...Anencephaly is a serious birth defect in which a baby is born without parts of the brain and skull. It is a type of neural tube defect; these are birth defects that happen during the first month of pregnancy, and it’s usually before a woman knows she is pregnant. Keywords: N/A Birth Defects: Anencephaly Birth defects are a structural or/and a functional of abnormalities that are present at birth that cause physical or mental disability. They’re the leading cause of death for infants and a fetus during the first year of life, and they can be fatal. Anencephaly is an example of a neural tube defect, a condition that results from an error in the first weeks of embryonic development. The term embryonic development refers to the changes that take...
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...www.elsevier.com/locate/atoures Annals of Tourism Research, Vol. 32, No. 1, pp. 93–111, 2005 Ó 2005 Elsevier Ltd. All rights reserved. Printed in Great Britain 0160-7383/$30.00 doi:10.1016/j.annals.2004.05.001 MARKET SEGMENTATION A Neural Network Application Jonathan Z. Bloom University of Stellenbosch, South Africa Abstract: The objective of the research is to consider a self-organizing neural network for segmenting the international tourist market to Cape Town, South Africa. A backpropagation neural network is used to complement the segmentation by generating additional knowledge based on input–output relationship and sensitivity analyses. The findings of the self-organizing neural network indicate three clusters, which are visually confirmed by developing a comparative model based on the test data set. The research also demonstrated that Cape Metropolitan Tourism could deploy the neural network models and track the changing behavior of tourists within and between segments. Marketing implications for the Cape are also highlighted. Keywords: segmentation, SOM neural network, input–output analysis, sensitivity analysis, deployment. Ó 2005 Elsevier Ltd. All rights reserved. ´ ´ Resume: Segmentation du marche: une application du reseau neuronal. Le but de la ´ ´ recherche est de considerer un reseau neuronal auto-organisateur pour segmenter le marche ´ ´ ´ touristique international a Cape Town, en Afrique du Sud. On utilise un reseau neuronal de ` ´ retropropogation pour...
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...EXECUTIVE SUMMARY INTRODUCTION/BACKGROUND The objective of the thesis is to predict and optimize the mechanical properties of Aircraft fuselage aluminium (AA5083). Firstly, data-driven modelling techniques such as Artificial Neural – Fuzzy networks and regressive analysis are used and by making the effective use of experimental data, FIS membership function parameters are trained. At the core, mathematical model that functionally relates tool rotational speed and forward movement per revolution to that of Yield strength, Ultimate strength and Weld quality are obtained. Also, simulations are performed, and the actual values are compared with the predicted values. Finally, multi-objective optimization of mechanical properties fuselage aluminium was undertaken using Genetic Algorithm to improve the performance of the tools industrially. AIMS AND OBJECTIVES Objectives of the dissertation include Understanding the basic principles of operation of Friction Stir Welding (FSW). Gaining experience in modelling and regressive analysis. Gaining expertise in MATLAB programming. Identifying the best strategy to achieve the yield strength, Ultimate Tensile strength and Weld quality of Friction Stir Welding. Performing optimization of mechanical properties of FSW using Genetic Algorithm. I To draw conclusions on prediction of mechanical properties of FSW optimization of aircraft fuselage aluminium. ACHIEVEMENTS The basic principles of friction welding of the welding...
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...Stereoscopic Building Reconstruction Using High-Resolution Satellite Image Data Anonymous submission Abstract—This paper presents a novel approach for the generation of 3D building model from satellite image data. The main idea of 3D modeling is based on the grouping of 3D line segments. The divergence-based centroid neural network is employed in the grouping process. Prior to the grouping process, 3D line segments are extracted with the aid of the elevation information obtained by using area-based stereo matching of satellite image data. High-resolution IKONOS stereo images are utilized for the experiments. The experimental result proved the applicability and efficiency of the approach in dealing with 3D building modeling from high-resolution satellite imagery. Index Terms—building model, satellite image, 3D modeling, line segment, stereo I. I NTRODUCTION Extraction of 3D building model is one of the important problems in the generation of an urban model. The process aims to detect and describe the 3D rooftop model from complex scene of satellite imagery. The automated extraction of the 3D rooftop model can be considered as an essential process in dealing with 3D modeling in the urban area. There has been a significant body of research in 3D reconstruction from high-resolution satellite imagery. Even though a natural terrain can be successfully reconstructed in a precise manner by using correlation-based stereoscopic processing of satellite images [1], 3D building reconstruction...
