Introduction forFidel, R., Mark Pejtersen, A., Cleal, B., & Bruce, H. (2004). A multidimensional approach to the study of human information interaction: A case study of collaborative information retrieval. Journal of the American Society for Information Science and Technology, 55(11), 939-953.
My presentation for Kharkiv AI club about capsule networks. Introduction to capsule networks theory, basics. Links, references, explanations of capsules and routing
Using Deep Learning to Find Similar DressesHJ van Veen
Report by Luís Mey ( https://www.linkedin.com/in/lu%C3%ADs-gustavo-bernardo-mey-97b38927/ ) on Udacity Machine Learning Course - Final Project: Use Deep Learning to Find Similar Dresses.
Image Captioning Generator using Deep Machine Learningijtsrd
Technologys scope has evolved into one of the most powerful tools for human development in a variety of fields.AI and machine learning have become one of the most powerful tools for completing tasks quickly and accurately without the need for human intervention. This project demonstrates how deep machine learning can be used to create a caption or a sentence for a given picture. This can be used for visually impaired persons, as well as automobiles for self identification, and for various applications to verify quickly and easily. The Convolutional Neural Network CNN is used to describe the alphabet, and the Long Short Term Memory LSTM is used to organize the right meaningful sentences in this model. The flicker 8k and flicker 30k datasets were used to train this. Sreejith S P | Vijayakumar A "Image Captioning Generator using Deep Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42344.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42344/image-captioning-generator-using-deep-machine-learning/sreejith-s-p
Covers SCRUM Artifacts topic in detail along with necessary linked topics understanding.
Below are SCRUM Artifacts covered in this presentation:
Product Backlog
Sprint Backlog
Increment / Product Increment
Deep learning algorithms for intrusion detection systems in internet of thin...IJECEIAES
Due to technological advancements in recent years, the availability and usage of smart electronic gadgets have drastically increased. Adoption of these smart devices for a variety of applications in our day-to-day life has become a new normal. As these devices collect and store data, which is of prime importance, securing is a mandatory requirement by being vigilant against intruders. Many traditional techniques are prevailing for the same, but they may not be a good solution for the devices with resource constraints. The impact of artificial intelligence is not negligible in this concern. This study is an attempt to understand and analyze the performance of deep learning algorithms in intrusion detection. A comparative analysis of the performance of deep neural network, convolutional neural network, and long short-term memory using the CIC-IDS 2017 dataset.
My presentation for Kharkiv AI club about capsule networks. Introduction to capsule networks theory, basics. Links, references, explanations of capsules and routing
Using Deep Learning to Find Similar DressesHJ van Veen
Report by Luís Mey ( https://www.linkedin.com/in/lu%C3%ADs-gustavo-bernardo-mey-97b38927/ ) on Udacity Machine Learning Course - Final Project: Use Deep Learning to Find Similar Dresses.
Image Captioning Generator using Deep Machine Learningijtsrd
Technologys scope has evolved into one of the most powerful tools for human development in a variety of fields.AI and machine learning have become one of the most powerful tools for completing tasks quickly and accurately without the need for human intervention. This project demonstrates how deep machine learning can be used to create a caption or a sentence for a given picture. This can be used for visually impaired persons, as well as automobiles for self identification, and for various applications to verify quickly and easily. The Convolutional Neural Network CNN is used to describe the alphabet, and the Long Short Term Memory LSTM is used to organize the right meaningful sentences in this model. The flicker 8k and flicker 30k datasets were used to train this. Sreejith S P | Vijayakumar A "Image Captioning Generator using Deep Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42344.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42344/image-captioning-generator-using-deep-machine-learning/sreejith-s-p
Covers SCRUM Artifacts topic in detail along with necessary linked topics understanding.
