Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems. © 2013 IEEE.

Optimization of an effective extraction procedure for the analysis of microcystins in soils and lake sediments

Microcystin analysis in sediments and soils is considered very difficult due to low recovery for extraction. This is the primary limiting factor for understanding the fate of toxins in the interface between water and sediment in both the aquatic ecosystem as well as in soils. In the present study, a wide range of extraction solvents were evaluated over a wide range of pH, extraction approaches and equilibration time to optimize an effective extraction procedure for the analysis of microcystins in soils and lake sediments. The number of extractions required and acids in extraction solutions were also studied. In this procedure, EDTA-sodium pyrophosphate solution was selected as an extraction solvent based on the adsorption mechanism study. The optimized procedure proved to be highly efficient and achieved over 90% recovery. Finally, the developed procedure was applied to field soil and sediment sample collected from Chinese lakes during bloom seasons and microcystins were determined in six of ten samples. (c) 2005 Elsevier Ltd. All rights reserved.

Optimization by orthogonal array design and humoral immunity of the bivalent vaccine against Aeromonas hydrophila and Vibrio fluvialis infection in crucian carp (Carassius auratus L.)

Aeromonas hydrophila and Vibrio fluvialis are the causative agents of a serious haemorrhagic septicaemia that affects a wide range of freshwater fish in China. In order to develop a bivalent anti-A. hydrophila and anti-V. fluvialis formalin-killed vaccine to prevent this disease, an orthogonal array design (OAD) method was used to optimize the production conditions, using three factors, each having three levels. The effects of these factors and levels on the relative per cent survival for crucian carp were quantitatively evaluated by analysis of variance. The final optimized formulation was established. The data showed that inactivation temperature had a significant effect on the potency of vaccine, but formalin concentration did not. The bivalent vaccine could elicit a strong humoral response in crucian carp (Carassius auratus L.) against both A. hydrophila and V. fluvialis simultaneously, which peaked at 3 or 5 weeks respectively. Antibody titres remained high until week 12, the end of the experiment, after a single intraperitoneal injection. The verification experiment confirmed that an optimized preparation could provide protection for fish at least against A. hydrophila infection, and did perform better than the non-optimized vaccine judged by the antibody levels and protection rate, suggesting that OAD is of value in the development of improved vaccine formulations.

Optimization of RP-HPLC analysis of low molecular weight organic acids in soil

RP-HPLC analysis for low molecular weight organic acids in soil solution has been optimized. An Atlantis (TM) C-18 column was used for the analyses. An optimal determination for eleven organic acids in soil solution was found at room temperature (25 degrees C) and 220 nm detection wavelength, with a mobile phase of 10 mM KH2PO4 -CH3OH (955, pH 2.7), a flow rate of 0.8 mL/min and 10 mu L sample size. The detection limits ranged 3.2-619 ng/mL, the coefficients of variation ranged 1.3-4.6%, and the recoveries ranged 95.6-106.3% for soil solution with standard addition on the optimal conditions proposed.

The optimization of high performance liquid chromatographic method for analysis of trace microcystins in natural water bodies

The ratio of methanol., water and trifluoroacetic acid ( TFA) was regulated to change the polarity and the pH of the rinse solution and the eluent, so as to improve the high performance liquid chromatography HPLC) detection method for trace microcystines (MCs) in natural water bodies. The results showed that 40 % similar to 45 % methanol-water solution containing 0. 1 % TFA could get good effects on the rinse of impurity, and 70% methanol-water solution containing 0. 1% TFA could elute all the MCs in solid phase extraction ( SPE) cartridge ( C-18), In this way. it is suggested that, in analysis of environmental samples with high concentration of impurity, impurity should be washed with 40% similar to 45% methanol-water solution containing 0. 1% TFA, and MCs should be eluted with 70% similar to 100% methanol-water solution containing 0. 1% TFA.

Use of microbial community to evaluate performance of a wetland system in treating Pb/Zn mine drainage

The performance of a wetland system in treating lead (Pb)/zinc (Zn) mine drainage was evaluated by using the polyurethane foam unit (PFU) microbial community (method), which has been adopted by China as a standardized procedure for monitoring water quality. The wetland system consisted of four cells with three dominant plants: Typha latifolia, Phragmites australis and Paspalum distichum. Physicochemical characteristics [pH, EC, content of total suspended solid (TSS) and metals (Pb, Zn, Cd, and Cu)] and PFU microbial community in water samples had been investigated from seven sampling sites. The results indicated that the concentrations of Pb, Zn, Cd, Cu, and TSS in the mine drainage were gradually reduced from the inlet to the outlet of the wetland system and 99%, 98%, 75%, 83%, and 68% of these metals and TSS respectively, had been reduced in concentration after the drainage passed through the wetland system. A total of 105 protozoan species were identified, the number of protozoa species and the diversity index (DI) gradually increased, while the heterotrophic index (HI) gradually decreased from the inlet to the outlet of the wetland system. The results indicated that DI, HI, and total number species of protozoa could be used as biological indicators indicating the improvement of water quality.

Motor control optimization of compliant one-legged locomotion in rough terrain

While underactuated robotic systems are capable of energy efficient and rapid dynamic behavior, we still do not fully understand how body dynamics can be actively used for adaptive behavior in complex unstructured environment. In particular, we can expect that the robotic systems could achieve high maneuverability by flexibly storing and releasing energy through the motor control of the physical interaction between the body and the environment. This paper presents a minimalistic optimization strategy of motor control policy for underactuated legged robotic systems. Based on a reinforcement learning algorithm, we propose an optimization scheme, with which the robot can exploit passive elasticity for hopping forward while maintaining the stability of locomotion process in the environment with a series of large changes of ground surface. We show a case study of a simple one-legged robot which consists of a servomotor and a passive elastic joint. The dynamics and learning performance of the robot model are tested in simulation, and then transferred the results to the real-world robot. ©2007 IEEE.

