2,110 research outputs found

    Proposal for the Awakening Behavior Detection System Using Images and Adaptation for Fluctuation of Brightness Quantity in the Captured Image

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    Recently, accidents such that seniors fall down from the bed in care facilities or hospitals are increased. To prevent these accidents, we have developed the awakening behavior detection system using Neural Network. In this paper, it is a problem that the detection success rate of the current system using captured image in the clinical site is not enough. So, we analyze the captured image in the clinical site. From the result of the histogram analysis, it proves that the fluctuation of brightness quantity makes decrease the detection capability. Therefore, to decrease the influence of the brightness quantity, the histogram of the captured image should be equalized. Finally, we show that the histogram equalization reduces fluctuation of brightness quantity, numerically

    Deep Regionlets for Object Detection

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    In this paper, we propose a novel object detection framework named "Deep Regionlets" by establishing a bridge between deep neural networks and conventional detection schema for accurate generic object detection. Motivated by the abilities of regionlets for modeling object deformation and multiple aspect ratios, we incorporate regionlets into an end-to-end trainable deep learning framework. The deep regionlets framework consists of a region selection network and a deep regionlet learning module. Specifically, given a detection bounding box proposal, the region selection network provides guidance on where to select regions to learn the features from. The regionlet learning module focuses on local feature selection and transformation to alleviate local variations. To this end, we first realize non-rectangular region selection within the detection framework to accommodate variations in object appearance. Moreover, we design a "gating network" within the regionlet leaning module to enable soft regionlet selection and pooling. The Deep Regionlets framework is trained end-to-end without additional efforts. We perform ablation studies and conduct extensive experiments on the PASCAL VOC and Microsoft COCO datasets. The proposed framework outperforms state-of-the-art algorithms, such as RetinaNet and Mask R-CNN, even without additional segmentation labels.Comment: Accepted to ECCV 201

    Tres arquitecturas neuronales implementadas en la detección y categorización de anomalías en paneles fotovoltaicos

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    Solar panels are useful and efficient tools. They need to be kept in excellent working condition, but as time goes by, they suffer from external failures manifested in the environment. Therefore, the need for effective monitoring of such systems is highlighted. Neural models are perfect candidates to perform physical damage recognition. In this case, we compare the performance of three artificial neural networks, the multilayer perceptron, the densely connected neural network, and the ResNet-50 network in this identification problem. What is intended to be obtained from this method is the practical demonstration of the use of neural networks to solve real problems.Los paneles solares son herramientas útiles y eficientes. Necesitan mantenerse en excelente estado de funcionamiento, pero a medida que pasa el tiempo, sufren fallos por externos manifestados en el ambiente. Por lo tanto, se resalta la necesidad de hacer un seguimiento efectivo de dichos sistemas. Los modelos neuronales son candidatos perfectos para realizar el reconocimiento de los daños físicos. En este caso, se compara el desempeño de tres redes neuronales artificiales, el perceptrón multicapa, la red neuronal densamente conectada y la red ResNet-50 en este problema de identificación. Lo que se pretende obtener de este método es la demostración práctica del uso de las redes neuronales para solucionar problemas reales

    Multi-night cortico-basal recordings reveal mechanisms of NREM slow-wave suppression and spontaneous awakenings in Parkinson's disease

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    Sleep disturbance is a prevalent and disabling comorbidity in Parkinson’s disease (PD). We performed multi-night (n = 57) at-home intracranial recordings from electrocorticography and subcortical electrodes using sensing-enabled Deep Brain Stimulation (DBS), paired with portable polysomnography in four PD participants and one with cervical dystonia (clinical trial: NCT03582891). Cortico-basal activity in delta increased and in beta decreased during NREM (N2 + N3) versus wakefulness in PD. DBS caused further elevation in cortical delta and decrease in alpha and low-beta compared to DBS OFF state. Our primary outcome demonstrated an inverse interaction between subcortical beta and cortical slow-wave during NREM. Our secondary outcome revealed subcortical beta increases prior to spontaneous awakenings in PD. We classified NREM vs. wakefulness with high accuracy in both traditional (30 s: 92.6 ± 1.7%) and rapid (5 s: 88.3 ± 2.1%) data epochs of intracranial signals. Our findings elucidate sleep neurophysiology and impacts of DBS on sleep in PD informing adaptive DBS for sleep dysfunction

