This talk was given during Monitorama EU 2018.
Observability, like other ops practices, has hard and soft benefits. No logs - no root cause, that’s a hard benefit. A soft benefit is when we have more confidence in an observable system. Then we can be more productive in developing it. The trouble with soft benefits like confidence, is how to measure them. Does observability actually make us more productive? How about other activities, such as post-mortems? Why is alert fatigue so bad? Turns out, there are plenty of studies about the impact of such activities on our brain, our behavior, our productivity. In this session, we’ll explore what [neuro]science says about such practices so that:
We turn soft benefits into hard benefits
We can encourage a culture where we get the benefits and avoid the traps
Be prepared for surprises, as some “best practices” aren’t “best” at all.
In the spring of this year I have mapped the vast majority (>95%) of shops and retail areas in Nottingham, the 8th largest retail centre in the UK, serving a market of around 1 million people. In addition I have repeated the exercise for a Maidenhead a town of 70,000 which is only a local shopping centre.
Comprehensive mapping of retail outlets allows a more rigorous analysis of OSM data, with significant implications for how we should collect and map data for shops. These include: better support from mapping tools (particularly for mapping change), defining a usable classification for retail areas, and improving consistency in tagging.
These need to be cross-checked for different countries, so I hope this provokes extensive contributions from other participants.
Slides for the SF Python meetup tutorial Introduction to Deep Learning. The tutorial goes over a simple code that trains a fully connected neural network to classify handwritten digits from the MNIST dataset.
Associated Github repo:
https://github.com/Dataweekends/intro_deep_learning_sf_python_meetup
In the spring of this year I have mapped the vast majority (>95%) of shops and retail areas in Nottingham, the 8th largest retail centre in the UK, serving a market of around 1 million people. In addition I have repeated the exercise for a Maidenhead a town of 70,000 which is only a local shopping centre.
Comprehensive mapping of retail outlets allows a more rigorous analysis of OSM data, with significant implications for how we should collect and map data for shops. These include: better support from mapping tools (particularly for mapping change), defining a usable classification for retail areas, and improving consistency in tagging.
These need to be cross-checked for different countries, so I hope this provokes extensive contributions from other participants.
Slides for the SF Python meetup tutorial Introduction to Deep Learning. The tutorial goes over a simple code that trains a fully connected neural network to classify handwritten digits from the MNIST dataset.
Associated Github repo:
https://github.com/Dataweekends/intro_deep_learning_sf_python_meetup
We hosted a speaking series to bring together top CMO’s to hear how they are integrating and embracing new and changing technology platforms, defining marketing direction and to ultimately build deeper relationships with connected consumers.
Celebrated 2013 New Year all Over the World in One's Own Style with Great Joy jacqueline321
At the end of the year every individual prays and wishes that the forth coming year that will start the next day will bring good health and a happy life. The evening before the next year starts is celebrated by all in their own way.
Artificial Intelligence is the hot tech paradigm of the moment. It is the subject of a great deal of media hype, woes and mythologising. It seems worthwhile, therefore, to try to set the scene, look at some definitions, and see where it is currently being applied.
Not Dead Yet: Designing Great Experiences with Bad DataSonia Koesterer
By Sonia Koesterer
The world is imperfect. Every “happy path” intersects with dozens of crappy paths caused by typos, technical errors, and data that goes missing, is mis-assigned, adulterated, or is otherwise compromised/ stolen by evil data pirates. While you can’t prevent all data fails, you can avoid catastrophic failures, design graceful recoveries, and even turn the weakest points of your service into a strategic advantage. In short, you can create great services despite bad data.
The impact of data failure can be a humorous accident, minor inconvenience, or completely detrimental. For example, each year, the U.S. government falsely declares over 12,000 people dead due mostly to typos. In sheer percentage this is a rarity of a corner case of an edge case… but for those 12,000 individuals who suddenly lose their social security benefits, health insurance, bank accounts, and can’t easily prove they are alive, it’s catastrophic.
So design for the the edge-case! Understand the weakest points of your service, learn from them, and turn your failures into great experiences.
