With the progress of medical science and technology and the healthy changes in eating habits, the proportion of aged population is gradually increasing. Smart-home elderly care has thus attracted a lot of research attention in the recent past, and remains an active issue. Internet of Things (IoT) has been recognized as a key enabler for smart-home elderly care realization. In the literature, a large

Predicting the stock market is a widely studied field, either due to the curiosity in finding an explanation for the behavior of financial assets or for financial purposes. Among these studies the best techniques use neural networks as a prediction technique. More specifically, the best networks for this purpose are called recurrent neural networks (RNN) and provide an extra option when dealing with

Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications

Advanced metering infrastructure (AMI) is the core component of the smart grid. As the wireless connection between smart meters in AMI is featured with high packet loss and low transmission rate, AMI is considered as a representative of the low power and lossy networks (LLNs). In such communication environment, the routing protocol in AMI network is essential to ensure the reliability and real-time

In the field of system health management, the quality of rolling equipment is very important. Therefore, the fault diagnosis of rolling bearings has become a hot research topic. In this paper, the traditional fault feature extraction method is used to optimize the non-linear and non-stationary characteristics of the bearing vibration signal. Furthermore, in order to improve the performance of the fault

This paper utilizes an IoT platform called IoTtalk to shape “intelligence” into a house to make it a smart home. The developed project is called HomeTalk that serves as a platform to accommodate various smart applications in a house. We describe the following HomeTalk applications. The PlantTalk application takes care of house plants. The FishTalk application provides fish comfortable life in the fish

The text mining process typically involves the application of natural language processing (NLP) techniques, in order to obtain important information and extract insights from texts. This is achieved by detecting patterns, which are not explicitly a priori in this unstructured or semi-structured dataset. One of the most significant NLP tasks is Named Entity Recognition (NER). The NER process seeks to

In IoT environments, geo-tagged data have rapidly been emerging as smart things, e.g., mobile devices or connected cars, are generally equipped with the global positioning system (GPS) module. A large volume of geo-tagged data can be fundamental to providing applications of location-based services (LBSs). One of the important LBS applications is to provide continuous spatial keyword queries. A continuous

Internet of Things (IoT) is a kind of information carrier, which enables for all ordinary objects that can perform independent functions to realize interconnection. The standardization process of wireless local area networks (WLANs) which is an important network system of IoT is gradually advancing. IEEE 802.11ax will replace IEEE 802.11a/b/g/n/ac as the latest WLANs standard. The uplink transmission

High systolic blood pressure causes many problems, including stroke, brain attack, and others. Therefore, examining blood pressure and discovering issues related to it at the right time can help prevent the occurrence of health problems. Nowadays, health-based data brings a new dimension to healthcare by exploiting the real-time patients’ data to early detect systolic blood pressure (SBP). Furthermore

With rapid development of voice control technology, making speech recognition more precisely in various IoT domains have been an intractable problem to be solved. Since there are various conversation scenes, understanding the context of a dialog scene is a key issue of voice control systems. However, the reality is available training data for dialog system are always insufficient. In this paper, we

Data provenance focuses on the source of the data and on the identification of data sources and their transformations undergone over time. This paper proposes a generic method for collecting provenance data, and is a follow-up of a study carried out by the same authors in a Brazilian hemotherapy center. This method is based on the W3C’s Provenance Data Model (PROV-DM), and proposes a way to capture

Internet of Things (IoT) is the interconnection of thousands of heterogeneous addressable smart objects (i.e., devices embedded with sensors and actuators) with Internet connectivity. Internet of Mobile Things (IoMT) is characterized by considering the mobility of smart objects. For managing smart objects, it is necessary to provide a middleware. Mobile Hub (M-Hub) is an IoT middleware that collects

Alternaria leaf blotch, and rust are two common types of apple leaf diseases that severely affect apple yield. A timely and effective detection of apple leaf diseases is crucial for ensuring the healthy development of the apple industry. In general, these diseases are inspected by experienced experts one by one. This is a time-consuming task with unstable precision. Therefore, in this paper, we proposed

The original version of this article unfortunately contained a mistake in the AuthorGroup section.

