Simple approaches towards the design of an attached-growth sponge bioreactor (AGSB) for wastewater treatment and reuse.

Wastewater treatment and reuse is being emphasized due to the shortage of water sources and the continuous deterioration of the aquatic environment. In this study, a novel sponge bioreactor was studied as a low cost, high efficiency alternative for an attached growth biological system. This was designed by combining of number of sponge trays. This emerging technology has many beneficial properties in wastewater treatment and reuse. The approaches towards the conditions for system design were: (i) selection of sponge types; (ii) selection of sponge shapes; and (iii) selection of designated slope of sponge tray. They were determined through a series of experiments using a laboratory-scale unit with synthetic wastewater. It was then tested with a pilot-scale unit at the predetermined optimum conditions. The results indicate that the highest biomass growth was found at the sponge type with a cell count of 70-90 cells/in(2) (6.45 cm(2)) The relationship between biomass growth and biological oxygen consumption was well established. The prism-shaped sponge (triangular polyurethane sponge of 70-90 cells/in(2) with designated slope of sponge tray at 10 degrees) led to the best performance in terms of both organic and nutrient removal efficiency.     

A cross-layer analysis of TCP/link adaptation technologies over free-space optical links with Markov error model

This paper presents a comprehensive cross-layer framework on the performance of transmission control protocol (TCP) over a free-space optical (FSO) link, which employs automatic repeat request (ARQ) and adaptive modulation and coding (AMC) schemes. Not similar to conventional works in the literature of FSO, we conduct a Markov error model to accurately capture effects of burst errors caused by atmospheric turbulence on cross-layer operations. From the framework, we quantify the impacts of different parameters/settings of ARQ, AMC, and the FSO link on TCP throughput performance. We also discuss several optimization aspects for TCP performance.     

Molecular dynamics study on the effect of solution-wall interaction potential on the properties of solution in uniformly charged hydrophobic channel

We numerically investigate the effect of the solution-wall (i.e., water-wall and ion-wall) interaction potential on the properties of confined aqueous solution by using molecular dynamics (MD) simulations. The effect is determined by comparing results obtained from the MD simulation using the Lennard-Jones (L-J) potential for the water-wall and ion-wall interactions and those using a purely repulsive potential, i.e., the Weeks-Chandler-Andersen-like potential. In the MD simulations, 680 water molecules and 20 chloride ions are included between uniformly charged plates that are separated by 2.6 nm. The results show that the properties of solution are influenced only in the region close to the wall: The water molecules are more densely packed for the case of the L-J potential. Comparison of the results of the MD simulations in the case of the L-J potential with those provided by solving the Poisson-Boltzmann equation, we found that classical continuum theory fails to predict the ion density and electrostatic potential distributions in the region near to the wall, but far way from the wall, the prediction from the continuum theory is in line with the MD simulation.     

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.     

Downlink queuing model and packet scheduling for providing lossless handoff and QoS in AG mobile networks

Next generation mobile networks are expected to provide seamless personal mobile communication and quality-of-service (QoS) guaranteed IP-based multimedia services. Providing seamless communication in mobile networks means that the networks have to be able to provide not only fast but also lossless handoff. This paper presents a two-layer downlink queuing model and a scheduling mechanism for providing lossless handoff and QoS in mobile networks, which exploit IP as a transport technology for transferring datagrams between base stations and the high-speed downlink packet access (HSDPA) at the radio layer. In order to reduce handoff packet dropping rate at the radio layer and packet forwarding rate at the IP layer and provide high system performance, e.g., downlink throughput, scheduling algorithms are performed at both IP and radio layers, which exploit handoff priority scheduling principles and take into account buffer occupancy and channel conditions. Performance results obtained by computer simulation show that, by exploiting the downlink queuing model and scheduling algorithms, the system is able to provide low handoff packet dropping rate, low packet forwarding rate, and high downlink throughput.     

