This poster has been presented in INFORMS annual meeting 2015. And it can be seen as a "snapshot" of my thesis research work, with the elimination of more advanced developments.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
This article is all about what AI trends will emerge in the field of creative operations in 2024. All the marketers and brand builders should be aware of these trends for their further use and save themselves some time!
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
This article is all about what AI trends will emerge in the field of creative operations in 2024. All the marketers and brand builders should be aware of these trends for their further use and save themselves some time!
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Nutrition is the science that deals with the study of nutrients and their role in maintaining human health and well-being. It encompasses the various processes involved in the intake, absorption, and utilization of essential nutrients, such as carbohydrates, proteins, fats, vitamins, minerals, and water, by the human body.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Richard's entangled aventures in wonderlandRichard 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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Nutrition is the science that deals with the study of nutrients and their role in maintaining human health and well-being. It encompasses the various processes involved in the intake, absorption, and utilization of essential nutrients, such as carbohydrates, proteins, fats, vitamins, minerals, and water, by the human body.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Richard's entangled aventures in wonderlandRichard 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.
A report by thenetworkone and Kurio.
The contributing experts and agencies are (in an alphabetical order): Sylwia Rytel, Social Media Supervisor, 180heartbeats + JUNG v MATT (PL), Sharlene Jenner, Vice President - Director of Engagement Strategy, Abelson Taylor (USA), Alex Casanovas, Digital Director, Atrevia (ES), Dora Beilin, Senior Social Strategist, Barrett Hoffher (USA), Min Seo, Campaign Director, Brand New Agency (KR), Deshé M. Gully, Associate Strategist, Day One Agency (USA), Francesca Trevisan, Strategist, Different (IT), Trevor Crossman, CX and Digital Transformation Director; Olivia Hussey, Strategic Planner; Simi Srinarula, Social Media Manager, The Hallway (AUS), James Hebbert, Managing Director, Hylink (CN / UK), Mundy Álvarez, Planning Director; Pedro Rojas, Social Media Manager; Pancho González, CCO, Inbrax (CH), Oana Oprea, Head of Digital Planning, Jam Session Agency (RO), Amy Bottrill, Social Account Director, Launch (UK), Gaby Arriaga, Founder, Leonardo1452 (MX), Shantesh S Row, Creative Director, Liwa (UAE), Rajesh Mehta, Chief Strategy Officer; Dhruv Gaur, Digital Planning Lead; Leonie Mergulhao, Account Supervisor - Social Media & PR, Medulla (IN), Aurelija Plioplytė, Head of Digital & Social, Not Perfect (LI), Daiana Khaidargaliyeva, Account Manager, Osaka Labs (UK / USA), Stefanie Söhnchen, Vice President Digital, PIABO Communications (DE), Elisabeth Winiartati, Managing Consultant, Head of Global Integrated Communications; Lydia Aprina, Account Manager, Integrated Marketing and Communications; Nita Prabowo, Account Manager, Integrated Marketing and Communications; Okhi, Web Developer, PNTR Group (ID), Kei Obusan, Insights Director; Daffi Ranandi, Insights Manager, Radarr (SG), Gautam Reghunath, Co-founder & CEO, Talented (IN), Donagh Humphreys, Head of Social and Digital Innovation, THINKHOUSE (IRE), Sarah Yim, Strategy Director, Zulu Alpha Kilo (CA).
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
The search marketing landscape is evolving rapidly with new technologies, and professionals, like you, rely on innovative paid search strategies to meet changing demands.
It’s important that you’re ready to implement new strategies in 2024.
Check this out and learn the top trends in paid search advertising that are expected to gain traction, so you can drive higher ROI more efficiently in 2024.
You’ll learn:
- The latest trends in AI and automation, and what this means for an evolving paid search ecosystem.
- New developments in privacy and data regulation.
- Emerging ad formats that are expected to make an impact next year.