Below are SCRUM Artifacts covered in this presentation:
Product Backlog
Sprint Backlog
Increment / Product Increment
Deep learning algorithms for intrusion detection systems in internet of thin...IJECEIAES
Due to technological advancements in recent years, the availability and usage of smart electronic gadgets have drastically increased. Adoption of these smart devices for a variety of applications in our day-to-day life has become a new normal. As these devices collect and store data, which is of prime importance, securing is a mandatory requirement by being vigilant against intruders. Many traditional techniques are prevailing for the same, but they may not be a good solution for the devices with resource constraints. The impact of artificial intelligence is not negligible in this concern. This study is an attempt to understand and analyze the performance of deep learning algorithms in intrusion detection. A comparative analysis of the performance of deep neural network, convolutional neural network, and long short-term memory using the CIC-IDS 2017 dataset.
This thesis describes a method to find a part of online data in an offline
document. This method is able to find the offline document that belongs
to the online data from a set of offline documents, or vice versa. In order to
optimize the mapping between the online and the offline data, an optimal rotation
and resizing of the online data is calculated. This is useful since it produces
a better mapping between online and offline data, which makes several methods
that are only applicable for online data available for offline data, and vice
versa.
Results show that this method can be used for finding the offline document that
belongs to certain online data, since it succeeded in 98.07% of the cases for
the used dataset. The results also show that computing the optimal rotation and
resize factor significantly improves the mapping between online and offline
data. This improvement is 6.56% for the used dataset.
Slides from Portland Machine Learning meetup, April 13th.
Abstract: You've heard all the cool tech companies are using them, but what are Convolutional Neural Networks (CNNs) good for and what is convolution anyway? For that matter, what is a Neural Network? This talk will include a look at some applications of CNNs, an explanation of how CNNs work, and what the different layers in a CNN do. There's no explicit background required so if you have no idea what a neural network is that's ok.
In this report I will compare two different information system methodologies. I would talk about SSADM (Structure System Analysis and Design Methodologies) and XP (Extreme Programing).
From Model-based to Model and Simulation-based Systems ArchitecturesObeo
Achieving quality engineering through descriptive and analytical models
Systems architecture design is a key activity that affect the
overall systems engineering cost. It is hence fundamental
to ensure that the system architecture reaches a proper quality.
In this paper, we leverage on MBSE approaches and complement them
with simulation techniques, as a prom-ising way to improve the quality of the system architecture definition, and to come up with inno-vative solutions while securing the systems engineering process.
We cannot determine the Value of something unless we know it’s cost. But determining Value requires have tangible measures to be compared against the cost. In the Systems Engineering Paradigm, these are the Measures of Effectiveness, Measures of Performance, Technical Performance Measures, and Key Performance Parameters
Tese de doutorado em CIência da Informação Análise de dominio Organizacional ...Célia Dias
A presente pesquisa tem como objeto de estudo formulários da Metodologia DIRKS – Designing and Implementing Redordkeeping Systems, visando ao delineamento do domínio organizacional.
This thesis describes a method to find a part of online data in an offline
document. This method is able to find the offline document that belongs
to the online data from a set of offline documents, or vice versa. In order to
optimize the mapping between the online and the offline data, an optimal rotation
and resizing of the online data is calculated. This is useful since it produces
a better mapping between online and offline data, which makes several methods
that are only applicable for online data available for offline data, and vice
versa.
Results show that this method can be used for finding the offline document that
belongs to certain online data, since it succeeded in 98.07% of the cases for
the used dataset. The results also show that computing the optimal rotation and
resize factor significantly improves the mapping between online and offline
data. This improvement is 6.56% for the used dataset.
Slides from Portland Machine Learning meetup, April 13th.
Abstract: You've heard all the cool tech companies are using them, but what are Convolutional Neural Networks (CNNs) good for and what is convolution anyway? For that matter, what is a Neural Network? This talk will include a look at some applications of CNNs, an explanation of how CNNs work, and what the different layers in a CNN do. There's no explicit background required so if you have no idea what a neural network is that's ok.
In this report I will compare two different information system methodologies. I would talk about SSADM (Structure System Analysis and Design Methodologies) and XP (Extreme Programing).
From Model-based to Model and Simulation-based Systems ArchitecturesObeo
Achieving quality engineering through descriptive and analytical models
Systems architecture design is a key activity that affect the
overall systems engineering cost. It is hence fundamental
to ensure that the system architecture reaches a proper quality.
