Ankit K. Patel

Lakehead University

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Research Trends

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Co-Authors

Paul J. Bracewell

Statistics New Zealand

E. Blackie

Statistics New Zealand

Chris Boys

Rangat Mehta

Support Center for Advanced Telecommunications Technology Research Foundation

Samuel J Rooney

Brendon P Bracewell

Jinan Fiaidhi

Lakehead University

Ankur Chauhan

Deutsches Elektronen-Synchrotron DESY

Krish Mehta

Support Center for Advanced Telecommunications Technology Research Foundation

Nisarg Patel

University of California, San Francisco

Cooperative Institutions

Support Center for Advanced Telecommunications Technology Research Foundation

Victoria University of Wellington

Statistics New Zealand

Lakehead University

MacDiarmid Institute for Advanced Materials and Nanotechnology

Interfaces Traitements Organisation et Dynamique des Systèmes

Institute of Molecular Biology

Université Paris Cité

Centre National de la Recherche Scientifique

University of Otago

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Identifying fast bowlers likely to play test cricket based on age-group performances

International Journal of Sports Science & Coaching (2017)

Ankit K. Patel Paul J. Bracewell Aaron Gazley Brendon P Bracewell

A challenge for New Zealand cricket is identifying and retaining fast bowling talent. A methodology is described for determining individuals with a greater propensity to play test cricket for New Zealand, based solely on youth performances. Analyses were conducted on data from New Zealand youth test matches contested between 1986 and 2008, with subsequent selection for the test team as the dependent variable. Given the presence of collinearity and complex interactions amongst the variables, a regression tree technique was utilised, which ensured a pragmatic solution. After pruning, the regression tree indicated that average strike rate and average balls bowled per innings were key determining factors of future selection. Youth bowlers that had high workload (high average balls bowled) and high efficacy (low strike rate) accounted for 11/14 of those that went on to play test cricket for New Zealand. Interestingly, a further 2 of those 14 represented New Zealand in winter sports. Importantly, these results align with previous insights derived in literature. Extending this framework further enables the probability of playing test cricket for each individual to be determined by fitting a regression model to the regression tree residuals. This serves as a useful ranking system.

Pruning

Collinearity

Tree (set theory)

10.1177/1747954117710514

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Citations (7)

Distributed Approach for Clock Synchronization in Wireless Sensor Network

International Journal of Modern Trends in Engineering and Research (2014)

Ankit K. Patel Ankur Chauhan

Clock drift

Self-clocking signal

Data synchronization

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Energy Efficiency And Better Throughput In MANET Using Improved AOMDV

IJSRD : international journal for scientific research and development (2014)

Nisarg Patel Manojkumar B Patel Ankit K. Patel

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Roster-Based Optimisation for Limited Overs Cricket

Ankit K. Patel

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Mobile Crowd Sensing for Hypertensive Patient

Ankit K. Patel Jinan Fiaidhi Harsh Kapadia

The main aim is to detect Hypertension without considering Blood Pressure or any other medical test. The proposed method mainly focuses on generating huge database which contains symptoms of Hypertensive patients. In MCS environment, another key component is providing incentive to volunteers in-order to motivate them to take part in data collection phase. Feedback is given to the user about their current health status in form of incentive which is generated using Machine Learning technique like Random Forest Classifier

10.36227/techrxiv.12101409.v1

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Citations (1)

An Individual-based Team Rating Method for T20 Cricket

Journal of Sport and Human Performance (2017)

Ankit K. Patel Paul J. Bracewell Samuel J Rooney

Cricket is an ideal sport to isolate individual team member contribution with respect to winning. This is due to the volume of digital data available, combined with the relatively isolated nature of the batsman versus bowler contest observed per ball. Like many other sports, Cricket is reliant on the contribution of interacting individuals causing fluctuations in match outcomes. Understanding the quantifiable causes of this variation can help interested parties derive insight into team success and potential strategies for optimising performance. Understanding the individual dynamic within the team setting can lead to improved team ratings. The objective of this research was to develop a roster-based system for limited overs cricket by deriving a team rating as a combination of individual ratings. The intent was to build an adaptive optimisation system that selects a cricket team of 11 players from a list of available players, such that the optimal team produces the greatest team rating. The attributes used to define the individual ratings are based on the statistical significance and practical contribution to winning. An adaptive system was used to create the individual ratings using a modified version of a Product Weighted Measure. The weights for this system were created using a combination of a Random Forest and Analytical Hierarchical Process. The underlying framework of this system was validated by demonstrating an increase in the accuracy of predicted match outcomes compared to other established ranking methods for cricket teams. For the 2015/16 Big Bash, this approach outperformed the results outlined by Patel et al. (2016) by 12.3%. The results confirm that cricket team ratings based on the aggregation of individual playing ratings with attributes weighted towards winning limited over matches are superior to ratings based on summaries of team performances and match outcomes. This impact is highlighted by visualizing the variability of the ratings of Perth Scorchers during the 2015/2016 Australian Big Bash.

CONTEST

Team sport

Rating system

10.12922/jshp.v5i1.94

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Citations (3)

Smart home automation with a unique door monitoring system for old age people using Python, OpenCV, Android and Raspberry pi

Bhaumik Vaidya Ankit K. Patel Anand Panchal Rangat Mehta Krish Mehta

In this paper, smart home automation system particularly for old age people is proposed based on python, OpenCV, raspberry pi and android application. The appliances are controlled by the Raspberry pi server, which operates according to the user command (touch or voice) received from the mobile phone. A unique door monitoring system is designed based on face detection and recognition from a camera installed outside the main door, which can be accessed from the phone using android application. One interesting feature that has been added is that, all the appliances can also be controlled through the voice of user. For energy efficiency user can analyze the usage of each appliance from their phone. Moreover, user can also control the intensity of light as well as the speed of the fan. With all this features incorporated in a single system with good and simple user interface, this system is cost effective and perfect for old age people living alone in their houses.

Python

Raspberry Pi

Android application

Home Automation

10.1109/iccons.2017.8250582

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Citations (51)

Using a Predictive Rating System for Computer Programmers to Optimise Recruitment

IGI Global eBooks (2019)

Paul J. Bracewell Ankit K. Patel E. Blackie Chris Boys

Using a quantitative assessment system, the number of resumes reviewed to identify a suitable developer was reduced to 3.5% with a successful recruitment decision made in 10 working days of posting the job advertisement. This paper summarises the methodology for developing that rating system. The depth and quality of an available talent pool is a function of demand, which is demonstrated by comparing globally-scaled individual performance metrics. Public code repositories are accessed and the code quality assessed algorithmically. The performance score combines accuracy, timeliness and difficulty from a series of challenges. These three attributes form a meaningful predictive measure of performance by using a non-linear optimisation routine. Bootstrapping is used to validate the approach. This process randomly omitted a scored performance observation per coder in order to calculate the performance score from the retained scores. There was a strong relationship (r = 0.70) between the predicted 1-omitted-performance score with the actual omitted score highlighting the predictive power.

Bootstrapping (finance)

Predictive power

Code (set theory)

Quality Score

10.4018/978-1-5225-8356-1.ch020

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Internet of Things (IoT): A Literature Review

IJSRD : international journal for scientific research and development (2016)

Ankit K. Patel Biren M. Patel

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