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fortune ox background Washington (CNN) — Victims of major public corruption cases in Pennsylvania and Illinois are angry that President Joe Biden granted clemency this week to two convicted officials. The commutations were announced Thursday as part of a historic clemency package for 1,500 convicted criminals who, the White House said, “deserve a second chance.” The two convicted officials whose cases sparked outrage – a crooked Pennsylvania judge and a notorious Illinois fraudster – were both released from prison early and put on house arrest, due to the Covid-19 pandemic. Biden’s actions now end that punishment. The president has already faced bipartisan criticism over his highly controversial pardon of his son Hunter Biden, who was convicted earlier this year of 12 tax and gun crimes. CNN has reached out to the White House for comment on the commutations. Former Pennsylvania Judge Michael Conahan was convicted in 2011 in what was infamously called the “kids-for-cash” scandal , where he took kickbacks from for-profit detention centers in exchange for wrongly sending juveniles to their facilities. The case was widely considered to be one of the worst judicial scandals in Pennsylvania history. Like all of the other nearly 1,500 people who got commutations from Biden this week, Conahan was freed from prison due to Covid. His house arrest was set to end in 2026. The misconduct of Conahan and another Luzerne County judge led the Pennsylvania Supreme Court to throw out 4,000 juvenile convictions, and the discredited state judges were ordered to pay $200 million to the victims, according to the Associated Press . Sandy Fonzo – the mother of Edward Kenzakoski, who died by suicide after spending time behind bars as part of the kickback scheme – said she was “shocked... and hurt” after learning of Biden’s decision to commute the rest of Conahan’s punishment. “Conahan‘s actions destroyed families, including mine, and my son‘s death is a tragic reminder of the consequences of his abuse of power,” Fonzo told the Citizens’ Voice, a local outlet. “This pardon feels like an injustice for all of us who still suffer. Right now I am processing and doing the best I can to cope with the pain that this has brought back.” Pennsylvania Gov. Josh Shapiro, a Democrat, also said Friday at an unrelated news conference in Biden’s hometown of Scranton that, “I do feel strongly that President Biden got it absolutely wrong and created a lot of pain here in northeastern Pennsylvania.” There was similar fallout in Illinois, after Biden gave clemency to Rita Crundwell , the former comptroller of Dixon, a city of roughly 15,000 in the northern part of the state. She pleaded guilty in 2012 to a $54 million embezzlement scheme, which was believed to be the largest municipal fraud in US history. She was sentenced to almost 20 years in prison, nearly the maximum, though she moved to house arrest during the pandemic. She was supposed to be on house arrest until 2028, according to the Bureau of Prisons. “When I heard the news, I was completely shocked in disbelief, I was outraged and felt a complete sense of betrayal from the federal justice system, the White House and the president,” Dixon city manager Danny Langloss told CNN in an interview on Friday. Langloss, who said he doesn’t affiliate with a political party, was the police chief when Crundwell’s fraud was uncovered. He said he believes “justice wasn’t served here.” “I don’t like the idea ... that with several more years of her sentence to complete, she gets to walk free in the community that she betrayed and stole from,” Langloss said. Margaret Love, who served in the Justice Department as the US pardon attorney from 1990 to 1997, said the fallout from Biden’s latest commutations was a consequence of how the prison population was reduced during Covid – under the Trump administration. Congress passed the bipartisan CARES Act in March 2020, at the beginning of the pandemic, which, among other things, paved the way for the federal government to move about 12,000 inmates from federal prisons into home confinement. Many of these people have since completed their sentences, though plenty remain on house arrest. “Many people who were sent home were convicted of white-collar or nonviolent offenses and were considered safe bets to behave in the community,” Love said, adding that she believed the decision-making was tainted by racial discrimination. With grumblings among some Republicans about sending these convicts back to prison, Love said Biden “simply cleaned out this population” and took that option off the table. And to those upset that Biden let these criminals out of house arrest early, “you should have complained four years ago when they were released from prison,” Love said. The-CNN-Wire TM & © 2024 Cable News Network, Inc., a Warner Bros. Discovery Company. All rights reserved.

