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https://www.readbyqxmd.com/read/29048314/the-effectiveness-of-a-learning-strategies-program-for-university-students
#1
Cristina Roces Montero, Beatriz Sierra Y Arizmendiarrieta
BACKGROUND: University lecturers often complain about their students’ lack of learning strategies, but not many universities in Spain offer specific courses in this area. Studies on their effectiveness are also rare. METHOD: This study presents the results of a Learning Strategies Course implemented at the School of Teacher Training and Education, University of Oviedo, Spain. A quasi-experimental design was used with an experi-mental (n = 60) and a control group (n = 57) of students on the Educational Psychology course...
November 2017: Psicothema
https://www.readbyqxmd.com/read/29042585/compact-morphology-based-poly-metallic-nodule-delineation
#2
Timm Schoening, Daniel O B Jones, Jens Greinert
Poly-metallic nodules are a marine resource considered for deep sea mining. Assessing nodule abundance is of interest for mining companies and to monitor potential environmental impact. Optical seafloor imaging allows quantifying poly-metallic nodule abundance at spatial scales from centimetres to square kilometres. Towed cameras and diving robots acquire high-resolution imagery that allow detecting individual nodules and measure their sizes. Spatial abundance statistics can be computed from these size measurements, providing e...
October 17, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29040672/unsupervised-learning-of-spatiotemporal-interictal-discharges-in-focal-epilepsy
#3
Maxime O Baud, Jonathan K Kleen, Gopala K Anumanchipalli, Liberty S Hamilton, Yee-Leng Tan, Robert Knowlton, Edward F Chang
BACKGROUND: Interictal epileptiform discharges are an important biomarker for localization of focal epilepsy, especially in patients who undergo chronic intracranial monitoring. Manual detection of these pathophysiological events is cumbersome, but is still superior to current rule-based approaches in most automated algorithms. OBJECTIVE: To develop an unsupervised machine-learning algorithm for the improved, automated detection and localization of interictal epileptiform discharges based on spatiotemporal pattern recognition...
October 10, 2017: Neurosurgery
https://www.readbyqxmd.com/read/29040288/music-viewed-by-its-entropy-content-a-novel-window-for-comparative-analysis
#4
Gerardo Febres, Klaus Jaffe
Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust a textual description from its original scale of observation to an arbitrarily selected scale, (b) a method to model the structure of any textual description based on the shape of the symbol frequency profiles, and (c) the concept of higher order entropy as the entropy associated with the deviations of a frequency-ranked symbol profile from a perfect Zipfian profile...
2017: PloS One
https://www.readbyqxmd.com/read/29040142/proposal-of-a-budget-friendly-camera-holder-for-endoscopic-ear-surgery
#5
Orhan Ozturan, Alper Yenigun, Fadlullah Aksoy, Burak Ertas
Endoscopic ear surgery (EES) is increasingly a preferred technique in otologic society. It offers excellent visualization of the anatomical structures directly and behind the corners with variable angled telescopes. It also provides reduced operative morbidity due to being able to perform surgical interventions with less invasive approaches. Operative preparation and setup time and cost of endoscopy system are less expensive compared with surgical microscopes. On the other hand, the main disadvantage of EES is that the surgery has to be performed with 1 single hand...
October 16, 2017: Journal of Craniofacial Surgery
https://www.readbyqxmd.com/read/29039378/dna-encoding-training-using-3d-gesture-interaction
#6
Stelian Nicola, Flavia-Laura Handrea, Mihaela Crişan-Vida, Lăcrămioara Stoicu-Tivadar
The work described in this paper summarizes the development process and presents the results of a human genetics training application, studying the 20 amino acids formed by the combination of the 3 nucleotides of DNA targeting mainly medical and bioinformatics students. Currently, the domain applications using recognized human gestures of the Leap Motion sensor are used in molecules controlling and learning from Mendeleev table or in visualizing the animated reactions of specific molecules with water. The novelty in the current application consists in using the Leap Motion sensor creating new gestures for the application control and creating a tag based algorithm corresponding to each amino acid, depending on the position in the 3D virtual space of the 4 nucleotides of DNA and their type...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29037586/successive-and-discrete-spaced-conditioning-in-active-avoidance-learning-in-young-and-aged-zebrafish
#7
Peng Yang, Riki Kajiwara, Ayako Tonoki, Motoyuki Itoh
We designed an automated device to study active avoidance learning abilities of zebrafish. Open source tools were used for the device control, statistical computing, and graphic outputs of data. Using the system, we developed active avoidance tests to examine the effects of trial spacing and aging on learning. Seven-month-old fish showed stronger avoidance behavior as measured by color preference index with discrete spaced training as compared to successive spaced training. Fifteen-month-old fish showed a similar trend, but with reduced cognitive abilities compared with 7-month-old fish...
