This paper studies the relationship between a graph neural network (GNN) and a manifold neural network (MNN) when the graph is constructed from a set of points sampled from the manifold, thus encoding geometric inform...
详细信息
Secure system operations rely on reliable network structures. The loss of controllability may be the main reason to cause cascaded failures for complex network, e.g., Energy Internet (EI). However, the existing studie...
Secure system operations rely on reliable network structures. The loss of controllability may be the main reason to cause cascaded failures for complex network, e.g., Energy Internet (EI). However, the existing studies do not consider the network controllability to guide the system reconfiguration. To address this issue, the paper proposes a new structuring planning method for EI with consideration of controllability and economy. Firstly, the structure planning problem is modeled as a dynamic optimization problem with the tradeoff objectives of maximum social welfare and minimum driven nodes for long-term period. Then, a mixed maximum matching and deep deterministic policy gradient method is presented to obtain the approximate optimal planning solution with strong adaptability. Finally, simulation results demonstrate the effectiveness of the proposed method.
With the rapid advancement of data acquisition technologies, multiview data have been widely applied in fields such as social networks, computer vision, and natural language processing. Multiview data typically contai...
详细信息
Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally, customizing ACO for a specific problem requires the ...
Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally, customizing ACO for a specific problem requires the expert design of knowledge-driven heuristics. In this paper, we propose DeepACO, a generic framework that leverages deep reinforcement learning to automate heuristic designs. DeepACO serves to strengthen the heuristic measures of existing ACO algorithms and dispense with laborious manual design in future ACO applications. As a neural-enhanced meta-heuristic, DeepACO consistently outperforms its ACO counterparts on eight COPs using a single neural model and a single set of hyperparameters. As a Neural Combinatorial Optimization method, DeepACO performs better than or on par with problem-specific methods on canonical routing problems. Our code is publicly available at https://***/henry-yeh/DeepACO.
This paper presents a thorough exploration of Cryptoprocessors in the context of the Internet of Things (IoT). The focus is on hardware support, cryptographic processors, and energy-efficient designs to fortify the se...
详细信息
ISBN:
(数字)9798350369441
ISBN:
(纸本)9798350369458
This paper presents a thorough exploration of Cryptoprocessors in the context of the Internet of Things (IoT). The focus is on hardware support, cryptographic processors, and energy-efficient designs to fortify the security of IoT ecosystems. Leveraging insights from recent research papers, the survey examines various aspects of Cryptoprocessor implementations, ranging from lightweight countermeasures to advanced lattice-based post-quantum cryptography. The proposed paper amalgamates findings from studies on hardware architectures, energy-efficient designs, and innovative cryptographic algorithms to provide a holistic overview of state-of-the-art advancements in IoT security. The synthesis of this survey’s exploration aims to contribute to the ongoing discourse on securing IoT devices through robust hardware-backed cryptographic solutions.
We build on the Deep Q-Learning Network (DQN) to solve the N-Queens problem to propose a solution to the Golomb Ruler problem, a popular example of a one dimensional constraint satisfaction problem. A comparison of th...
详细信息
Integrating Unmanned Aerial Vehicles (UAVs) into the emerging sixth-generation and beyond (6G + ) cellular networks as aerial base stations represents a significant technological advancement. This integration offers n...
详细信息
ISBN:
(数字)9798350361261
ISBN:
(纸本)9798350361278
Integrating Unmanned Aerial Vehicles (UAVs) into the emerging sixth-generation and beyond (6G
+
) cellular networks as aerial base stations represents a significant technological advancement. This integration offers numerous benefits, including widespread accessibility, enhanced navigation, and simplified monitoring and management. A key element of this integration involves the instantaneous distribution of vital information throughout the transportation infrastructure. Characterized by their agility, mobility, and flexibility, UAVs play a crucial role in relieving data traffic loads, thereby offering additional access points. This function is essential for making prompt, precise, and well-informed decisions in Intelligent Transportation systems (ITS), utilizing data-centric insights. Deploying versatile Road Side Units (RSUs) for secure data collection and dissemination requires a robust framework for safe data transfer. Ensuring data governance in the Internet of Vehicles (IoV) network relies heavily on specific interactions between trusted parties. In response, we introduce an advanced encryption approach to promote secure data exchange in ITS, thus supporting the confidential transfer of information in IoV communications. This innovative encryption method can also perform encryption and decryption of ciphertexts, encompassing confidential data and facilitating secure communication.
In this study, the thermal management problem of the modern communication systems with small array sizes is addressed. A novel dual-functional active antenna design strategy is introduced for adjustable frequency of o...
In this study, the thermal management problem of the modern communication systems with small array sizes is addressed. A novel dual-functional active antenna design strategy is introduced for adjustable frequency of operation and cooling extension at millimeter-wave bands. The concept is based on placing different types of heatsinks on the same patch antenna. The electromagnetic and thermal behavior of the proposed heatsink structures are presented via simulations. Reconfigurable operation at 24, 26, and 28 GHz frequencies with 23 to 28 degrees of extra cooling in the chip as compared to the conventional patch is achieved.
In IoT-based smart agriculture systems, the acquisition of high-quality sensing data plays a key role in enabling informed decisions by farmers. However, the deployment of wireless sensors in remote agricultural areas...
In IoT-based smart agriculture systems, the acquisition of high-quality sensing data plays a key role in enabling informed decisions by farmers. However, the deployment of wireless sensors in remote agricultural areas often entails facing frequent network disconnections. Furthermore, the necessity for uninterrupted monitoring is in contrast with the energy-saving requirements of battery-operated IoT devices. In this paper, we propose a solution that decouples the connection between IoT sensors and the cloud by introducing an intermediary software stratum acting as an edge data proxy. More specifically, our framework assigns a Digital Shadow to each IoT device, endowed with the capability to predict forthcoming sensor values during devices' low-power modes or network disconnections. Three main contributions are provided in this paper. First, we present the architecture and operations of our framework, enabling the orchestration of phases of sensor readings and data forecasting and the consequential adjustment of the device sampling frequency. Second, we introduce a novel time series forecasting approach that aims at identifying diverse patterns in the sensor time series and at instantiating distinct Machine Learning (ML) models for each individual pattern. Third, we validate our framework through real-world soil moisture datasets. The experimental results showcase the efficacy of our approach in delivering accurate forecasts, outperforming single-model and context-aware methodologies.
In last decades, new manufacturing requirements have introduced new approaches for distributed control and automation, some of them introducing concepts as self-organization and emergence. BIOSOARM (a Bio-inspired Sel...
详细信息
暂无评论