The document provides an overview of a project on vision-based place recognition for autonomous robots. It outlines the objective to localize a robot within an environment using visual cues. The methodology will improve on previous work by combining successful aspects and avoiding limitations. It will use adaptive multi-scale classification to differentiate environments based on discriminative features. Challenges include variations in object appearance and limited robot resources. Testing will use datasets from Bielefeld University and ImageCLEF, as well as a custom data acquisition tool.
LISA 2011 Keynote: The DevOps Transformationbenrockwood
This document is a presentation on the DevOps transformation from Ben Rockwood, Director of Systems Engineering at Joyent, Inc. It covers several key topics:
- What is DevOps and how it is a cultural and professional movement, not just a tool or title. It involves collaboration between development and operations.
- How DevOps breaks down silos and prioritizes quality across the entire value stream from requirements to development to software to operations and services.
- How cloud computing changed the IT paradigm and led to a rise in tools for infrastructure as code and automation.
- An overview of operations management concepts and a brief history of influential thinkers in operations management like Taylor, Ford, Deming, and
Toward Tractable AGI: Challenges for System Identification in Neural CircuitryRandal Koene
This is the presentation I gave at AGI-12 (also called the Winter Intelligence 2012 conferece) in Oxford, UK, on Dec.11, 2012. There is an AGI-12 proceedings paper that accompanies this talk. I will make that available on my publications page at http://randalkoene.com and I will put both together on the http://carboncopies.org page about this event. The video (recorded by Adam Ford) should also appear soon.
Abstract. Feasible and practical routes to Artificial General Intelligence involve short-cuts tailored to environments and challenges. A prime example of a system with built-in short-cuts is the human brain. Deriving from the brain the functioning system that implements intelligence and generality at the level of neurophysiology is interesting for many reasons, but also poses a set of specific challenges. Representations and models demand that we pick a constrained set of signals and behaviors of interest. The systematic and iterative process of model building involves what is known as System Identification, which is made feasible by decomposing the overall problem into a collection of smaller System Identification problems. There is a roadmap to tackle that includes structural scanning (a way to obtain the “connectome”) as well as new tools for functional recording. We examine the scale of the endeavor, and the many challenges that remain, as we consider specific approaches to System Identification in neural circuitry.
This document summarizes the research topics and laboratories of the School of Computer Science at FDU, led by Professor Xiangyang Xue. The school's research includes natural language processing, multimodal dialogue, image classification, and cross-media search. Key laboratories study intelligent media computing, databases, software engineering, and information security. Application areas mentioned include interactive TV, education/gaming robots, and assistant technologies for future smart homes.
This document proposes representing scientific workflows as first-class citizens called research objects. It presents a model for workflow research objects that aggregates all necessary elements to understand an investigation. These include experiments, annotations, results, datasets and provenance. Research objects are encoded using semantic technologies like RDF and follow standards such as the Object Exchange model. The lifecycle of research objects is also described.
Understanding Java Garbage Collection and What You Can Do About It: Gil Tenejaxconf
Garbage Collection is an integral part of application behavior on Java platforms, yet it is often misunderstood. As such, it is important for Java developers to understand the actions you can take in selecting and tuning collector mechanisms, as well as in your application architecture choices. In this presentation, Gil Tene (CTO, Azul Systems) reviews and classifies the various garbage collectors and collection techniques available in JVMs today. Following a quick overview of common garbage collection techniques including generational, parallel, stop-the-world, incremental, concurrent and mostly-concurrent algorithms, he defines terms and metrics common to all collectors. He classifies each major JVM collector's mechanisms and characteristics and discusses the tradeoffs involved in balancing requirements for responsiveness, throughput, space, and available memory across varying scale levels. Gil concludes with some pitfalls, common misconceptions, and "myths" around garbage collection behavior, as well as examples of how some good choices can result in impressive application behavior.
Ross Tredinnick - Rebecca J. Holz Research Data Management Talk 4/16/2013rossTnick
The Living Environments Laboratory (LEL) uses virtual reality to help researchers across many disciplines visualize and interact with their data. The lab houses a CAVE (Cave Automatic Virtual Environment), which is a room-sized immersive virtual reality theater. Researchers work with the LEL staff to convert their data into 3D scenarios that can be explored in the CAVE. The LEL is developing an online digital curation system to help organize, preserve, and provide access to the wide variety of 3D models, scripts, textures, and research data generated through these visualization projects. The goal is to advance fields like healthcare, education, and design through innovative uses of virtual reality.
