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应用t-SNE算法探讨实验室检查在自身免疫性疾病诊断上临床意义
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作者 肖瑞平 朱有凯 《中国科技期刊数据库 医药》 2023年第8期59-62,共4页
应用机器学习算法t-SNE(t-Distributed Stochastic Neighbor Embedding)对自身免疫性疾病患者实验室检查数据进行数据分析,探索其中数据结构、数据之间的关系以及在自身免疫性疾病诊断方面的意义。方法 构建以t-SNE为基础的数据分析模型... 应用机器学习算法t-SNE(t-Distributed Stochastic Neighbor Embedding)对自身免疫性疾病患者实验室检查数据进行数据分析,探索其中数据结构、数据之间的关系以及在自身免疫性疾病诊断方面的意义。方法 构建以t-SNE为基础的数据分析模型,以原始实验室检查数据生成的大量高维数据集反复训练模型,确定各种重要参数和实验流程,最终对生成的一系列可视化散点图进行分析,揭示其中包含的信息和知识。结果 本研究建立了可靠性与实用性较强的数据分析模型以及具有临床实践意义的数据分析流程。通过对880例常见自身免疫性疾病病种的数据分析,发现超敏C反应蛋白将所有病例显著地分为两大类;同病种的病例具有明显聚集的数据簇结构,不同病例的数据点有重叠现象;通过比较不同的数据集分析结果,进一步简化了检查项目组合。结论 采用本研究建立的数据分析模型,能够将复杂的临床高维数据集通过计算简化为二维的可视化散点图。通过对散点图上重叠数据点的解析,快速地将疑难病例甄别出来,表明了数据分析模型的可靠性;研究结果表明超敏c反应蛋白可能在自身免疫性疾病的发生发展中具有启动者的作用;简化的检查项目组合也可以取得具有临床诊断价值的结果,在一定程度上节约了医疗资源。 展开更多
关键词 t-sne(t-distributed stochastic neighbor embedding) 自身免疫性疾病 数据分析 超敏C反应蛋白
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Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing
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作者 D.Jerusha T.Jaya 《Computer Systems Science & Engineering》 SCIE EI 2022年第9期1121-1132,共12页
Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers,providers and the workers. Requisition for Edge Computing based ite... Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers,providers and the workers. Requisition for Edge Computing based items havebeen increasing tremendously. Apart from the advantages it holds, there remainlots of objections and restrictions, which hinders it from accomplishing the needof consumers all around the world. Some of the limitations are constraints oncomputing and hardware, functions and accessibility, remote administration andconnectivity. There is also a backlog in security due to its inability to create a trustbetween devices involved in encryption and decryption. This is because securityof data greatly depends upon faster encryption and decryption in order to transferit. In addition, its devices are considerably exposed to side channel attacks,including Power Analysis attacks that are capable of overturning the process.Constrained space and the ability of it is one of the most challenging tasks. Toprevail over from this issue we are proposing a Cryptographic LightweightEncryption Algorithm with Dimensionality Reduction in Edge Computing. Thet-Distributed Stochastic Neighbor Embedding is one of the efficient dimensionality reduction technique that greatly decreases the size of the non-linear data. Thethree dimensional image data obtained from the system, which are connected withit, are dimensionally reduced, and then lightweight encryption algorithm isemployed. Hence, the security backlog can be solved effectively using thismethod. 展开更多
关键词 Edge computing(e.g) dimensionality reduction(dr) t-distributed stochastic neighbor embedding(t-sne) principle component analysis(pca)
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Light spectrum preference of Nile Tilapia (Oreochromis niloticus) under different hunger levels
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作者 Guang Jin Jian Zhao +5 位作者 Yadong Zhang Gang Liu Dezhao Liu Songming Zhu Yufang Shao Zhangying Ye 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2019年第5期51-57,共7页
In order to improve the light welfare of Nile tilapia in aquaculture,the influence of hunger level on light spectrum preference of Nile tilapia was explored in this study.The whole experiment was based on the emptying... In order to improve the light welfare of Nile tilapia in aquaculture,the influence of hunger level on light spectrum preference of Nile tilapia was explored in this study.The whole experiment was based on the emptying of the gastrointestinal contents,and carried out under the controlled laboratory conditions.The light spectrum preference was assessed by counting the head location of fish in each experimental tank,which containing seven compartments(i.e.,red,blue,white,yellow,black,green and public area).t-Distributed Stochastic Neighbor Embedding(t-SNE)was adopted to visualize the hunger level-based dynamic preference on light spectrum in two-dimensional space.According to the clustering results,significant differences in light spectrum preferences of Nile tilapia,under the different hunger levels,were indicated.In addition,the average visit frequency in green compartment was significantly lower than that in other color compartments throughout the whole experiment,and the total visit frequency in red compartment was relatively higher during the whole experiment. 展开更多
关键词 light welfare Nile tilapia hunger level light spectrum preference t-distributed stochastic neighbor embedding
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