Another difficulty is entanglement of the labels.

We present VersaPants, the first loose-fitting, textile-based capacitive sensing system for lower-body motion capture, built on the open-hardware VersaSens platform. By integrating conductive textile patches and a compact acquisition unit into a pair of pants, the system reconstructs lower-body pose without compromising comfort. Unlike IMU-based systems that require user-specific fitting or camera-based methods that compromise privacy, our approach operates without fitting adjustments and preserves user privacy. VersaPants is a custom-designed smart garment featuring 6 capacitive channels per leg. We employ a lightweight Transformer-based deep learning model that maps capacitance signals to joint angles, enabling embedded implementation on edge platforms. To test our system, we collected approximately 3.7 hours of motion data from 11 participants performing 16 daily and exercise-based movements. The model achieves a mean per-joint position error (MPJPE) of 11.96 cm and a mean per-joint angle error (MPJAE) of 12.3 degrees across the hip, knee, and ankle joints, indicating the model's ability to generalize to unseen users and movements. A comparative analysis of existing textile-based deep learning architectures reveals that our model achieves competitive reconstruction performance with up to 22 times fewer parameters and 18 times fewer FLOPs, enabling real-time inference at 42 FPS on a commercial smartwatch without quantization. These results position VersaPants as a promising step toward scalable, comfortable, and embedded motion-capture solutions for fitness, healthcare, and wellbeing applications.

We may earn revenue from the products available on this page and participate in affiliate programs. The company has been making great jackets, bags, and pretty much everything else you need for outdoor activities since 1973. "While Patagonia stuff is great, it's not usually cheap. Fortunately, REI currently has a ton of last year's products on sale with steep discounts. That includes some of the most popular items like the puffer jackets and the fleece pullovers.

How to Do It is Slate's sex advice column. Send it to Jessica and Rich here. I recently started casually online dating after leaving an abusive marriage, and it's been going great! There have been lots of nice guys, and we have had some sexy fun. That said, I've run into a weird situation that I'm almost certainly overthinking but am baffled by.

The applied research is the design and development of an automated folding and sewing machine for pleated pants. It represents a significant advancement in addressing the challenges associated with manual sewing processes. Traditional methods for creating pleats are labour-intensive, prone to inconsistencies, and require high levels of skill, making automation a critical need in the apparel industry. This research explores the technical feasibility and operational benefits of integrating advanced technologies into garment production, focusing on the creation of an automated machine capable of precise folding and sewing operations and eliminating the marking operation. The proposed machine incorporates key features such as a precision folding mechanism integrated into the automated sewing unit with real-time monitoring capabilities. The results demonstrate remarkable improvements: the standard labour time has been reduced by 93%, dropping from 117 seconds per piece to just 8 seconds with the automated system. Similarly, machinery time improved by 73%, and the total output rate increased by 72%. These enhancements translate into a cycle time reduction from 117 seconds per piece to an impressive 33 seconds, enabling manufacturers to meet customer demand more swiftly. By eliminating manual marking processes, the machine not only reduces labour costs but also minimizes waste through consistent pleat formation. This automation aligns with industry trends toward sustainability and efficiency, potentially reducing environmental impact by decreasing material waste and energy consumption.

Despite outstanding processes in many tasks, Large Language Models (LLMs) still lack accuracy when dealing with highly technical domains. Especially, telecommunications (telco) is a particularly challenging domain due the large amount of lexical, semantic and conceptual peculiarities. Yet, this domain holds many valuable use cases, directly linked to industrial needs. Hence, this paper studies how LLMs can be adapted to the telco domain. It reports our effort to (i) collect a massive corpus of domain-specific data (800M tokens, 80K instructions), (ii) perform adaptation using various methodologies, and (iii) benchmark them against larger generalist models in downstream tasks that require extensive knowledge of telecommunications. Our experiments on Llama-2-7b show that domain-adapted models can challenge the large generalist models. They also suggest that adaptation can be restricted to a unique instruction-tuning step, dicarding the need for any fine-tuning on raw texts beforehand.

Whoopi Goldberg and'View' guest Charlamagne Tha God argued over President Biden's pardon of Hunter and whether he was a liar. "The View" co-host Ana Navarro admitted that she relied on information given by ChatGPT after she was mocked for sharing false information about presidential pardons in her defense of President Biden. Biden came under fire this week for issuing a sweeping pardon to his son Hunter Biden on Sunday after repeatedly insisting he would not do so. Navarro, who identifies as a Republican but is an ardent supporter of Democrats who reliably offers liberal commentary on "The View" and on CNN, came out swinging against Biden's critics. She wrote on X, "Woodrow Wilson pardoned his brother-in-law, Hunter deButts. Bill Clinton pardoned his brother, Roger. Donald Trump pardoned his daughter's father-in-law, Charlie Kushner. And just appointed him Ambassador to France. But tell me again how Joe Biden'is setting precedent'?" Navarro's bizarre claim about Woodrow Wilson's pardon of a fictional brother-in-law named "Hunter deButts" instantly raised eyebrows.

The first piece of AI-generated video I ever made moved me to tears – tears of laughter. Given the chance to fool around with Runway AI's Gen-3 Alpha, I dropped in an image of an eagle carrying off a wolf. Moments later, the picture sprang into life. Except the bird only had one leg – and its plummeting prey sprouted wings from its tail and morphed into a wolf-headed goose. It was weird and hilarious.

Movement disorders impact muscle strength and mobility, and despite therapeutic efforts, many people with movement disorders have challenges functioning independently. Soft wearable robots, or exosuits, offer a promising solution for continuous daily support, however, commercially viable devices are not widely available. Here, we introduce a design framework for lower limb exosuits centered on a soft pneumatically driven fabric-based actuator. Our design consists of a novel multi-material textile sleeve that incorporates braided mesh and knit-elastic materials to realize hyper-bending actuators. The actuators incorporate 3D-printed self-sealing end caps that are attached to a semi-rigid human-robot interface to secure them to the body. We will demonstrate the effectiveness of our exosuit in generating enough force to assist during sit-to-stand transitions.