This presentation is given in (2015) . As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality.
This presentation is given in (2015) . As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality.
BCI or DNI is a direct communication pathway between an enhanced or wired brain and an external device. DNIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.
It consists of all details about BCI which are necessary, I sorted from net and implemented in PPT. For abstract U can mail me koushik.veldanda@gmail.com
(It is not my own talent,it is a collaboration of 4 to 5 PPT's , wiki and other sites.
But simply awesome )
Brain-computer interface (BCI) is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb. The interface enables a direct communications pathway between the brain and the object to be controlled. In the case of cursor control
As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't about convenience, for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades.
A Brain-computer interface, sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a brain and an external device. It is the ultimate in development of human-computer interfaces or HCI. BCIs being the recent development in HCI there are many realms to be explored. After experimentation three types of BCIs have been developed namely Invasive BCIs, Partially-invasive BCIs, Non-invasive BCIs.
Computer-brain interface is a mainstay of science fiction, and devices are available today to use our brainwaves as a computer input. But is it practical? How far away is it? Will "Big Brother" read our thoughts and hack our brains?
In this class, we will dive into the future of thought as input for wearable devices with real-world examples and code. Demonstrations will be shown using the Emotiv EPOC headset, a revolutionary high resolution, neuro-signal acquisition and processing wireless neuroheadset that uses a set of sensors to tune into electric signals produced by the brain to detect thoughts, feelings and expressions.
You will see the EEG neuroheadset and computer interface with examples of interfacing with desktop, mobile and wearable apps. We will dive into the roots of the technology, showing code and examples along with big pictures of the technology. You will walk away with an understanding of how this still evolving and largely unknown technology really works, how it can be used, as well as longer-term implications.
What is Brain Computer Interface?, How it Works?, On what it works?
It Is about the controlling computers or any programmable electronic device using brain, by implanting electrodes in brain.
PPT of my technical Seminar titled Brain-computer interface (BCI). This is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb.
!
Brain Computer Interface (BCI) aims at providing an alternate means of communication and control to people with severe cognitive or sensory-motor disabilities. These systems are based on the single trial recognition of different mental states or tasks from the brain activity. This paper discusses the major components involved in developing a Brain Computer Interface system which includes the modality to obtain brain signals and its related processing methods.
BCI or DNI is a direct communication pathway between an enhanced or wired brain and an external device. DNIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.
It consists of all details about BCI which are necessary, I sorted from net and implemented in PPT. For abstract U can mail me koushik.veldanda@gmail.com
(It is not my own talent,it is a collaboration of 4 to 5 PPT's , wiki and other sites.
But simply awesome )
Brain-computer interface (BCI) is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb. The interface enables a direct communications pathway between the brain and the object to be controlled. In the case of cursor control
As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't about convenience, for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades.
A Brain-computer interface, sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a brain and an external device. It is the ultimate in development of human-computer interfaces or HCI. BCIs being the recent development in HCI there are many realms to be explored. After experimentation three types of BCIs have been developed namely Invasive BCIs, Partially-invasive BCIs, Non-invasive BCIs.
Computer-brain interface is a mainstay of science fiction, and devices are available today to use our brainwaves as a computer input. But is it practical? How far away is it? Will "Big Brother" read our thoughts and hack our brains?
In this class, we will dive into the future of thought as input for wearable devices with real-world examples and code. Demonstrations will be shown using the Emotiv EPOC headset, a revolutionary high resolution, neuro-signal acquisition and processing wireless neuroheadset that uses a set of sensors to tune into electric signals produced by the brain to detect thoughts, feelings and expressions.
You will see the EEG neuroheadset and computer interface with examples of interfacing with desktop, mobile and wearable apps. We will dive into the roots of the technology, showing code and examples along with big pictures of the technology. You will walk away with an understanding of how this still evolving and largely unknown technology really works, how it can be used, as well as longer-term implications.
What is Brain Computer Interface?, How it Works?, On what it works?
It Is about the controlling computers or any programmable electronic device using brain, by implanting electrodes in brain.
PPT of my technical Seminar titled Brain-computer interface (BCI). This is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb.
!
Brain Computer Interface (BCI) aims at providing an alternate means of communication and control to people with severe cognitive or sensory-motor disabilities. These systems are based on the single trial recognition of different mental states or tasks from the brain activity. This paper discusses the major components involved in developing a Brain Computer Interface system which includes the modality to obtain brain signals and its related processing methods.
Presentation on Brain Computer Interface. It describes how our brain is used as a signaling mechanism for computer. different types of BCIs and its applications.
This power point presentation is about connecting the brain with an external device through which the parts lost by any injuries can be restored partially.
