Abstract The surface modification is a pivotal step in the field of the biomedical implant in order to improve its biomedical characteristics. A number of methods can be adopted to improve surface characteristics like coating, evaporation, sputtering, and ion implantation. The surface of any material can also be improved by machining. In the present work, an electric discharge drilling (EDD) was used

Abstract Vacuum counter-pressure casting (VCPC) process is an effective forming process of producing components with complex thin-walled characteristics. In this study, a surrogate-based optimization method with five process parameters is used to reduce the shrinkage porosity defect during the VCPC process of a complicated thin-walled aluminum alloy casing. The prediction of the shrinkage porosity

Abstract Fibre metal laminates (FMLs) are multilayered metal composite materials currently used in aeronautical structures, especially where fatigue and impact resistance are required. FMLs are produced in large panels and often require assembly using the drilling process for riveting purposes. Hole making is a critical machining process in the joining and assembly of aeronautical components, which

Abstract This report presents some new methodological opportunities that biophysics can offer for solving the fundamental problem of planetary ecology—deciphering the mechanism that maintains the equilibrium state of the biosphere. The Institute of Biophysics, Siberian Branch, Russian Academy of Sciences, where the author of this report works, is developing two complementary directions in ecological

Ferroelastic ABO4 type RETaO4 and RENbO4 ceramics (where RE stands for rare earth) are being investigated as promising thermal barrier coatings (TBCs), and the mechanical properties of RETaO4 have been found to be better than those of RENbO4. In this work, B-site substitution of tantalum (Ta) is used to optimize the thermal and mechanical properties of EuNbO4 fabricated through a solid-state reaction

This study was conducted to understand the relationship between various critical temperatures and the stability of the secondary phases inside the heat-affected-zone (HAZ) of welded Grade 91 (Gr.91) steel parts. Type IV cracking has been observed in the HAZ, and it is widely accepted that the stabilities of the secondary phases in Gr.91 steel are critical to the creep resistance, which is related to

With the increasing demand of power sources, it is of great significance to evaluate different power generation systems and optimize the energy structure. The emergy is proved to be a comprehensive and powerful way to evaluate the sustainability of a system. In this paper, emergy is used to compare ten power generation systems by two calculation methods of emergy indices. The emergy data of integrated

Compressed air energy storage (CAES) systems are promising for the application of a standalone hybrid system. This study adopts a scenario-based bi-level programming method to design a standalone hybrid system that mainly contains wind turbines, diesel generators (DGs), and a CAES system. The demand response is considered as a deferrable load. The uncertainties on the wind power outputs and load demand

Abstract In robotic polishing applications, the rotating polisher will generate strong vibration disturbance, which makes it more difficult to detect and control the contact force. This paper proposes a novel and practical method to detect and control the contact force using the built-in sensors (motor encoders and joint torque sensors) for actual robotic polishing in harsh conditions of strong vibration

Abstract The longitudinal-torsional mode horn has gained popularity recently for ultrasonic welding (USW) because it is more efficient than a conventional longitudinal horn. Addition of slanting grooves to the front mass to achieve torsionality is not a novel approach, and few works have already addressed this issue, but comparative studies about the effect of different groove parameters such as length

Abstract Blisk of aerospace engine is one of the sophisticated key parts in the aviation, which is difficult to machine considering its structural and material properties. The present paper develops a five-axis CNC milling machine for fabricating blisk with high-efficiency and high-quality as well as ensuring this milling machine with high precision and precision retention. Therefore, a precision analysis

Abstract In abrasive waterjet (AWJ) process, abrasive properties are of critical factors that influence machining performances. Abrasive process parameters including abrasive material, size and flow rate, exert a significant impact on cutting ability and quality of AWJ. In this paper, monolithic abrasive material (garnet, alumina and silicon carbide) and corresponding mixing abrasive materials are

Vibration analysis has been widely used for condition monitoring and fault diagnosis of rolling element bearings. The next step is to determine defect size from the measured vibrations which can be used in the decision making about the bearing replacement. This paper presents an experimental investigation of the defect size estimation from the vibration signals of two types of naturally generated defects

This paper proposes a new position tracking algorithm by integrating extended Kalman filter (EKF) and direction-of-arrival (DOA)-based geolocation into one factor graph (FG) framework. A distributed sensor network is assumed for detecting an anonymous target, where the process and observation equations in the state space model (SSM) are unknown. Importantly, the predicted state information can be utilized

