Techniques for integrating different types of multiple features effectively have been actively studied in recent years. Multiset canonical correlation analysis (MCCA), which maximizes the sum of pairwise correlations of inter-view (i.e., between different features), is one of the powerful methods for integrating different types of multiple features, and various MCCA-based methods have been proposed

Response surface methodology (RSM) refers to experimental designs for optimizing or developing processes, initially in manufacturing. In this paper, a new method is presented and an algorithm is implemented that modifies the axial part in a central composite design to achieve a good D-value and efficiency. The new designs are suitable for sequential experimentation. In comparison with known designs

The Road Side Unit (RSU) is an important part of the Internet of Vehicles (IoV), which collects a large number of user’s privacy information and connects vehicles to the Internet. The current RSU is running with static configurations, and the adversary can get enough time to analyze the vulnerability of the RSU and launch attacks, which poses a huge threat to the privacy security of the IoV. Under

Multi-set canonical correlation analysis (MCCA) is a famous multi-modal coherent subspace learning method. However, sample-based between-modal and within-modal covariance matrices of MCCA usually deviate from real covariance matrices due to noise information and limited sample size. The deviation will weaken the performance of MCCA, especially in image recognition. Aiming at this challenging issue

Most human-centred robotic applications require robots to follow a certain pre-defined path. This makes the robot’s autonomous movements acceptable and predictable for humans. Planning a trajectory for the robot thus involves guiding it along this desired path. The classical approach of segmenting a path into multiple waypoints and tracking them only works well in environments which are obstacle-free

Consumers’ environmental protection awareness promotes the quality of green products produced by remanufacturers, which requires higher input cost and more efforts but wins environmental reputation in return. In order to encourage remanufacturers to produce products with less pollution, government enacts environmental policy to subsidy the production of remanufacturing. This paper aims to analyze the

Based on the coupled Ginzburg-Landau equations and Jones matrices of the waveplates considered, a numerical model of an all-normal-dispersion fiber laser mode-locked by nonlinear polarization rotation has been proposed. The operating characteristics of the fiber laser discussed were studied numerically. It has been found that the proposed all-normal-dispersion mode-locked fiber laser (AND-MLFL) could

The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is

Crop disease diagnosis is an essential step in crop disease treatment and is a hot issue in agricultural research. However, in agricultural production, identifying only coarse-grained diseases of crops is insufficient because treatment methods are different in different grades of even the same disease. Inappropriate treatments are not only ineffective in treating diseases but also affect crop yield

Ball screw electro-mechanical actuators are commonly found in high precision motion control applications including aerospace systems as well as automated setups for industries. These actuators perform flight / application critical job and ball screw drives are responsible to provide precise linear motion while carrying thrust loading. A failure in ball screw drive may disturb positioning accuracy of

Doubly fed induction generators (DFIGs) are vulnerable to grid related electrical faults. Standards require DFIGs to be disconnected from the grid unless augmented with a fault ride through (FRT) capability. A fault current limiter (FCL) can enhance the overall stability of wind farms and allow them to maintain grid-code requirements. In this paper, a neuro fuzzy logic controlled parallel resonance

As a powerful tool, near-field acoustical holography (NAH) recognizes the sound source effectively. The traditional equivalent source method (ESM) calculated by the Tikhonov regularization method could be available in the low-frequency band. To improve the resolution quality of traditional ESM in the middle-frequency band and the high-frequency band, we introduced a fast iterative shrinkage/thresholding

One’s personality is widely accepted as an indicator of job performance, job satisfaction and tenure intention. The ability to measure an applicant’s personality in the selection process helps recruiters, hiring managers and the applicant make better hiring decisions. Our work shows that textual content of answers to standard interview questions related to past behaviour and situational judgement can

The increasing growth in the demand for cloud computing services, due to the increasing digital transformation and the high elasticity of the cloud, requires more efforts to improve the electrical energy efficiency of cloud data centers. In this paper, an energy-efficient hybrid (EEH) framework for improving the efficiency of consuming electrical energy in data centers is proposed and evaluated. The

Hospital biomedical engineering teams are responsible for establishing and regulating medical equipment management programs (MEMPs); these programs ensure the safety and reliability of medical devices. Concomitant with rapid technological advancements, medical devices have been developed that are now being integrated with information and communication technology. However, with the convergence of such

The development of computerized healthcare has been powered by diagnostic imaging and machine learning techniques. In particular, recent advances in deep learning have opened a new era in support of multimedia healthcare distribution. For earlier detection of Alzheimer’s disease, the study suggested the Improved Deep Learning Algorithm (IDLA) and statistically significant text information. The specific

