Cases are presented to reveal how modern computerised infra-red thermal imaging has the potential to assist in early breast cancer detection. The history of thermography and some recent controversies surrounding mammo...Cases are presented to reveal how modern computerised infra-red thermal imaging has the potential to assist in early breast cancer detection. The history of thermography and some recent controversies surrounding mammography are discussed. Examples of thermal imaging combined with naturopathic interventions are described. Since 2002, more than 8000 women in New Zealand have chosen to include thermal imaging as a part of their breast health management. Breast thermal imaging combined with relevant health advice, resulted in a perceived worthwhile benefit to patients in managing overall health.展开更多
Alzheimers disease(AD)is a chronic neurodegenerative disease.The symptoms include memoryand spatial learning dificulties,language disorders,and loss of motivation,which get worse overtime,eventually ending in death.No...Alzheimers disease(AD)is a chronic neurodegenerative disease.The symptoms include memoryand spatial learning dificulties,language disorders,and loss of motivation,which get worse overtime,eventually ending in death.No ffective treatments are available for AD,currently.Currenttreatments only attenuate symptoms temporarily and are associated with severe side ffects.Nearinfra-red(NIR)light has been studied for a long time.We investigated the effect of NIR on ADusing a transgenic mouse model,which was obtained by co-injecting two vectors carrying ADmutations in amyloid precursor protein(APP)and presenilin-i(PSEN1)into C57BL/6J mice.The irradiation equipment consisted of an accommodating box and an LED array.The wave-length of NIR light emitted from LED was between 1040 nm and 1090 nm.The power densitydelivered at the level of the mice was approximately 15 mW/cm^(2),Firstly,we treated the micewith NIR for 40 days,Then,the irradiation was suspended for 28 days.Finally,another 15 daystreatment was brought to mice.We conducted Morris water maze and immunofluorescenceanalysis to evaluate the effects of treatment.Immunofuorescence analysis was based on mea-suring the quantity of plaques in mouse brain slices,Our results show that NIR light improvesmemory and spatial learning ability and reduces plaques moderately.NIR light represents apotential treatment for AD.展开更多
In-process damage to a cutting tool degrades the surfacenish of the job shaped by machining and causes a signicantnancial loss.This stimulates the need for Tool Condition Monitoring(TCM)t...In-process damage to a cutting tool degrades the surfacenish of the job shaped by machining and causes a signicantnancial loss.This stimulates the need for Tool Condition Monitoring(TCM)to assist detection of failure before it extends to the worse phase.Machine Learning(ML)based TCM has been extensively explored in the last decade.However,most of the research is now directed toward Deep Learning(DL).The“Deep”formulation,hierarchical compositionality,distributed representation and end-to-end learning of Neural Nets need to be explored to create a generalized TCM framework to perform eciently in a high-noise environment of cross-domain machining.With this motivation,the design of dierent CNN(Convolutional Neural Network)architectures such as AlexNet,ResNet-50,LeNet-5,and VGG-16 is presented in this paper.Real-time spindle vibrations corresponding to healthy and various faulty congurations of milling cutter were acquired.This data was transformed into the time-frequency domain and further processed by proposed architectures in graphical form,i.e.,spectrogram.The model is trained,tested,and validated considering dierent datasets and showcased promising results.展开更多
