Fast Yet Effective Machine Unlearning

Unlearning the data observed during the training of a machine learning (ML) model is an important task that can play a pivotal role in fortifying the privacy and security of ML-based applications. This paper raises the following questions: (i) can we unlearn a single or multiple classes of data from an ML model without looking at the full training data even once? (ii) can we make the process of unlearning fast and scalable to large datasets, and generalize it to different deep networks? We introduce a novel machine unlearning framework with error-maximizing noise generation and impair-repair based weight manipulation that offers an efficient solution to the above questions. An error-maximizing noise matrix is learned for the class to be unlearned using the original model. The noise matrix is used to manipulate the model weights to unlearn the targeted class of data. We introduce impair and repair steps for a controlled manipulation of the network weights. In the impair step, the noise matrix along with a very high learning rate is used to induce sharp unlearning in the model. Thereafter, the repair step is used to regain the overall performance. With very few update steps, we show excellent unlearning while substantially retaining the overall model accuracy. Unlearning multiple classes requires a similar number of update steps as for the single class, making our approach scalable to large problems. Our method is quite efficient in comparison to the existing methods, works for multi-class unlearning, doesn't put any constraints on the original optimization mechanism or network design, and works well in both small and large-scale vision tasks. This work is an important step towards fast and easy implementation of unlearning in deep networks. We will make the source code publicly available

Relationship between anthropometric characteristics and aerobic fitness among Malaysian men and women

This cross-sectional study evaluated the relationships between anthropometric and aerobic fitness (rate of perceived exertion [RPE] and predicted maximal oxygen uptake [VO2max]) among 228 participants (age: 23.78±4.42 years). RPE and predicted VO2max were determined during the cycle ergometer exercise test. Data were also obtained for height, weight, body mass index (BMI), hip and waist (WC) circumferences. Data analysis revealed VO2max is correlated with WC (r=-0.571), weight (r=-0.521), waist-to-height ratio (WHtR) (r=-0.516), waist-to-hip ratio (WHR) (r=-0.487), and BMI (r=-0.47) in men, while, in women with WC (r=-0.581), weight (r=-0.571), WHtR (r=-0.545), BMI (r=-0.545), WHR (r=-0.473), and height (r=-0.287) (all P<0.05). Regression analysis showed WC was a significant predictor for VO2max in men and women (r 2=32.6% vs. 33.7%). The receiver operating characteristic curve of WC showed 0.786 and 0.831 for men and women, respectively. WC or abdominal obesity is the strongest predictor for VO2max, which is an indicator of aerobic fitness in Malaysian adults

A modified GRRAS checklist for the quality of reliability research in knee ultrasonography: An inter-rater agreement study

Introduction The original Guidelines for Reporting Reliability and Agreement Studies (GRRAS) checklist uses 15 items to assess the quality of reliability research. However, six of the 15 items have equal to or more than two sub-items which creates the potential for inconsistencies in reporting quality scoring within and between researchers. Therefore, as part of a wider systematic review examining the reliability of tibiofemoral joint articular cartilage ultrasonography (US), we modified the GRRAS checklist by separating all sub-items, yielding a new checklist with 24 items. Subsequently, the aim of this study was to determine the inter-rater agreement of the modified GRRAS (mGRRAS) checklist as a tool for assessing the quality of reliability research studies. Methods The mGRRAS checklist was used to assess the quality of studies selected specifically for inclusion in the systematic review (n=6). Each of the 24 items could be scored from zero to one, yielding a potential total score ranging from zero to 24. Higher scores represented overall higher quality of reliability research. Two researchers (R1, R2) scored the selected studies independently. If R1 or R2 were unable to decide on their score for any of the 24 items, a third researcher (R3) was available to facilitate the process further. Researchers’ scores were compared using the percent agreement statistic. Levels of agreement were classed: 71-80%, moderate; 81-90%, strong; 91-100%, almost perfect to perfect. Data were analysed using SPSS (v29). Results The total score for the six selected studies ranged from 15 to 21 out of 24. Neither R1 nor R2 required the assistance of R3 to decide on the score for any item. Inter-rater agreement was 83%, indicating that there was strong agreement between R1 and R2. Conclusion The mGRRAS checklist can improve quality scoring of reliability research studies due to its increased number of items. It can be used by raters independently, has strong inter-rater agreement, and may be useful for future assessment of the quality of knee US reliability research studies. Impact Measurement reliability is a prerequisite for valid interpretation of change in patients’ knee US data across time. The mGRRAS will assist clinicians to assess the quality of knee articular cartilage US reliability research and, in turn, choose which US method to employ in their clinical practice. References: Kottner J, Audige L, Brorson S, Donner A, Gajewski B, Hrobjartsson A, Roberts C, Shoukri M, Streiner D (2011) Guidelines for Reporting Reliability and Agreement Studies (GRRAS) Were Proposed. Journal of Clinical Epidemiology. 64, 96-106

