Presented at Bitkom AK Big Data & Advanced Analytics strategy workshop on 30 June 2021. We point to scalability across data schemata as a major current bottleneck on the road towards building a data-driven organization, and illustrate on the example of Analyst-2 (https://analyst-2.ai/) how Autonomous Analytics may provide a way forward.
Presented at Bitkom AK Big Data & Advanced Analytics strategy workshop on 30 June 2021. We point to scalability across data schemata as a major current bottleneck on the road towards building a data-driven organization, and illustrate on the example of Analyst-2 (https://analyst-2.ai/) how Autonomous Analytics may provide a way forward.
Continuous Integration: Getting your department to drink the Kool-AidJenKnight
Everyone wants automated regression, automated builds, and single click deployments. Who wouldn’t want day to day development blockers eliminated. However, getting these things happening in your office might often face fierce resistance. Here is how one small department banded together for success.
Presented by Jen Knight, Michael Benning
History, definition, need, attributes, applications of data warehousing ; difference between data mining, big data, database and data warehouse ; future scope
Nimalox is a non steroidal anti inflammatory drug with
analgesic and antipyretic properties and cox-2
selective inhibition
it's a study to re-branding Nimalox
MBA Cairo University
Tuning for Systematic Trading: Talk 2: Deep LearningSigOpt
This talk explains how to train deep learning and other expensive models with parallelism and multitask optimization to reduce wall clock time. Tobias Andreassen, who supports a number of our systematic trading customers, presented the intuition behind Bayesian optimization for model optimization with a single or multiple (often competing) metrics. Many times it makes sense to analyze a second metric to avoid myopic training runs that overfit on your data, or otherwise don’t represent or impede performance in real-world scenarios.
I created this deck some time ago for a client project. It was a quick introduction for the client on our approach to design, develop, and test their new product.
The hypothesis driven development approach is pretty well known now although I don't see it employed very often, possibly because of the cultural and logistical implications.
Continuous Integration: Getting your department to drink the Kool-AidJenKnight
Everyone wants automated regression, automated builds, and single click deployments. Who wouldn’t want day to day development blockers eliminated. However, getting these things happening in your office might often face fierce resistance. Here is how one small department banded together for success.
Presented by Jen Knight, Michael Benning
History, definition, need, attributes, applications of data warehousing ; difference between data mining, big data, database and data warehouse ; future scope
Nimalox is a non steroidal anti inflammatory drug with
analgesic and antipyretic properties and cox-2
selective inhibition
it's a study to re-branding Nimalox
MBA Cairo University
Tuning for Systematic Trading: Talk 2: Deep LearningSigOpt
This talk explains how to train deep learning and other expensive models with parallelism and multitask optimization to reduce wall clock time. Tobias Andreassen, who supports a number of our systematic trading customers, presented the intuition behind Bayesian optimization for model optimization with a single or multiple (often competing) metrics. Many times it makes sense to analyze a second metric to avoid myopic training runs that overfit on your data, or otherwise don’t represent or impede performance in real-world scenarios.
I created this deck some time ago for a client project. It was a quick introduction for the client on our approach to design, develop, and test their new product.
The hypothesis driven development approach is pretty well known now although I don't see it employed very often, possibly because of the cultural and logistical implications.
