Principal component analysis

Metabolon Unveils New Integrated Bioinformatics Platform

Retrieved on:

Thursday, February 29, 2024

Acquisition, PCA, Research, Lens, Edith Cowan University, Metabolomics, Bioinformatics, Biomarker, Principal component analysis, Medicine, Biology, Pharmaceutical industry

MORRISVILLE, N.C., Feb. 29, 2024 /PRNewswire/ -- Metabolon, Inc., the global leader in providing metabolomics solutions advancing a wide variety of life science research, diagnostic, therapeutic development, and precision medicine applications, today announced at Biomarkers UK the launch of its latest innovation: an integrated bioinformatics platform, advancing the landscape for metabolomics analysis in life sciences research.

Key Points:

Partial Least Squares–Discriminant Analysis (PLS-DA): Facilitates the interpretation of complex datasets, enabling the identification of distinctive biomarkers that drive group separation.
"Metabolon has developed a solid, scalable solution to the non-trivial problem of metabolomics biochemical interpretation, specifically tailored to their world-leading data acquisition platform.
Metabolon's new bioinformatics platform alleviates much of this manual burden, with client data pre-populated and ready for analysis, accelerating discovery with publication-ready charts, plots, data tables, and insights.
"Metabolon is thrilled to unveil this groundbreaking bioinformatics platform, marking a significant leap forward in metabolomics research," said Dr. Ray Moran, Senior Director of Bioinformatics at Metabolon.

Metabolon Unveils New Integrated Bioinformatics Platform

Retrieved on:

Thursday, February 29, 2024

Acquisition, PCA, Research, Lens, Edith Cowan University, Metabolomics, Bioinformatics, Biomarker, Principal component analysis, Medicine, Biology, Pharmaceutical industry

MORRISVILLE, N.C., Feb. 29, 2024 /PRNewswire/ -- Metabolon, Inc., the global leader in providing metabolomics solutions advancing a wide variety of life science research, diagnostic, therapeutic development, and precision medicine applications, today announced at Biomarkers UK the launch of its latest innovation: an integrated bioinformatics platform, advancing the landscape for metabolomics analysis in life sciences research.

Key Points:

Partial Least Squares–Discriminant Analysis (PLS-DA): Facilitates the interpretation of complex datasets, enabling the identification of distinctive biomarkers that drive group separation.
"Metabolon has developed a solid, scalable solution to the non-trivial problem of metabolomics biochemical interpretation, specifically tailored to their world-leading data acquisition platform.
Metabolon's new bioinformatics platform alleviates much of this manual burden, with client data pre-populated and ready for analysis, accelerating discovery with publication-ready charts, plots, data tables, and insights.
"Metabolon is thrilled to unveil this groundbreaking bioinformatics platform, marking a significant leap forward in metabolomics research," said Dr. Ray Moran, Senior Director of Bioinformatics at Metabolon.

Measuring market-based core inflation expectations

Retrieved on:

Thursday, February 15, 2024

Abstract

Key Points:

Abstract
We build a novel term structure model for pricing synthetic euro area core inflation-linked
swaps, a hypothetical swap contract indexed to core inflation.
The model provides estimates of market-based expectations for core inflation, as
well as core inflation risk premia, at daily frequency, whereas core inflation expectations from
surveys or macroeconomic projections are typically only available monthly or quarterly.
We
find that core inflation-linked swap rates are generally less volatile than headline inflationlinked swap rates and that market participants expected core inflation to be substantially
more persistent than headline inflation following the 2022 energy price spike.
In this paper, we aim to infer market-based core inflation expectations, which are otherwise
not directly observable because no financial asset directly tied to core inflation exists.
We deem this second assumption reasonable because HICP inflation itself is a linear combination
of core as well as energy and food inflation.
The level of 2 percent and relatively low volatility of
long-term inflation expectations suggests that inflation expectations are firmly anchored at the
ECB?s 2 percent inflation target.
This assumption appears reasonably uncontroversial,
as core inflation is a sub-component of headline inflation, which the observable headline ILS
rates are tied to.
Our estimates of core ILS rates reflect both market participants? genuine core
inflation expectations and a core inflation risk premium, but our model explicitly allows for
this decomposition.
The model-implied estimates of core ILS rates appear reasonable along several dimensions:
(i) like realized core inflation is less volatile than headline inflation, the core ILS rates are less
volatile than headline ILS rates, (ii) core ILS rates comove less with oil prices than headline
ILS rates, (iii) the core inflation expectations, as reflected in core ILS rates, typically evolve
similarly as the core inflation projections by Eurosystem staff, and (iv) consistent with market
commentary at the time, core ILS rates suggest that market participants expected core inflation
to be substantially more persistent than headline inflation following the 2022 energy price spike.
To the best of our knowledge, we are the first to price core ILS rates and decompose them into
market-based expectations for and risks around the core inflation outlook.
Our approach to inferring core ILS
rates from headline ILS rates, realized headline and core inflation as well as survey expectations
for headline and core inflation is also related to Ang et al.
Relative
to their study, we separately measure core inflation expectations and risk premia, we provide
core inflation expectations at a higher-frequency, and we provide evidence on the causal effects
ECB Working Paper Series No 2908

