Effect of ultrasound on removal of persistent organic pollutants (POPs) from different types of soils

A new and promising technology is utilization of sonochemistry on decontamination of polluted soil. The feasibility of this technology on treatment of contaminated soils (synthetic clay, natural farm clay, and kaolin) was studied by using two target persistent organic pollutants (POPs): hexachlorobenzene (HCB) and phenanthrene (PHE). The soils were highly contaminated in 500 mg/kg. The laboratory experiments were conducted with various conditions (moisture, power, and time duration). The effects of these parameters on ultrasonication (as well as the removal of contaminants) were examined. The reasonable moisture ratio of the slurry could be in range of 2:1–3:1. The process did not change pH values of soils. Experimental results showed that ultrasonication has a potential to reduce the high concentrations of these POPs.     

Fault detection and identification for a class of continuous piecewise affine systems with unknown subsystems and partitions

This paper establishes a novel online fault detection and identification strategy for a class of continuous piecewise affine (PWA) systems, namely, bimodal and trimodal PWA systems. The main contributions with respect to the state‐of‐the‐art are the recursive nature of the proposed scheme and the consideration of parametric uncertainties in both partitions and in subsystems parameters. In order to handle this situation, we recast the continuous PWA into its max‐form representation and we exploit the recursive Newton‐Gauss algorithm on a suitable cost function to derive the adaptive laws to estimate online the unknown subsystem parameters, the partitions, and the loss in control authority for the PWA model. The effectiveness of the proposed methodology is verified via simulations applied to the benchmark example of a wheeled mobile robot.     

The efficient lignocellulose-based sorbent for oil spill treatment from polyurethane and agricultural residue of Vietnam

In this study, new and efficient sorbent with density 0.2 g/cm³ was fabricated by incorporating rice straw into polyurethane matrix to get an open cell structure material with high oil uptake capacity. The influences of various important factors such as amount of adding rice straw, size of rice straw particles, and adsorption time on oil adsorption capacity of new sorbent material were investigated. The results showed that the oil absorption rate occurred fast in first 15–30 min, then slowed down and reached saturation level after about 2 h of treatment. Oil adsorption capacity of the new sorbent material was relatively high, up to 12.0 g/g. In comparison with pristine polyurethane or lignocellulosic materials, the new sorbents had higher oil adsorption capacity. Some characteristics of the as-obtained sorbent, such as surface shapes and porosity, were also studied by SEM analysis.     

Investigation of load transfer mechanisms in granular platforms reinforced by geosynthetics above cavities

Geosynthetic-reinforced soils constitute an interesting solution for bridging cavities. Many methods have been developed to analyze the stability of soil-geosynthetic-cavity systems, but none of them is able to take into account all the complexities of these mechanisms. Many researchers have assumed mechanisms developed in the reinforced granular platform when cavities appear, such as load transfer and expansion of materials. However, they are not fully understood because many factors can influence the design, such as the cavity opening processes, the type, and the density of the soil.In this study, a new laboratory apparatus is developed to simulate two different cavity opening procedures (trapdoor and progressive opening) for different geometric configurations. A series of tests is conducted for three granular soils with two different geosynthetic sheets. By measuring the shape of the surface soil settlement and the geosynthetic deflection, the expansion coefficient is calculated. A novel tactile pressure sensor is used to observe the load transfer during the cavity opening. The experimental data are analyzed and the influence of the experimental conditions (geometric and soil properties and the opening procedure) are also discussed. Correspondingly, elicited findings can be used to propose recommendations to improve the existing design methods.     

Secure Multi-hop Data Transmission in Cognitive Radio Networks Under Attack in the Physical Layer

Wireless Personal Communications - Cognitive radio networks (CRNs) have a shortcoming in that attackers can increase their ability to disturb secondary users (SUs). This paper focuses on jamming...     

Estimation and forecasting of machine health condition using ARMA/GARCH model

This paper proposes the hybrid model of autoregressive moving average (ARMA) and generalized autoregressive conditional heteroscedasticity (GARCH) to estimate and forecast the machine state based on vibration signal. The main idea in this study is to employ the linear ARMA model and the nonlinear GARCH model to explain the wear and fault condition of machine, respectively. The successful outcomes of the ARMA/GARCH prediction model can give obvious explanation for future states of machine, which enhance the worth of machine condition monitoring as well as condition-based maintenance in practical applications. The advance of the proposed model is verified in empirical results as applying for a real system of a methane compressor in a petrochemical plant.     

Greenhouse gas emission mitigation potential of rice husks for An Giang province, Vietnam

To evaluate the greenhouse gas (GHG) emission mitigation potential of rice husk utilization, a life cycle inventory analysis was conducted for 18 scenarios. The allocation of fuels, other than rice husks, was decided based on the current demand for and supply of rice husks. To prevent the bulky nature of rice husks, briquette production is also discussed. In the power generation scenarios, the differences between two capacities (5 MW and 30 MW) were analyzed. The results of analysis reveal that CH₄ and N₂O emissions from open burning contribute largely to the current GHG emissions. Therefore, ceasing open burning alone has a large GHG mitigation potential. The use of briquettes, even though GHG is emitted during the production stage, can still contribute to GHG emission mitigation as the production is more efficient than rice husk burning or dumping. In the power generation scenarios, most GHG emissions were derived from the combustion process. Therefore, gasification which has a little combustion process is the most efficient GHG mitigator. Both the replacement of grid electricity by generated electricity, and the replacement of diesel oil by pyrolyzed oil show larger GHG mitigation potentials than what could be derived from open burning cessation alone.     

Detecting Regular Visit Patterns

We are given a trajectory T\mathcal{T} and an area A\mathcal{A} . T\mathcal{T} might intersect A\mathcal{A} several times, and our aim is to detect whether T\mathcal{T} visits A\mathcal{A} with some regularity, e.g. what is the longest time span that a GPS-GSM equipped elephant visited a specific lake on a daily (weekly or yearly) basis, where the elephant has to visit the lake most of the days (weeks or years), but not necessarily on every day (week or year).     

Modular argumentation for modelling legal doctrines in common law of contract

To create a programming environment for contract dispute resolution, we propose an extension of assumption-based argumentation into modular assumption-based argumentation in which different modules of argumentation representing different knowledge bases for reasoning about beliefs and facts and for representation and reasoning with the legal doctrines could be built and assembled together. A distinct novel feature of modular argumentation in compare with other modular logic-based systems like Prolog is that it allows references to different semantics in the same module at the same time, a feature critically important for application of argumentation in legal domains like contract dispute resolution where the outcomes of court cases often depend on whether credulous or skeptical modes of reasoning were applied by the contract parties. We apply the new framework to model the doctrines of contract breach and mutual mistake.     

External Rewriting for Skeptical Proof Assistants

This paper presents the design, the implementation, and experiments of the integration of syntactic, conditional possibly associative-commutative term rewriting into proof assistants based on constructive type theory. Our approach is called external because it consists in performing term rewriting in a specific and efficient environment and checking the computations later in a proof assistant. Two typical systems are considered in this work: ELAN, based on the rewriting calculus, as the term rewriting-based environment, and Coq, based on the calculus of inductive constructions as the proof assistant. We first formalize the proof terms for deduction by rewriting and strategies in ELAN using the rewriting calculus with explicit substitutions. We then show how these proof terms can soundly be translated into Coq syntax where they can be directly type checked. For the method to be applicable for rewriting modulo associativity and commutativity, we provide an effective method to prove equalities modulo these axioms in Coq using ELAN. These results have been integrated into an ELAN-based rewriting tactic in Coq.