Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

Graph networks are a new machine learning (ML) paradigm that supports both relational reasoning and combinatorial generalization. Here, we develop universal MatErials Graph Network (MEGNet) models for accurate property prediction in both molecules and crystals. We demonstrate that the MEGNet models outperform prior ML models such as the SchNet in 11 out of 13 properties of the QM9 molecule data set. Similarly, we show that MEGNet models trained on $\sim 60,000$ crystals in the Materials Project substantially outperform prior ML models in the prediction of the formation energies, band gaps and elastic moduli of crystals, achieving better than DFT accuracy over a much larger data set. We present two new strategies to address data limitations common in materials science and chemistry. First, we demonstrate a physically-intuitive approach to unify four separate molecular MEGNet models for the internal energy at 0 K and room temperature, enthalpy and Gibbs free energy into a single free energy MEGNet model by incorporating the temperature, pressure and entropy as global state inputs. Second, we show that the learned element embeddings in MEGNet models encode periodic chemical trends and can be transfer-learned from a property model trained on a larger data set (formation energies) to improve property models with smaller amounts of data (band gaps and elastic moduli)

Bounds on RF cooperative localization for video capsule endoscopy

Wireless video capsule endoscopy has been in use for over a decade and it uses radio frequency (RF) signals to transmit approximately fifty five thousands clear pictures of inside the GI tract to the body-mounted sensor array. However, physician has no clue on the exact location of the capsule inside the GI tract to associate it with the pictures showing abnormalities such as bleeding or tumors. It is desirable to use the same RF signal for localization of the VCE as it passes through the human GI tract. In this thesis, we address the accuracy limits of RF localization techniques for VCE localization applications. We present an assessment of the accuracy of cooperative localization of VCE using radio frequency (RF) signals with particular emphasis on localization inside the small intestine. We derive the Cramer-Rao Lower Bound (CRLB) for cooperative location estimators using the received signal strength(RSS) or the time of arrival (TOA) of the RF signal. Our derivations are based on a three-dimension human body model, an existing model for RSS propagation from implant organs to body surface and a TOA ranging error model for the effects of non-homogenity of the human body on TOA of the RF signals. Using models for RSS and TOA errors, we first calculate the 3D CRLB bounds for cooperative localization of the VCE in three major digestive organs in the path of GI tract: the stomach, the small intestine and the large intestine. Then we analyze the performance of localization techniques on a typical path inside the small intestine. Our analysis includes the effects of number of external sensors, the external sensor array topology, number of VCE in cooperation and the random variations in transmit power from the capsule

Sensitivity Analysis for Measurements of Multipath Parameters Pertinent to TOA based Indoor Geolocation

Recently, indoor geolocation technologies has been attracting tremendous attention. For indoor environments, the fine time resolution of ultra-wideband (UWB) signals enables the potential of accurate distance measurement of the direct path (DP) between a number of reference sources and the people or assets of interest. However, Once the DP is not available or is shadowed, substantial errors will be introduced into the ranging measurements, leading to large localization errors when measurements are combined from multiple sources. The measurement accuracy in undetected direct path (UDP) conditions can be improved in some cases by exploiting the geolocation information contained in the indirect path measurements. Therefore, the dynamic spatial behavior of paths is an important issue for positioning techniques based on TOA of indirect paths. The objectives of this thesis are twofold. The first is to analyze the sensitivity of TOA estimation techniques based on TOA of the direct path. we studied the effect of distance, bandwidth and multipath environment on the accuracy of various TOA estimation techniques. The second is to study the sensitivity of multipath parameters pertinent to TOA estimation techniques based on the TOA of the indirect paths. We mainly looked into the effect of distance, bandwidth, threshold for picking paths, and multipath environment on the number of multipath components(MPCs) and path persistency. Our results are based on data from a new measurement campaign conducted on the 3rd floor of AK laboratory. For the TOA estimation techniques based on DP, the line of sight (LOS) scenario provides greatest accuracy and these TOA estimation techniques are most sensitive to bandwidth availability in obstructed line of sight (OLOS) scenario. All the TOA estimation algorithms perform poorly in the UDP scenario although the use of higher bandwidth can reduce the ranging error to some extent. Based on our processed results, The proposal for selecting the appropriate TOA estimation technique with certain constrains is given. The sensitivity study of multipath parameters pertinent to indirect-path-based TOA estimation techniques shows that the number of MPCs is very sensitive to the threshold for picking paths and to the noise threshold. It generally decreases as the distance increase while larger bandwidth always resolves more MPCs. The multipath components behave more persistently in line of sight (LOS) and obstructed line of sight (OLOS) scenarios than in UDP scenarios, and the use of larger bandwidth and higher threshold for picking paths also result in more persistent paths

Research and practices of large composite external wall panels for energy saving prefabricated buildings

