( MENAFN - EIN Presswire) Automotive Semiconductor Global market Report 2024 - Market Size, Trends, And Global Forecast 2024-2033 The Business Research Company's Early Year-End Sale! Get up to 30% off detailed market research reports-for a limited time only! LONDON, GREATER LONDON, UNITED KINGDOM, December 20, 2024 /EINPresswire / -- The Business Research Company's Early Year-End Sale! Get up to 30% off detailed market research reports-limited time only! What is the Projected Size of the Automotive Semiconductor Market? The automotive semiconductor market size has seen remarkable growth in recent years and is expected to grow from $54.94 billion in 2023 to $61.58 billion in 2024 at a compound annual growth rate CAGR of 12.1%. Key drivers of this growth include the increased demand for electric and hybrid vehicles, rise in disposable incomes, and the increased use of electronic components in the automotive industry. The market size is projected to achieve considerable growth in the next few years, reaching $97.3 billion in 2028 at a CAGR of 12.1%. The growth in the forecast period can be attributed to several trend-setting factors. For a detailed overview of the market, explore the sample report here: What Key Trends are Impacting the Automotive Semiconductor Market? The increasing popularity of autonomous vehicles, government initiatives for automotive semiconductors, and the increasing demand for passenger vehicles are some of the major trends expected to drive the market. Alongside these factors, advancements like resistive ram technology RRAM, product innovation, technology advancements, strategic partnerships, and the development of new products for automotive satellite camera modules are predicted to shape market trends. One of the significant drivers of the automotive semiconductor market is the increase in demand for electric and hybrid vehicles. This accelerated demand can be attributed in part to the economic impact of COVID-19, which has dampened demand for petrol and diesel cars but increased demand for electric and hybrid vehicles. Climate change concerns and ambitions to achieve net-zero emissions are driving the global shift toward emissions-free motoring, leading to a boom in the market for electric and hybrid vehicles. This shift not only benefits the environment but also helps to reduce reliance on petroleum products and supports local power vehicle production. The International Energy Agency reported that in 2022, electric car sales surpassed 10 million, reflecting a substantial increase from the previous year. Consequently, the growing demand for electric and hybrid vehicles is likely to drive the demand for automotive semiconductors during the forecast period. Who are the Key Industry Players in the Automotive Semiconductor Market? Notable companies operating in the automotive semiconductor market include Infineon Technologies AG, STMicroelectronics N.V, Texas Instruments Inc., Renesas Electronics Corp, and NXP Semiconductors N.V, among others. These market leaders are focused on leveraging emerging technologies and establishing partnerships to enhance their market position. What are the Segmentations in the Automotive Semiconductor Market? The automotive semiconductor market can be segmented by component Processors, Analog IC, Discrete Power, Sensor, Memory, Other Components; by vehicle type Passenger Vehicle, Light Commercial Vehicle, Medium and Heavy Commercial Vehicle; by propulsion type Internal Combustion Engine, Electric, Hybrid; and by application Powertrain, Safety, Body Electronics, Chassis, Telematics And Infotainment. What are the Regional Insights for the Automotive Semiconductor Market? Asia-Pacific was the largest region in the automotive semiconductor market in 2023, with robust growth set to continue through the forecast period. The regions covered in the market report include Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa. For a detailed analysis, check out the full report here: Browse Through More Similar Reports By The Business Research Company: Motor Vehicle And Parts Dealers Global Market Report 2024 Automobiles And Heavy Equipment Global Market Report 2024 Automotive Halogen Bulbs Global Market Report 2024 Learn More About The Business Research Company The Business Research Company has published over 15000+ reports across 27 industries and 60+ geographies. Designed with comprehensive and exclusive insights drawn from interviews with industry leaders and backed by extensive secondary research and 1,500,000 datasets. Contact us: The Business Research Company: ]( - Americas: +1 3156230293 - Asia: +44 2071930708 - Europe: +44 2071930708 Email us at ... Follow us on: LinkedIn | YouTube | Global Market Modelglobal-market-model Oliver Guirdham The Business Research Company +44 20 7193 0708 email us here Visit us on social media: Facebook X LinkedIn Legal Disclaimer: EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above. MENAFN19122024003118003196ID1109014314 Legal Disclaimer: MENAFN provides the information “as is” without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the provider above.LONDON (AP) — A woman who claimed mixed martial arts fighter Conor McGregor “brutally raped and battered” her in a Dublin hotel penthouse was awarded nearly 250,000 Euros ($257,000) on Friday by a civil court jury in Ireland. Nikita Hand said the Dec. 9, 2018, assault after a night of partying left her heavily bruised and suffering from post-traumatic stress disorder. McGregor testified that he never forced the woman to do anything against her will and said she fabricated the allegations after the two had consensual sex. His lawyer had called Hand a gold digger. The fighter, once the face of the Ultimate Fighting Championship but now past his prime, shook his head as the jury of eight women