Bidirectional optimization of the melting spinning process

This is the author's accepted manuscript (under the provisional title "Bi-directional optimization of the melting spinning process with an immune-enhanced neural network"). The final published article is available from the link below. Copyright 2014 @ IEEE.A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.National Nature Science Foundation of China, Ministry of Education of China, the Shanghai Committee of Science and Technology), and the Fundamental Research Funds for the Central Universities

Factors determining patients’ intentions to use point-of-care testing medical devices for self-monitoring: The case of international normalised ratio self-testing

This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. - Copyright @ 2012 Dove Medical Press LtdThis article has been made available through the Brunel Open Access Publishing Fund.Purpose: To identify factors that determine patients' intentions to use point-of-care medical devices, ie, portable coagulometer devices for self-testing of the international normalized ratio (INR) required for ongoing monitoring of blood-coagulation intensity among patients on long-term oral anticoagulation therapy with vitamin K antagonists, eg, warfarin. Methods: A cross-sectional study that applied the technology-acceptance model through a self-completed questionnaire, which was administered to a convenience sample of 125 outpatients attending outpatient anticoagulation services at a district general hospital in London, UK. Data were analyzed using descriptive statistics, factor analyses, and structural equation modeling. Results: The participants were mainly male (64%) and aged ≥ 71 years (60%). All these patients were attending the hospital outpatient anticoagulation clinic for INR testing; only two patients were currently using INR self-testing, 84% of patients had no knowledge about INR self-testing using a portable coagulometer device, and 96% of patients were never offered the option of the INR self-testing. A significant structural equation model explaining 79% of the variance in patients’ intentions to use INR self-testing was observed. The significant predictors that directly affected patients' intention to use INR self-testing were the perception of technology (β = 0.92, P < 0.001), trust in doctor (β = −0.24, P = 0.028), and affordability (β = 0.15, P = 0.016). In addition, the perception of technology was significantly affected by trust in doctor (β = 0.43, P = 0.002), age (β = −0.32, P < 0.001), and affordability (β = 0.23, P = 0.013); thereby, the intention to use INR self-testing was indirectly affected by trust in doctor (β = 0.40), age (β = −0.29), and affordability (β = 0.21) via the perception of technology. Conclusion: Patients’ intentions to use portable coagulometers for INR self-testing are affected by patients' perceptions about the INR testing device, the cost of device, trust in doctors/clinicians, and the age of the patient, which need to be considered prior to any intervention involving INR self-testing by patients. Manufacturers should focus on increasing the affordability of INR testing devices for patients’ self-testing and on the potential role of medical practitioners in supporting use of these medical devices as patients move from hospital to home testing.This study is funded by the Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH) program (EPSRC grant EP/GO12393/1)

Extending twin support vector machine classifier for multi-category classification problems

© 2013 – IOS Press and the authors. All rights reservedTwin support vector machine classifier (TWSVM) was proposed by Jayadeva et al., which was used for binary classification problems. TWSVM not only overcomes the difficulties in handling the problem of exemplar unbalance in binary classification problems, but also it is four times faster in training a classifier than classical support vector machines. This paper proposes one-versus-all twin support vector machine classifiers (OVA-TWSVM) for multi-category classification problems by utilizing the strengths of TWSVM. OVA-TWSVM extends TWSVM to solve k-category classification problems by developing k TWSVM where in the ith TWSVM, we only solve the Quadratic Programming Problems (QPPs) for the ith class, and get the ith nonparallel hyperplane corresponding to the ith class data. OVA-TWSVM uses the well known one-versus-all (OVA) approach to construct a corresponding twin support vector machine classifier. We analyze the efficiency of the OVA-TWSVM theoretically, and perform experiments to test its efficiency on both synthetic data sets and several benchmark data sets from the UCI machine learning repository. Both the theoretical analysis and experimental results demonstrate that OVA-TWSVM can outperform the traditional OVA-SVMs classifier. Further experimental comparisons with other multiclass classifiers demonstrated that comparable performance could be achieved.This work is supported in part by the grant of the Fundamental Research Funds for the Central Universities of GK201102007 in PR China, and is also supported by Natural Science Basis Research Plan in Shaanxi Province of China (Program No.2010JM3004), and is at the same time supported by Chinese Academy of Sciences under the Innovative Group Overseas Partnership Grant as well as Natural Science Foundation of China Major International Joint Research Project (NO.71110107026)

Backlund transformations and Hamiltonian flows

In this work we show that, under certain conditions, parametric Backlund transformations (BTs) for a finite dimensional integrable system can be interpreted as solutions to the equations of motion defined by an associated non-autonomous Hamiltonian. The two systems share the same constants of motion. This observation lead to the identification of the Hamiltonian interpolating the iteration of the discrete map defined by the transformations, that indeed will be a linear combination of the integrals appearing in the spectral curve of the Lax matrix. An application to the Toda periodic lattice is given.Comment: 19 pages, 2 figures. to appear in J. Phys.

Thermal transport measurements of individual multiwalled nanotubes

The thermal conductivity and thermoelectric power of a single carbon nanotube were measured using a microfabricated suspended device. The observed thermal conductivity is more than 3000 W/K m at room temperature, which is two orders of magnitude higher than the estimation from previous experiments that used macroscopic mat samples. The temperature dependence of the thermal conductivity of nanotubes exhibits a peak at 320 K due to the onset of Umklapp phonon scattering. The measured thermoelectric power shows linear temperature dependence with a value of 80 $\mu$V/K at room temperature.Comment: 4 pages, figures include

Graphene field-effect transistors based on boron nitride gate dielectrics

Graphene field-effect transistors are fabricated utilizing single-crystal hexagonal boron nitride (h-BN), an insulating isomorph of graphene, as the gate dielectric. The devices exhibit mobility values exceeding 10,000 cm2/V-sec and current saturation down to 500 nm channel lengths with intrinsic transconductance values above 400 mS/mm. The work demonstrates the favorable properties of using h-BN as a gate dielectric for graphene FETs.Comment: 4 pages, 8 figure