407 research outputs found
Ideas for rent: an overview of markets for technology
No full textThis article surveys some of the recent literature on technology markets, and summarizes its main issues and insights. We structure our analysis in three parts: the supply and demand of technology; the factors that condition the formation and growth of technology markets; industry structure and dynamic issues. In addition, we summarize some of the studies that have tried to document the size and growth of these markets. We find that the literature has focused mainly on the supply of technology, but several other aspects of these markets remain under-studied, including the demand for external technology, the role of uncertainty in technology markets, and the dynamic interaction between industry structure and the market for technology. Understanding these will illuminate whether markets for technology will continue to grow or remained confined to pockets of the economy. Copyright 2010 The Author 2010. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.
Metrics for analytics and visualization of big data with applications to activity recognition
No full textActivity recognition systems detect the hidden actions of an agent from sensor measurements made on the agents' actions and the environmental conditions. For such systems, metrics are important for both performance evaluation and visualization purposes. In this thesis, such metrics are developed and illustrated. For human activity recognition datasets, a reporting structure is described to visualize the metrics in a systematic manner. The other contribution of this thesis is to describe a visualization tool for estimating the orientation (attitude) of a rigid body from streaming motion sensor (accelerometer and gyroscope) data. A feedback particle filter (FPF) is implemented algorithmically to solve the estimation problem.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-05-01The student, Rohan Arora, accepted the attached license on 2016-04-25 at 10:47.The student, Rohan Arora, submitted this Thesis for approval on 2016-04-25 at 10:48.This Thesis was approved for publication on 2016-04-27 at 15:05.DSpace SAF Submission Ingestion Package generated from Vireo submission #9459 on 2016-07-07 at 14:17:57Made available in DSpace on 2016-07-07T21:18:02Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-04-27Embargo set by: Seth Robbins for item 93308
Lift date: 2018-07-07T21:18:16Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 93308 on 2018-07-08T09:15:30Z
The Inherent Grave Consequences of Glacial Retreat
No full textGlaciers are the protector of climate change. As glacier melting is a long-term process, it does not gain the same attention in comparison to other crises. The visible evidence of global warming is the glaciers. The main cause of glaciers melting is the rising temperature of the earth by CO2 emission and ocean warming. Deforestation, burning fossil fuels, transportation, and other human activities raise the atmospheric concentration of CO2 and other greenhouse gases (GHGs) which warm the planet and ultimately cause the glacier to melt. 90% of the earth’s warmth is absorbed by the ocean and is responsible for the melting of marine glaciers. The main deglaciation consequences are sea-level rise which has contributed to rising sea level by 2.7cm since 1961Glaciers are always been of substantial research as their long-term behavior is like a barometer to check the weather variability, change in flora and fauna, and economic activity. Deglaciation promises grave consequences for wildlife, plant, and the region’s people and a frightening future. This paper showcase how glaciers are melting and hearts are frozen
Improving the Accuracy of Recommender Systems Through Annealing
No full textCollaborative filtering (CF) is the most popular approach in recommender systems (RS). It makes use of a user item rating matrix and recommends on the basis of preferences and tastes of other users. It faces a number of issues like cold start problem, shilling attack problem and sparse matrix problems. Matrix Factorization (MF) is an efficient approach to get rid of sparse matrix problems. It is a highly reliable and robust technique that helps to predict those ratings to a user for an item that are not yet rated by him. This is done by mapping items and users to a latent space based on a given number of latent features. Minimization in MF is done by either Alternating Least Squares (ALS) method or Stochastic Gradient Descent (SGD) technique.
In this thesis, SGD is used to perform minimization on the matrix factorization function using the concept of singular value decomposition (SVD) to fill in missing entries in the sparse user item rating matrix. Using this base approach, a factor known as learning rate (η) is varied to determine the accuracy and convergence rate of recommender systems. This is done by using simulated annealing, which decrements the value of learning rate in each iteration and provides an optimal solution to minimize error in the system.
In this thesis, five simulated annealing schedules, along with a new proposed annealing schedule have been chosen to discuss the effect of learning rate on the accuracy of a movie recommender system. These annealing schedules are- exponential annealing, inverse scaling logarithmic cooling, linear multiplicative cooling and quadratic multiplicative cooling. Our proposed annealing schedule is named as Square Root Cooling (SRA). The experimental results on Movielens dataset prove that by employing exponential annealing schedule as the learning rate, minimum mean absolute error can be attained for the system at a lower value of learning rate. For higher learning rate values, SRA works the best. Apache Mahout 0.9 is chosen as the platform for the research
First generation Asian immigrants and mental health treatment
No full textAny first generation immigrant has a hard time assimilating to life in a new country, and this holds true for the Asian population and their mental health (Arora et al., 2020). This project focused on what impacts mental health of first generation Asian immigrants.Research presentationFaculty Mentor: Dr. Kathy Andrese
Towards automated classification of fine-art painting style: a comparative study
No full textThis thesis presents a comparative study of different classification methodologies for the task of fine-art genre classification. The problem of painting classification involves classifying new unknown paintings among different art genres. Two-level comparative study is performed for this classification problem. The first level reviews the performance of discriminative vs. generative models while the second level touches the features aspect of the paintings and compares Semantic-level features vs low-level and intermediate-level features present in the painting. Three models are studied and compared, namely - 1) A Discriminative model using a Bag-of-Words (BoW) approach; 2) A Generative model using BoW; 3) Discriminative model using Semantic-level features. Various experiments and techniques like Bag of Words model, Topic models and Classeme features are employed to get insights into potential of these automatic classification techniques for painting styles.M.S.Includes bibliographical referencesby Ravneet Singh Aror
Micro-power Pulsed-Doppler Radar Clutter and Displacement Source Classification Dataset
No full textThis is the official dataset for the ACM BuildSys 2019 publication One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification.
The training code for MSC-RNN can be found at https://github.com/dhruboroy29/MSCRNN
Kindly cite this work as:
@article{roy2019one,
title={One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification},
author={Roy, Dhrubojyoti and Srivastava, Sangeeta and Kusupati, Aditya and Jain, Pranshu and Varma, Manik and Arora, Anish},
journal={arXiv preprint arXiv:1909.03082},
year={2019}
}
</pre
Correction to: Visual acuity correlates with multimodal imaging-based categories of central serous chorioretinopathy (Eye, (2021), 10.1038/s41433-021-01788-4)
No full textIn this article the author name Ramesh Venkatesh was incorrectly written as Ramesh Vankatesh. The original article has been corrected
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