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The development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks
Proceedings of the 33rd Annual Hawaii International Conference on System Sciences
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A scheme for building a decision model of short-term liquidity analysis from domain experts is presented, which combines the features of both process tracing approach and output analysis approach. ...
The output analysis component applies Probability Neural Network to build a decision model based on the predictions of the initial model. ...
Concurrent Protocol Analysis and Probabilistic Neural Network The Concurrent Protocol Analysis is a well recognized method for using verbal data to study cognitive processes in many areas of science [ ...
doi:10.1109/hicss.2000.926652
dblp:conf/hicss/LiSS00
fatcat:6khqbfqpxrahpes7leekkkg6si
Paper titles
2020
2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)
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Perceived Temperature in Virtual Reality through Interactive Audio Markov Transition Field and Convolutional Long Short-Term Memory Neural Network for Manufacturing Quality Prediction Modeling of malware ...
for Improving Deep Learning in Image Classification Problem Implementation of a Four-class Motor Imagery BCI using Long Short-term Memory Neural Network Implementation of Dynamic Task Assignment for Smartphone ...
doi:10.1109/icce-taiwan49838.2020.9258179
fatcat:2eheaztzhncixhbvp7nrbzml4m
Role of Artificial Intelligence in the Early Diagnosis of Oral Cancer. A Scoping Review
2021
Cancers
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Thirty-six studies were included on the early detection of oral cancer based on images (photographs (optical imaging and enhancement technology) and cytology) with the application of AI models. ...
A search was performed in the PubMed, Web of Science, Embase and Google Scholar databases during the period from January 2000 to December 2020, referring to the early non-invasive diagnosis of oral cancer ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/cancers13184600
pmid:34572831
fatcat:qm7gaw5bmvctnowrjkd2izmrte
Assessment of Machine Learning Techniques in IoT-Based Architecture for the Monitoring and Prediction of COVID-19
2021
Electronics
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This research utilizes eight machine/deep learning techniques—Neural Network, Decision Table, Support Vector Machine (SVM), Naive Bayes, OneR, K-Nearest Neighbor (K-NN), Dense Neural Network (DNN), and ...
the Long Short-Term Memory technique—to detect coronavirus cases from time-sensitive information. ...
The findings of Table 3 and Figure 8 indicate that the models developed using the SVM, Neural Network, Naïve Bayes, K-NN, and Decision Table algorithms were successful in predicting verified and ...
doi:10.3390/electronics10151834
fatcat:byb7npucdfgwraksqrftldivfa
A Survey of Algorithms and Systems for Evacuating People in Confined Spaces
2019
Electronics
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The subject is now a multidisciplinary area of research where information and communication technologies (ICT), and in particular the Internet of Things (IoT), have a significant impact on sensing and ...
Starting from the history of emergency management research, we identify the emerging challenges concerning system optimisation, evacuee behaviour optimisation and data analysis, and the additional energy ...
patient. the velocity and the action of evacuees was determined by the social force model and the neural network model, respectively; the neural network had four inputs: the personality of an evacuee, ...
doi:10.3390/electronics8060711
fatcat:i6h2fpkyqrhgfpmjahvels5azu
Noise as a Resource for Computation and Learning in Networks of Spiking Neurons
2014
Proceedings of the IEEE
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I will also describe why these results are paving the way for a qualitative jump in the computational capability and learning performance of neuromorphic networks of spiking neurons with noise, and for ...
In addition, noise supports the self-organization of networks of spiking neurons, and learning from rewards. I will sketch here the main ideas and some consequences of these results. ...
Acknowledgment The author would like to thank S. Habenschuss, Z. Jonke, R. Legenstein, D. Pecevski, D. Potzinger, and E. Rueckert for scientific advice and help with the figures. ...
doi:10.1109/jproc.2014.2310593
fatcat:54mgt3scqje5flvjqnad45okfi
Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda
2021
Journal of Risk and Financial Management
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input data, and nature of the study; and 'model characteristics' are classified as data pre-processing, artificial intelligence technique, training algorithm, and performance measure. ...
We group the surveyed articles based on two major categories, namely, study characteristics and model characteristics, where 'study characteristics' are further categorized as the stock market covered, ...
Conflicts of Interest: The authors declare no conflict of interest. J. Risk Financial Manag. 2021, 14, 526 ...
doi:10.3390/jrfm14110526
fatcat:jthkt5lwnfa3vmh43vtgoo3kue
Artificial Intelligence for the Metaverse: A Survey
[article]
2022
arXiv
pre-print
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In this survey, we make a beneficial effort to explore the role of AI in the foundation and development of the metaverse. ...
In this context, metaverse, a term formed by combining meta and universe, has been introduced as a shared virtual world that is fueled by many emerging technologies, such as fifth-generation networks and ...
