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您选择的条件: 计算机应用技术(102)
  • Copula熵:理论和应用

    分类: 统计学 >> 数理统计学 分类: 数学 >> 统计和概率 分类: 计算机科学 >> 计算机应用技术 分类: 信息科学与系统科学 >> 信息科学与系统科学基础学科 提交时间: 2022-08-25

    摘要:统计独立性是统计学和机器学习领域的基础性概念,如何表示和度量统计独立性是该领域的基本问题。Copula理论提供了统计相关关系表示的理论工具,而Copula熵理论则给出了度量统计独立性的概念工具。本文综述了Copula熵的理论和应用,概述了其基本概念定义、定理和性质,以及估计方法。介绍了Copula熵研究的最新进展,包括其在统计学的六个基本问题(结构学习、关联发现、变量选择、因果发现、域自适应和正态性检验等)上的理论应用。讨论了前四个理论应用之间的关系,以及其对应的深层次的相关性和因果性概念之间的联系,并将Copula熵的(条件)独立性度量框架与基于核函数和距离相关的同类框架进行了对比。简述了Copula熵在理论物理学、理论化学、化学信息学、水文学、环境气象学、生态学、动物形态学、农学、认知神经学、运动神经学、计算神经学、心理学、系统生物学、生物信息学、临床诊断学、老年医学、精神病学、公共卫生学、经济学、社会学、教育学、法学、政治学,以及能源工程、土木工程、制造工程、可靠性工程、航空航天、通信工程、测绘工程和金融工程等领域的实际应用。

  • 基于数字报历史优秀版面的样式智能生成与微调

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-07-14

    摘要:

    目的 报纸一直是传播知识的重要载体,本文方法为实现经济、高效的报纸排版工作。

    方法 首先根据历史优秀版面训练概率模型来推断电子报版面的样式,并结合固定布局约束和用户约束保证样式有效,同时构建美学设计原理的量化方法进一步实现样式微调。

    结果 通过定性和定量评估,表明由本文模型推断出的样式参数精确度良好,且满足用户一定的需求。

    局限 本文方法暂时只支持单页电子报的自动生成,然而报纸排版多由多个版面组成,故未来的工作需要对报纸内容进行分页操作。

    结论 本文方法可以自动生成满足视觉美观性、层次性和可读性的报纸。

  • 数字报版面布局自动生成方法

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-07-13

    摘要:报纸版面对新闻有一个价值排序合理且美观新颖的展示,可以让读者面对众多新闻,在短时间获取最具价值的讯息和浏览乐趣。这是新闻报纸在众多媒体中的特色。然而,对于排版人员而言,手动制作直观、易读、美观的报纸版面布局往往需要耗费大量的时间成本。本文结合贝叶斯网络推断和约束规划技术,提出一种数字报版面布局自动生成方法。该方法首先基于历史版面数据驱动和专家经验对数字报版面的结构和属性建立推断模型,使得新生成的版面具有历史特定风格;然后利用推断结果建立混合整数约束规划模型计算版面布局,从而显著减少模型求解空间,提高布局质量。此外,推断模型提供多种可用候选结构为生成结果提供多样性,规划模型保证报纸版面内新闻不重叠、不溢出并具有良好的对齐性能。为了训练和验证模型,本文构建并公开了一个中文版面数据集。该数据集由数字报版面图片和相应的新闻内容组成,并带有详细版面新闻属性标记。最后,进行用户研究,结果表明了版面布局自动生成方法的有效性。

  • 图像的视觉感知质量评价新概念 ----单幅图像视觉感知质量评价和独立图像间的视觉感知质量比较

    分类: 生物学 >> 生物医药 分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-05-26

    摘要:

    直至现在,图像质量评价都没有涉及色彩问题。图像质量评价的文献多是评价图像质量(在压缩、传输等图像处理过程中)的变差(降质)程度。平面图像是一种二维的亮度分布。亮度是图像视觉质量的核心参量,没有亮度就没有图像,也就没有论及图像质量的可能。本文提出了三个层次的图像视觉感知质量评价(VPQA)指标:单幅单参数图像质量评价(SS_IQA),单幅五参数精细图像质量评价(SF_IQA),考虑彩色保真性的增强图像质量评价(CF_IQA)。横向论,可分为单幅的图像质量评价(SIQA),多幅图像质量比较,图像增强中的质量评价等三个方面。图像视觉质量评价是智能最佳化图像增强的不可或缺的工具。

