This document summarizes engineering applications of artificial immune systems (AIS). It begins with an overview of engineering problems and their challenges, including examples like non-linear control, pattern recognition, autonomous navigation, and anomaly detection. It then provides a brief survey of AIS applications in the literature, covering areas such as pattern recognition, search and optimization, robotics, and control. Finally, it discusses examples of AIS applications from the authors' own research labs, focusing on search and optimization, pattern recognition, machine learning, robotics, and bioinformatics. Specific algorithms discussed include CLONALG for multimodal search and combinatorial optimization, and opt-aiNet for multimodal search in dynamic environments.
Conjunto de slides com algumas notas relevantes sobre liderança. Material utilizado nos cursos de Empreendedorismo da Faculdade de Computação e Informática da Universidade Presbiteriana Mackenzie.
Slides do painel "The E-Commerce Checkout Análise das Influências para Conversão nas Telas de Checkout", realizado no Congresso Search & Vendas do projeto E-commerce Brasil, 15/03, São Paulo.
2012: Natural Computing - The Grand Challenges and Two Case StudiesLeandro de Castro
Talk presented at BRACIS 2012. A discussion about the Grand Challenges in Natural Computing Research and two real-world applications, one in Social Media Mining and another in E-Commerce.
Conjunto completo de slides usado na disciplina Computação Natural do Programa de Pós-Graduação em Engenharia Elétrica da Universidade Mackenzie. Fonte de referência: L. N. de Castro, "Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications", CRC Press, 2006.
SBRN 2010 (Simpósio Brasileiro de Redes Neurais). Lançamento do livro intitulado "Computação Natural: Uma Jornada Ilustrada", Ed. Livraria da Física, Autor: Leandro Nunes de Castro
Slides do curso completo de Introdução à Mineração de Dados. Esse material foi inicialmente gerado em 2008 para o primeiro curso sobre o assunto no Programa de Pós-Graduação em Engenharia Elétrica do Mackenzie e vem sendo continuamente atualizado e melhorado para atender às demandas do curso, do aluno e as rápidas mudanças do mercado. Última atualização em 2016.
Understanding the Role of Thermography in Energy Auditing: Current Practices...Matthew Louis Mauriello
Our talk at CHI2015 in Seoul, South Korea. Find more information at: http://www.cs.umd.edu/~mattm/
YouTube: https://www.youtube.com/watch?v=XzCuvr8QB4U
Makeability Lab: http://www.cs.umd.edu/~jonf/
ABSTRACT
The building sector accounts for 41% of primary energy consumption in the US, contributing an increasing portion of the country's carbon dioxide emissions. With recent sensor improvements and falling costs, auditors are increasingly using thermography-infrared (IR) cameras-to detect thermal defects and analyze building efficiency. Research in automated thermography has grown commensurately, aimed at reducing manual labor and improving thermal models. Though promising, we could find no prior work exploring the professional auditor's perspectives of thermography or reactions to emerging automation. To address this gap, we present results from two studies: a semi-structured interview with 10 professional energy auditors, which includes design probes of five automated thermography scenarios, and an observational case study of a residential audit. We report on common perspectives, concerns, and benefits related to thermography and summarize reactions to our automated scenarios. Our findings have implications for thermography tool designers as well as researchers working on automated solutions in robotics, computer science, and engineering.
Conjunto de slides com algumas notas relevantes sobre liderança. Material utilizado nos cursos de Empreendedorismo da Faculdade de Computação e Informática da Universidade Presbiteriana Mackenzie.
Slides do painel "The E-Commerce Checkout Análise das Influências para Conversão nas Telas de Checkout", realizado no Congresso Search & Vendas do projeto E-commerce Brasil, 15/03, São Paulo.
2012: Natural Computing - The Grand Challenges and Two Case StudiesLeandro de Castro
Talk presented at BRACIS 2012. A discussion about the Grand Challenges in Natural Computing Research and two real-world applications, one in Social Media Mining and another in E-Commerce.
Conjunto completo de slides usado na disciplina Computação Natural do Programa de Pós-Graduação em Engenharia Elétrica da Universidade Mackenzie. Fonte de referência: L. N. de Castro, "Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications", CRC Press, 2006.
