Most existing mobile robotic datasets primarily capture static scenes, limiting their utility for evaluating robotic performance in dynamic environments. To address this, we present a mobile robot oriented large-scale indoor dataset, denoted as THUD++ (TsingHua University Dynamic) robotic dataset, for dynamic scene understanding. Our current dataset includes 13 large-scale dynamic scenarios, combining both real-world and synthetic data collected with a real robot platform and a physical simulation platform, respectively. The RGB-D dataset comprises over 90K image frames, 20M 2D/3D bounding boxes of static and dynamic objects, camera poses, and IMU. The trajectory dataset covers over 6,000 pedestrian trajectories in indoor scenes. Additionally, the dataset is augmented with a Unity3D-based simulation platform, allowing researchers to create custom scenes and test algorithms in a controlled environment. We evaluate state-of-the-art methods on THUD++ across mainstream indoor scene understanding tasks, e.g., 3D object detection, semantic segmentation, relocalization, pedestrian trajectory prediction, and navigation. Our experiments highlight the challenges mobile robots encounter in indoor environments, especially when navigating in complex, crowded, and dynamic scenes. By sharing this dataset, we aim to accelerate the development and testing of mobile robot algorithms, contributing to real-world robotic applications.

Slate has relationships with various online retailers. If you buy something through our links, Slate may earn an affiliate commission. We update links when possible, but note that deals can expire and all prices are subject to change. All prices were up to date at the time of publication. It shouldn't be surprising that my list of my favorite books of 2024 includes a number of works by older writers working out what it means to make art as a career--what their creative future might look like.

In retail sales forecasting, accurately predicting future sales is crucial for inventory management and strategic planning. Traditional methods like LR often fall short due to the complexity of sales data, which includes seasonality and numerous product families. Recent advancements in machine learning (ML) provide more robust alternatives. This research benefits from the power of ML, particularly Random Forest (RF), Gradient Boosting (GB), Support Vector Regression (SVR), and XGBoost, to improve prediction accuracy. Despite advancements, a significant gap exists in handling complex datasets with high seasonality and multiple product families. The proposed solution involves implementing and optimizing a RF model, leveraging hyperparameter tuning through randomized search cross-validation. This approach addresses the complexities of the dataset, capturing intricate patterns that traditional methods miss. The optimized RF model achieved an R-squared value of 0.945, substantially higher than the initial RF model and traditional LR, which had an R-squared of 0.531. The model reduced the root mean squared logarithmic error (RMSLE) to 1.172, demonstrating its superior predictive capability. The optimized RF model did better than cutting-edge models like Gradient Boosting (R-squared: 0.942), SVR (R-squared: 0.940), and XGBoost (R-squared: 0.939), with more minor mean squared error (MSE) and mean absolute error (MAE) numbers. The results demonstrate that the optimized RF model excels in forecasting retail sales, handling the datasets complexity with higher accuracy and reliability. This research highlights the importance of advanced ML techniques in predictive analytics, offering a significant improvement over traditional methods and other contemporary models.

In product search, the retrieval of candidate products before re-ranking is more critical and challenging than other search like web search, especially for tail queries, which have a complex and specific search intent. In this paper, we present a hybrid system for e-commerce search deployed at Walmart that combines traditional inverted index and embedding-based neural retrieval to better answer user tail queries. Our system significantly improved the relevance of the search engine, measured by both offline and online evaluations. The improvements were achieved through a combination of different approaches. We present a new technique to train the neural model at scale. and describe how the system was deployed in production with little impact on response time. We highlight multiple learnings and practical tricks that were used in the deployment of this system.

