A direct approach for disturbance detection based on Principal Curves

Author(s):  
Danton Diego Ferreira ◽  
Jose Manoel de Seixas ◽  
Carlos Augusto Duque ◽  
Augusto S. Cerqueira ◽  
Paulo Fernando Ribeiro
Author(s):  
B. Roy Frieden

Despite the skill and determination of electro-optical system designers, the images acquired using their best designs often suffer from blur and noise. The aim of an “image enhancer” such as myself is to improve these poor images, usually by digital means, such that they better resemble the true, “optical object,” input to the system. This problem is notoriously “ill-posed,” i.e. any direct approach at inversion of the image data suffers strongly from the presence of even a small amount of noise in the data. In fact, the fluctuations engendered in neighboring output values tend to be strongly negative-correlated, so that the output spatially oscillates up and down, with large amplitude, about the true object. What can be done about this situation? As we shall see, various concepts taken from statistical communication theory have proven to be of real use in attacking this problem. We offer below a brief summary of these concepts.


2016 ◽  
Vol 77 (S 02) ◽  
Author(s):  
Kazimierz Niemczyk ◽  
Robert Bartoszewicz ◽  
Krzysztof Morawski ◽  
Izabela Popieluch
Keyword(s):  

Author(s):  
Louis Kaplow

Throughout the world, the rule against price fixing is competition law's most important and least controversial prohibition. Yet there is far less consensus than meets the eye on what constitutes price fixing, and prevalent understandings conflict with the teachings of oligopoly theory that supposedly underlie modern competition policy. This book offers a fresh, in-depth exploration of competition law's horizontal agreement requirement, presents a systematic analysis of how best to address the problem of coordinated oligopolistic price elevation, and compares the resulting direct approach to the orthodox prohibition. The book elaborates the relevant benefits and costs of potential solutions, investigates how coordinated price elevation is best detected in light of the error costs associated with different types of proof, and examines appropriate sanctions. Existing literature devotes remarkably little attention to these key subjects and instead concerns itself with limiting penalties to certain sorts of interfirm communications. Challenging conventional wisdom, the book shows how this circumscribed view is less well grounded in the statutes, principles, and precedents of competition law than is a more direct, functional proscription. More important, by comparison to the communications-based prohibition, the book explains how the direct approach targets situations that involve both greater social harm and less risk of chilling desirable behavior—and is also easier to apply.


Author(s):  
R. Rajakulasingam ◽  
J. Kho ◽  
G. Almeer ◽  
C. Azzopardi ◽  
S. L. James ◽  
...  

Abstract Objective We describe a novel and safe CT biopsy technique that we have termed the “Birmingham intervention tent technique (BITT).” This technique is ideal for biopsying osseous lesions where a direct approach is not possible due to difficult positioning. Methods The BITT uses a plastic surgical forceps clamp attached at an angle to the biopsy needle, creating a tent shape. The finger rings of the forceps is stabilized on the table. Results In our institution, we have already used the BITT successfully in over 10 cases. Conclusion The BITT is an inexpensive and reproducible technique.


Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2839
Author(s):  
Artvin-Darien Gonzalez-Abreu ◽  
Miguel Delgado-Prieto ◽  
Roque-Alfredo Osornio-Rios ◽  
Juan-Jose Saucedo-Dorantes ◽  
Rene-de-Jesus Romero-Troncoso

Monitoring electrical power quality has become a priority in the industrial sector background: avoiding unwanted effects that affect the whole performance at industrial facilities is an aim. The lack of commercial equipment capable of detecting them is a proven fact. Studies and research related to these types of grid behaviors are still a subject for which contributions are required. Although research has been conducted for disturbance detection, most methodologies consider only a few standardized disturbance combinations. This paper proposes an innovative deep learning-based diagnosis method to be applied on power quality disturbances, and it is based on three stages. Firstly, a domain fusion approach is considered in a feature extraction stage to characterize the electrical power grid. Secondly, an adaptive pattern characterization is carried out by considering a stacked autoencoder. Finally, a neural network structure is applied to identify disturbances. The proposed approach relies on the training and validation of the diagnosis system with synthetic data: single, double and triple disturbances combinations and different noise levels, also validated with available experimental measurements provided by IEEE 1159.2 Working Group. The proposed method achieves nearly a 100% hit rate allowing a far more practical application due to its capability of pattern characterization.


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