The Simulation of Typical Degradations of Underwater Images and Research on Quality Estimation Methods

为了建立完善的水声通信技术质量评价系统，准确描述和评价水下图像劣化特性有很大的实际意义。本文在分析总结水下图像劣化类型的基础上，搭建了水下图像劣化模型，并提出了劣化图像感知质量（PQoS，PerceivedQualityofService）的评测定义和预测算法。本文的主要研究工作包括： 调研、总结了水下图像在获取、传输、和处理各过程中的劣化类型和原因。重点分析了海水吸收、散射和硬件对水下光学成像的影响，水声图像压缩的必要性，以及劣化特点。 基于模板劣化模型和Jaffe-McGlamery模型进行了水下图像劣化仿真，成功模拟了光源分布、海水吸收和散射、高斯模糊、离焦模糊、运动模糊和色彩降维等...In order to construct a complete quality evaluation system for underwater communication, it is practically significant to describe and evaluate the properties of underwater image distortion precisely. Based on plenty of precedent work on analyzing and summarizing categories of underwater image distortion, underwater image distortion models have been built, and the definition and forecasting method...学位：工学硕士院系专业：信息科学与技术学院_通信与信息系统学号：2332011115316

The Simulation of Typical Degradations of Underwater Images and Research on Quality Estimation Methods

为了建立完善的水声通信技术质量评价系统，准确描述和评价水下图像劣化特性有很大的实际意义。本文在分析总结水下图像劣化类型的基础上，搭建了水下图像劣化模型，并提出了劣化图像感知质量（PQoS，PerceivedQualityofService）的评测定义和预测算法。本文的主要研究工作包括： 调研、总结了水下图像在获取、传输、和处理各过程中的劣化类型和原因。重点分析了海水吸收、散射和硬件对水下光学成像的影响，水声图像压缩的必要性，以及劣化特点。 基于模板劣化模型和Jaffe-McGlamery模型进行了水下图像劣化仿真，成功模拟了光源分布、海水吸收和散射、高斯模糊、离焦模糊、运动模糊和色彩降维等...In order to construct a complete quality evaluation system for underwater communication, it is practically significant to describe and evaluate the properties of underwater image distortion precisely. Based on plenty of precedent work on analyzing and summarizing categories of underwater image distortion, underwater image distortion models have been built, and the definition and forecasting method...学位：工学硕士院系专业：信息科学与技术学院_通信与信息系统学号：2332011115316

Quick estimation of end to end PQoS of image

本文介绍了一种新型的利用图像活动性(IAM)快速估计水下图像端到端体验质量的方法。首先引入结构相似度(SSIM)作为图像感知服务质量(PQo S)参数评价图像质量,将图像初始活动性(IAM)作为区分图像内容的本征参数;随后基于质量向量(QV)的概念,分别分析了非压缩图像的结构相似度,图像初实活动性与无条件丢失概率(SSIM-IAM.-ulp)之间的联合特性,以及压缩图像的结构相似性,压缩率与无条件丢失概率(SSIM-IAM.-ulp)之间的联合特性。最后,在上述联合特性的基础上提出了劣化图像SSIM的预测算法。测试实验证明,该类算法有较高的预测准确率,预测误差最低可达0.8%。This paper introduces a novel method for quick estimating the end to end Perceived Quality of Service( PQo S) of underwater image based on image activity measure( IAM). Structure Similarity( SSIM) is first introduced as the evaluation standard of image PQo S parameter to evaluate the quality of image,while the IAM of original image is utilized as an intrinsic parameter to discriminate the image contents. Then,based on the concept of quality vector( QV),the SSIM-ulp-IAM0 features for non-compressed picture are analyzed,and the SSIM-CR-ulp features for compressed picture are analyzed as well. On this basis,the prediction algorithm based on SSIM for the degraded image is proposed. Test experiment result shows that this kind of prediction algorithm has high accuracy rate,and the lowest prediction error reaches to 0. 8%.国家自然科学基金面上(61571377;61471308)项目资

