An examination of the literature on the topic of autopoietic, or self-producing systems, presented to accompany a research paper in Complex Systems 501 at the University of Michigan.
Object recognition is the process of identifying objects in images or videos. It involves segmenting objects from scenes, labeling objects, and extracting parametric descriptions. Object recognition has many applications including locating objects to recognize other objects or guide actions. It involves binding visual features into coherent objects and binding objects into spatial arrangements. Major challenges include handling different viewpoints and solving the binding problem of associating features with objects. Common approaches to object recognition include template matching, hierarchical processing of features, and recognizing objects as combinations of geometric parts or geons.
This presentation guide you through Neural Networks, use neural networksNeural Networks v/s Conventional
Computer, Inspiration from Neurobiology, Types of neural network, The Learning Process, Hetero-association recall mechanisms and Key Features,
For more topics stay tuned with Learnbay.
This document discusses social cognition and related topics including motivation and social processing goals, personal control, and social situations and social competence. Some key points include:
- Personal goals and priorities shift across the lifespan from achievement to balance to reevaluation.
- Older adults emphasize emotional goals by focusing on positive emotions and avoiding negative ones.
- Personal control involves both primary control of external actions and secondary cognitive control of the self. Both types of control strategies are important for well-being.
- Social contexts can facilitate cognition and memory in older adults, such as through collaborative problem solving and storytelling with others.
This document provides an overview of complexity theory and complex adaptive systems. It discusses how complex systems exist on the "edge of chaos," where they have enough stability to maintain their structure but also enough flexibility to adapt to changes. The edge of chaos allows systems to learn and evolve over time. It provides examples of how living systems, democracies, markets, and organizations can be considered complex adaptive systems that operate on the edge between order and disorder.
Object recognition is the process of identifying objects in images or videos. It involves segmenting objects from scenes, labeling objects, and extracting parametric descriptions. Object recognition has many applications including locating objects to recognize other objects or guide actions. It involves binding visual features into coherent objects and binding objects into spatial arrangements. Major challenges include handling different viewpoints and solving the binding problem of associating features with objects. Common approaches to object recognition include template matching, hierarchical processing of features, and recognizing objects as combinations of geometric parts or geons.
This presentation guide you through Neural Networks, use neural networksNeural Networks v/s Conventional
Computer, Inspiration from Neurobiology, Types of neural network, The Learning Process, Hetero-association recall mechanisms and Key Features,
For more topics stay tuned with Learnbay.
This document discusses social cognition and related topics including motivation and social processing goals, personal control, and social situations and social competence. Some key points include:
- Personal goals and priorities shift across the lifespan from achievement to balance to reevaluation.
- Older adults emphasize emotional goals by focusing on positive emotions and avoiding negative ones.
- Personal control involves both primary control of external actions and secondary cognitive control of the self. Both types of control strategies are important for well-being.
- Social contexts can facilitate cognition and memory in older adults, such as through collaborative problem solving and storytelling with others.
This document provides an overview of complexity theory and complex adaptive systems. It discusses how complex systems exist on the "edge of chaos," where they have enough stability to maintain their structure but also enough flexibility to adapt to changes. The edge of chaos allows systems to learn and evolve over time. It provides examples of how living systems, democracies, markets, and organizations can be considered complex adaptive systems that operate on the edge between order and disorder.
The Organization of the Living, Humberto Maturana, 1974David Alcántara
This document presents Humberto Maturana's theory of autopoiesis, which proposes that:
1) Living systems are autopoietic systems that continuously self-produce their own components through network interactions.
2) An autopoietic system's primary function is to realize its own autopoiesis or it will disintegrate.
3) The nervous system is a closed network of interacting neurons that generates states contributing to the organism's autopoiesis.
Software systems draw on our knowledge of the universe and the disciplines that study it. Our software architectures will benefit from drawing on other disciplines.
The document provides an introduction to complex adaptive systems theory. It discusses how complex systems like ecologies and social systems exist in a state of dynamic stability at the "edge of chaos" where they have enough stability to sustain themselves but also enough creativity for change and innovation. The edge of chaos allows systems to adapt to changes in their environment. Complex adaptive systems have several key characteristics, including that they are made up of autonomous agents that interact through shared rules in a networked structure, allowing for profuse experimentation and occasional rapid shifts in shape or direction in response to changes.
