Final Report - Regulatory Considerations for Adaptive Systems

This report documents the findings of a preliminary research study into new approaches to the software design assurance of adaptive systems. We suggest a methodology to overcome the software validation and verification difficulties posed by the underlying assumption of non-adaptive software in the requirementsbased- testing verification methods in RTCA/DO-178B and C. An analysis of the relevant RTCA/DO-178B and C objectives is presented showing the reasons for the difficulties that arise in showing satisfaction of the objectives and suggested additional means by which they could be satisfied. We suggest that the software design assurance problem for adaptive systems is principally one of developing correct and complete high level requirements and system level constraints that define the necessary system functional and safety properties to assure the safe use of adaptive systems. We show how analytical techniques such as model based design, mathematical modeling and formal or formal-like methods can be used to both validate the high level functional and safety requirements, establish necessary constraints and provide the verification evidence for the satisfaction of requirements and constraints that supplements conventional testing. Finally the report identifies the follow-on research topics needed to implement this methodology

Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report

This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning

Modelling and analysis of a modified Dodecapod parallel manipulator

Parallel manipulator is one of the areas of research extensively studied by many researchers from past 4-5 decades. Unlike their serial counterparts, parallel manipulators exhibit higher rigidity and controllability when operating at higher speeds. These attributes lead to their application in various fields such as machine tools, simulators and positioning systems. Present work is proposing a modified reconfigurable Dodecapod parallel manipulator. 3D model of the proposed manipulator is successfully developed and kinematics analysis is carried out. Re-configurable sliders are provided to vary the workspace as required. A few illustrative examples are demonstrated for various locations of slider, showing changes in workspace. The novelty of the present manipulator overcomes the workspace limitations of the general Stewart Gough manipulator. Present modified Dodecapod parallel manipulator is capable of improving local kinematic performance

Data Mining for Anomaly Detection

The Vehicle Integrated Prognostics Reasoner (VIPR) program describes methods for enhanced diagnostics as well as a prognostic extension to current state of art Aircraft Diagnostic and Maintenance System (ADMS). VIPR introduced a new anomaly detection function for discovering previously undetected and undocumented situations, where there are clear deviations from nominal behavior. Once a baseline (nominal model of operations) is established, the detection and analysis is split between on-aircraft outlier generation and off-aircraft expert analysis to characterize and classify events that may not have been anticipated by individual system providers. Offline expert analysis is supported by data curation and data mining algorithms that can be applied in the contexts of supervised learning methods and unsupervised learning. In this report, we discuss efficient methods to implement the Kolmogorov complexity measure using compression algorithms, and run a systematic empirical analysis to determine the best compression measure. Our experiments established that the combination of the DZIP compression algorithm and CiDM distance measure provides the best results for capturing relevant properties of time series data encountered in aircraft operations. This combination was used as the basis for developing an unsupervised learning algorithm to define "nominal" flight segments using historical flight segments

The effect of letrozole vs clomiphene citrate for ovulation induction in patients of infertility with polycystic ovarian syndrome

Background: The overall prevalence of primary infertility in India is 3.9% to 16.8%. PCOS being a recognized cause of infertility, affects 8 to 13% of all reproductive-age women. Clomiphene citrate (CC) is most commonly used as first line drug for ovulation induction. CC is selective estrogen receptor modulator (SERM) and has adverse effect on cervical mucus and endometrial receptivity resulting in low pregnancy rates. Letrozole an aromatase inhibitor is considered as better alternative drug due to its benefits over CC. Thus, the aim of the present study is to assess the effect of letrozole and clomiphene citrate for ovulation induction in women with PCOS and compare the pregnancy rates. Methods: This is a hospital based randomized controlled study conducted on 89 patients at Armed forces medical college in western Maharashtra from June 2019 to May 22. Women with infertility due to PCOS attending OPD/IPD who fulfilled the inclusion criteria were included in the study. The subjects were divided into two groups through computer generated randomization and Group A of 45 subjects received letrozole for ovulation induction while Group B with 44 subjects received clomiphene citrate (CC). Data was analyzed and comparison among the study groups was done with the help of unpaired t test or Mann-Whitney test. Results: The number of mature follicles after treatment was significantly greater in clomiphene citrate group (1.59 ± 1.04) as compared to letrozole (1.02 ± 0.76). However, there was statistically significant greater mono ovulation with letrozole (55.2% vs 40.3%, p=0.03). After ovulation induction, the mean endometrial thickness was significantly greater in letrozole group as compared to CC (9.85±2.32 mm vs. 8.45±1.53 mm; p<0.05). Ovulation rate with letrozole was 42.5% vs 32.5% and pregnancy rate was letrozole 20% vs CC 7.5% which was statistically significant (p<0.05). Conclusions: Letrozole is a better drug for ovulation induction in women with PCOS with an ovulatory cycles as pregnancy rates are higher and lesser chance of multiple pregnancy