This presentation is about why work/culture or organisation culture is important. It talks indirectly about how organisational profit are dependent on the various factors of human behaviour and one needs to keep one self updated with gen x & Y and time
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
Do you have a lot of complex jobs that you need to run as part of your application? Do they consist of multiple tasks and you wonder how to orchestrate them properly? Do you want to be able to easily scale their execution? Is availability of your workers important to you? If you answer “Yes” to these questions then AWS Simple Workflow is the right tool for you.
In this talk we will go through Amazon SWF and Java Flow Framework and you will see how to get a distributed job execution engine right out of the box. We will also compare SWF to alternative solutions, discuss real life experience, and of course enjoy a live demo.
The talk will be most useful to everyone who is interested in the design of distributed systems and is new to AWS SWF.
본 실습은 AWS IoT Edge 구성 요소인 AWS IoT Greengrass를 이용하여 산업 현장에서 활용되는 표준 통신 프로토콜(OPC-UA)을 AWS IoT 호환 프로토콜로 변환 전처리하는 과정을 실습합니다. 이렇게 수집된 데이터는 AWS IoT Analytics 을 통해 분석 및 BI에 활용될 수 있으며, 본 실습에서는 Amazon Sage Maker를 활용하여 예지 정비 모델을 작성 및 배포하고, 추가적으로 Amazon QuickSight를 통한 시각화 구현을 목표로 합니다.
In-silico study of ToxCast GPCR assays by quantitative structure-activity rel...Kamel Mansouri
The EPA tested several thousand chemicals in 700 toxicity-related in-vitro HTS bioassays through the ToxCast and Tox21 projects. However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in-silico methods, and quantitative structure-activity relationships (QSARs) are a cost effective approach to predict biological activity. The overall goal of this project was to use QSAR predictions to fill the data gaps in a larger environmental database of ~30K structures. The specific aim of the current work was to build QSAR models for multiple ToxCast assays using a subset of 1800 chemicals tested in 18 G-Protein Coupled Receptor (GPCR) assays. These assays are part of the aminergic category which was among the most active within the biochemical assays. Using PLSDA for the human histamine H1 GPCR assay, the classification accuracy reached 94% with a non-error rate of 89% in fitting and 80% in 5-fold CV, with only 2 latent variables. These results demonstrate the ability of QSAR models to predict bioactivity.
This session covers the most recent AWS IoT announcements at re:Invent. Learn about trends and use cases for the Internet of Things (IoT). Hear about how AWS customers are using AWS IoT to connect their devices to the cloud and solve business challenges with IoT.
We hosted a speaking series to bring together top CMO’s to hear how they are integrating and embracing new and changing technology platforms, defining marketing direction and to ultimately build deeper relationships with connected consumers.
Celebrated 2013 New Year all Over the World in One's Own Style with Great Joy jacqueline321
At the end of the year every individual prays and wishes that the forth coming year that will start the next day will bring good health and a happy life. The evening before the next year starts is celebrated by all in their own way.
Artificial Intelligence is the hot tech paradigm of the moment. It is the subject of a great deal of media hype, woes and mythologising. It seems worthwhile, therefore, to try to set the scene, look at some definitions, and see where it is currently being applied.
Not Dead Yet: Designing Great Experiences with Bad DataSonia Koesterer
By Sonia Koesterer
The world is imperfect. Every “happy path” intersects with dozens of crappy paths caused by typos, technical errors, and data that goes missing, is mis-assigned, adulterated, or is otherwise compromised/ stolen by evil data pirates. While you can’t prevent all data fails, you can avoid catastrophic failures, design graceful recoveries, and even turn the weakest points of your service into a strategic advantage. In short, you can create great services despite bad data.
The impact of data failure can be a humorous accident, minor inconvenience, or completely detrimental. For example, each year, the U.S. government falsely declares over 12,000 people dead due mostly to typos. In sheer percentage this is a rarity of a corner case of an edge case… but for those 12,000 individuals who suddenly lose their social security benefits, health insurance, bank accounts, and can’t easily prove they are alive, it’s catastrophic.
So design for the the edge-case! Understand the weakest points of your service, learn from them, and turn your failures into great experiences.
This presentation is about why work/culture or organisation culture is important. It talks indirectly about how organisational profit are dependent on the various factors of human behaviour and one needs to keep one self updated with gen x & Y and time
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
Do you have a lot of complex jobs that you need to run as part of your application? Do they consist of multiple tasks and you wonder how to orchestrate them properly? Do you want to be able to easily scale their execution? Is availability of your workers important to you? If you answer “Yes” to these questions then AWS Simple Workflow is the right tool for you.
