An Analytic Method for the Kinematics and Dynamics of a Multiple-Backbone Continuum RobotBin He, Zhipeng Wang, Qiang Li et al.|International Journal of Advanced Robotic Systems|2013 Continuum robots have been the subject of extensive research due to their potential use in a wide range of applications. In this paper, we propose a new continuum robot with three backbones, and provide a unified analytic method for the kinematics and dynamics of a multiple-backbone continuum robot. The robot achieves actuation by independently pulling three backbones to carry out a bending motion of two-degrees-of-freedom (DoF). A three-dimensional CAD model of the robot is built and the kinematical equation is established on the basis of the Euler-Bernoulli beam. The dynamical model of the continuum robot is constructed by using the Lagrange method. The simulation and the experiment's validation results show the continuum robot can exactly bend into pre-set angles in the two-dimensional space (the maximum error is less than 5% of the robot length) and can make a circular motion in three-dimensional space. The results demonstrate that the proposed analytic method for the kinematics and dynamics of a continuum robot is feasible.
Mapping and Evaluating the Urbanization Process in Northeast China Using DMSP/OLS Nighttime Light DataIn this paper, an Urban Light Index (ULI) is constructed to facilitate analysis and quantitative evaluation of the process of urbanization and expansion rate by using DMSP/OLS Nighttime Light Data during the years from 1992 to 2010. A unit circle urbanization evaluation model is established to perform a comprehensive analysis of the urbanization process of 34 prefecture-level cities in Northeast China. Furthermore, the concept of urban light space is put forward. In this study, urban light space is divided into four types: the core urban area, the transition zone between urban and suburban areas, suburban area and fluorescent space. Proceeding from the temporal and spatial variation of the four types of light space, the pattern of morphologic change and space-time evolution of the four principal cities in Northeast China (Harbin, Changchun, Shenyang, Dalian) is analyzed and given particular attention. Through a correlation analysis between ULI and the traditional urbanization indexes (urban population, proportion of the secondary and tertiary industries in the regional GDP and the built-up area), the advantages and disadvantages as well as the feasibility of using the ULI in the study of urbanization are evaluated. The research results show that ULI has a strong correlation with urban built-up area (R2 = 0.8277). The morphologic change and history of the evolving urban light space can truly reflect the characteristics of urban sprawl. The results also indicate that DMSP/OLS Nighttime Light Data is applicable for extracting urban space information and has strong potential to urbanization research.
Optimize Transfer Learning for Lung Diseases in Bronchoscopy Using a New Concept: Sequential Fine-TuningTao Tan, Zhang Li, Haixia Liu et al.|IEEE Journal of Translational Engineering in Health and Medicine|2018 Bronchoscopy inspection, as a follow-up procedure next to the radiological imaging, plays a key role in the diagnosis and treatment design for lung disease patients. When performing bronchoscopy, doctors have to make a decision immediately whether to perform a biopsy. Because biopsies may cause uncontrollable and life-threatening bleeding of the lung tissue, thus doctors need to be selective with biopsies. In this paper, to help doctors to be more selective on biopsies and provide a second opinion on diagnosis, we propose a computer-aided diagnosis (CAD) system for lung diseases, including cancers and tuberculosis (TB). Based on transfer learning (TL), we propose a novel TL method on the top of DenseNet: sequential fine-tuning (SFT). Compared with traditional fine-tuning (FT) methods, our method achieves the best performance. In a data set of recruited 81 normal cases, 76 TB cases and 277 lung cancer cases, SFT provided an overall accuracy of 82% while other traditional TL methods achieved an accuracy from 70% to 74%. The detection accuracy of SFT for cancers, TB, and normal cases are 87%, 54%, and 91%, respectively. This indicates that the CAD system has the potential to improve lung disease diagnosis accuracy in bronchoscopy and it may be used to be more selective with biopsies.