Sme 2014
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This document discusses factors that influence community acceptance of mining projects. It aims to identify critical factors and analyze their importance. An online survey was conducted of mining communities and control groups. The most important factors for mining communities were job opportunities, income increase, and infrastructure improvements. The most negatively correlated factors with acceptance were cultural impact, traffic/crime increases, and housing costs/shortages. Demographic analyses found mining communities had more males aged 26-54 with vocational educations. Control groups ranked job opportunities and noise pollution as most important. A discrete choice model is proposed to further study acceptance factors through experiments.
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as a basis for adapting livestock management to changing conditions. It is vital to the
livelihoods of many of the world’s poor people. It can contribute to the delivery of ecosystem
services. However, it is often undervalued, underused and under threat.
Drawing on 129 country reports, 15 reports from international organizations, 4 reports
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In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
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Control Flows and Loops
Conditional Statements
💻 Extra training through UiPath Academy:
Variables, Constants, and Arguments in Studio
Control Flow in Studio
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
From Natural Language to Structured Solr Queries using LLMs
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
Containers & AI - Beauty and the Beast!?!
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Keywords: AI, Containeres, Kubernetes, Cloud Native
Event Link: https://meine.doag.org/events/cloudland/2024/agenda/#agendaId.4211
"Choosing proper type of scaling", Olena Syrota
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Lee Barnes - Path to Becoming an Effective Test Automation Engineer.pdf
So… you want to become a Test Automation Engineer (or hire and develop one)? While there’s quite a bit of information available about important technical and tool skills to master, there’s not enough discussion around the path to becoming an effective Test Automation Engineer that knows how to add VALUE. In my experience this had led to a proliferation of engineers who are proficient with tools and building frameworks but have skill and knowledge gaps, especially in software testing, that reduce the value they deliver with test automation.
In this talk, Lee will share his lessons learned from over 30 years of working with, and mentoring, hundreds of Test Automation Engineers. Whether you’re looking to get started in test automation or just want to improve your trade, this talk will give you a solid foundation and roadmap for ensuring your test automation efforts continuously add value. This talk is equally valuable for both aspiring Test Automation Engineers and those managing them! All attendees will take away a set of key foundational knowledge and a high-level learning path for leveling up test automation skills and ensuring they add value to their organizations.
Session 1 - Intro to Robotic Process Automation.pdf
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
Mutation Testing for Task-Oriented Chatbots
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
Demystifying Knowledge Management through Storytelling
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
A Deep Dive into ScyllaDB's Architecture
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
ScyllaDB Tablets: Rethinking Replication
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation F...
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation Functions to Prevent Interaction with Malicious QR Codes.
Aim of the Study: The goal of this research was to develop a robust hybrid approach for identifying malicious and insecure URLs derived from QR codes, ensuring safe interactions.
This is achieved through:
Machine Learning Model: Predicts the likelihood of a URL being malicious.
Security Validation Functions: Ensures the derived URL has a valid certificate and proper URL format.
This innovative blend of technology aims to enhance cybersecurity measures and protect users from potential threats hidden within QR codes 🖥 🔒
This study was my first introduction to using ML which has shown me the immense potential of ML in creating more secure digital environments!
JavaLand 2024: Application Development Green Masterplan
My presentation slides I used at JavaLand 2024
GNSS spoofing via SDR (Criptored Talks 2024)
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
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"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor Ivaniuk
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From Natural Language to Structured Solr Queries using LLMs
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Session 1 - Intro to Robotic Process Automation.pdf
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Sme 2014
- 1. Identifying critical factors that influence community acceptance of mining projects Sisi Que Dr. Kwame Awuah-offei 1
- 2. Introduction The US consumes over 6.5 billion tons/year of mineral & energy resources ----20 tons/person/year Peru • 245 social conflicts in June 2012 • >2,400 injured, >200 killed (2006—2012) 2
- 4. Independent and transparent information Mine life Management Environmental and other impact Mine buffer social Infrastructure improve Population change Cultural impact Traffic and crime increase Social impact Economical impact Environmental Decision making mechanism Economical Management Characteristics of mine Water pollution Land pollution Noise pollution Air pollution Job opportunities Income increase Cost of housing or housing shortage Labor shortage for 4 other business
- 5. Demographic factors Age # of children Gender Job field Income Education 5
- 7. Importance of the Factors Median (95% confidence, distribution free) Mining factors Labor shortage for other business Population change Infrastructure improve Noise pollution Cultural impact Cost of housing or shortage Independent and transparent information Decision making mechanism Traffic and crime increase Income increase Mine buffer Mine life Job opportunities Water pollution Air pollution Land pollution Land pollution and subsidence 4 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 1 Not at all Important 2 Very Unimportant 3 Somewhat Unimportant 4 Neither Important nor Unimportant 5 Somewhat Important 6 Very Important 7 Extremely Important 7
- 8. Correlative analysis of mining communities • Traffic and crime increase • Water pollution • Air pollution • Land pollution • Population change • Cultural impact • Mine buffer • Job opportunity • Income increase • • • • • • Cultural impact Traffic and crime increase Cost of housing or shortage Land pollution Decision making mechanism Independent and transparent information • Mine buffer 8 • Mine life
- 9. Demographics of Respondents Gender Age 70% 60% 35% Mining 30% Control 50% 40% 15% 20% 10% 10% Control 20% 30% Mining 25% 5% 0% 0% Male 18—25 Female Education 26—34 35—54 55—64 >65 Annual income 40% 40% Mining Control Mining 30% 30% 20% 20% 10% 10% 0% Control 0% 9
- 10. Correlative analysis of non-mining communities • Job opportunity • Labor shortage for other businesses • Job opportunity • Noise pollution • Cost of housing or shortage • Infrastructure improvement • Labor shortage for other businesses • Information available 10
- 11. Mining and non-mining groups 1 2 Somewhat Unimportant 4 Neither Important nor Unimportant 5 Somewhat Important 6 Very Important 7 N—Median of ranking from non-mining communities Very Unimportant 3 M—Median of ranking from mining communities Not at all Important Extremely Important 11
- 12. Discrete Choice Model Mixed logit model (ML) Daniel McFadden 2000 Nobel Memorial Prize Multinomial probit model (MNP) Multinomial logit model (MNL) Random utility maximization (1959) Pni Prob U ni U nj , i j, i and j J (1) 12
- 13. 13
- 15. Literature Review Mining group Control group Final variables list Proposed framework for future research Burden study Discrete choice experiments Discrete choice model 15
- 16. 16
Editor's Notes
- In order to create a model for dragline energy efficiency we need to study the factors that affect energy efficiency
- Keep it if have time
- Before any analysis doing any analysis on data the outliers had to identified and removed to avoid ant inaccuarte inference