Kalman Filtering and Its Real‐Time Applications

Kalman filter was pioneered by Rudolf Emil Kalman in 1960, originally designed and developed to solve the navigation problem in Apollo Project. Since then, numerous applications were developed with the implementation of Kalman filter, such as applications in the fields of navigation and computer vision\u27s object tracking. Kalman filter consists of two separate processes, namely the prediction process and the measurement process, which work in a recursive manner. Both processes are modeled by groups of equations in the state space model to achieve optimal estimation outputs. Prior knowledge on the state space model is needed, and it differs between different systems. In this chapter, the authors outlined and explained the fundamental Kalman filtering model in real‐time discrete form and devised two real‐time applications that implemented Kalman filter. The first application involved using vision camera to perform real‐time image processing for vehicle tracking, whereas the second application discussed the real‐time Global Positioning System (GPS)‐aided Strapdown Inertial Navigation Unit (SINU) system implementation using Kalman filter. Detail descriptions, model derivations, and results are outlined in both applications

Bridging Exhibitionism and Internet Pornography: Is There A Link?

Exhibitionism is a distressing condition which may have a link with the increasing availability and usage of online sexual activities (OSA). We highlight a 42-year-old man who presented with a constant craving for OSA to achieve his sexual satisfaction which included exposing his genitalia to virtual partners, unsuspected strangers, and colleagues in public areas. His sexual behaviours were further reinforced by an online video chatting with genitalia exposure, which ended commonly with an exchange of masturbatory acts. He denied any problem with his erection and able to achieve orgasm via common sexual acts. There was no past psychiatric history nor family history of mental disorder. He volunteered to seek psychiatric help and subsequently given a psycho education on his illness and how to cope with the distress associated with his sexual acts. He was scheduled for an intensive psychotherapy to instil insight and hope to deal with his sexual difficulties

Unique Challenges for Mental Health in Inpatient Settings Amid the COVID-19 Pandemic

COVID-19 has impacted the world in many ways due to fears of contracting the pandemic, social distancing, and large-scale movement control rules. These have especially grave consequences for inpatient psychiatry. This article reviews measures taken to adapt to the new norm in inpatient care, both for standalone psychiatry units and consultation-liaison units. For inpatient units, changes have been made for personal protective equipment usage, screening and triaging policies, and training and educational policies. Consultation liaison units together with inpatient units have been required to expand the scope of coverage and difficulties by providing certain teleconsultation services. As the new norm takes precedence, Sabah has to embrace and empower community-based psychiatry services for better outreach and coverage. This article discusses the issues underlying the new norm in the management of inpatient psychiatry patients in both units and presents some points and practical solutions on the ground to instil hope

Unique challenges for mental health in inpatient settings amid the COVID-19 pandemic: Perspective from Sabah

COVID-19 has impacted the world in many ways due to fears of contracting the pandemic, social distancing, and large-scale movement control rules. These have especially grave consequences for inpatient psychiatry. This article reviews measures taken to adapt to the new norm in inpatient care, both for standalone psychiatry units and consultation-liaison units. For inpatient units, changes have been made for personal protective equipment usage, screening and triaging policies, and training and educational policies. Consultation liaison units together with inpatient units have been required to expand the scope of coverage and difficulties by providing certain teleconsultation services. As the new norm takes precedence, Sabah has to embrace and empower community-based psychiatry services for better outreach and coverage. This article discusses the issues underlying the new norm in the management of inpatient psychiatry patients in both units and presents some points and practical solutions on the ground to instil hope

Treatment for identical twins simultaneously developing an eating disorder precipitated by COVID-19 pandemic home quarantine

An eating disorder presenting simultaneously in identical twins remains a rarity in the literature. In this case report, we describe monozygotic twins who presented simultaneously with anorexia nervosa as a psychological effect of COVID-19 home quarantine. Both twins were previously well but developed food restriction, exercise, and mutual surveillance behaviours in competition with each other over three months in early 2020. There were no features of other mood, anxiety or psychotic disorders, and there was no organic disease. However, a strong family history of anxiety disorders and highly permeable familial boundaries were identified. Non-pharmacological management modalities including family therapy and psychotherapy were implemented, and tailored to the twins. We discuss the unique genetic and psychological interactions that conceivably explain the aetiology of this simultaneous presentation of an eating disorder in a pair of twins and examine a simple psychodynamic formulation of this simultaneous emergence. Lastly, we look at the sequelae of COVID-19 related quarantines and isolation as potentiators of eating disorders in adolescents whose education and potential employment were drastically curtailed by movement restrictions