LISA 2011 Keynote: The DevOps Transformationbenrockwood
This document is a presentation on the DevOps transformation from Ben Rockwood, Director of Systems Engineering at Joyent, Inc. It covers several key topics:
- What is DevOps and how it is a cultural and professional movement, not just a tool or title. It involves collaboration between development and operations.
- How DevOps breaks down silos and prioritizes quality across the entire value stream from requirements to development to software to operations and services.
- How cloud computing changed the IT paradigm and led to a rise in tools for infrastructure as code and automation.
- An overview of operations management concepts and a brief history of influential thinkers in operations management like Taylor, Ford, Deming, and
Toward Tractable AGI: Challenges for System Identification in Neural CircuitryRandal Koene
This is the presentation I gave at AGI-12 (also called the Winter Intelligence 2012 conferece) in Oxford, UK, on Dec.11, 2012. There is an AGI-12 proceedings paper that accompanies this talk. I will make that available on my publications page at http://randalkoene.com and I will put both together on the http://carboncopies.org page about this event. The video (recorded by Adam Ford) should also appear soon.
Abstract. Feasible and practical routes to Artificial General Intelligence involve short-cuts tailored to environments and challenges. A prime example of a system with built-in short-cuts is the human brain. Deriving from the brain the functioning system that implements intelligence and generality at the level of neurophysiology is interesting for many reasons, but also poses a set of specific challenges. Representations and models demand that we pick a constrained set of signals and behaviors of interest. The systematic and iterative process of model building involves what is known as System Identification, which is made feasible by decomposing the overall problem into a collection of smaller System Identification problems. There is a roadmap to tackle that includes structural scanning (a way to obtain the “connectome”) as well as new tools for functional recording. We examine the scale of the endeavor, and the many challenges that remain, as we consider specific approaches to System Identification in neural circuitry.
This document summarizes the research topics and laboratories of the School of Computer Science at FDU, led by Professor Xiangyang Xue. The school's research includes natural language processing, multimodal dialogue, image classification, and cross-media search. Key laboratories study intelligent media computing, databases, software engineering, and information security. Application areas mentioned include interactive TV, education/gaming robots, and assistant technologies for future smart homes.
This document proposes representing scientific workflows as first-class citizens called research objects. It presents a model for workflow research objects that aggregates all necessary elements to understand an investigation. These include experiments, annotations, results, datasets and provenance. Research objects are encoded using semantic technologies like RDF and follow standards such as the Object Exchange model. The lifecycle of research objects is also described.
Understanding Java Garbage Collection and What You Can Do About It: Gil Tenejaxconf
Garbage Collection is an integral part of application behavior on Java platforms, yet it is often misunderstood. As such, it is important for Java developers to understand the actions you can take in selecting and tuning collector mechanisms, as well as in your application architecture choices. In this presentation, Gil Tene (CTO, Azul Systems) reviews and classifies the various garbage collectors and collection techniques available in JVMs today. Following a quick overview of common garbage collection techniques including generational, parallel, stop-the-world, incremental, concurrent and mostly-concurrent algorithms, he defines terms and metrics common to all collectors. He classifies each major JVM collector's mechanisms and characteristics and discusses the tradeoffs involved in balancing requirements for responsiveness, throughput, space, and available memory across varying scale levels. Gil concludes with some pitfalls, common misconceptions, and "myths" around garbage collection behavior, as well as examples of how some good choices can result in impressive application behavior.
Ross Tredinnick - Rebecca J. Holz Research Data Management Talk 4/16/2013rossTnick
The Living Environments Laboratory (LEL) uses virtual reality to help researchers across many disciplines visualize and interact with their data. The lab houses a CAVE (Cave Automatic Virtual Environment), which is a room-sized immersive virtual reality theater. Researchers work with the LEL staff to convert their data into 3D scenarios that can be explored in the CAVE. The LEL is developing an online digital curation system to help organize, preserve, and provide access to the wide variety of 3D models, scripts, textures, and research data generated through these visualization projects. The goal is to advance fields like healthcare, education, and design through innovative uses of virtual reality.