SBRN 2010 (Simpósio Brasileiro de Redes Neurais). Lançamento do livro intitulado "Computação Natural: Uma Jornada Ilustrada", Ed. Livraria da Física, Autor: Leandro Nunes de Castro
Slides do curso completo de Introdução à Mineração de Dados. Esse material foi inicialmente gerado em 2008 para o primeiro curso sobre o assunto no Programa de Pós-Graduação em Engenharia Elétrica do Mackenzie e vem sendo continuamente atualizado e melhorado para atender às demandas do curso, do aluno e as rápidas mudanças do mercado. Última atualização em 2016.
Understanding the Role of Thermography in Energy Auditing: Current Practices...Matthew Louis Mauriello
Our talk at CHI2015 in Seoul, South Korea. Find more information at: http://www.cs.umd.edu/~mattm/
YouTube: https://www.youtube.com/watch?v=XzCuvr8QB4U
Makeability Lab: http://www.cs.umd.edu/~jonf/
ABSTRACT
The building sector accounts for 41% of primary energy consumption in the US, contributing an increasing portion of the country's carbon dioxide emissions. With recent sensor improvements and falling costs, auditors are increasingly using thermography-infrared (IR) cameras-to detect thermal defects and analyze building efficiency. Research in automated thermography has grown commensurately, aimed at reducing manual labor and improving thermal models. Though promising, we could find no prior work exploring the professional auditor's perspectives of thermography or reactions to emerging automation. To address this gap, we present results from two studies: a semi-structured interview with 10 professional energy auditors, which includes design probes of five automated thermography scenarios, and an observational case study of a residential audit. We report on common perspectives, concerns, and benefits related to thermography and summarize reactions to our automated scenarios. Our findings have implications for thermography tool designers as well as researchers working on automated solutions in robotics, computer science, and engineering.
Retrospective and Trends in Requirements Engineering for Embedded Systems: A ...Tarcísio Couto
In the embedded systems (ES) area, more than 50% of problems occur at system delivery and are related to misconceptions in capturing requirements. Also, requirements engineering (RE) is crucial to meet time, cost, and quality goals. An important step to improve the RE approaches for ES is to gain a detailed understanding of the retrospective and trends presented by the literature. We have conducted a systematic literature review to gain an in-depth understanding of trends and needs concerning RE research. We report on the main results of our study related to three research questions: what requirements should be considered during ES development? what are the RE contributions for ES? and what challenges/problems are identied in the research literature to RE for ES? Based on the results of the study, we draw conclusions for future RE research.
Air monitoring sensors and advanced analytics in exposure assessmentDrew Hill
https://doi.org/10.6084/m9.figshare.12354866.v2
We are in the middle of a movement in environmental sensors that is taking the world by storm— Californian governments and public health practitioners, in particular, are leading the nation in exploring and implementing environmental sensors in the production of highly granular, realtime air quality information. As this movement matures, we are seeing improved understanding of ambient exposures and insights that are truly actionable — for example informing community emissions reduction plans under the recent Assembly Bill 617. This innovation in air quality sensor science can be leveraged to improve measurements in the industrial and occupational spaces. This movement has also lead to innovations in analysis methods that facilitate exposure insights not feasible with standard filter, adsorbent, and general integrated samples. This presentation discusses recent advancements in these spaces and offer brief examples of their implementation and potential applicability toward the industrial and occupational hygiene spaces.
present the concept of Lab-Forming Fields (LFF) and Field-Forming Labs (FFL). LFF is to transform real service fields into lab-like places for bringing research methodologies in laboratories to real fields with IoT. FFL is to transform laboratories into real-field-like places for getting subjects’ behavior and experimental results closer and closer to the ones which are supposed to be obtained in the real service fields with VR. Next, I introduce indoor positioning technologies such as PDR (Pedestrian Dead Reckoning) as a key technology for human behavior sensing. Then I conclude this talk by briefly reporting on case studies of service kaizen in a restaurant and a warehouse respectively.