In this paper, we leverage on MBSE approaches and complement them
with simulation techniques, as a prom-ising way to improve the quality of the system architecture definition, and to come up with inno-vative solutions while securing the systems engineering process.
We cannot determine the Value of something unless we know it’s cost. But determining Value requires have tangible measures to be compared against the cost. In the Systems Engineering Paradigm, these are the Measures of Effectiveness, Measures of Performance, Technical Performance Measures, and Key Performance Parameters
Tese de doutorado em CIência da Informação Análise de dominio Organizacional ...Célia Dias
A presente pesquisa tem como objeto de estudo formulários da Metodologia DIRKS – Designing and Implementing Redordkeeping Systems, visando ao delineamento do domínio organizacional.
Informetrcs (2010)課堂導讀: Chapter 3
De Bellis, N. (2009). Bibliometrics and citation analysis: from the Science citation index to cybermetrics: Scarecrow.
1. 認知工作分析
Cognitive Work Analysis
Fidel, R., et al. "A Multidimensional Approach to the Study of
Human Information Interaction: A Case Study of Collaborative
Information Retrieval." Journal of the American Society for
Information Science and Technology 55.11 (2004): 939-53.
2011-03-22
陳啟亮 臺灣師範大學圖書資訊學研究所 博士班
Charles Chen (xxc.chen@gmail.com)
2. The authors
Raya Fidel
Center for Human-Information Interaction,
The Information School,
University of Washington, Seattle
Annelise Mark Pejtersen
Bryan Cleal
Cognitive Systems Engineering Center, Systems Analysis Department,
Risoe National Laboratory
Harry Bruce
The Information School,
University of Washington, Seattle
3. Approaches to the Study of HII
Pettigrew, et al. (2001) Fidel, R., et al. (2004)
• 認知取向 • 心理取向
Cognitive approaches The Psychological Approach
• 社會取向 • 社會取向
Social approaches The Social Approach
• 多元取向 • 多元取向
Multifaceted approaches Multidimensional Approaches
Pettigrew, K. E., Fidel, R., &Bruce, H. (2001). Conceptual frameworks in information behavior. in Annual Review of Information Science and
Technology (ARIST), 35, 43-78.
Fidel, R., et al. "A Multidimensional Approach to the Study of Human Information Interaction: A Case Study of Collaborative Information
Retrieval." Journal of the American Society for Information Science and Technology 55.11 (2004): 939-53. Print.
8. Control room in nuclear power plant. USA (2000)
http://www.our-energy.com/nuclear_technology_is_mature_and_safe.html
9. 1. Chernobyl: Nuclear Disaster in Ukraine
(1986, April)
http://www.life.com/gallery/57691/nuclear-
disasters#index/4
2.3.4. Russian Nuclear Power Plant Control
Room (1990)
http://hackedgadgets.com/2009/05/03/russian-nuclear-
power-plant-control-room/
5. After Chernobyl (2009)
http://www.corbisimages.com/Enlargement/Enlargement.a
spx?id=42-26910515
1 5
2 3 4
10. Cognitive Work Analysis
• 認知工作分析實際上與認知科學並沒有直接關係,根據
Rasmussen(1994),其理論依據來自於:
• 系統化思維(General System Thinking)
• 適應控制系統(Adaptive Control Systems)
• Gibson的環境心理學(Ecological Psychology)
• 重點:限制(constraint) 與 適應(adaptive)
• CWA 認為,在與工作相關的活動中進行資訊互動的人,是一
行動者/演員(actor) ,而非一般資訊系統所稱的使用者(user)
11. Cognitive Work Analysis: History
1960s 1990 1994
Rasmussen work in Riso Rasmussen, Pejtersen & Schmidt Rasmussen, Pejtersen & Goodstein
Taxonomy for cognitive work Cognitive systems engineering
analysis
CWA 認為,在與工作相關的活動中進行資
訊互動的人,是一「行動者/演員(actor)」,
而非一般資訊系統所稱的「使用者(user)」
理論基礎是:
系統化思維(general system thinking)
適應控制系統(adaptive control
systems)
Gibson的環境心理學(Ecological
Psychology);
以及各種不同工作領域中支援系統開發
的實地研究。
12. Cognitive Work Analysis: History
1960s 1990 1994
Rasmussen work in Riso Rasmussen, Pejtersen & Schmidt Rasmussen, Pejtersen & Goodstein
Taxonomy for cognitive work Cognitive systems engineering
analysis
1990s
Albrechtsen, H, Domain Analysis
LIS & Knowledge Organzation
Mark Pejtersen, A.
