Miracle-dz/UniFAR-FTUs huggingface dataset:
Two Shared-Aperture Antennas as a Building Block for Four-Port MIMO Array

In this paper, a four-antenna MIMO array composed of two shared-aperture building blocks is provided. The proposed building block is composed of a loop antenna and a slot antenna, in which the loop antenna and the slot antenna share the same rectangular clearance. Without any external decoupling structure, the proposed four-antenna MIMO array yields desirable isolation of better than 16.5 dB across the desired bands (3.4-3.6 GHz). And the ECC (envelope correlation coefficients) is much better than 0.1. Consequently, the proposed MIMO array is a good candidate for future metal-rimmed smartphone.
A 16-Beam Array Design for Access Points with 3-D Beam Coverage

This paper proposes a multi-beam array antenna design that yields directive beams toward different directions. The four-layer 16-by-16 feeding network provides phase delay profiles for a 4-by-4 antenna array to generate squint beams arranged in an axially symmetric fashion, which is particularly suitable for ceiling-mount or wall-mount access points. Simulation results verify that such a multi-beam array configuration can provide apparent pattern diversity. For a conventional transceiver, RF switches can be employed to facilitate beam scanning in a 3-D space. For a multi-transceiver device, coexisting beams can provide a wide coverage and support massive MIMO.
Low-Profile LTE / WWAN / GPS Antenna System Placed on the Bezel of the Laptop

This paper presents a low profile LTE / WWAN/ GPS antenna system placed on the bezel of the laptop. The size of the antenna is 70 × 12.5 × 3 mm3, which is designed for LTE/ WWAN and GPS applications. The antenna system is composed of a monopole antenna group and a shorting loop antenna. The high frequency band (1710-2690 MHz) and the GPS frequency (1575 MHz) are excited by the feed monopole antenna group, and the low frequency band (698-960 MHz), It is excited by the loop antenna which is formed by the coupling of the monopole antenna group branch and the shorting circuit metal plane. Then add 70 x 3 mm2 metal plane on the shorting-circuit metal plane to increase the radiation area so that the low frequency band has a better operation bandwidth covering the LTE / WWAN frequency band. Finally, the actual installation of the antenna system on the laptop's bezel also results in good antenna characteristics.
The Social Mentality of Netizens in the Guangdong-Hong Kong-Macao Greater Bay Area: Big Data Monitoring of Social Media

In 2019, the development plan for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was officially announced. This will be a useful boost to cooperation among Hong Kong, Macao, and the Pan-Pearl River Delta, and requires positive social mentality as a driving force. Analyzing the netizens' expression on social media has become the most important method to comprehend social mentality. Therefore, this study explores the social mentality of GBA netizens through social cognition, social perception, and social development efficiency. Specifically, this study utilizes big data methods to analyze how netizens in the GBA describe their social mentality.
Low-RCS Slot Array Antenna Using a Hybrid Metasurface

A slot array antenna with low radar cross section (RCS) is proposed by using a hybrid metasurface (HM) consisting of an anisotropic frequency selective absorber (AFSA) and a polarization rotation reflective surface (PRRS). Both the co-polarized and cross-polarized monostatic RCSs of the proposed antenna is significantly reduced for both in-band and out-of-band frequencies compared with the reference antenna. Moreover, the bistatic RCS is reduced in the angle ranges of because the incident waves are absorbed rather than reflected to other directions. The simulated results show that the RCS of the proposed slot array antenna is significantly reduced in the frequency range from 6 GHz to 18 GHz and the gain decreases about only 0.8 dB.
A Miniaturized Wideband Dual-Polarized 5G mm-Wave Antenna-in-Package (AiP) Array for Cellular Phones

