Abstract:The weight values in mixture distribution models usually depend on unknown or known parameters, which makes the model uncertain. To address this issue, we propose to determine the model weights based on Frobenius. Firstly, the multivariate Poisson distribution was truncated and homogenized to generate a multivariate Pseudo-Poisson distribution. Secondly, set function matrix of multivariate Pseudo-Poisson mixture distribution, multiple linear Pseudo-Boolean function matrix, multiple linear Pseudo-Boolean function matrix’s Frobenius norm were solved respectively according to the expression for countable mixture distribution. New weights were calculated and in turn a multivariate Pseudo-Poisson mixture distribution model was constructed. Finally, the correctness of the model was proved according to the normalization and nonnegativeness of the mixture distribution weights and the entire process of building model was demonstrated through simulation experiments. We also verified that arithmetic average is reasonable. The proposed model can provide a theoretical basis for applications and algorithm design of mixture distribution in machine learning.

Abstract:Molecular dynamics simulation can directly model the molecular behavior, making it convenient to investigate the microscopic mechanism of thermal conductance of boron nitride (BN) nanomaterials. However, there still no explicitly investigation to the size effect of the BN monolayer on its thermal properties. In this paper, the equilibrium molecular dynamics (EMD) combined with the Green-Kubo method was used to unravel and explain the relations between the system size and the thermal conductivity, phonon dispersion, and phonon density of states (DOS) of pristine BN monolayer. It was found that the thermal conductivity of the BN monolayer decreased with increasing the size of the sturcture, reaching a converged value (349±22) W/(m?K) at 4.1 nm×4.1 nm. This value was much smaller than the converging size (10 nm×10 nm) of graphene in calculating its thermal conductivity using EMD simulations, which implied the phonon-phonon scattering in BN monolayer was larger than that in graphene. Different from the thermal conductivity, the phonon dispersion and phonon DOS of the BN monolayer did not depend on the size of the structure. Our findings provide important reference for investigating the microscopic mechanisms of BN related materials by using the equilibrium molecular dynamics modeling.

Abstract:To investigate the feasibility of Microsoft Kinect camera for guiding percutaneous liver needle intervention, a puncture navigation system based on the second generation Kinect was developed. The two surfaces from preoperative computed tomograph (CT) and intraoperative Kinect RGB-depth images were extracted and matched for physical-to-image registration. Experiments were conducted on a general abdominal phantom and six beagles in vivo. The target registration error, user error, and target positioning error were used to evaluate navigation accuracy. The results show that target registration error, user error, and target positioning error of the phantom are (4.26±1.94) mm, (2.92±1.67) mm and (5.23±2.29) mm, respectively. In addition, two generations of Kinect were both tested, and the results imply that the second generation Kinect-based navigation is superior to the first-generation. For the animal experiment, the target positioning error was evaluated as (6.40±2.72) mm, and its lateral and longitudinal component were (4.30±2.51) mm and (3.80±3.11) mm, respectively. This study demonstrates that the Kinect camera has a potential of clinical application in percutaneous liver puncture navigation.

Abstract:In this paper, a binary geometrical pattern is used for the calibration of structured light system instead of conventional checkboard pattern. The pattern is designed based on pseudo-random coding theory, and the calibration procedure contains following steps. First, an accurate feature detector is proposed by utilizing the geometric property of the pattern elements. It is show that, with the proposed feature detector, feature points can be robustly localized with sub-pixel precision. Based on the extracted feature points, a topological structure is constructed to separate all the pattern elements. The pattern elements are extracted with affine transformation theory and bilinear interpolation. Secondly, to identify the pattern elements, the convolutional neural network technique is adopted, which is trained by collecting a large number of pattern element samples. After the decoding stage, code words of the feature points can be computed. According to the projective transformation principle, pattern feature points in the camera image plane can be transformed to the projector image plane with the corresponding code word. Finally, both intrinsic and extrinsic parameters of camera and projector can be calculated. Experimental results show that the re-projector error of projector calibration results can be controlled within 0.3 pixels. In comparison with conventional calibration methods, both calibration and 3D reconstruction precision can be improved by the proposed approach.

