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https://www.readbyqxmd.com/read/28092578/experienced-gray-wolf-optimization-through-reinforcement-learning-and-neural-networks
#1
E Emary, Hossam M Zawbaa, Crina Grosan
In this paper, a variant of gray wolf optimization (GWO) that uses reinforcement learning principles combined with neural networks to enhance the performance is proposed. The aim is to overcome, by reinforced learning, the common challenge of setting the right parameters for the algorithm. In GWO, a single parameter is used to control the exploration/exploitation rate, which influences the performance of the algorithm. Rather than using a global way to change this parameter for all the agents, we use reinforcement learning to set it on an individual basis...
January 10, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28092576/multiple-instance-learning-for-medical-image-and-video-analysis
#2
Gwenole Quellec, Guy Cazuguel, Beatrice Cochener, Mathieu Lamard
Multiple-Instance Learning (MIL) is a recent machine learning paradigm that is particularly well suited to Medical Image and Video Analysis (MIVA) tasks. Based solely on class labels assigned globally to images or videos, MIL algorithms learn to detect relevant patterns locally in images or videos. These patterns are then used for classification at a global level. Because supervision relies on global labels, manual segmentations are not needed to train MIL algorithms, unlike traditional Single-Instance Learning (SIL) algorithms...
January 10, 2017: IEEE Reviews in Biomedical Engineering
https://www.readbyqxmd.com/read/28092553/deep-aesthetic-quality-assessment-with-semantic-information
#3
Yueying Kao, Ran He, Kaiqi Huang
Human beings often assess the aesthetic quality of an image coupled with the identification of the image's semantic content. This paper addresses the correlation issue between automatic aesthetic quality assessment and semantic recognition. We cast the assessment problem as the main task among a multitask deep model, and argue that semantic recognition task offers the key to address this problem. Based on convolutional neural networks, we employ a single and simple multi-task framework to efficiently utilize the supervision of aesthetic and semantic labels...
January 11, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28092545/heterogeneous-face-recognition-a-common-encoding-feature-discriminant-approach
#4
Dihong Gong, Zhifeng Li, Weilin Huang, Xuelong Li, Dacheng Tao
Heterogeneous face recognition is an important yet challenging problem in face recognition community. It refers to matching a probe face image to a gallery of face images taken from alternate imaging modality. The major challenge of heterogeneous face recognition lies in the great discrepancies between different image modalities. Conventional face feature descriptors, e.g. LBP, HOG and SIFT, are mostly designed in a handcrafted way and thus generally fail to extract the common discriminant information from the heterogeneous face images...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28092540/robust-and-discriminative-labeling-for-multi-label-active-learning-based-on-maximum-correntropy-criterion
#5
Bo Du, Zengmao Wang, Lefei Zhang, Liangpei Zhang, Dacheng Tao
Multi-label learning draws great interests in many real world applications. It is a highly costly task to assign many labels by the oracle for one instance. Meanwhile, it is also hard to build a good model without diagnosing discriminative labels. Can we reduce the label costs and improve the ability to train a good model for multi-label learning simultaneously? Active learning addresses the less training samples problem by querying the most valuable samples to achieve a better performance with little costs...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28092522/active-self-paced-learning-for-cost-effective-and-progressive-face-identification
#6
Liang Lin, Keze Wang, Deyu Meng, Wangmeng Zuo, Lei Zhang
This paper aims to develop a novel cost-effective framework for face identification, which progressively maintains a batch of classifiers with the increasing face images of different individuals. By naturally combining two recently rising techniques: active learning (AL) and self-paced learning (SPL), our framework is capable of automatically annotating new instances and incorporating them into training under weak expert recertification. We first initialize the classifier using a few annotated samples for each individual, and extract image features using the convolutional neural nets...
January 16, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28092029/an-efficient-semi-supervised-learning-approach-to-predict-sh2-domain-mediated-interactions
#7
Kousik Kundu, Rolf Backofen
Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28090606/hierarchical-span-based-conditional-random-fields-for-labeling-and-segmenting-events-in-wearable-sensor-data-streams
#8
Roy J Adams, Nazir Saleheen, Edison Thomaz, Abhinav Parate, Santosh Kumar, Benjamin M Marlin
The field of mobile health (mHealth) has the potential to yield new insights into health and behavior through the analysis of continuously recorded data from wearable health and activity sensors. In this paper, we present a hierarchical span-based conditional random field model for the key problem of jointly detecting discrete events in such sensor data streams and segmenting these events into high-level activity sessions. Our model includes higher-order cardinality factors and inter-event duration factors to capture domain-specific structure in the label space...
