Abstract-- This paper investigates the integration of haptic feedback and virtual reality (VR) control interfaces to enhance teleoperation and telemanipulation of underwater ROVs (remotely operated vehicles). Traditional ROV teleoperation relies on low-resolution 2D camera feeds and lacks immersive and sensory feedback, which diminishes situational awareness in complex subsea environments. We propose SubSense - a novel VR-Haptic framework incorporating a non-invasive feedback interface to an otherwise 1-DOF (degree of freedom) manipulator, which is paired with the teleoperator's glove to provide haptic feedback and grasp status. Our results highlight the potential of multisensory feedback in immersive virtual environments to significantly improve remote situational awareness and mission performance, offering more intuitive and accessible ROV operations in the field. Remotely Operated V ehicles (ROVs) are indispensable tools in the marine industry, offering a safer and more cost-effective alternative to human divers [1]. Underwater ROVs are versatile platforms supporting a range of missions, from routine imaging and infrastructure inspection to complex tasks such as environmental monitoring [2], maintaining sub-sea infrastructure [3], [4], performing mine countermeasure and explosive ordinance disposal [5], salvaging, search-and-rescue [6], and deep-water expeditions [7]. With over 79% of subsea deployments done by ROVs, they play a crucial role in commerce, military, and science - enabling us to explore beyond the limits of human scuba divers [8]. Despite growing industrial demands and recent advancements, underwater ROVs still have inherent limitations, particularly in their immersive control and interaction capabilities.

The paper presents locality-sensitive hashing schemes for well-studied distance function between probability distributions. The new schemes are based on the ideas. The first one is to approximate the distance function of interest by another distance function for which LSH schemes are known. In particular, the paper shows how to approximate MIL divergence and triangular discrimination by the Hellinger distance, for which LSH schemes are known. The second is specific to the MIL divergence, and involves representing the latter distance function as a so-called Krein kernel, and designing an asymmetric LSH scheme.

Israel killed three Palestinians in a drone strike on Thursday in Tulkarem, a city and refugee camp in the occupied West Bank. That was during an Israeli raid – a near-daily occurrence in the West Bank – on the Tulkarem refugee camp, during which Israeli troops clashed with fighters from the Qassam Brigades, the military wing of Hamas, according to fighters in the city. Here's all you need to know about Israeli raids on Tulkarem: News reports say Israeli soldiers were deployed on rooftops and sent bulldozers into the camp to destroy large residential areas. Israel also reportedly set fire to people's homes and prevented local relief workers from putting the fires out. Experts say Israel's tactics during its raids appear to be part of a broader doctrine to collectively punish the population, ostensibly because pockets of armed resistance are fighting back against Israel's ever-entrenching occupation. Israel claims that it is conducting "counter-terrorism" operations.

In this paper, we extend our ensemble-based component model DEECo with the capability to use machine-learning and optimization heuristics in establishing and reconfiguration of autonomic component ensembles. We show how to capture these concepts on the model level and give an example of how such a model can be beneficially used for modeling access-control related problem in the Industry 4.0 settings. We argue that incorporating machine-learning and optimization heuristics is a key feature for modern smart systems which are to learn over the time and optimize their behavior at runtime to deal with uncertainty in their environment.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Making artificial intelligence (AI) work with humans requires having an internal data champion to help overcome fears and create a safe environment. That was the advice offered at Digital Procurement World in Amsterdam today in a session focused on combining humans and AI to help procurement become a top value driver in modern business. Working through overwhelming amounts of data and dealing with employee concerns that AI will take their jobs.

Many applications, or use "cases," of AI and machine learning already exist. The adoption of these use cases has been driven by both supply factors, such as technological advances and the availability of financial sector data and infrastructure, and by demand factors, such as profitability needs, competition with other firms, and the demands of financial regulation. As a subbranch of financial modeling, financial risk management has been evolving with the adoption of AI in parallel with its ever-growing role in the financial decision-making process. In his celebrated book, Bostrom (2014) denotes that there are two important revolutions in the history of mankind: the Agricultural Revolution and the Industrial Revolution. These two revolutions have had such a profound impact that any third revolution of similar magnitude would double the size of the world economy in two weeks. Even more strikingly, if the third revolution were accomplished by AI, the impact would be way more profound.

This paper describes the design and development of a prototype technique for artificial intelligence based on the fusion of genetic algorithm, neural network and fuzzy logic. It starts by establishing a relationship between the neural network and fuzzy logic. Then, it combines the genetic algorithm with them. Information fusions are at the confidence level, where matching scores can be reported and discussed. The technique is called the Genetic Neuro-Fuzzy (GNF). It can be used for high accuracy real-time environments.

This July 11, 2018, photo, shows a fragment of a US-made missile fired from a drone that struck a vehicle, killing all seven men inside on Jan. 26, 2018, instantly ending their lives, shredding their bodies into pieces, in Shabwa, Yemen. ATAQ, Yemen – Al-Qaida was giving away motorcycles up in the mountains -- that's what the kids in town were saying the day Abdullah disappeared. Early that morning, Mohsanaa Salem woke her 14-year-old son to go buy vegetables. The sun had just risen above the mountain ridge, and winter light filled the ravine where their mud brick house sat at the foot of a slope. "Let me sleep," Abdullah groaned from a mattress on the floor, surrounded by his brothers and sisters. One word from his father, though, and the boy was up and dressed, trudging out of the house to the market in a neighboring village. Three hours later, when he still hadn't returned, Mohsanaa and her husband began to worry.

The five-day event hosted around 4,500 exhibitors from more than 100 different countries. An estimated 100,000 visitors attended the annual event which focused on Artificial Intelligence as a key theme. Industry titans such as Google, Amazon, Alibaba and LinkedIn came together to discuss the latest trends. Google's Chief Decision Scientist Cassie Kozyrkov (left), LinkedIn's Chief Data Officer Igor Perisic (center) and Alibaba's Chief Machine Intelligence Scientist Wanli Min (right) debate on how AI is transforming decision making in major sectors On the hot topic of AI investment, the CDO of the networking and jobs portal Linkedin, Igor Perisic, spoke of the "blind spots" that companies integrating the technology into their businesses must be aware of. Alibaba's Chief Machine Intelligence Scientist, Wanli Min also explored how emerging technologies like autonomous vehicles and building smarter cities could meet the demands of swelling populations.

Artificial intelligence tools can draft contracts, write answers to legal complaints, or answer simple questions. They may not replace a lawyer's to-do list, but they could save time. Walmart and Nationwide Insurance are among the companies experimenting with how artificial intelligence tools can streamline their in-house legal departments and their work with outside counsel, and save money in the process. The use of more advanced data tools also is a growing cost-saving trend. That ultimately could drive law firms to change their thinking.