  • 基于可解释网络的电力负荷预测

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-04-26

    摘要:

    负荷预测能有效助力负荷供需的动态平衡,保障电力系统稳定运行。基于统计模型和基于深度学习是目前构建预测方法的两种思路,但是少有从可解释的角度构建负荷预测方法。本文利用深度神经网络的非线性拟合能力,以及指数平滑模型的可解释特性,提出了深度平滑因子模型(DeepES)。从实际负荷序列数据中的预测结果来看,DeepES模型实现了最优的预测效果,而且相比于传统单一因子作为网络输入的RNNs网络具有更精确、可解释性更好的负荷预测模型。

  • Dynamic Prediction of Abnormal Condition for Multiple Fused Magnesium Melting Processes Based on Video Continual Learning

    分类: 信息科学与系统科学 >> 控制科学与技术 分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-04-20

    摘要:

    Process industry is the pillar industry of national economy, particularly, the process of producing magnesia by fused magnesia furnace system is a typical category of process industry. Due to the complex smelting mechanism and changing production factors, abnormal working conditions often occur in fused magnesia furnace. The semi-molten condition is the most typical and harmful abnormal condition. In this paper, an adaptive pretraining-inference-dynamic training-validation semantic segmentation method based on industrial video is proposed for dynamic prediction of semi-molten condition of multiple fused magnesium furnaces. The experimental results show that compared with the prediction model without adaptive learning, the prediction performance of the adaptive learning model in this paper for multiple fused magnesium melting processes is significantly improved.

  • Fast detection method for Baggage pallet based on multi-layer

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-04-18

    摘要:

    In the self-service baggage check and sorting of civil aviation, it is an essential function to automatically detect whether pallets is added to the self-dropped baggage, but the pallets are largely obscured by the embedded baggage,which becomes a challenging problem.For this issue, a fast detection method for embedded baggage pallets based on multi-layer skeleton model registration is proposed. In order to describe the characteristics of the pallet, the point cloud skeleton model and the point-line model are constructed by the 3D point cloud model. During online detection, the designed banded feature description and extraction method is used to grab the border point cloud, and the proposed point-line potential energy iterative algorithm is used to registration the point-line model and horizontal border points. Then, point cloud iterative nearest point registration based on random sampling consistency is used to achieve accurate registration and pose calculation. As a result, the possibility of the existence of the pallet is judged. The effectiveness of the algorithm is verified by a variety of actual pallet detection experiments. A variety of typical comparative experimental results show that when the pallet point cloud is missing within 70%, the algorithm can still maintain the accuracy of 94% and the speed exceeds typical algorithm is more than 6 times.

  • 元宇宙应用的梦境理论:基本原理、方法和启示

    分类: 心理学 >> 认知心理学 分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-03-21

    摘要:

    [目的] 本文从提升人的价值和幸福感出发,以拓展和探寻元宇宙的应用为目标,综述了心理学关于梦境的理论假说。

    [方法] 通过文献综述的方法,综述了梦境的功能和理论基础,并在娱乐社交、技能学习、咨询测评、创伤治疗等方面,将元宇宙作为现实世界和梦中世界的补充对其应用前景和面临的挑战进行了讨论。

    [结果] 未来元宇宙的设计可以参照梦境这个与生俱来的虚拟现实体验,帮助调节人的心理和行为健康。

    [局限] 由于梦境研究的发展尚处发展阶段,本文尚未对梦境研究的行为和神经机制进行系统性综述。

    [结论] 本文基于梦境理论为元宇宙研究提供了新的理论指导与发展建议,为实现现实、梦境和元宇宙三者的协调发展提供了新的思路。

  • 基于文本数据增强的生活满意度预测模型优化

    分类: 心理学 >> 应用心理学 分类: 计算机科学 >> 计算机应用技术 提交时间: 2022-01-04

    摘要:[目的]随着网络大数据以及机器学习的方法的发展,越来越多研究结合文本分析与机器学习来预测满意度。在建立生活满意度预测模型的研究中,针对获取大量有效的有标注数据困难的问题,本研究提出基于文本数据增强以优化生活满意度预测模型。 [方法]改编大连理工词典后,以357份生活现状描述为原始文本、生活满意度量表自评分为标注,经过EDA和回译进行文本数据增强,利用传统机器学习算法建立预测模型。 [结果]结果显示,大连理工词典改编后,各模型预测能力大大提高;数据增强后,仅在线性回归模型上观察到回译和EDA的提升作用。使用原始数据进行训练的岭回归模型预测值与实际值的皮尔逊相关系数最高,达0.4131。 [结论]特征提取精度的提升可优化目前的生活满意度预测模型,但对于以词频为特征建立的生活满意度预测模型,基于回译和EDA进行的文本数据增强可能并不十分适用。