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...International Review of Business Research Papers Vol.2. No.4. December 2006, Pp. 39-50 eBusiness-Process-Personalization using Neuro-Fuzzy Adaptive Control for Interactive Systems Zunaira Munir1 , Nie Gui Hua2 , Adeel Talib3 and Mudassir Ilyas4 ‘Personalization’, which was earlier recognized as the 5th ‘P’ of e-marketing , is now becoming a strategic success factor in the present customer-centric e-business environment. This paper proposes two changes in the current structure of personalization efforts in ebusinesses. Firstly, a move towards business-process personalization instead of only website-content personalization and secondly use of an interactive adaptive scheme instead of the commonly employed algorithmic filtering approaches. These can be achieved by applying a neuro-intelligence model to web based real time interactive systems and by integrating it with converging internal and external e-business processes. This paper presents a framework, showing how it is possible to personalize e-business processes by adapting the interactive system to customer preferences. The proposed model applies Neuro-Fuzzy Adaptive Control for Interactive Systems (NFACIS) model to converging business processes to get the desired results. Field of Research: Marketing, e-business 1. Introduction: As Kasanoff (2001) mentioned, the ability to treat different people differently is the most fundamental form of human intelligence. "You talk differently to your boss than to...
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...the stronger trend. In this paper we investigate the use of the Hurst exponent to classify series of financial data representing different periods of time. Experiments with backpropagation Neural Networks show that series with large Hurst exponent can be predicted more accurately than those series with H value close to 0.50. Thus Hurst exponent provides a measure for predictability. KEY WORDS Hurst exponent, time series analysis, neural networks, Monte Carlo simulation, forecasting In time series forecasting, the first question we want to answer is whether the time series under study is predictable. If the time series is random, all methods are expected to fail. We want to identify and study those time series having at least some degree of predictability. We know that a time series with a large Hurst exponent has strong trend, thus it’s natural to believe that such time series are more predictable than those having a Hurst exponent close to 0.5. In this paper we use neural networks to test this hypothesis. Neural networks are nonparametric universal function approximators [9] that can learn from data without assumptions. Neural network forecasting models have been widely used in financial time series analysis during the last decade [10],[11],[12]. As universal function approximators, neural networks can be used for surrogate predictability. Under the same conditions, a time series with a smaller forecasting error than another is said to be more predictable. We study the Dow-Jones...
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...MIDTERM: CS 6375 INSTRUCTOR: VIBHAV GOGATE October, 23 2013 The exam is closed book. You are allowed a one-page cheat sheet. Answer the questions in the spaces provided on the question sheets. If you run out of room for an answer, use an additional sheet (available from the instructor) and staple it to your exam. • NAME • UTD-ID if known • SECTION 1: • SECTION 2: • SECTION 3: • SECTION 4: • SECTION 5: • Out of 90: 1 CS 6375 FALL 2013 Midterm, Page 2 of 13 October 23, 2013 CS 6375 FALL 2013 Midterm, Page 3 of 13 October 23, 2013 SECTION 1: SHORT QUESTIONS (15 points) 1. (3 points) The Naive Bayes classifier uses the maximum a posteriori or the MAP decision rule for classification. True or False. Explain. Solution: True. The decision rule for the Naive Bayes classifier is: P (Xi |Y = y) arg; max P (Y = y) y i One can think of P (Y = y) as the prior distribution and P (Xi |Y = y) as the data likelihood. Note that when we do the learning, we are using the MLE approach. The decision rule is using MAP inference but the learning algorithm is using the MLE approach. Make sure you understand what this distinction means. 2. (6 points) Let θ be the probability that “Thumbtack 1” (we will abbreviate it as T1) shows heads and 2θ be the probability that “Thumbtack 2” (we will abbreviate it as T2) shows heads. You are given the following Dataset (6 examples). T1 Tails T2 Heads T1 Tails T1 Tails T2 Heads T2 ...
