Green House Gas and Automatic Weather Station data analysis. We compare seasonal variation of CO2 & CH4 vs Wind Speed and Wind direction. How to analyze wind rose diagram.
At the technology round table strategic presentations on Industrial Refrigeration will be presented by leading industry representatives, followed by a panel discussion.
Air conditioning systems
2. Properties of moist air
3. Moist air processes
4. Space air conditioning
5. Indoor air quality--comfort and health
6. Heat transfer from human body
7. Heat transfer in building envelopes
8. Infiltration heat load and weatherizing
9. Computation of the heating load
10. Heat gain by solar radiation
11. Computation of the cooling load
12. Energy requirements for HVAC systems; building energy audit
13. Fans--performance, selection, and installation
14. Air flow in ducts and fittings
15. Design of duct systems
16. Codes & standards for building energy systems
17. Annual energy consumption
Convective Heat Transfer Measurements at the Martian SurfaceSamet Baykul
DATE: 2018.11.28
This is a review of an article which introduces a new sensing method to characterize the convective wind activity on the surface of Mars
TOPICS:
• Introduction
• Objective of the Study
• Cited Studies
• Setup
• Mathematical Model
• Experimental Backing
• Results and Discussions
• Conclusions
• Suggestions
At the technology round table strategic presentations on Industrial Refrigeration will be presented by leading industry representatives, followed by a panel discussion.
Air conditioning systems
2. Properties of moist air
3. Moist air processes
4. Space air conditioning
5. Indoor air quality--comfort and health
6. Heat transfer from human body
7. Heat transfer in building envelopes
8. Infiltration heat load and weatherizing
9. Computation of the heating load
10. Heat gain by solar radiation
11. Computation of the cooling load
12. Energy requirements for HVAC systems; building energy audit
13. Fans--performance, selection, and installation
14. Air flow in ducts and fittings
15. Design of duct systems
16. Codes & standards for building energy systems
17. Annual energy consumption
Convective Heat Transfer Measurements at the Martian SurfaceSamet Baykul
DATE: 2018.11.28
This is a review of an article which introduces a new sensing method to characterize the convective wind activity on the surface of Mars
TOPICS:
• Introduction
• Objective of the Study
• Cited Studies
• Setup
• Mathematical Model
• Experimental Backing
• Results and Discussions
• Conclusions
• Suggestions
I presentation I gave at the Zero Conference (https://zerokonferansen.no/) on the role of mitigation in the industry sector relative to other sectors. The session was Scenarier for et Grønt Industrieventyr on 1 November.
This is my presentation at AMS 2017 97th annual meeting. The topic was mainly talking about how we utilized ADS-B data Mode-S data to complement the insufficient of traditional weather data on aviation meteorology.
If you are interested in my research, welcome to refer my paper at https://ams.confex.com/ams/97Annual/webprogram/Paper306201.html.
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...debasishagri
Climate change is one of the most important global environmental challenges of this century. Green House Gases (GHGs) are the main culprit for this problem. Though much of research has already been done about the distribution and sources (and sinks) of GHGs , still much more uncertainties are present. Currently, there are only a few satellite instruments in orbit which are able to measure atmospheric GHGs. The High Resolution Infrared Radiation Sounder (HIRS), the Atmospheric InfraRed Sounder (AIRS), and the Infrared Atmospheric Sounding Interferometer (IASI) perform measurements in the thermal infrared (TIR) spectral region. But these are having low sensitivity to lower troposphere. In contrast to this, the sensitivity of instruments measuring reflected solar radiation in the near-infrared (NIR)/shortwave infrared (SWIR) spectral region is much more constant (with height) and shows maximum values near the surface. At present, SCIAMACHY aboard ENVISAT launched in 2002 and TANSO (Thermal And Near infrared Sensor for carbon Observation) aboard GOSAT (Greenhouse gases Observing SATellite) launched in 2009 are the only orbiting instruments measuring in NIR region. Among all the algorithms the WFM-DOAS algorithm (Weighting Function Modified Differential Optical Absorption Spectroscopy) developed at the University of Bremen for the retrieval of trace gases from SCIAMACHY (Buchwitz et al.2005) is mostly used. This is based on the principle of differential detection of radiance in gaseous absorption channels with respect to neighboring atmospheric transparent spectral channels (not influenced by gas) to detect the conc. of desired gas. But scattering at aerosol and/or cloud particles remains a major source of uncertainty for SCIAMACHY XCO2 retrievals(Houweling 2005, Schneising 2008).Of late with the use of new merged fit window approach scientists have come up with less than 0.5 ppm error in the estimation of CO2 in the presence of thin cirrus cloud(Reuter, Buchwitz et. al. 2010). Schneising et. al.,2007,retrieved d three year’s column-averaged CO2 dry air mole fraction from the SCIAMACHY instrument using the retrieval algorithm WFM-DOAS version 1.0, with precision of about 2 ppm. In India a study was undertaken to compare the atmospheric methane concentration pattern from SCIAMACHY with the vegetation dynamics from SPOT, showed fairly good correlation of methane emission with the rice cultivation(Goroshi et. al.).