Improvement in the process of Production Planning Applying the Simplex Methodijtsrd
The manufacture of metal-mechanical parts is very important in the industrial field. Due to the increasing demand in the market, the company under study decided to develop the application of this method, to be able to know the production planning of its products. This study is limited to two products with the most demand currently product A and product. A time study with a 95 confidence interval was also performed to determine the average processing time for each product, as well as the limits of each product. The result of the present investigation was to know the planning of the production of the two products with the most demand González Torres Arturo | GarcÃa Araiza Oscar S | RamÃrez Castañeda Armando I | GarcÃa Parada Ricardo Y | GarcÃa González Juan M "Improvement in the process of Production Planning Applying the Simplex Method" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | 2nd International Congress of Engineering , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd5820.pdf
http://www.ijtsrd.com/engineering/other/5820/improvement-in-the-process-of-production-planning-applying-the-simplex-method/gonzález-torres-arturo
Listing of Intellectual work of patanjali kashyap , mainly contains , name, details and reference of papers , presentations , patents , public speaking
Architectural Design of a Clinical Decision Support System for Clinical Triag...Luis Felipe Tabares Pérez
Clinical triage aims to prioritize patient treatments based on their health condition, in emergency departments. Most of its concerns are related to its effectiveness due to the short timeframes that health staff have for classifying patients and the lack of valuable, timely, and pertinent information available. This paper aims to analyze and discuss a feasible architectural approach to implement a clinical decision support system for clinical triage by adapting proposals from other scenarios.
Commercialization Options for a set of Wireless PatentsShanmukha S. Potti
Given a portfolio of patents, this project utilizes two approaches of study – one is analysis of the portfolio as a whole and the second is specific analysis limited to individual patent assets.
This process involves mining for crown jewels in a portfolio, using Patent Analytics.
Patent assets thus identified were mapped to a wireless value chain and an innovation value chain to determine preferred commercialization options.
Systematic Mapping Study on Software Engineering for Sustainability (SE4S) Henning Femmer
Background/Context : The ob jective of achieving higher sustainability in our lifestyles by information and communication technology has lead to a plethora of research activities in related fields. Consequently, Software Engineering for Sustainability (SE4S) has developed as an active area of research.
Objective/Aim: Although SE4S has gained much attention over the past few years and has resulted in a number of contributions, there is only one rigorous survey of the field. We would like to follow up on this systematic mapping study from 2012 with a more in-depth overview of the status of research, as most of the work has been conducted in the last 4 years.
Method: The applied method is a systematic mapping study through which we investigate which contributions were made over time, which software engineering knowledge areas are most explored, and which research type facets have been used, to distill a common understanding of the state-of-the-art in SE4S.
Results: We contribute an overview of current research topics and trends, and their distribution according to the research type facet and the application domains. Furthermore, we aggregate the topics into clusters and list proposed and used methods, frameworks, and tools.
Conclusion: The research map shows that impact currently is limited to few knowledge areas and there is need for a future roadmap to fill the gaps.
SensoDat: Simulation-based Sensor Dataset of Self-driving CarsChristian Birchler
Developing tools in the context of autonomous systems [22, 24 ], such as self-driving cars (SDCs), is time-consuming and costly since researchers and practitioners rely on expensive computing hardware and simulation software. We propose SensoDat, a dataset of 32,580 executed simulation-based SDC test cases generated with state-of-the-art test generators for SDCs. The dataset consists of trajectory logs and a variety of sensor data from the SDCs (e.g., rpm, wheel speed, brake thermals, transmission, etc.) represented as a time series. In total, SensoDat provides data from 81 different simulated sensors. Future research in the domain of SDCs does not necessarily depend on executing expensive test cases when using SensoDat. Furthermore, with the high amount and variety of sensor data, we think SensoDat can contribute to research, particularly for AI development, regression testing techniques for simulation-based SDC testing, flakiness in simulation, etc. Link to the dataset: https://doi.org/10.5281/zenodo.10307479
In a project Systems Engineering ensures the overall integrity of the design considering the space segment, the ground segment and the launch vehicle. Systems Engineering is an accepted practice in the space industry with an unstoppable growth and evolution because it brings a multi-disciplinary perspective that is critical to system product innovation, defect reduction and customer satisfaction. A systems engineer is a person who designs space missions and their vehicles by working together with engineers in the necessary disciplines. The technical leadership role of the systems engineer on a project is critical to the success of space projects driven by high safety and performance requirements, that is why demand is soaring for systems engineers in the space industries and government agencies worldwide ( including Spain). The session will help you to understand what makes an Effective Systems Engineer in terms of the expected competencies and the meaning of a Systems Engineering career path to a professional practitioner according to the world's leading organisations in the Space sector.