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...2 CHAPTER 2.1 2.2 2.3 Decision Making and Business Processes Why Do I Need To Know This LEARNING OUTCOMES Explain the difference between transactional data and analytical information, and between OLTP and OLAP. Define TPS, DSS, and EIS, and explain how organizations use these types of information systems to make decisions. Understand what AI is and the four types of artificial intelligence systems used by organizations today. Describe how AI differs from TPS, DSS, and EIS. Describe the importance of business process improvement, business process reengineering, business process modelling, and business process management to an organization and how information systems can help in these areas. This chapter describes various types of business information systems found across the enterprise used to run basic business processes and used to facilitate sound and proper decision making. Using information systems to improve decision making and re-engineer business processes can significantly help organizations become more efficient and effective. ? 2.4 2.5 As a business student, you can gain valuable insight into an organization by understanding the types of information systems that exist in and across enterprises. When you understand how to use these systems to improve business processes and decision making, you can vastly improve organizational performance. After reading this chapter, you should have gained an appreciation of the various kinds of information systems employed...
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...shoes on their feet all the time because they have no feeling in the bottom of the feet and can’t tell if it is hot or cold, so in winter they could get frostbite and in summer they could burn their feet on the hot pavement. This disease is not curable at this time only its symptoms are managed if they can be. The Federal Government, the National Institute of Neurological Disorders and Stroke a component of the National Institute of Health supports research on the brain and nervous system disorders including Spina Bifida. The Institute is conducting research at laboratories in Bethesda, Maryland. In one study by the institute scientists are looking at the hereditary basis of neural tube defects. The goal of the research is to find the genetic facts that make some children more susceptible to neural tube defects than others. Lessons...
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...EEL5840: Machine Intelligence Introduction to feedforward neural networks Introduction to feedforward neural networks 1. Problem statement and historical context A. Learning framework Figure 1 below illustrates the basic framework that we will see in artificial neural network learning. We assume that we want to learn a classification task G with n inputs and m outputs, where, y = G(x) , (1) x = x1 x2 … xn T and y = y 1 y 2 … y m T . (2) In order to do this modeling, let us assume a model Γ with trainable parameter vector w , such that, z = Γ ( x, w ) (3) where, z = z1 z2 … zm T . (4) Now, we want to minimize the error between the desired outputs y and the model outputs z for all possible inputs x . That is, we want to find the parameter vector w∗ so that, E ( w∗ ) ≤ E ( w ) , ∀w , (5) where E ( w ) denotes the error between G and Γ for model parameter vector w . Ideally, E ( w ) is given by, E(w) = ∫ y – z 2 p ( x ) dx (6) x where p ( x ) denotes the probability density function over the input space x . Note that E ( w ) in equation (6) is dependent on w through z [see equation (3)]. Now, in general, we cannot compute equation (6) directly; therefore, we typically compute E ( w ) for a training data set of input/output data, { ( x i, y i ) } , i ∈ { 1, 2, …, p } , (7) where x i is the n -dimensional input vector, x i = x i 1 x i 2 … x in T (8) x2 y2 … … Unknown mapping G xn ym z1 z2 Trainable model Γ … zm -1- model outputs y1 … inputs x1...
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...Title :Wind speed prediction using Artificial Neural Network (ANN) Abstract : The crisis of fossil based fuel around the world has led to the research of Renewable Energy sources. One of the oldest sources of Renewable energy was using the wind to generate electrical or mechanical power using windmills. To use it efficiently the wind speed which determines the wind power must be known beforehand. Wind speed is a random variable depending on meteorological variables like atmospheric pressure,temperature,relative humidity & such. Methods that are currently being applied to predict wind speed are Statistical, Intelligent systems, Time series, Fuzzy logic, neural networks.Our focus will be on using Artificial Neural Network to predict the wind speed in daily basis in this report. Chapter 1 1.1 Introduction Bangladesh has a 724 lm long coastal area where south-westerly tradewind& sea breeze makes the usage of wind as a renewable energy source very visible. But, not much systematic wind study has been made, adequate information on the wind speed over the country and particularly on wind speeds at hub heights of wind machines is not available. A previous study (1986) showed that for the wind monitoring stations of Bangladesh Meteorological Department (BMD) the wind speed is found to be low near the ground level at heights of around 10 meter. Chittagong – Cox’s Bazar seacoast and coastal off-shore islands appeared to have better wind speeds. Measurements...