Portfolio optimization is a hot research topic, which has attracted many researchers in recent decades. Better portfolio optimization model can help investors earn more stable profits. This paper uses three deep neural networks (DNNs), i.e., deep multilayer perceptron (DMLP), long short memory (LSTM) neural network and convolutional neural network (CNN) to build prediction-based portfolio optimization

We present numerical methods to enable accurate and robust level-set based simulation of anisotropic wet etching and non-planar epitaxy for semiconductor fabrication. These fabrication techniques are characterized by highly crystal orientation-dependent etch/growth rates, which lead to non-convex Hamiltonians in their description by the level-set equation. As a consequence, instable surface propagation

Internet-of-Things (IoT) represents a breakthrough for the current ICT market. In many IoT applications, sensors and actuators are distributed over very wide areas, sometimes not reached by terrestrial networks. In such scenarios, the satellite plays a significant role. In this paper, a Software-Defined Radio (SDR) - based satellite gateway for Internet-of-Remote-Things (IoRT) is proposed. The use

In order to simplify the design procedure of traditional neural network backstepping and improve the robustness and precision of control, an improved scheme is studied for a class of nonlinear systems. To avoid reconstructing virtual control inputs in each recursive step, RBF neural networks are utilized as approximators to estimate the desired feedback control of the whole system only. Meanwhile,

With the rapid growth of application demands and the real-time change of environmental situations, the defects of the UAV task network in adaptability, flexibility, and resilience are becoming more and more prominent. The current network architecture that the junction of points and lines is fixed cannot dynamically provide capacity requirements in real-time due to the failure nodes encountered in the

In the latest technologies for next generation using in Cyber-Physical Systems, 5G and IoT (Internet of Things) based solutions have a significant contribution. For the construction of such applications, component-based development approaches offer to produce systems by using pre-built tested and reliable components with shorter development time. At the architecture level, a software system can be

Traditional neural networks trained using point-based maximum likelihood estimation are deterministic models and have exhibited near-human performance in many image classification tasks. However, their insistence on representing network parameters with point-estimates renders them incapable of capturing all possible combinations of the weights; consequently, resulting in a biased predictor towards

Breathing is a natural and directly controllable human activity. Currently, some works have considered breath as a direct input controlling mechanism. The equipment relied upon in these works is generally complicated, expensive, inconvenient to wear, and sometimes insufficiently controllable. The use of breathing interaction is also limited to a certain scene and is not universal. This paper proposes

In wireless sensor networks, spatially distributed nodes provide location-dependent sensor information. Therefore, knowledge about the 3D position of all nodes is crucial for the numerous applications that require autonomous mobility. Furthermore, to acquire the nodes’ poses and the complete 6D network constellation, the 3D orientation of each node is also required. While many theoretical localization

Automotive Original Equipment Manufacturers (OEMs) require varying levels of functionalities and model details at different phases of the electric vehicles (EV) development process, with a trade-off between accuracy and execution time. This article proposes a scalable modelling approach depending on the multi-objective targets between model functionalities, accuracy and execution time. In this article

Due to the high demands of deep neural network (DNN) based applications on computational capability, it is hard for them to be directly run on mobile devices with limited resources. Computation offloading technology offers a feasible solution by offloading some computation-intensive tasks of neural network layers to edges or remote clouds that are equipped with sufficient resources. However, the offloading

As the system becomes more and more complex, we are usually in the state of indeterminacy. In the real world, the states of uncertainty and randomness are the two most common types of indeterminacy. An uncertain random graph is applied to describe a graph model with uncertainty and randomness simultaneously. This paper mainly focuses on the connectivity of two vertices in an uncertain random graph

This article proposes a novel discrete grey wolf optimization for the packing problem, called the two-dimensional strip packing (2DSP) problem without guillotine constraint. The 2DSP involves cutting pieces from a stock sheet with the objective of minimizing waste. To solve the 2DSP problem by the discrete grey wolf algorithm, many strategies are originally proposed. The searching and attacking operators

Multiple-input multiple-output (MIMO) antennas have been a mainstream technology in fifth generation (5G) communications. However, strong mutual coupling between both adjacent and nonadjacent elements is inevitable, especially among highly integrated devices. In this paper, a slit embedded mushroom electromagnetic bandgap structure (EBG) is primarily proposed to suppress the propagation of surface

With the development of the Internet of Things, FMCW (Frequency Modulated Continuous Wave) radars are widely used in medical treatment, human behavior detection, Internet of Vehicles and UAV (Unmanned Aerial Vehicle) detection. However, the existing systems have some shortcomings, such as high requirements for synchronization signal, lack of flexibility and high design cost. In this paper, to address