The purpose of this article is to present an analysis of the privacy principles of personal data prescribed in the General Data Protection Regulation and the treatment of data in Blockchain technology in its primary version, guided by the phases of the Data LifeCycle. The Data Life Cycle presents the stages in which the data act in a given process and are related to each other, forming a chain of dependence

The terminological composition of information management (IM) and knowledge management (KM) is described in order to evidence how much do these areas overlap within the library and information sciences (LIS) space. A term co-occurrence analysis is conducted as from documents extracted from Web of Science, covering the period 1980–2015. To examine the terminological (di) similarity two approaches are

Road transportation is the backbone of modern economies despite costing annually millions of human deaths and injuries and trillions of dollars. Twitter is a powerful information source for transportation but major challenges in big data management and Twitter analytics need addressing. We propose Iktishaf, developed over Apache Spark, a big data tool for traffic-related event detection from Twitter

The traditional design of voice collector has poor anti attack ability, which makes the encryption effect of voice transmission poor. Therefore, taking the mobile network voice collector as the research object, 3des-ecc algorithm is applied to the information transmission encryption of the mobile network voice collector.An improved speech signal collector is designed, which combines 3DES and ECC algorithm

High-dense deployment scenario is supposed to be the killer scenario of the future wireless networks. The next generation high efficiency wireless local area networks (WLANs) standard - IEEE 802.11ax, which will be released in the year 2019, directly faces to the high-dense deployment scenario. IEEE 802.11ax is one milestone of WLAN standardization. Thus, a series of media access control technologies

For fog computing network, how to effectively and quickly offload the task to fog nodes is a big challenge. In this paper, a task offloading scheme based on improved contract net protocol and beetle antennae search algorithm in fog computing networks is proposed. Firstly, the system mode of task offloading in fog computing network is described. Then, a contract net protocol is presented to obtain the

In the era of big data, the large-scale information network applications need to process and analyze increasingly complex graph structure relationships. However, traditional methods of representing network structures are difficult to reflect potential relationships between massive nodes. Graph Neural Network (GNN) based node representation learning is an emerging learning paradigm that embeds network

In wireless sensor and IoT networks dedicated to smart-cities, a leader node performs critical tasks such as generating encryption/decryption keys. In this paper, the leader is the node situated at the extreme left of the network. It is the node which starts the algorithm of searching the boundary nodes. These nodes will be used to monitor any sensitive, dangerous or inaccessible site. For this type

Due to the continuous evolving of mobile communication technologies, deploying small cells (SCs), also known as SC base stations (SBSs), is regarded as one of the feasible alternatives to provide better indoor signal quality to meet the ever-increasing demand for mobile broadband data in indoor environments. However, the co-tier uplink interference, i.e., interference between SBSs, increases when SBSs

One of the most widely used medical modality by healthcare industry is ultrasound imaging, which is often corrupted by multiplicative noise (known as speckle). The reduction of such kind of noise from ultrasound images is highly desirable for providing the proper diagnosis of a disease in real-time. The classical bilateral filter (CBF) is well known as most effective edge preserving and denoising filter

Over the years, fog computing has emerged as a paradigm to complement the cloud computing in handling the delay sensitive IoT applications in a better manner. Using fog resources, better performance such as in-time service delivery, reduced network load, optimal energy usage etc. can be achieved. With such performance gain, users availing the IoT services are more satisfied. A well-known metric Quality

As today’s Internet of Things (IoT) applications are becoming more complicated and intelligent, IoT devices alone can no longer well support the ever-increasing demand for powerful computation and high energy efficiency. Mobile Edge Computing (MEC) and 5G technology emerge as promising solutions, which enable IoT tasks to be offloaded to edge servers for effective processing. Though desirable, there

The era of intelligence has arrived. Intelligent multimodal information is essential for underwater engineering. Sound is an indispensable medium in underwater multi-modal information technology. Orthogonal frequency division multiplexing underwater acoustic communication technology can achieve high bit rate communication. However, the time-varying Doppler of the underwater acoustic channel will cause

Physical machines in modern datacenters are routinely upgraded due to their maintenance requirements, which involve migrating all the virtual machines they currently host to alternative physical machines. For this kind of datacenter upgrades, it is critical to minimize the time it takes to upgrade all the physical machines in the datacenter, so as to reduce disruptions to cloud services. To minimize

In cooperative communication, relay reduces the stored energy for its own transmission due to the energy consumption for forwarding the information from source node. In this paper, simultaneous wireless information and power transfer (SWIPT) for OFDM-based cooperative communication is proposed to save the relay’s energy by harvesting the radio frequency (RF) energy from source node. Subcarrier allocation

