Thursday, December 9, 2021

Cyber-Physical Systems (CPS) - Introduction

 


Definitions


NSF (2008) “Cyber-physical systems are physical, biological, and engineered 

systems whose operations are integrated, monitored, and/or controlled

by a computational core. Components are networked at every scale. 

Computing is ‘deeply embedded’ into every physical component, 

possibly even into materials. The computational core is an embedded 

system, usually demands real-time response, and is most often 

distributed. The behavior of a cyber-physical system is a fully-integrated 

hybridization of computational (logical) and physical action.”


NIST (website) “Cyber-Physical Systems (CPS) comprise interacting digital, analog, 

physical, and human components engineered for function through 

integrated physics and logic.”


CPS PWG NIST SP 

1500-201 (2017)

“Cyber-physical systems integrate computation, communication, 

sensing, and actuation with physical systems to fulfill time-sensitive

functions with varying degrees of interaction with the environment 

including human interaction.”


IEEE Standard 2413 

(2019)

“A cyber-physical system is a system in which the physical world, 

such as production sites, and the digitalized cyber world are 

harmoniously combined.”


An academic work 

group website on 

CPSs

“Cyber-Physical Systems (CPS) are integrations of computation, 

networking, and physical processes. Embedded computers and 

networks monitor and control the physical processes, with feedback 

loops where physical processes affect computations and vice versa.”


IEEE Technical 

Committee on CPS 

(website)

“CPS addresses the close interaction and deep integration between 

the cyber components such as sensing systems and the physical 

components such as varying environment and energy systems.”


ACM14 “Cyber-physical systems are systems with a coupling of the cyber 

aspects of computing and communications with the physical 

aspects of dynamics and engineering that must abide by the laws of 

physics.”

Cyber-Physical 

Systems Virtual 

Organization 

(website)

CPSs “are engineering systems that are built from, and depend 

upon, the seamless integration of computational algorithms and 

physical components.”


NASA (website)16 “Cyber-Physical (CPS) denotes the emerging class of physical 

systems that exhibit complex patterns of behavior due to highly 

capable embedded software components. Also known as hybrid 

systems (a hybrid of hardware and software), or mechatronic 

systems (mechanical + electronic), these include devices with 

content, or knowledge, that gives them unprecedented capabilities 

in interoperability and interaction, resilience, adaptivity, and 

emergent behavior.”


U.S. Department 

of Transportation 

(2014)

(From a presentation): A CPS is connected system with a path to 

vehicle automation using an infrastructure and new data for asset 

monitoring, predictive modeling, and control. Impacts safety, 

mobility, and the environment.


U.S. Department 

of Homeland 

Security 

(website)

“Smart networked systems with embedded sensors, processors 

and actuators that sense and interact with the physical world and 

support real-time, guaranteed performance in safety-critical

applications.”


Cyber-Physical 

Systems Program 

Solicitation NSF 

(2021)

“Cyber-physical systems (CPS) are engineered systems that are built 

from, and depend upon, the seamless integration of computation 

and physical components.”


 Note that IEEE Standard 2413 

states, “An IoT system is a cyberphysical 

system, which interacts with the physical world through sensors and actuators.” Does this imply equivalency?


Thursday, November 25, 2021

Quantum Computing - Quantum Computers - Evolution

 


SAP and Quantum Technologies

November 19, 2021 by Corinna Machmeier


According to a study by McKinsey, quantum computing could have a global market value of US$1 trillion by 2035.


Already, annual investments across the world are estimated to be US$22.5 billion, and analysts at IDC predict that 25% of the Fortune Global 500 will gain competitive advantage from quantum computing by 2023.


What SAP Is Doing

SAP has been conducting research into quantum technologies for many years and has built up considerable expertise in the process.


19 November 2021
First quantum computer to pack 100 qubits enters crowded race
IBM’s newest quantum-computing chip, revealed on 15 November, established a milestone of sorts: it packs in 127 quantum bits (qubits), making it the first such device to reach 3 digits. But the achievement is only one step in an aggressive agenda boosted by billions of dollars in investments across the industry.
https://www.nature.com/articles/d41586-021-03476-5


This new startup has built a record-breaking 256-qubit quantum computer
QuEra Computing, launched by physicists at Harvard and MIT, is trying a different quantum approach to tackle impossibly hard computational tasks.