The rapid release of 5G wireless communications networks has spurred renewed concerns regarding the interactions of higher radiofrequency (RF) radiation with living species. We examine RF exposure and absorption in ex vivo bovine brain tissue and a brain simulating gel at three frequencies: 1.9 GHz, 4 GHz and 39 GHz that are relevant to current (4G), and upcoming (5G) spectra. We introduce a highly

Radio frequency fingerprinting (RFF) based on RF transients is one of the most effective techniques for improving wireless security. For an efficient RFF development, RF transients need to be accurately detected. However, the detection of the transient starting point remains a main challenge due to the channel noise. In the literature, several methods have been presented to detect the starting point

A new rational bi-quartic spline interpolation scheme is constructed in this study. This rational bi-quartic spline has six free parameters that can be used to refine the final interpolating surface. The degree of smoothness attained is C 1 continuity. Image interpolation is one of the methods in image processing that is used to rescale the images, either downscaling or upscaling. The proposed rational

In this paper, we expand the Hamy mean (HM) operator and weighted Hamy mean (WHM) with fuzzy number intuitionistic fuzzy numbers (FNIFNs) to propose fuzzy number intuitionistic fuzzy Hamy mean (FNIFHM) operator and fuzzy number intuitionistic fuzzy weighted Hamy mean (FNIFWHM) operator. Then the MADM methods are proposed with these operators. In the end, we utilize an applicable example for comprehensive

This paper considers the coherent integration problem for a low-observable maneuvering target, where the velocity and acceleration result in range migration (RM) and Doppler frequency migration (DFM) within the coherent pulse interval. A novel method based on the frequency spectrum segment processing (FSSP) and the segmental Lv’s distribution (SLVD) is proposed to realize the long-time coherent integration

The recent outbreak of the coronavirus disease 2019 (COVID-19) has rapidly become a pandemic, which calls for prompt action in identifying suspected cases at an early stage through risk prediction. To suppress its further spread, we exploit the social relationships between mobile devices in the Social Internet of Things (SIoT) to help control its propagation by allocating the limited protective resources

With the explosive growth of mobile computing, new modes of human-computer interaction (HCI) are emerging and becoming feasible. Compared to vision-based systems that require lighting, radio frequency (RF)-based hand motion detection systems are becoming more popular in HCI applications. In real RF hand motion detection scenarios, the line-of-sight between the transmitter (Tx) and receiver (Rx) is

Person and vehicle re-identification (re-ID) are important challenges for the analysis of the burgeoning collection of urban surveillance videos. To efficiently evaluate such videos, which are populated with both vehicles and pedestrians, it would be preferable to have one unified framework with effective performance across both domains. Unfortunately, due to the contrasting composition of humans and

The presence of stray capacitance in ZnO (Zinc Oxide) surge arresters causes hurdles in arrester operation and non-uniform voltage distribution along the arrester column, especially for High Voltage (HV) and Extra high voltage (EHV) applications. Since the magnitude of stray capacitance is directly proportional to the arrester height; the shortening of surge arresters is a preeminent method to enhance

Electronic commerce or e-commerce includes the service and good exchange through electronic support like the Internet. It plays a crucial role in today’s business and users’ experience. Also, e-commerce platforms produce a vast amount of information. So, Recommender Systems (RSs) are a solution to overcome the information overload problem. They provide personalized recommendations to improve user satisfaction

Multi-task learning (MTL) is a learning paradigm which can improve generalization performance by transferring knowledge among multiple tasks. Traditional collaborative filtering recommendation methods suffer from cold start, sparsity and scalability problems. The latest research has shown that applying side information of knowledge graph can not only solve the problems above, but also improve the accuracy

This paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited, as is demonstrated. This novel hybrid data representation approach allows to simultaneously

Local anesthesia has certain harm to the patient, and the wrong position of the anesthesia point may result in poor anesthesia effect. Based on this, this study built an automatic positioning recognition model based on ultrasound image guidance technology. At the same time, this paper combined the actual requirements of anesthesia to establish a wireless positioning system based on ultrasonic infrared

This paper examines the reduction in the non-renewable power consumption of transport networks including core, metro and access layers when Video-on-Demand (VoD) content is cached in solar-powered fog data centres with Energy Storage Devices (ESDs). The effects of considering optical bypass routing and Mixed Line Rate (MLR) in the core network, the availability of solar renewable energy in the access

In this paper, a novel super-wideband multiple-input multiple-output (SWB-MIMO) antenna system with high isolation has been proposed, each antenna element consisting of a spade-shaped radiation patch, a defected ground structure (DGS) as well as a windmill-shaped decoupling structure. The elliptical slot etched on the radiation patch and the rectangular DGS are jointly utilized to make better the radiation

