scholarly journals Coherence between Decomposed Components of Wrist and Finger PPG Signals by Imputing Missing Features and Resolving Ambiguous Features

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4315
Author(s):  
Pei-Yun Tsai ◽  
Chiu-Hua Huang ◽  
Jia-Wei Guo ◽  
Yu-Chuan Li ◽  
An-Yeu Andy Wu ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Systematic Approach ◽  
Intrinsic Properties ◽  
The Third ◽  
Essential Step ◽  
Hemodynamic Information ◽  
Signal Processing Methods ◽  
Missing Feature ◽  
Feature Resolution ◽  
Background Feature

Background: Feature extraction from photoplethysmography (PPG) signals is an essential step to analyze vascular and hemodynamic information. Different morphologies of PPG waveforms from different measurement sites appear. Various phenomena of missing or ambiguous features exist, which limit subsequent signal processing. Methods: The reasons that cause missing or ambiguous features of finger and wrist PPG pulses are analyzed based on the concept of component waves from pulse decomposition. Then, a systematic approach for missing-feature imputation and ambiguous-feature resolution is proposed. Results: From the experimental results, with the imputation and ambiguity resolution technique, features from 35,036 (98.7%) of 35,502 finger PPG cycles and 36307 (99.1%) of 36,652 wrist PPG cycles can be successfully identified. The extracted features became more stable and the standard deviations of their distributions were reduced. Furthermore, significant correlations up to 0.92 were shown between the finger and wrist PPG waveforms regarding the positions and widths of the third to fifth component waves. Conclusion: The proposed missing-feature imputation and ambiguous-feature resolution solve the problems encountered during PPG feature extraction and expand the feature availability for further processing. More intrinsic properties of finger and wrist PPG are revealed. The coherence between the finger and wrist PPG waveforms enhances the applicability of the wrist PPG.

scholarly journals A Feature Set for Cytometry on Digitized Microscopic Images

2003 ◽  
Vol 25 (1) ◽  
pp. 1-36 ◽  
Author(s):  
Karsten Rodenacker ◽  
Ewert Bengtsson
Keyword(s):  
Image Analysis ◽  
Feature Extraction ◽  
Systematic Approach ◽  
Structural Features ◽  
Biomedical Image Analysis ◽  
Feature Sets ◽  
Biomedical Image ◽  
Rules Of Thumb ◽  
Quantitative Cytology ◽  
The Eu

Feature extraction is a crucial step in most cytometry studies. In this paper a systematic approach to feature extraction is presented. The feature sets that have been developed and used for quantitative cytology at the Laboratory for Biomedical Image Analysis of the GSF as well as at the Center for Image Analysis in Uppsala over the last 25 years are described and illustrated. The feature sets described are divided into morphometric, densitometric, textural and structural features. The latter group is used to describe the eu‐ and hetero‐chromatin in a way complementing the textural methods. The main goal of the paper is to bring attention to the need of a common and well defined description of features used in cyto‐ and histometrical studies. The application of the sets of features is shown in an overview of projects from different fields. Finally some rules of thumb for the design of studies in this field are proposed. Colour figures can be viewed onhttp://www.esacp.org/acp/2003/25‐1/rodenacker.htm.

scholarly journals REALITY, DREAM AND FANTASY IN THE SELECTION «THE NIGHT OF POLASTRI» BY ALBERT AYGUESPARSE

2019 ◽  
pp. 102-116
Author(s):  
Ярема Кравець
Keyword(s):  
Research Methodology ◽  
Systematic Approach ◽  
Syntactic Structure ◽  
Francophone Literature ◽  
Comparative Methods ◽  
Life And Death ◽  
The Third ◽  
Internal Dialogue ◽  
Light And Shadow ◽  
Voice And Silence

Aim. The paper examines lexico-grammatical and syntactic specificity of the third novelistic collection by Albert Ayguesparse (1900–1996) – one of the more prominent Belgian Francophone writers of the 20th c. It aims at outlining the more important characteristics of individual novellas in the selection, where the reader comes to know the polyphony of the writer’s short prose, moving from Lyrical Realism through tragic episodes of life to the enigmatic and the fantastic. Research methodology. The article employs a systematic approach with the use of literary-historical and comparative methods. On the basis of these two methods, the specificity of the author’s writing, syntactic structure of the text, individualized language of the characters, places of the light-and-shadow, voice-and-silence, life-and-death playing have been determined. Results. The study provides a wider analysis of the selection’s first novella, viz. «Monica sans tête» [«Monica Without the Head»], as well as the novellas «Les Bottes» [«The High Boots»], full of horror stories; «Le Point rouge» [«The Red Spot»], presenting an interest by the functioning of the internal dialogue; the psychological triptych «Les chasses d’Eros» [«The Hunts of Eros»], «Je me nomme Jérôme» [«My Name Is Jérôme»], «Monsieur Oscar» [«Mr. Oscar»], the mystic in its conception novella «Les Survivants» [«Those Who Survived»]. Research novelty. The article is the first in Ukrainian Literary Studies research into the famous Belgian writer’s novellas, with whose novels the Ukrainian reader got acquainted owing to the translation of his work «Notre ombre nous précède» [«Our Shadow’s Ahead»], published in 1984/1985 on the pages of the «Vitchyzna» [«Motherland»] magazine. Practical value. The article may become the basis for a deeper reading of the work of one of the leading representatives of contemporary Belgian Francophone literature, lexical-stylistic features of the writer’s novellas.

