Prashant K. Gupta

User-Satisfaction-Aware Power Management in Mobile Devices Based on Perceptual Computing

Present day portable devices such as laptops, smartphones, etc., offer their users fastest processors, advanced operating systems, and numerous applications. However, a large section of the users are critical to the available battery capacity and its lifetime. This is because performance of the battery and its lifetime as perceived by the users are quite subjective in nature. It depends directly on user satisfactions, which are usually expressed in terms of words. So, in this paper, we propose a user-satisfaction-aware energy management approach, called “perceptual computer power management approach (Per-C PMA),” based on the technique of perceptual computing. At the heart of our technique is the perceptual computer that processes the linguistic input of the users to aid in the selection of a suitable processor frequency, which plays a significant role in the overall energy consumption of the systems. The Per-C PMA minimizes the energy consumption, while still keeping the user satisfied with the perceived system performance. The Per-C PMA achieves 1) reductions of 42.26% and 10.84% in power consumption, and 2) improvements in the overall satisfaction ratings of 16% and 10%, when compared to other existing power-saving schemes such as ON-DEMAND and human and application-driven frequency scaling for processor power efficiency, respectively. Per-C PMA is the first such application of Per-C on any hardware platform. It is implemented as Ubuntu scripts for end users and can be downloaded from: http://sau.ac.in/∼cilab/. We have also provided the MATLAB files so that interested researchers can use it in their research. For the ease of the users, the Ubuntu scripts and the MATLAB codes are given in the graphical user interface mode; a demo video on how to use the software is also provided on the webpage.

Student oriented mobile based examination process

The industry that has been benefitted the most by the developments in VLSI technology is that of mobile phones. Modern day mobile handsets are referred to as smartphones and have reached to the hands of every person even in the remote corners of the world. Yet another revolutionary research was the development of the Android open source mobile OS which has made the mobile phones smarter. So, we decided to develop a mobile based examination system to reach the population even at the most remote areas. An Android driven examination system that we have designed and implemented is made with an intent to serve the education industry and provide efficient and reliable result along with powerful user interface. Our system aims at making the examination system a lot more convenient for the students as well as the faculty members and reducing the manual headache required in the traditional process. Googles Android is the most popular OS globally including India [2]. Android being so popular can be considered an OS that the masses have used in their smart phones; hence our system is designed considering the convenience of the faculty and the student taking the examination. Using the impeccable UI functionalities that have been provided using the Android Development Kit we have designed and implemented our system.

A novel approach based on computing with words for monitoring the heart failure patients

Abstract Developments in medical science have provided new ways in which care can be taken of people suffering from the risk of heart failure at reduced medical expenses, such as through wearable sensors. These are more efficient than traditional health monitoring methods such as in-person visits to medical practitioners, clinics, etc. Unfortunately, wearable sensors can measure quantitative parameters such as blood pressure and heart rate but not qualitative ones such as ease of respiration, pain, etc. The values of qualitative parameters are generally expressed by a sick person in the form of ‘words’. In real life scenarios, medical experts suggest plausible medical tests/treatment to patients using their experience based on his/her feedback in terms of ‘words’. In this paper, we propose a new approach, called heart monitoring through perceptual computing (HMT Per-C), that assesses the medical condition of a person (under the risk of heart failure) by processing user feedback in terms of ‘words’ and generates recommendations about the medical attention needed to be given to him/her. HMT Per-C is based on the technique of perceptual computing, which is a computing with words (CWW) technique that models ‘words’ using interval type-2 fuzzy sets. We have also compared the recommendations generated by perceptual computing with those generated by other CWW approaches viz., extension principle, symbolic method and 2-tuple. We have found that the extension principle, symbolic method and 2-tuple failed to give accurate results in 8%, 44% and 28% cases, respectively. Therefore, we believe that our proposed approach, HMT Per-C, is better, more user-friendly and close to real life scenarios. An outcome of the present work is the ready to use mobile app, “HMT Per-C”, that complements the data obtained from the devices like the oximeter but does not replace them. It can be downloaded freely from http://sau.ac.in/∼cilab/ .

Multi-objective linguistic optimization: Extensions and new directions using 2-tuple fuzzy linguistic representation model

Multi objective linguistic optimization is a useful mathematical technique to solve problems that interdependent criteria. In such problems, values of the objective functions may be unknown at some points, when the link between the variables and the objective functions are defined linguistically through if-then rules. While solving this type of problems, Tsukamoto based reasoning method has proved useful for converting objective function to a crisp form, and then using the resulting objective function to solve by any traditional optimization technique. However, this method suffers from a drawback that the resulting solution is in numeric form whereas it should have been in linguistic form, owing to the linguistic definition of if-then rules. So, here we propose 2-tuple fuzzy linguistic representation model based method for solving the Multi objective linguistic optimization problem. We demonstrate the novelty of our approach through a suitable example. We also prove that the proposed approach generates unique recommendation in linguistic form.

Sentiment analysis for design of computing with words based recommender

Sentiment analysis is a remarkable machine learning technique that accepts important words from a given text. It gives the output in the form of a sentiment score of each of the word and the overall text along with orientation of both (keywords and text) as being positive/ neutral/ negative. Social media has become a new platform for discussions in recent years due to growth in its reach. Sentiment analysis has proved to be quite useful in determining the collective response of people on any issue by analysing their opinions which are generally in the form of written texts. However, human beings do not understand numbers but language. So, we use the mathematical technique of perceptual computing to provide a mapping between numeric and linguistic data to generate recommendations. It is based on Zadehs computing with words (CWW). However, to generate recommendations from perceptual computing, we need problem specific linguistic terms and their associated interval values. Obtaining interval values may not be possible in scenarios where the number of subjects available for providing feedback is very less. So, here we propose a new approach that processes the linguistic information using perceptual computing based on the intervals extracted using the sentiment score using a sentiment analysis tool.