In recent years, imaging techniques are essential in our lives, such as security cameras and drive recorders. However, the visualization quality of these techniques sometimes is affected by scattering media, such as s...
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ISBN:
(纸本)9798331517939;9788993215380
In recent years, imaging techniques are essential in our lives, such as security cameras and drive recorders. However, the visualization quality of these techniques sometimes is affected by scattering media, such as smoke at a fire or fog during driving. To solve this problem, Peplography has been proposed. Peplography is an optical algorithm that emphasizes the object information presented in the scattering media, even when the density of the scattering media varies within the image. On the other hand, Peplography estimates the scattering media in each local region, and when the region is not defined appropriately, the estimation of the scattering media will not be visualized. Therefore, the purpose of this research is to find the optimal processing for each environment by experiment with various situations, such as when the size of the object in the image is small, when the density of the scattering media is heavy, and when the target object is various.
A combination of control Lyapunov functions (CLFs) and control barrier functions (CBFs) forms an efficient framework for addressing control challenges in safe stabilization. Developing an analytical control strategy, ...
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ISBN:
(纸本)9798350354416;9798350354409
A combination of control Lyapunov functions (CLFs) and control barrier functions (CBFs) forms an efficient framework for addressing control challenges in safe stabilization. Developing an analytical control strategy, known as the universal formula approach, which integrates CLF and CBF conditions, is recognized as a computationally efficient method for achieving safe stabilization. However, successful implementation of this universal formula relies on an accurate model, as any mismatch between the model and the actual system can compromise stability and safety. In this paper, we propose a new universal formula that leverages Gaussian processes (GPs) learning to address the safe stabilization problem in the presence of model uncertainty. By utilizing the results related to bounded learning errors, we achieve a high probability of stability and safety guarantees with the proposed universal formula. Additionally, we introduce a probabilistic compatibility condition to evaluate conflicts between the modified CLF and CBF conditions with GP learning results. In cases where compatibility assumptions fail, we propose a modified universal formula that relaxes stability constraints. We illustrate the effectiveness of our approach through a simulation of adaptive cruise control (ACC), highlighting its potential for practical applications in real-world scenarios.
Wearable sensor-based stress detection is a well-explored area of research in the domain of Affective computing and can be performed with the help of non-invasive sensing modalities like Electrodermal Activity (EDA). ...
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ISBN:
(纸本)9798350304367;9798350304374
Wearable sensor-based stress detection is a well-explored area of research in the domain of Affective computing and can be performed with the help of non-invasive sensing modalities like Electrodermal Activity (EDA). The EDA sensors with a wearable form factor are commonly available on commercial off-the-shelf devices. In recent years, with the increased availability of such wearable devices to end-users, these applications have become more pervasive and thus require a greater level of optimization for continuous usage on resource-constrained and battery-powered devices. While several research works have focused on designing Machine Learning and Deep Learning models for these tasks, very few focus on the resource footprint of these models. The balance between classification accuracy and computational resources is difficult to achieve with a manual design process and takes a long time. This is where automation plays a key role. In this work, we explore the applicability of automation Techniques such as Neural Architecture Search (NAS), to create tiny Stress Detection models suitable for round-the-clock inference, with minimal resource requirements, and low latency to perform in real-time, and show the trade-off between the various metrics on four publicly available datasets combined, and achieve an accuracy of 85.98% with a model size of 49.40 kB, which is comparable to the state-of-the-art counterparts.
Robotic processautomation (RPA) as one of the ramifications of the Artificial Intelligence, is emerging rapidly because of its adaptation across numerous industries day by day. As a result, organizations are able to ...
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In recent years, the Intent-driven Network (IBN) has been proposed to further enhance the intelligence of communication systems. In IBN, users can express their resource expectations through intents while the IBN perf...
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ISBN:
(纸本)9798350361261;9798350361278
In recent years, the Intent-driven Network (IBN) has been proposed to further enhance the intelligence of communication systems. In IBN, users can express their resource expectations through intents while the IBN performs resource scheduling to fulfill these intents. Many challenges of complex networks can be tackled by IBN such as the mobile edge computing (MEC) system. In a MEC system, limited computing resources are competed by the users which may cause the intent conflict. To solve this, in this paper, we introduce the IBN concept to the MEC system, where an intent conflict detection module is proposed. The proposed module is based on the Open Network automation Platform (ONAP) architecture. Moreover, by formulating the computing resource conflict problem as a Markov decision process (MDP) model, we employ an improved deep Qnetwork (DQN) algorithm to improve the efficiency of resource utilization. Simulation results demonstrate the completion time of intents is remarkably reduced in the proposed intent conflict resolution scheme.
Despite the rapid development of edge and fog computing technologies, including significant improvements in the characteristics of communication channels and computing devices themselves, the problems associated with ...
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This conference paper delves into the transformative synergy of Environmental computing, Agricultural Engineering, and Artificial Intelligence (AI) to forge sustainable ICT applications in agriculture. By amalgamating...
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This paper discusses the theory of embedded database SQLite and its application development on ARM platform, analyzes the characteristics of embedded database in detail, and expounds the architecture of embedded datab...
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Industries can profit from automation by increasing rate of production and decreasing errors, improving safety and stabilising the manufacturing process. High levels of profitability, dependability and safety come wit...
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The intelligent fire detection and response system integrates three key components: Fire Type Identification, Fire Tracking, and Dynamic Nozzle control. The Fire Identification component uses a multi-sensor setup (tem...
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