Preservation of local similarity structure is a key challenge in deep clustering. Many recent deep clustering methods therefore use autoencoders to help guide the model's neural network towards an embedding which is more reflective of the input space geometry. However, recent work has shown that autoencoder-based deep clustering models can suffer from objective function mismatch (OFM). In order to ...

We report new findings of total electron content (TEC) perturbations in the southern hemisphere at conjugate locations to the northern eclipse on August 21, 2017. We identified a persistent conjugate TEC depletion by 10%–15% during the eclipse time, elongating along magnetic latitudes with at least ∼5° latitudinal width. As the Moon's shadow swept southward, this conjugate depletion moved northward ...

A new technique for investigating dust charging in the PMSE (polar mesospheric summer echoes) source region is proposed and discussed in this paper. The first high-frequency (HF) modulation of the PMSE with varying pump power was employed during a recent experimental campaign at EISCAT (European Incoherent Scatter Scientific Association). Two experiment setups including HF pump power stepping as ...

The mesosphere and lower thermosphere (MLT) region is dominated globally by dynamics at various scales: planetary waves, tides, gravity waves, and stratified turbulence. The latter two can coexist and be significant at horizontal scales less than 500 km, scales that are difficult to measure. This study presents a recently deployed multistatic specular meteor radar system, SIMONe Peru, which can be ...

Diagrammatic reasoning (DR) problems are well known. However, solving DR problems represented in 4 × 1 Raven’s Progressive Matrix (RPM) form using computer vision and pattern recognition has not yet been tried. Emergence of deep learning techniques aided by advanced computing can be exploited to solve such DR problems. In this paper, we propose a new learning framework by combining LSTM and Convolutional ...

Electric fields are a ubiquitous feature of the ionosphere and are intimately linked with aurora through particle precipitation and field-aligned currents. They exhibit order-of-magnitude changes on temporal and spatial scales of seconds and kilometres respectively which are not easy to measure; knowing their true magnitude and temporal variability is important for a theoretical understanding of ...

Interaction of coherent structures known as blobs in the scrape-off layer of magnetically confined plasmas is investigated. Isolated and interacting seeded blobs, as well as full plasma turbulence, are studied by two-dimensional numerical simulations. The features of the blobs (position, size, amplitude) are determined with a blob tracking algorithm, which identifies them as coherent structures with ...

Spectral unmixing (SU) aims at decomposing the mixed pixel into basic components, called endmembers with corresponding abundance fractions. Linear mixing model (LMM) and nonlinear mixing models (NLMMs) are two main classes to solve the SU. This paper proposes a new nonlinear unmixing method base on general bilinear model, which is one of the NLMMs. Since retrieving the endmembers’ abundances represents ...

Automatic grading of retinal blood vessels from fundus image can be a useful tool for diagnosis, planning and treatment of eye. Automatic diagnosis of retinal images for early detection of glaucoma, stroke, and blindness is emerging in intelligent health care system. The method primarily depends on various abnormal signs, such as area of hard exudates, area of blood vessels, bifurcation points, ...

Typical person re-identification frameworks search for <i>k</i> best matches in a gallery of images that are often collected in varying conditions. The gallery usually contains image sequences for video re-identification applications. However, such a process is time consuming as video re-identification involves carrying out the matching process multiple times. In this paper, we propose a new method ...