Introduction: Infra-red (IR) thermometry is a safe and valid method to determine internal and surface temperature in human subjects. Under conditions of brain damage (head injury or stroke) knowledge of changes in the...Introduction: Infra-red (IR) thermometry is a safe and valid method to determine internal and surface temperature in human subjects. Under conditions of brain damage (head injury or stroke) knowledge of changes in the temperature of intracranial tissue is justified because of the vulnerability of neurons to accelerated damage at temperatures at the upper end of the febrile range. Aim: To determine the temperature at the inner canthus (IC) of the eye as a potential surrogate for brain temperature. Methods: Invasive monitoring of deep brain structures, lateral ventricle and deep white matter. IR temperature readings obtained at right and left IC. Results: ?Strong correlations were evident between R and L IC and brain. Close, as well as poor, agreement between?? sites was shown in some patients and at some times. For right hemispheric lesions four had a better correlation between TbrV and TRIC when compared to TLIC.? When the correlation between TbrV and TLIC was better compared to TbrV and TRIC, four had a predominant right hemispheric lesion. Conclusions: Improved techniques for IR thermal imaging accuracy at the bedside has the potential to improve temperature measurement agreement. The predominant lesion side may have a bearing on maximum ipsilateral IC temperature Further studies are ongoing in this pilot study population.展开更多
噪声环境下语音检测准确率偏低是短波通话面临的公开挑战。当前已有方法应用有限,其根源在于难以可靠地在噪音环境下提取准确且高效的语音特征。针对上述问题,提出了一个面向短波通信的低秩方向梯度直方图(Low-rank Histogram of Orient...噪声环境下语音检测准确率偏低是短波通话面临的公开挑战。当前已有方法应用有限,其根源在于难以可靠地在噪音环境下提取准确且高效的语音特征。针对上述问题,提出了一个面向短波通信的低秩方向梯度直方图(Low-rank Histogram of Oriented Gradient,LHOG)话音检测方法。首先,对目标音频源数据进行预处理,实现噪声环境下语音信息的可视化表征;然后,在HOG特征提取器中嵌入低秩化结构,缓解特征中的冗余信息,并降低噪声干扰,从而获得准确且高效的特征;最后,通过常用的SVM分类模型便可在噪声环境中准确快速地区分话音和噪声。测试结果表明,该方法的准确率达到了95.12%,误报率仅为0.96%,漏报率为13.14%。与现有主流方法的对比实验证明,该方法话音检测准确率高,资源占用少,能够有效提高短波通信侦控效率。展开更多
【目的】为解决群养环境下生猪音频难以分离与识别的问题,提出基于欠定盲源分离与E C A-EfficientNetV2的生猪状态音频识别方法。【方法】以仿真群养环境下4类生猪音频信号作为观测信号,将信号稀疏表示后,通过层次聚类估计出信号混合矩...【目的】为解决群养环境下生猪音频难以分离与识别的问题,提出基于欠定盲源分离与E C A-EfficientNetV2的生猪状态音频识别方法。【方法】以仿真群养环境下4类生猪音频信号作为观测信号,将信号稀疏表示后,通过层次聚类估计出信号混合矩阵,并利用lp范数重构算法求解lp范数最小值以完成生猪音频信号重构。将重构信号转化为声谱图,分为进食声、咆哮声、哼叫声和发情声4类,利用ECA-EfficientNetV2网络模型识别音频,获取生猪状态。【结果】混合矩阵估计的归一化均方误差最低为3.266×10^(−4),分离重构的音频信噪比在3.254~4.267 dB之间。声谱图经ECA-EfficientNetV2识别检测,准确率高达98.35%;与经典卷积神经网络ResNet50和VGG16对比,准确率分别提升2.88和1.81个百分点;与原EfficientNetV2相比,准确率降低0.52个百分点,但模型参数量减少33.56%,浮点运算量(FLOPs)降低1.86 G,推理时间减少9.40 ms。【结论】基于盲源分离及改进EfficientNetV2的方法,轻量且高效地实现了分离与识别群养生猪音频信号。展开更多
提出一种基于高压放电声音识别快速评估电池健康状态的方法,目的在于以尽可能短的时间评估锂电池的健康状态(State of Health,SOH),以便电池的重组和梯次利用。研究主要从电子迁移能力方面建立电池高压放电与健康状态的联系,分析电池在...提出一种基于高压放电声音识别快速评估电池健康状态的方法,目的在于以尽可能短的时间评估锂电池的健康状态(State of Health,SOH),以便电池的重组和梯次利用。研究主要从电子迁移能力方面建立电池高压放电与健康状态的联系,分析电池在高压静电场中发生放电的声谱图特征,并将其作为电池SOH快速评估的依据。同时,针对方壳型磷酸铁锂电池搭建了一套自动化检测装置,并进行装置的结构和控制系统设计,实现了在5 min内完成单体电池的检测,极大地提高了锂电池的检测效率。展开更多
文摘Cases are presented to reveal how modern computerised infra-red thermal imaging has the potential to assist in early breast cancer detection. The history of thermography and some recent controversies surrounding mammography are discussed. Examples of thermal imaging combined with naturopathic interventions are described. Since 2002, more than 8000 women in New Zealand have chosen to include thermal imaging as a part of their breast health management. Breast thermal imaging combined with relevant health advice, resulted in a perceived worthwhile benefit to patients in managing overall health.
基金supported by grants awarded by the National Major Scientic Research Program of China(Grant No.2011CB910404)the National Nature Science Foundation of China(Grant No.61227017)+1 种基金the State Key Basic Research Development Program of China(2012CB518103)National Outstanding Young Scientist Award of China(61425006).