Similar to 2004: Engineering Applications of Artificial Immune Systems (20)
2021: An Illustrated Journey into Natural ComputingLeandro de Castro
Natural Computing is a subfield of Computer Science and Engineering focused on the interdisciplinarity between computing and nature, and involves the development of new algorithms inspired by nature, computational solutions for the synthesis of natural phenomena, and the use of new natural materials with which to compute. The area has a great success in applications such as optimization, data analytics, robotics, bioinformatics, and many others.
The goal of this book is to spread natural computing mainly to those who are unfamiliar with it or who have little access to this subject field, but who want to know more about what is being investigated in the area. All of this without necessarily entering the technicalities of the specialized scientific literature. The book almost invariably talks about consolidated results, proposals, tools and solutions, already implemented and operating somewhere on the planet, striving to maintain the accuracy of concepts without making them too complicated for readers and, at the same time, without trivializing them.
This volume is an updated translation of the book originally written in Portuguese and titled "Computação Natural: Uma Jornada Ilustrada", published by Livraria da Física in 2010. The main source of reference for both, Portuguese and English versions, is titled “Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications”, published by CRC Press in June 2006, from where its structure and some examples were taken, but with an illustrated and lighter presentation.
2019: LCoN - Centro de Excelência em Inteligência ArtificialLeandro de Castro
O Laboratório de Computação Natural e Aprendizagem de Máquina foi reconhecido como um Centro de Excelência em Inteligência Artificial pela Intel Semicondutores do Brasil entre os anos 2017 e 2018. Em fevereiro de 2019 completamos 10 anos de operação e celebramos essa conquista trazendo um novo conjunto de slides institucionais com uma breve descrição do que fazemos e nossos principais resultados.
2018: What did I learn about Innovation and Entrepreneurship in IsraelLeandro de Castro
These slides were prepared based on a mission I did to Israel from 18th to 22nd of March, 2018, organized by Anjos do Brasil, APEX Brasil and ABVCAP. The information presented here were collected from my own writtings during the many visits we made and some material presented in the visits (cited as appropriate).
This set of slides was presented at the 2018 Mission Israel in Tel Aviv, March 21st, as a contribution of my participation in the mission. The mission was organized by ABVCAP, Anjos do Brazil, ApexBrasil and Israel Trade & Investment Brazil, to whom I thank for the opportunity and great knowledge provided.
2017: The Many Faces of Artificial Intelligence: From AI to Big Data - A Hist...Leandro de Castro
This set of slides briefly reviews the history of artificial intelligence from its origins in the early 1950's to the new trend of Big Data. It goes from AI, passing to Machine Learning, Natural Computing and finally reaching Big Data.
2016: Fundamentos Matemáticos para Inteligência ArtificialLeandro de Castro
Esse arquivo contém um resumo de alguns conceitos matemáticos importantes para aqueles interessados em áreas como inteligência artificial, computação natural, heurística em pesquisa operacional e logística, mineração de dados, big data, e demais temas associados. O material inclui uma revisão de álgebra linear, teoria de grafos, probabilidade e resolução de problemas via métodos de busca.
2016: Introdução à Mineração de Dados: Conceitos Básicos, Algoritmos e Aplica...Leandro de Castro
Conjunto de slides desenvolvido como material de apoio disponível para uso por professores e alunos da disciplina Mineração de Dados, assim como demais interessados no tema. Apresenta de forma sucinta o conteúdo do livro e os principais conceitos da área.
Apostila sobre "Análise de Mercado e Plano de Marketing" apresentado no curso "Primeiros Passos em Empreendedorismo e Inovação Tecnológica" da INTEC-UEFS em maio de 2015.