China’s Bear Equity Market: Is There an End in Sight?Sharp Co. ( OTCMKTS:SHCAY – Get Free Report ) was the recipient of a large drop in short interest in the month of December. As of December 15th, there was short interest totalling 2,900 shares, a drop of 25.6% from the November 30th total of 3,900 shares. Based on an average trading volume of 3,900 shares, the days-to-cover ratio is presently 0.7 days. Sharp Price Performance Sharp stock opened at $1.52 on Friday. The stock has a market capitalization of $3.95 billion, a P/E ratio of -4.47 and a beta of 0.80. The company’s fifty day moving average price is $1.51 and its 200 day moving average price is $1.49. The company has a debt-to-equity ratio of 3.15, a quick ratio of 0.84 and a current ratio of 1.21. Sharp has a 1 year low of $1.16 and a 1 year high of $1.91. Sharp Company Profile ( Get Free Report ) Further Reading Receive News & Ratings for Sharp Daily - Enter your email address below to receive a concise daily summary of the latest news and analysts' ratings for Sharp and related companies with MarketBeat.com's FREE daily email newsletter .

Aaron Judge wins second AL MVP in 3 seasons. Shohei Ohtani expected to win NL honorNone

Share Tweet Share Share Email Managing expenses effectively is crucial to maintaining financial integrity. However, the rise in fraudulent expense claims poses a significant challenge for organizations worldwide. Fraudulent activities not only drain resources but also damage trust within the workplace. Detecting such fraud manually can be tedious, time-consuming, and error-prone. This is where machine learning comes into play, offering innovative ways to combat expense fraud efficiently and proactively . What Is Expense Fraud? Expense fraud refers to the act of submitting false or exaggerated claims for reimbursement. Employees may manipulate receipts, inflate mileage claims, or create fake invoices to gain undeserved compensation. Common examples of expense fraud include: Submitting personal expenses as business-related costs. Altering the amounts on genuine receipts. Creating entirely fictitious receipts or invoices. Reimbursing duplicate claims for the same expense. These fraudulent activities can cost businesses thousands, if not millions, of dollars annually. While traditional audits can uncover some discrepancies, they often miss more sophisticated schemes. This highlights the need for advanced technologies like machine learning to tackle fraud more effectively. The Role of Machine Learning in Fraud Detection Machine learning (ML) leverages algorithms that analyze data, learn patterns, and make predictions. Unlike rule-based systems, ML models continuously improve over time as they process new data. In the context of expense fraud detection, machine learning offers the following advantages: Automated Data Analysis: ML systems can process vast amounts of expense data in real time, identifying anomalies that may signal fraudulent behavior. Pattern Recognition: By analyzing historical data, machine learning models can detect unusual patterns that deviate from normal expense behaviors. Risk Scoring: ML algorithms assign risk scores to expense claims, flagging those with high likelihoods of fraud for further review. Adaptive Learning: As fraud tactics evolve, machine learning models adapt by learning new patterns and identifying emerging threats. Key Machine Learning Techniques for Expense Fraud Detection Machine learning employs various techniques to identify fraudulent expense claims. Below are some of the most commonly used approaches: Supervised Learning Supervised learning involves training a model on labeled data, where the outcomes (fraudulent or non-fraudulent) are already known. The model learns to classify new expense claims based on the patterns it observes in the training data. Algorithms like decision trees, support vector machines (SVM), and neural networks are commonly used in supervised learning for fraud detection . Unsupervised Learning Unlike supervised learning, unsupervised learning works with unlabeled data. This approach is ideal for detecting unknown types of fraud. Techniques like clustering and anomaly detection help group similar data points and identify outliers. For instance, if an employee’s expense claim is significantly higher than their peers’, the system flags it for investigation. Natural Language Processing (NLP) Natural language processing is used to analyze text-based data, such as descriptions in expense claims. NLP can identify inconsistencies, suspicious keywords, or unusual phrasing that may indicate fraudulent intent. Reinforcement Learning Reinforcement learning involves training models through a reward-based system. In fraud detection, the algorithm receives rewards for accurately identifying fraudulent claims and penalties for false positives or negatives. This iterative process improves the model’s accuracy over time. Building an Effective Machine Learning Framework for Fraud Detection Implementing a machine learning-based expense fraud detection