Here are the key aspects of a production system:
- It involves the transformation of inputs (raw materials, components) into outputs (finished goods and services) through linked activities and processes.
- The main components are people, machines, materials, information and energy. These work together in a coordinated manner to produce goods and services.
- Production systems aim to achieve objectives like high productivity, quality products, low costs and flexibility through efficient use of resources.
- There are different types of production systems like job production, batch production, mass production and lean production systems. The type used depends on factors like volume, variety, costs etc.
- Production planning and control is important to ensure smooth workflow and meet production targets
This book provides a summary of The Social Psychology of Organizations by Daniel Katz and Robert L. Kahn. It begins with an introduction discussing the origins and focus of the book. The book then aims to extend previous research by conceptualizing organizations using an open system point of view. It analyzes organizational structures and processes using concepts like roles, norms, values, and subsystems. Overall, the book seeks to link the individual and organizational levels of analysis using the concept of organizational roles.
This document provides an introduction to complex adaptive systems theory. It explains that complex adaptive systems exist on the "edge of chaos," with enough stability to sustain themselves but also enough creativity for change and adaptation. Systems on this edge experience periods of order and disorder, with new patterns emerging during times of disequilibrium that allow for reintegration at a higher level of organization. The edge of chaos provides systems with the ability to learn, evolve, and adapt in response to changes in their environment.
This document discusses different types of systems:
1. Mechanistic systems operate with regularity dictated by their internal structure and causal laws of nature. Clocks and automobiles are examples of mechanistic systems that have no purposes of their own but serve the purposes of others.
2. Animate systems are living systems like people whose parts have no purposes of their own but function to enable the system to survive. Animate systems must interact with their environments to survive.
3. Social systems have purposes of their own and consist of parts including animate systems that also have purposes. Social systems are nested within larger social systems like governments.
4. Ecological systems contain mechanistic, animate, and social systems
Understanding complexity and Why Agile works only if done rightHrishikesh Karekar
An attempt to see agile from the context of complexity theory and why compromising on the basics won't help us be agile. A good understanding of complexity theory and application would help to have a robust agile implementation.
This document defines systems and types of systems. It discusses:
- Systems have organized parts that work together towards an overall goal, with inputs, processes, outputs, and feedback.
- Types of systems include deterministic and probabilistic, open and closed, natural and manufactured, social and machine.
- Deterministic systems operate predictably while probabilistic systems have uncertain behavior. Open systems interact with the environment but closed systems do not.
This document discusses systems thinking and key concepts related to systems. It defines systems thinking as the cognitive process of studying and understanding systems of any kind by examining the linkages and interactions between interconnected components. A system is defined as a set of elements organized in a structure that produces characteristic behaviors. Key components of systems include elements, interconnections, and function. The document contrasts System 1 and System 2 thinking and provides examples. It emphasizes that systems thinking is needed to address problems created by more simplistic levels of thinking.
Towards a social action analysis of organizationsAmir Ghazinoori
This document discusses different models for analyzing organizations, including their strengths and weaknesses. It argues that viewing organizations solely as closed systems or seeing their goals as separate from individuals poses problems. A social action model is proposed that focuses on 1) establishing the ends of different groups within organizations, 2) determining conflicts between these ends, and 3) understanding how ends relate to the social situation, both inside and outside the organization. This provides a paradigm that integrates individuals' goals into the analysis of organizations.
Structural Functionalism views society as a structure of interconnected institutions that work together to ensure stability and meet the needs of individuals. Theorists like Comte, Spencer, and Parsons proposed that societies function like organisms, with different parts adapting to maintain equilibrium. Critics argue it fails to account for social change, inequality, and conflict that can disrupt the balance between institutions.
Structural Functionalism views society as a structure of interconnected institutions that work together to ensure stability and meet the needs of individuals. Theorists like Comte, Spencer, and Parsons proposed that societies function like organisms where all parts depend on each other, and any imbalance or conflict in one area is resolved for the benefit of the whole system. Critics argue that Structural Functionalism ignores social tensions, contradictions, and inequalities that can lead to change rather than stability.
