Exciting advances have been made in artificial intelligence (AI) during the past decades. Among them, applications of machine learning (ML) and deep techniques brought human-competitive performances various tasks fields, including image recognition, speech recognition natural language understanding. Even Go, ancient game profound complexity, AI player already beat human world champions convincingly with without from human. In this work, we show that our unsupervised machines (Atom2Vec) can...

Pine wilt disease (PWD) is a global devastating threat to forest ecosystems. Therefore, feasible and effective approach precisely monitor PWD infection indispensable, especially at the early stages. However, precise definition of "early stage" rapid high-efficiency method detect have not been well established. In this study, we systematically divided into green, early, middle, late stages based on needle color, resin secretion, whether pine wood nematode (PWN) was carried. Simultaneously, an...

Gesture recognition is the central enabler of human-computer interaction (HCI). In addition to semantic information contained in gestures, gesture-based user identification can effortlessly enhance HCI system security. Recently, Wi-Fi-integrated sensing and communication (ISAC) technology has shown great potential a field hitherto occupied by computer vision radar sensing. this work, leveraging Wi-Fi sensing, we propose called WiGesID that achieves joint gesture human (JGRHI). The basic idea...

Deep learning (DL) has been widely applied in automatic modulation classification (AMC), while the superb performance highly depends on high-quality datasets. Motivated by this, AMC under few-shot conditions is considered this letter, where a novel network architecture proposed, namely relation (AMCRN), and verified with baseline methods. Experimental results state that accuracy of proposed AMCRN exceeds 90% 10% to 50% improvements are obtained compared classical schemes...

Pine wilt disease (PWD) has caused huge economic and environmental losses since it invaded China. Although early monitoring is an effective way to control this hazard, the window for stage hard identify, varies in different hosts environments. We used UAV-based multispectral images of Pinus thunbergii forest East China identify change number infected trees each month growing season. built classification models detect PWD infection stages by testing three machine learning algorithms—random...

Abstract With the development of big data and artificial intelligence, applications smart grid have received extensive attention. Specifically, accurate power system load forecasting plays an important role in safety stability production scheduling process. Due to limitations traditional methods dealing with large scale nonlinear time series data, this paper, we proposed Attention-BiLSTM (Attention based Bidirectional Long Short-Term Memory, Attention-BiLSTM) network do short-term...

By leveraging massive available data and hidden communication patterns, deep learning (DL) has enabled diverse applications in wireless network operations. In this paper, we consider radar-aided beam prediction multi-input multi-output (MIMO) systems with federated transfer (FTL) to preserve users' location privacy. Specifically, propose a novel structure, i.e., (RaFT-BP), achieve few samples-enabled distributed selection internet of vehicles (IoV) scenarios. Simulation results show that the...

As demand for high-capacity, low-latency communication rises, mmWave systems are essential enabling ultra-high-speed transmission in fifth-generation mobile technology (5G) and upcoming 6G networks, especially dynamic, data-scarce environments. However, deploying dynamic environments presents significant challenges, beam selection, where limited training data environmental variability hinder optimal performance. In such scenarios, computation offloading has emerged as a key enabler, allowing...

Deep reinforcement learning has been widely applied to solve the anti-jamming problems in wireless communications, achieving good results. However, most research assumes that communication system can obtain complete Channel State Information (CSI). Under limited CSI conditions, this paper models using Partially Observable Markov Decision Processes (POMDPs). In addition, it is challenging determine optimal exploration rate decay factor for decision algorithms exponential rate. This proposes...

Schematic diagram of the mechanisms by which phlorizin regulates metabolic disorders.

The novel framework of an integrated aeronautical communication and radar system (IACRS) to realize spectrum sharing is investigated. A non-orthogonal multiple access (NOMA)-motivated multi-input–multi-output (MIMO) scheme proposed for the dual-function system, which able detect aircraft while simultaneously transmitting dedicated messages. Specifically, NOMA-inspired technology utilized enable dual-spectrum sharing. superposition signals facilitated in power domain. Successive interference...

Abstract BACKGROUND Maize is one of the most important food crops in world. Many different varieties maize seeds are similar size and appearance, so distinguishing seed a significant research topic. This study used hyperspectral image processing coupled with convolutional neural network (CNN) subregional voting method to recognize seed. RESULTS First, visible near‐infrared (NIR‐visible) images were obtained. Savitzky–Golay (SG) smoothing first derivative (FD) pretreat raw spectra highlight...

