On uniform observation of nonuniformly observable systems

In [4,7,9,12], classes of nonlinear systems are considered for which observers can be designed. Although observability of nonlinear systems is known to be dependent on the input, the proposed observers have the property that the estimation error decays to zero irrespective of the input. In the first part of this paper, it is shown that this phenomenon follows from a common property of these systems: for all of them, the “unobservable states” with respect to some input, are in some sense “stable” (in the linear case, these systems are called detectable), and for this reason, a reduced order observer can be designed. In the second part is given a more general class of nonlinear systems for which such an observer can be designed.     

Shortcoming, problems and analytical comparison for flooding-based search techniques in unstructured P2P networks

Peer-to-Peer networks attracted a significant amount of interest because of their capacity for resource sharing and content distribution. Content distribution applications allow personal computers to function in a coordinated manner as a distributed storage medium by contributing, searching, and obtaining digital content. Searching in unstructured P2P networks is an important problem, which has received considerable research attention. Acceptable searching techniques must provide large coverage rate, low traffic load, and optimum latency. This paper reviews flooding-based search techniques in unstructured P2P networks. It then analytically compares their coverage rate, and traffic overloads. Our simulation experiments have validated analytical results.     

Comparing the Effects of Different Daily and Sub-Daily Downscaling Approaches on the Response of Urban Stormwater Collection Systems

Water Resources Management - Change in the spatiotemporal pattern of precipitation is one the most important effects of climate change. This may result in considerable changes in urban flooding and...     

GA-SVR: a novel hybrid data-driven model to simulate vertical load capacity of driven piles

Piles are widely applied to substructures of various infrastructural buildings. Soil has a complex nature; thus, a variety of empirical models have been proposed for the prediction of the bearing capacity of piles. The aim of this study is to propose a novel artificial intelligent approach to predict vertical load capacity of driven piles in cohesionless soils using support vector regression (SVR) optimized by genetic algorithm (GA). To the best of our knowledge, no research has been developed the GA-SVR model to predict vertical load capacity of driven piles in different timescales as of yet, and the novelty of this study is to develop a new hybrid intelligent approach in this field. To investigate the efficacy of GA-SVR model, two other models, i.e., SVR and linear regression models, are also used for a comparative study. According to the obtained results, GA-SVR model clearly outperformed the SVR and linear regression models by achieving less root mean square error (RMSE) and higher coefficient of determination (R²). In other words, GA-SVR with RMSE of 0.017 and R² of 0.980 has higher performance than SVR with RMSE of 0.035 and R² of 0.912, and linear regression model with RMSE of 0.079 and R² of 0.625.

     

Optimisation of solar photovoltaic (PV) parameters using meta-heuristics

Microsystem Technologies - This paper presents a critical analysis of the meta-heuristic techniques used in various researches on the optimisation of photovoltaic (PV) parameters, which involves...     

Lung nodules detection using semantic segmentation and classification with optimal features

Neural Computing and Applications - Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of...     

The Valve Metal Character of Zirconium as inferred from anode potential measurements in mineral acid solutions

A study on the value metal character of Zr in 0.1 M solutions of H₂SO₄, HNO₃, and H₃PO₄ has been performed using the anode potential as the primary variable in galvanostatic, potentiostatic, and capacity measurements. A method of surface pre-treatment, which suppresses both O₂ evolution and metal dissolution, has been described. Kinetic parameters of oxide growth have been calculated. The results indicate that:

• (i) the high field approximation is applicable following an exponential law, and
• (ii) the height and activation distance of the energy barrier for ion transport through the oxide phase (Verwey model) are the same three acids.

Measurements have been also made on the dielectric breakdown of oxide, and this occurs at potentials above 200 V. Direct capacity measurements give similar results as those based on reciprocal capacity calculated from galvanostatic experiments. It is concluded that the dominant anodic oxide species is ZrO₂ having a dielectric constant of 25. Open circuit potential measurements show that Zr is spontaneously oxidized in the three acids.     

Effect of the Te/Si ratio on the electrical characteristics of the amorphous chalcogenide switches

The effect of composition on amorphous chalcogenide threshold switches of the system Si _x Te_60-x As₃₀Ge₁₀, wherex = 5, 10, 12 and 20, has been studied. The compositionx = 5 shows the best switching characteristics, e.g. the smallest holding voltage (V _h = 0.4V), the highest ON state current (I _h = 45A) and smallest threshold voltage (V _s = 1.5V). Applying the three mechanisms of conductance of Mottet al. (Phil. Mag. 37 (1975) 961), it is found that for a particular composition ₂ < ₁ < ₀ (the pre-exponential factors) andW ₂ < (E _a –E ₁ +W ₁) < (E _c –E _f) (whereE _a,E _c andE _e = activation energies at band edge, fermi level and conduction band;W ₁ andW ₂ = activation energy for hopping). It was found that the density of states at the fermi levelN(E _f) increases with the decrease of silicon content. The results provided further evidence against thermal interpretations and thereby support electronic models of threshold switching for these glass systems.     

Current Understandings on Magnesium Deficiency and Future Outlooks for Sustainable Agriculture

The productivity of agricultural produce is fairly dependent on the availability of nutrients and efficient use. Magnesium (Mg²⁺) is an essential macronutrient of living cells and is the second most prevalent free divalent cation in plants. Mg²⁺ plays a role in several physiological processes that support plant growth and development. However, it has been largely forgotten in fertilization management strategies to increase crop production, which leads to severe reductions in plant growth and yield. In this review, we discuss how the Mg²⁺ shortage induces several responses in plants at different levels: morphological, physiological, biochemical and molecular. Additionally, the Mg²⁺ uptake and transport mechanisms in different cellular organelles and the role of Mg²⁺ transporters in regulating Mg²⁺ homeostasis are also discussed. Overall, in this review, we critically summarize the available information about the responses of Mg deficiency on plant growth and development, which would facilitate plant scientists to create Mg²⁺-deficiency-resilient crops through agronomic and genetic biofortification.