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If John von Neumann were designing a computer today, there’s no way he would build a thick wall between processing and memory. At least, that’s what computer engineer Naresh Shanbhag of the University of Illinois at Urbana-Champaign believes. 

For centuries, humans have been exploring the subsurface structure of planet Earth. Several Earth geophysical applications, such as mining, earthquake studies, and oil and gas exploration, have driven research that produced, over the years, ground-breaking theories and innovative technologies that image Earth’s subsurface. 

In the coming years, cities are expected to deal with an increasing number and type of services for their citizens, all having to do with overarching goals such as sustainability, environment, quality of life, energy saving, just to name a few. As the population living in urban areas is expected to double by 2050, there is a general consensus that any new process will require more than just an incremental upgrading of the cities’ organization, infrastructure, and services provided to its citizens.

Signal processing is always at the heart of the technology that differentiates today’s generations from those of the past is reaffirmed once again by the special issue on Machine Learning for Cognition in Radio Communications and Radar in IEEE Journal of Selected Topics in Signal Processing, February 2018.

The November 2017 special issue of SPM on deep learning for visual understanding surveyed deep-learning solutions under reinforcement; weakly supervised and multimodal settings, investigated their robustness; and presented overviews of their applications in domain adaptation, hashing, semantic segmentation, metric learning, inverse problems in imaging, image-to-text generation, and picture-quality assessment.

With the rapid development of multimedia technologies and the popularization of social networks, social multimedia content is being delivered to more and more users with a high quality of experience (QoE). However, as a huge amount of social users have ever-increasing demands to share and exchange multimedia content with each other, the current social multimedia analytics and delivery need to deal with various attacks perpetrated by malicious users or through spam content.

Speech and Language processing (SLP) is essentially a series of sequence-to-sequence learning problems. Conventional SLP systems map input to output sequences through module-based architectures where each module is independently trained. 

Neurotechnology is one of the hottest areas of engineering, and the technological achievements sound miraculous: Paralyzed people have controlled robotic limbs with their brains, while blind people are receiving implants that send signals to their visual centers.

Engineering safety and computer security have traditionally been viewed as separate fields: safety concentrates on the avoidance of physical harm; security protects information and privacy. When computers and physical plants did not interoperate, separation of safety and security was both reasonable and prudent. Given the advent of CPSs, we can no longer consider these problems as separate.

Recently, leveraging technological advances and using Big Data approaches for information management and processing in extreme events (e.g., Natural Disasters, Extreme Weather, Emergency Events, Diseases and etc.) have attracted much research attention. Multimedia is increasingly becoming the most important and valuable source for insights and information in extreme events.

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