In this talk we will go through Amazon SWF and Java Flow Framework and you will see how to get a distributed job execution engine right out of the box. We will also compare SWF to alternative solutions, discuss real life experience, and of course enjoy a live demo.
The talk will be most useful to everyone who is interested in the design of distributed systems and is new to AWS SWF.
본 실습은 AWS IoT Edge 구성 요소인 AWS IoT Greengrass를 이용하여 산업 현장에서 활용되는 표준 통신 프로토콜(OPC-UA)을 AWS IoT 호환 프로토콜로 변환 전처리하는 과정을 실습합니다. 이렇게 수집된 데이터는 AWS IoT Analytics 을 통해 분석 및 BI에 활용될 수 있으며, 본 실습에서는 Amazon Sage Maker를 활용하여 예지 정비 모델을 작성 및 배포하고, 추가적으로 Amazon QuickSight를 통한 시각화 구현을 목표로 합니다.
In-silico study of ToxCast GPCR assays by quantitative structure-activity rel...Kamel Mansouri
The EPA tested several thousand chemicals in 700 toxicity-related in-vitro HTS bioassays through the ToxCast and Tox21 projects. However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in-silico methods, and quantitative structure-activity relationships (QSARs) are a cost effective approach to predict biological activity. The overall goal of this project was to use QSAR predictions to fill the data gaps in a larger environmental database of ~30K structures. The specific aim of the current work was to build QSAR models for multiple ToxCast assays using a subset of 1800 chemicals tested in 18 G-Protein Coupled Receptor (GPCR) assays. These assays are part of the aminergic category which was among the most active within the biochemical assays. Using PLSDA for the human histamine H1 GPCR assay, the classification accuracy reached 94% with a non-error rate of 89% in fitting and 80% in 5-fold CV, with only 2 latent variables. These results demonstrate the ability of QSAR models to predict bioactivity.
This session covers the most recent AWS IoT announcements at re:Invent. Learn about trends and use cases for the Internet of Things (IoT). Hear about how AWS customers are using AWS IoT to connect their devices to the cloud and solve business challenges with IoT.
Intro to Biodesign: Working with Living ThingsLeticia Oxley
Introduction to principles of design done with biology. As designer seek new materials, biology may serve as both inspiration and a resource for new material practices. Likewise, as designers imagine new possibilities, designer may speculate where biology may take us with projects that approach design from a critical perspective.
This ppt describes one of the interesting algorithms to count the number of bits set in an unsigned integer.
x = (x & 0x55555555) + ((x>>1)&0x55555555));
x = (x&0x33333333) + ((x>>2)&0x33333333);
...
....
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore features and functions of AWS IoT services. First we will cover AWS IoT fundamentals, review best practices for IoT solutions, and look at some common architectural patterns. Then we will dive deep into AWS IoT Analytics. We will explain how AWS IoT Analytics runs sophisticated analytics on massive volumes of IoT data and helps operationalize analyses without requiring you to build an IoT analytics platform from the ground up. You will hear from TensorIoT, an AWS IoT Analytics partner, about how they are using AWS IoT Analytics. Leave this session with an understanding of how to start building IoT applications with AWS IoT.
Design is as good (or flawed) as the people who make itKayla J Heffernan
Talk given at UX Australia 2016 held in Melbourne.
ABOUT THE TALK:
No one sets out to intentionally design a system that is hard to use for - or worse, excludes or discriminates against - some users. Designers are trying their best. You're probably a good person, but a human nonetheless, therefore not perfect. Design can only be as good as the people who make it. Conversely, design is as flawed as the people who make it.
ABOUT THE SPEAKER:
Kayla Heffernan is a user and experiencer of products, frustrated with mediocrity and a passionate advocate for the voice of all users. Kayla is a UX designer at SEEK and also undertaking a PhD in Interaction Design looking at digital insertables. In her spare time… she doesn’t have any.
Geneve Monitoring event - InfluxDb and Loud ML presentationSebastien Leger
The presentation that was delivered at Seedspace for Geneve Monitoring Meetup on March 8, 2018. This talk was an introduction to Loud ML machine learning API and its integration with InfluxDb and Chronograf.