The design of a miniaturized wideband dual-polarized linear antenna-in-package (AiP) array consisting of 4 antenna elements is proposed for cellular phones with fifth generation mobile communications (5G) mm-Wave technologies. Based on |Snn| ≤ –10 dB, both of the two polarization (pol.) of the AiP array can cover from 24.99 GHz to 30.10 GHz and from 36.18 GHz to 40.26 GHz. The third generation partnership project (3GPP) bands n257, n261, and n260 can hence be accommodated as the local main bands. For band n258, the worst | Snn | values for both the two pol. are –7.52 dB, which are better than –6.0 dB. Band n258 can thus be covered as the roaming band. Scanning peak realized gains for both the two pol. are 9.57 dBi, 10.30 dBi, and 11.99 dBi at 26.0 GHz, 28.0 GHz, and 39.0 GHz, respectively. The whole size of the AiP array is 1.616 mm × 4.84 mm × 18.60 mm, i.e., 0.13 λo × 0.39 λo × 1.50 λo at 24.25 GHz.
Cumulative Conforming Control Chart Assuming Discrete Weibull Distribution

Time Between Events (TBE) charts have advantages over the traditional control charts when monitoring high quality processes with very low defect rates. This article introduces a new discrete TBE control chart following discrete Weibull distribution. The design of the proposed chart is derived analytically and discussed numerically. Moreover, the performance is assessed by using the Average Run Length (ARL) and the Coefficient of Variation of Run Length (CVRL). Besides simulation studies, the proposed scheme is also illustrated using four real data examples.
Deep Learning of Biomechanical Dynamics in Mobile Daily Activity and Fall Risk Monitoring*

Smart health is paving a promising way for modern health management. Daily activity and fall risk monitoring is one important application that urges smart technologies, resulting from the fact that there are 29 million falls and 7 million fall injuries per year, and also the fact that appropriate exercise can lower the risk of death by up to 20 to 70%. However, it is very challenging to accurately identify an activity due to the diversity of the human biomechanical dynamics. Main reasons include: even a same person usually has different motion characteristics when performing a same activity; there are many different activities in our daily lives; and the sensor wearing habit may be different. In this paper, focusing on these challenges, a new intelligent computational approach is proposed for robust activity detection, leveraging biomechanical dynamics enhancement and deep learning technologies. It can unveil deep hidden biomechanical patterns from the mobile phone-sensed motion data, and robustly detect 17 types of daily and fall activities performed by 30 people. The detection accuracy of 11,770 activities is as high as 93.9%, indicating the effectiveness of the proposed approach. This research is expected to greatly advance mobile daily activity and fall risk monitoring in smart health era.
A Closed-Loop Controller for Cable-Driven Hyper-Redundant Manipulator with Joint Angle Sensors *

A cable-driven hyper-redundant manipulator is especially suited for manipulations in confined spaces. In most of the existing approaches, a controller is often designed to actuate the joints by pulling the corresponding cables without the feedback from remote sensors at the joints. The un-modeled elongations of these cables due to unknown tensions often cause a decrease in control precision. To improve the performance of such a manipulator, this paper presents an investigation where miniature potentiometers are integrated into the joints for angle feedback. Furthermore, a puller-follower controller is developed to control the three cables of a universal joint for not only closed- loop joint angle control but also cable tension preservation. Applying the Hooke’s Law, the cable tension is represented by its deformation. In this way, the controller is designed to realize both the desired angles and the cable deformations, without force sensing on the cables. Finally, experiments on a single joint and multiple joints were conducted to verify the effectiveness of this proposed controller.
A Novel Wideband Circular Patch Antenna With Conical Radiation Pattern

In this contribution, a novel ultra-wideband antenna with conical radiation pattern is proposed and discussed in detail. This antenna is intended to operate in the frequency range from 4 GHz to 7.8 GHz. With the combination of a circular patch, conical cavity and feeding, the antenna provides a wide bandwidth and conical radiation pattern. The operation principle of the antenna has been presented. Simulated results show that the proposed antenna yields an impedance bandwidth (VSWR < 2.0) of 131.3% for the conical beam is from 3.35 GHz to 16.18 GHz, but the radiation pattern of the antenna is split between 7.8 GHz and 16 GHz. The cone radiation pattern of the antenna has no side lobes between 3.35 GHz and 7.8 GHz (79.8%), and the maximum gain is greater than 6 dBi in the frequency band. Moreover, a cone metal is added to improve the impedance bandwidth. The proposed antenna has a low profile, low cost and high power capacity to be suitable for ultra-wideband (UWB) system.
Preliminary Study in Motion Assistance of Soft Exoskeleton Robot based on Data-driven Kinematics Model Learning