system requires careful planning and execution. Below are the critical steps: Data Collection and Preprocessing The first step is gathering expense-related data, such as receipts, invoices, and transaction records. Preprocessing this data is crucial to ensure accuracy and consistency. Steps include: Cleaning and removing duplicate entries. Converting unstructured data into structured formats. Normalizing numerical data for better model performance. Feature Engineering Feature engineering involves selecting and creating relevant variables (features) that help the model identify fraud. Examples include: Frequency of claims per employee. Average claim amount by department. Expense categories with unusually high costs. Model Training and Testing Once features are defined, the next step is training machine learning models. A portion of the data is used for training, while the rest is reserved for testing. This ensures that the model performs well on unseen data. Deployment and Monitoring After successful testing, the model is deployed to monitor expense claims in real-time. Continuous monitoring and periodic retraining are essential to maintain effectiveness and adapt to new fraud patterns. Challenges in Machine Learning-Based Fraud Detection While machine learning offers powerful tools for expense fraud detection, it is not without challenges. Some common obstacles include: Data Quality Issues: Inaccurate or incomplete data can lead to unreliable model predictions. High False Positives: Over-sensitive models may flag legitimate claims as fraudulent, leading to inefficiencies. Evolving Fraud Tactics: Fraudsters continuously adapt, requiring models to be updated regularly. Privacy Concerns: Handling sensitive financial data necessitates strict adherence to data protection regulations. Addressing these challenges requires a collaborative approach involving robust data governance, regular model audits, and input from domain experts. Benefits of Machine Learning in Expense Fraud Detection Despite the challenges, machine learning brings numerous benefits to expense fraud detection: Efficiency: Automating fraud detection reduces the manual workload, allowing finance teams to focus on high-priority tasks. Accuracy: ML models often outperform traditional methods, identifying subtle patterns that humans might miss. Scalability: Machine learning systems can handle large volumes of data, making them suitable for organizations of all sizes. Cost Savings: By preventing fraud, businesses can save significant amounts of money that would otherwise be lost. Real-World Applications of Machine Learning in Expense Fraud Detection Many organizations have successfully implemented machine learning to combat expense fraud. For instance: Corporate Finance Departments: Large corporations use ML tools to monitor employee expense reports, flagging anomalies in real-time. Expense Management Software: Companies like Expensify and Concur integrate machine learning algorithms to provide fraud detection features for their clients. Financial Institutions: Banks and credit card companies employ ML models to detect suspicious transactions that could indicate fraudulent expense claims. Conclusion Expense fraud is a pressing issue that requires proactive measures to mitigate its impact on businesses. Machine learning offers a transformative solution, enabling organizations to detect and prevent fraud with unprecedented efficiency.Furthermore, By leveraging techniques like supervised and unsupervised learning, natural language processing, and reinforcement learning, companies can build robust fraud detection systems that evolve alongside emerging threats. Although challenges remain, the benefits of machine learning far outweigh the drawbacks, making it an indispensable tool in the fight against expense fraud. Organizations that invest in this technology not only safeguard their finances but also foster a culture of transparency and trust . Related Items: Catching Fraud Before It Strikes , Expense Fraud Detection , machine learning Share Tweet Share Share Email Recommended for you Can Machine Learning Models Truly Revolutionize Retail Sales Forecasting? AI and Machine Learning Reshape Modern Data Center Operations How Machine Learning is Driving a New Era in Healthcare? CommentsSignificant milestones in life and career of Jimmy CarterEx-Colorado footballer Bloom dedicates time to fulfilling wishes for older adults

