Seek for Success: A Visualization Approach for Understanding the Dynamics of Academic Careers.

How to achieve academic career success has been a long-standing research question in social science research. With the growing availability of large-scale well-documented academic profiles and career trajectories, scholarly interest in career success has been reinvigorated, which has emerged to be an active research domain called the Science of Science (i.e., SciSci). In this study, we adopt an innovative dynamic perspective to examine how individual and social factors will influence career success over time. We propose ACSeeker, an interactive visual analytics approach to explore the potential factors of success and how the influence of multiple factors changes at different stages of academic careers. We first applied a Multi-factor Impact Analysis framework to estimate the effect of different factors on academic career success over time. We then developed a visual analytics system to understand the dynamic effects interactively. A novel timeline is designed to reveal and compare the factor impacts based on the whole population. A customized career line showing the individual career development is provided to allow a detailed inspection. To validate the effectiveness and usability of ACSeeker, we report two case studies and interviews with a social scientist and general researchers.

Ecological risk, health risk assessment, and pollution source analysis of Xinli Lake wetland based on triangular fuzzy number.

Wetland environmental pollution has become a global problem involving the ecological environment and human health. This study measured the concentration of seven potentially toxic elements (PTEs Hg, Cd, Zn, Cu, Cr, Pb, and As) in the soil upstream of the Xinli Lake wetland in China. Based on the fuzzy theory, the sources, spatial distribution, ecological risks, and health risks of pollutants are studied. The result shows that the concentrations of the seven potentially toxic elements are close to or exceed the background value, and their spatial distribution showed irregular changes. The soil upstream of the wetland has not been seriously polluted, and Cd, which has higher bioavailability, is the priority element for ecological risk. Pollutants do not harm human health; children face higher health risks; Pb and As have the highest carcinogenic and non-carcinogenic risks, respectively. Zn, Cu, Cr, Pb, and As in the study area are derived from agricultural activities, while Hg and Cd are mainly affected by soil-forming parent materials. Attention should be paid to controlling the intensity of agricultural activities to avoid excessive input and accumulation of pollutants that would harm the ecological environment and human health.

A High Precision Real-time Premature Ventricular Contraction Assessment Method based on the Complex Feature Set.

This paper presents a high precision and low computational complexity premature ventricular contraction (PVC) assessment method for the ECG human-machine interface device. The original signals are preprocessed by integrated filters. Then, R points and surrounding feature points are determined by corresponding detection algorithms. On this basis, a complex feature set and feature matrices are obtained according to the position feature points. Finally, an exponential Minkowski distance method is proposed for PVC recognition. Both public dataset and clinical experiments were utilized to verify the effectiveness and superiority of the proposed method. The results show that our R peak detection algorithm can substantially reduce the error rate, and obtained 98.97% accuracy for QRS complexes. Meanwhile, the accuracy of PVC recognition was 98.69% for the MIT-BIH database and 98.49% for clinical tests. Moreover, benefiting from the lightweight of our model, it can be easily applied to portable healthcare devices for human-computer interaction.