Cloud containers represent a new, light-weight alternative to virtual machines in cloud computing. A user job may be described by a container graph that specifies the resource profile of each container and container dependence relations. This work is the first in the cloud computing literature that designs efficient market mechanisms for container based cloud jobs. Our design targets simultaneously

Mobile Crowd Sensing (MCS) is an emerging paradigm, it engages ordinary mobile device users to effectively contribute sensed data using mobile applications. The unique characteristics of MCS bring a lot of new challenges. First, contributing valuable data quality utilizes users’ mobile resources, and private information; making it essential to adequately reward the participants however the Service

Deep learning is widely used in classification tasks to achieve advanced performance. However, in the face of well-designed image classifications, such as the Fast Gradient Sign Method (FGSM), there are glaring errors. This paper proposes a new technique to eliminate interference using generative adversarial networks (GAN), called multi-branch perturbed generative adversarial networks(MBP-GAN). MBP-GAN

The intrusion detection system (IDS) is a crucial part in the network administration system to detect some types of cyber attack. IDS is categorized as a classifying machine thus it is likely to engage with the machine learning schemes. Many studies have demonstrated how to apply machine learning schemes to IDS even though they cannot provide optimum results. To tackle this issue, deep learning schemes

Vehicular ad hoc network (VANET) is expected one of promising network forms for intelligent transportation system which supports road safety applications, in-vehicle entertainment and arriving automatic driving. Establishing and maintaining stable connections in VANETs are challenging on account of the high mobility of vehicles, dynamic vehicle topology, and time-varying vehicle density. Clustering

Feature subspace learning is a crucial issue in pattern analysis. However, it remains challenging when partial samples are unlabeled, which will cause weak discrimination. In this paper, we present a novel semi-supervised learning model that is capable of utilizing labeled and unlabeled training data simultaneously to learn discriminative feature subspace while preserving their locality. To achieve

The Global Positioning System (GPS) is not only widely used in navigation, measurement and other services, but also an indispensable key equipment for the military. With the increasing complexity of the communication environment and the increasing number of interference factors, the recognition of GPS interference signal types is a prerequisite for the development of efficient anti-interference means

How to estimate channel parameters more effectively, intelligently and accurately is the key problem to realize the requirements of intelligent and adaptive short-wave communication system. Based on the detailed analysis of chirp signal and fractional Fourier transform, an intelligent channel parameter estimation system is constructed. By building and training the regression model of multilayer fully

Combining conformable differential definition and Adomian decomposition method (ADM) algorithm, the dynamics of a new 4-D fractional-order chaotic system was studied through numerical simulation in this paper. The dissipation of the system and the stability of the equilibrium points were analyzed. The evolution of the coexistence attractors with different parameters and orders were analyzed through

White blood cells (Leukocytes) are considered to be an essential part of the human body’s immune system. The count of WBCs is considered to be a parameter for the indication of disease. Over time several methods have been proposed to classify these WBCs into their subtypes namely Neutrophils, Eosinophils, Basophils, Lymphocytes, and Monocytes which helps in the estimation of the body’s WBC count. These

For the frequency spectrum leakage and fence effect generated in Fast Fourier Transform (FFT) during asynchronous sampling and integral period truncation affect the precision of harmonic detection, a new algorithm for harmonic analysis based on four-spectrum-line interpolation FFT with second-order self-convolution window with five-term Maximum-Sidelobe-Decay (MSD) was proposed and the polynomial fitting

The combination of edge and cloud computing is going to make the Internet of Things (IoT) rapid, light, and more reliable. IoT and cloud-edge computing are distinct disciples that have evolved separately over time. However, they are increasingly becoming interdependent, and are what the future holds. A crucial aspect is how to design a compound of cloud and edge computing architectures, and implement

It is conducive to the application of sEMG signals in helping disabled people through combining wearable devices with deep learning. Therefore, design of sEMG gesture recognition system using deep learning based on wearable device is proposed in this paper. The system is mainly consisted of wearable sEMG acquisition device and sEMG gesture recognition method based on deep learning. In the wearable

With the rapid development of wireless devices in recent years, the hardware tolerance of wireless devices has gradually become narrowed. Traditional radio frequency fingerprint(RF fingerprint) recognition methods are usually used based on single signal features, which will fail to characterize the subtle differences of wireless devices. Therefore, aiming at the shortcomings of traditional radio frequency