  • 基于游戏行为的黑暗人格预测技术研究

    分类: 心理学 >> 应用心理学 分类: 计算机科学 >> 计算机应用技术 提交时间: 2021-07-08

    摘要:[目的]本研究利用DOTA2游戏行为数据,实现对DOTA2玩家黑暗人格三维度的无侵入识别。[方法]本文利用Clarity 2解析包对DOTA2的游戏日志文件进行解析,提取玩家的游戏行为特征,并利用黑暗十二条量表对玩家的行为特征进行标注,采用机器学习的方法实现对黑暗人格三维度的识别。 [结果]结果发现,在马基雅维利主义、自恋和精神病态三维度上,采用高斯过程回归算法建立的模型在效度和信度上表现最佳,模型预测值与真实值之间的相关系数在0.31-0.45之间,重测信度在0.33-0.53之间。 [局限]本研究未将被试的言语行为特征纳入到建模过程中,使得游戏行为特征不够全面。 [结论]研究结果发现游戏行为数据能够帮助预测个体的黑暗人格,并且通过高斯过程回归建立的模型具有最高信效度。

  • 基于深度学习神经网络的电池分容阶段容量预测的方法

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2021-05-29

    摘要: 本文提出了一个使用深度学习方法预测锂离子电池分容工序的容量的解决方案。该方案从化成和分容工序中提取部分工步的物理观测值记录作为特征,训练了一个深度神经网络(Deep Neural Network, DNN)实现了电池容量的精准预测。据测试,该模型预测的电池容量与真实值相比,平均百分比绝对误差(Mean Absolute Percentage Error, MAPE)仅为0.78%。将该模型与生产线结合,可以大大缩减生产时间与能耗,降低电池生产成本。

  • 二维光学刺激下的视觉感知定律

    分类: 计算机科学 >> 计算机应用技术 分类: 医学、药学 >> 医学、药学其他学科 分类: 工程与技术科学 >> 光学工程 提交时间: 2021-05-24

    摘要: 人类对刺激量的感知分为数量感知和质量感知。无论是韦伯-费克纳(Weber-Fechner)的对数感觉定律还是史蒂文斯(Stevens)的幂函数感觉定律,都是关于感觉量与一维亮度刺激之间定量关系的定律。图像属于具有二维亮度分布特征的刺激量。本文研究的是二维亮度刺激的质量的感知,即二维亮度刺激质量好坏程度的感知。好坏程度是一个模糊的心理学概念,因此我们需要用模糊数学的方法来量化图像视觉感知质量的好坏程度,即建立一个模糊隶属函数PQ来定量表示图像视觉质量的好与坏的程度。

  • Small Private Online Judge: A New Tool for Empirical Education Research

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-09-30

    摘要: This paper puts forward the concept of Small Private Online Judge (SPOJ). Compared with Massive Open Online Judge (MOOJ), SPOJ has advantages in structured data acquisition of students' virtual behavior for its specific function and tight coupling with the classroom. SPOJ-based empirical education research can be conducted within "Acquisition-Analysis-Application" (3A) Framework. The case study of a SPOJ program clarifies the standard pattern of SPOJ-based 3A research and highlights the emergence of education-intelligence concept. The challenges of SPOJ-based empirical education research and implications of SPOJ are also discussed.

