Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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Heng, Sovannarith, Phet Aimtongkham, Van Nhan Vo, Tri Gia Nguyen, and Chakchai So-In. 2020. "Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks" Sensors 20, no. 21: 6217. https://doi.org/10.3390/s20216217

Heng, Sovannarith, Phet Aimtongkham, Van Nhan Vo, Tri Gia Nguyen, and Chakchai So-In. 2020. "Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks" Sensors 20, no. 21: 6217. https://doi.org/10.3390/s20216217

ZoomText is the most popular screen magnifier for Windows. Windows also has a built-in magnifier that can be turned on through ease of access settings.

Heng S, Aimtongkham P, Vo VN, Nguyen TG, So-In C. Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks. Sensors. 2020; 20(21):6217. https://doi.org/10.3390/s20216217

Heng, S.; Aimtongkham, P.; Vo, V.N.; Nguyen, T.G.; So-In, C. Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks. Sensors 2020, 20, 6217. https://doi.org/10.3390/s20216217

SuperNova is available in three editions ranging from just magnification, to magnification with speech, and then magnification with screen reading. It has the industry’s only true touchscreen functionality and can be run on tablets and computers with lower processing and memory speeds. More information can be found on the Dolphin Website.

Heng S, Aimtongkham P, Vo VN, Nguyen TG, So-In C. Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks. Sensors. 2020; 20(21):6217. https://doi.org/10.3390/s20216217

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Heng, S.; Aimtongkham, P.; Vo, V.N.; Nguyen, T.G.; So-In, C. Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks. Sensors 2020, 20, 6217. https://doi.org/10.3390/s20216217

Screen magnification software allows users with low vision to read what is on the computer screen by enlarging and enhancing the text. The software often has some basic screen-reading functions as well.

Abstract: The transmission of high-volume multimedia content (e.g., images) is challenging for a resource-constrained wireless multimedia sensor network (WMSN) due to energy consumption requirements. Redundant image information can be compressed using traditional compression techniques at the cost of considerable energy consumption. Fortunately, compressed sensing (CS) has been introduced as a low-complexity coding scheme for WMSNs. However, the storage and processing of CS-generated images and measurement matrices require substantial memory. Block compressed sensing (BCS) can mitigate this problem. Nevertheless, allocating a fixed sampling to all blocks is impractical since each block holds different information. Although solutions such as adaptive block compressed sensing (ABCS) exist, they lack robustness across various types of images. As a solution, we propose a holistic WMSN architecture for image transmission that performs well on diverse images by leveraging saliency and standard deviation features. A fuzzy logic system (FLS) is then used to determine the appropriate features when allocating the sampling, and each corresponding block is resized using CS. The combined FLS and BCS algorithms are implemented with smoothed projected Landweber (SPL) reconstruction to determine the convergence speed. The experiments confirm the promising performance of the proposed algorithm compared with that of conventional and state-of-the-art algorithms. Keywords: adaptive sampling; block compressed sensing; feature selection; fuzzy logic system; wireless multimedia sensor networks