OSMC 2022 | Unifying Observability Weaving Prometheus, Jaeger, and Open Sourc...NETWAYS
Observability is a hugely popular topic, however, for open-source users, significant challenges remain. For starters, related licensing is frequently problematic—and even when it works, there is no pure Apache 2.0 licensed technology to get data collection and visibility into your logs, metrics, and traces. Thankfully, this is gradually changing as the community builds new capabilities into OpenSearch Dashboards to unify the visualization of logs from OpenSearch, metrics from PromQL compatible systems, and traces from Jaeger. In this session, we’ll examine how this important project is evolving as a fork of the previously popular ELK stack. We’ll also take a closer look at the current state of OpenSearch and Jaeger and discuss how these efforts are going to provide a foundation for unified observability to the open-source communities. By using OpenTelemetry for data collection, this foundation provides a pure Apache 2.0 licensed open-source platform for unified observability. OpenSearch also includes features like Alerting and Machine Learning, which are not part of Jaeger today. The work on this foundational integration is well underway and will provide open-source users with a solid alternative to vendor controlled and provided solutions. This also opens up the marketplace for solutions to be created to host and manage these at scale, something we’ve seen with countless other CNCF projects. This talk will be presented by a contributor and maintainer of OpenSearch, Jaeger, and OpenTelemetry, which are all vibrant user communities. Join the conversation!
Is React The Best Thing Since Sliced Bread?Synerzip
In this webinar, we’ll cover fundamentals of the React library, including how state is managed and how to combine it with other popular JavaScript libraries to minimize development effort and maximize your capabilities.
Covered in this webinar:
- What are React’s strengths?
- How does it compare to other popular frameworks?
- Does React use an MVC paradigm or something else?
- What are other popular JS libraries that are often combined with React?
Crude-Oil Scheduling Technology: moving from simulation to optimizationBrenno Menezes
Scheduling technology either commercial or homegrown in today’s crude-oil refining industries relies on a complex simulation of scenarios where the user is solely responsible for making many different decisions manually in the search for feasible solutions over some limited time-horizon i.e., trial-and-error heuristics. As a normal outcome, schedulers abandon these solutions and then return to their simpler spreadsheet simulators due to: (i) time-consuming efforts to configure and manage numerous scheduling scenarios, and (ii) requirements of updating premises and situations that are constantly changing. Moving to solutions based in optimization rather than simulation, the lecture describes the future steps in the refactoring of the scheduling technology in PETROBRAS considering in separate the graphic user interface (GUI) and data communication developments (non-modeling related), and the modeling and process engineering related in an automated decision-making with built-in problem representation facilities and integrated data handling features among other techniques in a smart scheduling frontline.
A review of the paper “Ad Click Prediction: a View from the Trenches”
The paper discusses predicting ad click--through rates (CTR) which is a massive-scale learning problem central to the multi-billion dollar online advertising industry.
Presented by Mazen & Arzam in the Data Intensive Computing class at KTH, Stockholm, Sweden.
Link of the paper: http://research.google.com/pubs/pub41159.html
Debug, Analyze and Optimize Games with Intel Tools - Matteo Valoriani - Codem...Codemotion
Use the full potential of your favorite platform while improving a videogame's frame rate and performance with GPA (Graphic Performance Analyzer), a free tool powered by Intel. Featuring a convenient panel overlay, you can quickly identify problem areas and experiment with improvements without having to recompile the source code. System Analyzing to isolate common bottlenecks that affect your game's performance in real time. Analyze performance on a single frame down to the draw call level. Identify where you can evenly distribute workloads across the CPU and GPU.
Debug, Analyze and Optimize Games with Intel Tools - Matteo Valoriani - Codem...Codemotion
Use the full potential of your favorite platform while improving a videogame's frame rate and performance with GPA (Graphic Performance Analyzer), a free tool powered by Intel. Featuring a convenient panel overlay, you can quickly identify problem areas and experiment with improvements without having to recompile the source code. System Analyzing to isolate common bottlenecks that affect your game's performance in real time. Analyze performance on a single frame down to the draw call level. Identify where you can evenly distribute workloads across the CPU and GPU.
2020 vision - the journey from research lab to real-world productKTN
This presentation, delivered by Jag Minhas, CEO and Founder, Sensing Feeling, was the first presentation of the Implementing AI: Vision Systems Webinar.