Digital painting is a process of creating a digital artwork using modern human-computer interaction technologies. One of the core enabling technologies is the real-time tracking of user’s strokes, which is generally supplied by a digital tablet with a stylus. While the digital tablet technology provides highly accurate tracking, the drawing should be done with a rigid stylus on a plastic surface. This

The prosumer market allows prosumers to sell their energy surplus to consumers. The prosumer should offer the amount of energy to sell and its unit price to the contracted consumers while economically operating their system. This paper presents optimal operations and business strategies to maximize the prosumer’s benefit by utilizing an energy storage system and ensuring a contract with residential

Combined with the WRSR and improved CRITIC objective assignment method, this paper measures and grades the institutional innovation levels of high-tech industries in various provinces (cities and districts) in China, compares them horizontally and vertically, and interprets the temporal and spatial difference. Advanced members are located in the eastern coastal area, and the backward members are mainly

This paper presents a novel dual-mode wound rotor synchronous machine (DWRSM) for variable speed applications. The proposed machine combines the advantages of both the conventional wound rotor synchronous machine (CWRSM) and the brushless wound rotor synchronous machine (BWRSM). Unlike the existing BWRSM, through the dual-mode operation of the proposed machine, constant torque is achieved in the constant

To intercept maneuvering target considering impact angle constraint and actuator faults, a novel three-dimensional (3D) guidance law is proposed in this paper. To guarantee the interception, the multi-variable super-twisting-algorithm-like (STA-like) is adopted in the proposed guidance law, so as to drive the line-of-sight (LOS) angle to the desired value and its rate to zero in finite time in both

This paper presents a miniaturized RF MEMS tunable bandpass filter design developed by application of folded ridged quarter-mode substrate integrated waveguide cavity. Using packaged RF MEMS SP4T chips, a switchable reactive loading is applied to the folded ridged quarter-mode substrate integrated waveguide cavity, tuning the resonance frequency. Overall miniaturizations of 70.3% and 78.8% are achieved

Presently, A wide range of unlabeled and minimal style data significantly decreases the current motion sequence’s reuse ability. An important method of data reuse has a successful classification and fragment separation, which has been discussed in this research. This paper focuses on these particular problems and the tremendous progress of deep learning in design and symbolic fields. A Limited Boltzmann

This paper proposes an improved AdaBoost classifier for sonar images with low resolution ratio and noise. First, Histogram of oriented gradient (HOG) is used to perform feature extraction, and a weak classifier is obtained by Support vector machine (SVM) at the same time. Then, multiple SVM models are constructed for target classification based on the AdaBoost cascade classification framework. A new

The number of academic papers being published is increasing rapidly, and recommending sufficient citations to assist researchers in writing papers is a non-trivial task. Conventional recommendation approaches may not be optimal, as the recommended papers may already be known to the users or may be solely relevant to the surrounding context but not to other concepts discussed in the manuscript. In this

Until now, every evolution of communication standard was driven by the need for providing high-speed connectivity to the end-user. However, 5G marks a radical shift from this focus as 5G and beyond networks are being designed to be future-proof by catering to diverse requirements of several use cases. These requirements include Ultra-Reliable Low Latency Communications, Massive Machine-Type Communications

The performances of heuristic algorithms are highly dependent on the parameters used, and usually difficult to determine subjectively. Thus, how to balance the relations between the qualities of the solutions and the values of the parameters has been a hot and lasting topic in the field of optimization research. This article presented a statistical method to estimate the efficient parameter values

Lightning disturbance may be misjudged as dc fault by the primary protection in the flexible high voltage dc (HVDC) grid. To solve this problem, an auxiliary fault identification strategy based on convolutional neural network with branch structures (BR-CNN) is proposed in this paper. In the proposed scheme, the voltage and current characteristic matrix is constructed as the input matrix of BR-CNN model

A robust disturbance-rejection problem for an uncertain singular system is considered in this paper. An equivalent-input-disturbance (EID) method is applied to improve disturbance-rejection performance. At first, the disturbance estimation is obtained by the EID method; Then, the disturbance estimation is compensation to the control input channel to offset the adverse effect of external disturbance

This paper proposes two novel methods to classify semantic vigilance levels by utilizing EEG directed connectivity patterns with their corresponding graphical network measures. We estimate the directed connectivity using relative wavelet transform entropy (RWTE) and partial directed coherence (PDC) and the graphical network measures by graph theory analysis (GTA) at four frequency bands. The RWTE and