全球化与中国高技术发展战略   总被引：6，自引：1，他引：5  

蒲淳  刘细文 《科学学研究》1999,17(2):46-54

近些年来,全球化已经成为世界各国政府和经济界讨论的热门话题之一。它主要是指世界各国经济走向开放,走向市场化,经济相互依赖,整个世界经济趋向于整合的现象。全球化对于发展中国家的作用,既有积极的一面,也有不利的一面。本文分析了全球化对中国发展高技术及其产业的影响,讨论了中国高技术发展的战略选择。  相似文献   

Museum Informatics and Information Infrastructures: Supporting Collaboration across Intra-Museum Boundaries     

Paul F. Marty 《Archives and Museum Informatics》1999,13(2):169-179

This paper examines the development of an information infrastructure involving collaborative technologies at the Spurlock Museum, a museum of world history and culture at the University of Illinois. It details a socio-technological system that was designed to pack and re-locate 45,000 artifacts across campus to a new museum facility. It addresses the question of how the information infrastructure of the Spurlock promotes collaboration among the various departments at the museum working on this move and encourages the sharing of common data resources across internal museum boundaries.  相似文献   

《武警医学》作者学术不端认知与行为调查分析     

李小萍  武建虎  尤伟杰 《编辑学报》2013,25(1):57-59

为了解医学期刊作者对学术不端的认知及其行为情况,以为更好地防止学术不端提供一些思路和方法,以近2年在《武警医学》发表过文章的作者作为调查对象.调查结果表明:多数作者对学术不端的认识不全面,部分科室学术不端情况比较严重;但多数作者希望共同抵制学术不端行为.  相似文献   

古典与现代融合 人文与环保并重--哈尔滨医科大学图书馆新馆的特色及建设经验     

曲章义  张明伟  史兴伟  张海燕  曹望虹 《大学图书馆学报》2010,28(4):96-101

哈尔滨医科大学图书馆新馆以整体和谐、节能环保和人性化、先进性为设计理念,在建筑风格上体现传统古典与现代创新有机融合,在内饰装修和家具制作上力争做到节能与环保并重、人性化和人文化相互映衬。经过三年多的精雕细琢,打造了一个恢弘古朴、环境优雅、设备先进、功能齐全的精品图书馆,成为学校的标志性景观建筑和学生学习的最佳场所。新馆采取藏、借、阅一体化的"一站式"全开架大流通管理模式,极大地方便了广大师生读者。在出入双向门禁、阅览室读卡识别、阅览桌椅实木材质和节能照明等多个方面为国内首创。  相似文献   

数学建模的专业教学实践与认识   总被引：1，自引：0，他引：1  

谢亮  方勤  黄珍华  熊小兵 《黑龙江高教研究》2004,(12):116-118

开设数学建模课,一方面可以培养学生的数学建模能力,提高学生把专业理论知识运用于实践的能力;另一方面,数学建模课的学习却在一定程度上影响了专业课的学习。因而如何将数学建模思想和方法融入到大学专业主干课程的教学中,是当前数学和专业教学体系、内容、方法改革面临的一个新课题。  相似文献   

Counterfactual can be strong in medical question and answering     

《Information processing & management》2023,60(4):103408

Medical question and answering is a crucial aspect of medical artificial intelligence, as it aims to enhance the efficiency of clinical diagnosis and improve treatment outcomes. Despite the numerous methods available for medical question and answering, they tend to overlook the data generation mechanism’s imbalance and the pseudo-correlation caused by the task’s text characteristics. This pseudo-correlation is due to the fact that many words in the question and answering task are irrelevant to the answer but carry significant weight. These words can affect the feature representation and establish a false correlation with the final answer. Furthermore, the data imbalance mechanism can cause the model to blindly follow a large number of classes, leading to bias in the final answer. Confounding factors, including the data imbalance mechanism, bias due to textual characteristics, and other unknown factors, may also mislead the model and limit its performance.In this study, we propose a new counterfactual-based approach that includes a feature encoder and a counterfactual decoder. The feature encoder utilizes ChatGPT and label resetting techniques to create counterfactual data, compensating for distributional differences in the dataset and alleviating data imbalance issues. Moreover, the sampling prior to label resetting also helps us alleviate the data imbalance issue. Subsequently, label resetting can yield better and more balanced counterfactual data. Additionally, the construction of counterfactual data aids the subsequent counterfactual classifier in better learning causal features. The counterfactual decoder uses counterfactual data compared with real data to optimize the model and help it acquire the causal characteristics that genuinely influence the label to generate the final answer. The proposed method was tested on PubMedQA, a medical dataset, using machine learning and deep learning models. The comprehensive experiments demonstrate that this method achieves state-of-the-art results and effectively reduces the false correlation caused by confounders.  相似文献   

医学人工智能发展态势分析及问题浅析     

申喜凤  李美婷  南嘉乐  张维宁  孙媛媛  车美龄  高东平 《科技管理研究》2023,(7):193-198

为探究医学人工智能发展态势以及我国医学人工智能存在的问题，从医学人工智能领域论文、临床试验、医疗器械产品3个维度进行态势分析，量化分析结果显示我国和全球医学人工智能发表论文数量均呈迅速增长趋势，发文数量及高被引论文方面我国处于国际前列；人工智能临床试验开展数量和面向疾病种类较多，但临床试验注册质量有待提高；我国人工智能医疗器械获批数量逐年增加，医疗人工智能产品认证稳步推进。医学人工智能发展的同时在理论层面、技术层面、伦理法律层面以及应用层面依旧面临着诸多问题和挑战。  相似文献