文摘Alzheimers disease(AD)is a chronic neurodegenerative disease.The symptoms include memoryand spatial learning dificulties,language disorders,and loss of motivation,which get worse overtime,eventually ending in death.No ffective treatments are available for AD,currently.Currenttreatments only attenuate symptoms temporarily and are associated with severe side ffects.Nearinfra-red(NIR)light has been studied for a long time.We investigated the effect of NIR on ADusing a transgenic mouse model,which was obtained by co-injecting two vectors carrying ADmutations in amyloid precursor protein(APP)and presenilin-i(PSEN1)into C57BL/6J mice.The irradiation equipment consisted of an accommodating box and an LED array.The wave-length of NIR light emitted from LED was between 1040 nm and 1090 nm.The power densitydelivered at the level of the mice was approximately 15 mW/cm^(2),Firstly,we treated the micewith NIR for 40 days,Then,the irradiation was suspended for 28 days.Finally,another 15 daystreatment was brought to mice.We conducted Morris water maze and immunofluorescenceanalysis to evaluate the effects of treatment.Immunofuorescence analysis was based on mea-suring the quantity of plaques in mouse brain slices,Our results show that NIR light improvesmemory and spatial learning ability and reduces plaques moderately.NIR light represents apotential treatment for AD.
文摘In-process damage to a cutting tool degrades the surfacenish of the job shaped by machining and causes a signicantnancial loss.This stimulates the need for Tool Condition Monitoring(TCM)to assist detection of failure before it extends to the worse phase.Machine Learning(ML)based TCM has been extensively explored in the last decade.However,most of the research is now directed toward Deep Learning(DL).The“Deep”formulation,hierarchical compositionality,distributed representation and end-to-end learning of Neural Nets need to be explored to create a generalized TCM framework to perform eciently in a high-noise environment of cross-domain machining.With this motivation,the design of dierent CNN(Convolutional Neural Network)architectures such as AlexNet,ResNet-50,LeNet-5,and VGG-16 is presented in this paper.Real-time spindle vibrations corresponding to healthy and various faulty congurations of milling cutter were acquired.This data was transformed into the time-frequency domain and further processed by proposed architectures in graphical form,i.e.,spectrogram.The model is trained,tested,and validated considering dierent datasets and showcased promising results.
文摘Introduction: Infra-red (IR) thermometry is a safe and valid method to determine internal and surface temperature in human subjects. Under conditions of brain damage (head injury or stroke) knowledge of changes in the temperature of intracranial tissue is justified because of the vulnerability of neurons to accelerated damage at temperatures at the upper end of the febrile range. Aim: To determine the temperature at the inner canthus (IC) of the eye as a potential surrogate for brain temperature. Methods: Invasive monitoring of deep brain structures, lateral ventricle and deep white matter. IR temperature readings obtained at right and left IC. Results: ?Strong correlations were evident between R and L IC and brain. Close, as well as poor, agreement between?? sites was shown in some patients and at some times. For right hemispheric lesions four had a better correlation between TbrV and TRIC when compared to TLIC.? When the correlation between TbrV and TLIC was better compared to TbrV and TRIC, four had a predominant right hemispheric lesion. Conclusions: Improved techniques for IR thermal imaging accuracy at the bedside has the potential to improve temperature measurement agreement. The predominant lesion side may have a bearing on maximum ipsilateral IC temperature Further studies are ongoing in this pilot study population.
文摘噪声环境下语音检测准确率偏低是短波通话面临的公开挑战。当前已有方法应用有限,其根源在于难以可靠地在噪音环境下提取准确且高效的语音特征。针对上述问题,提出了一个面向短波通信的低秩方向梯度直方图(Low-rank Histogram of Oriented Gradient,LHOG)话音检测方法。首先,对目标音频源数据进行预处理,实现噪声环境下语音信息的可视化表征;然后,在HOG特征提取器中嵌入低秩化结构,缓解特征中的冗余信息,并降低噪声干扰,从而获得准确且高效的特征;最后,通过常用的SVM分类模型便可在噪声环境中准确快速地区分话音和噪声。测试结果表明,该方法的准确率达到了95.12%,误报率仅为0.96%,漏报率为13.14%。与现有主流方法的对比实验证明,该方法话音检测准确率高,资源占用少,能够有效提高短波通信侦控效率。
文摘提出一种基于高压放电声音识别快速评估电池健康状态的方法,目的在于以尽可能短的时间评估锂电池的健康状态(State of Health,SOH),以便电池的重组和梯次利用。研究主要从电子迁移能力方面建立电池高压放电与健康状态的联系,分析电池在高压静电场中发生放电的声谱图特征,并将其作为电池SOH快速评估的依据。同时,针对方壳型磷酸铁锂电池搭建了一套自动化检测装置,并进行装置的结构和控制系统设计,实现了在5 min内完成单体电池的检测,极大地提高了锂电池的检测效率。
