Loess as a Collapsible Soil: Some Basic Particle Packing

Loess is the most important collapsible soil; possibly the only engineering soil in which real collapse occurs. A real collapse involves a diminution in volume - it would be an open metastable packing being reduced to a more closely packed, more stable structure. Metastability is at the heart of the collapsible soils problem. To envisage and to model the collapse process in a metastable medium, knowledge is required about the nature and shape of the particles, the types of packings they assume (real and ideal), and the nature of the collapse process - a packing transition upon a change to the effective stress in a media of double porosity. Particle packing science has made little progress in geoscience discipline - since the initial packing paradigms set by Graton and Fraser (1935) - nevertheless is relatively well-established in the soft matter physics discipline. The collapse process can be represented by mathematical modelling of packing – including the Monte Carlo simulations - but relating representation to process remains difficult. This paper revisits the problem of sudden packing transition from a micro-physico-mechanical viewpoint (i.e. collapse imetan terms of structure-based effective stress). This cross-disciplinary approach helps in generalization on collapsible soils to be made that suggests loess is the only truly collapsible soil, because it is only loess which is so totally influenced by the packing essence of the formation process.

Power control in cognitive radios, Internet-of Things (IoT) for factories and industrial automation

Cognitive radio (CR) is fast emerging as a promising technology that can meet the machine-to machine (M2M) communication requirements for spectrum utilization and power control for large number of machines/devices expected to be connected to the Internet-of Things (IoT). Power control in CR as a secondary user can been modelled as a non-cooperative game cost function to quantify and reduce its effects of interference while occupying the same spectrum as primary user without adversely affecting the required quality of service (QoS) in the network. In this paper a power loss exponent that factors in diverse operating environments for IoT is employed in the non-cooperative game cost function to quantify the required power of transmission in the network. The approach would enable various CRs to transmit with lesser power thereby saving battery consumption or increasing the number of secondary users thereby optimizing the network resources efficiently.