The document discusses how to protect assets from an impending inflation crisis. It argues that government spending will debase the US dollar and lead to high inflation. It recommends tangible assets as a hedge, particularly rare coins, which have historically outperformed gold with no risk of government confiscation. Certain rare US coin varieties that are in high demand and low supply could be the ultimate hedge against inflation.
C:\Documents And Settings\Administrador\Escritorio\Plancha Manual De Mantenim...adriana marcela
Este documento fornece instruções em 4 passos para limpar e manter uma ferro de passar. Primeiro, desmonte a ferro em suas peças. Segundo, lave todas as peças com um pano úmido. Terceiro, limpe as partes essenciais como a placa e o vaporizador. Por último, monte novamente a ferro verificando se todas as peças encaixam corretamente.
Temperature Monitoring System with 4 Sensorsvackerdxb
The TV2 stores over 80,000 temperatures for each sensors, which means that it will store over 1.5 year of temperature history if you are sampling temperature once every 10 minutes. If you are logging temperature and humidity it will store nine months of history for each of the four sensors. Although the TV2 can store and display temperature from absolute zero to thousands of degrees, the actual temperatures collected depends on the type of sensors being used.
The document discusses the use of LiDAR (light detection and ranging) technology for various applications such as flood plain mapping, transportation infrastructure, forestry management, and more. It provides details on LiDAR accuracy standards, processing methods, and deliverable data formats. The presentation aims to help audiences understand how LiDAR data can aid in decision-making processes.
This document summarizes a tutorial on visual object recognition. It discusses several key topics:
1. Detection via classification using sliding windows and global appearance features like histograms or gradients.
2. Local invariant features for detection and description, as well as using them for specific object recognition.
3. Visual words and "bags of words" representations for image categorization by clustering local features.
4. Current challenges in visual object recognition like handling scale, clutter, context and learning with minimal supervision.
The document discusses surveying methods for salt marshes. It outlines the challenges of surveying in marshes, which include dense vegetation, soft ground, watercourses, and tidal effects. The method used involves plotting 50-foot intervals with GPS and an Argo, an amphibious ATV, to access lines and collect data. The Argo can navigate vegetation and shallow water, providing views over the marsh, but requires skill, maintenance, safety procedures, and results in mud and wetness.
Cinemappy: a Context-aware Mobile App for Movie Recommendations boosted by DB...Vito Ostuni
Cinemappy is a context-aware mobile app that recommends movies and cinemas to users based on their preferences and context. It uses a content-based recommender system boosted by DBpedia data. The app takes into account various contextual factors like location, time, companion, and geographic relevance to provide personalized recommendations. Cinemappy aims to improve recommendations by exploiting implicit user feedback and using a hybrid approach combining content-based and collaborative filtering methods.
This document discusses research into applying adaptive processes like evolutionary, individual, and social learning to embodied and situated agents. The researchers aimed to analyze how these agents could learn to categorize objects through simulated and real-world experiments. For individual learning, they implemented an algorithm based on simulated annealing that improved performance by replacing external stochasticity with internal stochasticity. For social learning, they modeled imitation between an expert agent and student, using a hybrid social-individual learning approach that helped students learn faster and more often acquire an adaptive behavior.
Keynote delivered at the 1st International Workshop on Process in the Large (IW-PL), September 13, 2010, Hoboken, NJ in conjunction with the BPM 2010 conference.
The document summarizes the process of conducting a contextual user research workshop. The summary is:
1) The workshop involves identifying users, collecting data through contextual inquiry, and assimilating the data using affinity diagramming.
2) Contextual inquiry involves building rapport with users, observing them in their environment, conversing to understand their needs, and gathering notes, photos and videos.
3) Affinity diagramming is used to assimilate the collected data. It involves grouping notes collaboratively and individually, adding labels, and reorganizing the notes into overarching themes.
This document outlines user research methods that can be used from exploration to ideation. It discusses contextual inquiry to understand users in their environments, group interpretation to make sense of findings, affinity diagramming to organize insights into themes, wall walking to generate design ideas, identifying hot ideas, and visioning sessions to flesh out concepts. The goal is to use these qualitative research techniques to deeply understand users and generate innovative design solutions that meet user needs.
The document discusses using design thinking to tackle complex public problems. It provides examples of government innovation labs around the world that use human-centered design and co-creation with citizens and businesses to develop new public policies and services. The document outlines key aspects of design thinking such as empathizing with users, iterating ideas through prototyping, and taking a systemic view to create sustainable solutions. It argues that design thinking can help governments better engage citizens and private sector partners in reinventing public services and shaping the future.