October 13, 2017: Neuroscience Research
https://www.readbyqxmd.com/read/29037206/effects-of-continuous-visual-feedback-during-sitting-balance-training-in-chronic-stroke-survivors
#8
Laura Pellegrino, Psiche Giannoni, Lucio Marinelli, Maura Casadio
BACKGROUND: Postural control deficits are common in stroke survivors and often the rehabilitation programs include balance training based on visual feedback to improve the control of body position or of the voluntary shift of body weight in space. In the present work, a group of chronic stroke survivors, while sitting on a force plate, exercised the ability to control their Center of Pressure with a training based on continuous visual feedback. The goal of this study was to test if and to what extent chronic stroke survivors were able to learn the task and transfer the learned ability to a condition without visual feedback and to directions and displacement amplitudes different from those experienced during training...
October 16, 2017: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/29036085/local-receptive-field-constrained-stacked-sparse-autoencoder-for-classification-of-hyperspectral-images
#9
Xiaoqing Wan, Chunhui Zhao
As a competitive machine learning algorithm, the stacked sparse autoencoder (SSA) has achieved outstanding popularity in exploiting high-level features for classification of hyperspectral images (HSIs). In general, in the SSA architecture, the nodes between adjacent layers are fully connected and need to be iteratively fine-tuned during the pretraining stage; however, the nodes of previous layers further away may be less likely to have a dense correlation to the given node of subsequent layers. Therefore, to reduce the classification error and increase the learning rate, this paper proposes the general framework of locally connected SSA; that is, the biologically inspired local receptive field (LRF) constrained SSA architecture is employed to simultaneously characterize the local correlations of spectral features and extract high-level feature representations of hyperspectral data...
June 1, 2017: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
https://www.readbyqxmd.com/read/29035422/the-use-of-telemedicine-and-mobile-technology-to-promote-population-health-and-population-management-for-psychiatric-disorders
#10
REVIEW
Carolyn Turvey, John Fortney
PURPOSE OF REVIEW: This article discusses recent applications in telemedicine to promote the goals of population health and population management for people suffering psychiatric disorders. RECENT FINDINGS: The use of telemedicine to promote collaborative care, self-monitoring and chronic disease management, and population screening has demonstrated broad applicability and effectiveness. Collaborative care using videoconferencing to facilitate mental health specialty consults has demonstrated effectiveness in the treatment of depression, PTSD, and also ADHD in pediatric populations...
October 16, 2017: Current Psychiatry Reports
https://www.readbyqxmd.com/read/29035234/a-generalized-methodology-for-data-analysis
#11
Plamen P Angelov, Xiaowei Gu, Jose C Pr
Based on a critical analysis of data analytics and its foundations, we propose a functional approach to estimate data ensemble properties, which is based entirely on the empirical observations of discrete data samples and the relative proximity of these points in the data space and hence named empirical data analysis (EDA). The ensemble functions include the nonparametric square centrality (a measure of closeness used in graph theory) and typicality (an empirically derived quantity which resembles probability)...
October 12, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/29033305/machine-learning-of-human-pluripotent-stem-cell-derived-engineered-cardiac-tissue-contractility-for-automated-drug-classification
#12
Eugene K Lee, David D Tran, Wendy Keung, Patrick Chan, Gabriel Wong, Camie W Chan, Kevin D Costa, Ronald A Li, Michelle Khine
Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-derived cardiomyocytes and three-dimensional engineered cardiac tissue constructs to better recapitulate human heart function and drug responses. As these new platforms become increasingly sophisticated and high throughput, the drug screens result in larger multidimensional datasets...
October 12, 2017: Stem Cell Reports
https://www.readbyqxmd.com/read/29033260/predicting-microrna-biological-functions-based-on-genes-discriminant-analysis
#13
Tao Ding, Junhua Xu, Mengmeng Sun, Shanshan Zhu, Jie Gao
Although thousands of microRNAs (miRNAs) have been identified in recent experimental efforts, it remains a challenge to explore their specific biological functions through molecular biological experiments. Since those members from same family share same or similar biological functions, classifying new miRNAs into their corresponding families will be helpful for their further functional analysis. In this study, we initially built a vector space by characterizing the features from miRNA sequences and structures according to their miRBase family organizations...
September 29, 2017: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/29031664/nonlinearity-aware-based-dimensionality-reduction-and-over-sampling-for-ad-mci-classification-from-mri-measures
#14
Peng Cao, Xiaoli Liu, Jinzhu Yang, Dazhe Zhao, Min Huang, Jian Zhang, Osmar Zaiane
Alzheimer's disease (AD) has been not only a substantial financial burden to the health care system but also an emotional burden to patients and their families. Making accurate diagnosis of AD based on brain magnetic resonance imaging (MRI) is becoming more and more critical and emphasized at the earliest stages. However, the high dimensionality and imbalanced data issues are two major challenges in the study of computer aided AD diagnosis. The greatest limitations of existing dimensionality reduction and over-sampling methods are that they assume a linear relationship between the MRI features (predictor) and the disease status (response)...
