月月友

.A development team with both strength and technology.

项目简介:月月友平台是一个以数据统计分析为主的,改善因非病理性因素引起的月经不适的平台。本平台不仅具有基本经期预测和记录的功能;还能定期更新妇科知识的短视频,同时,用户还可以通过实时弹幕进行讨论;以推送文章的形式帮助女性更好地应对轻微不适;除此之外,还运用简单的数据分析,让用户了解到不同的外界刺激对女性经期的影响程度,并且借助地理布局展示出来。本平台特点之处在于以发送弹幕的形式给用户提供一个在线经验分享的机会,用简单的数据对比分析出外界因素对经期的干扰性,并使用图表和地理分布等可视化数据展示给用户。
项目链接:www.moonlet.cn
项目作者:熊飞燕、余浩、卫笑

基于FastNewman算法的肥胖症辨证论治中核心中药及配伍研究

.A development team with both strength and technology.

项目简介:探讨中医治疗肥胖症的核心中药及其配伍规律。方法: 基于文献挖掘收集并整理出 230 例中医诊疗肥胖症的辨 证处方, 采用复杂网络中的节点中心性评估和聚类分析等方法, 首先通过构建“中药”网络模型, 引入复杂网络节点中心性分析思 想, 对“中药”节点进行多角度评估计算, 挖掘核心中药节点。其次, 选取复杂网络聚类算法 FastNewman 对中药网络进行聚类分 析, 探究中药之间的组合规律。结果: “茯苓”“白术”“陈皮”“山楂”和“泽泻”等是诊疗肥胖症最常使用的药物, “白术”“泽泻”与 “茯苓”为最常配

SA-SOM algorithm for detecting communities in complex networks

.A development team with both strength and technology.

项目简介:SA-SOM algorithm for detecting communities in complex networks, Modern Physics Letter B, 2017, 31(29) : 1750262 (17 pages). (SCI).(参与作者:王嫣然Yanran Wang, 黄小敏Xiaoming Huang, 胡梦宇Mengyu Hu)

逍遥纸鸢

.A development team with both strength and technology.

项目简介:纸鸢来自于民间发扬于民间,从中国东周春秋时期,至今已两千多年。风筝,古时称为「鹞」,北方谓「鸢」。 直至东汉期间,蔡伦发明造纸术后,坊间才开始以纸做风筝,称为「纸鸢」,本次的作品名字从此而来。由此便发生了一系列的联想,从纸鸢的分类、造型、主题来制作了后续的三张典型风筝类型的图形图像设计。
项目链接:暂无
项目作者:美工组

中医绿皮书

.A development team with both strength and technology.

项目简介: “中医绿皮书”是一款基于APICloud平台设计实现的一款针对学生课后巩固的移动客户端,包含题库、讲堂、兴趣圈三大模块,主要实现习题练习与观看名师讲堂的功能,旨在保证学生对讲课内容的理解与知识点的记忆,另有兴趣圈功能培养学生的思维和学习兴趣,提高学生的学习主动性以及学习效率。为医学生提供最新的题库与视频。
项目链接:暂无
项目作者:徐良钰、谭安佳、陈扬义

易小二

.A development team with both strength and technology.

项目简介:本系统是基于Acpicloud平台设计实现的二手交易平台的移动客户端,包含首页、商品分类、购物车、订单管理、商品上架和个人信息六大模块,主要实现二手交易功能,旨在为校园内的二手交易市场提供安全、合法、严格的审核机制,优化校园内二手交易的交易流程,提高二手交易过程的效率。
项目链接:暂无
项目作者:鄢亮、杨海旖、吴雅楠

中医健康管理

.A development team with both strength and technology.

项目简介:中医健康管理系统APP实现了集健康生活、健康服务、健康百科为一体的知识库型移动健康管理应用。该系统虽然不能解决人们看病难、看病贵的问题,但根据中医预防治未病的理念和整体观,在日常生活中注意健康饮食、健康运动、健康睡眠,知晓健康常识,从日常细节中注意个人健康及保健,无疑将提高人们的健康状况,降低发病率。因此该APP以纯净为特点作为人们日常生活的小百科依然有较大的开发价值。
项目链接:暂无
项目作者:向金伟、彭子雄、李敏

青囊相助

.A development team with both strength and technology.

项目简介:本系统是基于Android平台设计实现的青囊相助的移动客户端,包含药物使用手册、中药处方库、药物配伍禁忌和体质分析四大模块,主要实现知识浏览功能,旨在增强学生的自学能力,培养学生的学习兴趣,提高学生的学习主动性以及学习效率。
项目链接:暂无
项目作者:安卓组

舌诊辅助医疗系统

.A development team with both strength and technology.

项目简介:本系统是一个安卓版的舌象辅助诊断系统,主要运用于中医电子病历系统之中,大致功能是:医生通过自主选择舌质等部位的主要特征,形成一个舌部诊断代码,然后提交到数据库进行匹配,最后返回相对准确的舌部诊断供医生使用。其主要意义在于:解决了舌诊数据规范化程度低,难于量化与重复这一主要问题;打破了医生只能依据视觉及临床经验来进行诊断这一常规,减轻了医生的负担;且本系统可移植性强,能嵌入到多种系统之中重复使用。
项目链接:暂无
项目作者:肖云、曾山、夏龙龙、李艳、高杰

校园淘

.A development team with both strength and technology.

项目简介:校园淘二手商品交易平台是电子商务的一种具体应用,是一个虚拟化的市场,借助互联网为需求双方提供一个快捷方便的交易平台。凡是想要在网上买卖二手商品的人,只要在校园淘二手商品交易网上注册,找到或发布需要交易的商品,留下相应的信息,买卖双方取得联系即可进行交易。相对于现实中,客户需要大量的时间,花费大量的精力,都未必能买到称心如意的二手商品。
项目链接:暂无
项目作者:安卓组

掌上大学城

.A development team with both strength and technology.

项目简介:“掌上大学城APP”是一款基于Android系统、以高校校园用户为核心的移动信息服务手机软件,现正在试运营中,该APP上所有的功能实现及信息发布都是以方便大学生生活为基本出发点,力求做到深入校园生活,方便大学生生活,改变大学生生活,为大学城师生提供独特方便快捷的生活方式!
项目链接:暂无
项目作者:夏龙龙、李艳、高杰、张颖、刘东仪、阮斯炜

时至孕来

.A development team with both strength and technology.

项目简介:“时至孕来”APP将孕妇相关医学知识与移动互联网相结合,基于Android平台,设计和实现可以为孕妇提供孕妇健康资讯、育儿资讯、孕妇心理咨询与测评以及定期检查提醒等服务的移动应用程序,以人为本,旨在为孕妇这一特殊群体提供辅助性的健康知识和意见,实现个性化的健康医疗资讯服务,让孕妇可以健康平安地度过孕期,成功分娩。
项目链接:暂无
项目作者:安卓组

中医美容

.A development team with both strength and technology.

项目简介:随着科学技术的不断发展,互联网已经逐步融入了人们的生活并成为第一大媒体;移动智能终端设备功能也不停的推陈出新而日趋强大。人们获取信息的途径及方法随着移动互联网时代的到来变得更加便捷及多样化,信息传播的方式也在原有的基础上得到了不断的拓宽。 本系统抓住这个最佳时机将中医这一传统行业推陈出新,开发中医美容养生APP,实现了针灸美容、药膳美容、气功美容和按摩美容方法推荐,3D穴位图预览,体质测试等功能,使用户在辨证论治理论与中医整体观念指导下,根据自己的体质选择合适的调养方法,运用药膳改善或恢复机体的生理功能。 本系统在设计过程中使用APICloud Studio作为开发环境,APICloud作为开发平台,APICloud云数据库作为数据库,并通过JavaScript语言同时调用iOS和Android两个平台的模块,实现iOS与Android跨平台APP。
项目链接:暂无
项目作者:安卓组

流浪汉字

.A development team with both strength and technology.