As one of the key technologies of 5G, Cloud Radio Access Networks (C-RAN) with cloud BBUs (Base Band Units) pool architecture and distributed RRHs (Remote Radio Heads) can provide the ubiquitous services. When failure occurs at RRH, it can’t be alleviated in time and will lead to a significant drop in network performance. Therefore, the cell outage compensation (COC) problem for RRH in 5G C-RAN is

School bullying is a common social problem, and school violence is considered to be the most harmful form of school bullying. Fortunately, with the development of movement sensors and pattern recognition techniques, it is possible to detect school violence with artificial intelligence. This paper proposes a school violence detecting method based on improved Relief-F and Dempster-Shafe (D-S) algorithms

A new meminductor based hyperchaotic oscillator and its mathematical model were presented. Meanwhile, some basic dynamic properties such as equilibrium point and stability were analyzed. Through Lyapunov exponents and bifurcation diagram and other commonly used dynamic analysis methods, the system’s dynamic characteristics were analyzed, and observed several special dynamic phenomena, such as coexisting

The mechanism of Coordinated Multi-Point (CoMP) can improve the spectral efficiency of the 4G and 5G cellular network, and also can reduce transmitting power of base stations (BSs). However, CoMP requires a large amount of energy due to extra signal processing and backhaul traffic. In this paper, an energy-efficient algorithm based on optimal dynamic clustering mechanism (ODCEM) for CoMP networks is

As an important material and technical support of the data link system, the communication network system not only plays an “adhesive” role in integrating the combat forces, optimizing the operational composition and realizing the complementary advantages of the system, but also greatly expands the system functions of the data link due to the accelerated expansion of the communication technology functions

The original version of this article unfortunately contained a mistake in the Affiliation section.

In wireless Internet of Things (IoT) systems, the multi-input multi-output (MIMO) and cognitive radio (CR) techniques are usually involved into the mobile edge computing (MEC) structure to improve the spectrum efficiency and transmission reliability. However, such a CR based MIMO IoT system will suffer from a variety of smart attacks from wireless environments, even the MEC servers in IoT systems are

The Filter Bank Multicarrier (FBMC), one of the multi-carrier modulation technique are subjected to extreme intensities of Peak to Average Power Ratio (PAPR). Moreover, the FBMC is a firm user, like the waveform-centred framework in the unconventional wireless communication frameworks, such as the 5G telecommunication system. This system framework acts as an alternative to the Orthogonal Frequencies

In this paper, we study the distributed DOS problem in wireless multiple relays networks. By formulating cooperative scheduling as an extended multi-stage stopping problem, an optimal strategy is proposed achieving the maximal average network throughput for distributed channel access. The strategy is in a tri-level threshold structure, and the optimality is rigorously proved. Close-form expression

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such as real-time collision warning in vehicular

In extreme learning machine (ELM), a large number of hidden nodes are required due to the randomly generated hidden layer. To improve network compactness, the ELM with smoothed ℓ0 regularizer (ELM-SL0 for short) is studied in this paper. Firstly, the ℓ0 regularization penalty term is introduced into the conventional error function, such that the unimportant output weights are gradually forced to zeros

3D point cloud is one of the most common and basic 3D object representation model that is widely used in virtual/augmented reality applications, e.g., immersive communication. Compression of 3D point cloud is a big challenge because of its huge data volume and irregular data structure. In this paper, we propose a sampling-based compression algorithm for 3D point clouds. First, a 3D point cloud was

Resources allocation (RA) is a challenging task in many fields and applications including communications and computer networks. The conventional solutions of such problems usually come with a time and memory cost, especially for massive networks such as Internet-of-Things (IoT) networks. In this paper, two RA deep network models are proposed for enabling a clustered underlay IoT deployment, where a

The authors have retracted this article [1] as it overlaps significantly with a previously published article by Aboul-Dahab et al. [2]. All authors agree with this retraction.

In recent years, with the rapid development of Internet of Things (IoTs) and artificial intelligence, vehicular networks have transformed from simple interactive systems to smart integrated networks. The accompanying intelligent connected vehicles (ICVs) can communicate with each other and connect to the urban traffic information network, to support intelligent applications, i.e., autonomous driving

Wireless Powered Communication (WPC) provides an effective solution to the contradiction between information transmission and energy consumption for Internet of Things (IoT) terminals. In this paper, a clustered-Non-Orthogonal Multiple Access (C-NOMA) based WPC model is proposed. Base Station (BS) transfers Radio Frequency (RF) energy to all terminals in the downlink, while terminals transmit information