We develop a new quantile autoregression neural network (QARNN) model based on an artificial neural network architecture. The proposed QARNN model is flexible and can be used to explore potential nonlinear relationships among quantiles in time series data. By optimizing an approximate error function and standard gradient based optimization algorithms, QARNN outputs conditional quantile function...

The Current Issue of the Sudanese Journal of Paediatrics (SJP) reflects on the engraved old heritage of the Sudanese to help the needy by highlighting the story of the Hawadith Street Initiative (HSI) [1]. Named after the street on which it was founded, which translates indirectly to “Accidents Lane”, HSI was established in 2012 to meet Sudan’s child health insurance gap by crowdfunding medical...

Hyperspectral image (HSI) denoising is a prerequisite for many subsequent applications. For an HSI, the level and type of noise often vary with different bands and spatial positions, which make it difficult to effectively remove noise while preserving textures and edges. To alleviate this problem, we propose a new total-variation model. The main contribution of the proposed approach lies in tha...

Studies examining acute oxygenation and perfusion changes in irradiated skin are limited. Hyperspectral imaging (HSI), a method of wide-field, diffuse reflectance spectroscopy, provides noninvasive, quantified measurements of cutaneous oxygenation and perfusion. This study examines whether HSI can assess acute changes in oxygenation and perfusion following irradiation. Skin on both flanks of nu...

The search for invariants is a fundamental aim of scientific endeavors. These invariants, such as Newton’s laws of motion, allow us to model and predict the behavior of systems across many different problems. In the nascent field of Human-Swarm Interaction (HSI), a systematic identification of fundamental invariants is still lacking. Discovering and formalizing these invariants will provide a f...

Compression of Hyper Spectral Image (HSI) is an important issue in remote sensing applications due to its huge data size. An efficient technique for HSI compression is proposed based on Discrete Wavelet Transform (DWT) and Tucker Decomposition (TD) with Adaptive Least Squares (ALS) method. This technique exploits both the spatial and spectral information in the images. ALS method is used to com...

Dietary salt intake modulates the renin-angiotensin system (RAS); however, little is known about the effect of salt intake on the progression of glomerulonephritis. We investigated the glomerular expression of TGF-beta1 type I (TbetaRI) and II (TbetaRII) TGF-beta receptors and RAS components in rats with antithymocyte serum (ATS) nephritis on normal (NSI)-, low (LSI)-, and high-salt intake (HSI...

The development of improved preservation techniques and the reliable assessment of donor grafts are main fields of research in transplantation medicine. Normothermic machine perfusion (NMP) is a promising alternative to static cold storage of organs, maintaining physiological conditions during preservation. In combination with NMP, we introduce hyperspectral imaging (HSI) as a novel approach fo...

A novel Symmetric Sparse Representation (SSR) method has been presented to solve the band selection problem in hyperspectral imagery (HSI) classification. The method assumes that the selected bands and the original HSI bands are sparsely represented by each other, i.e., symmetrically represented. The method formulates band selection into a famous problem of archetypal analysis and selects the r...

Sparse representation classification (SRC) is being widely investigated on hyperspectral images (HSI). For SRC methods to achieve high classification performance, not only is the development of sparse representation models essential, the designing and learning of quality dictionaries also plays an important role. That is, a redundant dictionary with well-designated atoms is required in order to...