737 research outputs found

    System Identification of a Micro Aerial Vehicle

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    The purpose of this thesis was to implement an Model Predictive Control based system identification method on a micro-aerial vehicle (DJI Matrice 100) as outlined in a study performed by ETH Zurich. Through limited test flights, data was obtained that allowed for the generation of first and second order system models. The first order models were robust, but the second order model fell short due to the fact that the data used for the model was not sufficient

    Document Management System

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    The debate of using paper documents over computer documents has been a long topic of interest, there has been a lot of research done on the topic. Also, experiments have been done to evaluate the performance of users working with computers v/s working manually with no definitive conclusions (Chris Anderson, 2010) (Askwal, 1985) (Noyes and Graland, 2008). However, one cannot deny the time it takes to store and go through papers manually. Every year, new policies help the user understand the guidelines and operational procedures that they have to follow while being employed by a company. Keeping track of such documents as well as assigning tasks to certain users for revising such are tasks that are lengthy and cumbersome, and are not automated. The software proposed in this paper would help an organization maintain documents, reducing unnecessary tasks and the disk space on the machine

    AIDS: The Dreadful Breach in the Immune System (World AIDS Day Guest Comment)

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    World AIDS Day Guest Comment by Dr. Aman Sharm

    Glyphosate Resistance of <em>Chloris virgata</em> Weed in Australia and Glyphosate Mobility Are Connected Problems

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    The purpose of this review paper is to address two major aspects of glyphosate application on farmers’ fields. The first aspect is the development of glyphosate resistance in weeds like Chloris virgata, and the second aspect is glyphosate mobility, which is directly controlled by soil sorption processes and indirectly by molecule degradation processes. This is a global problem, as excessive glyphosate residues in groundwater, drinking water, and urine of subsistence farmers from intensive agricultural localities have been reported, which can pose a risk to human health. Approaches like biochar as a possible strategy to control glyphosate leaching and crop competition as a cultural method to control glyphosate-resistant weed like Chloris virgata can be the potential solutions of the glyphosate resistance and glyphosate mobility

    Privacy preserving data mining

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    A fruitful direction for future data mining research will be the development of technique that incorporates privacy concerns. Specifically, we address the following question. Since the primary task in data mining is the development of models about aggregated data, can we develop accurate models without access to precise information in individual data records? We analyze the possibility of privacy in data mining techniques in two phasesrandomization and reconstruction. Data mining services require accurate input data for their results to be meaningful, but privacy concerns may influence users to provide spurious information. To preserve client privacy in the data mining process, techniques based on random perturbation of data records are used. Suppose there are many clients, each having some personal information, and one server, which is interested only in aggregate, statistically significant, properties of this information. The clients can protect privacy of their data by perturbing it with a randomization algorithm and then submitting the randomized version. This approach is called randomization. The randomization algorithm is chosen so that aggregate properties of the data can be recovered with sufficient precision, while individual entries are significantly distorted. For the concept of using value distortion to protect privacy to be useful, we need to be able to reconstruct the original data distribution so that data mining techniques can be effectively utilized to yield the required statistics. Analysis Let xi be the original instance of data at client i. We introduce a random shift yi using randomization technique explained below. The server runs the reconstruction algorithm (also explained below) on the perturbed value zi = xi + yi to get an approximate of the original data distribution suitable for data mining applications. Randomization We have used the following randomizing operator for data perturbation: Given x, let R(x) be x+€ (mod 1001) where € is chosen uniformly at random in {-100…100}. Reconstruction of discrete data set P(X=x) = f X (x) ----Given P(Y=y) = F y (y) ---Given P (Z=z) = f Z (z) ---Given f (X/Z) = P(X=x | Z=z) = P(X=x, Z=z)/P (Z=z) = P(X=x, X+Y=Z)/ f Z (z) = P(X=x, Y=Z - X)/ f Z (z) = P(X=x)*P(Y=Z-X)/ f Z (z) = P(X=x)*P(Y=y)/ f Z (z) Results In this project we have done two aspects of privacy preserving data mining. The first phase involves perturbing the original data set using ‘randomization operator’ techniques and the second phase deals with reconstructing the randomized data set using the proposed algorithm to get an approximate of the original data set. The performance metrics like percentage deviation, accuracy and privacy breaches were calculated. In this project we studied the technical feasibility of realizing privacy preserving data mining. The basic promise was that the sensitive values in a user’s record will be perturbed using a randomizing function and an approximate of the perturbed data set be recovered using reconstruction algorithm
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