The low actuating voltage and quick bending responses of ICPF (ionic conducting polymer film) are considered very useful and attractive for the construction of various types of actuators and sensors. In this paper, first we present an octopod underwater microrobot which has eight legs, and each leg is made up of two pieces of ICPF. Then we use theory analysis to illustrate the motion mechanism of the microrobot, and study the octopod gait of the microrobot to perform transverse and rotation movement when the legs of crab collaborate. Finally, the experimental results indicate that the octopod gait above is feasible.
Abstract Background Integrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative computational methods capable of managing high-dimensional and heterogeneous datasets are required to unlock the full potential of such rich and diverse data. Methods We propose a Multi-Omics integration framework with auxiliary Classifiers-enhanced AuToencoders (MOCAT), for comprehensive utilization of both intra- and inter-omics information. Additionally, attention mechanisms with confidence learning are incorporated for enhanced feature representation and trustworthy prediction. Results Extensive experiments were conducted on four benchmark datasets to evaluate the effectiveness of our proposed model, including BRCA, ROSMAP, LGG, and KIPAN. Our model significantly improved most evaluation measurements and consistently surpassed the state-of-the-art methods. Ablation studies showed that the auxiliary classifiers significantly boosted classification accuracy in both the ROSMAP and LGG datasets. Moreover, the attention mechanisms and confidence evaluation block contributed to improvements in the predictive accuracy and generalizability of our model. Conclusions The proposed framework exhibits superior performance in disease classification and biomarker discovery, establishing itself as a robust and versatile tool for analyzing multi-layer biological data. This study highlights the significance of elaborated designed deep learning methodologies in dissecting complex disease phenotypes and improving the accuracy of disease predictions.
In order to ensure the real-time property of the virtual surgery system and improve the model rendering speed, we propose an acceleration collision detection algorithm based on invisible separated surface. Meanwhile, to reduce the local deformation and the loss of important information caused by virtual cutting maximally in the medical preoperative diagnosis and surgery planning, we propose a surface model cutting algorithm on the basis of removing the intersecting grid cell. Under the premise of ensuring the system's real-time property, the algorithm deals the triangle mesh with a series of operation like subdividing, projection and so on. The experimental results show that the collision detection method has improved the action speed of virtual equipment touching with the model surface. The cutting algorithm can be implemented easily and retain the original information better, which is expected to help to improve the accuracy of the diagnosis judged by the doctor according to the patient's condition.
The location of the vehicle plate is the core and most difficult technique in the vehicle plate auto-recognition system. In this paper, a novel algorithm of searching color point-pairs in locating vehicle plate is proposed. On the other hand, to decrease the time used to search the color point-pairs, the edge detection technique of image processing is used to pre-locate the areas the color point-pairs belong to. Through the experiment, it is proved that the algorithm proposed is valid and the results are satisfiable.
"Dragon of puncturing mud" Robot is one kind robot of special type, as it can pave PE pipe, PVC pipe, cable and optical fiber cable under the mud, there are abroad appliance foreground and developing value. This paper presents the characteristics of the world representative air-powered mole of which the direction is controllable. According to the turning principle of "Dragon of Puncturing Mud" Robot, a design scheme is put forward on the robot turning device. Virtual prototype of the robot turning device has been done, swaying principle of the robot head is described and mechanism simulation on the turning device is researched. Kinematics model of "Dragon of puncturing mud" Robot are established and through applying Lagrange function, dynamics model of "dragon of puncturing mud" robot are established, by the robot moving simulation, kinematics equation and dynamic equation can factually reflect the sport rule of "dragon of puncturing mud" robot's whole reality. This paper can provide academic references for selecting power fountain and the engineering appliance of "dragon of puncturing mud" robot.
Underwater images often suffer from color distortion and loss of contrast. This is due to the absorption and scattering of light as it travels through water. Although the physical process of underwater imaging is similar to that of haze images in the air. However, traditional dehazing methods cannot produce good results due to the different attenuation of light under different wavelengths in underwater conditions. To overcome this problem, we propose a novel underwater image restoration method based on local depth information priors. First, we use a computer vision-based multi-view geometry method to estimate the local depth information of the image for parameter estimation of the depth compensation model. According to the characteristics of underwater optical imaging, we introduce an underwater color correction method using depth compensation. Second, we propose a method for estimating the global depth image with local depth information priors. Finally, we adopt the global depth image to recover the underwater image. Experimental results demonstrate that the recovered images can achieve better visual quality of underwater images compared to several state-of-the-art methods.
Color image segmentation has been widely applied to diverse fields in the past decades for containing more information than gray ones. The traditional level set algorithm calculates the level set energy function based on the gray value of the gray image. A level set algorithm based on color space is proposed, which is based on weightings of different channels, and the energy function of the level set is rewritten. The k-means algorithm is used to pre-segment, initialize the level set contour curve and the sign distance function, and achieve the unsupervised segmentation of the algorithm. The steps of the algorithm are given. The adaptability and accuracy of different types of color image are solved. Compared to other popular algorithms, it has the competitive performances both on speed and accuracy. The experiments performed on real-world data sets demonstrate the validity of the proposed algorithm.
This paper presents the constraint dynamic modelling of a six-link elbow-bracing manipulator. This system is kinematically redundant when it is asked to perform spatial trajectory tracking tasks. Hence the extra degrees of freedom (DOFs) can be used to assign additional motion such as constraint forces control without violating end-effect's functions, which can improve the manipulator's performance such as minimizing energy requirements. Since the control of the constraint forces will not affect the end-effect's position, the hybrid force and position control method is proposed. The control scheme consists of two terms: constraint forces control with the incorporation of proportional (p) controller and trajectory tracking control. In addition, the motion equations of motors are incorporated into the constraint dynamics of the system. So that the energy consumption can be calculated by integrating the product of the voltage and current. This study is based on our previous works, which can achieve the control of three constraint forces. Finally, simulation experiments along with comparative studies of previous works such as: with no constraint force and one constraint force are conducted. The results show that the proposed method achieves prior energy-efficient performance and tracking accuracy.
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