June 2016: Proceedings of the ... International Conference on Machine Learning
https://www.readbyqxmd.com/read/28090605/domain-adaptation-methods-for-improving-lab-to-field-generalization-of-cocaine-detection-using-wearable-ecg
#9
Annamalai Natarajan, Gustavo Angarita, Edward Gaiser, Robert Malison, Deepak Ganesan, Benjamin M Marlin
Mobile health research on illicit drug use detection typically involves a two-stage study design where data to learn detectors is first collected in lab-based trials, followed by a deployment to subjects in a free-living environment to assess detector performance. While recent work has demonstrated the feasibility of wearable sensors for illicit drug use detection in the lab setting, several key problems can limit lab-to-field generalization performance. For example, lab-based data collection often has low ecological validity, the ground-truth event labels collected in the lab may not be available at the same level of temporal granularity in the field, and there can be significant variability between subjects...
September 2016: Proceedings of the ACM International Conference on Ubiquitous Computing
https://www.readbyqxmd.com/read/28088900/synaptic-plasticity-dementia-and-alzheimer-disease
#10
Pietro Giusti, Stephen D Skaper, Laura Facci, Morena Zusso
Neuroplasticity is not only shaped by learning and memory but is also a mediator of responses to neuron attrition and injury (compensatory plasticity). As an ongoing process it reacts to neuronal cell activity and injury, death, and genesis, which encompasses the modulation of structural and functional processes of axons, dendrites, and synapses. The range of structural elements that comprise plasticity includes long-term potentiation (a cellular correlate of learning and memory), synaptic efficacy and remodelling, synaptogenesis, axonal sprouting and dendritic remodelling, and neurogenesis and recruitment...
January 13, 2017: CNS & Neurological Disorders Drug Targets
https://www.readbyqxmd.com/read/28088356/advancing-the-prediction-accuracy-of-protein-protein-interactions-by-utilizing-evolutionary-information-from-position-specific-scoring-matrix-and-ensemble-classifier
#11
Lei Wang, Zhu-Hong You, Shi-Xiong Xia, Feng Liu, Xing Chen, Xin Yan, Yong Zhou
Protein-Protein Interactions (PPIs) are essential to most biological processes and play a critical role in most cellular functions. With the development of high-throughput biological techniques and in silico methods, a large number of PPI data have been generated for various organisms, but many problems remain unsolved. These factors promoted the development of the in silico methods based on machine learning to predict PPIs. In this study, we propose a novel method by combining ensemble Rotation Forest (RF) classifier and Discrete Cosine Transform (DCT) algorithm to predict the interactions among proteins...
January 11, 2017: Journal of Theoretical Biology
https://www.readbyqxmd.com/read/28079727/how-supervisor-experience-influences-trust-supervision-and-trainee-learning-a-qualitative-study
#12
Leslie Sheu, Jennifer R Kogan, Karen E Hauer
PURPOSE: Appropriate trust and supervision facilitate trainees' growth toward unsupervised practice. The authors investigated how supervisor experience influences trust, supervision, and subsequently trainee learning. METHOD: In a two-phase qualitative inductive content analysis, phase one entailed reviewing 44 internal medicine resident and attending supervisor interviews from two institutions (July 2013 to September 2014) for themes on how supervisor experience influences trust and supervision...
January 10, 2017: Academic Medicine: Journal of the Association of American Medical Colleges
https://www.readbyqxmd.com/read/28078685/peer-assessment-of-professional-behaviours-in-problem-based-learning-groups
#13
Chris Roberts, Christine Jorm, Stacey Gentilcore, Jim Crossley
CONTEXT: Peer assessment of professional behaviour within problem-based learning (PBL) groups can support learning and provide opportunities to identify and remediate problem behaviours. OBJECTIVES: We investigated whether a peer assessment of learning behaviours in PBL is sufficiently valid to support decision making about student professional behaviours. METHODS: Data were available for two cohorts of students, in which each student was rated by all of their PBL group peers using a modified version of a previously validated scale...
January 12, 2017: Medical Education
https://www.readbyqxmd.com/read/28073525/delineation-of-the-role-of-nutrient-variability-and-dreissenids-mollusca-bivalvia-on-phytoplankton-dynamics-in-the-bay-of-quinte-ontario-canada
#14
Yuko Shimoda, Sue B Watson, Michelle E Palmer, Marten A Koops, Shan Mugalingam, Andrew Morley, George B Arhonditsis
The Bay of Quinte, a Z-shaped embayment at the northeastern end of Lake Ontario, has a long history of eutrophication problems primarily manifested as spatially extensive algal blooms and predominance of toxic cyanobacteria. The purpose of this study was to identify the structural changes of the phytoplankton community induced by two environmental alterations: point-source phosphorus (P) loading reduction in the late 1970s and establishment of dreissenid mussels in the mid-1990s. A combination of statistical techniques was used to draw inference about compositional shifts of the phytoplankton assemblage, the consistency of the seasonal succession patterns along with the mechanisms underlying the algal biovolume variability in the Bay of Quinte over the past three decades...