  • Better Than Reference In Low Light Image Enhancement Conditional Re-Enhancement Networks

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-08-26

    摘要: Low light images suffer from severe noise, low brightness, low contrast, etc. In previous researches, many image enhancement methods have been proposed, but few methods can deal with these problems simultaneously. In this paper, to solve these problems simultaneously, we propose a low light image enhancement method that can combined with supervised learning and previous HSV (Hue, Saturation, Value) or Retinex model based image enhancement methods. First, we analyse the relationship between the HSV color space and the Retinex theory, and show that the V channel (V channel in HSV color space, equals the maximum channel in RGB color space) of the enhanced image can well represent the contrast and brightness enhancement process. Then, a data-driven conditional re-enhancement network (denoted as CRENet) is proposed. The network takes low light images as input and the enhanced V channel as condition, then it can re-enhance the contrast and brightness of the low light image and at the same time reduce noise and color distortion. It should be noted that during the training process, any paired images with different exposure time can be used for training, and there is no need to carefully select the supervised images which will save a lot. In addition, it takes less than 20 ms to process a color image with the resolution 400*600 on a 2080Ti GPU. Finally, some comparative experiments are implemented to prove the effectiveness of the method. The results show that the method proposed in this paper can significantly improve the quality of the enhanced image, and by combining with other image contrast enhancement methods, the final enhancement result can even be better than the reference image in contrast and brightness. (Code will be available at https://github.com/hitzhangyu/image-enhancement-with-denoise)

  • PandaDB:一种面向异构数据的智能融合管理系统

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-07-20

    摘要: 随着大数据应用的不断深入,大规模结构化、非结构化数据带来的异构数据的融合管理、关联计算和即席查询需求日益突出。现有异构数据融合管理技术与系统存在着数据模型表示能力弱、查询执行实时性差等问题。本文提出了适用于结构化、非结构化数据融合管理和语义计算的智能属性图模型,并定义了相关属性操作符和查询语法。基于该模型实现了异构数据融合管理系统PandaDB,并详细介绍了PandaDB的总体架构、存储机制、查询机制、属性协存、AI算法调度和分布式架构。测试实验和案例证明,PandaDB的协存机制和分布式架构具备较好的性能加速效果,并可应用在关联数据发布、个人相册管理、学术图谱实体消歧等融合数据智能管理的场景。

  • Learning an Adaptive Model for Extreme Low-light Raw Image Processing

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-04-14

    摘要: Low-light images suffer from severe noise and low illumination. Current deep learning models that are trained with real-world images have excellent noise reduction, but a ratio parameter must be chosen manually to complete the enhancement pipeline. In this work, we propose an adaptive low-light raw image enhancement network to avoid parameter-handcrafting and to improve image quality. The proposed method can be divided into two sub-models: Brightness Prediction (BP) and Exposure Shifting (ES). The former is designed to control the brightness of the resulting image by estimating a guideline exposure time t 1 . The latter learns to approximate an exposure-shifting operator ES, converting a low-light image with real exposure time t 0 to a noise-free image with guideline exposure time t 1 . Additionally, structural similarity (SSIM) loss and Image Enhancement Vector (IEV) are introduced to promote image quality, and a new Campus Image Dataset (CID) is proposed to overcome the limitations of the existing datasets and to supervise the training of the proposed model. In quantitative tests, it is shown that the proposed method has the lowest Noise Level Estimation (NLE) score compared with BM3D-based low-light algorithms, suggesting a superior denoising performance. Furthermore, those tests illustrate that the proposed method is able to adaptively control the global image brightness according to the content of the image scene. Lastly, the potential application in video processing is briefly discussed.

  • 完整的嗅觉神经通路假设及建模

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-04-03

    摘要:嗅觉神经通路研究是嗅觉研究的基础,对脑科学研究同样具有多方面的重要意义。综合已有相关研究成果,探索了完整的嗅觉神经通路假设。该神经通路包括以嗅球层为核心的前端部分、以内嗅皮质为核心的中端部分和以齿状回为核心的后端部分。在此基础上,本文构建了完整的嗅觉神经通路结构模型,并进行了初步分析。

  • 基于自我介绍视频的人格预测技术研究

    分类: 心理学 >> 应用心理学 分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-03-08

    摘要:人格影响着个体的工作生活方式,对于个体的心理疏导、职业发展等具有重要指导意义。传统方法通过量表测评人格得分存在个体拒绝回答、盲目作答等问题,近年来随着机器学习的发展为人格识别提供了新的思路。本文使用被试者自我介绍视频和大五人格量表得分,经过关键点提取、特征降维、建模、迭代调参等步骤,针对不同人格维度得到不同的预测模型。测试结果表明,基于自我介绍视频的人格预测模型在各维度都接近或达到中等相关,能够提供无侵扰的人格自动识别,为人格测量提供了新的思路。

