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1.
Antepartum Foetal surveillance is the most vital epoch of investigation during the pregnancy period. This surveillance would provide an opening to plan and manage the Foetus during Intrapartum and Antepartum stages of pregnancy. Moreover, it will help to identify high risk Foetuses during pregnancies which are complicated by maternal health conditions like diabetes mellitus, intrauterine growth restriction, etc. The foetal electrocardiogram (fECG) signal can be detected in the course of pregnancy from the Antepartum stage. Generally, fECG signal analysis is not carried out for Foetal surveillance. Rather, the traditional methodologies like phonocardiogram, etc. are being utilized. The reason is the unavailability of an effective methodology for providing good quality fECG signal. The proposal of a hybrid tactic called Bayesian Deep Belief Network (BDBN) for fECG signal enhancement is presented in this article. The proposed BDBN technique involves Baye’s filtering methodology in amalgamation with Deep Belief Network. The Baye’s filtering was employed to eliminate undesired signal components. Deep learning (DL) technique was utilized with Deep belief network (DBN) to extract high quality fECG signal. The methodology resulted with good quality fECG signal which is indeed valuable for timely Physician analysis. 相似文献
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本文对1—5岁汉族儿童使用双宾结构的状况进行了考察。首先对儿童语言中双宾结构的结构类型、句法功能及其发展状况进行了描述分析;在此基础上,讨论了儿童习得汉语双宾结构的机制。 相似文献
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Lee Huntington Philip Sanford Zeskind Julie R. Weiseman 《Infant behavior & development》1985,8(3):301-308
Spontaneous startles have been reported to occur most frequently in quiet sleep, less frequently in active sleep and drowse, and relatively nonexistent in the waking states. These findings may be a result of a focus on infants whose prenatal histories reflect a restricted range of the conditions to which normal newborns are exposed. The present study examined the spontaneous startle behavior of 30 newborn infants characterized by high numbers of obstetric complications and by indicators of prenatal malnutrition, but within the range of normal, healthy newborns. In this sample, startles were not limited to the sleep and drowse states. Because individual differences in a number of neonatal behaviors have been related to autonomic nervous system (ANS) functioning, the different pattern of spontaneous startles observed in this sample may be related to the functional integrity of this system. 相似文献
4.
An alternating least squares method for iteratively fitting the longitudinal reduced-rank regression model is proposed. The method uses ordinary least squares and majorization substeps to estimate the unknown parameters in the system and measurement equations of the model. In an example with cross-sectional data, it is shown how the results conform closely to results from eigenanalysis. Optimal scaling of nominal and ordinal variables is added in a third substep, and illustrated with two examples involving cross-sectional and longitudinal data.Financial support by the Institute for Traffic Safety Research (SWOV) in Leidschendam, The Netherlands is gratefully acknowledged. 相似文献
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This study investigated longitudinal relations between measures of neonatal state behavior and developmental outcome in a sample of preterm infants (N = 16). Results indicate that irritability/reactivity in the neonatal period is positively associated with Bayley scores and exploratory play at 8 months. Conversely, neonatal alertness was not associated with these developmental measures. These preliminary findings, based on a small sample, are discussed in the context of preterm function. 相似文献
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基于工作要求-资源理论, 本研究探讨了两种社交媒体使用目的对员工工作绩效影响的内部作用机制, 进而分析两种社交媒体使用目的对员工工作绩效的影响效果。通过369份“领导者-下属”匹配数据, 研究发现:(1)基于工作、社交的社交媒体使用均促进员工工作绩效; (2)基于工作、社交的社交媒体使用均通过工作投入影响工作绩效, 基于社交的社交媒体使用还通过关系冲突影响工作绩效; (3)社交媒体的工作使用和社交使用对员工工作绩效的影响存在相互替代关系。本研究结果不仅从理论上拓展了社交媒体使用的研究视角, 为后续研究提供新的理论框架, 同时通过比较分析为组织管理社交媒体使用提供了新思路。 相似文献
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In this work, we attempted to find out the relationship between different gait patterns and their corresponding cognitive states by using different statistical and machine learning approaches. This paper strongly focusses on the simulations followed by implementation of the proposed cognitive states i.e. (i) EmotionOriented State (EOS) (ii) Thinking Oriented State (TOS) (iii) Memory Oriented State(MOS) (iv) Simple Regular Oriented State (SROS). A novel approach was implemented by creating different environmental contexts for different gaits in our lab. An experimental method was performed to isolate movement artifact using Independent Component Analysis from recorded EEG(Electroencephalogram) signals. Measurement of joint angles from joint positions captured using Kinect V2 sensors was done with the help of OpenSim software. The relationship between different gaits and mental states was established using Pearsons Correlation Coefficient, ANOVA(Analysis of variance) and SVM(Support Vector Machine) classifier respectively. A strong relationship was found between them. The SVM classifier for the EOS and the non-EOS states based on joint angles inferred an accuracy of 81.08%. The ROC Curve for SVM classification depicted an AUC (area under the curve) of 0.9724. 相似文献
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