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The undefeated Vernon Panthers will look to ground some northern birds in the semifinals at the 2024 Tsumura Basketball Invitational Girls High School Basketball tournament in the Fraser Valley. The Panthers will face the Duchess Park Condors of Prince George at 4:30 p.m. Friday, Dec. 13. Dave Tetreault's crew advanced to the Select 16 semifinals by freezing the South Delta Sun Devils 63-54 in a Thursday quarterfinal. The Sun Devils led 14-1 before the Panthers got going, tying the game at the half, then taking their own 13-point lead late in the third quarter. But South Delta clawed back to pull ahead 54-52, only to see the Panthers end the game on an 11-0 run. Paige Leahy led VSS with 19 points, Chloe Collins added 15, and Adie Janke had 14. Collins and Janke nailed key three-point shots in the final quarter for the Cats. The Panthers will next face the smothering defence of the Condors, who defeated Langley's Walnut Grove Gators 88-27 in their quarterfinal. Duchess Park held the Gators to just 11 first-half points. In the Super 16 bracket, the Kelowna Owls were bounced from the championship side, falling 62-56 to Langley's Brookswood Bobcats. The Owls held Grade 10 phee-nom Jordyn Nohn to just 17 points. Nohr erupted for 52 points in the Bobcats' opening round game. Mavleen Chahal led the Owls with 25 points while Ava Thiessen scored all 12 of her points from the three-point line. On the consolation side, the Okanagan Mission Huskies of Kelowna evened their tournament record at 1-1 with a 56-50 win over the Sa-Hali Sabres of Kamloops. The Huskies face the Semiahmoo Thunderbirds of Surrey at 11:45 a.m. The Owls will take on the Lord Tweedsmuir Panthers of Surrey at 4:30 p.m. For schedule and scores, .At Eindhoven Air Base, they have an AI robot to secure part of the terrain. This robot can address people, for example, to identify themselves. It is still a test, only in Eindhoven. But if the test is successful, more Dutch defence sites will be secured this way. The patrol robot ‘Badger’ has two robot eyes that blink regularly. On top is an orange flashing light. The large wheels ensure that they can handle different terrains. The robot is full of cameras. “It has a 360-degree view”, says Atilla, commander of the patrol area at Eindhoven Air Base. “It can drive around independently”. Badger starts by taking images, for example of the thirteen kilometre long fence at the air base. “When it drives its route, the robot checks whether these images are still the same.” The robot sees everything that deviates from the normal. Lights still on at an odd time, open doors, someone in the bushes or an unknown vehicle on the terrain. “If the robot discovers a hole in the fence or something else that is different, that does not match the images made beforehand”. A security guard will then receive a notification on his phone or laptop. This can be useful for Defence to discover activists who want to enter the site in time. The robot can also talk to itself. Badger has a built-in microphone. It can be listened to remotely. For example, the robot can also ask, ‘Can you identify yourself?’. `Security guards can then talk to the person remotely via the robot. The robot is intended as a supplement, not a replacement. “If something is wrong, a security guard must intervene”. Arming a robot is certainly not the intention. “It is a means to help the security guards to drive extra patrols, especially at night. The robot has a heat image. At night, the robot sees more than a security guard can see. Then we can use it well”. According to Atilla, the robot has a bright future for the airbase if the Defence considers the test successful. “In the future, we can use it to drive patrols to guard aircraft here”. Source: Studio040 Translated by: Seetha Save my name, email, and website in this browser for the next time I comment. Δ document.getElementById( "ak_js_1" ).setAttribute( "value", ( new Date() ).getTime() );

Dejounte Murray is rejoining the Pelicans vs. Toronto and drawing inspiration from his motherFormer President Jimmy Carter , the 39th president of the United States and a tireless advocate for peace and human rights, has passed away at the age of 100, his office confirmed on Sunday. Carter , who had been under hospice care since February 2023 at his home in Plains, Georgia, became the first U.S. president to reach the age of 100. His wife of 77 years, Rosalynn Carter , died just weeks earlier, on November 19, 2023, at the age of 96. Carter ’s milestone 100th birthday in October 2024 was marked by widespread tributes, including a message from President Joe Biden. In a video shared with CBS News, Biden praised Carter as a moral force for the nation and the world, calling him a voice of courage and compassion and a cherished friend to him and his family. Born in Georgia, Carter was elected president in 1976 as a Democrat, defeating the incumbent Republican Gerald Ford in the aftermath of the Watergate scandal. His presidency was marked by significant challenges, including the Iran hostage crisis, which persisted for 444 days and contributed to his loss in the 1980 election to Ronald Reagan. Despite leaving office with relatively low popularity, Carter ’s post-presidency efforts earned him widespread admiration, leading many to view him as one of the most impactful former presidents. Awarded the Nobel Peace Prize in 2002 for his global human rights work, Carter spent decades advocating for peaceful conflict resolution, democratic principles, and social justice. In 1982, he and Rosalynn established the Carter Center at Emory University in Atlanta. Through the center, the