This document discusses the design principles of advanced task elicitation systems. It begins with an introduction that outlines the motivation and challenges of manual task elicitation in software development. It then reviews related work on task elicitation systems and the need to evaluate their design principles empirically. The methodology section describes a design science research approach used to conceptualize and evaluate an artifact called REMINER. Evaluation results show that semi-automatic task elicitation and leveraging imported knowledge bases can significantly increase elicitation productivity compared to manual elicitation. The discussion covers limitations and opportunities for future research at the intersection of task elicitation and software development processes.
The second day of lectures from Aalto University School of Economics’ ITP summer programme’s Strategy and Experience. https://itp.hse.fi/
Contents: Empathic design, personas, design research and methods.
This document provides an overview and agenda for a Puppet workshop. Puppet is an automated system configuration management tool. The workshop agenda includes installing and initializing Puppet, creating modules for user management and Apache site configuration, using templates, and setting up reporting and a dashboard. The document explains Puppet concepts like manifests, modules, templates, and functions. It also provides examples of Puppet configuration language and directory structures for modules.
The document describes an ontology-driven e-learning environment that uses adaptive testing to identify knowledge gaps. It consists of the following:
1. An ontology is used to structure educational content and provide the underlying logic for an adaptive multiple choice test.
2. The adaptive test evaluates student answers and tailors subsequent questions to map the student's knowledge based on the ontology.
3. Students receive customized learning materials based on the concepts in the ontology that their test responses indicated they do not fully understand.
4. The system aims to minimize guessing on tests and provide individually tailored feedback and learning instructions to bridge differences in competencies between educational levels.
The digital universe is booming, especially metadata and user-generated data. This raises strong challenges in order to identify the relevant portions of data which are relevant for a particular problem and to deal with the lifecycle of data. Finer grain problems include data evolution and the potential impact of change in the applications relying on the data, causing decay. The management of scientific data is especially sensitive to this. We present the Research Objects concept as the means to indentify and structure relevant data in scientific domains, addressing data as first-class citizens. We also identify and formally represent the main reasons for decay in this domain and propose methods and tools for their diagnosis and repair, based on provenance information. Finally, we discuss on the application of these concepts to the broader domain of the Web of Data: Data with a Purpose.
This document discusses the intersection of machine learning and search-based software engineering (ML & SBSE). It provides examples of how data miners can find signals in software engineering artifacts using machine learning techniques. It then discusses how better algorithms do not necessarily lead to better mining yet and emphasizes the importance of sharing data, models, and analysis methods. Finally, it outlines a vision for "discussion mining" to guide teams in walking across the space of local models, with the goal of building a science of localism in ML and SBSE.
The document proposes a recommendation system that incorporates semantics to address limitations of traditional recommenders. It uses ontologies to represent user interests and item annotations, and employs semantic inference and similarity methods. An evaluation on movie ratings shows the semantic approach improves accuracy, especially for cold-start users with small profiles. Further experimentation analyzes how the structure of different taxonomy affects performance of the semantic methods.
This document discusses ontology design and development. It describes the ontology development process, which includes pre-development, development, and post-development activities. Development activities involve specification, conceptualization, formalization, and implementation. The document also outlines methodologies for ontology design, which guide the construction of consistent ontologies through management, development-oriented, and support activities. These activities work together to efficiently develop complex ontologies.
This document discusses user experience (UX) methods and how to choose the right method for a project. It emphasizes understanding the questions that need answers and exploring different ways to get those answers. The document provides examples of mixing methods, such as combining interviews with participatory design. It also discusses adjusting methods based on constraints like resources, time, and access to users. The overall message is that UX planning should focus on the research questions rather than following an ideal process, and can be more creative by considering these types of constraints.
The document discusses user-centric design (UCD) and user experience (UX). It defines UX and discusses how UCD focuses on involving intended users throughout the design process through iterative testing. The basic UCD workflow involves concept, research, prototyping, testing, building, and post-launch testing. It also discusses the Five Planes Model for structuring UCD and covers creating user personas and stories to understand users.