I presentation I gave at the Zero Conference (https://zerokonferansen.no/) on the role of mitigation in the industry sector relative to other sectors. The session was Scenarier for et Grønt Industrieventyr on 1 November.
This is my presentation at AMS 2017 97th annual meeting. The topic was mainly talking about how we utilized ADS-B data Mode-S data to complement the insufficient of traditional weather data on aviation meteorology.
If you are interested in my research, welcome to refer my paper at https://ams.confex.com/ams/97Annual/webprogram/Paper306201.html.
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...debasishagri
Climate change is one of the most important global environmental challenges of this century. Green House Gases (GHGs) are the main culprit for this problem. Though much of research has already been done about the distribution and sources (and sinks) of GHGs , still much more uncertainties are present. Currently, there are only a few satellite instruments in orbit which are able to measure atmospheric GHGs. The High Resolution Infrared Radiation Sounder (HIRS), the Atmospheric InfraRed Sounder (AIRS), and the Infrared Atmospheric Sounding Interferometer (IASI) perform measurements in the thermal infrared (TIR) spectral region. But these are having low sensitivity to lower troposphere. In contrast to this, the sensitivity of instruments measuring reflected solar radiation in the near-infrared (NIR)/shortwave infrared (SWIR) spectral region is much more constant (with height) and shows maximum values near the surface. At present, SCIAMACHY aboard ENVISAT launched in 2002 and TANSO (Thermal And Near infrared Sensor for carbon Observation) aboard GOSAT (Greenhouse gases Observing SATellite) launched in 2009 are the only orbiting instruments measuring in NIR region. Among all the algorithms the WFM-DOAS algorithm (Weighting Function Modified Differential Optical Absorption Spectroscopy) developed at the University of Bremen for the retrieval of trace gases from SCIAMACHY (Buchwitz et al.2005) is mostly used. This is based on the principle of differential detection of radiance in gaseous absorption channels with respect to neighboring atmospheric transparent spectral channels (not influenced by gas) to detect the conc. of desired gas. But scattering at aerosol and/or cloud particles remains a major source of uncertainty for SCIAMACHY XCO2 retrievals(Houweling 2005, Schneising 2008).Of late with the use of new merged fit window approach scientists have come up with less than 0.5 ppm error in the estimation of CO2 in the presence of thin cirrus cloud(Reuter, Buchwitz et. al. 2010). Schneising et. al.,2007,retrieved d three year’s column-averaged CO2 dry air mole fraction from the SCIAMACHY instrument using the retrieval algorithm WFM-DOAS version 1.0, with precision of about 2 ppm. In India a study was undertaken to compare the atmospheric methane concentration pattern from SCIAMACHY with the vegetation dynamics from SPOT, showed fairly good correlation of methane emission with the rice cultivation(Goroshi et. al.).
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
2. G.H.G
1.G.H.G(Green House Gases)
We are using PICARRO machine for measurement of
GHG like CO2 and CH4.
Mechanism of Picarro machine is cavity ring down
spectroscopy method
9. AWS
1.AWS(Atmospheric Weather Sensor):
We used to get this Wind speed , Wind
direction,Temprature and Humidity data from
different sensors locating in 10m,20m&30m
tower.