A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition

Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.

     

Research on Action Strategies and Simulations of DRL and MCTS-based Intelligent Round Game

International Journal of Control, Automation and Systems - The reinforcement learning problem of complex action control in multiplayer online battlefield games has brought considerable interest in...     

Protein interaction networks: centrality,modularity, dynamics,and applications

In the post-genomic era, proteomics has achieved significant theoretical and practical advances with the development of high-throughput technologies. Especially the rapid accumulation of protein-protein interactions (PPIs) provides a foundation for constructing protein interaction networks (PINs), which can furnish a new perspective for understanding cellular organizations, processes, and functions at network level. In this paper, we present a comprehensive survey on three main characteristics of PINs: centrality, modularity, and dynamics. 1) Different centrality measures, which are used to calculate the importance of proteins, are summarized based on the structural characteristics of PINs or on the basis of its integrated biological information; 2) Different modularity definitions and various clustering algorithms for predicting protein complexes or identifying functional modules are introduced; 3) The dynamics of proteins, PPIs and sub-networks are discussed, respectively. Finally, the main applications of PINs in the complex diseases are reviewed, and the challenges and future research directions are also discussed.     

Optimization of uncertain acoustic metamaterial with Helmholtz resonators based on interval model

Uncertainties existing in the acoustic metamaterial may strongly affect its unusual properties. Aiming at this actuality, the interval model is introduced to treat with uncertainties existing in the acoustic metamaterial with Helmholtz resonators. Frequency intervals in which the sound intensity transmission coefficients are certainly less than the required value and the effective bulk moduli are certainly negative are defined as conservative approximations. Frequency intervals in which the sound intensity transmission coefficients may be less than the required value and the effective bulk moduli may be negative are defined as unsafe approximations. The proportion of the conservative approximation and the unsafe approximation is defined as an approximate precision. Based on the quantification of uncertainties of the sound intensity transmission coefficients and the negative effective bulk moduli, an optimization model for the interval acoustic metamaterial with Helmholtz resonators is constructed. Numerical results showed that even suffering from effects of interval parameters, unusual properties of the optimized acoustic metamaterial (such as the bandgap of the sound transmission and the negative effective bulk modulus) could be improved.     

高分2号图像业务化大气校正查找表的设计与实现

为实现高分2号图像(GF2)业务化大气校正,利用矢量6S模型(6SV)将辐射传输散射与吸收进行分离计算,其中散射部分采用涵盖各种大气模式、气溶胶类型、成像几何等条件下的大气校正查找表(look-up tables,LUTs)表示,大气吸收部分采用6SV拟合计算的6种大气模式下大气透过率的经验公式表示,这种处理有效简化了查找表大小.在内存4 GB、主频3.10 GHz条件下,通过比较基于本查找表方法和基于FLAASH大气校正软件对北京地区一景GF2数据处理.结果表明:以6SV模型直接大气校正法结果作为真值,两者的绝对误差分别为0.8%和2.6%,处理时间分别为77 s和240 s,该大气校正查找表在处理精度和效率更加适合业务化大气校正.     

论残疾人非制度化利益表达

残疾人通常根据其政治、经济、精神和社会保障等利益需要进行利益表达。当残疾人的利益表达机制不完善、缺乏利益表达意识、社会利益输出不平衡等因素造成制度化利益表达受阻,残疾人只能无奈地选择非常规的、非制度化利益表达方式。通过健全残疾人社会保障服务体系、保证残疾人制度化利益表达渠道畅通、引导残疾人合理运用网络新媒体进行利益表达,是规避由非制度化利益表达造成的社会不和谐因子的有效途径。     

层间接触状态和横向力大小对车辙贡献率的影响

车辙贡献率是反映沥青路面各结构层车辙病害程度的一个主要参数,可用于指导沥青路面的设计和施工.利用三维有限元计算软件建立三维有限元模型用于理论分析,将有限元计算结果与理论解进行对比,验证了该三维有限元模型的可靠性.采用实测的轮胎接地压力,考虑不同层间接触状态和横向力大小,结合有限元计算的数据,分析了沥青路面结构层的车辙贡献率.结果表明:在层间完全连续状态下,横向力大小的选取不能简单地选取最大垂直轮胎接地压力的一定比例,而是要根据所研究的具体情况具体分析.在对沥青路面车辙贡献率的研究中,可以忽略层间接触状态,即假定层间完全连续.     

“双储”模式下的节能控制在小区供水系统中的应用

根据城市居民对供水的可靠性、稳定性、经济节能性的需求,课题组提出了一种基于"双储"模式的供水系统,并按照本市德胜住宅小区的供水要求,设计了一套由储水池、气压罐、变频器、多台水泵机组等主要设备构成的全自动变频恒压供水系统.经过近半年的运行测试,系统有效地解决了传统供水方式中存在的问题,增强了系统的总体性能,有明显的节能效果.     

Ni-Cr-Fe-Si-B合金涂层及铝青铜基体熔合区组织的研究

采用钨极氩弧焊方法在铝青铜基体上施焊了Ni—Cr-Fe-Si—B合金涂层，并运用金相显微镜、扫描电子显微镜及能谱分析了喷涂层、熔合区及热影响区的组织形貌和成分分布。结果表明，喷焊时，在涂层与基体界面两侧各组元均发生了明显的扩散，Cu、Ni组元间可相互取代，基体融合区组织的基本组成仍为α (α γ2)，但同时也形成了Cu2FeAl7、NiAl3等新相，且融合区组织细小，涂层与基体间为冶金态结合。     

Thermodynamic reassessment of the Cd−Zn system

The Cd−Zn system has been thermodynamically reassessed with the CALPHAD method by combining more recent experimental data, in particular the activities of zinc in the liquid phase. A good agreement is obtained between the calculated and experimental thermodynamic parameters as well asphase boundaries.