项目简介: 汉字是我国最古老的文化之一,汉字因为时代的改变而不断改变着,我们的作品是想要将汉字的发展和文化带进我们现代的生活中来,古时女子多爱首饰物件,至今也不变,我们的作品将汉字与物件融合在一起,既有现代的特点,又承载着文化的发展,将汉字发展呈现眼前。
项目链接:暂无
项目作者:美工组

檀木香挂坠

.A development team with both strength and technology.

项目简介: 檀木香挂坠外形耐看,以黑檀木为材料,圆饼状,外部金乌阴阳八卦纹案寓意平安美好,内部设计精巧,可装多种芳香气味的中草药研制细末,有益身体健康。可拆卸更换香料。可挂至房间,车内。实用性、观赏性都是极高的。
项目链接:暂无
项目作者:美工组

鱼莲纹银香囊

.A development team with both strength and technology.

项目简介:香囊又名香袋、花囊。有各种古老神奇、博大精深的图案纹饰,形状各异、大小不等,内可装多种芳香气味的中草药研制细末。香囊长约十厘米,宽五厘米,厚二厘米。 金属香囊具有外形耐看使用等特点,内部设计精巧,既可随身佩戴,又可挂至床头。其悠久的文化底蕴与其自身精致的外表相得益彰,配合多种中草药有益于身体健康,实用性、观赏性都是极高的。
项目链接:暂无
项目作者:美工组

跳蚤屋

.A development team with both strength and technology.

项目简介: 为大学生提供二手物品的详细信息,目前无法核实个人信息,因此只限于信息提供
项目链接:暂无
项目作者:网站组

糖友之家

.A development team with both strength and technology.

项目简介:《糖友之家》是一个以网站为形式的针对广大人群的糖尿病知识普及和防控平台。众 所周知,科学健康的饮食习惯对于防治糖尿病有重要作用,所以本平台从日常饮食入手, 注重血糖的监测与控制,来防治糖尿病。
项目链接:暂无
项目作者:网站组

智慧南山

.A development team with both strength and technology.

项目简介:“智慧养老院管理服务平台”基于物联网技术,为养老机构提供智能化信息管理设备和服务平台,彻底避免了信息系统重复构建、维护实施成本高、信息孤岛和资源难以整合的弊病。 基于人员、物品定位信息衍生出来的各种服务,也大幅提升了养老机构的管理效率和护理质量,同时实现对养老机构内相关人员、设备器械(医疗检测设备、办公设备、护理设备等)和物品(药品、医用垃圾、安全设备、消防设备等)的动态、实时的追踪管理。
项目链接:暂无
项目作者:网站组

期刊投稿与评审平台AGER

.A development team with both strength and technology.

项目简介:本项目主要征集关于能量技术和地理科学方面地论文,本网站页面为英文页面,同时对投稿者从论文的书写,编辑,和审阅做了多方面的指导
项目链接:www.astp-agr.com
项目作者:网站组

中医美容

.A development team with both strength and technology.

项目简介:为广大爱美人士提供专业指导,分为肤质检测,食谱推荐,中医美容,联系我们,为美丽的您提供更美丽的服务。
项目链接:暂无
项目作者:网站组

医学辩论平台

.A development team with both strength and technology.

项目简介:本项目主要关注医学医疗领域的常见问题,引导大众关注医疗问题,关心医学发展。本项目的主要目的,是组织对医学医疗领域问题的辩论,使大众通过平台,发布自己的看法,意见和建议。
项目链接:暂无
项目作者:网站组

医食吾忧

.A development team with both strength and technology.

项目简介: 关注中医亚健康,为亚健康人群提供持续疗养的健康食谱。
项目链接:暂无
项目作者:网站组

国家海洋局第一海洋研究所

.A development team with both strength and technology.

项目简介: 海水入侵与土壤盐渍化课题组
项目链接:www.soasi.org.cn
项目作者:网站组

大学生信息发布平台

.A development team with both strength and technology.

项目简介: 本项目专注于大学校园的信息发布,旨在为各个社团,学校同学提供更好的信息发布,信息推送,信息交流服务。
项目链接:暂无
项目作者:网站组

药材辨识平台

.A development team with both strength and technology.

项目简介:本项目以中草药辨识为主题,旨在帮助广大医药专业学习者在众多浩如烟海的草药中快速识别和记忆。
项目链接:暂无
项目作者:网站组

Computing communities in complex networks using the Dirichlet processing Gaussian mixture model with(SCI)

.A development team with both strength and technology.

项目简介: Community detection becomes a significant tool for the complex network analysis. The study of the community detection algorithms has received an enormous amount of attention. It is still an open question whether a highly accurate and efficient algorithm is found in most data sets. We propose the Dirichlet Processing Gaussian Mixture Model with Spectral Clustering algorithm for detecting the community structures. The combination of traditional spectral algorithm and new non-parametric Bayesian model provides high accuracy and quality. We compare the proposed algorithm with other existing community detecting algorithms using different real-world data sets and computer-generated synthetic data sets. We show that the proposed algorithm results in high modularity, and better accuracy in a wide range of networks. We find that the proposed algorithm works best for the large size of the data sets.
项目链接:暂无
项目作者:李刘欢Liuhuan Li, 梁俊Jun Liang

On Herb Compatibility Rule of Insomnia Based on Machine Learning Approaches

.A development team with both strength and technology.

项目简介:Abstract—Recent research in machine learning has led to significant progress in various research fields. Especially, the knowledge discovery using this method in Traditional Chinese Medicine (TCM) has been becoming a hot topic. In this paper, we studied on the herb compatibility rule of insomnia using some machine learning approaches. We have extracted insomnia data set with 807 samples from the real-world Electronic Medical Records (EMRs). After cleaning and selecting the theme data referring to the prescriptions and their herbs, we constructed the herb network analysis model using the theory of complex network. In order to explore the hidden relationships among the herbs, we trained each herb node in network to obtain the herb embeddings using the Skip-Gram model in word embedding theory. After acquiring the vocabulary of herbs with the formation of vectors, we calculated the similarity among any two herb embeddings, and clustered these herb embeddings into seven communities using the Spectral Clustering (SC) algorithm. The experimental results shed light on that the methodologies used in this paper can objectively and effectively discover the relationships among herbs, and reveal the herb compatibility and herb clusters for clinical treatment research of insomnia. Index Terms—Insomnia, Core Herb, Herb Community, Word Embedding, Spectral Clustering Algorithm
项目链接:暂无
项目作者:李刘欢Liuhuan Li

Sedimentary Environment Analysis by Grain-Size Data Based on Mini Batch K-Means Algorithm (SCI)

.A development team with both strength and technology.

项目简介:During the last several decades, researchers have made significant advances in sedimentary environment interpretation of grainsize analysis, but these improvements have often depended on the subjective experience of the researcher and were usually combined with other methods. Currently, researchers have been using a larger number of data mining and knowledge discovering methods to explore the potential relationships in sediment grain-size analysis. In this paper, we will apply bipartite graph theory to construct a Sample/Grain-Size network model and then construct a Sample network model projected from this bipartite network. Furthermore, we will use the Mini Batch K-means algorithm with the most appropriate parameters (reassignment ratio ϵ = 0 025 and mini batch = 25) to cluster the sediment samples. We will use four representative evaluation indices to verify the precision of the clustering result. Simulation results demonstrate that this algorithm can divide the Sample network into three sedimentary categorical clusters: marine, fluvial, and lacustrine. According to the results of previous studies obtained from a variety of indices, the precision of experimental results about sediment grain-size category is up to 0.92254367, a fact which shows that this method of analyzing sedimentary environment by grain size is extremely effective and accurate.
项目链接:暂无
项目作者:(学生):朱延辉Yanhui Zhu,贾雅琳Yalin Jia

基于CNM-Centrality算法的失眠症辩证论治中核心中药及配伍研究

.A development team with both strength and technology.

