Malaria 3 point_0h
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The document describes a web-based malaria disease surveillance and mapping project in northern Botswana. The project aimed to address slow reporting times and inefficiencies in the existing paper-based system by developing (1) smartphone forms for health workers to enter and submit data in real-time, and (2) a web-based tool for aggregating, analyzing, and mapping reported cases on an interactive map. The project helped reduce reporting times from 3-4 weeks to near real-time, and allowed health officials to more immediately investigate and respond to reported outbreaks.
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The document describes a web-based malaria surveillance and mapping project in northern Botswana. The project aimed to address slow reporting times from a paper-based system by developing (1) smartphone forms for health workers to enter data in real-time and (2) a web tool to view aggregated data and map reported cases. This allowed officials to more quickly analyze outbreaks compared to the previous paper system where it took up to 4 weeks to aggregate data.
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This document is a resume for Jay L. Stanley Jr. that summarizes his 25+ years of experience developing software and hardware systems across various industries including medical, military, and banking. It outlines his technical skills and experience developing projects using multiple programming languages, databases, operating systems, and development tools. It also provides details of his educational background and work history at various companies where he served in senior software engineering and leadership roles.
Event tracking for real time unaware sensitivity analysis
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects in Chennai, 2013 IEEE JAVA, .NET Projects in Trichy, 2013 IEEE JAVA, .NET Projects in Karur, 2013 IEEE JAVA, .NET Projects in Erode, 2013 IEEE JAVA, .NET Projects in Madurai, 2013 IEEE JAVA, .NET Projects in Salem, 2013 IEEE JAVA, .NET Projects in Coimbatore, 2013 IEEE JAVA, .NET Projects in Tirupur, 2013 IEEE JAVA, .NET Projects in Bangalore, 2013 IEEE JAVA, .NET Projects in Hydrabad, 2013 IEEE JAVA, .NET Projects in Kerala, 2013 IEEE JAVA, .NET Projects in Namakkal, IEEE JAVA, .NET Image Processing, IEEE JAVA, .NET Face Recognition, IEEE JAVA, .NET Face Detection, IEEE JAVA, .NET Brain Tumour, IEEE JAVA, .NET Iris Recognition, IEEE JAVA, .NET Image Segmentation, Final Year JAVA, .NET Projects in Pondichery, Final Year JAVA, .NET Projects in Tamilnadu, Final Year JAVA, .NET Projects in Chennai, Final Year JAVA, .NET Projects in Trichy, Final Year JAVA, .NET Projects in Erode, Final Year JAVA, .NET Projects in Karur, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Tirunelveli, Final Year JAVA, .NET Projects in Madurai, Final Year JAVA, .NET Projects in Salem, Final Year JAVA, .NET Projects in Tirupur, Final Year JAVA, .NET Projects in Namakkal, Final Year JAVA, .NET Projects in Tanjore, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Bangalore, Final Year JAVA, .NET Projects in Hydrabad, Final Year JAVA, .NET Projects in Kerala, Final Year JAVA, .NET IEEE Projects in Pondichery, Final Year JAVA, .NET IEEE Projects in Tamilnadu, Final Year JAVA, .NET IEEE Projects in Chennai, Final Year JAVA, .NET IEEE Projects in Trichy, Final Year JAVA, .NET IEEE Projects in Erode, Final Year JAVA, .NET IEEE Projects in Karur, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Tirunelveli, Final Year JAVA, .NET IEEE Projects in Madurai, Final Year JAVA, .NET IEEE Projects in Salem, Final Year JAVA, .NET IEEE Projects in Tirupur, Final Year JAVA, .NET IEEE Projects in Namakkal, Final Year JAVA, .NET IEEE Projects in Tanjore, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Bangalore, Final Year JAVA, .NET IEEE Projects in Hydrabad, Final Year JAVA, .NET IEEE Projects in Kerala, Final Year IEEE MATLAB Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE MATLAB Projects, Academic Final Year IEEE MATLAB Projects 2013, Academic Final Year IEEE MATLAB Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB
Java event tracking for real-time unaware sensitivity analysis
This paper introduces an event tracking platform for online sensitivity analysis in large-scale real-time data acquisition systems. The platform is designed to succinctly interpret real-time data and translate it into timely corrective actions. It assumes systems can capture data in real-time and adapt flexibly. The proposed event tracking method describes variables and system state as collections of events, with more frequent input variables having greater impact on analysis. Experiments showed the method was 10% more computationally efficient and required only 0.5% of the time of an entropy-based method, without loss of accuracy.
