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"Privacy-preserving anomaly counting for time-series data in edge-assis" by Shijin Chen, Willy Susilo et al.

Crowdsensing is an emerging data collection paradigm that enables data collected from a large number of Internet of Things devices to support effective decision-making. Anomaly counting as a data analysis method allows the identification of unintended behaviors to enhance decision-making capabilities. However, ensuring the sensing data privacy and increasing the willingness of data providers are significant challenges to guarantee quality decision-making. This paper proposes a flexible mechanism to provide the service of privacy-preserving anomaly counting for time-series data in edge-assisted crowdsensing. Specifically, to protect the sensing data of the data providers, a secure secret sharing protocol is designed based on additive secret sharing. Next, a privacy-preserving anomaly counting algorithm based on the windowed Gaussian anomaly detector is proposed, and multiple secure sub-protocols are employed as building blocks to guarantee the privacy of the counting result and the sens ....

Anomaly Detection , Homomorphic Encryption , Privacy Protection , Time Series Data ,

Solving brain dynamics gives rise to flexible machine-learning models

MIT researchers solved a differential equation behind the interaction of two neurons through synapses to unlock a new type of speedy and efficient artificial intelligence algorithms. ....

Gerald Teschl , Sildomar Monteiro , Daniela Rus , Max Tschaikowski , Alexander Amini , Mathias Lechner , Aaron Ray , Aurora Flight Sciences , Research Affiliate Ramin Hasani , Artificial Intelligence Laboratory , Aalborg University , Machine Learning Group , University Of Vienna , Nature Machine , Computer Science , Affiliate Ramin Hasani , Liquid Cfc , Lucas Liebenwein , Mit Csail , Neural Networks , Differential Equations , Liquid Neural Networks , Time Series Data , Daniela Rus , Losed Form Continuous Time Cfc Neural Network , Fc Models ,

Taking a magnifying glass to data center operations

The MIT Lincoln Laboratory Supercomputing Center has released a dataset containing more than a million jobs run on its TX-GAIA supercomputer, with the goal of using this data to feed AI research into optimizing data center resources. The team has kicked off the MIT Datacenter Challenge to mobilize this research. ....

United States , Baolin Li , Vijay Gadepally , Neil Thompson , Siddharth Samsi , Us Department Of Defense , Artificial Intelligence Laboratory , International Conference For High Performance Computing , Professor Charles Leiserson Supertech Research Group , Us Air , Lincoln Laboratory Supercomputing Center , Professor Devesh Tiwari At Northeastern University , International Symposium On High , Laboratory Supercomputing Center , High Performance Computer Architecture , Distributed Processing Symposium , Annual Conference , North American Chapter , Computational Linguistics , Embedded Computing Conference , International Conference , High Performance Computing , Devesh Tiwari , Northeastern University , Datacenter Challenge , Professor Charles Leiserson ,

Deep-learning technique predicts clinical treatment outcomes

MIT and IBM researchers develop a new deep learning methodology that simulates counterfactual, time-varying and dynamic treatment strategies for critically ill patients, allowing doctors to choose the best course of action. ....

Zach Shahn , Mohamed Ghalwash , Prithwish Chakraborty , Yuria Utsumi , Piyush Madan , Rui Li Meng , Watson Ai Lab , Institute For Medical Engineering , Proceedings Of Machine Learning Research , Cloud Services Daby Sow , Li Wei Lehman , Medical Engineering , Machine Learning Research , Hybrid Cloud Services Daby Sow , Massachusetts Institute Of Technology , It News , It Research , Mit Ibm Watson Ai Laboratory , Institute For Medical Engineering And Science Imes , Deep Learning , Ai In Medicine , 5g Net , Ausal Counterfactual Prediction , G Computation Algorithm , Recurrent Neural Networks , Nonlinear Dynamics ,

Fabrication of Freestanding Pressure-Sensitive Nano-Sheet

This article discusses research into the fabrication of freestanding pressure-sensitive nano-sheet (PSNS) using a sacrificial layer process. ....

New York , United States , San Diego , Megan Craignov , Megan Craig , Frontier Cellular Research , Proceedings Of The Institution Mechanical Engineers , Journal Of Aerospace Engineering , Nanosheet Technology , Journal Of The American Chemical Society , Journal Of The American Helicopter Society , International Journal Of Heat , Journal Of Biomedical Materials Research Part , Teflon Plate , Aluminum Plate , Pressure Sensitive Nano Sheet , Optical Pressure , Temperature Sensitive Paints , Surface Pressure Measurements , Fluid Mechanics , Mechanical Engineers , Aerospace Engineering , Data Driven Approach , Noise Reduction , Pressure Sensitive Paint Data Based , Modal Expansion ,