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SPM Article

There have been three key revolutions in the way that research has become accessible: publishing, code, and data. The second and third revolutions are still taking place, particularly driven by the rise of machine-learning and artificial intelligence research in the last decade. When I started my research career in 1995, the World Wide Web was still in its infancy. The popular Netscape browser had just been launched. Search engines were not widely used. While many academics owned e-mail addresses, few had web pages. If they did, they were not kept current.
The title of this editorial is borrowed from a popular children’s lullaby from the 1800s, which reads “Twinkle, twinkle, little star, how I wonder what you are!” It reminds me of the vast expanse of unexplored space (and science) that lie before us. 
 
The human race has always been fascinated by space - and who would not be? Its shining stars continually challenge us to get closer and unravel their mysteries. Civilizations old and new have been defined by their relationship with space and by their contribution to astronomy. 
 

The authors of [1], which was published in the November 2017 issue of IEEE Signal Processing Magazine, wish to add an acknowledgment to their article. The acknowledgment is as follows: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (number 2016R1A2B2014525) and by a grant from the National Science Foundation (IIS-1116656) awarded to Alan C. Bovik.

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The Bio-Imaging and Signal Processing Technical Committee (BISP-TC) of the IEEE Signal Processing Society (SPS) promotes activities in the broad technical areas of computerized image and signal processing with a clear focus on applications in biology and medicine.

As part of the IEEE Signal Processing Society (SPS), the Speech and Language Technical Committee (SLTC) promotes research and development activities for technologies that are used to process speech and natural language.

The knowledge of spatial distributions of physical quantities, such as radio-frequency (RF) interference, pollution, geomagnetic field magnitude, temperature, humidity, audio, and light intensity, will foster the development of new context-aware applications. For example, knowing the distribution of RF interference might significantly improve cognitive radio systems [1], [2].

Backscatter presents an emerging ultralow-power wireless communication paradigm. The ability to offer submilliwatt power consumption makes it a competitive core technology for Internet of Things (IoT) applications. In this article, we provide a tutorial of backscatter communication from the signal processing perspective as well as a survey of the recent research activities in this domain, primarily focusing on bistatic backscatter systems.

The IEEE Signal Processing Society Sensor Array and Multichannel Technical Committee (SAM TC) promotes activities within the technical areas of sensor array processing and multichannel statistical signal processing, including:

Advances in engineering and health science have brought a significant improvement in health care and increased life expectancy. As a result, there has been a substantial growth in the number of older adults around the globe, and that number is rising. According to a United Nations report, between 2015 and 2030, the number of adults over the age of 60 is projected to grow by 56%, with the total reaching nearly 2.1 billion by the year 2050 [1].

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