Slides dos cursos de Empreendedorismo e Planejamento Estratégico do Bacharelado em Ciência da Computação e Sistemas de Informação da Universidade Mackenzie.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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The Art of the Pitch: WordPress Relationships and Sales
2004: Engineering Applications of Artificial Immune Systems
1. Engineering ApplicationsEngineering Applications
of Artificial Immuneof Artificial Immune
SystemsSystems
Leandro Nunes de Castro
Fernando José Von Zuben
lnunes@unisantos.br; vonzuben@dca.fee.unicamp.br
Natural Computing Laboratory / Catholic University of Santos
Wernher von Braun Center for Advanced Research
Laboratory for Bioinformatics and Bio-Inspired Computing / Unicamp
Financial Support: CNPq, FAPESP, FAEP
2. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune2
(Labs Involved in this
Research)
Catholic University of Santos
Wernher von Braun Center
for Advanced Research
Laboratory of Bioinformatics
and Bioinspired Computing
Natural Computing Lab
3. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune3
Topics
Engineering Problems and Their
Challenges
Examples of Engineering Problems
Engineering Applications of AIS: Brief
Survey from the Literature
Examples of Engineering Applications of
AIS from our Research Labs
Discussion
5. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune5
Engineering Problems
Real-World Problems
An imprecise and incomplete classification:
Pattern Recognition and Classification
Machine Learning
Data Mining
Search and Optimization
Robotics
Control
Industrial Applications
6. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune6
Engineering Problems
Some Common Features:
Difficulty in modelling
Poorly defined
Dynamic environments
Large number of variables
Missing or noisy variables (attributes)
Highly nonlinear
Difficulty in finding derivatives
Combinatorial solutions (NP-Complete/NP-Hard)
14. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune14
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification /
Machine Learning / Data Mining:
Spectra Recognition
Dasgupta et al., 1999
Surveillance of Infectious Diseases
Tarakanov et al., 2000
Medical Data Analysis
Carter, 2000
Virus Detection and Elimination
Kephart, 1994
Somayaji et al., 1997
Okamoto & Ishida, 1999
Lamont et al., 1999
15. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune15
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification /
Machine Learning / Data Mining:
Computer and Network Security
Kephart, 1994
Hedberg, 1996
Kim & Bentley, 1999a,b
Dasgupta, 1999
Gu et al., 2000
Hofmeyr & Forrest, 2000
Skormin et al., 2001
Anchor et al., 2002
Dasgupta & González, 2002
Wang & Hirsbrunner, 2002
de Paula et al., 2004
16. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune16
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification /
Machine Learning / Data Mining:
Time Series Data
Dasgupta & Forrest, 1996
Image Processing and Inspection
Aisu & Mizutani, 1996
McCoy & Devarajan, 1997
Sathyanath & Sahin, 2001
Bendiab et al., 2003
Web Mining
Lee et al., 2003
Secker et al., 2003
Oda & White, 2003
17. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune17
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification / Machine Learning /
Data Mining:
Fault (Anomaly) Detection
Ishida, 1990
Kayama et al., 1995
Xanthakis et al., 1996
D’haeseleer et al., 1996
Bradley & Tyrrell, 2000
Shulin et al., 2002
Taylor & Corne, 2003
González et al., 2003
Esponda et al., 2003
Kaers et al., 2003
Araujo et al., 2003
Branco et al., 2003
18. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune18
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification /
Machine Learning / Data Mining:
Machine Learning
Watkins, 2001
Hunt & Cooke, 1996
Hightower et al., 1996
Potter & de Jong, 1998
Bersini, 1999
Nagano & Yonezawa, 1999
Timmis & Neal, 2001
de Castro & Von Zuben, 2001
Watkins et al., 2004
19. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune19
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification /
Machine Learning / Data Mining:
Associative Memory
Gibert & Routen, 1994
Abbattista et al., 1996
Recommender System
Cayzer & Aickelin, 2004
Inductive Problem Solving
Slavov & Nikolaev, 1998
Bankruptcy Prediction
Cheh, 2002
20. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune20
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification /
Machine Learning / Data Mining:
Clustering/Classification
