Gopalakrishna Palem

This study is aimed at Attribution of Food borne illnesses to Food Commodities with the goal of Measuring probability and magnitude of disease outbreaks at a specific region and time based on historical outbreak data. The question that this kind of study aims at answering is: Government has a target for disease control – what is the probability tha...

Maintenance accounts for approx. 30% of the lifecyle costs of a high-speed train, making it the largest rolling stock operating cost factor besides energy. Predictive maintenance, also known as Condition Based Maintenance (CBM) aims to reduce these unnecessary costs by basing the maintenance need on the actual condition of themachine rather than on...

A Demo Video on Predictive Maintenance. Copy of this can also be found on: http://www.youtube.com/watch?v=nfQ4U4tBnuY

Take an example of electric vehicle (EV) that you drive home and connect to the electric grid, letting it figure out your next commute requirement from the calendar appointments on your hand-held or mobile, and your grid’s active load usage and non-peak hours from the energy provider, all summed up to auto-tune its own recharging schedule to reduce...

Problems such as inaccurate diagnoses and poor drug-adherence pose challenges to individual health and safety. These challenges are now being alleviated, if not completely eradicated, with big data analytics using personalized drug regimes, follow-up alerts and real-time diagnosis monitoring. Pervasive and context-aware monitoring solutions are imp...

Advancement in the big-data technologies in combination with machine-to-machine (M2M) interconnectivity and predictive analytics is creating new possibilities for real-time analysis of machine components for identifying and avoiding breakdowns in the early stages ahead of time. Designing such a condition-based maintenance system for high-speed flee...

What business owners want? • Gain new customers • Retain old customers and make them come back (again and again) • Edge out the competition • The Million Dollar Question: How? • Enter Big Data Analytics.

A case studies brief by Cenacle Research presenting a variety of Healthcare Analytics solutions crafted to the needs of: + Individuals (Patients) ▪ Personalized Healthcare + Care Providers (Hospitals) ▪ Clinical Decision Support Systems + Control & Monitoring Boards (Govt. and Statutory Boards) ▪ Population Health Analytics ▪ Real-time Epide...

Cenacle Research is engaged in building Predictive Analytics Engines for Automotive, Healthcare, Retail, Energy and BFSI sector. This is our latest Big data Analytics offering for effective Resource Management. For effective resource management, Big Data offers: Actionable Insights that let you make Informed Decisions, with the capability to: +...

Cenacle Research is engaged in building Predictive Analytics Engines for Automotive, Healthcare, Retail, Energy and BFSI sector. This is our latest Big data Analytics offering for Restaurant Business. Our latest Resurant Order Prediction System helps you Predict your customer orders, and know how your restaurant orders are going to be affected by...

The recent surge in big data technologies has left many executives, both of well-established organizations and emerging startups, wondering how best to harness big data. In particular, the analytics aspect of big data is enticing for both information technology (IT) service providers and non-IT firms because of its potential for high returns on inv...

This study is aimed at Attribution of Food borne illnesses to Food Commodities with the goal of Measuring probability and magnitude of disease outbreaks at a specific region and time based on historical outbreak data. The question that this kind of study aims at answering is: Government has a target for disease control – what is the probability tha...

A Demo Video on Predictive Maintenance. Also can be found at: http://youtu.be/GUg4FjhTRS0

Transparency in administration and effective corporate governance leads to huge volumes of public data that when processed with analytical procedures yield meaningful insights into the nature of the data and the business operations generating that data. A case in point being the recent public release of United States Medicare charges for healthca...

Emergence of uniquely addressable embeddable devices has raised the bar on Telematics capabilities. Though the technology itself is not new, its application has been quite limited until now. Sensor based telematics technologies generate volumes of data that are orders of magnitude larger than what operators have dealt with previously. Real-time big...

Maintenance service log data for stage-3 analytics. This is a monte-carlo simulated data perfectly exhibiting all the six failure probabilities of weibull curves. This acts as historical maintenance data for the expert system to get trained on for predicting the failure probabilities of new components.

Sentiment Analysis has many key applications in social networking and marketing. The fundamental principle involved is: "Classifying the polarity at the document, sentence, or feature/aspect level — whether the expressed opinion is positive, negative, or neutral"

Sequence indexing is the art of manipulating objects. It tries to answer one simple question: Given a collection of objects, how do we create, access, and identify various groups of objects drawn from that collection? Most games consist of large collections of objects, so it can be seen how understanding these concepts might be useful for game deve...

Mathematically a system is said to be solved if its future states can be predicted from the information provided by the present and past state history. In this paper, we examine the problem of solving Artificial Life systems using the principles of state-machines. The observable functionality of natural life systems is so tightly woven around the c...

Oracles are hypothetical machines that can compute any function in unit time. They are representatives of the ontic truth that is independent of any theory or model. Artificial life systems are synthetic models that try to capture the ontic truth through epistemic inferences. Their descriptions are epistemic perceptions of the observer. Understandi...

Data-dependencies play an important role in the performance of learning algorithms. In this paper we analyze the concepts of data dependencies in the context of artificial sys-tems. When a problem and its solution are viewed as points in a system configuration, variations in the problem configurations can be used to study the variations in the so-l...