scholarly journals Phishing Scam Detection on Ethereum: Towards Financial Security for Blockchain Ecosystem

2020 ◽  
Author(s):  
Weili Chen ◽  
Xiongfeng Guo ◽  
Zhiguang Chen ◽  
Zibin Zheng ◽  
Yutong Lu
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Systematic Approach ◽  
Financial Security ◽  
Feature Extraction Method ◽  
Blockchain Technology ◽  
Ensemble Algorithm ◽  
Identification Model

In recent years, blockchain technology has created a new cryptocurrency world and has attracted a lot of attention. It also is rampant with various scams. For example, phishing scams have grabbed a lot of money and has become an important threat to users' financial security in the blockchain ecosystem. To help deal with this issue, this paper proposes a systematic approach to detect phishing accounts based on blockchain transactions and take Ethereum as an example to verify its effectiveness. Specifically, we propose a graph-based cascade feature extraction method based on transaction records and a lightGBM-based Dual-sampling Ensemble algorithm to build the identification model. Extensive experiments show that the proposed algorithm can effectively identify phishing scams.

Discriminant Criteria for Pattern Classification

2011 ◽  
pp. 30-57
Author(s):  
David Zhang ◽  
Fengxi Song ◽  
Yong Xu ◽  
Zhizhen Liang
Keyword(s):  
Feature Extraction ◽  
Pattern Classification ◽  
The Other ◽  
Linear Projection ◽  
Linear Discriminant ◽  
Large Margin ◽  
The Third ◽  
Fisher Discriminant ◽  
Squared Error ◽  
Fisher Discriminant Criterion

As mentioned in Chapter II, there are two kinds of LDA approaches: classification- oriented LDA and feature extraction-oriented LDA. In most chapters of this session of the book, we focus our attention on the feature extraction aspect of LDA for SSS problems. On the other hand,, with this chapter we present our studies on the pattern classification aspect of LDA for SSS problems. In this chapter, we present three novel classification-oriented linear discriminant criteria. The first one is large margin linear projection (LMLP) which makes full use of the characteristic of the SSS problems. The second one is the minimum norm minimum squared-error criterion which is a modification of the minimum squared-error discriminant criterion. The third one is the maximum scatter difference which is a modification of the Fisher discriminant criterion.

COST-EFFECTIVENESS ANALYSIS: CAN WE REDUCE VARIABILITY IN COSTING METHODS?

2003 ◽  
Vol 19 (2) ◽  
pp. 407-420 ◽  
Author(s):  
Taghreed Adam ◽  
David B. Evans ◽  
Marc A. Koopmanschap
Keyword(s):  
Cost Effectiveness ◽  
Systematic Approach ◽  
Methodological Issue ◽  
Cost Effectiveness Analysis ◽  
Economic Evaluations ◽  
Policy Makers ◽  
The Third ◽  
Effectiveness Analysis ◽  
Sources Of Variation ◽  
Made In

Objectives: The need for consistency and standardization of methods for economic appraisals has been recognized for some time and has led to the development of several sets of guidelines for economic evaluations and for costs. Despite this, considerable diversity is still apparent in applied studies. Some of these diversities might be defensible, and some might not. The objectives of this study are to explore sources of variations in the methods used in applied studies and to discuss the nature of these variations and the possibility of reducing some of them.Methods: We first use a systematic approach to identify the major sources of variation in costing methods used in applied economic evaluations. We then compare the methods used with the recommendations made in available guidelines.Results: Four possible sources of variation are identified. The first is where guidelines do not agree in their recommendations; therefore, it is not surprising that applied studies use different methods. The second is where guidelines agree in principle but provide little detail on how to comply with their recommendations; and the third is where a particular methodological issue is not discussed in guidelines. The fourth reason is simply lack of compliance with accepted guidelines.Conclusions: Variability in costing methods used in applied studies raises questions about the validity of their results and makes it difficult to compare the results of different studies. We discuss the implications for the transferability and generalizability of results and suggest ways to minimize the variability in the methods so that the results of costing studies and economic evaluations can be of more value to policy-makers.