The production process and application of large composite external wall panels (composite panels for short) are introduced in this paper. Composite panels with both load bearing and thermal insulation were formed by pouring normal concrete (NC) and ceramsite foamed concrete (CFC) continuously according to particular technological requirements, which made two layers into a seamless whole. The layers of NC and CFC are for load bearing and thermal insulation respectively. The composite panels were manufactured in the scale of industrial production, and applied to several energy saving prefabricated buildings successively, instead of polystyrene sandwich composite panels (sandwich panel for short) as external wall panels. There are several obvious advantages of the composite panel over the sandwich panel or outer benzoic board. Firstly, it solved the problems of durability of polystyrene and the complex production process of the sandwich pane, the production process of the external wall was thus greatly simplified. In addition, the fire risk was much reduced

A Windmill-Shaped SSPP Waveguide for High-Efficiency Microwave and Terahertz Propagation

We propose a novel type of spoof surface plasmon polariton (SSPP) waveguide based on windmill-shaped units for high-efficiency microwave and terahertz propagation. The dependence of terahertz dispersion characteristics on geometrical parameters of the proposed waveguide is detailed and investigated. Compared with the conventional comb-shaped and T-shaped SSPP waveguide units, the proposed windmill-shaped unit shows a lower asymptotic frequency and stronger field-confinement characteristics for the supported fundamental SSPP mode. To demonstrate the properties of the windmill-shaped SSPP waveguide, a tapered conversion is designed to connect the windmill-shaped SSPP waveguide and the microstrip for smooth momentum and impedance matching. The simulated results show that the whole waveguide has excellent transmission performance with S11 < −10 dB and S21 > −1 dB from 0 THz to 5.68 THz, as well as a large out-of-band rejection response (S21 < −80 dB). Then, a scaled microwave windmill-shaped waveguide prototype is fabricated and measured. The numerical and experimental results are in good agreement, which further validates the proposed SSPP waveguide design. The proposed waveguide has excellent microwave and terahertz propagation and rejection characteristics, which may have great potential applications in various microwave and terahertz devices and circuits

A Windmill-Shaped SSPP Waveguide for High-Efficiency Microwave and Terahertz Propagation

We propose a novel type of spoof surface plasmon polariton (SSPP) waveguide based on windmill-shaped units for high-efficiency microwave and terahertz propagation. The dependence of terahertz dispersion characteristics on geometrical parameters of the proposed waveguide is detailed and investigated. Compared with the conventional comb-shaped and T-shaped SSPP waveguide units, the proposed windmill-shaped unit shows a lower asymptotic frequency and stronger field-confinement characteristics for the supported fundamental SSPP mode. To demonstrate the properties of the windmill-shaped SSPP waveguide, a tapered conversion is designed to connect the windmill-shaped SSPP waveguide and the microstrip for smooth momentum and impedance matching. The simulated results show that the whole waveguide has excellent transmission performance with S11 −1 dB from 0 THz to 5.68 THz, as well as a large out-of-band rejection response (S21 < −80 dB). Then, a scaled microwave windmill-shaped waveguide prototype is fabricated and measured. The numerical and experimental results are in good agreement, which further validates the proposed SSPP waveguide design. The proposed waveguide has excellent microwave and terahertz propagation and rejection characteristics, which may have great potential applications in various microwave and terahertz devices and circuits

Research on the Construction Method of Intelligent Prediction and Analysis Model for the Whole Process of Power Grid Project Cost

The government’s supervision of power grid enterprises will gradually focus on the transmission and distribution price, and the investment and income will be more strictly supervised. Under the new management requirements, the company must pay more attention to the compliance of the investment process, further strengthen the investment risk control, put an end to inefficient or invalid investment, strengthen the all-round and whole process supervision, and scientifically and accurately determine and carry out effective project cost control and management. It is the key to achieve project management objectives, and also an important measure of investment fine management and control. This paper takes historical cost data as the research object, constructs the whole process intelligent prediction and analysis model of power grid project cost, assists investment decision-making, reduces the balance rate, and improves the efficiency and efficiency of the company’s investment and lean management level

Facile fabrication of PS/Fe3O4@PANi nanocomposite particles and their application for the effective removal of Cu2+

This work presents a simple and straightforward approach to fabricating multifunctional nanocomposite particles which possess a core of a polystyrene (PS) particle, a transition layer of magnetic Fe3O4 nanoparticles (NPs), and an outer shell of adsorbable polyaniline (PANi). In detail, the positively charged Fe3O4 NPs synthesized via the chemical co-precipitation method are directly loaded onto the negatively charged surfaces of the PS particles obtained by emulsifier-free emulsion polymerization through electrostatic self-assembly; subsequently, the coating of the resultant PS/Fe3O4 nanocomposite particles with PANi was successfully achieved by virtue of the "swelling-diffusion-interfacial-polymerization method'' (SDIPM). Furthermore, the adsorption of Cu2+ by PS/Fe3O4@ PANi nanocomposite particles was investigated by changing the initial pH value, adsorption time, and initial concentration of the adsorbate. The adsorption data in our work follow a pseudo-second-order kinetics model and fit the Langmuir isotherm model. The PS/Fe3O4@ PANi nanocomposite particles show that the maximum adsorption capacity is up to 181.5 mg g(-1) at pH 5. More importantly, these nanocomposite particles can be easily recovered using an external magnetic field owing to the presence of Fe3O4 NPs, and the regenerated nanocomposite particles can be repeatedly used for eight cycles without significant loss of their adsorption capacity