A multi-layer perceptron-based approach for early detection of BSR disease in oil palm trees using hyperspectral images

Basal Stem Rot (BSR) disease caused by Ganoderma boninense is identified as the biggest threat in oil palm industry in Malaysia, resulting in significant yield losses. Effective BSR disease detection is important for plantation management to ensure stable palm oil production. Existing method is done by experience personnel, via visual inspection it is very time consuming. Rapid development of unmanned aerial vehicle (UAV) and machine learning has the potential to address this issue with higher efficiency. This paper proposed a new framework to automate BSR disease detection with UAV images to improve time efficiency and automate detection process. The proposed method has two steps, first hyperspectral image (HSI) pre-processing, followed by artificial neural network disease detection. Multilayer-Perceptron model is introduced to learn spectral features from different infection stages. The model is trained with ground truth collected by trained surveyors. The HSI sample size consists of 2 healthy trees, 5 Stage A (mild infection), 5 Stage B (moderate infection), and 3 Stage C (severe infection). Performance is examined with support vector machine (SVM), 1 dimensional convolutional network (1D CNN), and several vegetation indices, namely Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge (NDRE), Optimised Soil-Adjusted Vegetation Index (OSAVI), and Merris Terrestrial Chlorophyll Index (MTCI). All machine learning algorithms can segregate infection stages, MLP modal had a highest overall accuracy 86.67%, compared to SVM and 1D CNN at 66.67% and 73.33%. Whereas for vegetation index, it can only detect Stage C tree, and not able to differentiate between Healthy, Stage A and Stage B tree. In term of computational cost, MLP modal had balance performance with moderate training time, but faster inference time. It demonstrates effectiveness on BSR disease detection, even at early infection stage

Noise reduction methods for terrain phase estimation of InSAR images

Despite decades of scientists' effort, absolute phase determination of interferometry synthetic aperture radar (InSAR) image still remains unsolved. InSAR measurement derived from phase data is not only ambiguous by its modulo-2pi mathematical-ill pose, but also further corrupted by noise. Therefore, we suggest an adaptive least mean square (LMS) algorithm based on steepest descent method for noise reduction purpose. Besides, a scheme which incorporates such filter into a Itoh two-dimensional phase-unwrapping is proposed. The phase estimation procedures are implemented to reconstruct a simulated interferogram of terrain structure. For the quantitative assessment, we employ different types of quality metrics to measure the estimated outcome of InSAR terrain image which includes root mean square error (RMSE) and signal-to-noise ratio (SNR). The estimated outcomes are also reconstructed into three dimensional plotting for visual assessment. By refering to the similar scheme, other noise reduction filters include wieners filter and median filter are implemented for performance comparison. The simulated results show that the proposed method is able to filter noise without corrupted the useful phase information and achieves lowest error energy among other filters. Thus, it is a valuable technique for InSAR terrain phase estimation

Modelling and simulation for InSAR

This paper demonstrates models and simulation methods of interferometry synthetic aperture radar (InSAR). The InSAR models are presented in detail, which includes modelling of radar signal geometry, wrapped phase estimation, and phase map estimation. Furthermore, an error model based on interferometric scale is derived by refering to aforementioned models. To consider the real condition of the return signal echo, Gaussian white noise model is applied into simulation model as noisy phase image generation. Moreover, simulation also take scence into challenging terrain conditions like fringes and spiral. The noise or extreme terrain structure might induce interferometry observation, which may lead to undeterminable phase map. To overcome these issues, we implement the well-known difficult task, which are two-dimensional phase unwrapping, and de-noising algorithm. Simulation models discussed in the paper are not only the powerful tools for surface deformation estimation (or digital elevation map generation), but also useful for advance research on InSAR phase unwrapping