Exoskeleton is widely used to enhance human mobility. Especially in recent years, the soft exoskeleton robots have developed rapidly, which could realize natural human-machine physiological coupling. However, the motion patterns and physiological parameters are significant various between different subjects. The parameters of the soft exoskeletons change differently during motion. In this paper, we proposed kinematics model based on data-driven model learning. The proposed model learning method not only has the fast learning ability of model-based controller, but also has the adaptability of sensor-based controller. Firstly, we use the data of the rigid model to pre-train the kinematics model network, which can make the output of the network consistent with the kinematics model. Then, we use the sensors to collect the actual motion data and send the motion data into the pre-trained neural network model. By increasing the iteration times of training, the network model outputs model parameters that are consistent with the trend of the simulation model. Through the training and learning of the bionic motion platform, the speed of learning adaptation in human body can be accelerated.
From Virtuality To Reality: A Learning-based Point Cloud Labeling Method With Synthesis Scene

This paper proposes a machine learning based point cloud labeling algorithm. To classify point cloud in a sparse scan of both virtual and real scene as basic geometrical elements like planar and edge, a rendering dataset in virtual environment is created and labeled. Then the principal component analysis (PCA) is applied to calculate local geometrical features of point cloud. An in-depth analysis is performed by training several machine learning models with PCA features and experiments in which the trained models are applied to on both rendering point cloud and laser scan of real scene are conducted to validate that our approach is scale-invariant and effective on both rendering point cloud and point cloud of real scene.
A Design For An Exoskeletal Device With Reduced Reliance On Joint Alignment

As robotic exoskeletons begin to find more use in the areas of medicine and rehabilitation, efforts to improve comfort and reduce the chance of injury for wearers have resulted in the development of joint mechanisms with extra passive degrees of freedom. The added redundancy in such mechanisms enables the system to accommodate for joint axis misalignments between the exoskeleton and the human skeleton, as well as deviations from ideal circular motion that are inherent in normal human body motion. However, proper measurement of joint positions and torques, and by extension proper position and impedance control of the exoskeleton still relies on the approximate alignment of these joint axes. This paper presents a method for such a system to calculate the pose and torque about a human elbow joint for a wider variety of possible mounting positions. Using the developed calibration procedure, the main joint of the exoskeleton can be located as much as 110 mm away from the elbow and still position the elbow to within 10 degrees of a given flexion angle and measure torques to within 13 percent of the actual value. An elbow exoskeleton was developed employing this system and tested for comfort. The wearer was able to comfortably move their elbow in any desired motions using the device’s passive mode. These results demonstrate the feasibility of using such a system on a robotic rehabilitation device and open up more possibilities for future exoskeleton designs not limited by joint placement.
A K/Ka Multi-Polarized Dielectric Rod Antenna Based on A Wideband Band OMT

In this paper, a wideband multi-polarized dielectric rod antenna is proposed. By employing the orthomode transducer (OMT) feeding structure which is realized by using ridged waveguides, the impedance bandwidth of the antenna is widened effectively and the multi-polarized radiation performance is achieved. The antenna can be operated in dual polarization in the frequency range of 21-34 GHz, while operated in circularly polarization (AR < 3 dB) in the frequency range of 29.9-30.2 GHz. The antenna can be used in satellite and 5G communications.
An Enhanced U-Net for Brain Tumor Segmentation