项目简介:基于CNM-Centrality算法的失眠症辩证论治中核心中药及配伍研究,中草药, 2017, 48(18): 3897-3900. (中文核心期刊)
项目链接:暂无
项目作者:王嫣然(第一作者),王明珠,胡梦宇等

Symptom Distribution Regulation of Core Symptoms in Insomnia based on Infomap-SA Algorithm

.A development team with both strength and technology.

项目简介:Symptom Distribution Regulation of Core Symptoms in Insomnia based on Infomap-SA Algorithm, 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES2017), IEEE, Anyang, China, October 13-16, 2017, 210-213 (EI).
项目链接:暂无
项目作者:乔雨露Yulu Qiao, 朱延辉Yanhui Zhu, 贾雅琳Yalin Jia

An Alogrithm Q-PSO for Community Detection in Complex Networks

.A development team with both strength and technology.

项目简介:An Alogrithm Q-PSO for Community Detection in Complex Networks, 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES2017), IEEE, Anyang, China, October 13-16, 2017, 68-71 (EI).
项目链接:暂无
项目作者:史远Yuan Shi, 朱友泽Youze Zhu, 乔雨露Yulu Qiao

Acupoint selection principles in acupuncture and moxibustion for obesity based on Q-PSO algorithm

.A development team with both strength and technology.

项目简介:To explore core acupoints and acupoint selection principles in acupuncture and moxibustion for obesity. from syndrome differentiation prescriptions of the acupuncture- moxibustion therapy in 808 obesity prescriptions. by using node centrality and cluster analysis methods in complex network. Metliods: Firstly. an acupoint network model is established. and acupoint nodes are assessed and calcu- lated in multiple aspects by introducing the node centrality analysis idea of complex network. to excavate core acupoint nodes. Secondly, a cluster analysis is carried out on acupoint network by the cluster algo- rithm Q—P50 in complex network. to investigate the acupoint combination principles.
项目链接:暂无
项目作者:李刘欢Liuhuan Li

基于二分图的疾病与中药关联性研究

.A development team with both strength and technology.

项目简介:基于二分图的疾病与中药关联性研究,世界科学技术——中医药现代化,2016,18(4):575-581.(科技核心期刊)
项目链接:暂无
项目作者:李梦箐(第一作者),朱友泽等

An algorithm J-SC for detecting communities in Complex Networks(SCI)

.A development team with both strength and technology.

项目简介:Currently, community detection in complex networks has become a hot-button topic. In this paper, based on the Spectral Clustering (SC) algorithm, we introduce the idea of Jacobi iteration, and then propose a novel algorithm J-SC for community detection in complex networks. Furthermore, the accuracy and efficiency of this algorithm are tested by some representative real-world networks and several computergenerated networks. The experimental results indicate that the J-SC algorithm can accurately and effectively detect the community structure in these networks. Meanwhile, compared with the state-ofthe-art community detecting algorithms SC, SOM, K-means, Walktrap and Fastgreedy, the J-SC algorithm has better performance, reflecting that this new algorithm can acquire higher values of modularity and NMI. Moreover, this new algorithm has faster running time than SOM and Walktrap algorithms.
项目链接:暂无
项目作者:王明珠Mingzhu Wang, 王嫣然Yanran Wang, 洪哲昊Zhehao Hong, 朱延辉Yanhui Zhu

An algorithm Walktrap-SPM for detecting overlapping community structure(SCI)

.A development team with both strength and technology.

项目简介:In this paper, based on Walktrap algorithm with the idea of random walk, and by selecting the neighbor communities, introducing improved signed probabilistic mixture (SPM) model and considering the edges within the community as positive links and the edges between the communities as negative links, a novel algorithm Walktrap-SPM for detecting overlapping community is proposed. This algorithm not only can identify the overlapping communities, but also can greatly increase the objectivity and accuracy of the results. In order to verify the accuracy, the performance of this algorithm is tested on several representative real-world networks and a set of computer-generated networks based on LFR benchmark. The experimental results indicate that this algorithm can identify the communities accurately, and it is more suitable for overlapping community detection. Compared with Walktrap, SPM and LMF algorithms, the presented algorithm can acquire higher values of modularity and NMI. Moreover, this new algorithm has faster running time than SPM and LMF algorithms.
项目链接:暂无
项目作者:朱友泽Youze Zhu, 史远Yuan Shi

AGER期刊投稿与评审平台 Advances in Geo-Energy Research

.A development team with both strength and technology.

项目简介: 本项目主要征集关于能量技术和地理科学方面地论文,本网站页面为英文页面,同时对投稿者从论文的书写,编辑,和审阅做了多方面的指导
项目链接:www.yandy-ager.com
项目作者:网站组

戏曲版十二生肖

.A development team with both strength and technology.

项目简介:十二生肖文化和戏曲文化两种中华传统文化元素相结合而成的身着特色戏曲服饰的戏曲版十二生肖形象。作品通过生肖动物形象特征、民间评价、民间神话与戏曲行当外貌特征、行当特点、历史故事等进行比对,两两相匹配。
项目链接:暂无
项目作者:美工组

广寒宫

.A development team with both strength and technology.

项目简介:广寒宫,淡雅宁静,极具出世的书香气,将其实体化,添加精致的细节,以月宫,月,玉兔为元素,做成桌面 微景观(摆件)。在月宫中有一只玉兔,显得灵动活泼,它对月捣药。药即中药,我们设 置中药香薰,好闻又健康。一系列摆件,精致好看,有观赏价值。 适用于多种场景,体现历史文化的同时传播中医药之美。
项目链接:暂无
项目作者:美工组

心安勿梦

.A development team with both strength and technology.

项目简介:心安勿梦是一个中医药类失眠诊治网站,针对疫情期间患创伤后应激障碍(PTSD)的失眠 人群的不同失眠症状和证候,网站将提供相关量表测试,进行辨证分型,帮助人们分析自身的 PTSD 指数和睡眠情况,并给出相应的治疗方案。
项目链接:暂无
项目作者:陶嘉懿、许淑雨、李莉

餐餐可营

.A development team with both strength and technology.

项目简介:“餐餐可营”是一款关于健康饮食的美食平台,餐餐要营养,餐餐要经营,才可赢在生活,赢在朝夕。平台基于对用户全方面的膳食调查,为不同用户提供合理多样化的饮食推荐,为更多的用户提供更多的膳食选择。在为用户丰富菜单的同时,平台还提供了菜品的做法,节省了用户寻找烹饪方式和食材的时间。同时平台附上了“膳食小贴士”,避免饮食禁忌引起的不适。“我们寄托在美食上的不仅仅是味蕾的享受,有时候更多的反而是味道带来的记忆。”我们抱着这样的态度做出了这款网站,希望能够让用户从一日三餐中收获爱与健康。
项目链接:meal.daieq.cn
项目作者:文隽然、李歆妤、金叶

显而易健

.A development team with both strength and technology.

项目简介:本项目以中医传统健身为主题,同时以中医茶饮辅之,旨在为各年龄层次人群提供中医健身的信息,以便进行锻炼养生。
项目链接:dy.stuctft.cn
项目作者:杜勇、方小能、高宝云

穴益生

.A development team with both strength and technology.

项目简介:“穴益生”是基于APICloud平台设计开发的一款面向大众,传播中医保健文化知识的移动客户端,主要为用户提供养生健康指导、穴位保健以及向大众科普中医药知识和一些常见疾病的预防和治疗方法。客户端内置了一个3D人体模型能够清晰展示了人体的各个穴位、内置的按摩手法教学简单易学能够让用户更快速得获取需要的知识和技能,此外首页还会根据用户需求定制化推送食疗,艾灸的养生小知识,提升用户的使用体验。
项目链接:暂无
项目作者:安卓组

美食每Calorie

.A development team with both strength and technology.

