Composite Deep Belief Network approach for enhanced Antepartum foetal electrocardiogram signal

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.     

Multilevel metric rank match for person re-identification

Metric learning is one of the important ways to improve the person re-identification (ReID) accurate, of which triplet loss is the most effect metric learning method. However, triplet loss only ranks the extracted feature at the end of the network, in this paper, we propose a multilevel metric rank match (MMRM) method, which ranks the extracted feature on multilevel of the network. At each rank level, the extracted features are ranked to find the hard sample pairs and the backward dissemination triplet loss. Each rank level has different penalize value to adjust the network, in which the value is bigger with the deeper level of the whole network. Experiment results on CUHK03, Market1501 and DukeMTMC datasets indicate that The MMRM algorithm can outperform the previous state-of-the-arts.     

The Twofold Assumption: A Response to Cole-Turner,Moritz, Peters and Peterson

Abstract

The article discusses points and perspectives offered by the four respondents to the R.J. Russell Fellow Lectures for 2013/14. Joshua M. Moritz and Ron Cole-Turner bring in new material from biblical and patristic traditions relevant for the proposal of deep incarnation. How does the concept of deep incarnation fare in relation to tradition and science? Ted Peters and Daniel J. Peterson raise questions about the compatibility between a compatibilist view of divine action and creaturely freedom on the one hand, and ideas of kenosis on the other. Which models of kenosis models are workable, and which forms of compatibilism?     

Incarnation Deep and Wide: A Response to Niels Gregersen

Abstract

This paper responds to Professor Niels Gregersen's theology of deep incarnation by doing three things. Section 1 summarizes and defines the idea of deep incarnation, with particular reference to what is intended by the key adjective “deep.” Section 2 engages Gregersen's proposal critically in relation to traditional options within the Christian doctrine of the incarnation. If Gregersen's language of “incarnation” is to be taken seriously as a proposal that is grounded in but goes beyond traditional ideas, its best chance for success lies in being as clear as possible about relationship with its traditional sources. Finally, Section 3 offers a few suggestions concerning the promise of deep incarnation for contemporary theology, especially for theology informed in part by serious engagement with the natural sciences.     

Acting with Feeling from Duty

A central claim in Kantian ethics is that an agent is properly morally motivated just in case she acts from duty alone. Bernard Williams, Michael Stocker, and Justin Oakley claim that certain emotionally infused actions, such as lending a compassionate helping hand, can only be done from compassion and not from duty. I argue that these critics have overlooked a distinction between an action's manner, how an action is done, and its motive, the agent's reason for acting. Through a range of examples I demonstrate how an emotion can determine an action's manner without also serving as the motive. Thus, it is possible for an agent to act compassionately from duty alone. This distinction between the manner and the motive of an action not only restores a central claim in Kantian ethics but it also allows for an expanded role of emotions in moral action.     

The impact of surface acting on coworker-directed voluntary workplace behaviours

The effects of emotional labour, that is, managing one’s emotions for work, not only predict a range of intrapersonal and organizational outcomes but can also spillover to affect non-work relationships. Despite this, relatively little is known about whether the performance of surface acting affects behaviours towards more proximal organizational members, how this occurs, and the role of supportive relationships in influencing this relationship. In this article, we examine the relationships between surface acting, state positive and negative affect, and co-worker support on co-worker-directed interpersonal behaviours in the workplace. Survey data collected at multiple time points suggest a moderated mediation model, in which surface acting interacts with co-worker support to influence employees’ voluntary behaviours through state affect. Specifically, our findings suggest that surface acting increases subsequent engagement in deviance behaviours by increasing the experience of negative affective states, especially when co-worker support is low. Surface acting also decreases the subsequent engagement of organizational citizenship behaviour through decreasing the experience of positive affective states. We conclude with a discussion of how surface acting can consequently lead to negative spirals in the organization and the implications of this for practice.     

Rolling element bearing fault diagnosis using convolutional neural network and vibration image

Detecting in prior bearing faults is an essential task of machine health monitoring because bearings are the vital components of rotary machines. The performance of traditional intelligent fault diagnosis methods depend on feature extraction of fault signals, which requires signal processing techniques, expert knowledge, and human labor. Recently, deep learning algorithms have been applied widely in machine health monitoring. With the capacity of automatically learning complex features of input data, deep learning architectures have great potential to overcome drawbacks of traditional intelligent fault diagnosis. This paper proposes a method for diagnosing bearing faults based on a deep structure of convolutional neural network. Using vibration signals directly as input data, the proposed method is an automatic fault diagnosis system which does not require any feature extraction techniques and achieves very high accuracy and robustness under noisy environments.     

On aggressiveness and violence in adolescence1

When considering aggressiveness and violence during adolescence, we must take into account multiple senses, which range from the healthy assertion of one's own space before others to the repetition of traumatic violent experiences such as the violation of bodily and spatial‐temporal boundaries. The author presents a survey of the views of different authors within psychoanalytical literature which allows us to question these terms, and turn then to the exploration of clinical practice. In studying the latter, acting out is brought to the fore, noting that not every adolescent act connotes a risk. The acts tackled in this case are those that, owing to their characteristics, may often endanger the very life of the adolescent. The author presents clinical material that focuses on adolescent acting out, highlighting the question of how to create, through the transference‐countertransference axis, a space within the analytic session where the patient's capacity to think may be incorporated, thus allowing the anticipation of action.     

情绪劳动策略与工作满意度关系的元分析

采用元分析方法探讨情绪劳动策略(包括表层扮演和深层扮演)与工作满意度的关系。经筛选, 共有120篇文献226个独立样本符合元分析标准(N = 79659)。元分析结果发现, 表层扮演与工作满意度有显著负相关, 深层扮演与工作满意度有显著正相关。调节效应检验发现, 不同表层扮演测量工具、文化背景差异、行业类型差异对表层扮演与工作满意度的关系没有显著影响; 不同工作满意度测量工具对表层扮演与工作满意度的关系有显著影响, 表现为单维的JSS工作满意度量表的调节效果高于多维的MSQ量表。不同深层扮演测量工具、不同工作满意度测量工具、文化背景差异对深层扮演与工作满意度的关系有显著影响, 分别表现为深层扮演量表Grandey (2003)、Diefendorff, Croyle和Gosserand (2005)、Brotheridge和Lee (2003)调节效应依次减小, 单维的JSS工作满意度量表的调节效果低于多维的MSQ量表, 东方文化背景的调节效果高于西方; 行业类型的差异对深层扮演与工作满意度关系的影响不显著。