“With the largest education program in our history and an impressive roster of exhibitors, ISC West continues to define innovation, foster connections, and offer solutions to the challenges of today and tomorrow. It is a must-attend event for those who drive the future of security." Three ...
This research work is funded by the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia through the project number MoE-IF-UJ-22-0708-3. Conflicts of Interest The authors declare no conflict of interest. References Shah, A.A.; Piro, G.; Grieco, L.A.; Boggia, G...
and the learning rate is 𝜂=0.01η=0.01; and (3) the parameters of the unexpected jobs: the maximum number of simultaneous unexpected jobs is 1, and to allow for transmission delays, the characteristics of each job in K are generated following the principle that 𝑐𝑘<𝑑𝐾+1ck<dK...
For training, a maximum of 40 epochs was available with an initial learning rate of 0.001. In this case, 30% of the data was used to validate, and 70% of the data to train. The parameters of the layers for this network were found in such a way that the lowest possible MSE will ...
New engineered systems joining physical and digital solutions are being employed in industry, education, etc. These new systems are networked by default, and private information is shared among the different components related to users, critical infrastructures, or business operations. In this context,...
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Some respondents emphasized the need to promote Inuit health through public education, ensuring that people understand the benefits of quitting binge drinking, smoking and drug use, and promoting the adoption of healthy behaviors such as healthy food choices and active living as a living lifestyle: ...
Moreover, the complex interdependencies between the cyber and physical domains are discussed in detail, providing insightful guidelines for key features and design decisions for future smart grid testbeds. Keywords: cyberattacks; cyber–physical systems; education; power systems; real-time testbed; ...
(2) machine learning-based methods [4,5,6,7], such as k-nearest neighbors (KNN), support vector machines (SVM), and decision trees (DT), etc. and (3) deep learning-based methods [8,9,10,11], such as deep belief networks (DBN), stacked autoencoders (SAE), convolutional neural ...