bottom-up long term memory learning
Long term olfactory memories are stabilised via protein synthesis in Camponotus fellah ants
... olfactory learning and ...of learning and ...olfactory learning that are retrievable several days after training are indeed based on de novo protein ...two long-chain hydrocarbons, one paired ...
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Machine learning in FX trading with long short-term memory recurrent neural networks
... machine learning is suitable for predic- tion tasks, but these techniques cannot be used to explain the underlying economic ...machine learning which make it more suit- able to financial market prediction ...
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Arrhythmia Classification Using Long Short-Term Memory with Adaptive Learning Rate
... adaptive learning rate (ALR) as adaptive learning rate ...spectrogram learning to classify normal, atrial fibrillation (AF), noisy, and other ...
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First demonstration of olfactory learning and long term memory in honey bee queens
... as long as 1 month ( ...that memory plays a key role in the long-distance migrations of animals such as fish, turtles and birds (Milner-Gulland et ...
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Sentiment Analysis of Afaan Oromoo Facebook Media Using Deep Learning Approach
... LSTM is one of the recent successful algorithms in sentiment analysis and other natural language processing tasks. (Wang, et al., 2015)Described that identifying the sentiment of these social media blogs is a challenging ...
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Investigating the effects of the BDNF Val66Met polymorphism and physical activity on executive functioning, short term memory, long term memory and learning in older adults
... pattern of results in that, in a population of 205 older adults (Mean Age = 72.7 years) Val carriers benefit more from increased PA than Met carriers do. They reported active Val carriers performed significantly better ...
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Convolutional neural network-based model for web-based text classification
... deep learning approaches follow is as follows: First, input sentences are represented as a sequence of ...A term called “one-hot vector” represents each word in that ...deep learning models are ...
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Original Article Learning-dependent LTP and synaptic ultrastructural modification after physical exercise in rats with middle cerebral artery occlusion: relevance for learning and memory
... of learning and memory performance following physical ...of learning and memory are accompanied by long-term enhan- cement of synaptic transmission efficacy and synaptic ...
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Unified Framework For Deep Learning Based Text Classification
... Deep learning has emerged as a very popular approach for solving large scale pattern recognition ...deep learning based AI systems that have been trained to do sentiment analysis on social media or business ...
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The Research of Low Earth Orbit Prediction of Satellite Based on Deep Neural Network
... the long short-term memory neural network prediction is carried out based on the actual data of X, Y and Z coordinates of the satellite's geocentric inertial coordinate ...the learning samples ...
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The use of peer teaching to promote active learning amongst senior medical students
... Students found that the preparation process aided them in remembering what they have learned and which they believed would be stored in their long-term memory. This is in agreement with other ...
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NETWORK INTRUSION DETECTION USING DEEP NEURAL NETWORKS
... deep learning based approach is to implement such an effective and flexible ...deep learning, and Long Short Term Memory (LSTM) architecture is applied to a Recurrent Neural Network ...
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THE EFFECT OF HYPERGLYCEMIA O HIPPOCAMPUS EUROAL DESITY I FEMALE RATS
... spatial learning and ...involving long-term synaptic potentiation and depression, dendrite remodeling, synaptic turnover, and neurogenesis in the case of the dentate gyrus ...short-term ...
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ASPECT BASED SENTIMENT ANALYSIS USING ATTENTION MECHANISM AND GATED RECURRENT NETWORK
... machine learning algorithms started to play a major role in sentiment analysis ...machine learning, it has become possible to train more complex models on large data ...deep learning networks are ...
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Earthquake Prediction System by LSTM
... systemdeep learning technique called long short-term memory with gradient descent optimization algorithms(LSTM- AdaGrad ) networks predicting future earthquakes using data of past earthquakes ...
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Enhanced recurrent neural network for short-term wind farm power output prediction
... involves long short-term memory (LSTM) and a dropout regularisation (LSTM- Dropout) model for learning nonlinear temporal features from the wind series data to control ...the learning ...
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The effects of continuous versus partial reinforcement schedules on associative learning, memory and extinction in Lymnaea stagnalis
... influenced learning and/or the duration of memory ...produce learning and long-term ...in learning and long-term memory that persists for 2 days but not for ...
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Prediction of Multi Currency Exchange Rates Using Deep Learning
... deep learning models which include top foreign exchange (Forex) ...Deep Learning model using Support Vector Regressor (SVR), Artificial Neural Network (ANN), Long Short-Term Memory ...
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The role of memory stores in mobile-based English learning environment: A case study of Iranian learners
... Working Memory - At this stage and process, learners choose some of the words and images for further processing in working memory and then they form the representation of sounds and images in their working ...
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A quantitative proteomic analysis of long-term memory
... most memory systems (as based on sheer neuron numbers) we have chosen to use a reductionist model sys- tem of memory formation in ...of learning and ...including long-term memo- ries ...
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