Globally, breast cancer is reported as a primary cause of death in women. More than 1.8 million new breast cancer cases are diagnosed every year. Because of the current limitations on clinical imaging, researchers are motivated to investigate complementary tools and alternatives to available techniques for detecting breast cancer in earlier stages. This article presents a review of concepts and electromagnetic techniques for microwave breast imaging. More specifically, this work reviews ultra-wideband (UWB) antenna sensors and their current applications in medical imaging, leading to breast imaging. We review the use of UWB sensor based microwave energy in various imaging applications for breast tumor related diseases, tumor detection, and breast tumor detection. In microwave imaging, the back-scattered signals radiating by sensors from a human body are analyzed for changes in the electrical properties of tissues. Tumorous cells exhibit higher dielectric constants because of their high water content. The goal of this article is to provide microwave researchers with in-depth information on electromagnetic techniques for microwave imaging sensors and describe recent developments in these techniques.

The KITSUNE satellite is a 6-unit CubeSat platform with the main mission of 5-m-class Earth observation in low Earth orbit (LEO), and the payload is developed with a 31.4 MP commercial off-the-shelf sensor, customized optics, and a camera controller board. Even though the payload is designed for Earth observation and to capture man-made patterns on the ground as the main mission, a secondary mission is planned for the classification of wildfire images by the convolution neural network (CNN) approach. Therefore, KITSUNE will be the first CubeSat to employ CNN to classify wildfire images in LEO. In this study, a deep-learning approach is utilized onboard the satellite in order to reduce the downlink data by pre-processing instead of the traditional method of performing the image processing at the ground station. The pre-trained CNN models generated in Colab are saved in RPi CM3+, in which, an uplink command will execute the image classification algorithm and append the results on the captured image data. The on-ground testing indicated that it could achieve an overall accuracy of 98% and an F1 score of a 97% success rate in classifying the wildfire events running on the satellite system using the MiniVGGNet network. Meanwhile, the LeNet and ShallowNet models were also compared and implemented on the CubeSat with 95% and 92% F1 scores, respectively. Overall, this study demonstrated the capability of small satellites to perform CNN onboard in orbit. Finally, the KITSUNE satellite is deployed from ISS on March 2022.

Changes in the environment occur in cities due to increased urbanization and population growth. Sustainable Development Goal (SDG) 11 is intrinsically linked to the environment, one facet of which is the need for universal access to secure, inclusive, and accessible green and public places. As urban heat islands (UHI) have the potential to negatively influence cities and their residents, existing resources and data must be used to identify and quantify these effects. To address this, we present the use of satellite-derived (2013–2022) and meteorological data (2014–2020) to assess intra-urban heat islands in Manila City, Philippines. The assessment includes (a) understanding the temporal variability of air temperature measurements and outdoor thermal comfort based on meteorological data, (b) comparative and correlative analysis between common Land-Use Land Cover indicators (Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-up Index (NDBI)) and Land Surface Temperature (LST), (c) spatial and temporal analysis of LST using spatial statistics techniques, and (d) generation of an intra-urban heat island (IUHI) map with a recommended class of action using a suitability analysis model. Finally, the areas that need intervention are compared to the affected population, and suggestions to enhance the thermal characteristics of the city and mitigate the effects of UHI are established.

In this paper, an inkjet-printed flexible Radio-Frequency Identification (RFID) tag antenna is proposed for an ultra-high frequency (UHF) sensor application. The proposed tag antenna facilitates a system-level solution for low-cost and faster mass production of RFID passive tag antenna. The tag antenna consists of a modified meander line radiator with a semi-circular shaped feed network. The structure is printed on photo paper using silver nanoparticle conductive ink. The generic design outline, as well as tag antenna performances for several practical application aspects are investigated. The simulated and measured results verify the coverage of universal UHF RFID band with an omnidirectional radiation pattern and a long-read range of 15 ft. In addition, the read range for different bending angles and lifetimes of the tag antenna are also demonstrated.

Polymers used on low earth orbit (LEO) spacecraft surface suffer from an ultraviolet (UV) irradiation and orbital atomic oxygen (AO) erosion. These degradations may change the total electron emission yield (TEEY) of the materials and ultimately result in unexpected surface charging. In this paper, we chose polyimide (PI) film, a thermal control material, and carried out two types of ground-based degradation. The degradation methods were UV irradiation with five different equivalent solar hours, and AO erosion with two fluences equivalent to 0.5 and 1 year LEO flight time, respectively. Using an Auger microscope-based TEEY measurement system with a scanning measuring method, the TEEY of virgin and degraded PI films were tested and analyzed comparatively. The X-ray photoelectron spectrum, field-emission scanning electron microscope, and computational simulations were also used for element bonds analysis, roughness imaging, and electron depth calculation to discover the mechanisms of the degradation and their effects on the TEEY of the material.