scholarly journals Estimation of the Conditional Probability Using a Stochastic Gradient Process

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ali Labriji ◽  
Abdelkrim Bennar ◽  
Mostafa Rachik
Keyword(s):  
Conditional Probability ◽  
Large Volume ◽  
Cost Estimation ◽  
Low Cost ◽  
Estimation Method ◽  
Large Datasets ◽  
Full Potential ◽  
Conditional Probabilities ◽  
Imaging Processing ◽  
Estimation Algorithms

The use of conditional probabilities has gained in popularity in various fields such as medicine, finance, and imaging processing. This has occurred especially with the availability of large datasets that allow us to extract the full potential of the available estimation algorithms. Nevertheless, such a large volume of data is often accompanied by a significant need for computational capacity as well as a consequent compilation time. In this article, we propose a low-cost estimation method: we first demonstrate analytically the convergence of our method to the desired probability and then we perform a simulation to support our point.

scholarly journals A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data

Computation ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 80
Author(s):  
Christos Kalyvas ◽  
Manolis Maragoudakis
Keyword(s):  
Big Data ◽  
Estimation Method ◽  
Current Approach ◽  
Large Datasets ◽  
Support Vector ◽  
Full Potential ◽  
Decision Boundary ◽  
K Nearest Neighbor ◽  
Advantages And Disadvantages ◽  
Very Large Datasets

One of the most common tasks nowadays in big data environments is the need to classify large amounts of data. There are numerous classification models designed to perform best in different environments and datasets, each with its advantages and disadvantages. However, when dealing with big data, their performance is significantly degraded because they are not designed—or even capable—of handling very large datasets. The current approach is based on a novel proposal of exploiting the dynamics of skyline queries to efficiently identify the decision boundary and classify big data. A comparison against the popular k-nearest neighbor (k-NN), support vector machines (SVM) and naïve Bayes classification algorithms shows that the proposed method is faster than the k-NN and the SVM. The novelty of this method is based on the fact that only a small number of computations are needed in order to make a prediction, while its full potential is revealed in very large datasets.

An Absolute Phase Estimation Method for Interferometry Imagery

2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim
Keyword(s):  
Noise Suppression ◽  
Estimation Method ◽  
Phase Image ◽  
Phase Estimation ◽  
Phase Reconstruction ◽  
Estimation Algorithms ◽  
Absolute Phase ◽  
Filtering Rate ◽  
Interferometric Phase ◽  
Image Performance

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

The dependence of the majority voting decision-making probabilities on a multi-expert binary system experts number

2020 ◽  
pp. 7-14
Author(s):  
E. D. Avedyan ◽  
Le Thi Trang Linh
Keyword(s):  
Decision Making ◽  
Binary System ◽  
Conditional Probability ◽  
Majority Voting ◽  
Correct Solution ◽  
Conditional Probabilities ◽  
Analytical Results ◽  
Independent Expert ◽  
Mutually Independent

The article presents the analytical results of the decision-making by the majority voting algorithm (MVA). Particular attention is paid to the case of an even number of experts. The conditional probabilities of the MVA for two hypotheses are given for an even number of experts and their properties are investigated depending on the conditional probability of decision-making by independent experts of equal qualifications and on their number. An approach to calculating the probabilities of the correct solution of the MVA with unequal values of the conditional probabilities of accepting hypotheses of each statistically mutually independent expert is proposed. The findings are illustrated by numerical and graphical calculations.

A low-cost, large-volume general purpose water sampler

2005 ◽  
Vol 33 (1) ◽  
pp. 123-128
Author(s):  
R. P. Grayson ◽  
A. J. Plater
Keyword(s):  
Large Volume ◽  
Low Cost ◽  
General Purpose ◽  
Water Sampler

Keynote

2021 ◽  
Vol 48 (4) ◽  
pp. 3-3
Author(s):  
Ingo Weber
Keyword(s):  
Cost Estimation ◽  
Estimation Method ◽  
Main Topic ◽  
System Throughput ◽  
Distributed Ledger ◽  
Smart Contract ◽  
Distributed Ledger Technology ◽  
Wide Range ◽  
The Cost ◽  
Application Developers

Blockchain is a novel distributed ledger technology. Through its features and smart contract capabilities, a wide range of application areas opened up for blockchain-based innovation [5]. In order to analyse how concrete blockchain systems as well as blockchain applications are used, data must be extracted from these systems. Due to various complexities inherent in blockchain, the question how to interpret such data is non-trivial. Such interpretation should often be shared among parties, e.g., if they collaborate via a blockchain. To this end, we devised an approach codify the interpretation of blockchain data, to extract data from blockchains accordingly, and to output it in suitable formats [1, 2]. This work will be the main topic of the keynote. In addition, application developers and users of blockchain applications may want to estimate the cost of using or operating a blockchain application. In the keynote, I will also discuss our cost estimation method [3, 4]. This method was designed for the Ethereum blockchain platform, where cost also relates to transaction complexity, and therefore also to system throughput.

scholarly journals Let Them Eat Chaya: Cultural Revitalization through Culinary Offerings in Belize

Heritage ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1511-1525
Author(s):  
Lauren Griffith ◽  
Cameron Griffith
Keyword(s):  
Supply Chain ◽  
Low Cost ◽  
Full Potential ◽  
Cultural Revitalization ◽  
Dramatic Shift

The Belizean culinary landscape has experienced a dramatic shift in recent years, with an abundance of “fresh” and “local” dishes (i.e., salads) appearing on restaurant menus. While many tourists appreciate the option of ordering salad, there is a truly local green that might be equally or better suited to the tourist market given what we know about tourists’ interests in both authenticity and healthful eating. This paper explores both host and guest attitudes towards chaya, a leafy green that is high in protein and may have anti-diabetic properties. We argue that tourists enjoy eating chaya but restauranteurs are not taking advantage of its potential as a sustainable, low-cost dish that could also help preserve traditional foodways. Though restauranteurs are apt to cite supply chain issues as one of the reasons they are reluctant to make chaya a menu mainstay, we also believe that when a food occupies an ambiguous place in the local foodscape—as chaya does—local hosts may be unable to leverage it to is full potential.

Improving the Public Acceptance of WTE: Session 8

2007 ◽  
Author(s):  
Peter A. Napoli ◽  
Lindsey Sampson ◽  
Robin Davidov ◽  
Bettina Kamuk
Keyword(s):  
Natural Gas ◽  
Low Cost ◽  
Waste To Energy ◽  
Public Acceptance ◽  
Full Potential ◽  
The Public ◽  
Public Consumption ◽  
Energy Plant ◽  
Consumption Demand

This topic is important because of the growing need for us to produce and supply low cost energy for public consumption. Demand has increased exponentially, and in order to reduce dependence on foreign oil, coal, and natural gas we need to utilize waste to its full potential. Three major waste to energy plant expansions are happening now at Olmstead WTE, Minnesota and at Lee and Hillsborough Counties, in Florida. New “Greenfield” construction is planned at Harford, Carroll, and Fredrick Counties, in Maryland.

Attitude estimation Algorithms using low cost IMU

2015 ◽  
Vol 8 (11) ◽  
pp. 113-126 ◽  
Author(s):  
Dung Duong Quoc ◽  
Jinwei Sun ◽  
Van Nhu Le
Keyword(s):  
Low Cost ◽  
Attitude Estimation ◽  
Estimation Algorithms
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