Using Feature Weighting as a Tool for Clustering Applications

The weighted variant of k-Means (Wk-Means), which assigns values to features based on their relevance, is a well-known approach to address the shortcoming of k-Means with data containing noisy and irrelevant features. This research aims first to explore how feature weighting can be used for feature selection, second to investigate the performance of Minkowski weighted k- Means (MWk-Means), and its intelligent variant, on datasets defined in different p-norms, and third to address the problem of missing values with a weighted variant of k-Means. A partial distance approach is used to address the problem of missing values for weighted variant of k- Means. Anomalous clustering has been successfully used to detect natural clusters and initialize centroids in k-means type algorithms. Similarly, extensive work has been carried out on using feature weights to rescale features under Minkowski Lp metrics for p ≥ 1 . In this thesis, aspects from both of these approaches enable feature weights to be detected based on natural clusters present in the training data, but the clusters are not limited to spherical shape. Two methods, mean-FSFW and max-FSFW, are developed as further extensions of intelligent Minkowski Weighted k-Means(iMWk-Means), where feature weights are used as indices for feature selection with no requirement for user-specified parameters. The proposed feature selection methods are able to significantly reduce the number of noisy features. These methods are further extended to mean-FSFWextPD and max-FSFWextPD to address missing values and are found to be better alternatives than existing imputation methods. The effect of feature weighting on clustering of dataset defined in varying p-norms is further explored in the thesis. An algorithm that translates a dataset into different p-norms has been proposed. The capability of MWk-Means to read true shapes of clusters defined in different p- norms is explored. To address the problem of missing feature values in weighted variant of k-Means, different missing-value imputation methods are tested. The MWk-Means and its intelligent variant are further extended to incorporate the partial distance approach, specifically to address the problem of missing values. All these methods are tested in both synthetic and real-world datasets against three models of noise - noisy feature added, feature blurring and cluster-wise feature blurring - where applicable. These noises are generated from Gaussian and uniform distribution with three different strength of noise, i.e., no noise, half noise and full noise Overall, results demonstrate that feature weighting can improve feature selection. The partial- distance approach, with feature weights, is effective at ignoring missing values, and cluster retrieval in various p-norm spaces is effective

VALIDATED RP HPLC METHOD DEVELOPMENT FOR EXEMESTANE IN TABLET DOSAGE FORM

The aim of this present work was to develop stability indicating LC method, which is selective, accurate, simple, precise, reliable, cost effective and rapid for the quantification of all possible degradants and determination of exemestane. In addition, to develop and validate Stability Indicating Method for the determination of impurities (degradation products) in exemestane API by RP-HPLC. Finally, validate the developed method as per ICH guidelines

CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals

Background: We developed CEPS as an open access MATLAB® GUI (graphical user interface) for the analysis of Complexity and Entropy in Physiological Signals (CEPS), and demonstrate its use with an example data set that shows the effects of paced breathing (PB) on variability of heart, pulse and respiration rates. CEPS is also sufficiently adaptable to be used for other time series physiological data such as EEG (electroencephalography), postural sway or temperature measurements. Methods: Data were collected from a convenience sample of nine healthy adults in a pilot for a larger study investigating the effects on vagal tone of breathing paced at various different rates, part of a development programme for a home training stress reduction system. Results: The current version of CEPS focuses on those complexity and entropy measures that appear most frequently in the literature, together with some recently introduced entropy measures which may have advantages over those that are more established. Ten methods of estimating data complexity are currently included, and some 28 entropy measures. The GUI also includes a section for data pre-processing and standard ancillary methods to enable parameter estimation of embedding dimension m and time delay τ (‘tau’) where required. The software is freely available under version 3 of the GNU Lesser General Public License (LGPLv3) for non-commercial users. CEPS can be downloaded at https://bitbucket.org/deepak_panday/ceps/src/pipeline_v2/. In our illustration on PB, most complexity and entropy measures decreased significantly in response to breathing at 7 breaths per minute, differentiating more clearly than conventional linear, time- and frequency-domain measures between breathing states. In contrast, Higuchi fractal dimension increased during paced breathing. Conclusions: We have developed CEPS software as a physiological data visualiser able to integrate state of the art techniques. The interface is designed for clinical research and has a structure designed for integrating new tools. The aim is to strengthen collaboration between clinicians and the biomedical community, as demonstrated here by using CEPS to analyse various physiological responses to paced breathing

Complexity and Entropy in Physiological Signals (CEPS): Resonance Breathing Rate Assessed Using Measures of Fractal Dimension, Heart Rate Asymmetry and Permutation Entropy