This talk was given during Activate Conference 2019. Lucene has a lot of options for configuring similarity, and Solr inherits them. Similarity makes the base of your relevancy score: how similar is this document to the query? The default similarity (BM25) is a good start, but you may need to tweak it for your use-case. In this session, you will learn how BM25 works and how you may want to change its parameters. Then, we'll move to other similarity classes: DFR, DFI, IB and LM. You will learn the thinking behind them, how that thinking translates to the similarity score, and which parameters allow you to tweak how score evolves based on things like term frequency or document length. By the end, you’ll have a good understanding of which similarity options are likely to work well for your use-case. You'll know which tunables are available and whether you need to implement a custom similarity class. As an example, we’ll focus on E-commerce, where you often end up ignoring term frequency altogether.
Key Takeaway
1) What are the built-in Lucene/Solr similarities and what they do
2) Which similarity to use for which use-case
3) How to use a custom similarity class in Solr
Learn more about search relevance and similarity: sematext.com/blog/search-relevance-solr-elasticsearch-similarity
This talk was given during DockerCon EU 2018.
It ain't just a whim - to be able to continue innovating, we’ve moved our good old static production to containers. We needed to be elastic, fast, reliable and production ready at any time - that's why we chose Docker. But like in most enterprises, lots of our apps run on the JVM and most JVMs’ ergonomics assume they “own” the server they are running on. So how do you containerize JVM apps? Should you really increase JVM heap if you have spare memory? What about OS caches? What are the differences between JDK 8, 9 and 10 when it comes to container awareness? Outages because of out of memory errors? Slowness because of long garbage collection and poor environment visibility? Long story short, in this session, we’ll look at the gotchas of running JVM apps in containers and teach you how to avoid costly mistakes.
Top 3 things attendees will learn:
1. Key differences between various JVM versions relevant for containerized Java apps.
2. Best practices for running JVM in containers.
3. Avoiding common pitfalls when running containerized JVM applications.
This talk was given during DevOps Con 2017.
Have you ever spent time digging through various terminals, greping, lessing, awking and trying to find that few log lines that may be important? Have you every done that under time pressure, because mission critical services were not working? Have you every heard from your developers that they can’t tell you anything, because they don’t have access to application logs? Have you ever considered a centralized storage for logs, but time and resources are not on your side?
If you said yes, to any of the above questions, than this talk is for you. During the talk we’ll introduce you to the world of log centralization and analysis, both when it comes to open source, but also commercial tools. We will go from top to bottom and learn how to setup log centralization and analysis for servers, virtualized environments and containers. We will get from log shipping, through centralized buffering to storage and analysis to show you, that having a centralized log analysis tool is not a rocket science.
Finally, you will see how useful is to combine the logs from all your servers in a single place for blazingly fast correlation.
This talk was given during Lucene Revolution 2017.
They say optimize is bad for you, they say you shouldn't do it, they say it will invalidate operating system caches and make your system suffer. This is all true, but is it true in all cases?
In this presentation we will look closer on what optimize or better called force merge does to your Solr search engine. You will learn what segments are, how they are built and how they are used by Lucene and Solr for searching. We will discuss real-life performance implications regarding Solr collections that have many segments on a single node and compare that to the Solr where the number of segments is moderate and low. We will see what we can do to tune the merging process to trade off indexing performance for better query performance and what pitfalls are there waiting for us. Finally, at the end of the talk we will discuss possibilities of running force merge to avoid system disruption and still benefit from query performance boost that single segment index provides.
This talk was given during Lucene Revolution 2017 and has two goals: first, to discuss the tradeoffs for running Solr on Docker. For example, you get dynamic allocation of operating system caches, but you also get some CPU overhead. We'll keep in mind that Solr nodes tend to be different than your average container: Solr is usually long running, takes quite some RSS and a lot of virtual memory. This will imply, for example, that it makes more sense to use Docker on big physical boxes than on configurable-size VMs (like Amazon EC2).
The second goal is to discuss issues with deploying Solr on Docker and how to work around them. For example, many older (and some of the newer) combinations of Docker, Linux Kernel and JVM have memory leaks. We'll go over Docker operations best practices, such as using container limits to cap memory usage and prevent the host OOM killer from terminating a memory-consuming process - usually a Solr node. Or running Docker in Swarm mode over multiple smaller boxes to limit the spread of a single issue.
