A study on “the impact of data analytics in covid 19 health care system”Dr. C.V. Suresh Babu
A Study on “The Impact of Data Analytics in COVID-19 Health Care System”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A study on the impact of data analytics in COVID-19 health care systemDr. C.V. Suresh Babu
Through the disperse of novel coronavirus illness globally, existence became considerably contrived. Data analytics have experienced powerful development over the past few years. As it happens, it’s exceptionally considerable to take advantage of data analytics to assist mankind in a prompt as well as factually precise method to forestall additionally restrain the advancement of the widespread, sustain gregarious balance and evaluate the influence of the widespread. The unforeseen significant number of coronavirus disease instances has disturbed medical care system in many economies furthermore eventuated in an insufficiency of dormitory in the hospices. For this reason, prognosticating quantity of coronavirus infection instances is indispensable for administrations to adopt the necessary measures. The count of coronavirus disease instances could be correctly anticipated by taking into account historical records of announced instances side by side few extraneous components that impact the disseminate of the COVID-19 . Hence, the principal aim out of this research is to contemporaneously consider historical data and the extraneous components. This paper explores how data analytics can play a role in health care especially in novel coronavirus illness.
A study on “the impact of data analytics in covid 19 health care system”Dr. C.V. Suresh Babu
A Study on “The Impact of Data Analytics in COVID-19 Health Care System”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A study on the impact of data analytics in COVID-19 health care systemDr. C.V. Suresh Babu
Through the disperse of novel coronavirus illness globally, existence became considerably contrived. Data analytics have experienced powerful development over the past few years. As it happens, it’s exceptionally considerable to take advantage of data analytics to assist mankind in a prompt as well as factually precise method to forestall additionally restrain the advancement of the widespread, sustain gregarious balance and evaluate the influence of the widespread. The unforeseen significant number of coronavirus disease instances has disturbed medical care system in many economies furthermore eventuated in an insufficiency of dormitory in the hospices. For this reason, prognosticating quantity of coronavirus infection instances is indispensable for administrations to adopt the necessary measures. The count of coronavirus disease instances could be correctly anticipated by taking into account historical records of announced instances side by side few extraneous components that impact the disseminate of the COVID-19 . Hence, the principal aim out of this research is to contemporaneously consider historical data and the extraneous components. This paper explores how data analytics can play a role in health care especially in novel coronavirus illness.
Transctriptional Science aims to re-evaluate existing data in the context of the translational sciences paradim in order to secure reliability and validity of data used for hypothesis generation, project design and decision making at a highest possible level of confidence
The aim of this review is to summarize the current research studies on dissolvable brain implant consisting of pressure and temperature sensors that can monitor traumatic brain injury and Parkinson’s disease.Full articles with each line detailing available @pharmacyhighlights.com
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
Although the lungs are one of the most vital organs in the body, they are vulnerable to infection and injury. COVID-19 has put the entire world in an unprecedented difficult situation, bringing life to a halt and claiming thousands of lives all across the world. Medical imaging, such as X-rays and computed tomography (CT), is essential in the global fight against COVID-19, and newly emerging artificial intelligence (AI) technologies are boosting the power of imaging tools and assisting medical specialists. AI can improve job efficiency by precisely identifying infections in X-ray and CT images and allowing further measurement. We focus on the integration of AI with X-ray and CT, both of which are routinely used in frontline hospitals, to reflect the most recent progress in medical imaging and radiology combating COVID-19.
Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context. Contextual processing of patient data along with personalized medical knowledge can lead to actionable information for better and timely decisions. We present a system called kHealth capable of aggregating multisensory and multimodal data from sensors (passive sensing) and answers to questionnaire (active sensing) from patients with asthma. We present our preliminary data analysis comprising data collected from real patients highlighting the challenges in deploying such an application. The results show strong promise to derive actionable information using a combination of physiological indicators from active and passive sensors that can help doctors determine more precisely the cause, severity, and control level of asthma. Information synthesized from kHealth can be used to alert patients and caregivers for seeking timely clinical assistance to better manage asthma and improve their quality of life.
Paper: http://www.knoesis.org/library/resource.php?id=2153
Citation:
Pramod Anantharam, Tanvi Banerjee, Amit Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan, Shalini G. Forbis, Knowledge-driven Personalized Contextual mHealth Service for Asthma Management in Children , IEEE 4th International Conference on Mobile Services, June 27 - July 2, 2015, New York, USA.
March 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Teleradiology is a branch of telemedicine in which telecommunication systems are used to transmit radiological images from one location to another. Interpretation of all noninvasive imaging studies, such as digitized x-rays, CT, MRI, ultrasound, and nuclear medicine studies, can be carried out in such a manner.