项目简介:“美食每 Calorie”是基于 APICloud 平台设计开发的一款面向大众,传播中医健康饮食文化的校园外卖移动客户端,其包含首页、周围、订单和个人中心四大模块,主要为用户提供提前点餐从而避免排队、健康订餐指导、营养膳食搭配以及向大众科普饮食知识和一些常见疾病的预防和治疗方法,提供更好的用户体验,可让用户更加便捷的点餐、规划饮食以及了解健康饮食信息。
项目链接:暂无
项目作者:安卓组

皮影戏

.A development team with both strength and technology.

项目简介:皮影戏,是一种以兽皮或纸板做成的人物剪影以表演西游故事,表面上讲的是降妖除魔,但内涵却是影射人间,天庭与西天表面和谐,背地里勾心斗角,实际上就是人与人之间、派与派之间的关系。
项目链接:暂无
项目作者:美工组

冬奥城市邮票

.A development team with both strength and technology.

项目简介:《冬奥城市邮票》由九张邮票组成,以冬奥各项目运动员比赛的风姿为主体,北京标志建筑为背景,运动员的朝气与首都的生机交相辉映,既表现了冬奥会的运动精神,又体现了冬奥城市的文化底蕴和出色发展。是文化自信的表现!
项目链接:暂无
项目作者:美工组

清 瑞兽迎冬奥

.A development team with both strength and technology.

项目简介:《清 瑞兽迎冬奥》所创作出的是参加2020年北京冬季奥运会的古代五大瑞兽,他们身着清代八旗兵甲电以运动员的专业技术动作表现冬季奥运会的运动项目通过作品画面星现出冬奥会的精彩,非凡、卓越。
项目链接:暂无
项目作者:美工组

枫叶-蝴蝶-游方

.A development team with both strength and technology.

项目简介:本作品设计灵感来源于中国非物质文化遗产苗绣和西湖绸伞。将苗绣元素经过设计与重上色,置于绸伞伞面表现文化与色彩的碰撞。作品根据苗族传说分为三部分:古枫树诞生蝴蝶妈妈,蝴蝶妈妈与水中的游方(水泡)相恋生下人类始祖姜央。 本作品设计灵感来源于中国非物质文化遗产苗绣和西湖绸伞。将苗绣元素经过设计与重上色,置于绸伞伞面表现文化与色彩的碰撞。作品根据苗族传说分为三部分:古枫树诞生蝴蝶妈妈,蝴蝶妈妈与水中的游方(水泡)相恋生下人类始祖姜央。 本作品设计灵感来源于中国非物质文化遗产苗绣和西湖绸伞。将苗绣元素经过设计与重上色,置于绸伞伞面表现文化与色彩的碰撞。作品根据苗族传说分为三部分:古枫树诞生蝴蝶妈妈,蝴蝶妈妈与水中的游方(水泡)相恋生下人类始祖姜央。
项目链接:暂无
项目作者:美工组

养生苑

.A development team with both strength and technology.

项目简介:本项目以测试用户体质并根据体质推荐出相应的医疗方法为主题,可视化展示中药,证候与症状,同时展示症状与中药之间的关联关系,提供体质测试记录和用户自身症状。旨在提高人们身体素质。
项目链接:暂无
项目作者:邬朝磊、周心熠、辛白雪

医岁集-中医古籍智能检索平台

.A development team with both strength and technology.

项目简介:医岁集-中医古籍智能检索平台是在加强中医药古籍经典的应用推广的背景下,基于中医 药古籍的知识关联性,为用户提供古籍的内容搜索功能,实现智能检索,并以朝代为节点, 动态地展示了各时期中医药古籍的发展历程。
项目链接:暂无
项目作者:张利江、胡雪萍、廖志凯

深耕红色印记—窑洞变奏曲

.A development team with both strength and technology.

项目简介:深耕红色印记—窑洞变奏曲通过窑洞灯火、窑洞文化、窑洞之旅、窑洞故事四大功能镌刻文化瑰宝、赓续红色血脉,以“发扬革命精神,答好新时代窑洞对”为主题,将窑洞红色历史与人文旅游相结合,规划导览路线,通过作答方式引导红色故事的践行学习。
项目链接:暂无
项目作者:文隽然、李歆妤、金叶

体善堂—健身功法动态展示平台

.A development team with both strength and technology.

项目简介:体善堂—健身功法动态展示平台是为广大用户提供了基于中医传统健身功法动态展示平台。通过中国传统文化瑰宝‘皮影戏’,实现功法多动作分解与引导,增强功法学习的趣味性,提升用户体验感。
项目链接:www.stuctft.cn
项目作者:方小能、杜勇、高宝云

廿四时节

.A development team with both strength and technology.

项目简介:廿四食节 APP 以冬奥会开幕式 24 节气倒计时为灵感,结合中医文化及饮食知识,设计出 的一款智能推荐 APP,使不同节气的差异化推送,实现帮助用户理解节气养生,食疗保健, 达到与自然的协调,弘扬中国传统文化的目的。
项目链接:暂无
项目作者:黄烈涵、刘佩、周瑾杉

中医通-机器人智能问诊平台

.A development team with both strength and technology.

项目简介:“中医通——机器人智能问诊平台”是一款基于对中医药知识感兴趣,同时也对全体社会 人群提供中医药知识分享、保健建议、在线机器人对话问诊,获取穴位保健、体质辨识等 中医药知识,设计的在线机器人智能问诊平台。
项目链接:暂无
项目作者:邓科、杨琮杰

敦煌福禄寿

.A development team with both strength and technology.

项目简介:在中国传统神话故事中“福”、“禄”、“寿”是汉族民间信仰的三位神仙,分别象征“幸福”、“吉利”和“长寿”。“福寿双全”“福寿无疆”“福星高照”是民间百姓最常说的几句祝词。《敦煌福禄寿》由三张以福禄寿三个汉字为主体,融入敦煌传统藻井纹样元素组成的平面设计,利用手帐系列实体产品致力于展现汉字美、宣传汉字美以及让汉字美走向世界,让汉语言艺术之美更广泛地被世人所认知,让古老的艺术瑰宝显现风采。
项目链接:暂无
项目作者:美工组

五常山海

.A development team with both strength and technology.

项目简介:《五常山海》利用明信片这样一种不用信封就可以直接投寄的写有文字内容的带有图像卡片的设计形式,将儒家“五常”和“五行”以及四种神兽和四季的对应。仁——木,麒麟。义——金,驺虞。礼——火,鎏金铁芯铜龙。智——水,白泽。信——土,獬豸。
项目链接:暂无
项目作者:美工组

A time simulated annealing-back propagation algorithm and its application in disease prediction(SCI)

.A development team with both strength and technology.

项目简介:In this paper, based on the Back Propagation (BP) neural network algorithm, we introduce the idea of the Simulated Annealing (SA), and then propose a new neural network algorithm: Time Simulated Annealing-Back Propagation (TSA-BP) algorithm. The proposed algorithm can improve the convergence rate and numerical stability. By using this proposed algorithm, the learning rates and initial weights in the BP neural network could be easily adjusted. We show that the TSA-BP algorithm could reduce the errors caused by human-made factors. Several numerical experiments have been tested by using different disease data. Furthermore, we compared the TSA-BP algorithm to the other existing, well-known algorithms. Numerical results show higher accuracy and efficiency of the TSA-BP algorithm.
项目链接:暂无
项目作者:(学生):王明珠Mingzhu Wang, 朱延辉Yanhui Zhu,贾雅琳Yalin Jia

Community detection in complex networks using Node2vec with spectral clustering(SCI)

.A development team with both strength and technology.

