Purpose: The aim of this paper is to develop a standardized and reliable measurement tool for assessing information-seeking behavior of undergraduate students.Design/methodology/approach: Based on information literacy...Purpose: The aim of this paper is to develop a standardized and reliable measurement tool for assessing information-seeking behavior of undergraduate students.Design/methodology/approach: Based on information literacy and information-seeking behavior theories, expert advice and students' interview, items of undergraduates' informationseeking behavior indicators were selected. With the analysis of homogeneity reliability, item analysis and factor analysis, this study constructs an assessment system to evaluate reliability and validity of the scale.Findings: The information-seeking behavior scale for undergraduates has divided undergraduates' information-seeking behavior into seven dimensions, which include 46 items. The reliability analysis of Cronbach's α was 0.910, and the coefficient of split-half reliability was0.817. The results of factor analysis showed that Kaiser-Meyer-Olkin(KMO) was 0.864,which indicates 55.536% of the total variation could be explained by the above seven dimensions.Research limitations: Due to a small sample size and limited sample distribution, further research need be conducted in an expanded sample size in order to explore the application scope of this evaluation system; in addition, the stability of the scale also need be confirmed.Practical implications: The paper sets up an information-seeking behavior evaluation system for undergraduates and explores the characteristics of their information-seeking behavior.This study provides guidance for the development of future information literacy education and the improvement of the information literacy level of undergraduates.Originality/value: An information-seeking behavior scale for undergraduates has been developed, which comprehensively covers information need, information source, information evaluation, information retrieval, information management, information utilization and information morality. The scale is proved to have good reliability, validity, popularity anddiscrimination that it is qualified to be an assessment tool of information-seeking behavior for Chinese undergraduates.展开更多
To eliminate unnecessary background information,such as soft tissues in original CT images and the adverse impact of the similarity of adjacent spines on lumbar image segmentation and surgical path planning,a two‐sta...To eliminate unnecessary background information,such as soft tissues in original CT images and the adverse impact of the similarity of adjacent spines on lumbar image segmentation and surgical path planning,a two‐stage approach for localising lumbar segments is proposed.First,based on the multi‐scale feature fusion technology,a non‐linear regression method is used to achieve accurate localisation of the overall spatial region of the lumbar spine,effectively eliminating useless background information,such as soft tissues.In the second stage,we directly realised the precise positioning of each segment in the lumbar spine space region based on the non‐linear regression method,thus effectively eliminating the interference caused by the adjacent spine.The 3D Intersection over Union(3D_IOU)is used as the main evaluation indicator for the positioning accuracy.On an open dataset,3D_IOU values of 0.8339�0.0990 and 0.8559�0.0332 in the first and second stages,respectively is achieved.In addition,the average time required for the proposed method in the two stages is 0.3274 and 0.2105 s respectively.Therefore,the proposed method performs very well in terms of both pre-cision and speed and can effectively improve the accuracy of lumbar image segmentation and the effect of surgical path planning.展开更多
基金supported by the National Social Science Foundation of China(Grant No.:11BTQ044)the Innovative Training Program for College Students in Changsha University(Grant No:CW11255)
文摘Purpose: The aim of this paper is to develop a standardized and reliable measurement tool for assessing information-seeking behavior of undergraduate students.Design/methodology/approach: Based on information literacy and information-seeking behavior theories, expert advice and students' interview, items of undergraduates' informationseeking behavior indicators were selected. With the analysis of homogeneity reliability, item analysis and factor analysis, this study constructs an assessment system to evaluate reliability and validity of the scale.Findings: The information-seeking behavior scale for undergraduates has divided undergraduates' information-seeking behavior into seven dimensions, which include 46 items. The reliability analysis of Cronbach's α was 0.910, and the coefficient of split-half reliability was0.817. The results of factor analysis showed that Kaiser-Meyer-Olkin(KMO) was 0.864,which indicates 55.536% of the total variation could be explained by the above seven dimensions.Research limitations: Due to a small sample size and limited sample distribution, further research need be conducted in an expanded sample size in order to explore the application scope of this evaluation system; in addition, the stability of the scale also need be confirmed.Practical implications: The paper sets up an information-seeking behavior evaluation system for undergraduates and explores the characteristics of their information-seeking behavior.This study provides guidance for the development of future information literacy education and the improvement of the information literacy level of undergraduates.Originality/value: An information-seeking behavior scale for undergraduates has been developed, which comprehensively covers information need, information source, information evaluation, information retrieval, information management, information utilization and information morality. The scale is proved to have good reliability, validity, popularity anddiscrimination that it is qualified to be an assessment tool of information-seeking behavior for Chinese undergraduates.
基金Original Innovation Joint Fund:L202010 and the National Key Research and Development Program of China:2018YFB1307604National Key Research and Development Program of China,Grant/Award Numbers:2018YFB1307604。
文摘To eliminate unnecessary background information,such as soft tissues in original CT images and the adverse impact of the similarity of adjacent spines on lumbar image segmentation and surgical path planning,a two‐stage approach for localising lumbar segments is proposed.First,based on the multi‐scale feature fusion technology,a non‐linear regression method is used to achieve accurate localisation of the overall spatial region of the lumbar spine,effectively eliminating useless background information,such as soft tissues.In the second stage,we directly realised the precise positioning of each segment in the lumbar spine space region based on the non‐linear regression method,thus effectively eliminating the interference caused by the adjacent spine.The 3D Intersection over Union(3D_IOU)is used as the main evaluation indicator for the positioning accuracy.On an open dataset,3D_IOU values of 0.8339�0.0990 and 0.8559�0.0332 in the first and second stages,respectively is achieved.In addition,the average time required for the proposed method in the two stages is 0.3274 and 0.2105 s respectively.Therefore,the proposed method performs very well in terms of both pre-cision and speed and can effectively improve the accuracy of lumbar image segmentation and the effect of surgical path planning.
