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Alec Baldwin is stepping into the world of reality TV. The actor and his wife Hilaria have unveiled plans for a TLC reality series about their family. The pair shared the news with an Instagram video. The series tentatively titled 'The Baldwins' is due for release in 2025.
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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 \
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A TV station was forced to make a public apology after focusing on a fan's cleavage during coverage of a volleyball match between Turkey and the United States.<br/><br/>As defending champions Turkey triumphed in a 3-2 victory over the US, the camera cut to the ecstatic reactions of the crowd, relayed in slow motion for effect.<br/><br/>But it was their focus on one female supporter dressed in Turkey's colors that caused a backlash on social media, as several seconds of the woman jumping in jubilation was deemed too much for the intended audiences.<br/><br/>As the woman was reportedly forced to take her social media channels offline following criticism, Turkish TRT Spor released a statement blaming the coverage on its host broadcaster in the US.<br/><br/>They said an 'unwanted image' had appeared during the broadcast, blaming the 'disturbing situation' on the US. <br/><br/>'This image, which is completely contrary to our publication policy, originates from the US broadcaster, and the discomfort felt by this situation has been conveyed to the other party,' the statement read. <br/><br/>Fans erupted on Monday as Turkey prevailed in a hard-fought tie-breaker to overcome the Americans 3-2 in the FIVB Nations League.<br/><br/>As the crowd celebrated the victory on the pitch, the camera held its gaze for a few moments on the reaction of one fan dressed in all red.<br/><br/>The female supporter jumped on the spot, elated by the victory.<br/><br/>But broadcast in slow motion, critics in Turkey were offended by the woman's dress code.<br/><br/>The woman was sadly targeted by threats and insulting messages after the clip was broadcast, before being pushed to close her accounts, according to Turkish media.<br/><br/>With no mention of the woman or abuse endured, the broadcaster shared a press release on Monday after the game.<br/><br/>'We would like the public to know that the shooting and direction of the match was carried out by the US broadcaster,' the statement read.<br/><br/>They said TRT Spor and all other broadcasters using the US stream showed the images relayed to them 'without the possibility of intervention'.<br/><br/>'Therefore, this image which is completely contrary to our publication policy, originates from the US broadcaster, and the discomfort felt by this situation has been conveyed to the other party.<br/><br/>'TRT, in its capacity and responsibility as Turkey's public broadcaster, will continue to be a strong supporter of Turkish sports,' the statement said, wishing the Turkish team luck in their upcoming matches against Thailand, Dominican Republic, China, and Brazil later this month.<br/><br/>Not all agreed. One user on Twitter wrote: 'They should apologize to the real woman, why did they do it?' <br/><br/>Another said: 'She's happy to leave her alone'<br/><br/>But others thought the channel was right to 'apologise' for offending local sensibilities.
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