Docker is all the rage these days. While one doesn't hear much about Solr on Docker, we're here to tell you not only that it can be done, but also share how it's done.
We'll quickly go over the basic Docker ideas - containers are lighter than VMs, they solve "but it worked on my laptop" issues - so we can dive into the specifics of running Solr on Docker.
We'll do a live demo showing you how to run Solr master - slave as well as SolrCloud using containers, how to manage CPU assignments, constraint memory and use Docker data volumes when running Solr in containers. We will also show you how to create your own containers with custom configurations.
Finally, we'll address one of the core Solr questions - which deployment type should I use? We will demonstrate performance differences between the following deployment types:
- Single Solr instance running on a bare metal machine
- Multiple Solr instances running on a single bare metal machine
- Solr running in containers
- Solr running on virtual machine
- Solr running on virtual machine using unikernel
For each deployment type we'll address how it impacts performance, operational flexibility and all other key pros and cons you ought to keep in mind.
An updated talk about how to use Solr for logs and other time-series data, like metrics and social media. In 2016, Solr, its ecosystem, and the operating systems it runs on have evolved quite a lot, so we can now show new techniques to scale and new knobs to tune.
We'll start by looking at how to scale SolrCloud through a hybrid approach using a combination of time- and size-based indices, and also how to divide the cluster in tiers in order to handle the potentially spiky load in real-time. Then, we'll look at tuning individual nodes. We'll cover everything from commits, buffers, merge policies and doc values to OS settings like disk scheduler, SSD caching, and huge pages.
Finally, we'll take a look at the pipeline of getting the logs to Solr and how to make it fast and reliable: where should buffers live, which protocols to use, where should the heavy processing be done (like parsing unstructured data), and which tools from the ecosystem can help.
Running High Performance and Fault Tolerant Elasticsearch Clusters on DockerSematext Group, Inc.
Sematext engineer Rafal Kuc (@kucrafal) walks through the details of running high-performance, fault tolerant Elasticsearch clusters on Docker. Topics include: Containers vs. Virtual Machines, running the official Elasticsearch container, container constraints, good network practices, dealing with storage, data-only Docker volumes, scaling, time-based data, multiple tiers and tenants, indexing with and without routing, querying with and without routing, routing vs. no routing, and monitoring. Talk was delivered at DevOps Days Warsaw 2015.
Large Scale Log Analytics with Solr (from Lucene Revolution 2015)Sematext Group, Inc.
In this talk from Lucene/Solr Revolution 2015, Solr and centralized logging experts Radu Gheorghe and Rafal Kuć cover topics like: flow in Logstash, flow in rsyslog, parsing JSON, log shipping, Solr tuning, time-based collections and tiered clusters.
From Zero to Production Hero: Log Analysis with Elasticsearch (from Velocity ...Sematext Group, Inc.
This talk covers the basics of centralizing logs in Elasticsearch and all the strategies that make it scale with billions of documents in production. Topics include:
- Time-based indices and index templates to efficiently slice your data
- Different node tiers to de-couple reading from writing, heavy traffic from low traffic
- Tuning various Elasticsearch and OS settings to maximize throughput and search performance
- Configuring tools such as logstash and rsyslog to maximize throughput and minimize overhead
Sematext's DevOps Evangelist, Stefan Thies (@seti321), takes a Docker Logging tour through the different log collection options Docker users have, the pros and cons of each, specific and existing Docker logging solutions, tooling, the role of syslog, log shipping to ELK Stack, and more. Q&A session at end.
For the Docker users out there, Sematext's DevOps Evangelist, Stefan Thies, goes through a number of different Docker monitoring options, points out their pros and cons, and offers solutions for Docker monitoring. Webinar contains actionable content, diagrams and how-to steps.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
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Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
3. Agenda
Interacting with tools
monitoring, alerts...
Learning new tools
methods for IT
Interacting with people
meetings, feedback...
Daily structure
when are we the most productive?
10. Learning methods suitable for IT
Curious child
Apprentice
Crash test
Filling card Dancer
Place switch Parrot
Mastering Box king
Cetacan Memory palace
Monitorama EU
login: _
TutorImmersion
Enables certainty and autonomy.
We like patterns. Certainty: I know the site crashes every day at 7PM, when users come online. This is much better than the site crashing randomly, because that would be more stressful.