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...NEURAL NETWORKS by Christos Stergiou and Dimitrios Siganos | Abstract This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained. Finally, the mathematical models involved are presented and demonstrated. Contents: 1. Introduction to Neural Networks 1.1 What is a neural network? 1.2 Historical background 1.3 Why use neural networks? 1.4 Neural networks versus conventional computers - a comparison 2. Human and Artificial Neurones - investigating the similarities 2.1 How the Human Brain Learns? 2.2 From Human Neurones to Artificial Neurones 3. An Engineering approach 3.1 A simple neuron - description of a simple neuron 3.2 Firing rules - How neurones make decisions 3.3 Pattern recognition - an example 3.4 A more complicated neuron 4. Architecture of neural networks 4.1 Feed-forward (associative) networks 4.2 Feedback (autoassociative) networks 4.3 Network layers 4.4 Perceptrons 5. The Learning Process 5.1 Transfer Function 5.2 An Example to illustrate the above teaching procedure 5.3 The Back-Propagation Algorithm 6. Applications of neural networks 6.1 Neural networks in practice 6.2 Neural networks in medicine 6.2.1 Modelling and Diagnosing the Cardiovascular...
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...Introduction Business applications utilize the specific technologies mentioned earlier to try and make better sense of potentially enormous variability (for example, unknown patterns/relationships in sales data, customer buying habits, and so on). However, within the corporate world, AI is widely used for complex problem-solving and decision-support techniques in real-time business applications. The business applicability of AI techniques is spread across functions ranging from finance management to forecasting and production. In the fiercely competitive and dynamic market scenario, decision-making has become fairly complex and latency is inherent in many processes. In addition, the amount of data to be analyzed has increased substantially. AI technologies help enterprises reduce latency in making business decisions, minimize fraud and enhance revenue opportunities. Definition of AI AI is a broad discipline that promises to simulate numerous innate human skills such as automatic programming, case-based reasoning, neural networks, decision-making, expert systems, natural language processing, pattern recognition and speech recognition etc. AI technologies bring more complex data-analysis features to existing applications. There are many definitions that attempt to explain what Artificial Intelligence (AI) is. I like to think of AI as a science that investigates knowledge and intelligence, possibly the intelligent application of knowledge. Knowledge and Intelligence are as...
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...Chemical Product and Process Modeling Volume 2, Issue 3 2007 Article 12 Nonlinear Modelling Application in Distillation Column Zalizawati Abdullah, Universiti Sains Malaysia Norashid Aziz, Universiti Sains Malaysia Zainal Ahmad, Universiti Sains Malaysia Recommended Citation: Abdullah, Zalizawati; Aziz, Norashid; and Ahmad, Zainal (2007) "Nonlinear Modelling Application in Distillation Column," Chemical Product and Process Modeling: Vol. 2 : Iss. 3, Article 12. Available at: http://www.bepress.com/cppm/vol2/iss3/12 DOI: 10.2202/1934-2659.1082 ©2007 Berkeley Electronic Press. All rights reserved. Nonlinear Modelling Application in Distillation Column Zalizawati Abdullah, Norashid Aziz, and Zainal Ahmad Abstract Distillation columns are widely used in chemical processes and exhibit nonlinear dynamic behavior. In order to gain optimum performance of the distillation column, an effective control strategy is needed. In recent years, model based control strategies such as internal model control (IMC) and model predictive control (MPC) have been revealed as better control systems compared to the conventional method. But one of the major challenges in developing this effective control strategy is to construct a model which is utilized to describe the process under consideration. The purpose of this paper is to provide a review of the models that have been implemented in continuous distillation columns. These models are categorized under three major groups: fundamental...
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...Project – an Automated Make-up color selection system. Supervisor – Dr. H.L.Premarathne Field(s) of concern – Artificial Neural Networks, Fuzzy Logic, Image Processing, Data Classification, make-up Background: Women typically like to be in the centre of attraction of other the people. In order to be elegant looking and to get the attention of others, ladies often use make-up. Make-up is a favorite topic of women, and is a primary concern, not only when attending functions such as weddings, parties, but in day-to-day life when going for work too. The success of make-up relies on how well one can select the colors that matches her skin color, eye color, shape of the face and other relevant features. Make-up is also an art; hence one should have a good artistic eye to select the make-up which suits her. Inappropriate applying of make-up will cause a person to be in the centre of sarcasm and annoyance, instead of being in the centre of attraction. This is why; ladies often take the service of a beautician. A beautician is a professional who’s trained and who has expertise knowledge on beauty therapy and make-up. With experience, a beautician can match the make-up colors to suit a person, according to her appearance and personality. However, one does not need the help of a beautician, if that person can choose the appropriate make-up colors for herself. Introduction: Selection of colors for a make-up is vital for a Beautician as well as for any lady who rely on make-up...
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