Unsupervised learning in hexagonal boron nitride memristor-based spiking neural networks.

Resistive random access memory (RRAM) is an emerging non-volatile memory technology that can be used in neuromorphic computing hardware to exceed the limitations of traditional von Neumann architectures by merging processing and memory units. Two-dimensional (2D) materials with non-volatile switching behavior can be used as the switching layer of RRAMs, exhibiting superior behavior compared to conventional oxide-based devices. In this study, we investigate the electrical performance of 2D hexagonal boron nitride (h-BN) memristors towards their implementation in spiking neural networks (SNN).

Utilization characteristics and importance of woody biomass resources on the rural-urban fringe in botswana.

This article examines the utilization characteristics and importance of woody biomass resources in the rural-urban fringe zones of Botswana. In the literature for Africa, attention has been given to the availability and utilization of biomass in either urban or rural environments, but the rural-urban fringe has been neglected. Within southern Africa, this neglect is not justified; the rural-urban fringe, not getting the full benefits available in urban environments in Botswana, has developed problems in woody biomass availability and utilization that require close attention.

ENVIRONMENTAL AUDITING: Use of Landsat Thematic Mapper Data to Assess Seasonal Rangeland Changes in the Southeast Kalahari, Botswana.

/ Management problems arise in semiarid rangeland that are characterized by marked wet and dry seasons because of forage deficiencies in the dry season. These natural vegetation rangelands can sustain livestock all year long when forage and senesced grass are available into the dry season. Seasonal range condition data are required to provide a basis for pasture management to help locate dry season cover and thereby minimize overstocking and degradation.