Scott Graham - Independence KY, US Michael Grady - Cincinnati OH, US Stephen Weagraff - Orlando FL, US Michael Sauer - Cleves OH, US Rahul Jindal - Longwood FL, US
International Classification:
G06F015/16
US Classification:
709/203000
Abstract:
The present invention is directed toward a framework for consistent and minimized development of Web-based applications. A preferred Web-based application of the present invention is built on a web server framework utilizing industry standard technologies relating to Web development and deployment. These technologies fall into three main areas: browser technology, Web server technology, and application server technology. A preferred Web architecture of the present invention is preferably based on HTTP, utilizing a browser, Middleware, and a Web Server, the Web Server comprising Java servlets, Java Server Pages, Java Beans, and a Web Server Framework. This architecture follows a standard Model, View, Controller pattern. Preferably, the initial servlet is the Controller, the Java Beans are the Model, and the JSP is the View. Preferred frameworks include an Error Framework, a Logging and Tracing Framework, a Connection Framework, a Reference Data Framework, a Security Framework, and an International Framework.
Rahul Jindal - Longwood FL, US Rohit Aggarwal - Sanford FL, US Mike Sauer - North Bend OH, US
International Classification:
G06F 15/16 G06F 11/00
US Classification:
709228000, 714049000, 714E11187
Abstract:
Software intended to operate in a clustered environment can be tested for appropriate failover behavior through the use of an automated tool which allows failover to be simulated without requiring that the application be deployed in a cluster environment and observing the effects of actual failover. Such an automated tool can measure the characteristics of one or more session objects created by the application and provide appropriate messages for a developer when those characteristics indicate improper coding for failover.
Bayesian Modeling Of Pre-Transplant Variables Accurately Predicts Kidney Graft Survival
Eric A. Elster - Kensington MD, US Doug Tadaki - Frederick MD, US Trevor S. Brown - Washington DC, US Rahul Jindal - Silver Spring MD, US
International Classification:
A61B 5/00
Abstract:
An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.
Rapid Cyber Solutions, Inc. since May 2013
President and CTO
Convergys Apr 2010 - May 2013
Director, Enterprise Architecture
Convergys Dec 2007 - Apr 2010
Director, Web Product Development
Convergys Mar 2007 - Dec 2007
Director (Technical) Solution Development
Convergys Jan 2001 - Mar 2007
Chief Technology Architect for Infinys Platform
Education:
The Ohio State University 1986 - 1987
University of Toledo 1985 - 1986
Indian Institute of Technology, Kanpur 1981 - 1985
Skills:
Telecommunications High Availability Customer Service Wireless Java Enterprise Edition Solution Architecture Vendor Management SaaS Business Analysis Product Management Cloud Computing PMP Product Development Program Management SDLC Requirements Analysis SOA Project Portfolio Management
Rapid Cyber Solutions, Inc.
President and Chief Technology Officer
Convergys Apr 2010 - May 2013
Director, Enterprise Architecture
Convergys Dec 2007 - Apr 2010
Director, Web Product Development
Convergys Mar 2007 - Dec 2007
Director Solution Development
Convergys Jan 2001 - Mar 2007
Chief Technology Architect For Infinys Platform
Education:
The Ohio State University 1986 - 1987
Master of Science, Masters, Computer Science
The University of Toledo 1985 - 1986
Indian Institute of Technology, Kanpur 1981 - 1985
The Ohio State University;M.s.;1986 – 1987;
Master of Science, Masters
Skills:
Telecommunications Solution Architecture Enterprise Architecture Cloud Computing Saas Requirements Analysis Java Enterprise Edition Sdlc Enterprise Software Wireless Vendor Management Product Management High Availability Business Analysis Program Management Soa Software Project Management Product Development Architecture Software Development Crm Integration Testing Unix Customer Service Security Mobile Devices Distributed Systems Project Management Pmp Strategy Management E Commerce Java Pre Sales Agile Methodologies Oracle Project Portfolio Management Leadership Networking Sql It Strategy Outsourcing Business Intelligence Web Applications Web Services Business Process Process Improvement Consulting Service Delivery