Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design

Designing products to meet consumers' preferences is essential for a business's success. We propose the Gradient-based Survey (GBS), a discrete choice experiment for multiattribute product design. The experiment elicits consumer preferences through a sequence of paired comparisons for partial profiles. GBS adaptively constructs paired comparison questions based on the respondents' previous choices. Unlike the traditional random utility maximization paradigm, GBS is robust to model misspecification by not requiring a parametric utility model. Cross-pollinating the machine learning and experiment design, GBS is scalable to products with hundreds of attributes and can design personalized products for heterogeneous consumers. We demonstrate the advantage of GBS in accuracy and sample efficiency compared to the existing parametric and nonparametric methods in simulations

XRCC1 codon 399Gln polymorphism is associated with radiotherapy-induced acute dermatitis and mucositis in nasopharyngeal carcinoma patients

BACKGROUND: To evaluate the association between single nucleotide polymorphisms (SNPs) at the 194 and 399 codons of XRCC1, and the risk of severe acute skin and oral mucosa reactions in nasopharyngeal carcinoma patients in China. METHODS: 114 patients with nasopharyngeal carcinoma were sequentially recruited in this study. Heparinized peripheral blood samples were taken for SNPs analysis before the start of radiation treatment. SNPs in XRCC1 (194Arg/Trp and 399Arg/Gln) gene were analyzed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Dermatitis at upper neck and oral mucositis were clinically recorded according to the Common Terminology Criteria for Adverse Events v.3.0. RESULTS: The variant allele frequencies were 0.289 for XRCC1 194Trp and 0.263 for XRCC1 399Gln. Of the 114 patients, 24 experienced grade 3 acute dermatitis and 48 had grade 3 acute mucositis. The XRCC1 399Arg/Gln was significantly associated with the development of grade 3 dermatitis (Odds Ratio, 2.65; 95% CI, 1.04–6.73; p = 0.037, χ2 = 4.357). In addition, it was also associated with higher incidence of grade 3 mucositis with a borderline statistical significance (Odds Ratio, 2.11; 95% CI, 0.951–4.66; p = 0.065, χ2 = 3.411). The relationship between XRCC1 194Arg/Trp and acute dermatitis, and mucositis was not found. CONCLUSIONS: Our investigation shows, for the first time, that patients with the XRCC1 399Arg/Gln genotype were more likely to experience severe acute dermatitis and oral mucositis. With further validation, the information can be used to determine personalized radiotherapy strategy

Radiolysis of aqueous solution containing copper ions

Copper and copper alloys are widely used in the field of nuclear materials. The effects of aqueous solutions that have undergone copper ion radiolysis on the generation of H2O2, O2, and H2 must be considered for material corrosion control and hydrogen explosion risk assessment. In this study, a γ-radiolysis experiment of an aqueous solution containing copper ions was conducted to explore the effects of different absorbed doses, absorption dose rates, and Cu2+ concentrations on the generation of H2O2, O2, and H2. The results showed that with an increase in the absorbed dose (0-1.80 kGy), the concentrations of H2O2 and H2(g) firstly increased and then tended to stabilize under steady-state concentrations of 5.41×10-6 and 7.91×10-5 mol/L, respectively, whereas the concentration of O2(g) remained at 9.04×10-4 mol/L. The presence of Cu2+ enhanced the equilibrium concentrations of H2 and H2O2 by one and two orders of magnitude, respectively, which in turn promoted the generation of H2O2 and H2; however, it had a negligible effect on O2 generation. The equilibrium concentrations of H2O2 and H2 increased with an increase in the absorption dose rate. Specifically, when the absorption dose rate was increased from 1.40 to 46.93 Gy/min, the equilibrium concentrations of H2O2 and H2 increased from 4.56×10-6 and 1.78×10-5 mol/L to 2.46×10-5 and 3.81×10-4 mol/L, respectively, whereas O2 remained essentially unaffected within this absorption dose rate range. In addition, based on the kinetics of water radiolysis and two-film theory of gas-liquid mass transfer, we constructed a calculation model for the radiolysis of aqueous solutions containing copper ions. Compared with the experimental data, the absolute values of the normalized mean bias in the simulation results were mostly between 1% and 7%, with a maximum of approximately 24%, thereby demonstrating the effectiveness and correctness of the calculation model. Accordingly, the model was used to calculate the radiolytic behavior of an aqueous solution containing copper ions under C6+ ion irradiation, and the simulation results matched well with the experimental data reported in the literature, indicating that the model can be expanded to other applications