The document discusses how to protect assets from an impending inflation crisis. It argues that government spending will debase the US dollar and lead to high inflation. It recommends tangible assets as a hedge, particularly rare coins, which have historically outperformed gold with no risk of government confiscation. Certain rare US coin varieties that are in high demand and low supply could be the ultimate hedge against inflation.
C:\Documents And Settings\Administrador\Escritorio\Plancha Manual De Mantenim...adriana marcela
Este documento fornece instruções em 4 passos para limpar e manter uma ferro de passar. Primeiro, desmonte a ferro em suas peças. Segundo, lave todas as peças com um pano úmido. Terceiro, limpe as partes essenciais como a placa e o vaporizador. Por último, monte novamente a ferro verificando se todas as peças encaixam corretamente.
Temperature Monitoring System with 4 Sensorsvackerdxb
The TV2 stores over 80,000 temperatures for each sensors, which means that it will store over 1.5 year of temperature history if you are sampling temperature once every 10 minutes. If you are logging temperature and humidity it will store nine months of history for each of the four sensors. Although the TV2 can store and display temperature from absolute zero to thousands of degrees, the actual temperatures collected depends on the type of sensors being used.
The document discusses the use of LiDAR (light detection and ranging) technology for various applications such as flood plain mapping, transportation infrastructure, forestry management, and more. It provides details on LiDAR accuracy standards, processing methods, and deliverable data formats. The presentation aims to help audiences understand how LiDAR data can aid in decision-making processes.
This document summarizes a tutorial on visual object recognition. It discusses several key topics:
1. Detection via classification using sliding windows and global appearance features like histograms or gradients.
2. Local invariant features for detection and description, as well as using them for specific object recognition.
3. Visual words and "bags of words" representations for image categorization by clustering local features.
4. Current challenges in visual object recognition like handling scale, clutter, context and learning with minimal supervision.
The document discusses surveying methods for salt marshes. It outlines the challenges of surveying in marshes, which include dense vegetation, soft ground, watercourses, and tidal effects. The method used involves plotting 50-foot intervals with GPS and an Argo, an amphibious ATV, to access lines and collect data. The Argo can navigate vegetation and shallow water, providing views over the marsh, but requires skill, maintenance, safety procedures, and results in mud and wetness.
Cinemappy: a Context-aware Mobile App for Movie Recommendations boosted by DB...Vito Ostuni
Cinemappy is a context-aware mobile app that recommends movies and cinemas to users based on their preferences and context. It uses a content-based recommender system boosted by DBpedia data. The app takes into account various contextual factors like location, time, companion, and geographic relevance to provide personalized recommendations. Cinemappy aims to improve recommendations by exploiting implicit user feedback and using a hybrid approach combining content-based and collaborative filtering methods.
This document discusses research into applying adaptive processes like evolutionary, individual, and social learning to embodied and situated agents. The researchers aimed to analyze how these agents could learn to categorize objects through simulated and real-world experiments. For individual learning, they implemented an algorithm based on simulated annealing that improved performance by replacing external stochasticity with internal stochasticity. For social learning, they modeled imitation between an expert agent and student, using a hybrid social-individual learning approach that helped students learn faster and more often acquire an adaptive behavior.
Keynote delivered at the 1st International Workshop on Process in the Large (IW-PL), September 13, 2010, Hoboken, NJ in conjunction with the BPM 2010 conference.
The document summarizes the process of conducting a contextual user research workshop. The summary is:
1) The workshop involves identifying users, collecting data through contextual inquiry, and assimilating the data using affinity diagramming.
2) Contextual inquiry involves building rapport with users, observing them in their environment, conversing to understand their needs, and gathering notes, photos and videos.
3) Affinity diagramming is used to assimilate the collected data. It involves grouping notes collaboratively and individually, adding labels, and reorganizing the notes into overarching themes.
This document outlines user research methods that can be used from exploration to ideation. It discusses contextual inquiry to understand users in their environments, group interpretation to make sense of findings, affinity diagramming to organize insights into themes, wall walking to generate design ideas, identifying hot ideas, and visioning sessions to flesh out concepts. The goal is to use these qualitative research techniques to deeply understand users and generate innovative design solutions that meet user needs.
The document discusses using design thinking to tackle complex public problems. It provides examples of government innovation labs around the world that use human-centered design and co-creation with citizens and businesses to develop new public policies and services. The document outlines key aspects of design thinking such as empathizing with users, iterating ideas through prototyping, and taking a systemic view to create sustainable solutions. It argues that design thinking can help governments better engage citizens and private sector partners in reinventing public services and shaping the future.