The first steps in teleradiology date back to 1929 when a medical image was transmitted via telegraph to a distant location
Developing data services: a tale from two Oregon universitiesAmanda Whitmire
While the generation or collection of large, complex research datasets is becoming easier and less expensive all the time, researchers often lack the knowledge and skills that are necessary to properly manage them. Having these skills is paramount in ensuring data quality, integrity, discoverability, integration, reproducibility, and reuse over time. Librarians have been preserving, managing and disseminating information for thousands of years. As scholarly research is increasingly carried out digitally, and products of research have expanded from primarily text-based manuscripts to include datasets, metadata, maps, software code etc., it is a natural expansion of scope for libraries to be involved in the stewardship of these materials as well. This kind of evolution requires that libraries bring in faculty with new skills and collaborate more intimately with researchers during the research data lifecycle, and this is exactly what is happening in academic libraries across the country. In this webinar, two researchers-turned-data-specialists, both based in academic libraries, will share their experiences and perspectives on the development of research data services at their respective institutions. Each will share their perspective on the important role that libraries can play in helping researchers manage, preserve, and share their data.
Transctriptional Science aims to re-evaluate existing data in the context of the translational sciences paradim in order to secure reliability and validity of data used for hypothesis generation, project design and decision making at a highest possible level of confidence
The aim of this review is to summarize the current research studies on dissolvable brain implant consisting of pressure and temperature sensors that can monitor traumatic brain injury and Parkinson’s disease.Full articles with each line detailing available @pharmacyhighlights.com
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
Although the lungs are one of the most vital organs in the body, they are vulnerable to infection and injury. COVID-19 has put the entire world in an unprecedented difficult situation, bringing life to a halt and claiming thousands of lives all across the world. Medical imaging, such as X-rays and computed tomography (CT), is essential in the global fight against COVID-19, and newly emerging artificial intelligence (AI) technologies are boosting the power of imaging tools and assisting medical specialists. AI can improve job efficiency by precisely identifying infections in X-ray and CT images and allowing further measurement. We focus on the integration of AI with X-ray and CT, both of which are routinely used in frontline hospitals, to reflect the most recent progress in medical imaging and radiology combating COVID-19.
Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context. Contextual processing of patient data along with personalized medical knowledge can lead to actionable information for better and timely decisions. We present a system called kHealth capable of aggregating multisensory and multimodal data from sensors (passive sensing) and answers to questionnaire (active sensing) from patients with asthma. We present our preliminary data analysis comprising data collected from real patients highlighting the challenges in deploying such an application. The results show strong promise to derive actionable information using a combination of physiological indicators from active and passive sensors that can help doctors determine more precisely the cause, severity, and control level of asthma. Information synthesized from kHealth can be used to alert patients and caregivers for seeking timely clinical assistance to better manage asthma and improve their quality of life.
Paper: http://www.knoesis.org/library/resource.php?id=2153
Citation:
Pramod Anantharam, Tanvi Banerjee, Amit Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan, Shalini G. Forbis, Knowledge-driven Personalized Contextual mHealth Service for Asthma Management in Children , IEEE 4th International Conference on Mobile Services, June 27 - July 2, 2015, New York, USA.
March 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Teleradiology is a branch of telemedicine in which telecommunication systems are used to transmit radiological images from one location to another. Interpretation of all noninvasive imaging studies, such as digitized x-rays, CT, MRI, ultrasound, and nuclear medicine studies, can be carried out in such a manner.
The first steps in teleradiology date back to 1929 when a medical image was transmitted via telegraph to a distant location
Developing data services: a tale from two Oregon universitiesAmanda Whitmire
While the generation or collection of large, complex research datasets is becoming easier and less expensive all the time, researchers often lack the knowledge and skills that are necessary to properly manage them. Having these skills is paramount in ensuring data quality, integrity, discoverability, integration, reproducibility, and reuse over time. Librarians have been preserving, managing and disseminating information for thousands of years. As scholarly research is increasingly carried out digitally, and products of research have expanded from primarily text-based manuscripts to include datasets, metadata, maps, software code etc., it is a natural expansion of scope for libraries to be involved in the stewardship of these materials as well. This kind of evolution requires that libraries bring in faculty with new skills and collaborate more intimately with researchers during the research data lifecycle, and this is exactly what is happening in academic libraries across the country. In this webinar, two researchers-turned-data-specialists, both based in academic libraries, will share their experiences and perspectives on the development of research data services at their respective institutions. Each will share their perspective on the important role that libraries can play in helping researchers manage, preserve, and share their data.