2004
2003
Fidel, R., & Pejtersen, A. M. From
Albrechtsen, H., & Pejtersen, A. M.
information behaviour
Cognitive work analysis and
research to the design of
work centered design of
information systems: The
classification schemes.
CWA framework
1998
Sanderson, P
Cognitive work analysis and
the analysis, design, and
1999
evaluation of HCI systems
HCI Kim J Vicente Cognitive Work
Analysis: Toward Safe,
Productive, and Healthy
Computer-Based Work
Work Analysis
13. Cognitive Work Analysis: onion framework
工作領域分析
(WDA)
手段-目的結構 活動分析(AA)
任務情境
實際工作 工作領域
環境
決策判斷
心智策略
組織分析
分工與社會組織
行為者的
資源與價值
分析人格特徵
人因工程分析
知覺行動能力
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
14. Cognitive Work Analysis: onion framework
環境
• 有什麼因素在
組織外部影響?
實際工作
環境
行為者
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
15. Cognitive Work Analysis: onion framework
工作領域
工作領域分析 • 工作領域中有
(WDA) 哪些目標?
手段-目的結構
• 限制?
實際工作
環境
• 優先順序?
• 功能?
• 物體上的程序?
• 利用哪些工具?
行為者
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
16. Cognitive Work Analysis: onion framework
組織分析
工作領域分析 • 團隊如何分工?
(WDA) • 使用哪些標準?
手段-目的結構
• 組織的本質?
實際工作
環境
科層制、民主
制、無秩序?
• 組織性的價值
為何?
組織分析
分工與社會組織
行為者
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
17. Cognitive Work Analysis: onion framework
任務分析
工作領域分析 • 任務是什麼(例
(WDA)
活動分析(AA)
如,設計導覽
手段-目的結構
任務情境 功能)?
實際工作
環境
工作領域 • 產生資訊問題
的任務目標為
何?
• 其限制?
• 涉及的功能?
• 所使用的工具?
組織分析
分工與社會組織
行為者
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
18. Cognitive Work Analysis: onion framework
決策工作分析
工作領域分析 • 做了哪些決策
(WDA)
活動分析(AA)
(例,選擇哪種
手段-目的結構
任務情境 導覽模式)?
實際工作
環境
工作領域 • 決策需要哪些
資訊?
• 哪些資訊資源
決策判斷 是有用?
組織分析
分工與社會組織
行為者
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
19. Cognitive Work Analysis: onion framework
策略工作分析
工作領域分析 • 哪些策略是可
(WDA)
活動分析(AA)
能的(例,瀏覽、
手段-目的結構
任務情境 分析)?
實際工作
環境
工作領域 • 行動者偏好哪
種策略?
• 需要哪些資訊?
決策判斷 • 偏好哪些資訊
心智策略
來源?
組織分析
分工與社會組織
行為者
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
20. Cognitive Work Analysis: onion framework
個人資源與價值
工作領域分析 • 行為者受過哪
(WDA)
活動分析(AA)
些正規訓練?
手段-目的結構
任務情境 • 是哪種專家?
實際工作
環境
工作領域 • 有哪些主題領
域或工作領域
的經驗?
決策判斷 • 個人的優先順
心智策略
序為何?
• 個人的價值觀
為何?
組織分析
分工與社會組織
行為者的
資源與價值
分析人格特徵
人因工程分析
知覺行動能力
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis framework. Information
Research, 10(1), 10-11.