Brain Computer Interface Next Generation of Human Computer InteractionSaurabh Giratkar
In the area of HCI research the main focus is on defining new ways of human interaction with computer system. With the passes of time a number of inventions have been made in this field. In initial days we used only keyboards to access our computer system (e.g. in Unix Terminal). In Second phase, after invention of mouse and other pointing devices, we started using graphical user interface using pointing devices like mouse which make the use of computer more easy and comfortable. Nowadays we are using pressure-driven mechanism, i.e. touch screen, which is common at ATMs, Mobile phones and PDAs etc. Although it is not as common in daily works but the release of tablet PCs and its popularity shows that the day is not much far when we wouldn’t be having keyboards and mouse at all.
All of these inventions have been made for balancing the requirements of society and user. E.g. Games, Multimedia Applications etc are not possible using only-Keyboard so we need mouse driven system for such applications, similarly we cannot have large keyboard on mobile so we need a touch screen system for mobiles. In addition to these traditional HCI models, there are some more advance HCI technology too for adding more flexibility and hence making the product more useful. E.g. swap card system at office doors for attendance and ATM-swap card for shopping. Speech processing systems are also there where we can access our computer system using our speech. Fig 1 shows most popular traditional HCI system.
A Brain –computer Interface (BCI) is a technology which allows a human to control a computer, peripheral, or other electronic device with thought.
The computer translate electric signals into data which is used to control a computer or a device linked to a computer
Layer between OS and distributed applications,Hides complexity and heterogeneity of distributed system ,Bridges gap between low-level OS communications and programming language abstractions,Provides common programming abstraction and infrastructure for distributed applications.
1.0 Introduction
1.1 Objectives
1.2 Some Simple Definition of A.I.
1.3 Definition by Eliane Rich
1.4 Definition by Buchanin and Shortliffe
1.5 Another Definition by Elaine Rich
1.6 Definition by Barr and Feigenbaum
1.7 Definition by Shalkoff
1.8 Summary
1.9 Further Readings/References
Artificial Neural Network / Hand written character RecognitionDr. Uday Saikia
1. Overview
2.Development of System
3.GCR Model
4.Proposed model
5.Back ground Information
6. Preprocessing
7.Architecture
8.ANN(Artificial Neural Network)
9.How the Human Brain Learns?
10.Synapse
11.The Neuron Model
12.A typical Feed-forward neural network model
13.The neural Network
14.Training of characters using neural networks
15.Regression of trained neural networks
16.Training state of neural networks
17.Graphical user interface….
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
3.
It is the study of brain functions.
A collaboration in which a brain accepts and
controls a mechanical device.
Direct communication pathway between a brain
and an external device.
Thus BCI extracts electro-physical signals from
suitable components of the brain and process
them to generate control signals for computers,
robotic machines or communication devices.
4. “ A Brain-Computer Interface is a communication
system that do not depend on peripheral nerves
and muscles “
[J. R. Wolpaw et al. “Brain-computer interface
technology: A review of the first international
meeting,” IEEE Trans. Rehab. Eng., vol. 8, no.
2, pp. 164–173, 2000]
5.
Brain-Computer Interfaces (BCI)
◦ Interaction between the human neural system and
machines
◦ Goal
Enabling people (especially disabled) to communicate
and control devices by mere thinking.
◦ BCI is a control system
6.
1924: Hans Berger discovers the EEG
Analyses the interrelation of EEG and brain
diseases.
1970: First developments to use brain waves
as input
ARPA has vision of enhanced human
First step in the right direction
7.
1990: First successful experiments with
monkeys
Implanting electrode arrays into monkey
brains
Recording of monkeys„ brain waves
2000: Monkeys control robots by thoughts
8.
More non-invasive than invasive approaches
Brain reading by eg. EEG, MEG or fMRI
2004: First human benefits from research
9.
10. BASIC COMPONENTS:
• Implant device
• Signal recording and
processing
• External device used for
control
• Feedback section to the
subject
11.
12. • Brain is made out of
neurons
• Brain detects and
translates the signal of
brain to tangible action
• Same principle different
clearness
• More accurate signal
detection from invasive
BCI
13.
14. What is logical scheme of BCI?
appropriate feature extraction
Signal Features
Brain
Psychological
Effort
(Intention)
Computer
Classification
Of Intent
appropriate feedback strategy
computer training
user training
Modification of
EEG Brain Signals
Environment
15. What is the motivation for BCI Research ?
Only in USA, more than 200,000
patients live with the motor
consequences of serious injury.
Motivation for Patients: is to give
disable people to communicate, to
operate prostheses, and even to
operate wheelchairs using brain
signals
Nicolelis, 2001
Only the INVASIVE SURGEON TECHNIQUE allows putting
electrode into a very local area of a brain uniting a few
neurons. These neurons could be belong to the cortex
center, for example, for finger control.
16.
17. BCI Types
Invasive BCI:
implant electrodes directly onto a patient’s
brain.
Non-Invasive:
implant medical scanning devices to read
brain signals.
18. What is invasive technology for BCI ?
Philip Kennedy and Roy Bakay (Emory University in
Atlanta) were first to install a brain implant in a
human that produced signals of high enough quality
to simulate movement.
Implant was installed in 1998 and the patient lived
long enough to start working with the implant,
eventually learning to control a computer cursor.