By Siobhan Roberts
November 17, 2021

In 2019, Google announced that its 53-qubit machine had achieved quantum supremacy—performing a task not manageable by a conventional computer—but IBM challenged the claim. The same year, IBM launched its 53-bit quantum computer. In 2020, IonQ unveiled a 32-qubit system that the company said was the “world’s most powerful quantum computer.” And just this week IBM launched its new 127-qubit quantum processor, which the press release described as a “minor miracle of design.” “The big news, from my perspective, is it works,” says Jay Gambetta, IBM’s vice-president of quantum computing.

Now QuEra claims to have made a device with far more qubits than any of those rivals.

2019
https://www.technologyreview.com/2019/01/29/66141/what-is-quantum-computing/











Wednesday, October 20, 2021

Technical Director - Educational Games Development - 20 October 2021

 Technical Director, GT School (Remote) - $320,000/year USD

Crossover for Work  Mumbai, Maharashtra, India Remote 13 hours ago  6 applicants

Full-time · Executive

1,001-5,000 employees · Information Technology & Services

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Actively recruiting


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Crossover for Work Mumbai, Maharashtra, India Remote


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Crossover is the world's #1 source of remote full-time jobs. Our clients offer top-tier pay for top-tier talent. We're recruiting this role for our client, GT School. Have you got what it takes?


Are you a manager of game developers looking for the next big challenge? Do you have a strong programming and cloud background, enough to be considered an expert? There's no greater challenge right now than in the education sector, and we want you on our team!


We are GT School. Gifted and talented ("GT") kids are in dire need of support, and we think the next generation of educational software can fix the problem. We're building the metaverse of education, and we need someone to construct an advanced software development assembly line that is unlike any other.


Our "software factory" model is unique. Each product is carefully architected, using the latest cloud technologies, before the software engineers get involved. The software engineers get repeatable, well-structured tasks that get tested for quality and suitability. At this level, your job is to design and improve the whole system that defines, measures, and ensures the completion of all the software developers' tasks.


If you are deeply technical and want to build something impactful and visionary that will last, we want to hear from you!


What You Will Be Doing


As a leader at our fully cloud-based engineering organization, you will be:

Leading with your technical expertise: You will guide the team with the software development experience you’ve gained over the years, pointing them in the right direction on the most complex challenges and newest technologies.

Spending one day per week digging deep into the product: By getting your hands dirty with the architecture and coding challenges, you will draw technical insights on how to move them to web-scale.

What You Won’t Be Doing

Project managing the work of low-level managers. We lead by doing, not by being hands-off.

Overseeing steady-state operations. Our culture is continuous improvement. You will never stop improving quality and productivity with deep knowledge and hard evidence.

Basic Requirements


Technical Director key responsibilities

5+ years of experience with coding or architectural design. You’ll have to pass a coding test to get this job.

5+ years of leadership experience running enterprise software development. You need to have developed software at scale.

Ability to work 100% remotely from your own home office.

About GT School


GT School is a stealth educational startup in Austin, Texas, the center of educational innovation in the US. We are building an online community focusing on the most underserved customer base in US education - GT kids (gifted and talented). We are a remote first company who hires globally via Crossover.


There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you!


Working with Crossover


This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover. The compensation level for this role is $160 USD/hour, which equates to $320,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic.


What to expect next:

You will receive an email with a link to start your self-paced, online job application.

Our hiring platform will guide you through a series of online “screening” assessments to check for basic job fit, job-related skills, and finally a few real-world job-specific assignments.

Important! If you do not receive an email from us:

First, emails may take up to 15 minutes to send, refresh and check again.

Second, check your spam and junk folders for an email from Crossover.com, mark as “Not Spam” since you will receive other emails as well.