6

of monetary policy shocks on core inflation expectations and risk premia.
Specifically, we decompose the synthetic core ILS rates
into average expected core inflation over the lifetime of the swap contract and a core inflation
risk premium that compensates investors for core inflation risk.
In
our model below, this term is constant over time and relatively small, so we will simply refer
to the core inflation risk premium as the difference between the core ILS rate and the average
expected core inflation over the lifetime of the swap contract.
3.2
Core ILS rates

To have a joint model for headline and core ILS rates, we need one further assumption on the
dynamics of realized core inflation.
The assumption that core inflation is driven by the same set of factors as headline inflation
should be relatively uncontroversial: since headline inflation is a weighted average of core and
food and energy inflation, it should reflect any factors driving core inflation.
If there are factors
driving food and energy inflation, which do not show up in core inflation, then those factors
should still show up in headline inflation.
In step two, to be able to infer the factor
loadings of core inflation, we would regress realized core inflation onto the estimated latent
factors to identify the additional parameters in equation (12).
Before the fourth
quarter of 2016, the SPF did not ask respondents for their core inflation expectations, so we
are not able to use survey-based information about core inflation before then.
Before
2016, the fitted core inflation series is somewhat above the realized one, potentially reflecting
that the model has limited information about core inflation over this early period due to the
lack of information about core inflation from surveys.
This could have been the
case if one of the factors moved core inflation and energy and food inflation in exactly offsetting
direction, so the overall impact on headline inflation was exactly zero.
During 2021, for example, there were
ECB Working Paper Series No 2908

25

Figure 7: Decomposition of synthetic core ILS rates
2y core ILS

5y core ILS

5
4

5
ILS

premia

exp

4

ILS

premia

exp

3

3

2

2

1

1

0

0

-1

-1

-2
2017 2018 2019 2020 2021 2022 2023

-2
2017 2018 2019 2020 2021 2022 2023

10y core ILS

5y5y core ILS

5
4

5
ILS

premia

exp

4

ILS

premia

exp

3

3

2

2

1

1

0

0

-1

-1

-2
2017 2018 2019 2020 2021 2022 2023

-2
2017 2018 2019 2020 2021 2022 2023

Note: Synthetic core ILS rates decomposed into genuine core inflation expectations and core inflation risk
premia.
ECB Working Paper Series No 2908
26

Figure 8: Decomposition of ILS rates
2y ILS

5y ILS

5
4

5
ILS

premia

exp

4

3

3

2

2

1

1

0

0

-1

-1

-2
2006

2010

2014

2018

2022

-2
2006

ILS

2010

10y ILS

2018

2022

5
ILS

premia

exp

4

3

3

2

2

1

1

0

0

-1

-1

-2
2006

2014

exp

5y5y ILS

5
4

premia

2010

2014

2018

2022

-2
2006

ILS

2010

premia

2014

2018

exp

2022

Note: ILS rates decomposed into genuine core inflation expectations and core inflation risk premia.
We find that the headline inflation risk premium
indeed does responds more strongly than the core inflation risk premium.
The key
assumption underlying our approach is that traded headline ILS rates span core inflation, which
ECB Working Paper Series No 2908

35

should be reasonably uncontroversial as core inflation is a sub-component of headline inflation.
We fit the model to euro area headline ILS rates, realized headline and core inflation, and
both headline and core inflation expectations reported in the SPF.
Decomposing our core ILS rates into genuine core inflation expectations and core
inflation risk premia shows that shorter maturities mainly reflect core inflation expectations,
while the core inflation risk premium matters relatively more for longer maturities.
Our results suggest that a monetary policy tightening surprise significantly lowers
near-term core inflation expectations, although less so than it lowers headline inflation expectations.

