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This study explores robotic telepresence in classrooms, from the perspectives of both the remote students (operators) and their in-person classmates. Analyzing a subset of field study data from 35 participants (22 operators, 13 classmates), we ...

Tensor transposition is a fundamental operation in tensor calculations with various applications. However, a naive implementation that copies each element from the source tensor to the transposed position in the _target tensor requires double space, making ...

Heterogeneous multiprocessor architecture is frequently employed as an economical and efficient means of providing excellent parallel processing capabilities while keeping production cost and power consumption under control. Although this architecture ...

Depthwise separable convolution (DSC) is a popular method for constructing lightweight neural networks. However, the pointwise convolution (PWC) has a much larger number of parameters than the depthwise convolution (DWC), causing the imbalanced parameter ...

Several photonic microring resonators (MRRs) based analog accelerators have been proposed to accelerate the inference of integer-quantized Convolutional Neural Networks (CNNs) with remarkably higher throughput and energy efficiency compared to their ...

Caching content at the edge network is a popular and effective technique widely deployed to alleviate the burden of network backhaul, shorten service delay, and improve service quality. However, there has been some controversy over privacy violations in ...

As artificial intelligence techniques become more sophisticated, we anticipate that robots collaborating with humans will develop their own intentions, leading to potential conflicts in interaction. This development calls for advanced conflict resolution ...

Safety-critical systems are often designed as real-time distributed systems. Despite the need for strong guarantees of safety and reliability in these systems, applying formal verification methods to real-time distributed systems at the implementation ...

The Internet of Bio-Nano Things (IoBNT) is collaborative cell biology and nanodevice technology interacting through Molecular Communication (MC). The IoBNT can be accomplished by using the Information and Communication Theory (ICT) study of biological ...

Performance diagnosis systems are defined as detecting abnormal performance phenomena and play a crucial role in cloud applications. An effective performance diagnosis system is often developed based on artificial intelligence (AI) approaches, which can ...

Nowadays, GPUs significantly boost rendering performance. However, the high memory requirements limit their use, especially on low-end mobile platforms. Compression techniques have been widely adopted to reduce memory consumption but face two primary ...

Erasure coding is a known redundancy technique that has been popularly deployed in modern storage systems to protect against failures. By introducing a small portion of coded redundancy into data storage, erasure coding is shown to provide higher ...

Holographic Storage is an old idea that has always promised high density and fast random access, but has never been commercially competitive with Hard Disk Drives (HDDs) and Solid State Devices (SSDs). In Project HSD at Microsoft Research we asked the ...

Predicting air quality using multimodal data is crucial to comprehensively capture the diverse factors influencing atmospheric conditions. Therefore, this study introduces a multimodal learning framework that integrates outdoor images with traditional ...

Multi-sensor IoT devices often rely on renewable energy and batteries to support diverse field deployments. A device’s sensors use significant energy, so careful energy management is needed to maximize its operating time while meeting application ...

Color formulation prediction aims to get different _target colors based on a specified color range. It was difficult for existing color matching methods to achieve accurate nonlinear mapping from _target colors to formulations due to the overlook of the ...

In this paper, we consider the issue of online portfolios with transaction costs, and combine long and short term forecasting approaches to address both returns and risks. Specifically, we measure transaction costs by adding the ℓ₁ norm to the objective ...

Mamba — the selective SSM (S6) model, makes up for inherent shortcomings of Transformer in long sequence processing and has been gaining significant attention from researchers. In this paper, we employ Mamba to build a multimodal chat model — Multimodal ...

Currently, there is a significant gap in the conversion of mathematical theorems from natural language to logical expressions, specifically in the form of first-order predicate logic. To address this issue, this paper presents a corpus of mathematical ...

In recent years, large language models (LLMs) have demonstrated remarkable capabilities across various natural language processing tasks. This study explores the application of LLMs for data augmentation in text-pair classification tasks, such as semantic ...