scholarly journals PENGENALAN TAS RANSEL PADA CITRA DIGITAL DENGAN EKSTRAKSI FITUR TEKSTUR MENGGUNAKAN METODE GRAY LEVEL CO-OCCURRENCE MATRIX

2018 ◽  
Vol 4 (4) ◽  
pp. 258
Author(s):  
Cahya Rahmad ◽  
Mungki Astiningrum ◽  
Ade Putra Lesmana
Keyword(s):  
Feature Extraction ◽  
Texture Feature ◽  
Gray Level ◽  
Significant Development ◽  
Average Percentage ◽  
The Road ◽  
The Third ◽  
Last Stage ◽  
On The Road ◽  
Occurrence Matrix

The Backpack is one type of bag that experienced significant development. Many people buy it for their needs. However, when assessing a backpack directly or on the road, he could not recognize the backpack. The generally people want to buy backpacks must look at the price, color, shape, features, and the main ingredients of manufacture. Therefore, in image processing, there is a feature extraction theory for the process of recognizing an object. The backpack itself has a different texture. So that the introduction of the object is better done texture feature extraction with the gray level Co-occurrence matrix method. After that, then get the uniqueness of the backpack image to the classification with the image of the backpack in the database. The last stage in this study the authors conducted trials in 3 conditions. The first condition is based on a backpack photo-taking background. The second condition is based on the pixel capacity of the camera to retrieve the backpack image. And the third condition is based on the brightness of the backpack image. Of these three conditions, a percentage of matching values was obtained in the first condition with an average percentage of 90%, the second condition with an average percentage of 80% and last on the third condition with an average percentage of 70%.

scholarly journals Signal Processing Methods for Identification of Induction Motor Bearing Fault

2019 ◽  
Vol 8 (3) ◽  
pp. 143-151
Keyword(s):  
Signal Processing ◽  
Feature Extraction ◽  
Induction Motor ◽  
Dominant Mode ◽  
Processing Methods ◽  
Vibration Signals ◽  
Bearing Fault ◽  
Vibration Signal Analysis ◽  
Signal Processing Methods ◽  
Motor Bearing

To diagnose early faults as soon as possible, the feature extraction of vibration signals is very important in real engineering applications. Recently, the advanced signal processing-based weak feature extraction method has been becoming a hot research topic. The dominant mode of failure in rolling element bearings is spalling of the races or the rolling elements. Localized defects generate a series of impact vibrations every time whenever running roller passes over the surface of a defect. Therefore, vibration analysis is a conventional method for bearing fault detection. However, the measured vibration signals of rotating machinery often present nonlinear and non-stationary characteristics. This paper deals with the diagnosis of induction motor bearing based on vibration signal analysis. It provides a comparative study between traditional signal processing methods, such as Power Spectrum, Short Time Fourier Transform, Wavelet Transform, and Hilbert Transform. Performances of these techniques are assessed on real vibration data and compared for healthy and faulty bearing.

Fractal and Wavelet Methods Used in the Feature Extraction of Machining Processing from 3D Machined KDP Surfaces

2007 ◽  
Vol 364-366 ◽  
pp. 284-289
Author(s):  
Ming Jun Chen ◽  
Qi Long Pang ◽  
Jing He Wang ◽  
K. Cheng
Keyword(s):  
Feature Extraction ◽  
Spatial Frequency ◽  
Single Point ◽  
Diamond Turning ◽  
Machining Process ◽  
Material Structure ◽  
Intrinsic Properties ◽  
Fractal Method ◽  
Wavelet Method ◽  
Wavelet Methods

Fractal and wavelet methods have been used in this study to analyze the KDP surfaces machined by accurate milling and SPDT (Single Point Diamond Turning) method respectively. Through the 2D wavelet method, the 3D origin machined surfaces were separated into the 3D overlaying roughness surfaces and 3D material structure surfaces. The overlaying roughness surfaces were composed of a large number of length scales superimposed roughness surfaces that are generated from the various vibrations in the machining process. The wavelet method can analyze the information of spatial frequency (vibrations in the machining process) and fractal method can reveal the intrinsic properties of roughness topography. Compared with the conventional methods, the integration of wavelet and fractal is more suitable to characterize the machined crystal KDP surface.

Sign in / Sign up

Export Citation Format

Share Document