Toward a sustainable land management of vernacular landscape in the highlands of south-western Saudi Arabia: indigenous and statutory experiences

The vernacular landscape of the highlands of south-western Saudi Arabia comprises three distinct elements: natural, agricultural and built. The highlands are currently facing land use planning problems which result in deforestation, despite significant attempts at afforestation by several governmental agencies (especially the Ministry of Agriculture and Water) and by municipal governments in the area. Intentions towards more sustainable forms of land management now characterize official documents. With regard to landscape issues, this is marked by a discourse of sustainable land management and the sponsorship of initiatives addressing the relationship between land management and the environment. This paper demonstrates that the approach to sustainable land management is technical, rational and scientific. A more balanced approach would combine scientific knowledge and practice with traditional expertise.     

A hybrid contextual compression technique using wavelet and contourlet transforms with PSO optimized prediction

Contextual compression is an essential part of any medical image compression since it facilitates no loss of diagnostic information. Although there are many techniques available for contextual image compression still there is a need for developing an efficient and optimized technique which would produce good quality images at lower bit rates. This article presents an efficient contextual compression algorithm using wavelet and contourlet transforms to capture the fine details of the image, along with directional information to produce good quality at high Compression Ratio (CR). The 2D discrete wavelet transform, which uses the simplest Daubechies wavelets, db1, or haar wavelet, is chosen and used to get the subband coefficients. The approximate coefficients of the higher subbands undergo contourlet transform employing length N ladder filters for capturing the directional information of the subbands at different scale and orientations. An optimized approach is used for predicting the quantized and the normalized subband coefficients resulting in improved compression performance. The proposed contextual compression approach was evaluated for its performance in terms of CR, Peak Signal to Noise Ratio, Feature SIMilarity index, Structure SIMilarity Index, and Universal quality (Q) after reconstruction. The results clarify the efficiency of the proposed method over other compression techniques.     

Control of large model mismatch systems using multiple models

H _∞ control is an effective approach to handle model uncertainties. However, when modeling mismatch is large, it tends to be challenging to meet the desired requirements of both stability and performance by only using a single H _∞ controller. This study presents a switching method to enhance the robust stability and performance of H _∞ control by dividing the range of dynamics into multiple uncertain models. The candidate robust controllers are designed by solving a set of linear matrix inequalities for each uncertain model. A structural scheduling logic that selects the most proper controller into closed-loop is proposed. The selected controller can ensure bounded exponentially weighted H _∞ norm of the closed-loop switching systems. This work analyses their robust stability and disturbance attenuation performance via a linear fractional transformation by using the small gain theorem. The effectiveness of this method is validated with a fist-order inertial system with pure time delay.     

Real-time energy optimization of HEVs under-connected environment: a benchmark problem and receding horizon-based solution

In this paper, we propose a benchmark problem for the challengers aiming to energy efficiency control of hybrid electric vehicles (HEVs) on a road with slope. Moreover, it is assumed that the targeted HEVs are in the connected environment with the obtainment of real-time information of vehicle-to-everything (V2X), including geographic information, vehicle-toinfrastructure (V2I) information and vehicle-to-vehicle (V2V) information. The provided simulator consists of an industriallevel HEV model and a traffic scenario database obtained through a commercial traffic simulator, where the running route is generated based on real-world data with slope and intersection position. The benchmark problem to be solved is the HEVs powertrain control using traffic information to fulfill fuel economy improvement while satisfying the constraints of driving safety and travel time. To show the HEV powertrain characteristics, a case study is given with the speed planning and energy management strategy.     

Morphology based particle segregation by electrostatic charge

A novel charge-based technique for classifying fractal-like aerosol agglomerates based on their morphology is demonstrated. The study discusses the application of this technique to flame soot aerosols where singly and doubly net-charged agglomerates of similar sizes were segregated using electrostatic classifiers and shown to have different morphologies. The flexibility and simplicity of this technique does not limit its application to aerosols, making it an attractive candidate for performing particle shape selection of different types of nano and micromaterials.