  • Perspectives on Active Preventive Measures of Wuhan People against COVID-19 Epidemic at Home: A Comparative Study

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-02-24

    摘要: Background:The COVID-19 Epidemic emerged in Wuhan, Hubei province, China. Ever since Wuhan lockdown on January 23rd, mass quarantines were exercised on Wuhan and other epidemic areas of China. We aimed to clarify how ordinary Wuhan people defend against COVID-19 epidemic at home through the Internet survey. Methods:A questionnaire survey, consisting of 30 questions were posted on the Internet. The following aspects were investigated: household preventive measures, self-monitoring of discomfort symptoms, immunity boosting against the epidemic, frequency and reasons of outgoing and mental status of the isolated people. The questionnaire was circulated on Wechat. We marked the areas based on the surveyed network IP addresses and categorized respondents into group A(Wuhan), B(Hubei Province excluding Wuhan ), C, and D based on the epidemic severity of their areas announced by Baidu.com at 17:00 on February 8, 2020. And a comparative study was conducted to illustrate how Wuhan people took the anti-COVID-19 strategies and how efficient these preventive measures were. Findings:In terms of discomfort symptoms, Wuhan, as Group A, had the lowest asymptomatic percentages (70.2%), compared to the average 78.5% (±7%). Considering the three typical symptoms for the COVID-19, i.e., cough, fever and fatigue, Wuhan (9.67%) greatly deviated from the average (7.68%). The fatigue was the most significant factor in the deviation, exceeding the average by 1.35%. In terms of household protection measures, most people or families were able to take effective protection measures with very low frequency of going out, but the percentage of those who took this practice was obviously smaller in Wuhan and Hubei Province. From the aspect of going out, most of the people in Wuhan only went out for shopping and work, with a small number of people for social gathering. In terms of immunity boosting, compared with Group C and D, it was relatively lower in Wuhan. Overall, most people chose to enhance their immunity through regular schedule, exercise, sufficient nutrition. Only 33.44% of people in Group A did not go out, and 59.97% had to go out for living supplies, which was the highest level among the four groups. However, the percentage of people who went out for work and unnecessary activities remains the lowest while 1% of the population went out for public welfare activities, higher than other groups. Worry about the family health topped all the parameters for all the groups. Among them, Wuhan has reached a maximum of 49.61%, higher than the average level of 36.62% (± 10.69%). Mental status except for feeling bored and lonely were the highest in Wuhan. Suggestions:When the epidemic prevention and control is still in a sticky state, and Wuhan started a stricter control measure, the closed management of communities, on Feb 11, 2020, it is expected that our findings can provide some insights into the current household preventive actions and arouse more attentions of the public to some ignored preventive precautions. Unnecessary outgoing should be strictly abandoned. Regular schedule, exercises and nutrition were the top 3 measures participants would choose to enhance their own immunity system. It seems that people in Wuhan would choose nutrition and regular scheduler rather than exercises as the primary immunity-boosting ways. Exercise should be especially advocated as an effective way to enhance the immunity system. In terms of physical condition, people in Wuhan should take more active measures when symptoms occurred. The mentality is also an important aspect requiring intensive attention with the conduct of stricter control management in Wuhan while the rest groups gradually resume to work and ordinary life.

  • 人工智能在新型冠状病毒(2019-nCoV)肺炎的应用进展:需求和机遇

    分类: 计算机科学 >> 计算机应用技术 提交时间: 2020-02-15

    摘要: [目的]探究人工智能在新型冠状病毒(2019-nCoV)的诊断、治疗和控制中的应用场景和进展,以利用人工智能为新型冠状病毒肺炎的防控提供助力。 [方法]剖析新型冠状病毒肺炎防控的技术需求,从人工智能基因测序、辅助诊断、远程专家系统、药物筛查与研制等方面,分析当前的应用进展,挖掘应用的机遇。 [结果]中国是新型冠状病毒疫情最严重的国家,存在诸多的技术短板有待科技助力,AI能在疫情防控中发挥出重要的作用,但目前处于初步阶段,缺乏经过验证的落地成果;AI辅助诊断领域重复性研发较多,其他方面研究较少。 [局限]当前应用的数据大部分来自网站报道,如有更多的学术性成果,进展的分析将更全面。 [结论]需要加大投入和调控,在数据、算法和算力共享的基础上,各方面全面展开研发。