Emergent spatio-temporal multimodal learning using a developmental network

Sequential Learning-Based Energy Consumption Prediction Model for Residential and Commercial Sectors

The use of electrical energy is directly proportional to the increase in global population, both concerning growing industrialization and rising residential demand. The need to achieve a balance between electrical energy production and consumption inspires researchers to develop forecasting models for optimal and economical energy use. Mostly, the residential and industrial sectors use metering sensors that only measure the consumed energy but are unable to manage electricity. In this paper, we present a comparative analysis of a variety of deep features with several sequential learning models to select the optimized hybrid architecture for energy consumption prediction. The best results are achieved using convolutional long short-term memory (ConvLSTM) integrated with bidirectional long short-term memory (BiLSTM). The ConvLSTM initially extracts features from the input data to produce encoded sequences that are decoded by BiLSTM and then proceeds with a final dense layer for energy consumption prediction. The overall framework consists of preprocessing raw data, extracting features, training the sequential model, and then evaluating it. The proposed energy consumption prediction model outperforms existing models over publicly available datasets, including Household and Korean commercial building datasets.

Multisensory Integration as a Window into Orderly and Disrupted Cognition and Communication

During our everyday lives, we are confronted with a vast amount of information from several sensory modalities. This multisensory information needs to be appropriately integrated for us to effectively engage with and learn from our world. Research carried out over the last half century has provided new insights into the way such multisensory processing improves human performance and perception; the neurophysiological foundations of multisensory function; the time course for its development; how multisensory abilities differ in clinical populations; and, most recently, the links between multisensory processing and cognitive abilities. This review summarizes the extant literature on multisensory function in typical and atypical circumstances, discusses the implications of the work carried out to date for theory and research, and points toward next steps for advancing the field.