Analysis of organoselenium compounds in human urine using active carbon and chemically modified silica sol-gel surface-assisted laser desorption/ionization high-resolution time-of-flight mass spectrometry

Laser desorption/ionization time-of-flight mass spectra of three thermally labile low molecular weight organoselenium compounds (selenomethionine, selenoethionine, trimethylselenonium iodide) in human urine matrix have been obtained by using surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS). Four active layers, active carbon, silica sol-gel, and silica sol-gel impregnated with crown ether and with active carbon, were deposited on three different support substrates: (i) microscope slide coverslips; (ii) Al foil; and (iii) Cu tapes. Primarily protonated molecular ions and alkali metal adducts were observed in the mass spectra. A mixed-silica sol-gel and active carbon substrate active layer gave the best signal response for all compounds. Sol-gel substrates offered very clean backgrounds compared to the pure active carbon layers; however, the mass spectral signal intensities acquired were substantially lower for the sol-gel surfaces than those of the pure active carbon under the same conditions. Cu tape and Al foil support materials gave strong mass spectra of molecular ions and alkali metal molecular ion adducts, with lower Na and K adducts found with the Cu tape than with Al foil. Glass coverslips gave no response under all experimental conditions examined. Aerosol deposition was used to prepare SALDI substrates to avoid the localized "sweet spot" phenomenon encountered in conventional SALDI substrate preparation. Various nebulizers were examined and found to be effective in producing SALDI films with controlled and reproducible thicknesses. We were able to obtain exact mass identification of all three selenium species by high-resolution TOF-MS. To the best of our knowledge, this is the first time low molecular weight organoselenium compounds have been identified by SALDI-high-resolution TOF-MS.     

Symmetric Orthogonal Complex-Valued Filter Bank Design by Semidefinite Programming

A new design method for complex-valued two-channel finite impulse response (FIR) filter banks with both orthogonality and symmetry properties is developed. Based on a novel linear matrix inequality (LMI) characterization of trigonometric curves, the optimal design of perfect-reconstruction filter banks is cast into a semidefinite programming (SDP) problem. The dimension of the resulting SDP problem is further reduced by exploiting convex duality. Consequently, the globally optimal solution can be found for any practical filter length and desired regularity order.     

Dyna-Q-based vector direction for path planning problem of autonomous mobile robots in unknown environments

Reinforcement learning (RL) is a popular method for solving the path planning problem of autonomous mobile robots in unknown environments. However, the primary difficulty faced by learning robots using the RL method is that they learn too slowly in obstacle-dense environments. To more efficiently solve the path planning problem of autonomous mobile robots in such environments, this paper presents a novel approach in which the robot’s learning process is divided into two phases. The first one is to accelerate the learning process for obtaining an optimal policy by developing the well-known Dyna-Q algorithm that trains the robot in learning actions for avoiding obstacles when following the vector direction. In this phase, the robot’s position is represented as a uniform grid. At each time step, the robot performs an action to move to one of its eight adjacent cells, so the path obtained from the optimal policy may be longer than the true shortest path. The second one is to train the robot in learning a collision-free smooth path for decreasing the number of the heading changes of the robot. The simulation results show that the proposed approach is efficient for the path planning problem of autonomous mobile robots in unknown environments with dense obstacles.     

CAR-Miner: An efficient algorithm for mining class-association rules

Building a high accuracy classifier for classification is a problem in real applications. One high accuracy classifier used for this purpose is based on association rules. In the past, some researches showed that classification based on association rules (or class-association rules – CARs) has higher accuracy than that of other rule-based methods such as ILA and C4.5. However, mining CARs consumes more time because it mines a complete rule set. Therefore, improving the execution time for mining CARs is one of the main problems with this method that needs to be solved. In this paper, we propose a new method for mining class-association rule. Firstly, we design a tree structure for the storage frequent itemsets of datasets. Some theorems for pruning nodes and computing information in the tree are developed after that, and then, based on the theorems, we propose an efficient algorithm for mining CARs. Experimental results show that our approach is more efficient than those used previously.