Modeling Count-based Raster Data with ArcGIS and RAzavea
This presentation outlines the conceptual framework for building regression models of event counts where the unit of analysis is small. It explains how ArcGIS for Desktop can be used to build raster data sets that are modeled as generalized linear models within the open source R package.
More and more cities, regions and countries gather point cloud data through airborne Lidar sensors. We explain what is point cloud data, discuss Flanders' large point cloud and the challenges that pose the task of computing a 3D model for each building in Flanders.
Modeling Count-based Raster Data with ArcGIS and RAzavea
This presentation outlines the conceptual framework for building regression models of event counts where the unit of analysis is small. It explains how ArcGIS for Desktop can be used to build raster data sets that are modeled as generalized linear models within the open source R package.
More and more cities, regions and countries gather point cloud data through airborne Lidar sensors. We explain what is point cloud data, discuss Flanders' large point cloud and the challenges that pose the task of computing a 3D model for each building in Flanders.
Slides presented by me on behalf of Geonovum and the project on the Geospatial Sensor Webs conference 2016 organized by 52North in Münster, Germany:
http://52north.org/about/other-activities/geospatial-sensor-webs-conference
The slides give an overview of the Smart Emission project with a focus on the data infrastructure, data management (ETL) and providing access to sensor data via OGC-standards (SOS, WMS, WFS, STA).
Multiobjective Design of Micro- and Macrostructures.
"To craft and analyze algorithms that search for optimal structures is the subject of the research in the multiobjective optimization and decision analysis group, and in the talk, we will discuss approaches, their theoretical limits, as well as applications to challenging design problems across multiple scales."
An assessment-based process for modifying the built fabric of historic centre...Beniamino Murgante
An assessment-based process for modifying the built fabric of historic centres: the case of Como in Lombardy
Pier Luigi Paolillo, Alberto Benedetti, Umberto Baresi, Luca Terlizzi, Giorgio Graj -Polytechnic of Milan
Presentation of a geotagging approach for social media content with a refined language modelling approach. Presented at PAISI workshop, co-located with PA-KDD 2015, Ho Chi Minh City, Vietnam
Geotagging Social Media Content with a Refined Language Modelling ApproachSymeon Papadopoulos
Presentation of a geotagging approach for social media content with a refined language modelling approach. Presented at PAISI workshop, co-located with PA-KDD 2015, Ho Chi Minh City, Vietnam
Detecting Semantic Drift for ontology maintenance - Acting on Change 2016PERICLES_FP7
This presentation was delivered by Sándor Darányi (University of Borås, Sweden) and Panos Mitzias (CERTH/ITI, Greece) at PERICLES final project conference 'Acting on Change: New Approaches and Future Practices in LTDP' (Wellcome Collection Conference Centre, London, 30 Nov -1 Dec 2016).
This 'PERICLES in practice' session covered the PERICLES approach in addressing evolving semantics and the use of Somoclu and SemaDrift in the detection of drift to alert ontology maintenance and object appraisal by designated workflows.
http://pericles-project.eu
Stability issues in the electric power grid originate from the rising of renewable energy generation and the increasing number of electric vehicles. The uncertainty and the distributed nature of generation and consumption demand for optimal allocation of energy resources, which, in the absence of sufficient control reserve for power generation, can be achieved using demand-response. A price signal can be exploited to reflect the availability of energy. In this paper, market-based energy allocation solutions for small energy grids are discussed and implemented in a simulator, which is released for open use. Artificial neural network controllers for energy prosumers can be designed to minimize individual and overall running costs. This enables a better use of local energy production from renewable sources, while considering residents’ necessities to minimize discomfort.
As electricity is difficult to store, it is crucial to strictly maintain the balance between production and consumption. The integration of intermittent renewable energies into the production mix has made the management of the balance more complex. However, access to near real-time data and communication with consumers via smart meters suggest demand response. Specifically, sending signals would encourage users to adjust their consumption according to the production of electricity. The algorithms used to select these signals must learn consumer reactions and optimize them while balancing exploration and exploitation. Various sequential or reinforcement learning approaches are being considered.
Online violence amplifies IRL discriminations, and the lack of diversity grows in a vicious circle. Understanding cyber-violence, its forms and mechanisms, can help us fight back. To process massive volumes of data, AI finally comes into play for good.
More Related Content
Similar to From spatial complexity to real estate prices: statistical and stochastic models by Sarah Soleiman-Halevy, PhD Candidate @Meilleurs Agents
Slides presented by me on behalf of Geonovum and the project on the Geospatial Sensor Webs conference 2016 organized by 52North in Münster, Germany:
http://52north.org/about/other-activities/geospatial-sensor-webs-conference
The slides give an overview of the Smart Emission project with a focus on the data infrastructure, data management (ETL) and providing access to sensor data via OGC-standards (SOS, WMS, WFS, STA).
Multiobjective Design of Micro- and Macrostructures.
"To craft and analyze algorithms that search for optimal structures is the subject of the research in the multiobjective optimization and decision analysis group, and in the talk, we will discuss approaches, their theoretical limits, as well as applications to challenging design problems across multiple scales."