This book discusses organizational psychology from an open systems perspective. It examines how organizations function as social systems with complex interactions between individuals and subsystems. The book defines key concepts like organizational roles, effectiveness, and structures. It presents a framework for understanding how organizations develop over time and compares different models of organizational theory. The goal is to analyze organizations using an integrated social science approach that considers both micro and macro levels of analysis.
The document discusses systems thinking and various systems thinking concepts and tools. It defines systems thinking as examining how problems are created and seeing the big picture by understanding how structure influences system performance. It discusses key systems thinking concepts like complex adaptive systems, feedback loops, stocks and flows. It also outlines different systems thinking tools like causal loop diagrams, stock and flow maps, behavior over time graphs and system archetypes that can help understand complex systems.
Describe the levels of organization in living system and some of .pdfamritashinfosalys
Describe the levels of organization in living system and some of the methods of classification.
Describe the levels of organization in living system and some of the methods of classification.
Solution
Answer:
The levels of organization in living system are:
(1) Organelle and cellular level
All living organisms have cellular level of organization, be it unicellular or multicellular. The
cell is the unit of life which carries out the necessay functions for survival. The functions are in
turn divided among different organelles present inside the cell. The prokaryotes have small set of
organelles while eukaryotes have richer collection of organelles which are more complex.
(2) Tissue level
Tissues are composed of similar type of cells which are same in origin and function. For
example, nerve cells have the same origin and function and forms the nervous tissue. These are
found in multicellular organisms.
(3) Organ level
Different tissues having similar functions together form the organ system in multicellular
organisms. Stomach is a digestive organ which are composed of muscular tissue for contraction
and secretory epithelium for gastric juice secretion.
(4) Organ system
When a number of organs group together to perform one or more functions, it forms an organ
system. Examples-Respiratory system, endocrine sytem and circulatory system, etc.
(5) Organism
An entire living being which can carry out all the necessary functions for basic processes is
called organism. An organism is usually made up of organ systems, but may be unicellular as in
case of bacteria.
Some methods of biological classification have been discussed as under:
(1) Natural system of classification:
In this system of classification, anatomy, physiology, pathology, biochemistry, reproduction &
cytology are taken into account to compare relationships among organisms. It is considered
advantageous over the artificial system of classification. This sytem was proposed by Bentham
and Hooker.
(2) Artificial sytem:
In this sytem of classification, external features such as form and shape are used for comparing
relationships among organisms. Since it does not take into account the internal properties such as
anatomy, pathology and biochemistry among others, it is difficult to to study evolution. Linnaeus
system of classification is considered as artificial.
(3) Phylogenetic classification:
It is classified on the basis of evolutionary relationships among organisms and is based upon
Darwin\'s theory of natural selection.
(4) Phenetic classification:
For classification, it takes relies upon similarities and disimilarities among organisms, but do not
take into account the evolutionary relationships.
(5) Cytotaxonomy:
It is classified based upon cytological features such as number of chromosomes..
This seminar report provides an overview of systems thinking and key concepts. It defines systems thinking as viewing problems as parts of an overall system rather than in isolation. A system is a collection of parts integrated to accomplish an overall goal, with inputs, processes, outputs and outcomes, and feedback. Systems can be biological, mechanical, social, or other types and range from simple to complex. Systems theory studies principles that can be applied to all types of systems. Some basic principles of systems thinking discussed are that change is slow but lasting, cause and effect are not always closely linked, and easy answers often do not address complexity. The report also lists examples of systems principles like how a system's behavior depends on its structure and how systems seek
The document discusses theories of systems and homeostasis. It proposes that Beer's "3-4-5" model of homeostasis assumes a fixed system identity, whereas recent work suggests identity is plastic and adapts to environmental changes. The concept of a "trialogue" is introduced as a three-way conversation between managing the present, creating the future, and negotiating identity, allowing systems to maintain continuity while adapting their identity over time in response to pressures.
The document discusses systems thinking and key concepts about systems. It defines a system as (1) created by nature or humans, (2) physical, abstract, or composed of humans, (3) separated from its environment by a border, and (4) either open or closed. Systems are hierarchical with different levels that influence levels below but cannot be directly derived from higher levels. The document contrasts mechanistic and systemic worldviews and discusses open systems, feedback, homeostasis, and learning systems.
