...Running head: ACCURACY OF DATA INPUT Accuracy of data input Intro Printed questionnaires Since we are working with a document that was created digitially, then printed on paper making it analog, the trick will be finding a method that easily converts the questionnaire's answers back to digital. Options are limited, since we would be relying on the individual's handwritten marks. The ability to scan test using scantrons has been around for a while, and has proven to be an efficient and effective way to quickly grade test. However, scantrones, or OMRs, rely on the testee to fill in bubbles using only #2 pencils. For the purposes of our questionaire, this would work, but #2 pencils would have to be supplied with the questionaire. A better method would be using OCR technology that scans and recongnizes the document based on light properties. With this method, the questionaires could be filled out using any analog input device, pencils or pens. Telephone survey Telephone surveys used to be conducted primarily by a pool of telemarketers that would use terminals to input the user's responses to questions. However, automated voice technology has enable a greater number of calls to go out that ask the user questions based on prerecorded questions. Because of this method, automated survey's rely on user input from touchtone key input, or automated voice response. Automated voice response systems has improved, but they rely on the background noice from the user’s side to be quite...
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...Security of resources 2. Compare input with master data b. Effectiveness Goals A & B c. Efficient employment of resources d. Input accuracy 3. Immediately separate checks and RA’s e. Effectiveness Goals A & B f. Security of resources 4. Compare checks and RA’s g. Input validity h. Input accuracy 1. Document design a. Effectiveness goal A b. Efficient employment of resources c. Input accuracy 2. Written approvals d. Security of resources e. Input validity 3. Preformatted screens f. Effectiveness goal A g. Efficient employment of resources h. Input accuracy 4. Online prompting i. Effectiveness goal A j. Efficient employment of resources k. Input accuracy 5. Populate input screens with master data l. Effectiveness goal A m. Efficient employment of resources n. Input validity o. Input accuracy 6. Compare input data with master data p. Effectiveness goal A q. Efficient employment of resources r. Input validity s. Input accuracy 7. Procedures for rejected inputs t. Input completeness u. Input accuracy 8. Programmed edit checks v. Effectiveness goal A w. Efficient employment of resources x. Input accuracy 9. Confirm input acceptance y. Input completeness 10. Automated data entry z. Effectiveness goal...
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...Template for Control Matrix – add or delete rows as needed | |Control Goals of the XXX Company XXX process | | |Control Goals of the operations process |Control goals of the information process | | |Ensure effectiveness of |Ensure efficient |Ensure security |For the Accounting Record inputs, |For the Accounts | | |operations by achieving the |employ-ment of |of resources |ensure: |Receivable master data, | | |following goals: |resources (people,|(source | |ensure: | |Recommended control plans | |computers) |document) | | | | | | | | | | | ...
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...Chapter 7 1. A process by which organizations select objectives, establish processes to achieve objectives, and monitor performance is |a. |enterprise risk management | |b. |internal control | |c. |organizational governance | |d. |risk assessment | ANS: C 2. A process, effected by an entity’s board of directors, management and other personnel, applied in strategy setting and across the enterprise, designed to identify potential events that may effect the entity, and manage risk to be within its risk appetite, to provide reasonable assurance regarding the achievement of entity objectives. |a. |enterprise risk management | |b. |internal control | |c. |organizational governance | |d. |risk assessment |...
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...The computation time and the accuracy rate are the two main measurements for evaluating the performance of the IDS. So our goal is to focus on reducing the computation time and finding an efficient detection mechanism to improve the accuracy rate of the proposed algorithm for recognizing the network traffic. A. Overview The algorithm consists two phases: the classification phase and clustering phase. In the classification phase, the artificial neural network, one of the core methods of Computational Intelligence is used to create the classifier from the known network traffic data. The neural network it identifies the input pattern and tries to output the corresponding class. It can map input patterns to their associated output patterns using their mapping capabilities. They can be trained with known examples of a problem...
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... * Tracking the Learners’ Progress Strengths: One of the strengths of the teacher’s spreadsheet was the use of conditional formatting. Conditional formatting was helpful by easily presenting data, by formatting a range of cells depending on certain grades or scores means that analysing and categorising data will much easier with a visual representation and the teacher can make more accurate conclusions. The way the tables are laid out, and by defining a range is very useful for a teacher when it comes to neatly organising a spreadsheet with many tables of class’s results. By defining a range means that tables are easy to input into formulae, and will help reduce errors. AutoSum is very beneficial to a teacher because it simply adds up an entire column without having to add each cell individually. This saves a lot of time, and helps reduce errors, especially if there is lots of students’ data. Weaknesses: Macros are not included in the spreadsheet, which would’ve been very useful for a teacher. Macros stop repetitive tasks being completed over and over again. This is useful as it saves a lot of time to the teacher, e.g. if they click a customised button which filters data or changes sheets. This will also improve the usability of the spreadsheet and make the data input easier. Goal seek, which also isn’t included in the spreadsheet, would also be very beneficial for a teacher. Goal seek is where a cell total changes in order to reach a possible result, and this...