and four men returned the verdict after deliberating for about six hours in the High Court in Dublin. He was mobbed by cameras as he left court but did not comment. He later said on the social platform X that he would appeal the verdict and the “modest award.” People are also reading... Hand's voice cracked and her hands trembled as she read a statement outside the courthouse, saying she would never forget what happened to her but would now be able to move on with her life. She thanked her family, partner, friends, jurors, the judge and all the supporters that had reached out to her online, but particularly her daughter. “She has given me so much strength and courage over the last six years throughout this nightmare to keep on pushing forward for justice,” she said. “I want to show (her) and every other girl and boy that you can stand up for yourself if something happens to you, no matter who the person is, and justice will be served.” The Associated Press generally does not name alleged victims of sexual violence unless they come forward publicly, as Hand has done. Under Irish law, she did not have the anonymity she would have been granted in a criminal proceeding and was named publicly throughout the trial. Her lawyer told jurors that McGregor was angry about a fight he had lost in Las Vegas two months earlier and took it out on his client. “He’s not a man, he’s a coward,” attorney John Gordon said in his closing speech. “A devious coward and you should treat him for what he is.” Gordon said his client never pretended to be a saint and was only looking to have fun when she sent McGregor a message through Instagram after attending a Christmas party. He said Hand knew McGregor socially and that they had grown up in the same area. She said he picked her and a friend up in a car and shared cocaine with them, which McGregor admitted in court, on the way to the Beacon Hotel. Hand said she told McGregor she didn't want to have sex with him and that she was menstruating. She said she told him “no” as he started kissing her but he eventually pinned her to a bed and she couldn't move. McGregor put her in a chokehold and later told her, “now you know how I felt in the octagon where I tapped out three times,” referring to a UFC match when he had to admit defeat, she said. Hand had to take several breaks in emotional testimony over three days. She said McGregor threatened to kill her during the encounter and she feared she would never see her young daughter again. Eventually, he let go of her. “I remember saying I was sorry, as I felt that I did something wrong and I wanted to reassure him that I wouldn’t tell anyone so he wouldn’t hurt me again,” she testified. She said she then let him do what he wanted and he had sex with her. A paramedic who examined Hand the next day testified that she had never before seen someone with that intensity of bruising. A doctor told jurors Hand had multiple injuries. Hand said the trauma of the attack had left her unable to work as a hairdresser, she fell behind on her mortgage and had to move out of her house. Police investigated the woman’s complaint but prosecutors declined to bring charges, saying there was insufficient evidence and a conviction was unlikely. McGregor, in his post on X, said he was disappointed jurors didn't see all the evidence prosecutors had reviewed. He testified that the two had athletic and vigorous sex, but that it was not rough. He said “she never said ‘no’ or stopped” and testified that everything she said was a lie. “It is a full blown lie among many lies,” he said when asked about the chokehold allegation. “How anyone could believe that me, as a prideful person, would highlight my shortcomings.” McGregor’s lawyer told jurors they had to set aside their animus toward the fighter. “You may have an active dislike of him, some of you may even loathe him – there is no point pretending that the situation might be otherwise,” attorney Remy Farrell said. “I’m not asking you to invite him to Sunday brunch.” The defense said the woman never told investigators McGregor threatened her life. They also showed surveillance video in court that they said appeared to show the woman kiss McGregor’s arm and hug him after they left the hotel room. Farrell said she looked “happy, happy, happy.” McGregor said he was “beyond petrified” when first questioned by police and read them a prepared statement. On the advice of his lawyer, he refused to answer more than 100 follow-up questions. The jury ruled against Hand in a case she brought against one of McGregor’s friends, James Lawrence, whom she accused of having sex with her in the hotel without consent. Copyright 2024 The Associated Press. All rights reserved. This material may not be published, broadcast, rewritten or redistributed without permission. Be the first to know Get local news delivered to your inbox!jackpot party casino slot 。

Bed capacity management is of critical importance to health systems, impacting patient care and safety, operational efficiency, system sustainability and financial performance. Efforts to improve and streamline management often are isolated to regions within the center and may lead to suboptimal resource utilization, inconsistent patient care, and inefficiencies between care units for transfers and other care coordination. Assessment of end-to-end bed demand management globally from admission to discharge eliminates many of the unintended consequences of localized optimization efforts. Froedtert Health identified improving capacity management as an important and targetable goal that could be achieved through AI, machine learning and data analytics approaches. Understanding and dissecting patient flow and its sources allowed the team to create a suite of predictive tools designed specifically for the care coordination