Predictive entropy search for efficient global optimization of black-box functions

We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that maximizes the expected information gained with respect to the global maximum. PES codifies this intractable acquisition function in terms of the expected reduction in the differential entropy of the predictive distribution. This reformulation allows PES to obtain approximations that are both more accurate and efficient than other alternatives such as Entropy Search (ES). Furthermore, PES can easily perform a fully Bayesian treatment of the model hyperparameters while ES cannot. We evaluate PES in both synthetic and real-world applications, including optimization problems in machine learning, finance, biotechnology, and robotics. We show that the increased accuracy of PES leads to significant gains in optimization performance.

Manopt, a matlab toolbox for optimization on manifolds

Optimization on manifolds is a rapidly developing branch of nonlinear optimization. Its focus is on problems where the smooth geometry of the search space can be leveraged to design effcient numerical algorithms. In particular, optimization on manifolds is well-suited to deal with rank and orthogonality constraints. Such structured constraints appear pervasively in machine learning applications, including low-rank matrix completion, sensor network localization, camera network registration, independent component analysis, metric learning, dimensionality reduction and so on. The Manopt toolbox, available at www.manopt.org, is a user-friendly, documented piece of software dedicated to simplify experimenting with state of the art Riemannian optimization algorithms. By dealing internally with most of the differential geometry, the package aims particularly at lowering the entrance barrier. © 2014 Nicolas Boumal.

Fixed-rank matrix factorizations and Riemannian low-rank optimization

Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and then exploit the Riemannian quotient geometry of the search space in the design of a class of gradient descent and trust-region algorithms. The proposed algorithms generalize our previous results on fixed-rank symmetric positive semidefinite matrices, apply to a broad range of applications, scale to high-dimensional problems, and confer a geometric basis to recent contributions on the learning of fixed-rank non-symmetric matrices. We make connections with existing algorithms in the context of low-rank matrix completion and discuss the usefulness of the proposed framework. Numerical experiments suggest that the proposed algorithms compete with state-of-the-art algorithms and that manifold optimization offers an effective and versatile framework for the design of machine learning algorithms that learn a fixed-rank matrix. © 2013 Springer-Verlag Berlin Heidelberg.

Optimization of growth and fatty acid composition of a unicellular marine picoplankton, Nannochloropsis sp., with enriched carbon sources

A unicellular marine picoplankton, Nannochloropsis sp., was grown under CO2-enriched photoautotrophic or/and acetate-added mixotrophic conditions. Photoautotrophic conditions with enriched CO2 of 2800 mul CO2 l(-1) and aeration gave the highest biomass yield (634 mg dry wt l(-1)), the highest total lipid content (9% of dry wt), total fatty acids (64 mg g(-1) dry wt), polyunsaturated fatty acids (35% total fatty acids) and eicosapentaenoic acid (EPA, 20:5omega3) (16 mg g(-1) dry wt or 25% of total fatty acids). Mixotrophic cultures gave a greater protein content but less carbohydrates. Adding sodium acetate (2 mM) decreased the amounts of the total fatty acids and EPA. Elevation of CO2 in photoautotrophic culture thus enhances growth and raises the production of EPA in Nannochloropsis sp.

Optimization of control parameters for petroleum waste composting

Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical parameters were monitored to evaluate their influence on the microbial communities present in composting. The CO2 evolution and the number of microorganisms were measured as the activity of composting. The results demonstrated that the optimum temperature, pH and moisture content were 56.5 - 59.5 degreesC, 7.0 - 8.5 and 55 % - 60%, respectively. Under the optimum conditions, the removal efficiency of petroleum hydrocarbon reached 83.29% after 30 days composting.

Design and optimization of photonic crystal coupling layer for bi-color quantum well infrared photodetectors

Finite difference time domain (FDTD) method is used for the simulation and analysis of electromagnetic field in the top coupling layer of GaAs/AlGaAs quantum well infrared photodetector (QWIP). Simulation results demonstrated the coupling efficiencies and distributions of electromagnetic (EM) field in a variety of 2D photonic crystal coupling layer structures. A photonic crystal structure for bi-color-QWIP is demonstrated with high coupling efficiency for two wavelengths.

Optimization of metamorphic InGaAs quantum wells on GaAs grown by molecular beam epitaxy

We investigate the molecular beam epitaxy growth of metamorphic InxGa(1-x)As materials (x up to 0.5) on GaAs substrates systematically. Optimization of structure design and growth parameters is aimed at obtaining smooth surface and high optical quality. The optimized structures have an average surface roughness of 0.9-1.8 nm. It is also proven by PL measurements that the optical properties of high indium content (55%) InGaAs quantum wells are improved apparently by defect reduction technique and by introducing Sb as a surfactant. These provide us new ways for growing device quality metamorphic structures on GaAs substrates with long-wavelength emissions.

Fabrication and optical optimization of spot-size converters with strong cladding layers

A silicon-on-insulator (SOI) optical fiber-to-waveguide spot-size converter (SSC) overlaid with specially treated silica is investigated for integrated optical circuits. Unlike the conventional process of simply depositing the hot silica on silicon waveguides, two successive layers of silicon dioxide were grown on etched SSC structures by PECVD (plasma-enhanced chemical vapor deposition). The two layers have 0.8% index contrast and supply stronger cladding for an incident light beam. Additionally, this process is able to reduce the effective refractive index of the input mode to less than 1.47 (extremely close to that of the fiber), substantially weakening the unwanted back reflection. Exploiting this technology, it was demonstrated that the SSC showed a theoretical low mode mismatch loss of 1.23 dB for a TE-like mode and has an experimental coupling efficiency of 66%.