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...Document design – a control plan in which source document is designed to make it easier to prepare the document initially and later to input data from the document. Written/electronic approvals – form of signature or initials on a document to indicate that someone has authorized the event. Preformatted screens – control the entry of data be defining the acceptable format of each data field. Online prompting – requests user input or asks questions that the user must answer. Populate input screens with master data – the clerk enters the identification code for an entity and the system retrieves data about that entity from the master data. Compare input data with master data – we can determine the accuracy and validity of the input data. Procedures for rejected inputs – designed to ensure that erroneous data are corrected and resubmitted for processing. Programmed edit checks – automatically performed by data entry programs upon entry of the input data. Reasonableness checks or limit checks – test whether the contents of the data entered fall within predetermined limits. Document/record hash totals – reflect a summarization of any numeric data field within the input document or record, such as item numbers or quantities on a customer order. Mathematical accuracy checks – compare calculations performed manually to those performed by the computer to determine whether a document has been entered correctly. Check digit verification – involves the inclusion...
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...Minimal ANN (MANN) model for Data Classification Gunanidhi Pradhan, Bhubanananda Orissa School of Engineering, Cuttack gunanidhi_p@rediffmail.com Gadde Vyshnavi Kalyan,Final Yr IT,ANITS vyshv.sanjana@gmail.com Suresh Chandra Satapathy, MIEEE, Anil Neerukonda Institute of Technology & Sciences (ANITS), Vishakapatnam Dist sureshsatapathy@ieee.org Bhabatosh Mitra,FM University, Balasore bhaba_mit@yahoo.co.uk Sabyasachi Pattnaik,,FM University, Balasore spattnaik40@yahoo.co.in Abstract- Data Classification is a prime task in Data mining. Accurate and simple data classification task can help the clustering of large dataset appropriately. In this paper we have experimented and suggested a simple ANN based classification models called as Minimal ANN ( MANN) for different classification problems. The GA is used for optimally finding out the number of neurons in the single hidden layered model. Further, the model is trained with Back Propagation (BP) algorithm and GA (Genetic Algorithm) and classification accuracies are compared. It is revealed from the simulation that our suggested model can be a very good candidate for many applications as these are simple with good performances. Keywords- ANN, Genetic Algorithm, Data classification I. INTRODUCTION Data classification is a classical problem extensively studied by statisticians and machine learning researchers. It is an important problem in variety of engineering and scientific disciplines such as biology, psychology, medicines, marketing...
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...decimal numbers through a string of binary digits. The Word 'Computer'usually refers to the Center Processor Unit plus Internal memory. Computer is an advanced electronic device that takes raw data as input from the user and processes these data under the control of set of instructions (called program) and gives the result (output) and saves output for the future use. It can process both numerical and non-numerical (arithmetic and logical) calculations.The basic components of a modern digital computer are: Input Device,Output Device,Central Processor. A Typical modern computer uses LSI Chips. Charles Babbage is called the "Grand Father" of the computer.The First mechanical computer designed by charles Babbage was called Analytical Engine. It uses read-only memory in the form of punch cards. Four Functions about computer are: accepts data | Input | processes data | Processing | produces output | Output | stores results | Storage | Input (Data): Input is the raw information entered into a computer from the input devices. It is the collection of letters, numbers, images etc. Process: Process is the operation of data as per given instruction. It is totally internal process of the computer system. Output: Output is the processed data given by computer after data processing. Output is also called as Result. We can save these results in the storage devices for the future use. Uses of Computer Education : Getting the right kind of information is a major...
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...definition I have determined that defines a data type is different types of data that will include a range of value or a specific type of data in a storage formant. A variable that is stored as data in a computer program has to be a specific data type. There are many different types of data that includes dates, values, numbers, and characters to name a few. Different data types can be used by a large number of database applications. A specific kind of data is usually required in certain fields of a database. For example, if a business has a database for all the employees a different data type would be used for each kind of data. The start date for an employee could be stored in a date format, but a wage/salary amount would be stored as an integer. If database types are kept the same in all the records then the applications are easily search, compare, and sort different records. Data typing is important if you want to keep a business managed. Data entry is important because it is a way of organizing data that keeps a business well managed. Data entry is very important if you want to manage information and records in a computer software program. Data entry assures accuracy of company’s data and all information keeps up to date. Accuracy is very important in data entry validation. Validation of data entry will reduce the problems of inaccuracy if incorrect data is input. When creating a data entry the format for each field can input. The date, time, number, character, etc. format...
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...Jr. CIS/319 Version 8 April 29, 2012 Ike Shia Abstract This paper is to focus on the accuracy, convenience, different types of storage methods, and the roles they play as far as the speed of the systems. Throughout the paper it discusses the best input and output methods for various hardware and software. Accuracy of Data Accuracy of data input is important. What method of data input would be best for each of the following situations and why: As far for printed questionnaires the best method for data input would be a keyboard, because it permits one to produce the required test that formulates the questionnaires. The best method for a telephone survey would be voice recognition and recording system because a voice input device can be programmed to distinguish and record answers spoken into the receiver allowing it to all be computed. Bank checks would best be used in a scanning method that recognizes bar codes. To be more specific a magnetic scanning input device would be the exact system to use. This system reads the numbers at the bottom of the checks and will mechanically make modifications to the correct accounts. It will input the codes in a system will magnetize the information at the bottom of the check for simple interpretation. For retail tags the best data input for would be a bar code scanner as well. This specific scanner is called an optical scanning input device. By using a bar code scanner it would be unnecessary to use a keyboard to enter numbers...