The k-nearest neighbor (kNN) algorithm is a classic supervised machine learning algorithm. It is widely used in cyber-physical-social systems (CPSS) to analyze and mine data. However, in practical CPSS applications, the standard linear kNN algorithm struggles to efficiently process massive data sets. This paper proposes a distributed storage and computation k-nearest neighbor (D-kNN) algorithm. The

The problem of classifying imbalanced data is one of the active research directions in machine learning and bioinformatics. The imbalance of data will greatly degrade the accuracy of classifiers. Good oversampling methods can improve the diversity and validity of new samples, which cannot only solve the imbalance problem of sample data, but also greatly improve the classification accuracy. In this

Medical images are playing an important role in the medical domain. A mature medical visual question answering system can aid diagnosis, but there is no satisfactory method to solve this comprehensive problem so far. Considering that there are many different types of questions, we propose a model called CGMVQA, including classification and answer generation capabilities to turn this complex problem

In this paper, a wide-band distributed model that can approximate the behaviour of square and octagonal inductors, both with and without tapering, is presented. This paper also presents a novel way of accurately modelling the lateral coupling in the substrate. The presented model can be applied to any foundry process, and its validity has been demonstrated using a novel technology, the D01GH GaN process

Various kinds of auxiliary data in web services have been proved to be valuable to handler data sparsity and cold-start problems of recommendation. However, it is challenging to develop effective approaches to model and utilize these various and complex information. Due to the flexibility in modelling data heterogeneity, heterogeneous information network (HIN) has been adopted to model auxiliary data

A large body of work has offered compelling evidence of the influence of social context on individual decision-making, but the reasons why individuals tend to cooperate with others remain elusive. The prisoner’s dilemma constitutes a powerful, yet elementary, social game to study the drivers underlying cooperation. Here, we empirically examined a prisoner’s dilemma game where small groups of participants

Recently, it has gained lots of interests to jointly learn the embeddings of knowledge graph (KG) and text information. However, previous work fails to incorporate the complex structural signals (from structure representation) and semantic signals (from text representation). This paper proposes a novel text-enhanced knowledge graph representation model, which can utilize textual information to enhance

During the construction of indoor environmental semantic maps by robot Vision SLAM (VSLAM), there exist some problems such as low label classification accuracy and low precision under the situation of sparse feature points. In this case, this paper proposes an indoor three-dimensional semantic VSLAM algorithm based on Mask Regional Convolutional Neural Network (RCNN). Firstly, an Oriented FAST and

The ultra-dense network (UDN) based on mobile edge computing (MEC) is an important technology, which can achieve the low-latency of 5G communications and enhance the quality of user experience. However, how to improve the task offloading efficiency is a hot topic of UDN under the constraint on the limited wireless resources. In this article, we propose a heuristic task offloading algorithm HTOA to

In this paper, we demonstrate a perceptual-based 3D skeleton motion data refinement method based on a bidirectional recurrent autoencoder, called BRA-P. Three main technical contributions are made by the proposed network. First, the proposed BRA-P can address noisy data with different noise types and amplitudes using one network, and this attribute makes the approach more suitable for raw motion data

Compressed signal processing (CSP) is a branch of compressive sensing (CS), which gives a direction to solve a class of signal processing problems directly from the compressive measurements of a signal. CSP utilizes the information preserved in the compressive measurements of a signal to solve certain inference problems like: classification, detection, and estimation, without reconstructing the original

With the widespread adoption of the internet of things (IoT) technologies towards building a smart city, connected devices often offload computation tasks to nearby edge locations (base stations) to reduce overall computation and network delay. However, serving an ever-increasing number of end devices at these traditional edge locations is becoming impossible, subsequently making them fail to deliver

Communication networks for healthcare environments support various application types and should be capable of providing them with the required Quality of Service (QoS) in terms of reliable data delivery, considerable data rate and low latency. The introduction of Tactile Internet (TI) healthcare applications is expected to upgrade the level of provided services to patients. The requirements of these

Partial multi-label learning (PML), which tackles the problem where each training instance is associated with multiple candidate labels which only a subset are valid. In this paper, we propose a simple but effective batch-wise PML model, PML-SE, which tackles PML problem with a self-ensemble approach (SE), namely the ensembles of model and predictions. Specially, PML-SE introduces a teacher model to

An electrically tunable metasurface is designed for radar cross-section (RCS) reduction application in this paper. It consists of $24\times 24$ cells individually loaded with variable capacitors so that their phase profiles can be independently controlled by the bias voltage. Therefore, based on the diffusive scattering principle and reflect-array theory, we arrange the adaptive phase differences between