项目简介:Community structure in complex networks has been proven to be valuable in a variety of fields, such as biology, social media, health, etc. Researchers have investigated a significant amount of algorithms in complex network analysis and community detection. However, most of them are not expressive to acquire the node and edge representations observed in complex networks. In this paper, we present a new algorithm based on spectral clustering to detect the communities. To improve the performance of the spectral clustering algorithm, we consider an algorithmic framework for learning continuous feature representations for nodes in networks. The proposed algorithm learns a mapping of nodes to low-dimensional space of features that provided a richer representation in learning. The algorithm continues to apply the spectral clustering method to calculate the similarity among any two node embeddings and finish the community detection in the given networks. Experiments show that the proposed algorithm exceeds other state-of-the-art community detection algorithms among various real-world networks from diverse domains and synthetic networks. The algorithm provides a high-quality and accuracy performance in a wide range of data sets.
项目链接:暂无
项目作者:(学生): 李刘欢Liuhuan Li , 梁俊Jun Liang

基于 J - SC 算法的失眠症核心症状及其共现规律研究(中文核心)

.A development team with both strength and technology.

项目简介:目的 挖掘失眠症的核心症状及其共现规律。方法 从湖北中医药大学附属国医堂睡眠记忆专科抽取诊断为失眠 的门诊病例资料约 807 例,首先,构建失眠症的“症状”网络模型,对“症状”节点进行多指标的评估,计算出“症状”网络 的核心节点。其次,利用复杂网络聚类算法 J - SC 对构建的网络模型进行聚类分析。结果 通过中心性指标的综合计算 结果: 入睡困难、夜尿频、多梦、舌红、舌苔白等症状是失眠症的核心症状。聚类分析结果: 以入睡困难、舌红为核心,伴见 腰膝酸软、潮热盗汗等症状,常出现于不寐中的心肾不交或肾阳虚、肾阴虚证; 以多梦为核心,伴见急躁易怒、头晕目胀、 耳鸣咽干等症状,常出现于不寐中的肝火扰心证; 以舌苔白为核心,伴见乏力神疲、腹胀便溏、面色不华等症状,常出现于 不寐中的心脾气血两虚证; 另还有常见多噩梦、易惊醒、伴气短自汗的心胆气虚证; 多见胸闷脘痞,口苦头重等症状的痰 热扰心证。结论 运用复杂网络分析方法对失眠症的症状进行深入挖掘,结果具有较高的精确度和效率,且探寻的核心 症状及其共现规律,具有较高的临床实证性。
项目链接:暂无
项目作者:(学生):李刘欢Liuhuan Li

Sedimentary environment prediction of grain-size data based on machine learning approach(SCI)

.A development team with both strength and technology.

项目简介:Grain size is one of the most important records for sedimentary environment, and researchers have made remarkable progress in the interpretation of sedimentary environments by grain size analysis in the past few decades. However, these advances often depend on the personal experience of the scholars and combination with other methods used together. Here, we constructed a prediction model using the K-nearest neighbors algorithm, one of the machine learning methods, which can predict the sedimentary environments of one core through a known core. Compared to the results of other studies based on the comprehensive data set of grain size and four other indicators, this model achieved a high precision value only using the grain size data. We have also compared our prediction model with other mainstream machine learning algorithms, and the experimental results of six evaluation metrics shed light on that this prediction model can achieve the higher precision. The main errors of the model reflect the length of the conversation area of sedimentary environment, which is controlled by the sedimentary dynamics. This model can provide a quick comparison method of the cores in a similar environment; thus, it may point out the preliminary guidance for further study.
项目链接:暂无
项目作者:(学生):朱延辉Yanhui Zhu

IoT-based Epidemic Monitoring via Improved Gated Recurrent Unit Model(SCI)

.A development team with both strength and technology.

项目简介:During the Coronavirus Disease 2019 (COVID-19) pandemic, non-contact health monitoring and human activity detection by various sensors have attracted tremendous attention. Robot monitoring will result in minimizing the life threat to health providers during the COVID-19 pandemic period. How to improve the performance and generalization of the monitoring model is a critical but challenging task. This paper constructs an epidemic monitoring architecture based on multi-sensor information fusion and applies it in medical robots’ services, such as patient-care, disinfection, garbage disposal, etc. We propose a gated recurrent unit model based on a genetic algorithm (GA-GRU)to realize the effective feature selection and improve the effectiveness and accuracy of the localization, navigation, and activity monitoring for indoor wireless sensor networks (WSNs). By using two GRU layers in the GA-GRU, we improve the generalization capability in multiple WSNs. All these advantages of GA-GRU make it outperform other representative algorithms in a variety of evaluation metrics. The experiments on the WSNs verify that the proposed GA-GRU leads to successful runs and provides optimal performances. These results suggest the GA-GRU method may be preferable for epidemic monitoring in medicine and allied areas with particular relation to the control of the epidemic or pandemic such as COVID-19 pandemic.
项目链接:暂无
项目作者:(学生):李刘欢Liuhuan Li, 黄明芳Mingfang Huang,杨长国Changguo Yang

An efficient Long Short-Term Memory model based on Laplacian Eigenmap in artificial neural networks(SCI)

.A development team with both strength and technology.

项目简介:A new algorithm for data prediction based on the Laplacian Eigenmap (LE) is presented. We construct the Long Short-Term Memory model with the application of the LE in artificial neural networks. The new Long Short-Term Memory model based on Laplacian Eigenmap (LE-LSTM) reserves the characteristics of original data using the eigenvectors derived from the Laplacian matrix of the data matrix. LE-LSTM introduces the projection layer embedding data into a lower dimension space so that it improves the efficiency. With the implementation of LE, LE-LSTM provides higher accuracy and less running time on various simulated data sets with characteristics of multivariate, sequential, and time-series. In comparison with previously reported algorithms such as stochastic gradient descent and artificial neural network with three layers, LE-LSTM leads to many more successful runs and learns much faster. The algorithm provides a computationally efficient approach to most of the artificial neural network data sets.
项目链接:暂无
项目作者:(学生):朱延辉Yanhui Zhu ,李刘欢Liuhuan Li

Prediction and analysis of net ecosystem carbon exchange based on gradient boosting regression and random forest(SCI)

.A development team with both strength and technology.

项目简介:Carbon balance is essential to keep ecosystems sustainable and healthy. Net ecosystem carbon exchange ( NEE ), which is affected by a bunch of meteorological variables to different extent, helps to gauge the balance of the carbon cycle between biological organisms and atmosphere. In this study, the NEE data is collected from two flux measuring sites. Gradient boosting regression algorithm is employed to predict NEE based on the meteorology and flux data from site UK-Gri. During the training process, KFold cross-validation algorithm is implemented to avoid overfitting, and random forest algorithm is implemented to identify the important variables influencing NEE mostly. The four most important variables are found to be global radiation, photosynthetic active radiation, minimum soil temperature, and latent heat. The regression model was compared with three state-of-the-art prediction models: support vector machine, stochastic gradient descent, and bayesian ridge to verify its performance. The experimental results show that this regression model outperforms the other three models, and gives higher value of R-squared, lower values of mean absolute error and root mean squared error. To verify the regression model’s generalization ability, the data from the second flux site, NL-Loo, was employed, and the hybrid data of the two sites was used. The results show that this model performs well on the hybrid data, too. In practical terms, the gradient boosting regression model provides many tunable hypterparameters and loss functions, which make it more flexible and accurate compared to the other three models. This study has conclusively demonstrated for the first time that the combination of gradient boosting regression and random forest models should be considered as valuable tools to make effective prediction for NEE and acquire reliable important variables influencing NEE mostly. The methodologies could be useful in the research fields of ecosystem stability evaluation, environmental restoration, trend analysis of climate change, and global warming monitori
项目链接:暂无
项目作者:(学生):朱延辉Yanhui Zhu, 李刘欢Liuhuan Li

An analysis model of diagnosis and treatment for COVID-19 pandemic based on medical information fusion(SCI)

.A development team with both strength and technology.