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...ing. This approach is robust to geometric and photometric learning. We found that classification using features extracted transformations, and showed less than 5% error on the LFPW manually from facial images using principal component anal- dataset. ysis yielded on average 40% classification accuracy. Using fea- The facial landmarks (eyes, eyebrows, nose, mouth) are intutures extracted by facial landmark detection, we received on itively the most expressive features in a face, and could also average 52% classification accuracy. However, when we used serve as good features for emotion classification. a convolutional neural network, we received 65% classification accuracy. 1.3 1 Support vector machines are widely used in classification problems, and is an optimization problem that can be solved in its dual form, Introduction Detecting facial expressions is an area of research within computer vision that has been studied extensively, using many different approaches. In the past, work on facial image analysis concerned robust detection and identification of individuals [5]. More recently, work has expanded into classification of faces based on features extracted from facial data, as done in [6], and using more complex systems like convolutional neural networks, as done in [1] and [2]. In our project, we...
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...Computer A. Definition Computer an electronic device for storing and processing data, typically in binary form, according to instructions given to it in a variable program. (Oxford Dictionary) Computer is general purpose machine, commonly consisting of digital circuitry, that accepts (inputs), stores, manipulates, and generates (outputs) data as numbers, text, graphics, voice, video files, or electrical signals, in accordance with instructions called a program. (Business Dictionary) B. Characteristics (Computer Notes, DINESH THAKUR) *Speed: - As you know computer can work very fast. It takes only few seconds for calculations that we take hours to complete. *Accuracy: - The degree of accuracy of computer is very high and every calculation is performed with the same accuracy. The accuracy level is 7 determined on the basis of design of computer. *Diligence: - A computer is free from tiredness, lack of concentration, fatigue, etc. It can work for hours without creating any error. If millions of calculations are to be performed, a computer will perform every calculation with the same accuracy. Due to this capability it overpowers human being in routine type of work. *Versatility: - It means the capacity to perform completely different type of work. You may use your computer to prepare payroll slips. *Power of Remembering: - Computer has the power of storing any amount of information or data. Any information can be stored and recalled as long as you require it, for any numbers...
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...separate set of data not used in the training to evaluate the performance of a model. • Describe the different validation methods to evaluate model performance. • Explain the different measures used to measure model performance, including lift chart. • Describe a systematic search process to find the best performing model. 5-1 Study Guide 5: Performance Evaluation Reading material Textbook Chapter 5 (exclude 5.5, 5.6, 5.9 & 5.10) Kennedy et al, Section 11.2. 1. Performance evaluation It important to recognize that performance evaluation is the task involved in step 6 (training and testing) and constitutes the key component in comparing multiple models in step 7 of the data mining process, described in Study Guide 4. Training is a process of transforming a set of data into a model using a learning algorithm. Once the data is ready (after steps 2, 3 and 4) and an algorithm is selected (step 5), training is a straightforward process (the first part in step 6). Refer to the data mining process in pages 4-1 and 4-2. In this Study Guide, we focus on issues related to model evaluation (the second part of step 6), i.e. we want evaluate how well the trained model will perform for unseen or future data. 2. Use only unseen data for performance evaluation In evaluating the performance of a model, we are evaluating how well the model generalizes (as opposed to memorize) the seen data in the training set. The training data is said to have...
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...Minimal ANN (MANN) model for Data Classification Gunanidhi Pradhan, Bhubanananda Orissa School of Engineering, Cuttack gunanidhi_p@rediffmail.com Gadde Vyshnavi Kalyan,Final Yr IT,ANITS vyshv.sanjana@gmail.com Suresh Chandra Satapathy, MIEEE, Anil Neerukonda Institute of Technology & Sciences (ANITS), Vishakapatnam Dist sureshsatapathy@ieee.org Bhabatosh Mitra,FM University, Balasore bhaba_mit@yahoo.co.uk Sabyasachi Pattnaik,,FM University, Balasore spattnaik40@yahoo.co.in Abstract- Data Classification is a prime task in Data mining. Accurate and simple data classification task can help the clustering of large dataset appropriately. In this paper we have experimented and suggested a simple ANN based classification models called as Minimal ANN ( MANN) for different classification problems. The GA is used for optimally finding out the number of neurons in the single hidden layered model. Further, the model is trained with Back Propagation (BP) algorithm and GA (Genetic Algorithm) and classification accuracies are compared. It is revealed from the simulation that our suggested model can be a very good candidate for many applications as these are simple with good performances. Keywords- ANN, Genetic Algorithm, Data classification I. INTRODUCTION Data classification is a classical problem extensively studied by statisticians and machine learning researchers. It is an important problem in variety of engineering and scientific disciplines such as biology, psychology, medicines, marketing...
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