Nicosia et al., 2001
Timmis, 2001
de Castro & Timmis, 2002a
Neal, 2002
Zhao & Huang, 2002
Greensmith & Cayzer, 2003
Ceong et al., 2003
Di & Xuefeng, 2003
Nasaroui et al., 2003
21. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune21
AIS: Brief Survey from the
Literature
Pattern Recognition and Classification /
Machine Learning / Data Mining:
Bioinformatics
Recognition of promoter sequences: Cooke & Hunt,
1995
Protein structure prediction: Michaud et al., 2001
Spectra classification: Lamont et al., 2004
Gene expression data analysis: Bezerra & de Castro,
2003; Ando & Iba, 2003
Analysis of biological systems: Roy et al., 2002
Bioarrays: Tarakanov et al., 2002
22. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune22
AIS: Brief Survey from the
Literature
Search and Optimization:
Numerical Function Optimization
Mori et al., 1993
Bersini & Varela, 1990
Chun et al., 1998
Huang, 2000
Gaspar & Hirsbrunner, 2002
de Castro & Von Zuben, 2002
de Castro & Timmis, 2002b
Hong & Zong-Yuan, 2002
Walker & Garrett, 2003
23. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune23
AIS: Brief Survey from the
Literature
Search and Optimization:
Constrained Optimization
Hajela & Yoo, 1999
Inventory Optimization
Joshi, 1995
Time Dependent Optimization
Gaspar & Collard, 2000
24. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune24
AIS: Brief Survey from the
Literature
Search and Optimization:
Combinatorial Optimization
Mori et al., 1997, 1998
Endoh et al., 1998
Toma et al., 1999
Hart & Ross, 1999
King et al., 2001
Cui et al., 2001
Costa et al., 2002
Coello Coello et al., 2003
Cutello et al., 2003
Koko et al., 2003
25. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune25
AIS: Brief Survey from the
Literature
Robotics:
Autonomous Navigation
Watanabe et al., 1999
Michelan & Von Zuben, 2002
Hart et al., 2003
Vargas et al., 2003
Canham et al., 2003
Collective Behavior
Mitsumoto et al., 1996
Lee & Sim, 1997
Walking Robots
Ishiguro et al., 1998
26. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune26
AIS: Brief Survey from the
Literature
Control:
Identification, Synthesis and Adaptive Control
Bersini, 1991
Ishida & Adachi, 1996
Krishnakumar & Neidhoefer, 1999
Ding & Ren, 2000
Kim, 2001
Lau & Wong, 2003
Sequential Control
Ootsuki & Sekiguchi, 1999
Feedback Control
Takahashi & Yamada, 1997
27. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune27
The references from this brief and incomplete
survey can be found at:
www.dca.fee.unicamp.br/~lnunes/AIS.html
An extensive and constantly updated bibliography
on AIS can be found at:
http://ais.cs.memphis.edu/papers/ais_bibliography.pdf
AIS: Brief Survey from the
Literature
31. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune31
Search and Optimization
Multimodal Search
CLONALG (de Castro & Von Zuben, 2002)
Pr
M
Select
Clone
Pn
C
C*
(1)
(2)
(3)
(5)
Re-select
Nd
(6)
Maturate
(4)
32. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune32
Search and Optimization
Multimodal Search
CLONALG (de Castro & Von Zuben, 2002)
CLONALG Standard GA
34. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune34
Search and Optimization
Combinatorial Search
Copt-aiNet (de Sousa et al., 2004)
35. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune35
Search and Optimization
CLONALG (de Castro & Von Zuben, 2002)
DEMO 1: CLONALGDEMO 1: CLONALG
36. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune36
Search and Optimization
Multimodal Search
opt-aiNet (de Castro & Timmis, 2002b)
The algorithm for opt-aiNet is an adaptation of a
discrete artificial immune network usually applied
in data analysis
Features of opt-aiNet:
population size dynamically adjustable
exploitation and exploration of the search-space
capability of locating multiple optima
automatic stopping criterion
37. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune37
Search and Optimization
Multimodal Search
opt-aiNet (de Castro & Timmis, 2002b)
1. Initialize population (initial number not relevant)
2. While not [constant memory population], do
2.1 Calculate fitness and generate clones for each network cell.
2.2 Mutate clones proportionally to fitness and determine the fitness again.
2.3 Calculate the average fitness.
2.4 If average fitness does not vary, then continue. Else, return to step 2.1
2.5 Calculate the affinity among cells and suppress all but one whose affinities
are less than the suppression threshold σs and determine the number of
network cells after suppression.
