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Earth\u27s shadow will blanket the moon during a lunar eclipse on March 14
No full textA lunar eclipse is happening on Pi Day this year.
Lunar eclipses occur when Earth lines up between the Sun and the Moon, allowing the Moon to fall in our planet’s shadow. Although the Moon gets much darker, we can still see the shrouded satellite glow red and orange during a total eclipse. Earth’s atmosphere refracts sunlight, changing its trajectory and allowing some light to shine on the Moon. This is the light we see at dawn and dusk, when the sky turns from blue to yellow or orange. Thus, the eclipsed Moon is illuminated by all of Earth’s sunrises and sunsets
Schizophrenia: Breaking the Myths
No full textThroughout the years, schizophrenia has been commonly misunderstood and misrepresented within the media. Film, television, news outlets, and even social media frequently fail to do research before involving mental health, both intentionally and unintentionally creating turmoil for innocent people. Most of the depictions created are completely false and fail to properly reflect the reality of the disorder. Mental health is a hot topic, especially with young adults and college students. However, to this day schizophrenia still continues to be one of the most misunderstood and stigmatized mental disorders. By being educated on the reality of schizophrenia, we can help eliminate all negative stigmatization towards those who are affected by it
Visualizing RF Signal Strength in Mobile Ad Hoc Networks using CloudRF API and Known Path Loss Models
Get PDFA Mobile Ad hoc Network (MANET) is a spontaneous network consisting of wireless nodes which are mobile and self-configuring. Devices in MANET can move freely in any direction independently and change its link frequently to other devices that are within range. Due to its dynamic nature, accurate mapping of radio frequency (RF) signal strength is crucial for optimizing network performance. While path loss models, ray tracing, and radio propagation software are widely employed for predicting RF signal strength, a significant knowledge gap exists in assessing the accuracy of these tools in the context of MANET.
This research project consists of two parts. The first part evaluates the performance of three popular path loss models: the Friis Transmission Equation, Okumura, and Okumura-Hata. Additionally, CloudRF, a cloud-based RF signal strength platform, is evaluated alongside these traditional models using the ITU-R P.1546 model configuration. The evaluation uses measured data from two Persistent Systems MPU5 military radios in two different environments, suburban and urban Champaign, IL, with radios in line-of-sight at distances up to 1000 feet. The second part of the project involves building a dynamic mapping platform that utilizes a WebSocket connection to acquire GPS data from the radios, makes requests to CloudRF API, and saves the calculations in a KML file, which is then uploaded to Google Earth for visualization every second. This visualization enables us to observe the dynamic changes in signal strength as nodes move, which gives us an understanding of their behavior and performance
