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Introduction Currently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of the algorithm logic, often accompanied by flowcharts. A challenge with this mode of dissemination is the potential for under-specification in the algorithm definition, which leads to ambiguity and vagueness. Methods This study examines incidents of under-specification that occurred during the implementation of 34 narrative phenotyping algorithms in the electronic Medical Record and Genomics (eMERGE) network. We reviewed the online communication history between algorithm developers and implementers within the Phenotype Knowledge Base (PheKB) platform, where questions could be raised and answered regarding the intended implementation of a phenotype algorithm. Results We developed a taxonomy of under-specification categories via an iterative review process between two groups of annotators. Under-specifications that lead to ambiguity and vagueness were consistently found across narrative phenotype algorithms developed by all involved eMERGE sites. Discussion and conclusion Our findings highlight that under-specification is an impediment to the accuracy and efficiency of the implementation of current narrative phenotyping algorithms, and we propose approaches for mitigating these issues and improved methods for disseminating EHR phenotyping algorithms.

Aiming at the problems of complex structure, heavy weight and difficult manufacturing of manipulator, a design scheme of rope-driven three-fingered manipulator is proposed based on bionics principle to meet different functional requirements. The actual motion of the manipulator is controlled by the cable drive and the bending of the distal knuckle is realized by coupling connection. The three-dimensional solid model of the manipulator is established by using the design software, and the motion simulation analysis of the solid model is carried out to obtain its motion law. The results of motion analysis show that the speed of the manipulator changes smoothly in the motion process, and the change of speed has little effect on the stability of the objects grasped by the manipulator. Finally, a prototype of the manipulator is made according to the design results. The prototype model can be used not only in practical teaching, but also in theoretical research. It can provide some reference for the practical application of multi-fingered and multi-joint manipulators.

The identification and compensation of angle kappa is crucial for the centration of the operative zone in corneal refractive surgeries, such as the prevalent Small Incision Lenticule Extraction (SMILE) surgery. However, SMILE still relies on the surgeons’ subjective estimation rather than the precise measurement to compensate for the angle kappa. This may expose potential issues in prior studies of the centration technique in SMILE as well as affect actual surgical outcomes. Therefore, we have developed a method to identify angle kappa based on the surgical machine VisuMax with image recognition with computer vision techniques.

Cognitive radio (CR) is a promising technique for improving the efficiency of utilizing the precious radio spectrum. A cognitive radio network (CRN) testbed not only can verify concepts, algorithms, and protocols for CR, but also can reveal practical problems and guide future research. Vision, architecture, intensive computing, frequency band shifting, security, ultra-wideband receiver and potential applications are discussed in this paper. In support of our arguments, experiments and demonstrations are reported as well.

This is the second paper in a series of using cognitive radio network as wireless sensor network. The motivation of the paper is to push the convergence of radar and communication systems into a unified cognitive network. This paper studies this vision from a secure point of view. We propose two methods for robust spectrum sensing in the same framework of cognitive radio network. The first method is based on robust principal component analysis (PCA), to separate spectrum sensing results into the low rank signal matrix and the sparse attack matrix. Using sparse attack cancellation in least squares, the second method iteratively estimates the relative transmitted power of primary user under the threats of attackers. Then the relative transmitted power of primary user can be calculated from the recovered signal matrix. Both two methods can detect the sparse compromised cognitive radio nodes and effectively obtain the relative transmitted power.