项目简介:Exploring the complicated relationships underlying the clinical information is essential for the diagnosis and treatment of the Coronavirus Disease 2019 (COVID-19). Currently, few approaches are mature enough to show operational impact. Based on electronic medical records (EMRs) of 570 COVID-19 inpatients, we proposed an analysis model of diagnosis and treatment for COVID-19 based on the machine learning algorithms and complex networks. Introducing the medical information fusion, we constructed the heterogeneous information network to discover the complex relationships among the syndromes, symptoms, and medicines. We generated the numerical symptom (medicine) embeddings and divided them into seven communities (syndromes) using the combination of Skip-Gram model and Spectral Clustering (SC) algorithm. After analyzing the symptoms and medicine networks, we identified the key factors using six evaluation metrics of node centrality. The experimental results indicate that the proposed analysis model is capable of discovering the critical symptoms and symptom distribution for diagnosis; the key medicines and medicine combinations for treatment. Based on the latest COVID-19 clinical guidelines, this model could result in the higher accuracy results than the other representative clustering algorithms. Furthermore, the proposed model is able to provide tremendously valuable guidance and help the physicians to combat the COVID-19.
项目链接:暂无
项目作者:(学生):黄明芳Mingfang Huang

HMM-BiMM: Hidden Markov Model-based word segmentation via improved Bi-directional Maximal Matching algorithm(SCI)

.A development team with both strength and technology.

项目简介:Combining with the Hidden Markov Model and Bi-directional Maximal Matching algorithm, a new word segmentation algorithm, HMM-BiMM, is presented. In terms of the sub-dictionary matching, it can implement a fast word segmentation. After segmenting the text by the Bidirectional Maximal Matching (BiMM), the remaining text connected by the remaining single words will be segmented again by the strategy of the Hidden Markov Model (HMM). By the HMM, this algorithm can realize the dictionary dynamic update by the new segmentation words and improve the segmentation accuracy accordingly. Compared with five representative algorithms in the real-world clinical text (symptom), we show that the HMM-BiMM algorithm achieves the highest efficiency and accuracy for symptom text segmentation. In detail, this algorithm has around 3% in precision and 70% in running time improved to the BiMM.
项目链接:暂无
项目作者:(学生):颜兴宇Xingyu Yan, 熊晓凡Xiaofan Xiong , 黄玉精Yujing Huang, 朱海涛Haitao Zhu

Machine learning-based seawater concentration pathway prediction(SCI)

.A development team with both strength and technology.

项目简介:This paper constructs a prediction model based on Multilayer Perceptron (MLP) to explore the formation mechanism of brine (seawater evaporation or freezing). Four brine sets are extracted from the published, real-world data, and the simulation test with the same six chemical substance features. After integrated comparative experiments on six evaluation metrics, the results show that this model outperforms the other baseline prediction algorithms, achieving the highest precision 0.9625 and at least 8.45% improvement. Furthermore, for predicting the real-world test set, the results confirm the existence of freezing brine for the first time in Laizhou Bay area, China. This model is also used to analyze the mixed simulation results for brine and fresh groundwater. The experimental results indicate that only two out of twentynine samples of various concentrations change formation mechanisms after mixing. Overall, the model can effectively distinguish the evaporation and freezing brine, and discover the seawater concentration pathway.
项目链接:暂无
项目作者:(学生):梁俊Jun Liang, 杨长国Changguo Yang, 黄明芳Mingfang Huang

A Robotic Vision Model via Xception and Light Gradient Boosting Machine(EI,CCF C)

.A development team with both strength and technology.

项目简介:Image classification plays a significant role in robotic vision. This paper proposes an image classification model: Xception-LightGBM, which combines with Xception and Light Gradient Boosting Machine for hybrid image classification. The proposed algorithm produces the image feature extraction via Xception and classifies these feature vectors using Light Gradient Boosting Machine (LightGBM). The Xception-LightGBM model is compared with five representative image prediction models, such as VGG16, VGG19, InceptionV3, DenseNet121, and Xception. The experiments on six data sets demonstrate this proposed model leads to successful runs and provides optimal performances. It shows this model achieves the best results for all six evaluation metrics: accuracy, precision, recall, F1-Score, loss, and Jaccard. Furthermore, this proposed model acquires the highest accuracy on six image data sets, which has at least 1.1% in accuracy improved to the Xception architecture. It suggests this model may be preferable for robotic vision.
项目链接:暂无
项目作者:(学生):黄明芳Mingfang Huang,颜兴宇Xingyu Yan

An Improved Heterogeneous Graph Convolutional Network for Inter-Relational Medicine Representation Learning (SCI)

.A development team with both strength and technology.

项目简介:Medicine representation learning which aims at uncovering hidden medicine relationships has emerged as a significant technique to imitate a doctor’s cognitive reasoning process. The majority of present research focuses on the intuitive relationships between medication and diagnosis, however, ignores the inherent properties of medicines. This study uses a heterogeneous graph convolutional network (HGCN) and a spectral clustering (SC) algorithm to investigate the associated knowledge underlying clinical treatment. Based on the chronic obstructive pulmonary disease (COPD) clinical data, we construct a medicine-property heterogeneous network consisting of two types of nodes involving medicines and their properties, and three types of edges referring to the inter-medicine, inter-property, and medicine-property relations. HGCN is used to aggregate the neighbor nodes’ information and then generalize the medicine and property embeddings. Then, SC is leveraged to divide these embeddings into the syndromes to which they belong. To verify the model performance, a series of experiments referring to the baseline comparison, ablation study, and parameter sensitivity test have been carried out. Compared to three baseline models and their variants on six evaluation metrics, the experimental results demonstrate that the HGCN-SC model outperforms the baseline approaches in medicine combination identification and has around 3.0% improvement in accuracy over the SC.
项目链接:暂无
项目作者:学生:Xingyu Yan 颜兴宇,Mingfang Huang 黄明芳

Conflict-based search with D* lite algorithm for robot path planning in unknown dynamic environments(SCI)

.A development team with both strength and technology.

项目简介:This study proposes a locally observable robot pathfinding algorithm, conflict-based search with D* lite (CBS-D*), to realize automatic and effective pathfinding in mixed environments with dynamic obstacles. It presents a prejudgment mechanism of collision avoidance and investigates a wait and circuity strategy to promote pathfinding performance. Compared with the D* lite, the experimental results demonstrate that CBS-D* achieves a higher success rate and obstacle avoidance number, and a lower time step. By this collision avoidance mechanism, CBS-D* gives all successes in pathfinding in various dynamic environments, while D* lite may result in some failures. Specifically, CBS-D* has around 31% in the average success rate of pathfinding improved to D* lite in a 32 × 32 map. Furthermore, CBS-D* gives a superiority of self-adaptability and intelligence in unknown dynamic environments.
项目链接:暂无
项目作者:学生作者:Zhuping Zhou (周朱平), Mengyuan Jin (金梦园), Xiaolian Yang (阳小莲)

Blockchain-Based Healthcare and Medicine Data Sharing and Service System (EI)

.A development team with both strength and technology.

项目简介:As the remarkable development of blockchain technology, it attracts a considerable attentions and has a significant impact on various scientific domains, such as healthcare and medicine industry. However, in real-world scenarios of healthcare and medicine applications, data sharing and service are confronted with some challenges because the data has the characteristics of multi-source, heterogeneity, large-scale, etc. Moreover, security and management issues during the stages of data extraction, storage, transfer, access, etc., should be taken into account for healthcare and medicine data sharing and service. To provide a more flexible, reliable, and convenient service for healthcare and medicine, this paper proposes a data sharing and service system, termed HMChain, developed on blockchain technology. This system consists of three layers referring to a data extraction and storage layer for multi-source data integration and distributed data storage, a data management layer for data secure transfer and access, and a data application layer for various user-oriented services. Furthermore, several healthcare and medicine data sharing and service scenarios have been depicted in detail. Overall, this system can provide convenient services for healthcare management, clinical research, medicine traceability, neuroscience research, etc.
项目链接:
项目作者:学生作者:阳小莲(Xiaolian Yang), 邬朝磊(Chaolei Wu), 颜兴宇(Xingyu yan)

2015首届全国中医药院校程序设计竞赛陈世浪、姜晓苹、杨火(一等奖)

.A development team with both strength and technology.