Third, we will send to whatever email account you indicated on the Apply form - by default, that is the email address you use as your LinkedIn username and it might be different than the one you have already checked.

If all else fails, just reset your password by visiting https://www.crossover.com/auth/reset-password if you already applied using LinkedIn EasyApply.

Crossover Job Code: LJ-4643-IN-Mumbai-TechnicalDirec


https://www.linkedin.com/jobs/collections/recommended/?currentJobId=2766439523


Saturday, September 18, 2021

IoT Protocols

 

https://cloud.google.com/iot/docs/concepts/protocols

https://docs.oracle.com/en/cloud/paas/iot-cloud/develop/iot-connectivity-protocols.html

https://azure.microsoft.com/en-in/overview/internet-of-things-iot/iot-technology-protocols/

https://www.avsystem.com/blog/iot-protocols-and-standards/

2020

https://www.nabto.com/guide-iot-protocols-standards/


A Comprehensive Review on IoT Protocols’ Features in Smart Grid Communication

by Lilia TightizOrcID andHyosik Yang *OrcID

Department of Computer Engineering, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea

*

Author to whom correspondence should be addressed.

Energies 2020, 13(11), 2762; https://doi.org/10.3390/en13112762

https://www.mdpi.com/1996-1073/13/11/2762



Internet of Things: Architectures, Protocols, and Applications

Pallavi Sethi1 and Smruti R. Sarangi 1

Journal of Electrical and Computer Engineering / 2017 

Volume 2017 |Article ID 9324035 | https://doi.org/10.1155/2017/9324035

https://www.hindawi.com/journals/jece/2017/9324035/



A Survey of Protocols and Standards for Internet of Things

Tara Salman, Raj Jain

Department of Computer Science and Engineering

Washington University in St. Louis

https://arxiv.org/ftp/arxiv/papers/1903/1903.11549.pdf



Wednesday, August 11, 2021

Agile Software Development Methodology

 


https://www.agilealliance.org/agile101/


https://www.infoworld.com/article/3237508/what-is-agile-methodology-modern-software-development-explained.html

https://agilemanifesto.org/


Kent Beck

Mike Beedle

Arie van Bennekum

Alistair Cockburn

Ward Cunningham

Martin Fowler

James Grenning

Jim Highsmith

Andrew Hunt

Ron Jeffries

Jon Kern

Brian Marick

Robert C. Martin

Steve Mellor

Ken Schwaber

Jeff Sutherland

Dave Thomas


Embracing Agile: How to master the process that’s transforming management 

by Darrell K. Rigby, Jeff Sutherland, and Hirotaka Takeuchi

From the HBR Magazine (May 2016)

https://hbr.org/2016/05/embracing-agile

___________________


https://www.youtube.com/watch?v=WjwEh15M5Rw

___________________

Monday, July 26, 2021

Data Science Research - Journals, Papers and Areas

 Data Science - Areas of Research

Top ten areas - MIT Press - 2020

https://hdsr.mitpress.mit.edu/pub/d9j96ne4/release/2

2020

https://www.analyticsinsight.net/top-10-research-challenge-areas-pursue-data-science/


Data Science - Journals

Journal of Management Analytics

Publish open access in this journal

Focuses on the theory of data analytics and its application in traditional business disciplines, such as accounting, finance, and supply chain management.



2021

Data Science Methodologies: Current Challenges and Future Approaches

I˜nigo Martineza,, Elisabeth Viles, Igor G Olaizolaa

Preprint submitted to Big Data Research - Elsevier

June 15, 2021

https://arxiv.org/pdf/2106.07287


Research questions:

• RQ1: What methodologies can be found on the literature to manage data science projects?

• RQ2: Are these available methodologies prepared to meet the demands of current challenges?


7. Development Workflows for Data Scientists 

Development Workflows for Data Scientists by Github and O’Reilly Media

8. Big Data Ideation, Assessment and Implementation
Big data ideation, assessment and implementation by Martin Vanauer

10. Agile Delivery Framework
Larson and Chang proposed a framework based on the synthesis of agile principles with Business Intelligence (BI), fast analytics and data science. There are two layers of strategic tasks: (A) the top layer includes BI delivery and (B) the bottom layer includes fast analytics and data science.