This document discusses the design principles of advanced task elicitation systems. It begins with an introduction that outlines the motivation and challenges of manual task elicitation in software development. It then reviews related work on task elicitation systems and the need to evaluate their design principles empirically. The methodology section describes a design science research approach used to conceptualize and evaluate an artifact called REMINER. Evaluation results show that semi-automatic task elicitation and leveraging imported knowledge bases can significantly increase elicitation productivity compared to manual elicitation. The discussion covers limitations and opportunities for future research at the intersection of task elicitation and software development processes.
The second day of lectures from Aalto University School of Economics’ ITP summer programme’s Strategy and Experience. https://itp.hse.fi/
Contents: Empathic design, personas, design research and methods.
This document provides an overview and agenda for a Puppet workshop. Puppet is an automated system configuration management tool. The workshop agenda includes installing and initializing Puppet, creating modules for user management and Apache site configuration, using templates, and setting up reporting and a dashboard. The document explains Puppet concepts like manifests, modules, templates, and functions. It also provides examples of Puppet configuration language and directory structures for modules.
The document describes an ontology-driven e-learning environment that uses adaptive testing to identify knowledge gaps. It consists of the following:
1. An ontology is used to structure educational content and provide the underlying logic for an adaptive multiple choice test.
2. The adaptive test evaluates student answers and tailors subsequent questions to map the student's knowledge based on the ontology.
3. Students receive customized learning materials based on the concepts in the ontology that their test responses indicated they do not fully understand.
4. The system aims to minimize guessing on tests and provide individually tailored feedback and learning instructions to bridge differences in competencies between educational levels.
The digital universe is booming, especially metadata and user-generated data. This raises strong challenges in order to identify the relevant portions of data which are relevant for a particular problem and to deal with the lifecycle of data. Finer grain problems include data evolution and the potential impact of change in the applications relying on the data, causing decay. The management of scientific data is especially sensitive to this. We present the Research Objects concept as the means to indentify and structure relevant data in scientific domains, addressing data as first-class citizens. We also identify and formally represent the main reasons for decay in this domain and propose methods and tools for their diagnosis and repair, based on provenance information. Finally, we discuss on the application of these concepts to the broader domain of the Web of Data: Data with a Purpose.
This document discusses the intersection of machine learning and search-based software engineering (ML & SBSE). It provides examples of how data miners can find signals in software engineering artifacts using machine learning techniques. It then discusses how better algorithms do not necessarily lead to better mining yet and emphasizes the importance of sharing data, models, and analysis methods. Finally, it outlines a vision for "discussion mining" to guide teams in walking across the space of local models, with the goal of building a science of localism in ML and SBSE.
The document proposes a recommendation system that incorporates semantics to address limitations of traditional recommenders. It uses ontologies to represent user interests and item annotations, and employs semantic inference and similarity methods. An evaluation on movie ratings shows the semantic approach improves accuracy, especially for cold-start users with small profiles. Further experimentation analyzes how the structure of different taxonomy affects performance of the semantic methods.
This document discusses ontology design and development. It describes the ontology development process, which includes pre-development, development, and post-development activities. Development activities involve specification, conceptualization, formalization, and implementation. The document also outlines methodologies for ontology design, which guide the construction of consistent ontologies through management, development-oriented, and support activities. These activities work together to efficiently develop complex ontologies.
This document discusses user experience (UX) methods and how to choose the right method for a project. It emphasizes understanding the questions that need answers and exploring different ways to get those answers. The document provides examples of mixing methods, such as combining interviews with participatory design. It also discusses adjusting methods based on constraints like resources, time, and access to users. The overall message is that UX planning should focus on the research questions rather than following an ideal process, and can be more creative by considering these types of constraints.
The document discusses user-centric design (UCD) and user experience (UX). It defines UX and discusses how UCD focuses on involving intended users throughout the design process through iterative testing. The basic UCD workflow involves concept, research, prototyping, testing, building, and post-launch testing. It also discusses the Five Planes Model for structuring UCD and covers creating user personas and stories to understand users.