Online Communities in Citizen Science & BirdCamsAndrea Wiggins
This document discusses online citizen science communities and bird cams. It describes how citizen science involves members of the public engaging in real-world scientific research through crowdsourcing and collaboration. It then focuses on how bird cams, which livestream nests and feeders, have emerged as online communities where people can observe and discuss bird activity in real-time. While most viewers never chat, many read discussions. Bird cams present unexpected outcomes like self-organizing social groups and emotional engagement. Sustainability relies on donations, merchandise, and fundraising by chat participants.
Free as in Puppies: Compensating for ICT Constraints in Citizen ScienceAndrea Wiggins
This document discusses how citizen science project organizers address issues related to participation and data quality when limited by resource constraints. It notes that while ideal information and communication technologies (ICT) could help with recruitment, retention, and data quality, free ICT options are often not sufficient due to lack of funding. The document presents three citizen science projects that have contrasting resource levels and explores how they creatively address these issues through alternative solutions like in-person outreach, paper data collection, and process optimization. It concludes by discussing implications for practice, policy, and CSCW research around leveraging complementary resources when full ICT capabilities are not possible.
The Organization of the Living, Humberto Maturana, 1974David Alcántara
This document presents Humberto Maturana's theory of autopoiesis, which proposes that:
1) Living systems are autopoietic systems that continuously self-produce their own components through network interactions.
2) An autopoietic system's primary function is to realize its own autopoiesis or it will disintegrate.
3) The nervous system is a closed network of interacting neurons that generates states contributing to the organism's autopoiesis.
Software systems draw on our knowledge of the universe and the disciplines that study it. Our software architectures will benefit from drawing on other disciplines.
The document provides an introduction to complex adaptive systems theory. It discusses how complex systems like ecologies and social systems exist in a state of dynamic stability at the "edge of chaos" where they have enough stability to sustain themselves but also enough creativity for change and innovation. The edge of chaos allows systems to adapt to changes in their environment. Complex adaptive systems have several key characteristics, including that they are made up of autonomous agents that interact through shared rules in a networked structure, allowing for profuse experimentation and occasional rapid shifts in shape or direction in response to changes.
Here are the key aspects of a production system:
- It involves the transformation of inputs (raw materials, components) into outputs (finished goods and services) through linked activities and processes.
- The main components are people, machines, materials, information and energy. These work together in a coordinated manner to produce goods and services.
- Production systems aim to achieve objectives like high productivity, quality products, low costs and flexibility through efficient use of resources.
- There are different types of production systems like job production, batch production, mass production and lean production systems. The type used depends on factors like volume, variety, costs etc.
- Production planning and control is important to ensure smooth workflow and meet production targets
This book provides a summary of The Social Psychology of Organizations by Daniel Katz and Robert L. Kahn. It begins with an introduction discussing the origins and focus of the book. The book then aims to extend previous research by conceptualizing organizations using an open system point of view. It analyzes organizational structures and processes using concepts like roles, norms, values, and subsystems. Overall, the book seeks to link the individual and organizational levels of analysis using the concept of organizational roles.
This document provides an introduction to complex adaptive systems theory. It explains that complex adaptive systems exist on the "edge of chaos," with enough stability to sustain themselves but also enough creativity for change and adaptation. Systems on this edge experience periods of order and disorder, with new patterns emerging during times of disequilibrium that allow for reintegration at a higher level of organization. The edge of chaos provides systems with the ability to learn, evolve, and adapt in response to changes in their environment.
This document discusses different types of systems:
1. Mechanistic systems operate with regularity dictated by their internal structure and causal laws of nature. Clocks and automobiles are examples of mechanistic systems that have no purposes of their own but serve the purposes of others.
2. Animate systems are living systems like people whose parts have no purposes of their own but function to enable the system to survive. Animate systems must interact with their environments to survive.
3. Social systems have purposes of their own and consist of parts including animate systems that also have purposes. Social systems are nested within larger social systems like governments.
4. Ecological systems contain mechanistic, animate, and social systems
Understanding complexity and Why Agile works only if done rightHrishikesh Karekar
An attempt to see agile from the context of complexity theory and why compromising on the basics won't help us be agile. A good understanding of complexity theory and application would help to have a robust agile implementation.
This document defines systems and types of systems. It discusses:
- Systems have organized parts that work together towards an overall goal, with inputs, processes, outputs, and feedback.
