Recent Advances in RecBole: Extensions with more Practical Considerations

RecBole has recently attracted increasing attention from the research community. As the increase of the number of users, we have received a number of suggestions and update requests. This motivates us to make some significant improvements on our library, so as to meet the user requirements and contribute to the research community. In order to show the recent update in RecBole, we write this technical report to introduce our latest improvements on RecBole. In general, we focus on the flexibility and efficiency of RecBole in the past few months. More specifically, we have four development targets: (1) more flexible data processing, (2) more efficient model training, (3) more reproducible configurations, and (4) more comprehensive user documentation. Readers can download the above updates at: https://github.com/RUCAIBox/RecBole.Comment: 5 pages, 3 figures, 3 table

An IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health

Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment

Optimized highway deep learning network for fast single image super-resolution reconstruction

With the success of the deep residual network for image recognition tasks, the residual connection or skip connection has been widely used in deep learning models for various vision tasks, including single image super-resolution (SISR). Most existing SISR approaches pay particular attention to residual learning, while few studies investigate highway connection for SISR. Although skip connection can help to alleviate the vanishing gradient problem and enable fast training of the deep network, it still provides the coarse level of approximation in both forward and backward propagation paths and thus challenging to recover high-frequency details. To address this issue, we propose a novel model for SISR by using highway connection (HNSR), which composes of a nonlinear gating mechanism to further regulate the information. By using the global residual learning and replacing all local residual learning with designed gate unit in highway connection, HNSR has the capability of efficiently learning different hierarchical features and recovering much more details in image reconstruction. The experimental results have validated that HNSR can provide not only improved quality but also less prone to a few common problems during training. Besides, the more robust and efficient model is suitable for implementation in real-time and mobile systems

Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography

Despite the new ideas were inspired in medical treatment by the rapid advancement of three-dimensional (3D) printing technology, there is still rare research work reported on 3D printing of coronary arteries being documented in the literature. In this work, the application value of 3D printing technology in the treatment of cardiovascular diseases has been explored via comparison study between the 3D printed vascular solid model and the computer aided design (CAD) model. In this paper, a new framework is proposed to achieve a 3D printing vascular model with high simulation. The patient-specific 3D reconstruction of the coronary arteries is performed by the detailed morphological information abstracted from the contour of the vessel lumen. In the process of reconstruction which has 5 steps, the morphological details of the contour view of the vessel lumen are merged along with the curvature and length information provided by the coronary angiography. After comparing with the diameter of the narrow section and the diameter of the normal section in CAD models and 3D printing model, it can be concluded that there is a high correlation between the diameter of vascular stenosis measured in 3D printing models and computer aided design models. The 3D printing model has high-modeling ability and high precision, which can represent the original coronary artery appearance accurately. It can be adapted for prevascularization planning to support doctors in determining the surgical procedures

Sustainable Improvement of Planting Quality for a Planar 5R Parallel Transplanting Mechanism from the Perspective of Machine and Soil Interaction

The poor shape of the cavity formed by the planar 5R parallel transplanting mechanism will cause Salvia miltiorrhiza seedlings to tilt while transplanting them. In order to improve the quality of the cavity in Salvia miltiorrhiza planting, this paper analyzed the structural composition and working principle of a planar 5R parallel transplanting mechanism for Salvia miltiorrhiza and established the bidirectional coupling model between the transplanting mechanism and the soil. Based on the model, a regression analysis model and the influence of three factors and five levels were obtained by using the experimental optimization design method, which reflected the relationship between the parameters of the mechanism on the parameters of the cavity. In terms of the optimization objective and regression model, the optimal parameter combination of the transplanting mechanism was obtained by multi-objective parameter optimization. A virtual test of cavity formation was conducted on the transplanting mechanism for Salvia miltiorrhiza with an optimal parameter combination. The results proved that the parameters of cavity output via the regression model and the measurement from the bidirectional coupling model were basically consistent, which verifies the accuracy of our parameter optimization for the transplanting mechanism. This paper provides a new approach to the sustainable improvement of a Salvia miltiorrhiza transplanting mechanism from the perspective of the interaction between the machine and the soil