Carters traveled to developing nations to monitor elections, strengthen democratic institutions, and campaign for human rights. They also led efforts to eradicate diseases and provided critical support for victims of oppression. Carter was also known for his hands-on involvement with Habitat for Humanity, where he and Rosalynn could often be found building homes for underserved families. His dedication to public service after his presidency transformed his reputation, with many referring to him as " America’s greatest ex-president. " Carter , who became the oldest living former president after George H.W. Bush’s death in 2018, was also the first U.S. president born in a hospital. At 56, he left the White House relatively young, allowing him to dedicate over four decades to humanitarian work, which became the hallmark of his legacy.

(BPT) - Tech gifts are consistently some of the most popular presents to give and receive during the holidays. In fact, according to the annual Consumer Technology Holiday Purchase Patterns report , a record 233 million U.S. adults (89%) will buy tech products during the 2024 holiday season. But with so many devices out there, it can be hard to decide on the perfect option for the loved one on your list. A tablet like the new Fire HD 8 from Amazon offers the versatility of an all-in-one device, with access to streaming, gaming, video chatting, reading or writing all at your fingertips. Fire HD 8 also features a vibrant 8-inch HD display and lightweight, portable design, for high-quality entertainment on the go. Plus, Fire HD 8 comes with three new AI features that can help you get the most out of your tablet experience. Check them out below and learn how they can help you with daily tasks this holiday season and beyond. 1. Meet your personal writing assistant Do you struggle with writing a heartfelt message or finessing a tricky email? Fear not! Writing Assist is here to help. Writing Assist works as part of your Fire tablet's device keyboard and compatible apps, including email, Word documents and social media. In just a few taps, you can transform your writing from good to great. Try Writing Assist's pre-set styles to turn a simple email into a professionally written note. Or, you can ask Writing Assist for grammar suggestions to make your writing more concise, or elaborate on your ideas. You can even "emojify" your writing to add more fun and personality. 2. Learn more in less time Say goodbye to scrolling through pages of information. The new Webpage Summaries feature allows you to learn pertinent information as quickly as possible. Available on the Silk browser on Fire tablets, Webpage Summaries provides quick insights on web articles. In a matter of seconds, this feature will distill the key points in an article or on a webpage into a clear, concise summary of what you need to know. 3. Get creative with your device wallpaper With Wallpaper Creator, you can easily add a touch of creative flair and customization to your tablet's home screen. You can choose from one of the curated prompts to get started on creating a unique background. Or, if you're ready to let your imagination run wild, type a description of what you'd like to see. For example, you can ask for an image of a tiger swimming underwater or a watercolor-style image of a desert landscape in space. Wallpaper Creator will then turn your vision into a reality, delivering a high-resolution image that you can use as your tablet's wallpaper. Celebrate an AI-powered holiday season Writing Assist, Webpage Summaries, and Wallpaper Creator are now available on Amazon's new Fire HD 8 and other compatible Fire tablet devices, including the latest Fire HD 10 and Fire Max 11 tablets. To learn more, or to order a new Fire tablet this gift-giving season, visit Amazon.com .Published 5:33 pm Sunday, December 29, 2024 By Data Skrive Let’s take a look at the injury report for the Charlotte Hornets (7-24), which currently has five players listed (including LaMelo Ball), as the Hornets ready for their matchup with the Chicago Bulls (14-18, two injured players) at Spectrum Center on Monday, December 30 at 7:00 PM ET. Watch the NBA, other live sports and more on Fubo. What is Fubo? Fubo is a streaming service that gives you access to your favorite live sports and shows on demand. Use our link to sign up. The Hornets fell in their most recent game 106-94 against the Thunder on Saturday. Miles Bridges scored a team-high 19 points for the Hornets in the loss. The Bulls enter this contest on the heels of a 116-111 victory against the Bucks on Saturday. Josh Giddey put up 23 points, 15 rebounds and 10 assists for the Bulls. Sign up for NBA League Pass to get live and on-demand access to NBA games. Get tickets for any NBA game this season at StubHub. Catch NBA action all season long on Fubo. Not all offers available in all states, please visit BetMGM for the latest promotions for your area. Must be 21+ to gamble, please wager responsibly. If you or someone you know has a gambling problem, contact 1-800-GAMBLER .