General Systems Theory (GST), as it was introduced by Karl Ludwig von Bertalannfy, had a significant, yet mostly unacknowledged influence on systems theory. The purpose of the current review is to highlight and assess the application of the aforementioned theory in the healthcare field and suggest a new approach to the public hearing healthcare sector. A systematic literature review has been conducted

Daily inspection of ground crack over mine goaf is a necessary task for environmental protection and mining safety. However, the traditional manual inspection method is time-consuming, misjudgement-prone and with potential dangers because the goaf normally locates in remote regions and inevitably induces complicated and gullies-cross landform. Therefore, Unmanned Aerial Vehicle(UAV) is adopted to capture

Low-rank (LR) and total variation (TV) are two most frequent priors that occur in image processing problems, and they have sparked a tremendous amount of researches, particularly for moving from scalar to vector, matrix or even high-order based functions. However, discretization schemes used for TV regularization often ignore the difference of the intrinsic properties, so it will lead to the problem

Mobile edge computing (MEC) is a suitable solution to improve computational capabilities in vehicular environments, and the computation offloading plays a critical role in MEC. After the computation task generates, in traditional offloading strategies, vehicles offload data only when they have entered the communication range of the MEC server, which greatly increases the time cost and cannot satisfy

We present a light and efficient approach named Latent Fusion network for fast and accurate hand pose estimation from a single depth image. Our method innovatively decomposes 3D joint regression into 2D plane localization and 1D axis estimation from different spatial perspectives. We design multiple latent heatmap regression branches to predict hand pose separately and a fusion network to output the

This paper presents a modular grid-connected single-phase system based on series-connected current-source module integrated converters (MICs). The modular configuration improves the reliability, redundancy and scalability of photovoltaic (PV) distributed generators. In this system, each PV panel is connected to a dc/ac inverter to permit individual Maximum Power Point Tracking (MPPT) operation for

Fast Frequency Hopping/Direct Sequence (FFH/DS) hybrid spread spectrum is an effective technique of the communication network for the robot swarms operating in complex electromagnetic environment. It combines the advantages of both Frequency Hopping Spread Spectrum (FHSS) and Direct Sequence Spread Spectrum (DSSS), and also uses the diversity-combining in time and frequency domain to effectively reject

An original music album is a collection of music created by an online musician, and is a special form of User Generated Content. This paper aims to identify the factors that drive original music album diffusion in online music community. Based on information acceptance theory and social networking, this study constructed a diffusion model of original music albums. To empirically test the theoretically

This paper proposes a sub-frame layer RDO algorithm to further improve coding performance of low-delay hierarchical prediction structure in High Efficiency Video Coding. In the proposed algorithm, each frame is segmented into two sub-frames according to motion intensity, and a sub-frame layer is taken as a basic optimizing unit. An inter-frame dependency model is proposed to quantify inter-frame dependency

For the power system interconnected with the large-scale offshore wind power through VSC-HVDC, such as SZ power grid, it may be engaged with transient frequency stability and lack of related control due to the randomness, fluctuation and intermittence of the wind. This paper proposes a transient frequency control strategy for the power system interconnected with offshore wind power through VSC-HVDC

Certain species of ants can carry out tasks in dense work spaces while maintaining their ability to accurately manipulate heavy loads, and these advantages are of interest to the robotics community. We consider a robotic swarm of $N\ge 6$ agents that assumes the task of moving a load through a cluttered space. This forces the swarm to carefully manipulate the orientation of the load, while transporting

Multiprocessor scheduling is one of the thrust areas in the field of computational science. There are various traditional scheduling techniques exist for the allocation and processing of jobs. But the performance of these techniques reduce in terms of makespan and waiting time when a large number of jobs are allocated to multiprocessors. In this paper, a new stochastic evolutionary technique is proposed

Vehicle-to-infrastructure (V2I) communication is an important enabler for intelligent transportation and rail traffic management systems, which are expected to provide significant road traffic safety and efficiency enhancements. Such systems require a level of dependability of the wireless communication link that can be hard to support by state-of-the-art technologies. Transmissions in the millimeter

Recently, unmanned aerial vehicles (UAVs) as flying wireless communication platform have attracted much attention. Benefiting from the mobility, UAV aerial base stations can be deployed quickly and flexibly, and can effectively establish Line-of-Sight communication links. However, there are many challenges in UAV communication system. The first challenge is energy constraint, where the UAV battery