Data Management for Librarians: An IntroductionGarethKnight
The document provides an introduction to data management for librarians, outlining key concepts such as the research data lifecycle, challenges in managing digital data over time, best practices for organizing, documenting, and storing data, and resources for data management support. Common problems include difficulty locating, accessing, and understanding data in the long run without proper planning and preservation strategies. The role of librarians is to educate researchers on best practices and provide support and training resources.
20-minute speed-run presentation on what metrics and web analytics information startups need to collect. Focuses on companies with a lean methodology, and the kinds of data that will actually help them achieve product/market fit before the money runs out.
The document summarizes a workshop organized by the Effectsplus Systems and Networks cluster to discuss different modeling approaches used in projects to assess security and privacy challenges. The workshop aims to identify areas of collaboration, publicly available models, and gaps for future research. The agenda outlines presentations on various modeling techniques from 11 projects on the first day and discussions on collaboration opportunities on the second day.
JPSearch is a set of specifications that aims to provide interoperability for image search across different systems and repositories. It defines interfaces and protocols for data exchange in a modular and flexible architecture. The goal is to ensure portability of metadata and allow consumers to search across multiple sources without being locked into a single system. JPSearch includes specifications for ontology registration, query formats, embedding metadata in image files, and data interchange between repositories. It is developed following ISO procedures and is currently maintaining and extending existing specifications.
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
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.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
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
Things to Consider When Choosing a Website Developer for your Website | FODUUFODUU
Choosing the right website developer is crucial for your business. This article covers essential factors to consider, including experience, portfolio, technical skills, communication, pricing, reputation & reviews, cost and budget considerations and post-launch support. Make an informed decision to ensure your website meets your business goals.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
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.
1. Vision-Based Place Recognition for
Autonomous Robots
First Seminar - Project Overview
Team Members:
Ahmed Abd-El Fattah Mohammed
Ahmed Saher Maher
Mourad Aly Mourad
Yasser Hassan Ahmed
1
Saturday, December 11, 2010 1
2. Prof.Dr Mohamed Roushdy
Dr. Mohamed Abdel Megeed
Dr. Safaa Amin
T.A. Mohamed Fathy
Supervisors
2
Saturday, December 11, 2010 2
3. Agenda
Objective What Methodology How
Theoretical Background Improve previous work
Motivation Adaptive Multi-Scale
Classification
Problem Definition
Challenges
System Architecture
Testing Platform
Conventional Pattern
Recognition System Architecture Development Tools
Related Work
Time Plan When
ImageCLEF
Our Progress
Top Related Systems
Next Objective
References
3
Saturday, December 11, 2010 3
4. Objective
Where am I ?
4
Saturday, December 11, 2010 4
5. Theoretical Background
Where are we in the field of computer science ?
Pattern Image
Recognition Processing
Computer
Computer Vision
Science
Artificial
Intelligence
5
Saturday, December 11, 2010 5
6. Motivation
Interested in robot vision.
Has many applications, help in rescue missions.
Co-operation between our university and Bielefeld
University.
6
Saturday, December 11, 2010 6
7. Problem Definition
Meeting Room
Vision-Based Place Recognition for Autonomous Robot
What does it mean ?
7
Saturday, December 11, 2010 7
8. Problem Definition
SLAM
Simultaneous Localization And Mapping.
Our problem is to focus on localization issues in most
SLAM systems.
8
Saturday, December 11, 2010 8
9. Conventional PR System Architecture
Training Phase Testing Phase
Sensing Sensing
Pre-Processing Pre-Processing
Feature Extraction Feature Extraction
Training Classification
Knowledge Decision
Base 9
Saturday, December 11, 2010 9
10. Related Work
ImageCLEF
ImageCLEF 2010
22-23th September 2010
A yearly contest which focuses on information retrieval
using image processing. It branches to many applications
including robot vision.