Abstract:Electrocardiogram (ECG) has been widely used in studying the characteristics of human cardiac electronic activities and the diagnosis of cardiac related diseases. Conductive paste or gel was usually used in conventional wet contact electrode. However, it may cause burden, discomfort and skin allergies to the subject, which make it not suitable for long-term monitoring of ECG signals. To address this issue, this paper proposed a non-contact electrode which obtains the ECG signal through the capacitive coupling between skin and electrode sensing layer. Additionally, a physiological signal acquisition system based on ADS1299 was also built, so that a paste-free, non-contact ECG measurement could be achieved. Then, the effects of material and thickness of the insulating layer between non-contact electrode and skin on the ECG signal measurement were systemically investigated. The results show that the non-contact electrode can obtain high-quality ECG signals, and the insulation parameters have significant effect on ECG signal quality. Specifically, ECG signal quality achieves the best when cotton material was used as insulation layer. It was also observed that the smaller insulation thickness, the better ECG signal quality. The results of this study could provide important experimental and theoretical basis for further application of non-contact electrodes in mobile healthcare monitoring.

Abstract:Entity Resolution assigns data objects corresponding to the same real world entity described in one or more data sources into the same group, which plays an important role in data cleaning, data integration, and data mining. However, the features of the entity may evolve over time irregularly, which makes the entity resolution significantly challenging. Traditional approaches can only tackle the issue that the feature of an entity changes regularly with time but can not deal with the case that the feature changes irregularly over time. An approach based on classification was proposed to solve this problem. Firstly, the random forest, a machine learning algorithm, was used to calculate the similarity of records. Consequently, new two-stage clustering algorithm was employed to perform the record clustering. Finally, the evaluation on real data sets shows that the approach can effectively improve the resolution accuracy of the evolutionary entity.

Abstract:Falls are the first leading cause of unintentional injury deaths in the eldly. About one third of elderlies larger than 65 years old happens to fall each year, which causes huge harm to the human body especially the hip joint. Using inflatable air bag to reduce damage is the most effective means for falling protection at present. In this paper, some key technologies such as overall composition, positioning accuracy, inflatable mechanism and parameters of the capsule were studied and implemented in the wearable fall protective airbag. The system is composed of power module, main control module, sensing module, positioning module, communication module, inflatable mechanism, compressed gas cylinder and capsule structure. It supports two positioning methods of GPS and WIFI, where the indoor positioning accuracy is about 60 m and the outdoor is only about 7 m. Additionally, the optimized structure parameters of an inflatable mechanism and a bionic shock absorber based on the structure of the human hip were designed. The reliability test of sprinting was carried out on 8 g, 12 g and 16 g, and the average time of filling gas is 386.9 ms with high speed dynamic recorder. A 3D geometric model of human hip was accomplished by importing the 2D computed tomography images of the hip, and a finite element model of the airbag was completed with the finite element analysis software ANSYS. The models of sideway fall were established in the case of absence in falls protective side and presence in hip protection cushion airbag protection. Comparison shows that the hip-protected’s good performance is achieved, with decreasing the peak impact force of the hip by 70% and the absorption of energy by 83.8%.

Abstract:5-(4-Carboxyphenyl)-10,15,20-triphenylporphyrin (TPP) is a porphyrin derivation with high symmetry and conjugated π bond. Porphyrins are critical precursor of many bio-compounds, such as heme and chloroplast. And its unique structure contributes to a special spectroscopy. In this article, the effect of polarity and pH of solution on the optical property of TPP was analyzed by detecting the absorption and emission spectra in different solvent. Then, we discussed how the molecular structure changed before and after protonation by theoretically circulating several basic parameter of different conformations. Finally, we predicted its prospects for photodynamic therapy according to the photodynamic reaction efficiency shown in vitro.