项目简介:2015首届全国中医药院校程序设计竞赛
项目链接:暂无
项目作者: 陈世浪、姜晓苹、杨火

2015首届全国中医药院校程序设计竞赛 余涵、朱友泽、王嫣然(一等奖)

.A development team with both strength and technology.

项目简介:2015首届全国中医药院校程序设计竞赛 余涵、朱友泽、王嫣然(一等奖)
项目链接:暂无
项目作者:余涵、朱友泽、王嫣然

2017第二届全国中医药院校程序设计竞赛-裴卫、彭福阳、李刘欢(二等奖)

.A development team with both strength and technology.

项目简介:2017第二届全国中医药院校程序设计竞赛-裴卫、彭福阳、李刘欢 二等奖
项目链接:暂无
项目作者:裴卫、彭福阳、李刘欢

2018第三届全国中医药院校大学生程序设计竞赛二等奖-彭福阳、余周、黄明芳

.A development team with both strength and technology.

项目简介:2018第三届全国中医药院校大学生程序设计竞赛二等奖-彭福阳、余周、黄明芳
项目链接:暂无
项目作者:彭福阳、余周、黄明芳

2019第四届全国中医药院校程序设计竞赛二等奖-余周、宋续仁、叶新颖

.A development team with both strength and technology.

项目简介:余周、宋续仁、叶新颖
项目链接:暂无
项目作者:余周、宋续仁、叶新颖

2021年第五届全国中医药院校大学生程序设计竞赛二等奖 涂诺辛格 熊黎 吴徵靖

.A development team with both strength and technology.

项目简介:2021年第五届全国中医药院校大学生程序设计竞赛二等奖 涂诺辛格 熊黎 吴徵靖
项目链接:暂无
项目作者:涂诺辛格 熊黎 吴徵靖

第十届蓝桥国赛三等奖-彭福阳

.A development team with both strength and technology.

项目简介:第十届蓝桥国赛三等奖-彭福阳
项目链接:暂无
项目作者:彭福阳

第十届蓝桥国赛三等奖-余周

.A development team with both strength and technology.

项目简介:第十届蓝桥国赛三等奖-余周
项目链接:暂无
项目作者:余周

第十一届蓝桥国赛三等奖-朱海涛

.A development team with both strength and technology.

项目简介:第十一届蓝桥国赛三等奖-朱海涛
项目链接:暂无
项目作者:朱海涛

第十一届蓝桥国赛三等奖-汪明

.A development team with both strength and technology.

项目简介:第十一届蓝桥国赛三等奖-汪明
项目链接:暂无
项目作者:汪明

第十一届蓝桥国赛二等奖-涂诺辛格

.A development team with both strength and technology.

项目简介:第十一届蓝桥国赛二等奖-涂诺辛格
项目链接:暂无
项目作者:涂诺辛格

第十二届蓝桥国赛三等奖-杨晓东

.A development team with both strength and technology.

项目简介:第十二届蓝桥国赛三等奖-杨晓东
项目链接:暂无
项目作者:杨晓东

第十二届蓝桥国赛一等奖-涂诺辛格

.A development team with both strength and technology.

项目简介:第十二届蓝桥国赛一等奖-涂诺辛格
项目链接:暂无
项目作者:涂诺辛格

第十三届蓝桥杯国赛一等奖-熊黎

.A development team with both strength and technology.

项目简介:第十三届蓝桥杯国赛一等奖-熊黎
项目链接:暂无
项目作者:熊黎

CCPC2021GZB湖北中医药大学 吴徵靖、李嘉颖、方静(铜奖)

.A development team with both strength and technology.

项目简介:CCPC2021GZB湖北中医药大学 吴徵靖、李嘉颖、方静(铜奖)
项目链接:暂无
项目作者:吴徵靖、李嘉颖、方静

CCPC2021SHRB湖北中医药大学 涂诺辛格、熊黎、吴徵靖(铜奖)

.A development team with both strength and technology.

项目简介:CCPC2021SHRB湖北中医药大学 涂诺辛格、熊黎、吴徵靖(铜奖)
项目链接:暂无
项目作者:涂诺辛格、熊黎、吴徵靖

CCPC2022GCQ湖北中医药大学李嘉颖、吴徵靖、张琦扬(铜奖)

.A development team with both strength and technology.

项目简介:CCPC2022GCQ湖北中医药大学李嘉颖、吴徵靖、张琦扬(铜奖)
项目链接:暂无
项目作者:李嘉颖、吴徵靖、张琦扬

A network slicing algorithm for cloud-edge collaboration hybrid computing in 5G and beyond networks (SCI)

.A development team with both strength and technology.

项目简介:Edge computing can effectively provide a promising solution with ultra-low latency for a variety of user-oriented services in 5G and beyond networks. The existing studies, however, are unable to provide a flexible resource allocation strategy for various network slices with different user demands in edge computing. This paper proposes a new network slicing algorithm for cloud-edge collaboration hybrid computing (CECHC) in 5G and beyond networks. This algorithm designs a flexible and effective resource allocation strategy primarily for three network slices based on diversified requirements. Moreover, the CECHC model is designed with optimally distributed units (DUs) and centralized units (CUs) deployments to improve storage capability and computing power. This allows for more convenient function partitioning for different network slices. To validate the performance of the proposed algorithm, a series of agent-based simulations are conducted in various network models. The experimental results demonstrate that the proposed algorithm deployed in CECHC outperforms other network models, including fog computing (FC), multi-access edge computing (MEC), and the original CECHC models. It provides the lowest latency for various network slices and achieves all successful runs with different storage capabilities and computing power.
项目链接:暂无
项目作者:学生作者:Ruiling Li (李瑞灵),Xiaolian Yang (阳小莲),Mengyuan Jin (金梦园)

Graph-based medicine embedding learning via multiple attentions (SCI)

.A development team with both strength and technology.

项目简介:Clinical knowledge reasoning provides a new perspective for intelligent diagnosis and therapy. This study constructs a multi-relational medicine-attribute network, which refers to three different types of relationships: inter-medicine, inter-attribute, and medicine-attribute. Then, a multi-relation-based graph attention network (GAT) model combined with the spectral clustering (SC) algorithm, termed MGAT-SC, is presented to train the medicine embeddings and explore the regularity of medicine combinations. Based on real-world clinical data, the GAT model realizes the information aggregation of neighbor nodes and generates the embeddings of medicines and their attributes via a multi-head attention mechanism. Then, the SC method is utilized to divide the medicines and their embeddings. We design and conduct a series of experiments to verify the model’s performance. The experimental results show that the MGAT-SC outperforms the representative baselines and their variants in terms of five evaluation metrics and achieves around 6.0% improvement in accuracy compared to the SC algorithm.
项目链接:暂无
项目作者:学生作者:颜兴宇(Xingyu Yan),黄明芳(Mingfang Huang),阳小莲(Xiaolian Yang),颜怡(Yi Yan)

银海观-中医目诊证方药食谱关联推荐平台

.A development team with both strength and technology.

项目简介:银海观-中医目诊方药食谱关联推荐平台是一款基于中医目诊五轮学说,以糖尿病为研究实例,动态展示眼部不同病证特征,通过中医证候-方药-食谱关联关系,实现基于不同证候的方药/食谱个性化推荐平台。
项目链接:www.yisuiji.cn
项目作者:张利江,胡雪萍,廖志凯

杏林源-药本溯源

.A development team with both strength and technology.

项目简介:杏林源—药本溯源是在保障药品质量安全背景下,基于中药的药本溯源开发设计,实现了药本溯源全流程数据管理和监测,动态展示了中药——半夏的生长及制药的关键过程,可视化对比展示了不同地区的代表药物及其成分对比。
项目链接:暂无
项目作者:付志豪,李文琪,王志豪

方士笺-COVID-19中医辨证论治

.A development team with both strength and technology.