center. Froedtert Health was able to improve patient care, operationalize key performance indicators and streamline operations through more effective staff deployment and utilization and by pre-emptively responding to anticipated changes in patient bed demand. This led to optimized allocation of resources, improved patient flow, better coordination between departments and cost savings. Ravi Teja Karri is a machine learning engineer at Froedtert ThedaCare Health. He and two colleagues will be speaking on these achievements at HIMSS25 in a session titled "Improving Capacity Planning and Bed Demand Forecasting Using Machine Learning." We interviewed Karri to get a sneak peek at what he plans to discuss in March at HIMSS25 during his session. Q. What is the overarching theme of your session, and why is it especially relevant to healthcare and health IT today? A. The overarching theme of our session is focused on improving hospital capacity management and bed demand forecasting through the application of artificial intelligence and machine learning techniques. This topic is increasingly relevant in healthcare as hospitals face unpredictable changes in patient volume. Seasonal surges, unplanned admissions and fluctuating patient needs make it challenging to maintain an optimal allocation of resources. Leveraging AI and ML to predict bed demand and patient flow enables hospitals to optimize staffing, allocate beds and streamline operations, resulting in enhanced patient care and overall efficiency. Our session also will explore how healthcare organizations can leverage AI and ML to transform processes into anticipatory workflows rather than reactive ones. This proactive approach enables more accurate forecasting of patient volumes and better interdepartmental coordination, ultimately enhancing patient experience through more efficient resource allocation and timely care delivery. Integrating these predictive models into daily operations enables healthcare organizations to better anticipate demand fluctuations, minimize overcrowding risks and enhance interdepartmental coordination. Q. You are focusing on AI and ML, important technologies in healthcare today. How are they being used in healthcare in the context of your session's focus and content? A. Our session focuses on artificial intelligence and machine learning technologies , specifically their application in predictive analytics for bed demand forecasting and capacity management in hospitals. ML models are designed to analyze large datasets, including historical patient admissions, discharge trends, seasonal illness patterns and other factors, to forecast future hospital capacity needs. We will explore how these models can predict patient flow and bed demand, enabling healthcare organizations to make more informed decisions about resource allocation, staffing and patient care management. These predictive models use algorithms to identify patterns and trends in patient admissions, length of stay and discharge rates, enabling hospitals to forecast fluctuations in demand with a high degree of accuracy. ML integrates data from multiple sources, including emergency departments, surgical units and outpatient care, to provide a comprehensive view of organizational capacity. This analysis helps hospital leadership and care coordinators to anticipate surges in bed demand – like those experienced during flu seasons or following natural disasters – and plan effectively to ensure that resources are available when needed most. By implementing these technologies, healthcare institutions can transition from a reactive approach to a more proactive and anticipatory model of patient flow management. In our session, we will examine how machine learning can be effectively applied in healthcare to predict bed demand and enhance capacity management. By analyzing historical data such as patient admission rates, discharge patterns and seasonal trends, ML models can forecast hospital capacity needs. These predictions enable healthcare organizations to optimize resource allocation, plan staffing requirements and deliver improved patient care, enabling a proactive rather than reactive approach to operations. We also will discuss how these ML models can be integrated into healthcare workflows, transforming predictions into action for hospital staff. Rather than remaining in experimental environments or isolated tools, the predictions are processed, stored and made available for decision making through business intelligence platforms. These BI tools enable healthcare staff to access insights for effective planning, such as allocating beds, managing staffing and coordinating patient discharges, ultimately improving operational efficiency and patient outcomes. Q. What is one of the various takeaways you hope attendees will leave your session with and be able to apply when they return home to their organizations? A. A key takeaway we hope attendees will gain from our session is the knowledge to implement machine learning-based predictive analytics tools to enhance their own hospital's capacity management. Attendees will discover how predictive models can accurately forecast bed demand and identify potential bottlenecks in patient flow before they occur. These insights will empower leaders to make data-driven decisions, allocate resources more efficiently, and avoid overburdening units or staff during peak periods. By using this toolkit, healthcare providers can minimize last-minute staffing adjustments, optimize bed utilization, and ensure patient care remains uninterrupted during periods of high demand. Predicting patient flow across the entire hospital, rather than in isolated units, allows for optimized resource allocation across departments and minimization in delays caused by mismatches between patient demand and available resources. This will foster better communication between clinical teams and operational leaders, resulting in smoother transitions between patient care stages and improved overall patient experience. Ravi Teja Karri's session, "Improving Capacity Planning and Bed Demand Forecasting Using Machine Learning," is scheduled for Tuesday, March 4, at 10:15 a.m. at HIMSS25 in Las Vegas . Follow Bill's HIT coverage on LinkedIn: Bill Siwicki Email him: bsiwicki@himss.org Healthcare IT News is a HIMSS Media publication

