Machine has intelligence without mind so it can not sense difference between safety situations and dangerous situations it is not self-aware of situations. In future it can have sense and mind of situations as human has to support human in dangerous situations.
This topic is fascinating and highlights the crucial intersection of machine intelligence and control systems.
Large-scale machine mind modeling can significantly enhance our ability to manage complex, adaptive networks, ultimately leading to more efficient and intelligent systems.
Excited to see how these advancements will shape the future of distributed networks!
🚀 Quantum K Nearest Neighbor (QKNN) 🌟
Alessandro Berti has shared his earlier work on Quantum K Nearest Neighbor—an innovative leap towards integrating quantum computing with machine learning. In this work, we dive into:
🔹 Encoding Techniques: We explore how two different encoding methods affect the complexity of the quantum classifier, shedding light on the potential impact these choices have on the performance of QKNN.
🔹 Qiskit Implementation: Step-by-step, we break down how to implement the QKNN classifier in Qiskit, opening doors for those ready to explore the frontier of quantum-enhanced machine learning.
This is just the beginning of how quantum computing can revolutionize machine learning. Interested in learning more about the interplay between quantum mechanics and AI?
🔗 https://lnkd.in/gNm2ePEU
Follow for updates on cutting-edge research and quantum breakthroughs. Let’s unravel the future of quantum intelligence together!
#QuantumComputing#MachineLearning#QKNN#QuantumAI#Qiskit#QuantumInnovation#ArtificialIntelligence#QuantumResearch#QuantumTech#QuantumAlgorithms#DataScience
PostDoc Researcher in Quantum Algorithms @ University of Pisa║Co-Host @ PointerPodcast║Co-Founder & Head of Mentorship @ Superhero Valley║Qiskit Advocate
🎊 My (old) first work is out! Quantum K Nearest Neighbor
📖 This is the journal version of my very first work at the beginning of my PhD (4 years ago!), and it has just been published on #Quantum#Machine#Intelligence!
In this work:
🟣 We study how two different #encoding techniques affect the #complexity of the quantum classifier;
🟣 We describe in detail how to #implement the classifier in Qiskit;
🟣 Eventually, we evaluate the #performance of the QKNN w.r.t. known datasets.
🙏🏻Thanks to Anna Bernasconi, Gianna M. Del Corso, and Riccardo Guidotti
👀Are you interested in quantum classifiers?
👇🏻Then, take a look at this article in the first comment below!
PostDoc Researcher in Quantum Algorithms @ University of Pisa║Co-Host @ PointerPodcast║Co-Founder & Head of Mentorship @ Superhero Valley║Qiskit Advocate
🎊 My (old) first work is out! Quantum K Nearest Neighbor
📖 This is the journal version of my very first work at the beginning of my PhD (4 years ago!), and it has just been published on #Quantum#Machine#Intelligence!
In this work:
🟣 We study how two different #encoding techniques affect the #complexity of the quantum classifier;
🟣 We describe in detail how to #implement the classifier in Qiskit;
🟣 Eventually, we evaluate the #performance of the QKNN w.r.t. known datasets.
🙏🏻Thanks to Anna Bernasconi, Gianna M. Del Corso, and Riccardo Guidotti
👀Are you interested in quantum classifiers?
👇🏻Then, take a look at this article in the first comment below!
Building #Wearescience. A non-scientist with a new Philosophy and Sociology of Science. FOUNDER OF - Conversational Science Communication ( CSC) & Global Scientific Linguistics ( GSL)
Reposting
#computationalelectromagnetics research by Dr.Rayhan Khan at the fag end of my post.
● Here is a brief on what
Computational
Electromagnetic is -
● Also definition of
Eectro Magnetism !
Enjoy :-
👇
" Computational electromagnetics (CEM), computational electrodynamics or electromagnetic modeling is the process of modeling the interaction of electromagnetic fields with physical objects and the environment using computers.
It typically involves using computer programs to compute approximate solutions to Maxwell's equations to calculate antenna performance, electromagnetic compatibility, radar cross section and electromagnetic wave propagation when not in free space. A large subfield is antenna modeling computer programs, which calculate the radiation pattern and electrical properties of radio antennas, and are widely used to design antennas for specific applications. "
Background
Several real-world electromagnetic problems like electromagnetic scattering, electromagnetic radiation, modeling of waveguides etc., are not analytically calculable, for the multitude of irregular geometries found in actual devices. Computational numerical techniques can overcome the inability to derive closed form solutions of Maxwell's equations under various constitutive relations of media, and boundary conditions.
This makes computational electromagnetics (CEM) important to the design, and modeling of antenna, radar, satellite and other communication systems, nanophotonic devices and high speed silicon electronics, medical imaging, cell-phone antenna design, among other applications."