Watch Sreekant Lanka from iQuanti and Irina Klein from OneMain Financial as they dive into the future of paid search and explore the trends, strategies, and technologies that will shape the search marketing landscape.
If you’re looking to assess your paid search strategy and design an industry-aligned plan for 2024, then this webinar is for you.
5 Public speaking tips from TED - Visualized summarySpeakerHub
From their humble beginnings in 1984, TED has grown into the world’s most powerful amplifier for speakers and thought-leaders to share their ideas. They have over 2,400 filmed talks (not including the 30,000+ TEDx videos) freely available online, and have hosted over 17,500 events around the world.
With over one billion views in a year, it’s no wonder that so many speakers are looking to TED for ideas on how to share their message more effectively.
The article “5 Public-Speaking Tips TED Gives Its Speakers”, by Carmine Gallo for Forbes, gives speakers five practical ways to connect with their audience, and effectively share their ideas on stage.
Whether you are gearing up to get on a TED stage yourself, or just want to master the skills that so many of their speakers possess, these tips and quotes from Chris Anderson, the TED Talks Curator, will encourage you to make the most impactful impression on your audience.
See the full article and more summaries like this on SpeakerHub here: https://speakerhub.com/blog/5-presentation-tips-ted-gives-its-speakers
See the original article on Forbes here:
http://www.forbes.com/forbes/welcome/?toURL=http://www.forbes.com/sites/carminegallo/2016/05/06/5-public-speaking-tips-ted-gives-its-speakers/&refURL=&referrer=#5c07a8221d9b
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
Everyone is in agreement that ChatGPT (and other generative AI tools) will shape the future of work. Yet there is little consensus on exactly how, when, and to what extent this technology will change our world.
Businesses that extract maximum value from ChatGPT will use it as a collaborative tool for everything from brainstorming to technical maintenance.
For individuals, now is the time to pinpoint the skills the future professional will need to thrive in the AI age.
Check out this presentation to understand what ChatGPT is, how it will shape the future of work, and how you can prepare to take advantage.
A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
It's part of a Data Science Corner Campaign where I will be discussing the fundamentals of DataScience, AIML, Statistics etc.
Time Management & Productivity - Best PracticesVit Horky
Here's my presentation on by proven best practices how to manage your work time effectively and how to improve your productivity. It includes practical tips and how to use tools such as Slack, Google Apps, Hubspot, Google Calendar, Gmail and others.
The six step guide to practical project managementMindGenius
The six step guide to practical project management
If you think managing projects is too difficult, think again.
We’ve stripped back project management processes to the
basics – to make it quicker and easier, without sacrificing
the vital ingredients for success.
“If you’re looking for some real-world guidance, then The Six Step Guide to Practical Project Management will help.”
Dr Andrew Makar, Tactical Project Management
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...Applitools
During this webinar, Anand Bagmar demonstrates how AI tools such as ChatGPT can be applied to various stages of the software development life cycle (SDLC) using an eCommerce application case study. Find the on-demand recording and more info at https://applitools.info/b59
Key takeaways:
• Learn how to use ChatGPT to add AI power to your testing and test automation
• Understand the limitations of the technology and where human expertise is crucial
• Gain insight into different AI-based tools
• Adopt AI-based tools to stay relevant and optimize work for developers and testers
* ChatGPT and OpenAI belong to OpenAI, L.L.C.
More than Just Lines on a Map: Best Practices for U.S Bike Routes
This session highlights best practices and lessons learned for U.S. Bike Route System designation, as well as how and why these routes should be integrated into bicycle planning at the local and regional level.
Presenters:
Presenter: Kevin Luecke Toole Design Group
Co-Presenter: Virginia Sullivan Adventure Cycling Association
Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...DevGAMM Conference
Has your project been caught in a storm of deadlines, clashing requirements, and the need to change course halfway through? If yes, then check out how the administration team navigated through all of this, relocating 160 people from 3 countries and opening 2 offices during the most turbulent time in the last 20 years. Belka Games’ Chief Administrative Officer, Katerina Rudko, will share universal approaches and life hacks that can help your project survive unstable periods when there seem to be too many tasks and a lack of time and people.
Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...
Optimized scheduling of sequential resource allocation systems (poster)
1. 5.2 Static random switches
Static random switches are defined only by the set of the enabled
untimed transitions and not by the state itself, i.e.,
Ξi = Ξj if the vanishing states vi and vj activate the same set
of untimed transitions
• The corresponding policy space contains all the “static-
priority” policies
• Mathematically, the proposed restriction corresponds to
a state space aggregation
• Hence, we can refine the obtained solution through
(partial) disaggregation
4. The methodological framework (demo with an example resource allocation system)1. Background and motivation
Resource allocation in flexibly automated operations
Optimized Scheduling of Sequential Resource Allocation Systems
Ran Li (rli63@gatech.edu)
Spyros Reveliotis (spyros@isye.gatech.edu)
WS1 WS2
I/O Port
Process route:
WS1 -> WS2 -> WS1
0
1
2
3 4
5
6
7
8
9
μ2 / (μ1 + μ2)
13
12
14
17
23
μ2 / (μ2 + μ3)
18
20
19
22
11
55
56
58
59
60
62
65
26
28
29 30
51
53
μ3 / (μ2 + μ3)
μ2 / (μ1 + μ2)
μ1 / (μ1 + μ2)
49
50 47
48
44
46
45
25
323334
36
37
38
4041
57
63
27
35
64
10
16
15
μ2 / (μ2 + μ3)
μ3 / (μ2 + μ3)
μ1 / (μ1 + μ2)
24
μ1 / (μ1 + μ2)
μ2 / (μ1 + μ2)
31
39
42
μ2 / (μ1 + μ2)
μ1 / (μ1 + μ2)
43
μ3 / (μ2 + μ3)
μ2 / (μ2 + μ3)
61
μ2 / (μ1 + μ2)
μ1 / (μ1 + μ2)
52
μ2 / (μ2 + μ3)
54
μ3 / (μ2 + μ3) μ2 / (μ2 + μ3)
21
μ3 / (μ2 + μ3)
maximize ζ η(ζ) = π(ζ) T • r
subject to
Ξi
T • 1 = 1.0 for all vi
ε ≤ ξij for all vi and all j in {1,…,k(i)}
where
Ξi = < ζij: j=1,…,k(i) > the random switch
for vanishing state vi
ζ = the vector collecting all ζij
ε = a minimal degree of randomization in
each Ξi
π(ζ) = the steady-state distribution for
tangible states, defined by the pricing of
each element of ζ
r = the vector collecting the reward rates
at the tangible states
4.1 The example system
A flexibly automated production cell
Objective
Maximize long-run time average throughput
Configuration
2 workstations (WS): each with 1 server, 2 buffer slots
The jobs in processing occupy their buffer slots
1 process type with 3 stages
Stage j takes exponentially distributed time length with rate µj
4.2 Generalized stochastic Petri-net
(GSPN)
Route t0 – p0 – t1 … p6 – t7: the process route
• Untimed transitions: their firing is immediate,
and models the allocation of resources
• Timed transitions: their firing has an
exponentially distributed delay time, has lower
priority than the firing of untimed transitions,
and models the processing of job instances
• Places: Model the different process stages
Places p7 - p10: Model resource availability
Place p11 and its arcs (the red subnet): Models the
applied DAP.