An assessment-based process for modifying the built fabric of historic centre...Beniamino Murgante
An assessment-based process for modifying the built fabric of historic centres: the case of Como in Lombardy
Pier Luigi Paolillo, Alberto Benedetti, Umberto Baresi, Luca Terlizzi, Giorgio Graj -Polytechnic of Milan
Presentation of a geotagging approach for social media content with a refined language modelling approach. Presented at PAISI workshop, co-located with PA-KDD 2015, Ho Chi Minh City, Vietnam
Geotagging Social Media Content with a Refined Language Modelling ApproachSymeon Papadopoulos
Presentation of a geotagging approach for social media content with a refined language modelling approach. Presented at PAISI workshop, co-located with PA-KDD 2015, Ho Chi Minh City, Vietnam
Detecting Semantic Drift for ontology maintenance - Acting on Change 2016PERICLES_FP7
This presentation was delivered by Sándor Darányi (University of Borås, Sweden) and Panos Mitzias (CERTH/ITI, Greece) at PERICLES final project conference 'Acting on Change: New Approaches and Future Practices in LTDP' (Wellcome Collection Conference Centre, London, 30 Nov -1 Dec 2016).
This 'PERICLES in practice' session covered the PERICLES approach in addressing evolving semantics and the use of Somoclu and SemaDrift in the detection of drift to alert ontology maintenance and object appraisal by designated workflows.
http://pericles-project.eu
Stability issues in the electric power grid originate from the rising of renewable energy generation and the increasing number of electric vehicles. The uncertainty and the distributed nature of generation and consumption demand for optimal allocation of energy resources, which, in the absence of sufficient control reserve for power generation, can be achieved using demand-response. A price signal can be exploited to reflect the availability of energy. In this paper, market-based energy allocation solutions for small energy grids are discussed and implemented in a simulator, which is released for open use. Artificial neural network controllers for energy prosumers can be designed to minimize individual and overall running costs. This enables a better use of local energy production from renewable sources, while considering residents’ necessities to minimize discomfort.
Similar to From spatial complexity to real estate prices: statistical and stochastic models by Sarah Soleiman-Halevy, PhD Candidate @Meilleurs Agents (20)
As electricity is difficult to store, it is crucial to strictly maintain the balance between production and consumption. The integration of intermittent renewable energies into the production mix has made the management of the balance more complex. However, access to near real-time data and communication with consumers via smart meters suggest demand response. Specifically, sending signals would encourage users to adjust their consumption according to the production of electricity. The algorithms used to select these signals must learn consumer reactions and optimize them while balancing exploration and exploitation. Various sequential or reinforcement learning approaches are being considered.
Online violence amplifies IRL discriminations, and the lack of diversity grows in a vicious circle. Understanding cyber-violence, its forms and mechanisms, can help us fight back. To process massive volumes of data, AI finally comes into play for good.
In the energy sector, the use of temporal data stands as a pivotal topic. At GRDF, we have developed several methods to effectively handle such data. This presentation will specifically delve into our approaches for anomaly detection and data imputation within time series, leveraging transformers and adversarial training techniques.
Natasha shares her experience to delve into the complexities, challenges, and strategies associated with effectively leading tech teams dispersed across borders.
Nour and Maria present the work they did at Tweag, Modus Create innovation arm, where the GenAI team developed an evaluation framework for Retrieval-Augmented Generation (RAG) systems. RAG systems provide an easy and low-cost way to extend the knowledge of Large Language Models (LLMs) but measuring their performance is not an easy task.
The presentation will review existing evaluation frameworks, ranging from those based on the traditional ML approach of using groundtruth datasets, including Tweag's, to those that use LLMs to compute evaluation metrics.
It will also delve into the practical implementation of Tweag's chatbot over two distinct documents datasets and provide insights on chunking, embedding and how open source and commercial LLMs compare.
Sharone Dayan, Machine Learning Engineer and Daria Stefic, Data Scientist, both from Contentsquare, delve into evaluation strategies for dealing with partially labelled or unlabelled data.
Laure talked about a very hot topic in the community at the moment with the ChatGPT phenomenon: how to supervise a PhD thesis in NLP in the age of Large Language Models (LLMs)?
Abstract: Who hasn't heard of the "Pilot Syndrome"? 85% of Data Science Pilots remain pilots and do not make it to the production stage. Let's build a production-ready and end-user-friendly Data Science application. 100% python and 100% open source.
Phase 1 | Building the GUI: create an interactive and powerful interface in a few lines of code
Phase 2 | Integrated back end: Manage your models and pipelines and create scenarios the smart way
"Nature Language Processing for proteins" by Amélie Héliou, Software Engineer @ Google Research
Abstract: Over the past few months, Large Language Models have become very popular.
We'll see how a simple LLM works, from input sentence to prediction.
I'll then present an application of LLM to protein name prediction.
Twitter: @Amelie_hel
"We are not passing by, and we are not a trend". What if an automated and large scale version of the Bechdel-Wallace test could confirm the speech of Alice Diop at the Cesar 2023?
That's the objective of BechdelAI : to build a tool based on Artificial Intelligence and open-source, allowing to measure the inequalities and the under-representation of women in movies and audiovisual.
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.
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.
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.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
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.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
The Internet of Things (IoT) is a revolutionary concept that connects everyday objects and devices to the internet, enabling them to communicate, collect, and exchange data. Imagine a world where your refrigerator notifies you when you’re running low on groceries, or streetlights adjust their brightness based on traffic patterns – that’s the power of IoT. In essence, IoT transforms ordinary objects into smart, interconnected devices, creating a network of endless possibilities.
Here is a blog on the role of electrical and electronics engineers in IOT. Let's dig in!!!!
For more such content visit: https://nttftrg.com/
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com