■ Electro Magnetism
https://lnkd.in/gJ5CF2sM
👇
" In physics, electromagnetism is an interaction that occurs between particles with electric charge via electromagnetic fields. The electromagnetic force is one of the four fundamental forces of nature. It is the dominant force in the interactions of atoms and molecules. Electromagnetism can be thought of as a combination of electrostatics and magnetism, which are distinct but closely intertwined phenomena."
👇
#Ershadspesk#Puresciencepurifies
I am thrilled to announce that my latest research has been published in IEEE Access! 🌟 This paper introduces a novel approach using physics-informed neural networks (PINNs) to identify modal field distributions in waveguides.
This research demonstrates the potential of PINNs as a robust alternative to conventional methods, such as Finite Element Analysis, for calculating waveguide modal field distributions. The implications extend to other electromagnetic problems governed by partial differential equations.
Let’s push the boundaries of what’s possible in computational electromagnetics! 💡
I want to extend my heartfelt thanks to my co-authors for their valuable contributions and to AFOSR for their support throughout my PhD.
Read the full paper here: https://lnkd.in/gyAR_Fi6#deeplearning#PINN#electromagnetics#ComputationalElectromagnetics#Waveguides
Over 75 years ago, Claude Shannon revolutionized the world with his groundbreaking paper "A Mathematical Theory of Communication." Shannon's work laid the foundation for information theory, profoundly impacting how we live and work today. His rigorous mathematical framework introduced fundamental units like the bit and entropy, shaping the way we measure and understand information.
Shannon's theory revolutionized communication, providing the framework for efficient communication systems we use daily. Concepts such as encoding, decoding, data compression, and error correction all stem from his pioneering work, impacting fields beyond communication like computer science, artificial intelligence, and genetics.
Today, Shannon's legacy lives on as information theory continues to be a crucial tool in developing new technologies. From 5G networks to quantum computing, Shannon's contribution remains undeniable. Let's honor him as the father of the digital age, recognizing his profound impact on the world we live in today. #ClaudeShannon#InformationTheory#DigitalAge#TechnologyInnovation
The Handbook of Multimodal-Multisensor Interfaces, Volume 2 is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals.
This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning.
Get it here: https://bit.ly/3WHpFQ0
Authors:
Sharon Oviatt, Incaa Designs,
Bjoern Schuller, University of Passau and Imperial College London,
Philip R. Cohen, VoiceBox Technologies,
Daniel Sonntag, German Research Center for Artificial Intelligence,
Gerasimos Potamianos, University of Thessaly,
Antonio Kruger, German Research Center for Artificial Intelligence.
#mulimodal#signal#processing#architectures#machinelearning#traitrecognition#cognitiveload#BehavioralSignals#socialsignals#Classifying#Multimodal#Data#AffectDetection ACM - Association for Computing Machinery
Researchers at Northeastern University Propose NeuFlow: A Highly Efficient Optical Flow Architecture that Addresses both High Accuracy and Computational Cost Concerns
Real-time, high-accuracy optical flow estimation is critical for analyzing dynamic scenes in computer vision. Traditional methodologies, while foundational, have often stumbled upon the computational versus accuracy problem, especially when executed...
https://lnkd.in/eCgJhieN#AI#ML#Automation
We encourage you to read the recently published article, "Towards Scalable Digital Modeling of Networks of Biorealistic Silicon Neurons." 📖 It has results in OPEN SOURCE!
📝 Authored by: Swagat Bhattacharyya; Praveen Raj Ayyappan; Jennifer O. Hasler
Volume: 13, Issue: 4, December 2023
Digital implementations of biorealistic neuron circuits for network computation have a trade-off between computational efficiency and biorealism. This work introduces efficient digital approximations for coupled Hodgkin-Huxley (HH) neurons using transistor-channel neural modeling and implements these models in C with both floating-point and 32-bit fixed-point arithmetic. This approach, which has been made open-source (https://loom.ly/7u6iNY4), allows for large-scale simulation of HH-like neurons, offering a scalable solution for digital modeling and paving the way for analog computing.
🔗 Read more on IEEE Xplore: https://loom.ly/7s34jWs
📖 This article has OPEN SOURCE results! https://loom.ly/7u6iNY4#IEEE#IEEEXplore#JETCAS#PopularArticles#ReadMore#CircuitsandSystems#graphicalabstract#ReadMore#OpenSource
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2moMachine has intelligence without mind so it can not sense difference between safety situations and dangerous situations it is not self-aware of situations. In future it can have sense and mind of situations as human has to support human in dangerous situations.