Event tracking for real time unaware sensitivity analysis
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects in Chennai, 2013 IEEE JAVA, .NET Projects in Trichy, 2013 IEEE JAVA, .NET Projects in Karur, 2013 IEEE JAVA, .NET Projects in Erode, 2013 IEEE JAVA, .NET Projects in Madurai, 2013 IEEE JAVA, .NET Projects in Salem, 2013 IEEE JAVA, .NET Projects in Coimbatore, 2013 IEEE JAVA, .NET Projects in Tirupur, 2013 IEEE JAVA, .NET Projects in Bangalore, 2013 IEEE JAVA, .NET Projects in Hydrabad, 2013 IEEE JAVA, .NET Projects in Kerala, 2013 IEEE JAVA, .NET Projects in Namakkal, IEEE JAVA, .NET Image Processing, IEEE JAVA, .NET Face Recognition, IEEE JAVA, .NET Face Detection, IEEE JAVA, .NET Brain Tumour, IEEE JAVA, .NET Iris Recognition, IEEE JAVA, .NET Image Segmentation, Final Year JAVA, .NET Projects in Pondichery, Final Year JAVA, .NET Projects in Tamilnadu, Final Year JAVA, .NET Projects in Chennai, Final Year JAVA, .NET Projects in Trichy, Final Year JAVA, .NET Projects in Erode, Final Year JAVA, .NET Projects in Karur, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Tirunelveli, Final Year JAVA, .NET Projects in Madurai, Final Year JAVA, .NET Projects in Salem, Final Year JAVA, .NET Projects in Tirupur, Final Year JAVA, .NET Projects in Namakkal, Final Year JAVA, .NET Projects in Tanjore, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Bangalore, Final Year JAVA, .NET Projects in Hydrabad, Final Year JAVA, .NET Projects in Kerala, Final Year JAVA, .NET IEEE Projects in Pondichery, Final Year JAVA, .NET IEEE Projects in Tamilnadu, Final Year JAVA, .NET IEEE Projects in Chennai, Final Year JAVA, .NET IEEE Projects in Trichy, Final Year JAVA, .NET IEEE Projects in Erode, Final Year JAVA, .NET IEEE Projects in Karur, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Tirunelveli, Final Year JAVA, .NET IEEE Projects in Madurai, Final Year JAVA, .NET IEEE Projects in Salem, Final Year JAVA, .NET IEEE Projects in Tirupur, Final Year JAVA, .NET IEEE Projects in Namakkal, Final Year JAVA, .NET IEEE Projects in Tanjore, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Bangalore, Final Year JAVA, .NET IEEE Projects in Hydrabad, Final Year JAVA, .NET IEEE Projects in Kerala, Final Year IEEE MATLAB Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE MATLAB Projects, Academic Final Year IEEE MATLAB Projects 2013, Academic Final Year IEEE MATLAB Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB
Ws For Aq
The document discusses a scenario where smoke from fires in Mexico causes high particulate matter (PM) concentrations over the eastern United States. It describes the goals of detecting and predicting the smoke plume and its impacts on air quality to help manage transportation safety. Key needs are real-time fire and smoke monitoring, PM and ozone forecasts, and analysis and delivery tools to provide information to managers and the public.
Technological Advancements in Semiconductor Manufacturing.pptx
Semiconductor manufacturing and semiconductor yield management is becoming more complex due to relentless advancements in technology. The ability to control critical dimensions is becoming increasingly important yet challenging as manufacturing processes continue to evolve. New production processes and variable machine configurations contribute to the complexity, generating high-dimensional, multi-collinear data that are difficult to analyze.
