BQ Leonardo, CR Steffens, SC Silva Fil., JL Mór, V Hüttner, EA Leivas, VS Rosa and SSC Botelho
Center of Computer Science, Federal University of Rio Grande, Brazil
Blueacre is specialised in the development of laser micro machining processes for the manufacturing of innovative medical devices in a variety of materials (Plastics, Ceramics, Glass, Metals)
Manufactures small to medium volumes on dedicated laser production equipment
Design and construction of customer specific laser micro machining equipment, including necessary product handling and automation
Key is the dedicated software used to control laser, optics and product handling
A pipelined approach to deal with image distortion in computer vision - BRACI...Cristiano Rafael Steffens
Image classification is a well-established problem in computer vision. Most state-of-the-art models rely on Convolutional Neural Networks to achieve near-human performance in that task. However, CNNs have shown to be susceptible to image manipulation, which undermines the trustability of perception systems. This property is critical, especially in unmanned systems, autonomous vehicles, and scenarios where light cannot be controlled. We investigate the robustness of several Deep-Learning based image recognition models and how the accuracy is affected by several distinct image distortions. The distortions include ill-exposure, low-range image sensors, and common noise types. Furthermore, we also propose and evaluate an image pipeline designed to minimize image distortion before the image classification is performed. Results show that most CNN models are marginally affected by mild miss-exposure...
Signal with amplitude outside the range accepted by the sensor
Enter damaged image. get restored image
Post-processing of damaged images at the moment of acquisition
sRGB Color Space
Restoration with aesthetic purposes
What we expect: Color correction,Texture Edges / Lines / Image gradient; Structures;
Modeling based on convolutional neural networks
Can Exposure, Noise and Compression affect Image Recognition? An Assessment o...Cristiano Rafael Steffens
Convolutional Neural Networks stand the current state-of-the-art in image recognition, as well as many computer vision tasks.
Nevertheless, these architectures have been shown to be vulnerable to image manipulations, which may undermine the reliability and safety of CNN-based models in autonomous and robotic applications. We present a rigorous evaluation of the robustness of several high-level image recognition models and investigate their performance under distinct image distortions. We propose a testing framework which emulates ill exposure conditions, low-range image sensors, lossy compression, as well as commonly observed noise types. One one side results measured in terms of accuracy, precision, and F1-Score, indicate that most CNN models are marginally affected by mild miss-exposure, heavy compression, and Poisson noise. Severe miss-exposure, impulse noise, or signal-dependent noise, on the other side, show a substantial drop in accuracy and precision. A careful evaluation of some typical image distortions, commonly observed in computer vision and machine vision pipelines, provides insights and directions for further developments in the field. Please refer to our github repo for code and data.
Blueacre is specialised in the development of laser micro machining processes for the manufacturing of innovative medical devices in a variety of materials (Plastics, Ceramics, Glass, Metals)
Manufactures small to medium volumes on dedicated laser production equipment
Design and construction of customer specific laser micro machining equipment, including necessary product handling and automation
Key is the dedicated software used to control laser, optics and product handling
A pipelined approach to deal with image distortion in computer vision - BRACI...Cristiano Rafael Steffens
Image classification is a well-established problem in computer vision. Most state-of-the-art models rely on Convolutional Neural Networks to achieve near-human performance in that task. However, CNNs have shown to be susceptible to image manipulation, which undermines the trustability of perception systems. This property is critical, especially in unmanned systems, autonomous vehicles, and scenarios where light cannot be controlled. We investigate the robustness of several Deep-Learning based image recognition models and how the accuracy is affected by several distinct image distortions. The distortions include ill-exposure, low-range image sensors, and common noise types. Furthermore, we also propose and evaluate an image pipeline designed to minimize image distortion before the image classification is performed. Results show that most CNN models are marginally affected by mild miss-exposure...
Signal with amplitude outside the range accepted by the sensor
Enter damaged image. get restored image
Post-processing of damaged images at the moment of acquisition
sRGB Color Space
Restoration with aesthetic purposes
What we expect: Color correction,Texture Edges / Lines / Image gradient; Structures;
Modeling based on convolutional neural networks
Can Exposure, Noise and Compression affect Image Recognition? An Assessment o...Cristiano Rafael Steffens
Convolutional Neural Networks stand the current state-of-the-art in image recognition, as well as many computer vision tasks.
