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⏲ 0:12 👁 10K
In 2018, a dedicated team from the University of Cambridge set out to unearth the secrets buried within this ancient abode. Their discovery, Shanidar Z, emerged as a groundbreaking find, offering an unprecedented glimpse into the lives of the Neanderthals. The cave, once a silent witness to Neanderthal burials, now reveals evidence of their sophisticated culture and profound respect for the deceased.<br/><br/>The flattened skull of Shanidar Z, compressed by the weight of time, presented a unique challenge to the researchers. In the confines of their laboratory, they embarked on a meticulous reconstruction, transforming fragile bone fragments into the visage of a woman who walked the earth thousands of centuries before us. Her features, strikingly human-like, bridge the gap between our species and our long-lost relatives.<br/><br/>This remarkable tale of discovery is not just a chronicle of the past but a mirror reflecting our own humanity. The documentary “Secrets of the Neanderthals”, now available on Netflix, captures the essence of this journey. It’s a story that transcends science and touches the core of our existence, reminding us of the intricate tapestry of human evolution.
⏲ 5:35 👁 10K
In this session, we delve into the crucial components of Open RAN: new front haul eCPRI, mid haul, and back haul connectivity. Understanding these elements is essential for optimizing network performance. We'll cover why new front haul eCPRI is needed, explain the roles of mid haul and back haul, and discuss the advancements required in Open RAN to meet the super-fast latency and throughput demands of modern networks. Join us to learn how these connectivity solutions enhance Open RAN deployments.<br/><br/>Welcome to Session 25! Today, we explore the essential parts of Open RAN connectivity: new front haul eCPRI, mid haul, and back haul. Understanding these components is key to enhancing network performance. We’ll discuss:<br/><br/>Why new front haul eCPRI is needed:<br/>* Enhanced Common Public Radio Interface (eCPRI) is an updated version of CPRI, essential for modern high-speed networks.<br/>* Benefits: Offers better bandwidth, reduced latency, and improved scalability compared to traditional CPRI.<br/><br/>What is mid haul:<br/>* Mid haul connects the centralized unit (CU) and distributed unit (DU) within the network.<br/>* Importance: Essential for efficient data transmission between the central and edge components, enabling flexibility in network deployment.<br/><br/>What is back haul:<br/>* Back haul refers to the connections between the distributed unit (DU) and the core network.<br/>* Role: Critical for carrying data from the edge of the network to the core, ensuring seamless communication and data flow.<br/><br/>Why these are needed in Open RAN:<br/>* These connectivity solutions enable the modular and scalable architecture of Open RAN.<br/>* Performance: They are crucial for achieving the desired network performance, including low latency and high throughput.<br/><br/>Advancements required in Open RAN:<br/>* Super-fast latency: To meet the demands of modern applications, Open RAN must continuously evolve to provide ultra-low latency.<br/>* High throughput: Ensuring high data transfer rates is necessary to support the growing data demands of users and applications.<br/><br/>By the end of this session, you'll have a clear understanding of how new front haul eCPRI, mid haul, and back haul connectivity work together to optimize Open RAN deployments, making them ready for the future of telecom networks.<br/><br/><br/>Subscribe to \
⏲ 5:5 👁 10K
Hello and welcome to Session 16 of our Open RAN series! Today, we're diving into the fascinating world of machine learning and its impact on Open RAN networks. We'll be focusing on how machine learning can boost Open RAN performance, specifically in predicting throughput based on MCS coding schemes. This is a crucial aspect for optimizing network performance and resource allocation in Open RAN environments.<br/><br/>1. Introduction to Machine Learning in Open RAN:<br/>Machine learning plays a pivotal role in enhancing Open RAN networks by enabling predictive capabilities, particularly in throughput optimization. By leveraging machine learning models, Open RAN can predict throughput based on the Modulation and Coding Scheme (MCS) coding scheme. Throughput prediction is critical for optimizing network performance and efficiently allocating resources, ensuring a seamless user experience.<br/><br/>2. Developing Machine Learning Models for Throughput Prediction:<br/>Developing a machine learning model for throughput prediction in Open RAN requires several key considerations. Firstly, the model needs to be trained on a dataset that includes throughput data and corresponding MCS values. The model should be designed to handle the complex relationships between these variables and predict throughput accurately. Mathematical functions and algorithms such as regression and neural networks are commonly used for this purpose, as they can effectively capture the underlying patterns in the data.<br/><br/>3. Deployment of Machine Learning Models in Open RAN:<br/>The deployment of machine learning models in Open RAN involves several steps. Once the model is trained and validated, it is deployed to the network where it operates in real-time. The model continuously monitors network conditions and predicts throughput based on incoming data. This information is then used to dynamically allocate network resources, optimizing performance and ensuring efficient operation.<br/><br/>4. Training Data Acquisition Process:<br/>Acquiring training data for the machine learning model involves collecting throughput data and corresponding MCS values from the network. This data is then cleaned and formatted to remove any inconsistencies or errors. The cleaned data is used to train the model, ensuring that it can accurately predict throughput in various network conditions. The training data acquisition process is crucial as it directly impacts the accuracy and reliability of the machine learning model.<br/><br/>Subscribe to \
⏲ 5:55 👁 10K
How to create Starbucks 3d paper coffee cup in Adobe illustrator 2023 quicktutorial | MJ graphics<br/><br/>In this quick tutorial, you will learn how to create Starbucks 3d paper coffee cup using Adobe Illustrator 2023.<br/><br/>Please let me know if you found this tutorial helpful. If you enjoyed the video, please like it. I would love to have you subscribe if you're new to my channel. Click on the bell icon to be notified of new videos.<br/><br/>#adobeillustratortutorial #3dtutorials #3dcup #mjgraphics
⏲ 1:31 👁 10K
When I helped a little girl I got fired but then I met her mom<br/>Japanese Manga in English<br/>Manga video to learn English
⏲ 12:49 👁 10K
Tajweed Course<br/>Surah Al-Ikhlas Learn Surah Al-Ikhlas with tajweed Surah Ikhlas word by word by Sayed Shafiq Attari
⏲ 12:17 👁 10K
Solving the Mystery Eggshells Under the Wardrobe by My Husband Learn English Through Story
⏲ 18:14 👁 10K
$900 Passive Daily - Learn the 2-Hour Workday Blueprint For Beginners - Digital Growth Community - Free Webinar<br/>Click to learn more:<br/>https://www.easyviralbiz.com<br/>https://www.facebook.com/EasyViralBiz/<br/>https://linktr.ee/easyviralbiz123<br/>https://bit.ly/m/easyviralbiz
⏲ 1:50:41 👁 10K
For relax your mind surah ikhlas Recitation
⏲ 0:25 👁 10K
Together, we can create a life that is a true reflection of your passions and aspirations. Welcome to our vibrant community, where the pursuit of happiness knows no bounds.
⏲ 0:34 👁 10K
Went matchmaking with the request of my cold blooded president<br/>Japanese Manga in English<br/>Manga video to learn English
⏲ 16:17 👁 10K
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