This intricate web of process data can be a hindrance in identifying the root causes of low yields or "excursions." However, data-driven methodologies present a powerful solution for these challenges. The implementation of big data analytics and machine learning techniques can help parse the overwhelming amount of data and extract insightful conclusions from it.
Risks (SWOT analysis)StrengthsWeaknessesNew monitoring tools.docx
Risks (SWOT analysis)
Strengths
Weaknesses
New monitoring tools offer significantly more versatility.
Rack Mounted
Solution
s has spent over a year working with newer monitoring tools in a development lab and data center environment for a proof of concept.
Dedicated environment ensures higher performance and more resilience than Big Brother
Modern day tools have mobility features: Front ends can be accessed using mobile devices.
Aggressive expansion plans into Europe is driving the need for evolutionary monitoring solutions.
Monitoring requirements and configuration is much more complex.
Significantly more data points and potential for false positives/negatives.
Additional data points results in more storage, increasing operational costs.
Regular patching is needed to keep systems “current” and “safe”.
Opportunities
Threats
Minimize human error in the alert identification and page initiation process.
Reduce System Administration rate by creating rate funded Monitoring service.
Will lay the foundation for more in-depth and flexible monitoring of applications and services.
Can be a data source for Rack Mounted
...
EDC In Clinical Trials| Electronic Data Capture In Clinical Trials
Unlock the transformative power of Electronic Data Capture (EDC) in clinical trials. EDC revolutionizes data management, ensuring real-time access, data accuracy, and streamlined processes. By replacing paper-based systems, it enhances efficiency, reduces errors, and expedites decision-making. Its adaptability facilitates various study designs, from traditional to decentralized trials. With features like remote monitoring and ePRO integration, EDC promotes patient-centricity. Embrace the future of clinical research, where EDC not only meets but exceeds the demands for precision, speed, and compliance, ultimately paving the way for more successful and patient-friendly trials.
Cascade
Riverbed Cascade provides network visibility and optimization through its flow-based solution. It collects and analyzes network flow data to assess application performance, identify optimization opportunities, and proactively detect and resolve issues. Cascade helps customers consolidate infrastructure, accelerate applications, and continuously monitor network and application performance. Customers can expect benefits like reduced troubleshooting time, lower costs, and a strong ROI from using Cascade for network optimization and visibility.
Processing Patterns for Predictive Business
The document discusses processing patterns for predictive business event processing. It introduces an event-decision architecture with multiple levels of inference including event refinement, situation refinement, impact assessment, and process refinement. Common inference algorithms like Bayesian belief networks are described. Finally, recurring patterns are mapped that apply classical inference techniques like Bayesian networks to business contexts like fraud detection, intrusion detection, and opportunistic trading.
Harbor Research - Smart Services, Product Analytics, & Intelligence
Product analytics tools that leverage data from connected products are enabling new capabilities for IT equipment manufacturers and opening up strategic opportunities. Early adopters have seen significant impacts, including double-digit revenue growth, 5-1% increases in return on sales for business units, and service productivity improvements of 20-35%. As product analytics evolves, it will create a "digital nervous system" through connected products that automates most functions and processes, allowing equipment manufacturers to achieve unprecedented customer intimacy and insight.
Processing Patterns for PredictiveBusiness
Processing Patterns for PredictiveBusiness. TUCON 2006, Tim Bass, CISSP, Principal Global Architect, TIBCO Software Inc.