10
Saturday, December 11, 2010 10
11. Related Work
1st Position
CVG
Olivier Saurer, Friedrich Fraundorfer, and Marc
Pollefeys – “Visual localization using global visual
features and vanishing points” - ETH Zurich,
Switzerland
Pros Cons
Focused on feature extraction
Used very primitive classification
phase developed new feature
methods.
extraction algorithms. 11
Saturday, December 11, 2010 11
12. Related Work
4th Position
Centro Gustavo Stefanini
W.Lucetti, E. Luchetti – “Combination of Classifiers
for Indoor Room Recognition” - Gustavo Stefanini
Research Center - Padua, 23 September 2010
Pros Cons
Focused on classification phase
Used very primitive feature
developed many new
extraction methods.
combination of classifiers. 12
Saturday, December 11, 2010 12
13. Agenda
Methodology
Objective What How
Theoretical Background Improve previous work
Motivation Adaptive Multi-Scale
Classification
Problem Definition
Challenges
System Architecture
Testing Platform
Conventional Pattern
Recognition System Architecture Development Tools
Time Plan
Related Work When
ImageCLEF Our Progress
Top Related Systems Next Objective
References
13
Saturday, December 11, 2010 13
14. Methodology
1. Improve previous work
Combine the pros of each group.
Try to avoid their mistakes and cons.
14
Saturday, December 11, 2010 14
15. Methodology
2. Adaptive Multi-Scale Classification
What is the meaning of an environment?
Env 1 Env 2 Env 3
Kitchen,Bathroom LivingRoom,Office BedRoom,Corridor
White illumination White illumination Yellow illumination
Color White Color Blue Color Brown
How can the system differentiate between
environments?
Differentiation using discriminative features only.
15
Saturday, December 11, 2010 15
16. Methodology
2. Adaptive Multi-Scale Classification
Unrecognized
Image PR System
for Env 1
(Kitchen,Bathroom)
Environment PR System
Start Current
Operating Environment for Env 2 Decision
Identifier (Office,Library)
PR System
for Env 3
(Bedrooms)
Simple classification
Full-scale PR systems
16
Saturday, December 11, 2010 16
17. Challenges
Objects’ appearance varies
due to
Cluttered background.
Difference in illumination.
Imaging conditions.
Recognition algorithms perform differently with different
environments.
It’s difficult to find a solution that is both resource efficient
and perform with high accuracy, due to the very limited
resources of a mobile robot.
17
Saturday, December 11, 2010 17
18. Testing Platforms
1) Bielefeld University’s workbench
2) ImageCLEF’s testing dataset.
3) Build our own data acquisition tool.
18
Saturday, December 11, 2010 18
20. Agenda
Objective What Methodology How
Theoretical Background Improve previous work
Motivation Adaptive Multi-Scale
Classification
Problem Definition
Challenges
System Architecture
Testing Platform
Conventional Pattern
Recognition System Architecture Development Tools
Related Work Time Plan
When
ImageCLEF Our Progress
Top Related Systems Next Objective
References
20
Saturday, December 11, 2010 20
21. Time Plan
2010 2011
Sep Oct Nov Dec Jan Feb Mar April May June July
Feasibility Study
Survey(1)-Project
Overview
Survey(2)-Project
In Depth
Developing Simple
PR System
Iterative System
Development
Deployment
Documentation
21
Saturday, December 11, 2010 21
22. Our Progress
Survey 1 Survey 2
(Project Overview) (Project in Depth)
-Problem definition. -Description of each
-Commonly used algorithm mentioned
algorithms in pattern in survey 1
recognition.
22
Saturday, December 11, 2010 22
23. Next Objective
Simple Pattern Recognition System
Image Decision
ImageCLEF ( Class 1 Or
Data Set Class 2 )
Simple PR
The system has theSystem to differentiate between 2
ability
classes.
23
Saturday, December 11, 2010 23
24. References
“The Robot Vision Track at ImageCLEF 2010”Andrzej Pronobis, Marco
Fornoni, Henrik I. Christensen, and Barbara Caputo.
“Evaluation of Bayes, ICA, PCA and SVM Methods for Classification”,
V.C.Chen. Radar Division, US Naval Research Laboratory.
Olivier Saurer, Friedrich Fraundorfer, and Marc Pollefeys – “Visual localization
using global visual features and vanishing points” - ETH Zurich, Switzerland
W.Lucetti, E. Luchetti – “Combination of Classifiers for Indoor Room
Recognition” - Gustavo Stefanini Research Center - Padua, 23 September
2010
24
Saturday, December 11, 2010 24
25. Contacts
Blog: autovpr.wordpress.com
Ahmed Saher Maher
a7med.saher@gmail.com
Ahmed Abd El-Fattah
ahmed.abdelfattah1@live.com
Mourad Aly Mourad
mouraad@windowslive.com
Yasser Hassan Ahmed
yasserhtd@hotmail.com Thanks!
25
Saturday, December 11, 2010 25