基于多元神经网络融合的分布式资源空间文本分类研究

针对实体产业对科技资源的服务需求,以服务效应作为资源文本分类标准,提出一种基于多元神经网络融合的分布式资源空间文本分类模型。设计了包含词嵌入层、卷积层、双向门控循环单元层、注意力机制层和softmax层的多元神经网络通路;在此基础上采用基于需求—效应—资源分类策略,完成了从定性科技资源需求到定量资源服务效应求解,再到定性科技资源输出的映射变换,重点解决了分布式科技资源局部和全局语义特征形式多样、文本长距离依赖特征显著、重要资源信息难以准确识别的问题,进而从分布式科技资源空间中快速准确地获取效应知识,提升实体产业产品研发效率和创新能力;通过万方专利科技资源数据集验证了所提方法的可行性和有效性,为更加全面地挖掘资源文本特征和按需服务实体产业提供了一种新的思路和手段。     

A deep neural network based classifier for brain tumor diagnosis

Classification process plays a key role in diagnosing brain tumors. Earlier research works are intended for identifying brain tumors using different classification techniques. However, the False Alarm Rates (FARs) of existing classification techniques are high. To improve the early-stage brain tumor diagnosis via classification the Weighted Correlation Feature Selection Based Iterative Bayesian Multivariate Deep Neural Learning (WCFS-IBMDNL) technique is proposed in this work. The WCFS-IBMDNL algorithm considers medical dataset for classifying the brain tumor diagnosis at an early stage. At first, the WCFS-IBMDNL technique performs Weighted Correlation-Based Feature Selection (WC-FS) by selecting subsets of medical features that are relevant for classification of brain tumors. After completing the feature selection process, the WCFS-IBMDNL technique uses Iterative Bayesian Multivariate Deep Neural Network (IBMDNN) classifier for reducing the misclassification error rate of brain tumor identification. The WCFS-IBMDNL technique was evaluated in JAVA language using Disease Diagnosis Rate (DDR), Disease Diagnosis Time (DDT), and FAR parameter through the epileptic seizure recognition dataset.     

一种标准模型下无证书签名方案的安全性分析与改进

无证书签名具有基于身份密码体制和传统公钥密码体制的优点，可解决复杂的公钥证书管理和密钥托管问题.Wu和Jing提出了一种强不可伪造的无证书签名方案，其安全性不依赖于理想的随机预言机.针对该方案的安全性，提出了两类伪造攻击.分析结果表明，该方案无法实现强不可伪造性，并在"malicious-but-passive"的密钥生成中心攻击下也是不安全的.为了提升该方案的安全性，设计了一个改进的无证书签名方案.在标准模型中证明了改进的方案对于适应性选择消息攻击是强不可伪造的，还能抵抗恶意的密钥生成中心攻击.此外，改进的方案具有较低的计算开销和较短的私钥长度，可应用于区块链、车联网、无线体域网等领域.     

Taxonomic importance of spore morphology in Thelypteridaceae from Northern Pakistan

Spore morphology of Thelypteridaceae species growing in Malakand Division, Northern Pakistan, was studied using both light microscopy and scanning electron microscopy. The taxa are Christella dentata and Glaphyropteridopsis erubescens in the subfamily Thelypteridoideae, and Phegopteris connectilis, Pseudophegopteris pyrrhorhachis, and Pseudophegopteris levingei in the subfamily Phegopteridoideae. The studied species exhibit differences in spore size, exospore thickness, color, and ornamentation. Spores of the studied species are monolete and medium‐sized, and shape is ellipsoidal in both polar and equatorial views. The average measurement of the polar diameter ranges from 27 μm to 31 μm, whereas in the equatorial direction it varied from 20 μm to 40 μm. The exospore thickness ranges from 1.2 μm to 2.4 μm. Reticulate, laevigate with microgranules, cristate, and coarsely echinate surface ornamentation are observed among the species. Multivariate analysis including unweighted pair group method with arithmetic mean and principal component analysis was used for the grouping and discrimination of species and genera.     

Bioecology of macrobenthic communities in the microtidal monsoonal Kodungallur–Azhikode Estuary,southwest coast of India

A comprehensive study of the macrobenthic communities in the Kodungallur–Azhikode Estuary (KAE) was conducted during 2009–2011 period. A total of 18,846 organisms were collected, with 60% being malacostracans, followed by polychaetes (20%), molluscs (9%) and ‘others’ group (11%). A total of 79 species in 71 genera belonging to 49 families were identified, with 33 spp. being polychaetes, 26 spp. being malacostracans, 11 spp. being molluscs and 9 spp. being in the ‘others’ group. A single species of opportunistic amphipod (Americorophium triaeonyx) comprised more than 62.05% of the total numerical abundance of macrobenthos. The other dominant species were Obelia bidentata, Arcuatula senhousia, Cirolana fluviatilis, Prionospio cirrifera and Capitella sp. Canonical correspondence analysis (CCA) results indicated environmental parameters such as water column salinity, turbidity, sediment Eh, substratum type, chlorophyll‐a concentration, depth and organic matter in sediment were the significant factors influencing the distribution of macrobenthic species in the KAE. The present study provides baseline information for future KAE benthic studies.