The Convolutional Neural Network (CNN) has been in rapid development these years. It is applied to many fields. Among these, brain tumor segmentation is one of foci. Researchers delves into this with different ways. Some researchers use 3D CNN to handle the brain images for tumor segmentation, and others use 2D CNN modified from models of natural images in semantic segmentation to process separate slices of brain images. Based on properties of brain images and the inherent contradiction of semantic segmentation, we chose 2D U-Net as basic model and modified the skip connection in it to propose our model. To verify effect of our model, we introduced our brain image dataset and made experiments on it and BraTS 2017 dataset. Experiments shows that proposed model outperforms the original U-Net.
A 22–29 GHz Voltage-Biased LC-VCO with Suppressed Flicker Noise over Tuning Range in 22nm FD-SOI

This paper presents a 22–29 GHz voltage biased LC-VCO in 22nm FD-SOI achieving a figure-of-merit (FOM) of 188~190 dBc/Hz over the tuning range. Thanks to the noise filtering tank formed by decoupling capacitor and source side coupled inductor, the flicker noise upconversion can be suppressed significantly without degrading the phase noise (PN) at 1/f2 region. To obtain a consistent low 1/f3 corner along with the frequency tuning, a common centroid layout technique is used for switched capacitor bank (SCB) implementation. The post layout simulation shows that the 1/f3 corner is well below 50kHz over the tuning range in different process corners. The PN@1MHz is −110.2 dBc/Hz at center frequency with a power consumption of 8.8mW.
Preliminary Design of Helix-Loaded, High Gain Planar Endfire Circularly Polarized Antenna

Conceptual design of a helix-loaded, high gain planar endfire circularly polarized antenna (PECPA) is envisioned. An axial-mode helix is excited by a complementary dipole PECPA at its basic form, while a low profile of about 0.034-wavelength is maintained. In this way, endfire directivity and front-to-back ratio (FTBR) can be enhanced to 7.1dBi and 14dB, respectively. Design considerations with preliminary numerical results on key parameters of the proposed antenna are discussed.
Intelligent Quality of Service Aware Traffic Forwarding for Software-Defined Networking/Open Shortest Path First Hybrid Industrial Internet

Driven by the emerging advanced information and communication technologies, e.g., artificial intelligence, 5G wireless communications, big data analytics, etc., industrial Internet serves as a key enabling technology to realize intelligent manufacturing, and has been attracting considerable attentions from academia and industry. However, the traditional industrial networks can hardly satisfy the quality of service (QoS) requirements for some mission-critical industrial applications (e.g., fault detection, advanced control, remote monitoring, predictive maintenance, etc.) due to network heterogeneity, traffic congestion, dynamic end-to-end latency, reliability issues, and so on. The emerging software-defined networking (SDN) has been considered as a promising architecture to improve the QoS of industrial applications by flexibly decoupling the control and data planes to control the network behaviours centrally. Owing to economy and policy considerations, a realistic solution is to incrementally deploy SDN in industrial networks instead of fully replacing traditional industrial routers with SDN-enabled switches. In this article, we consider a hybrid Industrial network consisting of conventional routers (e.g., running OSPF protocol) and SDN-enabled switches (e.g., running OpenFlow protocol), and propose an intelligent QoS-aware forwarding strategy to improve the QoS of industrial applications, by utilizing a single path minimum cost forwarding scheme and a K-path partition algorithm for multipath forwarding. Simulation results demonstrate that the proposed scheme not only guarantees the QoS requirements of industrial services, but also efficiently utilizes bandwidth resources by balancing traffic load in the SDN/OSPF hybrid industrial Internet.
Flow Shop Scheduling Problem with Limited Buffer Based on Hybrid Shuffled Frog Leaping Algorithm

Aiming at the flow shop scheduling problem with limited buffer, a hybrid shuffled frog-leaping algorithm (HSFLA) combining variable neighborhood search (VNS) and frog-leaping algorithm (SFLA) is proposed to minimize the makespan. To improve the quality of the initial solutions, a partial initial population is generated using the NEH algorithm and iterative greedy (IG). In order to avoid the problem of the original algorithm's premature convergence and producing infeasible solutions, the adaptive moving operator is introduced to improve the step size and crossover operator in the sub-population's updating part. A variable neighborhood search method based on three neighborhood structures is designed to enhance the local optimization ability of the algorithm. The performances of HSFLA were evaluated over car and rec benchmark problems. The computational results demonstrated that HSFLA has an effective performance for the flow shop scheduling problem with limited buffer.
Work Amplification of the Hydraulic Servo Actuator with a Miniature Accumulator*

