Things to Do in L.A. Tap to enable a layout that focuses on the article. How bad is California's housing shortage? It depends on who's doing the counting This is read by an automated voice. Please report any issues or inconsistencies here . Imagine you've finally taken your car to the mechanic to investigate that mysterious warning light that's been flashing on your dashboard for the past week and a half.

The RMS Titanic sank in the North Atlantic Ocean on April 15, 1912, after colliding with an iceberg during her maiden voyage from Southampton to New York. More than 1,500 people died when the ship, which was carrying 2,224 passengers and crew, sank under the command of Captain Edward Smith. Some of the wealthiest people in the world were on board, including property tycoon John Jacob Astor IV, great grandson of John Jacob Astor, founder of the Waldorf Astoria Hotel. Millionaire Benjamin Guggenheim, heir to his family's mining business, also perished, along with Isidor Straus, the German-born co-owner of Macy's department store. The ship was the largest afloat at the time and was designed in such a way that it was meant to be'unsinkable'.

Tech companies like to make two grand pronouncements about the future of artificial intelligence. First, the technology is going to usher in a revolution akin to the advent of fire, nuclear weapons, and the internet. And second, it is going to cost almost unfathomable sums of money. Silicon Valley has already triggered tens or even hundreds of billions of dollars of spending on AI, and companies only want to spend more. Their reasoning is straightforward: These companies have decided that the best way to make generative AI better is to build bigger AI models.

Fox News Flash top sports headlines are here. Check out what's clicking on Foxnews.com. The first score of the Super Bowl turned out to be historic, but the record didn't stand for long. Kansas City Chiefs kicker Harrison Butker drilled his second field goal of Super Bowl LVIII against the San Francisco 49ers, a 57-yarder that rewrote the record for longest kick in the "Big Game." And that previous record was hit in the first half by 49ers rookie kicker Jake Moody, who hit one home from 56 yards.

The credit rating agency Moody's has warned that water companies face an "elevated" risk from cyber attackers targeting drinking water, as suppliers wait on permission from the industry regulator to ramp up spending on digital security. Moody's said, in a report to investors, that hackers are increasingly zeroing in on infrastructure companies, including water and wastewater treatment companies, and the use of AI (artificial intelligence) could accelerate this trend. Last month, Southern Water, which supplies 4.6 million customers in the south of England, said the Black Basta ransomware group had claimed to have accessed its systems, posting a "limited amount" of data on the dark web. Separately, South Staffordshire Water apologised in 2022 after hackers stole customers' personal data. Moody's warned that the growing use of data-logging equipment to monitor water consumption, and the use of digital smart meters, made companies more vulnerable to attacks.

Signal quality assessment (SQA) is required for monitoring the reliability of data acquisition systems, especially in AI-driven Predictive Maintenance (PMx) application contexts. SQA is vital for addressing "silent failures" of data acquisition hardware and software, which when unnoticed, misinform the users of data, creating the risk for incorrect decisions with unintended or even catastrophic consequences. We have developed an open-source software implementation of signal quality indices (SQIs) for the analysis of time-series data. We codify a range of SQIs, demonstrate them using established benchmark data, and show that they can be effective for signal quality assessment. We also study alternative approaches to denoising time-series data in an attempt to improve the quality of the already degraded signal, and evaluate them empirically on relevant real-world data. To our knowledge, our software toolkit is the first to provide an open source implementation of a broad range of signal quality assessment and improvement techniques validated on publicly available benchmark data for ease of reproducibility. The generality of our framework can be easily extended to assessing reliability of arbitrary time-series measurements in complex systems, especially when morphological patterns of the waveform shapes and signal periodicity are of key interest in downstream analyses.

Although event logs are a powerful source to gain insight about the behavior of the underlying business process, existing work primarily focuses on finding patterns in the activity sequences of an event log, while ignoring event attribute data. Event attribute data has mostly been used to predict event occurrences and process outcome, but the state of the art neglects to mine succinct and interpretable rules how event attribute data changes during process execution. Subgroup discovery and rule-based classification approaches lack the ability to capture the sequential dependencies present in event logs, and thus lead to unsatisfactory results with limited insight into the process behavior. Given an event log, we are interested in finding accurate yet succinct and interpretable if-then rules how the process modifies data. We formalize the problem in terms of the Minimum Description Length (MDL) principle, by which we choose the model with the best lossless description of the data. Additionally, we propose the greedy Moody algorithm to efficiently search for rules. By extensive experiments on both synthetic and real-world data, we show Moody indeed finds compact and interpretable rules, needs little data for accurate discovery, and is robust to noise.

Two theorems and a lemma are presented about the use of jackknife es(cid:173) timator and the cross-validation method for model selection. Theorem 1 gives the asymptotic form for the jackknife estimator. Combined with the model selection criterion, this asymptotic form can be used to obtain the fit of a model. The model selection criterion we used is the negative of the average predictive likehood, the choice of which is based on the idea of the cross-validation method. Lemma 1 provides a formula for further explo(cid:173) ration of the asymptotics of the model selection criterion.

The hype cycles that come with emerging technologies can be perilous waters for early adopters and buyers. From the immutable yet seemingly impractical blockchain to artificial intelligence systems that are really just machine learning systems (which in turn are often really just rules-based software with data analytics), it's common for marketing departments to blur the lines between innovation and grift when selling new technologies, and for businesses to get snookered. One field that does appear to have long-term transformative potential is quantum computing and its cybersecurity cousin, quantum code breaking. But before we get started: actual quantum computers are not here. A small group of government-funded labs, industry titans and startups are toiling away, steadily increasing the number of cubic bits – or qubits – their supercomputers are capable of processing each year, but it will likely be a long time before businesses and other organizations can realistically buy one, or unleash its exponential computing power on their organization's problems.

Many of us could use more companionship in these times of social distancing and staying at home amid the COVID-19 pandemic. While you might not be able to have a dog or cat in your residence, perhaps a companion robot will do the trick. If you're looking for one with more personality, Panasonic has made another robot that might hold the answer. With the help of the Toyohashi University of Technology Michio Oka Laboratory, Panasonic created the cute Nicobo. It looks a bit like a cat that got itself stuck in a sock.