MALAGA, Spain (AP) — The last man to face — and beat — Rafael Nadal in professional tennis, 80th-ranked Botic van de Zandschulp , converted his 10th match point Friday to finally close out a 6-4, 6-7 (12), 6-3 victory over Daniel Altmaier and help the Netherlands reach its first Davis Cup final by sweeping Germany. Tallon Griekspoor, who is ranked 40th, sealed the 2-0 win for the Dutch in the best-of-three-match semifinal by hitting 25 aces and coming back to defeat Jan-Lennard Struff 6-7 (4), 7-5, 6-4. When it ended, appropriately, on an ace, Griekspoor shut his eyes, dropped to his knees and spread his arms wide. “We have been talking about this for two, three years,” Griekspoor said. “We believed in ourselves so much. We always felt like this was possible. To do it now feels unbelievable.” The other semifinal is Saturday, with No. 1-ranked Jannik Sinner and defending champion Italy taking on Australia . The championship will be decided Sunday. “We don’t have that top 5 player. We don’t that top 10 player. We don’t have that top 15 player,” Dutch captain Paul Harhuuis said. “But it’s a team effort. ... So proud of these guys.” In Friday's opener, van de Zandschulp was up a set and just a point away from leading 5-2 in the second when Altmaier began playing more aggressively and interacting more with the German fans, yelling and throwing uppercuts or raising his arms after key points. In the tiebreaker, Altmaier managed to save five match points before converting his own fourth set point to extend the contest. But van de Zandschulp — who upset four-time Grand Slam champion Carlos Alcaraz at the U.S. Open — quickly moved out front in the final set, even if he eventually needed five more match points in the last game before serving it out. “At some point, I didn’t know what to do any more on the match points,” van de Zandschulp said. “I had the toughest match of my life on Tuesday (against Nadal), so everything that comes next is maybe a little bit easier.” In the quarterfinals, van de Zandschulp outplayed Nadal for a 6-4, 6-4 result that marked the end of the 22-time Grand Slam champion’s career because the Netherlands went on to eliminate Spain 2-1. The 38-year-old Nadal announced last month that the Davis Cup would be his final event before retiring. Presumably because people purchased tickets ahead of time with plans to watch Nadal compete in the semifinals, there were hundreds of unoccupied blue or gray seats surrounding the indoor hard court at the Palacio de Deportes Jose Maria Martina Carpena in southern Spain on Friday. Now truly a neutral site, the place was not nearly as loud and rowdy as on Tuesday, although there were shouts of “Vamos, Rafa!” that drew laughter while van de Zandschulp played the 88th-ranked Altmaier. It took Griekspoor more than 75 minutes and nearly two full sets to figure out how to break No. 43 Struff and then did it twice in a row — to lead 6-5 in the second set, and then go up 1-0 in the third. That was plenty, because Griekspoor saved the only two break points he faced. The Netherlands hadn’t been to the semifinals since 2001. The Germans — whose best current player, two-time major finalist Alexander Zverev, is not on the team in Malaga — have won three Davis Cups, but not since 1993, when 1991 Wimbledon champion Michael Stich led them to the title. AP tennis: https://apnews.com/hub/tennis

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Several times following New England’s 24-21 loss to the Buffalo Bills, Patriots coach Jerod Mayo said he wanted to review the game film before making a final assessment of his team’s performance. He did, and on Monday he said the overarching feeling he was left with was one of pride. Going toe-to-toe with one of the best teams in the NFL is commendable. Mayo also remains confident this group has even more room for growth over its final two games this season. “To be frank, I don’t believe in good losses,” Mayo said. “I think there’s a lot to learn from the game. Look, we’re headed in the right direction, but it’s all about consistency, and we have to do that on a down-after-down, a game-after-game basis to be successful in this league.” What is also clear is that despite their 3-12 record, Patriots rookie quarterback Drake Maye wants people to know that he and his teammates believe in their coach. No matter what conversations might be going on outside the Patriots locker room regarding shortcomings by the coaching staff, or Mayo’s job status. “We’ve got his back, and he’s coached us hard. He wants to win. We all want to win. We’re all frustrated,” Maye said. “We’re just plays away, and it’s basically me turning the ball over. I think it’s just a testament to these guys that keep fighting. We keep fighting. Shoot, we’re not going to make the playoffs; we’re out of the race, and these guys are coming in, frustrated when we don’t score. ... So, I think we’re building something good, building something that feels right here, and I’m proud to be a Patriot.” Javascript is required for you to be able to read premium content. Please enable it in your browser settings.AT&T's CTO tells his US team there won't be 'one-for-one seating' upon the return to 5 days in office — read the memo

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