Autonomy: I can spin up an instance at 6AM, fiddle with the config, etc. This lowers the stress, like with rats.
It takes a long time for the brain to achieve peak performance on a difficult task. Up to 30 minutes.
Easily distracted, though. Which makes sense, 10K years ago, if you’d focus to make a fire and a tiger shows up, you’d better be easily distracted.
Inhibiting distractions (e.g. it’s just Rafal in his orange t-shirt), takes a lot of energy from the brain. And we need that energy.
Is the alert actionable? Is it tiger-actionable?
Learning tools and automation is not only about time, but also energy. Prefrontal cortex (thinking, decision-making) is slow and eats a lot of sugar.
When I say slow, I mean:
10-20KB/s memory throughput
3-4 elements in lower caches
Compare two things at once
Once we know stuff, we involve other parts of the brain, it’s much easier.
Resistance to learning may come from anxiety (we detect a status threat - am I stupid for not knowing Perl?). Can be a major blocker in learning.
One of us should say that learning is a crucial part of IT work. What is important is that we learn every day - we learn new tools, we learn new technologies, how we interact with them. The crucial part is that learning should be fun and as easy as it can be, because otherwise the exhaustion will come sooner or later especially nowadays where new tools are coming up every day.
The history of school is not as bright as we may think. In Austria in the 18th century teenagers and young man were causing trouble. Because of that the authorities came up with an idea to force young people to learn. They were put in schools for the major part of the day and given so much material that they didn't have "stupid" ideas. So it was not about expanding knowledge, but about keeping youngsters under control.
Because of that the teaching system was not developed well and you would be surprised how many schools actually don't teach people how to learn new knowledge in an efficient way.
We could ask how many of the audience actually tried to learn geography or history repeating the material over and over again. After that question we may ask how long they actually remembered details about what they were learning.
We need to say that brain encodes the information. We have two types of memory - the one that is responsible for short term storage and one that is responsible for keeping the "data" for long. We can easily access the short term storage memory and we accept all information there. The information that seems most important is sorted by our brain during sleep and we can access but it requires more effort. It is crucial to connect information with emotions, repetitions of common stuff, so that pieces of information in the long term storage can be easily connected with everyday life and thus easier accessible.
We should say that some of the methods are really suitable for IT and those are...
One of the common methods that is used to bring programmers closer together when it comes to their knowledge, i.e. during pair programming. One person from the pair is more experienced, while the other is less experienced. That way the less experienced programmer can gain knowledge and experience quicker.
Requirements:
* friendly team
* team members willing to share knowledge and not worrying about losing control
The good sides of that approach are:
* knowledge sharing
* no single point of failure when it comes to knowledge about the system
* quicker introduction of new people to the organization
* faster problem solving by having two engineers working on the same problem looking into it from different angles
* responsibility sharing
The not so good sides of that approach are:
* need of use double the time in some cases
* responsibility sharing
The crash test method is one of the best approaches to learn by example, especially if you want to gain knowledge about a certain technology - just go deeper. One of the examples of usage of this method are performance tests. They require certain, at least basic, knowledge about the system and when they are performed we learn about strong and weak points of the system, its limits, how it scales and so on. Of course a single performance test won't give us all the answers and we need to do a dozen of them to get some useful insights, etc.
The good side of that approach:
* learning by example allows to get more knowledge
* person can learn about strong and weak points of the technology in a controlled environment, without being stressed and learning "the hard way" - in production when things fail, under time pressure
The not so good sides of that approach:
* requires time and additional effort
* requires multiple repetitions to get useful insight
* requires basic knowledge about the system to get useful conclusions - without the basic knowledge the conclusions may be misleading
* the more complicated the test will be the more knowledge is required
As they say "In theory, theory and practice is the same, in practice they are not". This is what the researchers say about our brain and its ability to encode information. Most of us can't read a book from top to bottom and start using all the knowledge from that book in practice. That is not doable in majority of cases. What works though is repeating smaller cycles of learning and practicing, just like dancing. You read or you are shown a move and then you repeat that until you know it. Then the next move and next and so on. Once you know the basic moves you combine them into a dance and you practice. That way you improve.