Recurrent neural network: RNN is one of the foundational neural network architectures from which various deep architectures, such as long short-term memory (LSTM) and gated recurrent unit (GRU) networks ...
arXiv:2202.10336v1
fatcat:35isd745dbaqfnpzthnmbaosue
A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses
2015
Frontiers in Neuroscience
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The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks, with short-term and long-term plasticity. ...
of computational neuroscience models and for building brain-inspired computing systems. ...
Acknowledgments Some of the circuits described in this work were developed jointly with Chiara Bartolozzi, Elisabetta Chicca, and Srinjoy Mitra. ...
doi:10.3389/fnins.2015.00141
pmid:25972778
pmcid:PMC4413675
fatcat:oxoslvrbyneiraxcqcod5jphm4
IEEE Access Special Section Editorial: Mission-Critical Sensors and Sensor Networks (MC-SSN)
2021
IEEE Access
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In MCSSN, the advantages of linking multiple electronic support measures and electronic attack assets to achieve improved capabilities across a networked mission-critical force have yet to be quantified ...
To support critical missions, sensors and sensor networks need to be flexible and interactive and continuously work despite limited bandwidth, intermittent connectivity, and with a large number of devices ...
This algorithm detects the changes in precipitation clouds for short-term forecasting and improves power spectrum. ...
doi:10.1109/access.2021.3068830
fatcat:mcmdtikg2vfqvokgu7pnm6xofq
SOCAIRE: Forecasting and Monitoring Urban Air Quality in Madrid
2021
Environmental Modelling & Software
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A new operational tool for air quality forecasting in Madrid is presented. • Produces probabilistic forecasts via a pipeline of statistical and neural models. • Can foresee the probability distribution ...
Maciąg et al. (2019) is an example of an ensemble model with a neural network and an ARIMA, in a similar vein to what will be our proposal, applied successfully to a real urban environment in the city ...
inertia and short-term correction inputs similar to the two previous ones. ...
doi:10.1016/j.envsoft.2021.105084
fatcat:z7jhx4xqjbanrhyayqm5mmxega
Can Biological Quantum Networks Solve NP-Hard Problems?
2019
Advanced Quantum Technologies
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2019 pre-print arXiv:1902.03121v1 fatcat:pzzkkgcad5hazjzthkvwxqntneOther Versions
This paper presents a personal view of several fields of philosophy and computational neurobiology in an attempt to suggest a realistic picture of how the brain might work as a basis for perception, consciousness ...
This might evidently influence the functionality of some nodes and perhaps even the overall intelligence of the brain network, but hardly give it any dramatically enhanced functionality. ...
Acknowledgement This work has been partially supported by the Knut & Alice Wallenberg Foundation (KAW) (WACQT project), and by the EU Quantum Technologies Flagship (820363 -QpenSuperQ). ...
doi:10.1002/qute.201800081
fatcat:nud3r5wn3zbwbknq7hvbwamye4
Artificial Intelligence and Medicine: A literature review
[article]
2022
arXiv
pre-print
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2022 pre-print arXiv:2205.00322v1 fatcat:yyym7ysorrhqtltwlp6j2twcry
This review of the literature will highlight the emerging field of artificial intelligence in medicine and its current level of development. ...
Since its inception, a large number of researchers throughout the globe have been pioneering the application of artificial intelligence in medicine. ...
(A) For the liver X receptors, we employed a deep learning model with a long-short term memory network. ...
arXiv:2205.00322v2
fatcat:5f2qcmezjrajbok56xdnl5n4ou
2020 Index IEEE Transactions on Industrial Informatics Vol. 16
2020
IEEE Transactions on Industrial Informatics
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Forests-Based Model for Ultra-Short-Term Prediction of PV Characteristics; TII Jan. 2020 202-214 Imran, A., see Hussain, B., TII Aug. 2020 4986-4996 Imran, M., see Fu, S., TII Sept. 2020 6013-6022 ...
J., see Sun, Q., TII Aug. 2020 5137-5149 Meng, K., see Zhang, Y., TII July 2020 4390-4402 Meng, K., Jia, Y., Yang, H., Niu, F., Wang, Y., and Sun, D., Motion Planning and Robust Control for the Endovascular ...
Short-Term Forecasting of Heat Demand of Buildings for Efficient and Optimal Energy Management Based on Integrated Machine Learning Models. ...
doi:10.1109/tii.2021.3053362
fatcat:blfvdtsc3fdstnk6qoaazskd3i
Cryptocurrency Trading: A Comprehensive Survey
[article]
2022
arXiv
pre-print
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In recent years, the tendency of the number of financial institutions including cryptocurrencies in their portfolios has accelerated. ...
This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e.g., cryptocurrency trading systems, bubble ...
Conclusions We provided a comprehensive overview and analysis of the research work on cryptocurrency trading. This survey presented a nomenclature of the definitions and current state of the art. ...
arXiv:2003.11352v5
fatcat:l7eih2yoazbq5i5lv4wh7c24ha
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