γ-Radiolysis of the aqueous ammonia solution saturated by N2

In some reactors, ammonia and its radiolytic product (H2) are used to scavenge the oxidizing species (H2O2, O2, and •OH). A reducing chemical environment is thus created and the pH of the coolant is regulated simultaneously. In the present study, the radiolytic behaviors of deoxygenated ammonia solution were studied in the γ-ray field. The impacts of N2 pressure, gas-liquid volume ratio, and temperature on deoxygenated ammonia solution radiolysis were investigated. The pH and the concentrations of residual ammonia, H2, and nitrogen oxides (NO2- and NO3-) were analyzed. The results revealed that the variation of N2 pressure (0.5~5.0 MPa) and gas-liquid volume ratio had no influence on the concentrations of residual ammonia and nitrogen oxides. NO2- and NO3- concentrations were approximately 1 mg/L at room temperature when the absorbed dose was 28.8 kGy. However, the apparent concentration of H2 significantly decreased with the N2 pressure and gas-liquid volume ratio. The loss fraction of ammonia considerably declined from 26.5% to 8.4% when the temperature increased from 25 to 200 ℃, demonstrating that the radiolysis of ammonia was suppressed at the elevated temperature. However, the concentrations of NO2- and NO3- increased to 34 and 3 times, respectively, at 200 ℃ compared to those at 25 ℃. In addition, a radiolysis model of ammonia-containing coolant was established in the present study. The maximum relative error between experimental data and calculation results at any temperature was 4.1%. The model was thereafter used to calculate residual ammonia concentration with the absorbed dose under different initial ammonia concentrations. The results revealed that it was necessary to replenish ammonia regularly when using it alone to inhibit oxidizing species

Precise Shrink Fitting Design of the High Strength Gear Mold for the Precision Forging of Noncircular Spur Bevel Gears

Shrink fitting of forging mold (SFFM) is an effective method for improving mold strength, extending the mold’s service life and reducing the manufacturing cost of forging mold. However, due to the asymmetric geometry and complex stress distribution, the precise design of SFFM for the precision forging of noncircular bevel gears is very difficult. In this paper, a new precise design method of SFFM for the precision forging of noncircular bevel gears is proposed, which mainly includes the following five parts. First, a new design method for the mold parting surface—the curved surface parting method—is proposed to design the forging mold of noncircular spur bevel gears. Then, new dimension design methods for the gear mold and shrink rings based on the uniform shrinkage force are proposed. Third, a new design method for the inhomogeneous interference value between shrink rings and the gear mold is developed to provide a precise, uniform shrinkage force. After that, a strength correction method for the shrink-fitted gear mold is proposed to ensure the gear mold and shrink rings have sufficient strength both in the assembly process of the shrink-fitted gear mold and precision in the forging process of noncircular spur bevel gears. Ultimately, finite element simulations and verification experiments are performed to verify the proposed precise design method of SFFM for the precision forging of noncircular bevel gears. The precise design method of SFFM proposed in this paper is not only applicable to the precise design of the high-strength gear mold for noncircular bevel gears, but can also provide a valid reference for the precise design of the high-strength mold for other complicated asymmetric parts

A track following visual navigation model car based on FPGA

Conference Name:2013 2nd International Conference on Measurement, Instrumentation and Automation, ICMIA 2013. Conference Address: Guilin, China. Time:April 23, 2013 - April 24, 2013.Korea Maritime University; Hong Kong Industrial Technology Research Centre; Inha UniversityA novel adaptive track finding algorithm is designed, which combines the function of track finding and image binarization. The combination of these two functions allows the system to determine the binarization threshold adaptively, and perform accurate visual navigation in diverse lighting and track conditions. A circular arc path planning strategy with a single measurable control parameter is used to guide the model car to the track. The circular arc path planning strategy is easy to implement and delivers fast and accurate responses to the track. ? (2013) Trans Tech Publications, Switzerland

Sound Speed Inversion Based on Multi-Source Ocean Remote Sensing Observations and Machine Learning

Ocean sound speed is important for underwater acoustic applications, such as communications, navigation and localization, where the assumption of uniformly distributed sound speed profiles (SSPs) is generally used and greatly degrades the performance of underwater acoustic systems. The acquisition of SSPs is necessary for the corrections of the sound ray propagation paths. However, the inversion of SSPs is challenging due to the intricate relations of interrelated physical ocean elements and suffers from the high costs of calculations and hardware deployments. This paper proposes a novel sound speed inversion method based on multi-source ocean remote sensing observations and machine learning, which adapts to large-scale sea regions. Firstly, the datasets of SSPs are generated utilizing the Argo thermohaline profiles and the empirical formulas of the sound speed. Then, the SSPs are analyzed utilizing the empirical orthogonal functions (EOFs) to reduce the dimensions of the feature space as well as the computational load. Considering the nonlinear regression relations of SSPs and the observed datasets, a general framework for sound speed inversion is formulated, which combines the designed machine learning models with the reduced-dimensional feature representations, multi-source ocean remote sensing observations and water temperature data. After being well trained, the proposed machine learning models realize the accurate inversion of the targeted ocean region by inputting the real-time ocean environmental data. The experiments verify the advantages of the proposed method in terms of the accuracy and effectiveness compared with conventional methods