Image registration is the basis of medical image analysis whichhas profound significance in the field of medical image processing. In order to improve its accuracy, a method based on chaotic brain ...storm optimization algorithm in objective space(CBSO-OS) is proposed. The CBSO-OS increases its ability of global exploitation by replacing random function with guass map. Compared with other four optimization algorithms in image registration experiments, the root mean square error of the proposed algorithm is reduced by 0.69%, 2.26%, 3.54% and 1.37%, respectively. Meanwhile, the translation error of the proposed registration algorithm is the smallest. Experimental results show that the proposed registration algorithm effectively reduces the registration error of medical images so as to provide doctors with high-precision registered images.
The difficulty of the information extraction task lies in dealing with the task-specific label schemas and heterogeneous data structures. Recent work has proposed methods based on large language ...models to uniformly model different information extraction tasks. However, these existing methods are deficient in their information extraction capabilities for Chinese languages other than English. In this paper, we propose an end-to-end chat-enhanced instruction tuning framework for universal information extraction (YAYI-UIE), which supports both Chinese and English. Specifically, we utilize dialogue data and information extraction data to enhance the information extraction performance jointly. Experimental results show that our proposed framework achieves state-of-the-art performance on Chinese datasets while also achieving comparable performance on English datasets under both supervised settings and zero-shot settings.
Shaoqing Wang1, Xiancun Yang2, Meixia Su1, Qiang Liu1 1Department of MRI, Shandong Medical Imaging Research Institute Affiliated to Shandong University, Jinan, Shandong, 250021, People's Republic of ...China; 2Department of Interventional Radiology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong, 250021, People's Republic of China Correspondence: Qiang Liu (2002md@163.com) Aims To evaluate the diagnostic value of three- dimensional rotational angiography (3D-RA) of intracranial micro-aneurysms (diameter ≤ 3 mm) and provide guidance on the value of endovascular treatment. Materials and methods 43 patients with intracranial micro-aneurysms were analyzed retrospectively, all patients had undergone angiography with both conventional 2D-DSA(Two-Dimensional Digital Subtraction Angiography) and rotational angiography with three-dimensional reconstruction; the frequency of detection of aneurysms, depiction of aneurysm neck, radiation dose, and the dosage of contrast agent were recorded respectively. Results 55 pieces of aneurysms were detected out from the 43 cases with intracranial micro-aneurysms by 3D-RA. But only 39 cases were detected out using 2D-DSA from the 55 samples, there were significant differences with regards to detection rate (P < 0.05). There were significant differences in radiation dose and dosage of contrast agent (P < 0.05) between the two methods of using 3D-RA can improve the detection rate of micro-aneurysms, which bestows obvious advantages on displaying the shape of aneurysms, the aneurysm neck at the best angle, and the relationship with the parent artery, at the same time, the amount of contrast agent and radiation dose are reduced in 3D-RA compared to 2D-DSA.
Vehicle-Infrastructure cooperation is an advanced development stage of autonomous driving, which helps to upgrade the capability of vehicles by fully implementing real-time information interaction ...among vehicles, roads and pedestrians. However, perception, computing and communication are usually decoupled in today's vehicle-road coordination applications, which significantly adds delay and cost to the system. In this paper, we propose and implement a platform that integrates perception, computing and communication to provide timely roadside feature maps to vehicles for vision fusion. A neural processing unit (NPU) for computing and a cellular vehicle-to-everything (C-V2X) wireless baseband IP for communication are both implemented on FPGA. We evaluate the effectiveness of the proposed platform using CoBEVT algorithm on the camera track of the OPV2V perception dataset. The experimental result show that our platform can expand the view of vehicles as well as improve information freshness in terms of end-to-end delay.
The cultural algorithm, as a dual-inheritance framework designed for optimization problems, can incorporate any population-adopted evolutionary computation technique in its population space. On the ...other hand, based on the Five-Elements Cycle Model derived from the ancient Chinese Five Elements (metal, wood, water, fire, earth) theory, the five-elements cycle optimization algorithm was proved to be effective in solving continuous function optimization problems. In this work, we propose a multi-objective cultural algorithm with a five-elements-cycle-optimization-based population space, where the five-element cycle model is adopted as the evolution scheme in the population space of the cultural algorithm framework. Simulation results on 12 classic benchmark problems show that the proposed algorithm can effectively solve continuous optimization functions and obtains satisfactory non-dominated solutions compared with 8 representative multi-objective algorithms.
To deal with the low efficiency in the traditional flocculation link of steel plant wastewater treatment, an intelligent dosing system combined with image recognition, LightGBM algorithm, and ...self-learning ability is proposed to automatically monitor water quality and recommend optimal dosage analyzing both image and water quality parameters. Images acquired from the industrial camera and water parameters from underwater detectors are used as input for the dosing models which are trained by the LightGBM algorithm, then the recommended dosage could be given by the model and sent to an automatic dosing system controlled by a programmable logic controller (PLC), which forms a closed- loop for intelligent dosing. The resulting parameters are also iteratively recorded for self-learning. Based on two high-density pools with one adopting the proposed intelligent dosing system and the other completely manually-controlled, the experiment shows that the proposed intelligent dosing system completely realizes unmanned control and improves the average water qualification rate up to 97.52%, increasing it by 85.81% compared with traditional artificial dosing, and dosing costs decrease by approximately 41%.
Many high-quality biological pathways are presented in figures and text in biomedical literature. They are great resources for studies of biological mechanisms and precision medicine practices. These ...pathways need to be carefully curated, reconciled, and transformed into a computable form. Current manual curation approaches are inadequate in keeping up with the pace of the literature growth. New bio-curation approaches are needed to streamline the identification of gene interactions from pathway figures and text. This paper proposes a pathway curation approach for identifying genes and their interactions using both figures and text of biomedical articles. Our method integrates deep learning-based object detection models with a Google optical character recognition service to extract genes and their interactions from pathway figures. Our pipeline was evaluated on the figures from PubMed publications with manual annotations. The results demonstrated that our model could effectively retrieve genes and their interactions in pathway figures. The proposed pipeline may accelerate various applications of the latest biomedical discoveries. We also developed a web server at http://pathwaydeep.top to provide the gene interaction curation on uploaded pathway figures and corresponding articles.
Machining precision and low-speed stability of permanent magnet linear motors is influenced by thrust ripple that results from resistance disturbance and load disturbance. Considering the slow ...convergence of nonsingular fast terminal sliding mode control, this paper proposes an approach to nonsingular fast terminal sliding mode control, designs the control law for active permanent magnet linear motors by adopting attractor to design reaching law, and makes a comparison through simulation and nonsingular fast terminal sliding mode.
Longitudinal social network clustering is an emerging research area with many applications. Previous research typically focuses on the development of the clusters in the longitudinal network. In this ...paper, we propose an alternative method for longitudinal social network clustering, in which we assume that the clustering and the evolution of the network are the results of its inner structure, the strength of the ties among the nodes in the network. We estimate the strength of the ties based on the evolution of the network over time through a continuous Markov process and then clustering the network based on the strength of the ties of the whole network. A simulation study shows that the proposed method performs well under a variety of conditions. The application of the method is illustrated through the analysis of a real set of data.
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