2.6 Introduce a percentage of randomly generated cells and return to step 2.
3. EndWhile
38. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune38
Search and Optimization
Multimodal Search
opt-aiNet (de Castro & Timmis, 2002b)
39. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune39
Search and Optimization
Communications Engineering
Search for the optimal Wiener equalizer
opt-aiNet (Attux et al., 2003)
Optimal Wiener Equalizer
y(n) = wT
.x(n)
JW
= E{[s(n-d) – y(n)]2
}
CHANNEL EQUALIZER
s(n) x(n) y(n)
40. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune40
Search and Optimization
Optimal Wiener Equalizer
The Constant Modulus (CM) criterion is used for
blind equalization
To find the CM global optimum is equivalent to
determining the optimal Wiener solution (best
equalizer)
CM results in a multi-modal problem
JCM = E{[R2 - |y(n)|2
]2
}
[ ]
[ ]2
4
2
)(
)(
nsE
nsE
R =
41. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune41
Search and Optimization
Optimal Wiener Equalizer via CM Search
Sample performance
HC1 = 1 + 0.4z-1
+ 0.9z-2
+ 1.4z-3
42. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune42
Search and Optimization
opt-aiNet (de Castro & Timmis, 2002b)
DEMO 2: opt-aiNetDEMO 2: opt-aiNet
43. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune43
Pattern Recognition
Classification and Clustering
CLONALG (de Castro & Von Zuben, 2002)
(a) Input patterns
(b) 0 generations
(c) 50 generations
(d) 100 generations
(e) 200 generations
44. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune44
Pattern Recognition
Classification and Clustering
aiNet (de Castro & Von Zuben, 2001)
Definition:
aiNet is an edge-weighted graph, not necessarily fully
connected, composed of a set of nodes and sets of node
pairs with a weight assigned specified to each connected
edge.
Features:
knowledge distributed among cells
competitive learning (unsupervised)
constructive model with pruning phases
generation and maintenance of diversity
52. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune52
Pattern Recognition
The Immune Response of aiNet
0 50 100 150 200 250
10
1
10
2
10
3
10
4
Primary, Secondary and Cross-Reactive Immune Responses
Iteration
AntibodyConcentration
Ag1 Ag1, Ag11, Ag2
Responses to Ag1
Response
to Ag2
Response
to Ag11
53. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune53
Pattern Recognition
aiNet (de Castro & Von Zuben, 2001)
DEMO 3: aiNetDEMO 3: aiNet
54. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune54
Pattern Recognition
Detection of Buffer Overflow Attacks
ADENOIDS (de Paula et al., 2004)
An ID framework inspired by the architecture of
the immune system
Prototype of an IDS based on the proposed
framework
Elaborates on some ideas from Aickelin et al.,
2002 about the Danger Theory as a missing link
for AIS
55. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune55
Pattern Recognition
Danger Theory (Matzinger, 2002)
56. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune56
Pattern Recognition
Detection of Buffer Overflow Attacks
Desirable features based on the immune system
(danger theory)
Automated intrusion recovery
Attack signature extraction
Potential to improve behavior-based detection
57. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune57
Pattern Recognition
Framework for Intrusion Detection
58. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune58
Machine Learning
Neural Network Initialization
SAND (de Castro & Von Zuben, 2001a)
Initial neural network (NN) weights:
learning speed
generalization performance
Correlation: initial set of weights and initial
repertoire of immune cells and molecules
SAND: a Simulated ANnealing model to
increase population Diversity
59. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune59
Machine Learning
Neural Network Initialization
Affinity measure:
Proposed cost (energy) function:
∑
=
−=
L
i
ii yxED
1
2
)(
∑
=
=
N
i
i
N 1
1
II
( ) 2/1
IIT
R =
)1(100(%) RE −×=
Average unit vector
Resultant vector (distance from the
origin of the coordinate system)
Percentage energy
60. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune60
Machine Learning
Neural Network Initialization
Ab → weight vector
Diverse antibodies in ℜL
→ neurons with well
distributed weight vectors in ℜL
SAND is applied separately to each network layer
The vectors (Ab) have unitary norms and can be
normalized to avoid neuron saturation
62. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune62
Machine Learning
RBF Neural Network Center Selection
de Castro & Von Zuben, 2001
The performance of the RBF neural network
depends on the number, positions and
dispersions of the basis functions composing
the network hidden layer
Traditional methods:
randomly choose input vectors from the training
data set;
vectors obtained from unsupervised clustering
algorithms;
vectors obtained by supervised learning schemes.
63. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune63
Machine Learning
RBF Neural Network Center Selection
Solution based on aiNet
65. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune65
Machine Learning
RBF Neural Network Center Selection
-0.5 0 0.5 1 1.5 2 2.5
-0.5
0
0.5
1
1.5
2
2.5
ICS
Iris data set
Best performance
66. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune66
Machine Learning
Boolean Neural Network (ABNET)
de Castro et al., 2003
Main Features:
clustering, or grouping of similar patterns
capability of solving binary tasks
growing learning with pruning phases
Main loop of the algorithm
Choose randomly an antigen (pattern)
Determine the cell Abk with highest affinity
Update the weight vector of this cell
Increase the concentration level (τj) of this cell
Attribute va = k
67. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune67
Machine Learning
ABNET
Ab population
Ab re-selection
Clone Death
Affinity maturation
Most stimulated cell Non-stimulated cell
Ab selection
Antigenic stimuli
Neurons (k)
Competition
Split Prune
Weight
update
Winner Inactive neuron
Input patterns
69. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune69
Machine Learning
ABNET
Animals data set
ABNET(0-valuedweightsomitted)
Lion
Tiger
Wolf
Dog
Fox
Cat
Horse/Zebra
Cow
Owl/Hawk
Dove
Hen
Duck
Goose
Eagle
Mammals
Birds
70. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune70
Machine Learning
ABNET (de Castro et al., 2003)
DEMO 4: ABNETDEMO 4: ABNET
71. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune71
Robotics
Autonomous Navigation based on AIS
Michelan & Von Zuben, 2002
Based on the works:
Ishiguro et al., 1997; Farmer et al., 1986
72. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune72
Robotics
Autonomous Navigation based on AIS
Autonomous control system of a mobile robot
based on the immune network theory
Each network node corresponds to a specific
antibody and describes a particular control action
for the robot
The antigens are the current state of the robot
The network dynamics corresponds to the
variation of antibody concentration levels, which
change according to both mutual interaction of
antibody nodes and of antibodies and antigens
It is proposed an evolutionary mechanism to
determine the network configuration
73. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune73
Robotics
Autonomous Navigation based on AIS
74. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune74
Robotics
Autonomous Navigation based on AIS
Objectives of navigation
Antibody structure
garbageEcollisionEstepEtEtE −−−−= )1()(
75. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune75
Robotics
Autonomous Navigation based on AIS
Network example
76. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune76
Robotics
Autonomous Navigation based on AIS
Dynamics
)()()(
)(
11
takmtamtam
dt
tdA
i
N
k
iikik
N
j
jji
i
−+−= ∑∑
==
))(5.0exp(1
1
)1(
tA
ta
i
i
−+
=+
77. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune77
Robotics
Autonomous Navigation based on AIS
Immune network
Evolved network
78. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune78
Robotics
Autonomous Navigation based on AIS
Implementation on Khepera II®
: Vargas et al., 2003
80. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune80
Bioinformatics
Gene Expression Data Analysis
Bezerra & de Castro, 2003
de Sousa et al., 2004
The Problem
Clustering gene expression data
Recent approach in bioinformatics that surged with the
development of the DNA Microarrays
DNA Microarrays
Experimental technique that measures the expression level
of many genes simultaneously
A quantitative change in the scale of the experiments led to
a qualitative change in the analyses, where the genes may
be studied under a genome wide perspective
81. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune81
Bioinformatics
Gene Expression Data Analysis
Genes belonging to the same cluster may,
among other things
Share the same regulatory system
Have similar properties or functions
Code products that interact physically
Experimental Data
Gene expression data of the budding yeast
Saccharomyces cerevisiae, obtained from Eisen et
al. (1998)
Total of 2467 genes in 79 different conditions
82. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune82
Bioinformatics
Gene Expression Data Analysis
Clusters initially analyzed C, E, F and H (68
genes)
Results with full set: No natural cluster
85. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune85
Discussion
Vast number of applications available
Great potential for further applications and
developments
Some issues that still deserve investigation:
Formal aspects
Comparison (theoretical and empirical) with other
approaches
Loads of testing
Real benefits (Are they really useful?)
Danger theory
How far to stretch the metaphor?
86. ICARIS 2004 - Engineering Applications of AIS - Leandro Nune86
Discussion
Current trends in our labs
Improvements on the many versions of aiNet
Optimization on dynamic environments
Bioinformatics, mainly gene expression data analysis
Feedforward neural network training
Danger theory
Anomaly detection
This Tutorial on the Web:
www.dca.fee.unicamp.br/~lnunes/AIS.html