Detection of chest pathologies using autocorrelation functionsIJECEIAES
An important feature of image analysis is texture, seen in all images, from aerial and satellite images to microscopic images in biomedical research. A chest X-ray is the most common and effective method for diagnosing severe lung diseases such as cancer, pneumonia, and tuberculosis. The lungs are the largest X-ray object. The correct separation of the shapes and sizes of the contours of the lungs is an important reason for diagnosis, because of which an intelligent information environment can be created. Despite the use of X-rays, to identify the diagnosis, there is a chance that the disease will not be detected. In this sense, there is a risk of development, which may be fatal. The article deals with the problems of pneumonia clustering using the autocorrelation function to obtain the most accurate result. This provides a reliable tool for diagnosing lung radiographs. Image pre-processing and data shaping play an important role in revealing a well-functioning basis of the nervous system. Therefore, images from two classes were selected for the task: healthy and with pneumonia. This paper demonstrates the applicability of the autocorrelation function for highlighting interest in lung radiographs based on the fineness of textural features and k-means extraction.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
SES for Monitoring Diseases Outbreak: case of Onchocerciasis in Nigeria
1. OGUNDELE Olukunle Ayodeji 370063 Environmental factor based SES for monitoring Diseases Outbreak: Case of Onchocerciasis in Nigeria. Institute for Geoinformatics (Ifgi) University of Muenster, Germany. July 8, 2011 M.Sc. Geoinformatics (2010 – 2012) Masters‘ Thesis of Prof. Pebesma Edzer Dr. Remke Alber Supervisors
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5. Environmental factor based SES for Monitoring Diseases Outbreak: Case of Onchocerciasis in Nigeria . Ogundele Olukunle A. | Date: 04.08.11
6. Epidemiological Concept and Geospatial Technology Environmental factor based SES for Monitoring Diseases Outbreak: Case of Onchocerciasis in Nigeria . Ogundele Olukunle A. | Date: 04.08.11
7. Onchocerciasis Event Service: - Study framework Environmental factor based SES for Monitoring Diseases Outbreak: Case of Onchocerciasis in Nigeria . Ogundele Olukunle A. | Date: 04.08.11 Rule Modeling Sensor Data Characteristics: E.g. Water Temperature, Water Velocity and PH Environmental Factors: E.g. Hydrology Physical and Chemical Conditions Service Model Model Language: Event Pattern Markup Language (EML) Event Logic: (SES) Filtering Method for Notification Web Notification Model WNS Service: Notification on email and SMS System Input: E.g. Output Events; Messages; Location Information: E.g. Endemic Region, Rivers, Settlements Input: Conditions (Parameters) Data Characteristics EML Schema User Requirement: E.g. Location requirement; Stage interest Rules Documentations and Formalization; Process Flow; Geoprocesing; Complex Event Modeling
8. Model Formalization and Evaluation Environmental factor based SES for Monitoring Diseases Outbreak: Case of Onchocerciasis in Nigeria . Ogundele Olukunle A. | Date: 04.08.11
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11. …… I can do all things through Christ, my strength. Thanks everyone Environmental factor based SES for Monitoring Diseases Outbreak: Case of Onchocerciasis in Nigeria . Ogundele Olukunle A. | Date: 04.08.11
12. Environmental factor based SES for Monitoring Diseases Outbreak: Case of Onchocerciasis in Nigeria . Ogundele Olukunle A. | Date: 04.08.11 Yes!, More thanks these people Prof. Pebesma Edzer. Prof. Mafuyai A. Dr. Remke Albert. Dr. Ajayi Ola Simon Jirka Thomas Everding Andreas Johnen
Editor's Notes
I will first give the background and objectives of the study in the Introduction part, then I will give the case overview of the study. Next, I will discuss the involvement of geospatial technology in epidemiological concepts; the current state and propossed strategy. I will highlight the motivation for deciding on rule based model for this study. Then I will present the proposed service model and give the current work state in summary
There are factors that affects affect disease outbreak, they play important role and determine possible time when there will be an outbreak. One main factor is the environmental factor which directly affects the host, vectors and diseases organisms. Environmental factors relate with the overall lifecycle of the disease and of the vector and they are key determinant to every stage of the disease lifecycle. Such stages are crucial for outbreak of diseases. For instance the moment a fly is out to spread the disease, the infection is already on An important question will be “What are the possible means off modelling these important stages in the cycle, provide notifications for possible outbreaks. Therefore I look into how to use environmental factors in developing models which can be implemented in an event service environment to notify users of possible outbreaks in near real time. The objectives are:…..