Model as a
discrete event
system
State space for
the timed
dynamics
The underlying
optimization
problem
4.3 State transition diagram for the underlying
semi-Markov process (SMP) with reward
Tangible state: only timed transitions are enabled, and
their branching probabilities are determined by
exponential race
Tangible state with rewards: the timed transition that
models the output (i.e., transition t7) is enabled
Vanishing state: at least one untimed transition is
enabled
Vanishing state with a random switch: at least two
untimed transitions are enabled, and a decision of “which
fires first” is needed
Flexibly automated production cell Automated guided vehicles (AGV) 2D traffic system of free-ranging mobile agents
Multi-thread software
Stage I-1
Stage I-2
Process Type I
Stage II-1
Stage II-2a Stage II-2b
Stage II-3
Process Type II
Choose one
alternative
Resources and
Requirement on them
All these applications can be abstracted as
sequential resource allocation systems (RAS)
Sequential resource allocation systems
• A sequential resource allocation system consists
of several process types, and reusable but finite
resources of different types.
• A job instance of a process type can be
executed by going through a number of stages.
• Each stage requires a certain amount of certain
resource types and a random processing time.
• The job instances of different process types, or
the same process type but different stages, may
compete for the required resource.
2. Problem definition
Objective
• Maximize some time-related performance measure, while
• maintaining behavioral correctness (e.g., avoid deadlocks).
What can be regulated?
• Allocation of resources to the competing job instances
3. Method overview The logical control problem has been
well studied in the community of discrete
event systems.
The performance control problem is in
the domain of stochastic optimization.
This research defines a discrete event
model as the framework for solving
performance control problem while
integrating the existing logical control
results, and develops the supporting
methodology.RAS Domain
LogicalControl
SystemStateModel
PerformanceControl
Configuration Data
Feasible
Actions
Admissible
Actions
Event Commanded
Action
Deadlock
A pattern of “circular waiting”: all jobs in a given set cannot
advance to their next stage since they are waiting for
resources currently allocated to some other job in the set.
Optimal deadlock avoidance policy (DAP)
Forbid the actions that will unavoidably lead to deadlock
states.
Stage 2 job
instance
WS2WS1
Stage 1 job
instance
No job instances can advance further, because all
buffers are full
Optimal DAP: not load new jobs if total number of
job instances in stages 1 and 2 is three
Deadlock and deadlock avoidance in the example system Implementation
t0
t1
t2
t3
t4
t5
t6
t7
p0
p1
p2
p3
p4
p5
p6
p7
p8
p9 p10
p11
Untimed Transitions
Timed Transitions
rate = µ1
rate = µ2
rate = µ3
5. Coping with the underlying complexity
t2 and t6 are enabled
at state 25, but firing
one transition does
not disable the other
5.1 Random switch refinement
Some random switches are not necessary since they do
not reflect “real conflicts” in resource allocation
Example:
We can replace {t2, t6} by
the singleton {t2}, but not
{t6} : firing t6 first “lost”
the possibility to reach
the tangible state 39
For each vanishing state, the
replacement can be
performed if it does not
impact the potential to reach
any tangible states.
Such a refinement maintains
the performance potential of
the policy space
…√
X
4.4 Mathematic programming formulation
Note that the vanishing states can be “collapsed” to tangible
states since they have zero sojourn times and zero rewards.
Then the SMP becomes a continuous time Markov chain
(CTMC)
The steady-state distribution π(ζ) can either be
(i) computed through the “balance equation”, or
(ii) estimated through steady-state simulation
The whole
state space
The green and yellow nodes correspond to the two static random
switches that remain in the state space of the example RAS of Section
4, after refinement of the initial random switches.
4.5. Computational challenges
Explosion of vi => Explosion of ζij
Explosion of π(ζ)
In the example system:
3 stages
2 single servers
2 buffers of capacity 2
19 tangible states
47 vanishing states
20 random switches
27 decision variables
state
space
Increasing system size =>
5.3 Stochastic approximation: coping with the
explosion of π(ζ)
A typical iteration of stochastic approximation is:
ζk+1 = ζk + γk Yk
ζk is the vector of decision variables at iteration k, γk is the
positive step size, and Yk is the improvement direction.