- Types of systems include deterministic and probabilistic, open and closed, natural and manufactured, social and machine.
- Deterministic systems operate predictably while probabilistic systems have uncertain behavior. Open systems interact with the environment but closed systems do not.
This document discusses systems thinking and key concepts related to systems. It defines systems thinking as the cognitive process of studying and understanding systems of any kind by examining the linkages and interactions between interconnected components. A system is defined as a set of elements organized in a structure that produces characteristic behaviors. Key components of systems include elements, interconnections, and function. The document contrasts System 1 and System 2 thinking and provides examples. It emphasizes that systems thinking is needed to address problems created by more simplistic levels of thinking.
Towards a social action analysis of organizationsAmir Ghazinoori
This document discusses different models for analyzing organizations, including their strengths and weaknesses. It argues that viewing organizations solely as closed systems or seeing their goals as separate from individuals poses problems. A social action model is proposed that focuses on 1) establishing the ends of different groups within organizations, 2) determining conflicts between these ends, and 3) understanding how ends relate to the social situation, both inside and outside the organization. This provides a paradigm that integrates individuals' goals into the analysis of organizations.
Structural Functionalism views society as a structure of interconnected institutions that work together to ensure stability and meet the needs of individuals. Theorists like Comte, Spencer, and Parsons proposed that societies function like organisms, with different parts adapting to maintain equilibrium. Critics argue it fails to account for social change, inequality, and conflict that can disrupt the balance between institutions.
Structural Functionalism views society as a structure of interconnected institutions that work together to ensure stability and meet the needs of individuals. Theorists like Comte, Spencer, and Parsons proposed that societies function like organisms where all parts depend on each other, and any imbalance or conflict in one area is resolved for the benefit of the whole system. Critics argue that Structural Functionalism ignores social tensions, contradictions, and inequalities that can lead to change rather than stability.
This book discusses organizational psychology from an open systems perspective. It examines how organizations function as social systems with complex interactions between individuals and subsystems. The book defines key concepts like organizational roles, effectiveness, and structures. It presents a framework for understanding how organizations develop over time and compares different models of organizational theory. The goal is to analyze organizations using an integrated social science approach that considers both micro and macro levels of analysis.
The document discusses systems thinking and various systems thinking concepts and tools. It defines systems thinking as examining how problems are created and seeing the big picture by understanding how structure influences system performance. It discusses key systems thinking concepts like complex adaptive systems, feedback loops, stocks and flows. It also outlines different systems thinking tools like causal loop diagrams, stock and flow maps, behavior over time graphs and system archetypes that can help understand complex systems.
Describe the levels of organization in living system and some of .pdfamritashinfosalys
Describe the levels of organization in living system and some of the methods of classification.
Describe the levels of organization in living system and some of the methods of classification.
Solution
Answer:
The levels of organization in living system are:
(1) Organelle and cellular level
All living organisms have cellular level of organization, be it unicellular or multicellular. The
cell is the unit of life which carries out the necessay functions for survival. The functions are in
turn divided among different organelles present inside the cell. The prokaryotes have small set of
organelles while eukaryotes have richer collection of organelles which are more complex.
(2) Tissue level
Tissues are composed of similar type of cells which are same in origin and function. For
example, nerve cells have the same origin and function and forms the nervous tissue. These are
found in multicellular organisms.
(3) Organ level
Different tissues having similar functions together form the organ system in multicellular
organisms. Stomach is a digestive organ which are composed of muscular tissue for contraction
and secretory epithelium for gastric juice secretion.
(4) Organ system
When a number of organs group together to perform one or more functions, it forms an organ
system. Examples-Respiratory system, endocrine sytem and circulatory system, etc.
(5) Organism
An entire living being which can carry out all the necessary functions for basic processes is
called organism. An organism is usually made up of organ systems, but may be unicellular as in
case of bacteria.
Some methods of biological classification have been discussed as under:
(1) Natural system of classification:
In this system of classification, anatomy, physiology, pathology, biochemistry, reproduction &
cytology are taken into account to compare relationships among organisms. It is considered
advantageous over the artificial system of classification. This sytem was proposed by Bentham
and Hooker.
(2) Artificial sytem:
In this sytem of classification, external features such as form and shape are used for comparing
relationships among organisms. Since it does not take into account the internal properties such as
anatomy, pathology and biochemistry among others, it is difficult to to study evolution. Linnaeus
system of classification is considered as artificial.