INTRODUCING NWA QUALITY ANALYST® 7

Retrieved on:

Tuesday, January 9, 2024

Statistical process control, Principal, Process control, Principal component analysis, Statistics, Microsoft, Feedback, PLS, Process capability, Analytics, Regression analysis, PCA, Version 7 Unix, SPC, UI, Organization, Video game

PORTLAND, Ore., Jan. 9, 2024 /PRNewswire/ -- Northwest Analytics has launched the next generation of NWA Quality Analyst® with the release of version 7. It continues a long tradition of supporting data-driven decision making with industrial analytics.

Key Points:

PORTLAND, Ore., Jan. 9, 2024 /PRNewswire/ -- Northwest Analytics has launched the next generation of NWA Quality Analyst® with the release of version 7.
Northwest Analytics launches the next generation of NWA Quality Analyst® Version 7 for industrial manufacturers.
The release of NWA Quality Analyst 7 marks a significant step forward with an emphasis on underline technology to ensure peak performance.
To see NWA Quality Analyst 7's functionality in-action and ask questions directly to our experienced team including Application Engineers, register for the "Lunch & Learn Series: Data-Driven Decision Making with NWA Quality Analyst 7".

INTRODUCING NWA QUALITY ANALYST® 7

Retrieved on:

Tuesday, January 9, 2024

PORTLAND, Ore., Dec. 6, 2023 /PRNewswire/ -- Northwest Analytics has launched the next generation of NWA Quality Analyst® with the release of version 7. It continues a long tradition of supporting data-driven decision making with industrial analytics.

Key Points:

Northwest Analytics launches the next generation of NWA Quality Analyst® with the release of Version 7 for industrial manufacturers.
PORTLAND, Ore., Dec. 6, 2023 /PRNewswire/ -- Northwest Analytics has launched the next generation of NWA Quality Analyst® with the release of version 7.
The release of NWA Quality Analyst 7 marks a significant step forward with an emphasis on underline technology to ensure peak performance.
To see NWA Quality Analyst 7's functionality in-action and ask questions directly to our experienced team including Application Engineers, register for the "Lunch & Learn Series: Data-Driven Decision Making with NWA Quality Analyst 7".

WiMi Developed RPSSC Technology With Multiple Advantages in Hyperspectral Image Processing

Retrieved on:

Wednesday, January 3, 2024

First, the RPSSC uses principal component analysis (PCA) and LDA algorithms to downscale the original hyperspectral image.

Key Points:

First, the RPSSC uses principal component analysis (PCA) and LDA algorithms to downscale the original hyperspectral image.
WiMi's RPSSC technology has multiple technical advantages in realizing the comprehensive utilization of spectral and spatial features of hyperspectral images.
RPSSC technology marks an important breakthrough for WiMi in the field of hyperspectral image classification.
WiMi's RPSSC technology represents the cutting edge of hyperspectral image classification.

WiMi Proposed Multi-View Fusion Algorithm Based on Artificial Intelligence Machine Learning

Retrieved on:

Thursday, October 19, 2023

BEIJING, Oct. 19, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that its R&D team applied machine learning algorithms to image fusion and introduced a multi-view fusion algorithm based on artificial intelligence machine learning.

Key Points:

BEIJING, Oct. 19, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that its R&D team applied machine learning algorithms to image fusion and introduced a multi-view fusion algorithm based on artificial intelligence machine learning.
Multi-view fusion algorithm based on artificial intelligence machine learning is algorithm that utilize machine learning technique for joint learning and fusion of multiple views obtained from different viewpoints or information sources.
Multi-view fusion algorithm studied by WiMi usually include steps such as data pre-processing, multi-view fusion, feature learning, model training and prediction.
Multi-view fusion algorithm based on artificial intelligence machine learning have technical advantages such as data richness, information complementarity, model fusion capability, and adaptivity, which make multi-view algorithm has great potential and application value in dealing with complex problems and multi-source data analysis.