Actuator performance is an important factor limiting the dynamic characteristics of the robot. In this paper, the energy transfer capability of the hydraulic servo actuator is improved by adding a miniature accumulator. We established the dynamic model of the system and obtained the optimal inflation pressure of the gas in the accumulator by numerical method. Both numerical analysis and virtual prototype simulation show this design can enlarge the work of the actuator to about 1.66 times the original. It allows the actuator to maintain high performance while reducing mass and volume.
An Ultra Low-power Low-offset Double-tail Comparator

In double tail comparators, the pre-amplifier amplifies the input differential voltage and when the output Vcm of the pre-amplifier becomes larger than Vth of the latch input transistors, the latch is activated and finalizes the comparison. As a result, the pre-amplification delay is fixed to a value and cannot be set at the minimum required delay, to save power and improve offset. In fact, when the latch is activated the pre-amplifier output differential voltage is still growing but the latch finishes the comparison before the maximum differential gain is formed and applied to the latch. In this paper, a comparator is proposed in which the preamplifier is turned off when the maximum gain is achieved so that always the maximum possible gain is applied to the latch. Therefore, not only the input referred offset is improved but also the power consumption of the pre-amplifier is saved. Simulations in 0. 18µm technology show with an appropriate pre-amplification delay the average power is saved by up to 75% while the offset voltage is reduced by about 30%.
A calibration method with anistropic weighting for LiDAR and stereo camera system

Calibrating the extrinsic matrices between sensors is a significant pre-processing step of sensor fusion. Most of existing calibration methods use point-based rigid registration algorithm which considers the point coordinate error isotropic and uses the least square solution to estimate the extrinsic matrices. However, the error distribution of point coordinates is anisotropic due to the internal measurement properties of sensors, leading to decreased calibration accuracy. To solve this problem, we proposed an anisotropy weighting method: first we construct weighting matrices based on error distributions models of sensors; second we use surveying adjustment to further improve the calibration accuracy iteratively. We verified the effectiveness of our method through simulations. Compared with traditional methods, the accuracy is improved by about 45%. Moreover, our method can be applied in most of calibration methods to reduce the influence of anisotropic data and improve the accuracy.
Novel Yoke Structured Electromagnetic Thermography for Inspection of Natural Fatigue Cracks

Nondestructive detection of small fatigue cracks is a significative and challenging task in evaluating the properties of material. This paper proposes a novel yoke structured eddy current pulsed thermography (ECPT) system for micro fatigue cracks inspection on irregularly shaped metallic materials. The proposed detection model provides a region of interest with a relatively uniform magnetic field. The detectability and thermal contrast of omnidirectional micro fatigue cracks are enhanced remarkably. In addition, the configuration has advantages of dramatically increasing portability and efficiency for detecting complex workpiece since the detection is completely in the open view of the infrared camera. Finally, experimental studies have been conducted on natural fatigue cracks in order to validate the reliability and efficiency of the proposed sensing structure.
Tactile Servo Using Dynamic Tactile Jacobian Estimator

Nowadays, a wide variety of service robots have been developed to assistant humans in performing tasks that are dull and repetitive, such as household chores. Tactile perception can play a critical role in a service robot to improve its performance. Thus, the robot control method with tactile perception, Tactile servo, was proposed. However, the common tactile servo cannot deal with the targets so generally and flexibly. To enhance the performance of the tactile servo, this study is to present an agile and versatile tactile servo by the dynamic tactile Jacobian estimator which can generate an adjustable tactile Jacobian instead of a fixed tactile Jacobian used in the common tactile servo. In the experimental validation, this research utilized the objects with different shapes for experimenting, and this research confirmed the feasibility of the tactile servo using the dynamic tactile Jacobian estimator in final. This paper explains the method and demonstrates the results.