(3) Phylogenetic classification:
It is classified on the basis of evolutionary relationships among organisms and is based upon
Darwin\'s theory of natural selection.
(4) Phenetic classification:
For classification, it takes relies upon similarities and disimilarities among organisms, but do not
take into account the evolutionary relationships.
(5) Cytotaxonomy:
It is classified based upon cytological features such as number of chromosomes..
This seminar report provides an overview of systems thinking and key concepts. It defines systems thinking as viewing problems as parts of an overall system rather than in isolation. A system is a collection of parts integrated to accomplish an overall goal, with inputs, processes, outputs and outcomes, and feedback. Systems can be biological, mechanical, social, or other types and range from simple to complex. Systems theory studies principles that can be applied to all types of systems. Some basic principles of systems thinking discussed are that change is slow but lasting, cause and effect are not always closely linked, and easy answers often do not address complexity. The report also lists examples of systems principles like how a system's behavior depends on its structure and how systems seek
The document discusses theories of systems and homeostasis. It proposes that Beer's "3-4-5" model of homeostasis assumes a fixed system identity, whereas recent work suggests identity is plastic and adapts to environmental changes. The concept of a "trialogue" is introduced as a three-way conversation between managing the present, creating the future, and negotiating identity, allowing systems to maintain continuity while adapting their identity over time in response to pressures.
The document discusses systems thinking and key concepts about systems. It defines a system as (1) created by nature or humans, (2) physical, abstract, or composed of humans, (3) separated from its environment by a border, and (4) either open or closed. Systems are hierarchical with different levels that influence levels below but cannot be directly derived from higher levels. The document contrasts mechanistic and systemic worldviews and discusses open systems, feedback, homeostasis, and learning systems.
Online Communities in Citizen Science & BirdCamsAndrea Wiggins
This document discusses online citizen science communities and bird cams. It describes how citizen science involves members of the public engaging in real-world scientific research through crowdsourcing and collaboration. It then focuses on how bird cams, which livestream nests and feeders, have emerged as online communities where people can observe and discuss bird activity in real-time. While most viewers never chat, many read discussions. Bird cams present unexpected outcomes like self-organizing social groups and emotional engagement. Sustainability relies on donations, merchandise, and fundraising by chat participants.
Free as in Puppies: Compensating for ICT Constraints in Citizen ScienceAndrea Wiggins
This document discusses how citizen science project organizers address issues related to participation and data quality when limited by resource constraints. It notes that while ideal information and communication technologies (ICT) could help with recruitment, retention, and data quality, free ICT options are often not sufficient due to lack of funding. The document presents three citizen science projects that have contrasting resource levels and explores how they creatively address these issues through alternative solutions like in-person outreach, paper data collection, and process optimization. It concludes by discussing implications for practice, policy, and CSCW research around leveraging complementary resources when full ICT capabilities are not possible.
Citizen science projects can be categorized in different ways based on levels of public participation and types of scientific tasks involved. Some key typologies include contributory vs collaborative vs co-created projects, and projects involving data collection, processing, and transcription tasks. The level of public participation and task complexity determine scalability, technology requirements, volunteer management needs, and implications for project design such as evaluating resources and goals, recognizing tradeoffs, and addressing constraints to determine the appropriate design.
The document discusses different typologies of citizen science projects based on their goals and tasks. It identifies nine common labels for citizen science projects that vary based on their research domain and key features. The typologies are based on the level of participation from contributory to collaborative to co-created. The presentation evaluates the relative pros and cons of each approach and provides implications for project design, emphasizing the need to honestly evaluate resources and goals to make appropriate design choices.
Citizen Science 101: What Every Researcher Should Know About Crowdsourcing Sc...Andrea Wiggins
This document provides an overview of citizen science and how the public can engage with scientific research. It defines citizen science as members of the public participating in real-world scientific research through crowdsourcing, collaboration, and online communities. It discusses different models of participation from contributory to co-created research. Examples provided include projects in ecology, ornithology, astronomy, and other fields that have successfully engaged volunteers to collect large datasets and make new discoveries. Quality assurance mechanisms are emphasized to validate data collected by non-experts.