$76.5 Billion Worldwide Image Recognition Industry to 2027 - Players Include Attrasoft, Google, Hitachi, Honeywell International and NEC - ResearchAndMarkets.com

Retrieved on:

Wednesday, December 28, 2022

Software, Technology, Artificial Intelligence, Research, Artificial intelligence, Growth, SURF, Algorithm, PCA, Information technology, Principal component analysis, ROI, Machine learning, Principal, R, Medical device, AI

It utilizes machine vision technologies with predefined algorithms and artificial intelligence (AI) to interpret a matrix of numerical values in a digital image.

Key Points:

It utilizes machine vision technologies with predefined algorithms and artificial intelligence (AI) to interpret a matrix of numerical values in a digital image.
The algorithm maps out a pattern or relationship in subsequent images to improve the accuracy of the results.
Some of the commonly used algorithms include Principal Component Analysis (PCA), Scale-invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF).
Furthermore, the increasing utilization of image recognition technologies for digital marketing applications is providing a thrust to the market growth.

Wage developments and their determinants since the start of the pandemic

Retrieved on:

Monday, January 16, 2023

= Wage developments and their determinants since the start of the pandemic =

Key Points:

= Wage developments and their determinants since the start of the pandemic =
Published as part of the ECB Economic Bulletin, Issue 8/2022.
The coronavirus (COVID-19) pandemic has greatly affected labour markets and wage growth indicators in the euro area.
The combination of these factors has made assessing underlying wage pressures and the outlook for wage growth extremely challenging.
Wage growth indicators have been extremely volatile since the start of the pandemic, partly owing to the impact of job retention schemes, complicating the assessment of wage developments.
Different statistical treatments of these support measures have also made it difficult to compare wage developments across euro area countries.
In this unusual economic environment, standard empirical models provide only limited help in analysing wage developments in the euro area.
Normally, wage developments can be assessed against empirical regularities by observing the Phillips curve, which links wage growth to economic or labour market slack, past and/or expected inflation, and productivity.
This article discusses wage developments and the main factors that have influenced them since the start of the pandemic.
First, it reviews developments in a broad range of wage measures for the euro area since the start of the pandemic and discusses their usefulness as signals of wage pressures.
Second, the article looks at how wage developments have differed across sectors, reflecting the heterogeneous impact of the pandemic shock.
A key indicator in the assessment of wage growth in the euro area is the annual growth rate of compensation per employee.
The differences in the growth rates of different wage measures have moderated over time but remain substantial.
For example, in the second quarter of 2022 indicators of year-on-year wage growth ranged from 2.4% (negotiated wages) to 4.5% (compensation per employee).
Total labour input at the start of the pandemic fell substantially, by around 16%, owing mainly to the drop in hours worked per employee.
CPE growth can be decomposed into negotiated wages, social security contributions, hours worked per employee and the residual wage drift.
A principal component analysis of wage growth indicators and negotiated wage growth can also be used to assess underlying wage measures.
[10] Estimating the common drivers across a range of wage indicators also suggests that wage pressures have remained moderate.
Another way to mitigate the impact of pandemic-related distortions in the assessment of wage pressures is to estimate underlying wage growth pressures across different wage indicators.
Overall, underlying wage growth has been relatively moderate since the start of the pandemic, and it now stands close its long-term trend.
Wage growth has varied greatly across the main sectors of the economy since the start of the pandemic.
This is because developments in wage growth as a cost factor were broadly similar to those for the price of output.
Developments in real producer prices have diverged strongly across different sectors of the economy, with implications for expected wage and price pressures.

Insights on the Image Recognition Global Market to 2027 - Increasing Utilization of Image Recognition Technologies for Digital Marketing Applications Drives Growth

Retrieved on:

Friday, December 30, 2022

Image recognition refers to a technological solution used for identifying objects, people, places and actions in images.

Key Points:

Image recognition refers to a technological solution used for identifying objects, people, places and actions in images.
It utilizes machine vision technologies with predefined algorithms and artificial intelligence (AI) to interpret a matrix of numerical values in a digital image.
Furthermore, the increasing utilization of image recognition technologies for digital marketing applications is providing a thrust to the market growth.
What is the structure of the global image recognition market and who are the key players?