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Title          
 Complex Classification Using Advanced Machine... 
 
Abstract
 In this report, we studied different complex classification models such as Gradient Descent, Multiclass Classification. We also used different Machine Learning tools such as LibSVM, MEGAm, and FastDT to design a complex classifier based on OVA and AVA approaches. We also designed 2 different Rank classifier using MEGAm library and evaluated its performance on the OHSUMED database. The binary classification accuracy (0-1) error using 20 different queries and 10 retrieved documents for each query was 33% for Ranking Classifier 1. The binary classification accuracy for Ranking Classifier 2 was 37%. However, the average ranking performance, as evaluated using DCG metric, was roughly 8% better for Ranking Classifier 2 as compared with Ranking Classifier 1. This improvement comes from the cost function used to penalize the mis-ranking.
 
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Added By - ravigarg
Subject - Computer Science
Document Type - Term Paper
 
 
   
   

 

Title          
  A Machine Learning approach to localization ... 
 
Abstract
 Many sensor network related applications require precise knowledge of the location of constituent nodes. In these applications,it is desirable for the wireless nodes to be able to autonomously determine their locations before they start sensing and transmitting data. Most existing localization algorithms rely on anchor nodes whose locations are known to determine the positions of the remaining nodes using methods such as triangulation or trilateration. In this work, we consider the scenario where anchor nodes are not equipped with any self-positioning functionality, and do not have the knowledge about their positions. In such cases, anchor nodes respond to a "HELLO" signal transmitted by the localizing node. The response to "HELLO" signal can be used by the localizing node to estimate the time of arrival (ToA) or Received Signal Strength Indicator (RSSI). We use such ToA or RSSI measurements to learn node locations using Support Vector Machines (SVM). We cast the problem into a regression and a multiclass classification setting, and demonstrate the high localization accuracy achieve by this approach as compared with the traditional Least Squares based solution. We also demonstrate that strategically choosing the evaluation order o...
 
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Added By - ravigarg
Subject - Computer Science
Document Type - Term Paper
 
 
   
   

 

Title          
 Tunable Thermal Conductivity 
 
Abstract
 This paper lists methods for tuning and enhancing thermal conductivity. Heat transfer applications have a lot of challenges such as, raise the thermal conductivity, control thermal conductivity to be changeable within the same application, and working in very accurate applications like micro combustors and electronic etc. All these requirements couldn’t be achieved by the traditional methods of heat transfer. Therefore, a lot of techniques which are related mainly to the nanotechnology are working on these issues. In this paper we will subjected to some of the methods of tuning thermal conductivity in order to control the heat transfer process.
 
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Added By - ajayvs
Subject - Mechanical Engineering
Document Type - Term Paper
 
 
   
   

 

Title          
  
 
Abstract
 This paper lists the principles of Laser-Induced Breakdown Spectroscopy (LIBS) and gives a brief review of some research work done on its tilization in the applications of the detection of aerosols and fine particles in gaseous flows. Laser-induced breakdown spectrometry (LIBS), also referred to as laser-induced plasma spectroscopy, is one of the new spectroscopy techniques developed by adopting high power, pulsed and narrow bandwidth lasers. The LIBS system is a stand-off or remote sensing technique which permits non-intrusive qualitative and quantitative  measurements. The principle of the LIBS technique is illustrated in figure (1). A pulsed laser beam is focused at the test point and produces a spark due to the high electric field. The spark generates high-density plasma which excites various atomic elements present in the focal volume.
 
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Added By - ajayvs
Subject - Mechanical Engineering
Document Type - Term Paper
 
 
   
   

 

Title          
 Fiber-Optic based Dynamic Pressure sensor for... 
 
Abstract
 Acquiring accurate, transient measurements in harsh environments has always pushed the limits of available measurement technology. Until recently, the technology to directly measure certain properties in extremely high temperature environments has not existed. Advancements in optical measurement technology have led to the development of measurement techniques for pressure, temperature, acceleration, skin friction, etc. using extrinsic Fabry-Perot interferometry (EFPI). The basic operating principle behind EFPI enables the development of sensors that can operate in the harsh conditions associated with turbine engines, high-speed combustors, and other aerospace propulsion applications where the flow environment is dominated by high frequency pressure and temperature variations caused by combustion instabilities, blade-row interactions, and unsteady aerodynamic phenomena. Using micromachining technology, these sensors are quite small and therefore ideal for applications where restricted space or minimal measurement interference is a consideration. In order to help demonstrate the general functionality of this measurement technology, sensors and signal processing electronics currently under development by Luna Innovations were used to...
 
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Added By - ajayvs
Subject - Mechanical Engineering
Document Type - Term Paper
 
 
   
   

 

Title          
 The Combustion of Aluminum in Solid Rocket Pr... 
 