Event Driven Architecture (EDA), November 2, 2006
Event Driven Architecture (EDA), SOA Seminar Crystal City, Virginia, November 2nd, 2006, Tim Bass, CISSP, Principal Global Architect, Director. Co-Chair, Event Processing Reference Architecture Working Group (EPRAWG)
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Data analytics to improve home broadband cx & network insight
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Women's Maltreatment Redressal System based on Machine Learning Techniques
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Event tracking for real time unaware sensitivity analysis
Event tracking for real time unaware sensitivity analysis
Java event tracking for real-time unaware sensitivity analysis
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Event tracking for real time unaware sensitivity analysis
Event tracking for real time unaware sensitivity analysis
Technological Advancements in Semiconductor Manufacturing.pptx
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Harbor Research - Smart Services, Product Analytics, & Intelligence
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UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
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Malaria 3 point_0h
- 1. WWW Web based
- 2. Web Based Malaria Disease Surveillance & Mapping Project Overview Problem Solution Technical Details Challenges Feedback & Results
- 3. Overview CURRENTLY PAPER BASED REPORTS ARE DATA CLERKS MALARIA REPORTING COLLECTED ENTER DATA AFFECTS SYSTEM AND SENT INTO SYSTEM NORTHERN BACK TO TO BE AREAS OF MOH AT THE AGGREGATED BOTSWANA END OF THE & ANALYZED MONTH
- 5. Slow turnaround time Problem 3 - 4 weeks Paper based system cumbersome & inefficient No immediate notifications of outbreaks Data entry, analysis and aggregation timely & expensive
- 6. Solution Forms developed for smartphone data entry Health workers trained how to enter & submit data using smartphone Web based tool developed to view data real-time DATA SITE MAPPING OF SMS BREAKDOWN EXPORT TO CASES & SITES NOTIFICATIONS REPORTING AND EXCEL WITH CASE OF REPORTED STATISTICS AGGREGATION INFORMATION CASES
- 10. Demo: Healthcare Workers Perspective
- 11. Technical Details Smartphone Forms Web based aggregation and analysis tool
- 12. Smartphone Forms
- 13. Challenges
- 14. Feedback and Results Increased dialogue Officials at MoH can between users about immediately escalate how the reporting process could work & investigate better reported cases Dramatic increase turnaround time for data aggregation and analysis
- 16. Overlaying case map with net distribution and chemically treated site maps to gauge effectiveness
- 17. Partners
Editor's Notes
- - Ministry of Health wishes to to eliminate malaria completely by 2015- Ministry of Health has standard reporting forms that are filled out for weekly reports- When a positive case is reported another form is filled out with the individual case detailsDrivers come and collect forms every two weeks and deliver them to HQ in GaboroneData clerks constantly are entering data into spreadsheets which are then aggregated and analysis
- Human error from data entry or data cleaning is an extra burden-Other issues such as illegible handwriting. Picking up and delivering forms to HQ is time consuming and expensiveCurrent protocol requires a positive case to be called in. Often the calls are missed or never made at all.Full time Data clerks are employed
- - 3 forms were developed for the smartphones - weekly reporting - case investigation - immediate case followup- 90% of health workers in Chobe were trained on how to use the phones e.g nurses, doctors, lab technicians16 health facilities were issued with a smartphone-MoH officials can login to site to view data real time- web based system allows them to login from any location with a secure password
- -Recently a large public servant strikes caused some disruption in reporting. Some health workers were replaced. -Normally health workers are rotated once a year some some rotations have occurred which mean nurses will have to be trained-A couple users were irresponsible and using the phone to surf sites and download a lot of data which depleted the allotted data package which meant data couldn’t be uploaded -Some users experienced some difficulties with upload data but are located in remote locations. We will be doing a joint site visit in late OCT to resolve these issues.
- -Users feel more connected to the reporting process. They can also view data themselves from other sites as well-SMS notifications allow MoH officials to follow and call health workers about reported cases- Users have been providing feedback about how they would like the forms to be structured
- Expansion to 20 new sites in eastern Botswana with higher incidences ratesSMS announcements to health workers, individual SMSing to specific site-Overlaying case map with net distribution and chemically treated site maps to gauge effectiveness-Other notifiable disease include: MDR TB, Polio, Rabies, Ebola, Cholera, etc…
- HP have allowed us access to host the service on their secure cloud.