Sentiments classification in stock network public opinion space based on long-short memory convolution neural network

Deep learning is used to deal with natural language processing problems. Some are based on phrases and some are based on words. This article is inspired by the pixel level in the CV world and therefore retrains the neural network from a character perspective. Neural networks do not need to know about word lookup table or word2vec in advance, and the knowledge of these words is often high-dimensional and it is difficult to apply to convolutional neural networks. In addition, our long-short term memory convolutional neural networks no longer need to know the syntax and semantics in advance. The purpose of this paper is to analyse the investor's psychological characteristics and investment decision-making behaviour characteristics, to study the investor sentiment in the network public opinion space

Sentiments classification in stock network public opinion space based on long-short memory convolution neural network

Deep learning is used to deal with natural language processing problems. Some are based on phrases and some are based on words. This article is inspired by the pixel level in the CV world and therefore retrains the neural network from a character perspective. Neural networks do not need to know about word lookup table or word2vec in advance, and the knowledge of these words is often high-dimensional and it is difficult to apply to convolutional neural networks. In addition, our long-short term memory convolutional neural networks no longer need to know the syntax and semantics in advance. The purpose of this paper is to analyse the investor's psychological characteristics and investment decision-making behaviour characteristics, to study the investor sentiment in the network public opinion space

Research on stock similarity and community division based on user attention sequence

We conduct research from the perspective of user groups and analyze the differences in the users' attention and posting order in different time periods to vectorize stocks and build relationships from the generatedx vectors. This provides a new perspective for the complex network cconstruction and community division of network public opinion space. The experiment result show that we can get the community division consistent with reality using our model

A Quantum Ant Colony Multi-Objective Routing Algorithm in WSN and Its Application in a Manufacturing Environment

In many complex manufacturing environments, the running equipment must be monitored by Wireless Sensor Networks (WSNs), which not only requires WSNs to have long service lifetimes, but also to achieve rapid and high-quality transmission of equipment monitoring data to monitoring centers. Traditional routing algorithms in WSNs, such as Basic Ant-Based Routing (BABR) only require the single shortest path, and the BABR algorithm converges slowly, easily falling into a local optimum and leading to premature stagnation of the algorithm. A new WSN routing algorithm, named the Quantum Ant Colony Multi-Objective Routing (QACMOR) can be used for monitoring in such manufacturing environments by introducing quantum computation and a multi-objective fitness function into the routing research algorithm. Concretely, quantum bits are used to represent the node pheromone, and quantum gates are rotated to update the pheromone of the search path. The factors of energy consumption, transmission delay, and network load-balancing degree of the nodes in the search path act as fitness functions to determine the optimal path. Here, a simulation analysis and actual manufacturing environment verify the QACMOR’s improvement in performance

Application of a small-scale model test in distinguishing of water inrush in the Wufeng Tunnel

Objective Water inrush in karst tunnel has a great influence on tunnel safety. Methods Taking the Wufeng Tunnel of Yilai Expressway as the research object, the risk of water inrush in the tunnel was identified though field hydrogeological investigation, borehole water level and indoor rainfall monitoring, numerical simulation and small-scale model tests. Results The test results show that the risk of water inrush in the tunnel is mainly affected by the relative spatial position between the karst pipeline and tunnel, including the water pressure of the pipeline. The influence of seepage on the tunnel can be effectively reduced by increasing the thickness of the overlying soil when the test water pressure is 0.2 MPa. But with the increase in water pressure, the seepage of pipeline water is not only vertical seepage but also includes horizontal seepage. The intermittent cracks in the waterproof layer expand, which finally results in water inrush damage in the tunnel. The numerical simulation results show that the maximum shear force of the Wufeng Tunnel is at the arc and shoulder, which may easily form tensile shear failure along this part under groundwater seepage. The finding is consistent with the test results of the small-scale model. The water inrush in the tunnel is the coupling effect of the shear force and seepage field. Conclusion The primary factor of water inrush in the tunnel is water pressure and is closely related to the thickness of water barrier rock