Abstract
 The trophy piece of technology in any modern rocket system is without question the liquid bi-propellant engine. Despite their sophistication, power, and precision the workhorse responsible for launching men and machines into space is based on solid rocket technology more than 700 years old. The earliest historical use of gunpowder dates back to the 300 B.C where in modern day China bamboo tubes filed with gunpowder were thrown into fires during celebrations, the noise warding away evil spirits. 500 years later in 1232 A.D at the battle of Kai-fung-fu the Chinese military used the first recorded rockets against the invading Mongol Horde. As the Mongols moved through china, they took emerging technologies with them and by 1241 A.D, the rocket had made it to the battlefields of Europe. By 1300 A.D, arsenals around Europe had some rocket technology, based entirely on the use of gunpowder for propulsive motive. A lack of control over rocket trajectories hindered much development by western militaries, who also found the tendency of a misguided missile to start a fire counterproductive. In the Eighteenth century, work had begun on developing a more powerful propellant, and although some progress had been made the independent work of Rob...
 
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Added By - ajayvs
Subject - Aeronautics and Astronautics
Document Type - Term Paper
 
 
   
   

 

Title          
 Gender Classification Using Support Vector Ma... 
 
Abstract
 Automatic face recognition is a classic problem in the area of computer vision research. This problem is still a very active area of research in vision community. The primary reason for this problem to get so much attention is the fact that face recognition finds application in many commercial applications and can work as a biometric in many law enforcement applications. The problem of Automatic face recognition can be formally defined as follows: Given a set of representative training images for each person in the database, determine the identity of a new face images from the stored data. There have been several techniques proposed in literature to extract different type of features related to shape, color, etc. of the face. Some of the techniques simply use the image pixel values as the features and reduce the dimension of these features by applying some constraints such that classification property of training image is preserved. In Project 1 of this course, we examined different kind of feature reduction method and used nearest neighbor approach as the classifier. The fundamental problem with the use of nearest neighbored approach as classifier is that the probability of error is quite high (twice as compared with Bayes classi...
 
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Added By - ravigarg
Subject - Computer Science
Document Type - Term Paper
 
 
   
   

 

Title          
 A Comparative Study of Different Face Recogni... 
 
Abstract
 Automatic face recognition is a classic problem in the area of computer vision research. This problem is still a very active area of research in vision community. The primary reason for this problem to get so much attention is the fact that face recognition finds application in many commercial applications and can work as a biometric in many law enforcement applications [1]. The problem of Automatic face recognition can be formally defined as follows: Given a set of representative training images for each person in the database, determine the identity of a new face images from the stored data. There have been several techniques proposed in literature to extract different type of features related to shape, color, etc. of the face. Some of the techniques simply use the image pixel values as the features and reduce the dimension of these features by applying some constraints such that classifcation property of training image is preserved.In this report, we discuss some of these methods which are widely used in literature and promise to exhibits good recognition accuracy. We will use Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Sparse representation and Random projection for the task of face recognition and ...
 
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Added By - ravigarg
Subject - Computer Science
Document Type - Term Paper
 
 
   
   

 

Title          
 Evaluation of Phase & Magnitude based Feature... 
 
Abstract
 Given a speech signal, there are two most important information that can be extracted from it. One being the linguistic information (about what is being said) and other being the speaker specific information (about who is speaking). This report is about the task of speaker recognition where the goal is to determine the speaker identity, from a group of known speaker, which closely matches with input sample. This problem become even more tough when there is limited amount of test and train data, a mismatch between the surrounding conditions while recording the test and train data, or in noisy environments. In this thesis, we consider the problem of speaker identification in noisy and bandlimited telephonic environments using the Gaussian Mixture Model approach combined with sub-band based feature extraction. We implement a sub-band based Posteriori Union Model described by Reynolds [1]. Then, we extend sub-band based approach to combine the phase based feature ModGDF and Magnitude based feature MFCC using several feature recombination techniques described in this thesis. These sub-band based feature recombination methods gives 46% identification accuracy, in best case, on NTIMIT database with little or no increase in computation.
 
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Added By - ravigarg
Subject - Computer Science
Document Type - Term Paper
 
 
   
   

 

Title          
 Application of Multiresolution Analysis in Re... 
 
Abstract
 Multiresolution analysis deals with multi-scale characterization of signals, whereas Renormalization group involves multi-scale analysis of lattice spin systems. Although, developed independently for entirely different purposes, these two fascinating techniques share intriguing conceptual similarity that compelled many researchers to investigate this connection. This article is an introductory review(meant for beginners in both the areas) of those research works that may inspire readers to study further on this topic.
 
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Added By - soumikpsu
Subject - Physics
Document Type - Term Paper
 
 
   
   

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