October 6, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/29030801/deep-arm-ear-ecg-image-learning-for-highly-wearable-biometric-human-identification
#15
Qingxue Zhang, Dian Zhou
In this study, to advance smart health applications which have increasing security/privacy requirements, we propose a novel highly wearable ECG-based user identification system, empowered by both non-standard convenient ECG lead configurations and deep learning techniques. Specifically, to achieve a super wearability, we suggest situating all the ECG electrodes on the left upper-arm, or behind the ears, and successfully obtain weak but distinguishable ECG waveforms. Afterwards, to identify individuals from weak ECG, we further present a two-stage framework, including ECG imaging and deep feature learning/identification...
October 13, 2017: Annals of Biomedical Engineering
https://www.readbyqxmd.com/read/29030547/the-hidden-flow-structure-and-metric-space-of-network-embedding-algorithms-based-on-random-walks
#16
Weiwei Gu, Li Gong, Xiaodan Lou, Jiang Zhang
Network embedding which encodes all vertices in a network as a set of numerical vectors in accordance with it's local and global structures, has drawn widespread attention. Network embedding not only learns significant features of a network, such as the clustering and linking prediction but also learns the latent vector representation of the nodes which provides theoretical support for a variety of applications, such as visualization, link prediction, node classification, and recommendation. As the latest progress of the research, several algorithms based on random walks have been devised...
October 13, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29029394/long-non-coding-rna-h19-induces-hippocampal-neuronal-apoptosis-via-wnt-signaling-in-a-streptozotocin-induced-rat-model-of-diabetes-mellitus
#17
Yu-Hao Zhao, Tie-Feng Ji, Qi Luo, Jin-Lu Yu
Defects in hippocampal synaptic plasticity and disorders of memory and learning are the central nervous system complications of diabetes mellitus (DM). Here, we used a streptozotocin-induced rat DM model to investigate the effects of long non-coding RNA H19 (lncRNA H19) on learning and memory and apoptosis of hippocampal neurons, and the involvement of the Wnt signaling. Our data demonstrate that lncRNA H19 is highly expressed in rats with DM. Over-expression of lncRNA H19 increased positioning navigation latency in DM rats and decreased duration of space exploration...
September 12, 2017: Oncotarget
https://www.readbyqxmd.com/read/29028612/where-do-spontaneous-first-impressions-of-faces-come-from
#18
Harriet Over, Richard Cook
Humans spontaneously attribute a wide range of traits to strangers based solely on their facial features. These first impressions are known to exert striking effects on our choices and behaviours. In this paper, we provide a theoretical account of the origins of these spontaneous trait inferences. We describe a novel framework ('Trait Inference Mapping') in which trait inferences are products of mappings between locations in 'face space' and 'trait space'. These mappings are acquired during ontogeny and allow excitation of face representations to propagate automatically to associated trait representations...
October 10, 2017: Cognition
https://www.readbyqxmd.com/read/29028213/classification-of-imbalanced-data-by-oversampling-in-kernel-space-of-support-vector-machines
#19
Josey Mathew, Chee Khiang Pang, Ming Luo, Weng Hoe Leong
Historical data sets for fault stage diagnosis in industrial machines are often imbalanced and consist of multiple categories or classes. Learning discriminative models from such data sets is challenging due to the lack of representative data and the bias of traditional classifiers toward the majority class. Sampling methods like synthetic minority oversampling technique (SMOTE) have been traditionally used for such problems to artificially balance the data set before being trained by a classifier. This paper proposes a weighted kernel-based SMOTE (WK-SMOTE) that overcomes the limitation of SMOTE for nonlinear problems by oversampling in the feature space of support vector machine (SVM) classifier...
October 10, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29028211/online-heterogeneous-transfer-by-hedge-ensemble-of-offline-and-online-decisions
#20
Yuguang Yan, Qingyao Wu, Mingkui Tan, Michael K Ng, Huaqing Min, Ivor W Tsang
In this paper, we study the online heterogeneous transfer (OHT) learning problem, where the target data of interest arrive in an online manner, while the source data and auxiliary co-occurrence data are from offline sources and can be easily annotated. OHT is very challenging, since the feature spaces of the source and target domains are different. To address this, we propose a novel technique called OHT by hedge ensemble by exploiting both offline knowledge and online knowledge of different domains. To this end, we build an offline decision function based on a heterogeneous similarity that is constructed using labeled source data and unlabeled auxiliary co-occurrence data...
October 10, 2017: IEEE Transactions on Neural Networks and Learning Systems
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