Massive multimedia services have been considered as one the most prominent characteristics for smart cities. In this paper, we propose an energy-efficient content delivery system via device-to-device communications, which realizes large-scale among mobile devices with constrained energy, unpredictable demand, limited storage, random mobility, and opportunistic transmission. The highlights of paper lie in two parts. On theoretical end, through exploring relationship coding, transmission, a...

Security and availability are two crucial issues in device-to-device (D2D) communication, with its fast development fourth-generation (4G) Long-Term Evolution Advanced (LTE-Advanced) networks. In this paper, we propose a secure data sharing protocol, which merges the advantages of public key cryptography symmetric encryption, to achieve security D2D communication. Specifically, public-key-based digital signature, combined mutual authentication mechanism cellular network, guarantees entity...

Data service has been considered as one the most prominent characteristics for Industrial Internet of Things (IIoT). This paper studies how to design an optimal computing manner a general IIoT system. On theory end, we analyze relationship between data processing and energy consumption through investigating content correlation captured data. Importantly, derive exact expression performance by combining computation with intelligence. application efficient way obtain threshold approximating...

This study aims to develop an effective and reliable method for estimating rice quality indices yield, addressing the growing need rapid, non-destructive, accurate predictions in modern agriculture. Field experiments were conducted 2018 at Suiling Water Conservancy Comprehensive Experimental Station (47°27′ N, 127°06′ E), using Longqingdao 3 as test variety. Measurements included leaf area index (LAI), chlorophyll content (SPAD), nitrogen (LNC), spectral reflectance during tillering,...

It is well known that cross-modal services, including audio, video, and haptic signals, will inevitably become the mainstream of multimedia applications. However, because there are significant differences among these three kinds signals in terms transmission delay, jitter, reliability, how to effectively transmit process them an extremely challenging problem. Unlike traditional tactile Internet which mainly focuses on haptic, this work proposes a collaborative communications mechanism by...

Cross-modal applications that elaborately integrate audio, video, and haptic streams will become the mainstream of eHealth systems. However, existing stream schedulers usually fail to simultaneously meet cross-modal transmission requests in terms low latency, high reliability, throughput, complexity. To circumvent this dilemma, article proposes a general scheduling scheme by fully taking advantage characteristics different modal their underlying temporal, spatial, semantic relevance....

UAV-based object detection aims at locating and recognizing targets in aerial images, which is widely applied to traffic surveillance, disaster rescue anomaly monitoring. However, due expensive sensors complicated architectures, it unrealistic deploy precise but heavy multi-modal detectors into UAV nodes. To get over the dilemma, inspired by model compression cross-modal signal processing techniques, this paper proposes a knowledge distillation (CKD) enabled paradigm, achieves comparable...

Mass services and applications have been reviewed as prominent characteristics of the smart city. However, a traditional mobile communication network cannot provide considerable environment in this complicated network. Moreover, requirement for different types is quite discrepant, QoE or users' satisfaction be calculated by unified standard. Meanwhile, cache computing resources treated with great importance researchers industrial community complex In article, we first deal issue propose...

To explore the development and validation of automated machine learning (AutoML) models for 18F-FDG PET imaging-based radiomics signatures to predict treatment response in elderly patients with diffuse large B-cell lymphoma (DLBCL). A retrospective analysis was conducted on 175 (≥ 60 years) DLBCL diagnosed between March 2015 2023 at two medical centers, a total 1010 lesions. The baseline features training cohort were processed using AutoML model AutoGluon generate score (radscore) lesion...

With the development of human–machine interactions, users are increasingly evolving toward an immersion experience with multidimensional stimuli. Facing this trend, cross-modal collaborative communication is considered effective technology in Industrial Internet Things (IIoT). In article, we focus on open issues about resource reuse, pair interactivity, and user assurance to improve Quality Service (QoS) users' satisfaction. Therefore, propose a novel architecture modal-aware allocation...

Abstract Identification of damage and selection a restoration strategy in concrete structures is contingent upon automatic inspection for crack detection assessment. Most research on deep learning models autonomous has focused solely measuring dimensions, omitting the generalization power model. This utilizes novel step transfer (STL) added extreme machine (ELM) approach to develop an assessment surface cracks structures. STL helpful mining generalized abstract features from different sets...

Cracks are a common form of damage in infrastructure, posing significant risks to both personal safety and property. Along with the development deep learning, visual-based crack automatic detection has been widely studied. However, this task is still challenging due complex topology, noisy backgrounds, unbalanced categories, etc. To address these challenges, research proposes novel hybrid network, named CrackNet, which leverages strengths CNN transformer. On encoder side, CNNs employed...

With the development of mobile communication human activity recognition (HAR) with smartphones has attracted a lot attentions in recent years. On other hand, appearance deep learning technologies makes it possible to extract features automatically instead hand-crafted extracting traditional machine methods. Among model, CNN-based HAR methods dominate studies compared RNN-based In this paper, we propose multi-layer parallel LSTM network recognize activities. The experimental results on public...

In the last few years, smart parking has been focused due to development of indoor position technology. There are several systems for garage. But there two major problems in these systems. The first one is detection space occupation, and second navigation. To solve problems, we propose a system combining WiFi wireless sensor network. this system, geomagnetic sensors used detect occupation spaces, A prototype developed.

Physical layer security (PLS) is emerging as an attractive paradigm to complement or even replace complex cryptography. Although information-theoretical transmission optimization and physical-layer key generation have been thoroughly researched, there still exist many critical issues be tackled before PLS extensively applied. In this article, we investigate the prospect for exploiting artificial intelligent (AI) edge computing (EC) facilitate practical application of PLS. First, two...

Objectives This study aims to develop 7×7 machine-learning cross-combinatorial methods for selecting and classifying radiomic features used construct Radiomics Score (RadScore) of predicting the mid-term efficacy prognosis in high-risk patients with diffuse large B-cell lymphoma (DLBCL). Methods Retrospectively, we recruited 177 DLBCL from two medical centers between October 2012 September 2022 randomly divided them into a training cohort (n=123) validation (n=54). We finally extracted 110...

Real-time hand tracking is fundamental to human gesture recognition. However, due the huge computation, previous studies are either off-line or limited given poses. In order satisfy requirement of real-time tracking, in this paper we propose a real time method using Kinect. Firstly extract region from depth image output Then achieve parameters. During procedure extraction, cascade structure with recursive connected component algorithm improve efficiency and reserve connection relationships...

With multimedia dominating the digital contents, device-to-device communication has been proposed as a promising data offloading solution in big area. As quality of experience (QoE) is major determining factor success new applications, we propose QoE-driven cooperative content dissemination (QeCS) scheme this paper. In particular, all users predict QoE potential connections characterized by mean opinion score (MOS), and send results to provider (CP). Then, CP formulates weighted directed...

The IEEE 802.15.4 standard provides appealing features to simultaneously support real-time and non realtime traffic, but it is only capable of supporting communications from at most seven devices. Additionally, cannot guarantee delay bounds lower than the superframe duration. Motivated by this problem, in paper we propose an Explicit Guaranteed time slot Sharing Allocation scheme (EGSA) for beacon-enabled networks. This providing tighter splitting Contention Free access Period (CFP) into...

K-nearest neighbor (KNN) is a popular classification algorithm with good scalability, which has been widely used in many fields. When dealing imbalanced data, minority examples are given the same weight as majority existing KNN algorithm. In this paper, we pay more attention to class than class, and increase of according local characteristic distribution. addition, compare proposed Weighted Distance (WDKNN). Experimental results show that our performs better WDKNN data sets.