A general principled relational learning framework based on maximizing similarity. Designed for large-scale supervised and semi-supervised learning in noisy multi-dimensional networks with arbitrary relational autocorrelation (homophily and heterophily).
A general principled relational learning framework based on maximizing similarity. Designed for large-scale supervised and semi-supervised learning in noisy multi-dimensional networks with arbitrary relational autocorrelation (homophily and heterophily).
What is NLP? (Neurolinguistic Programming)Jacob Laguerre
This presentation is about Neurolinguistic Programming or NLP for short. NLP was founded by John Grinder and Richard Bandler, back in the 1970s and has since, spread all over the world. Richard has defined NLP as "an attitude, backed by a methodology, that leaves behind a trail of techniques". It is through the use of this novel technology that average people learn how to "run their own brains" and create a subjective reality that enables them to become all that they can be.
Check out my website at https://www.pciinstitute.net for more awesome content
NYAI #23: Using Cognitive Neuroscience to Create AI (w/ Dr. Peter Olausson)Maryam Farooq
Dr. Peter Olausson started his career as a cognitive neuroscientist and spent over a decade at Yale University researching how our memories, motivation and cognitive control together affect decision-making. Before starting COGNITUUM, Peter was focusing on new breakthroughs in the information solutions that shape the human experience, including cognitive computing, data analytics, neuromanagement, and knowledge networks. Peter received his PhD in neuropharmacology at the University of Gothenburg in Sweden and his postdoctoral training at Yale University.
COGNITUUM has developed a general intelligence framework that provides a viable pathway towards human-level machine intelligence. The platform features continuous and real-time learning from any data source.
Jeff Hawkins NAISys 2020: How the Brain Uses Reference Frames, Why AI Needs t...Numenta
Jeff Hawkins presents a talk on "How the Brain Uses Reference Frames to Model the World, Why AI Needs to do the Same." In this talk, he gives an overview of The Thousand Brains Theory and discusses how machine intelligence can benefit from working on the same principles as the neocortex.
This talk was first presented at the NAISys conference on November 10, 2020. You can find a re-recording of the talk here: https://youtu.be/mGSG7I9VKDU
The quest to create artificial general intelligence has largely followed a “brain in a vat” approach, aiming to build a disembodied mind that can carry out the kinds of logical reasoning and inference that humans are capable of, usually demonstrated through language. This approach may some day pay off, but it’s not how nature did it. Intelligence did not evolve to solve abstract problems – it evolved to adaptively control behaviour in the real world. Living organisms are agents that can act, for their own reasons, in pursuit of their own goals – most fundamentally, to persist as a self through time. By charting the evolution of agency, we can see the origins of action and the concomitant emergence of behavioural control systems; the transition from pragmatic perception-action couplings to more and more internalised semantic representations; and, on our lineage, a trajectory of increasing cognitive depth and ever more sophisticated mapping and modelling of the world and the self. The resultant accumulation of causal knowledge grants the ability to simulate more complex scenarios, to predict and plan over longer timeframes, to optimise over more competing goals at once, and ultimately to exercise conscious rational control over behaviour. In this way, intelligent entities – agents – evolved, with greater and greater autonomy, flexibility, and causal power in the world. To realise intelligence in artificial systems, it may similarly be necessary to develop embodied, situated agents, with meaning and understanding grounded in relation to real-world goals, actions, and consequences.
What is NLP? (Neurolinguistic Programming)Jacob Laguerre
This presentation is about Neurolinguistic Programming or NLP for short. NLP was founded by John Grinder and Richard Bandler, back in the 1970s and has since, spread all over the world. Richard has defined NLP as "an attitude, backed by a methodology, that leaves behind a trail of techniques". It is through the use of this novel technology that average people learn how to "run their own brains" and create a subjective reality that enables them to become all that they can be.
Check out my website at https://www.pciinstitute.net for more awesome content
NYAI #23: Using Cognitive Neuroscience to Create AI (w/ Dr. Peter Olausson)Maryam Farooq
Dr. Peter Olausson started his career as a cognitive neuroscientist and spent over a decade at Yale University researching how our memories, motivation and cognitive control together affect decision-making. Before starting COGNITUUM, Peter was focusing on new breakthroughs in the information solutions that shape the human experience, including cognitive computing, data analytics, neuromanagement, and knowledge networks. Peter received his PhD in neuropharmacology at the University of Gothenburg in Sweden and his postdoctoral training at Yale University.
COGNITUUM has developed a general intelligence framework that provides a viable pathway towards human-level machine intelligence. The platform features continuous and real-time learning from any data source.
Jeff Hawkins NAISys 2020: How the Brain Uses Reference Frames, Why AI Needs t...Numenta
Jeff Hawkins presents a talk on "How the Brain Uses Reference Frames to Model the World, Why AI Needs to do the Same." In this talk, he gives an overview of The Thousand Brains Theory and discusses how machine intelligence can benefit from working on the same principles as the neocortex.
This talk was first presented at the NAISys conference on November 10, 2020. You can find a re-recording of the talk here: https://youtu.be/mGSG7I9VKDU
The quest to create artificial general intelligence has largely followed a “brain in a vat” approach, aiming to build a disembodied mind that can carry out the kinds of logical reasoning and inference that humans are capable of, usually demonstrated through language. This approach may some day pay off, but it’s not how nature did it. Intelligence did not evolve to solve abstract problems – it evolved to adaptively control behaviour in the real world. Living organisms are agents that can act, for their own reasons, in pursuit of their own goals – most fundamentally, to persist as a self through time. By charting the evolution of agency, we can see the origins of action and the concomitant emergence of behavioural control systems; the transition from pragmatic perception-action couplings to more and more internalised semantic representations; and, on our lineage, a trajectory of increasing cognitive depth and ever more sophisticated mapping and modelling of the world and the self. The resultant accumulation of causal knowledge grants the ability to simulate more complex scenarios, to predict and plan over longer timeframes, to optimise over more competing goals at once, and ultimately to exercise conscious rational control over behaviour. In this way, intelligent entities – agents – evolved, with greater and greater autonomy, flexibility, and causal power in the world. To realise intelligence in artificial systems, it may similarly be necessary to develop embodied, situated agents, with meaning and understanding grounded in relation to real-world goals, actions, and consequences.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
BREEDING METHODS FOR DISEASE RESISTANCE.pptxRASHMI M G
Plant breeding for disease resistance is a strategy to reduce crop losses caused by disease. Plants have an innate immune system that allows them to recognize pathogens and provide resistance. However, breeding for long-lasting resistance often involves combining multiple resistance genes
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.