Mental illness and injuries: emerging health challenges of urbanisation in South Asia

This article was published in the BMJ (Online) [© 2017 BMJ Publishing Group] and the definitive version is available at: http://doi.org10.1136/bmj.j1126 The Journal's website is at: http://www.bmj.com/content/357/bmj.j1126Publishe

Comparison of Sarcopenia Indices Based on Fall History and Level of Fear of Falling among Community-dwelling Older Adults in Selangor, Malaysia

Introduction: Sarcopenia, one of the geriatric syndromes characterized by changes in muscle mass, muscle strength and physical performance, may lead to falls in older adults. Objective: This study aimed to compare sarcopenia indices, fall history, and fear of falling (FoF) among community-dwelling older adults. Methods: : This cross-sectional study involved 201 participants (mean age = 68.45 ± 6.30 years). Fall history and FoF were recorded through assisted questionnaires and the short Fall-Efficacy Scale-international, respectively. Sarcopenia indices were measured including muscle mass (bioelectrical impedance analysis), muscle strength (JAMAR hand dynamometer), and physical performance (5-time chair stand test). Analysis of covariance (ANCOVA) was conducted to compare sarcopenia indices between fall history and FoF while controlling for age and gender. The level of statistical significance was set at p<0.05. Results: A total of 71 (35%) participants reported of a fall during the past 12 months, while approximately half of the participants demonstrated a higher concern for falls (50.2%). Those without a fall history scored significantly better in all sarcopenia indices (all p<0.05). Additionally, participants with a lower concern of falling had significantly better sarcopenia indices (p<0.05) compared to those with a greater concern of falls, except for muscle mass (p=0.052). Conclusion: Fall history and fear of falling may lead to symptoms of sarcopenia. These findings can provide evidence for promoting health education and continuous screening among older adults at risk of falls and sarcopenia

Reliability Assessment of Main Engine Subsystems Considering Turbocharger Failure as a Case Study

Safe operation of a merchant vessel is dependent on the reliability of the vessel’s main propulsion engine. Reliability of the main propulsion engine is interdependent on the reliability of several subsystems including lubricating oil system, fuel oil system, cooling water system and scavenge air system. Turbochargers form part of the scavenge sub system and play a vital role in the operation of the main engine. Failure of turbochargers can lead to disastrous consequences and immobilisation of the main engine. Hence due consideration need to be given to the reliability assessment of the scavenge system while assessing the reliability of the main engine. This paper presents integration of Markov model (for constant failure components) and Weibull failure model (for wearing out components) to estimate the reliability of the main propulsion engine. This integrated model will provide more realistic and practical analysis. It will serve as a useful tool to estimate the reliability of the vessel’s main propulsion engine and make efficient and effective maintenance decisions. A case study of turbocharger failure and its impact on the main engine is also discussed

Impact of Late Shift Rapid Response Team (RRT) Input on Length of Stay and Discharge Destination in Emergency Care.

Prolonged length of stay (LOS) is a significant financial burden to the hospitals. Although Physiotherapists (PT) are expanding their role in different areas of health care, including Emergency Care (EC), the impact of late shift PT input on LOS is not yet known. The objective was to determine the impact of the late shift Rapid Response Team (RRT) input on LOS and discharge destination. Patients who are referred to the RRT Physiotherapy/Occupational Therapy (PT/OT) include those with musculoskeletal conditions, cardio-respiratory and neurological problems. The therapists establish patient’s premorbid mobility level, social status and complete mobility and balance assessments. The outcome measures considered for this study was LOS and discharge destination. A total of 131 patients were assessed during 2016/2017. Out of 131, 72 patients were discharged on the day of treatment. Out of 138 patients referred during 2017/2018, 79 patients were discharged on the day of assessment. Most patients had significant comorbidities when admitted as the number of comorbidities is approximately four conditions for both durations. The discharge destination included from patients own home, rehabilitation hospital, long stay wardand interim placementfrom ward and this has saved 151 bed days in the hospital. Late shift RRT service in the ED resulted in reduced LOS and improved discharge destination