthy, Cambron-McCabe, 1992 ) . In happening carelessness on a instructor ‘s behalf, one must see the mature and developmentally appropriate behaviour. There are many factors that have to be taken into consideration overall when a negligent claim is filed. Some of such factors are the instructor ‘s enfranchisement, the instructor ‘s preparation, the environment in which the hurt occurred, the instructional activity, and the care of the equipment ( McCarthy, Cambron-McCabe, 1992 ) . How the jurisprudence is stated and the compulsory responsibility of attention can be really intimidating to many instructors and educational professionals. Furthermore, because of such bullying of the Negligent Tort Law, school territories and brotherhoods have mandated specific ordinances, along with policies and processs to forestall such possible incidents from happening ( McCarthy, Cambron-McCabe, 1992 ) . It could be just to state that overall, instructors have the duty to protect their pupils, and the pupils have the right to be protected while in attention of the school. However, when can a instructor ‘s duty take precedency over a pupil ‘s single rights? Hypothetically, a scenario may affect a pupil, whether knowing or non-intentional, seting another pupils wellness or safety in danger. The instructor must look at the public assistance of the pudding stone of pupils and has the right and duty to take the one pupil who is endangering the public assistance of the category from the activity/classroom, or environment to guarantee the wellbeing of the remainder of the category. Some could reason that excepting or taking the pupil is in direct misdemeanor of his/her single rights. The instructor ‘s chief duty of sensible attention could hold been jeopardized due to that pupil ‘s actions as good. Article 2 The 2nd article, Response and Responsibility in the Classroom by Edgar Baguio discusses duties of pupils within the schoolroom. Although Baguio introduces the thought of response of the pupil, which entails how a pupil reacts to a instructor ‘s schoolroom direction system, duty ( Baguio, 2008 ) . Responsibility defines the pupil ‘s occupation of following policies and processs in the schoolroom ( Baguio, 2008 ) . Baguio farther discusses that an effectual schoolroom consists of non merely a instructor, but of pupils who follow through with the schoolroom duties ( Baguio, 2008 ) . He believes that both parties must make their duties so it is easier to trust and swear one another ( Baguio, 2008 ) . The schoolroom direction system becomes less of an issue when trust is established. Article 3 The article Parent-Teacher Conferencing, by Joseph C. Rotter, Edward H. Robinson III, and Mary Ann Fey, discusses the importance of communicating between instructors and parents. It is expressed that there is a important demand for effectual parent-teacher conferencing is the â€Å" legitimate right of parent to hold a voice in the instruction of their kid † ( Rotter et al, pg. 7, 1987 ) . Over the old ages, parents have been progressively more interested in their kids ‘s day-to-day educational activities. Communication is the key. â€Å" When instructors and parents view the educational procedure as a collaborative attempt, the parent-teacher conference becomes a cardinal instructional scheme that will heighten the kid ‘s growing and advance more effectual acquisition † ( Rotter et al, pg. 8, 1987 ) . The article besides addresses the different alterations that affect instructor and parent relationships. The primary concern is the alteration of the household construction and kineticss. The traditional household has changed to being blended, holding individual parents, or holding same sex parents. Because of the obvious alterations, parents and teachers no longer portion common experiences ( Rotter et al, 1987 ) . A opportunity to hold day-to-day interaction has created an obvious cuneus between instructors and parents. The inquiry is how to make full that spread. Communication is the cardinal to making solid dealingss between instructors and parents. Having parent-teacher conferences allows for the most direct signifier of communicating that can be the most meaningful nexus between place and school for the pupil ( Rotter et al, 1987 ) . However, the signifier of communicating is an of import factor. Harmonizing to Rotter et Al, as an pedagogue, holding heat, empathy, regard, concreteness, genuineness, immediateness, and confrontation are of import qualities to hold, but besides cognizing how and when to portray such qualities are requirements for effectual communicating ( Rotter et al, 1987 ) . Article 4 Sarah Ganly wrote Rights and Responsibilities of a Teacher and a Student. Ganly addresses teacher duty within the schoolroom and the rights of the pupils ( Ganly, 2007 ) . Student safety is one of the most of import duties of the instructor ( Ganly, 2007 ) . However, what is different with this peculiar article in comparing to the others is that the parent ‘s rights are addressed. Galley ‘s article addresses that parents have the right to direct their kids to school cognizing that their kid will be safe while in the attention of the school and its instructors ( Ganly, 2007 ) . Teacher ‘s liability and answerability are examined within this article. The illustration of such is that, the jurisprudence states that instructors are â€Å" held apt for a pupil ‘s public assistance if injury is foreseeable † ( Ganly, 2007 ) . Every state of affairs must be viewed separately, and if any, palliating fortunes must be taken into history excessively. When acquisition activities are off premises, the instructor ‘s rights and duties should non be taken lightly. Although, there are many policies and processs that go into readying of field trips, the pupils degree of safety should ever be examined and be the first precedence of instructors and schools. It is a instructor ‘s duty to guarantee the safety and wellbeing of each pupil on a field trip. In order for the instructor to keep overall safety for the pupils, they may hold to be forced to conflict upon a pupil ‘s single rights. This state of affairs within itself can be considered â€Å" grey affair † and fortunes have to be analyzed suitably without premises. Because of the many instances of carelessness and inappropriate behaviour go oning with schools across the state, the rights and duties of pupils and instructors has been a hot controversial issue. There seems to be a important sum of failure of recognition of the direct relationship between pupil â €˜s rights and instructor ‘s duties. Decision I feel confident that my method of schoolroom direction is really appropriate. It is a cross between Wong ‘s Pragmatic Classroom Model and Kagan, Kyle, and Scott ‘s Win-Win Discipline Model. I believe it is the pedagogue ‘s duty to learn pupils how to self-monitor their ain behaviour and keep them accountable. The ultimate ends I have for my pupils is to be able to pull off themselves suitably, to be able to run into their demands through responsible picks, and to be able to develop life accomplishments that will function them into the hereafter. The mix attack of Wong, Kagan, Kyle, and Scott works good for me to promote pupils to take ownership of their learning experience and overall success. Using both Wong ‘s Pragmatic Classroom Model and the Win-Win Discipline Model allows me to keep the pupils responsible for their ain behaviour, larning and success, they both hold the instructor responsible to working hard to keep a safe, positive schoolroom environment that helps pupil work to accomplish personal ends.