the increase in irrigated crop areas lead to the requirements for freshwater will in fact rise significantly. Considering this kind of need, this study aims to develop a low cost irrigation system that provide the mon...
详细信息
the proceedings contain 79 papers. the topics discussed include: an interactive approach for query-based multi-document scientific text summarization;enhancing Persian word sense disambiguation with large language mod...
ISBN:
(纸本)9798331511272
the proceedings contain 79 papers. the topics discussed include: an interactive approach for query-based multi-document scientific text summarization;enhancing Persian word sense disambiguation with large language models techniques and applications;assessing users' influence on respondents in conversation quality: a quantitative study on reddit based on the cooperative principle;non-negative matrix factorization improves residual neural networks;cluster sampling: a cluster-driven sampling strategy for deep metric learning;a scalable blockchain-based educational network for data storage and assessment;towards efficient capsule networks through approximate squash function and layer-wise quantization;automated software design using machine learning with natural language processing;evaluation of efficient electrocardiomatrix-based identification using deep learning methods;disturbance rejection in quadruple-tank system by proposing new method in reinforcement learning;and an improved and accurate measure for mining correlated high-utility itemsets.
Traffic prediction is essential for intelligent transportation systems and smart city applications, yet existing spatio-temporal models face limitations. these include inadequate spatial feature extraction, neglect of...
详细信息
Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more complex. Follow...
详细信息
ISBN:
(纸本)9781665457019
Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more complex. Following the path of traditional softwareengineering, machine learning engineers have begun to reuse large-scale pre-trained models (PTMs) and fine-tune these models for downstream tasks. Prior works have studied reuse practices for traditional software packages to guide software engineers towards better package maintenance and dependency management. We lack a similar foundation of knowledge to guide behaviors in pre-trained model ecosystems. In this work, we present the first empirical investigation of PTM reuse. We interviewed 12 practitioners from the most popular PTM ecosystem, Hugging Face, to learn the practices and challenges of PTM reuse. From this data, we model the decision-making process for PTM reuse. Based on the identified practices, we describe useful attributes for model reuse, including provenance, reproducibility, and portability. three challenges for PTM reuse are missing attributes, discrepancies between claimed and actual performance, and model risks. We substantiate these identified challenges with systematic measurements in the Hugging Face ecosystem. Our work informs future directions on optimizing deep learning ecosystems by automated measuring useful attributes and potential attacks, and envision future research on infrastructure and standardization for model registries.
Small uncrewed aerial systems, sUAS, provide an invaluable resource for performing a variety of surveillance, search, and delivery tasks in remote or hostile terrains which may not be accessible by other means. Due to...
详细信息
ISBN:
(纸本)9798350311921
Small uncrewed aerial systems, sUAS, provide an invaluable resource for performing a variety of surveillance, search, and delivery tasks in remote or hostile terrains which may not be accessible by other means. Due to the critical role sUAS play in these situations, it is vital that they are well configured in order to ensure a safe and stable flight. However, it is not uncommon for mistakes to occur in configuration and calibration, leading to failures or incomplete missions. To address this problem, we propose a set of self-adaptive mechanisms and implement them into a self-adaptive framework, CICADA, for Controller Instability-preventing Configuration Aware Drone Adaptation. CICADA dynamically detects unstable drone behavior during flight and adapts to mitigate this threat. We have built a prototype of CICADA using a popular open source sUAS simulator and experimented with a large number of different configurations. Experimental results show that CICADA's adaptations reduce controller instability and enable the sUAS to recover from a significant number of poor configurations. In cases where we cannot complete the intended mission, invoking alternative adaptations may still help by allowing the vehicle to loiter or land safely in place, avoiding potentially catastrophic crashes.
Withthe rapid development of the software industry, software supply chains have become increasingly complex and diverse. Critical software domains such as operating systems, databases and web servers extensively adop...
详细信息
the plane is the fundamental characteristic for describing the shape of polyhedral buildings. Roof plane segmentation of airborne LiDAR point clouds is an important step in 3D building model reconstruction. Existing m...
详细信息
Large companies today compete in terms of innovation to enhance overall productivity by leveraging their technology with high speed, accuracy, reliability, and ease of operation as tools to support their productivity....
详细信息
With Industry 4.0's technological advancements, the convenience and affordability of Artificial Intelligence (AI) and IoT have increased. However, customers still face long waiting times in payment queues during t...
详细信息
暂无评论