The development of smart cities and deep learning technology is changing our physical world to a cyber world. As one the main applications, Internet Vehicles has been developing rapidly. However, privacy leakage delay problem for data collection remain as key concerns behind fast intelligence technologies. If original collected are directly uploaded cloud processing, it will bring huge load pressure network communication. Moreover, during this process, lead privacy. To end, in article we...

The intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system is widely used in temporary emergency scenarios. Our goal to minimize the energy consumption of MEC by jointly optimizing UAV locations, IRS phase shift, task offloading, resource allocation with a variable number UAVs. To this end, we propose flexible scheduling (FRES) framework employing novel deep progressive reinforcement learning that includes following innovations....

The purpose of this study is to determine if amino acid neurotransmitters such as gamma-aminobutyric (GABA), taurine, glutamate (Glu), and aspartate (Asp) can scavenge activated carbonyl toxicants. In vitro, direct reaction between malondialdehyde (MDA) acids was researched using different analytical methods. results indicated that scavenging function taurine GABA very strong Glu Asp weak in pathophysiological situations. provided perspective into the mechanism targets MDA protecting nerve...

Abstract YBa 2 Cu 3 O 7-x (YBCO) films with low microwave surface resistance ( R S ) are essential for high temperature superconducting devices. The oxygen pressure during deposition has been found to influence significantly. In this work, we deposited highly c -axis aligned YBCO on single crystal MgO(001) substrates under different pressures via pulsed laser ablation. Their detailed microstructure was characterized three-dimensional reciprocal space mapping (3D-RSM) method and their also...

To address the vehicle-bridge coupling vibration issue of Qingyuan Maglev Tourist Line, it is necessary to establish a maglev vehicle–bridge dynamics simulation model that reflects actual line conditions. Based on vehicle and bridge structural parameters this paper utilizes multi-body software create medium–low-speed model, employs finite element construct model. Using modal reduction method, imported into through rigid–flex interface, establishing suspension system–bridge The accuracy...

As a new type of rail transit vehicle, maglev trains have extremely high requirements for safety and reliability. With the gradual commercial operation trains, how to scientifically effectively assess analyze risks train equipment has become an urgent issue be addressed. Against backdrop practical application projects, this paper integrates domestic international risk analysis models, proposes steps conducting transit, establishes system entire lifecycle transit. Based on results fault...

Different types of ore deposits exhibit distinct metal sources, physicochemical conditions, and ore-forming processes. Galena, a key sulfide in Pb-Zn deposits, possesses trace elements that may be utilized for classifying deposit types. Presently, research on based galena is sparse, there lack robust methods distinguishing using these elements. In this study, we demonstrate deep learning algorithm, the galena, can effectively The model training process UMAP visualization, evaluation was...

Soybean seed purity is a critical factor in agricultural products, standardization of quality, and food processing. In this study, laser-induced breakdown spectroscopy (LIBS) as an effective technology was successfully used to identify ten varieties soybean seeds. We improved the traditional sample preparation scheme for LIBS. Instead grinding squashing, we propose time-efficient method by pressing seeds into rubber sand filled with culture plates through ruler ensure relatively uniform...

Due to increasing awareness of environmental and economic issues for network operators, energy-efficiency has received much attention lately becomes one the major design goals in wireless networks. Since power consumption base stations (BS) occupies most energy cost entire cellular networks, this paper, we propose a novel saving method denoted as clustering BS-off (CBSO) scheme that all cells are cooperated dynamically adjusted switch on/off along with space time. Instead adopting unified...

Deep learning-based approaches for automatic depression recognition offer advantages of low cost and high efficiency. However, symptoms are challenging to detect vary significantly between individuals. Traditional deep learning methods often struggle capture model these nuanced features effectively, leading lower accuracy. This paper introduces a novel multimodal method, HYNMDR, which utilizes hypergraphs represent the complex, high-order relationships among patients with depression. HYNMDR...

By analyzing the data transmission Collisions for wireless sensor networks, due to shortage of energy efficiency and latency in MAC protocol, we propose a distributed TDMA scheduling protocol based on coloring algorithm (TDMA-CA), which uses spatial reuse channel. It allocates different colors conflict nodes arranges distinct slots each color by scheduling. Simulation results show that TDMA-CA is better than SMAC terms both efficient latency.

The purpose of the image quality assessment is to evaluate consistently with human's subjective evaluation. In assessment, many structural features have been used measure degradation an image. However, most existing methods are block-based, which ignores among neighboring blocks. this paper, we argue that human visual system perceives distortions not only depends on local (intra-block structure) distortions, but also relates their neighborhoods (inter-block texture). Based insight, propose a...

Chatbot-customer interaction is becoming increasingly prevalent. However, prior literature has not focused on the influence of chatbot-customer brand advocacy. In this paper, we study mechanism consumer Through a questionnaire survey 312 e-commerce users who used artificial intelligence-powered chatbot platforms, our shows that functional anthropomorphic interactions significantly affect Furthermore, customer experiences an intermediary role between and

The current culture that encourages online dating, and interaction makes large-scale social network users vulnerable to miscellaneous personal identifiable information leakage. To this end, we take a first step toward modeling privacy leakages in networks from both technical economic perspectives.From perspective, use Markov chain propose dynamic attack-defense tree-based model, which is temporal-aware, characterize an attack effort made by attacker corresponding countermeasure responded...

Topology control is important for heterogeneous sensor networks in order to minimize the total network power consumption under constraint that all nodes' connectivity requirements are satisfied. To address this issue, an optimization problem first formulated, which formally proved be NP-hard. For practical applications, effective solution, named topology adaptation algorithm (TAA), proposed. TAA adopts both graph theory and maximum flow find prespecified node disjoint paths with low time...

In real-world applications, wireless sensor networks often consist of a large number nodes with constraint battery resources. How to reduce the power consumption and maximize network life, becomes most important goal topology control schemes in networks. During operation networks, may spend different levels energy, result uneven distribution residual energy nodes. order extend it is essential adjust burden dynamically, so as achieve balance among under consideration at this paper, we...

Network connectivity is a critical property that provides communication foundation for most wireless sensor network (WSN) applications to operate successfully. Existing results on the WSN analysis are primarily based uniform distribution of sensors in bounded field interest. However, can be non-uniform practice due diverse deployment strategies, deviations and geographical limitations. We thus investigate random following Gaussian it simulate various nonuniform distributions. Specifically,...

This paper proposes a methodology for detecting intrusion in wireless sensor networks using Weak Hidden Markov Models (W-HMM). W-HMM is non-parametric version of models (HMM), wherein state transition probabilities are reduced to rules reachability. In particular, we introduce scoring scheme and deviation alarm mechanisms detect intrusion. Simulation results show that the efficient.