WebSphere Technical University: Introduction to the Java Diagnostic ToolsChris Bailey
IBM provides a number of free tools to assist in monitoring and diagnosing issues when running
any Java application - from Hello World to IBM or third-party, middleware-based applications. This
session introduces attendees to those tools, highlights how they have been extended with IBM
middleware product knowledge, how they have been integrated into IBM’s development tools,
and how to use them to investigate and resolve real-world problem scenarios
Presented at the WebSphere Technical University 2014, Dusseldorf
CK: from ad hoc computer engineering to collaborative and reproducible data s...Grigori Fursin
Designing novel computer systems and optimizing their software is becoming too tedious, ad hoc, time consuming and error prone due to enormous number of available design and optimization choices. Empirical autotuning combined with run-time adaptation and machine learning has been demonstrating some potential to address above challenges for several decades but is still far from the widespread production. The main reasons include unbearably long exploration and training times, ever changing tools and their interfaces, lack of a common experimental methodology, lack of diverse and representative benchmarks, and lack of unified mechanisms for knowledge building and exchange apart from publications where reproducibility and reusability of results is often not even considered.
I will present our community-driven solution to above problems based on our open-source Collective Knowledge technology (CK) that can gradually organize, exchange and reuse knowledge and experience in computer engineering. CK helps share various artifacts (benchmarks, data sets, libraries, tools) as unified, reusable and Python-based components with JSON meta description via GITHUB. Researchers can then quickly prototype and crowdsource various experimental workflows such as performance and energy autotuning, design space exploration and run-time adaptation. At the same time, CK continuously analyzes and extrapolates all collected knowledge using powerful data science techniques to automatically model computer systems' behavior, predict better optimizations or hardware configurations, and eventually enable faster, more power efficient, reliable and self-tuning software and hardware. Furthermore, CK can record any unexpected behavior in a reproducible way and expose it to an interdisciplinary community to find missing features and improve models. Live demo of our approach is available at http://cknowledge.org/repo .
Performance Test Automation With GatlingKnoldus Inc.
Gatling is a lightweight dsl written in scala by which you can treat your performance test as a production code means you can easily write a readable code to test the performance of an application it s a framework based on Scala, Akka and Netty.
Advanced Optimization for the Enterprise WebinarSigOpt
Building on the TWIML eBook, TWIMLcon event and TWIML podcast series that explore Machine Learning Platforms in great detail, this webinar examines the machine learning platforms that power enterprise leaders in AI. SigOpt CEO Scott Clark will provide an overview of critical technical capabilities that our customers have prioritized in their ML platforms.
Review these slides to learn about:
- Critical capabilities for data, experiment and model management
- Tradeoffs between building and buying these capabilities
- Lessons from the implementation of these platforms by AI leaders
Why focus on these platforms and the capabilities that power them? Nearly every company is investing in machine learning that differentiates products or generates revenue. These so-called "differentiated models" represent the biggest opportunity for AI to transform the business. Most of these teams find success hiring expert data scientists and machine learning engineers who can build these models. But most of these teams also struggle to create a more sustainable, scalable and reproducible process for model development, and have begun building ML platforms to tackle this challenge.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
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.
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.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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.
2. What is WinOpt ?
Windows Optimization Tool .
For the architects to make early design decisions on
the building to incorporate energy efficiency
measures.
2
3. What WinOpt does ?
Takes input from user.
Finds out the most energy efficient configuration for
the building by performing optimal number of
simulations .
Displays output in tabular and graphical form for
analytics.
3
4. PARAMETERS
Azimuth angle
Window to wall ratio
Overhang depth
Aspect ratio
Glass type – SHGC, U factor, VLT
4
6. Algorithms of WinOpt
A hybrid global algorithm that uses
Hooke-Jeeves algorithm – It can be run using multiple
starting points .
Particle Swarm Optimization algorithm – For the
continuous independent variables to reduce
computation time.
6
12. What’s next ?
Convert single zone to 5 zone model.
Include optimization for Life Cycle energy, Life Cycle
cost.
Caching the results for quick retrieval.
Improve the visualization.
Add new parameters.
Utilize computer clusters to speed up the simulations.
12