Beijing’s One Million Mu Plain Afforestation Project involves planting large areas with the exotic North American tree species Fraxinus pennsylvanica Marsh (ash). As an species, ash is very vulnerable to infestations by emerald borer (EAB), a native Chinese wood pest. In early stage of EAB infestation, attacked trees show no obvious sign. Once stand has reached late damage stage, death occurs rapidly. Therefore, there need for efficient detection methods stress over areas. The combination...

In computer systems, information leaks from the physical hardware through side-channel signals such as power draw. We can exploit these to infer state of ongoing computational tasks without having direct access device. This paper investigates application recent deep learning techniques analysis in both classification machine and anomaly detection. use real data collected three different devices: an Arduino, a Raspberry Pi, Siemens PLC. For we compare performance Multi-Layer Perceptron Long...

Abstract The bruise on apples is a common damage mainly caused during the picking and transportation stages, but its detection robustness has not been satisfactory using traditional machine learning method, precision of with short formation time light degree low, it easily affected by variable complex environment, especially bright spots. In this paper, long‐wave near infrared (LW‐NIR 930–2,548 nm) hyperspectral imaging system for acquiring reflectance images bruised were developed in study....

Regulating the motion of nanoscale objects on a solid surface is vital for broad range technologies such as nanotechnology, biotechnology, and mechanotechnology. In spite impressive advances achieved in field, there still lack robust mechanism which can operate under wide situations controllable manner. Here, we report capable controllably driving directed any nanoobjects (e.g., nanoparticles, biomolecules, etc.) both liquid forms. We show via molecular dynamics simulations that nanoobject...

Pine wilt disease (PWD) is known for its high lethality and rapid transmission, earning it the name “cancer of pine tree”. The prompt removal infested trees an effective measure preventing controlling disease. Accurate efficient monitoring technologies are crucial scientific prevention control this plant Currently, numerous remote sensing studies have been conducted on However, there limited research temporal identification PWD-infested forest stands over large areas. To build classification...

Recently, the performance of automatic modulation recognition (AMC) has been dramatically improved with assistance federated learning (FL). However, FL-based AMC still faces issue secure sharing local model parameters, resulting in poor anti-attack capacity. Motivated by this, a Blockchain-federated (BFL) framework is proposed for this letter, where cooperatively trained parameters Blockchain. In addition, parameter validity evaluation method designed therein aggregation process, which...

The increasing number of smart vehicles is leading to an scarcity spectrum resources for the internet (IoV), which has given rise urgent requirement automatic modulation classification (AMC) in cognitive radio (CR) systems. Meanwhile, flexibility unmanned aerial (UAVs), AMC implemented based on UAVs considered effective method achieve reliable communication between intelligent vehicles. However, distributed UAV task implementation, real-time data needs be transmitted and a cloud server. This...

Multi-document extractive summarization relies on the concept of sentence centrality to identify most important sentences in a document. Although some research has introduced graph-based ranking algorithms such as PageRank and HITS into text summarization, we propose new approach under hub-authority framework this paper. Our combines content with cues "cue phrase", "sentence length" "first sentence" explores sub-topics multi-documents by bringing features these algorithms. We provide an...

A rapid and nondestructive method is greatly important for the classification of aflatoxin B1 (AFB1) concentration single maize kernel to satisfy ever-growing needs consumers food safety. novel AFB1 was developed on basis near-infrared (NIR) hyperspectral imaging (1100–2000 nm). Four groups samples with different concentrations (10, 20, 50, 100 ppb) one group control were prepared, which preprocessed Savitzky–Golay (SG) smoothing first derivative (FD) algorithms their raw NIR spectra. key...

Efficient and green transmission of communication sensing (C&S) signals is a vital problem in Internet Things (IoT) networks. In this article, we propose variational autoencoder (VAE)-empowered deep learning (DL) network to fuse reconstruct the integrated C&S signals. Specifically, present convolutional neural input data SAR images into combined representation, which can then be transmitted other nodes space–air–ground–ocean-integrated IoT Instead directly transmitting data, fused feature...