Kennedy, P.R., Bakay R.A.
(1998) Restoration of neural
output from a paralysed patient
by a direct brain connection.
Neuroreport. ;9(8):1707-11
10 array of electrodes, each separated by 400 μm
John P. Donoghue, et al.
Assistive technology and robotic
control using motor cortex
ensemble-based neural interface
systems in humans with
tetraplegia. J Physiol 579.3
(2007) pp 603–611
19. Disability Level and Application:
BCI for common people
Communication
Most Disable
people
Neuroprosthetics
Health people
Environmental
control
Robotics /
Manipulators/
Mobility devices
24.
Any controllable machines
◦
◦
◦
◦
For answering yes/no questions
For word processing
Wheelchair
Virtual Reality
Usually, Computer screen and the output is
the selection of targets or cursor movement
25.
Successful Story, Wearable BCI
BCI2000
◦ A successful transition of the whole BCI system to the
portable device
◦ No machine learning
◦ Limited computational power (limited signal processing)
◦ A general-purpose system for (BCI) research
Source Module (new device new driver)
Signal Processing Module (reusable, No Machine Learning)
User Application Module (UDP/IP support to be running in any
machine)
◦ Platform
Microsoft Windows™ 2000/XP
C++ language
26.
Mobility
◦ Communication technologies
Bluetooth
802.11(wire less –WLAN)
GSM/GPRS
◦ PDA instead of stationary computer
Dry Electrode instead of wet (reducing
montage time)
Making the BCI transparent
◦ No need to change electrodes for a reasonable long
time
27.
28. Theta
waves [4, 7.5] associated with reverie,
daydreaming, meditation, creative ideas
Delta waves [0,4] Hz associated with deep sleep and in
the awake state were thought to indicates physical defects
in the brain.
29. Alpha
wave(8-13hz)-its indicates both a relaxed
and attention mode of the brain.
Beta
wave(13-30 hz)-it is the brain wave usually
associated with activity thinking, active attention.
30. CHARACTERISTICS OF BRAIN WAVES
Gamma
waves-within 35Hz-it reflect the mechanism of
consciousness.
Mu
wave(8-12)hz –associated with Motor activity,
31.
Steps for the function of BCI.
1.user wired to a multi-electrode EEG skin cap,
which is connected to a pc running BCI2000.
2.user of the signal asked to generate a series
of signals.
3.EEG potential record and analyze the signal
4.the software attempt to match these signal to
previous recorded signals.
5.at last identified words are wrapped on
output devices like-screen or speech
synthesizer.
32. Undergone
through
hurdle brain
surgery.
New surgery for
each up gradation
Risky and
complicated eyes
surgery.
Use
wearable
computing devices.
External device is
good option.
Glasses and Lasik
operation is best
options.
33. BCI DRAWBACKS
THE DRAWBACKS OF BCI :
- THE BRAIN IS INCREDIBLY COMPLEX,
- THE SIGNAL IS WEAK & PRONE TO INTERFENCE,
- THE EQUIPMENTS IS LESS THAN PORTABLE,
34.
Berlin Brain-Computer-Interface
◦ Joint Venture of several German research
organisations
◦ Supported by the Ministry of Education and
Research
Graz Brain-Computer-Interface
◦ Wide range of research topics
◦ Impressive combination of BCI and FES (Functional
Electrical Stimulation)
36. • A potential therapeutic tool.
• BCI is an advancing technology promising paradigm shift in
areas like Machine Control, Human Enhancement, Virtual
reality and etc. So, it’s potentially high impact technology.
• Several potential applications of BCI hold promise for
rehabilitation and improving performance, such as treating
emotional disorders (for example, depression or anxiety),
easing chronic pain, and overcoming movement disabilities due
to stroke.
• Will enable us to achieve singularity very soon.
• Intense R&D in future to attain intuitive efficiency.
37. Star wars
Humans dive into a
virtual world by
connecting their
brains directly to a
computer.
Harder concentration
to the fan to blow for
simulating the ball to
float
38.
39.
[1] IEEE Xplorer Digital Library website(Through
SJCE Server)
http://ieeexplore.ieee.org/Xplore
[2] Wikipedia - internet encyclopedia
http://en.wikipedia.org/wiki/Braincomputer_interface
40. • Sixto Ortiz Jr., "Brain-Computer Interfaces: Where Human and
Machine Meet," Computer, vol. 40, no. 1, pp. 17-21, Jan., 2007
• F. Babiloni, A. Cichocki, and S. Gao, eds., special issue, “BrainComputer Interfaces: Towards Practical Implementations and Potential
Applications,” ComputationalIntelligence and Neuroscience, 2007
• P. Sajda, K-R. Mueller, and K.V. Shenoy, eds., special issue, “Brain
Computer Interfaces,” IEEE Signal Processing Magazine,Jan. 2008
• The MIT Press – “Toward Brain-Computer Interfacing”
• Wikipedia, HowStuffWorks and various other website sources…