A typical choice of Yk for the average-reward problem of
irreducible Markov chains is the estimated gradient. In this work,
we adapt the Likelihood Ratio gradient estimator with a sample
size of 2N regenerative cycles at each iteration, then:
where
p is transition probability
u is revisiting time to the reference state
Λ is sum of likelihood ratio of p, i.e.
k
uj
jj
jj
k
k
mmp
mmp
1
1
1
)(
),(
),(
1111
1
212
1
0
1
12222
2
22
12
12
2
12
2
22
12
22
12
12
2
)()(
])()[(])()[(
2ˆ
i
i
i
i
i
i
i
i
i
i
i
i
u
uk k
u
uk k
u
uk k
u
uk k
u
uk kkii
N
i
u
uk kkii
N
mrmr
mruumruu
u
N
Y
6. Conclusion
An integrated framework for real-
time management of sequential
resource allocation systems based
on
• the (formal) representational
power of GSPNs;
• a parsimonious representation
of the underlying conflicts;
• a pertinent specification of the
set of target scheduling
policies;
• results from sensitivity analysis
of Markov reward processes.
The table shows the effectiveness of the complexity
control of 20 RAS configurations
(Config. 1 is the example system of Section 4)
R.S. = random switch(es)
D.V. = decision variable(s)
Config.
Origin Apply refinement Apply static R.S.
Num. of
R.S.
Num. of
D.V.
Num. of
R.S.
Num. of
D.V.
Num. of
R.S.
Num. of
D.V.
1 20 27 5 5 2 2
2 4 4 1 1 1 1
3 40 56 11 11 2 2
4 128 177 35 35 2 2
5 1,007 1,374 269 269 2 2
6 71 84 9 9 1 1
7 346 463 49 49 2 2
8 742 966 112 112 2 2
9 4,304 5,498 677 677 2 2
10 13,302 20,948 2,083 2,290 13 15
11 7,573 11,368 1,513 1,513 4 4
12 2,781 4,018 678 678 4 4
13 2,468 3,759 609 609 5 5
14 519 693 106 106 5 5
15 4,256 5,887 759 759 6 6
16 1,851 2,534 243 243 6 6
17 163,695 270,738 30,805 35,420 15 17
18 74,655 109,948 12,313 12,313 4 4
19 322,052 525,166 80,142 85,117 19 22
20 788,731 1,270,562 139,496 154,069 14 17
0
1
2
3
5
6
7
8
9
μ2 / (μ1 + μ2)
12
17
23
μ2 / (μ2 + μ3)
18
19
22
11
55
62
65
26
28
29
51
53
μ3 / (μ2 + μ3)
μ2 / (μ1 + μ2)
μ1 / (μ1 + μ2)
49
50 47
44
46
45
25
323334
36
38
4041
63
35
64
10
16
15
μ2 / (μ2 + μ3)
μ3 / (μ2 + μ3)
μ1 / (μ1 + μ2)
24
μ1 / (μ1 + μ2)
μ2 / (μ1 + μ2)
31
39
42
μ2 / (μ1 + μ2)
μ1 / (μ1 + μ2)
43
μ3 / (μ2 + μ3)
μ2 / (μ2 + μ3)
61
μ2 / (μ1 + μ2)
μ1 / (μ1 + μ2)
52
μ2 / (μ2 + μ3)
54
μ3 / (μ2 + μ3) μ2 / (μ2 + μ3)
21
μ3 / (μ2 + μ3)
t3
t3
t5
t5
t6
26
28
29 30
t6
t2
25 36
37
38
27
t2
35
t3
t6
t5
t0
31
t3
t6
t6
t3
t5
39
t0
t3
t3
t5
t5
t6
t6
t2
25
27
t2
t3
t6
t5
t0
t3
t6
t6
t3
t5
t0
26
28
29 30
36
37
38
35
31
39
t3
t3
t5
t5
t6
t6
t2
25
27
t2
t3
t6
t5
t0
t3
t6
t6
t3
t5
t0
26
28
29 30
36
37
38
35
31
39
t3
26
t6
t2
25 36
38
31
t5
39
t0