For the purpose of this study, I take the case of River blindness diseases caused by Onchocerciasis parasite. The parasite causes blindness and severe skin diseases in tropical regions of the world. Nigeria is one of the countries having this disease challenge, having 100 thousand of its inhabitants blinded already by the parasite. One great problem is that the damage caused by this disease is irreversible. Once someone is blind by the parasite, there is no cure; you can only kill the parasites. This disease carried in the head of black fly and deposited in human host during feeding on blood. The outbreak and spread of this disease rely on the activities and survival of black fly. It is common the rural areas where black flies have favourable environment to habit and reproduce. So, it will be profitable to create a system that supports decisions against outbreak of this disease and action for intervention.
A challenging case will be for CHEW in a village has the responsibility to treat and also warn the community of the danger of diseases. He has the challenge of routinely warning them of the knowledgeable diseases because he did not know exactly when the disease is breaking out. He does not know when the parasites will mature, when the larvae will develope in the water and when the flies are breaking out to infest people with the disease. Therefore, he needs a system where he can register his location and the stage interested in (e.g. fly outbreak) and the system takes care of the rest by checking for his subscription if there is a match and send message as SMS to him to inform him of the action to be taken.
Looking at this requirement, the question is what existing techniques can provide such near real time notification. I tried to look at current method of integrated Geospatial technology and disease monitoring in epidemiological concept. The current methods are not enough… The common and most used method is the creation of risk maps and predictive models using geo-archive and health surveillance data. This is core geoprocessing which is not adequate for notification support for outbreak. The maps are presented through the web map service techniques to support decisions and inform the public to bring the analysis output close to users. But this is a pull method that requires constant access or request of updates and update exercises from experts Therefore I proposed an integration of the last layer that is powered by Sensor web Enablement in completing on time notification of intending outbreak. This should take less effort from users. Using the observations from sensors to create events that will in turn trigger notifications which are sent to the users, users can receive alert and warnings to help in their decision making.
I decided to narrow down the formalization of the model to the event service component of the system. I worked on the event model that can be used to create notification for early warning of possible outbreak of disease and how it fits into the whole system. This formed the core of my study framework which I divided into three part. I will only concentrate on two with time permission. I have been able to develop set of rules using the environmental parameters as defined by scholars to make a process flow for different stages of events. This I then formalized using modeling language and diagram. The model is to be translated into SES service using Event Pattern Markup Language (EML) and will be registered as services.
I have been able to formalize the event model and to briefly explain it, I will use the SES diagram as introduced to me by Thomas Everding. I developed the filters into components that I used through out the process model. There are two main filters, the Simple Filter and the Complex Filter. The simple filter only takes in one input and gives out multiple outputs. The complex filter takes in maximum of 2 inputs and carry out an operations on them and gives multiple output as well. This was built into a tree-like process model. Taking the example of breeding notification where water temperature, velocity and PH are main factors to successful breeding. There are minimum and maximum range that support survival and activities of the vector. This determine the long or short period of lifecycle, the strength of breeding and the level of risk These conditions were modeled over the period of underwater lifecycle to trigger an out going notification of an outbreak of larvae and fly.
I am motivated to examine and propose the SWE layer integration of geospatial technology with epidemiological concept because I want to use the strength of rule based model which is more efficient in modeling complex event process to monitor the complex lifecycle of the diseases and also the vectors. This approach also will enhance the use of advanced geospatial technology in public health domain better than the common risk mapping and mathematical predictive model . By developing an event service that uses environmental phenomenon to accurately model the lifecycle of vectors and disease outbreak, near real time early warning can be achieved. Also promoting optimum use of the environmental data. Lastly, dispersed expert knowledge from previous and current researches can use useful to build a warning system that can accurately predict and control diseases. At the same time, experts knowledge will be put into better use.
I already completed the rule formalization and modeling. I have it modeled using annotations and diagrams. What is left to do technically is creating the SES service using EML. There are several challenges in making rule based models for black fly lifecycle which is the same for other vector of diseases. One of the problem is the event handling by the complex filter that needs two parameters with an AND operation. If tone of the event input is no available, then that part of the model will not run until there is an input. This is a complication I still need to fully understand and find a way to adapt my model to the situation or propose a solution. I expect to have a framework for using rule based model for Diseases Outbreak using the environmental factors to predict outbreak in the end, stating some challenges and prospects of using SES as one of the rule based model for the model. Probably recommend the model for implementation and testing in Nigeria.