Background: As technology becomes more sophisticated, more accessible methods of interpretating Big Data become essential. We have continued to develop Complexity and Entropy in Physiological Signals (CEPS) as an open access MATLAB® GUI (graphical user interface) providing multiple methods for the modification and analysis of physiological data. Methods: To demonstrate the functionality of the software, data were collected from 44 healthy adults for a study investigating the effects on vagal tone of breathing paced at five different rates, as well as self-paced and un-paced. Five-minute 15-s recordings were used. Results were also compared with those from shorter segments of the data. Electrocardiogram (ECG), electrodermal activity (EDA) and Respiration (RSP) data were recorded. Particular attention was paid to COVID risk mitigation, and to parameter tuning for the CEPS measures. For comparison, data were processed using Kubios HRV, RR-APET and DynamicalSystems.jl software. We also compared findings for ECG RR interval (RRi) data resampled at 4 Hz (4R) or 10 Hz (10R), and non-resampled (noR). In total, we used around 190–220 measures from CEPS at various scales, depending on the analysis undertaken, with our investigation focused on three families of measures: 22 fractal dimension (FD) measures, 40 heart rate asymmetries or measures derived from Poincaré plots (HRA), and 8 measures based on permutation entropy (PE). Results: FDs for the RRi data differentiated strongly between breathing rates, whether data were resampled or not, increasing between 5 and 7 breaths per minute (BrPM). Largest effect sizes for RRi (4R and noR) differentiation between breathing rates were found for the PE-based measures. Measures that both differentiated well between breathing rates and were consistent across different RRi data lengths (1–5 min) included five PE-based (noR) and three FDs (4R). Of the top 12 measures with short-data values consistently within ± 5% of their values for the 5-min data, five were FDs, one was PE-based, and none were HRAs. Effect sizes were usually greater for CEPS measures than for those implemented in DynamicalSystems.jl. Conclusion: The updated CEPS software enables visualisation and analysis of multichannel physiological data using a variety of established and recently introduced complexity entropy measures. Although equal resampling is theoretically important for FD estimation, it appears that FD measures may also be usefully applied to non-resampled data

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Beyond HRV. Extending the range of autonomic measures associated with heart rate variability – the effects of transcutaneous electroacupuncture (TEAS)

© 2021 David Mayor, Deepak Panday, Tony Steffert and Hari Kala Kandel.Background: Heart rate variability (HRV) is useful in acupuncture research as a measure of autonomic response. However, although it accurately reflects parasympathetic activity, there is less agreement on whether and how HRV can assess sympathetic activity. This study explores some potential autonomic measures beyond HRV that may do so, and investigates the effects of different frequencies and amplitudes of transcutaneous electroacupuncture (TEAS) on these measures.Peer reviewedFinal Published versio

Intervention of Climate-Smart Practices in Wheat under Rice-Wheat Cropping System in Nepal

Besides a proper agronomic management followed by Nepalese farmers, wheat (Triticum aestivum L.) production has been severely affected by changing climate. There are many interventions, including climate-smart practices, to cope with this situation and possibly enhance crop and soil productivity. Field experiments were set up in a randomized complete block design with six treatments (TRT) with four replications in three locations (LOC) during wheat-growing seasons in Nepal from 2014 to 2016. Treatments included (i) Controlled Practice (CP), (ii) Improved Low (IL), (iii) Improved High (IH), (iv) Climate Smart Agriculture Low (CSAL), (v) Climate Smart Agriculture Medium (CSAM), and (vi) Climate Smart Agriculture High (CSAH), whereas those LOC were Banke, Rupandehi and Morang districts. There was a significant main effect of TRT and LOC on grain yield and a significant interactionn effect of TRT × LOC on biomass yield in 2014–2015. About 55.5% additional grain yield was produced from CSAM treatment compared to CP in 2014–2015. Among locations, grain yield was the highest in Banke (3772.35 kg ha–1) followed by Rupandehi (2504.47 kg ha–1) and Morang districts (2504.47 kg ha–1). In 2015–2016, there was a significant interaction effect of TRT × LOC on grain and biomass yields. The highest grain yield was produced from CSAH treatment in Banke district in 2015–2016. Overall, grain yield and other parameters showed a better response with either of the climate-smart interventions (mostly CSAH or CSAM) despite variability in geography, climate, and other environmental factors indicating the potential of climate-smart practices to improve wheat production in southern plains of Nepal

Intervention of Climate‐Smart Practices in Wheat under Rice‐ Wheat Cropping System in Nepal

Besides a proper agronomic management followed by Nepalese farmers, wheat (Triticum aestivum L.) production has been severely affected by changing climate. There are many interventions, including climate‐smart practices, to cope with this situation and possibly enhance crop and soil productivity. Field experiments were set up in a randomized complete block design with six treatments (TRT) with four replications in three locations (LOC) during wheat‐growing seasons in Nepal from 2014 to 2016. Treatments included (i) Controlled Practice (CP), (ii) Improved Low (IL), (iii) Improved High (IH), (iv) Climate Smart Agriculture Low (CSAL), (v) Climate Smart Agriculture Medium (CSAM), and (vi) Climate Smart Agriculture High (CSAH), whereas those LOC were Banke, Rupandehi and Morang districts. There was a significant main effect of TRT and LOC on grain yield and a significant interactionn effect of TRT × LOC on biomass yield in 2014– 2015. About 55.5% additional grain yield was produced from CSAM treatment compared to CP in 2014–2015. Among locations, grain yield was the highest in Banke (3772.35 kg ha−1 ) followed by Rupandehi (2504.47 kg ha−1 ) and Morang districts (2504.47 kg ha−1 ). In 2015–2016, there was a significant interaction effect of TRT × LOC on grain and biomass yields. The highest grain yield was produced from CSAH treatment in Banke district in 2015–2016. Overall, grain yield and other parameters showed a better response with either of the climate‐smart interventions (mostly CSAH or CSAM) despite variability in geography, climate, and other environmental factors indicating the potential of climate‐smart practices to improve wheat production in southern plains of Nepal