Fractional-Order PID Controllers for Temperature Control:A Review

Fractional-order proportional integral derivative (FOPID) controllers are becoming increasingly popular for various industrial applications due to the advantages they can offer. Among these applications, heating and temperature control systems are receiving significant attention, applying FOPID controllers to achieve better performance and robustness, more stability and flexibility, and faster response. Moreover, with several advantages of using FOPID controllers, the improvement in heating systems and temperature control systems is exceptional. Heating systems are characterized by external disturbance, model uncertainty, non-linearity, and control inaccuracy, which directly affect performance. Temperature control systems are used in industry, households, and many types of equipment. In this paper, fractional-order proportional integral derivative controllers are discussed in the context of controlling the temperature in ambulances, induction heating systems, control of bioreactors, and the improvement achieved by temperature control systems. Moreover, a comparison of conventional and FOPID controllers is also highlighted to show the improvement in production, quality, and accuracy that can be achieved by using such controllers. A composite analysis of the use of such controllers, especially for temperature control systems, is presented. In addition, some hidden and unhighlighted points concerning FOPID controllers are investigated thoroughly, including the most relevant publications

3D-Hog Embedding Frameworks for Single and Multi-Viewpoints Action Recognition Based on Human Silhouettes

This paper has been presented at : 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Given the high demand for automated systems for human action recognition, great efforts have been undertaken in recent decades to progress the field. In this paper, we present frameworks for single and multi-viewpoints action recognition based on Space-Time Volume (STV) of human silhouettes and 3D-Histogram of Oriented Gradient (3D-HOG) embedding. We exploit fast-computational approaches involving Principal Component Analysis (PCA) over the local feature spaces for compactly describing actions as combinations of local gestures and L 2 -Regularized Logistic Regression (L 2 -RLR) for learning the action model from local features. Outperforming results on Weizmann and i3DPost datasets confirm efficacy of the proposed approaches as compared to the baseline method and other works, in terms of accuracy and robustness to appearance changes

Impact of the societal response to COVID-19 on access to healthcare for non-COVID-19 health issues in slum communities of Bangladesh, Kenya, Nigeria and Pakistan: Results of pre-COVID and COVID-19 lockdown stakeholder engagements

Introduction: With COVID-19, there is urgency for policymakers to understand and respond to the health needs of slum communities. Lockdowns for pandemic control have health, social and economic consequences. We consider access to healthcare before and during COVID-19 with those working and living in slum communities.Methods: In seven slums in Bangladesh, Kenya, Nigeria and Pakistan, we explored stakeholder perspectives and experiences of healthcare access for non-COVID-19 conditions in two periods: pre-COVID-19 and during COVID-19 lockdowns.Results: Between March 2018 and May 2020, we engaged with 860 community leaders, residents, health workers and local authority representatives. Perceived common illnesses in all sites included respiratory, gastric, waterborne and mosquitoborne illnesses and hypertension. Pre-COVID, stakeholders described various preventive, diagnostic and treatment services, including well-used antenatal and immunisation programmes and some screening for hypertension, tuberculosis, HIV and vectorborne disease. In all sites, pharmacists and patent medicine vendors were key providers of treatment and advice for minor illnesses. Mental health services and those addressing gender-based violence were perceived to be limited or unavailable. With COVID-19, a reduction in access to healthcare services was reported in all sites, including preventive services. Cost of healthcare increased while household income reduced. Residents had difficulty reaching healthcare facilities. Fear of being diagnosed with COVID-19 discouraged healthcare seeking. Alleviators included provision of healthcare by phone, pharmacists/drug vendors extending credit and residents receiving philanthropic or government support; these were inconsistent and inadequate.Conclusion: Slum residents\u27 ability to seek healthcare for non-COVID-19 conditions has been reduced during lockdowns. To encourage healthcare seeking, clear communication is needed about what is available and whether infection control is in place. Policymakers need to ensure that costs do not escalate and unfairly disadvantage slum communities. Remote consulting to reduce face-to-face contact and provision of mental health and gender-based violence services should be considered

Wavelength tunable soliton rains in a nanotube-mode locked Tm-doped fiber laser

We report soliton rains in a tunable Tm-doped fiber laser mode locked by carbon nanotubes. We also detect their second- and third-harmonics. We achieve a tunability of over 56 nm, from 1877 to 1933 nm, by introducing a polarization-maintaining isolator and two in-line polarization controllers. This makes our system promising as a tunable filter for ultrafast spectroscopy.We acknowledge funding from ERC Grant Hetero2D, EPSRC Grants Nos. EP/L016087/1, EP/K017144/1, EP/K01711X/1 and the China Scholarship Council

Immunogenicity and protective efficacy of the Mycobacterium avium subsp. paratuberculosis attenuated mutants against challenge in a mouse model

Johne’s disease (JD), caused by Mycobacterium avium subsp. paratuberculosis (MAP), results in serious economic losses worldwide especially in cattle, sheep and goats. To control the impact of JD on the animal industry, an effective vaccine with minimal adverse effects is urgently required. In order to develop an effective vaccine, we used allelic exchange to construct three mutant MAP strains, leuD, mpt64 and secA2. The mutants were attenuated in a murine model and induced cytokine responses in J774A.1 cell. The leuD mutant was the most obviously attenuated of the three constructed mutant strains. Our preliminary vaccine trial in mice demonstrated different levels of protection were induced by these mutants based on the acid-fast bacilli burden in livers and spleens at 8 and 12 weeks post challenge. In addition, vaccination with leuD mutant induced a high level of IFN- production and significant protective efficacy in both the reduction of inflammation and clearance of acid-fast bacilli, as compared with the mock vaccinated group

Blue Laser Diode-Based Visible Light Communication and Solid-State Lighting

In this chapter, we review our recent work on blue laser diode-based visible light communication and solid-state lighting. Gallium nitride (GaN) phosphor-converted white light-emitting diodes (Pc-WLEDs) are emerging as an indispensable solid-state lighting (SSL) source for next-generation display system and the lighting industry. Together with the function of lighting, visible light communication (VLC) using Pc-WLEDs has gained increasing attention to fulfill the growing demand for wireless data communication. Practically, the low modulation response and low emitting intensity of light-emitting diodes (LED) are the drawbacks for the development of ultrahigh-speed VLC and high-quality SSL system. Blue GaN laser diode (LD) and remote phosphor-based white light can be used for both high-speed VLC and SSL simultaneously. We demonstrated a color-rendering index (CRI) of 93.8, a correlated color temperature (CCT) of 4435 K, and a data rate of 1.6 Gbps under NRZ-OOK modulation by an exciting blue laser diode on narrowband green−/red-emitting composite phosphor film. This work opens up exciting possibilities for future high-speed indoor VLC and high-quality SSL

Financial Fraud Detection Model Based on Random Forest

Business's accelerated globalization has weakened regulatory capacity of the law and scholars have been paid attention to fraud detection in recent years. In this study, we introduced Random Forest (RF) for financial fraud technique detection and detailed features selection, variables’ importance measurement, partial correlation analysis and Multidimensional analysis. The results show that a combination of eight variables has the highest accuracy. The ratio of debt to equity (DEQUTY) is the most important variable in the model. Moreover, we applied four statistic methodologies, including parametric and non-parametric models to construct detection models and concluded that Random Forest has the highest accuracy and the non-parametric models have higher accuracy than non-parametric models. However, Random Forest can improve the detection efficiency significantly and have an important practical implication