Nevertheless, these architectures have been shown to be vulnerable to image manipulations, which may undermine the reliability and safety of CNN-based models in autonomous and robotic applications. We present a rigorous evaluation of the robustness of several high-level image recognition models and investigate their performance under distinct image distortions. We propose a testing framework which emulates ill exposure conditions, low-range image sensors, lossy compression, as well as commonly observed noise types. One one side results measured in terms of accuracy, precision, and F1-Score, indicate that most CNN models are marginally affected by mild miss-exposure, heavy compression, and Poisson noise. Severe miss-exposure, impulse noise, or signal-dependent noise, on the other side, show a substantial drop in accuracy and precision. A careful evaluation of some typical image distortions, commonly observed in computer vision and machine vision pipelines, provides insights and directions for further developments in the field. Please refer to our github repo for code and data.
Welding Groove Mapping: Image Acquisition and Processing on Shiny Surfaces - ...Cristiano Rafael Steffens
We propose a Vision-Based Measurement (VBM) system and evaluate how different algorithms impact the results. The proposed system joins hardware and software to image the welding plates using a single CMOS camera, run computer vision algorithms and control the welding equipment. A complete prototype, using a commercial linear welding robot is presented.
Authors: Cristiano R. Steffens, Bruno Q. Leonardo, Sidnei Carlos S. Filho, Valquiria Hüttner, Vagner S. Rosa, Silvia Silva C. Botelho
11°International Conference on Computer Vision Theory and Applications - VISAPP 2016
Uma rápida introdução ao OpenCV apresenta somente o essencial. Esta apresentação vai direto ao ponto, trazendo exemplos para sair programando. Todos os algoritmos foram testados utilizando a versão 2.4.10 da biblioteca. Comentários no código em Pt-Br.
Um sistema de detecção de chamas utilizando apenas dados espaciais para detecção de fogo utilizando câmeras hand-held. Revisão dos trabalhos de Phillips (2002), Chen (2004), Celik (2007/2008/2009), Borges (2010) e Chenebert (2011). Utilização de Random Forests Breiman (2001) para extração e classificação das regiões.
Welding Groove Mapping: Image Acquisition and Processing on Shiny Surfaces - ...Cristiano Rafael Steffens
We propose a Vision-Based Measurement (VBM) system and evaluate how different algorithms impact the results. The proposed system joins hardware and software to image the welding plates using a single CMOS camera, run computer vision algorithms and control the welding equipment. A complete prototype, using a commercial linear welding robot is presented.
Authors: Cristiano R. Steffens, Bruno Q. Leonardo, Sidnei Carlos S. Filho, Valquiria Hüttner, Vagner S. Rosa, Silvia Silva C. Botelho
11°International Conference on Computer Vision Theory and Applications - VISAPP 2016
Uma rápida introdução ao OpenCV apresenta somente o essencial. Esta apresentação vai direto ao ponto, trazendo exemplos para sair programando. Todos os algoritmos foram testados utilizando a versão 2.4.10 da biblioteca. Comentários no código em Pt-Br.
Um sistema de detecção de chamas utilizando apenas dados espaciais para detecção de fogo utilizando câmeras hand-held. Revisão dos trabalhos de Phillips (2002), Chen (2004), Celik (2007/2008/2009), Borges (2010) e Chenebert (2011). Utilização de Random Forests Breiman (2001) para extração e classificação das regiões.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Vision-Based System for Welding Groove Measurements for Robotic Welding Applications - ICRA 2016
1. Vision-Based System for
Welding Groove Measurements
for Robotic Welding Applications
BQ Leonardo, CR Steffens, SC Silva Fil., JL Mór, V Hüttner, EA Leivas, VS
Rosa and SSC Botelho
cristianosteffens@furg.br
Center of Computer Science, Federal University of Rio Grande, Brazil
3. Welding is easy! Isn’t it?
• Manual process affects the quality of the weld
• Rework
• Material waste
• Weak and breakable final product
• Reproducibility and regularity
• The human side
• Welding is unhealthy – ergonomy, heat and fumes
• Laborious and repetitive task
9. Conclusion
• Modular Vision-Based Measurement for linear welding robots
• Machine Vision can be used on reflective metallic surfaces
• Avoided complicated hardware setup
• State of the art algorithms offer better cost-benefit ratio
• Developed a complete solution, featuring illumination, image
acquisition and processing, robot operation and welding equipment
setup