Preschool potential development education research of multiple births

【目的】对2002年出生的河北籍缴氏五胞胎兄妹进行教育实验研究,以考察学龄前潜能发展教育对多胞胎幼儿发展的作用。【方法】采用自身对照实验,对五胞胎施以"评估-指导-发展"循环互动模式为基础的个性化潜能发展教育,并对其发展进行阶段性评估,对测验结果进行统计分析。【结果】历经31个月的个性化潜能发展教育,五胞胎的智能发展水平由入园时(4.1岁)的平均智能发育商96.6提高到了6岁时的115,平均提高了19个百分点,干预效果显著。五胞胎6.3岁时的瑞文智商平均达124.6,其中有两人(一男一女)的智商达到130以上。【结论】五胞胎接受个性化潜能发展教育的结果验证了已有的研究发现,即以评估儿童各领域能力发展为基础的个性化教育是一种可行的、有效的早期教育模式。【Objective】 To explore the effect of the potential development preschool education on the development of Xi quintuplets born in Hebei Province,2002.【Methods】 Applying the individualized education in potential development based on ＂evaluation-guidance-development＂ interactive mode,the development of Xi quintuplets was accessed each semester and the test results were analyzed statistically.【Results】 After 31-month potential development individualized education,the average development quotient of the quintuplets rose from 97（4.1 years old）to 115 at age 6,and an average rise of 19 percentages;the intervention effect was significant.The average IQ（CRT）of the quintuplets at age 6.3 years was 124.6;the IQ of two（one boy and one girl among them）,reached over 130.【Conclusions】 The development results of the quintuplets confirm our previous research results that the individualized education,assessing each sub-field of early childhood development,is a feasible and effective form of early education

Electrochemical Determination of Dopamine Based on Metal-Substituted Polyoxometalates Composites

本文构建了基于取代型多酸与还原氧化石墨烯（RGO）复合材料的多巴胺电化学传感器. 首先,通过水热法合成了十一钨镍杂多钨硅酸盐K2H2SiW11NiO39·xH2O（SiW11Ni）,利用Hummers法与化学还原法合成了还原氧化石墨烯. 并使用SEM、XRD与FTIR等测试方法对材料进行了表征. 将SiW11Ni与RGO按照一定的比例滴涂在玻碳电极表面,以便成功构建出传感界面（SiW11Ni-RGO/GCE）. 然后,采用电化学阻抗法与循环伏安法等方法研究了传感界面的电化学性质. 优化实验条件后,利用该传感器通过循环伏安法对多巴胺进行定量检测,并且氧化过程展现出较为良好的性能. 其检出限为3.2 μmol·L -1（S/N = 3）,灵敏度为9.71 μA·(μmol·L -1·cm -2) -1,线性范围为10 ~ 80 μmol·L -1. 同时,所制备的传感器表现出良好的稳定性与抗干扰能力. 该传感器修饰过程简单、成本低、电化学性能良好,为多酸在化学传感领域的应用提供新思路.In this report, a dopamine electrochemical sensor based on metal-substituted polyoxometalates and reduced graphene oxide (RGO) composite was successfully constructed. The K2H2SiW11NiO39·xH2O (SiW11Ni) was synthesized by hydrothermal method, while the RGO was prepared by Hummers' method and chemical reduction method. The above-mentioned materials were characterized by SEM, FTIR and XRD. The as-synthesized SiW11Ni and RGO composites were modified on the surface of glassy carbon electrode (GCE) by drop coating method, and the sensing interface (SiW11Ni-RGO/GCE) was successfully constructed. The electrochemical properties of the sensing interface were studied by electrochemical impedance spectroscopy and cyclic voltammetry. After optimizing the experimental conditions, dopamine could be quantitatively detected by cyclic voltammetry with good performance. The limit of detection was 3.2 μmol·L -1 (S/N = 3), the sensitivity was 9.71 μA·(μmol·L -1·cm -2) -1, and the linear range was 10 to 80 μmol·L -1.河北科技大学博士启动基金No(81/1181222);大学生创新创业训练计划项目No(2018065);河北省高等学校科学技术研究项目No(ZD2018037);河北省高等学校科学技术研究项目No(QN2019032);与国家自然科学基金资助No(81872669)通讯作者:任聚杰,籍雪平E-mail:[email protected];[email protected]:RENJu-jie,JIXue-pingE-mail:[email protected];[email protected]. 河北科技大学理学院化学系,河北 石家庄 0500182. 河北工业职业技术学院,河北 石家庄 0500913. 河北医科大学药学院,河北 石家庄 0500171. Department of Chemistry, School of Science , Hebei University of Science and Technology, Shijiazhuang 050018, Hebei, China2. Department of Construction Engineering, Hebei College of Industry and Technology, Shijiazhuang 050091, Hebei, China3. School of Pharmacy,Hebei Medical University, Shijiazhuang 050017, Hebei, Chin