项目简介:方士笺-中医辨证论治是通过动态展示病毒入侵过程,来介绍 COVID-19 对人体的侵害。同时利用中医辨证论治的治疗方案,来阐释中医药治疗的科学性和有效性。并通过检索平台为用户提供知识检索。
项目链接:暂无
项目作者:谭佳雨,高天成,李婧

五色中国茶

.A development team with both strength and technology.

项目简介:本作品以中国茶申遗成功为背景,以中医五色养生理论为基础,以《神农百草经》和《黄帝内经》为支撑,表达了茶与中医的密切联系,让茶文化与中医之根深入土壤,开出绚烂之花。
项目链接:暂无
项目作者:肖书婷,肖敏渲,李文琪

经络中药集

.A development team with both strength and technology.

项目简介:《经络中药集》由五幅作品组成,以五个代表经络和其对应的中医药为主体,加以经络运行时间,了解何时养生更为有效,体现了中医药的作用本质和博大精深,并将其作品做成本子、橡皮等文创产品,让古老的中医药更具魅力。
项目链接:暂无
项目作者:刘洛辰,聂贝贝

TCM生信

.A development team with both strength and technology.

项目简介:TCM(中医)生信——病证症方因多元智联分析平台是一款集中医辨证论治和生物信息学为一体的多元知识关联分析 APP,不仅可以进行中西医的疾病、证候、症状、处方、基因的查询和关联分析还能通过机器人交互的方式获得知识。
项目链接:暂无
项目作者:安卓组

中医目诊——疾病辅助诊断平台

.A development team with both strength and technology.

项目简介: “中医目诊——疾病辅助诊断平台”是一款面向专注于中医目诊以及全社会人群提供的中医目诊知识分享、疾病辅助自测、在线机器人对话问诊、通过观察眼睛来诊断全身疾病设计的辅助诊断系统。
项目链接:暂无
项目作者:安卓组

基于ChebNet的交通流量预测模型

.A development team with both strength and technology.

项目简介:本作品将ChebNet模型应用到交通流量的预测上面,并采用了加利福尼亚州高速公路交通数据集来验证模型的准确度,与三个变体模型相比,实验结果显示,ChebNet模型在交通流量预测方面更为精确,预测效果与真实效果更为贴合。
项目链接:暂无
项目作者:陈彩玉、肖书婷、全姣胤

机器人动态路径规划算法(Robots-D*)研究

.A development team with both strength and technology.

项目简介:研究提出了一种部分可观测的机器人路径规划算法,即机器人动态路径规划算法 (Robots-D*),以实现机器人在移动多障碍物的混合动态环境中自动有效的寻路。 该算法以曼哈顿距离为启发式函数,并将增量搜索范围扩展到 3 阶邻居。它提出了一种避障的预判机制,并研究了机器人的等待和电路策略,以提高成功率。与具有代表性的 D*lite 算法相比,实验结果表明,ROBOTS-D*在暴露于移动障碍物较多的动态环境中时,其成功率和防撞次数均更高。
项目链接:暂无
项目作者:姚池雨,周朱平,颜怡

罕见药源

.A development team with both strength and technology.

项目简介:罕见药源平台是一款基于世界罕见濒危药用植物数据构建的工具,旨在通过地图模板和详细文件数据库,以可视化效果展示濒危药材的种类分布和相关知识。该平台提供全球植物数据库,涵盖了各地的罕见濒危药用植物数据,用户可以通过交互式地图模板直观地查看药材的分布情况。同时,平台还提供详细的植物档案和相关知识,包括形态特征、生长习性、药用价值等方面的信息,以满足用户对植物学知识的需求。通过图表、图形等可视化效果,生动地展现濒危药材的严峻现状,引起用户的关注和重视。这个平台的推出将为医药行业、生态保护机构以及个人用户提供一个便捷的工具,帮助他们更好地了解、保护和管理罕见药用植物资源,从而促进医药科研、生态保护和可持续发展的共同进步。
项目链接:暂无
项目作者:付志豪,李垠垠,赵程,桂佳颖,张翼暄

脑海灯塔——解锁阿尔兹海默症之谜, 守护记忆之光科普平台

.A development team with both strength and technology.

项目简介:本团队设计并开发了《脑海灯塔——解锁阿尔兹海默症之谜, 守护记忆之光科普平台》,提供可视化的病变过程,并包括就医、治疗、药物分析、 症状研发、基因研究等相关的知识库,致力于通过权威、准确、易懂的信息,帮助公众更好地了解阿尔茨海默症,提高对该疾病的认知和重视程度。通过视频将基因突变过程进行了可视化展示,生动展示了基因的变化过程,并在首页提供了阿尔兹海默症的相关搜索,让用户可以根据需求自行了解相关信息。同时提供学术交流区,促进学术界的交流与合作,达到知识共享,讨论并解决问题的目的。
项目链接:暂无
项目作者:谭佳雨 解雨劼 邹青 叶梓轩 王珺玥

健康胃士--病证处方关联平台

.A development team with both strength and technology.

项目简介:“健康胃士--病证处方关联平台”是一款集胃肠疾病、证候、诊断方式以及对应中成药推荐为一体的胃肠疾病诊治辅助平台APP。 为专注于胃肠相关知识的用户提供疾病关联知识以及通过智能机器人的交互式问答实现辅助疾病诊治的功能。
项目链接:暂无
项目作者:李彩蝶,代嘉鑫,代睿,周嘉乐,胡玥

医脑通——疾病与基因关联诊断平台

.A development team with both strength and technology.

项目简介:“医脑通——疾病与基因关联诊断平台”是一款面向专注于脑部疾病与相关基因以及面向全社会人群、帮助用户了解脑部疾病疾病而设计的关联诊断科普APP,软件内内置了大量的脑部疾病相关知识、方便用户能够查询了解。同时软件内设置机器人板块,当用户想要快速获取到自己想要了解的知识时,通过向机器人提问来快速获取自己想要的答案。
项目链接:暂无
项目作者:李晋松、孙堃、付学顺、耿亦如

稀药录

.A development team with both strength and technology.

项目简介:“稀药录”是一款面向全社会人群、 帮助用户普及濒危动植物药材的 APP,软件内内置了许多濒危动植物药材相关知识和视频、 方便用户能够查询了解,还设置了智能图片识别功能,遇到未知动植物药材时可快速识别与了解相关知识。
项目链接:暂无
项目作者:高天成 陈思颖 祝李叶 邱俊苹

榫卯工艺——古建筑中的数学

.A development team with both strength and technology.

项目简介:本作品以天坛4.18国际古迹遗址日为背景,以古建筑为载体,榫卯工艺为支撑,示了中国古代数学中蕴含的匠人智慧,使中国古代数学能够在历史的长河中生生不息。
项目链接:暂无
项目作者:胡玥、邱俊苹、耿亦如

基于深度学习的脑瘤自动检测模型研究

.A development team with both strength and technology.

项目简介:基于YOLOv5算法的脑瘤核磁共振成像的自动检测模型,以期辅助临床医生诊断脑瘤、规划治疗和监测治疗效果,为医生提供更为准确的医学影像信息,提高脑瘤治疗效果和生存率
项目链接:暂无
项目作者:裘迷奥,孙锦涛,全姣胤,刘铭

基于多视图深度神经网络的呼吸道疾病基因预测研究

.A development team with both strength and technology.

项目简介:本研究提出了一种名为RDG-GONet的多视图深度神经网络模型,用于预测疾病基因。RDG-GONet通过整合疾病-基因关联和基因-基因本体(GO)注释关联的多视图信息,学习疾病和基因的深度特征,并在每个训练步骤中同时优化神经网络。在大规模的疾病-基因关联数据集上的实验结果表明,RDG-GONet在预测疾病基因上的性能优于现有的方法。未来的研究将致力于进一步优化模型,提高预测的准确性,并将其应用于医学等多种领域。
项目链接:暂无
项目作者:陶文韬,陶信予,方瑞珍








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