    Alterations in The States and Contents of Consciousness: Empirical and Theoretical Aspects

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    The main purpose of the present doctoral thesis is to investigate subjective experiences and cognitive processes in four different types of altered states of consciousness: naturally occurring dreaming, cognitively induced hypnosis, pharmacologically induced sedation, and pathological psychosis. Both empirical and theoretical research is carried out, resulting in four empirical and four theoretical studies. The thesis begins with a review of the main concepts used in consciousness research, the most influential philosophical and neurobiological theories of subjective experience, the classification of altered states of consciousness, and the main empirical methods used to study consciousness alterations. Next, findings of the original studies are discussed, as follows. Phenomenal consciousness is found to be dissociable from responsiveness, as subjective experiences do occur in unresponsive states, including anaesthetic-induced sedation and natural sleep, as demonstrated by post-awakening subjective reports. Two new tools for the content analysis of subjective experiences and dreams are presented, focusing on the diversity, complexity and dynamics of phenomenal consciousness. In addition, a new experimental paradigm of serial awakenings from non-rapid eye movement sleep is introduced, which enables more rapid sampling of dream reports than has been available in previous studies. It is also suggested that lucid dreaming can be studied using transcranial brain stimulation techniques and systematic analysis of pre-lucid dreaming. For blind judges, dreams of psychotic patients appear to be indistinguishable from waking mentation reports collected from the same patients, which indicates a close resemblance of these states of mind. However, despite phenomenological similarities, dreaming should not be treated as a uniform research model of psychotic or intact consciousness. Contrary to this, there seems to be a multiplicity of routes of how different states of consciousness can be associated. For instance, seemingly identical time perception distortions in different alterations of consciousness may have diverse underlying causes for these distortions. It is also shown that altered states do not necessarily exhibit impaired cognitive processing compared to a baseline waking state of consciousness: a case study of time perception in a hypnotic virtuoso indicates a more consistent perceptual timing under hypnosis than in a waking state. The thesis ends with a brief discussion of the most promising new perspectives for the study of alterations of consciousness.Siirretty Doriast

    Cognitive Performance and Morning Levels of Salivary Cortisol and α-Amylase in Children Reporting High vs. Low Daily Stress Perception

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    The aim of the present study was to assess the effects of daily stress perception on cognitive performance and morning basal salivary cortisol and alpha-amylase levels in healthy children aged 9-12. Participants were classified by whether they had low daily perceived stress (LPS, n = 27) or a high daily perceived stress (HPS, n = 26) using the Children Daily Stress Inventory (CDSI). Salivary cortisol and alpha-amylase were measured at awakening and 30 minutes later. Cognitive performance was assessed using the Cognitive Drug Research assessment system. The HPS group exhibited significantly poorer scores on speed of memory (p < .05) and continuity of attention (p < .05) relative to the LPS group. The HPS group also showed significantly lower morning cortisol levels at awakening and at +30 minutes measures in comparison with the LPS group (p < .05), and mean morning cortisol levels were negatively correlated with speed of memory (p < .05) in the 53 participants. No significant differences were observed between both groups in alpha-amylase levels. These findings suggest that daily perceived stress in children may impoverish cognitive performance via its modulating effects on the HPA axis activit

    Effective emotional regulation : bridging cognitive science and buddhist perspective

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    Emotions are an important part of human experience and how individuals regulate them denotes the level of personal happiness. The study of this regulation processes have been made from different traditions, that have used different tools to understand and explain them. In this article we approach the emotional regulation processes from two different perspectives: Tibetan Buddhist and Cognitive Psychology. We describe the understand­ing of emotional regulation processes from both traditions, trying to get the concepts as close as we can, so that at the end we will be able to propose a guideline model for the development of educational programs for the training of emotional regulation abilities.Las emociones son una parte importante de la experiencia humana y cómo los individuos las regulan denota el nivel de felicidad personal. El estudio de estos procesos regulativos ha sido llevado a cabo por diferentes tradiciones, que han utilizado distintas herramientas para comprenderlos y explicarlos. En este artículo nos acercamos a los procesos de regula­ción emocional a partir de dos perspectivas diferentes: el budismo tibetano y la psicología cognitiva. Se describe la concepción de los procesos de regulación emocional de ambas tradiciones, analizando los conceptos tan de cerca como sea posible, para así proponer un modelo de referencia para el desarrollo de programas educativos para la formación de las habilidades de regulación emocional
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