Archeomusicologists commonly use methods based on the physical properties and the relative tuning system of a musical instrument in order to estimate its tones. However, because the musician often alters the tones’ frequency, for example, while playing in wind instruments by means of embouchure or by stressing the string in string instruments, the current methods that neglect the musician’s interaction

Nanosheet (NS) and nanowire (NW) FET architectures scaled to a gate length ( $L_{\textbf {G}}$ ) of 16 nm and below are benchmarked against equivalent FinFETs. The device performance is predicted using a 3D finite element drift-diffusion/Monte Carlo simulation toolbox with integrated 2D Schrödinger equation based quantum corrections. The NS FET is a viable replacement for the FinFET in high performance

Identifying tiny objects with extremely low resolution is generally considered a very challenging task even for human vision, due to limited information presented inside the object areas. There have been very limited attempts in recent years to deal with low-resolution recognition. The existing solutions rely on either generating super-resolution images or learning multi-scale features. However, their

Choreography-driven microservice composition has provided a better way to integrate components in the Cyber-physical-Social System (CPSS). Choreography is a global contract that specifies interactions among microservices participating in a composite service. After modeling a choreography, a problem arises here is whether the choreography specification at design time can be implemented correctly by

Computer-aided diagnosis systems (CADs) present valuable second opinions to radiologists in diagnosis. Many studies on thyroid nodules have proposed various CADs to provide a binary result, benignity or malignancy, for doctors, ignoring interpretability of more ultrasonic features that could be more useful. We develop an interpretable CADs (iCADS) that utilizes deep-learning networks’ classification

In this paper, an eight-arm Archimedean spiral antenna (ASA) is proposed to generate multiple orbital angular momentum (OAM) modes over a respectable frequency band (1.9-3GHz). Firstly, the principle of radiation by eight-arm ASA with right-hand spiral line is analyzed and simulated. It is demonstrated that the OAM modes and polarizations of the generated vortex waves are reconfigurable by changing

A new look-up table based behavioral model for dynamic nonlinear power amplifiers is proposed. This model labelled as hybrid look-up tables model is based on the combination of a memoryless look-up table sub-model and a nested look-up tables one. It is demonstrated that the proposed model circumvents the computational complexity associated with the parameters identification in analytically defined

Aiming at Travel Salesman Problem (TSP) that ant colony algorithm is easy to fall into local optima and slow convergence, a multi-colony ant algorithm using both generative adversarial nets (GAN) and adaptive stagnation avoidance strategy (GAACO) is proposed. First, to improve the convergence speed of the algorithm, we introduce a GAN model based on the game between convergence speed and solution quality

From a global perspective, an Internet of Vehicles task offloading solution based on mobile edge computing is proposed, which satisfies the application requirements (high reliability) strictly. The average time for completing a task can be minimized with the reasonable task offloading solution. Firstly, we model the wireless network, the transmission time and the movement of vehicles. Besides, heterogeneous

Due to extensive research on complex networks, fractal analysis with scale invariance is applied to measure the topological structure and self-similarity of complex networks. Fractal dimension can be used to quantify the fractal properties of the complex networks. However, in the existing box covering algorithms, accurately calculating the fractal dimension of complex networks is still an NP-hard problem

With the growing concerns about energy saving and security problems in wireless sensor networks (WSNs), we investigated a joint energy saving scheduling and secure routing algorithm for critical event reporting in WSN. When a critical event has been detected, the notification must be safely sent to the sink node through the uplink transmission, and the sink node needs to broadcast the alarm messages

Compact and low profile power converters are the main business of today’s power industry. A significant volume of a power converter is occupied by the power transformer. This article proposes a unique solution that would make the power converters low profile. Instead of designing a power converter by using a single bulky transformer, the solution proposed is to split the main bulky transformer into

State of health (SOH) monitoring and remaining useful life (RUL) prediction are the key to ensuring the safe use of lithium-ion batteries. However, the commonly used models are inefficient in predicting accuracy and do not have the ability to capture local regeneration of battery cells. In this paper, a temporal convolutional network (TCN) based SOH monitoring model framework of lithium-ion batteries

Current iris recognition technology faces practical difficulties. For example, due to the unsteady morphology of a heterogeneous iris generated by a variety of different devices and environments, the traditional processing methods of statistical learning or cognitive learning for a single iris source are not effective. The existing iris data set size and situational classification constraints make

Networks had an increasing impact on modern life since network cybersecurity has become an important research field. Several machine learning techniques have been developed to build network intrusion detection systems for correctly detecting unforeseen cyber-attacks at the network-level. For example, deep artificial neural network architectures have recently achieved state-of-the-art results. In this