MASR: Metadata Aware Speech Representation

In the recent years, speech representation learning is constructed primarily as a self-supervised learning (SSL) task, using the raw audio signal alone, while ignoring the side-information that is often available for a given speech recording. In this paper, we propose MASR, a Metadata Aware Speech Representation learning framework, which addresses the aforementioned limitations. MASR enables the inclusion of multiple external knowledge sources to enhance the utilization of meta-data information. The external knowledge sources are incorporated in the form of sample-level pair-wise similarity matrices that are useful in a hard-mining loss. A key advantage of the MASR framework is that it can be combined with any choice of SSL method. Using MASR representations, we perform evaluations on several downstream tasks such as language identification, speech recognition and other non-semantic tasks such as speaker and emotion recognition. In these experiments, we illustrate significant performance improvements for the MASR over other established benchmarks. We perform a detailed analysis on the language identification task to provide insights on how the proposed loss function enables the representations to separate closely related languages

Using Participatory Statistics to Examine the Impact of Interventions to Eradicate Slavery: Lessons from the Field

This CDI Practice Paper by Pauline Oosterhoff, Sowmyaa Bharadwaj, Danny Burns, Aruna Mohan Raj, Rituu B. Nanda and Pradeep Narayanan reflects on the use of participatory statistics to assess the impact of interventions to eradicate slavery and bonded labour. It deals with: (1) the challenges of estimating changes in the magnitude of various forms of slavery; (2) the potential of combining participatory approaches with statistical principles to generate robust data for assessing impact of slavery eradication; and (3) the practical and ethical questions in relation to working with people living within a context of modern slavery. The paper draws lessons from the realities of using participatory statistics to support the evaluation of a slavery eradication programme in North India.UK Department for International Developmen

A gender synchronized family planning intervention for married couples in rural India: study protocol for the CHARM2 cluster randomized controlled trial evaluation.

BackgroundPrior research from India demonstrates a need for family planning counseling that engages both women and men, offers complete family planning method mix, and focuses on gender equity and reduces marital sexual violence (MSV) to promote modern contraceptive use. Effectiveness of the three-session (two male-only sessions and one couple session) Counseling Husbands to Achieve Reproductive Health and Marital Equity (CHARM) intervention, which used male health providers to engage and counsel husbands on gender equity and family planning (GE + FP), was demonstrated by increased pill and condom use and a reduction in MSV. However, the intervention had limited reach to women and was therefore unable to expand access to highly effective long acting reversible contraceptives such as the intrauterine device (IUD). We developed a second iteration of the intervention, CHARM2, which retains the three sessions from the original CHARM but adds female provider- delivered counseling to women and offers a broader array of contraceptives including IUDs. This protocol describes the evaluation of CHARM2 in rural Maharashtra.MethodsA two-arm cluster randomized controlled trial will evaluate CHARM2, a gender synchronized GE + FP intervention. Eligible married couples (n = 1200) will be enrolled across 20 clusters in rural Maharashtra, India. Health providers will be gender-matched to deliver two GE + FP sessions to the married couples in parallel, and then a final session will be delivered to the couple together. We will conduct surveys on demographics as well as GE and FP indicators at baseline, 9-month, and 18-month follow-ups with both men and women, and pregnancy tests at each time point from women. In-depth interviews will be conducted with a subsample of couples (n = 50) and providers (n = 20). We will conduct several implementation and monitoring activities for purposes of assuring fidelity to intervention design and quality of implementation, including recruitment and tracking logs, provider evaluation forms, session observation forms, and participant satisfaction surveys.DiscussionWe will complete the recruitment of participants and collection of baseline data by July 2019. Findings from this work will offer important insight for the expansion of the national family planning program and improving quality of care for India and family planning interventions globally.Trial registrationClinicalTrial.gov, NCT03514914

Current Opinion on Food Sustainability for Liver Associated Health Problems: Facts and Myths with Case Study

The liver is the second-largest organ in our body which separates the nutrients and waste as they move through our biological process system and it additionally produces bile, a substance that carries toxins out of your body and aids in digestion. There are several myths associated with liver spread amongst masses. It is a vital necessity to make society devoid of such myths and aware of the real scenario. This review aimed to summarize the different facts and myths associated with health problems of liver and highlight the importance of food sustainability approach with the help of some case studies. A comprehensive literature search was conducted using various databases between 2006 and 2022 that focused on the various facts and myths associated with liver related health issues. Myths create nothing but false notions and fear amongst people. Some case studies were summarized to clear all the conflict statements commonly related with liver diseases in the society. Myths like nothing other than water is considered a good beverage for the liver, but recent studies have proven that measured quantities of coffee and herbal tea intake is healthy for the body. Additionally, coffee has a protective effect on the organ liver. Similarly, hepatitis can spread through casual contacts. Although it is proven that hepatitis B, C and autoimmune hepatitis, do not spread on having casual contact or sharing food and drink. A substantial myth states that blood tests can detect problems associated with the liver, but doctors rarely suggest blood tests for liver functioning. This review is focused to resolve several myths associated with the liver which are often considered true by masses