The document discusses challenges and opportunities for data management in citizen science projects. It identifies developing data management plans, establishing data policies, developing supporting cyberinfrastructure or technology platforms, and ensuring data quality as key issues. A survey of citizen science projects found the greatest dissatisfaction with processes for sharing data and presenting results, but that data management planning was better than average. Top priorities for improvement included tools for analyzing, visualizing, documenting and describing data, as well as training. The presentation calls on USGS to lead by example in promoting data sharing, developing clear and reusable policies and platforms, and demonstrating best practices for data quality.
With Great Data Comes Great ResponsibilityAndrea Wiggins
Presentation at the Conference on Public Participation in Scientific Research, providing a vision for the future of data management in citizen science.
Crowdsourcing Scientific Work: A Comparative Study of Technologies, Processes...Andrea Wiggins
Slides from my successful dissertation defense. The research focused on the role of technologies in supporting participation and organizing processes in citizen science projects, and the impacts of these processes on scientific outcomes.
Mechanisms for Data Quality and Validation in Citizen ScienceAndrea Wiggins
This document summarizes a survey of data quality and validation mechanisms used in citizen science projects. The survey found that most projects use expert review and that projects use an average of 2.5 validation methods, often in combination. Larger projects and those with more funding tend to use fewer validation methods that require more human resources. Common validation methods included expert review, photo submissions, paper data sheets, and replication by multiple participants. Future work should focus on validation of data analysis methods and developing tools to help projects plan quality assurance procedures.
From Conservation to Crowdsourcing: A Typology of Citizen ScienceAndrea Wiggins
1) The document presents a typology of six types of citizen science projects based on their primary goals and level of virtuality or physical interaction. The six types are: action & intervention, conservation & stewardship, investigation, virtual science, education & outreach, and physical science.
2) Examples are provided for each type, including the Great Sunflower Project for investigation and Galaxy Zoo for virtual science.
3) The typology is intended to help guide future research on citizen science by providing a framework to identify different project designs, technologies used, and implications for areas like task design and cyberinfrastructure.
Motivation by Design: Technologies, Experiences, and IncentivesAndrea Wiggins
Invited presentation at Citizen Cyberscience Summit 2012 on the topic of designing citizen science technologies and experiences to motivate contribution.
Data Intensive Collaboration in Science and Engineering: CSCW workshop themesAndrea Wiggins
The document discusses key themes in digital scholarship infrastructure and ecosystems. It identifies themes such as contexts, infrastructures, reusability, and tensions. Contexts refer to domains, locations, and openness. Infrastructures include social, technical, and sustainability aspects. Reusability covers data, tools, and curation. Tensions arise from factors like growth, flexibility, and sustainability over time. The document analyzes these themes in relation to digital scholarship.
Secondary data analysis with digital trace dataAndrea Wiggins
This document discusses secondary data analysis using digital trace data. It provides examples from research on free/libre open-source software projects. The document outlines that secondary data analysis uses existing data collected for other purposes. Digital trace data consists of records of online activity that can provide longitudinal data at a large scale. Challenges include understanding the original data collection and limitations, as well as preparing large volumes of data for analysis. The document provides an example of analyzing email networks within FLOSS projects and classifying projects based on success criteria.
Open Source, Open Science, & Citizen ScienceAndrea Wiggins
This document summarizes Andrea Wiggins' background and research interests in open source software, open science, and citizen science. Her research focuses on how technologies support distributed collaboration, open participation, and communities of practice in contexts like open source software development, scientific research, and citizen science projects. She is conducting a comparative case study of citizen science projects to understand the role of technology in public participation in scientific research.
Reclassifying Success and Tragedy in FLOSS ProjectsAndrea Wiggins
This document summarizes research that replicated and extended a prior study classifying open-source software projects as successful, tragic, or indeterminate based on their growth and development. The replication classified over 117,000 projects using similar criteria as the original study. Extensions explored varying the definition of release rates and comparing classifications over time. Results showed some changes in project classifications over a 6-month period, demonstrating the potential instability of classifications. The study highlights challenges in large-scale analysis of open-source data and offers recommendations for future work.
Dissertation proposal defense for a comparative case study of virtual citizen science projects, focusing on the concepts of virtuality, technology, organizing, participation, and outcomes.
Successfully defended with no revisions on 5 May, 2010.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.