In this article the conceptual framework is presented for designing integral methodologies for the management of data science projects. The framework proposes  three foundation stones: project, team and data & information management.


The disciplinary research landscape of data science reflected in data science journals

Lingzi Hong , William Moen , Xinchen Yu , Jiangping Chen 

Information Discovery and Delivery (2020)

The research questions for the study are:

RQ1. What is the population of journals that focus on topics of data science?

RQ2. What disciplinary landscape of data science is reveal


Important - Table - Top keywords of disciplines



Saturday, July 24, 2021

Data Science - Techniques

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2:19:54 What is Regression? 2:21:23 Linear vs Logistic Regression 2:33:51 Linear Regression 2:25:27 Where is Linear Regression used? 2:27:11 Understanding Linear Regression 2:37:00 What is R-Square?
2:46:35 Logistic Regression 2:51:22 Logistic Regression Curve 2:53:02 Logistic Regression Equation 2:56:21 Logistic Regression Use-Cases 2:58:23 Demo 3:00:57 Implement Logistic Regression 3:02:33 Import Libraries 3:05:28 Analyzing Data 3:11:52 Data Wrangling 3:23:54 Train & Test Data 3:20:44 Implement Logistic Regression 3:31:04 SUV Data Analysis
3:38:44 Decision Trees 3:39:50 What is Classification? 3:42:27 Types of Classification 3:42:27 Decision Tree 3:43:51 Random Forest 3:45:06 Naive Bayes 3:47:12 KNN 3:49:02 What is Decision Tree? 3:55:15 Decision Tree Terminologies 3:56:51 CART Algorithm 3:58:50 Entropy 4:00:15 What is Entropy? 4:23:52 Random Forest 4:27:29 Types of Classifier 4:31:17 Why Random Forest? 4:39:14 What is Random Forest? 4:51:26 How Random Forest Works? 4:51:36 Random Forest Algorithm 5:04:23 K Nearest Neighbour 5:05:33 What is KNN Algorithm? 5:08:50 KNN Algorithm Working 5:14:55 kNN Example 5:24:30 What is Naive Bayes? 5:25:13 Bayes Theorem 5:27:48 Bayes Theorem Proof 5:29:43 Naive Bayes Working 5:39:06 Types of Naive Bayes
5:53:37 Support Vector Machine 5:57:40 What is SVM? 5:59:46 How does SVM work? 6:03:00 Introduction to Non-Linear SVM 6:04:48 SVM Example
6:06:12 Unsupervised Learning Algorithms - KMeans 6:06:18 What is Unsupervised Learning? 6:06:45 Unsupervised Learning: Process Flow 6:07:17 What is Clustering? 6:09:15 Types of Clustering 6:10:15 K-Means Clustering 6:10:40 K-Means Algorithm Working 6:16:17 K-Means Algorithm 6:19:16 Fuzzy C-Means Clustering 6:21:22 Hierarchical Clustering 6:22:53 Association Clustering 6:24:57 Association Rule Mining 6:30:35 Apriori Algorithm 6:37:45 Apriori Demo
6:40:49 What is Reinforcement Learning? 6:42:48 Reinforcement Learning Process 6:51:10 Markov Decision Process 6:54:53 Understanding Q - Learning 7:13:12 Q-Learning Demo 7:25:34 The Bellman Equation
7:48:39 What is Deep Learning? 7:52:53 Why we need Artificial Neuron? 7:54:33 Perceptron Learning Algorithm 7:57:57 Activation Function 8:03:14 Single Layer Perceptron 8:04:04 What is Tensorflow? 8:07:25 Demo 8:21:03 What is a Computational Graph? 8:49:18 Limitations of Single Layer Perceptron 8:50:08 Multi-Layer Perceptron 8:51:24 What is Backpropagation? 8:52:26 Backpropagation Learning Algorithm 8:59:31 Multi-layer Perceptron Demo
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