May 2016: Harmful Algae
https://www.readbyqxmd.com/read/28066963/phenotiki-an-open-software-and-hardware-platform-for-affordable-and-easy-image-based-phenotyping-of-rosette-shaped-plants
#15
Massimo Minervini, Mario Valerio Giuffrida, Pierdomenico Perata, Sotirios A Tsaftaris
Phenotyping is important to understand plant biology but current solutions are either costly, not versatile or difficult to deploy. To solve this problem, we present Phenotiki, an affordable system for plant phenotyping which, relying on off-the-shelf parts, provides an easy to install and maintain platform, offering an out-of-box experience for a well established phenotyping need: imaging rosette-shaped plants. The accompanying software (with available source code) processes data originating from our device seamlessly and automatically...
January 9, 2017: Plant Journal: for Cell and Molecular Biology
https://www.readbyqxmd.com/read/28066703/how-common-are-wm-deficits-in-children-with-difficulties-in-reading-and-mathematics
#16
Susan E Gathercole, Francesca Woolgar, Rogier A Kievit, Duncan Astle, Tom Manly, Joni Holmes
The extent to which deficits in working memory (WM) are characteristic of children with reading and mathematics difficulties was investigated in a large sample aged 5-15 years reported to have problems in attention, learning and memory. WM performance was highly correlated with reading and mathematics scores. Although deficits in individual tests of short-term memory (STM) and WM occurred in less than half of the children with detected learning difficulties, three-quarters of the children with low reading and mathematics scores obtained one or more WM scores in the deficit range...
December 2016: Journal of Applied Research in Memory and Cognition
https://www.readbyqxmd.com/read/28062244/identification-of-time-varying-neural-dynamics-from-spike-train-data-using-multiwavelet-basis-functions
#17
Song Xu, Yang Li, Qi Guo, Xiao-Feng Yang, Rosa H M Chan
BACKGROUND: Tracking the changes of neural dynamics based on neuronal spiking activities is a critical step to understand the neurobiological basis of learning from behaving animals. These dynamical neurobiological processes associated with learning are also time-varying, which makes the modeling problem challenging. NEW METHOD: We developed a novel multiwavelet-based time-varying generalized Laguerre-Volterra (TVGLV) modeling framework to study the time-varying neural dynamical systems using natural spike train data...
January 4, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28061800/does-a-pbl-based-medical-curriculum-predispose-training-in-specific-career-paths-a-systematic-review-of-the-literature
#18
Jordan Tsigarides, Laura R Wingfield, Myutan Kulendran
BACKGROUND: North American medical schools have used problem-based learning (PBL) structured medical education for more than 60 years. However, it has only recently been introduced in other medical schools outside of North America. Since its inception, there has been the debate on whether the PBL learning process predisposes students to select certain career paths. OBJECTIVES: To review available evidence to determine the predisposition of specific career paths when undertaking a PBL-based medical curriculum...
January 7, 2017: BMC Research Notes
https://www.readbyqxmd.com/read/28061777/whatsapp-messenger-as-a-tool-to-supplement-medical-education-for-medical-students-on-clinical-attachment
#19
Lewis Raiman, Richard Antbring, Asad Mahmood
BACKGROUND: Instant messaging applications have the potential to improve and facilitate communication between hospital doctors and students, hence generating and improving learning opportunities. This study aims to demonstrate the feasibility and acceptability of instant messaging communication to supplement medical education for medical students whilst on clinical attachment. METHODS: A total of 6 WhatsApp Messenger (WhatsApp Inc.) groups were created for medical students on clinical attachment...
January 6, 2017: BMC Medical Education
https://www.readbyqxmd.com/read/28060838/attitudes-and-readiness-of-students-of-healthcare-professions-towards-interprofessional-learning
#20
Mari Kannan Maharajan, Kingston Rajiah, Suan Phaik Khoo, Dinesh Kumar Chellappan, Ranjit De Alwis, Hui Cing Chui, Lui Lee Tan, Yee Ning Tan, Shin Yee Lau
OBJECTIVES: To evaluate the attitudes and readiness of students of healthcare professions towards interprofessional learning. METHODOLOGY: A cross-sectional study design was used. Two different scales were used to measure the readiness for and perception of interprofessional learning; these were the 'Readiness for Interprofessional Learning Scale' and the 'Interdisciplinary Education Perception Scale'. A convenience sampling method was employed. The sample was drawn from undergraduate students enrolled in years 1 to 5 of medical, dental, pharmacy and health sciences programme...
2017: PloS One
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