Cyber Monday 2024 is nearly over, but there are plenty of tech deals to consider if you're looking for a few things for yourself or to give as gifts this year. As it has been for a few years now, Cyber Monday is basically just an extension of Black Friday: most of the best Black Friday deals have now become the best Cyber Monday deals (unless they've sold out), and there tend to be a few surprises thrown in as Cyber Monday exclusives. A number of our favorite gadgets continue to be on sale for Cyber Monday even as the day draws to a close, including earbuds, tablets, robot vacuums and much more. These are the best Cyber Monday deals you can still get right now. We expect most of these sales to expire tonight, so we recommend grabbing what you want before the end of today.

Advancements in artificial intelligence, machine learning, and deep learning have catalyzed the transformation of big data analytics and management into pivotal domains for research and application. This work explores the theoretical foundations, methodological advancements, and practical implementations of these technologies, emphasizing their role in uncovering actionable insights from massive, high-dimensional datasets. The study presents a systematic overview of data preprocessing techniques, including data cleaning, normalization, integration, and dimensionality reduction, to prepare raw data for analysis. Core analytics methodologies such as classification, clustering, regression, and anomaly detection are examined, with a focus on algorithmic innovation and scalability. Furthermore, the text delves into state-of-the-art frameworks for data mining and predictive modeling, highlighting the role of neural networks, support vector machines, and ensemble methods in tackling complex analytical challenges. Special emphasis is placed on the convergence of big data with distributed computing paradigms, including cloud and edge computing, to address challenges in storage, computation, and real-time analytics. The integration of ethical considerations, including data privacy and compliance with global standards, ensures a holistic perspective on data management. Practical applications across healthcare, finance, marketing, and policy-making illustrate the real-world impact of these technologies. Through comprehensive case studies and Python-based implementations, this work equips researchers, practitioners, and data enthusiasts with the tools to navigate the complexities of modern data analytics. It bridges the gap between theory and practice, fostering the development of innovative solutions for managing and leveraging data in the era of artificial intelligence.

Robot vacuums can help automate a chore you may loathe doing yourself. And even if you don't mind vacuuming regularly, it's undeniable that it takes time out of your day that you could be using for other things. The Black Friday and Cyber Monday time period is a great time to look for one of these smart home gadgets because you can often find them for hundreds of dollars off their usual prices -- this year is no different. We've seen steep discounts on many of our favorite robot vacuum cleaners, as well as some cordless vacuums too. These are the best Cyber Monday vacuum deals you can still get in the final hours of the sale.

Life as a WIRED Gear writer comes with certain demands. Many of us are into outdoor activities, like climbing, running, skiing, camping, or biking. But these sports are expensive, and you need specialized clothing in order to not freeze to death. That's not including all the time we spend shuffling boxes around and forcing our spouses to help us unbox TVs and move around treadmills and pizza ovens. Do you, too, want people to look at you and think, "That person spends most of their time swinging kettle bells and watching videos of self-driving cars?" Thanks to Cyber Monday, you can.

Robot vacuums can help automate a chore you may loathe doing yourself. And even if you don't mind vacuuming regularly, it's undeniable that it takes time out of your day that you could be using for other things. The Black Friday and Cyber Monday time period is a great time to look for one of these smart home gadgets because you can often find them for hundreds of dollars off their usual prices -- this year is no different. These are the best Cyber Monday vacuum deals you can get this year. Shark AI Ultra robot vacuum with self-emptying base for 300 ( 300 off): A version of one of our top picks, this Shark robot vacuum cleans both carpet and hard flooring well, has an easy-to-use app, a self-cleaning brushroll and a bagless self-emptying base that can hold up to 60 days worth of debris before you need to empty it.

That means it's time to settle in for some serious winter gaming. These Cyber Monday gaming deals can help. Seriously, this is one of the best times of the year to make those hardware upgrades you've been mulling over, whether that's a nicer keyboard, a new monitor, some upgrades to your gaming desktop, or heck, even a new PS5. We've even got a couple of video game deals in here if you've been patiently waiting for a sale. Be sure to check out our live Cyber Monday deals tracker for more. We've spotted a few deals on the PlayStation 5 Slim with a variety of different games and bundles.