Context dependent fuzzy modelling and its applications

Fuzzy rule-based systems (FRBS) use the principle of fuzzy sets and fuzzy logic to describe vague and imprecise statements and provide a facility to express the behaviours of the system with a human-understandable language. Fuzzy information, once defined by a fuzzy system, is fixed regardless of the circumstances and therefore makes it very difficult to capture the effect of context on the meaning of the fuzzy terms. While efforts have been made to integrate contextual information into the representation of fuzzy sets, it remains the case that often the context model is very restrictive and/or problem specific. The work reported in this thesis is our attempt to create a practical frame work to integrate contextual information into the representation of fuzzy sets so as to improve the interpretability as well as the accuracy of the fuzzy system. Throughout this thesis, we have looked at the capability of the proposed context dependent fuzzy sets as a stand alone as well as in combination with other methods in various application scenarios ranging from time series forecasting to complicated car racing control systems. In all of the applications, the highly competitive performance nature of our approach has proven its effectiveness and efficiency compared with existing techniques in the literature

Context dependent fuzzy modelling and its applications

Fuzzy rule-based systems (FRBS) use the principle of fuzzy sets and fuzzy logic to describe vague and imprecise statements and provide a facility to express the behaviours of the system with a human-understandable language. Fuzzy information, once defined by a fuzzy system, is fixed regardless of the circumstances and therefore makes it very difficult to capture the effect of context on the meaning of the fuzzy terms. While efforts have been made to integrate contextual information into the representation of fuzzy sets, it remains the case that often the context model is very restrictive and/or problem specific. The work reported in this thesis is our attempt to create a practical frame work to integrate contextual information into the representation of fuzzy sets so as to improve the interpretability as well as the accuracy of the fuzzy system. Throughout this thesis, we have looked at the capability of the proposed context dependent fuzzy sets as a stand alone as well as in combination with other methods in various application scenarios ranging from time series forecasting to complicated car racing control systems. In all of the applications, the highly competitive performance nature of our approach has proven its effectiveness and efficiency compared with existing techniques in the literature

Building Footprint Extraction in Dense Areas using Super Resolution and Frame Field Learning

Despite notable results on standard aerial datasets, current state-of-the-arts fail to produce accurate building footprints in dense areas due to challenging properties posed by these areas and limited data availability. In this paper, we propose a framework to address such issues in polygonal building extraction. First, super resolution is employed to enhance the spatial resolution of aerial image, allowing for finer details to be captured. This enhanced imagery serves as input to a multitask learning module, which consists of a segmentation head and a frame field learning head to effectively handle the irregular building structures. Our model is supervised by adaptive loss weighting, enabling extraction of sharp edges and fine-grained polygons which is difficult due to overlapping buildings and low data quality. Extensive experiments on a slum area in India that mimics a dense area demonstrate that our proposed approach significantly outperforms the current state-of-the-art methods by a large margin.Comment: Accepted at The 12th International Conference on Awareness Science and Technolog

The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021

Background: Tackling the spread of COVID-19 remains a crucial part of ending the pandemic. Its highly contagious nature and constant evolution coupled with a relative lack of immunity make the virus difficult to control. For this, various strategies have been proposed and adopted including limiting contact, social isolation, vaccination, contact tracing, etc. However, given the heterogeneity in the enforcement of these strategies and constant fluctuations in the strictness levels of these strategies, it becomes challenging to assess the true impact of these strategies in controlling the spread of COVID-19.Methods: In the present study, we evaluated various transmission control measures that were imposed in 10 global urban cities and provinces in 2021 Bangkok, Gauteng, Ho Chi Minh City, Jakarta, London, Manila City, New Delhi, New York City, Singapore, and Tokyo.Findings: Based on our analysis, we herein propose the population-level Swiss cheese model for the failures and pit-falls in various strategies that each of these cities and provinces had. Furthermore, whilst all the evaluated cities and provinces took a different personalized approach to managing the pandemic, what remained common was dynamic enforcement and monitoring of breaches of each barrier of protection. The measures taken to reinforce the barriers were adjusted continuously based on the evolving epidemiological situation.Interpretation: How an individual city or province handled the pandemic profoundly affected and determined how the entire country handled the pandemic since the chain of transmission needs to be broken at the very grassroot level to achieve nationwide control

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

A novel fuzzy inferencing methodology for simulated car racing

Abstract—This paper describes and further extends the fuzzy inferencing system which won the simulated car racing compe-tition that was arranged as part of FuzzIEEE 2007 conference. The details of the winning non-stationary fuzzy controller and its results are presented. A novel approach to further improve the performance of the winning controller is described and formalised. We term the new fuzzy inferencing method a ‘context-dependent fuzzy inference system’. The concept of a ‘context-dependent fuzzy set ’ that is utilised by the fuzzy system is introduced. Finally, a comparison between context-dependent fuzzy inference system and various existing techniques are carried out on the simulated car racing application. The results show a better performance for context-dependent fuzzy inference systems in stochastic circumstances

Electrical properties and stability of low temperature annealed (Zn,Cu) co-doped (Ni,Mn)3O4 spinel thin films

Toward the development of infrared (IR) detectors, nickel–manganite-based thin films were initially prepared from (Ni0.2Mn2.8–xCux)Cl2 (0.010 ≤ x ≤ 0.040) solutions using the liquid flow deposition (LFD) method. The influence of Cu on the negative temperature coefficient of resistance (NTCR) characteristic of the films annealed at 400°C was investigated. It was found that the incorporation of Cu can effectively enhance electrical conductivity; however, it degrades both the thermal sensitivity and stability of the nickel–manganite films. The investigation was extended by further modifying the composition with Zn. The results revealed that by co-doping Cu with a proper amount of Zn the temperature coefficient of resistance (TCR) could be tailored, while a relatively low resistivity (ρ) of the final products was retained. Specially, when 0.01 mol Zn was added to a precursor solution containing 0.025 mol Cu, the resulting specimen possessed a TCR = 2.82% K–1 and a ρ = 820 Ω (measured at RT). More importantly, compared to Zn-free films, the (Zn,Cu) co-doped compositions showed much improved electrical stability, with an aging coefficient (ΔR/R) as low as 4.6%, after aging at 150°C in air for 500 h. The results suggest that the (Zn,Cu) co–doped (Ni,Mn)3O4 thin films have a promising application in IR detectors