Forwarded from Algorithm of truth
FLAT EARTH DONT EXIST ! please dont go back . dont follow/support brain downgrade
Forwarded from Algorithm of truth
WE REMEMBER YOU FLAT EARTH THEORY IS A JESUITS PSY OP, FOR STOP PEOPLE FROM UNDERSTUNDING FREE ENERGY MODELS
Forwarded from Algorithm of truth
Forwarded from Algorithm of truth
Denver airport art........middle est....the sword is killing the star.
The Fertile Crescent is a historical region of the Middle East. The expression "Fertile Crescent" was coined in the twenties by archaeologistames This region is often referred to as the" cradle of civilization " due to its extraordinary importance in human history from the Neolithic to the Bronze and Iron Ages. Among other things, it was in the fertile valleys of the four great rivers of the region (Nile, Jordan, Tigris and Euphrates) where the first agricultural civilizations and the first great nations of Antiquity developed. The Sumerians, in particular, considered the representatives of the first settled civilization in history, flourished in Mesopotamia.
The Fertile Crescent is a historical region of the Middle East. The expression "Fertile Crescent" was coined in the twenties by archaeologistames This region is often referred to as the" cradle of civilization " due to its extraordinary importance in human history from the Neolithic to the Bronze and Iron Ages. Among other things, it was in the fertile valleys of the four great rivers of the region (Nile, Jordan, Tigris and Euphrates) where the first agricultural civilizations and the first great nations of Antiquity developed. The Sumerians, in particular, considered the representatives of the first settled civilization in history, flourished in Mesopotamia.
The Internet of bio-nano things (IoBNT) is an emerging paradigm employing nanoscale (~1–100 nm) biological transceivers to collect in vivo signaling information from the human body and communicate it to healthcare providers over the Internet. Bio-nano-things (BNT) offer external actuation of in-body molecular communication (MC) for targeted drug delivery to otherwise inaccessible parts of the human tissue. BNTs are inter-connected using chemical diffusion channels, forming an in vivo bio-nano network, connected to an external ex vivo environment such as the Internet using bio-cyber interfaces. Bio-luminescent bio-cyber interfacing (BBI) has proven to be promising in realizing IoBNT systems due to their non-obtrusive and low-cost implementation. BBI security, however, is a key concern during practical implementation since Internet connectivity exposes the interfaces to external threat vectors, and accurate classification of anomalous BBI traffic patterns is required to offer mitigation. However, parameter complexity and underlying intricate correlations among BBI traffic characteristics limit the use of existing machine-learning (ML) based anomaly detection methods typically requiring hand-crafted feature designing. To this end, the present work investigates the employment of deep learning (DL) algorithms allowing dynamic and scalable feature engineering to discriminate between normal and anomalous BBI traffic. During extensive validation using singular and multi-dimensional models on the generated dataset, our hybrid convolutional and recurrent ensemble (CNN + LSTM) reported an accuracy of approximately ~93.51% over other deep and shallow structures. Furthermore, employing a hybrid DL network allowed automated extraction of normal as well as temporal features in BBI data, eliminating manual selection and crafting of input features for accurate prediction. Finally, we recommend deployment primitives of the extracted optimal classifier in conventional intrusion detection systems as well as evolving non-Von Neumann architectures for real-time anomaly detection.