The good things about the method:
* allows for very good encoding as theoretical knowledge is encoded while using physical moves (even clicking)
* taking smaller steps helps noticing what is not clear and allows to fully dig into the topic
The not so good things about the method:
* requires time
* requires patience
We all like to stay inside our comfort zone - it is nice there, we feel good about it, almost nothing can surprise us, etc. However such situation is the very opposite to good when it comes to learning new stuff. Because of that the place switch method suggest that people should be switched between projects, take different responsibilities - all of course within or close to their skills - you can't put devops person as a Java architect, unless you really want the project to fail drastically.
The good things about this method:
* encourages people to learn new things
* stops people from sticking in a single position helping them develop their own skills
* avoids having single points of failure inside the company as multiple people will eventually have similar knowledge about certain parts which makes the team being less stressed
* works well when combined with tutor method, i.e. pair programming or pair problem solving
The not so good things about this method:
* some people get angry when being forced to get out of their comfort zone, which can introduce conflicts in the team
* after the switch of places the overall productivity of the team will drop for a while until the knowledge is gathered
Method not exactly for developers, but in general for people interested in sharing their knowledge by giving talks. The idea is that when you need to give a speech, demo, talk or anything similar one of the ways to prepare is rehearsal. However, the rehearsal should be done in a certain way. By introducing emotions and trying to visualise the place where you'll be giving the talk, presentation or product demo will help you connect the emotions to the thing that you want to present. By doing that your mind will connect the emotions with the things you want to say or demo and help you not fall into pitfalls when doing the actual thing in front of the audience.
The good things about the method:
* allows to prepare upfront
* reduces stress of the person that is doing the rehearsals
* allows to prepare really well for the upcoming task, i.e. Steve Jobs was doing hundreds of rehearsals on the actual stage before giving the talk during Apple keynote
The not so good things about the method:
* requires time and preparation upfront
* not suitable for people doing everything at the last possible time
Use pen & paper. Make notes of everything that you think is important - you have a new command that will be useful, note that down. You see a programming language structure that you think will be of use - note that down. You see a one-liner that you think you will reuse - note that down. If you think something is or may be important, just make a note and keep those notes. Having such notes will help you get back to the topic, command, etc. and quickly remind yourself about the topic and help memorize that and encode into the long term memory.
The good things about that method:
* additional resources needed on the desk ;)
* degree of being self-organized is needed
* analyze while you learn/read/practice is the key
The not so good things about that method:
* may become copy+paste method if not used correctly
Don't try learning everything about a single topic in one step, don't go too deep. For a novice person, one trying to learn how to use linux, it doesn't make sense to learn everything about kernel functions, they only need to know how to configure their desktop, setup security properly and so on. Take it easy on yourself and your brain, try to switch from topic to topic without going too deep. The depth of knowledge will come gradually when you will get more and more experience with a given technology, infrastructure piece and so on. Of course that doesn't mean that you can omit things - after all there are always methods like apprentice method where you can learn from a more experienced colleague.
The good things about that method:
* encourages taking small steps
* small steps help memorize knowledge better
* very good when combined with dancer method or apprentice
* helps avoiding stressful situations with too much knowledge to be learned at the same time
The not so good things about that method:
* very bad for people who are easily distracted
* not good when you have a lot on your mind and you do a lot of context switching (distraction)
One of those methods that is very useful for some of us. When you are learning new things try explaining the thing that you just learned like you would have to teach someone. That way you repeat things that you've learned, you ask additional questions and of course you answer. You see what things are super clear and which are not and that makes you dig more and try to understand the topic better. This can also work when you do something in a team - if someone asks a question you may want to answer it and explain, which will develop more consistent knowledge inside your brain.
The good things about that method:
* very well suited for people who want to learn all about a given topic, because it encourages you to ask and dig into the topic
* encourages asking even the hard questions
* encodes information very well helping in long distance learning
The not so good things about that method:
* can be abused by those who like to say that they know everything
* if someone wants to just slide through the topic that method won't stop one from doing that
Context-switching reduces brain activity. If the meeting also isn’t interesting, is soon after lunch, we may fall asleep :)
If the meeting creates a status threat (e.g. someone tells me what to do => I’m not feeling that significant), I may get defensive (either being too passive, or somewhat rebellious).
If the meeting is about meeting new people, it’s probably more useful. First impression matters (we tend to quickly classify someone new as friend/foe, and if we don’t get positive stuff, we default to foe). And we’re more likely to see more negative stuff if we can’t see facial expressions.
