[PDF] Top 20 C – Minimizer Algorithm: A New Technique for Data Minimization
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C – Minimizer Algorithm: A New Technique for Data Minimization
... There are some methods such as Karnaugh maps, in which visualization becomes difficult when number of variables become more than five, and Quine McCluskey method, which overcomes the dra[r] ... See full document
5
Constrained simultaneous algebraic reconstruction technique (C SART) —a new and simple algorithm applied to ionospheric tomography
... Artificial Data We used a 2D test scenario for testing the performance of the C-SART algorithm in comparison with the SART algo- ...IRI2007. Data were obtained for the Greenwich meridian for ... See full document
9
Tasks scheduling technique using league championship algorithm for makespan minimization in IaaS cloud
... This new method had been expperimented to solve image enhancement problem in a ...a new evolutionary algorithm known as League Championship Algorithm (LCA) for global optimization, which ... See full document
5
Test Case Generation and Minimization using UML Activity Diagram in Model Driven Environment
... format. Data of generated files are extracted through code and store it into ...and minimization is presented through ...of new technique for optimum number of test cases generation and ... See full document
5
A Traffic Minimization Approach for Big Data in Map Reduce Job by Intermediate Data Partition Technique
... improve data locality is crucial to the performance of ...increasing data locality for better ...with data locality, including the capacity region and theoretical bounds on the delay performance, ... See full document
7
A Survey on Different Image Segmentation Technique for Brain Tumor Detection from MRI
... watershed algorithm, when used directly with raw data ...clustering technique and used two techniques; the first is watershed technique with new merging procedures based on mean ... See full document
6
A Novel Technique For Secure Data Transmission Using Cryptography And Steganography
... the new encryption standard suggested by NIST to renew DES in ...AES algorithm can back any combination of data (128 bits) and key length of 128, 192, and 256 ...The algorithm is referred to ... See full document
5
Enhancement of Service and Data Security in Multi-Cloud Environment
... of data cannot efficiently manage the ...multiple data storage in order to allow the applications to choose therelevant ...or data into the cloud using the various security storage methods and ... See full document
5
Visual Image Sequential Motion Detection via Half Quadratic Minimization Method
... subtraction algorithm is proposed in [18], which can constantly update the parameters and select the appropriate number of components for each ...segmentation algorithm by quantizing each pixel into ... See full document
9
A new reweighted l1 minimization algorithm for image deblurring
... obtain from the original image u []. This is a widely studied subject and many correspond- ing approaches have been developed, and one of them is to minimize some cost functionals []. The simplest method is a Tikhonov ... See full document
11
Firefly Algorithm Based Data Hiding Technique
... reversible data hiding (RDH) to prevent the secret data from theft, illegal copying and unlawful ...secret data which was embedded in that ...secret data is an important task so that it will ... See full document
11
Distributed Data Aggregation Based Energy Efficient Cluster Algorithm for Heterogeneous Wireless Sensor Network
... clustering algorithm: extending network lifetime, eliminating the clustering process within a number of iterations, minimizing control overhead, producing well-distributed cluster heads and compact ... See full document
6
Clustering of Datasets by using Centroid Based Method
... group data into K ...representative data from raw data to be a centroid in each K data ...each data to the closest group by calculating the Euclidean distance between each data ... See full document
7
An Efficient Data Reduction Technique using Change Coding for Wireless Visual Sensor Network
... First, image is Capture by using Images Sensor and Store in Local Database using raspberry pi. The Logitech USB camera is used as a image sensor for capturing the images. For reduction of the image, image processing is ... See full document
6
A New Synthesis Algorithm for Minimization of Coplanar Distributed Antenna Arrays in WSNs
... a new distributed array synthesis algorithm is introduced to construct a close replica of the array pattern using fewer ...this algorithm, the three antenna array parameters (number of nodes, nodes ... See full document
13
New Similarity Performance Measures of Fuzzy Transportation and its Application
... table minimization, three types of peformance measures are done with ...an algorithm which is a new approach in the logistics industrial systems field by employing reduced fuzzy transportation table ... See full document
8
Design and Development of Optimized Asymmetrical 15 Level Inverter Using Genetic Algorithm
... In order to increase the quality of the output power it is necessary to reduce the harmonics present in the output waveform. For reducing the harmonics many methods have been suggested such as Sinusoidal PWM, Space ... See full document
9
Advanced Algorithm for Reduction of Real Power Loss Dr. K. Lenin
... Monkeys don‟t share information and learning from each other, so this easily makes the algorithm to trap in the local optimum solution .Also the improvement in the position is in the range of − , + and it has been ... See full document
7
Diabetes data prediction using data classification algorithm
... Classification Algorithm. The diabetes dataset is a taken as the training data and the details of the patient are taken as testing ...training data are classified by using the RF classifier and ... See full document
5
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
... In this paper, we present some greedy learning algorithms for constructing sparse nonlinear re- gression and classification models with Mercer kernels. In particular, our focus is on selecting an optimal subset from a ... See full document
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