21. Cognitive Work Analysis: 手段-目的分析
Means-Ends Analysis
目的、限制
優先性 (價值觀)
一般功能
物理程序
物理資源、工具
Reference:
Fidel, R., & Pejtersen, A. M. (2004). From information behaviour research to the design of information systems: The cognitive work analysis
framework. Information Research, 10(1), 10-11.
22. Cognitive Work Analysis: 工作領域分析
Work Domain Analysis, WDA
書後索引工作的領域分析
Reference:
陳啟亮(2008)。書後索引之編製行為研究。未出版之碩士論文,國立臺灣師範大學圖書資訊學研究所。
25. Research: Collaborative information retrieval
Case: Microsoft Design Team:
• a single case of making navigation function design. (Help
and Support Center, HSC)
Data collecting method
• naturalistic field study: interview, observation, content
analysis (email, documents)
26. Microsoft – Product Support Service
Internet Archive. http://support.microsoft.com 2007-07-18
27. Microsoft HSC Design Team: Environments
• Microsoft Corporation
• Products & Projects: Help & Support Center
• Project division:
Test, Development, Program Management, and Design
• Design Team:
Product Designer, Visual Designer, Usability Engineer,
Project Manager
• Task: The Case of Navigation Design Work
Environment
Work Domain
Analysis
Task
Analysis
Organizational
Analysis
28. Actors: a product designer & his colleagues
• Neil, the product design lead
• Resources: colleagues
• Artifacts: to-do list, prototype, previous system
• Task Goals & Priorities:
provide a high-quality design,
fit user behavior and user preferences
• Environment constraint:
Work
Environment
Work Domain
limited time, Analysis
Task
ensure coordinated with other teams
Analysis
Organizational
Analysis Strategy
• Strategies: Neil
find used navigation model
29. Actors: Decision Ladder
• Spent all time between analysis - evaluation
• Decision making did not share with his colleagues
• 3rd phase (planning) did not involve CIR
Work
Environment
Work Domain
Analysis
Task
Analysis
Decision
Organizational
Analysis Strategy
Neil
Notice:
CIR(Collaborative Information Retrieval) doesn’t include
action-taking behavior (?)
30. CIR: Motives: Cognitive
• Inexperience: Novice to
Microsoft (need personal network,
Work
previous system, interpretations)
• Value: The quality of
Environment
design decision making
Work Domain
Analysis
Task Analysis (need references, informal feedback to
their ideas, and opinions)
Decision
Strategy
• Knowledge: lack of web
Organizational
design tacit knowledge
Analysis Neil (need Nail & Lily’s knowledge &
Product
designer
interpretation)
• Drawback-of-CIR:
information overload
31. CIR: Organization of the Team’s Work
Define Organizational Task:
• Organizational Constraint
• Actor’s responsibility
Work
Environment
Work Domain
Analysis • Collaboration with others
Task Analysis
Decision
Microsoft Culture
Strategy
• the boundaries of the task
Organizational
Analysis Neil
Product
responsibility are not
designer
always clear
• Not documented
• Rely on their own personal
network
32. CIR: Task and Decision
Task: (strategy & decision)
• Search for design
Work
Environment
constraints (access sources)
Work Domain
Analysis
• decision making of
Task
Analysis
navigation design (no formal
design guide)
Decision
Strategy
• Prepare for
Organizational
communication with
Analysis Neil
Product
others (quality)
designer
• Collaborative creative
(quality)
• Drawback-of-CIR:
no creation & innovation
33. Challenges to the CIR process
Actors 對行為者而言,CIR的挑戰是:
• 需要花時間討論
Spend time in discussions
• 不同行為者,在CIR過程中有不同的立場。
Difference actors have different stakes in the process, or have different priorities
• CIR中成員的理解不同
The understanding of problems might various
• 新手需邀請專家參與
Notice involve other expert actors
• 討論或協作中會發生資訊過載
Information overload
34. Discussion
Multiple dimensions
Such interdependencies suggest that focusing on a single
dimension may not only provide a partial understanding, but
might also be misleading.
Contributions to the Study of CIR
Notice:
The goals of CWA research?
What the difference between CWA & IB research?