If it’s about solving problems, usually collaboration makes learning easier (it’s a reason why pair programming is efficient). Language structures thoughts and we can use visuals to make processing even faster.
One class of problem solving is planning, so let’s talk more about that.
We like patterns, so if we’re not planning something upfront, the brain will constantly try to mold this frame of reference, taking resources in the background. Effectively making it hard to focus.
Planning itself is resource-intensive, that’s why it’s often better to do it in the morning, when our brains are still fresh. It’s also nice to do some planning at the end of the day, to tie loose ends, but that serves a different purpose: we tend not to like unfinished stuff.
Let’s talk about estimations. It’s best to make them conservative. If we don’t meet what we plan for, we get an away response from the brain (the fight-flight mechanism trying to stay away from danger => procrastinate, hard to focus). We also have a tendency to overfit for the plan, so basically we’ll rush, make mistakes, cut out stuff that may be important, etc.
If we meet expectations, we get a bit of a towards response (some dopamine, basically making us a bit “addicted” to accomplishing tasks. Not bad, ha?). If we exceed expectations, we get a strong towards response.
Dividing into small bits helps get a sense of progress (more stuff may be met).
Don’t assume you can multitask thinking. I can make an omelet and fries at the same time, but I can’t fix a bug and decide where to have my vacation at the same time.
Sprint review is a form of feedback, so let’s talk about that, and hopefully cover things like post mortems, pull request comments, yearly performance reviews and whatnot.
Our brain constantly looks for what’s wrong (the tiger). And wants to control things. So it comes naturally to say: you did this wrong, do it my way, and wrap it into “constructive feedback”. Which often fails because it creates a status threat.
We’re really good at picking up when our status feels challenged and become defensive. It’s why we say that stage fright is greater than fear of death. This anxiety activates the fight-flight mechanism and inhibits the CPU.
The simple presence of a person that’s perceived as having a higher status triggers this system in most of us. That’s why micromanagement is bad.
Instead of appreciating success/failure, it’s often better to appreciate effort. When we appreciate our own effort we get dopamine, so we’re more likely to raise to the next challenge, because we’re addicted to doing that. Evaluation of success creates status threats.
Rather than telling someone what to do, it’s often better to ask questions and facilitate their own insights, help them make a change.
We can also facilitate change and lower status threats by sharing our own insights (provided they don’t count as bragging) and… I’m going to use the F word here: feelings.
Sharing feelings invites empathy. Empathy lowers the status threat.
One thing about feelings: they happen anyway. Suppressing them is expensive (energy-wise), and it’s more efficient to take them up into consciousness and think about their significance. Then, we can use this information to control behavior. This shifts activity from our limbic system (fight-flight mechanism) to our prefrontal cortex (the CPU).
Sleep is important. Too little sleep means the amygdala larger, which in turn makes us more anxious but less able to focus.
Brain eats glucose. Though some studies suggest that it can eat fat if it constantly gets too little glucose, which might actually be better. Either way, the brain needs energy, up to 20% of the body’s energy, though it’s only up to 2% of the mass.
That’s why in the morning, after an hour or two from when we wake up, it’s easiest to focus. That’s when it’s best to do the important stuff. It’s usually recommended not to wake up suddenly, not to snooze the alarm clock, otherwise we disturb the natural process of waking up.
Before lunch, we tend to run out of glucose, so it’s harder to focus, so we should do something more relaxing. After lunch, we need something more stressful to get “activated”. Then, towards the end of the day, we tend to get tired again, so more relaxing activities are better.
Usually bad, because it tends to take more time and energy than anticipated, and we’re left with little to do the important stuff.
Plus, our brain is an emergency junkie. We’re quick to label something easy as urgent and deal with it right away, delaying what’s important. Even if we refrain from doing those things, it may hurt, because they still linger there, like idle threads that still have to be visited by the CPU.
Some Emails may not be bad, may help with planning. If we account for urgency as a factor of importance, and still end up with a decent plan, we should be good to go.
Low brain activity (e.g. from switching activities), if it’s under low stress, stimulates creativity. That’s when we’re more likely to have insights.
That’s why we sometimes “park” a topic or “let it bake”, or “sleep on it”.