Stock Shocker: Major Decline for Tech Player Unveils Hidden InsightsVanTrust Real Estate Acquires Strategically Located Salt Lake County Site to Build Four New Industrial Warehouses

NEW YORK (AP) — U.S. stocks rose to records Friday after data suggested the job market remains solid enough to keep the economy going, but not so strong that it raises immediate worries about inflation . The S&P 500 climbed 0.2%, just enough top the all-time high set on Wednesday, as it closed a third straight winning week in what looks to be one of its best years since the 2000 dot-com bust. The Dow Jones Industrial Average dipped 123.19 points, or 0.3%, while the Nasdaq composite rose 0.8% to set its own record. Javascript is required for you to be able to read premium content. Please enable it in your browser settings.

What appeared to be a high-rise fire near 5th and Bixel streets in downtown Los Angeles on Thursday night caught the attention of a group of young people, who quickly began recording the disaster unfolding before them to share on social media. The video was livestreamed on Citizen, a public safety mobile app, which was then posted on the Citizen app’s social media account on X. The video shows smoke billowing from the top of the building and an orange glow. The video was posted under the headline “#Breaking News Fire in Downtown High-Rise. Flames and smoke are billowing from the top floors of the structure. Avoid the area.” “You can smell it,” a woman from the group can be heard saying. “You can smell, like, the paper burning inside... I smell burnt paper.” “This is crazy,” the young man recording says. But the fire was not a real disaster, the group soon learned. It was Hollywood make believe, a phony fire created for the filming of a movie. In fact the building at 1201 W. 5th St. belongs to the Los Angeles Center Studios, a 20-acre studio campus that includes event venues and six 18,000-square-foot sound stages among other amenities, according to its website . The fake fire was so believable that the Los Angeles Fire Department had to put out the word on social media, urging residents not to call them to report it. “We were letting them know it was a movie set and there was no danger,” said fire department spokesperson Margaret Stewart. On the social media site X, the department wrote : “We appreciate the concerned citizens calling but — the fire visible on the roof of 1201 W 5th by Bixel in [downtown L.A.] is not real - it is part of a movie/tv shoot. It is planned to be active until 3 a.m. Please share the word!” Stewart said it was easy to think it was a real fire because camera crews were at the top of the building and not visible. As the group of young people who videotaped the fabricated fire continued to watch the building that night they began to deduce that the fire was perhaps not real. The smoke was white, the fire was not spreading and they heard no crackling or popping sounds that fires make. Commentators watching the livestream typed responses on the Citizen app, noting that the fire was part of a movie set. “It’s not a real fire folks,” a viewer wrote which the young man recording read out loud. “It’s Hollywood magic.” The group who videotaped the scene, embarrassed, laugh at the situation, expressing relief that they are not identified in the video. “Whatever. They don’t see our faces,” one of the women says.